Unlike dietary restriction, rapamycin fails to extend lifespan and reduce transcription stress in progeroid DNA repair‐deficient mice

2.2. Effect of rapamycin on parameters of healthspan of Ercc1^{Δ /−} mice

Although rapamycin appears inert in extending life span it might still alleviate some of the features of organ functional decline that were previously rescued by DR (Vermeij, Dollé, et al., 2016). Rapamycin, like DR, is known for reducing cancer (Anisimov et al., 2010; Blagosklonny, 2012; Livi et al., 2013; Rao et al., 2004). Neoplastic lesions were not observed in any of the moribund and cross‐sectional animals fed rapamycin or control diet, consistent with the previous observation of absent neoplasia in short‐lived Ercc1 ^∆/− mice (Dollé et al., 2011). Additionally, no obvious macroscopical differences in major organs and tissues were noted between rapamycin‐fed and control‐treated animals.

The liver exhibits substantial age‐related pathology in Ercc1 ^∆/− mice (Dollé et al., 2011; Gregg et al., 2012; Selfridge et al., 2001), in particular hepatocyte polyploidization that possibly follows from unrepaired DNA interstrand cross‐links (Grillari et al., 2007) and is strongly reduced by DR (Vermeij, Dollé, et al., 2016). Flow cytometry confirmed the rise in the fraction of large 16 N polyploid nuclei in the aging Ercc1 ^∆/− liver, but unlike DR, medium‐dose rapamycin (14 ppm) feeding did not attenuate the increase in polyploidization (Figure S2d).

To explore effectiveness of high‐dose rapamycin (42 ppm), we examined its impact on endothelial function by studying aortic endothelium‐dependent relaxation to acetylcholine (ACh) in organ bath setups. Unlike DR, which is consistently protective, rapamycin has been reported as toxic in human aged arteries and in rodent models, but paradoxically also protective in blood vessels in healthy aging mice (Habib et al., 2014; Harari et al., 2018; Jabs et al., 2008; Kim et al., 2010; Lesniewski et al., 2017). Contrary to previously reported protection by DR (Vermeij, Dollé, et al., 2016; Wu et al., 2017), endothelium‐dependent responses were decreased by rapamycin in both Ercc1 ^∆/− and WT mice, supporting the toxic effects that were reported, among others, in human aged arteries (Figure S3a,b).

Ercc1 ^∆/− mice develop progressive neurological and neurodegenerative changes (Borgesius et al., 2011; de Waard et al., 2010; Jaarsma et al., 2013), which are strongly attenuated by DR (Vermeij, Dollé, et al., 2016). Next, we investigated the effect of high‐dose rapamycin (42 ppm) on neurological and neurodegenerative changes in Ercc1 ^∆/− mice. This cohort was examined weekly for the onset of tremors and loss of motor performance on an accelerating rotarod; two neurological symptoms that develop in a predictable way in Ercc1 ^∆/− mice (de Waard et al., 2010) and that are dramatically delayed or attenuated in DR‐treated animals (Vermeij, Dollé, et al., 2016). Rapamycin did not alter the onset of tremors (Figure ​(Figure3a),3a), nor improve accelerating rotarod performance (Figure ​(Figure3b3b and Figure S3c). At 16 weeks of age, when showing severe motor abnormalities, the mice were sacrificed for neuropathological and biochemical analyses. Immunoblot analysis confirmed reduced relative S6^S240/244 phosphorylation (Figure ​(Figure3c3c and Figure S4a,b) in neocortex, consistent with mTORC1 inhibition and liver data (Figure ​(Figure1e).1e). In line with mTORC1 inhibition, we also observed a trend, albeit non‐significant, of increased expression of markers of autophagy (Figure S3d,e and Figure S4c,d).

