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Discovery of a Hidden Proinflammatory Signaling Proteome Using a Large-Scale, Targeted Antibody Microarray Platform

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Cancer Systems and Integrative Biology

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2660))

Abstract

Dynamic post-translational processes regulate protein expression in eukaryotic cells. However, the processes are difficult to assess on a proteomic scale because protein levels actually reflect the sum of individual biosynthesis and degradation rates. These rates are presently hidden from the conventional proteomic technologies. We present here a novel and dynamic, antibody microarray-based time-resolved approach to simultaneously measure not only the total protein changes but also the rates of biosynthesis of low abundance proteins in the proteome of lung epithelial cells. In this chapter, we describe the feasibility of this technique by investigating the complete proteomic kinetics of 507 low abundance proteins in cultured cystic fibrosis (CF) lung epithelial cells using 35[S] methionine or 32[P] and the consequences of repair by gene therapy with [wildtype] CFTR. This novel antibody microarray-based technology identifies relevant, hidden proteins whose regulation by the CF genotype would never have been detected by simple measurements of total proteomic masses.

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References

  1. Gygi SP, Rist B, Gerber SA et al (1999) Quantitative analysis of complex mixtures using isotope-coded affinity tags. Nat Biotechnol 17:994–999

    Article  CAS  PubMed  Google Scholar 

  2. Ideker T, Thorsson V, Ranish JA et al (2001) Integrated genomic and proteomic analyses of a systematically perturbed metabolic network. Science 292:929–934

    Article  CAS  PubMed  Google Scholar 

  3. Greenbaum D, Jansen R, Gerstein M (2002) Analysis of mRNA expression and protein abundance data: an approach for the comparison of the enrichment features in the cellular population of proteins and transcripts. Bioinformatics 18:585–596

    Article  CAS  PubMed  Google Scholar 

  4. Lian Z, Kluger Y, Greenbaum DS et al (2002) Genomic and proteomic analysis of the myeloid differentiation program: global analysis of gene expression during induced differentiation in the MPRO cell line. Blood 100:3209–3220

    Article  CAS  PubMed  Google Scholar 

  5. McRedmond JP, Park SD, Reilly DF et al (2004) Integration of proteomics and genomics in platelets: a profile of platelet proteins and platelet-specific genes. Mol Cell Proteomics 3(2):133–144

    Article  CAS  PubMed  Google Scholar 

  6. Patton WF (2000) A thousand points of light: the application of fluorescence detection technologies to two-dimensional gel electrophoresis and proteomics. Electrophoresis 21:1123–1144

    Article  CAS  PubMed  Google Scholar 

  7. Sanford EJ, Smolka MB (2002) A field guide to the proteomics of post-translational modifications in DNA repair. Proteomics 22(15–16):e2200064. https://doi.org/10.1002/pmic.202200064

    Article  CAS  Google Scholar 

  8. Krijgsveld J, Ketting RF, Mahmoudi T et al (2003) Metabolic labeling of C. elegans and D. melanogaster by quantitative proteomics. Nat Biotechnol 21:927–931

    Article  CAS  PubMed  Google Scholar 

  9. Huang RP (2001) Detection of multiple proteins in an antibody-based protein microarray system. J Immun Methods 255:1–13

    Article  CAS  Google Scholar 

  10. Haab BB (2003) Methods and applications of antibody microarrays in cancer research. Proteomics 3:2116–2122

    Article  CAS  PubMed  Google Scholar 

  11. Glokler J, Angenendt P (2003) Protein and antibody microarray technology. J Chromatogr B Analyt Technol Biomed Life Sci 797:229–240

    Article  CAS  PubMed  Google Scholar 

  12. de Wildt RMT, Mundy CR, Gorick BD, Tomlinson IM (2000) Antibody arrays for high throughput screening of antigen-antibody interactions. Nat Biotechnol 18:989–994

    Article  PubMed  Google Scholar 

  13. Belov L, Huang P, Barber N et al (2003) Identification of repertoires of surface antigens on leukemias using an antibody microarray. Proteomics 3:2147–2154

    Article  CAS  PubMed  Google Scholar 

  14. Michaud GA, Salcius M, Zhou F et al (2003) Analyzing antibody specificity with whole proteome microarrays. Nat Biotechnol 21:1509–1512

    Article  CAS  PubMed  Google Scholar 

  15. Nielsen UB, Cardone MH, Sinskey AJ et al (2003) Profiling receptor tyrosine kinase activation by using Ab microarrays. Proc Natl Acad Sci U S A 100(16):9330–9335

    Article  PubMed  PubMed Central  Google Scholar 

  16. Pollard HB, Eidelman O, Jozwik C, Huang W, Srivastava M et al (2006) de Novo biosynthetic profiling of high abundance proteins in cystic fibrosis lung epithelial cells. Mol Cell Proteomics 5:1628–1637

    Article  CAS  PubMed  Google Scholar 

  17. Pollard HB, Eidelman O, Srivastava M, Jozwik C et al (2007) Protein microarray platforms for clinical proteomics. Proteomics Clin Appl 1(9):934–952

    Article  CAS  PubMed  Google Scholar 

  18. Srivastava M, Eidelman O, Jozwik C et al (2006) Antibody microarray platform for serum proteomics of cystic fibrosis. Mol Genet Metab 87:303–310

    Article  CAS  PubMed  Google Scholar 

  19. Chen Z, Dodig-Crnković T, Schwenk JM, Tao SC (2018) Current applications of antibody microarrays. Clin Proteomics 15:7–22

    Article  PubMed  PubMed Central  Google Scholar 

  20. Tusher VG, Tibshirani R, Chu G (2001) Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci U S A 98:5116–5121

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Correspondence to Meera Srivastava .

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Jozwik, C., Eidelman, O., Srivastava, M. (2023). Discovery of a Hidden Proinflammatory Signaling Proteome Using a Large-Scale, Targeted Antibody Microarray Platform. In: Kasid, U.N., Clarke, R. (eds) Cancer Systems and Integrative Biology. Methods in Molecular Biology, vol 2660. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3163-8_15

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  • DOI: https://doi.org/10.1007/978-1-0716-3163-8_15

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-3162-1

  • Online ISBN: 978-1-0716-3163-8

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