Michiel Wels

The human small intestinal microbiota is driven by rapid uptake and conversion of simple carbohydrates

The human gastrointestinal tract (GI tract) harbors a complex community of microbes. The microbiota composition varies between different locations in the GI tract, but most studies focus on the fecal microbiota, and that inhabiting the colonic mucosa. Consequently, little is known about the microbiota at other parts of the GI tract, which is especially true for the small intestine because of its limited accessibility. Here we deduce an ecological model of the microbiota composition and function in the small intestine, using complementing culture-independent approaches. Phylogenetic microarray analyses demonstrated that microbiota compositions that are typically found in effluent samples from ileostomists (subjects without a colon) can also be encountered in the small intestine of healthy individuals. Phylogenetic mapping of small intestinal metagenome of three different ileostomy effluent samples from a single individual indicated that Streptococcus sp., Escherichia coli, Clostridium sp. and high G+C organisms are most abundant in the small intestine. The compositions of these populations fluctuated in time and correlated to the short-chain fatty acids profiles that were determined in parallel. Comparative functional analysis with fecal metagenomes identified functions that are overrepresented in the small intestine, including simple carbohydrate transport phosphotransferase systems (PTS), central metabolism and biotin production. Moreover, metatranscriptome analysis supported high level in-situ expression of PTS and carbohydrate metabolic genes, especially those belonging to Streptococcus sp. Overall, our findings suggest that rapid uptake and fermentation of available carbohydrates contribute to maintaining the microbiota in the human small intestine.

Phenotypic and genomic diversity of Lactobacillus plantarum strains isolated from various environmental niches

Lactobacillus plantarum is a ubiquitous microorganism that is able to colonize several ecological niches, including vegetables, meat, dairy substrates and the gastro-intestinal tract. An extensive phenotypic and genomic diversity analysis was conducted to elucidate the molecular basis of the high flexibility and versatility of this species. First, 185 isolates from diverse environments were phenotypically characterized by evaluating their fermentation and growth characteristics. Strains clustered largely together within their particular food niche, but human fecal isolates were scattered throughout the food clusters, suggesting that they originate from the food eaten by the individuals. Based on distinct phenotypic profiles, 24 strains were selected and, together with a further 18 strains from an earlier low-resolution study, their genomic diversity was evaluated by comparative genome hybridization against the reference genome of L. plantarum WCFS1. Over 2000 genes were identified that constitute the core genome of the L. plantarum species, including 121 unique L. plantarum-marker genes that have not been found in other lactic acid bacteria. Over 50 genes unique for the reference strain WCFS1 were identified that were absent in the other L. plantarum strains. Strains of the L. plantarum subspecies argentoratensis were found to lack a common set of 24 genes, organized in seven gene clusters/operons, supporting their classification as a separate subspecies. The results provide a detailed view on phenotypic and genomic diversity of L. plantarum and lead to a better comprehension of niche adaptation and functionality of the organism.

Data mining in the Life Sciences with Random Forest: a walk in the park or lost in the jungle?

In the Life Sciences ‘omics’ data is increasingly generated by different high-throughput technologies. Often only the integration of these data allows uncovering biological insights that can be experimentally validated or mechanistically modelled, i.e. sophisticated computational approaches are required to extract the complex non-linear trends present in omics data. Classification techniques allow training a model based on variables (e.g. SNPs in genetic association studies) to separate different classes (e.g. healthy subjects versus patients). Random Forest (RF) is a versatile classification algorithm suited for the analysis of these large data sets. In the Life Sciences, RF is popular because RF classification models have a high-prediction accuracy and provide information on importance of variables for classification. For omics data, variables or conditional relations between variables are typically important for a subset of samples of the same class. For example: within a class of cancer patients certain SNP combinations may be important for a subset of patients that have a specific subtype of cancer, but not important for a different subset of patients. These conditional relationships can in principle be uncovered from the data with RF as these are implicitly taken into account by the algorithm during the creation of the classification model. This review details some of the to the best of our knowledge rarely or never used RF properties that allow maximizing the biological insights that can be extracted from complex omics data sets using RF.

Identification of genetic loci in Lactobacillus plantarum that modulate the immune response of dendritic cells using comparative genome hybridization.

