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The Novel Therapies theme of the CDT will focus on Increasing the supply and development of antimicrobials & vaccines
Antimicrobials are drugs used to treat bacterial, viral, fungal and parasitic infections. Amid the rise in AMR, the development of new antimicrobials has been stifled. Approaches and potential PhD projects to develop new antimicrobial therapies include:
- Improved (pre-clinical) assessment of combination therapies, using multiple antimicrobials together to increase efficacy and prevent emergence of resistance;
- Bacteriophage-based therapy, use of (natural and engineered) viruses that infect bacteria or use of the viral enzymes as antimicrobials;
- Repurposing and reengeering of existing drugs;
- Discovery and characterisation of new antimicrobials and antimicrobial delivery vehicles.
On the other hand, vaccines are essential tools to prevent infectious diseases by stimulating the immune system to produce a protective response against specific pathogens. Vaccine-oriented projects can focus on, e.g.
- Discovery, using advanced physical-sciences methods to identify potential antigens or developing new formulations of weakened forms of the pathogen that can induce an immune response without causing disease; or on
- Process engineering required for increasing the supply of existing or vaccines in development.
Research Theme Contacts:
Prof Joanne Santini and Prof Bart Hoogenboom
2025 Projects
- Reverse epitope discovery for Tuberculosis vaccine design using deep learning.
Supervisors
Project Details:
Rationale & Background
Drug-resistant tuberculosis (TB) accounts for one out of every three deaths from antimicrobial resistance. To reduce this burden more efficacious vaccines are needed. Development of better vaccines is critically limited by insufficient insights into the mechanisms of protective immunity. An emergent approach to antigen discovery starts by characterizing immunodominant T cell responses in vivo and then works back from their T cell receptor (TCR) sequence to their antigen targets.1 This reverse epitope discovery approach offers an exciting prospect for complex pathogens such as Mycobacterium tuberculosis (Mtb), where traditional vaccine design has had limited success. However, experimental throughput of antigen discovery remains low. In this project, we will develop deep learning approaches to prioritise peptides for experimental testing.
Deep learning has recently begun to achieve breakthrough success on important problems in biology, as illustrated by this year’s Nobel prize for computational protein design. However, there remain significant knowledge gaps in the application of AI to protein science. This project addresses one of the most pressing of them: Predicting protein-protein interactions between the highly variable and flexible loops of immune receptors and their ligands. Anchored by a concrete focus on developing better vaccines to TB, and driven by unique datasets and interdisciplinary collaborations, this projects aims to make transformative progress on this grand challenge in computational biology.
Aims & Objectives
1. To rank putative targets by in silico predictions of MHC binding
In preliminary work, we have identified T cell receptor motifs among the TCR repertoire at the site of a Tuberculin skin test, and linked these to subject major histocompatibility complex (MHC) alleles.2 The binding of peptides to MHC poses a major constraint on which antigens are likely to be targeted by the TCRs of interest, which we will leverage by using existing machine learning models to probabilistically rank peptides for the MHCs of interest.
2. To develop deep learning approaches to predict targets based on TCR sequence
Recent advances allow prediction of TCR binding to pMHCs for which some experimental training data is available. We will use SCEPTR3, a protein language model for TCRs developed in our group, to map TCR motifs to known pMHCs. However, only few TCR-pMHC pairing are known for TB, so we will next generalise the contrastive learning approach we developed to train SCEPTR to train predictors that can rank peptides unseen during training. Progress in generalisable prediction of TCR-pMHC specificity will have substantial impact beyond TB, if successful.
Skills
This project provides a powerful platform for application of machine learning to biomedical research, invaluable to academia and industry. The student will develop expertise in large language models for the prediction of protein function, and contribute substantial new knowledge in the field. They will also acquire expertise in immunology as part of an international Wellcome Trust funded team including computational biologists, wet-lab scientists and clinicians focused on discovering the T cell determinants of protection and pathogenesis in Tuberculosis.
