Molecular probes to diagnose pathoadapatations in bacterial infections

Lead Research Organisation: Durham University
Department Name: Chemistry


Chronic bacterial infections present a significant challenge to the NHS within hospital and social settings and contribute to the growing threat of antimicrobial resistance. Bacteria evolve and diversify within hosts, particularly in immunocompromised individuals, leading to persistent, difficult to manage infections. This process of 'pathoadaptation' leads to phenotypic changes such as altered protein expression, resistance to antimicrobials, or gain or loss of virulence traits. Reliable identification of pathoadaptations is hence crucial for the successful design and treatment of bacterial infections. Currently, pathoadaptations can be identified using molecular omics techniques focussing on gene expression, proteomics or metabolomics. However, these approaches are technically demanding, expensive and time-intensive, highlighting the need for faster diagnostics.

We propose a novel molecular probe-based strategy to rapidly identify epidemiologically important pathotypes based on bacterial surface properties linked to virulence, host colonisation and antimicrobial resistance. In preliminary experiments, we have demonstrated that arrays of fluorescent glycopolymers can differentiate a range of genotypes of a model organism - the opportunistic respiratory pathogen Pseudomonas aeruginosa. Our method can reliably distinguish engineered transposon-insertion mutants differing in their display of virulence factors, and between P. aeruginosa isolates originating from cystic fibrosis (CF) patients, demonstrating the potential of our system to identify pathoadaptations typical for persistent clinical infections.

We will build on this foundation to create comprehensive, multidimensional glycopolymer sensor arrays to differentiate clinical P. aeruginosa pathotypes associated with lung infections. The sensor arrays will be incorporated within fibre-optic technology to characterise pathotypes when grown on surfaces in mixed populations typical for P. aeruginosa lung infections. Our proposed work has a clear translational pathway to clinical use, guided by principles of Public and Patient Involvement and Engagement (PPIE). Besides providing new diagnostic tools for cost-effective and rapid monitoring of bacterial infections, informing treatment strategies including choice of antibiotics, our array technology could be used to diagnose other types of microbial pathogens including respiratory viruses.


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