Coevolution of Viruses and the Immune System
Inside our body, a battle rages between the immune system and disease-causing pathogens. Striving for an advantage, pathogens constantly evolve to evade detection by the immune system.
In 2010, Microsoft researchers—together with colleagues from Murdoch University in Western Australia, the University of Western Australia, and Fundación Ciencia para la Vida in Chile—explored this evolutionary struggle. Their study focused on human leukocyte antigen (HLA) molecules, which sample cellular proteins and present them on the cellular surface for examination by our immune system. (See Mapping the Landscape of Host-Pathogen Coevolution: HLA Class I Binding and Its Relationship with Evolutionary Conservation in Human and Viral Proteins).
When viruses infect a cell, they bring their own genetic material into the cell and use cellular resources to propagate. As a result, HLA molecules present viral proteins on the infected cell’s surface, spurring an immune attack on the "odd" cells. However, viruses often mutate to evade detection, altering the protein segments that HLA molecules are most likely to present.
On the other side, the distribution of the thousands of HLA variants present in human populations can change over many generations. This sets up an evolutionary game: viruses on one side, our immune system on the other. To analyze this contest, the researchers quantified HLA-binding preferences according to targeting efficiency, a novel measure that captures the correlation between HLA-binding affinities and the genetic conservation in the targeted regions. In theory, HLA molecules should draw attention to protein segments that are shared across related viral species, as such regions should be functionally important and thus immutable.
Analysis of targeting efficiencies indicated that HLA molecules do indeed prefer to target such conserved regions. The magnitude of this preference varies in a way that shows evidence of target splitting, where two different HLA loci focus on different viral families. This phenomenon is consistent with theoretical biology predictions for predator-prey models and indicates that targeting efficiency as a measure of the HLA-virus links will be useful in analyzing viral evolution. Furthermore, in many cases the host’s total targeting efficiency scores for various viruses correlate with clinical outcomes, offering a potentially useful system of measures for analyzing infection outcomes in individual patients or entire human populations under different conditions, such as post-vaccination or following a previous viral infection.
Primary Researchers
Simon Mallal is director of the Institute for Immunology and Infectious Diseases at Murdoch University and a clinical immunologist and immunopathologist at Royal Perth Hospital. He studied Medicine at the University of Western Australia; has managed patients with HIV, autoimmune, and allergic disease in Perth since 1987; and supervises the associated routine diagnostic immunology and molecular biology laboratory. He is a clinical immunologist trained in Internal Medicine and Immunopathology and completed a post-doctoral Fellowship in Infectious Diseases at the Johns Hopkins School of Medicine.
He has had a longstanding research interest in the major histocompatibility complex (MHC) and genetic influences on clinical outcomes in HIV and other diseases. More recently, he has focused on viral adaptation to HLA-restricted immune responses and the implications of this for HIV vaccine immunogen design. His group also studies the genetics and pathogenesis of hypersensitivity to abacavir and nevirapine and the long-term complications of anti-retroviral therapy with a particular focus on mitochondrial toxicity and subcutaneous fat wasting. He was the recipient of the West Australian Premier’s Award in Science in 2005.
Tomer Hertz received his B.Sc. degree in Computer Science and the Amirim Interdisciplinary Program in the Humanities for outstanding students from the Hebrew University in 1999, and his Ph.D. in Computational Neuroscience from the Hebrew University in 2007. He then received postdoctoral training in the Microsoft Research eScience group, working with Nebojsa Jojic.
His general research interests are in machine learning and computational immunology. His research in the field of machine learning focuses mainly on learning distance functions using equivalence constraints, with applications in semi-supervised learning, clustering, and kernel learning. Within the field of computational immunology, he has developed a framework for major histocompatibility complex (MHC) protein-peptide binding prediction and MHC supertype classification. His recent work focuses on T-cell and B-cell immunodominance, HLA binding prediction and its applications in vaccine design, sieve analysis, improved epitope mapping protocols, developing computational models of T-cell immunodominance, and developing a high-throughput platform for high-resolution mapping of B-cell responses by using antigen microarrays.
Nebojsa Jojic is a principal researcher at Microsoft Research. Nebojsa is interested in machine-learning approaches to building compact representations of natural signals that reveal patterns of scientific and practical importance.
