The DOI matches its Crossref record; 70 of the 70 references it cites were found in a registry or an index.
Strains, functions and dynamics in the expanded Human Microbiome Project
Open accessAbstract
The characterization of baseline microbial and functional diversity in the human microbiome has enabled studies of microbiome-related disease, diversity, biogeography, and molecular function. The National Institutes of Health Human Microbiome Project has provided one of the broadest such characterizations so far. Here we introduce a second wave of data from the study, comprising 1,631 new metagenomes (2,355 total) targeting diverse body sites with multiple time points in 265 individuals. We applied updated profiling and assembly methods to provide new characterizations of microbiome personalization. Strain identification revealed subspecies clades specific to body sites; it also quantified species with phylogenetic diversity under-represented in isolate genomes. Body-wide functional profiling classified pathways into universal, human-enriched, and body site-enriched subsets. Finally, temporal analysis decomposed microbial variation into rapidly variable, moderately variable, and stable subsets. This study furthers our knowledge of baseline human microbial diversity and enables an understanding of personalized microbiome function and dynamics.
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
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 source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Comparative genomic analyses usually test for correlations between traits.”
From A phylogenetic approach to comparative genomics (2025) · cites this paper as [77]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“While our inherited genome is essentially stable for the lifetime of the host, the microbiome is immensely diverse (Mosca et al., 2016;Pasolli et al., 2019), dynamic (Lloyd-Price et al., 2017), and responsive to external input, enhancing its potential as a target for therapeutic intervention”
From The Microbiota-Gut-Brain Axis (2019) · cites this paper as Lloyd-Price et al., 2017
In the citing paper
“Despite the low number of samples, these results suggest that the environment has more influence on the gut microbiome than the pathological condition, which is in accordance with recent findings 22,23 .”
From Healthspan and lifespan extension by fecal microbiota transplantation into progeroid mice (2019) · cites this paper as [23]
In the citing paper
“Most of the bacterial communities found in the tumoral milieu are present commonly in the gut microbiome (Human Microbiome Project, 2012b; Lloyd-Price et al., 2017)”
From Tumor Microbiome Diversity and Composition Influence Pancreatic Cancer Outcomes (2019) · cites this paper as Lloyd-Price et al., 2017
In the citing paper
“Studies of both a baseline adult population21–23 and ‘demonstration’ populations with specific disease states established typical ranges (for some populations) of microbial membership and enzymatic repertoires across the body, combinations of metabolic functions that were either prevalent or strain-specific, and some of the host factors (such as race or ethnicity) that determine this variation.”
From The Integrative Human Microbiome Project (2019) · cites this paper as [23]
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
Fast gapped-read alignment with Bowtie 2
Langmead, B., & Salzberg, S. L. (2012) · Nature Methods · doi:10.1038/nmeth.1923 · Cited by 56,400
