Dataset Information

A Robust Metatranscriptomic Technology for Population-Scale Studies of Diet, Gut Microbiome, and Human Health.

ABSTRACT: A functional readout of the gut microbiome is necessary to enable precise control of the gut microbiome's functions, which support human health and prevent or minimize a wide range of chronic diseases. Stool metatranscriptomic analysis offers a comprehensive functional view of the gut microbiome, but despite its usefulness, it has rarely been used in clinical studies due to its complexity, cost, and bioinformatic challenges. This method has also received criticism due to potential intrasample variability, rapid changes, and RNA degradation. Here, we describe a robust and automated stool metatranscriptomic method, called Viomega, which was specifically developed for population-scale studies. Viomega includes sample collection, ambient temperature sample preservation, total RNA extraction, physical removal of ribosomal RNAs (rRNAs), preparation of directional Illumina libraries, Illumina sequencing, taxonomic classification based on a database of >110,000 microbial genomes, and quantitative microbial gene expression analysis using a database of ~100 million microbial genes. We applied this method to 10,000 human stool samples and performed several small-scale studies to demonstrate sample stability and consistency. In summary, Viomega is an inexpensive, high-throughput, automated, and accurate sample-to-result stool metatranscriptomic technology platform for large-scale studies and a wide range of applications.

SUBMITTER: Hatch A

PROVIDER: S-EPMC6791206 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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A Robust Metatranscriptomic Technology for Population-Scale Studies of Diet, Gut Microbiome, and Human Health.

Hatch Andrew A Horne James J Toma Ryan R Twibell Brittany L BL Somerville Kalie M KM Pelle Benjamin B Canfield Kinga P KP Genkin Matvey M Banavar Guruduth G Perlina Ally A Messier Helen H Klitgord Niels N Vuyisich Momchilo M

International journal of genomics 20191001

A functional readout of the gut microbiome is necessary to enable precise control of the gut microbiome's functions, which support human health and prevent or minimize a wide range of chronic diseases. Stool metatranscriptomic analysis offers a comprehensive functional view of the gut microbiome, but despite its usefulness, it has rarely been used in clinical studies due to its complexity, cost, and bioinformatic challenges. This method has also received criticism due to potential intrasample va ...[more]

PMID: 31662956

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Project description:BackgroundThe human gut harbors trillions of microbes that play dynamic roles in health. While the microbiome contributes to many cardiometabolic traits by modulating host inflammation and metabolism, there is an incomplete understanding regarding the extent that and mechanisms by which individual microbes impact risk and development of cardiovascular disease (CVD). The Framingham Heart Study (FHS) is a multi-generational observational study following participants over decades to identify risk factors for CVD by correlating genetic and phenotypic factors with clinical outcomes. As a large-scale population-based cohort with extensive clinical phenotyping, FHS provides a rich landscape to explore the relationships between the gut microbiome and cardiometabolic traits.MethodsWe performed 16S rRNA gene sequencing on stool from 1423 participants of the FHS Generation 3, OMNI2, and New Offspring Spouse cohorts. Data processing and taxonomic assignment were performed with the 16S bioBakery workflow using the UPARSE pipeline. We conducted statistical analyses to investigate trends in overall microbiome composition and diversity in relation to disease states and systematically examined taxonomic associations with a variety of clinical traits, disease phenotypes, clinical blood markers, and medications.ResultsWe demonstrate that overall microbial diversity decreases with increasing 10-year CVD risk and body mass index measures. We link lifestyle factors, especially diet and exercise, to microbial diversity. Our association analyses reveal both known and unreported microbial associations with CVD and diabetes, related prescription medications, as well as many anthropometric and blood test measurements. In particular, we observe a set of microbial species that demonstrate significant associations with CVD risk, metabolic syndrome, and type 2 diabetes as well as a number of shared associations between microbial species and cardiometabolic subphenotypes.ConclusionsThe identification of significant microbial taxa associated with prevalent CVD and diabetes, as well as risk for developing CVD, adds to increasing evidence that the microbiome may contribute to CVD pathogenesis. Our findings support new hypothesis generation around shared microbe-mediated mechanisms that influence metabolic syndrome, diabetes, and CVD risk. Further investigation of the gut microbiomes of CVD patients in a targeted manner may elucidate microbial mechanisms with diagnostic and therapeutic implications.

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Dataset Information

A Robust Metatranscriptomic Technology for Population-Scale Studies of Diet, Gut Microbiome, and Human Health.

Publications

A Robust Metatranscriptomic Technology for Population-Scale Studies of Diet, Gut Microbiome, and Human Health.

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