SNU CBE

HIT-MAP: A Scalable Approach to Multimodal Mapping of Subcellular Organization

2025 · Cell Reports Methods

저자

Gege Qian, 김준원 (Joonwon Kim), Richa Tiwari, Benjamin J. Polacco, Antoine Forget, Leah V. Schaffer, Hark Kyun Kim, Jiahao Gao, Yuan Zhou, Gwendolyn Μ. Jang, Marcus R. Kelly, Xiaoyu Zhao, Helene Foussard, Liudeng Zhang, Nevan J. Krogan, Trey E. Ideker, Alejandro Chavez

연구주제

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NTIS 과학기술표준분류

가장 가까운 분류(보건의료 > 신약·의약품개발 > 약효검색)가 화학·화공 범위 밖이다. 배정 근거: AI 키워드가 잡은 NTIS 과제의 분류.

AI 연구 키워드·방법

endogenous protein tagging 단백질-단백질 상호작용 subcellular protein organization

affinity purification mass spectrometry immunofluorescence imaging

키워드 (OpenAlex)

protein-protein interaction affinity purification mass spectrometry protein complexes Perturb-seq HEK293T cells

초록

Multimodal mapping of subcellular protein organization through imaging and interaction proteomics has been mostly confined to large consortia, owing to high per-target costs, reliance on target-specific antibodies or libraries of epitope-tagged cDNAs, and the lack of unified pipelines for coordinated data acquisition. Here, we present HIT-MAP (high-throughput integrated tagging for cell mapping), an end-to-end framework that couples endogenous epitope tagging with optimized wide-field immunofluorescence imaging and affinity purification-mass spectrometry (AP-MS). Applied to a pilot set of 16 representative proteins in HEK293T cells, HIT-MAP recovers 576 high-confidence protein-protein interactions, identifies canonical complexes, and resolves cross-modality protein communities. Integrative analysis identifies CCDC12 as a previously uncharacterized component of the Bact spliceosomal compl…

이 논문을 지원한 국가R&D 과제 (NTIS 성과)

NTIS 성과DB(2020–24)에서 DOI 매칭 없음

인접 그래프

노드 hover = 이웃 강조 · 1회 클릭 = 고정 · 고정된 노드 다시 클릭 = 페이지 이동

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교수 1

김준원

키워드 1

단백질-단백질 상호작용