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A nutritional memory effect counteracts the benefits of dietary restriction in old mice

Nature Metabolism volume 1, pages 1059–1073 (2019)Cite this article

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Abstract

Dietary restriction (DR) during adulthood can greatly extend lifespan and improve metabolic health in diverse species. However, whether DR in mammals is still effective when applied for the first time at old age remains elusive. Here, we report results of a late-life DR-switch experiment using 800 mice. Female mice aged 24 months were switched from an ad libitum (AL) diet to DR or vice versa. Strikingly, the switch from DR to AL acutely increases mortality, whereas the switch from AL to DR causes only a weak and gradual increase in survival, suggesting the body has a memory of earlier nutrition. RNA sequencing in liver and brown and white adipose tissue (BAT and WAT, respectively) demonstrates a largely refractory transcriptional and metabolic response in fat tissue to DR after an AL diet, particularly in WAT, and a proinflammatory signature in aged preadipocytes, which is prevented by chronic DR feeding. Our results provide evidence for a ‘nutritional memory’ as a limiting factor for DR-induced longevity and metabolic remodelling of WAT in mammals.

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Fig. 1: Demography of dietary restriction in mice.
Fig. 2: Post-switch weight change correlates with survival outcome under late-onset DR.
Fig. 3: Detection of an age- and tissue-specific transcriptional memory of prior AL feeding.
Fig. 4: WAT-specific impairment of mitochondrial biogenesis under late-onset DR.
Fig. 5: WAT-specific transcriptional memory predicts impaired activation of de novo lipogenesis under late-onset DR.
Fig. 6: DR remodels lipid flux in adipose tissue.
Fig. 7: Chronic, but not late-onset, DR reprograms lipid synthesis to promote mitochondrial membrane synthesis.

Data availability

The data that support the findings of this study are available from the corresponding authors upon request. Raw bulk RNA-sequencing data are available under accession numbers GSE92486 and GSE124772 on the NCBI Gene Expression Omnibus database. Analysed lipidomics data are available under Supplementary Table 5.

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Acknowledgements

We thank R. Weindruch, J. Nelson, R. Miller, C. Selman, D. Withers and F. Kiefer for their advice on the mouse dietary restriction protocol and Dietmar Vestweber and the Max Planck Institute for Molecular Biomedicine, Münster, Germany, for kindly allowing us to conduct our studies at their facilities. We further thank I. Gravemeier, U. Hill, J. Matutat, A. Mesaros and B. Neuhaus for assistance with mouse work. We thank T. Wyss-Coray and the Tabula Muris consortium for kindly granting access to their single-cell transcriptome atlas, and for advice and supervision during the corresponding analysis. We acknowledge funding from the Max Planck Society, Bundesministerium für Bildung und Forschung Grant SyBACol 0315893A-B (to AB and LP) and the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement number 268739 to L.P. M.J.O.W., A.N. and Q.Z. thank the BBSRC (BB/P013384/1) and the MRC (MR/M004821/1) for financial support.

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Authors and Affiliations

  1. Max Planck Institute for Biology of Ageing, Cologne, Germany

    Oliver Hahn, Lisa F. Drews, Takashi Tatsuta, Lisonia Gkioni, Oliver Hendrich, Thomas Langer, Sebastian Grönke & Linda Partridge

