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Cited by 15Gut microbiota and healthGenomics and Phylogenetic StudiesMicrobial Community Ecology and Physiology

Bioinformatic Methodologies in Assessing Gut Microbiota

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Fox, James Douglas, Sims, Austin, Ross, Morgan, Bettag, Jeffery, Wilder, Alexandra, Natrop, Dylan, Borsotti, Alison, Kolli, Sree +6 more·2024·Microbiology Research
DOI 10.3390/microbiolres15040170PMC PMC12381627
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Abstract

Bioinformatic methodologies play a crucial role in the assessment of gut microbiota, offering advanced tools for analyzing complex microbial communities. These methodologies involve high-throughput sequencing technologies, such as 16S rRNA gene sequencing and metagenomics, which generate vast amounts of data on microbial diversity and functional potential, as well as whole-genome sequencing, which, while being more costly, has a more expansive potential. Bioinformatics tools and algorithms process these data to identify microbial taxa and quantify and elucidate their roles within the microbiome. Advanced statistical and computational models further enable the identification of microbiota patterns associated with various diseases and health conditions. Overall, bioinformatic approaches are essential for deciphering the complexities of gut microbiota so that, in the future, we may be able to discover treatments and technologies aimed at restoring or optimizing the microbiome. The goal of this review is to describe the differences in methodology and utilization of 16S versus whole-genome sequencing to address the increased understanding of the role that the gut microbiome plays in human physiology and pathology.

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  • Advances in sequencing technologies and bioinformatics have significantly enhanced our ability to profile microbial communities, providing insights into their contributions to health and disease.

    “Advances in sequencing technologies and bioinformatics have significantly enhanced our ability to profile these microbial communities, providing insights into their contributions to health and disease [65].”

    From The Seven Methods for the Evaluation of Nutritional Status—ABCDEFG: Narrative Review (2026) · cites this paper as [65]

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  1. [1]Carter J; Bettag J; Morfin S; Manithody C; Nagarapu A; Jain A; Nazzal H; Prem S; Unes M; McHale M; Gut Microbiota Modulation of Short Bowel Syndrome and the Gut–Brain Axis. Nutrients 2023, 15, 2581. 37299543 PMC10255811
  2. [2]Bettag J; Po L; Cunningham C; Tallam R; Kurashima K; Nagarapu A; Hutchinson C; Morfin S; Nazzal M; Lin C-J; Novel Therapeutic Approaches for Mitigating Complications in Short Bowel Syndrome. Nutrients 2022, 14, 4660. 36364922 PMC9658734
  3. [3]Verma H; Verma A; Bettag J; Kolli S; Kurashima K; Manithody C; Jain A Role of Effective Policy and Screening in Managing Pediatric Nutritional Insecurity as the Most Important Social Determinant of Health Influencing Health Outcomes. Nutrients 2023, 16, 5. 38201835 PMC10780641
  4. [5]Zhao Q; Elson CO Adaptive immune education by gut microbiota antigens. Immunology 2018, 154, 28– 37. 29338074 PMC5904715
  5. [6]Honda K; Littman DR The microbiota in adaptive immune homeostasis and disease. Nature 2016, 535, 75– 84. 27383982
