This project seeks to advance the frontiers of bioscience discovery by improving our understanding of how thermodynamic constraints can limit bacterial adaptation to challenging environments. We seek to better understand the strategies by which a bacterial pathogen can adapt to host immune response through metabolic remodelling and by employing alternate modes of respiration; a trait especially important for environmental pathogens such as Mycobacterium avium, a slow-growing bacterium found in soil and brackish water that can cause chronic infections in humans and animals.
Background. Mycobacterial genomes are highly GC-biased resulting in higher frequencies of ambiguous gene attributions. These ambiguous gene annotations often include words such as ‘hypothetical’, ‘putative’ or ‘probable.’ This ambiguity, in turn, has confounded the identification of key metabolic pathways. We assert that this systematic ambiguity in annotation for the entire genus has obscured prediction of novel phenotypes by M. avium and perhaps other taxonomically related species.
Preliminary data. Building on a novel and as yet unpublished observation, we have discovered that a Mycobacterium avium is capable of long-term survival and replication at low oxygen concentrations a trait associated with large-scale programmatic changes in gene expression with concomitant change in the protein composition of the replicating bacilli. The result of these changes is coordinated global metabolic remodelling with the induction of genes associated with both electron and nutrient transport as well as central metabolism. We have not yet defined the respiratory basis for this trait nor the terminal electron acceptor(s) involved. Our results are concordant with other reports of mycobacterial bioenergetics [1-3].
Objective. This project will use the Constraint-Based Reconstruction and Analysis Toolbox (COBRA toolbox) [4] in MATLAB to model genome-scale metabolic network reconstructions of bacterial energetics taking into account ATP economics, required environmental trade-offs and the thermodynamic constraints of respiration, as described [2]. Starting from various annotations of the selected M. avium genomes, general models will be constructed and tested for feasibility under both oxic and anoxic environmental conditions. Once defined, these general models will be further constrained by gene expression and proteomic results as well as in-vitro measurements of membrane potential and other physiological characteristics from oxic and hypoxic laboratory experiments. The novel aspect of this work will be the development of a bioenergetic-focussed modelling methodology using the COBRA toolbox.
We envision this project combining both computational work with laboratory skill development and is best suited to an applicant who desires significant dual-track experience.
Impact. In addition to authorship on a manuscript currently in preparation, we anticipate the impact of this project to be high. Bioenergetics underpin the capacity for bacterial adaptation and phenotype development. This is especially important in terms of pathogenic organisms with environmental reservoirs where the transition between environment and host is especially challenging. This project will clarify our understanding of bacterial adaptation and phenotype development from both the theoretical and applied perspective in a manner is currently underdeveloped in the literature.
References
1. Hards, K. and G.M. Cook, Targeting bacterial energetics to produce new antimicrobials. Drug Resist Updat, 2018. 36: p. 1-12.
2. McKinlay, J.B., G.M. Cook, and K. Hards, Chapter Four - Microbial energy management—A product of three broad tradeoffs, in Advances in Microbial Physiology, R.K. Poole, Editor. 2020, Academic Press. p. 139-185.
3. Cook, G.M., et al., Energetics of Respiration and Oxidative Phosphorylation in Mycobacteria. Microbiol Spectr, 2014. 2(3).
4. Heirendt, L., et al., Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0. Nat Protoc, 2019. 14(3): p. 639-702.
Entry requirements:
Requirements are a First-class Bachelor’s degree or overseas equivalent in maths, physics or other natural science. The student will be expected to use high-performance computing resources and perform MATLAB coding with optimization using IBM Cplex and Gurobi. The primary tool for this work will be the Cobra Toolbox which will require software development. The student will learn about genome scale modelling, rich data workflow to incorporate gene expression, metabolomics and proteomics. A successful candidate will understand sparse matrix operations and ordinary differential equations among other mathematical concepts.
The student should be interested in scholarship in the life sciences, but does not require specific training, skills nor experience. Among the data and techniques available for the student to become familiar with are microbiological culture, fluorescent and light microscopy, biochemical assays to define media constituents and their rate of consumption, cryoelectron microscopy, mass-spectroscopy, bioreactor operation, real-time PCR, proteomics and metabolomics.
The University of Leicester English language requirements apply where applicable.
Application advice:
To apply please refer to https://le.ac.uk/study/research-degrees/research-subjects/respiratory-sciences
With your application, please include:
- CV
- Personal statement explaining your interest in the project, your experience and why we should consider you
- Degree Certificates and Transcripts of study already completed and if possible transcript to date of study currently being undertaken
- Evidence of English language proficiency if applicable
- In the reference section please enter the contact details of your two academic referees in the boxes provided or upload letters of reference if already available.
- In the research proposal section please provide the name of the supervisors and project title (a proposal is not required)
Project / Funding Enquiries: Dr John E. Pearl: [Email Address Removed]
Application enquiries to [Email Address Removed]
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