Multi-omics Comparative Analysis Reveals Multiple Layers of Host Signaling Pathway Regulation by the Gut Microbiota

Manes, Nathan P.; Shulzhenko, Natalia; Nuccio, Arthur; Azeem, Sara; Morgun, Andrey; Nita‐Lazar, Aleksandra

doi:10.1128/msystems.00107-17

Cited by 21 publications

(14 citation statements)

References 84 publications

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“…We chose to analyze the epitranscriptome in the intestine, and more precisely in the cecum, which is in close contact with the gut microbiota and undergoes profound physiological and morphological changes in the absence of a microbiota 37 . We further included the liver, whose gene expression is also known to be influenced by commensal bacteria 38 . Although the expression of methyltransferases and demethylases was high in the spleen at mRNA and protein levels ( Supplementary Fig.…”

Section: Resultsmentioning

confidence: 99%

Impact of the gut microbiota on the m6A epitranscriptome of mouse cecum and liver

et al. 2020

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The intestinal microbiota modulates host physiology and gene expression via mechanisms that are not fully understood. Here we examine whether host epitranscriptomic marks are affected by the gut microbiota. We use methylated RNA-immunoprecipitation and sequencing (MeRIP-seq) to identify N6-methyladenosine (m 6 A) modifications in mRNA of mice carrying conventional, modified, or no microbiota. We find that variations in the gut microbiota correlate with m 6 A modifications in the cecum, and to a lesser extent in the liver, affecting pathways related to metabolism, inflammation and antimicrobial responses. We analyze expression levels of several known writer and eraser enzymes, and find that the methyltransferase Mettl16 is downregulated in absence of a microbiota, and one of its target mRNAs, encoding S-adenosylmethionine synthase Mat2a, is less methylated. We furthermore show that Akkermansia muciniphila and Lactobacillus plantarum affect specific m 6 A modifications in mono-associated mice. Our results highlight epitranscriptomic modifications as an additional level of interaction between commensal bacteria and their host.

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Section: Resultsmentioning

confidence: 99%

Impact of the gut microbiota on the m6A epitranscriptome of mouse cecum and liver

et al. 2020

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“…Commensals adjust their lifestyle to the host niche that they inhabit. The dynamics of this adaptation process have been elegantly studied at the bacterial population level, taking into consideration the extreme complexity of microbiomes and the challenge of population size (38)(39)(40). Molecular adaptation strategies used by individual microbes have been difficult to resolve in these complex habitats, however.…”

Section: Discussionmentioning

confidence: 99%

Active bacterial modification of the host environment through RNA polymerase II inhibition

Ambite

Filenko

Zaldastanishvili

et al. 2021

Journal of Clinical Investigation

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“…Here, we define an analyte as a biological entity with a name, a numeric value, and a unit of measurement. However, data from a single ome may lack rich functional insight [1] or may miss signals that are present in another ome [2]. Thus, multi-omic studies are increasingly common [3, 4], offering the potential to formulate progressively more comprehensive perspectives on biological processes [5–8].…”

Section: Introductionmentioning

confidence: 99%

VOLARE: visual analysis of disease-associated microbiome-immune system interplay

et al. 2019

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Background: Relationships between specific microbes and proper immune system development, composition, and function have been reported in a number of studies. However, researchers have discovered only a fraction of the likely relationships. "Omic" methodologies such as 16S ribosomal RNA (rRNA) sequencing and time-of-flight mass cytometry (CyTOF) immunophenotyping generate data that support generation of hypotheses, with the potential to identify additional relationships at a level of granularity ripe for further experimentation. Pairwise linear regressions between microbial and host immune features provide one approach for quantifying relationships between "omes", and the differences in these relationships across study cohorts or arms. This approach yields a top table of candidate results. However, the top table alone lacks the detail that domain experts such as microbiologists and immunologists need to vet candidate results for follow-up experiments. Results: To support this vetting, we developed VOLARE (Visualization Of LineAr Regression Elements), a web application that integrates a searchable top table, small in-line graphs illustrating the fitted models, a network summarizing the top table, and on-demand detailed regression plots showing full sample-level detail. We applied VOLARE to three case studies-microbiome:cytokine data from fecal samples in human immunodeficiency virus (HIV), microbiome:cytokine data in inflammatory bowel disease and spondyloarthritis, and microbiome:immune cell data from gut biopsies in HIV. We present both patient-specific phenomena and relationships that differ by disease state. We also analyzed interaction data from system logs to characterize usage scenarios. This log analysis revealed that users frequently generated detailed regression plots, suggesting that this detail aids the vetting of results. Conclusions: Systematically integrating microbe:immune cell readouts through pairwise linear regressions and presenting the top table in an interactive environment supports the vetting of results for scientific relevance. VOLARE allows domain experts to control the analysis of their results, screening dozens of candidate relationships with ease. This interactive environment transcends the limitations of a static top table.

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Multi-omics Comparative Analysis Reveals Multiple Layers of Host Signaling Pathway Regulation by the Gut Microbiota

Cited by 21 publications

References 84 publications

Impact of the gut microbiota on the m6A epitranscriptome of mouse cecum and liver

Impact of the gut microbiota on the m6A epitranscriptome of mouse cecum and liver

Active bacterial modification of the host environment through RNA polymerase II inhibition

VOLARE: visual analysis of disease-associated microbiome-immune system interplay

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