Background Probiotics can be used to stimulate or regulate epithelial and immune cells of the intestinal mucosa and generate beneficial mucosal immunomodulatory effects. Beneficial effects of specific strains of probiotics have been established in the treatment and prevention of various intestinal disorders, including allergic diseases and diarrhea. However, the precise molecular mechanisms and the strain-dependent factors involved are poorly understood. Methodology/Principal Findings In this study, we aimed to identify gene loci in the model probiotic organism Lactobacillus plantarum WCFS1 that modulate the immune response of host dendritic cells. The amounts of IL-10 and IL-12 secreted by dendritic cells (DCs) after stimulation with 42 individual L. plantarum strains were measured and correlated with the strain-specific genomic composition using comparative genome hybridisation and the Random Forest algorithm. This in silico “gene-trait matching” approach led to the identification of eight candidate genes in the L. plantarum genome that might modulate the DC cytokine response to L. plantarum. Six of these genes were involved in bacteriocin production or secretion, one encoded a bile salt hydrolase and one encoded a transcription regulator of which the exact function is unknown. Subsequently, gene deletions mutants were constructed in L. plantarum WCFS1 and compared to the wild-type strain in DC stimulation assays. All three bacteriocin mutants as well as the transcription regulator (lp_2991) had the predicted effect on cytokine production confirming their immunomodulatory effect on the DC response to L. plantarum. Transcriptome analysis and qPCR data showed that transcript level of gtcA3, which is predicted to be involved in glycosylation of cell wall teichoic acids, was substantially increased in the lp_2991 deletion mutant (44 and 29 fold respectively). Conclusion Comparative genome hybridization led to the identification of gene loci in L. plantarum WCFS1 that modulate the immune response of DCs.

Complete Genome Sequence of Lactococcus lactis subsp. lactis KF147, a Plant-Associated Lactic Acid Bacterium

Lactococcus lactis is a lactic acid bacterium used in the production of many fermented dairy products. We report the complete genome sequence of L. lactis subsp. lactis KF147, a nondairy strain isolated from mung bean sprouts. The circular chromosome of 2,598,144 bp, the largest among the sequenced lactococcal strains, encodes many properties related to adaptation to the plant environment.

Complete resequencing and reannotation of the Lactobacillus plantarum WCFS1 genome.

There is growing interest in the beneficial effects of Lactobacillus plantarum on human health. The genome of L. plantarum WCFS1, first sequenced in 2001, was resequenced using Solexa technology. We identified 116 nucleotide corrections and improved function prediction for nearly 1,200 proteins, with a focus on metabolic functions and cell surface-associated proteins.

Lactobacillus paracasei Comparative Genomics: Towards Species Pan-Genome Definition and Exploitation of Diversity

Lactobacillus paracasei is a member of the normal human and animal gut microbiota and is used extensively in the food industry in starter cultures for dairy products or as probiotics. With the development of low-cost, high-throughput sequencing techniques it has become feasible to sequence many different strains of one species and to determine its “pan-genome”. We have sequenced the genomes of 34 different L. paracasei strains, and performed a comparative genomics analysis. We analysed genome synteny and content, focussing on the pan-genome, core genome and variable genome. Each genome was shown to contain around 2800–3100 protein-coding genes, and comparative analysis identified over 4200 ortholog groups that comprise the pan-genome of this species, of which about 1800 ortholog groups make up the conserved core. Several factors previously associated with host-microbe interactions such as pili, cell-envelope proteinase, hydrolases p40 and p75 or the capacity to produce short branched-chain fatty acids (bkd operon) are part of the L. paracasei core genome present in all analysed strains. The variome consists mainly of hypothetical proteins, phages, plasmids, transposon/conjugative elements, and known functions such as sugar metabolism, cell-surface proteins, transporters, CRISPR-associated proteins, and EPS biosynthesis proteins. An enormous variety and variability of sugar utilization gene cassettes were identified, with each strain harbouring between 25–53 cassettes, reflecting the high adaptability of L. paracasei to different niches. A phylogenomic tree was constructed based on total genome contents, and together with an analysis of horizontal gene transfer events we conclude that evolution of these L. paracasei strains is complex and not always related to niche adaptation. The results of this genome content comparison was used, together with high-throughput growth experiments on various carbohydrates, to perform gene-trait matching analysis, in order to link the distribution pattern of a specific phenotype to the presence/absence of specific sets of genes.