  2. Cellular Networks and Systems Biology, CECAD, University of Cologne, Cologne, Germany

    Oliver Hahn & Andreas Beyer

  3. Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA

    Oliver Hahn

  4. Inositide lab, The Babraham Institute, Cambridge, UK

    An Nguyen, Qifeng Zhang & Michael J. O. Wakelam

  5. Department of Molecular & Integrative Physiology and the Geriatrics Center, University of Michigan, Ann Arbor, USA

    Scott Pletcher

  6. Center for Molecular Medicine Cologne, University of Cologne, Cologne, Germany

    Andreas Beyer

  7. Department of Genetics, Evolution and Environment, Institute of Healthy Ageing, University College London, London, UK

    Linda Partridge

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Contributions

S.G., A.B., M.J.O.W. and L.P. designed the experiments and drafted the manuscript together with O. Hahn. S.P. conceptualized and performed power analyses to determine the required number of animals for the switch experiments, and guided the mortality data analysis. O. Hendrich performed the RNA-seq. L.F.D. performed qPCR and western blot experiments. T.T. and T.L. designed and conducted the in vitro pulse–chase experiments with L.F.D. and L.G. Q.Z. and M.J.O.W. conducted the lipidomic profiling. A.N. conceptualized and performed the lipidome network analysis. O. Hahn performed most of the lifespan and bioinformatic analyses. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Michael J. O. Wakelam, Andreas Beyer, Sebastian Grönke or Linda Partridge.

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Extended data

Extended Data Fig. 1 Food intake of AL and DRAL mice.

Body weights for chronic and switch AL cohorts. Solid lines indicate when chronic DR and diet switches were applied. The dashed lines indicates linear fit of weight gain for both cohorts. Slope of linear fits are indicated below. n = 45 biologically independent animals per diet. b, Averaged daily food intake per mouse. Each point represents the values from one cohort, encompassing 6 cages each. n = 3 cohorts per diet. c, Average daily food uptake for 3- and 5-weeks post-switch, split by cohorts and individual cage. n = 6 biologically independent cages per diet and cohort. Two-sided Wilcoxon rank-sum test, adjusted for multiple testing. d, Averaged daily food intake per mouse after normalizing against average body weight. Each point represents the values from one cohort, encompassing six cages. n = 3 cohorts per diet. Means ± s.e.m.

Extended Data Fig. 2 Demography of dietary restriction for each of the three breeding cohorts.

a, Pre- and post-switch weight curves for chronic and switch diet mice from the 3 breeding cohorts (± 95% confidence intervals). Solid and dashed lines indicate the time point for diet switch and tissue collection, respectively. Tissues were collected from the F3 cohort only. The number above the graph indicates total cohort size at birth. n = 15 biologically independent animals per diet and cohort. b, Cohort-specific post-switch KM survival curves for chronic and switch diet cohorts. Cox regression (dashed line) was used to avoid making assumptions about the shape of the trajectories. c, Cohort-specific distribution of P values as computed from n = 1,000 Cox regression analyses with random down-sampling of DRAL and DR cohorts to match the size of AL/ALDR cohorts. Analyses were run relative to the pre- and post-switch control. The dashed line indicates significance threshold. Whiskers represent 1st and 5th quartiles, box edges represent 2nd and 4th quartiles, and the centre line represents the 3rd quartile/median. Outliers are marked by points. b,c, Biologically independent animals per cohort at start of switch: F1: n = 58 (AL) n = 69 (DR), n = 72 (DRAL), n = 57 (ALDR); F2: n = 55 (AL) n = 69 (DR), n = 69 (DRAL), n = 56 (ALDR); F3: n = 44 (AL) n = 52 (DR), n = 53 (DRAL), n = 44 (ALDR). Means ± s.e.m.

Extended Data Fig. 3 Transcriptional reprogramming in response to early-onset DR and late-onset AL.

a, Heatmap of unsupervised clustering of expression changes for ALDR switch-resistant genes in BAT (n = 3–5 per group; colour bar represents z score range). b, Boxplot representation of scaled expression levels of differentially up- and downregulated genes under chronic DR as opposed to chronic AL controls in livers of ALDR switch mice at a young age. Whiskers represent 1st and 5th quartiles, box edges represent 2nd and 4th quartiles, and the centre line represents the 3rd quartile/median. c,d, Heatmap of expression changes for ALDR switch-resistant genes in BAT (c) and WAT (d) of young ALDR switch mice (n = 3 per group; colour bar represents z score range). Biologically independent animals used for RNA-seq: Liver: n = 3 (AL, DR, ALDR, DRAL, ALDR 5m, AL 5m); BAT: n = 3 (AL, DR, DRAL, AL 5m, ALDR 5m) n = 5 (ALDR); WAT: n = 3 (AL, DR, ALDR, AL 5m) n = 5 (ALDR, DRAL).

