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Differentially Expressed Soluble Proteins in Aortic Cells from Atherosclerosis-Susceptible and Resistant Pigeons¹

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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Soluble proteins in aortic smooth muscle cells cultured from atherosclerosis-susceptible White Carneau and atherosclerosis-resistant Show Racer pigeons were extracted and separated on 2-dimensional electrophoresis gels. Spots were analyzed with Phoretix software and compared between the 2 breeds. Proteins differentially expressed were arrayed on a map, plotting molecular weight against isoelectric point. Eight discrete zones were identified, 5 that included only proteins unique to susceptible cells and 3 that included proteins unique to resistant cells. Of the 88 differentially expressed proteins from susceptible cells, 41 were located in unique zones, whereas 29 of 82 differentially expressed proteins from resistant cells were in unique zones. Selected proteins from susceptibility, and resistance zones were annotated by peptide mass fragments, molecular weights, isoelectric points, and correspondence with genes differentially expressed between cells from the 2 breeds. Some of the annotated proteins (such as smooth muscle myosin phosphatase, myosin heavy chain, fatty acid-binding protein, ribophorin, heat shock protein, and tumor necrosis factor -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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Atherosclerotic cardiovascular disease is the leading cause of death in economically developed countries, including the United States. Despite a variety of hypotheses that have attempted to explain the initiation of atherosclerotic lesions, the underlying cause(s) remains unclear. Numerous complex gene-environment interactions are believed to be involved in the disease (Breslow, 2000).

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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Cell Culture

Pigeons were obtained from the University of New Hampshire (UNH) colonies, which are housed in fly coops at ambient temperature and allowed free access to water, Purina Pigeon Chow Checkers (Purina Mills, St. Louis, MO) and Kaytee Bay-Mor High Calcium Pigeon Grit (Red) (Kaytee Products, Chilton, WI). These colonies were established in 1962 with birds obtained from Palmetto Pigeon Plant (Sumter, SC) and have been closed colonies since that time. The colonies are maintained under the supervision of the UNH Animal Care and Use Committee. Replicate primary aortic smooth muscle cell cultures were prepared from 5 one- to three-day-old WC or SR squabs of mixed genders according to the method developed in this laboratory (Smith et al., 1965). Cultures were allowed to grow for 7 to 8 d until a monolayer was obtained. Primary aortic cell cultures without subculture have previously been shown to correspond closely with cells in the celiac bifurcation of the aorta from the respective breeds of pigeons. Morphological, ultrastructural, and biochemical changes characteristic of atherogenesis in these predisposed areas of lesion formation in susceptible WC aortas are apparent in WC aortic cell cultures, but with a greatly accelerated time frame (8 d in vitro corresponds to 2 to 3 yr in vivo; Smith and Smith, 1974).

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.

	RESULTS

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Variations in growth patterns may occur in all cell culture studies, which can produce differences in the proteome. In the replicate analyses of each fraction in each breed, the 2-D gel patterns were reproducible, which indicated that the primary cell culture system is consistent in demonstrating protein patterns (Figure 1). Actin was detected in all culture pools from both breeds and provided a landmark on the gels for Phoretix comparisons.

View larger version (97K): [in this window] [in a new window]   Figure 1. Representative 2-dimensional electrophoretic gel of soluble proteins (1 of 3 replicates) extracted from a culture pool of aortic cells from atherosclerosis-susceptible (A) White Carneau (WC) and (B) resistant Show Racer (SR) pigeons. MW = molecular weight.

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.

View larger version (11K): [in this window] [in a new window]   Figure 2. Consensus map of differentially expressed soluble proteins having isoelectric points (pI) between 4 and 10, extracted from 3 replicate culture pools of aortic cells from atherosclerosis-susceptible White Carneau (WC) and resistant Show Racer (SR) pigeons. Boxes identify unique zones found exclusively in WC and SR pigeons. ACT = activin-binding protein; CYK = cyclin; FBP = fatty acid-binding protein; HSP = heat shock protein; IKB = inhibitor of I β; LUM = lumican; MAN = mannosidase; MYH = myosin heavy chain; PGM = phosphoglucomutase; PRO = peroxiredoxin; RPN = ribophorin; SMM = smooth muscle myosin phosphatase; STK = serine threonine kinase; STP = serine threonine protein kinase; TNF = Tumor necrosis factor -inducing factor; TRO = tropomyosin.

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.

	DISCUSSION

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The virtual map of differentially expressed proteins, showing specific zones in which proteins associated with either susceptibility or resistance are exclusively located, should prove useful in identifying phenotypes or species susceptible to atherosclerosis, or both, even though only a limited number of specific proteins in these zones were annotated. This approach is consistent with diagnostic goals stated for the use of proteomics in clinical settings (Marko-Vargo and Fehniger, 2004). Furthermore, phenotypic markers can be more useful than genetic markers in determining susceptibility to complex diseases (Cambien and Tiret, 2007). Further tests of the unique zones in the virtual map using proteins from lesion-prone and lesion-resistant areas of arteries in other species and humans are warranted.

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:

1. In the Electrophoret IQ 2000 system used, the amount of protein in some differentially expressed spots that appeared on the 2-D gels was not sufficient to provide satisfactory PMF.
   
2. For those spots that produced good PMF, identification was difficult, because the pigeon genome has not been characterized. Pimental-Smith (2000) reported that chickens, turkeys, and quail are monophyletic with guinea fowl as the basal branch, but the pigeon is a distinct species. We have confirmed these results by clustering sequences of the pigeon NADH4 gene with those of these other avian species (Anderson, 2007). According to McGregor and Dunn (2006), identification of proteins from PMF for a species whose genome is not characterized is difficult. Consequently, the probable identities presented in Table 3 showed low MOWSE scores in numerous blast queries. These identities were derived by interrogating databases for various species, including chickens, with the PMF, considering the apparent pI and MW from gels. However, correspondence of the probable protein identities with genes differentially expressed between WC and SR aorta cells from the same culture pools used for protein extraction provides a much greater degree of confidence in the annotations listed. Annotations in Table 4 were determined on the basis of pI, MW, and location on 2-D gel maps of known proteins. However, those tentative identities were also supported by correspondence with differentially expressed genes. As the genomes for more avian species become available, predicted annotations of more proteins in unique zones may permit interpretation of the pigeon disease process.
   

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

 
Use of the UNH Center for Structural Biology facilities (V. N. Reinhold, director) is gratefully acknowledged. We extend special thanks to Heidi Geissler (UNH Center for Structural Biology) for invaluable technical assistance and advice. We also thank Margaret Coburn (UNH Department of Animal & Nutritional Sciences) for assistance in manuscript preparation. A portion of this work was submitted by M. L. Gilman in partial fulfillment of MS requirements in animal and nutritional sciences at UNH. Supported in part by National Institutes of Health grant #1R15HLO72786-01 to S. C. Smith and E. C. Smith (UNH Department of Animal & Nutritional Sciences).

	FOOTNOTES

 
¹ This is Scientific Contribution number 2351 from the New Hampshire Agricultural Experiment Station.

Received for publication January 29, 2008. Accepted for publication March 7, 2008.

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This Article Abstract Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via Google Scholar Google Scholar Articles by Smith, S. C. Articles by Taylor, R. L. Search for Related Content PubMed PubMed Citation Articles by Smith, S. C. Articles by Taylor, R. L., Jr.