尺寸排阻-反相液相色谱-质谱联用技术在大鼠肾脏翻译后修饰蛋白质鉴定中的应用

Proteomics is an emerging field that has been shown to play a crucial role in unveiling the mechanisms underlying physiological and pathological processes, and liquid chromatography-mass spectrometry (LC-MS) is one of the most important methods employed in this field. However, in complex biological systems, such as eukaryotes, it is challenging to perform a comprehensive and unbiased proteome analysis due to the high complexity of biological samples and enormous differences in sample contents. For example, post-translational modifications (PTMs) in proteins are imperative for cell signaling, but post-translationally modified proteins account for about 1% of the total proteins in a single cell, making their identification extremely difficult. Therefore, chromatographic separation methods based on different principles are generally applied to reduce the complexity of biological samples and enrich trace proteins for their identification through mass spectrometry (MS). In this study, we developed a new proteomics method by combining size exclusion chromatography (SEC) and reversed-phase chromatography (RPLC), to separate and identify trace proteins in complex systems. SEC was used to separate and enrich kidney-specific proteins. After optimization of the method, it was found that 30 mmol/L of ammonium acetate could efficiently separate rat kidney proteins from the total protein fraction so that they could be eluted based on their relative molecular mass. Sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) analysis and LC-MS results showed that our SEC separation method not only refined the protein composition of the biological sample but also enhanced the relative contents of trace proteins through multiple injections. The collected protein fractions were further concentrated through ultrafiltration centrifugation followed by freeze-drying, which further improved the recovery of trace proteins by approximately 90% and largely decreased the time required with the use of freeze-drying alone. Thereafter, five protein fractions were separately digested using trypsin, and the resultant peptides were further analyzed by reverse phase chromatography-MS analysis. In the RPLC column, the peptides were isolated mainly based on their hydrophobicity. As a result, by combining SEC and RPLC, 23621 peptides and 1345 proteins were identified from the kidney, with an increase in numbers by 69% and 27%, respectively, when compared to those obtained using the common 2D strong cation exchange (SCX)-RPLC-MS method. However, no significant difference was observed in the pI and grand average of hydropathicity (GRAVY) values. Gene ontology (GO) analysis revealed an increase in the number of proteins in each cell component, especially the membrane. Furthermore, identification of a higher rate of identified peptides than proteins suggested that the protein coverage was also improved, thereby facilitating the detection of PTM proteins. Consequently, five common PTMs in biological processes, including methylation, acetylation, carbamylation, oxidation, and phosphorylation, were examined and compared between the two methods. As expected, the number of post-translationally modified peptides identified using SEC-RPLC-MS were 1.7-1.9 times more than those determined using the SCX-RPLC-MS method. Especially for the identification of phosphorylated peptides, we could achieve the level of the targeted enrichment strategy; however no significant difference was observed in the extents of phosphorylation among serine, threonine, and tyrosine. These results further indicate that upon combining SEC and RPLC, high efficiency could be achieved by decreasing the complexity of the protein sample, and the identification was unbiased. Finally, the phosphorylation of some kidney proteins, such as spectrin, L-lactate dehydrogenase, and ATPases, was found, which is critical for their functions. In summary, the SEC-RPLC-MS approach was developed for the identification of rat kidney proteins and is especially applicable for the identification of PTM proteins. Using this method, the identification efficiency for PTM peptides increased significantly. Therefore, this method has potential for better understanding the impact of PTM on kidney proteins and further elucidating the potential mechanisms underlying its physiological and pathological functions.