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Tyrosinase-based sequential proximity labeling for tracking proteome dynamics

Research Project

Project/Area Number 23K13855
Research Category

Grant-in-Aid for Early-Career Scientists

Allocation TypeMulti-year Fund
Review Section Basic Section 37030:Chemical biology-related
Research InstitutionKyoto University

Principal Investigator

朱 浩  京都大学, 工学研究科, 助教 (90874545)

Project Period (FY) 2023-04-01 – 2025-03-31
Project Status Granted (Fiscal Year 2023)
Budget Amount *help
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2024: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
Fiscal Year 2023: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
Keywordstyrosinase / proximity labeling / proteomics / AMPAR / mGluR1
Outline of Research at the Start

This research will develop a new proximity labeling (PL) method based on tyrosinase, which features non-cyototoxic and compatible with diverse enrichment tags and thus enables sequential PL for precisely tracking proteome dynamics. Specifically, the proteome around AMPAR during LTD will be analyzed.

Outline of Annual Research Achievements

Protein functions are tightly regulated by its localization and interaction with surrounding proteins, which are dynamically altered along a biological event. This research aims at developing a new enzyme for proximity labeling (PL) that enables sequential PL for tracking the dynamics of AMPAR-surrounding proteomes. As planned in the proposal, we have successfully developed tyrosinase-based PL in phase 1. We selected a small and simple bacterial tyrosinase (BmTyr) and firstly characterized its protein labeling properties in vitro. BmTyr enables fast protein labeling and broad amino acid modifications on proteins. We further demonstrated the subcellular-resolved PL and proteomics by BmTyr in living cells. Importantly, the BmTyr-catalyzed protein tagging features H2O2-free, low-background, and compatible with diverse probes, which potentially allows BmTyr to be developed as the first PL enzyme available for sequential PL. Lastly, we have demonstrated the applicability of BmTyr in live mouse brain for synpase-resolved PL and proteomics. The relevant results have recently been published on J. Am. Chem. Soc.

Current Status of Research Progress
Current Status of Research Progress

2: Research has progressed on the whole more than it was originally planned.

Reason

As planned in the proposal, we have successfully developed a new proximity labeling (PL) method based on tyrosinase in phase 1. Specifically, we selected a small and simple bacterial tyrosinase (BmTyr) for this purpose. We firstly characterized the protein labeling properties of BmTyr in vitro and identified its fast labeling kinetics and relatively broad amino acid coverage on proteins. We further demonstrated that BmTyr is genetically encodable and enables subcellular-resolved PL and proteomics in living cells, which is free of cyototoxic H2O2 and offers minimal background labeling. Beyond the scheduled research in the proposal, we have applied BmTyr in vivo to unveil the surrounding proteome of a neurotransmitter receptor in its resident synapse in a live mouse brain.

Strategy for Future Research Activity

This project is moving to phase 2 and 3 for tracking the dynamic proteome surrounding AMPAR during long-term depression in cultured neurons and in live mouse brains. As proof-of-principle, sequential proximity labeling (PL) will firstly be demonstrated in HEK293T cells for organelle labeling, e.g. nucleus or endoplasmic reticulum, in which the orthogonal enrichment of labeled proteins by two distinct types of phenol probes will be tested and optimized. Afterwards, BmTyr will be anchored to AMPAR via genetic engineering or affinity binding with an appropriate ligand or nanobody. The performance of BmTyr may need get evolved, e.g., enzymatic activity, for the sophisticated sequential PL.

Report

(1 results)
  • 2023 Research-status Report
  • Research Products

    (7 results)

All 2024 2023 Other

All Int'l Joint Research (1 results) Journal Article (1 results) (of which Int'l Joint Research: 1 results,  Peer Reviewed: 1 results) Presentation (5 results)

  • [Int'l Joint Research] Faculty of Science/University of Southern Denmark(デンマーク)

    • Related Report
      2023 Research-status Report
  • [Journal Article] Tyrosinase-Based Proximity Labeling in Living Cells and <i>In Vivo</i>2024

    • Author(s)
      Zhu Hao、Oh Jae Hoon、Matsuda Yuna、Mino Takeharu、Ishikawa Mamoru、Nakamura Hideki、Tsujikawa Muneo、Nonaka Hiroshi、Hamachi Itaru
    • Journal Title

      Journal of the American Chemical Society

      Volume: 146 Issue: 11 Pages: 7515-7523

    • DOI

      10.1021/jacs.3c13183

    • Related Report
      2023 Research-status Report
    • Peer Reviewed / Int'l Joint Research
  • [Presentation] Tyrosinase-based proximity labeling in living cells and in vivo2023

    • Author(s)
      Yuna Matsuda, Hao Zhu, Jae Hoon Oh, Takeharu Mino, Mamoru Ishikawa, Hideki Nakamura, Muneo Tsujikawa, Hiroshi Nonaka, Itaru Hamachi
    • Organizer
      日本化学会 第104春季年会
    • Related Report
      2023 Research-status Report
  • [Presentation] Development of ONOO-responsive protein labeling for ROS/RNS conditional proteomics2023

    • Author(s)
      Hao Zhu, Hiroaki Uno, Kyoichi Matsuba, Itaru Hamachi
    • Organizer
      日本化学会 第104春季年会
    • Related Report
      2023 Research-status Report
  • [Presentation] シナプスプロテオミクスを志向したチロシナーゼによるin vivo近傍タンパク質ラベル化法2023

    • Author(s)
      美野 丈晴、Hao Zhu、Jaehoon Oh、浜地 格
    • Organizer
      第17回バイオ関連化学シンポジウム
    • Related Report
      2023 Research-status Report
  • [Presentation] 過酸化亜硝酸塩(ONOO)応答性タンパク質ラベリングの開発2023

    • Author(s)
      Hao Zhu, Hiroaki Uno, Itaru Hamachi
    • Organizer
      第17回バイオ関連化学シンポジウム
    • Related Report
      2023 Research-status Report
  • [Presentation] Tyrosinase-based proximity labeling in living cells and in vivo2023

    • Author(s)
      Hao Zhu
    • Organizer
      第2回生命金属化学シンポジウム
    • Related Report
      2023 Research-status Report

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Published: 2023-04-13   Modified: 2024-12-25  

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