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 þ 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.

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.

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.

SummaryThe ability of bacteria to adapt to diverse environmental conditions is well-known. The process of bacterial adaptation to a niche has been linked to large changes in the genome content, showing that many bacterial genomes reflect the constraints imposed by their habitat. However, some highly versatile bacteria are found in diverse habitats that almost share nothing in common. Lactobacillus plantarum is a lactic acid bacterium that is found in a large variety of habitat. With the aim of unravelling the link between evolution and ecological versatility of L. plantarum, we analysed the genomes of 54 L. plantarum strains isolated from different environments. Comparative genome analysis identified a high level of genomic diversity and plasticity among the strains analysed. Phylogenomic and functional divergence studies coupled with gene-trait matching analyses revealed a mixed distribution of the strains, which was uncoupled from their environmental origin. Our findings revealed the absence of specific genomic signatures marking adaptations of L. plantarum towards the diverse habitats it is associated with. This suggests fundamentally similar trends of genome evolution in L. plantarum, which occur in a manner that is apparently uncoupled from ecological constraint and reflects the nomadic lifestyle of this species.

BackgroundProbiotics 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 FindingsIn 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).ConclusionComparative genome hybridization led to the identification of gene loci in L. plantarum WCFS1 that modulate the immune response of DCs.

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.

BackgroundBacterial cell surface-associated polysaccharides are involved in the interactions of bacteria with their environment and play an important role in the communication between pathogenic bacteria and their host organisms. Cell surface polysaccharides of probiotic species are far less well described. Therefore, improved knowledge on these molecules is potentially of great importance to understand the strain-specific and proposed beneficial modes of probiotic action.ResultsThe Lactobacillus plantarum WCFS1 genome encodes 4 clusters of genes that are associated with surface polysaccharide production. Two of these clusters appear to encode all functions required for capsular polysaccharide formation (cps2A-J and cps4A-J), while the remaining clusters are predicted to lack genes encoding chain-length control functions and a priming glycosyl-transferase (cps1A-I and cps3A-J). We constructed L. plantarum WCFS1 gene deletion mutants that lack individual (Δcps1A-I, Δcps2A-J, Δcps3A-J and Δcps4A-J) or combinations of cps clusters (Δcps1A-3J and Δcps1A-3I, Δcps4A-J) and assessed the genome wide impact of these mutations by transcriptome analysis. The cps cluster deletions influenced the expression of variable gene sets in the individual cps cluster mutants, but also considerable numbers of up- and down-regulated genes were shared between mutants in cps cluster 1 and 2, as well as between mutant in cps clusters 3 and 4. Additionally, the composition of overall cell surface polysaccharide fractions was altered in each mutant strain, implying that despite the apparent incompleteness of cps1A-I and cps3A-J, all clusters are active and functional in L. plantarum. The Δcps1A-I strain produced surface polysaccharides in equal amounts as compared to the wild-type strain, while the polysaccharides were characterized by a reduced molar mass and the lack of rhamnose. The mutants that lacked functional copies of cps2A-J, cps3A-J or cps4A-J produced decreased levels of surface polysaccharides, whereas the molar mass and the composition of polysaccharides was not affected by these cluster mutations. In the quadruple mutant, the amount of surface polysaccharides was strongly reduced. The impact of the cps cluster mutations on toll-like receptor (TLR)-mediated human nuclear factor (NF)-κB activation in host cells was evaluated using a TLR2 reporter cell line. In comparison to a L. plantarum wild-type derivative, TLR2 activation remained unaffected by the Δcps1A-I and Δcps3A-J mutants but appeared slightly increased after stimulation with the Δcps2A-J and Δcps4A-J mutants, while the Δcps1A-3J and Δcps1A-3J, Δcps4A-J mutants elicited the strongest responses and clearly displayed enhanced TLR2 signaling.ConclusionsOur study reveals that modulation of surface glycan characteristics in L. plantarum highlights the role of these molecules in shielding of cell envelope embedded host receptor ligands. Although the apparently complete cps clusters (cps2A-J and cps4A-J) contributed individually to this shielding, the removal of all cps cluste...

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.