The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
Moving pictures of the human microbiome
Open accessAbstract
BACKGROUND: Understanding the normal temporal variation in the human microbiome is critical to developing treatments for putative microbiome-related afflictions such as obesity, Crohn’s disease, inflammatory bowel disease and malnutrition. Sequencing and computational technologies, however, have been a limiting factor in performing dense time series analysis of the human microbiome. Here, we present the largest human microbiota time series analysis to date, covering two individuals at four body sites over 396 timepoints. RESULTS: We find that despite stable differences between body sites and individuals, there is pronounced variability in an individual’s microbiota across months, weeks and even days. Additionally, only a small fraction of the total taxa found within a single body site appear to be present across all time points, suggesting that no core temporal microbiome exists at high abundance (although some microbes may be present but drop below the detection threshold). Many more taxa appear to be persistent but non-permanent community members. CONCLUSIONS: DNA sequencing and computational advances described here provide the ability to go beyond infrequent snapshots of our human-associated microbial ecology to high-resolution assessments of temporal variations over protracted periods, within and between body habitats and individuals. This capacity will allow us to define normal variation and pathologic states, and assess responses to therapeutic interventions.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Figures
![Figure 1 Principal coordinates analysis of unweighted UniFrac distances between samples. (a) Costello et al. [6] samples. (b) M3, F4 time series samples. (c) M3, F4 time series, PC1 versus time (days). Panels (a,b) and (c) show two independent principal coordinates analyses. To compare the Costello et al. 454 data (a) with the time series Illumina data (b), these data were generated in a single principal coordinates analysis of UniFrac distances at 500 sequences per sample. Panel (c) does not contain the 454 data, so makes use of the increased sampling depth possible on Illumina (evenly sampled to 5,000 sequences per sample for UniFrac calculations).](/paper-figures/601978f4a5f14dce850c1ad072f786d6/moving-pictures-of-the-human-microbiome-figure-1.jpg)


Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“the fine structure of the healthy microbiota seems to be unique to individuals; intra-individual differences across time are typically much smaller than differences between individuals (Caporaso et al., 2011;Costello et al., 2009).”
From The Microbiota-Gut-Brain Axis (2019) · cites this paper as Caporaso et al., 2011
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Search and clustering orders of magnitude faster than BLAST
Edgar, R. C. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq461 · Cited by 21,098
A human gut microbial gene catalogue established by metagenomic sequencing
MetaHIT Consortium, Qin, J., Li, R., Raes, J., Arumugam, M., Burgdorf, K. S., Manichanh, C., Nielsen, T., Pons, N., Levenez, F., et al. (2010) · Nature · doi:10.1038/nature08821 · Cited by 11,624
Greengenes, a Chimera-Checked 16S rRNA Gene Database and Workbench Compatible with ARB
DeSantis, T. Z., Hugenholtz, P., Larsen, N., Rojas, M., Brodie, E. L., Keller, K., Huber, T., Dalevi, D., Hu, P., & Andersen, G. L. (2006) · Applied and Environmental Microbiology · doi:10.1128/aem.03006-05 · Cited by 10,891
Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample
Caporaso, J. G., Lauber, C. L., Walters, W. A., Berg-Lyons, D., Lozupone, C., Turnbaugh, P. J., Fierer, N., & Knight, R. D. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1000080107 · Cited by 9,944