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FIGURE 3

Rapamycin does not prevent nervous system abnormalities in Ercc1 ^∆/− mice. a, Onset of the neurological abnormality tremors with age in ad libitum control AIN93G diet supplemented with empty microcapsules (gray; Control‐M) and 42 ppm rapamycin (blue) fed Ercc1 ^∆/− mice. n = 8 animals per group. b, Average time spent on an accelerating rotarod of WT and Ercc1 ^∆/− mice weekly monitored between 11 and 16 weeks (n = 4; WT n = 3). A daily training period was given at 10 weeks of age. c, d, Quantified relative S6 phosphorylation (c) and levels of GFAP (astrocytosis) and NeuN (neurons) (d) by rapamycin in Ercc1 ^∆/− neocortex extracts. Four animals per group were used treated from 8 to 16 weeks of age. e, Representative pictures of transverse brain sections of 16‐week‐old control and rapamycin‐fed Ercc1 ^∆/− mice IF‐stained for GFAP. f, Quantification of the relative intensity of consecutive transverse brain sections immunoperoxidase‐stained for GFAP in neocortex. g, Representative immunofluorescent confocal images of the neocortex stained for NeuN (green) and p53 (red). h, p53‐positive cells counted in the neocortex of three consecutive transverse brain sections at the level of the bregma (Mouse Brain Atlas, Paxinos). i, Representative pictures of cerebellar brain sections of 16‐week‐old control and rapamycin‐fed Ercc1 ^∆/− mice IF‐stained for GFAP. j, Representative immunofluorescent confocal images of the cerebellum stained for Purkinje neurons by Calbindin (green). k, Stereological quantification of the total number of Purkinje neurons per brain. n = 3–6 mice. Mean ± SD and individual datapoints are indicated. **p < 0.01, ***p < 0.001

Using immunoblots, we next examined proxies of neuronal injury using GFAP, a marker that correlates with reactive astrocytosis, and NeuN, a general neuronal marker (Borgesius et al., 2011; de Waard et al., 2010). Rapamycin‐ and control‐treated Ercc1 ^∆/− mice expressed similar levels of GFAP and NeuN, suggestive of equal levels of neuronal injury (Figure ​(Figure3d3d and Figure S4e,f). Immunohistology confirmed that rapamycin‐fed mice displayed the same levels of GFAP immunoreactivity in the neocortex (Figure 3e,f). In addition, we found that the density of P53‐positive nuclei, representing a marker of genotoxic stress, is unaltered by rapamycin treatment in the neocortex (Figure 3g,h, arrows). In summary, our results show that rapamycin has no effect on behavioral deficits or neuropathology in Ercc1 ^∆/− mice, whereas these parameters were previously largely rescued by DR (Vermeij, Dollé, et al., 2016).

To further explore the differences between DR and rapamycin treatment in attenuating nervous system abnormalities in Ercc1 ^∆/− mice, we examined the cerebellum for GFAP staining (Figure ​(Figure3i)3i) and we directly compared cerebellar Purkinje cell degeneration from the current rapamycin and previously collected DR cohorts (Vermeij, Dollé, et al., 2016). Purkinje cells display relatively high vulnerability in aging humans and rodents (Andersen et al., 2003; Woodruff‐Pak et al., 2010), as well as progeroid DNA repair deficiency patients (Jaarsma et al., 2011, 2013; Weidenheim et al., 2009), and their degeneration may underlie motor dysfunction in progeria patients and mouse models (Jaarsma et al., 2013; Weidenheim et al., 2009). Immunostaining for calbindin to selectively outline Purkinje cells revealed multiple gaps in the staining of the molecular layer of control and rapamycin‐treated Ercc1 ^∆/− mice, indicative of Purkinje cell loss, while in DR cerebellum the PCs appeared more preserved (Figure ​(Figure3j,3j, asterisks). Importantly, quantitative analysis of Purkinje cells using a stereological approach confirmed that rapamycin‐fed Ercc1 ^∆/− mice showed a similar degree of Purkinje cell loss as ad libitum control fed Ercc1 ^∆/− mice, while Purkinje cell loss was significantly attenuated by DR (Figure ​(Figure3k).3k). Taken together, our results reveal that rapamycin, unlike DR, does not extend healthspan and is not neuroprotective in progeroid Ercc1 ^∆/− mice.

