Wang Haihe, Ong Edison, Kao John Y, Sun Duxin, He Yongqun
Department of Pathogen Biology, Harbin Medical University (Daqing), Daqing, China.
Unit for Laboratory Animal Medicine, University of Michigan, Ann Arbor, MI, United States.
Front Microbiol. 2021 Feb 25;12:633732. doi: 10.3389/fmicb.2021.633732. eCollection 2021.
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 (increased) and (depleted), as well as Gram-positive (increased) and (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.
肠道微生物群的改变与多种人类疾病有关。大多数现有的肠道微生物群研究都停留在识别疾病状态或健康状态之间微生物变化的阶段。受反向疫苗学(RV)的启发,我们开发了一种名为反向微生物组学(RM)的新策略,该策略扭转了这一过程:基于已识别的微生物变化,反向预测疾病和微生物变化背后的分子机制。我们的RM方法首先识别显著改变的微生物群谱,对所识别的微生物群的蛋白质组进行生物信息学分析,最后预测与微生物组相关疾病相关的潜在毒力或保护因子。作为一个案例研究,这种反向方法被应用于研究类风湿性关节炎(RA)的分子发病机制,RA是一种常见的自身免疫性和炎症性疾病。首先从已发表的数据中识别并注释与RA差异相关的细菌,然后使用宿主-微生物组相互作用本体(OHMI)进行建模和分类。我们的研究发现RA患者肠道微生物群中有14种物种增加,9种物种减少。使用Vaxign对两对物种的15个基因组序列进行比较分析:革兰氏阴性菌(增加)和(减少),以及革兰氏阳性菌(增加)和(减少)。总共预测有21种自身抗原与RA相关,其中5种先前已有实验证据表明与RA有关。此外,我们鉴定出94种潜在的黏附毒力因子,包括24种微生物ABC转运蛋白。虽然真核ABC转运蛋白是关键的RA诊断标志物和药物靶点,但我们首次鉴定出与RA相关的微生物ABC转运蛋白,并提出了RA发病机制的新假设。我们的研究表明,RM通过拓宽RV的范围,是一种从细菌水平到分子水平因素进行研究的新颖且有效的策略,能够进一步深入了解这些因素如何可能导致特定疾病下微生物变化的发展。