Li Haorong, Mazli Wan Nur Atiqah Binti, Hao Ling
Department of Chemistry, The George Washington University, Washington, District of Columbia, USA.
Department of Chemistry and Biochemistry, University of Maryland, College Park, Maryland, USA.
J Mass Spectrom. 2025 May;60(5):e5134. doi: 10.1002/jms.5134.
Proximity labeling (PL) proteomics has emerged as a powerful tool to capture both stable and transient protein interactions and subcellular networks. Despite the wide biological applications, PL still faces technical challenges in robustness, reproducibility, specificity, and sensitivity. Here, we discuss major analytical challenges in PL proteomics and highlight how the field is advancing to address these challenges by refining study design, tackling interferences, overcoming variation, developing novel tools, and establishing more robust platforms. We also provide our perspectives on best practices and the need for more robust, scalable, and quantitative PL technologies.
邻近标记(PL)蛋白质组学已成为一种强大的工具,可用于捕获稳定和瞬时的蛋白质相互作用以及亚细胞网络。尽管具有广泛的生物学应用,但PL在稳健性、可重复性、特异性和灵敏度方面仍面临技术挑战。在这里,我们讨论PL蛋白质组学中的主要分析挑战,并强调该领域如何通过优化研究设计、解决干扰、克服变异、开发新型工具以及建立更强大的平台来应对这些挑战。我们还就最佳实践以及对更强大、可扩展和定量的PL技术的需求提供了我们的观点。