Gene expression profile and aortic vessel distensibility in voluntarily

exercised spontaneously hypertensive rats – potential role of heat

shock proteins

Ulrika Hägg1, Maria E. Johansson1, Julia Grönros1, Andrew S. Naylor1, Ingibjörg H.

Jonsdottir1, 3, Göran Bergström1, 2, Per-Arne Svensson4, Li-ming Gan1, 2

1) Inst. of Physiology & Pharmacology, Dept. of Physiology, Göteborg University, Sweden

2) Dept. of Clinical Physiology, Cardiovascular Institute, Sahlgrenska University Hospital,

Göteborg, Sweden

3) Inst. of Stress Medicine, Göteborg, Sweden

4) Research Centre for Endocrinology and Metabolism (RCEM), Dept. of Internal Medicine,

Sahlgrenska Academy, Göteborg University, Sweden

Running head: Exercise, HSP gene expression and aortic distensibility

Corresponding author:

Li-ming Gan, MD, PhD Inst of Physiology and Pharmacology Dept of Physiology Box 432 405 30 Göteborg Sweden Phone: +46-31-773 3538 Fax: +46-31-773 35 12 Email: li-ming.gan@hjl.gu.seT

Articles in PresS. Physiol Genomics (May 24, 2005). doi:10.1152/physiolgenomics.00073.2005

Copyright © 2005 by the American Physiological Society.

2

Abstract

Physical exercise is considered to be beneficial for the cardiovascular health. Nevertheless,

the underlying specific molecular mechanisms still remain unexplored. In this study we aimed

to investigate the effects of voluntary exercise on vascular mechanical properties and gene

regulation patterns in spontaneously hypertensive rats. By using ultrasound biomicroscopy

(UBM) in an ex vivo perfusion chamber we studied the distensibility of the thoracic aorta.

Further, exercise-induced gene regulation was studied in aortae, using microarray analysis,

and validated with real-time PCR. We found that distensibility was significantly improved in

aortas from exercising compared to control rats (p<0.0001). Exercising rats demonstrated a

striking pattern of coordinated down-regulation of genes belonging to the heat shock protein

(HSP) family. In conclusion, voluntary exercise leads to improved vessel wall distensibility

and reduced gene expression of HSP60 and HSP70, which may indicate decreased oxidative

stress in the aortic vascular wall.

Keywords: microarray, ultrasound biomicroscopy, oxidative stress

3

Introduction

Numerous animal and human studies have provided evidence that physical exercise is

associated with improved cardiovascular health (4, 24). Nevertheless, the underlying

molecular mechanisms are as yet largely unknown.

Vessel stiffness has been shown being an independent predictor for cardiovascular events

(41). Both structural and functional components comprise determinants for the vascular

mechanical properties and both of them seem to be under the influence of vascular nitric

oxide (NO)-availability (39). We have previously seen that voluntary exercise in rats

influences the properties of the vessel wall by improving vascular compliance in vivo (13).

However, to be able to control for various confounding factors in vivo, such as metabolic as

well as hemodynamic parameters, we developed a novel ex vivo perfusion system for further

detailed study of small vessel distensibility.

Exercise is known to increase not only the production of free radical oxygen species (ROS)

(7), but also the synthesis of superoxide dismutases (SODs) (15), a phenomenon also

confirmed in our previous study (13). There is increasing evidence that oxidative stress plays

a critical role in the pathogenesis of atherosclerosis (5). The cellular stress response to

oxidative stress includes the heat shock proteins (HSP), a multigene family that range from 10

to 150 kDa in molecular size and show highly homologous sequences between different

species. Among the HSP proteins HSP60 has gained special interest in atherosclerosis. Serum

soluble HSP60 levels have been shown to correlate with carotid artery atherosclerosis in

humans (28). However, possible effects of physical exercise on vascular HSP expression still

remain unclear.

In the present study, we aim to further investigate effects of physical exercise on vascular

mechanical properties and explore gene regulation patterns in response to chronic voluntary

exercise.

4

Materials and Methods

Animals

The experiments were performed on 18 female spontaneously hypertensive rats (SHR)

(Taconic M&B Breeding & Research Centre, Bomholdtgaard, Denmark). Animals arrived at

the age of 8 weeks, and were acclimatised for one week before onset of the experiment. All

animals were housed at constant temperature (24oC) at a relative humidity of 50-60 %. A 12 h

dark/light cycle was maintained in the animal room. The rats had free access to standard

pellet chow and tap water. Animals were weighted weekly. The experimental protocol was

approved by the Regional Animal Ethic Committee, Göteborg University.

