Pan-genomic analysis of transcriptional modules across Salmonella Typhimurium reveals the regulatory landscape of different strains

Abstract

Salmonella enterica Typhimurium is a serious pathogen that is involved in human nontyphoidal infections. Tackling Typhimurium infections is difficult due to the species' dynamic adaptation to its environment, which is dictated by a complex transcriptional regulatory network (TRN). While traditional biomolecular methods provide characterizations of specific regulators, it is laborious to construct the global TRN structure from this bottom-up approach. Here, we used a machine learning technique to understand the transcriptional signatures of S. enterica Typhimurium from the top down, as a whole and in individual strains. Furthermore, we conducted cross-strain comparison of 6 strains in serovar Typhimurium to investigate similarities and differences in their TRNs with pan-genomic analysis. By decomposing all the publicly available RNA-Seq data of Typhimurium with independent component analysis (ICA), we obtained over 400 independently modulated sets of genes, called iModulons. Through analysis of these iModulons, we 1) discover three transport iModulons linked to antibiotic resistance, 2) describe concerted responses to cationic antimicrobial peptides (CAMPs), 3) uncover evidence towards new regulons, and 4) identify two iModulons linked to bile responses in strain ST4/74. We extend this analysis across the pan-genome to show that strain-specific iModulons 5) reveal different genetic signatures in pathogenicity islands that explain phenotypes and 6) capture the activity of different phages in the studied strains. Using all high-quality publicly-available RNA-Seq data to date, we present a comprehensive, data-driven Typhimurium TRN. It is conceivable that with more high-quality datasets from more strains, the approach used in this study will continue to guide our investigation in understanding the pan-transcriptome of Typhimurium. Interactive dashboards for all gene modules in this project are available at https://imodulondb.org/ to enable browsing for interested researchers.

Coordination of CcpA and CodY Regulators in Staphylococcus aureus USA300 Strains

“…2b ). This iModulon has been enriched in almost all bacteria and archaea for which iModulons have been calculated ( 20 , 22 – 25 ).…”

Proteome allocation is linked to transcriptional regulation through a modularized transcriptome

“…Recent advances in big data analytics have enabled the knowledge-enriched modularization of the transcriptome for various microbial species. 8,[11][12][13][14][15][16][17] Here we investigated if matched datasets of transcriptomes and proteomes could be modularized in the same way to reveal novel relationships between their compositions. Using ICA analysis of matched data sets we found that; 1) the modules of the proteome and the transcriptome are comprised of a similar list of gene products, 2) the modules in the proteome often represent combinations of modules from the transcriptome, 3) known transcriptional and post-translational regulation is reflected in differences between two sets of modules, allowing for knowledge-mapping when interpreting module functions, and 4) through statistical modeling, absolute proteome allocation can be inferred from the transcriptome alone.…”

“…10 iModulons could be knowledge-enriched, thus yielding a fundamental understanding of the composition of the transcriptome and how it changes between conditions. [11][12][13][14][15][16][17] ICA has now been applied to several organisms across the phylogenetic tree. 9 This advance led to discoveries of gene functions, 18 effects of mutations on protein complex regulation, 19 and identifying energetic trade-offs across sample conditions.…”

Coordination of CcpA and CodY regulators in Staphylococcus aureus USA300 strains

“…and genes involved in translation such as infA and fusA which encode translation initiation factor IF-1 and elongation factor G respectively(Figure 2b). This iModulon has been enriched in almost all bacteria and archaea for which iModulons have been calculated 20,[22][23][24][25] .…”