cDNA expression arrays reveal incomplete reversal of age-related changes in gene expression by calorie restriction

Mechanisms of Ageing and Development 155 (2000) 157 – 174 www.elsevier.com/locate/mechagedev

cDNA expression arrays reveal incomplete reversal of age-related changes in gene expression by calorie restriction Eun-Soo Han a,*, Susan G. Hilsenbeck b,1, Arlan Richardson a, James F. Nelson a a

Department of Physiology, The Uni6ersity of Texas Health Science Center, 7703 Floyd Curl Dri6e, San Antonio, TX 78229 -3900, USA b Department of Medicine, The Uni6ersity of Texas Health Science Center, 7703 Floyd Curl Dri6e, San Antonio, TX 78229 -3900, USA Received 29 February 2000; received in revised form 6 April 2000; accepted 6 April 2000

Abstract Calorie restriction (CR) extends life span and retards many age-related cellular and molecular changes in laboratory rodents. However, neither the breadth of its effects, its underlying mechanisms, nor the limits of its action is fully understood. Expression levels of 588 genes in livers from 3- and 24-month-old ad libitum-fed (AL), and 24-month-old CR (60% of AL intake) male C57BL/6J mice (four per group) were measured. Six genes met the statistical criteria for differential expression in old AL compared to young AL mice. Only one of these age-related changes was attenuated by CR. Four additional gene products, that did not change with age in AL mice, were differentially expressed in old CR compared to old AL mice. Northern and RT-PCR analyses confirmed differential expression of four of the six candidate genes identified by the array results. Many of the identified genes have not previously been reported to be affected by CR or aging. Some of the age-related changes in gene expression are consistent with an increased vulnerability of the aged liver to carcinogenic or other insults, with only partial protection against insult by CR. Incomplete reversal by CR of age-related changes in gene expression provides a potentially important path for probing the limits of CR action. These results also show the importance of independent

* Corresponding author. Tel.: +1-210-5676559; fax: +1-210-5674410. E-mail address: [email protected] (E.-S. Han) 1 Present address: Breast Center at Baylor College of Medicine, 1 Baylor Plaza, MS BCM600, Houston, TX 77030, USA. 0047-6374/00/$ - see front matter © 2000 Elsevier Science Ireland Ltd. All rights reserved. PII: S 0 0 4 7 - 6 3 7 4 ( 0 0 ) 0 0 1 1 9 - 6

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confirmation in expression array profiling of age-related changes in gene expression. © 2000 Elsevier Science Ireland Ltd. All rights reserved. Keywords: Aging; Calorie restriction; Gene expression

1. Introduction Although new genetic and pharmacologic interventions that extend mammalian life span are emerging (e.g. dw/dw mutation, deprenyl, melatonin) (Amstrong and Redman, 1991; Carrillo et al., 1994; Freisleben et al., 1994), calorie restriction (CR) remains the only intervention repeatedly shown to increase life span (\ 25%) and delay a wide spectrum of age-related diseases and physiological changes (Masoro, 1988; Weindruch and Walford, 1988; Masoro, 1990, 1992). Growing evidence supports a role for protection from oxidative insult and other stressors as a significant factor in the anti-aging action of CR, but the extent of this effect and the details of underlying mechanisms remain unknown (Masoro and Austad, 1996). Altered gene expression undoubtedly plays a significant role in directing those mechanisms and a better understanding of the pattern of gene expression unique to the CR phenotype should therefore illuminate the specific anti-aging mechanisms of CR. Barrows (1972) first suggested that CR altered the aging process at the level of gene expression. Young (1979) expanded this view by introducing the concept that nutrition might alter the aging process(es) by interacting at the structural and functional level of the gene. Lindell et al. (1982) suggested that CR biochemically stressed the organism and that compensatory transcription by RNA polymerase II would occur and thereby enhance gene expression. Richardson (1985) also hypothesized that CR retarded the age-related decline in gene expression. CR has been shown to alter the steady-state levels of a large number of mRNAs, including a2m-globulin (Richardson et al., 1987), tyrosine hydroxylase (Strong et al., 1990), androgen receptor (Song et al., 1991), catalase (Semsei et al., 1989; Rao et al., 1990), cytochrome p450 (Horbach et al., 1990), heat shock protein hsp 70 (Heydari et al., 1993) and superoxide dismutase (Cu/Zn) (Semsei et al., 1989; Rao et al., 1990) mRNA, and decrease apolipoprotein A1 (Waggoner et al., 1990), T-kininogen (Coeytaux et al., 1992), senescence marker protein (Chatterjee et al., 1989) and calcitonin (Kalu et al., 1988) mRNA. What remains unclear is what fraction of the population of expressed genes is altered by CR. A fuller knowledge of the extent and nature of the altered gene expression is needed to construct a better hypothesis for the anti-aging mechanism of CR. High-density cDNA arrays or microarrays have recently emerged as a tool to measure global gene expression in mice (Nguyen et al., 1995; Lockhart et al., 1996) and human (Chee et al., 1996; DeRisi et al., 1996; Pietu et al., 1996; Schena et al., 1996) as well as yeast and other organisms (Wodicka et al., 1997; Hilsenbeck et al., 1999). One of the most impressive applications of cDNA array profiling has been in yeast. DeRisi et al., (1997) conducted a comprehensive investigation (over 43 000 expression ratio measurements) of the temporal program of gene expression accom-

