Ancestral trajectory of infant gut microbiome assembly in non-industrialised populations

Ancestral trajectory of infant gut microbiome assembly in non-industrialised populations | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Biological Sciences - Article Ancestral trajectory of infant gut microbiome assembly in non-industrialised populations Timothy Rozday, Yan Shao, Hilary Browne, Ashray Gunjur, Bastiaan Haak, and 23 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6675732/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Infant gut microbiome assembly influences childhood growth and development. However, current understanding is based almost exclusively on infants from highly industrialised, high-income countries. Here, we present a high-resolution map of gut microbiome assembly in 596 infants from six non-industrialised countries across sub-Saharan Africa and South Asia. Microbiome assembly followed a unified trajectory comprising three distinct stages, characterised by the ordered acquisition and loss of bacterial species and functions. Progression through these stages is governed by breastfeeding and the timing of weaning, revealing an ancestral pattern of microbiome succession conserved across diverse non-industrialised populations. Core microbiome functions are rapidly established by a defined consortium of pioneer species, followed by age-dependent expansions in functional capacity, including pathways implicated in metabolism, immune regulation, and neurodevelopment. Comparison with infant microbiomes from highly industrialised populations reveals that key bacteria underpinning the ancestral assembly trajectory— Bifidobacterium, Lactobacillus and Prevotella —are depleted with industrialisation. Our microbiome assembly map provides a reference for optimising infant microbiome development and supporting child growth through rational design of next-generation infant probiotics, and highlights commensal microbes that should be prioritised for preservation amid global lifestyle transitions. Biological sciences/Microbiology/Microbial communities/Microbiome Biological sciences/Microbiology/Microbial communities/Metagenomics Biological sciences/Microbiology/Microbial genetics/Bacterial genetics Biological sciences/Microbiology/Microbial communities/Clinical microbiology Full Text Additional Declarations Yes there is potential Competing Interest. T.D.L. is the co-founder and CSO of Microbiotica. The other authors declare no competing interests. Ethical approval was obtained from the Oxford University Tropical Research Ethics Committee, and the institutional review boards of all CHAIN Network recruiting and coordinating institutions. Written informed consent was obtained from the parents or caregivers of all participants. Supplementary Files s1speciesdatabasegenomes.xlsx Supplementary table 1: Custom species-level genome database metadata. Metadata of all 1,941 species-representative genomes in the custom database used for metagenome abundance estimation, reporting genome name, GTDB-tk phylogeny, contig metrics, checkM scores and the source (“gtdb”: public from GTDB, “chain”: a MAG generated from metagenomes of this study). s2speciesabundanceprevalence.xlsx Supplementary table 2: Mean abundance and prevalence of each species within 596 non-hospitalised CHAIN study samples. s3specieskingroupmembership.xlsx Supplementary table 3: Kin-group of each species present in 596 non-hospitalised CHAIN study samples. s4samplemetadatatable.xlsx Supplementary table 4: Metadata of 596 non-hospitalised CHAIN study samples. s5cohortmetadatacolumns.xlsx Supplementary table 5: Descriptions and categorisation of sample metadata columns. s6cohortmetadatasummary.xlsx Supplementary table 6: Summary statistics of sample metadata. Continuous data are reported with mean and ±1 standard deviation in parentheses. Categorical data are transoformed into a list of binary (yes/no) variables, each of which are reported with counts and percentages in parentheses. Values also reported for various stratifications based on study site, country and continent. s7distancecorrelation.xlsx Supplemental table 7: Distance correlation between CHAIN sample microbiota variation and metadata categories. “distance_correlation” and “p_value” columns refer to the distance correlation results of just that set of metadata columns. “loo_distance_correlation” and “loo_p_value” columns refer to leave-one-out (LOO) distance correlation results. s8speciesagestage.xlsx Supplementary table 8: Species “stage” and peak age. s9speciesbreastfeedingassociation.xlsx Supplementary table 9: Breastfeeding association of each species. Parameters of partial Pearson correlation between species abundance and breastfeeding. s10microbiotaage.xlsx Supplemental table 10: Microbiota age fit scores. Fit score (R 2 ) of microbiota age model using a variety of different feature sets based on species abundance and UHGP-90 gene orthologue abundance in CHAIN non-hospitalised samples. s11uhgp90dietassociations.xlsx Supplementary table 11: Diet associations with UHGP-90 gene orthologues. Positive, significant (q<0.1) associations between all CAZy-annotated UHGP-90 gene orthologues (GOs) and diet metadata. s12ecdietcounterfactuals.xlsx Supplementary table 12: Enzyme commission aggregated diet