Hosted by Cardiff University's School of Medicine
Pathogens evolve much faster than their hosts, resulting in the emergence of new strains, or antibiotic-resistant bacteria. Many pathogens alter their gene expression in response to the host environment, allowing them to hide in latent or persister states. Our multilayered immune system provides a robust and tailored response to pathogens. However, the immune system is a double-edged sword, and when dysregulated, it can lead to long-term disease sequelae. Understanding the contribution of these multitude forces in controlling the balance between protection and susceptibility to infections requires a deep dive into the pathogen and its host. In my talk, I will explore how two vastly different bacterial pathogens engage our immune system. I will delve into their immune evasive strategies, the countermeasures we’ve evolved to combat them, and how systems-level approaches can enable a path forward for fully understanding infectious disease.
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Naeha Subramanian received her PhD from the National Institute of Immunology at Jawaharlal Nehru University in New Delhi, India. After completing postdoctoral training at the National Institutes of Health, she joined the Institute for Systems Biology; currently she is an Associate Professor and an Affiliate Associate Professor at the Department of Immunology, University of Washington. Her research focuses on the molecular mechanisms of innate immunity mediated by a class of cytosolic sensor proteins called NOD-like receptors (NLRs) that detect ligands of microbial or endogenous origin and stimulate innate immune activities. Gain of function mutations and polymorphisms in NLRs are associated with a host of severe human autoinflammatory and autoimmune disorders. The Subramanian lab aims to apply unbiased systems biology approaches to define NLR response phenotypes and associated signaling pathways. The goal is to provide insights into not only how NLRs normally function but to ultimately uncover new pathways to therapeutics for diseases related to aberrant NLR function.