QIIME allows analysis of high-throughput community sequencing data
Caporaso, J. G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F. D., Costello, E. K., Fierer, N., Peña, A. G., Goodrich, J. K., Gordon, J. I., et al. (2010) · Nature Methods · doi:10.1038/nmeth.f.303 · Cited by 34,887
Self-citationKimura, M. (1980) · Journal of Molecular Evolution · doi:10.1007/bf01731581 · Cited by 29,778
SPAdes: A New Genome Assembly Algorithm and Its Applications to Single-Cell Sequencing
Bankevich, A., Nurk, S., Antipov, D., Gurevich, A. A., Dvorkin, M. V., Kulikov, A. S., Lesin, V. M., Nikolenko, S., Pham, S., Prjibelski, A. D., et al. (2012) · Journal of Computational Biology · doi:10.1089/cmb.2012.0021 · Cited by 26,312
Search and clustering orders of magnitude faster than BLAST
Edgar, R. C. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq461 · Cited by 21,098
Inference from iterative simulation using multiple sequences
Gelman, A., & Rubin, D. B. (1992) · Statistical Science · doi:10.1214/ss/1177011136 · Cited by 16,627
Structure, function and diversity of the healthy human microbiome
The Human Microbiome Project Consortium (2012) · Nature · doi:10.1038/nature11234 · Cited by 11,726
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
Velvet: Algorithms for de novo short read assembly using de Bruijn graphsPreprint
Zerbino, D. R., & Birney, E. (2008) · Genome Research · doi:10.1101/gr.074492.107 · Cited by 9,587
Construction of Escherichia coli K‐12 in‐frame, single‐gene knockout mutants: the Keio collection
Baba, T., Ara, T., Hasegawa, M., Takai, Y., Okumura, Y., Baba, M., Datsenko, K. A., Tomita, M., Wanner, B. L., & Mori, H. (2006) · Molecular Systems Biology · doi:10.1038/msb4100050 · Cited by 7,858
Flagged first, then by citations
Cited by
Sorted by citations
Items 201–300 of 1,000
Microbiome diurnal rhythmicity and its impact on host physiology and disease risk
Nobs, S. P., Tuganbaev, T., & Elinav, E. (2019) · EMBO Reports · doi:10.15252/embr.201847129 · Cited by 91
Metaproteomics: A strategy to study the taxonomy and functionality of the gut microbiota
Wang, Y., Zhou, Y., Xiao, X., Zheng, J., & Zhou, H. (2020) · Journal of Proteomics · doi:10.1016/j.jprot.2020.103737 · Cited by 97
A framework for microbiome science in public health
Wilkinson, J. E., Franzosa, E. A., Everett, C., Li, C., trainees, H. R. A., Bae, S., Berzansky, I., Bhosle, A., Bjørnevik, K., Brennan, C. A., et al. (2021) · Nature Medicine · doi:10.1038/s41591-021-01258-0 · Cited by 92
Self-citationDiverse events have transferred genes for edible seaweed digestion from marine to human gut bacteria
Pudlo, N. A., Pereira, G. V., Parnami, J., Cid, M., Markert, S., Tingley, J. P., Unfried, F., Ali, A. Y., Varghese, N. J., Kim, K. S., et al. (2020) · Cell Host & Microbe · doi:10.1016/j.chom.2022.02.001 · Cited by 92
Lung Microbiome in Asthma: Current Perspectives
Loverdos, K., Bellos, G., Kokolatou, L., Vasileiadis, I., Giamarellos‐Bourboulis, E. J., Pecchiari, M., Koulouris, N. G., Koutsoukou, A., & Rovina, N. (2019) · Journal of Clinical Medicine · doi:10.3390/jcm8111967 · Cited by 91
Assessment of fecal DNA extraction protocols for metagenomic studies
Yang, F., Sun, J., Luo, H., Ren, H., Zhou, H., Lin, Y., Han, M., Chen, B., Liao, H., Brix, S., et al. (2020) · GigaScience · doi:10.1093/gigascience/giaa071 · Cited by 88
The impact of fixed orthodontic appliances on oral microbiome dynamics in Japanese patients