Self-citationDiversity of the Human Intestinal Microbial Flora
Eckburg, P. B., Bik, E. M., Bernstein, C. N., Purdom, E., Dethlefsen, L., Sargent, M., Gill, S. R., Nelson, K. E., & Relman, D. A. (2005) · Science · doi:10.1126/science.1110591 · Cited by 7,913
A core gut microbiome in obese and lean twins
Turnbaugh, P. J., Hamady, M., Yatsunenko, T., Cantarel, B. L., Duncan, A., Ley, R. E., Sogin, M. L., Jones, W. J., Roe, B. A., Affourtit, J. P., et al. (2009) · Nature · doi:10.1038/nature07540 · Cited by 7,823
Self-citationVaginal microbiome of reproductive-age women
Ravel, J., Gajer, P., Abdo, Z., Schneider, G. M., Koenig, S. S. K., McCulle, S. L., Karlebach, S., Gorle, R., Russell, J., Tacket, C. O., et al. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1002611107 · Cited by 4,254
Self-citationBacterial Community Variation in Human Body Habitats Across Space and Time
Costello, E. K., Lauber, C. L., Hamady, M., Fierer, N., Gordon, J. I., & Knight, R. (2009) · Science · doi:10.1126/science.1177486 · Cited by 3,231
Self-citationThe Effect of Diet on the Human Gut Microbiome: A Metagenomic Analysis in Humanized Gnotobiotic Mice
Turnbaugh, P. J., Ridaura, V. K., Faith, J. J., Rey, F. E., Knight, R., & Gordon, J. I. (2009) · Science Translational Medicine · doi:10.1126/scitranslmed.3000322 · Cited by 3,058 · cited 2×
“…together, our observations paint a picture of a human microbiome that is highly variable over time (Figures 2 and 3; Additional files 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15), but from which stable patterns of similarities and differences among body habitats and individuals emerge (Figure…”
BackgroundSelf-citationDevelopment of the Human Infant Intestinal Microbiota
Palmer, C., Bik, E. M., DiGiulio, D. B., Relman, D. A., & Brown, P. O. (2007) · PLoS Biology · doi:10.1371/journal.pbio.0050177 · Cited by 2,877
Cited by
Sorted by citations
Items 301–400 of 1,000
Environment dominates over host genetics in shaping human gut microbiota
Rothschild, D., Weissbrod, O., Barkan, E., Kurilshikov, A., Korem, T., Zeevi, D., Costea, P. I., Godneva, A., Kalka, I. N., & Bar, N. (2018) · Yearbook of pediatric endocrinology · doi:10.1530/ey.15.14.5 · Cited by 90
Gut microbiome in serious mental illnesses: A systematic review and critical evaluation
Nguyen, T. T., Hathaway, H., Kościółek, T., Knight, R. D., & Jeste, D. V. (2019) · Schizophrenia Research · doi:10.1016/j.schres.2019.08.026 · Cited by 80
Self-citationOptimizing sequencing protocols for leaderboard metagenomics by combining long and short reads
Sanders, J. G., Nurk, S., Salido, R. A., Minich, J. J., Xu, Z. Z., Zhu, Q., Martino, C., Fedarko, M. W., Arthur, T. D., Chen, F., et al. (2019) · Genome biology · doi:10.1186/s13059-019-1834-9 · Cited by 77
Self-citationThe human microbiome and autoimmunity
Proal, A. D., Albert, P. J., & Marshall, T. G. (2013) · Current Opinion in Rheumatology · doi:10.1097/bor.0b013e32835cedbf · Cited by 80
Intestinal parasitic infection alters bacterial gut microbiota in children
Toro-Londoño, M., Bedoya-Urrego, K., García-Montoya, G., Galván-Díaz, A. L., & Álzate, J. F. (2019) · PeerJ · doi:10.7717/peerj.6200 · Cited by 84
Coordinated change at the colony level in fruit bat fur microbiomes through time
Kolodny, O., Weinberg, M., Reshef, L., Harten, L. M., Hefetz, A., Gophna, U., Feldman, M. W., & Yovel, Y. (2018) · Nature Ecology & Evolution · doi:10.1038/s41559-018-0731-z · Cited by 82
Proal, A. D., & Marshall, T. G. (2018) · Frontiers in Pediatrics · doi:10.3389/fped.2018.00373 · Cited by 81
Guidelines for Transparency on Gut Microbiome Studies in Essential and Experimental Hypertension
