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The ongoing revolution in high-throughput sequencing continues to democratize the ability of small groups of investigators to map the microbial component of the biosphere. In particular, the coevolution of new sequencing platforms and new software tools allows data acquisition and analysis on an unprecedented scale. Here we report the next stage in this coevolutionary arms race, using the Illumina GAIIx platform to sequence a diverse array of 25 environmental samples and three known "mock communities" at a depth averaging 3.1 million reads per sample. We demonstrate excellent consistency in taxonomic recovery and recapture diversity patterns that were previously reported on the basis of metaanalysis of many studies from the literature (notably, the saline/ nonsaline split in environmental samples and the split between host-associated and free-living communities). We also demonstrate that 2,000 Illumina single-end reads are sufficient to recapture the same relationships among samples that we observe with the full dataset. The results thus open up the possibility of conducting large-scale studies analyzing thousands of samples simultaneously to survey microbial communities at an unprecedented spatial and temporal resolution.human microbiome | microbial community analysis | microbial ecology | next-generation sequencing H igh-throughput sequencing technologies have opened new frontiers in microbial community analysis by providing a cost-effective means of identifying the microbial phylotypes that are present in samples. These studies have revolutionized our understanding of the microbial communities in our bodies (1, 2) and on our planet (3-5). This revolution in sequencing technology, combined with the development of advanced computational tools that exploit metadata to relate hundreds of samples to one another in ways that reveal clear biological patterns, has reinvigorated studies of the 16S rRNA gene (6

The role of specific gut microbes in shaping body composition remains unclear. We transplanted fecal microbiota from adult female twin pairs discordant for obesity into germ-free mice fed low-fat mouse chow, as well as diets representing different levels of saturated fat and fruit and vegetable consumption typical of the USA. Increased total body and fat mass, as well as obesity-associated metabolic phenotypes were transmissible with uncultured fecal communities, and with their corresponding fecal bacterial culture collections. Co-housing mice harboring an obese twin’s microbiota (Ob) with mice containing the lean co-twin’s microbiota (Ln) prevented the development of increased body mass and obesity-associated metabolic phenotypes in Ob cagemates. Rescue correlated with invasion of specific members of Bacteroidetes from the Ln microbiota into Ob microbiota, and was diet-dependent. These findings reveal transmissible, rapid and modifiable effects of diet-by-microbiota interactions.

Archaea, primarily Crenarchaeota, are common in soil; however, the structure of soil archaeal communities and the factors regulating their diversity and abundance remain poorly understood. Here, we used barcoded pyrosequencing to comprehensively survey archaeal and bacterial communities in 146 soils, representing a multitude of soil and ecosystem types from across the globe. Relative archaeal abundance, the percentage of all 16S rRNA gene sequences recovered that were archaeal, averaged 2% across all soils and ranged from 0% to 410% in individual soils. Soil C:N ratio was the only factor consistently correlated with archaeal relative abundances, being higher in soils with lower C:N ratios. Soil archaea communities were dominated by just two phylotypes from a constrained clade within the Crenarchaeota, which together accounted for 470% of all archaeal sequences obtained in the survey. As one of these phylotypes was closely related to a previously identified putative ammonia oxidizer, we sampled from two long-term nitrogen (N) addition experiments to determine if this taxon responds to experimental manipulations of N availability. Contrary to expectations, the abundance of this dominant taxon, as well as archaea overall, tended to decline with increasing N. This trend was coupled with a concurrent increase in known N-oxidizing bacteria, suggesting competitive interactions between these groups.

The human microbiome substantially affects many aspects of human physiology, including metabolism, drug interactions and numerous diseases. This realization, coupled with ever-improving nucleotide sequencing technology, has precipitated the collection of diverse data sets that profile the microbiome. In the past 2 years, studies have begun to include sufficient numbers of subjects to provide the power to associate these microbiome features with clinical states using advanced algorithms, increasing the use of microbiome studies both individually and collectively. Here we discuss tools and strategies for microbiome studies, from primer selection to bioinformatics analysis.