Computerized wheel cage model for voluntary exercise

This model has previously been described in detail (36). In brief, the rats were randomly

divided into one exercising group (n=9) and one control group (n=9). All animals were

allocated individually into separate cages of the same size (41 x 31 x 23 cm), for 5 weeks.

Rats assigned to the exercising group had access to a running wheel (22.5 cm diameter)

attached to the side of the cage. Wheel revolutions were automatically registered with

customized computer software. As reported previously, there was no effect on blood pressure,

whereas body weights were increased in runners compared to controls at the end of the

experiment period (13). Also, the running activity increased during the first three weeks, and

thereafter plateaued and averaged at 16 km/24 hours.

Ex vivo determination of aortic vessel distensibility

Vessel preparation and ex vivo perfusion system

10 additional SHR (5 runners and 5 controls) underwent an identical experiment protocol. At

the end of the experiment period, the animals were decapitated and the descending thoracic

aortae were immediately dissected out and placed in chilled physiological saline solution

(0.9% NaCl) after measurement of the in vivo vessel length. The vessels were thereafter

5

mounted in a specially designed vessel chamber and the vessel segments were tied with two

3-0 silk laces to the cannulae in the perfusion line (Figure 1a). A hydrostatic pressure device

was used to create various intraluminal pressure levels and the perfusion and incubation

solutions were maintained at a constant temperature of 37°C. After 15 min non-recirculating

equilibration under 60 mmHg perfusion pressure, the vessel segment was stretched to its in

vivo length (approx. + 30%) and equilibrated for another 10 min. The flow was thereafter

stopped and the intraluminal pressure was increased from 50 to 150 mmHg with a 10 mmHg

incremental step during simultaneous visualization of the vessel structure using an ultrasound

biomicroscope system (UBM) (Vevo 600, Visualsonics, Toronto, Canada) equipped with a 55

MHz mechanical transducer, which provides a spatial resolution of 30 µm. Biological

validation of this model including vessel viability, has been described previously (11).

Data analysis

Inner vessel lumen diameter was measured off-line using the leading-to-leading edge

principle from the near to the far wall intima-lumen boundary (Figure 1b). A pressure-cross

sectional area curve was thereafter created and the paired data was also fitted to an arctangent

model with three independent parameters (α, β and γ), as described by Langewouters et al.

(18):

⎥⎦

⎤⎢⎣

⎡⎟⎟⎠

⎞⎜⎜⎝

⎛ −+×=

γβπα PATNCSA

2

where CSA is the calculated vessel cross sectional area, ATN is the arctangent and P is the

intraluminal pressure. By deriving the pressure-CSA equation with respect to pressure, a

compliance-pressure curve was obtained:

2

1

1)(

⎟⎟⎠

⎞⎜⎜⎝

⎛ −+

×=∂

∂=

γβγ

α

PPCSAPCompliance

Finally, the pressure-distensibility curve was created by normalizing vascular compliance to

CSA:

6

×=CSA

PlityDistensibi 1)(P

CSA∂

∂

Tissue preparation

After the 5 weeks training period, running wheels were locked 24 h prior to the day of

sacrifice, when the 18 female animals were injected with an overdose of pentobarbital

sodium. The aortae were dissected, divided and treated according to subsequent experiment.

RNA extraction

RNA was extracted using Trizol®Reagent (Life Technologies, Invitrogen, Paisley, Scotland)

according to the manufacturer’s protocol. In brief, aortae were pulverised using mortar and

pestle, during cooling with liquid nitrogen, and homogenized with a power homogenizer. Fat

and cell debris were removed by centrifugation (12000 x g, 10 min, 4oC). The RNA extraction

was further obtained by addition of chloroform and isopropyl alcohol in subsequent steps.

The RNA quality was verified spectrophotometrically using the SPECTRAmax Plus384

microplate reader (Molecular Devices Corp., Sunnyvale, CA), and registered digitally by Soft

Max PRO 3.1 (Molecular Devices). RNA purity (A260/A280) was set > 1.7.

Target preparation and Gene Chip hybridization.

Double-stranded cDNA was prepared using Superscript choice system (Life Technologies,

Paisley, UK) and an oligo (dT) 24-anchored T7 primer using 6.8 µg aortic RNA from each

rat. cDNA from runners (n=9) and controls (n=9) were pooled in groups of three. Biotin-

labelled cRNA was synthesized from 10 µl of cDNA by in vitro transcription with biotin-

labelled nucleotides and T7 RNA-polymerase (Enzo Diagnostics, Farmingdale, NY).

