Research projects funded in BristolBridge's third funding round

Three new interdisciplinary pump-priming projects were awarded funds in the third funding round in late May.  The University has kindly awarded BristolBridge funds from its EPSRC Institutional Sponsorship award for Global Challenges. With matched funding from BristolBridge, this funding has been assigned to tackling the global challenge of antimicrobial resistance with relevance to Official Development Assistance (ODA) and some of the projects below (indicated) were funded under this funding stream.


Evaluation of nano-mechanical cantilever-based biosensors as a novel, rapid approach to detect antifungal resistance in pathogenic Candida species 

Mervyn Miles (Physics), Elizabeth Johnson, Mark Fraser and Andy Borman (all Public Health England National Mycology Reference Laboratory, Bristol) and Monica Berry (Physics) 

Antifungal resistance is an increasing problem. Invasive fungal infections caused by Candida spp. continue to provoke substantial morbidity and mortality in immunocompromised patients, and those undergoing invasive procedures. Although accumulating evidence underscores the important role of appropriate antifungal therapy in clinical outcome for patients with candidiasis, in vitro patterns of antifungal susceptibility are known to vary substantially between different Candida species, with intrinsic resistance to antifungal agents in some species, and development of acquired resistance during treatment in others. Currently, susceptibility profiles for individual isolates are generated by laborious culture-based methods to measure minimum inhibitory concentrations (MICs) which typically take 24-48 hours to complete. These approaches are further complicated by the existence of species-specific breakpoint guidelines for MICs, with the result that accurate identification of the organism is required before MICs can be interpreted. Moreover, most current identification and susceptibility strategies require significant quantities of starting organism, which further lengthens the time to appropriate therapeutic decision.

Nanomechanical cantilevers (NMCs) are sensitive and powerful sensors that can detect extremely small forces and movements. Several studies have demonstrated that they can be used to characterise biological systems with hitherto unprecedented precision, and can detect the specific vibrations of individual living cells that results from metabolic activities and molecular motors. The proposal will investigate whether NMCs can be developed as a novel rapid method to detect antifungal resistance in pathogenic Candida isolates. NMCs might represent a highly sensitive and ultra-rapid novel method of establishing antifungal susceptibility profiles for pathogenic Candida spp. and may help in prescribing the most appropriate antifungal therapy promptly. 

Funded under Global Challenges: 

Towards devices for detecting antimicrobial resistance in resource-poor settings; on-chip magnetic separation, concentration and detection of bacteria

Annela Seddon (Physics), Jim Spencer (Cellular and Molecular Medicine) and Rob Hughes (Mechanical Engineering and Physics)

Achieving rapid and sensitive detection of bacteria in clinical samples in resource poor settings will counter the growth in, and reduce the impact of, antimicrobial resistance (AMR) by reducing inappropriate prescribing that drives resistance and enabling the timely administration of appropriate therapeutics. Current identification methods based on bacterial culture can take upwards of two days to obtain a definitive result, and may require additional sub-culturing and microbiological testing to identify strains and determine antibiotic susceptibility. These resources are not always available in low-middle income countries. The investigators are developing a solution based around magnetic capture in a microfluidic device, which will detect the presence of small numbers of bacteria in a clinical sample and identify whether these bacteria are antibiotic resistant. 

Mathematical modelling of the impact of novel AMR diagnostics for Neisseria gonorrhoeae

Katy Turner (Schools of Veterinary Sciences and Social and Community Medicine), Martin Homer (Engineering Maths), Hannah Christensen (Social and Community Medicine), Harriet Mills (Schools of Social and Community Medicine and Veterinary Sciences) and Darryl Hill (Cellular and Molecular Medicine)

Gonorrhoea is a sexually transmitted bacterial infection caused by Neisseria gonorrhoeae. It causes an estimated 78 million new infections worldwide each year, 82% in low and low-middle income countries (LMICs). Internationally, multidrug resistant N. gonorrhoeae is recognised as a serious clinical problem and is one of the pathogens on the CDC and WHO urgent priority list. The largest burden of gonorrhoea infection occurs in LMIC countries and causes significant morbidity, and may contribute to HIV transmission. The World Health Assembly recently approved a new Global Health Sector Strategy for sexually transmitted infections (STIs), which has prioritised gonorrhoea as one of 3 STIs for strategic global focus because of the importance of AMR. One of the targets is a 90% reduction in N. gonorrhoeae incidence globally and a concerted modelling effort will be required to inform how to reach this target. Sexually transmitted infections including gonorrhoea are a global problem of socio-economic disadvantage, with rates highest in the poorest countries. Within countries, gonorrhoea is concentrated in risk groups such as men who have sex with men, commercial sex workers and the most socio-economically disadvantaged groups in society (including women).

The project will develop a mathematical model of gonorrhoea and AMR transmission, to investigate the optimal methods for control in LMIC countries, specifically around improved diagnostics. The investiagtors will initially focus on Thailand, and on men who have sex with men (MSM) sexual networks. The investigators have strong links with WHO and ECDC to facilitate identifying local partners and data to parameterise country-specific models.

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