Marques, F. Z., Jama, H. A., Tsyganov, K., Gill, P. A., Rhys-Jones, D. R., Muralitharan, R. R., Muir, J. G., Holmes, A. J., & Mackay, C. R. (2019) · Hypertension · doi:10.1161/hypertensionaha.119.13079 · Cited by 80
Degradation of chondroitin sulfate by the gut microbiota of Chinese individuals
Shang, Q., Yin, Y., Zhu, L., Li, G., Yu, G., & Wang, X. (2016) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2016.01.055 · Cited by 76
Context and the human microbiome
McDonald, D. T., Birmingham, A., & Knight, R. D. (2015) · Microbiome · doi:10.1186/s40168-015-0117-2 · Cited by 76
Self-citationAlshehri, D., Saadah, O. I., Mosli, M. H., Edris, S., Al-Hindi, R. R., & Bahieldin, A. (2020) · Biomolecules and Biomedicine · doi:10.17305/bjbms.2020.5016 · Cited by 82
Spatial and temporal scales of aquatic bacterial beta diversity
Jones, S. E., Cadkin, T. A., Newton, R. J., & McMahon, K. D. (2012) · Frontiers in Microbiology · doi:10.3389/fmicb.2012.00318 · Cited by 76
Primate microbiomes over time: Longitudinal answers to standing questions in microbiome research
Björk, J. R., Dasari, M. R., Grieneisen, L., & Archie, E. A. (2019) · American Journal of Primatology · doi:10.1002/ajp.22970 · Cited by 76
Inferring human microbial dynamics from temporal metagenomics data: Pitfalls and lessons
Cao, H., Gibson, T. E., Bashan, A., & Liu, Y. (2016) · BioEssays · doi:10.1002/bies.201600188 · Cited by 73
NINJA-OPS: Fast Accurate Marker Gene Alignment Using Concatenated Ribosomes
Al‐Ghalith, G. A., Montassier, E., Ward, H. N., & Knights, D. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004658 · Cited by 74
Self-citationRegime shifts in marine communities: a complex systems perspective on food web dynamics
Yletyinen, J., Bodin, Ö., Weigel, B., Nordström, M. C., Bonsdorff, E., & Blenckner, T. (2016) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2015.2569 · Cited by 71
Prizment, A. E., Staley, C. M., Onyeaghala, G. C., Vivek, S., Thyagarajan, B., Straka, R. J., Demmer, R. T., Knights, D., Meyer, K. A., Shaukat, A., et al. (2020) · Alimentary Pharmacology & Therapeutics · doi:10.1111/apt.16013 · Cited by 76
Self-citationThe human archaeome: methodological pitfalls and knowledge gaps
Mahnert, A., Blohs, M., Pausan, M.-R., & Moissl‐Eichinger, C. (2018) · Emerging Topics in Life Sciences · doi:10.1042/etls20180037 · Cited by 69
Gut microbiome and Clostridioides difficile infection: a closer look at the microscopic interface
Sehgal, K., & Khanna, S. (2021) · Therapeutic Advances in Gastroenterology · doi:10.1177/1756284821994736 · Cited by 74
Implications of the human microbiome in inflammatory bowel diseases
Bakhtiar, S. M., LeBlanc, J. G., Salvucci, E., Ali, A., Martín, R., Langella, P., Chatel, J., Miyoshi, A., Bermúdez‐Humarán, L. G., & Azevedo, V. (2013) · FEMS Microbiology Letters · doi:10.1111/1574-6968.12111 · Cited by 74
Zapka, C. A., Leff, J. W., Henley, J. B., Tittl, J., Nardo, E. D., Butler, M. S., Griggs, R. K., Fierer, N., & Edmonds-Wilson, S. L. (2017) · mBio · doi:10.1128/mbio.00093-17 · Cited by 74
Self-citationMohammadzadeh, R., Mahnert, A., Duller, S., & Moissl‐Eichinger, C. (2022) · Current Opinion in Microbiology · doi:10.1016/j.mib.2022.102146 · Cited by 67
Gut microbiota and associated metabolites: key players in high-fat diet-induced chronic diseases
Du, W., Zou, Z., Ye, B., & Zhou, Y. Q. (2025) · Gut Microbes · doi:10.1080/19490976.2025.2494703 · Cited by 84
ghost-tree: creating hybrid-gene phylogenetic trees for diversity analyses
Fouquier, J., Rideout, J. R., Bolyen, E. K., Chase, J., Shiffer, A., McDonald, D. T., Knight, R. D., Caporaso, J. G., & Kelley, S. T. (2016) · Microbiome · doi:10.1186/s40168-016-0153-6 · Cited by 74
Self-citationCleanliness in context: reconciling hygiene with a modern microbial perspective