Kado, I., Hisatsune, J., Tsuruda, K., Tanimoto, K., & Sugai, M. (2020) · Scientific Reports · doi:10.1038/s41598-020-78971-2 · Cited by 87
Kumar, B., Lorusso, E., Fosso, B., & Pesole, G. (2024) · Frontiers in Microbiology · doi:10.3389/fmicb.2024.1343572 · Cited by 93
Shi, W., Qi, H., Sun, Q., Fan, G., Liu, S., Wang, J., Zhu, B., Liu, H., Zhao, F., Wang, X., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky1008 · Cited by 86
Tilocca, B., Pieroni, L., Soggiù, A., Britti, D., Bonizzi, L., Roncada, P., & Greco, V. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21114045 · Cited by 86
Lindstad, L. J., Lo, G., Leivers, S., Lu, Z., Michalak, L., Pereira, G. V., Røhr, Å. K., Martens, E. C., McKee, L. S., Louis, P., et al. (2021) · mBio · doi:10.1128/mbio.03628-20 · Cited by 95
The Skin Microbiome: Current Techniques, Challenges, and Future Directions
Santiago-Rodríguez, T. M., François, B. L., Macklaim, J. M., Doukhanine, E., & Hollister, E. B. (2023) · Microorganisms · doi:10.3390/microorganisms11051222 · Cited by 90
Pfeilmeier, S., Werz, A., Ote, M., Bortfeld‐Miller, M., Kirner, P., Keppler, A., Hemmerle, L., Gäbelein, C. G., Petti, G. C., Wolf, S., et al. (2024) · Nature Microbiology · doi:10.1038/s41564-023-01555-z · Cited by 90
Johnstone, N., Milesi, C., Burn, O., van den Bogert, B., Nauta, A., Hart, K. H., Sowden, P. T., Burnet, P. W. J., & Kadosh, K. C. (2021) · Scientific Reports · doi:10.1038/s41598-021-87865-w · Cited by 88
Lung microbiome alterations in NSCLC patients
Zheng, L., Sun, R., Zhu, Y., Li, Z., She, X., Jian, X., Yu, F., Deng, X., Sai, B., Wang, L., et al. (2021) · Scientific Reports · doi:10.1038/s41598-021-91195-2 · Cited by 84
The Interplay between Androgen and Gut Microbiota: Is There a Microbiota-Gut-Testis Axis
Li, X., Cheng, W., Shang, H., Wei, H., & Deng, C. (2021) · Reproductive Sciences · doi:10.1007/s43032-021-00624-0 · Cited by 86
The human microbiome encodes resistance to the antidiabetic drug acarbose
Balaich, J. N., Estrella, M. A., Wu, G. G., Jeffrey, P. D., Biswas, A. G., Zhao, L., Korennykh, A. V., & Donia, M. S. (2021) · Nature · doi:10.1038/s41586-021-04091-0 · Cited by 85
Lipopolysaccharide lipid A: A promising molecule for new immunity-based therapies and antibiotics
García-Vello, P., Lorenzo, F. D., Zucchetta, D., Zamyatina, A., Castro, C. D., & Molinaro, A. (2021) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2021.107970 · Cited by 86
Ji, B. W., Sheth, R. U., Dixit, P. D., Huang, Y., Kaufman, A., Wang, H. H., & Vitkup, D. (2019) · Nature Methods · doi:10.1038/s41592-019-0467-y · Cited by 84
Detection and Inhibition of Bacteria on a Dual‐Functional Silver Platform
Vedarethinam, V., Huang, L., Xu, W. L., Zhang, R., Gurav, D. D., Sun, X., Yang, J., Chen, R., & Qian, K. (2018) · Small · doi:10.1002/smll.201803051 · Cited by 82
A great-ape view of the gut microbiome
Nishida, A. H., & Ochman, H. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-018-0085-z · Cited by 84
Antibiotics-induced monodominance of a novel gut bacterial order
Hildebrand, F., Moitinho‐Silva, L., Blasche, S., Jahn, M. T., Gossmann, T. I., Huerta‐Cepas, J., Hercog, R., Lütge, M., Bahram, M., Pryszlak, A., et al. (2019) · Gut · doi:10.1136/gutjnl-2018-317715 · Cited by 93
Mechanistic insights into consumption of the food additive xanthan gum by the human gut microbiota
Ostrowski, M. P., Rosa, S. L. L., Kunath, B. J., Robertson, A., Pereira, G. V., Hagen, L. H., Varghese, N. J., Qiu, L., Yao, T., Flint, G., et al. (2022) · Nature Microbiology · doi:10.1038/s41564-022-01093-0 · Cited by 85
