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Anne-Claude Gingras: Perfecting Proteomics

By Jef Akst Anne-Claude Gingras: Perfecting Proteomics Photograph by Matthew Plexman Photography Assistant professor of molecular genetics, University of Toronto, Samuel Lunenfeld Research Institute at Mount Sinai Hospital. Age: 38 Anne-Claude Gingras liked science from a young age, but had never considered a career in research. Until she tried it one summer in college, that is. “The minute that I started doing experiments I realized that this is somet

By | February 1, 2011

Anne-Claude Gingras:
Perfecting Proteomics

Photograph by Matthew Plexman Photography

Assistant professor of molecular genetics, University of Toronto, Samuel Lunenfeld Research Institute at Mount Sinai Hospital. Age: 38

Anne-Claude Gingras liked science from a young age, but had never considered a career in research. Until she tried it one summer in college, that is. “The minute that I started doing experiments I realized that this is something that not only am I good at it, but I love it,” she says.

Having grown up on a small island near Quebec City, Gingras didn’t speak English, and, afraid to venture too far for grad school, she applied only to McGill University in Montreal. The language barrier was an obstacle at first, her graduate advisor Nahum Sonenberg agrees, but Gingras came highly recommended by a former student of his, so he agreed to take her on. “The amazing thing is,” Sonenberg says, “[by] the end of her PhD, she wrote better than any of the English-speaking people in my lab.”

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She spent the rest of her graduate career studying these factors and their activation or inhibition. Gingras found, for example, that phosphorylation inactivates molecules downstream of the PI 3-kinase and mTOR signaling pathways that normally inhibit tumor growth.2 This phenomenon now serves as a prognostic marker in a variety of cancers.

Her PhD work led to almost 50 peer-reviewed papers—probably a record number for a graduate student at McGill, according to Sonenberg. Some people thought that this number was a mistake, he says, “but they didn’t know her. Once you know her, you know that it’s possible.”

RESULTS: As a postdoc at the Institute for Systems Biology in Seattle, Gingras met one of her current collaborators, computational biologist Alexey Nesvizhskii, now at the University of Michigan, who introduced her to many of the computational techniques she uses today. Gingras, Nesvizhskii and several colleagues developed software, known as SAINT, to more efficiently and accurately interpret mass spectrometry data from large-scale proteomics studies, and to determine how much data is needed to be confident that protein-protein interactions are real and not just background noise.

Gingras is also helping develop a more user-friendly interface, known as ProHits, to help nonproteomics experts visualize the massive amounts of data. “We think this is going to change how a lot of people do science,” she says.

DISCUSSION: In 2005, Gingras started her own lab at the Samuel Lunenfeld Research Institute at Mount Sinai Hospital, and is working to systematically identify all the protein-protein interactions for each of the phosphatases in human cells, using yeast as a model.3 At the same time, the group probes the details of interesting phosphatases they discover, including one involved with abnormalities in brain capillaries.

Gingras has published more than 80 papers in her career, and has amassed nearly 9,000 citations. And they’re all solid papers, her colleagues say. “In terms of rigor, she’s maybe the best I have seen,” Sonenberg says. “That’s why she’s so successful.”

Literature Cited
1. A. Pause et al., “Insulin-dependent stimulation of protein synthesis by phosphorylation of a regulator of 5’-cap function,” Nature, 371:762-67, 1994. (Cited 664 times)
2. A.C. Gingras et al., “Regulation of translation initiation by FRAP/mTOR,” Gene Dev, 15:807-26, 2001. (Cited 695 times)
3. A. Breitkreutz et al., “A global protein kinase and phosphatase interaction network in yeast,” Science, 328:1043-46, 2010. (Cited 9 times) F1000 ID 3542957, Free F1000 Evaluation
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