Labelled cRNA was purified using RNeasy columns (Qiagen, Hilden, Germany) and 20 µg

cRNA was fragmented at 94°C for 35 min with 1 x fragmentation buffer (40 mM Tris-acetate

pH 8.0, 100 mM KOAc, 30 mM MgOAc) in a final volume of 40 µl. Fragmented cRNA was

then used to prepare a hybridization mix with herring sperm DNA (0.1 mg/ml), and four

7

control bacterial and phage cRNA (1.5 pM BioB, 5 pM BioC, 25 pM BioD, and 100 pM Cre)

samples to serve as internal controls for hybridization efficiency as directed by the

manufacturer (Affymetrix Inc, Santa Clara, CA). Aliquots of the hybridization cRNA

mixtures (10 µg cRNA in 200 µl hybridization mix) were hybridized to a RG-U34A DNA

microarray, washed, stained and scanned (Hewlett Packard, GeneArray scanner G2500A)

according to procedures developed by the manufacturer (Affymetrix). Gene expression was

analyzed on 3 x 2 DNA microarrays.

Microarray gene expression analysis.

To allow comparison of gene expression, the DNA microarrays were globally scaled to an

average intensity of 100. Scanned output files were analyzed with Microarray Suite 5.0

software (Affymetrix). These files are available at the GEO database

(http://www.ncbi.nlm.nih.gov/geo/; series GSE2418).

RNA expression levels were estimated by two algorithms; 1) the signal algorithm, which

computes the average difference between perfect match and mismatch probe cells for each

transcript or 2) the detection call which is given by an algorithm based on signal intensity and

signal quality. With the detection call a gene expression is classified as absent, marginal or

present (Affymetrix). For a gene to be classified as detectable and included in the analysis it

had to be called present in all 3 triplicates in either the running or control groups.

Genes with altered expression levels in running rats were identified by the change call

algorithm essentially as previously described (38). In brief, comparisons were made between

the results from the triplicate DNA microarrays used for analysis of the running rats, and the

triplicate DNA microarrays used for analysis of the non-running rats, generating a total of 9

comparisons. With the change call, a gene is classified as increased (I), marginally increased

(MI), no change (NC), decreased (D), or marginally decreased (MD). A change call of D or

MD was given a value of –1 and Diff Call of MI or I was given the value of 1. A change Call

8

Score was calculated by summarizing the values in all the 9 comparisons for each probe set.

The criterion for increased expression was change call score of equal or more than 7. The

criterion for decreased expression was change call score equal or less than -7. In addition, the

regulated genes should have a p value < 0.05 between the signal values from the running vs.

the control groups (Mann-Whitney test). Genes were identified using the Netaffex database

(www.affymetrix.com).

Quantification of gene expression in aortic tissue

cDNA synthesis for real-time PCR

cDNA synthesis was carried out by reverse transcription (RT) using ThermoScript™ RT-PCR

system (Invitrogen) according to the manufacturers’ protocol. In brief, 1 µg of total RNA was

used in a total volume of 20 µl, containing cDNA Synthesis Buffer 1x: DTT 5 mmol/L, dNTP

1mmol/L, Rnase OUT™ 40 U, Theromscript™ RT 15 U. Samples were incubated at 25oC (10

min), 50oC (50 min) and 85oC (5 min) on a Corbett Thermocycler (Corbett Research, Sydney,

Australia).

Relative quantification using real-time PCR

Relative quantification of mRNA expression was performed on a LightCycler (Roche

Diagnostics GmbH, Mannheim, Germany). For amplification 2 µl of diluted cDNA (1:8) was

added to 18 µl FastStart Master SYBR®green I reaction mixture (Roche Diagnostics GmbH,

Mannheim, Germany).

Oligonucleotides for LightCycler PCR assay

Oligonucleotide primers were designed using Primer Express version 1.0 (Perkin-Elmer

Applied Biosystems Inc.) for GAPDH, and LightCycler Probe Design Software version 1.0

(Roche Diagnostics GmbH, Mannheim, Germany) for HSP60 and HSP70, based on

sequences from the GenBank database (Table 1). GAPDH (glyceraldehyde-3-phosphate

9

dehydrogenase) was selected as endogenous control to correct for potential variation in RNA

loading or efficiency of the amplification reaction.

