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Novel “omics” approach for study of low-abundance, low-molecular-weight components of a complex biological tissue: regional differences between chorionic and basal plates of the human placenta

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Abstract

Tissue proteomics has relied heavily on two-dimensional gel electrophoresis, for protein separation and quantification, then single protein isolation, trypsin digestion, and mass spectrometric protein identification. Such methods are predominantly used for study of high-abundance, full-length proteins. Tissue peptidomics has recently been developed but is still used to study the most highly abundant species, often resulting in observation and identification of dozens of peptides only. Tissue lipidomics is likewise new, and reported studies are limited. We have developed an “omics” approach that enables over 7,000 low-molecular-weight, low-abundance species to be surveyed and have applied this to human placental tissue. Because the placenta is believed to be involved in complications of pregnancy, its proteomic evaluation is of substantial interest. In previous research on the placental proteome, abundant, high-molecular-weight proteins have been studied. Application of large-scale, global proteomics or peptidomics to the placenta have been limited, and would be challenging owing to the anatomic complexity and broad concentration range of proteins in this tissue. In our approach, involving protein depletion, capillary liquid chromatography, and tandem mass spectrometry, we attempted to identify molecular differences between two regions of the same placenta with only slightly different cellular composition. Our analysis revealed 16 species with statistically significant differences between the two regions. Tandem mass spectrometry enabled successful sequencing, or otherwise enabled chemical characterization, of twelve of these. The successful discovery and identification of regional differences between the expression of low-abundance, low-molecular weight biomolecules reveals the potential of our approach.

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References

  1. Chen J, Kahne T, Rocken C, Gotze T, Yu J, Sung JJY, Chen M, Hu P, Malfertheiner P, Ebert MPA (2004) Proteome analysis of gastric cancer metastasis by two-dimensional gel electrophoresis and matrix assisted laser desorption/ionization–mass spectrometry for identification of metastasis-related proteins. J Proteome Res 3(5):1009–1016. doi:10.1021/pr049916l

    Article  CAS  Google Scholar 

  2. Kim J, Kim SH, Lee SU, Ha GH, Kang DG, Ha NY, Ahn JS, Cho HY, Kang SJ, Lee YJ, Hong SC, Ha WS, Bae JM, Lee CW, Kim JW (2002) Proteome analysis of human liver tumor tissue by two-dimensional gel electrophoresis and matrix assisted laser desorption/ionization–mass spectrometry for identification of disease-related proteins. Electrophoresis 23(24):4142–4156

    Article  CAS  Google Scholar 

  3. Washburn MP, Wolters D, Yates JR (2001) Large-scale analysis of the yeast proteome by multidimensional protein identification technology. Nat Biotechnol 19(3):242–247

    Article  CAS  Google Scholar 

  4. Kline KG, Wu CC (2009) MudPIT analysis: application to human heart tissue. Methods Mol Biol 528:281–293

    Article  CAS  Google Scholar 

  5. Catherman AD, Skinner OS, Kelleher NL (2014) Top Down proteomics: facts and perspectives. Biochem Biophys Res Commun 445(4):683–693. doi:10.1016/j.bbrc.2014.02.041

    Article  CAS  Google Scholar 

  6. Catherman AD, Durbin KR, Ahlf DR, Early BP, Fellers RT, Tran JC, Thomas PM, Kelleher NL (2013) Large-scale top-down proteomics of the human proteome: membrane proteins, mitochondria, and senescence. Mol Cell Proteomics MCP 12(12):3465–3473. doi:10.1074/mcp.M113.030114

    Article  CAS  Google Scholar 

  7. Heroux MS, Chesnik MA, Halligan BD, Al-Gizawiy M, Connelly JM, Mueller WM, Rand SD, Cochran EJ, LaViolette PS, Malkin MG, Schmainda KM, Mirza SP (2014) Comprehensive characterization of glioblastoma tumor tissues for biomarker identification using mass spectrometry-based label-free quantitative proteomics. Physiol Genomics 46(13):467–481

