Novel Therapies
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
Available Projects for 2026 Entry
For full details on how to apply, please visit the Application Page
| Project Title | Description | Supervisors | Keywords |
|---|---|---|---|
| Mining metagenomes to uncover next-generation antimicrobial enzymes | Lucy van Dorp, Joanne Santini | Phages; Metagenomics; Endolysins; Antimicrobials; Host prediction; CRISPR; Microbial ecology; Evolutionary genomics | |
| Combining antibodies and antibiotics to combat one of the world’s most dangerous drug-resistant pathogens. | Jeremy Brown, Bart Hoogenboom | Acinetobacter baumannii; Monoclonal antibodies; Colistin; Antimicrobial resistance; Atomic force microscopy; RNA sequencing; Synergy; Therapeutics | |
| Micro and meso level strategies for combating resistant tuberculosis and other mycobacterial diseases | Alethea Tabor, Sanjib Bhakta | ||
| Harnessing bovine ultralong CDRs to discover novel antimicrobial peptide scaffolds | Christine Orengo, Gorka Lasso Cabrera | Ultralong CDRs, antibodies, structural bioinformatics, deep learning, antimicrobial peptides, protein modelling, evolutionary analysis, therapeutic discovery | |
| Engineering polymeric nanoparticles for targeted mucosal mRNA vaccine delivery | Julia Rho, Pratik Gurnani | mRNA vaccines, mucosal delivery, polymer nanoparticles, high-throughput screening, respiratory infections, antimicrobial resistance, vaccine delivery systems, non-viral vectors | |
| AI-guided NMR screening to fast-track antiviral drug discovery against emerging viral threats | Finn Werner, Chris Waudby | RNA polymerase, antiviral drug discovery, NMR spectroscopy, machine learning, fragment screening, ASFV, cryo-EM, laboratory automation, lead optimisation |
Projects in Progress
Student
Lucia Guillamet Garcia
Supervisors
Project Details:
Drug-resistant tuberculosis (TB) accounts for one in three deaths caused by antimicrobial resistance. To reduce this burden, more effective vaccines are urgently needed. Progress in vaccine development is critically limited by insufficient understanding of the mechanisms of protective immunity. A promising approach to antigen discovery begins by identifying immunodominant T cell responses in vivo and then works backwards from their T cell receptor (TCR) sequences to their antigen targets [1]. This reverse epitope discovery strategy is particularly exciting for complex pathogens like Mycobacterium tuberculosis (Mtb), where traditional vaccine design has had limited success. However, experimental throughput remains low, and this project is developing deep learning methods to prioritise peptides for testing.
Recent breakthroughs in deep learning have transformed biology, as highlighted by the Nobel Prize awarded for computational protein design. Yet, significant gaps remain in applying artificial intelligence to protein science. This project addresses one of the most pressing challenges: predicting protein-protein interactions between the highly variable and flexible loops of immune receptors and their ligands. With a concrete focus on TB vaccine development and supported by unique datasets and interdisciplinary collaborations, the project aims to make transformative progress in computational biology.
The project's first objective is to rank putative antigen targets using in silico predictions of MHC binding. Preliminary work has identified TCR motifs from the T cell repertoire at the site of a Tuberculin skin test and linked these to subject-specific major histocompatibility complex (MHC) alleles [2]. Since peptide binding to MHC is a key constraint on antigen recognition, existing machine learning models are being used to probabilistically rank peptides for the relevant MHCs.
The second objective is to develop deep learning approaches to predict antigen targets based on TCR sequence. The team is using SCEPTR [3], a protein language model for TCRs developed in-house, to map TCR motifs to known peptide-MHC complexes. Because few TCR-pMHC pairings are known for TB, the project is extending a contrastive learning approach to train models that can rank peptides not seen during training. Success in generalisable prediction of TCR-pMHC specificity would have broad impact beyond TB.
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
Student
Julie Lavollee
Supervisors
Project Details:
Klebsiella pneumoniae (Kpn) is a Gram-negative, opportunistic, hospital-acquired pathogen responsible for diseases such as pneumonia, pyogenic liver abscesses, and neonatal sepsis. The global spread of antimicrobial resistance, including beta-lactam and carbapenem resistance, has led the World Health Organization to classify Kpn as a priority 1 pathogen in urgent need of new antibiotics [1]. Its broad genomic and serotype diversity presents major challenges for developing effective antimicrobials and vaccines. The capsular polysaccharide (K-antigen) and lipopolysaccharide (O-antigen) are key virulence factors that help Kpn evade the immune system. With 79 K and 9 O characterised serotypes, this diversity limits the applicability of existing therapeutics and complicates drug repurposing. Capsule removal has been shown to reduce virulence and increase susceptibility to antibiotics and immune clearance.