Validation of PCR amplification

Standard curves for the three genes (GAPDH, HSP60 and HSP70) were obtained by plotting

log dilution (x-axis) against crossing point (Cp) values (y-axis) as described previously (13).

The correlation factor for linear regression analysis of the three studied genes was R2=0.99,

R2=0.99 and R2=0.97, respectively. Amplification efficiencies for the three genes, expressed

as the slopes of the standard curves, were similar: -3.6, -3.7 and –3.2, respectively. The

standard curves were subsequently used for calculations of the relative dilution value of each

unknown sample.

Validation of endogenous control gene

The calculated relative dilution values for GAPDH, obtained by the second derivative

maximum method (22), were similar in experimental and control groups (2.38 ± 0.34 and

2.48 ± 0.31, NS).

Validation of specificity

Specificity of the PCR product is validated by melting curve analyses. Further, the final PCR

product is verified as a single band on an agarose gel (data not shown).

Analysis of protein levels of HSP in serum

Enzyme immunoassay (ELISA) was performed for HSP60 and HSP70 according to the

manufacturer’s manual (HSP60 ELISA kit # EKS-600 and HSP70 ELISA kit # EKS-700,

Stressgen Biotechnologies Corporation, Victoria BC, Canada). The lower detection limits

were 3.125 and 0.78 ng/ml, for HSP60 and HSP70, respectively.

10

Immunohistochemistry

Thoracic aortic segments (3 mm) were fixed in 4% buffered formaldehyde, embedded in OCT

compound (Sakura) and frozen in chilled isopentane. Sections of 6-10 µm were cut on a

cryostat and slides were stored at –20oC. Following several standard pre-treatment steps,

sections were incubated with specific primary antibody (HSP60 or HSP70, # SPA-806 and #

SPA-810, Stressgen, Victoria, BC Canada, 1:100 dilution) for 24 h. Thereafter, slides were

incubated with secondary biotinylated antibodies (dilution 1:400, # BA-2001, Vector

Laboratories, Burlingame, CA) for 1 hr, and finally stained using Vectastain ABC and DAB

kits (Vector Laboratories).

Statistics

Generally, PRISMTM 4.0 (GraphPad, San Diego, CA) was used for statistical analysis. Data

are presented as mean ± standard error of the mean (SEM). Relative gene expression levels

between runners and controls were compared using non-parametric Mann-Whitney test. α,

β and γ values were obtained using the non-linear curving fitting formula according to

Langewouters et al. (18) in PRISMTM 4.0. The CSA- and distensibility-pressure

relationships for runners and controls were finally analyzed using two-way repeated

measurement ANOVA. A p value < 0.05 was considered to be statistically significant.

11

Results

Aortic vessel distensibility

The CSA-pressure curve was shifted upward in runners compared to controls (two-way

ANOVA, group x pressure, p<0.0001) (Figure 2a). Further, the aortic vessel distensibility-

pressure curve was shifted upward in running compared to control animals (two-way

ANOVA, pressure x group, p<0.0001) (Figure 2b).

Expression profiling of rat aorta

Gene expression in aortae from running and control SHR rats were analysed on triplicate RG-

U34A DNA microarrays (Affymetrix) analyzing approximately 7000 full-length gene

sequences and 1000 EST clusters. In aortae from both running and control rats approximately

3000 genes were classified as detectable using the detection call algorithm. Regulated genes

were identified as described in materials and methods. 38 probe sets representing 18

identifiable non-redundant genes were classified as downregulated (Table 2). 53 probe sets

representing 38 identifiable non-redundant genes were classified as upregulated. The

upregulated genes are under current investigation in our lab, and are not reported in the

current paper.

One striking pattern that was observed among the regulated genes was a downregulation of

genes in the HSP family in runners (10 out of 18 downregulated genes) compared to controls.

The regulated HSP genes belonged to the small HSP, HSP40, HSP60, HSP70, HSP90 and

HSP110 families (42). No HSP genes were classified as upregulated in the expression

profiling experiments. This indicates that aortae from running rats display a coordinated

downregulation of HSP genes.

Heat shock transcription factors (HSFs) are the major transcription factors controlling the

expression of HSP genes. The expression profiles were therefore re-searched in order to

investigate if transcriptional downregulation of HSF genes also occurred in aorta of running

12

rats. Three probe sets for HSF1 were present on the DNA microarray. No difference was

found between running and control groups. Neither was there any difference in gene

expression of eNOS between runners and controls.

