CoChat
Sign Up
Cited by 396

The role of the gut microbiome in the healthy adult status

D’Argenio, Valeria, Salvatore, Francesco·2015·Clinica Chimica Acta
DOI 10.1016/j.cca.2015.01.003
Open this paper in CoChat — free account

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.cca.2015.01.003

Cites

11 of 11 references verified0 citation errors · 0 not checkable

Statistics

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.

A few free checks a day · papers already verified open instantly · results are public

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?

  • More than 99% of the genes in our bodies are microbial, numbering over 10 million.

    “more than 99% of the genes in our bodies are microbial, numbering over 10 million (D' Argenio and Salvatore, 2015;Dinan et al., 2015;Donia et al., 2014;Gill et al.,”

    From The Microbiota-Gut-Brain Axis (2019) · cites this paper as D' Argenio and Salvatore, 2015

    The passage labeled Abstract estimates more than 5 million different genes in the human gut microbiome, supporting the general point that microbial genes are numerous. It does not establish either that they number over 10 million or that they constitute more than 99% of the genes in our bodies. The 99% figure in §2.1 refers instead to microbes estimated to be uncultivable; page numbers were not supplied for these passages. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

  • As humans have co-evolved with the microbiota, it plays a key role in programming all other bodily systems.

    “As we have co-evolved with this microbiota, it plays a key role in programming all other bodily systems (D' Argenio and Salvatore, 2015;Walsh et al., 2014).”

    From The Microbiota-Gut-Brain Axis (2019) · cites this paper as D' Argenio and Salvatore, 2015

