how to write the method part of a research paper

When you choose to publish with PLOS, your research makes an impact. Make your work accessible to all, without restrictions, and accelerate scientific discovery with options like preprints and published peer review that make your work more Open.

• PLOS Biology
• PLOS Climate
• PLOS Complex Systems
• PLOS Computational Biology
• PLOS Digital Health
• PLOS Genetics
• PLOS Global Public Health
• PLOS Medicine
• PLOS Mental Health
• PLOS Neglected Tropical Diseases
• PLOS Pathogens
• PLOS Sustainability and Transformation
• PLOS Collections
• How to Write Your Methods

Ensure understanding, reproducibility and replicability

What should you include in your methods section, and how much detail is appropriate?

Why Methods Matter

The methods section was once the most likely part of a paper to be unfairly abbreviated, overly summarized, or even relegated to hard-to-find sections of a publisher’s website. While some journals may responsibly include more detailed elements of methods in supplementary sections, the movement for increased reproducibility and rigor in science has reinstated the importance of the methods section. Methods are now viewed as a key element in establishing the credibility of the research being reported, alongside the open availability of data and results.

A clear methods section impacts editorial evaluation and readers’ understanding, and is also the backbone of transparency and replicability.

For example, the Reproducibility Project: Cancer Biology project set out in 2013 to replicate experiments from 50 high profile cancer papers, but revised their target to 18 papers once they understood how much methodological detail was not contained in the original papers.

What to include in your methods section

What you include in your methods sections depends on what field you are in and what experiments you are performing. However, the general principle in place at the majority of journals is summarized well by the guidelines at PLOS ONE : “The Materials and Methods section should provide enough detail to allow suitably skilled investigators to fully replicate your study. ” The emphases here are deliberate: the methods should enable readers to understand your paper, and replicate your study. However, there is no need to go into the level of detail that a lay-person would require—the focus is on the reader who is also trained in your field, with the suitable skills and knowledge to attempt a replication.

A constant principle of rigorous science

A methods section that enables other researchers to understand and replicate your results is a constant principle of rigorous, transparent, and Open Science. Aim to be thorough, even if a particular journal doesn’t require the same level of detail . Reproducibility is all of our responsibility. You cannot create any problems by exceeding a minimum standard of information. If a journal still has word-limits—either for the overall article or specific sections—and requires some methodological details to be in a supplemental section, that is OK as long as the extra details are searchable and findable .

Imagine replicating your own work, years in the future

As part of PLOS’ presentation on Reproducibility and Open Publishing (part of UCSF’s Reproducibility Series ) we recommend planning the level of detail in your methods section by imagining you are writing for your future self, replicating your own work. When you consider that you might be at a different institution, with different account logins, applications, resources, and access levels—you can help yourself imagine the level of specificity that you yourself would require to redo the exact experiment. Consider:

• Which details would you need to be reminded of? 
• Which cell line, or antibody, or software, or reagent did you use, and does it have a Research Resource ID (RRID) that you can cite?
• Which version of a questionnaire did you use in your survey? 
• Exactly which visual stimulus did you show participants, and is it publicly available? 
• What participants did you decide to exclude? 
• What process did you adjust, during your work? 

Tip: Be sure to capture any changes to your protocols

You yourself would want to know about any adjustments, if you ever replicate the work, so you can surmise that anyone else would want to as well. Even if a necessary adjustment you made was not ideal, transparency is the key to ensuring this is not regarded as an issue in the future. It is far better to transparently convey any non-optimal methods, or methodological constraints, than to conceal them, which could result in reproducibility or ethical issues downstream.

Visual aids for methods help when reading the whole paper

Consider whether a visual representation of your methods could be appropriate or aid understanding your process. A visual reference readers can easily return to, like a flow-diagram, decision-tree, or checklist, can help readers to better understand the complete article, not just the methods section.

Ethical Considerations

In addition to describing what you did, it is just as important to assure readers that you also followed all relevant ethical guidelines when conducting your research. While ethical standards and reporting guidelines are often presented in a separate section of a paper, ensure that your methods and protocols actually follow these guidelines. Read more about ethics .

Existing standards, checklists, guidelines, partners

While the level of detail contained in a methods section should be guided by the universal principles of rigorous science outlined above, various disciplines, fields, and projects have worked hard to design and develop consistent standards, guidelines, and tools to help with reporting all types of experiment. Below, you’ll find some of the key initiatives. Ensure you read the submission guidelines for the specific journal you are submitting to, in order to discover any further journal- or field-specific policies to follow, or initiatives/tools to utilize.

Tip: Keep your paper moving forward by providing the proper paperwork up front

Be sure to check the journal guidelines and provide the necessary documents with your manuscript submission. Collecting the necessary documentation can greatly slow the first round of peer review, or cause delays when you submit your revision.

Randomized Controlled Trials – CONSORT The Consolidated Standards of Reporting Trials (CONSORT) project covers various initiatives intended to prevent the problems of  inadequate reporting of randomized controlled trials. The primary initiative is an evidence-based minimum set of recommendations for reporting randomized trials known as the CONSORT Statement . 

Systematic Reviews and Meta-Analyses – PRISMA The Preferred Reporting Items for Systematic Reviews and Meta-Analyses ( PRISMA ) is an evidence-based minimum set of items focusing  on the reporting of  reviews evaluating randomized trials and other types of research.

Research using Animals – ARRIVE The Animal Research: Reporting of In Vivo Experiments ( ARRIVE ) guidelines encourage maximizing the information reported in research using animals thereby minimizing unnecessary studies. (Original study and proposal , and updated guidelines , in PLOS Biology .) 

Laboratory Protocols Protocols.io has developed a platform specifically for the sharing and updating of laboratory protocols , which are assigned their own DOI and can be linked from methods sections of papers to enhance reproducibility. Contextualize your protocol and improve discovery with an accompanying Lab Protocol article in PLOS ONE .

Consistent reporting of Materials, Design, and Analysis – the MDAR checklist A cross-publisher group of editors and experts have developed, tested, and rolled out a checklist to help establish and harmonize reporting standards in the Life Sciences . The checklist , which is available for use by authors to compile their methods, and editors/reviewers to check methods, establishes a minimum set of requirements in transparent reporting and is adaptable to any discipline within the Life Sciences, by covering a breadth of potentially relevant methodological items and considerations. If you are in the Life Sciences and writing up your methods section, try working through the MDAR checklist and see whether it helps you include all relevant details into your methods, and whether it reminded you of anything you might have missed otherwise.

Summary Writing tips

The main challenge you may find when writing your methods is keeping it readable AND covering all the details needed for reproducibility and replicability. While this is difficult, do not compromise on rigorous standards for credibility!

• Keep in mind future replicability, alongside understanding and readability.
• Follow checklists, and field- and journal-specific guidelines.
• Consider a commitment to rigorous and transparent science a personal responsibility, and not just adhering to journal guidelines.
• Establish whether there are persistent identifiers for any research resources you use that can be specifically cited in your methods section.
• Deposit your laboratory protocols in Protocols.io, establishing a permanent link to them. You can update your protocols later if you improve on them, as can future scientists who follow your protocols.
• Consider visual aids like flow-diagrams, lists, to help with reading other sections of the paper.
• Be specific about all decisions made during the experiments that someone reproducing your work would need to know.

Don’t

• Summarize or abbreviate methods without giving full details in a discoverable supplemental section.
• Presume you will always be able to remember how you performed the experiments, or have access to private or institutional notebooks and resources.
• Attempt to hide constraints or non-optimal decisions you had to make–transparency is the key to ensuring the credibility of your research.
• How to Write a Great Title
• How to Write an Abstract
• How to Report Statistics
• How to Write Discussions and Conclusions
• How to Edit Your Work

The contents of the Peer Review Center are also available as a live, interactive training session, complete with slides, talking points, and activities. …

The contents of the Writing Center are also available as a live, interactive training session, complete with slides, talking points, and activities. …

There’s a lot to consider when deciding where to submit your work. Learn how to choose a journal that will help your study reach its audience, while reflecting your values as a researcher…

• Bipolar Disorder
• Therapy Center
• When To See a Therapist
• Types of Therapy
• Best Online Therapy
• Best Couples Therapy
• Best Family Therapy
• Managing Stress
• Sleep and Dreaming
• Understanding Emotions
• Self-Improvement
• Healthy Relationships
• Student Resources
• Personality Types
• Guided Meditations
• Verywell Mind Insights
• 2024 Verywell Mind 25
• Mental Health in the Classroom
• Editorial Process
• Meet Our Review Board
• Crisis Support

How to Write a Methods Section for a Psychology Paper

Tips and Examples of an APA Methods Section

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Emily is a board-certified science editor who has worked with top digital publishing brands like Voices for Biodiversity, Study.com, GoodTherapy, Vox, and Verywell.

Verywell / Brianna Gilmartin 

The methods section of an APA format psychology paper provides the methods and procedures used in a research study or experiment . This part of an APA paper is critical because it allows other researchers to see exactly how you conducted your research.

Method refers to the procedure that was used in a research study. It included a precise description of how the experiments were performed and why particular procedures were selected. While the APA technically refers to this section as the 'method section,' it is also often known as a 'methods section.'

The methods section ensures the experiment's reproducibility and the assessment of alternative methods that might produce different results. It also allows researchers to replicate the experiment and judge the study's validity.

This article discusses how to write a methods section for a psychology paper, including important elements to include and tips that can help.

What to Include in a Method Section

So what exactly do you need to include when writing your method section? You should provide detailed information on the following:

• Research design
• Participants
• Participant behavior

The method section should provide enough information to allow other researchers to replicate your experiment or study.

Components of a Method Section

The method section should utilize subheadings to divide up different subsections. These subsections typically include participants, materials, design, and procedure.

Participants 

In this part of the method section, you should describe the participants in your experiment, including who they were (and any unique features that set them apart from the general population), how many there were, and how they were selected. If you utilized random selection to choose your participants, it should be noted here.

For example: "We randomly selected 100 children from elementary schools near the University of Arizona."

At the very minimum, this part of your method section must convey:

• Basic demographic characteristics of your participants (such as sex, age, ethnicity, or religion)
• The population from which your participants were drawn
• Any restrictions on your pool of participants
• How many participants were assigned to each condition and how they were assigned to each group (i.e., randomly assignment , another selection method, etc.)
• Why participants took part in your research (i.e., the study was advertised at a college or hospital, they received some type of incentive, etc.)

Information about participants helps other researchers understand how your study was performed, how generalizable the result might be, and allows other researchers to replicate the experiment with other populations to see if they might obtain the same results.

In this part of the method section, you should describe the materials, measures, equipment, or stimuli used in the experiment. This may include:

• Testing instruments
• Technical equipment
• Any psychological assessments that were used
• Any special equipment that was used

For example: "Two stories from Sullivan et al.'s (1994) second-order false belief attribution tasks were used to assess children's understanding of second-order beliefs."

For standard equipment such as computers, televisions, and videos, you can simply name the device and not provide further explanation.

Specialized equipment should be given greater detail, especially if it is complex or created for a niche purpose. In some instances, such as if you created a special material or apparatus for your study, you might need to include an illustration of the item in the appendix of your paper.

In this part of your method section, describe the type of design used in the experiment. Specify the variables as well as the levels of these variables. Identify:

• The independent variables
• Dependent variables
• Control variables
• Any extraneous variables that might influence your results.

Also, explain whether your experiment uses a  within-groups  or between-groups design.

For example: "The experiment used a 3x2 between-subjects design. The independent variables were age and understanding of second-order beliefs."

The next part of your method section should detail the procedures used in your experiment. Your procedures should explain:

• What the participants did
• How data was collected
• The order in which steps occurred

For example: "An examiner interviewed children individually at their school in one session that lasted 20 minutes on average. The examiner explained to each child that he or she would be told two short stories and that some questions would be asked after each story. All sessions were videotaped so the data could later be coded."

Keep this subsection concise yet detailed. Explain what you did and how you did it, but do not overwhelm your readers with too much information.

Tips for How to Write a Methods Section

In addition to following the basic structure of an APA method section, there are also certain things you should remember when writing this section of your paper. Consider the following tips when writing this section:

• Use the past tense : Always write the method section in the past tense.
• Be descriptive : Provide enough detail that another researcher could replicate your experiment, but focus on brevity. Avoid unnecessary detail that is not relevant to the outcome of the experiment.
• Use an academic tone : Use formal language and avoid slang or colloquial expressions. Word choice is also important. Refer to the people in your experiment or study as "participants" rather than "subjects."
• Use APA format : Keep a style guide on hand as you write your method section. The Publication Manual of the American Psychological Association is the official source for APA style.
• Make connections : Read through each section of your paper for agreement with other sections. If you mention procedures in the method section, these elements should be discussed in the results and discussion sections.
• Proofread : Check your paper for grammar, spelling, and punctuation errors.. typos, grammar problems, and spelling errors. Although a spell checker is a handy tool, there are some errors only you can catch.

After writing a draft of your method section, be sure to get a second opinion. You can often become too close to your work to see errors or lack of clarity. Take a rough draft of your method section to your university's writing lab for additional assistance.

A Word From Verywell

The method section is one of the most important components of your APA format paper. The goal of your paper should be to clearly detail what you did in your experiment. Provide enough detail that another researcher could replicate your study if they wanted.

Finally, if you are writing your paper for a class or for a specific publication, be sure to keep in mind any specific instructions provided by your instructor or by the journal editor. Your instructor may have certain requirements that you need to follow while writing your method section.

Frequently Asked Questions

While the subsections can vary, the three components that should be included are sections on the participants, the materials, and the procedures.

• Describe who the participants were in the study and how they were selected.
• Define and describe the materials that were used including any equipment, tests, or assessments
• Describe how the data was collected

To write your methods section in APA format, describe your participants, materials, study design, and procedures. Keep this section succinct, and always write in the past tense. The main heading of this section should be labeled "Method" and it should be centered, bolded, and capitalized. Each subheading within this section should be bolded, left-aligned and in title case.

The purpose of the methods section is to describe what you did in your experiment. It should be brief, but include enough detail that someone could replicate your experiment based on this information. Your methods section should detail what you did to answer your research question. Describe how the study was conducted, the study design that was used and why it was chosen, and how you collected the data and analyzed the results.

Erdemir F. How to write a materials and methods section of a scientific article ? Turk J Urol . 2013;39(Suppl 1):10-5. doi:10.5152/tud.2013.047

Kallet RH. How to write the methods section of a research paper . Respir Care . 2004;49(10):1229-32. PMID: 15447808.

American Psychological Association.  Publication Manual of the American Psychological Association  (7th ed.). Washington DC: The American Psychological Association; 2019.

American Psychological Association. APA Style Journal Article Reporting Standards . Published 2020.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

• PRO Courses Guides New Tech Help Pro Expert Videos About wikiHow Pro Upgrade Sign In
• EDIT Edit this Article
• EXPLORE Tech Help Pro About Us Random Article Quizzes Request a New Article Community Dashboard This Or That Game Popular Categories Arts and Entertainment Artwork Books Movies Computers and Electronics Computers Phone Skills Technology Hacks Health Men's Health Mental Health Women's Health Relationships Dating Love Relationship Issues Hobbies and Crafts Crafts Drawing Games Education & Communication Communication Skills Personal Development Studying Personal Care and Style Fashion Hair Care Personal Hygiene Youth Personal Care School Stuff Dating All Categories Arts and Entertainment Finance and Business Home and Garden Relationship Quizzes Cars & Other Vehicles Food and Entertaining Personal Care and Style Sports and Fitness Computers and Electronics Health Pets and Animals Travel Education & Communication Hobbies and Crafts Philosophy and Religion Work World Family Life Holidays and Traditions Relationships Youth
• Browse Articles
• Learn Something New
• Quizzes Hot
• This Or That Game
• Train Your Brain
• Explore More
• Support wikiHow
• About wikiHow
• Log in / Sign up
• Education and Communications
• College University and Postgraduate
• Academic Writing

How to Write Research Methodology

Last Updated: May 27, 2024 Approved

This article was co-authored by Alexander Ruiz, M.Ed. and by wikiHow staff writer, Jennifer Mueller, JD . Alexander Ruiz is an Educational Consultant and the Educational Director of Link Educational Institute, a tutoring business based in Claremont, California that provides customizable educational plans, subject and test prep tutoring, and college application consulting. With over a decade and a half of experience in the education industry, Alexander coaches students to increase their self-awareness and emotional intelligence while achieving skills and the goal of achieving skills and higher education. He holds a BA in Psychology from Florida International University and an MA in Education from Georgia Southern University. wikiHow marks an article as reader-approved once it receives enough positive feedback. In this case, several readers have written to tell us that this article was helpful to them, earning it our reader-approved status. This article has been viewed 523,052 times.

The research methodology section of any academic research paper gives you the opportunity to convince your readers that your research is useful and will contribute to your field of study. An effective research methodology is grounded in your overall approach – whether qualitative or quantitative – and adequately describes the methods you used. Justify why you chose those methods over others, then explain how those methods will provide answers to your research questions. [1] X Research source

Describing Your Methods

• In your restatement, include any underlying assumptions that you're making or conditions that you're taking for granted. These assumptions will also inform the research methods you've chosen.
• Generally, state the variables you'll test and the other conditions you're controlling or assuming are equal.

• If you want to research and document measurable social trends, or evaluate the impact of a particular policy on various variables, use a quantitative approach focused on data collection and statistical analysis.
• If you want to evaluate people's views or understanding of a particular issue, choose a more qualitative approach.
• You can also combine the two. For example, you might look primarily at a measurable social trend, but also interview people and get their opinions on how that trend is affecting their lives.

• For example, if you conducted a survey, you would describe the questions included in the survey, where and how the survey was conducted (such as in person, online, over the phone), how many surveys were distributed, and how long your respondents had to complete the survey.
• Include enough detail that your study can be replicated by others in your field, even if they may not get the same results you did. [4] X Research source

• Qualitative research methods typically require more detailed explanation than quantitative methods.
• Basic investigative procedures don't need to be explained in detail. Generally, you can assume that your readers have a general understanding of common research methods that social scientists use, such as surveys or focus groups.

• For example, suppose you conducted a survey and used a couple of other research papers to help construct the questions on your survey. You would mention those as contributing sources.

Justifying Your Choice of Methods

• Describe study participants specifically, and list any inclusion or exclusion criteria you used when forming your group of participants.
• Justify the size of your sample, if applicable, and describe how this affects whether your study can be generalized to larger populations. For example, if you conducted a survey of 30 percent of the student population of a university, you could potentially apply those results to the student body as a whole, but maybe not to students at other universities.

• Reading other research papers is a good way to identify potential problems that commonly arise with various methods. State whether you actually encountered any of these common problems during your research.

• If you encountered any problems as you collected data, explain clearly the steps you took to minimize the effect that problem would have on your results.

• In some cases, this may be as simple as stating that while there were numerous studies using one method, there weren't any using your method, which caused a gap in understanding of the issue.
• For example, there may be multiple papers providing quantitative analysis of a particular social trend. However, none of these papers looked closely at how this trend was affecting the lives of people.

Connecting Your Methods to Your Research Goals

• Depending on your research questions, you may be mixing quantitative and qualitative analysis – just as you could potentially use both approaches. For example, you might do a statistical analysis, and then interpret those statistics through a particular theoretical lens.

• For example, suppose you're researching the effect of college education on family farms in rural America. While you could do interviews of college-educated people who grew up on a family farm, that would not give you a picture of the overall effect. A quantitative approach and statistical analysis would give you a bigger picture.

• If in answering your research questions, your findings have raised other questions that may require further research, state these briefly.
• You can also include here any limitations to your methods, or questions that weren't answered through your research.

• Generalization is more typically used in quantitative research. If you have a well-designed sample, you can statistically apply your results to the larger population your sample belongs to.

Template to Write Research Methodology

Community Q&A

• Organize your methodology section chronologically, starting with how you prepared to conduct your research methods, how you gathered data, and how you analyzed that data. [13] X Research source Thanks Helpful 0 Not Helpful 0
• Write your research methodology section in past tense, unless you're submitting the methodology section before the research described has been carried out. [14] X Research source Thanks Helpful 0 Not Helpful 0
• Discuss your plans in detail with your advisor or supervisor before committing to a particular methodology. They can help identify possible flaws in your study. [15] X Research source Thanks Helpful 0 Not Helpful 0

You Might Also Like

• ↑ http://expertjournals.com/how-to-write-a-research-methodology-for-your-academic-article/
• ↑ http://libguides.usc.edu/writingguide/methodology
• ↑ https://www.skillsyouneed.com/learn/dissertation-methodology.html
• ↑ https://uir.unisa.ac.za/bitstream/handle/10500/4245/05Chap%204_Research%20methodology%20and%20design.pdf
• ↑ https://elc.polyu.edu.hk/FYP/html/method.htm

About This Article

To write a research methodology, start with a section that outlines the problems or questions you'll be studying, including your hypotheses or whatever it is you're setting out to prove. Then, briefly explain why you chose to use either a qualitative or quantitative approach for your study. Next, go over when and where you conducted your research and what parameters you used to ensure you were objective. Finally, cite any sources you used to decide on the methodology for your research. To learn how to justify your choice of methods in your research methodology, scroll down! Did this summary help you? Yes No

• Send fan mail to authors

Reader Success Stories

Prof. Dr. Ahmed Askar

Apr 18, 2020

Did this article help you?

M. Mahmood Shah Khan

Mar 17, 2020

Shimola Makondo

Jul 20, 2019

Zain Sharif Mohammed Alnadhery

Jan 7, 2019

Lundi Dukashe

Feb 17, 2020

Featured Articles

Trending Articles

Watch Articles

• Terms of Use
• Privacy Policy
• Do Not Sell or Share My Info
• Not Selling Info

Don’t miss out! Sign up for

wikiHow’s newsletter

• USC Libraries
• Research Guides

Organizing Your Social Sciences Research Paper

• 6. The Methodology
• Purpose of Guide
• Design Flaws to Avoid
• Independent and Dependent Variables
• Glossary of Research Terms
• Reading Research Effectively
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Applying Critical Thinking
• Choosing a Title
• Making an Outline
• Paragraph Development
• Research Process Video Series
• Executive Summary
• The C.A.R.S. Model
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tiertiary Sources
• Scholarly vs. Popular Publications
• Qualitative Methods
• Quantitative Methods
• Insiderness
• Using Non-Textual Elements
• Limitations of the Study
• Common Grammar Mistakes
• Writing Concisely
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Generative AI and Writing
• USC Libraries Tutorials and Other Guides
• Bibliography

The methods section describes actions taken to investigate a research problem and the rationale for the application of specific procedures or techniques used to identify, select, process, and analyze information applied to understanding the problem, thereby, allowing the reader to critically evaluate a study’s overall validity and reliability. The methodology section of a research paper answers two main questions: How was the data collected or generated? And, how was it analyzed? The writing should be direct and precise and always written in the past tense.

Kallet, Richard H. "How to Write the Methods Section of a Research Paper." Respiratory Care 49 (October 2004): 1229-1232.

Importance of a Good Methodology Section

You must explain how you obtained and analyzed your results for the following reasons:

• Readers need to know how the data was obtained because the method you chose affects the results and, by extension, how you interpreted their significance in the discussion section of your paper.
• Methodology is crucial for any branch of scholarship because an unreliable method produces unreliable results and, as a consequence, undermines the value of your analysis of the findings.
• In most cases, there are a variety of different methods you can choose to investigate a research problem. The methodology section of your paper should clearly articulate the reasons why you have chosen a particular procedure or technique.
• The reader wants to know that the data was collected or generated in a way that is consistent with accepted practice in the field of study. For example, if you are using a multiple choice questionnaire, readers need to know that it offered your respondents a reasonable range of answers to choose from.
• The method must be appropriate to fulfilling the overall aims of the study. For example, you need to ensure that you have a large enough sample size to be able to generalize and make recommendations based upon the findings.
• The methodology should discuss the problems that were anticipated and the steps you took to prevent them from occurring. For any problems that do arise, you must describe the ways in which they were minimized or why these problems do not impact in any meaningful way your interpretation of the findings.
• In the social and behavioral sciences, it is important to always provide sufficient information to allow other researchers to adopt or replicate your methodology. This information is particularly important when a new method has been developed or an innovative use of an existing method is utilized.

Bem, Daryl J. Writing the Empirical Journal Article. Psychology Writing Center. University of Washington; Denscombe, Martyn. The Good Research Guide: For Small-Scale Social Research Projects . 5th edition. Buckingham, UK: Open University Press, 2014; Lunenburg, Frederick C. Writing a Successful Thesis or Dissertation: Tips and Strategies for Students in the Social and Behavioral Sciences . Thousand Oaks, CA: Corwin Press, 2008.

Structure and Writing Style

I.  Groups of Research Methods

There are two main groups of research methods in the social sciences:

• The e mpirical-analytical group approaches the study of social sciences in a similar manner that researchers study the natural sciences . This type of research focuses on objective knowledge, research questions that can be answered yes or no, and operational definitions of variables to be measured. The empirical-analytical group employs deductive reasoning that uses existing theory as a foundation for formulating hypotheses that need to be tested. This approach is focused on explanation.
• The i nterpretative group of methods is focused on understanding phenomenon in a comprehensive, holistic way . Interpretive methods focus on analytically disclosing the meaning-making practices of human subjects [the why, how, or by what means people do what they do], while showing how those practices arrange so that it can be used to generate observable outcomes. Interpretive methods allow you to recognize your connection to the phenomena under investigation. However, the interpretative group requires careful examination of variables because it focuses more on subjective knowledge.

II.  Content

The introduction to your methodology section should begin by restating the research problem and underlying assumptions underpinning your study. This is followed by situating the methods you used to gather, analyze, and process information within the overall “tradition” of your field of study and within the particular research design you have chosen to study the problem. If the method you choose lies outside of the tradition of your field [i.e., your review of the literature demonstrates that the method is not commonly used], provide a justification for how your choice of methods specifically addresses the research problem in ways that have not been utilized in prior studies.

The remainder of your methodology section should describe the following:

• Decisions made in selecting the data you have analyzed or, in the case of qualitative research, the subjects and research setting you have examined,
• Tools and methods used to identify and collect information, and how you identified relevant variables,
• The ways in which you processed the data and the procedures you used to analyze that data, and
• The specific research tools or strategies that you utilized to study the underlying hypothesis and research questions.

