Compositional Protein Analysis of High Density Lipoproteins in Hypercholesterolemia by Shotgun LC-MS/MS and Probabilistic Peptide Scoring

A protein of a biological sample is usually quantified by immunological techniques based on antibodies. Mass spectrometry offers alternative approaches that are not dependent on antibody affinity and avidity, protein isoforms, quaternary structures, or steric hindrance of antibody-antigen recognition in case of multiprotein complexes. One approach is the use of stable isotope-labeled internal standards; another is the direct exploitation of mass spectrometric signals recorded by LC-MS/MS analysis of protein digests. Here we assessed the peptide match score summation index based on probabilistic peptide scores calculated by the PHENYX protein identification engine for absolute protein quantification in accordance with the protein abundance index as proposed by Mann and co-workers (Rappsilber, J., Ryder, U., Lamond, A. I., and Mann, M. (2002) Large-scale proteomic analysis of the human spliceosome. Genome Res. 12, 1231–1245). Using synthetic protein mixtures, we demonstrated that this approach works well, although proteins can have different response factors. Applied to high density lipoproteins (HDLs), this new approach compared favorably to alternative protein quantitation methods like UV detection of protein peaks separated by capillary electrophoresis or quantitation of protein spots on SDS-PAGE. We compared the protein composition of a well defined HDL density class isolated from plasma of seven hypercholesterolemia subjects having low or high HDL cholesterol with HDL from nine normolipidemia subjects. The quantitative protein patterns distinguished individuals according to the corresponding concentration and distribution of cholesterol from serum lipid measurements of the same samples and revealed that hypercholesterolemia in unrelated individuals is the result of different deficiencies. The presented approach is complementary to HDL lipid analysis; does not rely on complicated sample treatment, e.g. chemical reactions, or antibodies; and can be used for projective clinical studies of larger patient groups. A protein of a biological sample is usually quantified by immunological techniques based on antibodies. Mass spectrometry offers alternative approaches that are not dependent on antibody affinity and avidity, protein isoforms, quaternary structures, or steric hindrance of antibody-antigen recognition in case of multiprotein complexes. One approach is the use of stable isotope-labeled internal standards; another is the direct exploitation of mass spectrometric signals recorded by LC-MS/MS analysis of protein digests. Here we assessed the peptide match score summation index based on probabilistic peptide scores calculated by the PHENYX protein identification engine for absolute protein quantification in accordance with the protein abundance index as proposed by Mann and co-workers (Rappsilber, J., Ryder, U., Lamond, A. I., and Mann, M. (2002) Large-scale proteomic analysis of the human spliceosome. Genome Res. 12, 1231–1245). Using synthetic protein mixtures, we demonstrated that this approach works well, although proteins can have different response factors. Applied to high density lipoproteins (HDLs), this new approach compared favorably to alternative protein quantitation methods like UV detection of protein peaks separated by capillary electrophoresis or quantitation of protein spots on SDS-PAGE. We compared the protein composition of a well defined HDL density class isolated from plasma of seven hypercholesterolemia subjects having low or high HDL cholesterol with HDL from nine normolipidemia subjects. The quantitative protein patterns distinguished individuals according to the corresponding concentration and distribution of cholesterol from serum lipid measurements of the same samples and revealed that hypercholesterolemia in unrelated individuals is the result of different deficiencies. The presented approach is complementary to HDL lipid analysis; does not rely on complicated sample treatment, e.g. chemical reactions, or antibodies; and can be used for projective clinical studies of larger patient groups. Functional proteomics aims at identifying and quantifying proteins of biological systems. Often protein quantity is determined as a relative concentration difference between two states, e.g. non-stimulated cells versus stimulated cells. Two-dimensional gel electrophoresis (2DE) 1The abbreviations used are: 2DE, two-dimensional gel electrophoresis; 1DE, one-dimensional gel electrophoresis (SDS-PAGE); ACTS, actin; ALBU, serum albumin; apoX, apolipoprotein X (X = A-I, A-II, C-I, C-II, C-III, etc.); CE-UV, capillary electrophoresis with UV detection at 200 nm; CONA, concanavalin A; emPAI, exponentially modified protein abundance index; FA, formic acid; FETUA, fetuin; HC, hypercholesterolemia; HDL, high density lipoprotein; HDL-C, HDL cholesterol; INS, insulin; LACB, β-lactoglobulin; LCAT, lecithin-cholesterol acyltransferase; LDL, low density lipoprotein; LDL-C, LDL cholesterol; LYSC, lysozyme; MYG, myoglobin; N, normolipidemia; PAI, protein abundance index; PMSS, peptide match score summation; PMSSI, peptide match score summation index; PRVA, parvalbumin; rHDL, reconstituted HDL; SAA, serum amyloid protein A; SOMA, growth hormone (somatotropin); SpS, spectrum sampling; THYG, thyroglobulin. 1The abbreviations used are: 2DE, two-dimensional gel electrophoresis; 1DE, one-dimensional gel electrophoresis (SDS-PAGE); ACTS, actin; ALBU, serum albumin; apoX, apolipoprotein X (X = A-I, A-II, C-I, C-II, C-III, etc.); CE-UV, capillary electrophoresis with UV detection at 200 nm; CONA, concanavalin A; emPAI, exponentially modified protein abundance index; FA, formic acid; FETUA, fetuin; HC, hypercholesterolemia; HDL, high density lipoprotein; HDL-C, HDL cholesterol; INS, insulin; LACB, β-lactoglobulin; LCAT, lecithin-cholesterol acyltransferase; LDL, low density lipoprotein; LDL-C, LDL cholesterol; LYSC, lysozyme; MYG, myoglobin; N, normolipidemia; PAI, protein abundance index; PMSS, peptide match score summation; PMSSI, peptide match score summation index; PRVA, parvalbumin; rHDL, reconstituted HDL; SAA, serum amyloid protein A; SOMA, growth hormone (somatotropin); SpS, spectrum sampling; THYG, thyroglobulin. is capable of displaying thousands of protein spots on one gel. Changes in protein quantities are measured by densitometry of stained spots. Covalent staining of proteins with fluorescent cyanine dyes (DIGE technology) enables comparison of several samples on the same gel (1Tonge R. Shaw J. Middleton B. Rowlinson R. Rayner S. Young J. Pognan F. Hawkins E. Currie I. Davison M. Validation and development of fluorescence two-dimensional differential gel electrophoresis proteomics technology.Proteomics. 2001; 1: 377-396Crossref PubMed Scopus (809) Google Scholar). More recently, alternative shotgun LC-MS/MS-based approaches have been developed for global proteome analysis to obviate problems inherent to 2DE. When combined with differential isotope labeling of shotgun proteomics is a and for are several approaches for stable isotope and the one on sample and When proteome samples are of human as human plasma and is not to proteins quantitation of protein and S. A. 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