Saeed, H., Díaz, L. A., Gil‐Gómez, A., Burton, J. P., Bajaj, J. S., Romero‐Gómez, M., Arrese, M. A., Arab, J. P., & Khan, M. Q. (2024) · Clinical and Molecular Hepatology · doi:10.3350/cmh.2024.0811 · Cited by 84
Microbiome, Parkinson’s Disease and Molecular Mimicry
Miraglia, F., & Colla, E. (2019) · Cells · doi:10.3390/cells8030222 · Cited by 84
Nogacka, A. M., Gómez‐Martín, M., Suárez, A., González‐Bernardo, Ó., Reyes‐Gavilán, C. G. D. L., & González, S. (2019) · International Journal of Molecular Sciences · doi:10.3390/ijms20082051 · Cited by 85
Macroecological dynamics of gut microbiota
Ji, B. W., Sheth, R. U., Dixit, P. D., Tchourine, K., & Vitkup, D. (2020) · Nature Microbiology · doi:10.1038/s41564-020-0685-1 · Cited by 83
Mesnage, R., & Antoniou, M. N. (2020) · Current Research in Toxicology · doi:10.1016/j.crtox.2020.04.001 · Cited by 81
Towards Unraveling Macroecological Patterns in Rhizosphere Microbiomes
Brunel, C., Pouteau, R., Dawson, W., Pester, M., Ramirez, K. S., & van Kleunen, M. (2020) · Trends in Plant Science · doi:10.1016/j.tplants.2020.04.015 · Cited by 84
Utter, D. R., Borisy, G. G., Eren, A. M., Cavanaugh, C. M., & Welch, J. L. M. (2020) · Genome biology · doi:10.1186/s13059-020-02200-2 · Cited by 82
The role of the microbiota in the management of intensive care patients
Szychowiak, P., Villageois-Tran, K., Patrier, J., Timsit, J., & Ruppé, É. (2022) · Annals of Intensive Care · doi:10.1186/s13613-021-00976-5 · Cited by 86
Wiles, T. J., Wall, E. S., Schlomann, B. H., Hay, E. A., Parthasarathy, R., & Guillemin, K. J. (2018) · mBio · doi:10.1128/mbio.01877-18 · Cited by 80
Chen, Y.-H., Xue, F., Yu, S.-F., Li, X.-S., Liu, L., Jia, Y., Yan, W., Tan, Q.-R., Wang, H., & Peng, Z. (2020) · Journal of Affective Disorders · doi:10.1016/j.jad.2020.12.143 · Cited by 83
Dynamic linear models guide design and analysis of microbiota studies within artificial human guts
Silverman, J. D., Durand, H. K., Bloom, R. J., Mukherjee, S., & David, L. A. (2018) · Microbiome · doi:10.1186/s40168-018-0584-3 · 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
Bacterially mediated drug delivery and therapeutics: Strategies and advancements
Wu, L., Bao, F., Li, L., Yin, X., & Hua, Z. (2022) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2022.114363 · Cited by 80
The Core Human Microbiome: Does It Exist and How Can We Find It? A Critical Review of the Concept
Sharon, I., Quijada, N. M., Pasolli, E., Fabbrini, M., Vitali, F., Agamennone, V., Dötsch, A., Selberherr, E., Grau, J. H., Meixner, M., et al. (2022) · Nutrients · doi:10.3390/nu14142872 · Cited by 83
Sharing of Antimicrobial Resistance Genes between Humans and Food Animals
Cao, H., Bougouffa, S., Park, T.-J., Lau, A., Tong, M.-K., Chow, K., & Ho, P. (2022) · mSystems · doi:10.1128/msystems.00775-22 · Cited by 79
Fu, X., Ou, Z., Zhang, M., Meng, Y., Li, Y., Wen, J., Hu, Q., Zhang, X., Norbäck, D., Deng, Y., et al. (2021) · Microbiome · doi:10.1186/s40168-021-01091-0 · Cited by 79
Engineered bacterial extracellular vesicles for osteoporosis therapy
Liu, H., Li, M., Zhang, T., Liu, X., Zhang, H., Geng, Z., & Su, J. (2022) · Chemical Engineering Journal · doi:10.1016/j.cej.2022.138309 · Cited by 78
Proal, A. D., & Marshall, T. G. (2018) · Frontiers in Pediatrics · doi:10.3389/fped.2018.00373 · Cited by 81