  6. [7]Hooper LV; Littman DR; MacPherson AJ Interactions Between the Microbiota and the Immune System. Science 2012, 336, 1268– 1273. 22674334 PMC4420145
  7. [8]Clemente JC; Ursell LK; Parfrey LW; Knight R The Impact of the Gut Microbiota on Human Health: An Integrative View. Cell 2012, 148, 1258– 1270. 22424233 PMC5050011
  8. [10]Woese CR; Fox GE Phylogenetic structure of the prokaryotic domain: The primary kingdoms. Proc. Natl. Acad. Sci. USA 1977, 74, 5088– 5090. 270744 PMC432104
  9. [11]Lane DJ; Pace B; Olsen GJ; A Stahl D; Sogin ML; Pace NR Rapid determination of 16S ribosomal RNA sequences for phylogenetic analyses. Proc. Natl. Acad. Sci. USA 1985, 82, 6955– 6959. 2413450 PMC391288
  10. [12]Sanschagrin S; Yergeau E Next-generation Sequencing of 16S Ribosomal RNA Gene Amplicons. J. Vis. Exp 2014, e51709. PMC4828026 25226019
  11. [13]Ranjan R; Rani A; Metwally A; McGee HS; Perkins DL Analysis of the microbiome: Advantages of whole genome shotgun versus 16S amplicon sequencing. Biochem. Biophys. Res. Commun 2017, 469, 967– 977. PMC4830092 26718401
  12. [14]Jovel J; Patterson J; Wang W; Hotte N; O’Keefe S; Mitchel T; Perry T; Kao D; Mason AL; Madsen KL; Characterization of the Gut Microbiome Using 16S or Shotgun Metagenomics. Front. Microbiol 2016, 7, 459. 27148170 PMC4837688
  13. [16]Walker RW; Clemente JC; Peter I; Loos RJF The prenatal gut microbiome: Are we colonized with bacteria in utero? Pediatr. Obes 2017, 12 (Suppl. S1), 3– 17. 28447406 PMC5583026
  14. [17]Vélez-Ixta JM; Juárez-Castelán CJ; Ramírez-Sánchez D; Lázaro-Pérez N.d.S.; Castro-Arellano JJ; Romero-Maldonado S; Rico-Arzate E; Hoyo-Vadillo C; Salgado-Mancilla M; Gómez-Cruz CY; Post Natal Microbial and Metabolite Transmission: The Path from Mother to Infant. Nutrients 2024, 16, 1990. 38999737 PMC11243545
  15. [18]Wild CP The exposome: From concept to utility. Int. J. Epidemiol 2012, 41, 24– 32. 22296988
  16. [19]Sainz T; Pignataro V; Bonifazi D; Ravera S; Mellado MJ; Pérez-Martínez A; Escudero A; Ceci A; Calvo C Human Microbiome in Children, at the Crossroad of Social Determinants of Health and Personalized Medicine. Children 2021, 8, 1191. 34943387 PMC8700538
  17. [20]Lapidot Y; Reshef L; Maya M; Cohen D; Gophna U; Muhsen K Socioeconomic disparities and household crowding in association with the fecal microbiome of school-age children. npj Biofilms Microbiomes 2022, 8, 10. 35241676 PMC8894399
  18. [21]Yao Y; Cai X; Ye Y; Wang F; Chen F; Zheng C The Role of Microbiota in Infant Health: From Early Life to Adulthood. Front. Immunol 2021, 12, 708472. 34691021 PMC8529064
  19. [22]Caporaso JG; Lauber CL; Walters WA; Berg-Lyons D; Lozupone CA; Turnbaugh PJ; Fierer N; Knight R Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc. Natl. Acad. Sci. USA 2011, 108 (Supp. 1), 4516– 4522. 20534432 PMC3063599
  20. [23]Shahi SK; Zarei K; Guseva NV; Mangalam AK Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing. J. Vis. Exp 2019, e59980. PMC6945761 31680682
  21. [24]Funke G; von Graevenitz A; E Clarridge J; A Bernard K Clinical microbiology of coryneform bacteria. Clin. Microbiol. Rev 1997, 10, 125– 159. 8993861 PMC172946
  22. [26]Kimura M. A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. J. Mol. Evol 1980, 16, 111– 120. 7463489
  23. [27]Relman DA The Search for Unrecognized Pathogens. Science 1999, 284, 1308– 1310. 10334977
