Abstract

Alterations in the gut microbiome have been associated with various human diseases. Most existing gut microbiome studies stopped at the stage of identifying microbial alterations between diseased or healthy conditions. As inspired by reverse vaccinology (RV), we developed a new strategy called Reverse Microbiomics (RM) that turns this process around: based on the identified microbial alternations, reverse-predicting the molecular mechanisms underlying the disease and microbial alternations. Our RM methodology starts by identifying significantly altered microbiota profiles, performing bioinformatics analysis on the proteomes of the microbiota identified, and finally predicting potential virulence or protective factors relevant to a microbiome-associated disease. As a use case study, this reverse methodology was applied to study the molecular pathogenesis of rheumatoid arthritis (RA), a common autoimmune and inflammatory disease. Those bacteria differentially associated with RA were first identified and annotated from published data and then modeled and classified using the Ontology of Host-Microbiome Interactions (OHMI). Our study identified 14 species increased and 9 species depleted in the gut microbiota of RA patients. Vaxign was used to comparatively analyze 15 genome sequences of the two pairs of species: Gram-negative Prevotella copri (increased) and Prevotella histicola (depleted), as well as Gram-positive Bifidobacterium dentium (increased) and Bifidobacterium bifidum (depleted). In total, 21 auto-antigens were predicted to be related to RA, and five of them were previously reported to be associated with RA with experimental evidence. Furthermore, we identified 94 potential adhesive virulence factors including 24 microbial ABC transporters. While eukaryotic ABC transporters are key RA diagnosis markers and drug targets, we identified, for the first-time, RA-associated microbial ABC transporters and provided a novel hypothesis of RA pathogenesis. Our study showed that RM, by broadening the scope of RV, is a novel and effective strategy to study from bacterial level to molecular level factors and gain further insight into how these factors possibly contribute to the development of microbial alterations under specific diseases.

Highlights

  • Microbiota are widely recognized as the key player in maintaining host health

  • To address the important need for the identification of bacterial alteration and explore molecular mechanisms involved in disease development, we developed the new Reverse Microbiomics (RM) strategy

  • We applied the RM strategy to predict pathogenic auto-antigens and virulence factors associated with rheumatoid arthritis (RA) in the dysbiotic gut microbiota

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Summary

Introduction

Microbiota are widely recognized as the key player in maintaining host health. They have a profound impact on human diseases, including obesity (Baothman et al, 2016), diabetes (Alkanani et al, 2015), cardiovascular diseases (Tang et al, 2017), inflammatory bowel diseases, cancers (Lucas et al, 2017), and autoimmune diseases such as rheumatoid arthritis (Holmdahl et al, 2014). Dysbiosis represents an altered balance of protective and detrimental commensals that are associated with disease development. It is frequently characterized by enrichment or depletion of bacteria or fungi (Forbes et al, 2018; Huh and Roh, 2020). Recent microbiome studies have detected many bacterial alterations in various host conditions, which might contribute to the formation of dysbiosis (Logan et al, 2016; Colquhoun et al, 2020). It remains a huge challenge to systematically analyze and convert microbiome data into meaningful biological insights

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