Quantification of gene expression

HSP60 and HSP70 gene expression

A significant downregulation was detected in HSP60 gene expression in runners compared to

controls. Relative gene expression levels were 1.32 ± 0.13 in runners and 1.98 ± 0.16 in

controls (p<0.01) (Figure 3). Like HSP60, gene expression of HSP70 was downregulated by

83% in runners compared to controls after 5 weeks of exercise training. Relative gene

expression levels were 0.30 ± 0.15 in runners and 1.77 ± 0.45 in controls (p<0.001) (Figure

4).

Quantification of protein levels of HSPs in serum

In the majority of the serum samples, HSP protein levels were undetectable. This was true for

both runners and controls.

Immunohistochemical protein localisation of HSP60 and HSP70

Immunohistochemical staining of HSP60 in aortic vascular sections revealed homogenous

intimal and medial localisation of HSP60 in both running and control rats. The HSP70

staining revealed a similar staining pattern as HSP60 (Figure 5).

Tissue preparations incubated with media lacking primary antibody served as negative

controls. No immunoreactivity was detected in these slides, which verified the specificity of

the immunostaining.

13

Discussion

In this study, we showed increased aortic vessel distensibility following voluntary exercise.

We were also able to distinguish a coordinated pattern of gene expression downregulation of

heat shock proteins in response to voluntary physical exercise in SHR. The findings of

downregulated HSP60 and HSP70 were further validated with real-time PCR, and their

corresponding protein localizations in the aorta were demonstrated immunohistochemically.

At the level of transcription, the HSP response is regulated by the HSFs that interact with a

specific regulatory element, the heat shock element (HSE) present in the promoters of HSP

genes. The HSFs are expressed constitutively and have to be activated and undergo

trimerization to acquire their DNA-binding ability (33). This is in line with our microarray

analysis indicating no gene regulation of HSF genes. Several mitogen-activated kinases

(MAPKs) have been suggested to be important for the activation of HSFs in response to

oxidative and mechanical stress in vascular cells (20).

The HSP60 protein shows a highly homologous sequence between different species, from

bacteria to humans. Both chlamydial and human HSP60 have been shown to have cytokine-

like activity and induce tumour necrosis factor-α and matrix metalloproteinase production in

human and mouse macrophages (16). HSP60 binds to endothelial cells and macrophages via

the Toll-like receptor 4/CD14/MD2 receptor complex (23, 35), leading to activation of a

signalling cascade, eventually activating NF-κB and synthesis of pro-inflammatory mediators

e.g. E-selectin, ICAM-1 and VCAM-1. Further, antibodies against HSPs have been suggested

to exert direct cytotoxic effects through complement activation (34).

Although HSP60 is considered to be mostly expressed in mitochondria in response to various

types of stresses, it has also been found on the surface of stressed endothelial cells and

macrophages (37, 44). Extracellular HSP60 and HSP70 have been shown to induce

14

production and release of pro-inflammatory cytokines (1, 16). HSPs can be released to the

extracellular space during cell death or cell injury. However, spontaneous release of HSPs via

mechanisms suggested to involve lipid-rafts have been described (3). Also, Lancaster and

Febbraio very recently reported a novel release mechanism for HSP70 involving membrane

vesicles (exosomes) (17). Furthermore, Xu et al. found that HSP60 also exists in a soluble

form in the circulation, which is positively correlated with the severity of atherosclerosis,

suggesting a triggering role for HSP60 of an arterial inflammatory reaction (43). Also, serum

antibodies to the mycobacterial heat-shock protein 65 (mHSP65) have very recently been

reported to be associated with elevated coronary calcification (46). Studies in mice show that

vaccination with mHSP65 reduces the inflammatory process associated with atherosclerosis

(21). Although there could be distinct mechanisms controlling transcription, translation and

release of this chaperone, it is still conceivable that the observed coordinated down regulation

of HSPs gene expressions in the aortae of running rats may lead to a reduction of pro-

inflammatory cytokine release in the aorta. This may represent a novel anti-atherogenic

mechanism of voluntary exercise.