2.3. Genetically altering mTOR activity does not influence life span of Ercc1 ^{∆ /−} mice

The lack of effect of rapamycin indicates that inhibition of mTOR signaling does not interfere with life span of Ercc1 ^∆/− mice and that mTOR inhibition does not mediate the beneficial effect of DR in these mice. However, it is not excluded that in our DNA repair mutant mice rapamycin exerts additional negative effects other than via inhibiting mTOR activity. Therefore, we investigated modulation of mTOR activity bidirectionally via a genetic approach using Rheb ^+/− mice (Goorden et al., 2011) and Tsc1 ^+/− mice (Wilson et al., 2005), two key upstream regulators of mTORC1: RHEB is a small Ras‐related GTPase that stimulates mTORC1 activity, while TSC1 is a GTPase‐activating protein that converts RHEB to its GDP‐bound state thereby inactivating mTORC1 activity (Liu & Sabatini, 2020). As both mouse mutations are homozygously lethal, heterozygously mutating Rheb or Tsc1 has been shown to lower protein expression, and respectively suppress or enhance mTORC1 activity by one third (Goorden et al., 2011; Wesseling et al., 2017). Both these mouse models, which were studied previously in light of neuronal development but never life span, were crossed with Ercc1 ^∆/− mice in the same F1 C57BL6J/FVB hybrid background. In addition, we also crossed both lines with Xpg ^−/− mice, an additional DNA repair deficiency mouse model, with a highly similar life span and accelerated aging phenotype, that could also be substantially delayed by DR (Barnhoorn et al., 2014; Vermeij, Dollé, et al., 2016).

Consistent with the rapamycin treatment, reduced mTORC1 activity resulting from deletion of one Rheb allele did not alter the time of onset of neurological deficits (tremors and imbalance), the time of onset of kyphosis, and life span in Ercc1 ^∆/− mice (Figure 4a‐d; green lines) nor in Xpg ^−/− mice (Figure 4e‐h; green lines). Similarly, both Ercc1 ^∆/− and Xpg ^−/− mice crossed with Tsc1 ^+/− mice, experiencing chronic upregulation of mTORC1 activity, showed unaltered life span and time of onset of aging‐related phenotypes (Figure ​(Figure44 and Figure S5). These findings indicate that also by influencing mTORC1 activity genetically, our DNA repair‐deficient prematurely aging mice appear insensitive to the healthspan and life span‐modulating activity of mTOR inhibition.

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FIGURE 4

Genetically altering mTOR activity does not influence life span of Ercc1 ^∆/− mice. a–c, Onset of neurological abnormalities, tremors (a) and imbalance (b), and kyphosis (c) with age in Ad libitum fed Ercc1 ^∆/− Rheb ^+/− (green lines; reduced mTOR) and Ercc1 ^∆/− Tsc ^+/− (orange lines; increased mTOR) mutant mice and littermate control Ercc1 ^∆/− mice (black dotted lines). d, Survival of Ercc1 ^∆/− Rheb ^+/− (green lines; reduced mTOR) and Ercc1 ^∆/− Tsc ^+/− (orange lines; increased mTOR) mutant mice and littermate control Ercc1 ^∆/− mice (black dotted lines). n = 9 animals per group for Rheb ^+/− and Tsc ^+/− mutants and 20 for Ercc1 ^∆/− controls. e–h, survival curves (e) and onset of neurological abnormalities, tremors (f) and imbalance (g), and kyphosis (h) with age in Ad libitum fed Xpg ^−/− Rheb ^+/− (green lines; reduced mTOR) and Xpg ^−/− Tsc ^+/− (orange lines; increased mTOR) mutant mice and littermate control Xpg ^−/− mice (black dotted lines). n = 10 animals per group for Rheb ^+/− and Tsc ^+/− mutants and 21 for Xpg ^−/− controls. p values of the log‐rank test are indicated and refer to the comparison of each intervention group to its own control. When stratified for gender, log‐rank survival estimate p values were 0.0843 and 0.1983 for respectively Rheb ^+/− and Tsc ^+/− mutants in the Ercc1 ^∆/− background, and 0.4888 and 0.2631 for respectively Rheb ^+/− and Tsc ^+/− mutants in the Xpg ^−/− background

