Profiling the Gastrointestinal Microbiota.


Journal

Methods in molecular biology (Clifton, N.J.)
ISSN: 1940-6029
Titre abrégé: Methods Mol Biol
Pays: United States
ID NLM: 9214969

Informations de publication

Date de publication:
2021
Historique:
entrez: 25 3 2021
pubmed: 26 3 2021
medline: 12 6 2021
Statut: ppublish

Résumé

In this chapter, we provide a methodological description of the process to perform gastrointestinal (GIT) microbiota profiling on human stool samples. The process includes: (i) collection of feces, (ii) isolation of DNA from fecal community bacteria, (iii) selection of both 16S rDNA sequencing target and next-generation sequencing platform, and (iv) analysis and interpretation of sequence data. The process culminates into a comprehensive report on the GIT microbiota composition and structure that may translate into clinically actionable results.

Identifiants

pubmed: 33765312
doi: 10.1007/978-1-0716-1302-3_10
doi:

Substances chimiques

DNA, Bacterial 0
DNA, Ribosomal 0
RNA, Ribosomal, 16S 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

83-92

Références

Lagier JC, Million M, Hugon P et al (2012) Human gut microbiota: repertoire and variations. Front Cell Infect Microbiol 2:136
doi: 10.3389/fcimb.2012.00136
Caporaso JG, Lauber CL, Walters WA et al (2012) Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J 6:1621–1624
doi: 10.1038/ismej.2012.8
Davidson RM, Epperson LE (2018) Microbiome sequencing methods for studying human diseases. Methods Mol Biol 1706:77–90
doi: 10.1007/978-1-4939-7471-9_5
Bik EM (2016) The hoops, hopes, and hypes of human microbiome research. Yale J Biol Med 89:363–373
pubmed: 27698620 pmcid: 5045145
Donaldson GP, Lee SM, Mazmanian SK (2016) Gut biogeography of the bacterial microbiota. Nat Rev Microbiol 14:20–32
doi: 10.1038/nrmicro3552
Stearns JC, Lynch MD, Senadheera DB et al (2011) Bacterial biogeography of the human digestive tract. Sci Rep 1:170
doi: 10.1038/srep00170
Engen PA, Green SJ, Voigt RM et al (2015) The gastrointestinal microbiome: alcohol effects on the composition of intestinal microbiota. Alcohol Res 37:223–236
pubmed: 26695747 pmcid: 4590619
Schloss PD, Girard RA, Martin T et al (2016) Status of the archaeal and bacterial census: an update. MBio 7:e00201–e00216
doi: 10.1128/mBio.00201-16
Choo JM, Leong LE, Rogers GB (2015) Sample storage conditions significantly influence faecal microbiome profiles. Sci Rep 5:16,350
doi: 10.1038/srep16350
Ewing B, Hillier L, Wendl MC et al (1998) Base-calling of automated sequencer traces using phred. I. Accuracy assessment. Genome Res 8:175–185
doi: 10.1101/gr.8.3.175
Cole JR, Wang Q, Fish JA et al (2014) Ribosomal database project: data and tools for high throughput rRNA analysis. Nucleic Acids Res 42:D633–D642
doi: 10.1093/nar/gkt1244
McDonald D, Clemente JC, Kuczynski J et al (2012) The biological observation matrix (BIOM) format or: how I learned to stop worrying and love the ome-ome. Gigascience 1:7
doi: 10.1186/2047-217X-1-7
Posteraro B, Paroni Sterbini F, Petito V et al (2018) Liver injury, endotoxemia, and their relationship to intestinal microbiota composition in alcohol-preferring rats. Alcohol Clin Exp Res 42:2313–2325
doi: 10.1111/acer.13900
Segata N, Izard J, Waldron L et al (2011) Metagenomic biomarker discovery and explanation. Genome Biol 12:R60
doi: 10.1186/gb-2011-12-6-r60
Rescigno M (2017) The microbiota revolution: excitement and caution. Eur J Immunol 47:1406–1413
doi: 10.1002/eji.201646576
Salter SJ, Cox MJ, Turek EM et al (2014) Reagent and laboratory contamination can critically impact sequence-based microbiome analyses. BMC Biol 12:87
doi: 10.1186/s12915-014-0087-z
Paroni Sterbini F, Palladini A, Masucci L et al (2016) Effects of proton pump inhibitors on the gastric mucosa-associated microbiota in dyspeptic patients. Appl Environ Microbiol 82:6633–6644
doi: 10.1128/AEM.01437-16
Schloss PD, Westcott SL, Ryabin T et al (2009) Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol 75:7537–7541
doi: 10.1128/AEM.01541-09
Caporaso JG, Kuczynski J, Stombaugh J et al (2010) QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7:335–336
doi: 10.1038/nmeth.f.303
Schloss PD (2010) The effects of alignment quality, distance calculation method, sequence filtering, and region on the analysis of 16S rRNA gene-based studies. PLoS Comput Biol 6:e1000844
doi: 10.1371/journal.pcbi.1000844
Dhariwal A, Chong J, Habib S et al (2017) MicrobiomeAnalyst: a web-based tool for comprehensive statistical, visual and meta-analysis of microbiome data. Nucleic Acids Res 45:W180–W188
doi: 10.1093/nar/gkx295

Auteurs

Brunella Posteraro (B)

Dipartimento di Scienze Mediche e Chirurgiche, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy. brunella.posteraro@unicatt.it.

Flavio De Maio (F)

Dipartimento di Scienze Biotecnologiche di Base, Cliniche Intensivologiche e Perioperatorie, Università Cattolica del Sacro Cuore, Rome, Italy.

Antonio Gasbarrini (A)

Dipartimento di Scienze Mediche e Chirurgiche, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.

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Classifications MeSH