人类肠道微生物群是一个复杂的微生物群落,对宿主具有关键功能,包括各种化学品的转化。虽然已经使用单物种模型评估了对微生物的影响,它们在更复杂的微生物群落中的功能作用仍不清楚。在这项研究中,我们研究了在暴露于90种不同的异种生物物质后,在体外生物反应器系统中与96个深孔板组合培养的简化的人类肠道微生物群模型(SIHUMIx)的反应,包括54种植物保护产品和36种食品添加剂和染料,在环境相关的浓度。我们采用元蛋白质组学和代谢组学来评估细菌丰度的变化,短链脂肪酸(SCFA)的生产,和代谢途径的调节。我们的发现揭示了在所有三个类别中,54种植物保护产品中有23种和36种食品添加剂中有28种引起的重大变化。值得注意的亮点包括唑菌酯,氟草素,和乙氧基喹导致主要SCFA:乙酸的浓度大幅降低(log2FC<-0.5),丁酸盐,和丙酸。几种食品添加剂对细菌种类的相对丰度有显著影响;例如,酸性橙7和糖精导致丁酸梭菌减少75%,与对照相比,糖精导致大肠杆菌额外增加2.5倍。此外,两组都表现出各种途径的上调和下调,包括与组氨酸等氨基酸代谢有关的物质,缬氨酸,亮氨酸,和异亮氨酸,以及细菌分泌系统和能量途径,如淀粉,蔗糖,丁酸酯,和丙酮酸代谢。这项研究引入了一种有效的体外技术,该技术可以使用元蛋白质组学和代谢组学对90种化学物质进行高通量筛选简化且定义明确的人类肠道微生物群模型的结构和功能。我们相信这种方法将有助于表征化学-微生物群的相互作用,这对于监管化学风险评估尤其重要。
The human gut microbiota is a complex microbial community with critical functions for the host, including the transformation of various chemicals. While effects on microorganisms has been evaluated using single-species models, their functional effects within more complex microbial communities remain unclear. In this study, we investigated the response of a simplified human gut microbiota model (SIHUMIx) cultivated in an in vitro bioreactor system in combination with 96 deep-well plates after exposure to 90 different xenobiotics, comprising 54 plant protection products and 36 food additives and dyes, at environmentally relevant concentrations. We employed metaproteomics and metabolomics to evaluate changes in bacterial abundances, the production of Short Chain Fatty Acids (SCFAs), and the regulation of metabolic pathways. Our findings unveiled significant changes induced by 23 out of 54 plant protection products and 28 out of 36 food additives across all three categories assessed. Notable highlights include azoxystrobin, fluroxypyr, and ethoxyquin causing a substantial reduction (log2FC < -0.5) in the concentrations of the primary SCFAs: acetate, butyrate, and propionate. Several food additives had significant effects on the relative abundances of bacterial species; for example, acid orange 7 and saccharin led to a 75% decrease in Clostridium butyricum, with saccharin causing an additional 2.5-fold increase in E. coli compared to the control. Furthermore, both groups exhibited up- and down-regulation of various pathways, including those related to the metabolism of amino acids such as histidine, valine, leucine, and isoleucine, as well as bacterial secretion systems and energy pathways like starch, sucrose, butanoate, and pyruvate metabolism. This research introduces an efficient in vitro technique that enables high-throughput screening of the structure and function of a simplified and well-defined human gut microbiota model against 90 chemicals using metaproteomics and metabolomics. We believe this approach will be instrumental in characterizing chemical-microbiota interactions especially important for regulatory chemical risk assessments.