Gene-Wei Li

Gene-Wei Li

Assistant Professor of Biology

Gene-Wei Li develops quantitative tools to study the regulation and evolution of protein expression at both molecular and systems levels.

617-324-6703

Phone

68-223

Office

gwli@mit.edu

Email

Lab Website
Cindy Woolley

Assistant

617-253-6060

Assistant Phone

Education

  • PhD, 2010, Harvard University
  • SB, 2004, Physics, National Tsinghua University

Research Summary

Our goals are to derive a set of general principles governing the composition of the proteome, and to elucidate the mechanisms that govern precise protein levels. At the systems level, we want to understand the rationales, if they exist, for the protein expression levels that are observed in nature, and the consequences of proteome dysregulation and imbalance. At the mechanistic level, we want to uncover the molecular events that ensure optimal protein production despite the constant thermal fluctuations in living systems.

Awards

  • NSF Career Award, 2019
  • Pew Biomedical Scholar, 2017
  • Smith Family Award for Excellence in Biomedical Research, 2017
  • NIGMS R35 Maximizing Investigator Research Award, 2017
  • Sloan Research Fellowship, 2016
  • Searle Scholar, 2016
  • NIH Pathway to Independence Award, 2013

Key Publications

  1. Production of Protein-Complex Components Is Stoichiometric and Lacks General Feedback Regulation in Eukaryotes. Taggart, JC, Li, GW. 2018. Cell Syst 7, 580-589.e4.
    doi: 10.1016/j.cels.2018.11.003PMID:30553725
  2. Maturation of polycistronic mRNAs by the endoribonuclease RNase Y and its associated Y-complex in Bacillus subtilis. DeLoughery, A, Lalanne, JB, Losick, R, Li, GW. 2018. Proc. Natl. Acad. Sci. U.S.A. 115, E5585-E5594.
    doi: 10.1073/pnas.1803283115PMID:29794222
  3. Evolutionary Convergence of Pathway-Specific Enzyme Expression Stoichiometry. Lalanne, JB, Taggart, JC, Guo, MS, Herzel, L, Schieler, A, Li, GW. 2018. Cell 173, 749-761.e38.
    doi: 10.1016/j.cell.2018.03.007PMID:29606352
  4. Operon mRNAs are organized into ORF-centric structures that predict translation efficiency. Burkhardt, DH, Rouskin, S, Zhang, Y, Li, GW, Weissman, JS, Gross, CA. 2017. Elife 6, .
    doi: 10.7554/eLife.22037PMID:28139975
  5. Quantifying absolute protein synthesis rates reveals principles underlying allocation of cellular resources. Li, GW, Burkhardt, D, Gross, C, Weissman, JS. 2014. Cell 157, 624-35.
    doi: 10.1016/j.cell.2014.02.033PMID:24766808

Recent Publications

  1. Rapid accumulation of motility-activating mutations in resting liquid culture of Escherichia coli. Parker, DJ, Demetci, P, Li, GW. 2019. J. Bacteriol. , .
    doi: 10.1128/JB.00259-19PMID:31285239
  2. Production of Protein-Complex Components Is Stoichiometric and Lacks General Feedback Regulation in Eukaryotes. Taggart, JC, Li, GW. 2018. Cell Syst 7, 580-589.e4.
    doi: 10.1016/j.cels.2018.11.003PMID:30553725
  3. Genome-Wide Quantitation of Protein Synthesis Rates in Bacteria. Johnson, GE, Li, GW. 2018. Meth. Enzymol. 612, 225-249.
    doi: 10.1016/bs.mie.2018.08.031PMID:30502943
  4. Fitness advantages conferred by the L20-interacting RNA cis-regulator of ribosomal protein synthesis in Bacillus subtilis. Babina, AM, Parker, DJ, Li, GW, Meyer, MM. 2018. RNA 24, 1133-1143.
    doi: 10.1261/rna.065011.117PMID:29925569
  5. Maturation of polycistronic mRNAs by the endoribonuclease RNase Y and its associated Y-complex in Bacillus subtilis. DeLoughery, A, Lalanne, JB, Losick, R, Li, GW. 2018. Proc. Natl. Acad. Sci. U.S.A. 115, E5585-E5594.
    doi: 10.1073/pnas.1803283115PMID:29794222
  6. Evolutionary Convergence of Pathway-Specific Enzyme Expression Stoichiometry. Lalanne, JB, Taggart, JC, Guo, MS, Herzel, L, Schieler, A, Li, GW. 2018. Cell 173, 749-761.e38.
    doi: 10.1016/j.cell.2018.03.007PMID:29606352
  7. Genome-wide screen for genes involved in eDNA release during biofilm formation by Staphylococcus aureus. DeFrancesco, AS, Masloboeva, N, Syed, AK, DeLoughery, A, Bradshaw, N, Li, GW, Gilmore, MS, Walker, S, Losick, R. 2017. Proc. Natl. Acad. Sci. U.S.A. 114, E5969-E5978.
    doi: 10.1073/pnas.1704544114PMID:28674000
  8. Operon mRNAs are organized into ORF-centric structures that predict translation efficiency. Burkhardt, DH, Rouskin, S, Zhang, Y, Li, GW, Weissman, JS, Gross, CA. 2017. Elife 6, .
    doi: 10.7554/eLife.22037PMID:28139975
  9. Dynamic translation regulation in Caulobacter cell cycle control. Schrader, JM, Li, GW, Childers, WS, Perez, AM, Weissman, JS, Shapiro, L, McAdams, HH. 2016. Proc. Natl. Acad. Sci. U.S.A. 113, E6859-E6867.
    doi: 10.1073/pnas.1614795113PMID:27791168
  10. How do bacteria tune translation efficiency? Li, GW. 2015. Curr. Opin. Microbiol. 24, 66-71.
    doi: 10.1016/j.mib.2015.01.001PMID:25636133

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