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GENETICS |
Department of Animal and Nutritional Sciences, University of New Hampshire, Durham 03824
2 Corresponding author: bob.taylor{at}unh.edu.
| ABSTRACT |
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-inducing factor) corresponded to the current hypotheses to explain atherogenesis. In addition, the unique electrophoretic migration zones of proteins associated with susceptibility or resistance should prove useful as a diagnostic tool in clinical settings where species or phenotypes, or both, susceptible or resistant to atherosclerosis can be identified.
Key Words: atherosclerosis proteomics pigeon smooth muscle cell
| INTRODUCTION |
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In attempts to understand genetic components of this disease, the susceptible-resistant pigeon (Columba livia) model has been employed. The White Carneau (WC) pigeon develops naturally occurring (noninduced, spontaneous) atherosclerosis without elevated plasma cholesterol levels and in the absence of other known risk factors (Clarkson et al., 1959). These noninduced atherosclerotic lesions are morphologically and ultrastructurally similar to those seen in humans (Cooke and Smith, 1968; Santerre et al., 1972), even occurring at similar anatomical sites along the arterial tree (Kjaernes, 1981). Avian lesions (Siller, 1965), and especially pigeon lesions (St. Clair, 1998; Moghadasian et al., 2001), have been described as having greater similarities to human atherosclerosis than any other animal model of heart disease, including mice, monkeys, and swine.
St. Clair (1983) has reviewed numerous studies that clearly demonstrated that WC susceptibility resides at the level of the arterial wall. The Show Racer (SR) pigeon is resistant to the development of atherosclerosis under identical diet and housing conditions, and with similar blood cholesterol levels (Clarkson et al., 1959). Cross-breeding and backcross experiments demonstrated aortic atherosclerosis susceptibility to be inherited in a pattern consistent with an autosomal recessive Mendelian trait (Smith et al., 2001).
Although a recent study examined gene expression in the pigeon model (Guo et al., 2006), mRNA levels do not necessarily correlate with the amount of protein present in the cell (Gygi et al., 1999). Furthermore, the DNA blueprint of a species does not directly reveal the protein complexity of that organism (Peltonen and McKusick, 2001). One gene may encode multiple proteins as a result of mRNA splicing, RNA editing, or co- and posttranslational modifications. Therefore, the functional complexity indicated by the genome alone and identification of the gene responsible for susceptibility or resistance may not solely explain the metabolic basis for the susceptible phenotype. A more complete elucidation of gene expression can be achieved through characterization of the proteins that are the biological determinants of phenotype.
Changes in health status are the result of proteome changes in response to endogenous or exogenous, or both, stimuli. Healthy vs. diseased states can be distinguished by their respective proteomic profiles. The goal of clinical proteomics is to create proteome profiles for different stages of a disease so that even if specific proteins are not identified, an overall diagnostic pattern may be evident (Marko-Varga and Fehniger, 2004). McGregor et al. (2001) presented a protein expression map of vascular smooth muscle cells from human saphenous veins; however, few proteomic techniques have been used to study the aortic cell degeneration that occurs during atherogenesis (Zerkowski et al., 2004). A 2-dimensional (2-D) gel protein profile of rabbit aortic smooth muscle cells in vivo and in vitro was published without any protein identification (Weiss et al., 1992). Other arterial wall proteome studies focused on excreted proteins rather than on the protein composition of cells (Duran et al., 2003; You et al., 2003). More recently, Mayr et al. (2005) compared proteins involved in atherosclerosis in apolipoprotein E –/– mice with those in aortas of apolipoprotein E +/+ mice on a normal diet. The current status of proteomic studies of atherosclerosis is reviewed by Drake and Ping (2007), but the process of arterial degeneration remains poorly described. Little work has been done to discriminate between the initiation and progression phases of arterial lesion development.
