Pathogens and Host Defences Doctoral Training Partnership : Funding : Sussex Researcher School : Schools and services : �պ��

Pathogens and Host Defences Doctoral Training Partnership

This collaboratively-funded doctoral training programme aims to bridge the gap between human and veterinary infectious diseases research by building a cohort of students in the area of One Health, One Medicine. Covering a range of human and animal pathogens, it brings together the expertise of our partners across the South of England to provide a broad, cross-institutional training and research experience for students. Each researcher will be supervised by two of our partners and will benefit from cohort-building activities designed to build their networking and presentation skills.

Our Partner Institutions: University of Surrey (Guildford), �պ�� (Brighton), The Pirbright Institute, (Woking), and The Defence Science Technology Laboratory (DSTL) (Porton Down).

We are pleased to invite applications for PhD scholarships across our the partners of our Doctoral Training Partnership for the projects below.

Our scholarships cover UKRI level stipend (currently £18,622), PhD fees and research costs for 3.5 years and are open to UK applicants only. Dstl partnered studentships are open only to UK nationals who do not have dual nationality. Applicants should hold or be expected to obtain a good honours degree (first or upper second) or a masters degree in an appropriate discipline.

Application Deadline: Midnight, Monday 22^nd January 2024.

Interviews online: Week beginning 5^th February 2024.

How to apply: Our Application form can be found . Prospective students are asked to select up to four projects from those available, and are strongly encouraged to make contact with supervisors before applying. Applications require a CV, the names of two academic referees, and a personal statement outlining why you want to do a PhD, and your reasons for choosing their selected projects.

Cross-species regulation of coronavirus infection by m6A RNA methylation (23DTP02)

TITLE: Cross-species regulation of coronavirus infection by m6A RNA methylation

SUPERVISORS: Dr Hannah Burgess, University of Surrey (h.burgess@surrey.ac.uk)

Dr Helena Meier, The Pirbright Institute (Helena.maier@pirbright.ac.uk)

This is a fully-funded 3.5-year PhD opportunity to investigate the biology of coronaviruses across host species. During infection viruses commandeer host cell gene expression machinery to facilitate viral protein production. Understanding precisely how they depend on and manipulate such pathways can reveal new opportunities for controlling infections as well as unanticipated facets of cell biology.

We previously established that host factors that regulate RNA methylation at the N⁶- position of adenosine (m6A) are important for human coronavirus infection (Burgess et al, 2021). m6A modification is a cellular mechanism to control mRNA processing, stability and translation and in the the context of host-virus interactions, m6A has been shown to impact viral gene expression positively and negatively for different viruses, and also regulate the anti-viral immune response. Coronaviridae is a large virus family and animal coronaviruses (CoVs) represent a significant zoonotic reservoir in wildlife and a present threat to livestock in domesticated species. Though elements of the m6A installation enzyme complex are conserved, there are expression and sequence differences in the proteins involved among host species that could influence their role in CoV regulation.

This project will investigate the importance of m6A RNA modification across animal coronavirus and host species and will be based in the Burgess lab at the University of Surrey and the Maier Lab at the nearby Pirbright institute. Approaches to be used include culture of primary animal cell models of respiratory virus infection, immunoprecipitation-Mass Spectroscopy (IP-MS) to identify novel protein interactions as well as standard molecular biology and virology techniques (eg RT-qPCR, western blotting, immunofluorescence, plaque assay, TCID50) which will provide a comprehensive training in molecular virology.

We welcome applicants with a background and/or interest in molecular biology, cell biology, RNA biology and virology/microbiology. Interested applicants are encouraged to contact h.burgess@surrey.ac.uk in advance of making an application. Please note this opportunity is available only to those eligible for UK/home fees.

References:

Burgess HM, Depledge DP, Thompson L, et al. Targeting the m6A RNA modification pathway blocks SARS-CoV-2 and HCoV-OC43 replication. Genes Dev. 2021;35(13-14):1005-1019.

Doyle, N.; Simpson, J.; Hawes, P.C. and Maier, H.J. 2021. Coronavirus RNA synthesis takes place within membrane-bound sites. Viruses, 13: 2540.

Elucidating the basis of E. coli secondary infection associated with avian infectious bronchitis (23DTP03)

TITLE: Elucidating the basis of E. coli secondary infection associated with avian infectious bronchitis

SUPERVISORS: Dr Jai Mehat, University of Surrey (jw.mehat@surrey.ac.uk)

Dr Erica Bickerton, The Pirbright Institute (erica.bickerton@pirbright.ac.uk)

Safeguarding the global poultry sector against infectious disease is vital for global food security and safety. Avian infectious bronchitis is a highly contagious disease of poultry caused by infectious bronchitis virus (IBV). Some IBV strains render poultry susceptible to secondary infections caused by Avian Pathogenic Escherichia coli (APEC) leading to colibacillosis; a range of localized and systemic extra-intestinal infections that collectively cause economic losses to the industry. Whilst vaccines against APEC exist, broad cross-protection against the myriad strains involved is poor.

IBV infection causes immune suppression and failure to control bacterial infections and whilst it is known that IBV induces transcriptomic and physiological changes in the avian respiratory tract (RT) there is a significant knowledge gap in understanding how these changes promote APEC infection. We have previously defined the APEC lineages that cause primary infection of poultry, as well as opportunistic types that do not cause systemic colibacillosis in experimental models. We hypothesize that IBV facilitates subsequent co-infection by these “opportunist” E. coli. This project will test this hypothesis by studying the co-operative dynamics of IBV and APEC co-infection.

Using combination of in vitro models, we will (1) investigate basis of how IBV infection augments APEC colonisation of the RT, and (2) determine the combinations of IBV and APEC lineages that lead to most adverse outcomes.

As viral infections are known to cause perturbations in the microbiota, we will apply high-resolution metagenomics to test whether IBV infection promotes APEC abundance.

The project’s findings will improve fundamental understanding of IBV and E. coli interplay, which is not only key to enhancing protection and optimising vaccine strategies against APEC but will also advance our knowledge of viral-bacterial co-infections.

The prospective student will be trained in wet and dry lab experimentation, specifically in bacteriology and virology, metagenomic/bioinformatic analyses, eukaryotic cell culture, and metabolomics, in research groups which have an excellent track record of success in these areas. Candidates should apply to the Biosciences and Medicine PhD programme (October 2024) on the University of Surrey website.

References:

Mehat JW, van Vliet AHM, La Ragione RM. The Avian Pathogenic Escherichia coli (APEC) pathotype is comprised of multiple distinct, independent genotypes. Avian Pathol. 2021 doi:10.1080/03079457.2021.1915960

Steyn A, Keep S, Bickerton E, Fife M. The Characterization of chIFITMs in Avian Coronavirus Infection In Vivo, Ex Vivo and In Vitro. Genes (Basel). 2020. doi: 10.3390/genes11080918.