Extended Data Fig. 4 scRNA-seq profiling of the stromal–vascular fraction in young and old WAT.

a, t-SNE visualization of scRNA-seq data (FACS Smart-seq2) from the GAT stromal–vascular fraction, split by age. Preadipocytes as annotated by the Tabula Muris Consortium are coloured by age. b, Scatterplot representation of average expression levels of genes of young and old preadipocytes. Differentially expressed genes (DEGs) are indicated in blue. c, Representative GO enrichment of the top 300 differentially expressed genes between old and young preadipocytes. Lengths of bars represent negative ln-transformed P values, calculated using two-sided Fisher’s exact test. d, t-SNE visualisation of scRNA-seq data coloured by expression of two regulated genes, Ccl7 and Tgfb3. e, Scatterplot of expression differences between old and young preadipocytes (by scRNA-seq) versus expression differences between DR and AL (by bulk RNA-seq). The number of common DEGs in each quadrant is indicated in blue, and the number of ALDR switch-resistant genes is indicated in red. There was a significant inverse association as determined by two-sided Fisher’s exact test for common DEGs (P = 0.0026) and when analysis was limited to ALDR switch-resistant genes (P = 0.003). f, Representative GO enrichment of 91 switch-resistant genes following the inverse association in e. Lengths of bars represent negative ln-transformed P values, calculated using two-sided Fisher’s exact test. The complete list of enriched GO terms can be found in Supplementary Table 1. g, Violin plot representing expression of selected genes across all profiled cell types. Points indicate cell-wise expression levels, and the violin indicates average distribution of expression split by age. h, mRNA expression (RNA-seq) of the same genes WAT. Scd1 expression is shown in Fig. 5. Two-sided Wald test, adjusted for multiple testing. All scRNA-seq data represents cells that were derived and processes from n = 4 biologically independent mice per age group, encompassing a total of n = 1,962 biologically independent cells. Biologically independent animals used for bulk RNA-seq: n=3 (AL, DR, ALDR, AL 5m) n=5 (ALDR, DRAL). Means ± s.e.m., ***P < 0.0001.

Extended Data Fig. 5 Extended functional enrichment analysis of liver.

Representative GO enrichment of ALDR switch-resistant genes in the liver. Lengths of bars represent negative ln-transformed P values, calculated using two-sided Fisher’s exact test. Biologically independent animals used for RNA-seq: n = 3.

Extended Data Fig. 6 Thermogenic marker expression in WAT and BAT.

a, Distribution of gene-wise expression changes in BAT under chronic DR and switch diets relative to chronic AL feeding for genes associated with the GO term ‘Mitochondrion’ (n = 1299 genes). Whiskers represent 1st and 5th quartiles, box edges represent 2nd and 4th quartiles, and the centre line represents the 3rd quartile/median. Two-sided Wilcoxon rank-sum test, adjusted for multiple testing. b, mRNA expression (RNA-seq) of thermogenic marker genes in BAT. c, mRNA expression (RNA-seq) of marker for thermogenesis and mitochondrial biogenesis in BAT. d, Apoe mRNA expression (RNA-seq) in BAT. Two-sided Wald test, adjusted for multiple testing. e, Whole LICOR western blot image of Fig. 4d. f, Western blot analysis of UCP1 in WAT, with α-tubulin as loading control. Tissue extract from one BAT sample (very right lane) was included as positive control for the UCP1 antibody. g,h, mRNA expression (RNA-seq) of uncoupling-independent, thermogenic marker genes in WAT for creatine cycling (g) and Ca2+ cycling (h). Two-sided Wald test, adjusted for multiple testing. i, DRAL switch-resistant genes in WAT. Lengths of bars represent negative ln-transformed P values using two-sided Fisher’s exact test. The complete list of enriched GO terms can be found in Supplementary Table 4. Biologically independent animals used for RNA-seq: BAT: n = 3 (AL, DR, DRAL, AL 5m, ALDR 5m) n = 5 (ALDR); WAT: n = 3 (AL, DR, ALDR, AL 5m) n = 5 (ALDR, DRAL). The Western blot analysis was done once using tissues of n = 4 biologically independent animals per diet that were derived from the same cohort but were not identical to the mice used for RNA-seq. Means ± s.e.m., ***q < 0.0001.