This communication presents differences in the soluble proteome between WC and SR aortic cells. A gel map of differentially expressed protein spots is presented to indicate zones or patterns that are characteristic of susceptibility and resistance to atherogenesis in pigeons. Selected proteins from these unique zones were identified by their peptide mass fragments and by comparisons with genes found to be differentially expressed between cDNA from WC and SR aorta cells.
| MATERIALS AND METHODS |
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Extraction of Cell Proteins
The cell layer from twenty-five 40-mL culture flasks was rinsed with Hanks balanced salt solution; then cells were removed by mechanical scraping and sedimented in a Dounce homogenizer to yield 1 x 108 cells. Proteins were extracted sequentially based on solubility using the ReadyPrep Sequential Extraction Kit (Bio-Rad Laboratories, Hercules, CA). The most soluble proteins (fraction 1) were extracted by homogenization in 40 mM Tris base with DNase I and RNase A. Less soluble proteins (fraction 2) were extracted from the remaining pellet by homogenization with tributyl phosphine in a solution of 8 M urea, 4% (wt/vol) 3-[(3-cholamidoproyl)-dimethylammonia]-1-propanesulfonate, 40 mM Tris, and 0.2% (wt/vol) Bio-Lyte 3/10 ampholyte. Analyses of the insoluble and extremely hydrophobic proteins (fractions 3 and 4) were not pursued, because these extractions produced less than 20% of the required total protein. Such a yield would have necessitated a much large number (>125) of cultures to produce sufficient analyte material.
Electrophoretic Separation of Proteins
The Electrophoret IQ 2000 GelChip 2-D Array Technology System (Proteome Systems, Woburn, MA) in the UNH Proteomics Center was used to separate proteins from each extraction fraction on 2-D sodium dodecyl sulfate polyacrylamide gels. Separation in the first dimension was on 24 cm of Immobilized pH Gradient strips with a pH range 4 to 7 or 3 to 10, and the second dimension was run on 10 x 15 cm precast gels (Proteom IQ GelChip, 8 to 16% polyacrylamide). After separation, the protein spots were stained with Coomassie Blue. Most proteins differentially expressed between WC and SR were found within the pH 4 to 7 range, the range that gave better resolution of spots. However, separations over the pH 3 to 10 range showed several differentially expressed proteins in discrete zones above pH 7. Three replicate culture pools from each breed were subjected to the complete extraction and analysis procedure, and differentially expressed proteins were identified.
Analysis of Protein Spots
Digital gel photographs were taken with an Alpha Imager 3400 (Alpha Innotech, San Leandro, CA) and the spots were analyzed with Phoretix Software (Nonlinear Dynamics, version 6.01) to identify relative isoelectric point (pI) and molecular weight (MW). Individual spots were not identified on each gel. Only differentially expressed spots (WC vs. SR) identified by Phoretix Software were recorded. For these spots, the coefficient of variation was 22%. Selected differentially expressed spots were excised from gels, destained, subjected to trypsin digestion, and spotted on a matrix-assisted laser desorption ionization (MALDI) plate (Xcise System—Proteome Systems and Shimadzu Biotech, Columbia, MD). The MALDI plate was then subjected to time-of-flight mass spectroscopy with appropriate standard peptides for calibration. Peptide mass fingerprints (PMF) were entered into the Protein Prospector (http://prospector.ucsf.edu) MS-Fit program set for MW (±5 kDa) and pI (±1 pH unit) ranges as previously determined by Phoretix estimations. A PMF profile was considered acceptable if a minimum of 4 strong peaks were present. Based on preliminary experiments, the best PMF were obtained by eluting spots within 2 wk of separation on the gel. Search parameters used in Protein Prospector appear in Table 1
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| RESULTS |
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As diagramed in Figure 2
, certain zones corresponding to pI and MW ranges are characteristic of either susceptibility (WC) or resistance (SR) to atherosclerosis. These zones contain differentially expressed proteins exclusively associated with either susceptibility or resistance (Table 2
). This virtual gel map (Figure 2
) constructed from pI and MW determined by the Phoretix software displays only differentially expressed protein spots. Those tentatively identified (Tables 3
and 4
) are designated by letters on the gel map.
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Identifiable PMF profiles were obtained from 11 differential spots: 9 selected from the 8 unique zones and 2 lying outside the zones. All of these proteins corresponded with differentially expressed genes and, therefore, could be annotated. These proteins are listed in Table 3
and appear as abbreviations on the virtual map (Figure 2
). Five additional proteins were identified by pI, MW, and comparison with published gel maps after searching this data for genes identified by subtractive hybridization. These proteins also appear as abbreviations on the map and are listed in Table 4
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| DISCUSSION |
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Proteins of limited solubility and membrane proteins in general are difficult to analyze in 2-D gel proteomic systems and consequently are poorly represented in published 2-D gel profiles and in protein databases (McGregor and Dunn, 2006). After obtaining very low yields when trying to isolate solubility fractions 3 and 4 from the cells using the Ready-Prep Sequential Extraction procedure, we decided to work only with fractions 1 and 2 as a first step, because little data on proteins related to susceptibility or resistance to atherosclerosis is apparent in the literature. This limited our results to include primarily cytosolic proteins and few, if any, membrane-associated proteins. Nonetheless, there were 170 differentially expressed proteins observed.