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 59

  1. Grice EA, Kong HH, Conlan S, et al. Topographical and temporal diversity of the human skin microbiome. Science 2006;324:1190-2.
  2. González A, Vázquez-Baeza Y, Knight R. SnapShot: the human microbiome. Cell 2014;158:690-690.e1.
  3. Arumugam M, Raes J, Pelletier E, et al. Enterotypes of the human gut microbiome. Nature 2011;473:174-80.
  4. Flint HJ, Scott KP, Duncan SH, Louis P, Forano E. Microbial degradation of complex carbohydrates in the gut. Gut Microbes 2012;3:289-306.
  5. Walsh CJ, Guinane CM, O'Toole PW, Cotter PD. Beneficial modulation of the gut microbiota. FEBS Lett 2014. http://dx.doi.org/10.1016/j.febslet.2014.03.035. · DOI · Paper page
  6. Gajer P, Brotman RM, Bai G, et al. Temporal dynamics of the human vaginal microbiota. Sci Transl Med 2012;4:132ra152.
  7. Wu GD, Chen J, Hoffmann C, et al. Linking longterm dietary patterns with gut micro- bial enterotypes. Science 2011;334:105-8.
  8. Koren O, Goodrich JK, Cullender TC, et al. Host remodeling of the gut microbiome and metabolic changes during pregnancy. Cell 2012;150:470-80.
  9. Yatsunenko T, Rey FE, Manary MJ, et al. Human gut microbiome viewed across age and geography. Nature 2012;486:222-7.
  10. Perez-Cobas AE, Gosalbes MJ, Friedrichs A, et al. Gut microbiota disturbance during antibiotic therapy: a multi-omic approach. Gut 2013;62:1591-601.
  11. Palmer C, Bik EM, DiGiulio DB, Relman DA, Brown PO. Development of the human infant intestinal microbiota. PLoS Biol 2007;5:e177.
  12. Koenig JE, Spor A, Scalfone N, et al. Succession of microbial consortia in the develop- ing infant gut microbiome. Proc Natl Acad Sci U S A 2011;108:4578-85.
  13. Sharon I, Morowitz MJ, Thomas BC, Costello EK, Relman DA, Banfield JF. Time series community genomics analysis reveals rapid shifts in bacterial species, strains, and phage during infant gut colonization. Genome Res 2013;23:111-20.
  14. Stewart CJ, Marrs EC, Nelson A, et al. Development of the preterm gut microbiome in twins at risk of necrotising enterocolitis and sepsis. PLoS One 2013;8:e73465.
  15. Claesson MJ, Cusack S, O'Sullivan O, et al. Composition, variability, and temporal stability of the intestinal microbiota of the elderly. Proc Natl Acad Sci U S A 2011; 108:4586-91.
  16. Walker AW, Duncan SH, Louis P, Flint HJ. Phylogeny, culturing, and metagenomics of the human gut microbiota. Trends Microbiol 2014;22:267-74.
  17. Human Microbiome Project Consortium. A framework for human microbiome research. Nature 2012;486:215-21.
  18. Human Microbiome Project Consortium. Structure, function and diversity of the healthy human microbiome. Nature 2012;486:207-14.
  19. Turnbaugh PJ, Gordon JI. The core gut microbiome, energy balance and obesity. J Physiol 2009;587:4153-8.
  20. Sekirov I, Russell SL, Antunes LCM, Finlay BB. Gut microbiota in health and disease. Physiol Rev 2010;90:859-904.
  21. Cryan JF, O'Mahony SM. The microbiome-gut-brain axis: from bowel to behavior. Neurogastroenterol Motil 2011;23:187-92.
  22. Li L, Mendis N, Trigui H, Oliver JD, Faucher SP. The importance of the viable but non-culturable state in human bacterial pathogens. Front Microbiol 2014;5: 258.
  23. Morgan JL, Darling AE, Eisen JA. Metagenomic sequencing of an in vitro-simulated microbial community. PLoS One 2010;5:e10209.
  24. Woese CR, Fox GE, Zablen L, et al. Conservation of primary structure in 16S ribosom- al RNA. Nature 1975;254:83-6.
  25. Lee CK, Herbold CW, Polson SW, et al. Groundtruthing next-gen sequencing for microbial ecology-biases and errors in community structure estimates from PCR amplicon pyrosequencing. PLoS One 2012;7:e44224.
  26. Giannoukos G, Ciulla DM, Huang K, et al. Efficient and robust RNA-seq process for cul- tured bacteria and complex community transcriptomes. Genome Biol 2012;13:R23.
  27. Morgan XC, Huttenhower C. Meta'omic analytic techniques for studying the intesti- nal microbiome. Gastroenterology 2014;146:1437-48.
  28. Logares R, Haverkamp TH, Kumar S, et al. Environmental microbiology through the lens of high-throughput DNA sequencing: synopsis of current platforms and bioin- formatics approaches. J Microbiol Methods 2012;91:106-13.
  29. D'Argenio V, Casaburi G, Precone V, Salvatore F. Comparative metagenomic analysis of human gut microbiome composition using two different bioinformatic pipelines. Biomed Res Int 2014;2014:325340.
  30. Caporaso JG, Kuczynski J, Stombaugh J, et al. QIIME allows analysis of high- throughput community sequencing data. Nat Methods 2010;7:335-6.
  31. Schloss PD, Westcott SL, Ryabin T, et al. Introducing mothur: open-source, platform- independent, community supported software for describing and comparing micro- bial communities. Appl Environ Microbiol 2009;75:7537-41.
  32. Meyer F, Paarmann D, D'Souza M, et al. The metagenomics RAST server -a public resource for the automatic phylogenetic and functional analysis of metagenomes. BMC Bioinformatics 2008;9:386.
