Lactobacillus delbrueckii ssp. lactis and ssp. bulgaricus: a chronicle of evolution in action

Lactobacillus delbrueckii ssp. lactis and ssp. bulgaricus are lactic acid producing bacteria that are largely used in dairy industries, notably in cheese-making and yogurt production. An earlier in-depth study of the first completely sequenced ssp. bulgaricus genome revealed the characteristics of a genome in an active phase of rapid evolution, in what appears to be an adaptation to the milk environment. Here we examine for the first time if the same conclusions apply to the ssp. lactis, and discuss intra- and inter-subspecies genomic diversity in the context of evolutionary adaptation. RESULTS: Both L. delbrueckii ssp. show the signs of reductive evolution through the elimination of superfluous genes, thereby limiting their carbohydrate metabolic capacities and amino acid biosynthesis potential. In the ssp. lactis this reductive evolution has gone less far than in the ssp. bulgaricus. Consequently, the ssp. lactis retained more extended carbohydrate metabolizing capabilities than the ssp. bulgaricus but, due to high intra-subspecies diversity, very few carbohydrate substrates, if any, allow a reliable distinction of the two ssp.. We further show that one of the most important traits, lactose fermentation, of one of the economically most important dairy bacteria, L. delbruecki ssp. bulgaricus, relies on horizontally acquired rather than deep ancestral genes. In this sense this bacterium may thus be regarded as a natural GMO avant la lettre. CONCLUSIONS: The dairy lactic acid producing bacteria L. delbrueckii ssp. lactis and ssp. bulgaricus appear to represent different points on the same evolutionary track of adaptation to the milk environment through the loss of superfluous functions and the acquisition of functions that allow an optimized utilization of milk resources, where the ssp. bulgaricus has progressed further away from the common ancestor

Construction of a dairy microbial genome catalog opens new perspectives for the metagenomic analysis of dairy fermented products

Microbial communities of traditional cheeses are complex and insufficiently characterized. The origin, safety and functional role in cheese making of these microbial communities are still not well understood. Metagenomic analysis of these communities by high throughput shotgun sequencing is a promising approach to characterize their genomic and functional profiles. Such analyses, however, critically depend on the availability of appropriate reference genome databases against which the sequencing reads can be aligned. We built a reference genome catalog suitable for short read metagenomic analysis using a low-cost sequencing strategy. We selected 142 bacteria isolated from dairy products belonging to 137 different species and 67 genera, and succeeded to reconstruct the draft genome of 117 of them at a standard or high quality level, including isolates from the genera Kluyvera, Luteococcus and Marinilactibacillus, still missing from public database. To demonstrate the potential of this catalog, we analysed the microbial composition of the surface of two smear cheeses and one blue-veined cheese, and showed that a significant part of the microbiota of these traditional cheeses was composed of microorganisms newly sequenced in our study. Our study provides data, which combined with publicly available genome references, represents the most expansive catalog to date of cheese-associated bacteria. Using this extended dairy catalog, we revealed the presence in traditional cheese of dominant microorganisms not deliberately inoculated, mainly Gram-negative genera such as Pseudoalteromonas haloplanktis or Psychrobacter immobilis, that may contribute to the characteristics of cheese produced through traditional methods.https://doi.org/10.1186/1471-2164-15-110

Prediction of the intestinal resistome by a three-dimensional structure-based method

The intestinal microbiota is considered to be a major reservoir of antibiotic resistance determinants (ARDs) that could potentially be transferred to bacterial pathogens via mobile genetic elements. Yet, this assumption is poorly supported by empirical evidence due to the distant homologies between known ARDs (mostly from culturable bacteria) and ARDs from the intestinal microbiota. Consequently, an accurate census of intestinal ARDs (that is, the intestinal resistome) has not yet been fully determined. For this purpose, we developed and validated an annotation method (called pairwise comparative modelling) on the basis of a three-dimensional structure (homology comparative modelling), leading to the prediction of 6,095 ARDs in a catalogue of 3.9 million proteins from the human intestinal microbiota. We found that the majority of predicted ARDs (pdARDs) were distantly related to known ARDs (mean amino acid identity 29.8%) and found little evidence supporting their transfer between species. According to the composition of their resistome, we were able to cluster subjects from the MetaHIT cohort (n = 663) into six resistotypes that were connected to the previously described enterotypes. Finally, we found that the relative abundance of pdARDs was positively associated with gene richness, but not when subjects were exposed to antibiotics. Altogether, our results indicate that the majority of intestinal microbiota ARDs can be considered intrinsic to the dominant commensal microbiota and that these genes are rarely shared with bacterial pathogens

