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Differentially Expressed Soluble Proteins in Aortic Cells
from Atherosclerosis-Susceptible and Resistant Pigeons1
S. C. Smith, E. C. Smith, M. L. Gilman, J. L. Anderson, and R. L. Taylor Jr.2
Department of Animal and Nutritional Sciences, University of New Hampshire, Durham 03824
ABSTRACT 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
α-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
2008 Poultry Science 87:1328–1334
doi:10.3382/ps.2008-00051
INTRODUCTION
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
©2008 Poultry Science Association Inc.
Received January 29, 2008.
Accepted March 7, 2008.
1
This is Scientific Contribution number 2351 from the New Hampshire Agricultural Experiment Station.
2
Corresponding author: [email protected].
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). Crossbreeding 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
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DIFFERENTIALLY EXPRESSED PROTEINS IN PIGEON ATHEROSCLEROSIS
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
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
1329
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 × 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) BioLyte 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 × 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
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SMITH ET AL.
Table 1. Protein Prospector (V4.0.8) search parameters employed to identify differentially expressed pigeon
proteins (http://prospector.ucsf.edu)
Parameter
Selection
Area
Databases
MS-Fit
Swiss Prot.2007.04.19
NCBInr.2006.02.16
6
Trypsin
1 or 2 (varied)
Acrylamide
Hydrogen
Free acid
Phoretix value ± 5 kDa
Phoretix value ± 1 unit
DNA frame translation
Digest
Maximum # missed cleavages
Cystine modified by
N term
C term
Molecular weight
Isoelectric point
Homology mode
Minimum # matches with no amino acid substitutions
Minimum # peptides required to match
P factor
Met oxidation factor
Mass tolerance
Species
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.
Considerable difficulty was experienced in obtaining
good matches for pigeon PMF profiles in the various
databases queried. Consequently, from the top 10 candidates in a PMF search, the one was selected that corresponded to a gene differentially expressed between aortic
cell cultures from the 2 breeds. These genes were identified by representational difference analysis (Anderson,
2007). In some cases, protein spots without PMF were
identified on the basis of pI and MW if they corresponded
to a differentially expressed gene. Difficulties in identifying PMF profiles can be attributed to lack of predicted
protein identities, because the pigeon genome has not
been sequenced and because of the fact that pigeons and
doves are the only living family within the Columbiforme
order. Deoxyribonucleic acid studies show they have no
close relatives (Gibbs et al., 2001). Therefore, comparisons
of PMF profiles with other species are tenuous.
1
4 to 7 (varied)
0.4
1.0
±50 ppm
Gallus gallus, mammals, all species
RESULTS
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.
Several differences between the proteomes of cells from
the 2 breeds were observed. Most significant was the
finding that some proteins unique to either the susceptible
breed or the resistant breed migrated exclusively into
specific zones when a map of MW vs. pI was plotted for
the differentially expressed proteins from both solubility
fractions 1 and 2.
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
Table 2. Unique zones identified by isoelectric point (pI) and molecular
weight (MW) ranges characteristic of differentially expressed proteins
found exclusively in atherosclerosis-susceptible White Carneau (WC)
and resistant Show Racer (SR) pigeons
Zone
Susceptibility (WC)
1
2
4
6
8
Resistance (SR)
3
5
7
pI range
MW range
4.9
4.8
5.8
7.3
9.4
60 to 85
24.5 to 40
35 to 65
2 to 75
10 to 50
to
to
to
to
to
5.1
5.1
6.7
8.2
9.9
5.2 to 5.6
6.2 to 6.9
8.3 to 9.1
65 to 90
10 to 25
5 to 125
DIFFERENTIALLY EXPRESSED PROTEINS IN PIGEON ATHEROSCLEROSIS
1331
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.
only differentially expressed protein spots. Those tentatively identified (Tables 3 and 4) are designated by letters
on the gel map.
In the WC cells, 88 differentially expressed proteins
were found in extraction fractions 1 and 2. Nearly half
(41) of these were located in unique susceptibility zones.
In SR cells, 82 differentially expressed proteins were observed with approximately one-third (29) in unique resistance zones.
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
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 κβ; 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 α-inducing factor; TRO = tropomyosin.
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SMITH ET AL.
Table 3. Differentially expressed soluble proteins extracted from aortic cells of atherosclerosis-susceptible White Carneau (WC) and resistant Show
Racer (SR) pigeons identified by peptide mass fingerprints and corresponding genes1
Protein
Spot
Breed-solubility
fraction
Heat shock protein
Tumor necrosis factor α-inducing factor
Mannosidase
Tropomyosin
Cyclin
Serine threonine kinase
Smooth muscle myosin phosphatase
Activin-binding protein
Myosin heavy chain
Serine threonine protein kinase
Phosphoglucomutase
HSP
TNF
MAN
TRO
CYK
STK
SMM
ACT
MYH
STP
PGM
WC-1
WC-1
WC-1
WC-2
WC-2
SR-1
SR-1
SR-1
SR-2
SR-2
SR-2
Peptide
match
5/12
4/15
4/16
7/17
4/10
7/15
4/15
5/17
6/30
4/9
5/18
Phoretix observed
MOWSE
Score
16.6
11.5
9.3
4.7
15.2
9.8
0.5
6.7
1.1
4.7
4.7
Theoretical
pI
MW
pI
MW
5.0
4.8
9.6
5.0
7.8
5.4
5.8
6.0
8.3
8.3
8.3
80.0
24.0
14.0
32.0
45.0
70.0
100.0
32.0
125.0
97.0
66.0
5.1
5.5
9.4
4.7
7.9
5.0
5.4
5.6
9.4
8.5
8.6
73.5
20.6
13.3
32.8
42.8
71.9
107.0
38.2
119.3
101.7
71.9
1
pI = isoelectric point; MW = molecular weight.
proteins also appear as abbreviations on the map and are
listed in Table 4.
DISCUSSION
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 lesionresistant 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
Table 4. Differentially expressed soluble proteins extracted from aortic cells of atherosclerosis-susceptible White
Carneau (WC) and resistant Show Racer (SR) pigeons identified by isoelectric point (pI), molecular weight
(MW), and corresponding genes
Protein
Spot
Breed-solubility
fraction
Lumican
Ribophorin
Inhibitor of I κβ
Fatty acid-binding protein
Peroxiredoxin
LUM
RPN
IKB
FBP
PRO
WC-1
WC-1
WC-2
SR-1
SR-2
Phoretix observed
Theoretical
pI
MW
pI
MW
6.1
6.0
4.8
6.3
8.3
36.6
63.0
35.4
14.9
22.1
6.1
6.0
4.8
6.3
8.3
36.7
66.3
35.4
14.9
22.1
DIFFERENTIALLY EXPRESSED PROTEINS IN PIGEON ATHEROSCLEROSIS
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, α and β actin co-migrate in the 2D 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 TNFα (Wick et al., 2004). Consequently,
1333
the differential expression of heat shock protein (HSP 70)
in WC cells is consistent with the expression of TNFα
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 α-inducing factor, 2 serine threonine kinases, and
1 κβ 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).
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