The role of HSP70 in the development of atherosclerosis is somewhat disputed in the

literature. High serum levels of the inducible form of HSP70 seem to be of protective role

against atherogenesis (47). Gene transfection of HSP70 provides cardioprotection against

ischemia-reperfusion injury (14), and immunization against HSP70 facilitates intimal

thickening in balloon-injured rats (12). However, lower anti-HSP70 antibody levels have been

observed in patients with intermittent claudication, critical lower limb ischaemia, and

aneurysms (6, 27)

Following acute physical exercise, HSP70 mRNA levels have been shown to increase

transiently in rats, as well as HSP70 positive leukocytes in athletes (10, 32). Also, mRNA

expression of HSP72, the inducible form of HSP70, in skeletal muscle was increased during

acute cycling (9). In the present study, in order to avoid acute effects and study long-term

15

effects of exercise, running wheels were locked 24 h prior to sacrifice. As evident from the

study by Salo et al., the acutely increased HSP70 levels in skeleton muscles return to base-

line already after 6 h (32). Similar observations were made by Ferenbach et al., who found

that the acutely increased levels of HSP60 and HSP70 in human leukocytes were normalized

24 h post-exercise (10). Indeed, at rest HSP70 expression in leukocytes was significantly

lower in endurance athletes compared to untrained individuals. This has been suggested as a

consequence of adaptation upstream of the HSP level, such as increased antioxidative

capacity. This may support our theory of increased vascular NO-bioavailability following

chronic voluntary exercise (13).

Regulation of HSP expression has been shown to occur mainly at the level of transcription

(26) and intracellular overexpression of HSPs has been shown to lead to translocation of the

proteins to the cell surface. Using immunohistochemistry, we showed that HSP60 and HSP70

proteins are localized throughout the vessel wall with predominant intracellular distribution.

Also, by assessing serum levels of HSP60 and 70, we failed to show any detectable levels of

these proteins in SHR serum. Indeed, many post-transcriptional and translational processes

could be involved to determine the final functionality of HSP. Also, the potential time lag

between the transcriptional and translational steps may also contribute to the lack of apparent

difference between runners and controls regarding the release and vascular expression of HSP

proteins in the present study.

It is conceivable, that in these relatively healthy animals without severe atherosclerotic

lesions, the HSP release into the circulation is still low. Further, the lack of detectable

systemic levels in SHR cannot exclude local release or effects of HSPs in the vascular wall.

The source and regulatory mechanisms underlying the soluble HSPs in serum in man is still

debated. Regarding HSP60, increased levels have been associated with more advanced

16

vascular disease stages (43). Further studies are indeed required to address this interesting and

complicated issue.

Given that the heat shock factor is an acute stress transcription factor, mediating the de novo

synthesis of HSP, the concerted down-regulation of HSP family members may indicate

decreased vascular stressor stimuli. It is likely that the decreased HSP gene expression is a

consequence of physical activity rather than a cause to the improved vascular function

following exercise, at least in this relatively healthy animal model. However, this HSP

regulatory mechanism could be of potential importance in e.g. animal models of

atherosclerosis, with advanced vascular lesions. Indeed, physical exercise has been shown to

have beneficial effects on both progression and regression of atherosclerosis in mice (30, 31).

However, potential roles of HSP have, to the best of our knowledge, not been explored in

these exercised animals with human disease. Thus, the gene regulation data from the

microarray analysis may provide indices of early involvement of HSPs in exercise-induced

vascular effects. Future studies of the time windows of the transcriptional and translational

regulations of HSP, as well as usage of e.g. exercising atherosclerotic mouse models, may

shed further light on potential roles of the genetic regulation of HSPs for development of

atherosclerotic lesions.

High resolution UBM has been used successfully to image mouse cardiovascular morphology

and function in vivo (45). Using a custom-designed small vessel perfusion chamber,

morphology of the isolated aortae could be clearly visualized using UBM. To extend the

previous in vivo observation of increased aortic compliance (13), the isolated vessels were

studied in a physiological saline solution instead of calcium-free solution, used when only the

passive vascular mechanical properties are studied. Apparently, this ex vivo approach

facilitates extended physiological studies of the vessels also at the para-physiological pressure

levels. Further, thanks to the accurate measurement of the vessel lumen diameter, potential

confounding effects of different vessel calibres can be taken into account.

17

Vascular distensibility is controlled by both structural and functional components in the

vascular wall (39). By mechanically removing the endothelial cells, Boutouyrie et al.

demonstrated a decrease in aortic compliance (2). This may indicate a pivotal role for

endothelial-derived NO in the acquisition of high vascular compliance. Moreover, exercise-

induced flow increase has been shown to initiate a vascular remodelling process, resulting in

enlarged arteries (8, 25). The adaptation is suggested to be a consequence of increased shear

stress levels (40), which trigger NO-dependant vasodilation in order to normalize wall shear

(39).