associations measured by counterfactuals. Counterfactuals of aggregated positively-and-significantly-associated UHGP-90 gene orthologue (GO) relative abundance with and without diet metadata. s13beneficialfunctionskotable.csv Supplementary table 13: Beneficial functions and their categories and citations. List of beneficial functions defined by KEGG orthologues, along with their names, Enzyme Commission numbers, associated beneficial substances, citations, categories and whether they are detected in CHAIN non-hospitalised samples. s14beneficialfunctionssubstancestable.csv Supplementary table 14: Beneficial substances, pathways and functional modules. List of beneficial substances, pathways and modules with their KEGG codes, categories and citations. s15beneficialfunctionsageassociation.xlsx Supplementary table 15: Age distribution of beneficial function abundance. Mean relative abundance of each beneficial function stratified across 11 age bins spanning the 2–24 month age range. s16beneficialfunctionsspeciescontribution.xlsx Supplementary table 16: Species contribution for each beneficial function. Mean relative abundance of each beneficial function determined to originate from each species. s17speciesindnonind.xlsx Supplementary table 17: Species IND/Non-IND associations. Pearson correlation between species relative abundance and industrialisation (IND/Non-IND) results, with relative abundance in each settings reported and the assigned IND category (IND, Non-IND or Common). Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6675732","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Biological Sciences - Article","associatedPublications":[],"authors":[{"id":462684606,"identity":"5b328f4c-62f5-4b96-b0ff-5f96594dcc84","order_by":0,"name":"Timothy Rozday","email":"","orcid":"https://orcid.org/0000-0001-7016-0665","institution":"Wellcome Sanger Institute","correspondingAuthor":false,"prefix":"","firstName":"Timothy","middleName":"","lastName":"Rozday","suffix":""},{"id":462684607,"identity":"6136a894-409e-44cd-a00f-ec2de8a84c3f","order_by":1,"name":"Yan 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feature sets based on species abundance and UHGP-90 gene orthologue abundance in CHAIN non-hospitalised samples.\u003c/p\u003e","description":"","filename":"s10microbiotaage.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6675732/v1/72f69da7f05f9c5b7c54c683.xlsx"},{"id":83646152,"identity":"32ee1d05-bc31-4dbc-be77-c65c703c0952","added_by":"auto","created_at":"2025-05-30 05:30:08","extension":"xlsx","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":651925,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary table 11: Diet associations with UHGP-90 gene orthologues. \u003c/strong\u003ePositive, significant (q\u0026lt;0.1) associations between all CAZy-annotated UHGP-90 gene orthologues (GOs) and diet metadata.\u003c/p\u003e","description":"","filename":"s11uhgp90dietassociations.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6675732/v1/6499636b4726f5d795c45b8e.xlsx"},{"id":83646149,"identity":"733fa589-f2a5-420c-a183-8f85cfd09c69","added_by":"auto","created_at":"2025-05-30 05:30:08","extension":"xlsx","order_by":12,"title":"","display":"","copyAsset":false,"role":"supplement","size":24531,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary table 12: Enzyme commission aggregated diet associations measured by counterfactuals.\u003c/strong\u003e Counterfactuals of aggregated positively-and-significantly-associated UHGP-90 gene orthologue (GO) relative abundance with and without diet metadata.\u003c/p\u003e","description":"","filename":"s12ecdietcounterfactuals.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6675732/v1/f36364775b121892308cdb65.xlsx"},{"id":83646151,"identity":"da858ea9-f420-4c14-8267-4fdfb952f409","added_by":"auto","created_at":"2025-05-30 05:30:08","extension":"csv","order_by":13,"title":"","display":"","copyAsset":false,"role":"supplement","size":150689,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary table 13: Beneficial functions and their categories and citations.\u003c/strong\u003e List of beneficial functions defined by KEGG orthologues, along with their names, Enzyme Commission numbers, associated beneficial substances, citations, categories and whether they are detected in CHAIN non-hospitalised samples\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"s13beneficialfunctionskotable.csv","url":"https://assets-eu.researchsquare.com/files/rs-6675732/v1/a9615953a82d1d7724f3a4db.csv"},{"id":83646144,"identity":"12e7d21e-f90e-42a2-baee-b9c5d83edbc2","added_by":"auto","created_at":"2025-05-30 05:30:08","extension":"csv","order_by":14,"title":"","display":"","copyAsset":false,"role":"supplement","size":6961,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary table 14: Beneficial substances, pathways and functional modules.\u003c/strong\u003e List of beneficial substances, pathways and modules with their KEGG codes, categories and citations.\u003c/p\u003e","description":"","filename":"s14beneficialfunctionssubstancestable.csv","url":"https://assets-eu.researchsquare.com/files/rs-6675732/v1/bd59f86dbce1f77a56ddf6b6.csv"},{"id":83646150,"identity":"597a99bd-4859-4a69-b02e-5ed534c027ab","added_by":"auto","created_at":"2025-05-30 05:30:08","extension":"xlsx","order_by":15,"title":"","display":"","copyAsset":false,"role":"supplement","size":65588,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary table 15: Age distribution of beneficial function abundance.