Testing association between soil bacterial diversity and soil carbon storage on the Loess Plateau
Yang, Y., Dou, Y., & An, S. (2018) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2018.01.081 · Cited by 77
Jeong, H., Arif, B., Caetano‐Anollés, G., Kim, K. M., & Nasir, A. (2019) · Scientific Reports · doi:10.1038/s41598-019-42227-5 · Cited by 79
Microbiome as an immune regulator in health, disease, and therapeutics
Juarez, V. M., Montalbine, A. N., & Singh, A. K. (2022) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2022.114400 · Cited by 77
Ojala, T., Häkkinen, A.-E., Kankuri, E. M., & Kankainen, M. (2023) · Trends in Genetics · doi:10.1016/j.tig.2023.05.004 · Cited by 81
Profiling microbial strains in urban environments using metagenomic sequencing data
Zolfo, M., Asnicar, F., Manghi, P., Pasolli, E., Tett, A., & Segata, N. (2018) · Biology Direct · doi:10.1186/s13062-018-0211-z · Cited by 76
Helicobacter pylori Infection, the Gastric Microbiome and Gastric Cancer
Pereira‐Marques, J., Ferreira, R. M., Pinto-Ribeiro, I., & Figueiredo, C. (2019) · Advances in experimental medicine and biology · doi:10.1007/5584_2019_366 · Cited by 77
Casaburi, G., Duar, R. M., Brown, H. K., Mitchell, R. D., Kazi, S., Chew, S., Cagney, O., Flannery, R. L., Sylvester, K. G., Frese, S. A., et al. (2021) · Scientific Reports · doi:10.1038/s41598-020-80583-9 · Cited by 76
Ecology and molecular targets of hypermutation in the global microbiome
Roux, S., Paul, B. G., Bagby, S. C., Nayfach, S., Allen, M. A., Attwood, G. T., Cavicchioli, R., Chistoserdova, L., Gruninger, R. J., Hallam, S., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-23402-7 · Cited by 79
Over 50,000 Metagenomically Assembled Draft Genomes for the Human Oral Microbiome Reveal New Taxa
Zhu, J., Tian, L., Chen, P., Han, M., Song, L., Tong, X., Sun, X., Yang, F., Lin, Z., Liu, X., et al. (2021) · Genomics Proteomics & Bioinformatics · doi:10.1016/j.gpb.2021.05.001 · Cited by 76
Microbiome: Effects of Ageing and Diet
Salazar, N., González, S., Nogacka, A. M., Ríos-Covián, D., Arboleya, S., Gueimonde, M., & Reyes‐Gavilán, C. G. D. L. (2019) · Current Issues in Molecular Biology · doi:10.21775/cimb.036.033 · Cited by 75
Laforest‐Lapointe, I., Becker, A. B., Mandhane, P. J., Turvey, S. E., Moraes, T. J., Sears, M. R., Subbarao, P., Sycuro, L. K., Azad, M. B., & Arrieta, M. (2020) · Gut Microbes · doi:10.1080/19490976.2020.1857513 · Cited by 77
Bacterial Peptidoglycan Fragments Differentially Regulate Innate Immune Signaling
Bersch, K. L., DeMeester, K. E., Zagani, R., Chen, S., Wodzanowski, K. A., Liu, S., Mashayekh, S., Reinecker, H., & Grimes, C. L. (2021) · ACS Central Science · doi:10.1021/acscentsci.1c00200 · Cited by 78
The Kynurenine Pathway and Indole Pathway in Tryptophan Metabolism Influence Tumor Progression
Lu, Z., Zhang, C., Zhang, J., Su, W., Wang, G., & Wang, Z. (2025) · Cancer Medicine · doi:10.1002/cam4.70703 · Cited by 81
A statistical model for describing and simulating microbial community profiles
Ma, S., Ren, B., Mallick, H., Moon, Y. S., Schwager, E., Maharjan, S., Tickle, T. L., Lu, Y., Carmody, R. N., Franzosa, E. A., et al. (2021) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1008913 · Cited by 74
Self-citationPodlesny, D., Arze, C., Dörner, E., Verma, S., Dutta, S., Walter, J., & Fricke, W. F. (2022) · Microbiome · doi:10.1186/s40168-022-01251-w · Cited by 73
McNally, C. P., Eng, A., Noecker, C. A., Gagne‐Maynard, W., & Borenstein, E. (2018) · Frontiers in Microbiology · doi:10.3389/fmicb.2018.00365 · Cited by 74
