In silico characterisation of stand-alone response regulators of Streptococcus pyogenes

PLoS One. 2020 Oct 19;15(10):e0240834. doi: 10.1371/journal.pone.0240834. eCollection 2020.

Abstract

Bacterial "stand-alone" response regulators (RRs) are pivotal to the control of gene transcription in response to changing cytosolic and extracellular microenvironments during infection. The genome of group A Streptococcus (GAS) encodes more than 30 stand-alone RRs that orchestrate the expression of virulence factors involved in infecting multiple tissues, so causing an array of potentially lethal human diseases. Here, we analysed the molecular epidemiology and biological associations in the coding sequences (CDSs) and upstream intergenic regions (IGRs) of 35 stand-alone RRs from a collection of global GAS genomes. Of the 944 genomes analysed, 97% encoded 32 or more of the 35 tested RRs. The length of RR CDSs ranged from 297 to 1587 nucleotides with an average nucleotide diversity (π) of 0.012, while the IGRs ranged from 51 to 666 nucleotides with average π of 0.017. We present new evidence of recombination in multiple RRs including mga, leading to mga-2 switching, emm-switching and emm-like gene chimerization, and the first instance of an isolate that encodes both mga-1 and mga-2. Recombination was also evident in rofA/nra and msmR loci with 15 emm-types represented in multiple FCT (fibronectin-binding, collagen-binding, T-antigen)-types, including novel emm-type/FCT-type pairings. Strong associations were observed between concatenated RR allele types, and emm-type, MLST-type, core genome phylogroup, and country of sampling. No strong associations were observed between individual loci and disease outcome. We propose that 11 RRs may form part of future refinement of GAS typing systems that reflect core genome evolutionary associations. This subgenomic analysis revealed allelic traits that were informative to the biological function, GAS strain definition, and regional outbreak detection.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Antigens, Bacterial / genetics
  • Bacterial Outer Membrane Proteins / genetics
  • Bacterial Proteins / genetics
  • Carrier Proteins / metabolism
  • Computer Simulation
  • DNA, Bacterial / genetics
  • DNA, Intergenic / metabolism
  • Gene Expression Regulation, Bacterial / genetics*
  • Streptococcal Infections / genetics
  • Streptococcus pyogenes / genetics*
  • Streptococcus pyogenes / metabolism*
  • Virulence Factors / genetics

Substances

  • Antigens, Bacterial
  • Bacterial Outer Membrane Proteins
  • Bacterial Proteins
  • Carrier Proteins
  • DNA, Bacterial
  • DNA, Intergenic
  • Virulence Factors

Grants and funding

SJB received funding for this work in the form of an Australian Government PhD scholarship, which was conducted at the University of the Sunshine Coast.