    Article  CAS  Google Scholar 

  8. Wardman J, Fricker LD (2011) Quantitative peptidomics of mice lacking peptide-processing enzymes. Methods Mol Biol 768:307–323

    Article  CAS  Google Scholar 

  9. Che FY, Fricker LD (2005) Quantitative peptidomics of mouse pituitary: comparison of different stable isotopic tags. J Mass Spectrom 40(2):238–249

    Article  CAS  Google Scholar 

  10. Tajima Y, Ishikawa M, Maekawa K, Murayama M, Senoo Y, Nishimaki-Mogami T, Nakanishi H, Ikeda K, Arita M, Taguchi R, Okuno A, Mikawa R, Niida S, Takikawa O, Saito Y (2013) Lipidomic analysis of brain tissues and plasma in a mouse model expressing mutated human amyloid precursor protein/tau for Alzheimer's disease. Lipids Health Dis 12:68. doi:10.1186/1476-511x-12-68

    Article  CAS  Google Scholar 

  11. Chan RB, Oliveira TG, Cortes EP, Honig LS, Duff KE, Small SA, Wenk MR, Shui G, Di Paolo G (2012) Comparative lipidomic analysis of mouse and human brain with Alzheimer disease. J Biol Chem 287(4):2678–2688. doi:10.1074/jbc.M111.274142

    Article  CAS  Google Scholar 

  12. Korkes HA, Sass N, Moron AF, Câmara NOS, Bonetti T, Cerdeira AS, Da Silva IDCG, De Oliveira L (2014) Lipidomic assessment of plasma and placenta of women with early-onset preeclampsia. PLoS ONE 9(10), e110747. doi:10.1371/journal.pone.0110747

    Article  Google Scholar 

  13. Alvarez MT, Shah DJ, Thulin CD, Graves SW (2013) Tissue proteomics of the low-molecular weight proteome using an integrated cLC-ESI-QTOFMS approach. Proteomics 13(9):1400–1411

    Article  CAS  Google Scholar 

  14. Esplin MS, Merrell K, Goldenberg R, Lai Y, Iams JD, Mercer B, Spong CY, Miodovnik M, Simhan HN, van Dorsten P, Dombrowski M (2010) Proteomic identification of serum peptides predicting subsequent spontaneous preterm birth. Am J Obstet Gynecol 204(5):391.e391–391.e398. doi:10.1016/j.ajog.2010.09.021

    Google Scholar 

  15. Merrell K, Thulin CD, Esplin MS, Graves SW (2009) An integrated serum proteomic approach capable of monitoring the low molecular weight proteome with sequencing of intermediate to large peptides. Rapid Commun Mass Spectrom 23(17):2685–2696

    Article  CAS  Google Scholar 

  16. Roberts DJ, Post MD (2008) The placenta in pre-eclampsia and intrauterine growth restriction. J Clin Pathol 61(12):1254–1260. doi:10.1136/jcp.2008.055236

    Article  CAS  Google Scholar 

  17. Prouillac C, Lecoeur S (2010) The role of the placenta in fetal exposure to xenobiotics: importance of membrane transporters and human models for transfer studies. Drug Metab Dispos 38(10):1623–1635. doi:10.1124/dmd.110.033571

    Article  CAS  Google Scholar 

  18. Benirschke K, Kaufmann P, Baergen RN (2006) Pathology of the human placenta, 5th edn. Springer, NY

    Google Scholar 

  19. Hwang HS, Park SH, Park YW, Kwon HS, Sohn IS (2010) Expression of cellular prion protein in the placentas of women with normal and preeclamptic pregnancies. Acta Obstet Gynecol Scand 89(9):1155–1161

    Article  CAS  Google Scholar 

  20. Damsky CH, Fitzgerald ML, Fisher SJ (1992) Distribution patterns of extracellular matrix components and adhesion receptors are intricately modulated during first trimester cytotrophoblast differentiation along the invasive pathway, in vivo. J Clin Invest 89(1):210–222

