Ph.D.: The Hebrew University of Jerusalem, Israel
Post-doctorate: Microsoft Research, USA
Position: Senior Lecturer
The Shraga Segal Department of Microbiology, Immunology and Genetics
Faculty of Health Sciences
Computational and experimental approaches to studying immunodominance
In the arms race between pathogen and host, the adaptive immune system uses a diverse set of pattern detectors to identify and eliminate pathogens and pathogen infected cells. These detectors bind to short contiguous (T-cells, B-cells) and non-contiguous (B-cells) protein fragments called epitopes. During the course of an infection the immune system focuses its response to a small fraction of the thousands of potential targets. This phenomenon, known as immunodominance, is a fundamental property of the adaptive immune response. Understanding the mechanisms that govern immunodominance is crucial for designing vaccines. Immunodominance is a result of a large number of factors including immunological history, antigen processing and presentation, viral load and kinetics of viral expression, and host genetics.
We are developing computational and experimental tools to study the underlying mechanisms that govern T-cell and B-cell immunodominance in both natural infection and vaccination. The main research objective is to identify both viral and host features that define and modulate immunodominance hierarchies. The nature of our work is translational, integrating the design and application of computational approaches with clinical and laboratory studies that provide data for validating and refining our computational tools.
1. Using HLA binding predictors to study T-cell immunodominance – Human Leukocyte Antigen alleles present short peptides on the surface of cells to cytolytic T-cells. We and others have developed computational tools to predict which targets are likely to be presented to cytolytic T-cells. We are using these tools to develop computational tools for predicting which pathogenic targets are likely to become immunodominant, with applications to vaccine design and analysis of T-cell responses following both vaccination and natural infection.
2. Quantifying the effects of immunological history on immune responses to natural infection and vaccination – Previous exposure to pathogens and vaccination is one of the key factors that bias the response to a novel vaccine or infection. We are developing a high-throughput assay for profiling immunological history using the technology of antigen microarrays.
3. Using adjuvants to shift vaccine-induced immunodominance patterns – Adjuvants are widely used in licensed vaccines to boost the vaccine-induced immune responses. We are investigating the effects of different adjuvants on antibody immunodominance patterns.
4. Computational identification of host specificity determinants in influenza infection – Influenza pandemics occur when a novel strain is introduced into the human population from different animal hosts such as birds and swine. The molecular mechanisms that allow an influenza virus to adapt to the human host are poorly understood. We are developing an approach for computationally elucidating Influenza virus mutations that are essential for the adaptation to the host.
Hertz T., Nolan D., James I., John M., Gaudieri S., Phillips E., Huang J.C., Riadi G., Mallal S. and Jojic N. (2011). Mapping the Landscape of Host-Pathogen Coevolution: HLA Class I Binding and Its Relationship with Evolutionary Conservation in Human and Viral Proteins. Journal of Virology 85:1310-1321.
Meroz D., Yoon S.W., Ducatez M.F., Fabrizio T.P., Webby R.J., Hertz T.* and Ben-Tal* N. (2011). Putative amino acid determinants of the emergence of the 2009 influenza A (H1N1) virus in the human population. Proceedings of the National Academy of Sciences of the United States of America, 108: 13522–13527.
Hertz T., Ahmed H., Friedrich D., Horton H., Frahm N., McEl- rath J., Corey L. and Gilbert P. (2013). HIV-1 Vaccine Induced T-cell Reponses Cluster in Epitope Hotspots that Differ From Those Induced in Natural Infection with HIV-1. PLoS Pathogens 9(6):e1003404.
Hertz T., Oshansky-Weilnau, C., Roddam P.L., DeVincenzo J.P., Caniza M.A., Jojic N., Mallal S., Phillips E., James I., Thomas P., Halloran B. and Corey L. (201#). HLA Targeting Efficiency Correlates with Human T-Cell Response Magnitude and with Mortality from Influenza A Infection. PNAS 110(33):13492-13497.
Keating R., Hertz T., Lukens J.R., Harris T.L., Edwards B.A., Wehenkel M., McClaren J.L., Brown S.A., Surman S., Hurwitz J., Doherty P.C., Thomas P.G. and McGargill M.A. (2013). mTOR modulates the anti- body response to provide cross-protective immunity to lethal influenza infections. Nature immunology 14(12): 1266-1276.