In addition, an effectively written methodology section should:

• Introduce the overall methodological approach for investigating your research problem . Is your study qualitative or quantitative or a combination of both (mixed method)? Are you going to take a special approach, such as action research, or a more neutral stance?
• Indicate how the approach fits the overall research design . Your methods for gathering data should have a clear connection to your research problem. In other words, make sure that your methods will actually address the problem. One of the most common deficiencies found in research papers is that the proposed methodology is not suitable to achieving the stated objective of your paper.
• Describe the specific methods of data collection you are going to use , such as, surveys, interviews, questionnaires, observation, archival research. If you are analyzing existing data, such as a data set or archival documents, describe how it was originally created or gathered and by whom. Also be sure to explain how older data is still relevant to investigating the current research problem.
• Explain how you intend to analyze your results . Will you use statistical analysis? Will you use specific theoretical perspectives to help you analyze a text or explain observed behaviors? Describe how you plan to obtain an accurate assessment of relationships, patterns, trends, distributions, and possible contradictions found in the data.
• Provide background and a rationale for methodologies that are unfamiliar for your readers . Very often in the social sciences, research problems and the methods for investigating them require more explanation/rationale than widely accepted rules governing the natural and physical sciences. Be clear and concise in your explanation.
• Provide a justification for subject selection and sampling procedure . For instance, if you propose to conduct interviews, how do you intend to select the sample population? If you are analyzing texts, which texts have you chosen, and why? If you are using statistics, why is this set of data being used? If other data sources exist, explain why the data you chose is most appropriate to addressing the research problem.
• Provide a justification for case study selection . A common method of analyzing research problems in the social sciences is to analyze specific cases. These can be a person, place, event, phenomenon, or other type of subject of analysis that are either examined as a singular topic of in-depth investigation or multiple topics of investigation studied for the purpose of comparing or contrasting findings. In either method, you should explain why a case or cases were chosen and how they specifically relate to the research problem.
• Describe potential limitations . Are there any practical limitations that could affect your data collection? How will you attempt to control for potential confounding variables and errors? If your methodology may lead to problems you can anticipate, state this openly and show why pursuing this methodology outweighs the risk of these problems cropping up.

NOTE:   Once you have written all of the elements of the methods section, subsequent revisions should focus on how to present those elements as clearly and as logically as possibly. The description of how you prepared to study the research problem, how you gathered the data, and the protocol for analyzing the data should be organized chronologically. For clarity, when a large amount of detail must be presented, information should be presented in sub-sections according to topic. If necessary, consider using appendices for raw data.

ANOTHER NOTE: If you are conducting a qualitative analysis of a research problem , the methodology section generally requires a more elaborate description of the methods used as well as an explanation of the processes applied to gathering and analyzing of data than is generally required for studies using quantitative methods. Because you are the primary instrument for generating the data [e.g., through interviews or observations], the process for collecting that data has a significantly greater impact on producing the findings. Therefore, qualitative research requires a more detailed description of the methods used.

YET ANOTHER NOTE:   If your study involves interviews, observations, or other qualitative techniques involving human subjects , you may be required to obtain approval from the university's Office for the Protection of Research Subjects before beginning your research. This is not a common procedure for most undergraduate level student research assignments. However, i f your professor states you need approval, you must include a statement in your methods section that you received official endorsement and adequate informed consent from the office and that there was a clear assessment and minimization of risks to participants and to the university. This statement informs the reader that your study was conducted in an ethical and responsible manner. In some cases, the approval notice is included as an appendix to your paper.

III.  Problems to Avoid

Irrelevant Detail The methodology section of your paper should be thorough but concise. Do not provide any background information that does not directly help the reader understand why a particular method was chosen, how the data was gathered or obtained, and how the data was analyzed in relation to the research problem [note: analyzed, not interpreted! Save how you interpreted the findings for the discussion section]. With this in mind, the page length of your methods section will generally be less than any other section of your paper except the conclusion.

Unnecessary Explanation of Basic Procedures Remember that you are not writing a how-to guide about a particular method. You should make the assumption that readers possess a basic understanding of how to investigate the research problem on their own and, therefore, you do not have to go into great detail about specific methodological procedures. The focus should be on how you applied a method , not on the mechanics of doing a method. An exception to this rule is if you select an unconventional methodological approach; if this is the case, be sure to explain why this approach was chosen and how it enhances the overall process of discovery.

Problem Blindness It is almost a given that you will encounter problems when collecting or generating your data, or, gaps will exist in existing data or archival materials. Do not ignore these problems or pretend they did not occur. Often, documenting how you overcame obstacles can form an interesting part of the methodology. It demonstrates to the reader that you can provide a cogent rationale for the decisions you made to minimize the impact of any problems that arose.

Literature Review Just as the literature review section of your paper provides an overview of sources you have examined while researching a particular topic, the methodology section should cite any sources that informed your choice and application of a particular method [i.e., the choice of a survey should include any citations to the works you used to help construct the survey].

It’s More than Sources of Information! A description of a research study's method should not be confused with a description of the sources of information. Such a list of sources is useful in and of itself, especially if it is accompanied by an explanation about the selection and use of the sources. The description of the project's methodology complements a list of sources in that it sets forth the organization and interpretation of information emanating from those sources.

Azevedo, L.F. et al. "How to Write a Scientific Paper: Writing the Methods Section." Revista Portuguesa de Pneumologia 17 (2011): 232-238; Blair Lorrie. “Choosing a Methodology.” In Writing a Graduate Thesis or Dissertation , Teaching Writing Series. (Rotterdam: Sense Publishers 2016), pp. 49-72; Butin, Dan W. The Education Dissertation A Guide for Practitioner Scholars . Thousand Oaks, CA: Corwin, 2010; Carter, Susan. Structuring Your Research Thesis . New York: Palgrave Macmillan, 2012; Kallet, Richard H. “How to Write the Methods Section of a Research Paper.” Respiratory Care 49 (October 2004):1229-1232; Lunenburg, Frederick C. Writing a Successful Thesis or Dissertation: Tips and Strategies for Students in the Social and Behavioral Sciences . Thousand Oaks, CA: Corwin Press, 2008. Methods Section. The Writer’s Handbook. Writing Center. University of Wisconsin, Madison; Rudestam, Kjell Erik and Rae R. Newton. “The Method Chapter: Describing Your Research Plan.” In Surviving Your Dissertation: A Comprehensive Guide to Content and Process . (Thousand Oaks, Sage Publications, 2015), pp. 87-115; What is Interpretive Research. Institute of Public and International Affairs, University of Utah; Writing the Experimental Report: Methods, Results, and Discussion. The Writing Lab and The OWL. Purdue University; Methods and Materials. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper. Department of Biology. Bates College.

Writing Tip

Statistical Designs and Tests? Do Not Fear Them!

Don't avoid using a quantitative approach to analyzing your research problem just because you fear the idea of applying statistical designs and tests. A qualitative approach, such as conducting interviews or content analysis of archival texts, can yield exciting new insights about a research problem, but it should not be undertaken simply because you have a disdain for running a simple regression. A well designed quantitative research study can often be accomplished in very clear and direct ways, whereas, a similar study of a qualitative nature usually requires considerable time to analyze large volumes of data and a tremendous burden to create new paths for analysis where previously no path associated with your research problem had existed.

To locate data and statistics, GO HERE .

Another Writing Tip

Knowing the Relationship Between Theories and Methods

There can be multiple meaning associated with the term "theories" and the term "methods" in social sciences research. A helpful way to delineate between them is to understand "theories" as representing different ways of characterizing the social world when you research it and "methods" as representing different ways of generating and analyzing data about that social world. Framed in this way, all empirical social sciences research involves theories and methods, whether they are stated explicitly or not. However, while theories and methods are often related, it is important that, as a researcher, you deliberately separate them in order to avoid your theories playing a disproportionate role in shaping what outcomes your chosen methods produce.

Introspectively engage in an ongoing dialectic between the application of theories and methods to help enable you to use the outcomes from your methods to interrogate and develop new theories, or ways of framing conceptually the research problem. This is how scholarship grows and branches out into new intellectual territory.

Reynolds, R. Larry. Ways of Knowing. Alternative Microeconomics . Part 1, Chapter 3. Boise State University; The Theory-Method Relationship. S-Cool Revision. United Kingdom.

Yet Another Writing Tip

Methods and the Methodology

Do not confuse the terms "methods" and "methodology." As Schneider notes, a method refers to the technical steps taken to do research . Descriptions of methods usually include defining and stating why you have chosen specific techniques to investigate a research problem, followed by an outline of the procedures you used to systematically select, gather, and process the data [remember to always save the interpretation of data for the discussion section of your paper].

The methodology refers to a discussion of the underlying reasoning why particular methods were used . This discussion includes describing the theoretical concepts that inform the choice of methods to be applied, placing the choice of methods within the more general nature of academic work, and reviewing its relevance to examining the research problem. The methodology section also includes a thorough review of the methods other scholars have used to study the topic.

Bryman, Alan. "Of Methods and Methodology." Qualitative Research in Organizations and Management: An International Journal 3 (2008): 159-168; Schneider, Florian. “What's in a Methodology: The Difference between Method, Methodology, and Theory…and How to Get the Balance Right?” PoliticsEastAsia.com. Chinese Department, University of Leiden, Netherlands.

• << Previous: Scholarly vs. Popular Publications
• Next: Qualitative Methods >>
• Last Updated: May 30, 2024 9:38 AM
• URL: https://libguides.usc.edu/writingguide

• Affiliate Program

• UNITED STATES
• 台灣 (TAIWAN)
• TÜRKIYE (TURKEY)
• Academic Editing Services
• - Research Paper
• - Journal Manuscript
• - Dissertation
• - College & University Assignments
• Admissions Editing Services
• - Application Essay
• - Personal Statement
• - Recommendation Letter
• - Cover Letter
• - CV/Resume
• Business Editing Services
• - Business Documents
• - Report & Brochure
• - Website & Blog
• Writer Editing Services
• - Script & Screenplay
• Our Editors
• Client Reviews
• Editing & Proofreading Prices
• Wordvice Points
• Partner Discount
• Plagiarism Checker
• APA Citation Generator
• MLA Citation Generator
• Chicago Citation Generator
• Vancouver Citation Generator
• - APA Style
• - MLA Style
• - Chicago Style
• - Vancouver Style
• Writing & Editing Guide
• Academic Resources
• Admissions Resources

How to Write a Methods Section for a Research Paper

A common piece of advice for authors preparing their first journal article for publication is to start with the methods section: just list everything that was done and go from there. While that might seem like a very practical approach to a first draft, if you do this without a clear outline and a story in mind, you can easily end up with journal manuscript sections that are not logically related to each other. 

Since the methods section constitutes the core of your paper, no matter when you write it, you need to use it to guide the reader carefully through your story from beginning to end without leaving questions unanswered. Missing or confusing details in this section will likely lead to early rejection of your manuscript or unnecessary back-and-forth with the reviewers until eventual publication. Here, you will find some useful tips on how to make your methods section the logical foundation of your research paper.

Not just a list of experiments and methods

While your introduction section provides the reader with the necessary background to understand your rationale and research question (and, depending on journal format and your personal preference, might already summarize the results), the methods section explains what exactly you did and how you did it. The point of this section is not to list all the boring details just for the sake of completeness. The purpose of the methods sections is to enable the reader to replicate exactly what you did, verify or corroborate your results, or maybe find that there are factors you did not consider or that are more relevant than expected. 

To make this section as easy to read as possible, you must clearly connect it to the information you provide in the introduction section before and the results section after, it needs to have a clear structure (chronologically or according to topics), and you need to present your results according to the same structure or topics later in the manuscript. There are also official guidelines and journal instructions to follow and ethical issues to avoid to ensure that your manuscript can quickly reach the publication stage.

Table of Contents:

• General Methods Structure: What is Your Story? 
• What Methods Should You Report (and Leave Out)? 
• Details Frequently Missing from the Methods Section

More Journal Guidelines to Consider 

• Accurate and Appropriate Language in the Methods

General Methods Section Structure: What Is Your Story? 

You might have conducted a number of experiments, maybe also a pilot before the main study to determine some specific factors or a follow-up experiment to clarify unclear details later in the process. Throwing all of these into your methods section, however, might not help the reader understand how everything is connected and how useful and appropriate your methodological approach is to investigate your specific research question. You therefore need to first come up with a clear outline and decide what to report and how to present that to the reader.

The first (and very important) decision to make is whether you present your experiments chronologically (e.g., Experiment 1, Experiment 2, Experiment 3… ), and guide the reader through every step of the process, or if you organize everything according to subtopics (e.g., Behavioral measures, Structural imaging markers, Functional imaging markers… ). In both cases, you need to use clear subheaders for the different subsections of your methods, and, very importantly, follow the same structure or focus on the same topics/measures in the results section so that the reader can easily follow along (see the two examples below).

If you are in doubt which way of organizing your experiments is better for your study, just ask yourself the following questions:

• Does the reader need to know the timeline of your study? 
• Is it relevant that one experiment was conducted first, because the outcome of this experiment determined the stimuli or factors that went into the next?
• Did the results of your first experiment leave important questions open that you addressed in an additional experiment (that was maybe not planned initially)?
• Is the answer to all of these questions “no”? Then organizing your methods section according to topics of interest might be the more logical choice.

If you think your timeline, protocol, or setup might be confusing or difficult for the reader to grasp, consider adding a graphic, flow diagram, decision tree, or table as a visual aid.

What Methods Should You Report (and Leave Out)?

The answer to this question is quite simple–you need to report everything that another researcher needs to know to be able to replicate your study. Just imagine yourself reading your methods section in the future and trying to set up the same experiments again without prior knowledge. You would probably need to ask questions such as:

• Where did you conduct your experiments (e.g., in what kind of room, under what lighting or temperature conditions, if those are relevant)? 
• What devices did you use? Are there specific settings to report?
• What specific software (and version of that software) did you use?
• How did you find and select your participants?
• How did you assign participants into groups?  
• Did you exclude participants from the analysis? Why and how?
• Where did your reagents or antibodies come from? Can you provide a Research Resource Identifier (RRID) ?
• Did you make your stimuli yourself or did you get them from somewhere?
• Are the stimuli you used available for other researchers?
• What kind of questionnaires did you use? Have they been validated?
• How did you analyze your data? What level of significance did you use?
• Were there any technical issues and did you have to adjust protocols?

Note that for every experimental detail you provide, you need to tell the reader (briefly) why you used this type of stimulus/this group of participants/these specific amounts of reagents. If there is earlier published research reporting the same methods, cite those studies. If you did pilot experiments to determine those details, describe the procedures and the outcomes of these experiments. If you made assumptions about the suitability of something based on the literature and common practice at your institution, then explain that to the reader.

In a nutshell, established methods need to be cited, and new methods need to be clearly described and briefly justified. However, if the fact that you use a new approach or a method that is not traditionally used for the data or phenomenon you study is one of the main points of your study (and maybe already reflected in the title of your article), then you need to explain your rationale for doing so in the introduction already and discuss it in more detail in the discussion section .

Note that you also need to explain your statistical analyses at the end of your methods section. You present the results of these analyses later, in the results section of your paper, but you need to show the reader in the methods section already that your approach is either well-established or valid, even if it is new or unusual. 

When it comes to the question of what details you should leave out, the answer is equally simple ‒ everything that you would not need to replicate your study in the future. If the educational background of your participants is listed in your institutional database but is not relevant to your study outcome, then don’t include that. Other things you should not include in the methods section:

• Background information that you already presented in the introduction section.
• In-depth comparisons of different methods ‒ these belong in the discussion section.
• Results, unless you summarize outcomes of pilot experiments that helped you determine factors for your main experiment.

Also, make sure your subheadings are as clear as possible, suit the structure you chose for your methods section, and are in line with the target journal guidelines. If you studied a disease intervention in human participants, then your methods section could look similar to this:

Since the main point of interest here are your patient-centered outcome variables, you would center your results section on these as well and choose your headers accordingly (e.g., Patient characteristics, Baseline evaluation, Outcome variable 1, Outcome variable 2, Drop-out rate ). 

If, instead, you did a series of visual experiments investigating the perception of faces including a pilot experiment to create the stimuli for your actual study, you would need to structure your methods section in a very different way, maybe like this:

Since here the analysis and outcome of the pilot experiment are already described in the methods section (as the basis for the main experimental setup and procedure), you do not have to mention it again in the results section. Instead, you could choose the two main experiments to structure your results section ( Discrimination and classification, Familiarization and adaptation ), or divide the results into all your test measures and/or potential interactions you described in the methods section (e.g., Discrimination performance, Classification performance, Adaptation aftereffects, Correlation analysis ).

Details Commonly Missing from the Methods Section

Manufacturer information.

For laboratory or technical equipment, you need to provide the model, name of the manufacturer, and company’s location. The usual format for these details is the product name (company name, city, state) for US-based manufacturers and the product name (company name, city/town, country) for companies outside the US.

Sample size and power estimation

Power and sample size estimations are measures for how many patients or participants are needed in a study in order to detect statistical significance and draw meaningful conclusions from the results. Outside of the medical field, studies are sometimes still conducted with a “the more the better” approach in mind, but since many journals now ask for those details, it is better to not skip this important step.

Ethical guidelines and approval

In addition to describing what you did, you also need to assure the editor and reviewers that your methods and protocols followed all relevant ethical standards and guidelines. This includes applying for approval at your local or national ethics committee, providing the name or location of that committee as well as the approval reference number you received, and, if you studied human participants, a statement that participants were informed about all relevant experimental details in advance and signed consent forms before the start of the study. For animal studies, you usually need to provide a statement that all procedures included in your research were in line with the Declaration of Helsinki. Make sure you check the target journal guidelines carefully, as these statements sometimes need to be placed at the end of the main article text rather than in the method section.

Structure & word limitations

While many journals simply follow the usual style guidelines (e.g., APA for the social sciences and psychology, AMA for medical research) and let you choose the headers of your method section according to your preferred structure and focus, some have precise guidelines and strict limitations, for example, on manuscript length and the maximum number of subsections or header levels. Make sure you read the instructions of your target journal carefully and restructure your method section if necessary before submission. If the journal does not give you enough space to include all the details that you deem necessary, then you can usually submit additional details as “supplemental” files and refer to those in the main text where necessary.

Standardized checklists

In addition to ethical guidelines and approval, journals also often ask you to submit one of the official standardized checklists for different study types to ensure all essential details are included in your manuscript. For example, there are checklists for randomized clinical trials, CONSORT (Consolidated Standards of Reporting Trials) , cohort, case-control, cross‐sectional studies, STROBE (STrengthening the Reporting of OBservational studies in Epidemiology ), diagnostic accuracy, STARD (STAndards for the Reporting of Diagnostic accuracy studies) , systematic reviews and meta‐analyses PRISMA (Preferred Reporting Items for Systematic reviews and Meta‐Analyses) , and Case reports, CARE (CAse REport) .

Make sure you check if the manuscript uses a single- or double-blind review procedure , and delete all information that might allow a reviewer to guess where the authors are located from the manuscript text if necessary. This means that your method section cannot list the name and location of your institution, the names of researchers who conducted specific tests, or the name of your institutional ethics committee.  

Accurate and Appropriate Language in the Methods Section

Like all sections of your research paper, your method section needs to be written in an academic tone . That means it should be formal, vague expressions and colloquial language need to be avoided, and you need to correctly cite all your sources. If you describe human participants in your method section then you should be especially careful about your choice of words. For example, “participants” sounds more respectful than “subjects,” and patient-first language, that is, “patients with cancer,” is considered more appropriate than “cancer patients” by many journals.

Passive voice is often considered the standard for research papers, but it is completely fine to mix passive and active voice, even in the method section, to make your text as clear and concise as possible. Use the simple past tense to describe what you did, and the present tense when you refer to diagrams or tables. Have a look at this article if you need more general input on which verb tenses to use in a research paper . 

Lastly, make sure you label all the standard tests and questionnaires you use correctly (look up the original publication when in doubt) and spell genes and proteins according to the common databases for the species you studied, such as the HUGO Gene Nomenclature Committee database for human studies .  

Visit Wordvice AI’s AI Text Editor to receive a free grammar check and English editing services (including manuscript editing , paper editing , and dissertation editing ) before submitting your manuscript to journal editors.

We use cookies to give you the best experience possible. By continuing we’ll assume you’re on board with our cookie policy

• A Research Guide
• Research Paper Guide

How to Write a Methods Section for a Research Paper

• Purpose of methods section
• Key components
• How to describe
• Step-by-step guide
• Methods section formats
• Additional elements

Purpose of the Methods section

What key components must be included in the methods section.

• Research design. This is the most important section to help your audience see the methods used. Make sure to structure your research methodology correctly and follow the rules of the scientific field. Depending on your work type, the research design of a methods section should represent an outline with the basic introduction, set objectives, a lab/field environment, and other related elements.
• Participants. When dealing with a sample group or a case study, you must discuss the research participants. Always narrow things down to why a specific group of participants have been chosen and talk about how it will be helpful to stay objective and unbiased.
• Equipment. This part describes the set of tools that have been used. Writing a methods section can include software, hardware, voice recorders, chemical equipment, special labs, and more.
• Materials. Describe what materials have been used for your studies. Talk about the studies and procedures used based on the available data.
• Variables. Talk about independent and dependent variables. The independent variables are related to those elements of your research that can be changed, like the amount of water or the use of certain colors to replicate a process. As for dependent variables, these are those affected by specific changes. In other words, variables in a methods section can change during the process of studies, like the experiment outcome or exceptions in the sample group.
• Participant behavior . This is where you talk about what has been experienced by the participants (if relevant). A methods section example may include a description of actions taken, processes experienced, and the environment used to conduct the research.

How to describe your research design and procedures?

• Reflect on your hypothesis . Talk about variables or aspects you should research. This is a procedure section of a research paper where you describe the type of information you must collect as you work on your main arguments. Narrow down the scope of data that has to be evaluated.
• Define your research approach . In most cases, it can be either qualitative or quantitative. While you can choose a mixture of both for your paper, focusing on one to clarify a relevant section is recommended.
• Choose your research design type . If you are dealing with quantitative research, it’s possible to use experimental, quasi-experimental, correlational, or descriptive design methods. Suppose you are choosing a qualitative design methodology. In that case, you may approach ethnography (a method based on cultural immersion, inside research), phenomenology (research based on the perspective of an individual, an intuitive analytical variable), or a grounded method (social-based research).
• Define your research sampling method . The risk here is to generate excessive data, making it extremely challenging to see things to include and avoid. You can choose a probabilistic sampling method or a deterministic sampling approach, also known as non-random selection. Certain methods can fit better depending on the materials section of the research paper. If you still choose a non-random design, the only challenge is that the latter sampling method is more biased.
• Evaluate the best data collection method . Start your Methodology section by marking the difference between your primary (surveys, interviews) and secondary data (references that have already been published) sources.
• Choose an approach to data analysis . You can alternate between qualitative and quantitative data analysis methods section approaches.

Step-by-step guide on how to compose your Methods section

• Step 1: Focus on two main purposes of your Methods section. You should help your target audience understand your research project easier and make it possible to replicate all the vital processes.
• Step 2: Offer sufficient information to make replication unbiased and complete. While you may have your research project ready for publishing, providing overly detailed information is only sometimes necessary. Always check things twice to learn the requirements. Most importantly, keep your research transparent, provide a clear methodology, and keep every step easy to replicate.
• Step 3: To make things easier, imagine you are an individual in your target audience. Think about how you would replicate your study and what scientific paper methods you would find accessible. Ask yourself about what information you would require. Take notes and create 2-3 outlines for additional clarity.
• Step 4: Consider adding visual aid elements. It may include relevant flow charts, mind maps, checklists, or statistical data for your methodology. It will help your readers interpret the study and avoid unnecessary steps.
• Step 5: Always adhere to strict ethical standards and scientific guidelines. Even though the “Ethical Guidelines” section will be presented in another research paper part, you must show the main arguments and thesis concerning ethical rules. It will show that you are using strict standards and following the rules related to your discipline.

Methods section checklist

• Is your logic consistent in every section?
• Does your introduction provide sufficient background information?
• Does your methodology structure sound clear and follows a chronology of the research?
• Do you provide the results of your research in the same format?
• Can you replicate your study based on a given methodology?
• Do your readers have all the necessary objectives mentioned?
• Are the tools used mentioned?

Methods section formats and features

Additional elements to consider.

• Location specifics. This is where the location and research environment can make a major difference for replication purposes.
• Limitations of the research. Talk about the limitations and specifics of the tools and methods being used.
• Writing style and tone. Remember to write in the past tense and keep the same tone throughout your research paper.
• Ethical considerations. Clarify and specify all the ethical guidelines for your institution, a scientific journal methodology, and a field of science.
• Data analysis methodology.
• Participants and subjects.
• Data collection methodology.
• Things required to replicate the research.
• Addressing the research objectives.
• Basic research question.

• Writing a Research Paper
• Research Paper Title
• Research Paper Sources
• Research Paper Problem Statement
• Research Paper Thesis Statement
• Hypothesis for a Research Paper
• Research Question
• Research Paper Outline
• Research Paper Summary
• Research Paper Prospectus
• Research Paper Proposal
• Research Paper Format
• Research Paper Styles
• AMA Style Research Paper
• MLA Style Research Paper
• Chicago Style Research Paper
• APA Style Research Paper
• Research Paper Structure
• Research Paper Cover Page
• Research Paper Abstract
• Research Paper Introduction
• Research Paper Body Paragraph
• Research Paper Literature Review
• Research Paper Background
• Research Paper Methods Section
• Research Paper Results Section
• Research Paper Discussion Section
• Research Paper Conclusion
• Research Paper Appendix
• Research Paper Bibliography
• APA Reference Page
• Annotated Bibliography
• Bibliography vs Works Cited vs References Page
• Research Paper Types
• What is Qualitative Research

Receive paper in 3 Hours!

• Choose the number of pages.
• Select your deadline.
• Complete your order.

Number of Pages

550 words (double spaced)

Deadline: 10 days left

By clicking "Log In", you agree to our terms of service and privacy policy . We'll occasionally send you account related and promo emails.

Sign Up for your FREE account

• Langson Library
• Science Library
• Grunigen Medical Library
• Law Library
• Connect From Off-Campus
• Accessibility
• Gateway Study Center

Email this link

Writing a scientific paper.

• Writing a lab report
• INTRODUCTION

Writing a "good" methods section

"methods checklist" from: how to write a good scientific paper. chris a. mack. spie. 2018..

• LITERATURE CITED
• Bibliography of guides to scientific writing and presenting
• Peer Review
• Presentations
• Lab Report Writing Guides on the Web

The purpose is to provide enough detail that a competent worker could repeat the experiment. Many of your readers will skip this section because they already know from the Introduction the general methods you used. However careful writing of this section is important because for your results to be of scientific merit they must be reproducible. Otherwise your paper does not represent good science.