Vandegrift, R., Bateman, A. C., Siemens, K. N., Nguyen, M., Wilson, H. E., Green, J. L., Wymelenberg, K. G. V. D., & Hickey, R. J. (2017) · Microbiome · doi:10.1186/s40168-017-0294-2 · Cited by 77
Diagnostic and Prognostic Microbial Biomarkers in Inflammatory Bowel Diseases
Dubinsky, M. C., & Braun, J. G. (2015) · Gastroenterology · doi:10.1053/j.gastro.2015.08.006 · Cited by 71
Antibiotics and mental health: the good, the bad and the ugly
Dinan, K., & Dinan, T. (2022) · Journal of Internal Medicine · doi:10.1111/joim.13543 · Cited by 69
Face to Face: Evaluating Visual Comparison
Ondov, B., Jardine, N. L., Elmqvist, N., & Franconeri, S. (2018) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2018.2864884 · Cited by 69
Comparison of Storage Conditions for Human Vaginal Microbiome Studies
Bai, G., Gajer, P., Nandy, M., Ma, B., Yang, H., Sakamoto, J. M., Blanchard, M. H., Ravel, J., & Brotman, R. M. (2012) · PLoS ONE · doi:10.1371/journal.pone.0036934 · Cited by 70
Self-citationSocial Interaction, Noise and Antibiotic-Mediated Switches in the Intestinal Microbiota
Bucci, V., Bradde, S., Biroli, G., & Xavier, J. B. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002497 · Cited by 63
Publisher Correction: The gut–liver axis and the intersection with the microbiome
Tripathi, A., Debelius, J., Brenner, D. A., Karin, M., Loomba, R., Schnabl, B., & Knight, R. (2018) · Nature Reviews Gastroenterology & Hepatology · doi:10.1038/s41575-018-0031-8 · Cited by 70
Self-citationComparative study on the gut microbiotas of four economically important Asian carp species
Li, X., Yu, Y., Li, C., & Yan, Q. (2018) · Science China Life Sciences · doi:10.1007/s11427-016-9296-5 · Cited by 67
Temporal probabilistic modeling of bacterial compositions derived from 16S rRNA sequencing
Äijö, T., Müller, C. L., & Bonneau, R. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx549 · Cited by 64
Beyond phylotyping: understanding the impact of gut microbiota on host biology
Reigstad, C. S., & Kashyap, P. C. (2013) · Neurogastroenterology & Motility · doi:10.1111/nmo.12134 · Cited by 66
Timescales of gut microbiome dynamics
Schlomann, B. H., & Parthasarathy, R. (2019) · Current Opinion in Microbiology · doi:10.1016/j.mib.2019.09.011 · Cited by 69
Ho, P.-Y., Good, B. H., & Huang, K. C. (2022) · eLife · doi:10.7554/elife.75168 · Cited by 66
Microbial Determinants of Biochemical Individuality and Their Impact on Toxicology and Pharmacology
Patterson, A. D., & Turnbaugh, P. J. (2014) · Cell Metabolism · doi:10.1016/j.cmet.2014.07.002 · Cited by 66
The Dimension of Time in Host-Microbiome Interactions
Uhr, G. T., Dohnalová, L., & Thaiss, C. A. (2019) · mSystems · doi:10.1128/msystems.00216-18 · Cited by 70
Greenblum, S. I., Chiu, H.-C., Levy, R., Carr, R., & Borenstein, E. (2013) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2013.04.001 · Cited by 66
Profile of the skin microbiota in a healthy Chinese population
Zhai, W., Huang, Y., Zhang, X., Fei, W., Chang, Y., Cheng, S., Zhou, Y., Gao, J., Tang, X., Zhang, X., et al. (2018) · The Journal of Dermatology · doi:10.1111/1346-8138.14594 · Cited by 63
Inferring Dynamic Signatures of Microbes in Complex Host Ecosystems
Gerber, G. K., Onderdonk, A. B., & Bry, L. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002624 · Cited by 66
Hang, J., Desai, V., Zavaljevski, N., Yang, Y., Lin, X., Satya, R. V., Martinez, L. J., Blaylock, J. M., Jarman, R. G., Thomas, S. J., et al. (2014) · Microbiome · doi:10.1186/2049-2618-2-31 · Cited by 66
Risely, A., Waite, D. W., Újvári, B., Klaassen, M., & Hoye, B. J. (2017) · Molecular Ecology · doi:10.1111/mec.14326 · Cited by 62
Diversity, Stability, and Reproducibility in Stochastically Assembled Microbial Ecosystems
Goyal, A., & Maslov, S. (2018) · Physical Review Letters · doi:10.1103/physrevlett.120.158102 · Cited by 65
