SARS-CoV-2 Translational Research
SARS-CoV-2, the causative agent of Coronavirus Disease 2019 (COVID-19), is responsible for a global pandemic of immense scale and consequence, killing hundreds of thousands of people and disrupting the social and economic well-being of communities around the globe. While roughly 80% of cases are mild to asymptomatic, nearly 20% of cases present with severe symptoms that can require hospitalization. Clinicians and scientists around the globe are trying to understand the molecular basis of viral replication and pathogenesis in order to develop better diagnostics, novel treatments, and effective preventative therapies like vaccines.
In the Hultquist lab, we are using whole viral genome sequencing to track the epidemiological origins of the virus in our hospitals and in Chicago as a whole. These virological data are being used to supplement clinical and demographic datasets to develop holistic models of disease severity and treatment outcome using data science methods. In addition, we are performing biochemical characterization of novel mutations arising in viral populations to determine their functional consequence. Due to the expansive nature of our biobank, we are also able to conduct longitudinal sequencing studies that provide insight the evolutionary nature of SARS-CoV-2 as well as characterization of antiviral resistance mutations. Finally, we are employing functional genomic strategies to better understand the host factors underpinning viral replication, but also the host response to infection. By supplementing clinical datasets with additional information about the virus and host response, we hope to improve our options for the clinical management of COVID-19 as well as for the overall management of the pandemic.
Active Projects:
- Sequencing COVID-19 patient isolates to track viral epidemiology;
- Mapping the host factors involved in SARS-CoV-2 replication;
- Biochemical analysis of novel SARS-CoV-2 protein variants;
- Building holistic, multivariate models of disease outcome and severity.
- Identification of Remdesivir resistant mutations;
- Modeling of SARS-CoV-2 transmissibility using phylogeography and machine learning;
Supported by the Northwestern Memorial Foundation Dixon Family Translational Research Award, the Northwestern Cancer Center (NIH/NCI P30 CA060553) in collaboration with the Center for Structural Genomics of Infectious Diseases, the Clinical and Translational Science Award (CTSA) centers at Northwestern University and the University of Chicago (UL1 TR000150; UL1 TR002389), the SCRIPT Center (U19 AI135964) and the QCRG Antiviral Drug Discovery Program (U19 AI171110).