Literature DB >> 24013439

A microbial profiling method for the human microbiota using high-throughput sequencing.

Huei-Hun Elizabeth Tseng1, Meredith A J Hullar, Fei Li, Johanna W Lampe, Richard Sandstrom, Audra K Johnson, Lisa L Strate, Walter L Ruzzo, John Stamatoyannopoulos.   

Abstract

Study of the human microbiota in relation to human health and disease is a rapidly expanding field. To fully understand the complex relationship between the human gut microbiota and disease risks, study designs that capture the variation within and between human subjects at the population level are required, but this has been hampered by the lack of cost-effective methods to characterize this variation. Illumina sequencing is inexpensive and produces millions of reads per run, but it is unclear whether short reads can adequately represent the microbial community of a human host. In this study, we examined the utility of a profiling method, microbial nucleotide signatures (MNS), focused on low-depth sampling of the human microbiota using Ilumina short reads. This method is intended to aid in human population-based studies where large sample sizes are required to adequately capture variation in disease or phenotype differences. We found that, by calculating the nucleotide diversities along the sequenced 16S rRNA gene region, which did not require assembly or phylogenetic identification, we were able to differentiate the gut microbial nucleotide signatures of 9 healthy individuals. When we further subsampled the reads down to 40,000 reads (51 bp long) per sample, the diversity profiles were relatively unchanged. Applying MNS to a public datasets showed that it could differentiate body site differences. The scalability of our approach offers rapid classification of study participants for studies with the sample sizes required for epidemiological studies. Using MNS to classify the microbiome associated with a disease state followed by targeted in-depth sequencing will give a comprehensive understanding of the role of the microbiome in human health.

Entities:  

Year:  2013        PMID: 24013439      PMCID: PMC3764493          DOI: 10.4303/mg/235646

Source DB:  PubMed          Journal:  Metagenomics (Cairo)        ISSN: 2090-5181


  23 in total

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Review 5.  Diagnostics of inflammatory bowel disease.

Authors:  Susanna Nikolaus; Stefan Schreiber
Journal:  Gastroenterology       Date:  2007-11       Impact factor: 22.682

6.  Gut microbiota in human adults with type 2 diabetes differs from non-diabetic adults.

Authors:  Nadja Larsen; Finn K Vogensen; Frans W J van den Berg; Dennis Sandris Nielsen; Anne Sofie Andreasen; Bente K Pedersen; Waleed Abu Al-Soud; Søren J Sørensen; Lars H Hansen; Mogens Jakobsen
Journal:  PLoS One       Date:  2010-02-05       Impact factor: 3.240

7.  QIIME allows analysis of high-throughput community sequencing data.

Authors:  J Gregory Caporaso; Justin Kuczynski; Jesse Stombaugh; Kyle Bittinger; Frederic D Bushman; Elizabeth K Costello; Noah Fierer; Antonio Gonzalez Peña; Julia K Goodrich; Jeffrey I Gordon; Gavin A Huttley; Scott T Kelley; Dan Knights; Jeremy E Koenig; Ruth E Ley; Catherine A Lozupone; Daniel McDonald; Brian D Muegge; Meg Pirrung; Jens Reeder; Joel R Sevinsky; Peter J Turnbaugh; William A Walters; Jeremy Widmann; Tanya Yatsunenko; Jesse Zaneveld; Rob Knight
Journal:  Nat Methods       Date:  2010-04-11       Impact factor: 28.547

8.  Microbial induction of immunity, inflammation, and cancer.

Authors:  Julia B Greer; Stephen John O'Keefe
Journal:  Front Physiol       Date:  2011-01-26       Impact factor: 4.566

9.  The Ribosomal Database Project: improved alignments and new tools for rRNA analysis.

Authors:  J R Cole; Q Wang; E Cardenas; J Fish; B Chai; R J Farris; A S Kulam-Syed-Mohideen; D M McGarrell; T Marsh; G M Garrity; J M Tiedje
Journal:  Nucleic Acids Res       Date:  2008-11-12       Impact factor: 16.971

10.  Exploring microbial diversity and taxonomy using SSU rRNA hypervariable tag sequencing.

Authors:  Susan M Huse; Les Dethlefsen; Julie A Huber; David Mark Welch; David Mark Welch; David A Relman; Mitchell L Sogin
Journal:  PLoS Genet       Date:  2008-11-21       Impact factor: 5.917

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