  24. [28]Sacchi CT; Whitney AM; Reeves MW; Mayer LW; Popovic T Sequence Diversity of Neisseria meningitidis 16S rRNA Genes and Use of 16S rRNA Gene Sequencing as a Molecular Subtyping Tool. J. Clin. Microbiol 2002, 40, 4520– 4527. 12454145 PMC154644
  25. [30]Kattar MM; Chavez JF; Limaye AP; Rassoulian-Barrett SL; Yarfitz SL; Carlson LC; Houze Y; Swanzy S; Wood BL; Cookson BT Application of 16S rRNA Gene Sequencing to Identify Bordetella hinzii as the Causative Agent of Fatal Septicemia. J. Clin. Microbiol 2000, 38, 789– 794. 10655386 PMC86205
  26. [31]Srinivasan R; Karaoz U; Volegova M; MacKichan J; Kato-Maeda M; Miller S; Nadarajan R; Brodie EL; Lynch SV Use of 16S rRNA Gene for Identification of a Broad Range of Clinically Relevant Bacterial Pathogens. PLoS ONE 2015, 10, e0117617. 25658760 PMC4319838
  27. [32]Punina NV; Makridakis NM; Remnev MA; Topunov AF Whole-genome sequencing targets drug-resistant bacterial infections. Hum. Genom 2015, 9, 19. PMC4525730 26243131
  28. [33]Boers SA; Jansen R; Hays JP Understanding and overcoming the pitfalls and biases of next-generation sequencing (NGS) methods for use in the routine clinical microbiological diagnostic laboratory. Eur. J. Clin. Microbiol. Infect. Dis 2019, 38, 1059– 1070. 30834996 PMC6520317
  29. [34]Cason C; D’accolti M; Soffritti I; Mazzacane S; Comar M; Caselli E Next-generation sequencing and PCR technologies in monitoring the hospital microbiome and its drug resistance. Front. Microbiol 2022, 13, 969863. 35966671 PMC9370071
  30. [35]Didelot X; Bowden R; Wilson DJ; Peto TEA; Crook DW Transforming clinical microbiology with bacterial genome sequencing. Nat. Rev. Genet 2012, 13, 601– 612. 22868263 PMC5049685
  31. [36]Clarridge JE Impact of 16S rRNA Gene Sequence Analysis for Identification of Bacteria on Clinical Microbiology and Infectious Diseases. Clin. Microbiol. Rev 2004, 17, 840– 862. 15489351 PMC523561
  32. [37]Kameoka S; Motooka D; Watanabe S; Kubo R; Jung N; Midorikawa Y; Shinozaki NO; Sawai Y; Takeda AK; Nakamura S Benchmark of 16S rRNA gene amplicon sequencing using Japanese gut microbiome data from the V1–V2 and V3–V4 primer sets. BMC Genom. 2021, 22, 527. PMC8272389 34246242
  33. [38]Church DL; Cerutti L; Gürtler A; Griener T; Zelazny A; Emler S Performance and Application of 16S rRNA Gene Cycle Sequencing for Routine Identification of Bacteria in the Clinical Microbiology Laboratory. Clin. Microbiol. Rev 2020, 33. PMC7484979 32907806
  34. [40]Ames NJ; Ranucci A; Moriyama B; Wallen GR The Human Microbiome and Understanding the 16S rRNA Gene in Translational Nursing Science. Nurs. Res 2017, 66, 184– 197. 28252578 PMC5535273
  35. [41]Wallace BD; Wang H; Lane KT; Scott JE; Orans J; Koo JS; Venkatesh M; Jobin C; Yeh L-A; Mani S; Alleviating Cancer Drug Toxicity by Inhibiting a Bacterial Enzyme. Science 2010, 330, 831– 835. 21051639 PMC3110694
  36. [42]Escobar JS; Klotz B; Valdes BE; Agudelo GM The gut microbiota of Colombians differs from that of Americans, Europeans and Asians. BMC Microbiol. 2014, 14, 311. 25495462 PMC4275940
  37. [43]Yatsunenko T; Rey FE; Manary MJ; Trehan I; Dominguez-Bello MG; Contreras M; Magris M; Hidalgo G; Baldassano RN; Anokhin AP; Human gut microbiome viewed across age and geography. Nature 2012, 486, 222– 227. 22699611 PMC3376388
  38. [44]Schnorr SL; Candela M; Rampelli S; Centanni M; Consolandi C; Basaglia G; Turroni S; Biagi E; Peano C; Severgnini M; Gut microbiome of the Hadza hunter-gatherers. Nat. Commun 2014, 5, 3654. 24736369 PMC3996546