Thioredoxin reductase is a key factor in the oxidative stress response of Lactobacillus plantarum WCFS1

BackgroundThioredoxin (TRX) is a powerful disulfide oxido-reductase that catalyzes a wide spectrum of redox reactions in the cell. The aim of this study is to elucidate the role of the TRX system in the oxidative stress response in Lactobacillus plantarum WCFS1.ResultsWe have identified the trxB1-encoded thioredoxin reductase (TR) as a key enzyme in the oxidative stress response of Lactobacillus plantarum WCFS1.Overexpression of the trxB1 gene resulted in a 3-fold higher TR activity in comparison to the wild-type strain. Subsequently, higher TR activity was associated with an increased resistance towards oxidative stress. We further determined the global transcriptional response to hydrogen peroxide stress in the trxB1-overexpression and wild-type strains grown in continuous cultures. Hydrogen peroxide stress and overproduction of TR collectively resulted in the up-regulation of 267 genes. Additionally, gene expression profiling showed significant differential expression of 27 genes in the trxB1-overexpression strain. Over expression of trxB1 was found to activate genes associated with DNA repair and stress mechanisms as well as genes associated with the activity of biosynthetic pathways for purine and sulfur-containing amino acids. A total of 16 genes showed a response to both TR overproduction and hydrogen peroxide stress. These genes are involved in the purine metabolism, energy metabolism (gapB) as well as in stress-response (groEL, npr2), and manganese transport (mntH2).ConclusionBased on our findings we propose that overproduction of the trxB1-encoded TR in L. plantarum improves tolerance towards oxidative stress. This response coincides with simultaneous induction of a group of 16 transcripts of genes. Within this group of genes, most are associated with oxidative stress response. The obtained crossover between datasets may explain the phenotype of the trxB1-overexpression strain, which appears to be prepared for encountering oxidative stress. This latter property can be used for engineering robustness towards oxidative stress in industrial strains of L. plantarum.

Convergence in probiotic Lactobacillus gut-adaptive responses in humans and mice

Probiotic bacteria provide unique opportunities to study the global responses and molecular mechanisms underlying the effects of gut-associated microorganisms in the human digestive tract. In this study, we show by comparative transcriptome analysis using DNA microarrays that the established probiotic Lactobacillus plantarum 299v specifically adapts its metabolic capacity in the human intestine for carbohydrate acquisition and expression of exopolysaccharide and proteinaceous cell surface compounds. This report constitutes the first application of global gene expression profiling of a commensal microorganism in the human gut. A core L. plantarum transcriptome expressed in the mammalian intestine was also determined through comparisons of L. plantarum 299v activities in humans to those found for L. plantarum WCFS1 in germ-free mice. These results identify the niche-specific adaptations of a dietary microorganism to the intestinal ecosystem and provide novel targets for molecular analysis of microbial–host interactions which affect human health.

LAB-Secretome: a genome-scale comparative analysis of the predicted extracellular and surface-associated proteins of Lactic Acid Bacteria.

BackgroundIn Lactic Acid Bacteria (LAB), the extracellular and surface-associated proteins can be involved in processes such as cell wall metabolism, degradation and uptake of nutrients, communication and binding to substrates or hosts. A genome-scale comparative study of these proteins (secretomes) can provide vast information towards the understanding of the molecular evolution, diversity, function and adaptation of LAB to their specific environmental niches.ResultsWe have performed an extensive prediction and comparison of the secretomes from 26 sequenced LAB genomes. A new approach to detect homolog clusters of secretome proteins (LaCOGs) was designed by integrating protein subcellular location prediction and homology clustering methods. The initial clusters were further adjusted semi-manually based on multiple sequence alignments, domain compositions, pseudogene analysis and biological function of the proteins. Ubiquitous protein families were identified, as well as species-specific, strain-specific, and niche-specific LaCOGs. Comparative analysis of protein subfamilies has shown that the distribution and functional specificity of LaCOGs could be used to explain many niche-specific phenotypes.A comprehensive and user-friendly database LAB-Secretome was constructed to store, visualize and update the extracellular proteins and LaCOGs http://www.cmbi.ru.nl/lab_secretome/. This database will be updated regularly when new bacterial genomes become available.ConclusionsThe LAB-Secretome database could be used to understand the evolution and adaptation of lactic acid bacteria to their environmental niches, to improve protein functional annotation and to serve as basis for targeted experimental studies.