    Article  CAS  Google Scholar 

  21. Reimel BA, Pan S, May DH, Shaffer SA, Goodlett DR, McIntosh MW, Yerian LM, Bronner MP, Chen R, Brentnall TA (2009) Proteomics on fixed tissue specimens—a review. Curr Proteomics 6(1):63–69

    Article  CAS  Google Scholar 

  22. Robinson JM, Vandre DD, Ackerman WE (2009) Placental proteomics: a shortcut to biological insight. Placenta 30(9):13

    Google Scholar 

  23. Centlow M, Hansson SR, Welinder C (2009) Differential proteome analysis of the preeclamptic placenta using optimized protein extraction. J Biomed Biotechnol 2010 (2010). doi:10.1155/2010/458748

  24. Wang F, Shi Z, Wang P, You W, Liang G (2013) Comparative proteome profile of human placenta from normal and preeclamptic pregnancies. PLoS ONE 8(10):2013

    Google Scholar 

  25. Dunn WB, Brown M, Worton SA, Crocker IP, Broadhurst D, Horgan R, Kenny LC, Baker PN, Kell DB, Heazell AE (2009) Changes in the metabolic footprint of placental explant-conditioned culture medium identifies metabolic disturbances related to hypoxia and pre-eclampsia. Placenta 30(11):974–980

    Article  CAS  Google Scholar 

  26. Andersen HU, Fey SJ, Larsen PM, Nawrocki A, Hejnaes KR, Mandrup-Poulsen T, Nerup J (1997) Interleukin-1beta induced changes in the protein expression of rat islets: a computerized database. Electrophoresis 18(11):2091–2103. doi:10.1002/elps.1150181136

    Article  CAS  Google Scholar 

  27. Schröder S, Zhang H, Yeung ES, Jänsch L, Zabel C, Wätzig H (2008) Quantitative gel electrophoresis: sources of variation. J Proteome Res 7(3):1226–1234. doi:10.1021/pr700589s

    Article  Google Scholar 

  28. Mazur MT, Cardasis HL, Spellman DS, Liaw A, Yates NA, Hendrickson RC (2010) Quantitative analysis of intact apolipoproteins in human HDL by top-down differential mass spectrometry. Proc Natl Acad Sci U S A 107(17):7728–7733

    Article  CAS  Google Scholar 

  29. Ma B, Zhang K, Hendrie C, Liang C, Li M, Doherty-Kirby A, Lajoie G (2003) PEAKS: powerful software for peptide de novo sequencing by tandem mass spectrometry. Rapid Commun Mass Spectrom 17(20):2337–2342

    Article  CAS  Google Scholar 

  30. Xu F, Zou L, Lin Q, Ong CN (2009) Use of liquid chromatography/tandem mass spectrometry and online databases for identification of phosphocholines and lysophosphatidylcholines in human red blood cells. Rapid Commun Mass Spectrom 23(19):3243–3254

    Article  CAS  Google Scholar 

  31. Al-Saad KA, Siems WF, Hill HH, Zabrouskov V, Knowles NR (2003) Structural analysis of phosphatidylcholines by post-source decay matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. J Am Soc Mass Spectrom 14(4):373–382

    Article  CAS  Google Scholar 

  32. Shi Z, Long W, Zhao C, Guo X, Shen R, Ding H (2013) Comparative proteomics analysis suggests that placental mitochondria are involved in the development of pre-eclampsia. PLoS ONE 8(5):2013

    Google Scholar 

  33. DeSouza L, Diehl G, Rodrigues MJ, Guo J, Romaschin AD, Colgan TJ, Siu KW (2005) Search for cancer markers from endometrial tissues using differentially labeled tags iTRAQ and cICAT with multidimensional liquid chromatography and tandem mass spectrometry. J Proteome Res 4(2):377–386

