Matthew Torres

Contact Information

Email
mtorres35@gatech.edu
Phone
404-385-0401
Location
EBB 4009
Research Group
The Torres Lab
faculty picture

Matthew Torres

Adjunct Faculty, Associate Professor of Biological Sciences

Awards

K99/R00 NIH Pathway to Independence Award (2010 – 2016)

IBB Above and Beyond Award (2016)

Education

B.S., Biology, Humboldt State University, 1997; Ph.D., Biochemistry, University of North Carolina at Chapel Hill, 2007

Research

The Torres lab integrates mass spectrometry and experimental cell biology using the yeast model system to understand how networks of coordinated post-translational modifications (PTMs) modulate biological function. PTMs (e.g. phosphorylation, ubiquitination and over 300 others), which can be readily quantified by mass spectrometry (MS), often mediate dynamic protein-protein interactions through enhancement or disruption of binding and/or catalytic properties that can result in changes in protein specificity, stability, or cellular localization.

Emerging evidence suggests that dynamic PTM networks are critical for maintaining proper function in G protein and MAP-Kinase signaling pathways, which are important in neurotransmission, hormone responsiveness, and cell differentiation. The genes/proteins that comprise these signaling pathways have been mapped through classical genetics. The current challenge is to understand how these components are coordinately regulated to maintain proper pathway and cell function. My lab places special emphasis on understanding the networks of dynamic PTMs that coordinate G protein and MAP-Kinase signaling complexes - with the goal of identifying novel approaches to modulate signal transduction systems. We use a combination of tools including quantitative mass spectrometry, bioinformatics, and yeast genetics to explore testable systems-level hypotheses.

My current research interests can be grouped into four main categories: (1) coordinated PTM-based regulation of dynamic signaling complexes, (2)identification of novel signaling PTMs, (3) PTM networks in stress adaptation, and (4) technology development for regulatory PTM detection.

Research Keywords
Bioanalytical Chemistry and Biochemistry; Cell signaling; Post-Translational Modification; Machine Learning; Protein Structure/Function; Intrinsic Disorder