BackgroundThe inflammatory bowel diseases (IBD) Crohn's disease and ulcerative colitis result from alterations in intestinal microbes and the immune system. However, the precise dysfunctions of microbial metabolism in the gastrointestinal microbiome during IBD remain unclear. We analyzed the microbiota of intestinal biopsies and stool samples from 231 IBD and healthy subjects by 16S gene pyrosequencing and followed up a subset using shotgun metagenomics. Gene and pathway composition were assessed, based on 16S data from phylogenetically-related reference genomes, and associated using sparse multivariate linear modeling with medications, environmental factors, and IBD status.ResultsFirmicutes and Enterobacteriaceae abundances were associated with disease status as expected, but also with treatment and subject characteristics. Microbial function, though, was more consistently perturbed than composition, with 12% of analyzed pathways changed compared with 2% of genera. We identified major shifts in oxidative stress pathways, as well as decreased carbohydrate metabolism and amino acid biosynthesis in favor of nutrient transport and uptake. The microbiome of ileal Crohn's disease was notable for increases in virulence and secretion pathways.ConclusionsThis inferred functional metagenomic information provides the first insights into community-wide microbial processes and pathways that underpin IBD pathogenesis.

To the Editor: MetaPhlAn (metagenomic phylogenetic analysis) 1 is a method for characterizing the taxonomic profiles of whole-metagenome shotgun (WMS) samples that has been used successfully in large-scale microbial community studies 2,3 . This work complements the original species-level profiling method with a system for eukaryotic and viral quantitation, strain-level identification and strain tracking. These and other extensions make the MetaPhlAn2 computational package (http://segatalab. cibio.unitn.it/tools/metaphlan2/ and Supplementary Software) an efficient tool for mining WMS samples.Our method infers the presence and read coverage of cladespecific markers to unequivocally detect the taxonomic clades present in a microbiome sample and estimate their relative abundance 1 . MetaPhlAn2 includes an expanded set of ~1 million markers (184 ± 45 for each bacterial species) from >7,500 species (Supplementary Tables 1-3), based on the approximately tenfold increase in the number of sequenced genomes in the past 2 years. Subspecies markers enable strain-level analyses, and quasi-markers improve accuracy and allow the detection of viruses and eukaryotic microbes (a full list of additions is provided in Supplementary Notes 1-3 and Supplementary Fig. 1).We validated MetaPhlAn2 using 24 synthetic metagenomes comprising 656 million reads and 1,295 species (Supplementary Note 4 and Supplementary Table 4). MetaPhlAn2 proved more accurate (average correlation: 0.95 ± 0.05) than mOTU 4 and Kraken 5 (0.80 ± 0.21 and 0.75 ± 0.22, respectively) ( Fig. 1a, Supplementary Figs. 2-9 and Supplementary Tables 5-11),with fewer false positives (an average of 10, compared with 22 and 23 for mOTU and Kraken, respectively) and false negatives (an average of 12, compared with 27 for the other two methods), even when including genomes that were absent from the reference database (Supplementary Note 4). With the adoption of the BowTie2 fast mapper and support for parallelism, MetaPhlAn2 is more than ten times faster than MetaPhlAn, and its speed is comparable to that of other tested approaches ( Supplementary Fig. 10).We applied MetaPhlAn2 to four elbow-skin samples that we sequenced from three subjects (Fig. 1b, Supplementary Note 5 and Supplementary Table 12). Our data showed that Propionibacterium acnes and Staphylococcus epidermidis dominated these sites, in agreement with expected genus-level results 6 , while providing species-level resolution. Together with these core species, we found Malassezia globosa in 93.65% of samples and confirmed it by coverage analysis (Supplementary Fig. 11). Although M. globosa is a known colonizer of the skin, its metagenomic characterization highlights the ability of MetaPhlAn2 to identify non-prokaryotic species. Phages (e.g., for Propionibacterium) and double-stranded DNA viruses of the Polyomavirus genus were also consistently detected. We subsequently profiled the whole set of 982 samples from other body sites from the Human Microbiome Project (HMP), including 219 samples sequenced after the initi...