Faculty |
Wei QIN, Ph.D.

Wei Qin

Dr Wei Qin received a B.S. degree in Bioengineering from Beijing Institute of Technology in 2014. He completed his Ph.D. study at Peking University, where he conducted research with Prof. Chu Wang and Prof. Xing Chen on the development of chemoproteomic strategies to investigate how post-translational modifications, including O-GlcNAcylation and itaconation, regulate protein function. After completing his Ph.D. in 2019, he Joined Prof. Alice Ting lab at Stanford University as a postdoctoral associate where he developed novel proximity labeling methods for mapping subcellular RNA-protein interactions and dynamic protein trafficking. Dr. Qin joined School of Pharmaceutical Sciences, Tsinghua University, as a tenure-track assistant professor in March 2023. The goal of his study is to invent and disseminate transformative technologies for exploring proteome complexity, leveraging his unique strengths in chemical biology, proteomics and protein engineering.


Research interests

A protein’s life trajectory is the path that it chooses from synthesis to degradation and a slight change in its life trajectory can lead to huge differences in its functional outcomes. To describe a protein’s life trajectory, we would ask: “When was it?”, “Where was it?”, “What was it doing?” and “Who did it meet?”. Such four dimensional information is critical for understanding a protein’s dynamic roles across its lifetime in the cellular society. Quantitative proteomics provides a versatile platform to systematically assess specific protein features, but typically report on only a single dimension of information.

Our long-term research vision is to promote the revolution of proteomics from 1D to 4D, in order to describe each protein’s life trajectory in living cells. My lab will be focused on developing novel chemical and molecular tools, in combination with state-of-the-art proteomics, to simultaneously map dynamic timing, localization, function and interaction of proteomes, with the ultimate goal of better understanding essential mechanisms underlying the regulation of cellular physiology. Specifically, I have three major future directions to address different aspects of essential biological questions and lay the foundation for the eventual 4D proteomics.

1. Novel methods for spatiotemporally-resolved profiling of dynamic protein events.

Protein function is tightly regulated by its subcellular locations and dynamic movement between compartments. We have developed protein translocation profiling based on tandem proximity labeling. Although powerful, this technology requires two rounds of enrichment steps, which demand large starting materials and potentially sacrifice the sensitivity. We will further work on developing next-generation protein translocation profiling methods with higher efficiency.

2. Novel methods for spatiotemporally-resolved profiling of molecular interactions.

Cellular functions are tightly regulated by proteins, other biomolecules and their interactions, including protein–protein interactions (PPIs), protein–RNA/DNA interactions and protein–metabolite interactions. Such molecular interaction networks are central to most biological processes, while their dysregulation has been linked to a variety of human diseases including cancers, immune disorders and neurodegeneration. Methods enabling the large-scale discovery of molecular interactions in living cells have provided insights for biological exploration and therapeutic intervention. We aim to develop spatiotemporally-resolved proteomic methods to map diverse protein interactions and their dynamics. Meanwhile, we will further decipher functional protein interactions and understand their biological importance.

3. Discovery of functional protein PTMs in host-pathogen interface.

During bacterial infection, host cells recognize extracellular stimuli from invading pathogens and in response activate pro-inflammatory signals that protect the host. In the interface of host and pathogens, a variety of post-translational modifications (PTMs) are involved. For instance, many bacterial pathogens secrete virulence factors, also known as effector proteins, directly into host cells and a particularly interesting subset of effector post-translationally modify host proteins using novel chemistry that is not otherwise found in the mammalian proteome. The understanding of those functional PTMs in host-pathogen interface are largely impeded by the lack of tools to specifically label and manipulate those PTMs. We will work on developing new tools to understand how PTMs, including O-GlcNAcylation and itaconation, regulate pathogen infection and immune responses. We will also utilize state-of-the-art computational proteomic approaches to discover novel PTMs in host-pathogen interface.


Scientific contributions

1. Development of TransitID, a first-in-class technology to systematically study proteome trafficking; Development of functional proximity labeling to map functional subclasses in specific compartments.

2. Development of chemical probes for itaconation, which reveals new mechanisms underlying itaconate’s anti-inflammatory effect in macrophages.