References:
- Musvosvi et al. Nat Med 29, 258–269 (2023). https://www.nature.com/articles/s41591-022-02110-9
- Nagano et al. arXiv preprint (2024). https://arxiv.org/abs/2406.06397
- Turner et al. bioRxiv preprint (2024). https://doi.org/10.1101/2024.06.25.600676
Further Information :
- Q-Immuno lab page: https://qimmuno.com/- Innate2Adaptive group page: https://www.innate2adaptive.uk/
- TEMPEST project : https://wellcome.org/grant-funding/people-and-projects/grants-awarded/clonal-and-functional-t-cell-determinants
- Engineering novel bacteriophage-based antimicrobials.
Supervisors
Project Details:
Klebsiella pneumoniae (Kpn) is a Gram-negative, opportunistic, nosocomial pathogen causing a variety of diseases such as pneumonia, pyogenic liver abscesses and neonatal sepsis. Spread of antimicrobial resistance (including beta-lactam and carbapenem resistance) has resulted in WHO’s grouping of Kpn as a priority 1 pathogen for which new antibiotics are urgently needed (1). Kpn has broad genomic and serotype diversity which makes developing novel antimicrobials and vaccines particularly challenging. Kpn capsular polysaccharide (K-antigen) and lipopolysaccharide (O-antigen) are important virulence factors that can aid the bacterium in evading the immune system. Their remarkable diversity (79 and 9 different K and O characterised serotypes, respectively) poses additional challenges for developing therapeutics with broad applicability and limits the potential for repurposing existing drugs. Capsule removal results in decreased virulence, increased sensitivity to antibiotics and susceptibility to the immune system.
Bacteriophages (phages) (viruses that infect and kill bacteria) can be used as antimicrobials in combination with antibiotics to treat Kpn infections. Strains without an intact capsule are more susceptible to a wider range of phages. Some phages can use the capsule as their primary receptor and use catalytic domains (depolymerases) contained on their tail fibres/spikes to degrade the capsule (2). The mechanisms underlying capsule recognition/degradation and the role of the capsule in phage susceptibility is critical to the development of phages/depolymerases as novel antimicrobials.
The main objective of this project, a collaboration with UKHSA, is to understand the molecular interactions between depolymerases and Kpn capsules with the aim to engineer them for expanded host range. We have a large collection of well characterised Kpn phages that target diverse strains. Depolymerases that target a variety of capsule types will be identified bioinformatically, structures predicted using Alphafold 3, enzymes heterologously expressed in Escherichia coli and their activity characterised using a variety of biochemical and genetic approaches. The enzyme-capsule interaction will be interrogated using different biophysical techniques (e.g., mass spectrometry). We will use a combination of rational design and directed evolution to engineer depolymerases with different host range further interrogating the mechanism(s) of capsule degradation.
References
1. https://www.who.int/emergencies/disease-outbreak-news/item/2024-DON527
2. Cheetham et al. 2024. Specificity and diversity of Klebsiella pneumoniae phage-encoded capsule depolymerases. Essays in Biochemistry. In Press. https://doi.org/10.1042/EBC20240015
- Bioengineered smart antibacterials using synthetic cells.
Supervisors
Project Details:
Background
Antimicrobial resistance is a major growing global threat, exacerbated by a drought in the discovery of new antibiotics. Novel antibiotic technologies are urgently required to target both motile and biofilm-based bacteria. Bioengineering can offer innovative solutions. While engineering microbes to kill other bacteria is possible, using genetically engineered organisms poses many well-recognised issues: available tools are limited to a few model microorganisms, performance and stability issues of gene circuits, and the ongoing safety challenge of biocontainment.
Self-assembled and designed to mimic living cells, synthetic cells are artificial micron-sized compartments that possess many of the useful functionalities of genetically engineered organisms, while avoiding many drawbacks. These modular constructs can be engineered to synthesise, encapsulate, and release molecules to communicate with non-living and living cells in response to a variety of external stimuli. They can be built from both biological and synthetic parts, creating unique physical and chemical properties. Bioengineering synthetic cells will enable new and more precise methods to target and kill bacteria.