• Exact technical specifications and quantities and source or method of preparation
• Describe equipment used and provide illustrations where relevant.
• Chronological presentation (but related methods described together)
• Questions about "how" and "how much" are answered for the reader and not left for them to puzzle over
• Discuss statistical methods only if unusual or advanced
• When a large number of components are used prepare tables for the benefit of the reader
• Do not state the action without stating the agent of the action
• Describe how the results were generated with sufficient detail so that an independent researcher (working in the same field) could reproduce the results sufficiently to allow validation of the conclusions.
• Can the reader assess internal validity (conclusions are supported by the results presented)?
• Can the reader assess external validity (conclusions are properly generalized beyond these specific results)?
• Has the chosen method been justified?
• Are data analysis and statistical approaches justified, with assumptions and biases considered?
• Avoid: including results in the Method section; including extraneous details (unnecessary to enable reproducibility or judge validity); treating the method as a chronological history of events; unneeded references to commercial products; references to “proprietary” products or processes unavailable to the reader. 
• << Previous: INTRODUCTION
• Next: RESULTS >>
• Last Updated: Aug 4, 2023 9:33 AM
• URL: https://guides.lib.uci.edu/scientificwriting

Off-campus? Please use the Software VPN and choose the group UCIFull to access licensed content. For more information, please Click here

Software VPN is not available for guests, so they may not have access to some content when connecting from off-campus.

How to write the methods section of a research paper

Affiliation.

• 1 Respiratory Care Services, San Francisco General Hospital, NH:GA-2, 1001 Potrero Avenue, San Francisco, CA 94110, USA. [email protected]
• PMID: 15447808

The methods section of a research paper provides the information by which a study's validity is judged. Therefore, it requires a clear and precise description of how an experiment was done, and the rationale for why specific experimental procedures were chosen. The methods section should describe what was done to answer the research question, describe how it was done, justify the experimental design, and explain how the results were analyzed. Scientific writing is direct and orderly. Therefore, the methods section structure should: describe the materials used in the study, explain how the materials were prepared for the study, describe the research protocol, explain how measurements were made and what calculations were performed, and state which statistical tests were done to analyze the data. Once all elements of the methods section are written, subsequent drafts should focus on how to present those elements as clearly and logically as possibly. The description of preparations, measurements, and the protocol should be organized chronologically. For clarity, when a large amount of detail must be presented, information should be presented in sub-sections according to topic. Material in each section should be organized by topic from most to least important.

• Biomedical Research*
• Research Design
• Writing* / standards

• Privacy Policy

Home » Research Paper – Structure, Examples and Writing Guide

Research Paper – Structure, Examples and Writing Guide

Table of Contents

Research Paper

Definition:

Research Paper is a written document that presents the author’s original research, analysis, and interpretation of a specific topic or issue.

It is typically based on Empirical Evidence, and may involve qualitative or quantitative research methods, or a combination of both. The purpose of a research paper is to contribute new knowledge or insights to a particular field of study, and to demonstrate the author’s understanding of the existing literature and theories related to the topic.

Structure of Research Paper

The structure of a research paper typically follows a standard format, consisting of several sections that convey specific information about the research study. The following is a detailed explanation of the structure of a research paper:

The title page contains the title of the paper, the name(s) of the author(s), and the affiliation(s) of the author(s). It also includes the date of submission and possibly, the name of the journal or conference where the paper is to be published.

The abstract is a brief summary of the research paper, typically ranging from 100 to 250 words. It should include the research question, the methods used, the key findings, and the implications of the results. The abstract should be written in a concise and clear manner to allow readers to quickly grasp the essence of the research.

Introduction

The introduction section of a research paper provides background information about the research problem, the research question, and the research objectives. It also outlines the significance of the research, the research gap that it aims to fill, and the approach taken to address the research question. Finally, the introduction section ends with a clear statement of the research hypothesis or research question.

Literature Review

The literature review section of a research paper provides an overview of the existing literature on the topic of study. It includes a critical analysis and synthesis of the literature, highlighting the key concepts, themes, and debates. The literature review should also demonstrate the research gap and how the current study seeks to address it.

The methods section of a research paper describes the research design, the sample selection, the data collection and analysis procedures, and the statistical methods used to analyze the data. This section should provide sufficient detail for other researchers to replicate the study.

The results section presents the findings of the research, using tables, graphs, and figures to illustrate the data. The findings should be presented in a clear and concise manner, with reference to the research question and hypothesis.

The discussion section of a research paper interprets the findings and discusses their implications for the research question, the literature review, and the field of study. It should also address the limitations of the study and suggest future research directions.

The conclusion section summarizes the main findings of the study, restates the research question and hypothesis, and provides a final reflection on the significance of the research.

The references section provides a list of all the sources cited in the paper, following a specific citation style such as APA, MLA or Chicago.

How to Write Research Paper

You can write Research Paper by the following guide:

• Choose a Topic: The first step is to select a topic that interests you and is relevant to your field of study. Brainstorm ideas and narrow down to a research question that is specific and researchable.
• Conduct a Literature Review: The literature review helps you identify the gap in the existing research and provides a basis for your research question. It also helps you to develop a theoretical framework and research hypothesis.
• Develop a Thesis Statement : The thesis statement is the main argument of your research paper. It should be clear, concise and specific to your research question.
• Plan your Research: Develop a research plan that outlines the methods, data sources, and data analysis procedures. This will help you to collect and analyze data effectively.
• Collect and Analyze Data: Collect data using various methods such as surveys, interviews, observations, or experiments. Analyze data using statistical tools or other qualitative methods.
• Organize your Paper : Organize your paper into sections such as Introduction, Literature Review, Methods, Results, Discussion, and Conclusion. Ensure that each section is coherent and follows a logical flow.
• Write your Paper : Start by writing the introduction, followed by the literature review, methods, results, discussion, and conclusion. Ensure that your writing is clear, concise, and follows the required formatting and citation styles.
• Edit and Proofread your Paper: Review your paper for grammar and spelling errors, and ensure that it is well-structured and easy to read. Ask someone else to review your paper to get feedback and suggestions for improvement.
• Cite your Sources: Ensure that you properly cite all sources used in your research paper. This is essential for giving credit to the original authors and avoiding plagiarism.

Research Paper Example

Note : The below example research paper is for illustrative purposes only and is not an actual research paper. Actual research papers may have different structures, contents, and formats depending on the field of study, research question, data collection and analysis methods, and other factors. Students should always consult with their professors or supervisors for specific guidelines and expectations for their research papers.

Research Paper Example sample for Students:

Title: The Impact of Social Media on Mental Health among Young Adults

Abstract: This study aims to investigate the impact of social media use on the mental health of young adults. A literature review was conducted to examine the existing research on the topic. A survey was then administered to 200 university students to collect data on their social media use, mental health status, and perceived impact of social media on their mental health. The results showed that social media use is positively associated with depression, anxiety, and stress. The study also found that social comparison, cyberbullying, and FOMO (Fear of Missing Out) are significant predictors of mental health problems among young adults.

Introduction: Social media has become an integral part of modern life, particularly among young adults. While social media has many benefits, including increased communication and social connectivity, it has also been associated with negative outcomes, such as addiction, cyberbullying, and mental health problems. This study aims to investigate the impact of social media use on the mental health of young adults.

Literature Review: The literature review highlights the existing research on the impact of social media use on mental health. The review shows that social media use is associated with depression, anxiety, stress, and other mental health problems. The review also identifies the factors that contribute to the negative impact of social media, including social comparison, cyberbullying, and FOMO.

Methods : A survey was administered to 200 university students to collect data on their social media use, mental health status, and perceived impact of social media on their mental health. The survey included questions on social media use, mental health status (measured using the DASS-21), and perceived impact of social media on their mental health. Data were analyzed using descriptive statistics and regression analysis.

Results : The results showed that social media use is positively associated with depression, anxiety, and stress. The study also found that social comparison, cyberbullying, and FOMO are significant predictors of mental health problems among young adults.

Discussion : The study’s findings suggest that social media use has a negative impact on the mental health of young adults. The study highlights the need for interventions that address the factors contributing to the negative impact of social media, such as social comparison, cyberbullying, and FOMO.

Conclusion : In conclusion, social media use has a significant impact on the mental health of young adults. The study’s findings underscore the need for interventions that promote healthy social media use and address the negative outcomes associated with social media use. Future research can explore the effectiveness of interventions aimed at reducing the negative impact of social media on mental health. Additionally, longitudinal studies can investigate the long-term effects of social media use on mental health.

Limitations : The study has some limitations, including the use of self-report measures and a cross-sectional design. The use of self-report measures may result in biased responses, and a cross-sectional design limits the ability to establish causality.

Implications: The study’s findings have implications for mental health professionals, educators, and policymakers. Mental health professionals can use the findings to develop interventions that address the negative impact of social media use on mental health. Educators can incorporate social media literacy into their curriculum to promote healthy social media use among young adults. Policymakers can use the findings to develop policies that protect young adults from the negative outcomes associated with social media use.

References :

• Twenge, J. M., & Campbell, W. K. (2019). Associations between screen time and lower psychological well-being among children and adolescents: Evidence from a population-based study. Preventive medicine reports, 15, 100918.
• Primack, B. A., Shensa, A., Escobar-Viera, C. G., Barrett, E. L., Sidani, J. E., Colditz, J. B., … & James, A. E. (2017). Use of multiple social media platforms and symptoms of depression and anxiety: A nationally-representative study among US young adults. Computers in Human Behavior, 69, 1-9.
• Van der Meer, T. G., & Verhoeven, J. W. (2017). Social media and its impact on academic performance of students. Journal of Information Technology Education: Research, 16, 383-398.

Appendix : The survey used in this study is provided below.

Social Media and Mental Health Survey

• How often do you use social media per day?
• Less than 30 minutes
• 30 minutes to 1 hour
• 1 to 2 hours
• 2 to 4 hours
• More than 4 hours
• Which social media platforms do you use?
• Others (Please specify)
• How often do you experience the following on social media?
• Social comparison (comparing yourself to others)
• Cyberbullying
• Fear of Missing Out (FOMO)
• Have you ever experienced any of the following mental health problems in the past month?
• Do you think social media use has a positive or negative impact on your mental health?
• Very positive
• Somewhat positive
• Somewhat negative
• Very negative
• In your opinion, which factors contribute to the negative impact of social media on mental health?
• Social comparison
• In your opinion, what interventions could be effective in reducing the negative impact of social media on mental health?
• Education on healthy social media use
• Counseling for mental health problems caused by social media
• Social media detox programs
• Regulation of social media use

Thank you for your participation!

Applications of Research Paper

Research papers have several applications in various fields, including:

• Advancing knowledge: Research papers contribute to the advancement of knowledge by generating new insights, theories, and findings that can inform future research and practice. They help to answer important questions, clarify existing knowledge, and identify areas that require further investigation.
• Informing policy: Research papers can inform policy decisions by providing evidence-based recommendations for policymakers. They can help to identify gaps in current policies, evaluate the effectiveness of interventions, and inform the development of new policies and regulations.
• Improving practice: Research papers can improve practice by providing evidence-based guidance for professionals in various fields, including medicine, education, business, and psychology. They can inform the development of best practices, guidelines, and standards of care that can improve outcomes for individuals and organizations.
• Educating students : Research papers are often used as teaching tools in universities and colleges to educate students about research methods, data analysis, and academic writing. They help students to develop critical thinking skills, research skills, and communication skills that are essential for success in many careers.
• Fostering collaboration: Research papers can foster collaboration among researchers, practitioners, and policymakers by providing a platform for sharing knowledge and ideas. They can facilitate interdisciplinary collaborations and partnerships that can lead to innovative solutions to complex problems.

When to Write Research Paper

Research papers are typically written when a person has completed a research project or when they have conducted a study and have obtained data or findings that they want to share with the academic or professional community. Research papers are usually written in academic settings, such as universities, but they can also be written in professional settings, such as research organizations, government agencies, or private companies.

Here are some common situations where a person might need to write a research paper:

• For academic purposes: Students in universities and colleges are often required to write research papers as part of their coursework, particularly in the social sciences, natural sciences, and humanities. Writing research papers helps students to develop research skills, critical thinking skills, and academic writing skills.
• For publication: Researchers often write research papers to publish their findings in academic journals or to present their work at academic conferences. Publishing research papers is an important way to disseminate research findings to the academic community and to establish oneself as an expert in a particular field.
• To inform policy or practice : Researchers may write research papers to inform policy decisions or to improve practice in various fields. Research findings can be used to inform the development of policies, guidelines, and best practices that can improve outcomes for individuals and organizations.
• To share new insights or ideas: Researchers may write research papers to share new insights or ideas with the academic or professional community. They may present new theories, propose new research methods, or challenge existing paradigms in their field.

Purpose of Research Paper

The purpose of a research paper is to present the results of a study or investigation in a clear, concise, and structured manner. Research papers are written to communicate new knowledge, ideas, or findings to a specific audience, such as researchers, scholars, practitioners, or policymakers. The primary purposes of a research paper are:

• To contribute to the body of knowledge : Research papers aim to add new knowledge or insights to a particular field or discipline. They do this by reporting the results of empirical studies, reviewing and synthesizing existing literature, proposing new theories, or providing new perspectives on a topic.
• To inform or persuade: Research papers are written to inform or persuade the reader about a particular issue, topic, or phenomenon. They present evidence and arguments to support their claims and seek to persuade the reader of the validity of their findings or recommendations.
• To advance the field: Research papers seek to advance the field or discipline by identifying gaps in knowledge, proposing new research questions or approaches, or challenging existing assumptions or paradigms. They aim to contribute to ongoing debates and discussions within a field and to stimulate further research and inquiry.
• To demonstrate research skills: Research papers demonstrate the author’s research skills, including their ability to design and conduct a study, collect and analyze data, and interpret and communicate findings. They also demonstrate the author’s ability to critically evaluate existing literature, synthesize information from multiple sources, and write in a clear and structured manner.

Characteristics of Research Paper

Research papers have several characteristics that distinguish them from other forms of academic or professional writing. Here are some common characteristics of research papers:

• Evidence-based: Research papers are based on empirical evidence, which is collected through rigorous research methods such as experiments, surveys, observations, or interviews. They rely on objective data and facts to support their claims and conclusions.
• Structured and organized: Research papers have a clear and logical structure, with sections such as introduction, literature review, methods, results, discussion, and conclusion. They are organized in a way that helps the reader to follow the argument and understand the findings.
• Formal and objective: Research papers are written in a formal and objective tone, with an emphasis on clarity, precision, and accuracy. They avoid subjective language or personal opinions and instead rely on objective data and analysis to support their arguments.
• Citations and references: Research papers include citations and references to acknowledge the sources of information and ideas used in the paper. They use a specific citation style, such as APA, MLA, or Chicago, to ensure consistency and accuracy.
• Peer-reviewed: Research papers are often peer-reviewed, which means they are evaluated by other experts in the field before they are published. Peer-review ensures that the research is of high quality, meets ethical standards, and contributes to the advancement of knowledge in the field.
• Objective and unbiased: Research papers strive to be objective and unbiased in their presentation of the findings. They avoid personal biases or preconceptions and instead rely on the data and analysis to draw conclusions.

Advantages of Research Paper

Research papers have many advantages, both for the individual researcher and for the broader academic and professional community. Here are some advantages of research papers:

• Contribution to knowledge: Research papers contribute to the body of knowledge in a particular field or discipline. They add new information, insights, and perspectives to existing literature and help advance the understanding of a particular phenomenon or issue.
• Opportunity for intellectual growth: Research papers provide an opportunity for intellectual growth for the researcher. They require critical thinking, problem-solving, and creativity, which can help develop the researcher’s skills and knowledge.
• Career advancement: Research papers can help advance the researcher’s career by demonstrating their expertise and contributions to the field. They can also lead to new research opportunities, collaborations, and funding.
• Academic recognition: Research papers can lead to academic recognition in the form of awards, grants, or invitations to speak at conferences or events. They can also contribute to the researcher’s reputation and standing in the field.
• Impact on policy and practice: Research papers can have a significant impact on policy and practice. They can inform policy decisions, guide practice, and lead to changes in laws, regulations, or procedures.
• Advancement of society: Research papers can contribute to the advancement of society by addressing important issues, identifying solutions to problems, and promoting social justice and equality.

Limitations of Research Paper

Research papers also have some limitations that should be considered when interpreting their findings or implications. Here are some common limitations of research papers:

• Limited generalizability: Research findings may not be generalizable to other populations, settings, or contexts. Studies often use specific samples or conditions that may not reflect the broader population or real-world situations.
• Potential for bias : Research papers may be biased due to factors such as sample selection, measurement errors, or researcher biases. It is important to evaluate the quality of the research design and methods used to ensure that the findings are valid and reliable.
• Ethical concerns: Research papers may raise ethical concerns, such as the use of vulnerable populations or invasive procedures. Researchers must adhere to ethical guidelines and obtain informed consent from participants to ensure that the research is conducted in a responsible and respectful manner.
• Limitations of methodology: Research papers may be limited by the methodology used to collect and analyze data. For example, certain research methods may not capture the complexity or nuance of a particular phenomenon, or may not be appropriate for certain research questions.
• Publication bias: Research papers may be subject to publication bias, where positive or significant findings are more likely to be published than negative or non-significant findings. This can skew the overall findings of a particular area of research.
• Time and resource constraints: Research papers may be limited by time and resource constraints, which can affect the quality and scope of the research. Researchers may not have access to certain data or resources, or may be unable to conduct long-term studies due to practical limitations.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

You may also like

Data Analysis – Process, Methods and Types

Research Summary – Structure, Examples and...

Survey Instruments – List and Their Uses

Research Results Section – Writing Guide and...

What is a Hypothesis – Types, Examples and...

Tables in Research Paper – Types, Creating Guide...

• Advanced search

Advanced Search

How to Write the Methods Section of a Research Manuscript

• Find this author on Google Scholar
• Find this author on PubMed
• Search for this author on this site
• For correspondence: [email protected]
• Figures & Data
• Info & Metrics

The methods section of a manuscript is one of the most important parts of a research paper because it provides information on the validity of the study and credibility of the results. Inadequate description of the methods has been reported as one of the main reasons for manuscript rejection. The methods section must include sufficient detail so that others could repeat the study and reproduce the results. The structure of the methods section should flow logically and chronologically. There are multiple components of methods sections, including study design, materials used, study procedures, and data analysis. Each element must be adequately described and thoroughly detailed to provide an understanding of how the results were obtained and how to interpret the findings. Studies that involved humans or animals must include an ethics statement of approval from the appropriate governing body. The methods section should explain how subjects were identified and should state inclusion and exclusion criteria. All materials used to complete the study should be described in detail, including equipment, drugs, gases, chemicals, treatments, interventions, or other items. Study procedures should outline all steps taken to obtain the results and clearly state the outcome measures. Subheadings might be helpful for organizing the methods section into subsections when there is a considerable amount of information to report. A well-written methods section will guide the reader through the research process and provide adequate information to evaluate study validity and reproduce the work. The purpose of this paper is to provide guidance for writing the methods section of a manuscript.

• research paper
• science writing
• publication
• study protocol
• Introduction

Dissemination of research findings occurs through abstracts, posters, presentations, and manuscripts. 1 , - , 3 Writing the manuscript is considered the last step of the research process because it provides a detailed account of the research from start to finish. 4 , 5 The main components of a research paper include an abstract, the introduction, methods, results, discussion, and conclusions. 3 , 4 Each section of the manuscript is important and has a specific role in describing the research story. However, the methods are one of the most critical sections of a manuscript because the details are used to evaluate and determine the validity of the study and credibility of the results. 6 Validity in research refers to reliability of the measured results: the extent to which the study accurately measured what it intended (internal validity) and how the results can be applied to the general population beyond the study (external validity). 6 , 7

The methods section describes what was done to answer the research question. 8 This section specifies how the research was done, the rationale for the procedures, what materials were used, and how the results were analyzed, all in a clear, concise, and organized manner. 6 The description of the research should provide enough detail so others could repeat the study and reproduce the results. 6 , 9 , 10 Much of the methods section should be written before the study is initiated. Indeed, for funded research, a detailed methods section is written as part of the grant application. There are several aspects of the methods sections, and the essential elements will vary, depending on the type of study. Submission requirements differ among journals; therefore, it is important to consult the instructions for authors for the specific journal to ensure that all necessary elements are included. 11 The purpose of this paper is to describe the different components of the methods section and provide guidance for writing the methods section of a research paper.

• General Considerations

An inadequate description of methods has been identified as one of the top reasons for manuscript rejection. 12 It has been suggested that including too much information is better than having insufficient detail because irrelevant content can later be omitted. 12 The methods section of a research paper is analogous to a recipe. 10 , 13 A recipe is composed of multiple elements, including the list and quantity of ingredients, equipment and tools needed and applicable settings, and the detailed instructions for how to create the recipe. Similar to a recipe, there are different elements of methods to describe in a manuscript. In general, common components of the methods section include a description of the study design, materials used, study procedures, measurements or calculations, and the statistical tests used to analyze the results. Materials used to conduct research are comparable with the ingredients, tools, and equipment for a recipe. Materials represent what was studied, including subjects, equipment or devices, and treatments or interventions. 6 , 14 The steps to create a recipe are akin to study procedures such as the process for data collection, measurements, calculations, and statistical analysis. A summary of the different elements of the methods section is included in Table 1 . The individual components for each element may vary, depending on the nature of the study.

• View inline
• Download powerpoint

Methods Section Elements

Although similarities exist between a recipe and the methods section of a research paper, the methods section should not be formatted to read like a recipe. 13 Use past tense for writing the methods section because the study has been completed and describes what was already done. 6 , 9 , 10 , 13 , 14 The methods section should be structured for logical and chronological flow. 6 , 14 , 15 Use of subheadings can be helpful for organizing the different components for the methods section when there is a substantial amount of detail to describe. 6 , 13 However, subheadings may not be required by some journals. An excessive use of subheadings can be distracting to the reader by interrupting the flow of the manuscript. There should not be a subheading for every paragraph. This is particularly distracting when each subheading is followed by a short 1- or 2-sentence paragraph. Paragraphs with fewer than 3 sentences should be avoided; combine the information with another paragraph unless the journal to which the paper will be submitted requires specific subheadings. Subheadings can be useful as an outline when writing the methods section but then might be omitted in the final manuscript.

A common error in manuscript writing is reporting results in the methods section and vice versa. A frequently occurring example is including the number of subjects who participated in the research in the methods section when it was unknown how many met inclusion criteria before study initiation and subject screening. The methods section should only include information available during the planning phase, before study initiation. 10 , 16 There are instances in which study procedures may have changed after the study commencement. This information would be reported in the methods section but the outcomes stated in the results section. The results section should reflect the data obtained from study procedures because this information would be unknown before the study was completed.

• Study Design

The methods section often begins with an overall description of the study design and key attributes, including the type of study, setting, time frame, and procedures. 14 , 15 This provides an overview and context for how the study was conducted with further details and specifics described in subsequent subsections. Study design has been described as a road map for the methods section to provide information for how to understand the approach and interpret the results. 14

Common study designs include observational, bench evaluation, systematic review, randomized controlled trial, survey, and others. Guidelines for writing the manuscript include the Consolidated Standards of Reporting Trials (CONSORT) checklist for randomized controlled trials and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for systematic reviews. 17 , 18 Registration is another consideration for clinical trials and systematic reviews. The International Committee of Medical Journal Editors (ICMJE) 16 requires registration of clinical trials on a public trials registry. Many journals, including R espiratory C are , follow the recommendations for publication set forth by this group. A randomized controlled trial should also include the blinding mechanism and different treatment groups as applicable. 17 Although registration of a systematic review is often not a prerequisite for publication, registering the protocol supports transparency, decreases potential bias, and can help prevent duplication of reviews. 18 An observational study should report if the design was retrospective, prospective, a secondary or post hoc analysis, or other category of observational design. 7

The setting where the study occurred, if it included data from a single-center or multiple centers, and the time frame in which it took place must be included because these factors have implications for clinical practice, generalizability, and validity. 7 Potential study settings might include an ICU (or specific ICU type), medical surgical ward, emergency department, out-patient clinic, home-care environment, or simulation laboratory. The time frame is an essential element for context because practices and trends change over time. A prime example of this is prone positioning for treatment of hypoxemic respiratory failure as use substantially increased during the COVID-19 pandemic. 19

• Ethics Statement

The United States Department of Health and Human Services defines a human subject “as a living individual about whom an investigator (whether professional or student) conducting research obtains information or biospecimens through intervention or interaction with the individual, and uses, studies, or analyzes the biospecimens; or obtains, uses, studies, analyzes, or generates identifiable private information or identifiable biospecimens.” 20 The methods section must include a statement regarding approval from an institutional review board (IRB) or ethics committee for research that included human subjects. 16 Quality improvement studies and certain types of surveys are often not considered human subject research and therefore may not require IRB oversight but the decision is made by the IRB. Quality improvement projects, depending on requirements of the institution or organization, can be performed without IRB approval in some cases; however, IRB approval is needed before publication or presentation outside of the institution, and human subject determination is made by the IRB, not the investigators.

Animal studies also require ethics approval to be reported in the methods section. Research that involves animals is subject to approval from the local Institutional Animal Care and Use Committee and must be conducted in accordance with national guidelines, for example, the National Institute of Health Public Health Service Policy on Humane Care and Use of Laboratory Animals. 21 For journals that do not have a specific requirement for where to include the ethics statement within the methods section, many authors typically incorporate it in the initial general description of the study or with the detailed description of the subjects. Some studies have included it at the beginning of the methods section.

Characteristics of the study population should be described. This includes basic demographics (eg, adults or children, age, sex) and general health status such as if the individuals were healthy volunteers or had a specific diagnosis or condition. This information is also needed for control groups. 4 Inclusion criteria for how subjects were identified and selected should be detailed as well as reasons for exclusion. For example, an evaluation of a disease management program included adults ages ≥ 65 years and with COPD who were admitted to 1 of 5 hospitals during a specified time frame. 22 Patients were excluded if they left against medical advice, died during admission, transferred to a hospital outside of the health system, entered hospice care, refused home care, or were unable to participate in education. 22 In this example, subject characteristics (adults with COPD), selection and identification (hospital admission during defined time frame), and exclusion criteria are clearly stated.

When referring to human subjects in research, the terms subject and patient are often used interchangeably, but there is a difference. 23 A patient receives care to improve health, and care is individualized in each particular case. When a patient participates in research, he or she becomes a subject. In research, care is designed to create information and is the same for all subjects based on the study protocol. The individual conducting the research is not always involved in the patient care provided, thus also making the distinction between subject and patient. A common error is to use the word subjects exclusively when writing the manuscript. However, individuals are patients before enrollment. When referring to the broader population of individuals who might benefit from the research findings, the word patients is likely more correct. Participant and volunteer are other terms that can be used in place of subject. Individuals who participated in survey research are typically referred to as respondents . 24

In addition to humans, research subjects may also involve animals or organisms such as cells. When animals are studied, the methods should describe the species, weight, age, and sex of the animals. 6 Ring et al 25 used ex vivo porcine lungs to evaluate the effect of breathing pattern and nebulization on exhaled viral content during mechanical ventilation. The authors reported that the lungs were sourced from a retail processing facility and were from 6-month-old Yorkshire hybrid pigs that weighed 118 kg. In addition, it was noted that approval to conduct the study was granted by the local Institutional Animal Care and Use Committee. This publication demonstrates an appropriate description of animal subjects, including an ethics statement.

