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Characterization of the natural peptidome of four leeches by integrated proteogenomics and pseudotargeted peptidomics

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Abstract

Animal-derived drugs are an indispensable part of folk medicine worldwide. However, their chemical constituents are poorly approached, which leads to the low level of the quality standard system of animal-derived drugs and further causes a chaotic market. Natural peptides are ubiquitous throughout the organism, especially in animal-derived drugs. Thus, in this study, we used multi-source leeches, including Hirudo nipponica (HN), Whitmania pigra (WP), Whitmania acranulata (WA), and Poecilobdella manillensis (PM), as a model. A strategy integrating proteogenomics and novel pseudotargeted peptidomics was developed to characterize the natural peptide phenotype and screen for signature peptides of four leech species. First, natural peptides were sequenced against an in-house annotated protein database of closely related species constructed from RNA-seq data from the Sequence Read Archive (SRA) website, which is an open-sourced public archive resource. Second, a novel pseudotargeted peptidomics integrating peptide ion pair extraction and retention time transfer was established to achieve high coverage and quantitative accuracy of the natural peptides and to screen for signature peptides for species authentication. In all, 2323 natural peptides were identified from four leech species whose databases were poorly annotated. The strategy was shown to significantly improve peptide identification. In addition, 36 of 167 differential peptides screened by pseudotargeted proteomics were identified, and about one-third of them came from the leucine-rich repeat domain (LRR) proteins, which are widely distributed in organisms. Furthermore, six signature peptides were screened with good specificity and stability, and four of them were validated by synthetic standards. Finally, a dynamic multiple reaction monitoring (dMRM) method based on these signature peptides was established and revealed that one-half of the commercial samples and all of the Tongxinluo capsules were derived from WP. All in all, the strategy developed in this study was effective for natural peptide characterization and signature peptide screening, which could also be applied to other animal-derived drugs, especially for modelless species that are less studied in protein database annotation.

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References

  1. Ma C, Li X, Chen H. Research progress in the use of leeches for medical purposes. Tradit Med Res. 2021;2:56–69. https://doi.org/10.53388/TMR20200207159.

    Article  Google Scholar 

  2. Sobczak N, Kantyka M. Hirudotherapy in veterinary medicine. Ann Parasitol. 2014;60(2):89–92.

    PubMed  Google Scholar 

  3. Gu N. A preliminary study on the quality standards of Chinese medicine leeches and the basis of antithrombotic substances. Beijing, China: Beijing University of Traditional Chinese Medicine. 2020. https://doi.org/10.26973/d.cnki.gbjzu.2020.000684.

  4. Qiu J, Wang LN, Hu JH, Zhang YQ. Oral administration of leeches (Shuizhi): a review of the mechanisms of action on antiplatelet aggregation. J Ethnopharmacol. 2019;232:103–9. https://doi.org/10.1016/j.jep.2018.12.010.

    Article  PubMed  Google Scholar 

  5. Tang X, Chen M, Duan Z, Mwangi J, Li P, Lai R. Isolation and characterization of poecistasin, an anti-thrombotic antistasin-type serine protease inhibitor from leech Poecilobdella manillensis. Toxins (Basel). 2018;10(11):429. https://doi.org/10.3390/toxins10110429.

    Article  CAS  PubMed  Google Scholar 

  6. Ren Y, Yang Y, Wu W, Zhang M, Wu H, Li X. Identification and characterization of novel anticoagulant peptide with thrombolytic effect and nutrient oligopeptides with high branched chain amino acid from Whitmania pigra protein. Amino Acids. 2016;48(11):2657–70. https://doi.org/10.1007/s00726-016-2299-8.

    Article  CAS  PubMed  Google Scholar 

  7. Zhang ZY, Ma N, Tao LJ, Gong XY, Ye WC, Wang L. Linear peptides containing d-leucine with neuroprotective activities from the leech Whitmania pigra Whitman. J Nat Prod. 2019;82(8):2349–53. https://doi.org/10.1021/acs.jnatprod.9b00322.

    Article  CAS  PubMed  Google Scholar 

  8. Hu B, Xu L, Li Y, Bai X, Xing M, Cao Q, Liang H, Song S, Ji A. A peptide inhibitor of macrophage migration in atherosclerosis purified from the leech Whitmania pigra. J Ethnopharmacol. 2020;254:112723. https://doi.org/10.1016/j.jep.2020.112723.

    Article  CAS  PubMed  Google Scholar 

  9. Bai Y, Zhao Q, He M, Ye X, Zhang X. Extensive characterization and differential analysis of endogenous peptides from Bombyx Batryticatus using mass spectrometric approach. J Pharm Biomed Anal. 2019;163:78–87. https://doi.org/10.1016/j.jpba.2018.09.033.

