Pandemic Preparedness

Through Advanced Genomic Research

Our research leverages bioinformatics to deepen our understanding of emerging pathogen evolution and to develop predictive models for preparedness against infectious diseases. Harnessing the predictive power embedded within multi-species genomic data, including the dynamic interactions between hosts and pathogens, this research axis is dedicated to enhancing the computational toolbox available for pandemic preparedness, thereby addressing the gaps in our capacity to anticipate and effectively respond to global disease outbreaks. We collaborate with the Laboratoire de Santé Publique du Québec, and we are part of the Computational Analysis, Modelling and Evolutionary Outcomes (CAMEO) group within the Coronavirus Variants Rapid Response Network (CoVaRR-Net).

db.NetworksMutationsTime.2021_03_12

First wave of SARS-CoV-2 genomic evolution: Spanning trees done based on subsequences derived from >50,000 consensus sequences downloaded from GISAID as of July 10th, 2020. Subsequences are formed of high frequency mutations (found at a frequency of at least 5% worldwide at a certain point in time between March 1st and July 10th).  Credit: Isabel Gamache

Our Research Focus:

  • Genomic Surveillance & Pathogen Evolution Prediction: Our group excels in the continuous surveillance of pathogen variants. Through deep viral profiling and our collaboration with the Laboratoire de Santé Publique du Québec (LSPQ), we strive to understand the genetic diversity of viruses both within and across populations globally. Our tools for data visualization and imputation enhance our capabilities in monitoring dynamic transmissions and identifying evolutionary pressures on viruses.
  • Immunological Response to Emerging Pathogens: We study the interactions between pathogens and the human immune response. By exploring human leukocyte antigen (HLA) diversity and its influence on immune responses, our work is pivotal in developing strategies for T cell evasion and vaccine improvement. Integrating evolutionary biology with immunological insights, our predictive models are designed to anticipate how mutations affect pathogen evolution and immune evasion, providing critical insights for public health interventions.

Our holistic approach aids in formulating comprehensive pandemic preparedness strategies that consider both genetic diversity and health equity.

Current Group Contributors (alphabetical order):
Grenier JC, Hamelin D, Mostefai F, Poujol R, Rochefort-Boulanger C., Scicluna M.

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