Understanding metabolite production by the Lachnospiraceae family to support live biotherapeutic development
As part of our Monday seminar series, we are delighted to welcome our speaker:
Talk title: Understanding metabolite production by the Lachnospiraceae family to support live biotherapeutic development
Matthew Sorbara, PhD
Assistant Professor
Department of Molecular and Cellular Biology
University of Guelph
Hosted By
How to join
The event will be in person only, no need to register.
MSB 2172
Medical Sciences Building
University of Toronto
1 King’s College Circle
Toronto, ON M5S 1A8
If you have any questions about this event, please contact Debb Yorke at lmp.chairadmin@utoronto.ca.
Speaker: Matthew Sorbara PhD
Dr. Sorbara completed his undergraduate degree in Molecular Genetics and Microbiology at the University of Toronto (2009). He then completed his PhD training in Immunology with Dr. Dana Philpott, studying the regulation of NOD2-triggered proinflammatory responses by the autophagy protein ATG16L1 (2016 - University of Toronto). From 2016 to 2017, he worked as a postdoctoral fellow in the laboratory of Dr. Stephen Girardin studying the interaction of complement C3 with ATG16L1. In 2017, Dr. Sorbara joined the laboratory of Dr. Eric Pamer at Memorial Sloan Kettering Cancer Center (NYC) and in 2019 moved with the laboratory to the newly established Duchossois Family Institute at University of Chicago. In the Pamer laboratory, he studied the mechanisms through which the gut microbiota inhibits the expansion of antibiotic-resistant pathogens. Dr. Matthew Sorbara is currently an assistant professor at the University of Guelph in the Department of Molecular and Cellular Biology. His laboratory studies the gut microbiome and is focused on understanding how genomic diversity between isolates from the gut microbiota can be harnessed to develop effective live biotherapeutic products in the contexts of infection with antibiotic-resistant pathogens or Inflammatory Bowel Disease. The laboratory addresses these questions using a combination of bioinformatics, microbiology and immunology approaches using both in-vitro and in-vivo models.
