Jing Liu

Jing Liu

Undergraduate Student
University of Toronto
25 Harbord St., Toronto, ON M5S 3G5

Email: jingl.liu@mail.utoronto.ca

Current Research:

One of the most compelling questions in molecular evolution is how proteins evolved highly specific interactions to carry out useful work in cells. To study the evolution of these interactions, I am combining combinatorial biology with high-throughput screens to probe interactions that regulate one of the most ubiquitous signalling systems in Eukaryotes, G protein-coupled receptor (GPCR)-mediated signalling. Upon discovery of new interaction interfaces in high-throughput screens, I then model these interactions in silico to reveal molecular mechanisms of GPCR-G protein selectivity and further our understanding of how specific protein-protein interactions evolved.

Education:

  • M.Sc. (2023-Present) University of Toronto Department of Cell and Systems Biology
  • H.B.Sc. (2018-2023) University of Toronto Specialist in Pharmacology and Toxicology, Minor in Computer Science

Awards

  • University of Toronto Undergraduate Research Fund (2020)
  • University of Toronto Admission Scholarship (2018)

Peer-reviewed Publications (*Co-first)

  • Chen, S.K.*, Liu, J.*, Van Nynatten, A., Tudor-Price, B.M., & Chang, B.S.W. (2024). Sampling Strategies for Experimentally Mapping Molecular Fitness Landscapes Using High-Throughput Methods. Journal of Molecular Evolution. 92(4), pp. 402-414. doi: 10.1007/s00239-024-10179-8.
  • Scott B.M.*, Chen S.K.*, Van Nynatten A., Liu J., Scott R.K., Heon E., Peisajovich S., Chang B.S.W. 2024. Scaling up functional analyses of the G protein-coupled receptor rhodopsin. Journal of Molecular Evolution, 92(1), pp. 61–71. doi: https://doi.org/10.1007/s00239-024-10154-3. (*Co-first)

Oral and Poster Presentations

  • Liu J., Chen S.K., Chang B.S.W. 2023. Probing the Information Content of Protein Sequences to Understand Signaling Selectivity. Ontario Cell Biology Symposium. University of Guelph, Toronto, ON. (Poster presentation, Provincial)
  • Liu J., Chen S.K., Chang B.S.W. 2022. Investigating Evolutionary Pathways using Combinatorial Libraries. Mutational Scanning Symposium. MaRS Discovery District, Toronto, ON. (Poster presentation, International)
  • Liu J., Chen S.K., Chang B.S.W. 2022. Investigating Evolutionary Pathways using Combinatorial Libraries. Cell and Systems Biology Undergraduate Poster Session. University of Toronto, Department of Cell and Systems Biology, Toronto, ON. (Poster presentation, Institutional)
  • Liu J., Chen S.K., Chang B.S.W. 2021. A Single-cell Approach to Addressing the Variable Drug Response Problem. Undergraduate Research Talks. University of Toronto, Department of Cell and Systems Biology, Toronto, ON. (Oral presentation, Institutional)

Training/Experiences:

  • Summer Research Internship – University of Toronto Department of Cell & Systems Biology (2022)
  • Independent Research in Cell & Systems Biology (CSB497) – University of Toronto, Department of Cell & Systems Biology (2022)
  • Project in Pharmacology (PCL472) – University of Toronto, Department of Pharmacology and Toxicology (2021 – 2022)
  • Research Opportunity Program (ROP299Y) – University of Toronto, Department of Cell & Systems Biology (2019 – 2020)
  • Summer Research Internship – University of Toronto, Department of Cell & Systems Biology (2019)

Technical Strengths

  • Fully trained to run flow cytometry at Temerty Faculty of Medicine Flow Cytometry Facility (Beckmen Dickson Analyzers) University of Toronto Faculty of Medicine
  • Trained in flow cytometry (MACSQuant VYB machine & FlowJo software) University of Toronto Cell & Systems Biology – Chang Lab
  • Trained on confocal microscopes (Nikon Imaging Systems) University of Toronto Cell & Systems Biology – Plotnikov Lab
  • Trained in microscopy image analysis (ImageJ (FIJI) microscopy analysis software) University of Toronto Cell & Systems Biology – Plotnikov Lab Imaging Core
  • Programming: Python, Java, R, SQL, Linux
  • Trained to run jobs on high-performance computing clusters (Niagara supercomputer) University of Toronto – SciNet