Identification of proteins differentially expressed between WC and SR aortic cells were limited by 2 factors:
Nearly equal numbers of differentially expressed soluble proteins were found in each breed, and no major differences were found in obtaining usable PMF from proteins of either breed. The large difference between breeds (26% in WC vs. 67% in SR) in proteins that produced identifiable PMF in blasts could be due to proteins unique to susceptible individuals, which have not been characterized in other species, or to a greater degree of posttranslational modification in WC. Cells from WC are reported to be more active than SR cells in glycosylation (Wight, 1980). In either case, these proteins would not be found in existing databases.
Attempts to correlate the differentially expressed proteins that could be annotated with various hypotheses of atherogenesis are difficult because of the limited number of annotated proteins. However, data in Table 3
suggest that the smooth muscle cells of the WC and SR are in different metabolic states, although this distinction is less clear in the protein phenotypes than in the differentially expressed genotypes (Anderson, 2007). Smooth muscle myosin phosphatase and myosin heavy chain in the SR suggests the contractile phenotype, whereas their absence in WC indicates the synthetic phenotype (Owens et al., 2004). Unfortunately,
and β actin co-migrate in the 2-D gel system used, so this conclusion could not be confirmed by the obvious comparison of actin types.
A differentially expressed spot in SR cells, which corresponds to fatty acid-binding protein, is consistent with reduced fatty acid utilization by WC aorta cells in vitro and in vivo during atherogenesis (Cramer and Smith, 1976; Hajjar, et al., 1980). Fatty acid-binding proteins are essential in movement of fatty acids through the cytosol to mitochondria for oxidation and to the nucleus where fatty acids regulate transcription after binding to various nuclear receptors (Ordovas, 2007).
Ribophorin has been found to be associated with lipid droplets in adipocytes (Brasaemle et. al, 2004) and localized in the rough endoplasmic reticulum in hepatocytes where it functions to bind ribosomes (Rosenfeld et. al, 1984). In addition, in rapidly proliferating cells the synthesis of ribophorin increases dramatically. In the early stages of atherogenic involvement, during the transformation of WC cells to the synthetic and proliferative phenotype followed by accumulation of lipid (initially in the ER) (Cooke and Smith, 1968), an increased expression of ribophorin would be expected.
Heat shock proteins have been implicated in development of atherosclerosis by initiating a proinflammatory immune response (Xu, 2002), and their production can be induced by TNF
(Wick et al., 2004). Consequently, the differential expression of heat shock protein (HSP 70) in WC cells is consistent with the expression of TNF
and the development of atherosclerosis.
In attempting to reconcile the number of differentially expressed proteins with our previous finding that atherosclerotic susceptibility in pigeons is inherited in a single gene autosomal recessive pattern (Smith et al., 2001), it appears that the gene(s) involved must have a regulatory, rather than coding, function. If the gene involved in susceptibility-resistance codes for an enzyme involved in a metabolic function, one would expect to find only a small number of proteins expressed differentially between the susceptible and resistant breed. However, if the gene in question has a regulatory function (i.e., controls transcription or translation of a variety of other genes), then the number of differentially expressed proteins could be large. Another indication of the nature of the underlying gene is whether the proteins expressed differentially correspond with genes expressed differentially between breeds. Comparison studies in our laboratory have identified 137 differentially expressed genes (74 upregulated in WC and 63 in SR), some of which were shown to correspond to proteins found in this study. The number of differentially expressed genes would suggest that susceptibility-resistance is due to regulators of transcription, this suggestion being further supported by the finding of differentially expressed proteins such as tumor necrosis factor
-inducing factor, 2 serine threonine kinases, and 1
β inhibitor, all of which can have effects on gene transcriptionor translation, or both. Finally, heat shock proteins, upregulated in the WC, also act as chaperones for nuclear transcription factors (Xu, 2002), which could have significant effects on gene expression.
| ACKNOWLEDGMENTS |
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| FOOTNOTES |
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Received for publication January 29, 2008. Accepted for publication March 7, 2008.
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