Multi-target regulation by small RNAs synchronizes gene expression thresholds and may enhance ultrasensitive behavior

PLoS One. 2012;7(8):e42296. doi: 10.1371/journal.pone.0042296. Epub 2012 Aug 21.

Abstract

Cells respond to external cues by precisely coordinating multiple molecular events. Co-regulation may be established by the so-called single-input module (SIM), where a common regulator controls multiple targets. Using mathematical modeling, we compared the ability of SIM architectures to precisely coordinate protein levels despite environmental fluctuations and uncertainties in parameter values. We find that post-transcriptional co-regulation as exemplified by bacterial small RNAs (sRNAs) is particularly robust: sRNA-mediated regulation establishes highly synchronous gene expression thresholds for all mRNA targets without a need for fine-tuning of kinetic parameters. Our analyses reveal that the non-catalytic nature of sRNA action is essential for robust gene expression synchronization, and that sRNA sequestration effects underlie coupling of multiple mRNA pools. This principle also operates in the temporal regime, implying that sRNAs could robustly coordinate the kinetics of mRNA induction as well. Moreover, we observe that multi-target regulation by a small RNA can strongly enhance ultrasensitivity in mRNA expression when compared to the single-target case. Our findings may explain why bacterial small RNAs frequently coordinate all-or-none responses to cellular stress.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Feedback, Physiological
  • Gene Expression Regulation / genetics*
  • Models, Genetic*
  • RNA, Messenger / genetics
  • RNA, Messenger / metabolism
  • RNA, Untranslated / genetics*
  • Transcription, Genetic / genetics

Substances

  • RNA, Messenger
  • RNA, Untranslated

Grant support

This work was supported by the Bundesministerium für Bildung und Forschung (Virtual Liver Network) to SL and through the FORSYS partner program, grant number 0315294 (IMA). JMS acknowledges support by the DFG research training group Computational Systems Biology. This work was further supported by the European Commission, FP7-ICT-2009-4, BACTOCOM, Project Number 248919, to JMS and IMA. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.