\u003c/strong\u003e Mean relative abundance of each beneficial function stratified across 11 age bins spanning the 2–24 month age range.\u003c/p\u003e","description":"","filename":"s15beneficialfunctionsageassociation.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6675732/v1/dfad1eb145081f53353aa7d3.xlsx"},{"id":83646153,"identity":"7d0467d4-cdc4-4bc2-8aff-89c3e3acc50a","added_by":"auto","created_at":"2025-05-30 05:30:08","extension":"xlsx","order_by":16,"title":"","display":"","copyAsset":false,"role":"supplement","size":1193442,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary table 16: Species contribution for each beneficial function. \u003c/strong\u003eMean relative abundance of each beneficial function determined to originate from each species.\u003c/p\u003e","description":"","filename":"s16beneficialfunctionsspeciescontribution.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6675732/v1/547655d9c45f990bedd95809.xlsx"},{"id":83646148,"identity":"b40e4672-95a8-45a1-a391-95eb807f51b2","added_by":"auto","created_at":"2025-05-30 05:30:08","extension":"xlsx","order_by":17,"title":"","display":"","copyAsset":false,"role":"supplement","size":27487,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary table 17: Species IND/Non-IND associations.\u003c/strong\u003e Pearson correlation between species relative abundance and industrialisation (IND/Non-IND) results, with relative abundance in each settings reported and the assigned IND category (IND, Non-IND or Common).\u003c/p\u003e","description":"","filename":"s17speciesindnonind.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6675732/v1/0c759e201d110fef7fd648f5.xlsx"}],"financialInterests":"\u003cp\u003e\u003cstrong\u003eYes\u003c/strong\u003e there is potential Competing Interest. T.D.L. is the co-founder and CSO of Microbiotica. The other authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003eEthical approval was obtained from the Oxford University Tropical Research Ethics Committee, and the institutional review boards of all CHAIN Network recruiting and coordinating institutions. Written informed consent was obtained from the parents or caregivers of all participants.\u003c/p\u003e","formattedTitle":"Ancestral trajectory of infant gut microbiome assembly in non-industrialised populations","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6675732/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6675732/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eInfant gut microbiome assembly influences childhood growth and development. However, current understanding is based almost exclusively on infants from highly industrialised, high-income countries. Here, we present a high-resolution map of gut microbiome assembly in 596 infants from six non-industrialised countries across sub-Saharan Africa and South Asia. Microbiome assembly followed a unified trajectory comprising three distinct stages, characterised by the ordered acquisition and loss of bacterial species and functions. Progression through these stages is governed by breastfeeding and the timing of weaning, revealing an ancestral pattern of microbiome succession conserved across diverse non-industrialised populations. Core microbiome functions are rapidly established by a defined consortium of pioneer species, followed by age-dependent expansions in functional capacity, including pathways implicated in metabolism, immune regulation, and neurodevelopment. Comparison with infant microbiomes from highly industrialised populations reveals that key bacteria underpinning the ancestral assembly trajectory—\u003cem\u003eBifidobacterium, Lactobacillus \u003c/em\u003eand \u003cem\u003ePrevotella\u003c/em\u003e—are depleted with industrialisation. Our microbiome assembly map provides a reference for optimising infant microbiome development and supporting child growth through rational design of next-generation infant probiotics, and highlights commensal microbes that should be prioritised for preservation amid global lifestyle transitions.\u003c/p\u003e","manuscriptTitle":"Ancestral trajectory of infant gut microbiome assembly in non-industrialised populations","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-30 05:30:03","doi":"10.21203/rs.3.rs-6675732/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f160f0e3-47ec-4e1f-9411-e102c40425a2","owner":[],"postedDate":"May 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":49129454,"name":"Biological sciences/Microbiology/Microbial communities/Microbiome"},{"id":49129455,"name":"Biological sciences/Microbiology/Microbial communities/Metagenomics"},{"id":49129456,"name":"Biological sciences/Microbiology/Microbial genetics/Bacterial genetics"},{"id":49129457,"name":"Biological sciences/Microbiology/Microbial communities/Clinical microbiology"}],"tags":[],"updatedAt":"2025-08-22T10:37:51+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-30 05:30:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6675732","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6675732","identity":"rs-6675732","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}