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. 2018 Mar;3(3):337-346.
doi: 10.1038/s41564-017-0089-z. Epub 2018 Jan 8.

"VSports在线直播" Dynamics of metatranscription in the inflammatory bowel disease gut microbiome

Melanie Schirmer  1   2 , Eric A Franzosa  1   2 , Jason Lloyd-Price  1   2 , Lauren J McIver  1   2 , Randall Schwager  2 , Tiffany W Poon  1 , Ashwin N Ananthakrishnan  3 , Elizabeth Andrews  3 , Gildardo Barron  4 , Kathleen Lake  5 , Mahadev Prasad  6 , Jenny Sauk  3   7 , Betsy Stevens  3 , Robin G Wilson  3 , Jonathan Braun  8 , Lee A Denson  5 , Subra Kugathasan  6   9 , Dermot P B McGovern  4 , Hera Vlamakis  1 , Ramnik J Xavier  10   11   12   13 , Curtis Huttenhower  14   15
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Dynamics of metatranscription in the inflammatory bowel disease gut microbiome (VSports在线直播)

Melanie Schirmer et al. Nat Microbiol. 2018 Mar.

Abstract

Inflammatory bowel disease (IBD) is a group of chronic diseases of the digestive tract that affects millions of people worldwide. Genetic, environmental and microbial factors have been implicated in the onset and exacerbation of IBD. However, the mechanisms associating gut microbial dysbioses and aberrant immune responses remain largely unknown. The integrative Human Microbiome Project seeks to close these gaps by examining the dynamics of microbiome functionality in disease by profiling the gut microbiomes of >100 individuals sampled over a 1-year period. Here, we present the first results based on 78 paired faecal metagenomes and metatranscriptomes, and 222 additional metagenomes from 59 patients with Crohn's disease, 34 with ulcerative colitis and 24 non-IBD control patients. We demonstrate several cases in which measures of microbial gene expression in the inflamed gut can be informative relative to metagenomic profiles of functional potential. First, although many microbial organisms exhibited concordant DNA and RNA abundances, we also detected species-specific biases in transcriptional activity, revealing predominant transcription of pathways by individual microorganisms per host (for example, by Faecalibacterium prausnitzii). Thus, a loss of these organisms in disease may have more far-reaching consequences than suggested by their genomic abundances. Furthermore, we identified organisms that were metagenomically abundant but inactive or dormant in the gut with little or no expression (for example, Dialister invisus). Last, certain disease-specific microbial characteristics were more pronounced or only detectable at the transcript level, such as pathways that were predominantly expressed by different organisms in patients with IBD (for example, Bacteroides vulgatus and Alistipes putredinis). This provides potential insights into gut microbial pathway transcription that can vary over time, inducing phenotypical changes that are complementary to those linked to metagenomic abundances. The study's results highlight the strength of analysing both the activity and the presence of gut microorganisms to provide insight into the role of the microbiome in IBD VSports手机版. .

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Conflict of interest statement

Competing interests

DPBM is consulting for Cidara V体育安卓版. The authors declare no other competing financial interests.