• Equipment and Other Materials

Identify all equipment and other materials used in the study, including devices, related accessories, drugs, or chemicals. At first mention of any device, provide the specific name of the item, model number if applicable, and manufacturer information. Many scientific journals do not usually allow use of trademark or registration symbols. 10 The ICMJE recommends that manufacturer name and location be included in parentheses. 16 For example, a study that evaluated the safety and feasibility of breathing high-dose nitric oxide in healthy volunteers used a Sievers 280i nitric oxide analyzer (GE Analytical Instruments, Boulder, Colorado) to measure nitric oxide gas concentration. 26 Subsequent mentions of equipment should be noted by generic name versus trade name when possible. It is important that the methods section does not project any bias that an author may have for a specific device or manufacturer.

Use of figures can be an effective means of providing a visual description of the equipment setup, especially when there are many components involved. This can also help reduce the amount of text and improve understanding of how the equipment was assembled. Figures can be either a photograph of the equipment or a graphic illustration (line drawing), but all components should be clearly labeled. An illustration of the setup used to deliver high-dose nitric oxide in the aforementioned study is provided in Figure 1 . 26 Use of a photograph to depict the experimental setup for measuring peak expiratory flow during mechanical insufflation-exsufflation is demonstrated in Figure 2 . 27 Photographs should be of good quality and include all relevant items. In both examples, all components are clearly identified and labeled.

• Download figure
• Open in new tab

Graphic illustration of an experimental setup. From Reference 26.

Photograph of an experimental setup. From Reference 27.

In addition to naming the specific equipment used in the study, settings should also be included in the methods section because these details are highly relevant for duplication of the study. For example, the evaluation of peak expiratory flow during mechanical insufflation-exsufflation provided the pressure settings used during therapy. 27 Not only is this important for repeating the study, but it is also essential for assessing the validity of the results. If the settings were not typical of those used in the study population or in clinical practice, then this would introduce limitations to interpreting and understanding the results.

Equipment preparation is another consideration for the methods section. Describe the calibration process and the frequency for equipment that requires calibration. The flow meter used to measure peak expiratory flow during mechanical insufflation-exsufflation was calibrated and validated annually by the manufacturer. 27 If manufacturer standards for calibration are not followed, then the accuracy of the results may be affected. It should be noted that calibration and validation represent two different processes. 4 Both should be described as applicable.

In addition to equipment, identify all drugs, chemicals, gases, or other materials used specifically for the study. The details for drugs and gases should include the concentration, dose, frequency, and route of administration. Gases should also note the flow used. Chemicals should be noted with the name and concentration as applicable. Use the generic name for drugs. If the trade name for a drug is relevant to the study, then follow the same process for identifying equipment brands and manufacturer information and use the generic name after initial identification. Preparation information may be needed in some cases. For example, detailed preparation information was provided for the bacteriophage used in the animal study conducted by Ring et al. 25 The process for how the bacteriophage was prepared was described in detail as well as the amounts used for the study.

• Study Procedures

The methods section should explicitly detail all procedures, treatments, or interventions used in the study. This portion of the methods section describes how study procedures were performed, the chronological order of procedures, measurements or calculations made, and the specific data elements collected. A rationale may be needed for some procedures, depending on the audience. 6 Outcome measures are often included in the subsection for study procedures, but some authors report them in the overall description for study design.

A comprehensive explanation of the procedures is vital for providing adequate details for reproducibility and validity regardless of the study design. A retrospective cohort study investigated outcomes of children treated with continuous albuterol that contains benzalkonium chloride and preservative-free solutions. 28 Collected data were clearly stated and included subject demographics, diagnosis, mortality risk score, albuterol dose and duration, use of adjunctive therapies, and respiratory support. The methods section for this paper also reported the source of the data extraction (electronic medical records, database, manual chart review) and the process for how therapies were initiated, escalated, and de-escalated (intensivist discretion). 28 The basis for the use of therapies in this study is an important consideration for generalizability because practices vary among institutions and some care might involve the use of protocols.

Diagrams and flow charts can be helpful for illustrating processes or workflow. An evaluation of sputum volume obtained with different cough augmentation techniques outlined the protocol in an illustrated timeline for the sequence of interventions and data collection ( Fig. 3 ). 29 The timeline provides clear information for the procedures that were done, when they were done, and the data elements collected. Data were collected at baseline, at the end of the intervention, and then 1 h after the intervention, followed by a minimum 4-h washout period before the second intervention and data collection. 29 Details with regard to who performed the interventions (5 experienced respiratory clinicians), how they were administered (cough augmentation technique and settings), and subject information (positioning) were comprehensively described.

Illustrated timeline of study protocol that depicts chronological order. From Reference 29.

Measurements obtained during study procedures should be identified along with a description of how they were obtained and the devices used. For example, the same study measured ventilator parameters before, during, and after interventions by using a Fluxmed GrH monitor (MBMED, Buenos Aires, Argentina). 29 Procedures for measurements or techniques with established references do not have to be described in detail and can be omitted if the procedure could be repeated without the specific details. 6 , 12 , 14 This is a common practice for measurements obtained during spirometry. In those instances, provide the reference for the previous work without providing all of the additional details. In a study that aimed to correlate baseline spirometry with airway hyper-responsiveness in methacholine challenge, the reported testing was performed according to published guidelines. 30 The guideline was referenced without providing all the specifics. On the contrary, studies that used novel methods would need to be further described. 6

The outcome measures that address the research question should be clearly stated. Outcome measures are the dependent or response variables assessed to evaluate the impact of the research that is established before beginning the study. 6 , 8 Outcome measures may include both primary and secondary outcomes. The primary outcome is the main measure of the research question, and secondary outcomes provide additional information for interpreting results. The retrospective evaluation of different albuterol solutions used ICU and hospital length of stay as primary outcomes and duration of continuous albuterol, use and duration of adjunctive therapies, and need for mechanical ventilation as secondary outcomes. 28 The primary outcome was sputum volume for the trial that assessed cough augmentation techniques, and secondary outcomes were respiratory mechanics and hemodynamics. 29

• Statistical Analysis

The statistical analysis component is typically included as the last part of the methods section. This subsection describes how the collected data were analyzed through identification of the statistical tests that were used and the P value threshold for statistical significance. A clinical trial that evaluated the effect of endotracheal tube scraping during mechanical ventilation reported that categorical variables were analyzed with the chi-square or Fisher exact test, and continuous variables were presented as mean ± SD or median (interquartile range) based on distribution and analyzed with t test or Mann-Whitney test. 31 P < .05 was considered significant. The statistical analysis section of this paper distinctly identified the tests used to analyze specific data points and provided an explanation for when mean or median was reported.

The statistical analysis should also describe how the power analysis was conducted to determine the appropriate sample size. Justification for the approach should be provided when needed. For example, the study that evaluated the effect of endotracheal tube scraping calculated sample size for each treatment group based on previous institutional data for the mean duration of mechanical ventilation and determined that each group needed 136 subjects with an alpha of 0.05 and power of 0.80. 31 Citing references for the rationale and justification for the selected statistical tests is also an approach to support the choice of test. The previously noted evaluation of methacholine reactivity used a reference to support the use of partition analysis. 30 The software package and version used for data analysis should also be specified in the data analysis portion of the methods section. 16

• A Methods Model

Several publications were used throughout this paper to demonstrate the different elements of the methods section of a research paper. A summary of each of those elements and the individual components comprised within each subsection adapted from the endotracheal tube scraping clinical trial are included in Table 2 . 31 It is important to note how some items were further described in the text, such as the technique for airway suctioning, the definition of a successful spontaneous breathing trial, an explanation for extubation outcome, the elements of the ventilator-associated event prevention bundle, and how ventilator-associated events were defined. These specifics provide additional information to help determine validity and generalizability, and highlight the importance of including enough detail to duplicate the study.

Summary of Methods Elements and Details from a Published Paper

The methods section is an important part of a manuscript because it provides information on the validity of the study. One of the main reasons for manuscript rejection is an inadequate description of the methods. Enough detail must be provided so others could repeat the study and reproduce the results, similar to following a recipe. The methods section should be structured for logical and chronological flow, and be written in past tense. There are multiple components of the methods section that must be adequately described and thoroughly detailed to provide an understanding of how the results were obtained to interpret the findings. Subheadings can be helpful for organizing the methods section into subsections when there is a considerable amount of information to report, but subheadings should be used judiciously. A well-written methods section will guide the reader through the research process and provide adequate information to evaluate study validity and credibility of the results as well as reproduce the work.

• Correspondence: Denise Willis MSc RRT RRT-NPS AE-C FAARC, Respiratory Care Services, Arkansas Children’s Hospital, 1 Children’s Way, Slot 303, Little Rock, AR 72202. E-mail: WillisLD{at}archildrens.org

Ms Willis is a Section Editor for R espiratory C are .

Ms Willis presented a version of this paper at the symposium Research in Respiratory Care at AARC Congress 2022 held November 8, 2022, in New Orleans, Louisiana.

• Copyright © 2023 by Daedalus Enterprises
• Stenson JF ,
• Lendner M ,
• Annesley TM
• Ghasemi A ,
• Bahadoran Z ,
• Zadeh-Vakili A ,
• Montazeri SA ,
• Hosseinpanah F
• Azevedo LF ,
• Canário-Almeida F ,
• Almeida Fonseca J ,
• Costa-Pereira A ,
• Hespanhol V
• 16. ↵ International Committee of Medical Journal Editors . Recommendations for the conduct, reporting, editing, and publication of scholarly work in medical journals . Updated May 2022 . https://www.icmje.org/recommendations/ . Accessed July 6, 2023
• Zaccagnini M ,
• 20. ↵ United States Department of Health and Human Services . 45 Code of Federal Regulations Part 46 . https://www.hhs.gov/ohrp/regulations-and-policy/regulations/45-cfr-46/index.html . Accessed July 6, 2023
• 21. ↵ National Institutes of Health Office of Laboratory and Animal Welfare . Public Health Service Policy on Humane Care and Use of Laboratory Animals . https://olawnihgov/policies-laws/phs-policyhtm 2015 . Accessed July 6, 2023.
• Truumees M ,
• Tonzola D ,
• Cerrone F ,
• Zimmerman D ,
• Goodfellow LT
• Pestana K ,
• Sombatsaphay V ,
• Morais CCA ,
• Mueller AL ,
• Al-Subu AM ,
• Friestrom E ,
• Langkamp MR ,
• Yngsdal-Krenz RA ,
• Martinez-Alejos R ,
• Marti J-D ,
• Li Bassi G ,
• Gonzalez-Anton D ,
• Pilar-Diaz X ,
• Reginault T ,
• Hunninghake JC ,
• McCullough SB ,
• McCann ET ,
• Charlton ME ,
• Villanueva KA ,

In this issue

• Table of Contents
• Table of Contents (PDF)
• Cover (PDF)
• Index by author

Thank you for your interest in spreading the word on American Association for Respiratory Care.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Citation Manager Formats

• EndNote (tagged)
• EndNote 8 (xml)
• RefWorks Tagged
• Ref Manager

• Tweet Widget
• Facebook Like
• Google Plus One

Jump to section

Related articles, cited by....

• How it works
• Pay for essays
• Do my homework
• Term Paper Writing Service
• Do my assignment
• Coursework help
• Our Writers

Research Paper Structure: The Complete Guide

A professional writer with ten years of experience and a Ph.D. in Modern History, Catharine Tawil writes engaging and insightful papers for academic exchange. With deep insight into the impact of historical events on the present, she provides a unique perspective in giving students a feel for the past. Her writing educates and stimulates critical thinking, making her a treasure to those wading through the complexities of history.

A research paper is an academic work depicting the design and results of a study. It can be an academic assignment in undergraduate and postgraduate programs. Moreover, it is an integral requirement in doctoral programs, where postgrads’ research papers are published in reputable journals to add credibility to their research findings. 

Ordering different parts of a research paper is critical for fulfilling academic standards, streamlining your writing, and avoiding distractions and sidetracks. Although outlining may seem like a waste of time, it is the most efficient use of your time at the pre-writing stage, as it will help you order your thoughts and ideas and develop a plan of action to follow throughout the study. 

In this post, we’ll cover the basics of the research paper formatting, provide a basic template of a research paper structure, and provide a detailed description of each section, including the title page and abstract, introduction and literature review, methodology, results, discussion, and conclusion. You can skip to a specific section if you have questions or concerns about it or check out the full article for an in-depth understanding of the full structure. 

Essential Components of a Research Paper

Unlike other types of academic assignments, research papers have a structure more complex than a simple trio of introduction, body, and conclusion. You are expected to follow the established academic norms and include specific information for your paper to have any scientific value. The basic research paper structure example comprises the following parts:

Introduction

• Literature review

Methodology

• Acknowledgments

Please note that some sections of a research paper outlined above are optional. For example, you only need to include appendices if you wish to share a large volume of data that would make the paper unwieldy. You can also adjust this research paper setup to fit your study and word count requirements better. For instance, you can combine the results and discussion sections or the introduction and literature review.

Formatting Requirements

Although the research paper structure is basically the same for all fields of study and topics, the papers can look drastically different when following research paper formatting guidelines of various formatting styles, be it Chicago, MLA, or APA. You must learn the appropriate style at the onset of the writing process, so remember to ask your academic advisor about it if there’s no mention of the formatting style within general requirements.

Once you know which research paper formatting style to use, get your hands on the relevant formatting guidebook. You can find most of the requirements online or sign out a book from a college library. Considering most formatting guidebooks are huge, focus on the main aspects that can make or break your paper, such as:

• Margins, font, and spacing. Most research paper format guidelines require 1-inch margins on all sides, a legible font of at least 12 pt, and double-spaced lines. 
• Page numbering. Requirements vary, but typically, you’ll need to include page numbers in the upper right-hand corner, half an inch from the corner.
• Headings and subheadings. Refer to MLA or APA handbooks to learn specific research paper headings requirements or ask your professor, as the guidelines differ greatly. 
• In-text citations and reference list. In most cases, research paper in-text citations require the name of the main author along with the page number or the publication year. Reference list formatting varies across different styles, but you can use automatic citation generators to speed up the formatting process.

With formatting requirements out of the way, let’s now focus on individual components of a research paper to help you understand what each section should contain to be well received.

Title Page and Abstract

The research paper title page format depends on the required formatting style:

• MLA does not require a separate title page (unless specifically requested). Instead, in the upper left-hand corner of the first page, type your name, your instructor’s name, course name, and date (each on a new line, double-spaced). After that, center the title of the page and include its text.
• APA requires a separate title page, which should include the title of the paper, your name and affiliation, as well as the course name and number, your instructor’s name, and the assignment’s due date. 

A research paper abstract is brief summary of the main points of the research paper. Depending on the formatting style, it can be from 100 to 250 words long, highlighting the research objective, key methodology, and results highlights. An abstract should help readers decide if your work is worth reading at a glance. 

An APA research paper organization requires an abstract on a separate page, with the “Abstract” heading and the paper’s summary (without indent). Below the abstract, type “Keywords:” (in italics) and list the keywords researchers would use to find your paper in the library or online. 

The opening section of the research paper outline gives students pause because they never know what the introduction should entail. If you’re stuck with writer’s block and don’t know how to start the paper, answer these four questions, and you’ll have all the major pieces necessary for the introduction:

• What’s the context of the problem? Open with a general view of the issue and its current state without going into too much detail (that’s what the literature review is for). The background information should fit within one or two paragraphs and lead directly to the next point. 
• What is the issue? The problem statement or question is the core of this part of the research paper structure. Think of it as a thesis statement for an essay. Everything you write in other sections of a research paper should always tie to your problem statement.
• How do you plan to solve the problem? You can formulate research objectives or hypotheses that your study will try to achieve or prove. Short papers typically have one hypothesis, while longer works usually have two or more related objectives.
• How will your study improve the issue? The answer can circle back to the background you laid out at the beginning of the research paper introduction and highlight the benefits (and potential drawbacks and limitations) of your research. It’s the major “selling point” of the study, which should explain why anyone should care about it. 

You can always leave the introduction for last and tackle it once the rest of the paper is done. That’s especially helpful if you use writer’s block as an excuse to procrastinate and put off writing other parts of a research paper.

Literature Review

The primary objective of a research paper literature review is to provide context and prove the relevance of your topic, as specified in the introduction. To that end, you need to find credible, objective, and relevant sources and synthesize any data pertaining to your research. It’s important to avoid simple paraphrasing or summarization of reference data and instead provide its analysis and synthesize your own hypothesis.

Aside from the similarities found in references, this part of the research paper structure should also focus on discrepancies, contradictions, and knowledge gaps. These will prove your study has merit and can resolve the existing issues. Moreover, the knowledge gaps will help lead up to your main research question, which you may repeat near the end of the literature review.

Depending on the topic of your study, you can organize the literature review:

• Chronologically. You can go from the oldest sources published to the latest or from the latest events to situations long past. This approach is often the easiest, but it doesn’t fit all topics and fields of study.
• Thematically. If you wish to cover two or more aspects of the issue, you can dedicate a subsection to each and analyze them together in the final subsection of the literature review. This is the most popular approach, as it can work for most topics.
• Methodologically. If you want to focus on the differences and similarities in research methodology, you can split the literature review into several subsections, devoting each one to a single methodology. This approach works for select subjects and can make the most of systemic studies. 

If you’re working on an empirical study, you can stop there, but if your work is mostly theoretical, this stage of the research paper writing process could also involve developing a theoretical framework. It will help put your findings and results into perspective.

Although it may seem simple at first glance, a literature review takes a long time, most of which you’ll spend looking for reliable sources. Luckily, you can easily outsource this task. All you need to do is say, “Write my paper for me”, and our experts will take over ASAP. 

The research paper methodology section is an integral part of the piece, as it helps ensure the reproducibility of your results and increases your credibility. This part should answer two main questions:

• What? What did your study involve? What resources, software, materials, or samples did you use? What were the ethical considerations of your research?
• How? How much time did your study take? How did you choose participants? How did you collect data and analyze it?

Keep these questions in mind when working out a research design, picking data collection procedures and analysis techniques. If you rely on standard methods, a quick description with a citation would be enough for the methodology part of the research paper structure. But if you employ a unique approach, make sure to describe it in minute detail to ensure anyone can repeat the process and achieve the same results. 

For obvious reasons, the methodology section will differ greatly depending on your field of study and topic. For example, qualitative and quantitative research methods are vastly different. At the same time, quantitative analysis of sociology or linguistics research will be nothing like analyzing blood tests for nursing students or analyzing the success of a marketing campaign for a business and management class. While the tools (i.e., programming language or table processing software) may be similar, the application will be different, and you should highlight these distinctions in your methodology section. 

Although you can put off working on this section of the structure of a research paper, it can be helpful to put your methodology on paper before embarking on the study. A clear idea of the protocols you plan to employ should keep your study on track and minimize methodological errors. 

The research paper results present the study findings as the ultimate product of your research. Instead of the raw data, you can present analysis results and visual aids in the form of tables, figures, and graphs, provide statistical analysis results, and refer interested readers to appendices containing raw data.

Remember to follow the formatting style requirements for tables and figures, which differ for APA and MLA. The same applies to lists and other visual aids. You should also ensure these materials do not destroy your paper’s readability. For example, a three-page table is much more difficult to grasp than a couple of charts highlighting the same data. Moreover, if you plan to present your findings on a poster or a PowerPoint presentation, it pays to work out the best way to present your insights that will fit all formats, including print and projection.

It’s important to draw the line between the results and discussion parts of the research paper structure. The first presents analysis, while the latter relies on interpretations (or implications) of that analysis. Understanding the distinction can be quite challenging, especially if you’re working out the structure of a research paper for the first time.

Discussion and Conclusion

The research paper discussion connects the introduction and research question with the study results. Instead of merely analyzing data, this section should explain whether your initial hypothesis was correct or not. Moreover, the final section, along with the research paper conclusion, should cover the implications of the findings and their potential practical and theoretical applications. This part can also include the limitations of the study and the need for further research if you feel that it could be useful.

It may seem counterproductive, but you shouldn’t shy away from shortcomings, mistakes, and negative results achieved in your study. Instead of waiting for uncomfortable questions from your instructor, present the bad along with the good and hypothesize potential ways of correcting errors or minimizing the negative influences. In some cases, negative results can be just as valuable (if not more so) than positive findings.

Remember to include the research paper references and appendices after the conclusion to wrap up your work and make it better with careful editing, proofreading, and formatting.

What is the purpose of a research paper?

The main objective is to present and share research insights and discoveries, which you should account for when structuring a research paper. Adding literature review and methodology sections is critical for highlighting the study’s relevance and ensuring its reproducibility.

How do I structure the different sections of a research paper?

Structuring a research paper means adding an introduction, literature review, methodology, results, discussion, and conclusion. You can organize each of these sections thematically or chronologically or use a funnel structure, going from the broad context strokes to a narrow view of the problem.

What are the key formatting guidelines for a research paper?

Specific requirements for the structure of a research paper outline and its contents depend on the preferred formatting style. However, at its core, each formatting style focuses on readability. That’s where 12 pt to 14 pt font size and double line spacing come from. Refer to the relevant formatting style handbook for specific recommendations. 

How do I effectively write the introduction and literature review?

The introduction is a critical part of the research paper structure that should include your primary research objective (or question), hypotheses, and the study’s relevance. A literature review is designed to support the claims you make within the introduction by generously using reference data. 

What is the difference between the results and discussion sections?

Related posts

How to Write a Five-Paragraph Essay: Outlining and Writing Tips + Sample

How to start graduation speech: best tips from paper writing services wordsmith

Top 100 Ideas for Analytical Essay Topics

What are you waiting for?

You are a couple of clicks away from tranquility at an affordable price!

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• My Account Login
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Open access
• Published: 28 May 2024

Gut microbiome remodeling and metabolomic profile improves in response to protein pacing with intermittent fasting versus continuous caloric restriction

• Alex E. Mohr   ORCID: orcid.org/0000-0001-5401-3702 1 , 2 ,
• Karen L. Sweazea 1 , 2 , 3 ,
• Devin A. Bowes   ORCID: orcid.org/0000-0001-9819-2503 2 ,
• Paniz Jasbi 4 , 5 ,
• Corrie M. Whisner   ORCID: orcid.org/0000-0003-3888-6348 1 , 2 ,
• Dorothy D. Sears   ORCID: orcid.org/0000-0002-9260-3540 1 ,
• Rosa Krajmalnik-Brown   ORCID: orcid.org/0000-0001-6064-3524 2 ,
• Yan Jin 6 ,
• Haiwei Gu 1 , 6 ,
• Judith Klein-Seetharaman   ORCID: orcid.org/0000-0002-4892-6828 1 , 4 ,
• Karen M. Arciero 7 ,
• Eric Gumpricht 8 &
• Paul J. Arciero   ORCID: orcid.org/0000-0001-7445-6164 7 , 9  

Nature Communications volume  15 , Article number:  4155 ( 2024 ) Cite this article

6901 Accesses

332 Altmetric

Metrics details

• Metabolomics
• Risk factors

The gut microbiome (GM) modulates body weight/composition and gastrointestinal functioning; therefore, approaches targeting resident gut microbes have attracted considerable interest. Intermittent fasting (IF) and protein pacing (P) regimens are effective in facilitating weight loss (WL) and enhancing body composition. However, the interrelationships between IF- and P-induced WL and the GM are unknown. The current randomized controlled study describes distinct fecal microbial and plasma metabolomic signatures between combined IF-P ( n  = 21) versus a heart-healthy, calorie-restricted (CR, n  = 20) diet matched for overall energy intake in free-living human participants (women = 27; men = 14) with overweight/obesity for 8 weeks. Gut symptomatology improves and abundance of Christensenellaceae microbes and circulating cytokines and amino acid metabolites favoring fat oxidation increase with IF-P (p < 0.05), whereas metabolites associated with a longevity-related metabolic pathway increase with CR (p < 0.05). Differences indicate GM and metabolomic factors play a role in WL maintenance and body composition. This novel work provides insight into the GM and metabolomic profile of participants following an IF-P or CR diet and highlights important differences in microbial assembly associated with WL and body composition responsiveness. These data may inform future GM-focused precision nutrition recommendations using larger sample sizes of longer duration. Trial registration, March 6, 2020 (ClinicalTrials.gov as NCT04327141), based on a previous randomized intervention trial.

Similar content being viewed by others

Protein supplementation during an energy-restricted diet induces visceral fat loss and gut microbiota amino acid metabolism activation: a randomized trial

Gut microbiota plasticity is correlated with sustained weight loss on a low-carb or low-fat dietary intervention

Intermittent fasting modulates the intestinal microbiota and improves obesity and host energy metabolism

Introduction.

As a principal modulator of the gut microbiome (GM) and weight status, nutritional input holds great therapeutic promise for addressing a wide range of metabolic dysregulation 1 . Dependent on the host for nutrients and fluid, one of the main processes by which the GM affects host physiology is producing bioactive metabolites from the gastrointestinal (GI) contents. Nutrient composition, feeding frequency, and meal timing impact this dependency 2 , 3 . To maintain a stable community and ecosystem, the GM must regulate its growth rate and diversity in response to nutrient availability and population density 4 . Such maintenance is affected by caloric restriction (CR) coupled with periods of feeding and intermittent fasting (IF) 5 . Moreover, we’ve recently shown the nutritional composition and meal frequency during these periods alter the metabolizable energy for the host 6 . The current study incorporates protein pacing (P), defined as four meals/day consumed evenly spaced every 4 h, consisting of 25–50 g of protein/meal 7 , 8 , 9 . Indeed, we have previously characterized a dietary approach of calorie-restricted IF-P combined and P alone 7 , 8 . These studies included nutrient-dense meal replacement shakes, along with whole foods, to quantitatively examine beneficial changes in body composition and cardiometabolic, inflammatory, and toxin-related outcomes in healthy and overweight individuals 7 , 8 , 10 , 11 , 12 . Further, recent preclinical work in mice has identified dietary protein as having anti-obesity effects after CR that are partially modulated through the GM 13 . Thus, the need to examine this in humans is warranted.

In this current work, we compare the effects of two low-calorie dietary interventions matched for weekly energy intake and expenditure; continuous caloric restriction on a heart-healthy diet (CR) aligned with current United States (US) dietary recommendations 14 versus our calorie-restricted IF-P diet 8 , 15 , in forty-one individuals with overweight or obesity, over an 8-week intervention. We hypothesize an IF-P diet may favorably influence the GM and metabolome to a greater extent than a calorie-matched CR alone. This exploratory investigation utilizes data and samples from a randomized controlled trial (NCT04327141) that compares the effects of the CR versus IF-P diet on anthropometric and cardiometabolic outcomes, as previously published 15 . As an additional analysis, we select “high” and “low” responders based on relative weight loss (WL) for a subgroup examination of the IF-P diet to better elucidate potential differential responses to intermittent fasting and protein pacing. Of special note, one individual lost 15% of their initial body weight over the 8-week intervention; this individual is followed longitudinally for a year to explore the dynamics of their GM and fecal metabolome. Novel findings from the current study shows an IF-P regimen results in improved gut symptomatology, a more pronounced community shift, and greater divergence of the gut microbiome, including microbial families and genera, such as Christensenellaceae , Rikenellaceae , and Marvinbryantia , associated with favorable metabolic profiles, compared to CR. Furthermore, IF-P significantly increases cytokines linked to lipolysis, weight loss, inflammation, and immune response. These findings shed light on the differential effects of IF-P as a promising dietary intervention for obesity management and microbiotic and metabolic health.

