State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences Beijing, Research Unit of Proteomics & Research and Development of New Drug of Chinese Academy of Medical Sciences, Institute of Lifeomics, Beijing, PR China; School of Basic Medical, Anhui Medical University, Heifei, Anhui, PR China.
State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences Beijing, Research Unit of Proteomics & Research and Development of New Drug of Chinese Academy of Medical Sciences, Institute of Lifeomics, Beijing, PR China.
Mol Cell Proteomics. 2024 Nov;23(11):100852. doi: 10.1016/j.mcpro.2024.100852. Epub 2024 Oct 2.
Ubiquitination is crucial for maintaining protein homeostasis and plays a vital role in diverse biological processes. Ubiquitinome profiling and quantification are of great scientific significance. Artificial ubiquitin-binding domains (UBDs) have been widely employed to capture ubiquitinated proteins. The success of this enrichment relies on recognizing native spatial structures of ubiquitin and ubiquitin chains by UBDs under native conditions. However, the use of native lysis conditions presents significant challenges, including insufficient protein extraction, heightened activity of deubiquitinating enzymes and proteasomes in removing the ubiquitin signal, and purification of a substantial number of contaminant proteins, all of which undermine the robustness and reproducibility of ubiquitinomics. In this study, we introduced a novel approach that combines denatured-refolded ubiquitinated sample preparation (DRUSP) with a tandem hybrid UBD for ubiquitinomic analysis. The samples were effectively extracted using strongly denatured buffers and subsequently refolded using filters. DRUSP yielded a significantly stronger ubiquitin signal, nearly three times greater than that of the Control method. Then, eight types of ubiquitin chains were quickly and accurately restored; therefore, they were recognized and enriched by tandem hybrid UBD with high efficiency and no biases. Compared with the Control method, DRUSP showed extremely high efficiency in enriching ubiquitinated proteins, improving overall ubiquitin signal enrichment by approximately 10-fold. Moreover, when combined with ubiquitin chain-specific UBDs, DRUSP had also been proven to be a versatile approach. This new method significantly enhanced the stability and reproducibility of ubiquitinomics research. Finally, DRUSP was successfully applied to deep ubiquitinome profiling of early mouse liver fibrosis with increased accuracy, revealing novel insights for liver fibrosis research.
泛素化对于维持蛋白质的内稳态至关重要，在多种生物学过程中起着至关重要的作用。泛素组学的分析和定量具有重要的科学意义。人工泛素结合结构域（UBDs）已被广泛用于捕获泛素化蛋白。这种富集的成功依赖于 UBDs 在天然条件下识别天然空间结构的泛素和泛素链。然而，在天然裂解条件下使用会带来一些挑战，包括蛋白提取不足、去泛素化酶和蛋白酶体活性升高，从而去除泛素信号，以及大量杂质蛋白的纯化，这些都破坏了泛素组学的稳健性和可重复性。在本研究中，我们引入了一种新的方法，将变性-复性的泛素化样品制备（DRUSP）与串联杂交 UBD 相结合，用于泛素组学分析。该样品采用强变性缓冲液进行有效提取，然后通过过滤器进行复性。DRUSP 产生的泛素信号显著增强，几乎是对照方法的 3 倍。然后，8 种类型的泛素链被快速而准确地恢复；因此，它们被串联杂交 UBD 识别和高效、无偏地富集。与对照方法相比，DRUSP 在富集泛素化蛋白方面具有极高的效率，将整体泛素信号的富集提高了约 10 倍。此外，当与泛素链特异性 UBD 结合使用时，DRUSP 也被证明是一种通用的方法。这种新方法显著提高了泛素组学研究的稳定性和重现性。最后，DRUSP 成功应用于早期小鼠肝纤维化的深度泛素组学研究，提高了准确性，为肝纤维化研究提供了新的见解。
