Defining adaptive processes in a model bacterial species by integrating proteomic and metabolomic analytical strategies

Lead Research Organisation: King's College London
Department Name: Pharmaceutical Sciences


BBSRC RELEVANCE: This project, linking KCL and ASTA, is of direct relevance to BBSRC Strategic Policy areas "Systems approaches to the biosciences" and "Technology development for the biosciences" see As in the Impact section below, benefits in BBSRC Strategic Policy areas relating to antimicrobial resistance and agriculture are also expected outcomes.

AIM: To utilise cutting-edge technologies to investigate the complex regulators that facilitate transmission of Pseudomonas aeruginosa against its intra-species diversity.

BACKGROUND: The arrival of novel DNA sequencing technologies have led to an explosion of data on the microbiome of man and numerous environments. While such information provides a comprehensive catalogue of species, many of which cannot be cultured at present, the data give no insight into the function of the microbe nor the incisive question of how transmission to a new habitat occurs. The habitats that microbes colonise are diverse. A few key species can however transcend their original "boundaries" to colonise new niches. Despite attempts by several research centres to map routes of transmission of often highly antibiotic resistant species from the environment to man, the driving forces that enable a microbe to leave its normal habitat and colonise a new site are not currently known. This study will investigate key regulators of the adaptive potential of Pseudomonas aeruginosa as a model due to the extreme metabolic versatility and "ubiquitous" colonisation of new sites that it displays. This species and closely related taxa are moreover used widely in many industrial processes including bioremediation. In addition, due to its remarkable capacity to harbour antibiotic resistance genes chromosomally, P. aeruginosa is currently one of our greatest therapeutic challenges and poses an immense environmental threat.

HYPOTHESIS: The underlying hypothesis behind this project is that the phenotypic plasticity for adaptive processes that selectively enables a microbe to leave its normal habitat and colonise a new site is driven by a plethora of key regulators and signaling molecules, which in the case of P. aeruginosa accounts for nearly 10% of its genome. Current evidence indicates however that the phenotypic plasticity for adaptive processes lies at the level of the proteome and metabolome. Once transcribed, many of the proteins/metabolites involved may be modified (post-translational modification - PTM) to facilitate their transition. Mapping these processes therefore involves not only detection and quantitation of these complex biomolecules but their modified proteoforms. Until recently, high throughput detection of proteins and PTMs were outside the reach of bioscience. Today, with novel forms of Mass spectrometry (MS) and NMR spectroscopy, such analyses are possible but the technologies and skills have been limited to relatively few specialist laboratories.

PLAN: This Industrial CASE Studentship will build upon the experience of the supervisory team's work on P. aeruginosa from both academia (KDB, AJM) and industry (OB, HNS) to investigate the metabolome and proteome in relation to its population structure. Representative strains from selected lineages where hyper-adaptation to several ecological niches such as water, sewage, soil etc, will be selected for comparative in-depth analysis to elucidate regulatory markers. These will be validated using RNA expression analysis of each identified marker to corroborate their distribution and expression level. The project will be developed with the student combining training and experimental work through overlapping periods during the four years as outlined below.


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Studentship Projects

Project Reference Relationship Related To Start End Student Name
BB/M009513/1 01/10/2015 30/09/2023
2081503 Studentship BB/M009513/1 01/10/2018 30/09/2022 Louise Duncan