Intermittent fasting - protein pacing (IF-P) significantly influences gut microbiome (GM) dynamics compared to calorie restriction (CR)

We compared an IF-P vs. a CR per-protocol dietary intervention (matched for total energy intake and expenditure) over eight weeks to compare changes in weight, cardiometabolic outcomes, and the GM in men and women with overweight/obesity (IF-P: n  = 21; CR: n  = 20). One participant in each group were lost to follow-up due to non-compliance with dietary intervention (Fig.  1a ; CONSORT flow diagram: Supplementary Fig.  S1a ). The primary outcomes of dietary intake, body weight and composition responses, cardiometabolic outcomes, and hunger ratings after both dietary interventions are provided in our companion paper 15 . Briefly, after a one-week run-in period consuming their usual dietary intake (baseline diet), with no differences between groups at baseline for any dietary intake variable 15 , both dietary interventions significantly reduced total fat, carbohydrate, sodium, sugar, and energy intake by approximately 40% (~1000 kcals/day) from baseline levels (Fig.  1b ; Supplementary Data  1 ). By design, IF-P increased protein intake greater than CR during the intervention. The IF-P regimen consisted of 35% carbohydrate, 30% fat, and 35% protein for five to six days per week and a weekly extended modified fasting period (36–60 h) consisting of 350–550 kcals per day using randomization, as detailed previously 7 , 8 , 9 , 10 , 15 . In comparison, the CR regimen consisted of 41% carbohydrate, 38% fat, and 21% protein in accordance with current US dietary recommendations (Supplementary Table  S1 ) 14 , 16 . Using two-way factorial mixed model analysis of variance (ANOVA), significant macronutrient decreases drove energy reduction from dietary fat and carbohydrate ( p  < 0.001), with increased protein in the IF-P compared to CR ( p  < 0.001; Supplementary Fig.  S1b ; Supplementary Data  1 ). Regarding GI functioning and GM modulation, IF-P significantly decreased sugar and increased dietary fiber relative to CR (IF-P; pre, 20 ± 2 vs. post, 26 ± 2: CR; pre, 24 ± 3 vs. 24 ± 2 g/day; p  < 0.05). Despite similar average weekly energy intake (~9000 kcals/week) and physical activity energy expenditure (~350 kcals/day; p  = 0.260) during the intervention, participants following the IF-P regimen lost significantly more body weight (−8.81 ± 0.71% vs. −5.40 ± 0.67%; p  = 0.003; Fig.  1c ; Supplementary Data  1 ) and total, abdominal, and visceral fat mass and increased fat-free mass percentage (~2×; p  ≤ 0.030), as previously reported 15 . In addition, within-group analyses revealed a significant decrease in the reported frequency of total and lower-moderate GI symptoms (GI symptom rating score [GSRS] ≥4) over time for both IF-P and CR participants. However, when comparing the two dietary interventions at each time point, a more substantial reduction was observed in IF-P participants compared to CR participants (i.e., −9.3% vs. −5.4% and −13.2% vs. −3.9%, respectively; Table  1 ). The increased protein and lower sugar intake in IF-P compared to CR may have favorably mediated the GM and symptomatology.

a Study design with baseline participant characteristics. A registered dietitian counseled individuals from both groups each week. Time points with data collection are shown for both IF-P and CR participants. Icons created using BioRender.com. b Total daily caloric intake at each time point was not significantly different between IF-P and CR diet groups (two-sided Student’s t -test, p  < 0.05). Adjusted values are displayed by dividing total weekly intake by seven, to account for the fasting periods of IF-P. c IF-P participants lost significantly more weight over time versus CR participants. Points connected by line represent percent of weight compared to baseline weight for each participant. d Overall gut microbial colonization, as demonstrated by qPCR-based quantification of 16S rRNA gene copies per gram wet weight was unaffected by time or intervention (linear-mixed effects [LME] model, two-sided p  > 0.05). Alpha diversity metrics, e observed amplicon sequence variants (ASVs), and f Phylogenetic diversity at the ASV level significantly increased over time, independent of the intervention. g Intra-individual changes in GM community structure from baseline to weeks four and eight in IF-P participants shifted significantly throughout the IF-P intervention compared to CR as measured by the Bray-Curtis dissimilarity index (two-sided Wilcoxon rank-sum test). All box and whiskers plots display the box ranging from the first to the third quartile, and the center the median value, while the whiskers extend from each quartile to the minimum or maximum values. Heatmap of significant changes in h family- and i genus-level bacter i a by intervention. Colors indicate the within-group change beta coefficients over time for each cell, and asterisks denote significance. Black-white annotations on the bottom denote the significance of between-group change difference (by MaAsLin2 group × time interactions; p -values were corrected to produce adjusted values [ p .adj] using the Benjamini–Hochberg method). For all panels, IF-P: n  = 20, CR: n  = 19. Source data are provided as a Source Data file.

The substantial reduction in calorie intake of both groups (~40% from baseline) led us to investigate its potential impact on transient microbial colonization in the gut, as estimated by 16S rRNA gene copies (linear-mixed effects model [LME] time effect, p  = 0.114; Fig.  1d ; Supplementary Data  2 ). While it might be expected that a significant reduction in calorie intake could influence gut microbial colonization, our findings indicate that this reduction did not reach statistical significance within the timeframe of our study. This result contrasts with previous research that imposed more substantial energy restriction, such as a four-week regimen of ~800 kcal/day in participants with overweight/obesity, where overall gut microbial colonization notably decreased 4 . In addition to assessing microbial colonization, we also investigated whether the calorie reduction significantly influenced principal stool characteristics, including wet stool weight, Bristol stool scale (BSS), and fecal pH ( p  ≥ 0.066; Table  1 ). However, we did not observe statistically significant changes in these parameters over the course of the study. Moreover, there were no significant differences between the two dietary intervention groups over time (interaction effect, p  ≥ 0.051). In contrast, there were significant time effects for observed amplicon sequence variants (ASVs) and phylogenetic diversity (LME time effect, p  ≤ 0.023; Fig.  1e, f ; Supplementary Data  2 ), with values increasing at weeks four and eight compared to baseline (pairwise comparisons, p  ≤ 0.048); however, no interaction was observed for either alpha diversity metric (group × time effect, p  ≥ 0.925). To rule out the potential confounding effects of GI transit time 17 , BSS (as a surrogate marker) and stool pH were not significantly correlated with alpha diversity (Spearman correlations, p  ≥ 0.210). In relation to community composition, much of the intervention variance could be attributed to individual response upon testing nested permutational analysis of variance (PERMANOVA; R 2  = 0.749, p  = 0.001; Supplementary Table  S2 ), showcasing the highly individualistic landscape of the human GM in response to dietary intervention. However, a significant 1.8% of the variance was accounted for by the group × time interaction ( p  = 0.001). Moreover, individual responses over time showed variance between the two dietary interventions (PERMANOVA, R 2  = 0.123, p  = 0.003). This variability was apparent by assessing intra-individual differences, where a pronounced increase in Bray-Curtis dissimilarity was observed in the IF-P compared to the CR group after four (median Bray-Curtis dissimilarity, 0.53 [IQR: 0.47–0.61] vs. 0.38 [IQR: 0.33–0.47]) and eight weeks (0.50 [IQR: 0.41–0.55] vs. 0.39 [IQR: 0.33–0.45]; Fig.  1g ; Wilcoxon rank-sum test, p  ≤ 0.005).

To understand the taxa driving this GM variation from baseline to weeks four and eight between the two dietary interventions, we constructed MaAsLin2 linear-mixed models with the individual participant as a random factor 18 . We observed differential abundance patterns at the family and genus level in response to the IF-P but not the CR intervention. Of the 28 family and 69 genus-level features captured after filtering, a respective total of six and 18 taxa displayed significant interaction effects, with all significant time effects occurring from IF-P ( p .adj ≤ 0.10; Fig. 1h, i ; Supplementary Data  3 , 4 ). Notably, the changes observed at the four-week mark were more pronounced compared to those at eight weeks. These early alterations may signify an initial adaptation phase during which microbial populations respond to the modified substrate availability and nutrient composition, suggesting a degree of community resilience 19 . Increases were sustained to the third fecal collection for the family Christensenellaceae and the genera Incertae Sedis ( Ruminococcaceae family), Christensenellaceae R-7 group , and UBA1819 ( Ruminococcaceae family) (effect size > 2.0). Christensenellaceae is well regarded as a marker of a lean (anti-obesity) phenotype 20 and is associated with higher protein intake 21 . Other notable increases included Rikenellaceae , which, like Christensenellaceae , has been linked to reduced visceral adipose tissue and healthy metabolic profiles 22 , and Marvinbryantia , a candidate marker for predicting long-term weight loss success in individuals with obesity 23 . In addition, IF-P increased Ruminococcaceae , which has been noted to have an increased proteolytic and lipolytic capacity 24 . This shift in IF-P participants likely represents a change in GM substrate fermentation preferences as the diet regimen (relative protein and carbohydrate) and energy restriction is expected to increase the proteolytic: saccharolytic potential ratio 25 . In contrast, all taxa that decreased in IF-P participants were butyrate producers. These included the family Butyricicoccaceae and several genera such as Butyricicoccus (week four), Eubacterium ventriosum group (weeks four and eight), and Agathobacter (week four) (effect size < −2.0). When comparing monozygotic twin pairs, Eubacterium ventriosum group and another reduced genus, Roseburia , were more abundant in the higher body mass index (BMI) siblings 26 . Others, such as the mucosa-associated Butyricicoccus and Erysipelotricaceae UCG-003, have been positively correlated with insulin resistance and speculated to contribute to impaired glycolipid metabolism 27 .

Despite these changes in GM composition and increased fiber intake (+30% vs. baseline) of the IF-P participants 15 , we did not detect a significant shift in the abundance of the principal fecal short-chain fatty acids (SCFAs), acetate, propionate, butyrate, or valerate, as assessed by gas chromatography-mass spectrometry (GC–MS) (LME, p  ≥ 0.470; Supplementary Fig.  S1c ; Supplementary Data  5 ). Several factors likely contribute to this finding. For example, the distinct physical-chemical properties of fiber sources between IF-P and CR are inherently different. Participants adhering to the IF-P diet consumed most of their dietary fiber as liquid meal replacements (shakes) that are rich in non-digestible, oligosaccharide dietary-resistant starch 5 (RS5). In contrast, subjects on the CR regimen consumed their fiber from whole food sources such as vegetables, whole grains, and legumes. These fiber sources provided a mixture of soluble and insoluble fibers and a more complex fiber profile than IF-P participants. Moreover, even similar fiber profiles may function differently due to differences in food matrices and/or food preparation (cooking, raw consumption, etc.). Also of relevance is the timing of their fiber consumption. IF-P participants’ fiber intake was concentrated in fiber-rich shakes, offering immediate availability of fiber to the GI tract. In contrast, CR participants consumed fiber through whole foods, leading to a slower digestion and absorption process influenced by individual digestive transit times and enzymatic profiles. Interestingly, our results parallel recent work where participants more than doubled their fiber intake without affecting fecal SCFAs 28 . The disparate findings may be due to the type of dietary-resistant starch (RS) as a component of the nutrition regimen. In the current study, RS5 was included in the meal replacement shakes (eight grams/shake, two shakes/day, 16 g/day total). Prior research supports resistant starch intakes of >20 g/day favorably modulate SCFA production, primarily butyrate, over four to 12-week interventions 29 , 30 . Moreover, this lack of response in fecal SCFAs in both groups may have been further compounded by the significant reduction in energy intake in both groups, where the epithelia of the GI tract may have absorbed any potential increase in SCFAs from the dietary shift. It is worth noting that stool analysis may not be the most reliable biological surrogate for capturing SCFA flux over time 28 . Nevertheless, the changes in nutrient quality, timing, ratios, and the observed shift toward proteolytic activity suggest that the luminal matrix of digesta in the IF-P group impacted substrate availability for GM. This effect appears to be an influencing force in driving the observed beneficial shifts in microbial communities, such as Christensenellaceae and Incertae Sedis , as well as improvements in GI symptomatology in IF-P compared to CR. These results underscore the complexity of dietary influences on GM and highlight the need for further research to explore the impact of liquid meal replacements versus whole food sources on GM changes and SCFA status.

IF-P modulates circulating cytokines and gut microbiome taxa compared to CR

Caloric restriction and WL have been well known to positively influence inflammatory cytokine expression, with GM now emerging as an important modulator 31 . Surveying a panel of 14 plasma cytokines, we noted significant interaction (group × time) effects for IL-4, IL-6, IL-8, and IL-13 (LME, p  ≤ 0.034; Fig.  2a–d ; Supplementary Table  S3 ; Supplementary Data  6 ). These cytokines exhibited increases at weeks four and/or eight compared to baseline exclusively in the IF-P group (pairwise comparisons, p .adj ≤ 0.098), while no significant changes were observed in the CR group ( p .adj ≥ 0.562). Notably, IL-4 has been reported to display lipolytic effects 32 , and IL-8 has been positively associated with weight loss and maintenance 33 . Regarded as a proinflammatory myokine, IL-6 can acutely increase lipid mobilization in adipose tissue under fasting or exercise conditions 34 , 35 , 36 . IL-13 may be important for gut mucosal immune responses and is a stimulator of mucus production from goblet cells 37 , which has been recently reported to be influenced during a two-day-a-week fasting regimen in mice 38 . These results were of note considering the significant total body weight, fat, and visceral fat loss in the IF-P compared to the CR group. Surprisingly, correlational analysis with change (post – pre) in anthropometric and select plasma biomarker values with the cytokine profile did not reveal any significant associations after correcting for multiple testing effects ( p .adj ≥ 0.476; Supplementary Data  7 ). Plasma cytokines were, however, correlated with microbial composition for samples collected in the IF-P group during the intervention period (weeks four and eight) using graph-guided fused least absolute shrinkage and selection operator (GFLASSO) regression, revealing associations between cytokine-taxa pairs (Supplementary Fig.  S2a ). Of the four cytokines that increased in IF-P participants, we identified multiple significant correlations: Colidextribacter (rho = −0.55, p .adj = 0.015), Ruminococcus gauvreauii group (rho = 0.50, p .adj = 0.036), and Intestinibacter (rho = 0.45, p .adj = 0.086) with IL-4 (Supplementary Fig.  S2b ) and an unclassified genus from Oscillospiraceae (rho = −0.53, p .adj = 0.019), Colidextribacter (rho = −0.52, p .adj = 0.019), and Ruminoccus gauvreauii group (rho = 0.51, p .adj = 0.019) with IL-13 (Supplementary Fig.  S2c ).

a IL-4, b IL-6, c IL-8, and d IL-13: Each panel shows the cytokine concentration levels. Significant time effects and interaction effects (group × time) were detected using linear-mixed effects models (LME, two-sided p  < 0.05), indicating differential changes over the intervention period. IF-P participants exhibited significant increases in cytokine levels compared to baseline, as evidenced by pairwise comparisons adjusted for multiple testing using the Benjamini–Hochberg method (two-sided p .adj < 0.10). All box and whiskers plots display the box ranging from the first to the third quartile, and the center the median value, while the whiskers extend from each quartile to the minimum or maximum values. For all panels, IF-P: n  = 20, CR: n  = 19. Source data are provided as a Source Data file.

Displaying negative correlations for IL-4 and IL-13, Colidextribacter has been shown to be positively correlated to fat accumulation, insulin, and triglyceride levels in mice fed a high-fat diet 39 and positively correlated with products of lipid peroxidation, suggesting its potential role in promoting oxidative stress 40 . Conversely, Ruminoccus gauvreauii group was positively correlated with IL-4 and IL-13. Although limited information is available regarding the host interactions of this microbe, this genus is considered a commensal part of the core human GM and able to convert complex polysaccharides into a variety of nutrients for their hosts 41 . While these findings highlight the potential interplay between specific microbes and cytokine profiles, the directional influence—whether microbial changes drive cytokine alterations or vice versa—cannot be determined in this study setting. Furthermore, despite the change in cytokine profiles in the IF-P group, we did not detect any significant time or group × time effects when measuring lipopolysaccharide-binding protein (LBP; Δ pre/post, IF-P: 0.24 ± 0.31 vs CR: −0.93 ± 0.49 μg/mL; p  ≥ 0.254), a surrogate marker for gut permeability 42 . While the GM plays a crucial role in modulating the gut-immune axis, the observed cytokine fluctuations and microbial associations might also involve other factors. These include the production of specific metabolites due to shifts in microbial composition as well as the influence of the dietary regimen itself, which may have a central role in shaping these interactions.

IF-P and CR yield distinct circulating metabolite signatures and convergence of multiple metabolic pathways

To understand the potential differential impact of IF-P versus CR on the host, we surveyed the plasma metabolome, reliably detecting 136 plasma metabolites across 117 samples (i.e., QC CV < 20% and relative abundance > 1000 in 80% of samples). Based on outlier examination (random forest [RF] and principal component analysis [PCA]), no samples were categorized as outliers, and all data were retained for subsequent analysis. Metabolomic profile shifts were observed in both IF-P and CR groups compared with baseline (Canberra distance), however, these did not differ significantly by group or time (weeks four and eight; Wilcoxon rank-sum test, p  ≥ 0.087; Supplementary Fig.  S3a ). We prepared a general linear model (GLM) with age, sex, and time as covariates and corrected for false discovery rate (FDR). When controlling for these relevant covariates, we observed significant differences between IF-P and CR for 15 metabolites (Fig.  3a , Supplementary Table  S4 ): 2,3-dihydroxybenzoic acid, malonic acid, choline, agmatine, protocatechuic acid, myoinositol, oxaloacetic acid, xylitol, dulcitol, asparagine, n-acetylglutamine, sorbitol, cytidine, acetylcarnitine, and urate ( p .adj ≤ 0.089). To estimate the univariate classification performance of the 15 significant metabolites, we performed a receiver operating characteristic (ROC) analysis. Ten metabolites demonstrated a moderate area under the curve (AUC) (0.718–0.819), while five metabolites had an AUC < 0.70. Therefore, to improve classification performance, we constructed a supervised PLS-DA model using levels of the 15 significant metabolites ( p .adj ≤ 0.089) and analyzed variable importance in projection (VIP) scores (Supplementary Fig.  S3b ). Five metabolites with a VIP > 1.0 (2,3-dihydroxybenzoic acid, malonic acid, protocatechuic acid, agmatine, and myoinositol) were retained to construct an enhanced orthogonal projection to latent structures discriminant analysis (OPLS-DA) model. In contrast, the model fit was assessed with 100-fold leave-one-out cross-validation (LOOCV; see “Methods” section). Permutation testing showed the refined OPLS-DA model to have an acceptable fit to data ( Q 2  = 0.460, p  < 0.001), with appreciable explanatory capacity ( R 2  = 0.506, p  < 0.001; Supplementary Fig.  S3c ). The ROC analysis produced an area under the curve (AUC) of 0.929 (95% CI: 0.868–0.973, sensitivity = 0.8, specificity = 0.9; Supplementary Fig.  S3d ) between the CR and IF-P groups showing good accuracy of the GLM and providing strong support for the differential expression of these 15 metabolites between groups.

a Abundance and log fold-change of significant plasma metabolites between IF-P and CR groups as determined by a general linear model (GLM) adjusted for age, sex, and time. All GLM analyses utilized two-sided p -values, with multiple testing corrections applied using the Benjamini–Hochberg method ( p .adj). Metabolome pathway analysis was conducted for b IF-P and c CR using all reliably detected metabolites showing significantly altered pathways ( p .adj < 0.10) with moderate and above impact (>0.10). Impact scores were calculated using a hypergeometric test, while significance was assessed via a test of relative betweenness centrality, emphasizing the changes in metabolic network connectivity. For all panels, IF-P: n  = 20, CR: n  = 19. Source data are provided as a Source Data file.

Two metabolites, malonic acid, and acetylcarnitine, increased compared to the CR intervention. Several other investigators have noted the increase in acetylcarnitine via fasting protocols 43 , 44 . This increase is consistent with free fatty acid mobilization and increased transportation of these fatty acids via carnitine acylation into the mitochondria for fatty acid oxidation. These results would also be consistent with the expected ketogenesis, although not documented in our study, but noted by similar fasting interventions 44 . Relatedly, malonic acid, a naturally occurring organic acid, is a key regulatory molecule in fatty acid synthesis via its conversion to acetoacetate; hence, our results may reflect this increased synthesis in response to the mobilization and oxidation of fatty acids occurring during fasting. Other metabolites that decreased with IF-P include several sugar alcohols (myoinositol, dulcitol, and xylitol). Dulcitol (galactitol) is a sugar alcohol derived from galactose. It is possible that during fasting, levels of dulcitol decrease as glucose (initially) and free fatty acids (after 24–36 h of fasting) are preferentially utilized as energy substrates. One amino acid (asparagine) and one amino acid analog (N-acetylglutamine, associated with consumption of a Mediterranean diet 45 ) also decreased with IF-P relative to CR. Finally, 2,3-dihydroxybenzoic acid significantly decreased with IF-P. This metabolite is formed during the metabolism of flavonoids, as it is found abundantly in fruits, vegetables, and some spices. At the cellular level, this hydroxybenzoic acid functions as a cell signaling agent and has been speculated as a potentially protective molecule in various cancers 46 . It is unclear whether this metabolite decreased due to either dietary intake or metabolic processes related to high-protein intake or the fasting protocol. Collectively, the metabolic responses to these dietary regimens reflect the interrelationships of several anabolic and catabolic physiologic responses to three key components of these interventions: (a) the WL process itself, (b) changes in amount (and type) of macronutrient distribution (i.e., meal replacement shakes vs. whole food diet approach; higher vs. normal protein intakes), and (c) the adherence to fasting (IF-P only).

To determine the significantly impacted pathways of the dietary interventions, we grouped participant samples according to baseline or intervention period (weeks four and eight), with IF-P and CR assessed separately. A total of 14 pathways were significant in the IF-P group ( p .adj < 0.10; Fig.  3b ), with three displaying large impact coefficients (>0.5): (1) Glycine, serine, and threonine metabolism, (2) alanine, aspartate, and glutamate metabolism, and (3) ascorbate and aldarate metabolism. In comparison, 24 pathways were significant for the CR group (Fig.  3c ), with four showing large impact coefficients (>0.5): (1) Phenylalanine, tyrosine, and tryptophan biosynthesis, (2) alanine, aspartate, and glutamate metabolism, (3) citrate cycle (TCA cycle), and (4) glycine, serine and threonine metabolism. Notably, the glycine, serine, and threonine pathway has recently been found in preclinical models to play a pivotal role in longevity and related life-sustaining mechanisms independent of diet, though heavily impacted by fasting time and caloric restriction 47 . This may be partially related to the ability of glycine to increase tissue glutathione 48 , 49 and protect against oxidative stress 50 . In our analysis, this pathway was significant in both diet groups and is biochemically and topologically related to the additionally captured amino acid pathway, alanine, aspartate, and glutamate metabolism, as well as the energy-releasing pathway, the citrate cycle (TCA cycle). Notably, in the CR group, phenylalanine, tyrosine, and tryptophan biosynthesis, are important for neurotransmitter production and reported to be suppressed (tryptophan) in obesity 51 . This representation may have also been attributed to the differences in protein intake 52 or differences in dietary diversity 53 , yet to be determined. Regardless, we noted similar representations of pathway impact between IF-P and CR, with metabolic response centered on utilization of amino acids in addition to lipid turnover and energy pathways.

Gut microbiome and plasma metabolome latent factors indicate differential multi-omic signatures between IF-P and CR regimens

As the plasma metabolome has been suggested as a bidirectional mediator of GM influence on the host 54 , we performed a multi-omics factor analysis (MOFA) 55 to identify potential patterns of covariation and co-occurrence between the microbiome and circulating metabolites. Operating in a probabilistic Bayesian framework, MOFA simultaneously performs unsupervised matrix factorization to obtain overall sources of variability via a limited number of inferred factors and identifies shared versus exclusive variation across multiple omic data sets 55 . Eight latent factors were identified (minimum explained variance ≥2%; see “Methods” section), with the plasma metabolome and GM explaining 37.12% and 17.49% of the overall sample variability, respectively (Fig.  4a ). Based on significance and the proportion of total variance explained by individual factors for each omic assay, Factors 1 ( R 2  = 11.98) and 6 ( R 2  = 5.28) captured the greatest covariation between the two omic layers (Fig.  4a ; Supplementary Table  S5 ). In contrast, Factors 2 and 5 were nearly exclusive to the metabolome, and factors 3 and 4 to the GM. Interestingly, Factor 1 was significantly negatively correlated to dietary protein intake (Spearman rho = −0.270, p.adj = 0.021; Fig.  4b ) and captured the variation associated with the CR diet (Wilcoxon rank-sum test, p .adj = 3.2e-04; Fig.  4c ). Factor 6 had the greatest number of significant correlations, including negative associations with visceral adipose tissue, waist circumference, body weight, BMI, fat mass, android fat, subcutaneous adipose tissue, dietary sodium, carbohydrate, fat, energy intake (kcal), and sugar (Spearman rho ≤ −0.220, p .adj ≤ 0.075) and captured the variation associated with IF-P (Wilcoxon rank-sum test, p .adj = 0.007).

a The cumulative proportion of total variance explained ( R 2 ) and proportion of total variance explained by eight individual latent factors for each omic layer. b Spearman correlation matrix of the eight latent factors and clinical anthropometric and dietary covariates. Each circle represents a separate association, with the size indicating the significance (-log10 ( p -values)) and the color representing the effect size (hue) with its direction (red: positive; blue: negative). All correlations are calculated using two-sided tests. Asterisks within a circle denote significance after adjustment with the Benjamini–Hochberg method. c Scatter plot of Factors 1 and 6, with each dot representing a sample colored by intervention. Box and whisker plots illustrate significant differences between groups after adjusting for multiple testing using the Benjamini–Hochberg method (Wilcoxon rank-sum test; top = Factor 1, p .adj = 3.2e-04; right = Factor 6, p .adj = 0.007). The plots show boxes ranging from the first to the third quartile and the median at the center, with whiskers extending to the minimum and maximum values. d Factor 1 and 6 loadings of genera and metabolites with the largest weights annotated. Symbols: * p .adj < 0.10, ** p .adj < 0.01, *** p .adj < 0.001, **** p .adj < 1.0e-04. For all panels, IF-P: n  = 20, CR: n  = 19. Source data are provided as a Source Data file.

