Many functions in host–microbiota interactions are potentially influenced by intestinal transit times, but little is known about the effects of altered transition times on the composition and functionality of gut microbiota. To analyze these effects, we cultivated the model community SIHUMIx in bioreactors in order to determine the effects of varying transit times (TT) on the community structure and function. After five days of continuous cultivation, we investigated the influence of different medium TT of 12 h, 24 h, and 48 h. For profiling the microbial community, we applied flow cytometric fingerprinting and revealed changes in the community structure of SIHUMIx during the change of TT, which were not associated with changes in species abundances. For pinpointing metabolic alterations, we applied metaproteomics and metabolomics and found, along with shortening the TT, a slight decrease in glycan biosynthesis, carbohydrate, and amino acid metabolism and, furthermore, a reduction in butyrate, methyl butyrate, isobutyrate, valerate, and isovalerate concentrations. Specifically, B. thetaiotaomicron was identified to be affected in terms of butyrate metabolism. However, communities could recover to the original state afterward. This study shows that SIHUMIx showed high structural stability when TT changed—even four-fold. Resistance values remained high, which suggests that TTs did not interfere with the structure of the community to a certain degree.
1 November 2020 in Science of The Total Environment
Glyphosate is the world's most widely used herbicide, and its potential side effects on the intestinal microbiota of various animals, from honeybees to livestock and humans, are currently under discussion. Pigs are among the most abundant livestock animals worldwide and an impact of glyphosate on their intestinal microbiota function can have serious consequences on their health, not to mention the economic effects. Recent studies that addressed microbiota-disrupting effects focused on microbial taxonomy but lacked functional information. Therefore, we chose an experimental design with a short incubation time in which effects on the community structure are not expected, but functional effects can be detected. We cultivated intestinal microbiota derived from pig colon in chemostats and investigated the acute effect of 228 mg/d glyphosate acid equivalents from Roundup® LB plus, a frequently applied glyphosate formulation. The applied glyphosate concentration resembles a worst-case scenario for an 8-9 week-old pig and relates to the maximum residue levels of glyphosate on animal fodder. The effects were determined on the functional level by metaproteomics, targeted and untargeted meta-metabolomics, while variations in community structure were analyzed by 16S rRNA gene profiling and on the single cell level by microbiota flow cytometry. Roundup® LB plus did not affect the community taxonomy or the enzymatic repertoire of the cultivated microbiota in general or on the expression of the glyphosate target enzyme 5-enolpyruvylshikimate-3-phosphate synthase in detail. On the functional level, targeted metabolite analysis of short chain fatty acids (SCFAs), free amino acids and bile acids did not reveal significant changes, whereas untargeted meta-metabolomics did identify some effects on the functional level. This multi-omics approach provides evidence for subtle metabolic effects of Roundup® LB plus under the conditions applied.
The prevalence of inflammatory bowel disease (IBD) is rising globally; however, its etiology is still not fully understood. Patient genetics, immune system, and intestinal microbiota are considered critical factors contributing to IBD. Preclinical animal models are crucial to better understand the importance of individual contributing factors. Among these, the dextran sodium sulfate (DSS) colitis model is the most widely used. DSS treatment induces gut inflammation and dysbiosis. However, its exact mode of action remains unclear. To determine whether DSS treatment induces pathogenic changes in the microbiota, we investigated the microbiota-modulating effects of DSS on murine microbiota in vitro. For this purpose, we cultured murine microbiota from the colon in six replicate continuous bioreactors. Three bioreactors were supplemented with 1% DSS and compared with the remaining PBS-treated control bioreactors by means of microbiota taxonomy and functionality. Using metaproteomics, we did not identify significant changes in microbial taxonomy, either at the phylum or genus levels. No differences in the metabolic pathways were observed. Furthermore, the global metabolome and targeted short-chain fatty acid (SCFA) quantification did not reveal any DSS-related changes. DSS had negligible effects on microbial functionality and taxonomy in vitro in the absence of the host environment. Our results underline that the DSS colitis mouse model is a suitable model to study host-microbiota interactions, which may help to understand how intestinal inflammation modulates the microbiota at the taxonomic and functional levels.
Bisphenol S (BPS) is an industrial chemical used in the process of polymerization of polycarbonate plastics and epoxy resins and thus can be found in various plastic products and thermal papers. The microbiota disrupting effect of BPS on the community structure of the microbiome has already been reported, but little is known on how BPS affects bacterial activity and function. To analyze these effects, we cultivated the simplified human intestinal microbiota (SIHUMIx) in bioreactors at a concentration of 45 µM BPS. By determining biomass, growth of SIHUMIx was followed but no differences during BPS exposure were observed. To validate if the membrane composition was affected, fatty acid methyl esters (FAMEs) profiles were compared. Changes in the individual membrane fatty acid composition could not been described; however, the saturation level of the membranes slightly increased during BPS exposure. By applying targeted metabolomics to quantify short-chain fatty acids (SCFA), it was shown that the activity of SIHUMIx was unaffected. Metaproteomics revealed temporal effect on the community structure and function, showing that BPS has minor effects on the structure or functionality of SIHUMIx.
Traditional kefir, which is claimed for health-promoting properties, is made from natural grain-based kefir, while commercial kefirs are made of defined mixtures of microorganisms. Here, approaches are described how to discriminate commercial and traditional kefirs. These two groups of kefirs were characterized by in-depth analysis on the taxonomic and functional level. Cultivation-independent targeted qPCR as well as next-generation sequencing (NGS) proved a completely different microbial composition in traditional and commercial kefirs. While in the traditional kefirs, Lactobacillus kefiranofaciens was the dominant bacterial species, commercial kefirs were dominated by Lactococcus lactis. Volatile organic compounds (VOCs) analysis using headspace-gas chromatography-ion mobility spectrometry also revealed drastic differences between commercial and traditional kefirs; the former built a separate cluster together with yogurt samples. Lactose and galactose concentrations in commercial kefirs were considerably higher than in traditional kefirs, which is important regarding their health properties for people who have specific intolerances. In summary, the analyzed commercial kefirs do not resemble the microbial community and metabolite characteristics of traditional grain-based kefir. Thus, they may deliver different functional effects to the consumers, which remain to be examined in future studies.
When profiling the human gut microbiome, technical biases introduced by analytical approaches impede translational research, reducing data reliability and study comparability. Here, through a global study involving 23 labs, we analyzed a wide range of sequencing and bioinformatic approaches for the taxonomic profiling of two well-defined DNA reference reagents (RRs) comprised of 20 common gut bacteria. Through both shotgun and 16S rRNA gene amplicon sequencing, we aimed to isolate sources of bias and understand their impact on microbiome profiling accuracy. Importantly, minimum quality criteria (MQC) were established and are used to evaluate profiling performance. We found that the variability of shotgun sequencing data sets was greater than that of 16S rRNA gene amplicon sequencing and isolated sources of bias in wet and dry lab steps, such as sequencing depth, primer and database choices, rarefaction, and 16S copy number adjustment. This study presents well-defined RRs and MQC to combat technical bias, paving the way for reliable and comparable microbiome research. IMPORTANCE: This benchmark paper highlights the true level of variability in microbiome data across the world and across sectors, underscoring the critical need for the use of WHO International DNA Gut Reference Reagents (RRs) to elevate the quality of data in microbiome research. This global study is the first of its kind, revealing the reality of the bias in the field, comprehensively testing methodologies used by leading laboratories across the world, but also providing avenues for workflow optimization, to accelerate innovation and translational research and move the field forward.