Paul Wilmes

Treg induction by a rationally selected mixture of Clostridia strains from the human microbiota

Manipulation of the gut microbiota holds great promise for the treatment of inflammatory and allergic diseases. Although numerous probiotic microorganisms have been identified, there remains a compelling need to discover organisms that elicit more robust therapeutic responses, are compatible with the host, and can affect a specific arm of the host immune system in a well-controlled, physiological manner. Here we use a rational approach to isolate CD4+FOXP3+ regulatory T (Treg)-cell-inducing bacterial strains from the human indigenous microbiota. Starting with a healthy human faecal sample, a sequence of selection steps was applied to obtain mice colonized with human microbiota enriched in Treg-cell-inducing species. From these mice, we isolated and selected 17 strains of bacteria on the basis of their high potency in enhancing Treg cell abundance and inducing important anti-inflammatory molecules—including interleukin-10 (IL-) and inducible T-cell co-stimulator (ICOS)—in Treg cells upon inoculation into germ-free mice. Genome sequencing revealed that the 17 strains fall within clusters IV, XIVa and XVIII of Clostridia, which lack prominent toxins and virulence factors. The 17 strains act as a community to provide bacterial antigens and a TGF-β-rich environment to help expansion and differentiation of Treg cells. Oral administration of the combination of 17 strains to adult mice attenuated disease in models of colitis and allergic diarrhoea. Use of the isolated strains may allow for tailored therapeutic manipulation of human immune disorders.

A Dietary Fiber-Deprived Gut Microbiota Degrades the Colonic Mucus Barrier and Enhances Pathogen Susceptibility

Despite the accepted health benefits of consuming dietary fiber, little is known about the mechanisms by which fiber deprivation impacts the gut microbiota and alters disease risk. Using a gnotobiotic mouse model, in which animals were colonized with a synthetic human gut microbiota composed of fully sequenced commensal bacteria, we elucidated the functional interactions between dietary fiber, the gut microbiota, and the colonic mucus barrier, which serves as a primary defense against enteric pathogens. We show that during chronic or intermittent dietary fiber deficiency, the gut microbiota resorts to host-secreted mucus glycoproteins as a nutrient source, leading to erosion of the colonic mucus barrier. Dietary fiber deprivation, together with a fiber-deprived, mucus-eroding microbiota, promotes greater epithelial access and lethal colitis by the mucosal pathogen, Citrobacter rodentium. Our work reveals intricate pathways linking diet, the gut microbiome, and intestinal barrier dysfunction, which could be exploited to improve health using dietary therapeutics.

Community proteogenomics highlights microbial strain-variant protein expression within activated sludge performing enhanced biological phosphorus removal

Enhanced biological phosphorus removal (EBPR) selects for polyphosphate accumulating microorganisms to achieve phosphate removal from wastewater. We used high-resolution community proteomics to identify key metabolic pathways in ‘Candidatus Accumulibacter phosphatis’ (A. phosphatis)-mediated EBPR and to evaluate the contributions of co-existing strains within the dominant population. Overall, 702 proteins from the A. phosphatis population were identified. Results highlight the importance of denitrification, fatty acid cycling and the glyoxylate bypass in EBPR. Strong similarity in protein profiles under anaerobic and aerobic conditions was uncovered (only 3% of A. phosphatis-associated proteins exhibited statistically significant abundance differences). By comprehensive genome-wide alignment of 13 930 orthologous proteins, we uncovered substantial differences in protein abundance for enzyme variants involved in both core-metabolism and EBPR-specific pathways among the A. phosphatis population. These findings suggest an essential role for genetic diversity in maintaining the stable performance of EBPR systems and, hence, demonstrate the power of integrated cultivation-independent genomics and proteomics for the analysis of complex biotechnological systems.