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Figure 1:
Figure 1:. Longitudinal metagenomes and metatranscriptomes in inflammatory bowel disease.
(a) Bi-weekly stool samples were collected from 117 individuals (59 Crohn’s disease (CD), 34 ulcerative colitis (UC), and 24 non-IBD controls) over the course of one year each. The resulting data comprise 78 paired stool metagenomes/metatranscriptomes and 222 additional metagenomes. While most samples are part of short time courses, two long time courses per disease phenotype (with up to 17 time points) were also included. (b) Principal Coordinate Analysis (PCoA) on Bray-Curtis distance at the species level for all 300 metagenomic taxonomic profiles from 117 patients. In addition, 19 species are overlaid where their position represents the species’ weighted average score and indicates that samples in close proximity are likely to contain higher abundances of the respective organism. While the time courses highlight that inter-individual effects dominate the variation in taxonomic composition, longitudinal shifts were also observed, motivating the investigation of inter- and intra-personal dynamic patterns of microbial species.
Figure 2:
Figure 2:. Metatranscriptomic activities assigned to specific microbial species and disease phenotypes
(a) Summary of metagenomic and metatranscriptomic activities across all analyzed pathways as assigned to individual species (n=78). The activity of each species is first averaged within and subsequently across participants for DNA and RNA samples, respectively; only species that were detected in at least 10% of the samples are shown. Comparisons of DNA and RNA pathway levels per species are summarized for each point, with examples expanded in (b) and (c): Parabacteroides merdae (high DNA-RNA correlation, Spearman r=0.85) and Faecalibacterium prausnitzii (low correlation, Spearman r=0.35). Here, each point represents one sample (n=78)., indicating the species’ overall contribution to all pathways in its metagenome and metatranscriptome, including a linear fit with a 95% confidence interval. (d) and (e): Species that exhibited the largest and smallest disease-specific changes, respectively, after repeating the analysis described in (a) for each disease group separately. Results are summarized as triangles for each species connecting vertices representing the values for each disease group (CD n=46, UC n=21, non-IBD n=11). Overall, while functional potential is indicative of functional activity for many microbial organisms, others exhibited low DNA-RNA-correlation or disease-specific differences in functional activity.
Figure 3:
Figure 3:. Comparing species-specific metagenomic functional potential with metatranscriptomic functional activity
(a) Contributional alpha diversity of species represented in DNA (metagenomic) and RNA (metatranscriptomic) pathway profiles, calculated across all 78 paired samples. The mean, first and third quartiles are displayed. Pathways are ordered by the sum of their median DNA- and RNA-level diversity measures. While diversity was generally lower on the transcriptional level, as expected, we also observed that many specialized pathways were contributed by only one or few microbial species. (b) Differences in per-pathway DNA versus RNA contributions of microbial species, each point representing one pathway averaged first within samples from the same patient and subsequently across patients. The mean, first and third quartiles are displayed. Only pathways detected in at least 20% of metagenomic and metatranscriptomic samples (n=78) were included for a particular species, and only species contributing to at least 8 pathways across samples are displayed. Some microbial organisms exhibited a general tendency for over- or under-transcription, while others displayed pathway-specific activity patterns. (c) Example where pathway transcription is dominated by a single species. Relative contributions of the top 20 species in metagenomes (DNA) versus metatranscriptomes (RNA) for the dTDP-L-rhamnose biosynthesis I pathway (n=78). This pathway was one of the most over-transcribed pathways of F. prausnitzii, the species with the largest range in pathway-specific over- and undertranscription.
Figure 4:
Figure 4:. Dynamic changes in IBD-specific metatranscription over time
(a) Relative contribution of organisms to the methylerythritol phosphate pathway I (NONMEVIPP-PWY), including all time points and individuals (n=78).. Overtranscription is visible for A. putredinis in the absence of metagenomic disruption. (b) Relative contribution of organisms to the same pathway, restricted to the samples from one CD patient (M2021) over time. A. putredinis consistently over-transcribed this pathway within this individual. Increases in the HBI of this patient were observed at time points 2 and 4, uniquely where pathway transcription was partially contributed by Bacteroides vulgatus. (c) Differences in per-pathway DNA versus RNA contributions of microbial species across disease phenotypes, each point representing the perimeter of the disease-specific pathway triangles described in Fig. 2d+e. The mean, first and third quartiles are displayed. Only pathways detected in at least 20% of metagenomic and metatranscriptomic samples (n=78) were included for a particular species, and only species contributing to at least 8 pathways across samples are displayed. On average, Bacteroides vulgatus exhibited the largest disease-specific difference. (d) Changes in relative contribution of Bacteroides vulgatus to its transcribed pathways stratified by IBD phenotype. For this organism, IBD-specific dysbioses were particularly pronounced on the transcriptional level, with many pathways upregulated both in UC and in CD.
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References

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