4.2. Mouse models

The generation and characterization of Ercc1 ^∆/+ and Ercc1 ^+/− mice have been previously described (Weeda et al., 1997). Ercc1 ^∆/− mice were obtained by crossing Ercc1 ^∆/+ (in a pure C57BL6J or FVB background) with Ercc1 ^+/− mice (in a pure FVB or C57BL6J background, respectively) to yield Ercc1 ^∆/− offspring with a genetically uniform F1 C57BL6J/FVB hybrid background (see ref. (Barnhoorn et al., 2014) for motivation). Wild‐type F1 littermates were used as controls. Similarly, Xpg ^−/− mice have been characterized previously (Barnhoorn et al., 2014) and were generated by crossing Xpg ^+/− (in a pure C57BL6J background) with Xpg ^+/− mice (in a pure FVB background). Rheb ^+/− mice and Tsc ^+/− mice have both been described previously (Goorden et al., 2011) and were of a pure C57BL6J background. These heterozygous lines were first crossed with Ercc1 ^∆/+, Ercc1 ^+/−, and Xpg ^+/− mice (all in pure C57BL6J backgrounds) prior to the generation of F1 hybrid Ercc1 ^∆/− and Xpg ^−/− mice. Hence, all animals used in the studies described here were of the same genetic F1 C57BL6J/FVB hybrid background. Typical unfavorable characteristics, such as blindness in an FVB background or deafness in a C57BL6J background, do not occur in this hybrid background. All experiments were used with male and female mice, with numbers for each indicated, unless otherwise stated. Animals were divided randomly over all groups to prevent selection bias. Mice were clinically diagnosed daily in a blinded manner and, weighed, visually inspected weekly, and where indicated scored in a blinded fashion for gross morphological and motor abnormalities. Since the Ercc1 ^∆/− and Xpg ^−/− mice were smaller, food was administered within the cages and water bottles with long nozzles were used from around two weeks of age.

4.3. Dietary treatment with rapamycin

All animals were bred and maintained on AIN93G synthetic pellets (Research Diet Services B.V.; gross energy content 4.9 kcal/g dry mass, digestible energy 3.97 kcal/g, using 2.3 g/kg choline chloride instead of choline bitartrate). Microencapsulated rapamycin (eRapa) and empty microcapsules (Eudragit S100) were obtained from Southwestern Research Institute (San Antonio, TX, USA). 46.7, 140, and 420 mg eRapa, containing 10% Rapamycin, was added per kg AIN93G food mix, resulting in a 4.7, 14, and 42 ppm rapamycin supplemented diet. For the microcapsule control diet, 378 mg empty microcapsules were added per kg AIN93G food mix. Otherwise, normal AIN93G was used as control. The diets were processed into pellets which were radiated with 9 kGy (Isotron, Ede, the Netherlands). Supplemented eRapa and control diets were supplied ad libitum to the mice at either 4 or 8 weeks of age for the remainder of their life. On average, Ercc1 ^∆/− and Xpg ^−/− mice ate 2.3 g food per day. Dietary restriction was initiated at 7 weeks of age with 10% food reduction (2.1 g/day), when animals reached almost maximum body weight and development was completed. Dietary restriction was increased weekly by 10%, until it reached 30% dietary restriction (1.6 g/day) from 9 weeks of age onward. Food was given to the animals just before the start of the dark (active) period to avoid alteration of the biological clock.

4.4. Phenotype scoring

The mice were weighed and visually inspected weekly, and were scored in a blinded manner by three experienced research technicians for the onset of various phenotypical parameters. Whole‐body tremor was scored if mice were trembling for a combined total of at least 10 s when put on a flat surface for 20 s. Impaired balance was determined by observing the mice walking on a flat surface for 20 s. Mice that had difficulties in maintaining an upright orientation during this period were scored as having imbalance. Mice showing an abnormal curvature of the spine were scored as having kyphosis.

4.5. Behavioral analyses

Rotarod performance was assessed by measuring the average time spent on an accelerating rotarod (Ugo Basile). All animals were given four consecutive trials of a maximum of 5 min with inter‐trial intervals of 1 h. For weekly monitoring, the motor coordination performance was measured with two consecutive trials of a maximum of 5 min.

4.6. Immunoblotting

Liver extracts were prepared by mechanical disruption in lysis buffer (150 mM NaCl, 1% Triton X‐100, 50 mM Tris), which was supplemented with mini complete protease inhibitor (Roche Diagnostics) and phosphatase inhibitors (5 mM NaF, 1 mM Na‐orthovanadate). After mechanical disruption, lysates were incubated on ice for 1 h and subsequently centrifuged at 4°C for 20 min. Lysate (25–50 μg) was loaded on a 10% SDS–PAGE gel (Life Technologies LTD) and transferred to a PVDF transfer membrane (GE‐Healthcare Life Sciences). Rabbit anti‐S6 (Cell Signaling Technology; 2217S Lot5, RRID:AB_331355; 1:2000), rabbit anti‐pS6 (Ser 240/244, Cell Signaling Technology; 2215 Lot 14, RRID:AB_331682; 1:500), and mouse anti‐β‐Actin (Sigma Aldrich; A5441 Lot064M4789V, RRID:AB_476744; 1:25.000) were used for detection, semi‐quantified using the ImageJ software package (http://rsb.info.nih.gov/ij/index.html), and phosphorylated:total ratios relative to ad libitum samples were calculated.

Brain extracts were prepared by mechanical disruption in RIPA lysis buffer (50 mM Tris, 150 mM NaCl, 0.5% Sodium Dyoxycholate, 1% NP40, 1% SPS) which was supplemented with mini cOmplete protease inhibitor (Roche Diagnostics) and PhosStop phosphatase inhibitor (Roche Diagnostics). After mechanical disruption, lysates were subsequently centrifuged at 4°C for 20 min and any debris was discarded. Lysates (30 μg) were loaded on a 12 or 15% SDS–PAGE gel and transferred to a Nitrocellulate or PVDF transfer membrane using wet transfer. Membranes were blocked in 5% BSA or 5% milk for an hour at room temperature and incubated overnight at 4 °C. Following primary antibodies were used: rabbit anti‐pS6 (Ser 240/244, Cell Signaling Technology; 5364, RRID:AB_10694233; 1:1000), mouse anti‐S6 (Santa Cruz Biotechnology; SC‐74459, RRID:AB_1129205 1:1000), rabbit anti‐GFAP (DAKO; Z0334, RRID AB_10013382; 1:5000), chicken anti‐Neun (Millipore; ABN78, RRID:AB_10807945; 1:5000), rabbit anti‐Beclin (Cell Signaling Technology; 3738, RRID:AB_490837; 1:1000), rabbit anti‐LC3 (Cell Signaling Technology; 2775, RRID:AB_915950; 1:750), and mouse anti‐Actin (Millipore; MAB1501, RRID:AB_2223041; 1:20.000). Secondary antibodies were either horseradish peroxidase conjugated (HRP; Invitrogen; G‐21234, RRID:AB_2223041; 1:5000) or near‐infrared‐dye conjugated (IRDye; Licor Biotech, 926‐32212/926‐32213/926‐68075/926‐68075/926‐68072/926‐68073; 1:20.000) and were incubated for one hour at room temperature. Antibody recognition was done either with Pierce™ Enhanced Chemiluminescence (ECL) Western Blotting Substate (Thermo Scientific) and Chemi‐Doc MP Imaging system (Biorad) or by Odissey scanner (Licor Biotech). Levels of proteins were quantified using either ImageStudio (Licor Biotech) or ImageLab (Biorad).

4.7. FACS analysis of nuclear DNA content

Polyploidy levels were assessed based on propidium iodide (PI) fluorescence using FACS analysis (Duncan et al., 2010; McWhir et al., 1993). A small part of the left lobe (approximately 5 mm³) was dissected, cut into small fragments, and suspended in 800 μl PBS using a syringe (21G). A total of 300 μl homogenate was added to 300 μl 100% ethanol for fixation. Samples were stored for at least 24 h before further processing. After fixation, the liver homogenate was washed with ice‐cold PBS and subsequently incubated with a pepsin solution for 20 min. After washing in PBS/Tween‐20, cells were collected in 500 μl PBS supplemented with 5 μg/ml PI and 250 μg/ml RNase and samples were measured using the FACS (FACSCalibur, Becton Dickinson).

4.8. Histological procedures

Mice were anaesthetized with pentobarbital and perfused transcardially with 4% paraformaldehyde. The brain specimens were carefully dissected out, post‐fixed for 1 h in 4% paraformaldehyde, cryoprotected, embedded in 12% gelatin, rapidly frozen, and sectioned at 40 μm using a freezing microtome or stored at −80°C until use. Frozen sections were processed free floating using the ABC method (ABC, Vector Laboratories) or single‐, double‐, and triple‐labeling immunofluorescence (de Waard et al., 2010; Vermeij, Dollé, et al., 2016). Primary antibodies (supplier; catalogue number, RRID number; dilution) used in this study were as follows: rabbit anti‐GFAP (DAKO; Z0334, AB_10013382; 1:8000); mouse anti‐NeuN (Millipore; MAB377, AB_2298772; 1:1,000); rabbit anti‐P53 (Leica; NCL‐p53‐CMP5, AB_2744683; 1:1000); rabbit anti‐Calbindin (Swant; CB‐38a, AB_2314070; 1:20,000); mouse anti‐Calbindin (Sigma Aldrich; C9848, AB_2313712; 1:20,000); and goat anti‐FOXP2 (Santa Cruz Biotechnology; sc21069, AB_2107124; 1:1000). Alexa488‐, Cy3‐, and Cy5‐conjugated secondary antibodies raised in donkey (Jackson ImmunoResearch) diluted at 1:200 were used for confocal immunofluorescence. Sections were analyzed and photographed using an Olympus BX40 microscope. Immunofluorescence sections were analyzed using a Zeiss LSM700 confocal microscope. Mean intensities were quantified using Fiji.

4.9. Quantitative analysis of Purkinje cells

Quantification of Purkinje cells was done using the Optical Fractionator tool of the StereoInvestigator software package (MBF Bioscience), integrated in a Zeiss LSM700 confocal microscope setup. Cerebellar tissue was coronally cut serially into 40 μm sections. Every 8th section was double‐immunostained for calbindin (Swant; CB‐38a, RRID: AB_2314070; 1:20,000/Sigma Aldrich; C9848, RRID AB_2313712; 1:20,000) that stains the whole Purkinje neuron and FOXP2 (Santa Cruz Biotechnology; sc21069, RRID: AB_2107124; 1:1000) that selectively marks the nucleus of Purkinje cells. For each section, a contour of the cerebellar cortex was drawn in StereoInvestigator and confocal stacks (7–9 section per animal, 10–50 stacks per sections) were systematically sampled within this contour, using 40× oil lens and systematic random sampling (SRS) with a grid sizes of 820 × 520 μm or 740 × 470 μm. Typically, we collected around 275 sampling stacks per animal. In each stack, we counted Purkinje cells on the basis of their FOXP2+ nucleus in a counting box of 150 * 150 * 20 μm. Cells whose nucleus crossed either the upper surface or the lower or right sides of the counting frame were not counted, according to the optical fractionator counting rules. To obtain an estimate of the total number of Purkinje cells, we divided the counted number of cells by the relative fraction of tissue counted using the following formula

where Q ⁻: The particles counted, t: The section mounted thickness, h = Counting frame height, asf: Area sampling fraction, and ssf: Section sampling fraction. Using this approach, in WT‐Control mice (n = 7) we obtained an estimate of 227.220 ± 36.542 Purkinje cells, which is consistent with numbers found in other studies (Woodruff‐Pak et al., 2010).

4.10. Ex vivo vascular function

The responses of isolated aortic tissue were ex vivo measured in small‐wire myograph organ baths containing oxygenated Krebs–Henseleit buffer at 37°C. After preconstriction with 30 nM U46619, relaxation concentration–response curves to acetylcholine followed by 0.1 mM sodium nitroprusside, a nitric oxide donor, were constructed (Durik et al., 2012). To specifically reveal endothelium‐dependent responses, which in Ercc1 ^∆/− and their WT littermates almost exclusively consist of nitric oxide signaling, acetylcholine responses were corrected for the response to sodium nitroprusside.

4.11. Microarray‐based transcription stress analysis

Total RNA was extracted using QIAzol lysis Reagent from mouse liver. For increased purity, miRNAeasy Mini Kits (QIAGEN) were used. Addition of wash buffers RPE and RWT (QIAGEN) was done mechanically by using the QIAcube (QIAGEN) via the miRNeasy program, and tissue was stored at −80°C. The concentration of RNA was measured by Nanodrop (Thermo Fisher Scientific). RNA quality was assessed using the 2100 Bio‐Analyzer (Agilent Technologies) following the manufacturer's instructions. The quality of the RNA is expressed as the RNA integrity number (RIN, range 0–10). Samples with a RIN below 8 were excluded from analysis. Hybridization to Affymetrix HT MG‐430 PM Array Plates was performed at the Microarray Department of the University of Amsterdam according to Affymetrix protocols. Quality control and normalization were performed using the pipeline at www.arrayanalysis.org.

The linear model from Limma implemented in R was used to identify the DEGs. Pairwise comparisons for each genotype between ad libitum and dietary restriction samples were applied to calculate the fold change (FC), p value, and false discovery rate (FDR) for each probe set in the microarray. Cutoff values for a DEG were put at FDR <5% with FC ≥ |1.5|. For all mouse analyses, differentially expressed probe sets were considered as DEGs.

Pathway enrichment analysis was conducted via overrepresentation analysis (ORA). ORA was performed in the interactive pathway analysis (IPA) of complex genomics data software (Ingenuity Systems, Qiagen) by employing a pre‐filtered list of differentially expressed genes. The overrepresented canonical pathways were generated based on information in the Ingenuity Pathways Knowledge Base. A pathway was selected as deregulated when the p value in the Fisher test was lower than 0.01. Additionally, IPA transcription factor (TF) analysis was performed to identify the cascade of upstream transcriptional regulators that can explain the observed gene expression changes in the different lists of DEGs. To do this, data stored in the Ingenuity Knowledge Base, with prior information on the expected effects between TF and their target genes, were used. The analysis examines how many known targets of each TF are present in the list of DEGs, and also compares their direction of change to what is expected from the literature, in order to predict likely relevant transcriptional regulators. If the observed direction of change is mostly consistent with a particular activation state of the transcriptional regulator (“activated” or “inhibited”), then a prediction is made about that activation state. For each TF, two statistical measures are computed (overlap p value and activation z‐score). The overlap p value labels upstream regulators based on significant overlap between dataset genes and known targets regulated by a TF. The activation z‐score is used to infer the likely activation states of upstream regulators based on comparison with a model that assigns random regulation directions. Overlap p value lower than 0.05 and z‐score higher than |2| were selected as thresholds to identify a TF as relevant.

Limma was used to identify the DEGs among samples compared with the a d libitum fed control WT samples. Differentially expressed genes were selected using an FDR of <0.05 and a linear fold change of ±1.5. Next, probe sets in the Affymetrix array with multiple gene annotation were filtered out. BiomaRt was used to retrieve the gene length for the remaining probe sets (32,930 probe sets from 45,142 probe sets in the original microarray). Finally, a relative frequency (kernel density) plot of gene length and probability density for DEG in each comparison was drawn using the density function implemented in R. Kernel density estimates are related to histograms, but with the possibility to smooth and continuity by using a kernel function. The y‐axis represents the density probability for a specific range of values in the x‐axis.

All data files have been submitted to the NCBI gene expression omnibus (GEO) under accession number {"type":"entrez-geo","attrs":{"text":"GSE149029","term_id":"149029"}}GSE149029.

We thank E. Reiling, Y. van Loon, J. Kouwenberg, E. Haasdijk, E. Abs, M. Elgersma, P. de With, J. Rigters, and the animal caretakers for general assistance with mouse experiments. We acknowledge R. Strong for providing the encapsulated rapamycin. Financial support is acknowledged from the National Institute of Health (NIH)/National Institute of Aging (NIA) (AG17242), the National Institute for Public Health and the Environment and the Ministry of Health, Welfare and Sport of The Netherlands (S/132002), the Dutch CAA Foundation and ADPS Longevity Research Award (to W.P.V.), European Research Council Advanced Grant Dam2Age, ONCODE supported by the Dutch Cancer Society, and by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation—Project‐ID 73111208—SFB 829) and ZonMW memorabel (733050810).