Metaproteomics provides functional insight into activated sludge wastewater treatment

Background Through identification of highly expressed proteins from a mixed culture activated sludge system this study provides functional evidence of microbial transformations important for enhanced biological phosphorus removal (EBPR). Methodology/Principal Findings A laboratory-scale sequencing batch reactor was successfully operated for different levels of EBPR, removing around 25, 40 and 55 mg/l P. The microbial communities were dominated by the uncultured polyphosphate-accumulating organism “Candidatus Accumulibacter phosphatis”. When EBPR failed, the sludge was dominated by tetrad-forming α-Proteobacteria. Representative and reproducible 2D gel protein separations were obtained for all sludge samples. 638 protein spots were matched across gels generated from the phosphate removing sludges. 111 of these were excised and 46 proteins were identified using recently available sludge metagenomic sequences. Many of these closely match proteins from “Candidatus Accumulibacter phosphatis” and could be directly linked to the EBPR process. They included enzymes involved in energy generation, polyhydroxyalkanoate synthesis, glycolysis, gluconeogenesis, glycogen synthesis, glyoxylate/TCA cycle, fatty acid β oxidation, fatty acid synthesis and phosphate transport. Several proteins involved in cellular stress response were detected. Conclusions/Significance Importantly, this study provides direct evidence linking the metabolic activities of “Accumulibacter” to the chemical transformations observed in EBPR. Finally, the results are discussed in relation to current EBPR metabolic models.

Proteogenomic basis for ecological divergence of closely related bacteria in natural acidophilic microbial communities

Bacterial species concepts are controversial. More widely accepted is the need to understand how differences in gene content and sequence lead to ecological divergence. To address this relationship in ecosystem context, we investigated links between genotype and ecology of two genotypic groups of Leptospirillum group II bacteria in comprehensively characterized, natural acidophilic biofilm communities. These groups share 99.7% 16S rRNA gene sequence identity and 95% average amino acid identity between their orthologs. One genotypic group predominates during early colonization, and the other group typically proliferates in later successional stages, forming distinct patches tens to hundreds of micrometers in diameter. Among early colonizing populations, we observed dominance of five genotypes that differed from each other by the extent of recombination with the late colonizing type. Our analyses suggest that the specific recombinant variant within the early colonizing group is selected for by environmental parameters such as temperature, consistent with recombination as a mechanism for ecological fine tuning. Evolutionary signatures, and strain-resolved expression patterns measured via mass spectrometry–based proteomics, indicate increased cobalamin biosynthesis, (de)methylation, and glycine cleavage in the late colonizer. This may suggest environmental changes within the biofilm during development, accompanied by redirection of compatible solutes from osmoprotectants toward metabolism. Across 27 communities, comparative proteogenomic analyses show that differential regulation of shared genes and expression of a small subset of the ∼15% of genes unique to each genotype are involved in niche partitioning. In summary, the results show how subtle genetic variations can lead to distinct ecological strategies.

Characterization of Extracellular Polymeric Substances from Acidophilic Microbial Biofilms

ABSTRACT We examined the chemical composition of extracellular polymeric substances (EPS) extracted from two natural microbial pellicle biofilms growing on acid mine drainage (AMD) solutions. The EPS obtained from a mid-developmental-stage biofilm (DS1) and a mature biofilm (DS2) were qualitatively and quantitatively compared. More than twice as much EPS was derived from DS2 as from DS1 (approximately 340 and 150 mg of EPS per g [dry weight] for DS2 and DS1, respectively). Composition analyses indicated the presence of carbohydrates, metals, proteins, and minor quantities of DNA and lipids, although the relative concentrations of these components were different for the two EPS samples. EPS from DS2 contained higher concentrations of metals and carbohydrates than EPS from DS1. Fe was the most abundant metal in both samples, accounting for about 73% of the total metal content, followed by Al, Mg, and Zn. The relative concentration profile for these metals resembled that for the AMD solution in which the biofilms grew, except for Si, Mn, and Co. Glycosyl composition analysis indicated that both EPS samples were composed primarily of galactose, glucose, heptose, rhamnose, and mannose, while the relative amounts of individual sugars were substantially different in DS1 and DS2. Additionally, carbohydrate linkage analysis revealed multiply linked heptose, galactose, glucose, mannose, and rhamnose, with some of the glucose in a 4-linked form. These results indicate that the biochemical composition of the EPS from these acidic biofilms is dependent on maturity and is controlled by the microbial communities, as well as the local geochemical environment.

