A Strategy for Rapid Discovery of Marker Peptides Associated with Fibrinolytic Efficacy of Pheretima aspergillum Based on Bioinformatics Combined with Parallel Reaction Monitoring

Abstract

Quality control of animal-derived traditional Chinese medicines has improved dramatically as proteomics research advanced in the past few decades. However, it remains challenging to identify quality attributes with routine proteomics approaches since protein with fibrinolytic activity is rarely reported in pheretima, a typical animal-derived traditional medicine. A novel strategy based on bioinformatics combined with parallel reaction monitoring (PRM) was developed here to rapidly discover the marker peptides associated with a fibrinolytic effect. Potential marker peptides were found by lumbrokinase sequences' alignment and in silico digestion. The fibrinogen zymography was used to visually identify fibrinolytic proteins in pheretima. As a result, it was found that the fibrinolytic activity varied among different portions of pheretima. Fibrinolytic proteins were distributed regionally in the anterior and anterior-mid portion and there was no significant fibrinogenolytic activity observed in the mid-posterior and posterior portion. Finally, PRM experiments were deployed to validate and quantify selected marker peptides and a total of 11 peptides were identified as marker peptides, which could be potentially used in quality control of pheretima. This strategy provides a robust workflow to benefit the quality control of other animal-derived traditional medicines.

Keywords: Pheretima aspergillum; bioinformatics; fibrinolytic efficacy; lumbrokinase; parallel reaction monitoring.

Figure 1

Scheme for rapid discovery of LKs and marker peptides from P. aspergillum. (a) Discovery phase: discovery of potential marker peptides based on bioinformatics tools. (b) Application phase: validation and evaluation of potential marker peptides representing pheretima fibrinolytic activity by PRM combined as well as fibrinogen zymography.

Figure 2

The sequence alignments of LKs. (The meaning of “⋅⋅⋅” were the amino acid residues in the LKs sequences that were not shown in the figure.) We downloaded 36 LKs sequences from different earthworm species from the UniProtKB (http://www.uniprot.org/, accessed on 10 May 2020) and U.S. National Center for Biotechnology Information (NCBI) website (https://www.ncbi.nlm.nih.gov/, accessed on 10 May 2020) and compared using the MEGA 7 software. Eight amino acid residues located were identical or similar among the different LK: I(V)V(I)GG, FPWQ, SHS(F)C, HCVD(MQ), SGWG, GGPL, SWV(G)V(I), and PS(G)VY.

Figure 3

The fibrinogen zymogram of different PA portions (T: anterior portion of the PA, Q: anterior-midportion of the PA H: mid-posterior portion of the PA, W: posterior portion of the PA). Fibrinogen zymography was carried out using a 12% polyacrylamide gel that had been prepared in the presence of fibrinogen (0.5 mg/mL) and thrombin (0.012 BP/mL). We loaded 2 μL samples (5 mg/mL) that were diluted with sample loading buffer without reducing agent into a fibrin gel.

Figure 4

The number and ratio of target amino acid residues in T, Q, H, and W samples (The meanings of T, Q, H, and W are the same as those in Figure 3). The raw data were performed using Thermo Scientific Proteome Discoverer™ 2.2 software. MS/MS spectra were searched in the theoretical pheretima protein database obtained by transcriptomics (including 240,102 proteins). We detected 53, 77, 59, and 65 target peptides with shotgun proteomics from T, Q, H, W samples of PA, respectively.

Figure 5

(a) The normalized peak area of marker peptides in T, Q, H, and W samples with three replicates. (b) MS/MS spectra for the target marker peptides taking peptides NSYQFTGDTCTLSGWGR and WCCCVVGGR as examples (the meanings of T, Q, H, and W are the same with those in Figure 3). The raw data was processed using Skyline (Version 3.6.0) with the software settings according to the online tutorials (https://skyline.ms/wiki/home/software/Skyline/page.view?name=tutorial_prm, accessed on 5 March 2021). The peptide search results of DDA data from Proteome Discoverer analysis were used for spectral library building in skyline.