The role of platelets in the pathogenesis of Rift Valley fever (23DTP04)

TITLE: The role of platelets in the pathogenesis of Rift Valley fever virus

SUPERVISORS: Dr Dr Lisa Holbrook, University of Surrey (l.holbrook@surrey.ac.uk)

Dr Isabelle Dietrich, The Pirbright Institute (isabelle.dietrich@pirbright.ac.uk)

Rift Valley fever virus (RVFV) is a mosquito-transmitted, zoonotic, emerging bunyavirus categorised by the WHO as a high-consequence, priority pathogen due to its emergence and lack of effective and safe antiviral treatments. It causes viral haemorrhagic fever in humans and livestock characterised by necrotic lesions in major organs, leading to thrombocytopenia (low platelet numbers), coagulation defects that can cause bleeding as well as increased vascular permeability resulting in oedema, hypotension, shock, and death. How RVFV induces pathology remains largely unknown. A detailed understanding of the molecular and immune mechanisms underlying RVFV pathology will identify new avenues for therapeutics development.

Viruses associated with haemorrhagic fever cause destruction or dysfunction of platelets. Platelets are essential in haemostasis, a protective mechanism that prevents blood loss, for maintaining integrity of the vascular system and for immunity. They can be activated aberrantly by interaction with viruses or virus-infected cells causing them to adhere to endothelial cells, thereby reducing the number of circulating platelets, altering endothelial cell function, and increasing vascular permeability. Treatments which prevent or correct platelet loss and dysfunction in RVFV infection have the potential to reduce platelet-mediated pathology and to significantly improve clinical outcome.

This PhD studentship will examine the molecular and immune interactions between RVFV and platelets, characterising the mode of RVFV-induced platelet activation and thrombocytopenia. The student will evaluate the suitability of platelet-based diagnostic markers for RVFV infection detection that would allow distinction from other febrile illness-causing aetiologies relevant to RVFV-endemic countries and will explore modes of RVFV entry into cells. This project will be based in the well-equipped laboratories of the Pirbright Institute and the University of Surrey and the student will receive expert tuition in virology, platelet biology, molecular biology and imaging techniques.

Key references:

Rift Valley fever virus primes immune responses in Aedes aegypti cells.

Laureti M, Lee RX, Bennett A, Wilson LA, Sy VE, Kohl A, Dietrich I. Pathogens. 2023. 12(4):563.

Unique outbreak of Rift Valley fever in Sudan. Ahmed A, Ali Y, Elduma A, Eldigail MH, Mhmoud RA, Mohamed NS, Ksiazek TG, Dietrich I, Weaver SC., 2019. Emerg Infect Dis. 2020. 26(12):3030-3.

The Role of Platelets in the Pathogenesis of Viral Hemorrhagic Fevers. Zapata JC, Cox D, Salvato MS. PLoS Negl Trop Dis. 2014. 8(6): e2858.

Rift Valley fever: biology and epidemiology. Wright D, Kortekaas J, Bowden TA, Warimwe GM. J Gen Virol. 2019. 100(8):1187-1199.

In silico, knowledge-based investigation of immune signalling pathways in host defences across species (23DTP05)

TITLE:In silico, knowledge-based investigation of immune signalling pathways in host defences across species

SUPERVISORS: Prof Georgios Giamas, �պ��(g.giamas@sussex.ac.uk)

Dr Nicos Angelopoulos, The Pirbright Institute(nicos.angelopoulos@pirbright.ac.uk)

Following receptor triggering, signalling cascades are activated in cells of the innate and adaptive immune system which lead to downstream events like transcription factor activation, cytoskeletal changes, and increases in cellular adhesion and metabolism. These events are largely conserved across mammalian species and their modulation is pivotal for magnitude and duration of resulting immune responses.

The student will use computational and statistical tools to investigate signalling cascades and resulting activation events across species. Data from both institutes, as well as publicly available datasets and databases, will be collated and analysed. This will comprise data from human immune responses (�պ�� & public databases) and immune responses following viral infection of livestock (primarily pig; The Pirbright Institute). Pirbright Institute has already existing datasets from controlled infection experiments (e.g., influenza A) and new data (e.g., FMDV and ASFV) is generated continuously under the new BBSRC funding cycle (2023-2028). This includes datasets such as single cell RNA-seq, bulk RNA-seq from sorted cells and high dimensional flow cytometry data sets addressing transcription factor expression as well as proteins involved in cell cycle and cell adhesion. The student will use explainable AI such as Bayesian networks, for which the Computational Biology group at Pirbright Institute has experience in many biological contexts. They will also benefit from the expertise of the group with applied work on visualisation and integration of external biological databases and resources across multiple species (human, pig, and chicken).

It is expected that new hypotheses will be generated by the statistical models constructed, that will predict the outcome of immune activation resulting from different receptor triggering underlying signalling cascades. In the final phase of the project, we will seek collaborative (that is by sister projects), validation for these hypotheses in porcine (The Pirbright Institute) and human (�պ�� Sussex) in vitro models for T and B cell activation.

References:

Bayesian networks elucidate complex genomic landscapes in cancer:
Effect of mucosal adjuvant IL-1β on heterotypic immunity in a pig influenza model:
The structure-function relationship of oncogenic LMTK3:
PIK3Cδ expression by fibroblasts promotes triple-negative breast cancer progression:
Influence of PRRSV-1 vaccination and infection on mononuclear immune cells at the maternal-fetal interface:

Exploring the potential transmission dynamics of Rift Valley fever virus in livestock and humans in Great Britain (23DTP07)

TITLE: Exploring the potential transmission dynamics of Rift Valley fever virus in livestock and humans in Great Britain

SUPERVISORS: Dr Giovanni Lo Iacono, University of Surrey (g.loiacono@surrey.ac.uk

Dr Simon Gubbins, The Pirbright Institute (simon.gubbins@pirbright.ac.uk)

Rift Valley fever virus (RVFV) is a zoonotic virus transmitted by mosquitoes that is endemic in Africa. RVFV causes abortions in livestock and potentially severe disease in humans and has been identified by the World Health Organization as a priority disease for research. Although cases have not been reported in Europe, mosquitoes and livestock in the region (including in Great Britain) are known to be susceptible to infection, raising the possibility of outbreaks should the virus be introduced.

In this project you will investigate the zoonotic spread of RVFV in Great Britain following an incursion either via import of infected animals or wind-borne introduction of infected mosquitoes. You will consider three questions:

(i) What is the risk of onward spread in livestock?

(ii) What is the risk of spillover to humans and how does this risk vary amongst sectors of the population (e.g. farm workers, slaughterhouse workers or the general public)?

(iii) How might an incursion be detected (e.g. abortion surveillance, surveillance of livestock or workers at abattoirs)?

To address these questions, you will develop mathematical models for the transmission of RVFV between livestock and mosquitoes together with spillover to humans, a key factor that is omitted in most existing transmission models. You will use uncertainty and sensitivity analyses to identify and prioritise data gaps. Depending on the results from the initial modelling work and your interests, the project could develop in different directions. For example, you could generate additional data, extend the model to consider between-farm transmission and control measures or consider how risks may alter under different climate change scenarios.

You will be working in a multidisciplinary team with a strong network within the vector-borne disease community. The team comprises infectious disease modellers (Simon Gubbins and Gianni Lo Iacono), an entomologist (Marion England) and a virologist (Denise Marston).

The project would be suitable for candidates from the life sciences interested in learning sophisticated mathematical modelling and to those from physics, engineering or mathematics interested in applying their knowledge and skills in a infectious disease context. You will be based at The Pirbright Institute and the School of Veterinary Medicine, University of Surrey and will be joining an exciting and friendly community of PhD students.

You need to have a strong interest in multidisciplinary research and have excellent communication skills.

Discovering and characterising novel defence systems in pathogenic Serratia spp using microbiology and genomics (23DTP08)

TITLE: Discovering and characterising novel defence systems in pathogenic Serratia spp using microbiology and genomics

SUPERVISORS: Dr Giusy Mariano, University of Surrey (g.mariano@surrey.ac.uk)

Dr Tim Downing, The Pirbright Institute (tim.downing@pirbright.ac.uk)

Bacteriophages (aka phages) are specialised viruses of bacteria, which whom they have co-evolved for long periods of time. To combat phage infection, bacteria have ~170 antiphage systems against phages, with many more undiscovered. The molecular investigation of novel systems may hold the key to a new biotechnological revolution, such as CRISPR-Cas systems. Given the colossal diversity of bacteria, crucial topics remain poorly understood, particularly: the diversity of antiphage systems, phage-inhibition mechanisms, and the impact of antiphage systems on phage therapy.

Serratia marcescens is a common cause of multi-drug resistant infections in nosocomial settings, with a 44% mortality rate in neonates. Many Serratia spp. are resistant to most clinically used antibiotics, thus alternative therapies are urgently needed. Phage therapy presents an opportunity to manage S. marcescens outbreaks. However, for this to be effective the vast arsenal of antiphage systems in S. marcescens must be better understood from genetic, evolutionary, and microbiological perspectives.

This project will explore the diversity of antiphage systems in S. marcescens using these multidisciplinary approaches. The PhD student will characterise novel antiphage systems in the S. marcescens pangenome and link this with protein-protein interaction data. This will: a) associate antiphage system variation with Serratia ecological niches, b) establish a high-throughput method for antiphage system discovery, and c) determine chromosomal locations where antiphage systems are enriched, favouring their discovery in other pathogens,

The PhD student will explore the antiphage activity of the identified novel systems in vivo and in vitro, and conduct in-lab evolution experiments to understand their mobilization and distribution under different phage-mediated threats.

The project’s findings will expand our understanding of known antiphage systems and illuminate their evolution and mobilisation within different strains. This will could underpin the rational design of phage cocktails and to engineer new molecular tools.

Detecting horizontal gene transfer and recombination in diverse dsDNA viral genomes and pangenomes (23DTP09)

TITLE: Detecting horizontal gene transfer and recombination in diverse dsDNA viral genomes and pangenomes

SUPERVISORS: Dr Bingxin Lu, University of Surrey (b.lu@surrey.ac.uk)

Dr Tim Downing, The Pirbright Institute (tim.downing@pirbright.ac.uk)

Many global livestock diseases are caused by viruses. Among these, nucleocytoplasmic large DNA viruses (NCLDVs) are a significant challenge for economic and animal welfare reasons. Central to NCLDV evolution are horizontal gene transfer (HGT) and recombination, which contribute to the diversification of NCLDV's double-stranded (ds)DNA genomes. These processes facilitate the exchange of genetic material, bring proteins with novel functions into new viral hosts, and thus lead to the emergence of new viral phenotypes. Because NCLDV genomes are complex with high rates of structural variation, repetitive elements, and similarity between genome ends, it is challenging to detect and quantify HGT and recombination between genetically distinct lineages. Tools exist for HGT and recombination analysis for prokaryotic and eukaryotic organisms and certain viruses, but none have been optimised for the major livestock NCLDVs. You will develop novel methods to detect HGT and recombination in key livestock NCLDVs, including African swine fever virus and poxviruses. This inter-disciplinary PhD opportunity spanning bioinformatics, evolution and virus genomics is based at University of Surrey and Pirbright Institute.

Objectives:

HGT/recombination detection: You will use pangenomics and unsupervised machine learning (ML) to identify regions of interest in virus genomes to uncover novel HGT and recombination events.

Validation: You will verify potential HGT and recombination events using phylogenetics and compare results to existing tools, enhancing the reliability of your new approaches.

Training: You can avail of comprehensive training in cutting-edge methods, spanning ML, genomics, viral genetics and communicating science.

Future Research: You will lay the groundwork for exploring evolution in the poxvirus family and repurposing your tools to other dsDNA viruses.

Training/Development:

The journey from supervision to independent decision-making will be tailored to your needs. You will receive guidance in various domains detailed above. You will be supported by regular meetings, extensive assistance, and opportunities to develop critical skills in written and verbal science communication. You will be encouraged to participate in national and international conferences. Both the University and Institute offer a wide array of in-house training courses to further support your growth. Balancing work, well-being and careers is crucial, and guidance on this will be readily available.

Downing T, Angelopoulos N. doi: https://doi.org/10.1098/rsif.2023.0344

Decano AG, Downing T. doi: https://doi.org/10.1038/s41598-019-54004-5.

Bingxin Lu, Hon Wai Leong. doi: https://doi.org/10.1142/S0219720018400103.

Bingxin Lu, Hon Wai Leong. doi: https://doi.org/10.1142/S0219720016400035.

Wright C, et al. doi: https://doi.org/10.1098/rsfs.2019.0066

Dissecting the host response of RSV infection at the post-transcriptional and post-translational level (23DTP10)

TITLE: Dissecting the host response of RSV infection at the post-transcriptional and post-translational level

SUPERVISORS: Dr Sneha Pinto, University of Surrey (s.pinto@surrey.ac.uk)

Dr Christina Ernst, The Pirbright Institute (christina.ernst@pirbright.ac.uk)

Lower respiratory tract infections are one of the leading causes of morbidity and mortality. Notably, respiratory disease caused by respiratory syncytial virus (RSV) in humans and calves results in significant economic and global health burdens. However, our understanding of the disease and immunopathogenesis caused by bovine and human RSV and the role of post-translational modifications (PTM) in modulating cellular pathways, specifically involving RNA binding proteins (RBPs), has been poorly explored. Our previous work with the respiratory virus SARS-CoV-2 showed that several RBPs undergo dynamic alterations in phosphorylation and acetylation levels, including some that have been shown to interact directly with the viral genome through complementary CLIP data. Further preliminary results using RSV show that RBPs are often found within viral inclusion bodies formed through phase separation that can be dynamically regulated through PTMs.

This Ph.D. studentship aims to employ a systems-level approach to identify dynamically regulated proteins following human and bovine RSV infection and further explore the impact of PTMs on the binding specificity of RBPs. The project's objectives include investigating the host responses, profiling the RNA targets of dynamically regulated RBPs, elucidating the effect of PTMs on RNA binding preferences of RBPs, and exploring the impact on innate signalling cascades and cellular immune responses.

The supervisory team comprises Dr. Sneha Pinto (School of Biosciences, University of Surrey) and Dr. Christina Ernst (The Pirbright Institute)- Systems biologists with significant experience in employing multi-omics approaches to delineate signalling dynamics in innate immune response and upon infections and Dr. Dalan Bailey (TPI) and Dr. Lindsay Broadbent (UoS), with expertise in RSV biology and pathogenicity.

You will undertake a multi-disciplinary research project that uses cutting-edge proteomics and next-generation sequencing approaches to dissect the host responses to RSV infections whilst working between the School of Biosciences and The Pirbright Institute. You will also develop skills in study design, multivariable/integrated data analysis and scientific writing. You are encouraged to develop as a motivated and independent researcher by benefitting from the supervisory team's knowledge, experience and multidisciplinary focus.

Assessing the role of microRNAs (miRNAs) in CHIKV Cellular Entry and Their Therapeutic Applications (23DTP11)

TITLE: Assessing the role of microRNAs in CHIKV Cellular Entry and Their Therapeutic Applications

SUPERVISORS: Dr Leandro Castellano, �պ�� (l.castellano@sussex.ac.uk)

Dr Naomi Forrester-Soto, The Pirbright Institute

(Naomi.Forrester-Soto@pirbright.ac.uk)

This project aims to use CRISPR and next-generation sequencing (NGS) to define the role of microRNAs (miRNAs) in chikungunya virus (CHIKV) infection, enabling the development of therapeutics based on miRNAs or their targets to treat CHIKV-related diseases.

CHIKV, endemic in tropical regions, causes persistent and debilitating arthralgia. Climate change is allowing the Aedes Albopictus mosquito, a carrier of CHIKV and other viruses, to invade Europe, posing a threat to also these countries (Ainsworth C, Nature, 2023). Despite this, there are currently no licensed vaccines or specific antiviral drugs available. miRNAs, 22 nt long non-coding RNAs, regulate post-transcriptional gene expression and have the potential to control genes involved in host infection of multiple viruses. This makes them promising antivirals, particularly with the rise of mRNA vaccines and the validation of delivery systems of RNA. For instance, Miravirsen, an antisense inhibitor of miR-122 is currently in a Phase II clinical trial because strongly reduces hepatitis C virus (HCV) RNA levels in chronic HCV genotype 1 patients (Janssen et al., N Engl J Med, 2013).

We utilised genome-wide CRISPR functional screens, to identify genes and miRNAs involved in CHIKV infection. These screens uncovered both known mediators of CHIKV infection and novel factors, with miRNAs emerging as potential potent CHIKV entry inhibitors (unpublished).

This project will further explore miRNA regulatory mechanisms and interactions with viral RNA and assess how CHIKV entry and replication is controlled by miRNAs. Using cutting-edge NGS technology and advanced biochemical assays, we intend to decipher the miRNA-gene regulatory networks governing CHIKV entry.

Ultimately, our goal is to develop effective miRNA-based drugs for treating CHIKV disease, offering a promising avenue for future therapeutic interventions. As part of this we will also validate the ability of these miRNAs to inhibit CHIKV infection of mosquitoes, a key driver of outbreaks.

The student will be trained in different aspects of molecular biology, bioinformatics and virology:

Tissue culture. The project will give the student a firm grounding in mammalian cell culture and generating pseudotyped viruses for use in various entry and inhibition assays.

Viral infection in in vitro and in vivo models: The project will provide the student with training to perform in vitro infections at CL3 and in vivo infections in mosquitoes again at CL3. Basic virology techniques will be used including plaque assays and cytopathic infection assays. In addition, the student will learn microscopy to identify changes in cell infections over time.

Molecular biology. They will learn how to perform molecular biology and biochemical techniques, such as CRISPR genome editing, activation and interference, western blotting, RT-qPCR, vector cloning and reporter assays, prepare libraries for NGS related approaches.

Bioinformatics. They will learn how to analyse NGS data, such as RNA-seq and miRNA-seq, as well as genome mapping and sequence alignment, primer design, guide RNA design and others.

Unveiling the genetic landscape of Capripoxvirus attenuation and host interaction through multi-omics (23DTP13)

TITLE: Unveiling the genetic landscape of Capripoxvirus attenuation and host interaction through multi-omics

SUPERVISORS: Dr Arnoud van Vliet, University of Surrey (a.vanvliet@surrey.ac.uk)

Dr Caroline Wright, The Pirbright Institute (caroline.wright@pirbright.ac.uk)

Capripoxviruses (CaPVs) are among the most serious of animal poxviruses, all of which cause WOAH notifiable diseases. Linking virus genotype to phenotype followed by inclusion of this information into predictive models of disease outcome, would be a powerful tool supporting global disease prevention and control strategy.

However, many aspects of the host-response dynamics of CaPV infection require a deeper understanding, while the role of genomic variants of the virus is mostly unknown.

To delve into these virus-host dynamics, this project will comprise of two principal phases, working predominantly with lumpy skin disease virus (LSDV), of the CaPV genus:

Phase one, supervised by virology experts at the Pirbright Institute (TPI) and University of Surrey (UoS), will involve serial passage of native LSDV in cell culture and extended to include reporter virus infections. Phenotypic change, e.g., adaptation to different cell culture conditions, will be observed through changes in infectivity and/or replication. RNAseq and virus complete-genome sequencing will be performed on infected cells, pre- and post-observed phenotypic change, using the in-house Illumina NextSeq 2K NGS platform. Studies may be extended to use the in-house single cell sequencer at Pirbright, and the interrogation of in vivo samples (held within TPI biobanks).

Phase two, supervised by bioinformatic experts at UoS and TPI, will involve the application of exploratory models of longitudinal transcriptomic data to viral genomic data to identify key processes in virus: host infection dynamics. Integrated data from phase one will be further used to develop novel predictive models of disease outcome.

Training/Development:

Tailored journey to independent decision-making.

Specialist guidance throughout via informal and regular formal meetings.

Opportunities to develop critical thinking, written and verbal communication skills through participation in national and international conferences.

A range of in-house training courses offered by both institute and university.

‘Work placement’ opportunity at the Hartree Centre (STFC) (on application)

Balancing work, well-being and career is crucial, and guidance will be readily available to support this.

Wright C, Orton J, et al.

Zhao Y, Lu Y, Richardson S, Sreekumar M, Albarnaz JD, et al.

Darling AL, Ahmadi KR, Ward KA, Harvey NC, Couto Alves A, et al.

Fay PC, Wijesiriwardana N, Munyanduki H, Sanz-Bernardo B, Lewis I, Haga IR, Moffat K, van Vliet AHM, et al.

Machine learning methods for the prediction of viral epidemic potential in global surveillance systems (23DTP15)

TITLE: Machine learning methods for the prediction of viral epidemic potential in global surveillance systems

SUPERVISORS: Dr Alexessander Couto Alves (a.coutoalves@surrey.ac.uk)

Dr David King, DSTL (dking1@dstl.gov.uk)

In this PhD project you will join a team of scientists from the University of Surrey and the Defence Science and Technology Laboratory (DSTL) to develop novel machine learning approaches to detect and predict infectious disease epidemics. The outcomes of this project will aid health and security agencies to delineate strategies to prevent and control infectious disease.

Currently there are no fast, accurate and inexpensive methods to predict viral epidemic potential, limiting in-depth surveillance and vaccine development. Events such as the COVID-19 pandemic and Ebola outbreaks have revealed several critical challenges, including deficiencies in early detection and surveillance.

We hypothesize that a pangenome approach, integrating genomic features (e.g. genomic elements, protein domain structure, mutation frequency) with host-virus interaction features (e.g. viral load, transmission route, incubation period) and spatial and dynamic phylogenetics can predict epidemic potential.

One of the challenges in bioinformatics data science is how to harness the (sequential) recurrency and high-dimensionality of DNA to build models of complex genetic phenomena. Our project aims at addressing these challenges integrating machine learning with statistical genomics to accelerate the process of extracting predictive genetic features that identify viral strains of concern.

Together with our Surrey and DSTL team, you will develop novel computational methods to identify genetic signatures that predict epidemic potential. You will harness the power of large databases and explore high dimensional machine learning methods, Bayesian statistics, phylogenetics, and spatially resolved models to develop novel methodology.

These methods will be initially tested to predict COVID-19 pandemic. We will integrate vast quantities of SARS-CoV-2 genomes (and other viral epidemics) with epidemiological data to identify novel genomic biomarkers that will be used to predict future pan-/epidemics.

The project will be conducted at the University of Surrey Biosciences and Medicine PhD programme, under the supervision of Drs. Alexessander Couto Alves and Carlos Maluquer de Motes within the Surrey Artificial Intelligence Institute, the Bioinformatics Core Facility, and Drs. David King, Tom Maishman, and David Ulaeto at DSTL. You will be integrated in a team of PhD students and bioinformatic scientists working on method development for genomic data analysis and you will have the opportunity for a placement at DSTL accessing additional datasets and resources.

This project provides an excellent opportunity to develop skills in Artificial Intelligence, Bioinformatics, Population genetics and Virology. The student will benefit from a vibrant and collegial environment with technical infrastructure and scientific expertise to provide training and support.

Applicants should hold or expect to gain a degree in bioinformatics, data science, statistics, machine learning, artificial intelligence, computer science, mathematics, physics, biology, or a closely related life, environmental or physical science. The project will involve analysis of large data sets and some familiarity with programming, especially R or Python would be required

Bispecific molecules for targeted delivery of novel antiviral to infected cells (23DTP16)

TITLE: Bispecific molecules for targeted delivery of novel antiviral to infected cells

SUPERVISORS: Dr Rachel Simmonds, University of Surrey (rachel.simmonds@surrey.ac.uk)

Dr Tom Laws, DSTL (trlaws@dstl.gov.uk)

Project Description:

Enveloped viruses (those that hijack host-cell membranes as part of their infection cycle) include many that are medically important, such as SARS-COV-2, influenza and ebola. However, for many of these we do not have effective and well-tolerated anti-viral treatments. We have recently identified a very exciting potential treatment that could help with a wide range of viral infection, but it is not very good at discriminating between infected and non-infected cells.

In this project, you will investigate different ways of targeting these drugs specifically to virally infected cells using two different advanced nanotechnology approaches. Bispecific molecules target drugs to cells due to the specificity of the antibodies contained within them. Liposomes and niosomes use specialised vesicles to help keep the drugs soluble and stable and are especially useful for natural medicinal compounds.

The drugs we are interested in specifically target a function of the host cell machinery that is required by envelope viruses to replicate and produce more infectious virions. This is the so-called Sec61 translocon; the entry point to the cell’s secretory pathway.

Training opportunities:

Therefore, in this project you will receive a comprehensive training in mammalian cell biology, virology, pharmaceutical development and nanotechnology. You will learn interdisciplinary skills between the two project partners, in the Department of Microbiology at the University of Surrey, and DSTL. Your project will mostly be based at Surrey where you will learn cutting-edge molecular analysis of RNA, DNA, proteins and cells. You will be trained to work in high containment, as well as in cell imaging techniques including immunofluorescence, confocal microscopy and super-resolution imaging. As part of your project you will also visit DSTL to develop methodology to generate bispecific molecules and liposomes/niosomes containing our drugs of interest.

Student profile:

The ideal candidate for this post would have a passionate interest in cell and molecular biology, virology, drug development or nanotechnology. They will be passionate about research and have a strong sense of curiosity.

The degree subjects most relevant to this project are: Biochemistry, Molecular Biology, Biomedical Science, Microbiology, Infection & Immunity.

Designing an anti-viral drug for Rift Valley Fever (23DTP17)

TITLE: Designing an anti-viral drug against Rift Valley Fever

SUPERVISORS: Dr Anthony Oliver, �պ�� (antony.oliver@sussex.ac.uk)

Dr Rachel Ireland, DSTL (REIRELAND@mail.dstl.gov.uk)

Rift Valley Fever (RVF) is an acute viral haemorrhagic fever that is most commonly seen in domesticated animals but can also cause severe illness in humans.

The project will involve development of an anti-viral drug that targets the Cap-domain of the RVF L-protein. Crystals of the ‘Cap domain’ diffract to high resolution and are highly amenable to drug-discovery by compound/fragment-soaking approaches.

At Sussex, the candidate will be trained in the expression, purification, and crystallisation of recombinant proteins (using the heterologous host E. coli). In addition, they will use the XCHEM platform at Diamond Light Source (Didcot, UK) to carry out fragment-soaking experiments to identify ‘hit’ material. In parallel, the student will be trained in programming, AI-based techniques, and a range of chemoinformatic techniques that includes compound library selection, virtual screening, scaffold-hopping and rational drug design. At DSTL, the candidate will have access to considerable expertise in molecular virology, plus a wide range of techniques including automated approaches for medium-to-high throughout antiviral screening.

References
1. Structural basis for the inactivation of cytosolic DNA sensing by the vaccinia virus. Rivera-Calzada A, et al. Nat Commun. 2022 Nov 18;13(1):7062. doi: 10.1038/s41467-022-34843-z

2. Uncovering an allosteric mode of action for a selective inhibitor of human Bloom syndrome protein. Chen X, et al . Elife. 2021 Mar 1;10:e65339. doi: 10.7554/eLife.65339

3. Competence of mosquitoes native to the United Kingdom to support replication and transmission of Rift Valley fever virus. Parasit Vectors. Lumley S, et al. (2018). 2018 May 18;11:308. doi: 10.1186/s13071-018-2884-7

Characterisation of Receptors and responses to alpha viruses in human microglia (23DTP18)

TITLE: Characterisation of Receptors and responses to alpha viruses in human microglia

SUPERVISORS: Dr Fernando Martinez Estrada, University of Surrey

(f.martinezestrada@surrey.ac.uk)

Dr Thomas Laws, DSTL (TRLAWS@mail.dstl.gov.uk)

In this PHD project we propose to focus on human microglia which are the macrophages of the brain, and investigate the receptors for key equine encephalitis viruses. The project will train you on IPSC cell culture, CRISPR CAS9, Macrophage receptor biology, proteomics and advanced virology. We are seeking candidates with a background in immunology, cellular biology, cellular virology, or related fields for a PhD in Immunology.

The encephalitic alpha viruses are not well researched despite the potential for these diseases to cause debilitating human and equine outbreaks, causing sequelae. Alpha viruses are also credible biothreat agents. There is no licenced treatment for any encephalitic alphavirus and understanding the molecular and cellular basis of disease will be essential in the development and evaluation of therapeutic strategies. Alphaviruses infect and replicate in macrophages. Further understanding of viral receptors in these cells is paramount to identify strategies to mitigate severity and transmission.

Our lab research is expanding towards identifying interactions with alphaviruses in humans and your work will contribute with this initiative. We will:

1) Develop a reliable Microglia model to study Virus interactions

2) Establish the encephalitis virus binding proteome of microglia from different donors

3) Confirm proteomics findings with CRIPSR CAS9 methodology.

Investigating mechanisms of lymphopenia in traumatic haemorrhage and resuscitation (23DTP19)

TITLE: Investigating mechanisms of lymphopenia in traumatic haemorrhage and resuscitation

SUPERVISORS: Dr Dr Qibo Zhang, University of Surrey (qibo.zhang@surrey.ac.uk)

Dr Robert Purcell, DSTL (rpurcell@dstl.gov.uk)

The Combat Casualty Care programme of research at Dstl investigates means of reducing mortality and morbidity in casualties of traumatic injury. Haemorrhage is a leading cause of death in trauma. The pathophysiological responses to traumatic haemorrhage and resuscitation result in numerous sequelae in survivors [1].

One important response is persistent lymphopenia and immunosuppression. This may be associated with wound infection, sepsis and multiple organ dysfunction syndrome. Whilst the manifestation of lymphopenia following traumatic haemorrhage is well-recognised, the mechanisms are a subject of ongoing debate [1, 2, 3].

This PhD will explore the potential mechanisms of lymphopenia, using archived samples from pre-clinical in vivo (terminally anaesthetised porcine models of traumatic haemorrhage and resuscitation) and in vitro methods [4, 5]. In addition to access to a unique archive of tissue samples to explore the research question, the candidate will be supported by an experienced team of scientists at Dstl with expertise in the pathophysiology, cell biology, immunology and pathology of trauma and resuscitation. The School of Veterinary Medicine, University of Surrey, has a state-of-the-art pathology facility, with a team of veterinary pathologists, scientists and technicians to support the candidate.

This cross-disciplinary PhD project will include training in multiple laboratory techniques. The PhD candidate would join a multidisciplinary team at Dstl and the University of Surrey. This includes veterinary and medical clinicians, surgeons and pathologists, cell biologists, immunologists, physiologists, biomedical scientists and statisticians.

[1] Dobson GP, Morris JL, Letson HL. Why are bleeding trauma patients still dying? Towards a systems hypothesis of trauma. Frontiers in physiology. 2022 Sep 6;13:990903.

[2] Manson J, Cole E, De’Ath HD, et al. Early changes within the lymphocyte population are associated with the development of multiple organ dysfunction syndrome in trauma patients. Critical Care. 2016 Dec;20:1-0.

[3] Bergmann CB, Beckmann N, Salyer CE, et al. Lymphocyte immunosuppression and dysfunction contributing to persistent inflammation, immunosuppression, and catabolism syndrome (PICS). Shock. 2021 55(6):723-741.

[4] Watts SA, Smith JE, Woolley T, et al. Resuscitation with whole blood or blood components improves survival and lessens the pathophysiological burden of trauma and haemorrhagic shock in a pre-clinical porcine model. European Journal of Trauma and Emergency Surgery. 2023 Feb;49(1):227-39.

Searching for superspreaders using a multi-scale modelling approach (23DTP20)

TITLE: Searching for superspreaders using a multi-scale modelling approach

SUPERVISORS: Dr Klara Wanelik, University of Surrey (k.wanelik@surrey.ac.uk)

Dr Joseph Gillard, DSTL (jgillard@mail.dstl.gov.uk)

We are seeking applications for a PhD project to explore the critical role of superspreaders in the transmission dynamics of infectious diseases. Superspreaders, identified as individuals with a disproportionate impact on pathogen transmission, are key drivers of infectious disease spread (Lloyd-Smith et al. 2005). This research project aims to identify epidemiological signatures for different types of superspreaders in order to help inform disease control strategies.

The study will shed light on two types of superspreaders: Supershedders, individuals who shed more infectious particles than average, and supercontacters, individuals who have more social contacts than average. The project seeks to identify early indicators and distinctive patterns associate with the presence of supershedders and/or supercontacters in a population. It also seeks to explore specific features of supershedders and/or supercontactors, and how they impact on these patterns.

The successful candidate will develop an integrated multi-scale model that incorporates both within-host and between-host dynamics. This model will facilitate the simulation of disease outbreaks driven by (i) supershedders, (ii) supercontacters, or (iii) both supershedders and supercontacters. The candidate will have the opportunity to develop the within-host model at the Defence Science and Technology Laboratory (Dstl) and the between-host model at the University of Surrey, benefiting from the relevant expertise available at both institutions. The student will then use the outcomes from their simulations to search for epidemiological signatures for supershedders and/or supercontacters. They will parameterise and test their model using openly available datasets for a diverse range of viral pathogens, including Ebola and Lassa virus, benefitting again from the relevant expertise in the supervisory team.

This interdisciplinary research program offers a unique opportunity for the selected candidate to contribute to ground-breaking research in the fields of infectious diseases and public health. The candidate will be supported by a team of experienced supervisors and will have the opportunity to make a substantial contribution to understanding superspreader dynamics, thereby informing the development of more effective strategies for controlling infectious disease outbreaks. As well as receiving extensive training in state-of-the-art modelling techniques, the candidate will have an opportunity to interact and collaborate with experts from a wide range of different backgrounds across both institutions (including mathematicians, epidemiologists, virologists, ecologists and AI researchers). They will be based at the University of Surrey and will regularly visit Dstl (Porton Down), where they will also have an opportunity to gain insight into how science and technology are used in the defence and security sectors.

We encourage applications from candidates with a strong background in epidemiology and/or computational modelling. The successful applicant will become part of a dynamic and innovative research environment, contributing to the advancement of global public health. This project is part of the Pathogens and Host Defences DTP programme.

References

Lloyd-Smith, JO, Schreiber, SJ, Kopp, PE, Getz, WM. Superspreading and the effect of individual variation on disease emergence. Nature. 2005; 438: 355–359. doi: 10.1038/nature04153

Emerging tick-borne viruses: Unravelling Infection Mechanisms in host and tick cells (23DTP21)

TITLE: Emerging tick-borne viruses: Unravelling Infection Mechanisms in host and tick cells

SUPERVISORS: Dr Marine Petit, University of Surrey (m.petit@surrey.ac.uk)

Dr Sophie Smither, DSTL (sjsmither@mail.dstl.gov.uk)

Crimean-Congo Haemorrhagic Fever (CCHF) is a deadly tick-borne viral disease classified as a high-priority area for Research and Development by the World Health Organization (WHO). This disease is currently endemic in regions spanning Africa, Asia, Eastern Europe, and the Middle East. Caused by the CCHF Virus (CCHFV), it primarily spreads to humans through infected tick bites. Despite its substantial morbidity and mortality rates, our understanding of CCHFV's pathogenesis and host-virus interactions remains limited, leading to the absence of specific treatments or vaccines. CCHFV is handled in Containment Level (CL) 4 laboratories.

Your PhD project aims to identify the factors essential for CCHFV infection within host and vector cells to develop new strategies to limit CCHFV dissemination. Leveraging recent advancements in high-throughput technologies, such as RNA- and protein sequencing, and expertise in tick-borne virology, the PhD project will adapt established system virology approaches to study CCHFV infection, and its CL2 surrogate Hazara virus. To fully describe the CCHFV infection, your project will be divided in 3 main objectives:

1) Characterization of Hazara and CCHF virus infection in mammalian and tick cells.

2) Comparison of the cellular responses to infection between mammalian and vector system.

3) Identification of potential antiviral targets.

Your work will be crucial in assessing, (a) the suitability of Hazara as a model virus for the study of CCHFV, (b) if mammalian and vector cells use similar antiviral responses, and finally (c) if we can target conserved antiviral pathways to generate novel antiviral strategies through drug design. Ultimately you will contribute to development of future control and prevention strategies against CCHFV infection.

Benefits of the studentship:

The project will offer experience in virology, and cell biology as well as data analysis and bio-informatic techniques.

Briefly, you will learn mammalian and tick cell culture, as well as viral infection in both systems. You will establish protocol suitable for high containment work conditions and collect samples to collect extensive datasets. Finally, you will characterize the viral infection through bioinformatic analyses.

Finally, we envisage a workplan where the student is based at DSTL or Surrey for significant blocks of time to become embedded in the research, culture, and network within each institution.

Eligibility :

We are seeking candidates with a background in cellular biology, cellular virology, or related fields. Open to UK nationals only.

Bioengineered 3D Blood-Brain Barrier (BBB) Using Cellular/Polymer Bioinks (23DTP22)

TITLE: Bioengineered 3D Blood-Brain Barrier (BBB) Using Cellular/Polymer Bioinks

SUPERVISORS: Dr Dr. Alessandra Pinna, University of Surrey (a.pinna@surrey.ac.uk)

Prof. Riccardo D’Elia, DSTL (rvdelia@dstl.gov.uk)

The project will explore novel 3D printed blood brain barrier in vitro model (BBB) that accurately represents the brain tissue environment, allowing the study of drug delivery across the BBB and to the brain tissue reducing the need for animal experiments. In particular, the proposal aim is to use advanced tissue engineering technique, 3D bioprinter system, to incorporate various cell types such as brain BMECs, astrocyte, pericytes, and neurons into polymeric bioink, like hydroxypropyl methylcellulose (HPMC) or polyvinyl alcohol (PVA) based hydrogel.

Biological, structural, mechanical, and morphological characterization of the 3D printed BBB in vitro model will be investigated using a multi-technique approach involving SEM, FTIR, compression test, Uv-vis and fluoresce spectroscopy, cell-based assays including state of-the-art microscopy like confocal, super-resolution or scanning electron microscopy.

Spanning across materials science, design engineering, chemistry, biology and medicine, this proposal is truly multidisciplinary. The PhD candidate will develop a range of complementary skills in 3D printing fabrication, drug delivery testing and cutting-edge characterisation techniques in addition to unique training and expertise in cells biology at NPL. The successful applicant will have access to the professional training courses and support offered by NPL’s Postgraduate Institute for Measurement Science (PGI) and Surrey’s Doctoral College.

References.

1) Paone L.S., Benmassaoud M.M., Curran A., Vega S.L., Galie P.A. “A 3D-printed blood-brain barrier model with tunable topology and cell-matrix interactions”. Biofabrication. (2024), 16, 015005.

2) Mohammed A.A., Miao J., Ragaisyte I., Porter A.E., Myanta C.W., Pinna A. “3D printed superparamagnetic stimuli-responsive starfish-shaped hydrogels.” Heliyon. (2023), 9, e14682.

3) Morfill C., Pankratova S., Machado P., Fernando N.K., Regoutz A., Talamona F., Pinna A., Klosowski M., Wilkinson R.J. Fleck R.A., Xie F., Porter A.E., Kiryushko D. “Nanostars carrying multifunctional neurotrophic dendrimers protect neurons in pre- clinical in vitro models of neurodegenerative disorders". Appl. Mater. Interfaces. (2022), 14, 47445-47460.

4) Woods S., O’Brien L.M., Butcher W., Preston J.E., Georgian A.R., Williamson E.D., Salguero F.J., Modino F., Abbott N.J., Roberts C.W., D'Elia R.V. “Glucosamine-NISV delivers antibody across the blood-brain barrier: Optimization for treatment of encephalitic viruses”, J Control Release. (2020).

Projecting operational effectiveness under new and emerging viral threats (23DTP23)

TITLE: Projecting operational effectiveness under new and emerging viral threats

SUPERVISORS: Dr. Joaquin Prada, University of Surrey (j.prada@surrey.ac.uk)

Dr Joe Gillard (JGILLARD@dstl.gov.uk)

The recent SARS-CoV-2 global pandemic has highlighted the need to improve surveillance for new and emerging threats and improved preparedness in critical sectors. One such sector is the management of military personnel when a new respiratory viral infection emerges. This project aims to evaluate risk of spread of a novel virus in an illustrative set of typical military contexts and assess the impact in operation effectiveness. You will learn and combine stakeholder elicitation techniques with transmission disease dynamics modelling integrating biology with mathematics and statistics, and engineering. The project is a well-established collaboration between the University of Surrey and the Defence Science and Technology Laboratory. Outcomes from this project will inform key partners, such as the military medical community, of potential risks and mitigation strategies.

The Principal Supervisor at Surrey, Dr Joaquin Prada, has been developing mathematical models to inform public health policy over a decade, and his research group focuses on integrating these models with health economics and stakeholder elicitation methods. Dr Prada’s group supports animal and public health policy across various settings and has collaborated with partners worldwide. While this is not a veterinary project, you will have to apply through the Veterinary Medicine and Science PhD, due to the affiliation of the principal supervisor.

An in vitro human lung model for studying emerging pathogens of concern (23DTP24)

TITLE: An in vitro human lung model for studying emerging pathogens of concern

SUPERVISORS: Dr. Mark Chambers, University of Surrey (m.chambers@surrey.ac.uk)

Dr Dominic Jenner (dcjenner@dstl.gov.uk)

Pathogens transmitted naturally by air or deliberately released as such, interact with the epithelium lining the upper and lower respiratory tract. Along with alveolar macrophages, these epithelial cells constitute the first line of defence in the lung, so understanding their role in determining the outcome of pathogen exposure may lead to new interventions. Such studies require tractable experimental models that are physiologically relevant.

Nipah virus (NiV) infection is a newly emerging zoonosis that causes severe encephalitic and respiratory disease in humans. It is on the WHO list of emerging pathogens likely to cause severe outbreaks and for which few medical countermeasures exist, thus research is a priority.

In this project, the candidate will make use of an established model of the human LRT using commercially available primary pneumocytes co-cultured with pulmonary endothelial cells at air-liquid interface and develop an alternative model of the URT. The models will be developed to first perform infection experiments using human parainfluenza (respiro)virus type 3 (HPIV-3) as a safer surrogate of NiV. HPIV-3 and NiV are paramyxoviruses that employ the same mechanisms of cell entry. Readouts will include host and viral transcriptomics and inflammatory cytokine release and a comparison of infection in both models. They will then progress to the design of mRNA transgene vaccines for both HPIV-3 and NiV. Immunogenicity studies will be conducted in mice and serum antibody responses assessed by ELISA and T cell responses by flow cytometry methods.

The candidate will be responsible for transferring the lung models to DSTL where they will be evaluated as 3Rs replacement models for NiV infection studies. The serum antibodies from the mouse vaccination experiments will be assessed in the two lung models for their ability to block the infection and pathology caused by HPIV-3 and NiV.

Thorough training will be provided in tissue culture, immortalisation of cells, infection studies using air-liquid interface tissue culture models of the lung, the culture and propagation of viruses, gene expression, immunogenicity, ELISA, flow cytometry, along with assays for pathogen attachment and transmigration, cell death, cytokine production, transepithelial electrical resistance to measure barrier integrity, cell imaging/confocal microscopy, qPCR, and working safely at high containment.

Although using animals to produce antiserum through vaccination, this project contributes to the 3Rs by seeking an alternative to animal challenge. It will contribute tractable in vitro models that will lead to reduction and ultimately replacement for some studies that are currently undertaken in animals.

References:

Escaffre O, Borisevich V, Vergara LA, Wen JW, Long D, Rockx B. (2016). Characterization of Nipah virus infection in a model of human airway epithelial cells cultured at an air-liquid interface. J Gen Virol. 97(5):1077-1086.

Lee DF, Stewart GR, Chambers MA (2019). A co-culture model of the bovine alveolus. Version 2. F1000Res. 8:357.

Porotto M, Ferren M, Chen YW, Siu Y, Makhsous N, Rima B, Briese T, Greninger AL, Snoeck HW, Moscona A. (2019). Authentic Modeling of Human Respiratory Virus Infection in Human Pluripotent Stem Cell-Derived Lung Organoids. mBio. 10(3):e00723-19.

Smither SJ, Eastaugh LS, O'Brien LM, Phelps AL, Lever MS. (2022). Aerosol Survival, Disinfection and Formalin Inactivation of Nipah Virus. Viruses. 14(9):2057.

Dold C, Marsay L, Wang N, Silva-Reyes L, Clutterbuck E, Paterson GK, Sharkey K, Wyllie D, Beernink PT, Hill AV, Pollard AJ, Rollier CS. (2023). An adenoviral-vectored vaccine confers seroprotection against capsular group B meningococcal disease. Sci Transl Med. 15(701):eade3901.

Bayesian Models of Inter-Individual Variation in Host-Response to Vaccine and Antiviral Therapy (23DTP25)

TITLE: Bayesian Models of Inter-Individual Variation in Host-Response to Vaccine and Antiviral Therapy

SUPERVISORS: Dr. Alexessander Couto Alves, University of Surrey (a.coutoalves@surrey.ac.uk)

Dr Tom Maishman (tmaishman@dstl.gov.uk)

In this PhD project you will join a team of scientists from the University of Surrey and the Defence Science and Technology Laboratory (DSTL) to develop novel Bayesian statistical models of response to vaccine and antiviral therapy. The outcomes of this project will aid pharmaceutical companies, and research institutes to develop precision vaccines and antiviral therapies.

Currently there are no accurate and powerful methods to predict individual response to vaccine and antiviral therapy, hampering selection of countermeasures and the management of epidemics.

We hypothesize that groups of patients with different responses underpin part of the variability in response to vaccine and antiviral therapy. Consequently, conclusions about benefit or harm for most treatments can be deceptive and fail to distinguish the complex mixture of results indicating benefit for some, little benefit for others, and harm for a few.

One of the challenges in predicting individual responses to treatment is dealing with arbitrary survival functions and heterogeneous groups of individuals. Our project aims at addressing these challenges developing novel methodology combining survival analysis, Bayesian model averaging, and mixture models to jointly estimate from data the treatment effect and patient subgroup.

Together with our Surrey and DSTL team, you will develop novel computational methods to identify subgroups of patients with different response to treatment using Bayesian Mixture Models. You will harness the power of machine learning methods to implement arbitrary nonlinear hazard functions and explore Bayesian model averaging to build novel survival functions.

These methods will be initially tested datasets generated by our vaccine and antiviral studies to develop novel methodology. We will also test these methods in publicly available benchmark datasets for survival analysis to estimate individual response to treatment and vaccine.

The project will be conducted at the University of Surrey Biosciences and Medicine PhD programme, under the supervision of Drs. Alexessander Couto Alves and Christine S. Rollier within the Surrey Artificial Intelligence Institute, the Bioinformatics Core Facility, and Drs. Tom Maishman, and Tom R. Laws at DSTL. You will be integrated in a team of PhD students and bioinformatic scientists working on method development and you will have the opportunity for regular meetings at DSTL accessing additional datasets and resources.

This project provides an excellent opportunity to develop skills in Bayesian Statistics, Survival and Mixture Models, Vaccinology and Virology. The student will benefit from a vibrant and collegial environment with technical infrastructure and scientific expertise to provide training and support.

Applicants should hold or expect to gain a degree or equivalent, in bioinformatics, data science, statistics, machine learning, artificial intelligence, computer science, mathematics, physics, biology, or a closely related life, environmental or physical science. The project will involve analysis of large data sets and some familiarity with programming, especially R or Python would be required.

�պ�����

Sussex Researcher School

Pathogens and Host Defences Doctoral Training Partnership

Sussex Researcher School

�պ��