Synthetic gene-regulatory networks in the opportunistic human pathogen Streptococcus pneumoniae

Robin A Sorg, Clement Gallay, Laurye Van Maele, Jean-Claude Sirard, Jan-Willem Veening*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)
49 Downloads (Pure)

Abstract

Streptococcus pneumoniae can cause disease in various human tissues and organs, including the ear, the brain, the blood, and the lung, and thus in highly diverse and dynamic environments. It is challenging to study how pneumococci control virulence factor expression, because cues of natural environments and the presence of an immune system are difficult to simulate in vitro. Here, we apply synthetic biology methods to reverse-engineer gene expression control in S. pneumoniae A selection platform is described that allows for straightforward identification of transcriptional regulatory elements out of combinatorial libraries. We present TetR- and LacI-regulated promoters that show expression ranges of four orders of magnitude. Based on these promoters, regulatory networks of higher complexity are assembled, such as logic AND gates and IMPLY gates. We demonstrate single-copy genome-integrated toggle switches that give rise to bimodal population distributions. The tools described here can be used to mimic complex expression patterns, such as the ones found for pneumococcal virulence factors. Indeed, we were able to rewire gene expression of the capsule operon, the main pneumococcal virulence factor, to be externally inducible (YES gate) or to act as an IMPLY gate (only expressed in absence of inducer). Importantly, we demonstrate that these synthetic gene-regulatory networks are functional in an influenza A virus superinfection murine model of pneumonia, paving the way for in vivo investigations of the importance of gene expression control on the pathogenicity of S. pneumoniae.

Original languageEnglish
Article numberpnas.1920015117
Pages (from-to)27608-27619
Number of pages12
JournalProceedings of the National Academy of Sciences of the United States of America
Volume117
Issue number44
Early online date2020
DOIs
Publication statusPublished - 3-Nov-2020

Keywords

  • Pneumococcus
  • counterselection
  • superinfection
  • synthetic biology
  • toggle switch

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