Mapping adipocyte interactome networks by HaloTag-enrichment-mass spectrometry.
Junshi YazakiTakashi YamanashiShino NemotoAtsuo KobayashiYong-Woon HanTomoko HasegawaAkira IwaseMasaki IshikawaRyo KonnoKoshi ImamiYusuke KawashimaJun SeitaPublished in: Biology methods & protocols (2024)
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.
Keyphrases
- artificial intelligence
- high throughput
- mass spectrometry
- adipose tissue
- transcription factor
- protein protein
- insulin resistance
- endothelial cells
- network analysis
- high resolution
- amino acid
- fatty acid
- small molecule
- machine learning
- binding protein
- big data
- deep learning
- capillary electrophoresis
- gas chromatography
- sensitive detection
- loop mediated isothermal amplification
- pluripotent stem cells
- dna binding