Sato, Y., Yamagishi, J., Yamashita, R., Shinozaki, N. O., Ye, B., Yamada, T., Yamamoto, M. P., Nagasaki, M., & Tsuboi, A. (2015) · PLoS ONE · doi:10.1371/journal.pone.0131607 · Cited by 66
Probiotics: The Scientific Evidence in the Context of Inflammatory Bowel Disease
Celiberto, L. S., Bedani, R., Rossi, E. A., & Cavallini, D. (2015) · Critical Reviews in Food Science and Nutrition · doi:10.1080/10408398.2014.941457 · Cited by 67
Human seroreactivity to gut microbiota antigens
Christmann, B. S., Abrahamsson, T., Bernstein, C. N., Duck, L. W., Mannon, P., Berg, G. E., Björkstén, B., Jenmalm, M. C., & Elson, C. O. (2015) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2015.03.036 · Cited by 62
Nasopharyngeal microbiome diversity changes over time in children with asthma
Pérez-Losada, M., Alamri, L., Crandall, K. A., & Freishtat, R. J. (2017) · PLoS ONE · doi:10.1371/journal.pone.0170543 · Cited by 63
The Eukaryotic Microbiome: Origins and Implications for Fetal and Neonatal Life
Miller, W. B. (2016) · Frontiers in Pediatrics · doi:10.3389/fped.2016.00096 · Cited by 66
Jin, H., Hu, G., Sun, C., Duan, Y., Zhang, Z., Liu, Z., Zhao, X., & Chen, W. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab973 · Cited by 65
Colin, Y., Nicolitch, O., Nostrand, J. D. V., Zhou, J. Z., Turpault, M., & Uroz, S. (2017) · Scientific Reports · doi:10.1038/s41598-017-07639-1 · Cited by 64
Automation of QIIME2 Metagenomic Analysis Platform
Fung, C., Rusling, M., Lampeter, T., Love, C., Karim, A., Bongiorno, C., & Yuan, L. (2021) · Current Protocols · doi:10.1002/cpz1.254 · Cited by 62
Metwally, A. A., Yang, J., Ascoli, C., Dai, Y. D., Finn, P. W., & Perkins, D. L. (2018) · Microbiome · doi:10.1186/s40168-018-0402-y · Cited by 62
Modeling the temporal dynamics of the gut microbial community in adults and infants
Shenhav, L., Furman, O., Briscoe, L., Thompson, M., Silverman, J. D., Mizrahi, I., & Halperin, E. (2019) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006960 · Cited by 64
Paepe, K. D., Verspreet, J., Courtin, C. M., & de Wiele, T. V. (2019) · The ISME Journal · doi:10.1038/s41396-019-0550-5 · Cited by 60
Major Depressive Disorder and gut microbiota – Association not causation. A scoping review
Łoniewski, I., Misera, A., Skonieczna‐Żydecka, K., Kaczmarczyk, M., Kaźmierczak-Siedlecka, K., Misiak, B., Marlicz, W. M., & Samochowiec, J. (2020) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2020.110111 · Cited by 64
Su, X., Xu, J., & Ning, K. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts470 · Cited by 61
Airway Microbiota and the Implications of Dysbiosis in Asthma
Durack, J., Boushey, H. A., & Lynch, S. V. (2016) · Current Allergy and Asthma Reports · doi:10.1007/s11882-016-0631-8 · Cited by 62
Phytobiome metabolism: beneficial soil microbes steer crop plants' secondary metabolism
Korenblum, E., & Aharoni, A. (2019) · Pest Management Science · doi:10.1002/ps.5440 · Cited by 60
Berding, K., Holscher, H. D., Arthur, A. E., & Donovan, S. M. (2018) · The Journal of Nutritional Biochemistry · doi:10.1016/j.jnutbio.2018.01.002 · Cited by 61
Microbiome succession with increasing age in three oral sites
Liu, S., Wang, Y., Zhao, L., Sun, X., & Feng, Q. (2020) · Aging · doi:10.18632/aging.103108 · Cited by 60
Stochastic logistic models reproduce experimental time series of microbial communities
Descheemaeker, L., & de Buyl, S. (2020) · eLife · doi:10.7554/elife.55650 · Cited by 61
Sowah, S. A., Milanese, A., Schübel, R., Wirbel, J., Kartal, E., Johnson, T., Hirche, F., Grafetstätter, M., Nonnenmacher, T., Kirsten, R., et al. (2022) · Genome Medicine · doi:10.1186/s13073-022-01030-0 · Cited by 61
Interplay of dietary antioxidants and gut microbiome in human health: What has been learnt thus far?