Assessing the positive weights (feature importance) of Factor 1 revealed a microbial and metabolomic signature linked with CR, including the taxa Faecalibacterium , Romboutsia , and Roseburia , and the plasma metabolites myoinositol, agmatine, N-acetylglutamine, erythrose, and mucic acid (Fig.  4d ). Previous dietary restriction studies have reported co-occurrence of gut microbial taxa and plasma metabolites that span a wide variety of applications and investigations 56 . The specific co-occurrences observed in Factor 1 exhibited an abundance of butyrate-producing bacterial taxa that utilize carbohydrates as their predominant substrate and plasma metabolites that are generally involved in carbohydrate metabolism, such as erythrose, an intermediate in the pentose phosphate pathway (PPP), and mucic acid which is derived from galactose and/or galactose-containing compounds (i.e., lactose). These co-occurrence patterns biologically cohere considering the nutritional profile of the CR group and the large contribution of fiber-rich, unrefined carbohydrates and reduction in sugar (~50% kcal from sugar). Indeed, these nutritional changes may have influenced the GM to accommodate changes in dietary substrate more efficiently. One interesting co-occurrence was the genus Romboutsia and metabolite N-acetylglutamine. Romboutsia has been shown to produce several SCFAs and ferment certain amino acids, including glutamate 57 . N-acetylglutamine is biosynthesized from glutamate; thus, its co-occurrence with the abundance of Romboutsia encourages further exploration into this interaction 58 .

Factor 6 captured the signature associated with IF-P, with positive contributions from the taxa Incertae Sedis ( Ruminococcaceae family), Erysipelatoclostridium , Christensenellaceae R-7 group , Oscillospiraceae UCG-002, and Alistipes , and the plasma metabolites malonic acid, adipic acid, succinate, methylmalonic acid, and mucic acid (Fig.  4d ). Prior work has established that Alistipes increases from diets rich in protein and fat, and contributes to the highest number of putrefaction pathways (i.e., fermentation of undigested proteins in the GI tract) over the other commensals 59 . This could explain the co-occurrence of plasma metabolites from protein catabolism, such as 2-aminoadipid acid, adipic acid, and glutamic acid 22 , 59 . Oscillospiraceae has recently been viewed with next-generation probiotic potential, harboring positive regulatory effects in areas related to obesity and chronic inflammation 60 . Mentioned prior, recent studies have reported on the role of Christensenellaceae on human health, participating in host amino acid and lipid metabolism as well as fiber fermentation 20 , with Christensenellaceae R-7 group notably evidenced to correlate with visceral adipose tissue reduction 22 . As such, the elevated abundance of microbes in the GM of IF-P participants observed in this study in tandem with the co-occurrence of metabolites indicative of protein degradation and mobilization and oxidation of fatty acids, such as methylmalonic acid, malonic acid, and succinate, presents a nascent multi-omic signature of IF-P. In addition, and more pronounced in the IF-P vs CR group, participants decreased sugar intake by ~75% (kcals) compared to baseline levels. Considering the other regimental components of IF-P, the differences in multi-omic signatures likely display the selective pressures of these two interventions.

Gut microbiome (GM) composition is associated with weight loss (WL) responsiveness to IF-P diet

The IF-P intervention produced a microbiome and metabolomic response; however, the loss in body weight and fat across individuals varied (Fig.  5a ). To provide deeper characterization and explore differential features of WL responsiveness, we performed a GM-focused subgroup analysis by employing shotgun metagenomic and untargeted fecal metabolomic surveys in 10 individuals that either achieved ≥10% loss in body weight or bordered on clinically important WL (i.e., >5% BW; herein, ‘High’ and ‘Low’ responders) 61 . Importantly, baseline characteristics between WL responder classification did not differ significantly (baseline body weight: High, 108.9 ± 30.8 vs. Low, 81.9 ± 18.1 kg, p  = 0.117; Supplementary Table  S6 ). Assessing the GM at the fundamental taxonomic rank, species composition showed significant separation by weight loss response evaluated by Bray-Curtis dissimilarity (group × time: R 2  = 0.114, p  = 0.001; Fig.  5b ; Supplementary Table  S7 ), with most of the variation explained by the individual ( R 2  = 0.711, p  = 0.001). In comparison, species level alpha diversity did not differ significantly between classifications (group × time: p  ≥ 0.674; Fig.  5c, d ). Identifying 212 species after filtering, we noted significant differences in bacterial abundances between groups over time (Fig.  5e ; Supplementary Data  8 ). A total of 10 features increased in the High-responder group relative to the Low-response group over the eight-week study period, including Collinsella SGB14861 , Clostridium leptum , Blautia hydrogenotrophica , and less typified species; GGB74510 SGB47635 (unclassified Firmicutes), GGB3511 SGB4688 (unclassified Firmicutes), Faecalicatena contorta , Lachnospiraceae bacterium NSJ-29 , Phascolarctobacterium SGB4573 , GGB38744 SGB14842 (unclassified Oscillospiraceae ), and Massiliimalia timonensis (effect size ≥ 1.163, p .adj ≤ 0.092). The increase in Collinsella , a less characterized anaerobic pathobiont that produces lactate and has been associated with low-fiber intakes 62 , 63 and lipid metabolism 64 , may have been related to the periods of CR and IF, in conjunction with the greater influx of host-released fatty acids in the High-responder group. Relatedly, Clostridium leptum growth has been linked with increases in monounsaturated fat intake, reductions in blood cholesterol 65 , and stimulation of Treg induction (i.e., anti-inflammatory) 66 . The latter association is relevant to the SCFA-promoting (primarily butyrate) qualities of Clostridium leptum 67 . Blautia hydrogenotrophica , an acetogen with bidirectional metabolic cross-feeding properties (e.g., transfer of hydrogen and acetate), is also important for butyrate formation 68 . Taxa that decreased relative to the Low-responder group; Eubacterium ventriosum , Streptococcus salivarius , Eubacterium rectale , Anaerostipes hadrus , Roseburia inulinivorans , Mediterraneibacter glycyrrhizinilyticus , and Blautia massiliensis (effect size ≤ −1.690, p .adj ≤ 0.078), included butyrate producers, Eubacterium ventriosum , Eubacterium rectale , Roseburia inulinivorans , and others, such as Streptococcus salivarius , a nuclear factor kappa B (NF-κB) activity repressor 69 and Peroxisome proliferator-activated receptor gamma (PPARγ) inhibitor potentially influencing lipid and glucose metabolism 70 . Investigating monozygotic (MZ) twin pairs, Eubacterium ventriosum was more abundant in the higher BMI siblings 26 , with enhanced scavenging fermentation capabilities 71 . Roseburia inulinivorans is a mobile firmicute (flagella) that harbors a wide-ranging enzymatic repertoire able to act on various dietary polysaccharide substrates suggestive of the ability to respond to the availability of alternative dietary substrates 72 . While we noted a more variable shift in fecal total SCFAs, acetate, propionate, butyrate, or valerate (via targeted GC–MS), in the Low weight loss responders, there was no significant difference when compared to High weight loss responders (Wilcoxon rank-sum test, p  ≥ 0.210; Supplementaryl Fig.  S4a ; Supplementary Data  9 ).

a Relative weight loss over the eight-week intervention for each participant in the IF-P group. b NMDS ordination showed the personalized trajectories of participants’ microbiomes over time. Dotted lines connect the same individual and point toward the final sample collection. No significant time or group × time interaction effects for alpha diversity metrics, c observed species, and d the Shannon index. Box and whiskers plots display the box ranging from the first to the third quartile, and the center the median value, while the whiskers extend from each quartile to the minimum or maximum values. Volcano plots displaying differential abundance between High and Low weight loss responders for e microbial species and f functional pathways. Significant features were more enriched in High and Low weight loss responders colored orange and light blue, respectively. g Alluvial plot displaying the fecal metabolite profile at the subclass level (Human Microbiome Database). Most abundant metabolite subclasses displayed (i.e., ≥1%). Metabolome pathway analysis for h High and i Low weight loss responders using all reliably detected fecal metabolites showing altered pathways with moderate and above impact (>0.10). Impact was calculated using a hypergeometric test, while significance was determined using a test of relative betweenness centrality. j Grid-fused least absolute shrinkage and selection operator (GFLASSO) regression of species from differential abundance analysis displayed correlative relationships with fecal metabolites. Species with greater abundance in High (High > Low) and Low (Low > High) weight loss responders are separate‘. For all panels, High: n  = 5, Low: n  = 5. Source data are provided as a Source Data file.

Less affected compared to taxonomic features were the 275 microbial-affiliated metabolic pathways identified after filtering, of which gluconeogenesis III and guanosine ribonucleotides de novo biosynthesis were increased (effect size ≥ 0.108, p .adj = 0.079), while super pathway of L-alanine biosynthesis, sucrose degradation IV (sucrose phosphorylase), sucrose degradation III (sucrose invertase), super pathway of thiamine diphosphate biosynthesis III, and flavin biosynthesis I (bacteria and plants) were decreased in the High relative to the Low weight loss responder group (effect size ≤ −0.247, p .adj ≤ 0.079; Fig.  5f ; Supplementary Data  10 )

As the difference in microbial shifts versus function is well established, we also tracked the fecal metabolome to better understand metabolic modification/production and identify potential microbial metabolic targets for future weight loss interventions. Overall, we reliably detected (QC relative standard deviation > 20% and mean intensity value > 1000 in 80% of samples) and annotated 607 (Human Metabolome Database) compounds across fecal samples. Notably, we found the fecal metabolite profile of both subgroups abundant in amino acids, peptides, and analogs, with decreases in sulfates, furanones, and quaternary ammonium salts and increases in cholestane steroids, carboxylic acid derivatives, and imidazoles (Fig.  5g ). Assessing metabolite changes between groups did not yield significance when comparing logFC values (Wilcoxon rank-sum test, p .adj > 0.10; Supplementary Fig.  S4b ). Pathway analysis of High weight loss responders revealed prominent metabolic signatures relevant to lipid metabolism (glycerolipid and arachidonic metabolism), nucleotide turnover (pyrimidine metabolism), and aromatic amino acid formation (phenylalanine, tyrosine, and tryptophan biosynthesis; Fig.  5h , Supplementary Data  11 ). In comparison, the more prominent enriched pathways for Low weight loss responders included those related to amino acid and peptide metabolism (glycine, serine, and threonine, d-glutamine and d-glutamate, and tyrosine metabolism and arginine biosynthesis; Fig.  5i , Supplementary Data  12 ).

Finally, species captured by our differential abundance analysis were channeled into a GFLASSO model with the fecal metabolome library to select metabolically relevant compounds best predicted by microbial abundances. Restricting taxa and metabolites displaying stronger co-occurrence signals (GFLASSO coefficients > 0.02), we noted several patterns (Fig.  5j ). This included positive associations between GGB3511 SGB4688 (unclassified Firmicute) and malonic acid (important to fatty acid metabolism), as well as Roseburia inulinivorans and 3-Hydroxy-2-oxo-1H-indole-3-acetic acid. Negative associations included Phascolarctobacterium SGB4573 with the fatty acid ester, methyl sorbate, and Streptococcus salivarius (anti-inflammatory) with leukotriene B4 dimethylamide.

Differences detected in our subgroup analysis suggest that the GM composition plays a role in WL responsiveness during IF-P interventions. Notable differences in taxa and fecal metabolites suggest differing substrate utilization capabilities and nutrient-acquiring pathways between High and Low responders, despite being on the same dietary regimen. Although differences between High and Low responders were statistically significant for the microbiome data, the magnitude of differences varied, suggesting further research is needed to clarify these differences.

Long-term IF-P remodels the gut microbiome after substantial weight loss – A case study

Considering the microbiomic and metabolic importance of sustained WL, we additionally performed a longitudinal, exploratory case study analysis on the participant who lost the most body weight during the eight-week WL period (−15.3% BW, −24.9 kg). Under rigorous clinical supervision, this individual was guided through and comprehensively tracked over 52 weeks, strictly adhering to an IF-P regimen, including WL (0–16 weeks) and maintenance (16–52 weeks) periods, which included adjusting the calorie intake to maintain energy balance. Microbial richness and evenness at the species level displayed a general inverse trend with body weight reduction, although they converged at 52 weeks (Fig.  6a, b ). Species dissimilarity peaked at weeks four and 16, after which it plateaued, but remained consistently higher in comparison to baseline over the 52-week period (Fig.  6c ). Examining positive linear coefficients of a PERMANOVA model, constructed to detect variation between community compositions over time, dominant influences included several species within the Lachnospiraceae family such as Fusicatenibacter saccharivorans , Blautia wexlerae , Blautia massillensis , Anaerostipes hadrus , and Coprococcus comes and others like Akkermansia muciniphila (Fig.  6d ). Negative contributions included species from the Oscillospiraceae family, such as Ruminococcus bromii and Ruminococcus torques . Indeed, visualizing community composition over the sampling time points suggested specific GM remodeling (Fig.  6e ; Supplementary Data  13 ). Many keystone taxa prominent over time in the microbiome are highly relevant to the significant reduction in body weight and metabolic improvement of the case-study participant. For example, Blautia wexlerae , a commensal bacterium recently reported to confer anti-adipogenesis and anti-inflammatory properties to adipocytes 73 became visually more prominent over time. This association was also the case for the health-associated microbe, Anaerostipes hadrus , which converts inositol stereoisomers (including myoinositol) to propionate and acetate, apt to improve insulin sensitivity and reduce serum triglyceride levels 74 , translating to reduced host metabolic disease risk 75 . Other elevated taxa, like the mucin-degrading Akkermansia muciniphila and Bacteroides faecis , are negatively correlated with markers for insulin resistance 76 . There was also a notable bloom of Collinsella SGB14861 (anaerobic pathobiont producing lactate) 63 and suppression of Eubacterium rectale , Ruminococcus torques (associated with circadian rhythm disruption in mice) 77 , and Ruminococcus bromii (an exceptional starch degrader) 78 .

Change in alpha diversity metrics a observed species and b Shannon index with percentage of baseline body weight. c Bray-Curtis dissimilarity at the species level with d top PERMANOVA model coefficients (analysis: species~time). e Alluvial plot displaying the variation in abundance of the 20 most prevalent bacteria over time. For visual clarity, the less abundant taxa are not displayed. f Canberra distance of fecal metabolome with g top PERMANOVA model coefficients (analysis: pathway~time). h Pathway analysis of fecal metabolites comparing baseline to subsequent sample collections. Data are plotted as -log10(p) versus pathway impact. Node size corresponds to the proportion of metabolites captured in each pathway set, while node color signifies significance. Impact was calculated using a hypergeometric test, while significance was determined using a test of relative betweenness centrality. No p -value adjustments were made. Source data are provided as a Source Data file.

Compared to the more pronounced shifts in the GM, an inspection of Bray-Curtis dissimilarity at the microbial metabolic pathway level was much less affected (Supplementary Fig.  S5a ). Though positive contributions in multiple biosynthesis pathways were noted, as well as reductions in the superpathway of UDP-glucose-derived O-antigen building blocks biosynthesis and glucose and glucose-1-phosphate degradation (Supplementary Fig.  S5b ; Supplementary Data  14 ). We also tracked the fecal metabolome concordance with the GM to corroborate potential metabolic output. Shifts in metabolites captured by calculating the Canberra distance were prominent (Fig.  6f ), with positive influences from agrocybin (possessing antifungal activity 79 ), nicotinic acid (nicotinamide adenine dinucleotide precursor), and sulfate, and reductions in cadaverine (involved in the inhibition of intestinal motility 80 ), maltitol, acetohydroxamic acid (a urease inhibitor), and hypoxanthine, after removing the dominant amino acid subclass (Fig.  6g ; Supplementary Fig.  S5c ). At the chemical class level, we observed apparent shifts in chemical subclasses; cholestane steroids, amines, purines, and purine derivatives, and amino acids, peptides, and analogs (Supplementary Fig.  S5d ). Given our case-study approach, we performed a pathway analysis using all reliably detected fecal metabolites at each collection point over 52 weeks. Pathway analysis (Fig.  6h ) identified primary bile acid biosynthesis ( p  = 0.014) and cysteine and methionine metabolism ( p  = 0.096) as having the greatest significance, while the greatest impact (I) was observed in phenylalanine, tyrosine, and tryptophan biosynthesis and linoleic acid metabolism ( I  = 1.0). Alanine, aspartate, and glutamate metabolism ( I  = 0.756), vitamin B6 metabolism ( I  = 0.647), sulfur metabolism ( I  = 0.532), phenylalanine metabolism (I =  0.357), and nicotinate and nicotinamide metabolism ( I  = 0.194) also displayed marked pathway impacts (Supplementary Fig.  S5e ; Supplementary Data  15 ). Together, these integrated findings from the group comparisons (IF-P vs. CR), high vs. low responders, and the case study, suggest that the remodeling of the gut microbiome through sustained weight loss on an IF-P regimen not only alters the microbial composition but also influences key metabolic pathways and output, reflective of fat mobilization and metabolic improvement.

Our study demonstrates distinct effects of IF-P on gut symptomatology and microbiome, as well as circulating metabolites compared to continuous CR. We observed significant changes in the GM response to both interventions; however, the IF-P group exhibited a more pronounced community shift and greater divergence from baseline (i.e., intra-individual Bray-Curtis dissimilarities). This shift was characterized by increased specific microbial families and genera, such as Christensenellaceae , Rikenellaceae , and Marvinbryantia , associated with favorable metabolic profiles. Furthermore, IF-P significantly increased circulating cytokine concentrations of IL-4, IL-6, IL-8, and IL-13. These cytokines have been linked to lipolysis, WL, inflammation, and immune response. The plasma metabolome analysis revealed distinct metabolite signatures in IF-P and CR groups, with the convergence of multiple metabolic pathways. These findings shed light on the differential effects of IF regimens, including IF-P as a promising dietary intervention for obesity management and microbiotic and metabolic health.

While acknowledging individual contributions of WL, protein pacing, and IF, we propose that the beneficial shifts observed may be best characterized as the culmination of features inherent in our IF-P approach. For example, it is possible that microbial competition is leveraged during reduced and intermittent nutritional input periods, emphasizing nutrient composition and food matrix type (combination of whole food and meal replacements vs. primarily whole food), affecting available substrates for gut microbes. IF-P participants’ fiber intake was concentrated in fiber-rich (RS5 type) shakes, offering immediate availability of fiber to the GI tract. In contrast, CR participants consumed fiber through whole foods, leading to a slower digestion and absorption process influenced by individual digestive transit times and enzymatic profiles. This nutritional environment may create ecological niches that support symbiont microbial communities. In this investigation, we provide support of such remodeling, with intentional fasting and increased relative protein (protein pacing) consumption well-validated to improve body composition and metabolism during weight loss 7 , 8 , 15 . Our results align with previous studies on CR, where greater relative protein intake was associated with an increased abundance of Christensenella 81 . This increase is likely a result of increased amino acid-derived metabolites 21 . We also observed increased signatures of amino acid metabolism in the GM of IF-P participants, which may be attributed to increased nitrogen availability, prompting de novo amino acid biosynthesis. The liquid format of two of the daily meals and precise timing of high-quality protein consumption (Protein Pacing) in the IF-P regimen may have influenced these results, as amino acids play essential roles in microbial communities, acting as energy and nitrogen sources and essential nutrients for amino acid auxotrophs.

In addition to the differences in nutrient composition, the IF-P group exhibited a profound reduction (33%) in visceral fat 15 . This reduction is significant because visceral fat is highly correlated with GM. While the specific influence of GM on fat depots in our study remains unclear, the shift in cytokine profile and metabolic pathways suggests an interaction between GM and fat metabolism. Regarding GM-host interaction, we did not detect changes in gut permeability assaying LBP. However, correlations were found with cytokines IL-4 and IL-13 and microbes Colidextribacter (negative association) and Ruminoccus gauveauii group (positive association). These associations may reflect the direct impact of the dietary intervention, yet they also hint at a deeper crosstalk within the gut-immune axis. This crosstalk is known to play a pivotal role in modulating host inflammation and influencing adipose tissue signaling pathways 42 . Furthermore, the observed microbial shifts, including changes in populations of Christensenella , suggest a nuanced role for certain microbes in regulating metabolic health. Notably, certain strains of Christensenella have been implicated in the regulation of key metabolic markers, such as glycemia and leptin levels, and in promoting hepatic fat oxidation 82 .

Our findings also underscore that GM composition plays a role in WL responsiveness during IF-P interventions. Subgroup analysis based on WL responsiveness revealed significant differences in species composition at the taxonomic level. The High-responder group showed an increased abundance of certain bacteria associated with metabolic benefits and anti-inflammatory effects. In contrast, the Low-responder group exhibited an increased abundance of butyrate-producing and nutritionally adaptive species (e.g., Eubacterium ventriosum 71 and Roseburia inulinivorans 72 ). Fecal metabolome analysis further highlighted differences between the two subgroups, with distinct metabolic signatures and enrichment in specific metabolic pathways. Notably, the High WL responders displayed enrichment of fecal metabolites involved in lipid metabolism. In contrast, Low responders were more prominent in pathways related to the metabolism of amino acids and peptides, including glycine, serine, and threonine, d-glutamine, and d-glutamate, as well as tyrosine metabolism and arginine biosynthesis. The latter metabolic signature has been reported in individuals with severe obesity undergoing high-protein, low-calorie diets 83 . As both High and Low WL responders were consuming the same diet, our results suggest differences in GM composition and metabolism, which could play a role in determining the success of an IF-P regimen. Though, as these enrichment analyses were performed in an exploratory manner, we acknowledge the need for a more systematic approach to validate these findings.

Finally, we provide evidence of long-term GM stabilization from these changes by following one individual over 12 months. Dietary restriction is widely used to reduce fat mass and weight in individuals with or without obesity; however, weight regain after such periods presents a critical challenge, and the underlying homeostatic mechanisms remain largely elusive. Notably, keystone taxa that became more prominent over time were associated with anti-adipogenesis, improved insulin sensitivity, and reduced metabolic disease risk. The microbial shifts were accompanied by noticeable changes in the fecal metabolome, with shifts in various metabolites and chemical subclasses. Pathway analysis identified impacts on primary bile acid biosynthesis, cysteine and methionine metabolism, and other fat mobilization and metabolic improvement pathways. These shifts were accompanied by noticeable changes in the fecal metabolome, particularly in metabolites and chemical subclasses related to lipid metabolism, nucleotide turnover, and aromatic amino acid formation.

Despite the valuable insights from our study on the complex interactions between intermittent fasting, higher protein intake using protein pacing, the GM, and circulating metabolites in obese individuals, several limitations should be acknowledged. First, our reliance on fecal samples to represent the GM may have overlooked potential microbial populations in the upper GI tract. Including samples from proximal regions in future studies would provide a more comprehensive understanding of the gut microbiome’s response to IF-P and CR. In addition, the sample size for our study was determined based on the primary outcomes related to body weight and composition from the parent study 15 . This sample size may have reduced statistical power and potentially amplified individual variability among participants. However, it is important to note that the smaller RCT design allowed for more precise control over diet and lifestyle factors, minimizing potential confounding influences on the study outcomes. Furthermore, the study’s duration was limited to eight weeks, which prevented potential insights into the differential long-term effects between the two interventions. However, we were able to extend the follow-up duration and conduct periodic assessments for a year in our case-study participant, offering a more comprehensive understanding of the sustainability of the observed changes and the potential for weight regain for IF-P. The current study compared a combination of whole food and supplements (shakes and bars; IF-P) versus primarily whole food (CR), which together with variations in protein and fiber content and type may have influenced the gut symptomatology and nutrient absorption between groups. Additionally, study participants self-reported dietary intake daily, although there was close monitoring of intake through the return of empty food packaging/containers of consumed food and daily monitoring by investigators and weekly meetings with a registered dietitian. Overall, knowledge gaps are present in this research, including how the microbiome is rebuilt after food reintroduction and how overall caloric restriction and specific macronutrients contribute to this process. However, considering the multifactorial nature of weight loss and metabolic health, our work represents an important precedent for future work. Future investigators should consider integrating these factors to provide a more comprehensive understanding of the underlying mechanisms. Additional research is warranted to characterize the metabolic signature of IF-P, the time relationship between these fasting periods, and the analysis of these metabolic changes. A strength of our High-Low-responder and case-study analyses is the hypothesis-driving nature of the findings, from which targeted microbiome and/or precision nutrition interventions can be designed and tested.

In conclusion, our study provides valuable insights into the complex interactions among intermittent fasting and protein pacing, the GM, and circulating metabolites in individuals with obesity. Specifically, intermittent fasting - protein pacing significantly reduces gut symptomatology and increases gut microbes associated with a lean phenotype ( Christensenella ) and circulating cytokines mediating total body weight and fat loss. These findings highlight the importance of personalized approaches in tailoring dietary interventions for optimal weight management and metabolic health outcomes. Further research is necessary to elucidate the underlying mechanisms driving these associations and to explore the therapeutic implications for developing personalized strategies in obesity management. Additionally, future studies should consider investigating microbial populations in upper GI sections and potential intestinal tissue remodeling to gain a more comprehensive understanding of the gut microbiome’s role in these interventions.

Study design and participants

The protocol of the clinical trial was registered on March 6, 2020 (Clinicaltrials.gov; NCT04327141), and the results of the primary analysis have been published previously 15 . Briefly, participants were recruited from Saratoga Springs, NY, and were provided informed written consent in accordance with the Skidmore College Human Subjects Institutional Review Board before participation (IRB#: 1911-859), including consent for the use of samples and data from the current study. Each procedure performed was in adherence with New York state regulations and the Federal Wide Assurance, which follows the National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research, and in agreement with the Helsinki Declaration (revised in 1983). Their physicians performed a comprehensive medical examination/history assessment to rule out any current cardiovascular or metabolic disease. For at least six months before the start of the study, all eligible participants were either sedentary or lightly active (<30 min, two days/week of organized physical activity), with overweight or obesity (BMI > 27.5 kg/m2; % body fat > 30%), weight stable (±2 kg), and middle-aged (30–65 years). In addition, participants taking antibiotics, antifungals, or probiotics within the previous two months were excluded. Enrolled participants were matched for body weight, BMI, and body fat and randomly assigned to one of two groups: (a) IF-P ( n  = 21; 14 women; 7 men) or (b) CR ( n  = 20; 12 women; 8 men) for eight weeks. During a one-week run-in period, subjects maintained a stable body weight by consuming a similar caloric intake as their pre-enrollment caloric intake while maintaining their sedentary lifestyle. This was confirmed by matching their pre-enrollment dietary intake to the one-week run-in diet period 15 . Following baseline testing, participants were provided detailed instructions on their weight loss dietary regimen (Supplementary Table  S1 ) and received weekly dietary counseling and compliance/adherence monitoring from the research team via daily food records, and weekly registered dietitian meetings, along with weekly visits to the Human Nutrition and Metabolism laboratory at Skidmore College (Saratoga Springs, NY) for meal distribution and empty packet/container returns. All outcome variables were assessed pre (week 0), mid (week 4), and post (week 8). All participants were compensated $100 for successful completion of the study and received an additional monthly stipend of $75 for groceries (CR group only) or up to two meals per day of food supplements and meal replacements (IF-P only).

