The Expedit-Isotopomeric CrossLinking Mass Spectrometry (Expedit-ICLMS) technology for mapping global and dynamic protein-protein interaction networks

用于绘制全局和动态蛋白质-蛋白质相互作用网络的快速同位素交联质谱 (Expedit-ICLMS) 技术

• 批准号: 10596082
• 负责人: JEFFREY A RANISH
• 金额: $ 50.64万
• 依托单位: INSTITUTE FOR SYSTEMS BIOLOGY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10596082
• 关键词: Address; Affinity; Architecture; Biological Models; Biological Process; Biomedical Research; Biotechnology; Cell Nucleus; Cell physiology; Cells; Complex; Complex Mixtures; Consumption; Crosslinker; Data; Databases; Development; Diagnostic; Disease; Effectiveness; Genetic; Genome; Goals; Health; Human; Individual; Knowledge; Label; Maps; Mass Spectrum Analysis; Methods; Molecular; Organism; Peptides; Play; Protein Dynamics; Protein-Protein Interaction Map; Proteins; Proteome; Protocols documentation; Reagent; Reproducibility; Research Personnel; Resources; Role; Sampling; Signal Transduction; System; Technology; Therapeutic Intervention; Time; Yeasts; base; biological systems; cost; crosslink; effectiveness evaluation; experimental study; falls; gene regulatory network; improved; insight; interest; invention; network architecture; new technology; novel; protein protein interaction; targeted treatment; technology development; technology research and development; transmission process; yeast protein

SUMMARY This project seeks to develop new technology to enable global mapping of protein-protein interactions (PPIs) in a condition-specific, timely and affordable manner, by individual researchers interested in specific biological systems. Successful development of this technology is expected to have a transformative effect on all fields of biomedical research, directly addressing the purpose of the Focused Technology Research and Development R01 FOA (PAR-19-253). Global PPI networks are not only the most important resources for understanding the molecular mechanisms underlying normal and aberrant biological processes, but also the bases for understanding genetic interaction networks, constructing gene regulatory networks, and quantitative modeling of biological processes. Current technologies for mapping global PPI networks are labor intensive, time consuming, costly, plagued by false positives/negatives, and do not provide a way for individual researchers to efficiently map global PPI networks for particular biological systems. The proposed technology development is targeted to solve the two most important challenges facing crosslinking-mass spectrometry (CLMS)-based global PPI mapping studies: 1) the complexity of peptide mixtures derived from crosslinking samples with a large number of proteins and a large dynamic range of abundances, and 2) efficient and confident identification of crosslinked peptides by whole proteome database searches. We seek to overcome these challenges by developing a novel crosslinked peptide enrichment strategy, called Expedit, and combining it with the powerful capabilities of ICL crosslinkers, a new class of MS-cleavable, isotopomeric, bi- functional crosslinkers for crosslinked peptide identification. Unique features of ICLs permit 1) efficient determination of individual peptide masses in each crosslink from MS2 spectra, and 2) identification of crosslinked peptides by whole proteome database searching using a single MS2 spectrum per crosslinked peptide. The combination of Expedit with ICLMS is expected to address the major limitations of current CLMS approaches to enable routine large scale PPI studies for the first time. In the Aims, we will first synthesize novel Expedit reagents and evaluate their effectiveness for crosslinked peptide enrichment using increasingly complex mixtures. Once optimized, we will integrate Expedit with ICLMS and evaluate the effectiveness of the technology for building global PPI networks in yeast. We will evaluate the method in terms of the quantity and reproducibility of identified crosslinks/PPIs, the abundances of the identified proteins, their localization, affinities and complex membership (if available). We will compare our PPI networks to previously described yeast PPI networks. The effectiveness of the technology for crosslinked peptide identification will be evaluated by comparing it to state-of-the-art CLMS-based approaches. If successful, this project would provide a general and robust method for studying global PPIs and their dynamics that can be applied to any organism for which a sequenced genome is available.

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