Naliyadhara, N., Kumar, A., Gangwar, S. K., Devanarayanan, T. N., Hegde, M., Alqahtani, M. S., Abbas, M. A. E., Sethi, G., & Kunnumakkara, A. B. (2022) · Journal of Functional Foods · doi:10.1016/j.jff.2022.105365 · Cited by 69
Composition and stability of intestinal microbiota of healthy children within a Dutch population
de Meij, T. G. J., Budding, A. E., de Groot, E. F. J., Jansen, F. M., Kneepkens, C. M. F., Benninga, M. A., Penders, J., Bodegraven, A. A. V., & Savelkoul, P. H. M. (2015) · The FASEB Journal · doi:10.1096/fj.15-278622 · Cited by 63
Gut microbiota impact on stroke outcome: Fad or fact?
Winek, K., Meisel, A., & Dirnagl, U. (2016) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x16636890 · Cited by 59
Gut Bacteria and Neuropsychiatric Disorders
Dicks, L. M. T., Hurn, D., & Hermanus, D. (2021) · Microorganisms · doi:10.3390/microorganisms9122583 · Cited by 63
Temporal dynamics of prokaryotic communities in the marine sponge S arcotragus spinosulus
Hardoim, C. C. P., & Costa, R. (2014) · Molecular Ecology · doi:10.1111/mec.12789 · Cited by 59
Resilience in social insect infrastructure systems
Middleton, E., & Latty, T. M. (2016) · Journal of The Royal Society Interface · doi:10.1098/rsif.2015.1022 · Cited by 59
Ho, A., Ijaz, U. Z., Janssens, T., Ruijs, R., Kim, S.-Y., de Boer, W., Termorshuizen, A. J., van der Putten, W. H., & Bodelier, P. L. E. (2017) · GCB Bioenergy · doi:10.1111/gcbb.12457 · Cited by 58
Early settlers: which E. coli strains do you not want at birth?
Secher, T., Brehin, C., & Oswald, E. (2016) · American Journal of Physiology-Gastrointestinal and Liver Physiology · doi:10.1152/ajpgi.00091.2016 · Cited by 58
Metwally, A. A., Yu, P. S., Reiman, D. J., Dai, Y. D., Finn, P. W., & Perkins, D. L. (2019) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006693 · Cited by 61
Fecal microbiota diversity in survivors of adolescent/young adult Hodgkin lymphoma: a study of twins
Cozen, W., Yu, G., Gail, M. H., Ridaura, V. K., Nathwani, B. N., Hwang, A. E., Hamilton, A. S., Mack, T. M., Gordon, J. I., & Goedert, J. J. (2013) · British Journal of Cancer · doi:10.1038/bjc.2013.60 · Cited by 58
Self-citationHealth and Disease Imprinted in the Time Variability of the Human Microbiome
Martí, J. M., Martínez‐Martínez, D., Rubio, T., Gracia, C., Peña, M., Latorre, A., Moyá, A., & Peña-Garay, C. (2017) · mSystems · doi:10.1128/msystems.00144-16 · Cited by 60
A Journey on the Skin Microbiome: Pitfalls and Opportunities
Pistone, D., Meroni, G., Panelli, S., D’Auria, E., Acunzo, M., Pasala, A. R., Zuccotti, G., Bandi, C., & Drago, L. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22189846 · Cited by 61
What is the hologenome concept of evolution?