IF days consisted of ~350–550 kcals per day, in which participants were provided a variety of supplements and snacks. Protein pacing (P) days for IF-P consisted of four and five meals/day for women and men, respectively, two of which (breakfast and one other meal) were liquid meal replacement shakes with added whole foods (Whole Blend IsaLean® Shakes, 350/400 kcals, 30/36 g of protein/meal, 9 g of fiber); a whole food evening dinner meal (450/500 kcals men), an afternoon snack (200 kcals, men only), and an evening protein snack (IsaLean® or IsaPro® Shake or IsaLean Whole Blend® Bar; 200–250 kcals). This dietary regimen provided 1350–1500 and 1700–1850 kcals/day for women and men, respectively, and a macronutrient distribution targeting 35% protein, 35% carbohydrate, 20–30 g/day of fiber, and 30% fat. Isagenix International, LLC (Gilbert, AZ, USA) provided all meal replacement shakes, bars, beverages, and supplements. In comparison, participants assigned to the CR diet followed specific guidelines of the National Cholesterol Education Program Therapeutics Lifestyle Changes (TLC) diet of the American Heart Association with a strong Mediterranean diet influence of a variety of fresh vegetables, fruits, nuts, and legumes. The specific macronutrient distribution recommended was <35% of kcal as fat; 50%–60% of kcal as carbohydrates; 15% kcal as protein; <200 mg/dL of dietary cholesterol; and 20–30 g/day of fiber. The total calorie intake was 1200 and 1500 calories per day for women and men, respectively, during the 8-week weight loss intervention. In addition to weekly meetings with the registered dietitian and daily contact with research team members, subjects were provided detailed written instructions for their meal plans. They were closely monitored through daily participant-researcher communication (e.g., email, text, and mobile phone), two-day food diary analysis, weekly dietary intake journal inspections, weekly meal/supplement container distribution, and returning empty packets and containers.

Gastrointestinal (GI) symptom rating scale

Participants completed the 15-question GI symptom rating scale (GSRS) 84 at baseline, week four, and week eight. Briefly, each question is rated on a 7-point Likert scale (1 = absent; 2 = minor; 3 = mild; 4 = moderate; 5 = moderately severe; 6 = severe and 7 = very severe) and recalled from the previous week. Questions include symptoms related to upper abdominal pain, heartburn, regurgitation (acid reflux), empty feeling in the stomach, nausea, abdominal rumbling, bloating, belching, flatulence, and questions on defecation. The GSRS questionnaire provides explanations of each symptom, is understandable, and has reproducibility for measuring the presence of GI symptoms 85 . In our analysis, a score of ≥2 (minor) was defined as symptom presence, and a score ≥ 4 (moderate) was defined as moderate symptom presence. Furthermore, to better categorize symptom location, bloating, flatulence, constipation, diarrhea, stool consistency, defecation urgency, and sensation of not completely emptying bowels were classified as lower GI symptoms, and nausea, heartburn, regurgitation, upper abdominal pain, empty feeling in the stomach, stomach rumbling, and belching was classified as upper GI symptoms. Total scores were also generated for overall symptom and moderate symptom presence.

Fecal sample collection and DNA extraction

Participants were instructed to provide stool samples at baseline, week four, and week eight of the intervention. The case-study participant additionally provided samples at weeks 12, 16, 32, and 52. The entire bowel movement was collected and transported within 24 h of defecation to the Skidmore College Human Nutrition and Metabolism (Saratoga Springs, NY) laboratory using a cooler and ice packs and frozen at −80 °C. Samples were then sent to ASU (Phoenix, AZ) overnight on dry ice for analysis, where they were thawed at 4 °C and processed. Wet weight was recorded to the nearest 0.01 g after subtracting the weight of fecal collection materials. Stool samples were then rated according to the BSS 86 , homogenized in a stomacher bag, and the pH was measured (Symphony SB70P, VWR International, LLC., Radnor, PA, USA). Next, the extraction of DNA was performed using the DNeasy PowerSoil Pro Kit (Cat. No. 47016, Qiagen, Germantown, MD) per the manufacturer’s instructions. DNA concentration and quality were quantified using the NanoDrop™ OneC Microvolume UV-Vis Spectrophotometer (Thermo Scientific™, Waltham, MA) according to manufacturer instructions. The OD 260 /OD 280 ratio of all samples was ≥1.80 (demonstrating DNA purity).

Quantification of bacterial 16S rRNA genes

To estimate total bacterial biomass per sample (16S rRNA gene copies per gram of wet stool), DNA extracted from the fecal collections was assessed via quantitative polymerase chain reaction (qPCR) based on previously published methods 87 , 88 . Briefly, all 20 μL qPCR reactions contained 10 uL of 2X SYBR Premix Ex Taq ™ (Tli RNase H Plus) (Takara Bio USA, Inc., San Jose, CA, USA), 0.3 μM (0.6 μL) of each primer (926 F: AAACTCAAAKGAATTGACGG; 1062 R: CTCACRRCACGAGCTGAC), 2 μL DNA template (or PCR-grade water as negative control), and 6.8 μL nuclease-free water (Thermo Fisher Scientific, Waltham, MA, USA). PCR thermal cycling conditions were as follows: 95 °C for 5 min, followed by 35 cycles of 95 °C for 15 s, 61.5 °C for 15 s, and 72 °C for 20 s, then hold at 72 °C for 5 min, along with a melt curve of 95 °C for 15 s, 60 °C for 1 min, then 95 °C for 1 s. Quantification was performed using a QuantStudio3™ Real-Time PCR System by Applied Biosystems with QuantStudio Design and Analysis Software 1.2 from Thermo Fisher Scientific (Waltham, MA, USA). All samples were analyzed in technical replicates. For quality assurance and quality control, molecular negative template controls (NTC) consisting of PCR-grade water (Invitrogen, Waltham, MA, USA) and positive controls created by linearized plasmids were run on every qPCR plate. Standard curves were run-in triplicate and used for sample quantification, ranging from 10 7 to 10 1 copies/μL with a cycle threshold (CT) detection limit cutoff of 33. Reaction efficiency was approximately 101%, with a slope of −3.29 and R 2  ≥ 0.99.

Fecal microbiome analysis

Amplification of the 16S rRNA gene sequence was completed in triplicate PCRs using 96-well plates. Barcoded universal forward 515 F primers and 806 R reverse primers containing Illumina adapter sequences, which target the highly conserved V4 region, were used to amplify microbial DNA 89 , 90 . PCR, amplicon cleaning, and quantification were performed as previously outlined 90 . Equimolar ratios of amplicons from individual samples were pooled together before sequencing on the Illumina platform (Illumina MiSeq instrument, Illumina, Inc., San Diego, CA). Raw Illumina microbial data were cleaned by removing short and long sequences, sequences with primer mismatches, uncorrectable barcodes, and ambiguous bases using the Quantitative Insights into Microbial Ecology 2 (QIIME2) software, version 2021.8 91 .

16S rRNA sequencing produced 7,366,128 reads with a median of 53,776 per sample (range: 9512–470,848). Paired-end, demultiplexed data were imported and analyzed using QIIME2 software. Upon examination of sequence quality plots, base pairs were trimmed at position 20 and truncated at position 240 and were run through DADA2 to remove low-quality regions and construct a feature table using ASVs. Next, the ASV feature table was passed through the feature-classifier plugin 92 , which was implemented using a naive Bayes machine-learning classifier, pre-trained to discern taxonomy mapped to the latest version of the rRNA database SILVA (138.1; 99% ASVs from 515 F/806 R region of sequences) 93 . Based on an assessment of alpha rarefaction, a threshold of 6500 sequences/sample was established, retaining all samples for downstream analysis. A phylogenic tree was then constructed using the fragment-insertion plugin with SILVA at a p-sampling depth of the rarefaction threshold to impute high-quality reads and normalize for uneven sequencing depth between samples 94 . Alpha diversity (intra-community diversity) was measured using observed ASVs and the Phylogenetic diversity index. Additionally, the Shannon index was calculated for the subgroup and case-study analyses to capture richness and evenness at the species level. Beta diversity (inter-community diversity) was measured using Bray-Curtis dissimilarity.

For shotgun metagenomics, DNA was sequenced on the Illumina NextSeq 500 platform (Illumina, CA, USA) to generate 2 × 150 bp paired-end reads at greater sequencing depth with a minimum of 10 million reads. Raw Illumina sequencing reads underwent standard quality control with FastQC. Adapters were trimmed using TrimGalore. DNA sequences were aligned to Hg38 using bowtie2 95 . DNA sequences were then analyzed via the bio bakery pipeline 96 for taxonomic composition and potential functional content with MetaPhlAn4 and HUMAnN 3.0 (UniRef90 gene-families and MetaCyc metabolic pathways), using standard parameters. Functional profiling resulted in 8528 distinct Kyoto Encyclopedia of Genes and Genomes Orthology (KO) groups and 511 metabolic pathways, which align with previous human gut microbiome studies 96 .

Blood sample collection and biochemical analyses

All participants were tested between the hours of 6:00 a.m. and 9:00 a.m., after an overnight fast for body composition assessments (height, body weight, and total body composition) at weeks 0, 4, and 8. 12-h fasted venous blood samples (~20 mL) were collected into EDTA-coated vacutainer tubes and centrifuged (Hettich Rotina 46R5) for 15 min at 4000 ×  g at −4 °C. After separation, plasma was stored at −80 °C until analyzed. Undiluted plasma samples were sent to Eve Technologies (Calgary, Alberta, Canada) for assessment of inflammatory cytokines [Granulocyte-macrophage colony-stimulating factor [GM-CSF], interferon-γ (IFNγ), interleukin (IL)-β, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, IL-12p70, IL-13, IL-17A, IL-23, and Tumor necrosis factor-α (TNFα)] using a high human sensitivity 14-plex cytokine assay (Millipore, Burlington, MA). Circulating LBP concentrations were quantified in duplicate using 1000x diluted plasma samples. A commercially available kit was used per the manufacturer’s protocol (Cat No. EH297RB, Thermo Fisher Scientific, Inc, Waltham, MA; intra-assay coefficient variation [CV] <10%).

Targeted plasma metabolomic analysis

For the plasma metabolomic analysis, a 12-h fasted venous blood sample (~20 mL) was collected into EDTA-coated vacutainer tubes and centrifuged (Hettich Rotina 46R5) for 15 min at 4000 ×  g at 4 °C. After separation, 2 mL of plasma was aliquoted and stored at −80 °C at the Biochemistry Laboratory at Skidmore College (Saratoga Springs, NY, USA). Samples were then sent to the Arizona Metabolomics Laboratory at ASU (Phoenix, AZ, USA) overnight on dry ice for analysis, where they were thawed at 4 °C and processed. Briefly, 50 μL of plasma from each sample was processed to precipitate proteins and extract metabolites by adding 500 μL MeOH and 50 μL internal standard solution (containing 1810.5 μM 13 C 3 -lactate and 142 μM 13 C 5 -glutamic acid). The mixture was vortexed (10 s) and stored for 30 min at –20 °C, then centrifuged at 224,000 ×  g for 10 min at 4 °C. Supernatants (450 μL) were extracted, transferred to new Eppendorf vials, and dried (CentriVap Concentrator; Labconco, Fort Scott, KS, USA). Samples were then reconstituted in 150 μL of 40% phosphate-buffered saline (PBS)/60% acetonitrile (ACN) and centrifuged again at 22,000 ×  g at 4 °C for 10 min. Supernatants (100 µL) were transferred to an LC autosampler vial for subsequent analysis. Quality control (QC) was performed by creating a pooled sample from all plasma samples and injecting once every ten experimental samples to monitor system performance.

The highly-reproducible targeted LC–MS/MS method used in the current investigation was modeled after previous studies 97 , 98 , 99 . The specific metabolites included in our targeted detection panel are representative of more than 35 biological pathways most essential to biological metabolism and have been successfully leveraged for the sensitive and broad detection of effects related to diet 100 , diseases 101 , drug treatment 102 , environmental contamination 103 , and lifestyle factors 104 . Briefly, LC–MS/MS experiments were performed on an Agilent 1290 UPLC-6490 QQQ-MS system (Santa Clara, CA, USA). Each sample was injected twice for analysis, 10 µL using negative and 4 µL using positive ionization modes. Chromatographic separations were performed in hydrophilic interaction chromatography (HILIC) mode on a Waters Xbridge BEH Amide column (150 × 2.1 mm, 2.5 µm particle size, Waters Corporation, Milford, MA, USA). The flow rate was 0.3 mL/min, the autosampler temperature was maintained at 4 °C, and the column compartment was set at 40 °C. The mobile phase system was composed of Solvents A (10 mM ammonium acetate, 10 mM ammonium hydroxide in 95% H 2 O/5% ACN) and B (10 mM ammonium acetate, 10 mM ammonium hydroxide in 95% ACN/5% H 2 O). After the initial 1 min isocratic elution of 90% Solvent B, the percentage of Solvent B decreased to 40% at t  = 11 min. The composition of Solvent B was maintained at 40% for 4 min ( t  = 15 min).

The mass spectrometer was equipped with an electrospray ionization (ESI) source. Targeted data acquisition was performed in multiple-reaction monitoring (MRM) mode. The LC–MS system was controlled by Agilent MassHunter Workstation software (Santa Clara, CA, USA), and extracted MRM peaks were integrated using Agilent MassHunter Quantitative Data Analysis software (Santa Clara, CA, USA).

GC–MS fecal short-chain fatty acid analysis

Before GC–MS analysis of SCFAs, frozen fecal samples were first thawed overnight under 4 °C. Then, 20 mg of each sample was homogenized with 5 μL hexanoic acid—6,6,6-d 3 (internal standard; 200 µM in H 2 O), 15 μL sodium hydroxide (NaOH [0.5 M]), and 500 μL MeOH. Samples were stored at −20 °C for 20 min and centrifuged at 22,000 ×  g for 10 min afterward. Next, 450 μL of supernatant was collected, and the sample pH was adjusted to 10 by adding 30 μL of NaOH:H 2 O (1:4, v-v). Samples were then dried, and the residues were initially derivatized with 40 µL of 20 mg/mL MeOX solution in pyridine under 60 °C for 90 min. Subsequently, 60 µL of MTBSTFA containing d 27 -mysristic acid was added, and the mixture was incubated at 60 °C for 30 min. The samples were then vortexed for 30 s and centrifuged at 22,000 ×  g for 10 min. Finally, 70 µL of supernatant was collected from each sample and injected into new glass vials for GC–MS analysis.

GC–MS conditions used here were adopted from a previously published protocol 105 . Briefly, GC–MS experiments were performed on an Agilent 7820 A GC-5977B MSD system (Santa Clara, CA); all samples were analyzed by injecting 1 µL of prepared samples. Helium was the carrier gas with a constant flow rate of 1.2 mL/min. Separation of metabolites was achieved using an Agilent HP-5 ms capillary column (30 m × 250 µm × 0.25 µm). Ramping parameters were as follows: column temperature was maintained at 60 °C for 1 min, increased at a rate of 10 °C/min to 325 °C, and then held at this temperature for 10 min. Mass spectral signals were recorded at an m/z range of 50–600, and data extraction was performed using Agilent Quantitative Analysis software. Following peak integration, metabolites were filtered for reliability. Only those with QC CV < 20% and a relative abundance of 1000 in > 80% of samples were retained for statistical analysis.

Untargeted fecal metabolomic analysis

Briefly, each fecal sample (~20 mg) was homogenized in 200 µL MeOH:PBS (4:1, v-v, containing 1810.5 μM 13 C 3 -lactate and 142 μM 13 C 5 -glutamic Acid) in an Eppendorf tube using a Bullet Blender homogenizer (Next Advance, Averill Park, NY). Then 800 µL MeOH:PBS (4:1, v-v, containing 1810.5 μM 13 C 3 -lactate and 142 μM 13 C 5 -glutamic Acid) was added, and after vortexing for 10 s, the samples were stored at −20 °C for 30 min. The samples were then sonicated in an ice bath for 30 min. The samples were centrifuged at 22,000 ×  g for 10 min (4 °C), and 800 µL supernatant was transferred to a new Eppendorf tube. The samples were then dried under vacuum using a CentriVap Concentrator (Labconco, Fort Scott, KS). Prior to MS analysis, the obtained residue was reconstituted in 150 μL 40% PBS/60% ACN. A quality control (QC) sample was pooled from all the study samples.

The untargeted LC–MS metabolomics method used here was modeled after that developed and used in a growing number of studies 106 , 107 , 108 . Briefly, all LC–MS experiments were performed on a Thermo Vanquish UPLC-Exploris 240 Orbitrap MS instrument (Waltham, MA). Each sample was injected twice, 10 µL for analysis using negative ionization mode and 4 µL for analysis using positive ionization mode. Both chromatographic separations were performed in hydrophilic interaction chromatography (HILIC) mode on a Waters XBridge BEH Amide column (150 × 2.1 mm, 2.5 µm particle size, Waters Corporation, Milford, MA). The flow rate was 0.3 mL/min, autosampler temperature was kept at 4 °C, and the column compartment was set at 40 °C. The mobile phase was composed of Solvents A (10 mM ammonium acetate, 10 mM ammonium hydroxide in 95% H 2 O/5% ACN) and B (10 mM ammonium acetate, 10 mM ammonium hydroxide in 95% ACN/5% H 2 O). After the initial 1 min isocratic elution of 90% B, the percentage of Solvent B decreased to 40% at t  = 11 min. The composition of Solvent B maintained at 40% for 4 min ( t  = 15 min), and then the percentage of B gradually went back to 90%, to prepare for the next injection. Using mass spectrometer equipped with an electrospray ionization (ESI) source, we collected untargeted data from 70 to 1050 m/z.

To identify peaks from the MS spectra, we made extensive use of the in-house chemical standards (~600 aqueous metabolites), and in addition, we searched the resulting MS spectra against the HMDB library, Lipidmap database, METLIN database, as well as commercial databases including mzCloud, Metabolika, and ChemSpider. The absolute intensity threshold for the MS data extraction was 1000, and the mass accuracy limit was set to 5 ppm. Identifications and annotations used available data for retention time (RT), exact mass (MS), MS/MS fragmentation pattern, and isotopic pattern. We used the Thermo Compound Discoverer 3.3 software for aqueous metabolomics data processing. The untargeted data were processed by the software for peak picking, alignment, and normalization. To improve rigor, only the signals/peaks with CV < 20% across quality control (QC) pools, and the signals showing up in >80% of all the samples were included for further analysis. To ensure the robustness of our model validation, we employed an enhanced validation approach by repeating the LOOCV process 100 times. Each iteration involves excluding one sample from the dataset to serve as the test set, with the model being trained on the remaining samples. This approach, referred to as ‘repeated LOOCV’, was adopted to mitigate bias and provide a thorough validation of our model’s predictive capability. The method signifies the number of repetitions of the LOOCV process, rather than splitting the dataset into 100 equal parts.

Multi-omics data analysis

For MOFA, bacterial 16S rRNA ASVs and plasma metabolites were integrated using the MOFA2 package 55 . Before integration, ASV sequences were filtered (minimum of 5 ASV in greater than 10% of all samples), collapsed to the genus level, and scaled using a centralized-log-ratio, as described previously 109 . Plasma metabolites were scaled and normalized as described in the metabolome analysis. The inputs for MOFA model training comprised 53 taxa and 138 metabolites. The latent factors and feature loadings were extracted from the best-trained model with the built-in functions of MOFA2. After model fitting, the number of factors was estimated by requiring a minimum of 2% variance explained across all microbiome modalities.

Integrating microbial taxa with the same filtration as stated above (at the genus level from 16S amplicon sequencing and species level from metagenomic sequencing) and cytokine data and fecal metabolomic data, respectively, was conducted with GFLASSO (R package: GFLASSO, v0.0.0.9000). This correlation-based network solution can handle multiple response variables for a given set of predictors (in this case: 1. cytokine abundances predicted by microbial taxa response; and 2. fecal metabolite response predicted by microbial taxa). Solution parsimony was determined by an unweighted (i.e., presence or absence of association by imposing a correlation threshold) network structure. The regularization and fusion parameters were determined from the smallest root mean squared error (RMSE) estimate via cross-validation, accounting for interdependencies among microbial features. The tested parameters encompassed all combinations between λ and γ with values ranging from 0 to 1 (inclusive) in step increments of 0.1. GFLASSO coefficient matrices were constructed using a threshold coefficient of >0.02 to discern the strongest associative signals.

Statistical analysis

Gastrointestinal symptom scores were on the low end of the GSRS scale and not normally distributed; therefore, nonparametric statistical tests were applied. Symptom prevalence (number of scores ≥ 2) and moderate symptom prevalence (≥4) for total, upper, and lower GI GSRS clusters were analyzed using contingency tables. Specifically, differences between IF-P and CR GI symptoms at baseline were compared using a Fisher’s Exact test, whereas baseline vs. weeks four and eight values were compared with McNemar’s test. Stool weight, BSS, fecal pH, plasma cytokines and LBP, and SCFAs were assessed for normality with Q-Q plots and Shapiro-Wilk tests and log-transformed where appropriate. These were then tested for time and interaction (group × time) effects using linear-mixed effect (LME) models, with each participant included as a random effect.

For analysis and visualization of the microbiome data, artifacts generated in QIIME2 were imported into the R environment (v4.2.2) using the phyloseq package (v1.42.0) 110 . Before conducting downstream analyses, sequences were filtered to remove all non-bacterial sequences, including archaea, mitochondria, and chloroplasts. After assessing normality (Shapiro-Wilk’s tests), LME models were used to test the effect of time and the interaction of group and time with the covariates of age and sex with each participant included as a random effect on the alpha diversity metrics using the nLME package (v3.1.160). For beta diversity, a nested permutational analysis of variance (PERMANOVA) was conducted on Bray-Curtis dissimilarities using the Adonis test in the vegan package (v2.6.2) with 999 permutations. The PERMANOVA model incorporated the factors of time, individual, interaction (group × time), and participant (nested factor). A permutation test for homogeneity in multivariate dispersion (PERMDISP) was conducted using the ‘betadisper’ function in the vegan package to compare dispersion. To support the Adonis analysis, intra-individual differences were also compared between groups, as previously described 111 , by calculating the within-subject distance for paired samples (baseline vs. weeks four and eight) and testing for group distances (Wilcoxon rank-sum test). Differential abundance analysis was performed using MaAsLin2 (v1.12.0) 18 . To detect changes in microbial features between groups over time, we built linear-mixed models that include group, time, and their interaction, with age and sex as covariates and the participant as a random factor. Before analysis, raw counts from the ASV table were filtered for any sequence not present five times in at least 30% of all samples. A significant p-value for the product term indicates that changes in microbial features differed over time between groups. The Benjamini–Hochberg (BH) procedure was used to correct for multiple testing at ≤0.10. To assess the correlation between changes in specific taxa and biomarkers over the eight-week intervention, Spearman correlation tests were performed.

Univariate and multivariate analyses of plasma metabolites and metabolic ontology analysis were performed, and results were visualized using the MetaboAnalystR 5.0 112 . Human metabolomic data were mapped to the Kyoto Encyclopedia of Genes and Genomes (KEGG) human pathway library to analyze predicted states 113 . The data were log 10 -transformed, and Pareto scaled to approximate normality before all analyses. A GLM was constructed with age, sex, and time as covariates to determine significantly affected metabolites by group intervention. Levene’s test was performed to detect significant homogeneity. The BH procedure was used to correct for multiple testing at ≤0.10. Fecal metabolomic analysis for the subgroup comparison was performed by assessing logFC values between groups with a Wilcoxon rank-sum test with BH adjustment. For pathway analysis, the impact was calculated using a hypergeometric test, while significance was determined using a test of relative betweenness centrality. Importantly, the BH procedure was not applied to pathway and enzyme enrichment analyses for the subgroup assessment since these analyses involve testing the significance of multiple related hypotheses rather than independent hypotheses, which is too conservative, resulting in false negative results.

For MOFA, latent factors explaining ≥2.0% of model variance from the plasma metabolomic and amplicon microbiome data were used to perform Spearman correlations on anthropometric and nutritional data and compared between IF-P and CR groups using Wilcoxon rank-sum tests. The highest beta coefficients (>0.3) detected from GFLASSO models were further assessed by performing Spearman correlations of select microbial features with the response variables (i.e., cytokines and fecal metabolites). All statistical tests were performed with a significance level of p  < 0.05 and BH correction of p .adj < 0.10. In addition, we present data in this study in accordance with the ‘Strengthening The Organization and Reporting of Microbiome Studies’ (STORMS) guidelines for human microbiome research 114 .

Reporting summary

Further information on research design is available in the  Nature Portfolio Reporting Summary linked to this article.

Data availability

The microbiome sequencing data generated in this study have been deposited in the BioProject Database of National Centre for Biotechnology Information database under accession code PRJNA847971 . The metadata data linking the microbiome sequences with the appropriate sample ID and intervention in this study are provided in Supplementary Data  1 . The processed data are available at https://github.com/Alex-E-Mohr/GM-Remodeling-IF-ProteinPacing-vs-CaloricRestriction .  Source data are provided with this paper.

Code availability

The R code used for analysis and figure generation for reproducibility purposes are available at: https://github.com/Alex-E-Mohr/GM-Remodeling-IF-ProteinPacing-vs-CaloricRestriction . 115

Asnicar, F. et al. Microbiome connections with host metabolism and habitual diet from 1,098 deeply phenotyped individuals. Nat. Med. 27 , 321–332 (2021).

Article   CAS   PubMed   PubMed Central   Google Scholar  

Li, M. et al. Gut microbiota-bile acid crosstalk contributes to the rebound weight gain after calorie restriction in mice. Nat. Commun. 13 , 2060 (2022).

Article   ADS   CAS   PubMed   PubMed Central   Google Scholar  

Machado, A. C. D. et al. Diet and feeding pattern modulate diurnal dynamics of the ileal microbiome and transcriptome. Cell Rep. 40 , 111008 (2022).

Article   PubMed Central   Google Scholar  

von Schwartzenberg R.J. et al. Caloric restriction disrupts the microbiota and colonization resistance. Nature 595 , 272–277 (2021).

Maifeld, A. et al. Fasting alters the gut microbiome reducing blood pressure and body weight in metabolic syndrome patients. Nat. Commun. 12 , 1970 (2021).