    Article  CAS  Google Scholar 

  34. Kelleher NL (2004) Top-down proteomics. Anal Chem 76(11):197A–203A

    Article  Google Scholar 

  35. Gygi SP, Rist B, Griffin TJ, Eng J, Aebersold R (2002) Proteome analysis of low-abundance proteins using multidimensional chromatography and isotope-coded affinity tags. J Proteome Res 1(1):47–54

    Article  CAS  Google Scholar 

  36. Xu Z, Wu C, Xie F, Slysz GW, Tolic N, Monroe ME, Petyuk VA, Payne SH, Fujimoto GM, Moore RJ, Fillmore TL, Schepmoes AA, Levine DA, Townsend RR, Davies SR, Li S, Ellis M, Boja E, Rivers R, Rodriguez H, Rodland KD, Liu T, Smith RD (2014) Comprehensive quantitative analysis of ovarian and breast cancer tumor peptidomes. J Proteome Res 14(1):422–433. doi:10.1021/pr500840w

    Article  Google Scholar 

  37. Michalski A, Cox J, Mann M (2011) More than 100,000 detectable peptide species elute in single shotgun proteomics runs but the majority is inaccessible to data-dependent LC-MS–MS. J Proteome Res 10(4):1785–1793. doi:10.1021/pr101060v

    Article  CAS  Google Scholar 

  38. Paule S, Li Y, Nie G (2011) Cytoskeletal remodelling proteins identified in fetal–maternal interface in pregnant women and rhesus monkeys. J Mol Histol 42(2):161–166

    Article  CAS  Google Scholar 

  39. Orendi K, Kivity V, Sammar M, Grimpel Y, Gonen R, Meiri H, Lubzens E, Huppertz B (2011) Placental and trophoblastic in vitro models to study preventive and therapeutic agents for preeclampsia. Placenta 2011(32):023

    Google Scholar 

  40. Mutter WP, Karumanchi SA (2008) Molecular mechanisms of preeclampsia. Microvasc Res 75(1):1–8

    Article  CAS  Google Scholar 

  41. Bauer DE, Orkin SH (2011) Update on fetal hemoglobin gene regulation in hemoglobinopathies. Curr Opin Pediatr 23(1):1–8. doi:10.1097/MOP.0b013e3283420fd0

    Article  CAS  Google Scholar 

  42. Seydewitz HH, Witt I (1989) The fraction of high molecular weight (HMW) fibrinogen and phosphorylated fibrinopeptide A in fetal fibrinogen. Thromb Res 55(6):785–790

    Article  CAS  Google Scholar 

  43. Maurer MC, Peng JL, An SS, Trosset JY, Henschen-Edman A, Scheraga HA (1998) Structural examination of the influence of phosphorylation on the binding of fibrinopeptide A to bovine thrombin. Biochemistry 37(17):5888–5902

    Article  CAS  Google Scholar 

  44. Lu G, Zhu S, Ke Y, Jiang X, Zhang S (2013) Transplantation-potential-related biological properties of decidua basalis mesenchymal stem cells from maternal human term placenta. Cell Tissue Res 352(2):301–312

    Article  Google Scholar 

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Acknowledgments

This work was supported by the Department of Chemistry and Biochemistry, Brigham Young University. The authors would like to extend their gratitude to several individuals who participated in parts of this study: Dr Moana Hopoate-Sitake, Bruce Jackson, Jody Jones, Dr M. Sean Esplin, and the Mass Spectrometry Facility at BYU. We gratefully acknowledge the support provided by Intermountain Health Care (IHC) hospitals in making placental tissue samples available.

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The authors declare no competing financial considerations or other conflicts of interest.

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Correspondence to Steven W. Graves.

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Kedia, K., Nichols, C.A., Thulin, C.D. et al. Novel “omics” approach for study of low-abundance, low-molecular-weight components of a complex biological tissue: regional differences between chorionic and basal plates of the human placenta. Anal Bioanal Chem 407, 8543–8556 (2015). https://doi.org/10.1007/s00216-015-9009-3

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