    Article  CAS  PubMed  Google Scholar 

  10. He R, Ma H, Zhou J, Zhu Z, Lv X, Li Q, Wang H, Yan Y, Luo N, Di L, Wu Q, Duan J. High resolution mass profile of bufadienolides and peptides combing with anti-tumor cell screening and multivariate analysis for the quality evaluation of bufonis venenum. Mol. 2019;24(10):1943. https://doi.org/10.3390/molecules24101943.

    Article  CAS  Google Scholar 

  11. Shi H, Wang J, Liu F, Hu X, Lu Y, Yan S, Dai D, Yang X, Zhu Z, Guo Q. Proteome and phosphoproteome profiling reveals the regulation mechanism of hibernation in a freshwater leech (Whitmania pigra). J Proteomics. 2020;229:103866. https://doi.org/10.1016/j.jprot.2020.103866.

    Article  CAS  PubMed  Google Scholar 

  12. Cogne Y, Gouveia D, Chaumot A, Degli-Esposti D, Geffard O, Pible O, Almunia C, Armengaud J. Proteogenomics-guided evaluation of RNA-seq assembly and protein database construction for emergent model organisms. Proteome. 2020;20(10):e1900261. https://doi.org/10.1002/pmic.201900261.

    Article  CAS  Google Scholar 

  13. Robinson SD, Mueller A, Clayton D, Starobova H, Hamilton BR, Payne RJ, Vetter I, King GF, Undheim EAB. A comprehensive portrait of the venom of the giant red bull ant, Myrmecia gulosa, reveals a hyperdiverse hymenopteran toxin gene family. Sci Adv. 2018;4(9):4640. https://doi.org/10.1126/sciadv.aau4640.

    Article  CAS  Google Scholar 

  14. Langenegger N, Nentwig W, Kuhn-Nentwig L. Spider venom: components, modes of action, and novel strategies in transcriptomic and proteomic analyses. Toxins (Basel). 2019;11(10):611. https://doi.org/10.3390/toxins11100611.

    Article  CAS  PubMed  Google Scholar 

  15. Ward MJ, Rokyta DR. Venom-gland transcriptomics and venom proteomics of the giant Florida blue centipede. Scolopendra viridis Toxicon. 2018;152:121–36. https://doi.org/10.1016/j.toxicon.2018.07.030.

    Article  CAS  PubMed  Google Scholar 

  16. Khan MS, Guan DL, Kvist S, Ma LB, Xie JY, Xu SQ. Transcriptomics and differential gene expression in Whitmania pigra (Annelida: Clitellata: Hirudinida: Hirudinidae): contrasting feeding and fasting modes. Ecol Evol. 2019;9(8):4706–19. https://doi.org/10.1002/ece3.5074.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Liu Q, Bi Q, Zhang J, Qin W, Yi S, Hu Q, Sun J, Ji S, Tan N. A rapid and simple signature peptides-based method for species authentication of three main commercial Pheretima. J Proteome. 2022;255:104456. https://doi.org/10.1016/j.jprot.2021.104456.

    Article  CAS  Google Scholar 

  18. Han S, Zhao K, Cai S, Jiang M, Huang X, Chen S, Li S, Zhao M, Duan JA, Liu R. Discovery of peptide biomarkers by label-free peptidomics for discrimination of horn gelatin and hide gelatin from Cervus nippon Temminck. Food Chem. 2021;63:130347. https://doi.org/10.1016/j.foodchem.2021.130347.

    Article  CAS  Google Scholar 

  19. Wang CC, Bi QR, Huang DD, Wu SF, Gao M, Li Y, Xing L, Yao S, Guo DA. Identification of Pinelliae Rhizoma and its counterfeit species based on enzymatic signature peptides from toxic proteins. Phytomed. 2022;107:154451. https://doi.org/10.1016/j.phymed.2022.154451.

    Article  CAS  Google Scholar 

  20. Capriotti AL, Cannazza G, Catani M, Cavaliere C, Cavazzini A, Cerrato A, Citti C, Felletti S, Montone CM, Piovesana S, Laganà A. Recent applications of mass spectrometry for the characterization of cannabis and hemp phytocannabinoids: from targeted to untargeted analysis. J Chromatogr A. 2021;1655:462492. https://doi.org/10.1016/j.chroma.2021.462492.

    Article  CAS  PubMed  Google Scholar 

  21. Van BB, Selbach M. An introduction to advanced targeted acquisition methods. Mol Cell Proteome. 2021;20:100165. https://doi.org/10.1016/j.mcpro.2021.100165.

    Article  CAS  Google Scholar 

  22. Zhao H, Wang Y, Zhao L, Dong Z, Mi J, Wang J, Zeng J, Wang H, Wang L. Evaluation and verification of the characteristic peptides for detection of Staphylococcus aureus in food by targeted LC-MS/MS. Talanta. 2021;235:122794. https://doi.org/10.1016/j.talanta.2021.122794.