Project Summary
In this project, we will make and use synthetic cells to enact more targeted killing of bacteria by inducing spatial proximity. This will be achieved with two main objectives:
Objective 1: Develop synthetic cells that can attract specific bacteria towards them.
Objective 2: Develop synthetic cells that can detect and move towards bacteria and embed themselves in biofilms.
Our bioengineering solutions for bacterial targeting and killing using synthetic cells will open new methods for overcoming antimicrobial resistance. This project will be a step-change in the development of synthetic cells towards targeted and smart modulation of living systems.
Skills
The Booth group are experts in synthetic cell engineering and have applied them previously with bacteria. The Volpe group are experts in the study of both synthetic and biological active matter, systems capable of autonomous motion at the microscale, including vesicles, colloids, and bacterial cells. The student will be embedded within both research groups and learn skills across bioengineering, biochemistry, soft matter, and molecular biology. For more information about the groups, please visit www.boothlab.uk and www.activematterlab.org.
References
Booth 2016 Sci. Adv. DOI: 10.1126/sciadv.1600056
Hartmann 2023 JACS DOI: 10.1021/jacs.3c02350
Smith 2023 Nat. Chem. Biol. DOI: 10.1038/s41589-023-01374-7
Parkes 2024 bioRxiv DOI: 10.1101/2024.08.21.608917
Joseph 2017 Sci. Adv. DOI: 10.1126/sciadv.1700362
Makarcuk 2019 Nat. Commun. DOI: 10.1038/s41467-019-12010-1
Barbieri 2023 arXiv DOI: 10.48550/arXiv.2307.16165
- Synergistic efficacy of a monoclonal antibody therapy with colistin against AMR Acinetobacter baumannii.
Supervisors
Project Details:
Background
The World Health Organisation have identified the Gram-negative bacterium Acinetobacter baumannii as a top priority pathogen for new therapies. It is an increasingly common cause of pneumonia and sepsis, which are usually resistant to multiple antibiotics and have a mortality of 40+%. Monoclonal antibodies could be an effective treatment for AMR A. baumannii infections when used in conjunction with antibiotics. Since 2018, Brown has led an MRC-funded consortium developing an antibody therapy to A. baumannii, which has identified that IgG targeting several outer membrane protein antigens can protect against A. baumannii infection (Brown, unpublished). The group are now funded to isolate monoclonal antibodies to these antigens, which will be available in early 2025. Importantly, combining polyclonal antibodies and the antibiotic colistin (firstline therapy for carbapenem resistant A. baumannii infections) synergistically inhibits A. baumannii growth. This effect could considerably improve the protective efficacy of an antibody therapy and help overcome A. baumannii antibiotic resistance.
Aims
This project will use biophysical and more conventional molecular microbiological approaches to address the mechanisms underpinning this synergy through the following specific aims:
1. Use established atomic force microscopy techniques (Hoogenboom) in combination with other microscopy techniques (e.g., electron microscopy) to characterise the physical and morphology effects of:
(i) colistin and monoclonal IgG to outer membrane protein antigen separately on A. baumannii cell surface and bacterial viability
(ii) then analyse the effects of monoclonal antibody and colistin in combination using varying IgG to antibiotic ratios
2. Investigate the effects of colistin in combination with monoclonal antibody to outer membrane proteins on AMR A. baumannii stress responses and growth using in vitro biochemical assays and RNA sequencing.
PhD support
The Hoogenboom laboratory has established ground-breaking AFM techniques for analysing the cell surface of bacteria, recently extending these techniques to demonstrate profound effects of colistin on the A. baumannii cell surface (unpublished), and is supported by BBSRC and Wellcome Trust funding. The Brown laboratory is a leading research group into pneumonia pathogenesis that has recently been investigating A. baumannii, and is supported by MRC and Wellcome Trust funding. Brown and Hoogenboom have a track record of supervision of successful PhD studentships, including joint students. They co-supervise an existing PhD student investigating complement activity against A. baumannii. Alongside an excellent training in the scientific approach, a student working on this project will learn the following specific techniques:
- Culture, phenotyping, and potential mutagenesis of the AMR pathogen A. baumannii
- In vitro assays assessing the bacterial stress response, including culture, microscopy, and RNAseq
- Imaging of bacteria using atomic force microscopy and other advance microscopic techniques
The above combination of microbiology and nanotechnology skills would provide a successful PhD graduate with a strong basis for a future scientific career.