Extended Data Fig. 7 Triglyceride composition in WAT.

a, Distribution of TG species for the switch at young (left) and old (right) age classified according to the number of carbon atoms as proxy for TG-associated chain length. Values represent normalized relative abundances (0–100%) on a logarithmic scale. b, Selected TG groups classified according to associated chain length. Values are identical to the ones in a. One-way ANOVA followed by two-sided post-hoc Tukey test. c, Distribution of TG species for the switch at young (left) and old (right) age, classified according to the number of double bonds in TG-associated chains. Values represent normalized relative abundances (0–100%) on a logarithmic scale. d, Selected TG groups classified according to the number of double bonds. Values are identical to the ones in c. One-way ANOVA followed by two-sided post-hoc Tukey test. Biologically independent animals used for Lipidomics: n = 4 per diet. Means ± s.e.m., ***P < 0.001.

Extended Data Fig. 8 Fluorescence signal analysis of pulse–chase experiment outcome.

a, Cellular uptake profiles of exogenously supplied NBD-PG by explant-cultured adipocytes. Lipids were separated by TLC and analysed by fluorescence scanning. The TLC analysis was done once with lipid extracts from n = 3 biologically independent mice per diet (indicated above), with n = 3 technical replicates each. For each biological replicate, two technical replicates were co-incubated with NBD and one with just the transfection agent. The dashed line represents the paths used to quantify fluorescent signal distribution in Fig. 6d. Dashed boxes represent the areas used to quantify individual bands. Lipid species with low polarity run on top, with TGs being represented by the top band. Fluorescent lipids run slightly lower than non-fluorescent lipids. Standard phospholipids allowed the identification of lipid spots representing TG, DG and PG levels (the asterisks indicate unidentified lipid species). Applied non-fluorescent standard lipids involve: Tetra-oleoyl CL (TO-CL); CL-rich phospholipid-extract from heart; palmitoyl-oleoyl-DG (PODG), di-oleoyl-PG (DOPG); di-oleoyl-PA (DOPA). Fluorescent NBD-labelled lipids involve: PG, PA, PC, PE, PS. b, Relative fluorescent signal in each of the major bands. n = 3 biologically independent, 24-month-old animals per diet; technical replicates were averaged prior analysis. Two-sided t test. Data for the TG band are shown in Fig. 6e. c, Non-fluorescent scans of identical TLC plate after staining with CuSO4. Due to high abundance of TGs (upper band) in adipocytes, no phospholipids can be observed. Standard phospholipids allowed the identification of lipid spots.

Extended Data Fig. 9 Lipid reaction analysis in ALDR and DRAL mice.

a,b, Analysis of lipid pathway activity in WAT of ALDR (a) or DRAL (b) mice relative to AL control. Red and blue arrows show reactions with positive and negative activity, respectively. Coloured circles indicate relative log2-transformed abundance of lipid classes involved. c, mRNA expression (RNA-seq) of key genes mapping to differentially active pathways in Fig. 7a. Two-sided Wald test, adjusted for multiple testing. Biologically independent animals used: RNA-seq: n = 3 (AL, DR, ALDR, AL 5m) n = 5 (ALDR, DRAL); Lipidomics: n = 4 per diet. Means ± s.e.m., ***q < 0.0001.

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Hahn, O., Drews, L.F., Nguyen, A. et al. A nutritional memory effect counteracts the benefits of dietary restriction in old mice. Nat Metab 1, 1059–1073 (2019). https://doi.org/10.1038/s42255-019-0121-0

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