  39. [45]Ley RE; Bäckhed F; Turnbaugh P; Lozupone CA; Knight RD; Gordon JI Obesity alters gut microbial ecology. Proc. Natl. Acad. Sci. USA 2005, 102, 11070– 11075. 16033867 PMC1176910
  40. [47]Zhang T; Li Q; Cheng L; Buch H; Zhang F Akkermansia muciniphila is a promising probiotic. Microb. Biotechnol 2019, 12, 1109– 1125. 31006995 PMC6801136
  41. [48]Depommier C; Everard A; Druart C; Plovier H; Van Hul M; Vieira-Silva S; Falony G; Raes J; Maiter D; Delzenne NM; Supplementation with Akkermansia muciniphila in overweight and obese human volunteers: A proof-of-concept exploratory study. Nat. Med 2019, 25, 1096– 1103. 31263284 PMC6699990
  42. [49]Takewaki D; Suda W; Sato W; Takayasu L; Kumar N; Kimura K; Kaga N; Mizuno T; Miyake S; Hattori M; Alterations of the gut ecological and functional microenvironment in different stages of multiple sclerosis. Proc. Natl. Acad. Sci. USA 2020, 117, 22402– 22412. 32839304 PMC7486801
  43. [50]Clayton RA; Sutton G; Hinkle PS; Bult C; Fields C Intraspecific Variation in Small-Subunit rRNA Sequences in GenBank: Why Single Sequences May Not Adequately Represent Prokaryotic Taxa. Int. J. Syst. Evol. Microbiol 1995, 45, 595– 599. 8590690
  44. [51]Mellmann A; Cloud JL; Andrees S; Blackwood K; Carroll KC; Kabani A; Roth A; Harmsen D Evaluation of RIDOM, MicroSeq, and GenBank services in the molecular identification of Nocardia species. Int. J. Med. Microbiol 2003, 293, 359– 370. 14695064
  45. [52]Schloss PD; Handelsman J Introducing DOTUR, a Computer Program for Defining Operational Taxonomic Units and Estimating Species Richness. Appl. Environ. Microbiol 2005, 71, 1501– 1506. 15746353 PMC1065144
  46. [53]Bose N; Moore SD Variable Region Sequences Influence 16S rRNA Performance. Microbiol. Spectr 2023, 11, e0125223. 37212673 PMC10269663
  47. [54]Edgar RC Accuracy of taxonomy prediction for 16S rRNA and fungal ITS sequences. PeerJ 2018, 6, e4652. 29682424 PMC5910792
  48. [55]Johnson JS; Spakowicz DJ; Hong B-Y; Petersen LM; Demkowicz P; Chen L; Leopold SR; Hanson BM; Agresta HO; Gerstein M; Evaluation of 16S rRNA gene sequencing for species and strain-level microbiome analysis. Nat. Commun 2019, 10, 5029. 31695033 PMC6834636
  49. [56]Goyal A; Bittleston LS; E Leventhal G; Lu L; Cordero OX; Systems POL; States U Interactions between strains govern the eco-evolutionary dynamics of microbial communities. eLife 2022, 11, e74987. 35119363 PMC8884728
  50. [57]Weinroth MD; Belk AD; Dean C; Noyes N; Dittoe DK; Rothrock MJ; Ricke SC; Myer PR; Henniger MT; Ramírez GA; Considerations and best practices in animal science 16S ribosomal RNA gene sequencing microbiome studies. J. Anim. Sci 2022, 100, skab346. 35106579 PMC8807179
  51. [58]Rampini SK; Bloemberg GV; Keller PM; Büchler AC; Dollenmaier G; Speck RF; Böttger EC Broad-Range 16S rRNA Gene Polymerase Chain Reaction for Diagnosis of Culture-Negative Bacterial Infections. Clin. Infect. Dis 2011, 53, 1245– 1251. 21976460
  52. [59]Minich JJ; Humphrey G; Benitez RAS; Sanders J; Swafford A; Allen EE; Knight R High-Throughput Miniaturized 16S rRNA Amplicon Library Preparation Reduces Costs while Preserving Microbiome Integrity. mSystems 2018, 3, e00166– 18. PMC6222042 30417111