Relevant references:
Antimicrobial Resistance Collaborators. Global burden of bacterial antimicrobial resistance in 2019. Lancet 2022;399:629-655. https://doi.org/10.1016/S0140-6736(21)02724-0
Spellberg B, Rex JH. The value of single-pathogen antibacterial agents. Nat. Rev. Drug Discov. 2013; 12(12): 963. https://doi.org/10.1038/nrd3957-c1
Kamuyu G, et al. Sequential vaccination with heterologous Acinetobacter baumannii strains induces broadly reactive antibody responses. Front. Immunol. 2021;12:705533. https://doi.org/10.3389/fimmu.2021.705533
Kamuyu G, et al. Strain specific variations in Acinetobacter baumannii complement sensitivity. Front. Immunol. 2022; 13: 853690. https://doi.org/10.3389/fimmu.2022.853690
Benn G, et al. Phase separation in the outer membrane of Escherichia coli. Proc. Natl. Acad. Sci. USA 2021; 118 (44): e2112237118. https://doi.org/10.1073/pnas.2112237118
Webby M, et al. Lipids mediate supramolecular outer membrane protein assembly in bacteria. Sci. Adv. 2022; 8(44): adc9566. https://doi.org/10.1126/sciadv.adc9566
Benn G, et al. Complement-mediated killing of Escherichia coli by mechanical destabilization of the cell envelope. EMBO J 2024. https://doi.org/10.1038/s44318-024-00266-3
- High throughput, cell-free assays for selective antimicrobial hit identification
Supervisors
Project Details:
Supramolecular ion transporters (SITs) are molecules that can carry ions, such as chloride, across lipid bilayers. There is emerging evidence that SITs maybe valuable targets in the search for new antimicrobials which function by disrupting the homeostatic balance of pathogenic cells. However, not all SITs display antibacterial activity and there is consequently a gap in our knowledge of how to design new antibacterials with this mode of action.
This project will combine expertise from the Haynes group – who are experts in supramolecular ion transport and have recently reported a high-throughput and automated anion transport assay – with expertise in the Castoagnolo group, who are experts in bacterial lipids and designing lipophilic antimicrobial agents that are thought to function within the bacterial cell membrane. We will develop high-throughput and automated approaches to screening large libraries of potential antimicrobial agents in cell-free models for membrane-based modes of action, such as ion transport. In doing so, we aim to: (i) better understand the link between ion transport in cell-free models and toxicity to real bacterial cells; (ii) speed up the identification of new antimicrobials, and; (iii) learn how to design ion transporters with function against bacterial cells.
Students will gain experience in: (i) the design, preparation and characterisation of vesicle-models of cell membranes (soft materials); (ii) fluorescence analysis of ion transport processes (using fluorescence spectrophotometer and platereader technology); (iii) automated process development using available liquid handling robots.
Suggested reading
E. Feo and P. A. Gale, Current Opinion in Chemical Biology, 2024, 10235, DOI: 10.1016/j.cbpa.2024.102535.
K. Yang, L. Lee, H. A. Kotak, E. R. Morton, S. M. Chee, D. Nguyen, A. Keskküla and C. J. E. Haynes, ChemRxiv 2024, DOI: 10.26434/chemrxiv-2024-kxf0x.
S.-H. Kim, C. K. Hind, G. F. S. Fernandes, J. Wu, D. Semenya, M. Clifford, C. Marsh, S. Anselmi, A. J. Mason, J. D. Bruce, J. M. Sutton and D. Castagnolo, ACS Medicinal Chemistry Letters, 2024, 15, 239–249, DOI: 10.1021/acsmedchemlett.3c00460.