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Meta-analyses of studies of the human microbiota

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TLDR
The results show that cross-study comparisons of human microbiota are valuable when the studied parameter has a large effect size, but studies of more subtle effects on the human microbiota require carefully selected control populations and standardized protocols.
Abstract
Our body habitat-associated microbial communities are of intense research interest because of their influence on human health. Because many studies of the microbiota are based on the same bacterial 16S ribosomal RNA (rRNA) gene target, they can, in principle, be compared to determine the relative importance of different disease/physiologic/developmental states. However, differences in experimental protocols used may produce variation that outweighs biological differences. By comparing 16S rRNA gene sequences generated from diverse studies of the human microbiota using the QIIME database, we found that variation in composition of the microbiota across different body sites was consistently larger than technical variability across studies. However, samples from different studies of the Western adult fecal microbiota generally clustered by study, and the 16S rRNA target region, DNA extraction technique, and sequencing platform produced systematic biases in observed diversity that could obscure biologically meaningful compositional differences. In contrast, systematic compositional differences in the fecal microbiota that occurred with age and between Western and more agrarian cultures were great enough to outweigh technical variation. Furthermore, individuals with ileal Crohn's disease and in their third trimester of pregnancy often resembled infants from different studies more than controls from the same study, indicating parallel compositional attributes of these distinct developmental/physiological/disease states. Together, these results show that cross-study comparisons of human microbiota are valuable when the studied parameter has a large effect size, but studies of more subtle effects on the human microbiota require carefully selected control populations and standardized protocols.

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Journal ArticleDOI

The Microbiome in Inflammatory Bowel Disease: Current Status and the Future Ahead

TL;DR: The recent progress in microbiome research is described, from exploratory 16S-based studies, reporting associations of specific organisms with a disease, to more recent studies that have taken a more nuanced view, addressing the function of the microbiota by metagenomic and metabolomic methods.
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Shotgun metagenomics, from sampling to analysis

TL;DR: Computational approaches to overcome the challenges that affect both assembly-based and mapping-based metagenomic profiling, particularly of high-complexity samples or environments containing organisms with limited similarity to sequenced genomes, are needed.
References
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Robert C. Edgar
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TL;DR: UCLUST is a new clustering method that exploits USEARCH to assign sequences to clusters and offers several advantages over the widely used program CD-HIT, including higher speed, lower memory use, improved sensitivity, clustering at lower identities and classification of much larger datasets.
Journal ArticleDOI

Structure, function and diversity of the healthy human microbiome

Curtis Huttenhower, +253 more
- 14 Jun 2012 - 
TL;DR: The Human Microbiome Project Consortium reported the first results of their analysis of microbial communities from distinct, clinically relevant body habitats in a human cohort; the insights into the microbial communities of a healthy population lay foundations for future exploration of the epidemiology, ecology and translational applications of the human microbiome as discussed by the authors.
Journal ArticleDOI

A core gut microbiome in obese and lean twins

TL;DR: The faecal microbial communities of adult female monozygotic and dizygotic twin pairs concordant for leanness or obesity, and their mothers are characterized to address how host genotype, environmental exposure and host adiposity influence the gut microbiome.
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Structure, function and diversity of the healthy human microbiome

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