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Gavin MacBeath


PhD Macromolecular and Cellular Structure and Chemistry, The Scripps Research Institute, 1997
BS Genetics, University of Manitoba, 1991

The MacBeath laboratory develops and uses high-throughput, quantitative technologies to understand how proteins function within the complex context of the proteome. With a specific emphasis on receptor tyrosine kinase (RTK) signaling, our goal is to understand better how biological systems are organized and how best to intervene when these systems go awry.

MacBeath lab website

Research summary

RTKs constitute a large family of single-spanning membrane proteins found only in Metazoans. They mediate intercellular communication and regulate a wide variety of cellular processes, including growth, proliferation, migration, differentiation, and apoptosis. Misregulation of RTKs, or the pathways they control, results in developmental abnormalities, as well as a variety of human diseases, including cancer, diabetes, allergy and asthma, inflammation, osteoporosis, and immune deficiency.

RTKs often use the same proteins to elicit diverse or even opposing phenotypic responses. Using protein microarrays comprising almost every SH2 and PTB domain encoded in the human genome, we have constructed interactions maps for 25 RTKs, as well as many of the adapter proteins that are directly recruited to these receptors. These maps exhibit a surprisingly high level of qualitative overlap, raising questions as to how RTKs achieve specificity. By measuring binding affinities, we found that the recruitment profiles of RTKs differ substantially at the quantitative level and that these differences are sufficient to explain differences in the degree to which different intracellular signaling pathways are activated. A broad and unbiased analysis of six RTKs revealed that their signaling networks could be separated into an upstream layer comprising proteins that are activated in a linear fashion based on combinations of receptor-docking affinities, and a downstream layer comprising proteins that are activated in a nonlinear fashion. This result suggests that predictive models of RTK signaling can be parsed into discrete and more manageable layers. A major challenge for the future is understanding and modeling the nonlinear information-processing step that lies downstream of protein recruitment.

We are addressing this challenge by developing high-throughput technologies that can accurately monitor the abundance and posttranslational modification states of many different proteins in cellular lysates. Our approach is to use lysate microarray technology, in combination with small molecule- and RNAi-mediated perturbations, to investigate how information flows through signaling networks. Data from our studies are being used to construct predictive models of signaling, which should inform the rational design of new therapeutics.

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This page last modified on May 23rd, 2011