Hassouneh Sayf Al-Deen, Loftus Mark, Yooseph Shibu
Burnett School of Biomedical Sciences, Genomics and Bioinformatics Cluster, University of Central Florida, Orlando, FL, United States.
Department of Computer Science, Genomics and Bioinformatics Cluster, University of Central Florida, Orlando, FL, United States.
Front Microbiol. 2021 Jul 19;12:673632. doi: 10.3389/fmicb.2021.673632. eCollection 2021.
Inflammatory bowel disease (IBD) is a chronic disease of the gastrointestinal tract that is often characterized by abdominal pain, rectal bleeding, inflammation, and weight loss. Many studies have posited that the gut microbiome may play an integral role in the onset and exacerbation of IBD. Here, we present a novel computational analysis of a previously published IBD dataset. This dataset consists of shotgun sequence data generated from fecal samples collected from individuals with IBD and an internal control group. Utilizing multiple external controls, together with appropriate techniques to handle the compositionality aspect of sequence data, our computational framework can identify and corroborate differences in the taxonomic profiles, bacterial association networks, and functional capacity within the IBD gut microbiome. Our analysis identified 42 bacterial species that are differentially abundant between IBD and every control group (one internal control and two external controls) with at least a twofold difference. Of the 42 species, 34 were significantly elevated in IBD, relative to every other control. These 34 species were still present in the control groups and appear to play important roles, according to network centrality and degree, in all bacterial association networks. Many of the species elevated in IBD have been implicated in modulating the immune response, mucin degradation, antibiotic resistance, and inflammation. We also identified elevated relative abundances of protein families related to signal transduction, sporulation and germination, and polysaccharide degradation as well as decreased relative abundance of protein families related to menaquinone and ubiquinone biosynthesis. Finally, we identified differences in functional capacities between IBD and healthy controls, and subsequently linked the changes in the functional capacity to previously published clinical research and to symptoms that commonly occur in IBD.
炎症性肠病(IBD)是一种胃肠道的慢性疾病,其特征通常为腹痛、直肠出血、炎症和体重减轻。许多研究认为,肠道微生物群可能在IBD的发病和加重过程中发挥不可或缺的作用。在此,我们对之前发表的IBD数据集进行了一项新颖的计算分析。该数据集由从IBD患者和一个内部对照组采集的粪便样本中生成的鸟枪法序列数据组成。利用多个外部对照组,并结合适当的技术来处理序列数据的组成性问题,我们的计算框架能够识别并证实IBD肠道微生物群在分类学特征、细菌关联网络和功能能力方面的差异。我们的分析确定了42种细菌,它们在IBD与每个对照组(一个内部对照组和两个外部对照组)之间的丰度存在差异,且差异至少为两倍。在这42种细菌中,相对于其他每个对照组,有34种在IBD中显著升高。根据网络中心性和度数,这34种细菌在所有细菌关联网络中仍然存在,并且似乎发挥着重要作用。许多在IBD中升高的细菌种类与调节免疫反应、粘蛋白降解、抗生素耐药性和炎症有关。我们还发现与信号转导、孢子形成和萌发以及多糖降解相关的蛋白质家族的相对丰度升高,以及与甲基萘醌和泛醌生物合成相关的蛋白质家族的相对丰度降低。最后,我们确定了IBD与健康对照组在功能能力方面的差异,并随后将功能能力的变化与之前发表的临床研究以及IBD中常见的症状联系起来。