SUMMARY A systems level understanding of Gram-positive bacteria is important from both an environmental and health perspective, and is most easily obtained when high-quality, validated genomic resources are available. To this end, we constructed two ordered, barcoded, erythromycin-resistance- and kanamycin-resistance-marked single-gene deletion libraries of the Gram-positive model organism, Bacillus subtilis. The libraries comprise 3968 and 3970 genes, respectively, and overlap in all but four genes. Using these libraries, we update the set of essential genes known for this organism, provide a comprehensive compendium of B. subtilis auxotrophic genes, and identify genes required for utilizing specific carbon and nitrogen sources, as well as those required for growth at low temperature. We report the identification of enzymes catalyzing several missing steps in amino acid biosynthesis. Finally, we describe a suite of high-throughput phenotyping methodologies and apply them to provide a genome-wide analysis of competence and sporulation. Altogether, we provide versatile resources for studying gene function and pathway and network architecture in Gram-positive bacteria.

In this article we present MeDuSa (Multi-Draft based Scaffolder), an algorithm for genome scaffolding. MeDuSa exploits information obtained from a set of (draft or closed) genomes from related organisms to determine the correct order and orientation of the contigs. MeDuSa formalizes the scaffolding problem by means of a combinatorial optimization formulation on graphs and implements an efficient constant factor approximation algorithm to solve it. In contrast to currently used scaffolders, it does not require either prior knowledge on the microrganisms dataset under analysis (e.g. their phylogenetic relationships) or the availability of paired end read libraries. This makes usability and running time two additional important features of our method. Moreover, benchmarks and tests on real bacterial datasets showed that MeDuSa is highly accurate and, in most cases, outperforms traditional scaffolders. The possibility to use MeDuSa on eukaryotic datasets has also been evaluated, leading to interesting results.

Recent developments in sequencing technologies have given the opportunity to sequence many bacterial genomes with limited cost and labor, compared to previous techniques. However, a limiting step of genome sequencing is the finishing process, needed to infer the relative position of each contig and close sequencing gaps. An additional degree of complexity is given by bacterial species harboring more than one replicon, which are not contemplated by the currently available programs. The availability of a large number of bacterial genomes allows geneticists to use complete genomes (possibly from the same species) as templates for contigs mapping.Here we present CONTIGuator, a software tool for contigs mapping over a reference genome which allows the visualization of a map of contigs, underlining loss and/or gain of genetic elements and permitting to finish multipartite genomes. The functionality of CONTIGuator was tested using four genomes, demonstrating its improved performances compared to currently available programs.Our approach appears efficient, with a clear visualization, allowing the user to perform comparative structural genomics analysis on draft genomes. CONTIGuator is a Python script for Linux environments and can be used on normal desktop machines and can be downloaded from http://contiguator.sourceforge.net.

Bacterial metabolism plays a fundamental role in gut microbiota ecology and host-microbiome interactions. Yet the metabolic capabilities of most gut bacteria have remained unknown. Here we report growth characteristics of 96 phylogenetically diverse gut bacterial strains across 4 rich and 15 defined media. The vast majority of strains (76) grow in at least one defined medium, enabling accurate assessment of their biosynthetic capabilities. These do not necessarily match phylogenetic similarity, thus indicating a complex evolution of nutritional preferences. We identify mucin utilizers and species inhibited by amino acids and short-chain fatty acids. Our analysis also uncovers media for in vitro studies wherein growth capacity correlates well with in vivo abundance. Further value of the underlying resource is demonstrated by correcting pathway gaps in available genome-scale metabolic models of gut microorganisms. Together, the media resource and the extracted knowledge on growth abilities widen experimental and computational access to the gut microbiota.