Corbin, K. D. et al. Host-diet-gut microbiome interactions influence human energy balance: a randomized clinical trial. Nat. Commun. 14 , 3161 (2023).

Arciero, P. J. et al. Increased protein intake and meal frequency reduces abdominal fat during energy balance and energy deficit. Obesity 21 , 1357–1366 (2013).

Article   CAS   PubMed   Google Scholar  

Arciero, P. J. et al. Protein-pacing caloric-restriction enhances body composition similarly in obese men and women during weight loss and sustains efficacy during long-term weight maintenance. Nutrients 8 , 476 (2016).

Article   PubMed   PubMed Central   Google Scholar  

Mohr, A. E. et al. Exploratory analysis of one versus two-day intermittent fasting protocols on the gut microbiome and plasma metabolome in adults with overweight/obesity. Front. Nutr. 9 , 1036080 (2022).

He, F., Zuo, L., Ward, E. & Arciero, P. J. Serum polychlorinated biphenyls increase and oxidative stress decreases with a protein-pacing caloric restriction diet in obese men and women. Int. J. Environ. Res. Public Health 14 , 59 (2017).

Ives, S. J. et al. Multi-modal exercise training and protein-pacing enhances physical performance adaptations independent of growth hormone and BDNF but may be dependent on IGF-1 in exercise-trained men. Growth Horm. IGF Res. 32 , 60–70 (2017).

Zuo, L. et al. Comparison of high-protein, intermittent fasting low-calorie diet and heart healthy diet for vascular health of the obese. Front. Physiol. 7 , 350 (2016).

Article   ADS   PubMed   PubMed Central   Google Scholar  

Zhong, W. et al. High-protein diet prevents fat mass increase after dieting by counteracting Lactobacillus-enhanced lipid absorption. Nat. Metab. 4 , 1713–1731 (2022).

U.S. Department of Agriculture and U.S. Department of Health and Human Services. Dietary Guidelines for Americans, 2020-2025 , 9th edn DietaryGuidelines.gov (2020).

Arciero, P. J. et al. Intermittent fasting and protein pacing are superior to caloric restriction for weight and visceral fat loss. Obesity 31 , 139–149 (2023).

Lichtenstein, A. H. et al. 2021 Dietary guidance to improve cardiovascular health: a scientific statement from the american heart association. Circulation 144 , e472–e487 (2021).

Article   PubMed   Google Scholar  

Falony, G. et al. Population-level analysis of gut microbiome variation. Science 352 , 560–564 (2016).

Article   ADS   CAS   PubMed   Google Scholar  

Mallick, H. et al. Multivariable association discovery in population-scale meta-omics studies. PLos Comput. Biol. 17 , e1009442 (2021).

Lozupone, C. A., Stombaugh, J. I., Gordon, J. I., Jansson, J. K. & Knight, R. Diversity, stability and resilience of the human gut microbiota. Nature 489 , 220–230 (2012).

Waters, J. L. & Ley, R. E. The human gut bacteria Christensenellaceae are widespread, heritable, and associated with health. BMC Biol. 17 , 83 (2019).

Beaumont, M. et al. Quantity and source of dietary protein influence metabolite production by gut microbiota and rectal mucosa gene expression: a randomized, parallel, double-blind trial in overweight humans. Am. J. Clin. Nutr. 106 , 1005–1019 (2017).

Tavella, T. et al. Elevated gut microbiome abundance of Christensenellaceae, Porphyromonadaceae and Rikenellaceae is associated with reduced visceral adipose tissue and healthier metabolic profile in Italian elderly. Gut Microbes 13 , 1880221 (2021).

Bischoff, S. C. et al. Gut microbiota patterns predicting long-term weight loss success in individuals with obesity undergoing nonsurgical therapy. Nutrients 14 , 3182 (2022).

Vieira-Silva, S. et al. Species–function relationships shape ecological properties of the human gut microbiome. Nat. Microbiol. 1 , 16088 (2016).

Cummings, J. H. & Macfarlane, G. T. The control and consequences of bacterial fermentation in the human colon. J. Appl. Bacteriol. 70 , 443–459 (1991).

Tims, S. et al. Microbiota conservation and BMI signatures in adult monozygotic twins. ISME J. 7 , 707–717 (2013).

Atzeni, A. et al. Taxonomic and functional fecal microbiota signatures associated with insulin resistance in non-diabetic subjects with overweight/obesity within the frame of the PREDIMED-plus study. Front. Endocrinol. 13 , 804455 (2022).

Article   Google Scholar  

Oliver, A. et al. High-fiber, whole-food dietary intervention alters the human gut microbiome but not fecal short-chain fatty acids. Msystems 6 , e00115–e00121 (2021).

McOrist, A. L. et al. Fecal butyrate levels vary widely among individuals but are usually increased by a diet high in resistant starch. J. Nutr. 141 , 883–889 (2011).

Bendiks, Z. A., Knudsen, K. E. B., Keenan, M. J. & Marco, M. L. Conserved and variable responses of the gut microbiome to resistant starch type 2. Nutr. Res. 77 , 12–28 (2020).

Boulangé, C. L., Neves, A. L., Chilloux, J., Nicholson, J. K. & Dumas, M.-E. Impact of the gut microbiota on inflammation, obesity, and metabolic disease. Genome Med 8 , 42 (2016).

Shiau, M.-Y. et al. Mechanism of interleukin-4 reducing lipid deposit by regulating hormone-sensitive lipase. Sci. Rep. 9 , 11974 (2019).

Bruun, J. M., Pedersen, S. B., Kristensen, K. & Richelsen, B. Opposite regulation of interleukin‐8 and tumor necrosis factor‐α by weight loss. Obes. Res. 10 , 499–506 (2002).

Steensberg, A. et al. Production of interleukin‐6 in contracting human skeletal muscles can account for the exercise‐induced increase in plasma interleukin‐6. J. Physiol. 529 , 237–242 (2000).

Hall et al. Interleukin-6 stimulates lipolysis and fat oxidation in humans. J. Clin. Endocrinol. Metab. 88 , 3005–3010 (2003).

Wueest, S. et al. Interleukin-6 contributes to early fasting-induced free fatty acid mobilization in mice. Am. J. Physiol. Regul. Integr. Comp. Physiol. 306 , R861–R867 (2014).

Wu, D. et al. Interleukin-13 (IL-13)/IL-13 receptor α1 (IL-13Rα1) signaling regulates intestinal epithelial cystic fibrosis transmembrane conductance regulator channel-dependent Cl− secretion. J. Biol. Chem. 286 , 13357–13369 (2011).

Gamage, H. K. A. H. et al. Intermittent fasting has a diet-specific impact on the gut microbiota and colonic mucin O-glycosylation of mice. Preprint at bioRxiv https://doi.org/10.1101/2022.09.15.508181 (2022).

Song, E.-J., Shin, N. R., Jeon, S., Nam, Y.-D. & Kim, H. Lorcaserin and phentermine exert anti-obesity effects with modulation of the gut microbiota. Front. Microbiol. 13 , 1109651 (2023).

Wang, M. et al. Olive fruit extracts supplement improve antioxidant capacity via altering colonic microbiota composition in mice. Front. Nutr. 8 , 645099 (2021).

Qin, J. et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature 464 , 59–65 (2010).

Mohr, A. E., Crawford, M., Jasbi, P., Fessler, S. & Sweazea, K. L. Lipopolysaccharide and the gut microbiota: considering structural variation. FEBS Lett. 596 , 849–875 (2022).

Teruya, T., Chaleckis, R., Takada, J., Yanagida, M. & Kondoh, H. Diverse metabolic reactions activated during 58-hr fasting are revealed by non-targeted metabolomic analysis of human blood. Sci. Rep. 9 , 854 (2019).

Collet, T.-H. et al. A metabolomic signature of acute caloric restriction. J. Clin. Endocrinol. Metab. 102 , 4486–4495 (2017).

Vázquez-Fresno, R. et al. Metabolomic pattern analysis after mediterranean diet intervention in a nondiabetic population: a 1- and 3-year follow-up in the PREDIMED study. J. Proteome Res. 14 , 531–540 (2015).

Sankaranarayanan, R., Kumar, D. R., Patel, J. & Bhat, G. J. Do aspirin and flavonoids prevent cancer through a common mechanism involving hydroxybenzoic acids?—The metabolite hypothesis. Molecules 25 , 2243 (2020).

Aon, M. A. et al. Untangling determinants of enhanced health and lifespan through a multi-omics approach in mice. Cell Metab. 32 , 100–116.e4 (2020).

Sekhar, R. V. et al. Glutathione synthesis is diminished in patients with uncontrolled diabetes and restored by dietary supplementation with cysteine and glycine. Diabetes Care 34 , 162–167 (2011).

Nguyen, D., Hsu, J. W., Jahoor, F. & Sekhar, R. V. Effect of increasing glutathione with cysteine and glycine supplementation on mitochondrial fuel oxidation, insulin sensitivity, and body composition in older HIV-infected patients. J. Clin. Endocrinol. Metab. 99 , 169–177 (2014).

Chen, L. et al. Glycine transporter-1 and glycine receptor mediate the antioxidant effect of glycine in diabetic rat islets and INS-1 cells. Free Radic. Biol. Med. 123 , 53–61 (2018).

Breum, L., Rasmussen, M. H., Hilsted, J. & Fernstrom, J. D. Twenty-four–hour plasma tryptophan concentrations and ratios are below normal in obese subjects and are not normalized by substantial weight reduction 1, 2, 3. Am. J. Clin. Nutr. 77 , 1112–1118 (2003).

Fernstrom, J. D. et al. Diurnal variations in plasma concentrations of tryptophan, tryosine, and other neutral amino acids: effect of dietary protein intake. Am. J. Clin. Nutr. 32 , 1912–1922 (1979).

Chen, L. et al. Influence of the microbiome, diet and genetics on inter-individual variation in the human plasma metabolome. Nat. Med. 28 , 2333–2343 (2022).

Fan, Y. & Pedersen, O. Gut microbiota in human metabolic health and disease. Nat. Rev. Microbiol. 19 , 55–71 (2021).

Argelaguet, R. et al. Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets. Mol. Syst. Biol. 14 , e8124 (2018).

Anderson, E. M. et al. Temporal dynamics of the intestinal microbiome following short-term dietary restriction. Nutrients 14 , 2785 (2022).

Gerritsen, J. et al. A comparative and functional genomics analysis of the genus Romboutsia provides insight into adaptation to an intestinal lifestyle. Preprint at bioRxiv https://doi.org/10.1101/845511 (2019).

Caldovic, L. et al. N-acetylglutamate synthase: structure, function and defects. Mol. Genet. Metab. 100 , S13–S19 (2010).

Parker, B. J., Wearsch, P. A., Veloo, A. C. M. & Rodriguez-Palacios, A. The genus Alistipes: gut bacteria with emerging implications to inflammation, cancer, and mental health. Front. Immunol. 11 , 906 (2020).

Yang, J. et al. Oscillospira - a candidate for the next-generation probiotics. Gut Microbes 13 , 1987783 (2021).

Jensen, M. D. et al. 2013 AHA/ACC/TOS guideline for the management of overweight and obesity in adults. Circulation 129 , S102–S138 (2014).

Gomez-Arango, L. F. et al. Low dietary fiber intake increases Collinsella abundance in the gut microbiota of overweight and obese pregnant women. Gut Microbes 9 , 189–201 (2018).

Chen, J. et al. An expansion of rare lineage intestinal microbes characterizes rheumatoid arthritis. Genome Med. 8 , 43 (2016).

Astbury, S. et al. Lower gut microbiome diversity and higher abundance of proinflammatory genus Collinsella are associated with biopsy-proven nonalcoholic steatohepatitis. Gut Microbes 11 , 569–580 (2020).

Lim, R. R. X. et al. Gut microbiome responses to dietary intervention with hypocholesterolemic vegetable oils. npj Biofilms Microbiomes 8 , 24 (2022).

Atarashi, K. et al. Treg induction by a rationally selected mixture of Clostridia strains from the human microbiota. Nature 500 , 232–236 (2013).

Louis, P. & Flint, H. J. Diversity, metabolism and microbial ecology of butyrate‐producing bacteria from the human large intestine. FEMS Microbiol. Lett. 294 , 1–8 (2009).

Bui, T. P. N. et al. Mutual metabolic interactions in co-cultures of the intestinal Anaerostipes rhamnosivorans with an acetogen, methanogen, or pectin-degrader affecting butyrate production. Front. Microbiol. 10 , 2449 (2019).

Kaci, G. et al. Anti-inflammatory properties of streptococcus salivarius, a commensal bacterium of the oral cavity and digestive tract. Appl. Environ. Microbiol. 80 , 928–934 (2014).

Couvigny, B. et al. Commensal streptococcus salivarius modulates PPARγ transcriptional activity in human intestinal epithelial cells. PLoS ONE 10 , e0125371 (2015).

Barcenilla, A. et al. Phylogenetic relationships of butyrate-producing bacteria from the human gut. Appl. Environ. Microbiol. 66 , 1654–1661 (2000).

Scott, K. P. et al. Substrate-driven gene expression in Roseburia inulinivorans: importance of inducible enzymes in the utilization of inulin and starch. Proc. Natl Acad. Sci. USA 108 , 4672–4679 (2011).

Hosomi, K. et al. Oral administration of Blautia wexlerae ameliorates obesity and type 2 diabetes via metabolic remodeling of the gut microbiota. Nat. Commun. 13 , 4477 (2022).

Bui, T. P. N. et al. Conversion of dietary inositol into propionate and acetate by commensal Anaerostipes associates with host health. Nat. Commun. 12 , 4798 (2021).

Zeevi, D. et al. Structural variation in the gut microbiome associates with host health. Nature 568 , 43–48 (2019).

Brahe, L. K. et al. Specific gut microbiota features and metabolic markers in postmenopausal women with obesity. Nutr. Diabetes 5 , e159–e159 (2015).

Deaver, J. A., Eum, S. Y. & Toborek, M. Circadian disruption changes gut microbiome taxa and functional gene composition. Front Microbiol 09 , 737 (2018).

Ze, X., Duncan, S. H., Louis, P. & Flint, H. J. Ruminococcus bromii is a keystone species for the degradation of resistant starch in the human colon. ISME J. 6 , 1535–1543 (2012).

Ngai, P. H. K., Zhao, Z. & Ng, T. B. Agrocybin, an antifungal peptide from the edible mushroom Agrocybe cylindracea. Peptides 26 , 191–196 (2005).

Sánchez, M. et al. Modulatory effect of intestinal polyamines and trace amines on the spontaneous phasic contractions of the isolated ileum and colon rings of mice. Food Nutr. Res. 61 , 1321948 (2017).

Lassen, P. B. et al. Protein supplementation during an energy-restricted diet induces visceral fat loss and gut microbiota amino acid metabolism activation: a randomized trial. Sci. Rep. 11 , 15620 (2021).

Mazier, W. et al. A new strain of christensenella minuta as a potential biotherapy for obesity and associated metabolic diseases. Cells 10 , 823 (2021).

Salazar, N. et al. Fecal metabolome and bacterial composition in severe obesity: impact of diet and bariatric surgery. Gut Microbes 14 , 2106102 (2022).

Svedlund, J., Sjödin, I. & Dotevall, G. GSRS—clinical rating scale for gastrointestinal symptoms in patients with irritable bowel syndrome and peptic ulcer disease. Dig. Dis. Sci. 33 , 129–134 (1988).

Kulich, K. R. et al. Reliability and validity of the Gastrointestinal Symptom Rating Scale (GSRS) and Quality of Life in Reflux and Dyspepsia (QOLRAD) questionnaire in dyspepsia: a six-country study. Health Qual. Life Out. 6 , 12 (2008).

Riegler, G. & Esposito, I. Bristol scale stool form. A still valid help in medical practice and clinical research. Tech. Coloproctol. 5 , 163–164 (2001).

Yang, Y.-W. et al. Use of 16S rRNA gene-targeted group-specific primers for real-time PCR analysis of predominant bacteria in mouse feces. Appl. Environ. Microbiol. 81 , 6749–6756 (2015).

Gregoris, T. B. D., Aldred, N., Clare, A. S. & Burgess, J. G. Improvement of phylum- and class-specific primers for real-time PCR quantification of bacterial taxa. J. Microbiol. Methods 86 , 351–356 (2011).

Caporaso, J. G. et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc. Natl Acad. Sci. USA 108 , 4516–4522 (2010).

Caporaso, J. G. et al. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J. 6 , 1621–1624 (2012).

Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 37 , 852–857 (2019).

Bokulich, N. A. et al. Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin. Microbiome 6 , 90 (2018).

Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41 , D590–D596 (2012).

McKnight, D. T. et al. Methods for normalizing microbiome data: an ecological perspective. Methods Ecol. Evol. 10 , 389–400 (2019).

Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9 , 357–359 (2012).

Beghini, F. et al. Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3. Elife 10 , e65088 (2021).

Bapat, A. et al. Hypoxia promotes erythroid differentiation through the development of progenitors and proerythroblasts. Exp. Hematol. 97 , 32–46.e35 (2021).

Jasbi, P. et al. Metabolic profiling of neocortical tissue discriminates Alzheimer’s disease from mild cognitive impairment, high pathology controls, and normal controls. J. Proteome Res. 20 , 4303–4317 (2021).

Jasbi, P. et al. Microbiome and metabolome profiles of high screen time in a cohort of healthy college students. Sci. Rep. 12 , 3452 (2022).

Basile, A. J. et al. A four-week white bread diet does not alter plasma glucose concentrations, metabolic or vascular physiology in mourning doves, Zenaida macroura. Comp. Biochem. Physiol. Part A Mol. Integr. Physiol. 247 , 110718 (2020).

Article   CAS   Google Scholar  

Johnston, C. S. et al. Daily vinegar ingestion improves depression scores and alters the metabolome in healthy adults: a randomized controlled trial. Nutrients 13 , 4020 (2021).

Gu, H., Shi, X., Jasbi, P. & Patterson, J. Viruses as therapeutics, methods and protocols. Methods Mol. Biol. 2225 , 179–197 (2020).

He, H. et al. An integrative cellular metabolomic study reveals downregulated tricarboxylic acid cycle and potential biomarkers induced by tetrabromobisphenol A in human lung A549 cells. Environ. Toxicol. 38 , 7–16 (2023).

Mohr, A. E. et al. Association of food insecurity on gut microbiome and metabolome profiles in a diverse college-based sample. Sci. Rep. 12 , 14358 (2022).

Gu, H., Jasbi, P., Patterson, J. & Jin, Y. Enhanced detection of short‐chain fatty acids using gas chromatography mass spectrometry. Curr. Protoc. 1 , e177 (2021).

Qi, Y. et al. Metabolomics study of resina draconis on myocardial ischemia rats using ultraperformance liquid chromatography/quadrupole time-of-flight mass spectrometry combined with pattern recognition methods and metabolic pathway analysis. Évid. Based Complement. Altern. Med. 2013 , 438680 (2013).

Google Scholar  

Yao, W. et al. Integrated plasma and urine metabolomics coupled with HPLC/QTOF-MS and chemometric analysis on potential biomarkers in liver injury and hepatoprotective effects of Er-Zhi-Wan. Anal. Bioanal. Chem. 406 , 7367–7378 (2014).

Wei, Y. et al. Early breast cancer detection using untargeted and targeted metabolomics. J. Proteome Res. 20 , 3124–3133 (2021).

Haak, B. W. et al. Integrative transkingdom analysis of the gut microbiome in antibiotic perturbation and critical illness. mSystems 6 , e01148–20 (2021).

McMurdie, P. J. & Holmes, S. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLos One 8 , e61217 (2013).

Bokulich, N. A. et al. q2-longitudinal: longitudinal and paired-sample analyses of microbiome data. Msystems 3 , e00219–18 (2018).

Pang, Z. et al. MetaboAnalyst 5.0: narrowing the gap between raw spectra and functional insights. Nucleic Acids Res. 49 , W388–W396 (2021).

Kanehisa, M. & Goto, S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 28 , 27–30 (2000).

Mirzayi, C. et al. Reporting guidelines for human microbiome research: the STORMS checklist. Nat. Med. 27 , 1885–1892 (2021).

Mohr, A. E. et al. Gut microbiome remodeling and metabolomic profile in response to protein pacing with intermittent fasting versus continuous caloric restriction https://doi.org/10.5281/zenodo.10971120 (2024).

Download references

Acknowledgements

We thank the trial volunteers for their dedication and commitment to the study protocol. We are grateful for the research assistants from Skidmore College who provided valuable assistance with study protocol design, scheduling, recruitment, data testing, collection, entry, and statistical analysis, and preparation of manuscripts: Molly Boyce, Jenny Zhang, Melissa Haas, Olivia Furlong, Emma Valdez, Jessica Centore, Annika Smith, Kaitlyn Judd, Aaliyah Yarde, Katy Ehnstrom, Dakembay Hoyte, Sheriden Beard, Heather Mak, and Monique Dudar. We are grateful for the extensive guidance and counseling provided by the registered dietitian Jaime Martin. We thank research coordinator Michelle Poe for her superior dedication to all aspects of the study. This study was primarily funded by an unrestricted grant from Isagenix International LLC to P.J.A. (grant #:1911-859), with secondary funding provided to K.L.S.

Author information

Authors and affiliations.

College of Health Solutions, Arizona State University, Phoenix, AZ, USA

Alex E. Mohr, Karen L. Sweazea, Corrie M. Whisner, Dorothy D. Sears, Haiwei Gu & Judith Klein-Seetharaman

Biodesign Institute Center for Health Through Microbiomes, Arizona State University, Tempe, AZ, USA

Alex E. Mohr, Karen L. Sweazea, Devin A. Bowes, Corrie M. Whisner & Rosa Krajmalnik-Brown

Center for Evolution and Medicine, College of Liberal Arts and Sciences, Arizona State University, Tempe, AZ, USA

Karen L. Sweazea

School of Molecular Sciences, Arizona State University, Tempe, AZ, USA

Paniz Jasbi & Judith Klein-Seetharaman

Systems Precision Engineering and Advanced Research (SPEAR), Theriome Inc., Phoenix, AZ, USA

Paniz Jasbi

Center of Translational Science, Florida International University, Port St. Lucie, FL, USA

Yan Jin & Haiwei Gu

Human Nutrition and Metabolism Laboratory, Department of Health and Human Physiological Sciences, Skidmore College, Saratoga Springs, NY, USA

Karen M. Arciero & Paul J. Arciero

Isagenix International, LLC, Gilbert, AZ, USA

Eric Gumpricht

School of Health and Rehabilitation Sciences, Department of Sports Medicine and Nutrition, University of Pittsburgh, Pittsburgh, PA, USA

Paul J. Arciero

You can also search for this author in PubMed   Google Scholar

Contributions

Study conceived and designed: P.J.A. Manuscript preparation with input from all authors: A.E.M., K.L.S., D.A.B., P.J., C.M.W., D.D.S., R.K.-B., H.G., J.K.-S., K.M.A., E.G., and P.J.A. Randomized study design and execution: K.M.A., and P.J.A. Microbiome analysis: A.E.M., D.A.B., C.M.W., and R.K.-B. Blood analyte analysis: A.E.M., K.L.S., and P.J.A. Metabolomic analysis: A.E.M., Y.J., H.G., and P.J. Statistical analysis and data presentation: A.E.M., C.M.W., D.D.S., R.K.-B., and P.J.A. Supervision and funding: K.L.S., E.G., and P.J.A.

Corresponding author

Correspondence to Paul J. Arciero .

Ethics declarations

Competing interests.

P.J.A. is a consultant for Isagenix International LLC, the study’s sponsor, he is an advisory board member of the International Protein Board (iPB), and he receives financial compensation for books and keynote presentations on protein pacing ( www.paularciero.com ). Eric Gumpricht is employed by Isagenix International, LLC, the funding source for this research. Isagenix International, LLC had no role in the study design, data collection, analysis, or decision to publish. No authors have financial interests regarding the outcomes of this investigation. The other authors declare no competing interests.

Peer review

Peer review information.

Nature Communications thanks Gertrude Ecklu-Mensah, Saar Shoer, and Levi Teigen for their contribution to the peer review of this work. A peer review file is available.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary information, peer review file, description of additional supplementary files, reporting summary, source data, source data, rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

Mohr, A.E., Sweazea, K.L., Bowes, D.A. et al. Gut microbiome remodeling and metabolomic profile improves in response to protein pacing with intermittent fasting versus continuous caloric restriction. Nat Commun 15 , 4155 (2024). https://doi.org/10.1038/s41467-024-48355-5

Download citation

Received : 13 September 2023

Accepted : 26 April 2024

Published : 28 May 2024

DOI : https://doi.org/10.1038/s41467-024-48355-5

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

By submitting a comment you agree to abide by our Terms and Community Guidelines . If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

ORIGINAL RESEARCH article

This article is part of the research topic.

Optimization and Data-driven Approaches for Energy Storage-based Demand Response to Achieve Power System Flexibility

A Hybrid Neural Network Based on KF-SA-Transformer for SOC Prediction of Lithium-ion Battery Energy Storage Systems Provisionally Accepted

• 1 College of Electrical Engineering, Shanghai University of Electric Power, China
• 2 State Grid Xiongan New Area Electric Power Supply Company, China
• 3 Intellectual Property Academy, Shanghai University, China

The final, formatted version of the article will be published soon.

With the widespread application of energy storage stations, BMS has become an important subsystem in modern power systems, leading to an increasing demand for improving the accuracy of SOC prediction in lithium-ion battery energy storage systems. Currently, common methods for predicting battery SOC include the Ampere-hour integration method, open circuit voltage method, and modelbased prediction techniques. However, these methods often have limitations such as single-variable research, complex model construction, and inability to capture real-time changes in SOC. In this paper, a novel prediction method based on the KF-SA-Transformer model is proposed by combining modelbased prediction techniques with data-driven methods. By using temperature, voltage, and current as inputs, the limitations of single-variable studies in the Ampere-hour integration method and open circuit voltage method are overcome. The Transformer model can overcome the complex modeling process in model-based prediction techniques by implementing a non-linear mapping between inputs and SOC. The presence of the Kalman filter can eliminate noise and improve data accuracy. Additionally, a sparse autoencoder mechanism is integrated to optimize the position encoding embedding of input vectors, further improving the prediction process. To verify the effectiveness of the algorithm in predicting battery SOC, an open-source lithium-ion battery dataset was used as a case study in this paper. The results show that the proposed KF-SA-Transformer model has superiority in improving the accuracy and reliability of battery SOC prediction, playing an important role in the stability of the grid and efficient energy allocation.

Keywords: State-of-charge, Transformer Neural Network, Kalman filter, Sparse autoencoder, lithium-ion battery

Received: 27 Apr 2024; Accepted: 31 May 2024.

Copyright: © 2024 Xiong, Shi, Shen, Chen, Lu and Xu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Mx. Cong Xu, Intellectual Property Academy, Shanghai University, Shanghai, China

People also looked at