Bacterial transcriptional networks consist of hundreds of transcription factors and thousands of promoters. However, the true complexity of transcription in a bacterial pathogen and the effect of the environments encountered during infection remain to be established. We present a simplified approach for global promoter identification in bacteria using RNA-seq-based transcriptomic analyses of 22 distinct infection-relevant environmental conditions. Individual RNA samples were combined to identify most of the 3,838 Salmonella enterica serovar Typhimurium promoters in just two RNA-seq runs. Individual in vitro conditions stimulated characteristic transcriptional signatures, and the suite of 22 conditions induced transcription of 86% of all S. Typhimurium genes. We highlight the environmental conditions that induce the Salmonella pathogenicity islands and present a small RNA expression landscape of 280 sRNAs. This publicly available compendium of environmentally controlled expression of every transcriptional feature of S. Typhimurium constitutes a useful resource for the bacterial research community.
EnteroBase aims to establish a world-class, one-stop, user-friendly, backwards-compatible but forward-looking genome database, EnteroBase—together with a set of web-based tools, EnteroTools—to enable bacteriologists to identify, analyse, quantify and visualize genomic variation principally within the genera:
> Escherichia > Salmonella > the Yersiniae > Moraxella
EnteroBase is populated with over 100,000 of genomic assemblies derived from publicly available complete genomes, sequence read archives and user uploads.
Bowtie 2 is an ultrafast and memory-efficient tool for aligning sequencing reads to long reference sequences. It is particularly good at aligning reads of about 50 up to 100s or 1,000s of characters, and particularly good at aligning to relatively long (e.g. mammalian) genomes. Bowtie 2 indexes the genome with an FM Index to keep its memory footprint small: for the human genome, its memory footprint is typically around 3.2 GB. Bowtie 2 supports gapped, local, and paired-end alignment modes.
PATRIC is the Bacterial Bioinformatics Resource Center, an information system designed to support the biomedical research community’s work on bacterial infectious diseases via integration of vital pathogen information with rich data and analysis tools. PATRIC sharpens and hones the scope of available bacterial phylogenomic data from numerous sources specifically for the bacterial research community, in order to save biologists time and effort when conducting comparative analyses. The freely available PATRIC platform provides an interface for biologists to discover data and information and conduct comprehensive comparative genomics and other analyses in a one-stop shop. PATRIC is a NIH/NIAID-funded project of The University of Chicago with subcontract to the Biocomplexity Institute of Virginia Tech.
Wattam, A.R., D. Abraham, et al. (2014). “PATRIC, the bacterial bioinformatics database and analysis resource.” Nucl Acids Res 42 (D1): D581-D591.
Roary is a high speed stand alone pan genome pipeline, which takes annotated assemblies in GFF3 format (produced by Prokka (Seemann, 2014)) and calculates the pan genome. Using a standard desktop PC, it can analyse datasets with thousands of samples, something which is computationally infeasible with existing methods, without compromising the quality of the results. 128 samples can be analysed in under 1 hour using 1 GB of RAM and a single processor. To perform this analysis using existing methods would take weeks and hundreds of GB of RAM. Roary is not intended for meta-genomics or for comparing extremely diverse sets of genomes.
Andrew J. Page, Carla A. Cummins, Martin Hunt, Vanessa K. Wong, Sandra Reuter, Matthew T. G. Holden, Maria Fookes, Daniel Falush, Jacqueline A. Keane, Julian Parkhill, "Roary: Rapid large-scale prokaryote pan genome analysis", Bioinformatics, 2015;31(22):3691-3693 doi:10.1093/bioinformatics/btv421
SalFoS was created in January 2016 to manage and share data from the Genome Canada Salmonella Syst-OMICS project. The 2498 isolate collection at the heart of this database was assembled with the aim of representing not only the most frequent serotypes of Salmonella as a foodborne pathogen, but also maximal genomic diversity. SalFoS combines the results of genome sequencing with information such as geographic origin, phenotype, previous genotyping, virulence and antibiotic resistance.