Cao, Y., Sun, W. C., Wang, J., Sheng, G., Xiang, G., Zhang, T., Shi, W., Li, C., Wang, Y., Zhao, F., et al. (2019) · Cell Discovery · doi:10.1038/s41421-019-0105-y · Cited by 73
Emerging Frontiers in Microbiome Engineering
Inda, M. E., Broset, E., Lu, T. K., & de la Fuente‐Núñez, C. (2019) · Trends in Immunology · doi:10.1016/j.it.2019.08.007 · Cited by 74
Chromatin dynamics and histone modifications in intestinal microbiota-host crosstalk
Fellows, R., & Varga‐Weisz, P. (2019) · Molecular Metabolism · doi:10.1016/j.molmet.2019.12.005 · Cited by 77
Acquisition of oral microbiota is driven by environment, not host genetics
Mukherjee, C., Moyer, C. O., Steinkamp, H. M., Hashmi, S. B., Beall, C. J., Guo, X., Ni, A., Leys, E. J., & Griffen, A. L. (2021) · Microbiome · doi:10.1186/s40168-020-00986-8 · Cited by 77
Statistical approaches for differential expression analysis in metatranscriptomics
Zhang, Y., Thompson, K. N., Huttenhower, C., & Franzosa, E. A. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab327 · Cited by 72
Self-citationStahl-Rommel, S., Jain, M., Nguyen, H. N., Arnold, R. R., Auñón-Chancellor, S. M., Sharp, G. M., Castro, C. L., John, K. K., Juul, S., Turner, D., et al. (2021) · Genes · doi:10.3390/genes12010106 · Cited by 71
Cao, L., Gurevich, A. A., Alexander, K. L., Naman, C. B., Leão, T., Glukhov, E., Luzzatto‐Knaan, T., Vargas, F., Quinn, R., Bouslimani, A., et al. (2019) · Cell Systems · doi:10.1016/j.cels.2019.09.004 · Cited by 73
Self-citationBeyond PD-L1 Markers for Lung Cancer Immunotherapy
Wojas‐Krawczyk, K., Kalinka‐Warzocha, E., Grenda, A., Krawczyk, P. A., & Milanowski, J. (2019) · International Journal of Molecular Sciences · doi:10.3390/ijms20081915 · Cited by 71
Szafrański, S. P., Slots, J., & Stiesch, M. (2021) · Periodontology 2000 · doi:10.1111/prd.12363 · Cited by 71
Oral, Tongue-Coating Microbiota, and Metabolic Disorders: A Novel Area of Interactive Research
Li, Y., Cui, J., Liu, Y., Chen, K., Huang, L., & Liu, Y. (2021) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2021.730203 · Cited by 74
King, A. M., Zhang, Z., Glassey, E., Siuti, P., Clardy, J., & Voigt, C. A. (2023) · Nature Microbiology · doi:10.1038/s41564-023-01524-6 · Cited by 69
Kong, L., Lloyd-Price, J., Vatanen, T., Seksik, P., Beaugerie, L., Simon, T., Vlamakis, H., Sokol, H., & Xavier, R. J. (2020) · Gastroenterology · doi:10.1053/j.gastro.2020.08.045 · Cited by 69
Self-citationKunath, B. J., Hickl, O., Queirós, P., Martin‐Gallausiaux, C., Lebrun, L., Halder, R., Laczny, C. C., Schmidt, T., Hayward, M. R., Becher, D., et al. (2022) · Microbiome · doi:10.1186/s40168-022-01435-4 · Cited by 70
Assal, K. A., Prifti, E., Belda, E., Sala, P., Clément, K., Dao, M. C., Dore, J. M., Levenez, F., Taddei, C. R., Fonseca, D. C., et al. (2020) · Nutrients · doi:10.3390/nu12020278 · Cited by 72
Strain diversity in the microbiome: Lessons from Bacteroides fragilis
Carrow, H. C., Batachari, L. E., & Chu, H. (2020) · PLoS Pathogens · doi:10.1371/journal.ppat.1009056 · Cited by 68
Associations between the gut microbiome and metabolome in early life
Nguyen, Q. P., Karagas, M. R., Madan, J. C., Dade, E. F., Palys, T. J., Morrison, H. G., Pathmasiri, W., McRitche, S., Sumner, S., Frost, H. R., et al. (2021) · BMC Microbiology · doi:10.1186/s12866-021-02282-3 · Cited by 72
Viral biogeography of the mammalian gut and parenchymal organs