An understanding of why certain Acinetobacter species are more successful in causing nosocomial infections, transmission and epidemic spread in healthcare institutions compared with other species is lacking. We used genomic, phenotypic and virulence studies to identify differences between Acinetobacter species. Fourteen strains representing nine species were examined. Genomic analysis of six strains showed that the A. baumannii core genome contains many genes important for diverse metabolism and survival in the host. Most of the A. baumannii core genes were also present in one or more of the less clinically successful species. In contrast, when the accessory genome of an individual A. baumannii strain was compared to a strain of a less successful species (A. calcoaceticus RUH2202), many operons with putative virulence function were found to be present only in the A. baumannii strain, including the csu operon, the acinetobactin chromosomal cluster, and bacterial defence mechanisms. Phenotype microarray analysis showed that compared to A. calcoaceticus (RUH2202), A. baumannii ATCC 19606T was able to utilise nitrogen sources more effectively and was more tolerant to pH, osmotic and antimicrobial stress. Virulence differences were also observed, with A. baumannii ATCC 19606T, A. pittii SH024, and A. nosocomialis RUH2624 persisting and forming larger biofilms on human skin than A. calcoaceticus. A. baumannii ATCC 19606T and A. pittii SH024 were also able to survive in a murine thigh infection model, whereas the other two species were eradicated. The current study provides important insights into the elucidation of differences in clinical relevance among Acinetobacter species.

SummaryGenome-wide association studies (GWAS) in microbes have different challenges to GWAS in eukaryotes. These have been addressed by a number of different methods. pyseer brings these techniques together in one package tailored to microbial GWAS, allows greater flexibility of the input data used, and adds new methods to interpret the association results.Availability and implementation pyseer is written in python and is freely available at https://github.com/mgalardini/pyseer, or can be installed through pip. Documentation and a tutorial are available at http://pyseer.readthedocs.io.Supplementary information Supplementary data are available at Bioinformatics online.

The genome of about 10% of bacterial species is divided among two or more large chromosome-sized replicons. The contribution of each replicon to the microbial life cycle (for example, environmental adaptations and/or niche switching) remains unclear. Here we report a genome-scale metabolic model of the legume symbiont Sinorhizobium meliloti that is integrated with carbon utilization data for 1,500 genes with 192 carbon substrates. Growth of S. meliloti is modelled in three ecological niches (bulk soil, rhizosphere and nodule) with a focus on the role of each of its three replicons. We observe clear metabolic differences during growth in the tested ecological niches and an overall reprogramming following niche switching. In silico examination of the inferred fitness of gene deletion mutants suggests that secondary replicons evolved to fulfil a specialized function, particularly host-associated niche adaptation. Thus, genes on secondary replicons might potentially be manipulated to promote or suppress host interactions for biotechnological purposes.

Bacteria belonging to the genera Dickeya and Pectobacterium are responsible for significant economic losses in a wide variety of crops and ornamentals. During last years, increasing losses in potato production have been attributed to the appearance of Dickeya solani. The D. solani strains investigated so far share genetic homogeneity, although different virulence levels were observed among strains of various origins. The purpose of this study was to investigate the genetic traits possibly related to the diverse virulence levels by means of comparative genomics. First, we developed a new genome assembly pipeline which allowed us to complete the D. solani genomes. Four de novo sequenced and ten publicly available genomes were used to identify the structure of the D. solani pangenome, in which 74.8 and 25.2% of genes were grouped into the core and dispensable genome, respectively. For D. solani panregulon analysis, we performed a binding site prediction for four transcription factors, namely CRP, KdgR, PecS and Fur, to detect the regulons of these virulence regulators. Most of the D. solani potential virulence factors were predicted to belong to the accessory regulons of CRP, KdgR, and PecS. Thus, some differences in gene expression could exist between D. solani strains. The comparison between a highly and a low virulent strain, IFB0099 and IFB0223, respectively, disclosed only small differences between their genomes but significant differences in the production of virulence factors like pectinases, cellulases and proteases, and in their mobility. The D. solani strains also diverge in the number and size of prophages present in their genomes. Another relevant difference is the disruption of the adhesin gene fhaB2 in the highly virulent strain. Strain IFB0223, which has a complete adhesin gene, is less mobile and less aggressive than IFB0099. This suggests that in this case, mobility rather than adherence is needed in order to trigger disease symptoms. This study highlights the utility of comparative genomics in predicting D. solani traits involved in the aggressiveness of this emerging plant pathogen.