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Dynamic Proximity Tagging in Living Plant Cells with Pupylation-Based Interaction Tagging.
Ye, Ruiqiang; Lin, Zhuoran; Liu, Kun-Hsaing; Sheen, Jen; Chen, Sixue.
Affiliation
  • Ye R; Department of Molecular Biology and Centre for Computational and Integrative Biology, Massachusetts General Hospital, and Department of Genetics, Harvard Medical School, Boston, MA, USA. rqye@cemps.ac.cn.
  • Lin Z; CAS Center for Excellence in Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai, China. rqye@cemps.ac.cn.
  • Liu KH; State Key Laboratory of Crop Stress Biology for Arid Areas and College of Life Sciences, and Institute of Future Agriculture, Northwest Agriculture & Forestry University, Yangling, Shaanxi, China.
  • Sheen J; Department of Molecular Biology and Centre for Computational and Integrative Biology, Massachusetts General Hospital, and Department of Genetics, Harvard Medical School, Boston, MA, USA.
  • Chen S; State Key Laboratory of Crop Stress Biology for Arid Areas and College of Life Sciences, and Institute of Future Agriculture, Northwest Agriculture & Forestry University, Yangling, Shaanxi, China.
Methods Mol Biol ; 2690: 137-147, 2023.
Article in En | MEDLINE | ID: mdl-37450145
Identification of protein-protein interactions (PPIs) and protein kinase substrates is fundamental for understanding how proteins exert biological functions with their partners and targets. However, it is still technically challenging, especially for transient and weak interactions involved in most cellular processes. The proximity-tagging systems enable capturing snapshots of both stable and transient PPIs. In this chapter, we describe in detail the methodology of a novel proximity-based labeling approach, PUP-IT (pupylation-based interaction tagging), to identify PPIs using a protoplast transient expression system. We have successfully identified potential kinase substrates by targeted screening and tandem mass spectrometry analysis.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Bacterial Proteins / Plant Cells Language: En Journal: Methods Mol Biol Journal subject: BIOLOGIA MOLECULAR Year: 2023 Document type: Article Affiliation country: United States Country of publication: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Bacterial Proteins / Plant Cells Language: En Journal: Methods Mol Biol Journal subject: BIOLOGIA MOLECULAR Year: 2023 Document type: Article Affiliation country: United States Country of publication: United States