Shkoporov, A. N., Stockdale, S. R., Lavelle, A., Kondova, I. I., Hueston, C. M., Upadrasta, A., Khokhlova, E. V., van der Kamp, I., Ouwerling, B., Draper, L. A., et al. (2022) · Nature Microbiology · doi:10.1038/s41564-022-01178-w · Cited by 71
Dysbiosis in Functional Bowel Disorders
Enck, P., & Mazurak, N. (2018) · Annals of Nutrition and Metabolism · doi:10.1159/000488773 · Cited by 73
Ghimire, S., Roy, C., Wongkuna, S., Antony, L., Fenske, G. J., Maji, A., Keena, M. C., Foley, A., & Scaria, J. (2020) · mSystems · doi:10.1128/msystems.00620-19 · Cited by 71
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
Gut microbiota changes in preeclampsia, abnormal placental growth and healthy pregnant women
Huang, L., Cai, M., Li, L., Zhang, X., Xu, Y., Xiao, J., Huang, Q., Luo, G., Zeng, Z., Jin, C., et al. (2021) · BMC Microbiology · doi:10.1186/s12866-021-02327-7 · Cited by 68
Encapsulated Fecal Microbiota Transplantation: Development, Efficacy, and Clinical Application
Halaweish, H., Boatman, S. M., & Staley, C. M. (2022) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2022.826114 · Cited by 74
Host responses to mucosal biofilms in the lung and gut
Domingue, J. C., Drewes, J. L., Merlo, C. A., Housseau, F., & Sears, C. L. (2020) · Mucosal Immunology · doi:10.1038/s41385-020-0270-1 · Cited by 69
The Oral Microbiome Bank of China
Xian, P., Zhou, X., Xu, X., Yuqing, L., Li, Y., Li, J., Su, X., Huang, S., Xu, J., & Liao, G. (2018) · International Journal of Oral Science · doi:10.1038/s41368-018-0018-x · Cited by 65
Microbiome Is a Functional Modifier of P450 Drug Metabolism
Dempsey, J. L., & Cui, J. Y. (2019) · Current Pharmacology Reports · doi:10.1007/s40495-019-00200-w · Cited by 65
Shotgun metagenomics of dust microbiome from flight deck and cabin in civil aviation aircraft
Sun, Y., Fu, X., Li, Y., Yuan, Q., Ou, Z., Lindgren, T., Deng, Y., & Norbäck, D. (2020) · Indoor Air · doi:10.1111/ina.12707 · Cited by 65
Fu, X., Norbäck, D., Yuan, Q., Li, Y., Zhu, X., Hashim, J. H., Hashim, Z. B., Ali, F. A., Hu, Q., Deng, Y., et al. (2020) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2020.141904 · Cited by 70
Goals in Nutrition Science 2020-2025
Bassaganya-Riera, J., Berry, E. M., Blaak, E. E., Burlingame, B., le Coutre, J., van Eden, W., El‐Sohemy, A., German, J. B., Knorr, D., Lacroix, C., et al. (2021) · Frontiers in Nutrition · doi:10.3389/fnut.2020.606378 · Cited by 70
Enabling high‐throughput biology with flexible open‐source automation
Chory, E. J., Gretton, D., DeBenedictis, E. A., & Esvelt, K. M. (2021) · Molecular Systems Biology · doi:10.15252/msb.20209942 · Cited by 65
The interplay of obesity, gut microbiome and diet in the immune check point inhibitors therapy era
Spyrou, N., Vallianou, N. G., Kadillari, J., & Dalamaga, Μ. (2021) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2021.05.008 · Cited by 66
Roth, T. L., & Marson, A. (2021) · Annual Review of Pathology Mechanisms of Disease · doi:10.1146/annurev-pathmechdis-012419-032626 · Cited by 69
Malla, M. A., Dubey, A., Raj, A., Kumar, A., Upadhyay, N., & Yadav, S. (2022) · Environmental Pollution · doi:10.1016/j.envpol.2022.118851 · Cited by 65
Metagenome-derived virus-microbe ratios across ecosystems
López‐García, P., Gutiérrez‐Preciado, A., Krupovìč, M., Ciobanu, M., Deschamps, P., Jardillier, L. E., López‐Pérez, M., Rodríguez‐Valera, F., & Moreira, D. (2023) · The ISME Journal · doi:10.1038/s41396-023-01431-y · Cited by 64
Drinking Water Microbiome Project: Is it Time?