Exercise has been shown to generate production of ROS in the vasculature, which is believed

to be a consequence of increased systemic metabolism. Simultaneously, there is also

increasing evidence that exercise attenuates oxidative stress by upregulating the defence

system against free radicals (15). The elevation of ROS levels has several consequences in the

vascular wall, e.g. inactivation of NO, lipid peroxidation and triggering of stress protein

synthesis (19, 29). Indeed, in a previously published study, we showed a significant

upregulation of CuZnSOD in aortic tissues from the exercised animals compared to their

sedentary counterparts. Also, independently of vessel calibre, exercise improved aortic wall

distensibility, which could be a consequence of increased vascular NO-availability. Further,

in the same study we performed functional evaluations of the influence of free radicals on

acetylcholine-induced vasodilation in resistance arteries ex vivo. When incubating vessel

segments with a free radical scavenger (MnTBAP) the increased sensitivity of acetylcholine

in exercised animals compared to controls was abolished, indicating higher levels of oxidative

stress/low antioxidant capacity in sedentary animals. This data is line with findings by other

groups, and indicate an increased antioxidative capacity in vascular tissue in response to

chronic exercise (13). Thus, the coordinated downregulation of the de novo synthesis of HSP

family members could be a consequence of decreased ROS production due to an increased

vascular antioxidative capacity in the exercised animals.

18

In conclusion, voluntary physical exercise induced concerted down-regulation of HSP gene

expressions with concomitant improvement of aortic wall distensibility. Potential causal

relationships between HSP expression and vascular function may justify further

investigations.

19

Acknowledgements

We wish to thank laboratory technicians Gunnel Andersson and Jing Jia for excellent

technical assistance.

Grants

This work was supported by grants from the Swedish Medical Research Council (project LG

14601, 14602 and 15168), the Swedish Heart-Lung foundation, the Åke Wiberg Foundation,

Swegene, the Memorial Foundation of Lars Hierta, and the Magnus Bergvall Foundation.

Disclosures

No disclosures.

20

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26

Figure legends

Figure 1a: A schematic of the ex vivo vessel perfusion system; 1b: Typical UBM 2-D image

showing a longitudinal view of the thoracic aorta mounted in the vessel perfusion system at

intraluminal pressure levels of A) 50 mmHg B) 100 mmHg C) 150 mmHg. Double-headed

arrows indicate lumen diameter measurement according to the leading-to-leading edge

principle from the near to the far wall. Bar = 1 mm.

Figure 2a: Aortic pressure-CSA relationships in runners (■) and controls (๐), two-way

ANOVA p<0.0001; 2b: Aortic pressure-distensibility-CSA relationships in runners (■) and

controls (๐), two-way ANOVA p<0.0001.

Figure 3:

Relative gene expression of HSP60 in runners (solid bars) vs. controls (open bars) normalised

to GAPDH.

Figure 4:

Relative gene expression of HSP70 in runners (solid bars) vs. controls (open bars) normalised

to GAPDH.

Figure 5:

Typical immunohistochemical images showing protein localization of HSP60 in A) runner D)

control and HSP70 in B) runner E) control. Negative control in C) runner F) control. Bar =

100 µm.

27

Tables

Table 1. Oligonucleotide primers for real-time quantitative PCR.

Gene Oligonucleotide Sequence Accession number

GAPDH Forward primer 5’-GAA CAT CAT CCC TGC ATC CA-3’ NM_017008

Reverse primer 5’-CCA GTG AGC TTC CCG TTC A-3’

HSP60 Forward primer 5’-GGC TAT CGC TAC TGG T-3’ X54793

Reverse primer 5’-GCA AGT CGC TCG TTC A-3’

HSP70 Forward primer 5’-TCA TCA AGC GCA ACT CC-3’ Z27118

Reverse primer 5’-CGT TGG GGT TCG ATG TC-3’

28

Tabel 2. Genes classified as down regulated in rat aorta after exercise.

