Gut microbiota and body composition in anorexia nervosa inpatients in comparison to athletes, overweight, obese, and normal weight controls

High-throughput sequencing technologies have strongly impacted microbiology, providing a rapid and cost-effective way of generating draft genomes and exploring microbial diversity. However, sequences obtained from impure nucleic acid preparations may contain DNA from sources other than the sample. Those sequence contaminations are a serious concern to the quality of the data used for downstream analysis, causing misassembly of sequence contigs and erroneous conclusions. Therefore, the removal of sequence contaminants is a necessary and required step for all sequencing projects. We developed DeconSeq, a robust framework for the rapid, automated identification and removal of sequence contamination in longer-read datasets ( 150 bp mean read length). DeconSeq is publicly available as standalone and web-based versions. The results can be exported for subsequent analysis, and the databases used for the web-based version are automatically updated on a regular basis. DeconSeq categorizes possible contamination sequences, eliminates redundant hits with higher similarity to non-contaminant genomes, and provides graphical visualizations of the alignment results and classifications. Using DeconSeq, we conducted an analysis of possible human DNA contamination in 202 previously published microbial and viral metagenomes and found possible contamination in 145 (72%) metagenomes with as high as 64% contaminating sequences. This new framework allows scientists to automatically detect and efficiently remove unwanted sequence contamination from their datasets while eliminating critical limitations of current methods. DeconSeq's web interface is simple and user-friendly. The standalone version allows offline analysis and integration into existing data processing pipelines. DeconSeq's results reveal whether the sequencing experiment has succeeded, whether the correct sample was sequenced, and whether the sample contains any sequence contamination from DNA preparation or host. In addition, the analysis of 202 metagenomes demonstrated significant contamination of the non-human associated metagenomes, suggesting that this method is appropriate for screening all metagenomes. DeconSeq is available at http://deconseq.sourceforge.net/.

The recent introduction of massively parallel pyrosequencers allows rapid, inexpensive analysis of microbial community composition using 16S ribosomal RNA (rRNA) sequences. However, a major challenge is to design a workflow so that taxonomic information can be accurately and rapidly assigned to each read, so that the composition of each community can be linked back to likely ecological roles played by members of each species, genus, family or phylum. Here, we use three large 16S rRNA datasets to test whether taxonomic information based on the full-length sequences can be recaptured by short reads that simulate the pyrosequencer outputs. We find that different taxonomic assignment methods vary radically in their ability to recapture the taxonomic information in full-length 16S rRNA sequences: most methods are sensitive to the region of the 16S rRNA gene that is targeted for sequencing, but many combinations of methods and rRNA regions produce consistent and accurate results. To process large datasets of partial 16S rRNA sequences obtained from surveys of various microbial communities, including those from human body habitats, we recommend the use of Greengenes or RDP classifier with fragments of at least 250 bases, starting from one of the primers R357, R534, R798, F343 or F517.

The human gut is home to trillions of microbes, thousands of bacterial phylotypes, as well as hydrogen-consuming methanogenic archaea. Studies in gnotobiotic mice indicate that Methanobrevibacter smithii, the dominant archaeon in the human gut ecosystem, affects the specificity and efficiency of bacterial digestion of dietary polysaccharides, thereby influencing host calorie harvest and adiposity. Metagenomic studies of the gut microbial communities of genetically obese mice and their lean littermates have shown that the former contain an enhanced representation of genes involved in polysaccharide degradation, possess more archaea, and exhibit a greater capacity to promote adiposity when transplanted into germ-free recipients. These findings have led to the hypothesis that M. smithii may be a therapeutic target for reducing energy harvest in obese humans. To explore this possibility, we have sequenced its 1,853,160-bp genome and compared it to other human gut-associated M. smithii strains and other Archaea. We have also examined M. smithii's transcriptome and metabolome in gnotobiotic mice that do or do not harbor Bacteroides thetaiotaomicron, a prominent saccharolytic bacterial member of our gut microbiota. Our results indicate that M. smithii is well equipped to persist in the distal intestine through (i) production of surface glycans resembling those found in the gut mucosa, (ii) regulated expression of adhesin-like proteins, (iii) consumption of a variety of fermentation products produced by saccharolytic bacteria, and (iv) effective competition for nitrogenous nutrient pools. These findings provide a framework for designing strategies to change the representation and/or properties of M. smithii in the human gut microbiota.