  33. Vetrovsky T, Baldrian P. The variability of the 16S rRNA gene in bacterial genomes and its consequences for bacterial community analyses. PLoS One 2013;8:e57923.
  34. Brady A, Salzberg SL. Phymm and PhymmBL: metagenomic phylogenetic classifica- tion with interpolated Markov models. Nat Methods 2009;6:673-6.
  35. Boisvert S, Raymond F, Godzaridis E, Laviolette F, Corbeil J. Ray Meta: scalable de novo metagenome assembly and profiling. Genome Biol 2012;13:R122.
  36. Segata N, Bornigen D, Morgan XC, Huttenhower C. PhyloPhlAn is a new method for improved phylogenetic and taxonomic placement of microbes. Nat Commun 2013; 4:2304.
  37. Howe AC, Jansson JK, Malfatti SA, Tringe SG, Tiedje JM, Brown CT. Tackling soil diver- sity with the assembly of large, complex metagenomes. Proc Natl Acad Sci U S A 2014;111:4904-9.
  38. Namiki T, Hachiya T, Tanaka H, Sakakibara Y. MetaVelvet: an extension of Velvet assembler to de novo metagenome assembly from short sequence reads. Nucleic Acids Res 2012;40:e155.
  39. Peng Y, Leung HC, Yiu SM, Chin FY. Meta-IDBA: a de novo assembler for metagenomic data. Bioinformatics 2011;27:i94-i101.
  40. Delcher AL, Bratke KA, Powers EC, Salzberg SL. Identifying bacterial genes and endo- symbiont DNA with Glimmer. Bioinformatics 2007;23:673-9.
  41. Besemer J, Lomsadze A, Borodovsky M. GeneMarkS: a self-training method for prediction of gene starts in microbial genomes. Implications for finding sequence motifs in regulatory regions. Nucleic Acids Res 2001;29:2607-18.
  42. Abubucker S, Segata N, Goll J, et al. Metabolic reconstruction for metagenomic data and its application to the human microbiome. PLoS Comput Biol 2012;8:e1002358.
  43. Leimena MM, Ramiro-Garcia J, Davids M, et al. A comprehensive metatranscriptome analysis pipeline and its validation using human small intestine microbiota datasets. BMC Genomics 2013;14:530.
  44. Trapnell C, Roberts A, Goff L, et al. Differential gene and transcript expression analy- sis of RNA-seq experiments with TopHat and Cufflinks. Nat Protoc 2012;7:562-78.
  45. Mandlik A, Livny J, Robins WP, Ritchie JM, Mekalanos JJ, Waldor MK. RNA-Seq-based monitoring of infection-linked changes in Vibrio cholera gene expression. Cell Host Microbe 2011;10:165-74.
  46. Backhed F, Fraser CM, Ringel Y, et al. Defining a healthy human gut microbiome: Current concepts, future directions, and clinical applications. Cell Host Microbe 2012;12:611-22.
  47. Hollister EB, Gao C, Versalovic J. Compositional and functional features of the gastro- intestinal microbiome and their effects on human health. Gastroenterology 2014; 146:1449-58.
  48. Kostic AD, Xavier RJ, Gevers D. The microbiome in inflammatory bowel disease: current status and the future ahead. Gastroenterology 2014;146:1489-99.
  49. Severance EG, Yolken RH, Eaton WW. Autoimmune diseases, gastrointestinal disorders and the microbiome in schizophrenia: more than a gut feeling. Schizophr Res 2014. http://dx.doi.org/10.1016/j.schres.2014.06.027. · DOI
  50. Olivares M, Neef A, Castillejo G, et al. The HLA-DQ2 genotype selects for early intestinal microbiota composition in infants at high risk of developing coeliac disease. Gut 2014. http://dx.doi.org/10.1136/gutjnl-2014-306931. · DOI
  51. Wang Y, Hoenig JD, Malin KJ, et al. 16S rRNA gene based analysis of fecal microbiota from preterm infants with and without necrotizing enterocolitis. ISME J 2009;3: 944-54.
  52. Cani PD. Gut microbiota and obesity: lessons from the microbiome. Brief Funct Genomics 2013;12:381-7.
  53. Clarke SF, Murphy EF, Nilaweera K, et al. The gut microbiota and its relationship to diet and obesity: new insights. Gut Microbes 2012;3:186-202.
  54. Frank DN, Amand ALS, Feldman RA, Boedeker EC, Harpaz N, Pace NR. Molecular- phylogenetic characterization of microbial community imbalances in human inflam- matory bowel diseases. Proc Natl Acad Sci U S A 2007;104:13780-5.
  55. Sokol H, Seksik P. The intestinal microbiota in inflammatory bowel diseases: time to connect with the host. Curr Opin Gastroenterol 2010;26:327-31.
  56. Walker AW, Sanderson JD, Churcher C, et al. High-throughput clone library analysis of the mucosa-associated microbiota reveals dysbiosis and differences between inflamed and non-inflamed regions of the intestine in inflammatory bowel disease. BMC Microbiol 2011;11:7.
  57. Elson CO, Cong Y. Host-microbiota interactions in inflammatory bowel disease. Gut Microbes 2012;3:332-44.
  58. D'Argenio V, Precone V, Casaburi G, et al. An altered gut microbiome profile in a child affected by Crohn's disease normalized after nutritional therapy. Am J Gastroenterol 2013;108:851-2.
  59. Lemon KP, Armitage GC, Relman DA, Fischbach MA. Microbiotatargeted therapies: an ecological perspective. Sci Transl Med 2012;4:137rv5.

Cited by

Sorted by citations

Authors
D’Argenio, V., & Salvatore, F.
Venue
Clinica Chimica Acta
Publisher
Elsevier BV
Published
2015-12
Volume
451
Pages
97-102
ISSN
0009-8981
DOI
10.1016/j.cca.2015.01.003
Cited by
396
References
11
Language
en
Licence

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