Affy ID Gene titel Gene

symbol Score

Signal

C R

Signal

ratio

rc_AI236601_at Similar to heat shock protein 105 kDa

alpha --- -9 924 502 0.5

rc_AI176658_s_at Heat shock 27kDa protein 1 Hspb1 -9 3985 2614 0.7

rc_AA998683_g_at Heat shock 27kDa protein 1 Hspb1 -9 4379 2749 0.6

rc_AA800849_f_at --- --- -9 4195 3165 0.8

M55534mRNA_s_

at Crystallin, alpha B Cryab -9 1190 676 0.6

rc_AA942685_at Cytosolic cysteine dioxygenase 1 Cdo1 -9 1312 852 0.6

Z75029_s_at Heat shock 70kD protein 1A Hspa1a -9 2480 1581 0.6

L16764_s_at Heat shock 70kD protein 1A/1B Hspa1b

Hspa1a -9 4982 2897 0.6

rc_AI007820_s_at Heat shock 90kDa protein 1, beta Hspcb -9 1707 1126 0.7

rc_AA800551_at --- --- -9 678 293 0.4

rc_AA799570_at --- --- -9 158 105 0.7

U53922_at DnaJ-like protein Dnaja1 -9 1613 975 0.6

rc_AA944397_at Heat shock protein 1, alpha Hspca -9 633 309 0.5

rc_AA945704_at --- --- -9 662 325 0.5

rc_AA892238_at --- --- -8 146 80 0.5

S45392_at Heat shock 90kDa protein 1, beta Hspcb -8 1338 932 0.7

rc_AI236795_s_at Heat shock 90kDa protein 1, beta Hspcb -8 2637 1881 0.7

X77235_at ADP-ribosylation-like 4 Arl4 -8 339 236 0.7

rc_AA799518_g_at --- --- -8 204 113 0.6

rc_AA859648_at Similar to heat shock protein 40 --- -8 369 251 0.7

rc_AA800822_at --- --- -8 82 56 0.7

29

X78949_at Prolyl 4-hydroxylase alpha subunit P4ha1 -8 444 317 0.7

L26292_at Kruppel-like factor 4 (gut) Klf4 -8 416 272 0.7

rc_AA800850_at --- --- -8 189 129 0.7

X54793_at Heat shock protein 60 (liver) Hsp60 -8 986 692 0.7

rc_AI639015_at --- --- -8 24 11 0.4

U72620_at Pleiomorphic adenoma gene-like 1 Plagl1 -7 91 56 0.6

rc_AA925248_at Sodium channel, voltage-gated, type 6,

alpha polypeptide Scn6a -7 86 38 0.4

rc_AA819776_f_at Heat shock protein 1, alpha Hspca -7 225 142 0.6

L03294_g_at Lipoprotein lipase Lpl -7 500 373 0.7

rc_AA799539_at --- --- -7 43 27 0.6

rc_AA892532_at Protein disulfide isomerase-related

protein P5 -7 584 398 0.7

S55223_s_at

Tyrosine 3-monooxygenase/tryptophan

5-monooxygenase activation protein,

beta polypeptide

Ywhab -7 655 528 0.8

L03294_at Lipoprotein lipase Lpl -7 819 625 0.8

rc_AA800817_at --- --- -7 38 23 0.6

Z27118cds_s_at Heat shock 70kD protein 1A/1B Hspa1b

Hspa1a -7 1896 924 0.5

AF104362_at Osteomodulin Omd -7 197 106 0.5

M15562_g_at RT1 class II, locus Da RT1-Da -7 595 451 0.8

--- = not defined in netaffx (2005-01-13), C=controls, R=runners

30

Figure 1b

Figure 1a

Vessel

P

Vessel chamber

Ultrasound transducer

medium

Perfusion medium

Ultrasound biomicroscope

Vessel

P

Vessel chamber

Ultrasound transducer

medium

Perfusion medium

Ultrasound biomicroscope

31Figure 2a

500.6

0.8

1.0

1.2

1.4

1.6

1.8

In

Cro

ss-s

etio

nal a

rea

(mm

2 )

500

20

40

60

80

100

120

140

In

Dis

tens

ibili

ty (k

Pa-1

* 10

-3)

*

*

Figure 2b

tra

tra

70

lum

70

lum

*

ina

ina

*

90

l p

90

l p

**

1

ress

1

ress

*

10 1

ure (m

10 1

ure (m

*

30

mH

30

mH

*

**

150

g)

**

**

***

150

g)

32Figure 3

0.0

0.5

1.0

1.5

2.0

2.5

Controls Runners

Arb

itrar

y ge

ne e

xpre

ssio

n le

vel o

f HSP

60

norm

aliz

ed to

GA

PDH

**

Figure 4

0.0

0.5

1.0

1.5

2.0

2.5

Controls Ru

Arb

itrar

y ge

ne e

xpre

ssio

n le

vel o

f HSP

70

norm

aliz

ed to

GA

PDH

***

nners

33

Figure 5