  53. [60]Drevinek P; Hollweck R; Lorenz MG; Lustig M; Bjarnsholt T Direct 16S/18S rRNA Gene PCR Followed by Sanger Sequencing as a Clinical Diagnostic Tool for Detection of Bacterial and Fungal Infections: A Systematic Review and Meta-Analysis. J. Clin. Microbiol 2023, 61, e0033823. 37367430 PMC10575125
  54. [61]Janda JM; Abbott SL 16S rRNA Gene Sequencing for Bacterial Identification in the Diagnostic Laboratory: Pluses, Perils, and Pitfalls. J. Clin. Microbiol 2007, 45, 2761– 2764. 17626177 PMC2045242
  55. [62]Mignard S; Flandrois J 16S rRNA sequencing in routine bacterial identification: A 30-month experiment. J. Microbiol. Methods 2006, 67, 574– 581. 16859787
  56. [63]Woo PCY; Ng KHL; Lau SKP; Yip K-T; Fung AMY; Leung K-W; Tam DMW; Que T-L; Yuen K-Y Usefulness of the MicroSeq 500 16S Ribosomal DNA-Based Bacterial Identification System for Identification of Clinically Significant Bacterial Isolates with Ambiguous Biochemical Profiles. J. Clin. Microbiol 2003, 41, 1996– 2001. 12734240 PMC154750
  57. [64]Fox GE; Wisotzkey JD; Jurtshuk P How Close Is Close: 16S rRNA Sequence Identity May Not Be Sufficient to Guarantee Species Identity. Int. J. Syst. Evol. Microbiol 1992, 42, 166– 170. 1371061
  58. [65]Venter JC; Remington K; Heidelberg JF; Halpern AL; Rusch D; Eisen JA; Wu D; Paulsen IT; Nelson KE; Nelson W; Environmental Genome Shotgun Sequencing of the Sargasso Sea. Science 2004, 304, 66– 74. 15001713
  59. [66]Eckburg PB; Bik EM; Bernstein CN; Purdom E; Dethlefsen L; Sargent M; Gill SR; Nelson KE; Relman DA Diversity of the Human Intestinal Microbial Flora. Science 2005, 308, 1635– 1638. 15831718 PMC1395357
  60. [67]Bodor A; Bounedjoum N; Vincze GE; Erdeiné Kis Á; Laczi K; Bende G; Szilágyi Á; Kovács T; Perei K; Rákhely G Challenges of unculturable bacteria: Environmental perspectives. Rev. Environ. Sci. Bio/Technol 2020, 19, 1– 22.
  61. [68]Taş N; de Jong AE; Li Y; Trubl G; Xue Y; Dove NC Metagenomic tools in microbial ecology research. Curr. Opin. Biotechnol 2021, 67, 184– 191. 33592536
  62. [69]Turnbaugh PJ; Ley RE; Hamady M; Fraser-Liggett CM; Knight R; Gordon JI The Human Microbiome Project. Nature 2007, 449, 804– 810. 17943116 PMC3709439
  63. [70]Peterson J; Garges S; Giovanni M; McInnes P; Wang L; Schloss JA; Bonazzi V; McEwen JE; Wetterstrand KA; Deal C; The NIH Human Microbiome Project. Genome Res. 2009, 19, 2317– 2323. 19819907 PMC2792171
  64. [71]Joseph T; Peer I An Introduction to Whole-Metagenome Shotgun Sequencing Studies. Methods Mol. Biol 2021, 2243, 107– 122. 33606255
  65. [72]Pérez-Cobas AE; Gomez-Valero L; Buchrieser C Metagenomic approaches in microbial ecology: An update on whole-genome and marker gene sequencing analyses. Microb. Genom 2020, 6, e000409. PMC7641418 32706331
  66. [73]Chen K; Pachter L Bioinformatics for Whole-Genome Shotgun Sequencing of Microbial Communities. PLoS Comput. Biol 2005, 1, e24– 12. 16110337 PMC1185649
  67. [74]Satam H; Joshi K; Mangrolia U; Waghoo S; Zaidi G; Rawool S; Thakare RP; Banday S; Mishra AK; Das G; Next-Generation Sequencing Technology: Current Trends and Advancements. Biology 2023, 12, 997. 37508427 PMC10376292
  68. [75]Navgire GS; Goel N; Sawhney G; Sharma M; Kaushik P; Mohanta YK; Mohanta TK; Al-Harrasi A Analysis and Interpretation of metagenomics data: An approach. Biol. Proced. Online 2022, 24, 1– 22. 36402995 PMC9675974
  69. [77]Felczykowska A; Krajewska A; Zielińska S; Łoś JM Sampling, metadata and DNA extraction - important steps in metagenomic studies. Acta Biochim. Pol 2015, 62, 151– 160. 25680373