Genomic Characterization of the Taylorella Genus

The Taylorella genus comprises two species: Taylorella equigenitalis, which causes contagious equine metritis, and Taylorella asinigenitalis, a closely-related species mainly found in donkeys. We herein report on the first genome sequence of T. asinigenitalis, analyzing and comparing it with the recently-sequenced T. equigenitalis genome. The T. asinigenitalis genome contains a single circular chromosome of 1,638,559 bp with a 38.3% GC content and 1,534 coding sequences (CDS). While 212 CDSs were T. asinigenitalis-specific, 1,322 had orthologs in T. equigenitalis. Two hundred and thirty-four T. equigenitalis CDSs had no orthologs in T. asinigenitalis. Analysis of the basic nutrition metabolism of both Taylorella species showed that malate, glutamate and alpha-ketoglutarate may be their main carbon and energy sources. For both species, we identified four different secretion systems and several proteins potentially involved in binding and colonization of host cells, suggesting a strong potential for interaction with their host. T. equigenitalis seems better-equipped than T. asinigenitalis in terms of virulence since we identified numerous proteins potentially involved in pathogenicity, including hemagluttinin-related proteins, a type IV secretion system, TonB-dependent lactoferrin and transferrin receptors, and YadA and Hep_Hag domains containing proteins. This is the first molecular characterization of Taylorella genus members, and the first molecular identification of factors potentially involved in T. asinigenitalis and T. equigenitalis pathogenicity and host colonization. This study facilitates a genetic understanding of growth phenotypes, animal host preference and pathogenic capacity, paving the way for future functional investigations into this largely unknown genus

Genome Sequence of Taylorella equigenitalis MCE9, the Causative Agent of Contagious Equine Metritis▿

Taylorella equigenitalis is the causative agent of contagious equine metritis (CEM), a sexually transmitted infection of horses. We herein report the genome sequence of T. equigenitalis strain MCE9, isolated in 2005 from the urethral fossa of a 4-year-old stallion in France

Characterization of the gut microbiota by quantitative metagenomics: a promising tool for risk stratification in NAFLD patients

International audienc

Prevalence of streptococci in the intestinal flora

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Quality control of microbiota metagenomics by k-mer analysis

Background: The biological and clinical consequences of the tight interactions between host and microbiota are rapidly being unraveled by next generation sequencing technologies and sophisticated bioinformatics, also referred to as microbiota metagenomics. The recent success of metagenomics has created a demand to rapidly apply the technology to large case–control cohort studies and to studies of microbiota from various habitats, including habitats relatively poor in microbes. It is therefore of foremost importance to enable a robust and rapid quality assessment of metagenomic data from samples that challenge present technological limits (sample numbers and size). Here we demonstrate that the distribution of overlapping k-mers of metagenome sequence data predicts sequence quality as defined by gene distribution and efficiency of sequence mapping to a reference gene catalogue. [br/][br/] Results: We used serial dilutions of gut microbiota metagenomic datasets to generate well-defined high to low quality metagenomes. We also analyzed a collection of 52 microbiota-derived metagenomes. We demonstrate that k-mer distributions of metagenomic sequence data identify sequence contaminations, such as sequences derived from " empty " ligation products. Of note, k-mer distributions were also able to predict the frequency of sequences mapping to a reference gene catalogue not only for the well-defined serial dilution datasets, but also for 52 human gut microbiota derived metagenomic datasets. [br/][br/] Conclusions: We propose that k-mer analysis of raw metagenome sequence reads should be implemented as a first quality assessment prior to more extensive bioinformatics analysis, such as sequence filtering and gene mapping. With the rising demand for metagenomic analysis of microbiota it is crucial to provide tools for rapid and efficient decision making. This will eventually lead to a faster turnaround time, improved analytical quality including sample quality metrics and a significant cost reduction. Finally, improved quality assessment will have a major impact on the robustness of biological and clinical conclusions drawn from metagenomic studies