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Form of work
SalaryGrade UE07: £37,099 - £44,263 per annum (A revised salary range for this grade of £39,347 to £46,974 is planned to take effect from Spring 2024)
College of Science and Engineering / School of Biological Sciences / Institute of Quantitative Biology, Biochemistry and Biotechnology
Full time: 35 hours per week
Fixed Term: from 1st April 2024 – 31st March 2026 (24 months)
We are looking for a driven and enthusiastic post-doctoral researcher interested in working on the post-transcriptional roles of Helix-Turn-Helix transcription factors in an important bacterial pathogen (MRSA).
The Opportunity:
We recently found that many Helix-Turn-Helix domain transcription factors (HTH-TFs) from methicillin-resistant Staphylococcus aureus also globally bind RNA in vivo. Some HTH-TFs have well-established transcriptional roles in regulating MRSA infectivity and antibiotic resistance. Moreover, the transcription activity of numerous HTH-TFs can be controlled by small molecules, making them promising targets for developing novel antimicrobials.
Our data indicate that the regulatory impact of HTH-TFs is much more profound than anticipated, underscoring the need for a thorough characterisation of these proteins. We hypothesise that HTH-TFs post-transcriptionally control a substantial fraction of antibiotic resistance and virulence factors by altering the stability/translation of RNA substrates. RNA may also compete with HTH-TF transcriptional activities.
By integrating state-of-the-art biochemical, structural, and phenotypic approaches, you will obtain detailed mechanistic insights into (i) how key HTH-TFs bind both DNA and RNA molecules, (ii) how small molecule effectors control this activity, and (iii) how these RNA-binding activities impact gene expression during host infection. A detailed understanding of MRSA HTH-TF function and how its nucleic acid binding is regulated may underpin future therapeutic approaches.
Your skills and attributes for success:
Experience in structural and biophysical characterisation of protein-nucleic acid interactions
Experience with analysis of large datasets using Python and/or R
Demonstrated background in RNA Biology research.
Experience in biochemical approaches for studying protein-nucleic acid interactions.
Understanding of co- and post-transcriptional regulation of gene expression.