3. Development of novel chemoproteomic strategies for O-GlcNAcylation, unexpectedly discovering a side reaction between per-acetylated monosaccharides and cysteines during metabolic glycan labeling.


Honors and awards

2019 Beijing outstanding graduates

2019 National scholarship

2018 National scholarship


Selected publications

(1) Wei Qin#; Joleen S. Cheah#; Charles Xu; James Messing; Brian D. Freibaum; Steven Boeynaems; J. Paul Taylor; Namrata D. Udeshi; Steven A. Carr; Alice Y. Ting ; Dynamic mapping of proteome trafficking within and between living cells by TransitID, BioRxiv; Cell (in revision).

(2) Wei Qin; Samuel A. Myers; Dominique K. Carey; Steven A. Carr; Alice Y. Ting ;Spatiotemporally-resolved mapping of RNA binding proteins via functional proximity labeling reveals a mitochondrial mRNA anchor promoting stress recovery, Nature Communications, 2021,12(1).

(3) Wei Qin#; Kelvin F. Cho#; Peter E. Cavanagh#; Alice Y. Ting ; Deciphering Molecular Interactions by Proximity Labeling, Nature Methods, 2021, 18: 133-143.

(4) Wei Qin#; Yanling Zhang#; Huan Tang; Dongyang Liu; Ying Chen; Yuan Liu; Chu Wang ; Chemoproteomic Profiling of Itaconylation by Bioorthogonal Probes in Inflammatory Macrophages, Journal of the American Chemical Society, 2020, 142(25): 10894-10898.

(5) Wei Qin; Ke Qin; Yanling Zhang; Wentong Jia; Ying Chen; Bo Cheng; Linghang Peng; Nan Chen; Yuan Liu; Wen Zhou; Yan-Ling Wang; Xing Chen; Chu Wang ; S-glycosylation-based cysteine profiling reveals regulation of glycolysis by itaconate, Nature Chemical Biology, 2019, 15(10): 983-991.

(6) Wei Qin#; Ke Qin#; Xinqi Fan; Linghang Peng; Weiyao Hong; Yuntao Zhu; Pinou Lv; Yifei Du; Rongbing Huang; Mengting Han; Bo Cheng; Yuan Liu; Wen Zhou; Chu Wang; Xing Chen ; Artificial Cysteine S-Glycosylation Induced by Per-O-Acetylated Unnatural Monosaccharides during Metabolic Glycan Labeling, Angewandte Chemie International Edition, 2018, 57(7): 1817-1820.

(7) Wei Qin; Pinou Lv; Xinqi Fan; Baiyi Quan; Yuntao Zhu; Ke Qin; Ying Chen; Chu Wang; Xing Chen ; Quantitative Time-resolved Chemoproteomics Reveals that Stable O-GlcNAc Regulates Box C/D snoRNP Biogenesis, Proceedings of the National Academy of Sciences of the United States of America, 2017, 114(33): 6749-6758.

(8) Juan Liu#; Xuan Shao#; Wei Qin#; Yanling Zhang#; Feihong Dang; Qian Yang; Xin Yu; Yu-Xia Li; Xing Chen; Chu Wang; Yan-Ling Wang ; Quantitative chemoproteomics reveals O-GlcNAcylation of cystathionine γ-lyase (CSE) represses trophoblast syncytialization, Cell Chemical Biology, 2021, 28(6): 788-801.

(9) Wei Qin; Zhongyun Xie; Jingyang Wang; Linghang Peng; Guangshuo Ou; Chu Wang; Xing Chen ; Chemoproteomic Profiling of O-GlcNAcylation in Caenorhabditis elegans, Biochemistry, 2020, 59(34): 3129-3134.

(10) Wei Qin; Fan Yang; Chu Wang ; Chemoproteomic profiling of protein-metabolite interactions, Current Opinion in Chemical Biology, 2020, 54: 28-36.

(11) Ying Chen#; Wei Qin#; Chu Wang ; Functional Proteomics Driven by Chemical and Computational Approaches, Chinese Journal of Chemistry, 2022, 40(5): 628-634.