    Article  CAS  PubMed  Google Scholar 

  23. Lyu JW, Wang Y, Mao JW, Yao Y, Wang SJ, Zheng Y, Ye ML. Pseudotargeted MS method for the sensitive analysis of protein phosphorylation in protein complexes. Anal Chem. 2018;90(10):6214–21. https://doi.org/10.1021/acs.analchem.8b00749.

    Article  CAS  PubMed  Google Scholar 

  24. Yang J, Jin W, Liu D, Zhong Q, Zhou T. Enhanced pseudotargeted analysis using a segment data dependent acquisition strategy by liquid chromatography-tandem mass spectrometry for a metabolomics study of liquiritin in the treatment of depression. J Sep Sci. 2020;43(11):2088–96. https://doi.org/10.1002/jssc.202000107.

    Article  CAS  PubMed  Google Scholar 

  25. Zheng F, Zhao X, Zeng Z, Wang L, Lv W, Wang Q, Xu G. Development of a plasma pseudotargeted metabolomics method based on ultra-high-performance liquid chromatography-mass spectrometry. Nat Protoc. 2020;15(8):2519–37. https://doi.org/10.1038/s41596-020-0341-5.

    Article  CAS  PubMed  Google Scholar 

  26. Zhu XX, Wu H, Shaw PC, Peng W, Su WW. Identification of specific DNA markers for Hirudo in the Naoxintong capsule. J Sun Yat-sen Univ. 2020;59(01):114–24. https://doi.org/10.13471/j.cnki.acta.snus.2020.01.01.

    Article  Google Scholar 

  27. Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I, Adiconis X, Fan L, Raychowdhury R, Zeng Q, Chen Z, Mauceli E, Hacohen N, Gnirke A, Rhind N, Fdi Palma, Birren BW, Nusbaum C, Lindblad-Toh K, Friedman N, Regev A. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat Biotechnol. 2011;29(7):644–52. https://doi.org/10.1038/nbt.1883.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Haas BJ, Papanicolaou A, Yassour M, Grabherr M, Blood PD, Bowden J, Couger MB, Eccles D, Li B, Lieber M, MacManes MD, Ott M, Orvis J, Pochet N, Strozzi F, Weeks N, Westerman R, William T, Dewey CN, Henschel R, LeDuc RD, Friedman N, Regev A. De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis. Nat Protoc. 2013;8(8):1494–512. https://doi.org/10.1038/nprot.2013.084.

    Article  CAS  PubMed  Google Scholar 

  29. Fu L, Niu B, Zhu Z, Wu S, Li W. CD-HIT: accelerated for clustering the next-generation sequencing data. Bioinf. 2012;28(23):3150–2. https://doi.org/10.1093/bioinformatics/bts565.

    Article  CAS  Google Scholar 

  30. Chi H, Liu C, Yang H, Zeng WF, Wu L, Zhou WJ, Wang RM, Niu XN, Ding YH, Zhang Y, Wang ZW, Chen ZL, Sun RX, Liu T, Tan GM, Dong MQ, Xu P, Zhang PH, He SM. Comprehensive identification of peptides in tandem mass spectra using an efficient open search engine. Nat Biotechnol. 2018;36(11):1059. https://doi.org/10.1038/nbt.4236.

    Article  CAS  Google Scholar 

  31. Dupree EJ, Crimmins BS, Holsen TM, Darie CC. Developing well-annotated species-specific protein databases using comparative proteogenomics. Adv Exp Med Biol. 2019;1140:389–400. https://doi.org/10.1007/978-3-030-15950-4_22.

    Article  CAS  PubMed  Google Scholar 

  32. Walker AA, Robinson SD, Paluzzi JPV, Merritt DJ, Nixon SA, Schroeder CI, Jin JY, Goudarzi MH, Kotze AC, Dekan Z, Sombke A, Alewood PF, Fry BG, Epstein ME, Vetter I, King GF. Production, composition, and mode of action of the painful defensive venom produced by a limacodid caterpillar, Doratifera vulnerans. Proc Natl Acad Sci USA. 2021;18(118):e2023815118. https://doi.org/10.1073/pnas.2023815118.

    Article  CAS  Google Scholar 

  33. Ueberheide BM, Fenyo D, Alewood PF, Chait BT. Rapid sensitive analysis of cysteine rich peptide venom components. Proc Natl Acad Sci USA. 2009;106(17):6910–5. https://doi.org/10.1073/pnas.0900745106.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Tan H, Wang J, Song Y, Liu S, Lu Z, Luo H, Tang X. Antibacterial potential analysis of novel alpha-helix peptides in the Chinese wolf spider Lycosa sinensis. Pharma. 2022;14(11):2540. https://doi.org/10.3390/pharmaceutics14112540.