Bacteriophages (phages), viruses that infect and kill bacteria, offer a promising route for treating Kpn infections, especially when used in combination with antibiotics. Strains lacking an intact capsule are more vulnerable to a broader range of phages. Some phages use the capsule as a primary receptor and carry catalytic domains known as depolymerases on their tail fibres or spikes to degrade the capsule [2]. Understanding the molecular mechanisms of capsule recognition and degradation is essential for developing phage-based therapeutics and engineered depolymerases with broader host range.
This project, in collaboration with the UK Health Security Agency (UKHSA), aims to uncover the molecular interactions between depolymerases and Kpn capsules and to engineer these enzymes for expanded host range. The team is working with a large collection of well-characterised Kpn phages that target diverse strains. Depolymerases targeting various capsule types are being identified through bioinformatic analysis, with structural predictions generated using Alphafold 3. These enzymes are being heterologously expressed in Escherichia coli and their activity characterised using biochemical and genetic methods. Enzyme-capsule interactions are being studied using biophysical techniques such as mass spectrometry.
To expand host range and better understand capsule degradation mechanisms, the project is applying both rational design and directed evolution approaches to engineer depolymerases. This work will contribute to the development of novel antimicrobial strategies targeting one of the most clinically challenging pathogens.
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
Student:
Ann-Celine Clabout
Supervisors
Project Details:
Background
Antimicrobial resistance is a growing global threat, worsened by a lack of new antibiotic discoveries. Novel technologies are urgently needed to target both motile and biofilm-forming bacteria. Bioengineering offers innovative solutions. While genetically engineered microbes can be designed to kill bacteria, their use presents well-known challenges. These include limited tools restricted to a few model organisms, instability of gene circuits, and ongoing safety concerns around biocontainment.
Synthetic cells are artificial micron-sized compartments that self-assemble and mimic key functions of living cells. They offer many of the advantages of genetically engineered organisms while avoiding their drawbacks. These modular constructs can be engineered to synthesise, encapsulate, and release molecules in response to external stimuli, enabling communication with both living and non-living cells. Built from biological and synthetic components, synthetic cells possess unique physical and chemical properties. Their bioengineering opens new possibilities for precise bacterial targeting and killing.
This project is developing synthetic cells to induce spatial proximity and enable targeted bacterial killing. The two main objectives are:
Objective 1: Develop synthetic cells that attract specific bacteria.
Objective 2: Develop synthetic cells that detect and move toward bacteria and embed within biofilms.
These bioengineering strategies will introduce new methods for overcoming antimicrobial resistance. The project represents a step-change in the development of synthetic cells for smart and targeted modulation of living systems.
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
Student
Gus Molyneux
Supervisors
Project Details:
Supramolecular ion transporters (SITs) are molecules capable of carrying ions, such as chloride, across lipid bilayers. Emerging evidence suggests that SITs may be valuable targets in the search for new antimicrobials that function by disrupting the homeostatic balance of pathogenic cells. However, not all SITs display antibacterial activity, and there remains a gap in our understanding of how to design new antimicrobials with this mode of action.
This project combines expertise from the Haynes group, specialists in supramolecular ion transport and developers of a high-throughput automated anion transport assay, with the Castagnolo group, experts in bacterial lipids and the design of lipophilic antimicrobial agents that act within bacterial membranes. Together, the teams are developing high-throughput and automated approaches to screen large libraries of potential antimicrobial agents in cell-free models that mimic membrane-based mechanisms such as ion transport.
The project aims to:
- Better understand the relationship between ion transport in cell-free models and toxicity to bacterial cells
- Accelerate the identification of new antimicrobials
- Learn how to design ion transporters that are effective against bacterial cells
These efforts will contribute to the development of novel antimicrobial strategies and provide insights into membrane-targeting mechanisms that could help overcome antimicrobial resistance.
Suggested Reading
- Feo E and Gale PA. Current Opinion in Chemical Biology, 2024, 10235. DOI: 10.1016/j.cbpa.2024.102535
- Yang K et al. ChemRxiv, 2024. DOI: 10.26434/chemrxiv-2024-kxf0x
- Kim SH et al. ACS Medicinal Chemistry Letters, 2024, 15, 239–249. DOI: 10.1021/acsmedchemlett.3c00460