Optimized cross-linking mass spectrometry for in situ interaction proteomics

ecent development of mass spectrometer cleavable protein cross-linkers and algorithms for their spectral identification now permits large-scale cross-linking mass spectrometry (XL-MS). Here, we optimized the use of cleavable disuccinimidyl sulfoxide (DSSO) cross-linker for labeling native protein complexes in live human cells. We applied a generalized linear mixture model to calibrate cross-link peptide-spectra matching (CSM) scores to control the sensitivity and specificity of large-scale XL-MS. Using specific CSM score thresholds to control the false discovery rate, we found that higher-energy collisional dissociation (HCD) and electron transfer dissociation (ETD) can both be effective for large-scale XL-MS protein interaction mapping. We found that the density and coverage of protein-protein interaction maps can be significantly improved through the use of multiple proteases. In addition, the use of sample-specific search databases can be used to improve the specificity of cross-linked peptide spectral matching. Application of this approach to human chromatin labeled in live cells recapitulated known and revealed new protein interactions of nucleosomes and other chromatin-associated complexes in situ. This optimized approach for mapping native protein interactions should be useful for a wide range of biological problems.

质谱可裂解蛋白质交联剂及其谱图鉴定算法的近期进展，现已使大规模交联质谱（cross-linking mass spectrometry, XL-MS）得以广泛应用。本研究中，我们优化了可裂解二琥珀酰亚胺亚砜（disuccinimidyl sulfoxide, DSSO）交联剂的使用方案，用于活体人细胞内天然蛋白质复合物的标记。我们采用广义线性混合模型对交联肽段-谱图匹配（cross-link peptide-spectra matching, CSM）得分进行校准，以调控大规模XL-MS分析的灵敏度与特异性。通过设置特定的CSM得分阈值以控制错误发现率，我们发现高能碰撞解离（higher-energy collisional dissociation, HCD）与电子转移解离（electron transfer dissociation, ETD）均可有效用于大规模XL-MS蛋白质相互作用图谱的绘制。我们发现，通过使用多种蛋白酶进行酶解，可显著提升蛋白质相互作用图谱的密度与覆盖度。此外，使用样本特异性搜索数据库，可进一步提升交联肽段谱图匹配的特异性。将该方法应用于活体人细胞中标记的人类染色质，不仅重现了已知的蛋白质相互作用，还原位揭示了核小体与其他染色质相关复合物的新型蛋白质相互作用。这种用于绘制天然蛋白质相互作用图谱的优化方法，可为诸多生物学问题的研究提供有力支持。