Andrea Weisse, andrea.weisse@ed.ac.uk
Thamarai Dorai-Schneiders, thamarai.schneiders@ed.ac.uk
Project Description
Antibiotic resistance poses a global and severe threat to human, animal and planetary health. Typically, resistance arises through genetic mutations or via the acquisition of genes that allow bacteria to resist antibiotics. Transcription factors (TF) are part of the intrinsic response to antibiotic challenge and when upregulated control multiple genes. It has, for example, been shown that the last-line antibiotic, tigecycline, directly selects for enhanced expression of the global regulatory protein RamA.?Importantly, increases in RamA levels are not limited to tigecycline exposure alone but extend to other antibiotics, thereby highlighting the relevance of RamA in the intrinsic resistome.
In this project, we set out to quantitatively characterise the gene regulatory mechanisms of RamA that allow the clinically relevant bacterium Klebsiella pneumoniae to adapt their gene expression machinery to antibiotic challenges. We will analyse transcriptomics data using machine learning and bioinformatics to identify promoter signatures that lead to differential expression of RamA-regulated genes.