The Complex Exogenous RNA Spectra in Human Plasma: An Interface with Human Gut Biota?

Human plasma has long been a rich source for biomarker discovery. It has recently become clear that plasma RNA molecules, such as microRNA, in addition to proteins are common and can serve as biomarkers. Surveying human plasma for microRNA biomarkers using next generation sequencing technology, we observed that a significant fraction of the circulating RNA appear to originate from exogenous species. With careful analysis of sequence error statistics and other controls, we demonstrated that there is a wide range of RNA from many different organisms, including bacteria and fungi as well as from other species. These RNAs may be associated with protein, lipid or other molecules protecting them from RNase activity in plasma. Some of these RNAs are detected in intracellular complexes and may be able to influence cellular activities under in vitro conditions. These findings raise the possibility that plasma RNAs of exogenous origin may serve as signaling molecules mediating for example the human-microbiome interaction and may affect and/or indicate the state of human health.

VizBin - an application for reference-independent visualization and human-augmented binning of metagenomic data

AbstractBackgroundMetagenomics is limited in its ability to link distinct microbial populations to genetic potential due to a current lack of representative isolate genome sequences. Reference-independent approaches, which exploit for example inherent genomic signatures for the clustering of metagenomic fragments (binning), offer the prospect to resolve and reconstruct population-level genomic complements without the need for prior knowledge.ResultsWe present VizBin, a Java™-based application which offers efficient and intuitive reference-independent visualization of metagenomic datasets from single samples for subsequent human-in-the-loop inspection and binning. The method is based on nonlinear dimension reduction of genomic signatures and exploits the superior pattern recognition capabilities of the human eye-brain system for cluster identification and delineation. We demonstrate the general applicability of VizBin for the analysis of metagenomic sequence data by presenting results from two cellulolytic microbial communities and one human-borne microbial consortium. The superior performance of our application compared to other analogous metagenomic visualization and binning methods is also presented.ConclusionsVizBin can be applied de novo for the visualization and subsequent binning of metagenomic datasets from single samples, and it can be used for the post hoc inspection and refinement of automatically generated bins. Due to its computational efficiency, it can be run on common desktop machines and enables the analysis of complex metagenomic datasets in a matter of minutes. The software implementation is available at https://claczny.github.io/VizBin under the BSD License (four-clause) and runs under Microsoft Windows™, Apple Mac OS X™ (10.7 to 10.10), and Linux.

Generation of genome-scale metabolic reconstructions for 773 members of the human gut microbiota

Genome-scale metabolic models derived from human gut metagenomic data can be used as a framework to elucidate how microbial communities modulate human metabolism and health. We present AGORA (assembly of gut organisms through reconstruction and analysis), a resource of genome-scale metabolic reconstructions semi-automatically generated for 773 human gut bacteria. Using this resource, we identified a defined growth medium for Bacteroides caccae ATCC 34185. We also showed that interactions among modeled species depend on both the metabolic potential of each species and the nutrients available. AGORA reconstructions can integrate either metagenomic or 16S rRNA sequencing data sets to infer the metabolic diversity of microbial communities. AGORA reconstructions could provide a starting point for the generation of high-quality, manually curated metabolic reconstructions. AGORA is fully compatible with Recon 2, a comprehensive metabolic reconstruction of human metabolism, which will facilitate studies of host–microbiome interactions.

The dynamic genetic repertoire of microbial communities

Community genomic data have revealed multiple levels of variation between and within microbial consortia. This variation includes large-scale differences in gene content between ecosystems as well as within-population sequence heterogeneity. In the present review, we focus specifically on how fine-scale variation within microbial and viral populations is apparent from community genomic data. A major unresolved question is how much of the observed variation is due to neutral vs. adaptive processes. Limited experimental data hint that some of this fine-scale variation may be in part functionally relevant, whereas sequence-based and modeling analyses suggest that much of it may be neutral. While methods for interpreting population genomic data are still in their infancy, we discuss current interpretations of existing datasets in the light of evolutionary processes and models. Finally, we highlight the importance of virus–host dynamics in generating and shaping within-population diversity.