Protein catabolism by intestinal bacteria is infamous for releasing many harmful compounds, negatively affecting the health status, both locally and systemically. In a previous study, we enriched in protein degraders the fecal microbiota of five subjects, utilizing a medium containing protein and peptides as sole fermentable substrates and we monitored their evolution by 16S rRNA gene profiling. In the present study, we fused the microbiome data and the data obtained by the analysis of the volatile organic compounds (VOCs) in the headspace of the cultures. Then, we utilized ANOVA simultaneous component analysis (ASCA) to establish a relationship between metabolites and bacteria. In particular, ASCA allowed to separately assess the effect of subject, time, inoculum concentration, and their binary interactions on both microbiome and volatilome data. All the ASCA submodels pointed out a consistent association between indole and Escherichia–Shigella, and the relationship of butyric, 3-methyl butanoic, and benzenepropanoic acids with some bacterial taxa that were major determinants of cultures at 6 h, such as Lachnoclostridiaceae (Lachnoclostridium), Clostridiaceae (Clostridium sensu stricto), and Sutterellaceae (Sutterella and Parasutterella). The metagenome reconstruction with PICRUSt2 and its functional annotation indicated that enrichment in a protein-based medium affected the richness and diversity of functional profiles, in the face of a decrease of richness and evenness of the microbial community. Linear discriminant analysis (LDA) effect size indicated a positive differential abundance (p < 0.05) for the modules of amino acid catabolism that may be at the basis of the changes of VOC profile. In particular, predicted genes encoding functions belonging to the superpathways of ornithine, arginine, and putrescine transformation to GABA and eventually to succinyl-CoA, of methionine degradation, and various routes of breakdown of aromatic compounds yielding succinyl-CoA or acetyl-CoA became significantly more abundant in the metagenome of the bacterial community.

肠道细菌的蛋白质分解代谢因释放许多有害化合物而臭名昭著，对局部和全身的健康状况产生负面影响。在之前的一项研究中，我们利用含有蛋白质和肽的培养基作为唯一的可发酵底物，在蛋白质降解剂中富集了五名受试者的粪便微生物群，并通过 16S rRNA 基因分析监测了它们的进化。在本研究中，我们融合了微生物组数据和通过分析培养物顶部空间中的挥发性有机化合物 (VOC) 获得的数据。然后，我们利用方差分析同时成分分析 (ASCA) 来建立代谢物和细菌之间的关系。特别是，ASCA 允许分别评估受试者、时间、接种物浓度及其二元相互作用对微生物组和挥发性数据的影响。大肠杆菌-志贺氏菌，以及丁酸、3-甲基丁酸和苯丙酸与一些细菌分类群的关系，这些细菌分类群是 6 小时培养的主要决定因素，如毛梭菌科（Lachnoclostridiaceae）。梭菌), 梭菌科 (狭义梭菌), 和 Sutterellaceae (萨特雷拉 和 寄生虫）。使用 PICRUSt2 的宏基因组重建及其功能注释表明，面对微生物群落丰富度和均匀度的降低，基于蛋白质的培养基中的富集会影响功能谱的丰富度和多样性。线性判别分析 (LDA) 效应大小表明正差异丰度 (磷< 0.05）对于可能基于 VOC 分布变化的氨基酸分解代谢模块。特别是，预测的基因编码属于鸟氨酸、精氨酸和腐胺转化为 GABA 并最终转化为琥珀酰辅酶 A、甲硫氨酸降解的超途径的功能，以及产生琥珀酰辅酶 A 或乙酰辅酶 A 的芳香化合物的各种分解途径变得显着在细菌群落的宏基因组中更丰富。