Morris, J. (2018) · F1000Research · doi:10.12688/f1000research.14385.1 · Cited by 57
The Gut Microbiome in Autism: Study-Site Effects and Longitudinal Analysis of Behavior Change
Fouquier, J., Huizar, N. M., Donnelly, J., Glickman, C. M., Kang, D., Maldonado, J., Jones, R. A., Johnson, K. A., Adams, J. B., Krajmalnik‐Brown, R., et al. (2021) · mSystems · doi:10.1128/msystems.00848-20 · Cited by 59
Time of sample collection is critical for the replicability of microbiome analyses
Allaband, C., Lingaraju, A., Ramos, S. F., Kumar, T., Javaheri, H., Tiu, M. D., Machado, A. C. D., Richter, R. A., Elijah, E. O., Haddad, G. G., et al. (2024) · Nature Metabolism · doi:10.1038/s42255-024-01064-1 · Cited by 61
Self-citationAdvancing analytical algorithms and pipelines for billions of microbial sequences
González, A., & Knight, R. D. (2011) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2011.11.028 · Cited by 56
Self-citationFizzy: feature subset selection for metagenomics
Ditzler, G., Morrison, J. C., Lan, Y., & ROSEN, G. L. (2015) · BMC Bioinformatics · doi:10.1186/s12859-015-0793-8 · Cited by 56
Baksi, K. D., Kuntal, B. K., & Mande, S. S. (2018) · Frontiers in Microbiology · doi:10.3389/fmicb.2018.00036 · Cited by 55
Mackenzie, B. W., Chang, K., Zoing, M., Jain, R., Hoggard, M., Biswas, K., Douglas, R. G., & Taylor, M. W. (2019) · Scientific Reports · doi:10.1038/s41598-019-53975-9 · Cited by 56
Osmotic stress induces gut microbiota community shift in fish
Lai, K. P., Lin, X., Tam, N. Y.-K., Ho, J. C. H., Wong, M. K., Gu, J., Chan, T., & Tse, W. K. F. (2020) · Environmental Microbiology · doi:10.1111/1462-2920.15150 · Cited by 57
Synchrony and idiosyncrasy in the gut microbiome of wild baboons
Björk, J. R., Dasari, M. R., Roche, K., Grieneisen, L., Gould, T. J., Grenier, J., Yotova, V., Gottel, N., Jansen, D., Gesquiere, L. R., et al. (2022) · Nature Ecology & Evolution · doi:10.1038/s41559-022-01773-4 · Cited by 59
Self-citationStructure, functions, and diversity of the healthy human microbiome
Ahrodia, T., Das, S., Bakshi, S., & Das, B. (2022) · Progress in molecular biology and translational science · doi:10.1016/bs.pmbts.2022.07.003 · Cited by 55
Microbiota regulation of inflammatory bowel disease and colorectal cancer
Liu, Z., Cao, A., & Cong, Y. (2013) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2013.09.002 · Cited by 55
phyLoSTM: a novel deep learning model on disease prediction from longitudinal microbiome data
Sharma, D., & Xu, W. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab482 · Cited by 57
Personalized Nutrition Through The Gut Microbiota: Current Insights And Future Perspectives
Vandeputte, D. (2020) · Nutrition Reviews · doi:10.1093/nutrit/nuaa098 · Cited by 63
Mansfield, J. A., Bergin, S. W., Cooper, J. R., & Olsen, C. H. (2014) · Military Medicine · doi:10.7205/milmed-d-13-00546 · Cited by 54
The temporal dynamics of bacterial communities across human anterior nares
Camarinha‐Silva, A., Jáuregui, R., Pieper, D. H., & Wos‐Oxley, M. L. (2011) · Environmental Microbiology Reports · doi:10.1111/j.1758-2229.2011.00313.x · Cited by 56
A distributed cell division counter reveals growth dynamics in the gut microbiota
Myhrvold, C., Kotula, J. W., Hicks, W. M., Conway, N. J., & Silver, P. A. (2015) · Nature Communications · doi:10.1038/ncomms10039 · Cited by 52
Characterization of the gut microbiome in epidemiologic studies: the multiethnic cohort experience
Fu, B. C., Randolph, T. W., Lim, U., Monroe, K. R., Cheng, I. C., Wilkens, L. R., Marchand, L. L., Hullar, M. A. J., & Lampe, J. W. (2016) · Annals of Epidemiology · doi:10.1016/j.annepidem.2016.02.009 · Cited by 58
Dohlman, A. B., & Shen, X. (2019) · Experimental Biology and Medicine · doi:10.1177/1535370219836771 · Cited by 54
Amir, A., Zeisel, A., Zuk, O., Elgart, M., Stern, S., Shamir, O., Turnbaugh, P. J., Soen, Y., & Shental, N. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt1070 · Cited by 53
