Computational Biology of Infection Research
Computational biology of viral pathogens
The Research Department “Computational Biology for Infection Research” at the HZI studies rapidly evolving viral pathogens, such as influenza, hepatitis and human cytomegaloviruses and their coevolution with the adaptive immune response of the human host using computational techniques. A particular focus are influenza A viruses, where we combine epidemiological, genetic, antigenic and structural information on circulating viral strains to determine the antigenicity-altering areas on the protein structure, key sites and amino acid changes and analyze how these affect the viral fitness with regards to escaping human immune response [1, 3, 5]. In collaboration with infection biologists and immunologists from the HZI, the Hannover Medical School and the German Centre for Infection Research (DZIF), we also study the adaptation of influenza viruses to novel hosts and for maintaining fitness under immune selection in animal models. Viral pathogens such as hepatitis and human cytomegaloviruses differ from influenza viruses in that they cause chronic, not short-term infections. Together with collaborators we track the evolution of these pathogens and the corresponding adaptive immune ‘evolution’ of the host within individual patients over time. We thus aim to generate novel insights into pathogen-host co-evolution and identify leads of translational relevance, such as for development of a universal vaccine against hepatitis C virus infections.
Specifically, we focus on
- Computational prediction of vaccine strains for the human influenza A viruses
- Determining epitopes for broadly neutralizing antibodies for development of a “universal vaccine” against hepatitis C virus infections
- Detecting reassortment events and their relevance for adaptation in influenza viruses
- Reconstructing viral haplotypes from deep sequencing data
- Inference of viral spread trajectories with viral phylogeographies
- A.C. McHardy, B. Adams
The role of genomics in tracking the evolution of influenza A virus.
PLoS Pathogens 2009, 5(10): e1000566
- L. Steinbrück, A.C. McHardy
Inference of Genotype-Phenotype Relationships in the Antigenic Evolution of Human Influenza A (H3N2) Viruses.
PLoS Comput Biol 2012, 8(4): e1002492
- C. Tusche, L. Steinbrück, A.C. McHardy
Detecting patches of protein sites of influenza A viruses under positive selection.
Mol Biol Evol 2012, 29(8): 2063-2071
- C. Kratsch, T.R. Klingen, L. Muemken, L. Steinbrueck, A.C. McHardy
Determination of antigenicity-altering patches on the major surface protein of human influenza A/H3N2 viruses.
Virus Evolution 2016, 2(1)
- L. Steinbrück, T.R. Klingen, A.C. McHardy
Computational prediction of vaccine strains for human influenza A(H3N2) viruses.
J Virol 2014, 88(20): 12123-32
- T.R. Klingen, S. Reimering, C.A. Guzman, A.C. McHardy
In Silico Vaccine Strain Prediction for Human Influenza Viruses.
Trends Microbiol 2017, doi:10.1016/j.tim.2017.09.001
- Dr. Sebastian Muñoz
- Akash Bahai
- Thorsten Klingen
- Jens Loers
- Susanne Reimering
- Victoria Sack
- Gülsah Gabriel, Heinrich Pette Institute, Leibniz Institute for Experimental Virology, Hamburg
- Carlos Guzmán, Department of Vaccinology and Applied Microbiology, Helmholtz Centre for Infection Research (HZI), Braunschweig, Germany
- Thomas Pietschmann, Institute for Experimental Virology, Twincore Centre for Experimental and Clinical Infection Research, Hannover, Germany (DZIF collaboration)
- Thomas Schulz, Institute of Virology, Hannover Medical School (MHH), Hannover, Germany
- Klaus Schughart, Infection Genetics, Helmholtz Centre for Infection Research (HZI), Braunschweig, Germany
- Thomas Krey, Institute of Virology, Hannover Medical School (MHH), Hannover, Germany