Dataset Information

A tight cold-inducible switch built by coupling thermosensitive transcriptional and proteolytic regulatory parts.

ABSTRACT: Natural organisms have evolved intricate regulatory mechanisms that sense and respond to fluctuating environmental temperatures in a heat- or cold-inducible fashion. Unlike dominant heat-inducible switches, very few cold-inducible genetic switches are available in either natural or engineered systems. Moreover, the available cold-inducible switches still have many shortcomings, including high leaky gene expression, small dynamic range (<10-fold) or broad transition temperature (>10°C). To address these problems, a high-performance cold-inducible switch that can tightly control target gene expression is highly desired. Here, we introduce a tight and fast cold-inducible switch that couples two evolved thermosensitive variants, TFts and TEVts, as well as an additional Mycoplasma florum Lon protease (mf-Lon) to effectively turn-off target gene expression via transcriptional and proteolytic mechanisms. We validated the function of the switch in different culture media and various Escherichia coli strains and demonstrated its tightness by regulating two morphogenetic bacterial genes and expressing three heat-unstable recombinant proteins, respectively. Moreover, the additional protease module enabled the cold-inducible switch to actively remove the pre-existing proteins in slow-growing cells. This work establishes a high-performance cold-inducible system for tight and fast control of gene expression which has great potential for basic research, as well as industrial and biomedical applications.

SUBMITTER: Zheng Y

PROVIDER: S-EPMC6868347 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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A tight cold-inducible switch built by coupling thermosensitive transcriptional and proteolytic regulatory parts.

Zheng Yang Y Meng Fankang F Zhu Zihui Z Wei Weijia W Sun Zhi Z Chen Jinchun J Yu Bo B Lou Chunbo C Chen Guo-Qiang GQ

Nucleic acids research 20191201 21

Natural organisms have evolved intricate regulatory mechanisms that sense and respond to fluctuating environmental temperatures in a heat- or cold-inducible fashion. Unlike dominant heat-inducible switches, very few cold-inducible genetic switches are available in either natural or engineered systems. Moreover, the available cold-inducible switches still have many shortcomings, including high leaky gene expression, small dynamic range (<10-fold) or broad transition temperature (>10°C). To addres ...[more]

PMID: 31750522

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Project description:Antimicrobial resistance (AMR) continues to evolve as a major threat to human health, and new strategies are required for the treatment of AMR infections. Bacteriophages (phages) that kill bacterial pathogens are being identified for use in phage therapies, with the intention to apply these bactericidal viruses directly into the infection sites in bespoke phage cocktails. Despite the great unsampled phage diversity for this purpose, an issue hampering the roll out of phage therapy is the poor quality annotation of many of the phage genomes, particularly for those from infrequently sampled environmental sources. We developed a computational tool called STEP3 to use the "evolutionary features" that can be recognized in genome sequences of diverse phages. These features, when integrated into an ensemble framework, achieved a stable and robust prediction performance when benchmarked against other prediction tools using phages from diverse sources. Validation of the prediction accuracy of STEP3 was conducted with high-resolution mass spectrometry analysis of two novel phages, isolated from a watercourse in the Southern Hemisphere. STEP3 provides a robust computational approach to distinguish specific and universal features in phages to improve the quality of phage cocktails and is available for use at http://step3.erc.monash.edu/. IMPORTANCE In response to the global problem of antimicrobial resistance, there are moves to use bacteriophages (phages) as therapeutic agents. Selecting which phages will be effective therapeutics relies on interpreting features contributing to shelf-life and applicability to diagnosed infections. However, the protein components of the phage virions that dictate these properties vary so much in sequence that best estimates suggest failure to recognize up to 90% of them. We have utilized this diversity in evolutionary features as an advantage, to apply machine learning for prediction accuracy for diverse components in phage virions. We benchmark this new tool showing the accurate recognition and evaluation of phage component parts using genome sequence data of phages from undersampled environments, where the richest diversity of phage still lies.

Dataset Information

A tight cold-inducible switch built by coupling thermosensitive transcriptional and proteolytic regulatory parts.

Publications

A tight cold-inducible switch built by coupling thermosensitive transcriptional and proteolytic regulatory parts.

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