  70. [80]Head SR; Komori HK; LaMere SA; Whisenant T; Van Nieuwerburgh F; Salomon DR; Ordoukhanian P Library construction for next-generation sequencing: Overviews and challenges. BioTechniques 2014, 56, 61– 77. 24502796 PMC4351865
  71. [81]Gaulke CA; Schmeltzer ER; Dasenko M; Tyler BM; Thurber RV; Sharpton TJ Evaluation of the Effects of Library Preparation Procedure and Sample Characteristics on the Accuracy of Metagenomic Profiles. mSystems 2021, 6, e0044021. 34636674 PMC8510527
  72. [82]Meslier V; Quinquis B; Da Silva K; Oñate FP; Pons N; Roume H; Podar M; Almeida M Benchmarking second and third-generation sequencing platforms for microbial metagenomics. Sci. Data 2022, 9, 694. 36369227 PMC9652401
  73. [83]Ghurye JS; Cepeda-Espinoza V; Pop M Metagenomic Assembly: Overview, Challenges and Applications. Chall. Appl 2016, 89, 353– 362. PMC5045144 27698619
  74. [84]Khan J; Kokot M; Deorowicz S; Patro R Scalable, ultra-fast, and low-memory construction of compacted de Bruijn graphs with Cuttlefish 2. Genome Biol. 2022, 23, 190. 36076275 PMC9454175
  75. [85]Brinda K; Baym M; Kucherov G Simplitigs as an efficient and scalable representation of de Bruijn graphs. Genome Biol. 2021, 22, 96. 33823902 PMC8025321
  76. [87]Hills RD Jr.; Pontefract BA; Mishcon HR; Black CA; Sutton SC; Theberge CR Gut Microbiome: Profound Implications for Diet and Disease. Nutrients 2019, 11, 1613. 31315227 PMC6682904
  77. [88]Lewis JD; Chen EZ; Baldassano RN; Otley AR; Griffiths AM; Lee D; Bittinger K; Bailey A; Friedman ES; Hoffmann C; Inflammation, Antibiotics, and Diet as Environmental Stressors of the Gut Microbiome in Pediatric Crohn’s Disease. Cell Host Microbe 2015, 18, 489– 500. 26468751 PMC4633303
  78. [89]Margolis DJ; Fanelli M; Hoffstad O; Lewis JD Potential Association Between the Oral Tetracycline Class of Antimicrobials Used to Treat Acne and Inflammatory Bowel Disease. Am. J. Gastroenterol 2010, 105, 2610– 2616. 20700115
  79. [91]Draper LA; Ryan FJ; Smith MK; Jalanka J; Mattila E; Arkkila PA; Ross RP; Satokari R; Hill C Long-term colonisation with donor bacteriophages following successful faecal microbial transplantation. Microbiome 2018, 6, 220. 30526683 PMC6288847
  80. [92]Sokol H; Leducq V; Aschard H; Pham HP; Jegou S; Landman C; Cohen D; Liguori G; Bourrier A; Nion-Larmurier I; Fungal microbiota dysbiosis in IBD. Gut 2017, 66, 1039– 1048. 26843508 PMC5532459
  81. [93]Acinas SG; Klepac-Ceraj V; Hunt DE; Pharino C; Ceraj I; Distel DL; Polz MF Fine-scale phylogenetic architecture of a complex bacterial community. Nature 2004, 430, 551– 554. 15282603
  82. [94]Walter J. Ecological Role of Lactobacilli in the Gastrointestinal Tract: Implications for Fundamental and Biomedical Research. Appl. Environ. Microbiol 2008, 74, 4985– 4996. 18539818 PMC2519286
  83. [95]Rossi M; Martínez-Martínez D; Amaretti A; Ulrici A; Raimondi S; Moya A Mining metagenomic whole genome sequences revealed subdominant but constant Lactobacillus population in the human gut microbiota. Environ. Microbiol. Rep 2016, 8, 399– 406. 27043715
  84. [96]Kwong J; Mccallum N; Sintchenko V; Howden B Whole genome sequencing in clinical and public health microbiology. Pathology 2015, 47, 199– 210. 25730631 PMC4389090
  85. [97]Kuczynski J; Lauber CL; Walters WA; Parfrey LW; Clemente JC; Gevers D; Knight R Experimental and analytical tools for studying the human microbiome. Nat. Rev. Genet 2011, 13, 47– 58. 22179717 PMC5119550
