Citation: SHI Ruo-Han, YAN Guo-Quan, GAO Ming-Xia, ZHANG Xiang-Min. Deep Coverage in Identification of Proteome Based on Separation by Multi-dimensional Liquid Chromatography[J]. Chinese Journal of Analytical Chemistry, ;2022, 50(8): 1179-1187,1242. doi: 10.19756/j.issn.0253-3820.221117 shu

Deep Coverage in Identification of Proteome Based on Separation by Multi-dimensional Liquid Chromatography

1.
Department of Chemistry, Fudan University, Shanghai 200438, China;
2.
Institutes of Biomedical Sciences, Fudan University, Shanghai 200030, China

Corresponding author: YAN Guo-Quan, ZHANG Xiang-Min,
Received Date: 9 March 2022
Revised Date: 14 May 2022

Fund Project: Supported by the National Key Research and Development Program of China (No.2017YFA0505003) and the National Natural Science Foundation of China (No.21775027).

Sequence coverage of identified proteins could be significantly improved when human urine proteins were effectively separated based on multi-dimensional liquid chromatography (MDLC). The high-efficient two-dimensional (2D) separating system involved strong anion exchange chromatography as the first dimension (1^stD-SAX) and reversed phase liquid chromatography as the second dimension (2^ndD-RPLC). After optimization of separate conditions, the peak capacity of 2D chromatographic system exceeded 40000. With regard to technique demands and ability to identify, 50 fractions were collected in the first dimension and 64 fractions were collected in the second dimension respectively, with valid peak capacity reaching 3200. On the basis of this system, the separation of intact proteins as well as the deep coverage of identification could be realized in human urine proteome. Urine samples from a group of healthy volunteers were collected and pretreatment including centrifugation and ultrafiltration was conducted subsequently to purify samples. To further improve pertinence, all samples were initially separated by 1^stD-SAX, and the fraction 14 collected from 39 to 42 min was regarded as the main target. Fraction 14 was divided equally into two parts. One was digested and identified directly to obtain mass spectrometry (MS) data, while the other was further separated by 2^ndD-RPLC and 64 fractions were collected. Then the 64 fractions were digested and identified individually to obtain aggregate data. Statistics indicated that 628 proteins were identified without 2^ndD-RPLC separation while 2440 proteins were identified from 64 fractions. Among 588 proteins identified in common, the sequence coverage was significantly improved when a 2D separation was involved. Further analysis revealed that the sequence coverage of proteins composed of no more than 500 amino acids (AAs) reached 31.30%, a 2.02 fold-change compared with merely one-dimensional (1D) separation. For proteins composed of 501-1000 AAs, the sequence coverage increased from 7.79% in 1D separation to 21.35% in 2D separation. For larger proteins composed of over 1000 AAs, the sequence coverage could be enhanced by 3.87 times. These results verified the extraordinary improvement in coverage and reliability of identification when proteins were adequately separated by MDLC compared with the commonly used shotgun method. Meanwhile, the peptide counts from MS analysis could be increased to reduce the probability of mismatch or omission, thus contributing to acquiring more complete and detailed information on protein sequence, which was of great significance to realize deep coverage identification of proteome and establish more accurate proteomic databases.
- Urine,
- Proteomics,
- Multi-dimensional liquid chromatography,
- Strong anion exchange chromatography,
- Reversed phase liquid chromatography,
- Peak capacity,
- Deep coverage
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沈阳化工大学材料科学与工程学院沈阳 110142