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panying the metabolic shift from respiration to fermentation. This study showed that cDNA expression arrays allow rapid screening and quantification of differences in gene expression as little as 2-fold. Thus, this technology seems well suited to study the complex, multigenetic process induced by CR or aging. Our objective was to determine the extent of altered gene expression in the aging liver and the extent of attenuation of this alteration in long-term CR animals. Using the Affymetrix expression array system, Lee et al. (1999) recently reported a large number of changes in mRNA levels in the skeletal muscle of aging mice and partial reversal of these changes by CR. While extremely interesting, the results were not confirmed by other methods. Surprisingly, few studies using expression array profiling have established the reproducibility of the measurements or their validity by independent assays (Hilsenbeck et al., 1999). We therefore sought to determine the extent to which changes, observed by expression array profiling, could be verified by other methods. We report independently confirmed changes in gene expression in the liver of aged mice, only partial reversal of those changes by CR. However, all changes found by expression array profiling were not confirmed by independent assays.

2. Materials and methods

2.1. Animals and dietary procedures Male C57BL/6J mice were obtained at 4 weeks of age from Jackson Laboratories (Bar Harbor, ME) and housed individually in filter-topped microisolator cages under the care and supervision of the technical staff of the Animal Core of the Nathan Shock Center of Excellence in Basic Biology of Aging. Animals were kept on a cycle of 12:12 h dark:light (lights on at 05:00 h). The presence of murine virus antibodies: CAR bacillus, Ectromelia virus, Epizootic diarrhea of infant mice, Lymphocytic choriomeningitis virus, minute virus of mice, mouse adenovirus (M.Ad-FL), mouse adenovirus (M.Ad-K87), mouse hepatitis virus, murine cytomegalovirus, mycoplasma pulmonis, parvovirus, pneumonia virus of mice, polyoma, reovirus, Sendai virus and Theilers’s mouse encephalomyelitis virus was monitored quarterly with serum samples from sentinel animals by BioReliance (Rockville, MD). All tests were negative. The procedures and experiments involving use of mice were approved by the Institutional Animal Care and Use Committee and are consistent with the NIH Principles for the Utilization and Care of Vertebrate Animals Used in Testing, Research and Education, the Guide for the Care and Use of Laboratory Animals and the Animal Welfare Act (National Academy Press, Washington, DC). For the first 2 weeks, all mice were fed ad libitum (AL) Harlan Teklad LM-485 mouse/rat sterilizable diet 7912 (Madison, WI). At 6 weeks, some of the mice were allowed to continue on this diet AL until sacrifice (3 months (Group 3 months AL) or 24 months (Group 24 months AL) of age). The other mice were restricted to 60% of the mean food intake of Group AL until sacrifice (24 months (Group 24 months

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CR) of age). Food intake by AL mice was measured once a week and the amount ingested per day calculated. Intake was corrected for food not eaten (i.e. found in the bottom of the cage, :17.78%). CR mice were given their food allotment 1 h before the start of dark phase of the light cycle.

2.2. Tissue collection and RNA preparation Livers from four AL fed 3-month-old, four AL-fed 24-month-old and four CR 24-month-old mice were collected between 08:00 and 12:00 h and total RNA was extracted from each liver, as previously described (Sambrook et al., 1989). The RNA was digested with RNase-free DNase I (Boehringer-Mannheim, Indianapolis, IN) to remove genomic DNA contamination. Polyadenylated (poly A) RNA was isolated from the RNA by two rounds of affinity chromatography (Oligotex mRNA Kit, Qiagen, Valencia, CA).

2.3. Screening of mRNA by cDNA expression arrays Mouse Atlas™ cDNA expression arrays, containing a grid of 588 cDNA’s spotted in duplicate, were purchased from Clontech (Palo Alto, CA). We followed the vendor’s protocols, substituting a-33P dCTP for a-32P dATP for cDNA probe syntheses, to improve resolution of the signals for quantitation. The 10× dNTP mix provided by the manufacturer for dATP label was replaced by the 10× dNTP mix for dCTP label, which contained 5 mM each dATP, dGTP, dTTP and 50 mM dCTP. We performed five separate experiments, screening one sample from each group (i.e. a young AL, an old AL and an old CR) in the first four experiments and screening the pooled materials from the three groups in the final experiment. Signal quantitation was performed with a storage phosphorimaging system (Molecular Dynamics, Sunnyvale, CA).

2.4. Subcloning and Northern blot analysis Atlas™ cDNA array primer sequences (Clontech, Palo Alto, CA) to Gstp1 (glutathione S-transferase, pi 1) and Ybx1 (Y box protein 1), two of the genes identified by the array screenings to be altered by aging or CR, were obtained and the primers were synthesized in the Center for Advanced DNA Technologies at University of Texas Health Science Center at San Antonio. The cDNA fragment equivalent to the spotted cDNA fragment on the array was synthesized by reverse transcription polymerase chain reaction (RT-PCR) using Advantage™ RT-for-PCR Kit (Clontech) and the protocol described in the Custom Atlas™ Array Primers User Manual Kit (Clontech). This fragment was cloned into the TA cloning vector pCR II (TA Cloning Kit Dual Promoter, Invitrogen, Carlsbad, CA) using the vendor’s protocol. Five micrograms of the total RNA from the same source of total RNA used to prepare poly A RNA for the array experiments was fractionated on 1% agarose-formaldehyde gel and transferred to a nylon membrane using 20× SSC (0.3 M Nacl. 0.03 M sodium citrate). An oligonucleotide probe of 18S rRNA

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was used as a control (Van Remmen et al., 1996) for the loading volume. The riboprobes for Gstp1 and Tbx1 were synthesized from these cDNA clones with Sp6 and T7 RNA polymerases, respectively, following reaction conditions specified by the vendor (Promega, Madison, WI). Signal quantitation was performed with a Molecular Dynamics Phosphorimager (Sunnyvale, CA).

2.5. Semi-quantitati6e RT-PCR Semi-quantitative reverse transcription polymerase chain reaction (RT-PCR) was carried out by reverse transcribing the mRNA to cDNA with Moloney-Murine leukemia virus reverse transcriptase and oligo dT18 primer (Clontech) and measuring the amount of P32-labeled amplified PCR product from this cDNA template at the linear range of amplification. Custom Atlas primer sequences for some of differentially expressed genes selected by the array analyses were obtained from Clontech and synthesized in the Center for Advanced DNA Technologies at University of Texas Health Science Center at San Antonio. The PCR was carried out as described in the Custom AtlasTM Array Primers User Manual Kit (Clontech). The glyceraldehyde-3-phosphate dehydrogenase (G3PDH) mRNA (Clontech) was used to normalize the values from each sample. The G3PDH mRNA was amplified in the same tube where the target gene was amplifying. The PCR product was analyzed by acrylamide gel (5%) electrophoresis and the intensity of signal was quantitated with a phosphorimager.

2.6. Statistical analysis After quantitation, the log-transformed results of array experiments were analyzed using principal components analysis (PCA). In this approach, each gene is treated as an observation and each age group (young versus old) is treated as a variable. PCA results in two principal components. The first principal component (P1) represents the average level of expression of a gene across the age/diet groups, and the second principal component (P2) represents differences between age or diet groups within a gene. Based on pilot data from other experiments, when the observed differences in gene expression are due to experimental variability (i.e. repeated hybridization of the same pool of RNA), the distribution of P2 is approximately normal, with a mean of 0.0. We have used this fact, coupled with the assumption that a majority of genes will not be altered between the age/diet groups, to identify outliers that may represent genes that are truly altered in expression. We construct a 95% prediction interval on P2 using a robust estimator of the S.D. This estimate uses the middle 50% of the P2 distribution and is relatively unaffected by outlier values. The interval approximates the range of variability likely due to experimental variability. Genes with P2 values outside this interval from three out of five experiments are identified as outliers and candidates for further investigation (Hilsenbeck et al., 1999). Data from the array and the Northern blot analyses were expressed as log transformed ratios (24 months AL/3 months AL, 24 months CR/3 months AL or

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24 months CR/24 months AL). The Pearson correlation and linear regression analyses were used to study the correlation between the array hybridization data and the Northern blot data from Gstp1 and Ybx1 mRNAs. These data were also analyzed by one way (individual sample for the array hybridization) or two way (experiment (gel) and individual sample for the Northern blot) analysis of variance (ANOVA). Differences with P B0.05 were considered significant.

3. Results

3.1. Effect of aging on gene expression profiles and incomplete re6ersal of age-related changes in gene expression by CR Fig. 1a shows the hybridization patterns obtained in the experiment using the pooled RNA from young and old AL livers and 33P probes. Initially we used 32P probes, which gave similar results except cDNAs with high signal bled into domains of adjacent cDNAs and thus, prevented their quantitation. Fig. 1b shows the distribution of signal intensities of the 588 gene products in these two arrays as a correlation analysis. In the illustrated comparison, six products (circled and numbered in Fig. 1a) met statistical criteria (see Section 2) for candidate genes that are differentially expressed during aging. In addition to the experiment using RNA pooled from all mice in a given treatment, four separate comparisons using different pairs of young and old animals in each comparison were done. Table 1 summarizes the results from all five experiments. The six gene products shown in Fig. 1 met criteria for differential expression in at least two of the four experiments involving comparisons of individual mice. Four gene products (Gstt1 (glutathione S-transferase theta, 1), Gstp1, Gpcr2 (G-protein coupled receptor 2), and Spi2 -rs1 (serine protease inhibitor-2 related sequence 1)) decreased and two (Cdkn2c (cyclin dependent kinase inhibitor 2c) and Rad21 (RAD21 homolog)) increased with age. None of the age-related changes differed by \3-fold. Five of the six gene products that met statistical criteria for differential expression in old AL mice also met criteria for differential expression in old CR mice (Table 1). Only one of the set, Cdkn2c, failed to meet criteria for differential expression in old CR mice, indicating that CR failed to attenuate expression of most of the altered genes in this sample.

3.2. CR alters the expression of some genes unchanged during aging Table 2 lists the four genes whose expression met criteria for differential expression in old CR versus old AL mice. None of these gene products changed during aging in either AL or CR mice and none of the differences were \ 2-fold. One product (Ybx1 ) was lower and three (Ttf 1 (transcription termination factor 1), EGR-1 (early growth response 1), and Ctsl (cathepsin L)) were higher in CR mice.

Sample number Gene+

Change with age

Cdkn2c Rad21 Gstt1 Gstp1 Gpcr2 Spi2 -rs1

    ¡ ¡ ¡ ¡

a

Pooled

1.34* 1.55* 0.70* 0.47* 0.60* 0.55*

Old AL/Young AL

Old CR/Young AL

Attenuated by CR

1a

2a

3a

4a

1a

2a

3a

4a

1.62* 5.31* 0.70 0.29* 0.67* 0.60*

1.42* 1.16 0.49* 0.30* 0.69* 0.57*

0.97 0.95 0.94 1.01 1.16 1.29

0.92 1.31* 0.69* 0.54* 0.83 1.04

0.97 2.28* 0.89 0.34* 0.77* 1.11

1.26 0.90 0.58* 0.53* 0.76 0.71*

1.02 1.69* 0.80 0.39* 0.86 1.13

1.01 1.07 0.68* 0.34* 0.73* 0.74*

Yes No No No No No

Numbers are ratios of 24 months. AL/3 months; AL or 24 months; CR/3 months. AL mRNA levels detected by cDNA expression array. The gene symbols used are by the Mouse Genome Informatics Nomenclature. * Statistically significant ratio by robust 95% prediction interval.

+

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Table 1 The comparison of gene expression in the liver from the young (3 month-old AL) and old (24 month-old AL) C57BL/6J mice; calorie restriction (CR) only attenuates age-related change in expression level of one of six genes

163

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Fig. 1. (a) An example of the array hybridization pattern with pooled liver RNA samples obtained from young (top: 3-month-old AL) and old (bottom: 24-month-old AL) C57BL/6J mice. The locations of Cdkn2c (1), Gstt1 (2), Gstp1 (3), Gpcr2 (4), Rad21 (5) and Spi2 -rs1 (6) gene products are circled in each array membrane filter. (b) The distribution of signal intensities of the 588 gene products in these two arrays using log transformed data as a correlation analysis. The locations of six gene products are marked.

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Table 2 The comparison of gene expression in the liver from the ad libitum fed (24 month AL) and calorie restricted (24 month CR) C57BL/6J micea Gene+

Ybx1 Ttf 1 EGR1 Ctsl

Pooled sample

0.87 1.26 1.11 0.72

Individual sample

Diet with up-expression

1

2

3

4

0.42* 0.92 1.55* 1.72*

0.67* 2.02* 1.24 0.62

0.77* 1.53* 1.47* 1.85*

1.06 1.43* 1.33* 1.90*

AL CR CR CR

a

Numbers are ratios of CR/AL mRNA levels detected by cDNA expression array. The gene symbols used are by the Mouse Genome Informatics Nomenclature. * Statistically significant ratio by robust 95% prediction interval.

+

3.3. Confirmation of array results by Northern blot hybridization and RT-PCR We performed Northern blot analyses for two of the gene products that array hybridization indicated to be differentially expressed in one or more comparisons: namely, Gstp1 and Ybx1. Fig. 2 shows the strong concordance of the Northern

Fig. 2. Confirmation of gene products identified by the array hybridization using Northern blot hybridization. Five mg total RNA samples from young (Y 1 – 4) and old (O 1 – 4) liver were blotted in each lane and hybridized with 18s rRNA, which was used as a control for loading volume. After the 18s rRNA probe was stripped, the blot was re-probed for Gstp1, one of the gene products that was identified as a differentially expressed gene in young (3-month-old AL) and old (24-month-old AL) samples by the array screening. Y1: 3 months AL-1; O1: 24 months AL-1; Y2: 3 months AL-2; O2: 24 months AL-2; Y3: 3 months AL-3; O3: 24 months AL-3; Y4: 3 months AL-4; O4: 24 months AL-4. The four panels below the Northern blot are taken from the arrays of the corresponding age comparisons to show the hybridization signals of the Gstp1 gene product. The ratios of old:young Gstp1 mRNA, obtained from Northern and array hybridization, illustrate the close correspondence between the data obtained from the array and that from the Northerns.

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Table 3 The comparison of the array results with the Northern blot and the semi-quantitative RT-PCR resultsa Gene+ Sample pair

Ratio of 24:3 months Gstp1 3 months AL-1, AL-1 3 months AL-2, AL-2 3 months AL-3, AL-3 3 months AL-4, AL-4 Ratio of CR:AL Ybx1 24 months CR-1 24 months CR-2 24 months CR-3 24 months CR-4

Array

Northern

RT-PCR

1

2

Average

1

2

Average

24 months

0.29*

0.30

0.23

0.27

0.35

0.27

0.31

24 months

0.30*

0.41

0.38

0.40

0.29

0.29

0.29

24 months

1.01

1.00

0.96

0.98

1.25

0.71

0.98

24 months

0.54*

0.55

0.69

0.62

0.99

0.79

0.89

AL-1, 24 months

0.42*

0.45

0.45

0.45

0.50

0.54

0.52

AL-2, 24 months

0.67*

0.46

0.70

0.58

0.92

0.97

0.94

AL-3, 24 months

0.77*

0.86

0.77

0.82

0.92

1.02

0.97

AL-4, 24 months

1.06

0.95

0.88

0.92

0.90

0.90

0.90

a

Numbers are ratios of 24:3 months or CR:AL mRNA levels. The gene symbols used are by the Mouse Genome Informatics Nomenclature. * Statistically significant ratio by robust 95% prediction interval

+

analyses and the expression array analyses for Gstp1 in the four comparisons of individual mice. Table 3 shows that the ratios (24:3 months or CR:AL) of the individual comparisons for the mRNA levels obtained by the Northern and the array quantitation were strikingly similar. The Pearson correlation coefficient of the ratios obtained by the array versus the ratios obtained by Northern analysis was 0.96 (P B 0.001). Linear regression analysis of these data showed that intercept is no different from 0.0 (P =0.43) and slope is no different from 1.0 (P= 0.37), further indicating that the values are in good agreement. This is particularly noteworthy, since the ratios of individual paired comparisons varied 3-fold (i.e. the ratio of old AL mouse 1 to young AL mouse 1 versus the ratio of old AL mouse 3 to young AL mouse 3 for GST Pi 1 mRNA). The stability of these differences among individuals across array and Northern measurements indicates that the differences are not attributable to methodological variability and more likely reflect inter-animal variation. ANOVA of the Northern data further confirmed the expression array results. Because two separate gels were required to measure expression of a given gene for all individuals, 2-way ANOVA was used (main effects: gel and treatment). There was no significant effect of gel for either gene (P= 0.93 and 0.79 for Gstp1 mRNA and Ybx1 mRNA, respectively), however, there was an individual sample effect

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(PB0.01) for both genes. In Northern blot, for Gstp1 mRNA, samples 1, 2 and 4 show that 24:3 months ratios were different from 1.0 (P= 0.001), while sample 3 was no different from 1.0. The average 24:3 months ratio from the Northern blot was 0.57 (95%, CI 0.32 – 0.81), and the mean 24:3 months ratio from the array hybridization was 0.54 (95%, CI 0–1). The array and Northern data are not significantly different (P = 0.42) and both data showed that the Gstp1 mRNA was significantly differentially expressed between young and old samples. For Ybx1 mRNA, samples 1 and 2 show 24 months CR/24 months AL ratios different from 1.0 (P =0.01), sample 3 is borderline (P= 0.1) while sample 4 is no different from 1.0. The average 24 months CR/24 months AL ratio from the Northern blot was 0.69 (95%, CI 0.51 – 0.87) and the mean 24 months CR/24 months AL ratio from the array hybridization is 0.73 (95%, CI 0.31–1.15). The array and Northern data are not significantly different (P =0.50). Additional confirmation checks were conducted using semi-quantitative RTPCR. We first performed RT-PCR for the two genes checked by Northern analysis (Table 3). For Gstp1, three of four comparisons remained tightly correlated, but the fourth comparison did not correlate as well. Similarly, for Ybx1, two of four comparisons were tightly correlated, but the other two were less correlated. Table Table 4 The comparison of the array results with the semi-quantitative RT-PCR resultsa Gene+

Sample pair

Ratio of 24:3 months Cdkn2c 3 months 3 months 3 months 3 months Spi2 -rs1 3 months 3 months 3 months 3 months Ratio of CR:AL Ttf 1 24 24 24 24 Ctsl 24 24 24 24

AL-1, AL-2, AL-3, AL-4, AL-1, AL-2, AL-3, AL-4,

months months months months months months months months

Array

24 24 24 24 24 24 24 24

AL-1, AL-2, AL-3, AL-4, AL-1, AL-2, AL-3, AL-4,

months months months months months months months months

24 24 24 24 24 24 24 24

AL-1 AL-2 AL-3 AL-4 AL-1 AL-2 AL-3 AL-4

months months months months months months months months

CR-1 CR-2 CR-3 CR-4 CR-1 CR-2 CR-3 CR-4

RT-PCR 1

2

Average

1.62* 1.42* 0.97 0.92 0.60* 0.57* 1.29 1.04

1.32 1.13 0.89 1.01 0.68 2.18 0.90 1.03

2.48 1.23 0.89 1.09 0.74 3.91 1.06 1.66

1.90 1.18 0.89 1.05 0.71 3.05 0.98 1.34

0.92 2.02* 1.53* 1.43* 1.72* 0.62 1.85* 1.90*

1.10 0.64 0.46 1.06 1.99 0.44 2.04 1.17

0.57 1.29 1.00 0.85 1.74 0.58 1.98 1.32

0.84 0.96 0.73 0.96 1.87 0.51 2.01 1.25

a Numbers are ratios of 24 months. AL/3 months; AL or 24 months; CR/24 months; AL mRNA levels. + The gene symbols used are by the Mouse Genome Informatics Nomenclature. * Statistically significant ratio by robust 95% prediction interval.

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4 shows the results for four additional gene products. Pearson correlation coefficients for the ratios of signal intensity obtained by RT-PCR and array were high and statistically significant for four of six genes. However, two genes, Spi2 -rs1 and Ttf 1 showed no correlation with array results.

4. Discussion Using a commercial cDNA expression array, we identified six genes that were differentially expressed during aging in the liver of AL mice. Five of these six genes showed the same differential expression in old CR mice, providing additional confidence in the measurement. Only one of the six did not change with age in CR mice and thus, may be considered protected from age-related change by CR. Moreover, we identified four additional genes whose expression did not change with age, but whose expression was differentially expressed in old CR mice. To our knowledge, the majority of these gene products have not been previously reported to be affected by aging or CR. Also, when we compared these genes with the genes Lee et al. (1999) found to be differentially expressed in skeletal muscle of old and CR mice, we were unable to match any of the genes we identified with those of the earlier study. The results from the expression array screening are partly supported by excellent correlation of array data with Northern blot analyses of two of the candidate genes and further correlation of those genes by RT-PCR. In addition, using RT-PCR, array changes for two of four additional genes were confirmed. Using arrays from the same vendor with the same statistical approach for identifying candidate genes, a similar degree of correlation between the array data and Western analysis of encoded proteins was observed (Hilsenbeck et al., 1999). Expression arrays are screening tools and will only identify differential expression above a limiting threshold. However, the fact that most of the genes identified have not, to our knowledge, been reported to change with age or CR (see below), indicates that this approach will uncover a large number of genes heretofore not known to be affected by these variables. This study indicates that cDNA expression arrays are sensitive enough to detect differences in steady-state levels of gene expression as small as 30 – 40% — the magnitude of difference often observed in mammalian aging and CR studies (Pahlavani et al., 1994; Van Remmen et al., 1995). Moreover, because this study utilized relatively small sample sizes, it is likely that similar analyses performed on larger sample populations would have greater sensitivity and reveal more differences in gene expression levels. This particular commercial array is limited by the difficulty in measuring signals of gene products positioned next to products with a very strong signal. We found this problem could be lessened but not completely eliminated by using 33P instead of 32P to label probes. Nevertheless, it was still necessary to exclude two gene products from the list of differentially expressed genes, even though they met statistical criteria, because their signal intensity was clearly influenced by adjacent gene products whose stronger signals bled into their domain. Although each gene product was duplicated on the array, the duplicates were adjacent. Had the

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duplicates been positioned randomly, at least one of the spots in the two cases under discussion might have been measurable (i.e. not adjacent to an overlapping strong signal). In addition, some of the spots had to be excluded because of background contamination that clearly interfered with the signal intensity; random positioning would also have ameliorated this problem. This study revealed a diverse group of genes with altered expression levels in livers of old AL mice. The challenge as well as potential of expression array analysis is interpreting the biological significance of the pattern of altered gene expression (DeRisi et al., 1997; Wodicka et al., 1997). We recognize that the following discussion represents only one of many possible interpretations of the results. Although the bias of the measurement is limited only to the selection of genes for analysis, the large number of genes identified and their likely pleiotropic actions and interactions raises a cautionary note to any interpretation. Much further work is required to ‘mine’ these and other array data to reveal the wealth of information and insight they can provide. One class of changes that we observed in the aged liver is consistent with increased vulnerability to and/or pathological evidence of toxic insult. Rad21, increased in aged liver, is a calcium-binding protein (Yu et al., 1995). It is a mouse homolog of the rad21 gene of Schizosaccharomyces pombe, which is involved in the repair of ionizing radiation-induced DNA double-strand breaks (Mckay et al., 1996). Increased expression of this gene could indicate a response to the reported increase in DNA damage of the aged liver (Mullaart et al., 1990). Two members of the glutathione-S transferase (GST) gene family, Gstt1 and Gstp1, had reduced expression in aging liver. GST activity has been reported to decrease in most (Stohs et al., 1982; Laganiere and Yu, 1989), although not all (Spearman and Leibman, 1984) studies in aging liver. Declining activity of GST isoforms, which comprise a major enzymatic class involved in detoxification of carcinogens and other toxins, could increase vulnerability of aging cells to oxidative insult. Dietary anticarcinogens can induce the level of Gstt1 protein in the rat gastrointestinal tract and are most pronounced in the stomach (Van Lieshout et al., 1998). Gstp1 is another GST isoform. Mice lacking pi class GST had increased skin tumorigenesis (Henderson et al., 1998). Expression of Gpcr2, capable of mediating potentially important cardioprotective function (Stambaugh et al., 1997), was also reduced in aging liver. If this receptor plays a protective role in liver cells, its reduced expression could augment tissue vulnerability. Cdkn2c is a cyclin-dependent kinase (cdk4 and 6) inhibitor that was increased in old liver. Cdkn2c is highly induced during myogenic differentiation, potentially mediating permanent cell cycle arrest via inhibition of cdk4 and cdk6 (Cranklin and Xiong, 1996). It has been reported to increase as mouse embryo fibroblasts approached proliferative senescence (Zindy et al., 1997). Finally, the expression of Spi2-rs1, a contrapsin-like protein which inhibits trypsin activity but not chymotrypsin or elastase activity and is markedly induced in response to acute inflammation (Ohkubo et al., 1991), was reduced in aged liver. This latter result and our interpretation are noteworthy in its contrast to the interpretation, using array data, that skeletal muscle is undergoing stress (Lee et al., 1999). We note here the critical importance of collecting tissues from mice without stressing them, as there can be marked age differences in the response of systems and genes to stress.

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One of the most striking and potentially important findings of this study was that most of the age-related changes in gene expression levels were not attenuated by CR. CR only attenuated age altered expression of one of six genes. We recognize that this finding is limited by the small number of genes examined. However, assuming that the six age-altered genes are a random sample of all age-altered genes, the exact one-sided 95% binomial confidence interval for only one of six (17%) age-altered genes being attenuated by CR is 0–58%. In other words, the data are inconsistent with \58% of age-altered genes being attenuated by CR. Lee et al. (1999), using more gene-dense chip arrays, found a much larger number of genes (113) altered by age in mouse skeletal muscle. They also reported that only 63% of those changes were attenuated by CR. Using the same binomial approach, their data are consistent with only 71% of genes being attenuated by CR. These findings contradict the dogma, largely supported by the literature, that CR attenuates nearly all age-related changes in physiological, pathological and molecular processes (Richardson et al., 1987, Rao et al., 1990, Horbach et al., 1990). CR definitely attenuates and/or retards many aging phenomena and extends life span. However, possibly because of bias against publication of data with negative results, we know much less about the aging processes that CR is ineffective against. One strength of array analysis is that it encourages a more unbiased assessment of CR action. If the results of this study are indicative, array analysis will provide a rich database for identifying the limits of CR action as an anti-aging intervention. For example, we found that the age related decline in two GST gene products was unaffected by CR. This is somewhat surprising, because CR is effective in detoxifying a number of harmful products (Rao et al., 1990; Chen and Yu, 1996). If reduction in the activity of these detoxification enzymes contributes in a physiologically significant way to aging, restoration of this activity could complement and extend the anti-aging action of CR. Genes whose expression was up-regulated by CR were Ttf 1, EGR1 and Ctsl. The binding of Ttf 1 to specific rDNA termination elements is required to terminate mammalian ribosomal gene transcription by RNA polymerase I. It has been reported that the binding of Ttf 1 is the key event which leads to ATP-dependent nucleosome remodeling and transcriptional activation of mouse rDNA pre-assembled into chromatin (Langst et al., 1997) and Ttf 1 also prevents head-on collision between the DNA replication apparatus and the transcription machinery (Gerber et al., 1997). The EGR1, Zn-finger regulatory protein, is an ‘immediate early gene’ encoded inducible transcription factor. It has been shown that EGR1 functions in the protection of cells against UV damage (Huang and Adamson, 1995) and the expression of exogenous EGR1 in human breast and other tumor cells markedly reduced transformed growth and tumorigenicity (Huang et al., 1997). Ctsl is a lysosomal cysteine protease and belongs to the papain family. It is a potent endopeptidase and involved in the degradation of lysosomal protein substrates, such as collagen, elastin and azocasein (Turk et al., 1997). Total testis content of Ctsl mRNA was unchanged from 6 to 12 months, but decreased by 24 months to 58% of the content of a 6-month-old testis in brown Norway rats (Write et al., 1993). We have not encountered any report regarding the influence of CR on this

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gene expression. Ybx1 is the only gene that is identified as a down-regulated gene by CR. Ybx1 binds to the Y box of major histocompatibility complex (MHC) class II gene. Interferon gamma is the most potent inducer of class II MHC genes. One of the three DNA elements, which mediate the induction in the promoter region of class II MHC genes, is Y. The Ybx1 represses interferon gamma activation of class II major histocompatibility complex genes (Ting et al., 1994). Whether the changes in gene expression that have been identified in this study represent changes in expression per se, or changes in the distribution of cell types within the liver cannot be assessed by these studies. Also, which cells within the liver where these changes have occurred remains to be determined. Nevertheless, this study has identified genes heretofore not known to be affected by age or CR. These findings are novel and likely to provide impetus to many investigators with expertise in the functions of the identified genes to pursue more mechanistic studies to understand the physiological significance of these changes to the aging liver and to the anti-aging actions of CR.

Acknowledgements This work is supported by NIH grants AG-00746-02 (ESH), AG-14674-03S1 (ESH), AG-14674-03 (JFN) and animals were food restricted and maintained by the Animal Core of the Nathan Shock Center for Excellence in the Biology of Aging (AG-13319-05) (AR and JFN). The authors thank Dr Rhonda K. Hansen, and Dr Suzanne A.W. Fuqua for helping us with the use of computer program for quantitation of the array data.

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