    Article  CAS  Google Scholar 

  35. Xuan QH, Hu C, Yu D, Wang L, Zhou Y, Zhao X, Li Q, Hou X, Xu GW. Development of a high coverage pseudotargeted lipidomics method based on ultra-high performance liquid chromatography-mass spectrometry. Anal Chem. 2018;90(12):7608–16. https://doi.org/10.1021/acs.analchem.8b01331.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Pan HQ, Yao CL, Yang WZ, Yao S, Huang Y, Zhang YB, Wu WY, Guo DA. An enhanced strategy integrating offline two-dimensional separation and step-wise precursor ion list-based raster-mass defect filter: characterization of indole alkaloids in five botanical origins of Uncariae Ramulus Cum Unicis as an exemplary application. J Chromatogr A. 2018;1563:124–34. https://doi.org/10.1016/j.chroma.2018.05.066.

    Article  CAS  PubMed  Google Scholar 

  37. Eshghi A, Gaultney RA, England P, Brûlé S, Miras I, Sato H, Coburn J, Bellalou J, Moriarty TJ, Haouz A, Picardeau M. An extracellular Leptospira interrogans leucine-rich repeat protein binds human E and VE-cadherins. guolayiCell Microbiol. 2019;21(2):12949. https://doi.org/10.1111/cmi.12949.

    Article  CAS  Google Scholar 

  38. Sket B, Trontelj P. Global diversity of leeches (Hirudinea) in freshwater. Dev Hydrobiol. 2007;198(595):129–37. https://doi.org/10.1007/s10750-007-9168-0.

    Article  Google Scholar 

  39. Liu X, Gao MF, Kong Y. Bioactive constituents and pharmacological effects of leech. Chin J Pharm Biol. 2017;24:76–80. https://doi.org/10.19526/j.cnki.1005-8915.20170117.

    Article  Google Scholar 

  40. Liu XF, Liu CS, Yang YJ, Bai ZF, Wu LJ, Xu J, Liu J, Dai D. DNA barcodes of Shuizhi(Hirudo) and its adulterants studied based on COI gene. 2013;1(36):63-66. https://doi.org/10.3969/j.issn.1006-2157.2013.01.015.

  41. Guan NN, Suo SR, Qiao YH, Wang ZY, Feng D, Zhao X, Meng XD, Zhou DX. Study on finger print and 16 amino acids’s content determination of Hirudo by pre-column derivat ization-high performance liquid chromatography method. J Tradit Chin Med. 2020;13:592–9. https://doi.org/10.3969/j.issn.1674-1749.2020.04.009.

    Article  CAS  Google Scholar 

  42. Zeng WF, Zhou XX, Willems S, Ammar C, Wahle M, Bludau I, Voytik E, Strauss MT, Mann M. AlphaPeptDeep: a modular deep learning framework to predict peptide properties for proteomics. Nat Commun. 2022;13(1):7238. https://doi.org/10.1038/s41467-022-34904-3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Gessulat S, Schmidt T, Zolg DP, Samaras P, Schnatbaum K, Zerweck J, Knaute T, Rechenberger J, Delanghe B, Huhmer A, Reimer U, Ehrlich HC, Aiche S, Kuster B, Wilhelm M. Prosit: proteome-wide prediction of peptide tandem mass spectra by deep learning. Nat Methods. 2019;16(6):509–18. https://doi.org/10.1038/s41592-019-0426-7.

    Article  CAS  PubMed  Google Scholar 

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Funding

This work was financially supported by the Key Program of the National Natural Science Foundation of China (NO.82130111), National Natural Science Foundation of China (NO.81803716), and Chief Scientist of Qi-Huang Project of National Traditional Chinese Medicine Inheritance.

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Jingmei Liao: methodology, formal analysis, writing—original draft, visualization. Min Gao: methodology, formal analysis, writing—original draft, visualization. Qirui Bi: conceptualization, writing—review and editing, project administration. Yelin Ding: resources, writing—original draft. Dongdong Huang: software, formal analysis, visualization. Xiaoxiao Luo: formal analysis, visualization. Peilei Yang: resources. Yun Li: data curation. Yong, Huang, Changliang Yao: formal analysis. Jianqing Zhang: formal analysis. Wenlong Wei: formal analysis. Zhenwei Li: formal analysis.

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Correspondence to De-an Guo.

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Liao, J., Gao, M., Ding, Y. et al. Characterization of the natural peptidome of four leeches by integrated proteogenomics and pseudotargeted peptidomics. Anal Bioanal Chem 415, 2795–2807 (2023). https://doi.org/10.1007/s00216-023-04692-w

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