Project description:The intestinal microbiota plays a crucial role in protecting the host from pathogenic microbes, in modulating immunity and in regulating metabolic processes. We use the simplified human intestinal microbiota (SIHUMIx) consisting of eight bacterial species to study potential synergistic effects with a particular focus on detecting novel proteins with less than 100 amino acids (= sProteins), some of which may contribute to regulate the simplified human intestinal microbiota. Although several studies have shown that sProteins carry out a wide range of important functions, they are still often missed in genome annotations, and little is known about their structure and function in individual microbes and especially in microbial communities. In this study, we created a multi-species integrated proteogenomics search database (multi-species iPtgxDB) to enable a comprehensive identification of novel sProteins. Six of the eight SIHUMIx species, for which no complete genomes were available, were first sequenced and de novo assembled. Several proteomics approaches including two earlier optimized sProtein enrichment strategies were applied prior to mass spectrometric analysis to specifically increase the chances for novel sProtein discovery. Searching the MS/MS data against the multi-species iPtgxDB enabled us to identify 31 novel sProteins, of which the expression of 30 was supported by metatranscriptomics data. Using synthetic peptides, we were able to validate the expression of 25 novel sProteins. Importantly, when comparing the expression of these novel sProteins in single strain cultivations to the multi-species community grown in a bioreactor, we found that six of them were only identified in the SIHUMIx community, indicating a possible important role of sProteins in the organization of microbial communities. Furthermore, in silico prediction suggested that two of these novel sProteins have a potential antimicrobial function. We outline an integrated experimental and bioinformatics workflow for the discovery of novel sProteins in microbial communities that can be generically applied to other microbial communities. The further analysis of novel sProteins uniquely expressed in the multi-species community is expected to enable new insights into the structure, regulation and function of bacterial communities such as those of the human intestinal tract.

Project description: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, fluoroxypyr, 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.

Project description:Per- and polyfluoroalkyl substances (PFAS) are a very large (thousands of chemicals) category; these substances have important industrial and consumer product applications. PFAS are highly persistent in the environment, and some are known to pose human health hazard. Regulatory agencies worldwide are considering restrictions and outright bans of PFAS; however, little data exists to make informed decisions. Therefore, a prioritization strategy is urgently needed for evaluation of potential hazards of PFAS. Structure-based grouping could expedite selection of PFAS for testing; still, the hypothesis that structure-effect relationships exist requires confirmation. We tested 26 structurally diverse PFAS from 8 groups in two human cell types from organs that are thought to be targets for PFAS. We used human induced pluripotent stem cell-derived hepatocytes and cardiomyocytes and tested concentration-response effects on both cell function and gene expression. Few phenotypic effects were observed in hepatocytes, but negative chronotropy was observed for 8 of 26 PFAS. Substance- and cell-dependent transcriptomic changes were more pronounced; however, little evidence of group-specific effects was observed. In hepatocytes, we found up-regulation of stress-related and extracellular matrix organization pathways, and down-regulation of fat metabolism. In cardiomyocytes, contractility-related pathways were most affected. Using these data, we derived phenotypic and transcriptomic point of departure estimates and compared them to predicted PFAS exposures. The conservative estimates for bioactivity and exposure were used to derive margin-of-exposure (MOE) for each PFAS. We found that most (23 of 26) PFAS had MOE>1. Overall, our data suggests that chemical structure-based grouping of PFAS may not be an appropriate strategy to predict their biological effects. This means that testing of the individual PFAS would be needed for confident decision-making. Our proposed strategy of using two human cell types and considering both phenotypic and transcriptomic effects, combined with dose-response analysis, may be used for prioritization of PFAS.

			Action	DRS
	BPX_d13_1D.raw	Raw
	BPX_d13_1E.raw	Raw
	BPX_d13_1F.raw	Raw
	BPX_d15_1D.raw	Raw
	BPX_d15_1E.raw	Raw

Dataset Information

Chemical mixture effects on the simplified human intestinal microbiota (SIHUMIx): Assessing Bisphenols and PFAS at environmentally realistic concentrations

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets