The Centre aims to integrate scientists whose research interests span across traditional biological disciplines. This integration will provide a framework to address 6 key research themes in infection biology:
Past present and future pathogen evolution: How does new disease emerge, virulence evolve and drug resistance spread?
The analysis of ongoing viral epidemics, especially HIV and influenza, unequivocally demonstrate the pace of pathogen evolution in real time. Such events can be tracked by population genomic analysis, which can also be applied to bacterial and parasite genomes to follow the emergence of drug resistance, or changes in host range and pathogenesis. Although the underlying selection pressures appear predictable, in reality the complex interactions of emergent host-pathogen relationships and their interactions in a diverse host population create considerable uncertainty, generating risks as diseases transmit between humans and animals. In this theme, we will identify the genetic changes that provide the early-warning signals for disease emergence or drug resistance and exploit evolutionary analysis and modelling approaches to help predict, and limit, their spread through populations.
Polymorphism and diversity: How does evolution shape the genetic polymorphisms that contribute to disease susceptibility or resistance?
Polymorphism is to a large extent maintained in the human population by pathogens, and understanding the forces that maintain polymorphisms is of critical importance: for example the frequency of susceptible genotypes is a clear correlate of infection risk. Both the pattern and the specifics of host polymorphisms can instruct us how pathogens are contained and pathology minimised. In the context of chronic infections and co-infections, however, pathogen exposure may select for particularly complex and graduated genetic responses. These combinations of polymorphisms can regulate the quantitative levels of cytokines or select structural polymorphisms controlling ligand-binding by immune receptors, for example.
Optimal immunity: How has the immune system evolved to function optimally in the presence of multiple pathogens and diverse environmental conditions?
The immune system must operate in a highly variable environment in which coinfection is the norm and resources are frequently limiting. Traditionally, however, research has sought to understand host immunity in the context of a single pathogen under defined conditions. It is increasingly clear that removing one set of pathogens in a co-infection or altering commensal populations can generate a void exploited by other pathogens, leading to an imbalanced immune response, with potential for immunopathology including autoimmunity, allergy and asthma. New therapeutic strategies and vaccination approaches must address the need for optimal immunity in real world conditions to avoid these adverse immune consequences or the emergence of new pathogens.
Intrinsic and extrinsic signals: Can we exploit host and pathogen signalling networks to promote vaccine efficacy or disrupt parasite development?
Cell signalling events dominate the developmental programmes of both the immune system and pathogens. Moreover, these signalling pathways are among the most highly conserved processes in eukaryotic evolution, generating the possibility for interaction and interference between hosts and pathogens- with the potential for immune dysfunction or modulation. An exciting prospect, therefore, is to identify and manipulate host or pathogen signals in order to optimise immunity or disrupt parasite life histories.
Transmission biology and host range: What are the drivers of disease spread at the molecular and epidemiological level?
The emergence and spread of pathogens is determined by pathogen transmission mechanisms and a breakdown in host-range restriction. Both are central to infectious disease and require understanding of (i) the interaction between molecules at the host-pathogen interface and (ii) the interactions between species and populations at an epidemiological level. We aim to identify the key parameters governing transmission at these different levels, applying quantitative analysis and evolutionary theory to understand how pathogens spread. Combining these different approaches will foster new ideas and strategies for disease containment.
Promoting parameterisation: Can the interaction between traditional experimentation and quantitative analysis derive new insight into infection biology?
Laboratory research has progressed from a traditional focus on individual molecules or processes to an environment where high-throughput quantitative analytical approaches (e.g. next generation sequencing, quantitative proteomics, cytokine and transcript expression multiplexing) measure multiple infection components in parallel. This greatly increases the potential to interpret experiments at a system scale, through quantitative analysis and modelling. However, we believe that a key requirement of this interpretative power is a well-grounded knowledge of the biological system, enabling appropriate assumptions to be built into models and outputs to be identified that reflect established knowledge. At the molecular level, this improves the ability to identify and target pathogen processes; at the population level it helps to predict the impact of control strategies against pathogens.