Tissue immunity and immune memory in response to viral and bacterial lung infections
Not stated
- Location
- London, United Kingdom
- Funding
- Funded PhD Project (Students Worldwide)
- Application deadline
- 2 November 2026
About the project
About the Project A 2027 Crick PhD project with Andreas Wack. Project background and description We are interested in determinants of disease severity in lung infections including influenza, COVID and bacterial infections. We study this in organotypic lung in vitro models as well as in vivo models, using bacterial and viral strains that lead to infection in mice, including mouse-adapted SARS-CoV-2 virus. We are interested in several aspects: 1. How inflammatory processes, indispensable early in infection, can go out of control and contribute more to tissue damage than to an efficient antiviral response. In particular, we have shown that the antiviral cytokine family of interferons (IFNs), when present at too high levels or too late during viral infections, can aggravate disease by immunopathogenesis, delayed lung epithelial repair and unfavourable modulation of innate and adaptive immune cell function [1, 2]. 2. We study the biology of lung epithelia as they are crucial for the essential lung functions of air conductance and gas exchange, are often the main infection target of pathogens, produce key chemoattractants upon pathogen sensing, and must be repaired fast and efficiently to limit tissue damage and loss of lung functionality. We have shown recently that airway epithelia need to metabolically rewire for full differentiation [3], and it is unclear whether the above-mentioned IFN effects on lung epithelia may be mediated by modifying or directly blocking this metabolic rewiring. We also don’t know how other inflammatory drivers, hypoxia or infection impact on epithelial development and regeneration. 3. As humans constantly get acute lung infections, an important question is what imprint these infections leave behind after resolution, and what impact this has on subsequent infections. We have previously shown that influenza leads to persistent changes in lung immunity, through the establishment of a population of highly immunoreactive monocyte-derived alveolar macrophages (AMs) [4]. We found that this high immunoreactivity is a conserved blueprint in these cells (unpublished). Under the influence of the lung environment, monocyte-derived AMs however slowly lose their immunoreactivity (“immunosedation”) and become increasingly similar to the embryonic-derived, relatively unresponsive AM population that is also found in naïve mice [5]. The exact nature of the immunosedating signals from the lung environment to AMs, the question of whether or not epithelial and other non-immune cells in the lung also receive a lasting imprint during infection, and the crosstalk between these cell types are currently under investigation . The PhD project proposed here will be placed at the crossroads of tissue response to infection, metabolism, repair processes, and immune cell – epithelial interactions that take place at steady-state or during and after acute infections. The aim is to understand how the individual biography of infections modifies the response to subsequent infections. Well-characterised in vivo infection models, combined with in vitro organotypic cultures and state-of-the-art techniques (e.g. scRNAseq, ATACseq, Cut&Run, Scenith, spatial analysis strategies) will be used to understand how the interaction between immune and non-immune cells helps maintain lung immunity, propagate imprints but also adapt to a changing environment. Candidate background Candidates should be interested in the tissue response and tissue immunity to infection, as well as tissue immune memory imprinted by infection. Ideally, they find innate and adaptive immunity and memory equally interesting and have in vitro and/or in vivo experience in this area. Applications from individuals with a background in epithelial or endothelial cell biology, bioinformatics and experience in generation and analysis of epigenetic data would also be appreciated. Data mining of both in-house and published data is integral to this project. Lab-specific question Looking at the research undertaken in our lab, what aspect would you be most interested in exploring further? Drawing on your own research experience, what perspective, skill or approach would you bring to investigating it?