利用 HaloTag 富集质谱法绘制脂肪细胞相互作用组网络图。

IF 2.5 Q3 BIOCHEMICAL RESEARCH METHODS
Biology Methods and Protocols Pub Date : 2024-05-29 eCollection Date: 2024-01-01 DOI:10.1093/biomethods/bpae039
Junshi Yazaki, Takashi Yamanashi, Shino Nemoto, Atsuo Kobayashi, Yong-Woon Han, Tomoko Hasegawa, Akira Iwase, Masaki Ishikawa, Ryo Konno, Koshi Imami, Yusuke Kawashima, Jun Seita
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引用次数: 0

摘要

绘制体内自然状态下的蛋白质相互作用复合物图谱可以说是蛋白质网络分析的圣杯。检测蛋白质相互作用的化学计量一直是一项重要的技术挑战,因为很少有研究关注这一问题。不过,人工智能(AI)和蛋白质组学可能会解决这个问题。在此,我们介绍了基于HaloTag的亲和纯化质谱(HaloMS)的开发情况,这是一种用于发现蛋白质相互作用的高通量HaloMS检测方法。这种方法能快速捕获新表达的蛋白质,省去了传统的逐一检测的繁琐过程。作为原理验证,我们使用 HaloMS 评估了人类脂肪细胞中 17 种调控蛋白的蛋白复合物相互作用。脂肪细胞相互作用组网络通过体外牵引试验和基于人工智能的预测工具得到了验证。应用HaloMS探测脂肪细胞分化有助于鉴定以前未知的转录因子(TF)-蛋白质复合物,揭示整个蛋白质组的人类脂肪细胞TF网络,并揭示不同通路是如何整合的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mapping adipocyte interactome networks by HaloTag-enrichment-mass spectrometry.

Mapping protein interaction complexes in their natural state in vivo is arguably the Holy Grail of protein network analysis. Detection of protein interaction stoichiometry has been an important technical challenge, as few studies have focused on this. This may, however, be solved by artificial intelligence (AI) and proteomics. Here, we describe the development of HaloTag-based affinity purification mass spectrometry (HaloMS), a high-throughput HaloMS assay for protein interaction discovery. The approach enables the rapid capture of newly expressed proteins, eliminating tedious conventional one-by-one assays. As a proof-of-principle, we used HaloMS to evaluate the protein complex interactions of 17 regulatory proteins in human adipocytes. The adipocyte interactome network was validated using an in vitro pull-down assay and AI-based prediction tools. Applying HaloMS to probe adipocyte differentiation facilitated the identification of previously unknown transcription factor (TF)-protein complexes, revealing proteome-wide human adipocyte TF networks and shedding light on how different pathways are integrated.

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来源期刊
Biology Methods and Protocols
Biology Methods and Protocols Agricultural and Biological Sciences-Agricultural and Biological Sciences (all)
CiteScore
3.80
自引率
2.80%
发文量
28
审稿时长
19 weeks
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