Summary
RNA is common to all organisms. Despite its major function as the coding agent for protein synthesis, an increasing number of regulatory roles have been assigned to RNA. In bacteria, small RNAs (sRNAs) constitute the best-studied class of non-coding regulators estimated to control ~20% of all genes in a given organism. Most sRNAs affect gene expression by base-pairing with multiple target mRNAs resulting in either gene repression or activation. sRNA regulators are modular, versatile, and highly programmable, and thus have gathered momentum as control devices in synthetic biology and biotechnology.
My group has recently established artificial sRNAs as a potent genetic tool to screen, detect, and characterize microbial phenotypes. We have now extended this method by a novel sequencing approach, called LIGseq, allowing us to map sRNA-target interactions at the population level and in a high throughput manner. We have further shown that sRNAs expressed from the 3’ untranslated regions (UTRs) of mRNAs can serve as tuneable autoregulatory elements and thus bear ample possibilities for the design of artificial gene networks. I therefore posit that artificial sRNAs are powerful, yet understudied control elements of the synthetic biology toolbox with largely untapped regulatory potentials.
I thus propose to: 1) exploit artificial sRNAs to investigate the molecular principles underlying target selection and RNA duplex formation by bacterial non-coding RNAs, 2) harness the power of artificial sRNAs to study essential gene functions and the mechanisms underlying antibiotic resistance in bacteria, 3) employ 3’UTR-derived sRNAs as programmable feedback devices in synthetic gene regulatory circuits.
This combined work will generate the molecular framework to employ artificial sRNAs for synthetic biology applications and shed new light on medically relevant processes, such as antibiotic resistance of microbial pathogens.
My group has recently established artificial sRNAs as a potent genetic tool to screen, detect, and characterize microbial phenotypes. We have now extended this method by a novel sequencing approach, called LIGseq, allowing us to map sRNA-target interactions at the population level and in a high throughput manner. We have further shown that sRNAs expressed from the 3’ untranslated regions (UTRs) of mRNAs can serve as tuneable autoregulatory elements and thus bear ample possibilities for the design of artificial gene networks. I therefore posit that artificial sRNAs are powerful, yet understudied control elements of the synthetic biology toolbox with largely untapped regulatory potentials.
I thus propose to: 1) exploit artificial sRNAs to investigate the molecular principles underlying target selection and RNA duplex formation by bacterial non-coding RNAs, 2) harness the power of artificial sRNAs to study essential gene functions and the mechanisms underlying antibiotic resistance in bacteria, 3) employ 3’UTR-derived sRNAs as programmable feedback devices in synthetic gene regulatory circuits.
This combined work will generate the molecular framework to employ artificial sRNAs for synthetic biology applications and shed new light on medically relevant processes, such as antibiotic resistance of microbial pathogens.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101088027 |
| Start date: | 01-11-2023 |
| End date: | 31-10-2028 |
| Total budget - Public funding: | 1 999 913,00 Euro - 1 999 913,00 Euro |
Cordis data
Original description
RNA is common to all organisms. Despite its major function as the coding agent for protein synthesis, an increasing number of regulatory roles have been assigned to RNA. In bacteria, small RNAs (sRNAs) constitute the best-studied class of non-coding regulators estimated to control ~20% of all genes in a given organism. Most sRNAs affect gene expression by base-pairing with multiple target mRNAs resulting in either gene repression or activation. sRNA regulators are modular, versatile, and highly programmable, and thus have gathered momentum as control devices in synthetic biology and biotechnology.My group has recently established artificial sRNAs as a potent genetic tool to screen, detect, and characterize microbial phenotypes. We have now extended this method by a novel sequencing approach, called LIGseq, allowing us to map sRNA-target interactions at the population level and in a high throughput manner. We have further shown that sRNAs expressed from the 3’ untranslated regions (UTRs) of mRNAs can serve as tuneable autoregulatory elements and thus bear ample possibilities for the design of artificial gene networks. I therefore posit that artificial sRNAs are powerful, yet understudied control elements of the synthetic biology toolbox with largely untapped regulatory potentials.
I thus propose to: 1) exploit artificial sRNAs to investigate the molecular principles underlying target selection and RNA duplex formation by bacterial non-coding RNAs, 2) harness the power of artificial sRNAs to study essential gene functions and the mechanisms underlying antibiotic resistance in bacteria, 3) employ 3’UTR-derived sRNAs as programmable feedback devices in synthetic gene regulatory circuits.
This combined work will generate the molecular framework to employ artificial sRNAs for synthetic biology applications and shed new light on medically relevant processes, such as antibiotic resistance of microbial pathogens.
Status
SIGNEDCall topic
ERC-2022-COGUpdate Date
31-07-2023
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