  86. [98]Su YCF; Anderson DE; Young BE; Linster M; Zhu F; Jayakumar J; Zhuang Y; Kalimuddin S; Low JGH; Tan CW; Discovery and Genomic Characterization of a 382-Nucleotide Deletion in ORF7b and ORF8 during the Early Evolution of SARS-CoV-2. mBio 2020, 11, 10– 1128. PMC7374062 32694143
  87. [99]Lee HK; Lee CK; Tang JW-T; Loh TP; Koay ES-C Contamination-controlled high-throughput whole genome sequencing for influenza A viruses using the MiSeq sequencer. Sci. Rep 2016, 6, 33318. 27624998 PMC5022032
  88. [101]Sims D; Sudbery I; Ilott NE; Heger A; Ponting CP Sequencing depth and coverage: Key considerations in genomic analyses. Nat. Rev. Genet 2014, 15, 121– 132. 24434847
  89. [102]Durazzi F; Sala C; Castellani G; Manfreda G; Remondini D; De Cesare A Comparison between 16S rRNA and shotgun sequencing data for the taxonomic characterization of the gut microbiota. Sci. Rep 2021, 11, 3030. 33542369 PMC7862389
  90. [103]Laudadio I; Fulci V; Palone F; Stronati L; Cucchiara S; Carissimi C Quantitative Assessment of Shotgun Metagenomics and 16S rDNA Amplicon Sequencing in the Study of Human Gut Microbiome. OMICS J. Integr. Biol 2018, 22, 248– 254. 29652573
  91. [104]Campanaro S; Treu L; Kougias PG; Zhu X; Angelidaki I Taxonomy of anaerobic digestion microbiome reveals biases associated with the applied high throughput sequencing strategies. Sci. Rep 2018, 8, 1926. 29386622 PMC5792648
  92. [105]Yilmaz S; Singh AK Single cell genome sequencing. Curr. Opin. Biotechnol 2012, 23, 437– 443. 22154471 PMC3318999
  93. [106]Evrony GD; Hinch AG; Luo C Applications of Single-Cell DNA Sequencing. Annu. Rev. Genom. Hum. Genet 2021, 22, 171– 197. PMC8410678 33722077
  94. [107]Tahir UA; Katz DH; Avila-Pachecho J; Bick AG; Pampana A; Robbins JM; Yu Z; Chen Z-Z; Benson MD; Cruz DE; Whole Genome Association Study of the Plasma Metabolome Identifies Metabolites Linked to Cardiometabolic Disease in Black Individuals. Nat. Commun 2022, 13, 4923. 35995766 PMC9395431

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Authors
Fox, J. D., Sims, A., Ross, M., Bettag, J., Wilder, A., Natrop, D., Borsotti, A., Kolli, S., Mehta, S., Verma, H., Kurashima, K., Manithody, C., Verma, A., & Jain, A.
Affiliations
  • Saint Louis University (US)
  • Medical College of Wisconsin-Green Bay, De Pere, WI 54115, USA
Corresponding author
  • Ross, Morgan
  • Jain, Ajay
ORCID
Venue
Microbiology Research
Publisher
MDPI AG
Published
2024-12-03
Volume
15
Issue
4
Pages
2554-2574
ISSN
  • 2036-7473 (ISSN-L)
  • 2036-7481
DOI
10.3390/microbiolres15040170
PMC
PMC12381627
OpenAlex
W4405069157
Cited by
15
References
9
Citations by year
2026: 7 · 2025: 8
FWCI
2.04
Type
journal article
Language
en
Open access
Licence
Locations
  • Microbiology Research (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion, cc-by)
  • Europe PMC (PubMed Central) (acceptedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
the National Institutes of Health (NIH-1R01DK131136-01, NIH-R21AI169487-01, NIH-1R03 DK121046-01, NIH-P01AG078106-01, NIH-1U01 AI163064-01, NIH-1U01-DK61718)
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
gut microbiota, 16S rRNA gene sequencing, metagenomics, whole genome sequencing, microbial diversity, microbial community analysis, bioinformatics software, microbiota-based therapy

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 ›

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