Advertisement

Preparation of the Low Molecular Weight Serum Proteome for Mass Spectrometry Analysis

  • Timothy D. VeenstraEmail author
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 2024)

Abstract

The ability to cure or manage many diseases is highly dependent on the ability to correctly diagnose them at the earliest possible stage. Diagnosis relies heavily on biomarkers whether these be visual symptoms or molecules found within samples acquired from the patient. For conditions that lack useful biomarkers, researchers are often faced with the task of sifting through very complex biological samples (i.e., serum, plasma, urine, tissue, cells, etc.) with the hope of discovering a small number of molecules that are exquisitely diagnostic for the condition of interest. One discovery strategy that has been frequently used is to fractionate the biological samples being studied into simpler aliquots that can be more easily characterized using existing technologies. One such fractionation method is to isolate a specific portion based on a specific property (i.e., size, phosphorylation state, charge, etc.) of the proteins within the sample. This method provides a simplified sample that can be characterized at a higher coverage level than the complex sample from which it was derived. This chapter details one of these methods, the extraction and analysis of the low molecular weight proteome of human serum.

Key words

Low molecular weight proteome Mass spectrometry Serum Protein depletion Biomarkers 

Notes

Acknowledgments

This project has been funded in whole or in part with funds from Maranatha Baptist University. The mention of trade names, commercial products, or organizations does not imply endorsement by Maranatha Baptist University.

References

  1. 1.
    Karczewski KJ, Snyder MP (2018) Integrative omics for health and disease. Nat Rev Genet 19:299–310CrossRefGoogle Scholar
  2. 2.
    Aebersold R, Mann M (2016) Mass-spectrometric exploration of proteome structure and function. Nature 537:347–355CrossRefGoogle Scholar
  3. 3.
    Matsumoto M, Nakayama KI (2018) The promise of targeted proteomics for quantitative network biology. Curr Opin Biotechnol 54:88–97CrossRefGoogle Scholar
  4. 4.
    Paik YK, Omenn GS, Hancock WS et al (2017) Advances in the chromosome-centric human proteome project: looking to the future. Expert Rev Proteomics 14:1059–1071CrossRefGoogle Scholar
  5. 5.
    Gu H, Ren JM, Jia X et al (2016) Quantitative profiling of post-translational modifications by immunoaffinity enrichment and LC-MS/MS in cancer serum without immunodepletion. Mol Cell Proteomics 15:692–702CrossRefGoogle Scholar
  6. 6.
    Amit E, Obena R, Wang YT et al (2015) Integrating proteomics with electrochemistry for identifying kinase biomarkers. Chem Sci 6:4756–4766CrossRefGoogle Scholar
  7. 7.
    Bouamrani A, Hu Y, Tasciotti E et al (2010) Mesoporous silica chips for selective enrichment and stabilization of low molecular weight proteome. Proteomics 10:496–505CrossRefGoogle Scholar
  8. 8.
    Chertov O, Simpson JT, Biragyn A et al (2005) Enrichment of low-molecular-weight proteins from biofluids for biomarker discovery. Expert Rev Proteomics 2:139–145CrossRefGoogle Scholar
  9. 9.
    Pisanu S, Biosa G, Carcangiu L et al (2018) Comparative evaluation of seven commercial products for human serum enrichment/depletion by shotgun proteomics. Talanta 185:213–220CrossRefGoogle Scholar
  10. 10.
    Chen L, Zhai L, Li Y et al (2015) Development of gel-filter method for high enrichment of low-molecular weight proteins from serum. PLoS One 10:e0115862CrossRefGoogle Scholar
  11. 11.
    Adkins JN, Varnum SM, Auberry KJ et al (2002) Toward a human blood serum proteome - analysis by multidimensional separation coupled with mass spectrometry. Mol Cell Proteomics 1:947–955CrossRefGoogle Scholar
  12. 12.
    Dowling P, Ohlendieck K (2018) DIGE analysis of immunodepleted plasma. Methods Mol Biol 1664:245–257CrossRefGoogle Scholar
  13. 13.
    Seong Y, Yoo YS, Akter H, Kang MJ (2017) Sample preparation for detection of low abundance proteins in human plasma using ultra-high performance liquid chromatography coupled with highly accurate mass spectrometry. J Chromatogr B Analyt Technol Biomed Life Sci 1060:272–280CrossRefGoogle Scholar
  14. 14.
    Lim JM, Kim JH, Ryu MY et al (2018) An electrochemical peptide sensor for detection of dengue fever biomarker NS1. Anal Chim Acta 1026:109–116CrossRefGoogle Scholar
  15. 15.
    Colombo M, Looker HC, Farran B et al (2018) Apolipoprotein CIII and N-terminal prohormone b-type natriuretic peptide as independent predictors for cardiovascular disease in type 2 diabetes. Atherosclerosis 274:182–190CrossRefGoogle Scholar
  16. 16.
    Nagel M, Schulz J, Maderer A et al (2018) Cytokeratin-18 fragments predict treatment response and overall survival in gastric cancer in a randomized controlled trial. Tumour Biol 40:1010428318764007CrossRefGoogle Scholar
  17. 17.
    Keay SK, Szekely Z, Conrads TP et al (2004) An antiproliferative factor from interstitial cystitis patients is a frizzled 8 protein-related sialoglycopeptide. Proc Natl Acad Sci U S A 101:11803–11808CrossRefGoogle Scholar
  18. 18.
    Shimizu M, Doi S, Nakashima A et al (2018) N-terminal pro brain natriuretic peptide as a cardiac biomarker in Japanese hemodialysis patients. Int J Artif Organs 41:135–143CrossRefGoogle Scholar
  19. 19.
    Waybright TJ, Chan KC, Veenstra TD, Xiao Z (2013) Preparation of the low molecular weight serum proteome for mass spectrometry analysis. Methods Mol Biol 1061:279–289CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Applied SciencesMaranatha Baptist UniversityWatertownUSA

Personalised recommendations