Hull, N. M., Ling, F., Pinto, A. J., Albertsen, M., Jang, H., Hong, P., Konstantinidis, K. T., LeChevallier, M. W., Colwell, R. R., & Liu, W. (2019) · Trends in Microbiology · doi:10.1016/j.tim.2019.03.011 · Cited by 66
Structure of the Mucosal and Stool Microbiome in Lynch Syndrome
Yan, Y., Drew, D. A., Markowitz, A. J., Lloyd‐Price, J., Abu-Ali, G., Nguyen, L. H., Tran, C., Chung, D. C., Gilpin, K. K., Meixell, D. A., et al. (2020) · Cell Host & Microbe · doi:10.1016/j.chom.2020.03.005 · Cited by 65
Self-citationmbImpute: an accurate and robust imputation method for microbiome data
Jiang, R., Li, W. V., & Li, J. J. (2021) · Genome biology · doi:10.1186/s13059-021-02400-4 · Cited by 67
Probiotics maintain the intestinal microbiome homeostasis of the sailors during a long sea voyage
Zhang, J., Zhao, J., Jin, H., Lv, R., Shi, H., De, G., Yang, B. K., Sun, Z., & Zhang, H. (2020) · Gut Microbes · doi:10.1080/19490976.2020.1722054 · Cited by 64
Visualizing metagenomic and metatranscriptomic data: A comprehensive review
Aplakidou, E., Vergoulidis, N., Chasapi, M. N., Venetsianou, N. K., Kokoli, M., Panagiotopoulou, E., Iliopoulos, I., Karatzas, E., Pafilis, E., Georgakopoulos‐Soares, I., et al. (2024) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2024.04.060 · Cited by 64
Lu, L., Jiang, M., Zhu, C., He, J., & Fan, S. (2018) · Free Radical Biology and Medicine · doi:10.1016/j.freeradbiomed.2018.10.410 · Cited by 62
Lei, M., Menon, R., Manteiga, S., Alden, N., Hunt, C. L., Alaniz, R. C., Lee, K., & Jayaraman, A. (2019) · mSystems · doi:10.1128/msystems.00724-19 · Cited by 65
Impact of host genetics on gut microbiome: Take‐home lessons from human and mouse studies
Cahana, I., & Iraqi, F. A. (2020) · Animal Models and Experimental Medicine · doi:10.1002/ame2.12134 · Cited by 64
Understanding respiratory microbiome–immune system interactions in health and disease
Simone, S. K. D., Rudloff, I., Nold‐Petry, C. A., Forster, S. C., & Nold, M. F. (2023) · Science Translational Medicine · doi:10.1126/scitranslmed.abq5126 · Cited by 62
Human Gut Microbiota Plasticity throughout the Life Course
Thriene, K., & Michels, K. B. (2023) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph20021463 · Cited by 65
Metadata
- Authors
- Lloyd-Price, J., Mahurkar, A., Rahnavard, G., Crabtree, J., Orvis, J., Hall, A. B., Brady, A., Creasy, H. H., McCracken, C., Giglio, M. G., McDonald, D., Franzosa, E. A., Knight, R., White, O., & Huttenhower, C.
- Affiliations
- University of Maryland, Baltimore (US)
- Broad Institute (US)
- University of California San Diego (US)
- Corresponding author
- Huttenhower, Curtis
- ORCID
- Venue
- Nature
- Published
- 2017-09-20
- Volume
- 550
- Issue
- 7674
- Pages
- 61-66
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC5831082
- OpenAlex
- W2756958651
- Cited by
- 1,267
- References
- 70
- Citations by year
- 2026: 91 · 2025: 126 · 2024: 150 · 2023: 108 · 2022: 165 · 2021: 195 · 2020: 160 · 2019: 168 · 2018: 91 · 2017: 10
- FWCI
- 47.89
- Type
- journal article
- Language
- en
- Update notices
- erratum (2017-10-12)
- Open access
- hybrid
- doi.org
- Locations
- Nature (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- Funders
- National Institutes of Health
- National Human Genome Research Institute (U54HG004969, U54HG003079, U01HG004866, U01HG006537, R01HG004872, U54HG004968, U54HG004973)
- National Institute of Allergy and Infectious Diseases (U54AI084844)
- National Institute of Diabetes and Digestive and Kidney Diseases (U54DK102557, P30DK043351)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Physical Sciences › Environmental Science › Ecology › Microbial Community Ecology and Physiology
- Keywords
- human microbiome, metagenomics, Human Microbiome Project, microbial diversity, strain identification, phylogenetic diversity, functional profiling, pathway enrichment, temporal dynamics
- MeSH terms
- Humans, National Institutes of Health (U.S.), Organ Specificity, Phylogeny, Time Factors, United States, Metagenome, Molecular Sequence Annotation, Spatio-Temporal Analysis, Microbiota, Datasets as Topic
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