Keemei: cloud-based validation of tabular bioinformatics file formats in Google Sheets
Rideout, J. R., Chase, J., Bolyen, E. K., Ackermann, G. L., González, A., Knight, R. D., & Caporaso, J. G. (2016) · GigaScience · doi:10.1186/s13742-016-0133-6 · Cited by 53
Self-citationLung Microbiome Is Influenced by the Environment and Asthmatic Status in an Equine Model of Asthma
Fillion-Bertrand, G., Dickson, R. P., Boivin, R., Lavoie, J., Huffnagle, G. B., & Leclère, M. (2018) · American Journal of Respiratory Cell and Molecular Biology · doi:10.1165/rcmb.2017-0228oc · Cited by 54
Colin, Y., Goberna, M., Verdú, M., & Navarro‐Cano, J. A. (2019) · Journal of Environmental Management · doi:10.1016/j.jenvman.2019.04.023 · Cited by 55
Increased mucosal neutrophil survival is associated with altered microbiota in HIV infection
Hensley‐McBain, T., Wu, M. C., Manuzak, J. A., Cheu, R. K., Gustin, A. T., Driscoll, C. B., Zevin, A. S., Miller, C. J., Coronado, E., Smith, E. A., et al. (2019) · PLoS Pathogens · doi:10.1371/journal.ppat.1007672 · Cited by 53
Characterizing the postmortem human bone microbiome from surface-decomposed remains
Emmons, A. L., Mundorff, A. Z., Keenan, S. W., Davoren, J., Andronowski, J. M., Carter, D. O., & DeBruyn, J. M. (2020) · PLoS ONE · doi:10.1371/journal.pone.0218636 · Cited by 56
Fart, F., Rajan, S., Wall, R., Rangel, I., Mall, J. G., Tingö, L., Brummer, R. J., Repsilber, D., Schoultz, I., & Lindqvist, C. M. (2020) · Nutrients · doi:10.3390/nu12092610 · Cited by 55
Metadata
- Authors
- Caporaso, J. G., Lauber, C. L., Costello, E. K., Berg-Lyons, D., Gonzalez, A., Stombaugh, J., Knights, D., Gajer, P., Ravel, J., Fierer, N., Gordon, J. I., & Knight, R.
- Affiliations
- University of Colorado Boulder (US)
- Cooperative Institute for Research in Environmental Sciences (US)
- Stanford Medicine (US)
- University of Maryland, Baltimore (US)
- Washington University in St. Louis (US)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Knight, Rob
- ORCID
- Venue
- Genome Biology
- Published
- 2011-05-30
- Volume
- 12
- Issue
- 5
- Pages
- R50-R50
- ISSN
- 1465-6906 (ISSN-L)
- 1474-760X
- PMC
- PMC3271711
- OpenAlex
- W2126218947
- Cited by
- 1,138
- References
- 21
- Citations by year
- 2026: 25 · 2025: 50 · 2024: 69 · 2023: 80 · 2022: 68 · 2021: 88 · 2020: 102 · 2019: 93 · 2018: 83 · 2017: 84 · 2016: 78 · 2015: 79 · 2014: 78 · 2013: 82 · 2012: 61
- FWCI
- 30.93
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Genome biology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Digital Commons@Becker (Washington University School of Medicine) (submittedVersion)
- Funders
- Howard Hughes Medical Institute
- Bill and Melinda Gates Foundation
- Crohn's and Colitis Foundation of America
- Amazon Web Services
- Crohn's and Colitis Foundation
- National Institutes of Health (5u01ai070921-07, DK078669)
- National Human Genome Research Institute (R01HG004872, HG004872, HG004872-02S1)
- National Institute of Allergy and Infectious Diseases (AI070921, AI083264, UH2AI083264)
- National Institute of Diabetes and Digestive and Kidney Diseases (DK078669, P01DK078669)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Physical Sciences › Environmental Science › Ecology › Microbial Community Ecology and Physiology
- Health Sciences › Dentistry › Periodontics › Oral microbiology and periodontitis research
- Keywords
- human microbiome, temporal variation, core microbiome, microbial community dynamics, body site differences, interindividual variability, microbiome sequencing
- MeSH terms
- Bacteria, Computer Simulation, Humans, Obesity, Organ Specificity, RNA, Ribosomal, 16S, Seasons, Time Factors, Inflammatory Bowel Diseases, Genomics, Gastrointestinal Tract, Metagenome, High-Throughput Nucleotide Sequencing
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review