Multiomics analyses reveal dynamic bioenergetic pathways and functional remodeling of the heart during intermittent fasting

  1. Thiruma V Arumugam  Is a corresponding author
  2. Asfa Alli-Shaik
  3. Elisa A Liehn
  4. Sharmelee Selvaraji
  5. Luting Poh
  6. Vismitha Rajeev
  7. Yoonsuk Cho
  8. Yongeun Cho
  9. Jongho Kim
  10. Joonki Kim
  11. Hannah LF Swa
  12. David Tan Zhi Hao
  13. Chutima Rattanasopa
  14. David Yang-Wei Fann
  15. David Castano Mayan
  16. Gavin Yong-Quan Ng
  17. Sang-Ha Baik
  18. Karthik Mallilankaraman
  19. Mathias Gelderblom
  20. Grant R Drummond
  21. Christopher G Sobey
  22. Brian K Kennedy
  23. Roshni R Singaraja
  24. Mark P Mattson
  25. Dong-Gyu Jo
  26. Jayantha Gunaratne  Is a corresponding author
  1. Centre for Cardiovascular Biology and Disease Research, Department of Microbiology, Anatomy, Physiology and Pharmacology, School of Agriculture, Biomedicine and Environment, La Trobe University, Australia
  2. Department of Physiology, Yong Loo Lin School Medicine, National University of Singapore, Singapore
  3. School of Pharmacy, Sungkyunkwan University, Republic of Korea
  4. Translational Biomedical Proteomics Laboratory, Institute of Molecular and Cell Biology, Agency for Science, Technology and Research, Singapore
  5. National Heart Research Institute, National Heart Centre Singapore, Singapore
  6. Institute for Molecular Medicine, University of Southern Denmark, Denmark
  7. National Institute of Pathology "Victor Babes", Romania
  8. NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore
  9. Natural Products Research Center, Korea Institute of Science and Technology, Republic of Korea
  10. Translational Laboratories in Genetic Medicine, Agency for Science, Technology and Research, Singapore
  11. Cardiovascular and Metabolic Disorders Program, Duke-National University of Singapore, Singapore
  12. Department of Neurology, University Medical Center Hamburg-Eppendorf, Germany
  13. Department of Biochemistry, Yong Loo Lin School Medicine, National University of Singapore, Singapore
  14. Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
  15. Department of Neuroscience, Johns Hopkins University School of Medicine, United States
  16. Department of Anatomy, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
6 figures and 10 additional files

Figures

Figure 1 with 2 supplements
Impact of intermittent fasting on the heart proteome.

(a) Hierarchical clustering of proteins significantly differentially expressed in each IF group and AL group (one-way ANOVA with Dunnett’s test). The color scale denotes z-score normalized protein abundances. Red denotes higher protein abundance, and blue lower protein abundance. Gene ontology-based biological processes and pathways significantly enriched in representative protein clusters across the different groups. Selected enzymes specifically modulated within each cluster are highlighted. (b) IF-modulated kinases involved in metabolic pathways and signaling pathways. (c) Enrichment analysis of modulated processes and pathways in the different IF groups in comparison to the AL group (1-D annotation enrichment using Wilcoxon-Mann-Whitney test). Each dot represents a functional process or pathway. A positive enrichment score denotes higher protein abundance, and a negative enrichment score denotes lower protein abundance. n=4–5 mice in each experimental group.

Figure 1—figure supplement 1
Experimental design and details of the study cohort.

(a) Schema showing the experimental design of the current study. At the 6-month time point, mice were euthanized, and hearts were removed and processed for transcriptomic and proteomic analyses. Another set of mice were used for echocardiography experiments (n=10 mice/group) (b) Fasting blood glucose and ketone levels at the indicated time points. Values are the mean ± SEM (n=20 mice/group). *p<0.05, **p<0.01, ***p<0.001 compared to the AL group value (one-way ANOVA with Tukey’s post hoc test). (c) Average monthly body weights (g) of AL and IF mice during the experiments (6 months) (one-way ANOVA with Tukey’s post hoc test). (d) Overall compositional calorie intake by the mice in terms of protein, fat and carbohydrates per body weight (kcal/g).

Figure 1—figure supplement 2
IF-responsive proteins distribution across different fasting regimens.

(a) The overlap among the significantly differentially expressed proteins in each IF group compared to AL (one-way ANOVA with Dunnett’s post hoc test). (b) Volcano plot of terms from the MSigDB_Hallmark_2020 gene set for the enrichment of enzymes modulated with IF. The larger and darker-colored the point, the more significantly enriched the input gene set is for the term. (c) Comparison of kinase modulation across different IF regimens based on significance. Red indicates increased abundance, and blue indicates decreased abundance.

Figure 2 with 3 supplements
Differential effects of IF regimen functional processes.

(a) Functional transition network that shows functional remodeling of heart proteome in response to IF12 (a), IF16 (b), and EOD (c) GSEA for biological processes and pathways performed for each IF regimen comparison is shown as an enrichment map. Functions significantly enriched (p<0.01, nominal p-value from empirical phenotype-based permutation test in GSEA) among the upregulated and downregulated proteins for each comparison are indicated by red and blue nodes, respectively. The size of the nodes indicates the number of proteins within the node and edges link nodes that share common proteins. (d) Functional processes and pathways altered by changes in transcriptome and proteome abundances through different IF regimens (Benjamini-Hochberg FDR <0.05, 2-D annotation enrichment using MANOVA test). Each dot on the plot represents a modulation in pathway or process. The scores indicate abundance changes of transcriptome or proteome levels over AL. Upregulation and downregulation of components are denoted by positive and negative scores, respectively. n=4–5 mice in each experimental group.

Figure 2—figure supplement 1
Transcriptomics-based analysis.

(a) Hierarchical clustering of differentially expressed mRNAs in the three IF groups compared to the AL group. Upregulated genes are indicated in red and down-regulated genes are shown in blue. The color scale represents the log10 (average FPKM + 1) value. (b) Principal components analysis of RNA sequencing samples from AL, IF12, IF16, and EOD groups. (c) Venn diagram showing the distribution of differentially expressed mRNAs from IF12, IF16, and EOD groups compared to the AL group. (d) Volcano plots of differentially expressed mRNAs in IF12, IF16, and EOD groups compared to the AL group. The threshold of differential expression was set at p<0.05. Each dot represents an individual gene (blue: no significant difference; red: upregulated gene; green: down-regulated gene). Volcano plot of statistical significance (-log10 q-value) against enrichment (log2 fold change) of differentially expressed genes. (e) Significantly enriched GO terms in each category of the biological process for each IF group compared to the AL group. (n=5 mice/group). FPKM, fragments per kilobase of transcript per million mapped reads.

Figure 2—figure supplement 2
Comparison of IF-induced transcriptome and proteome rewiring.

(a) Comparison of proteome and transcriptome abundances in AL and different IF groups. Protein levels are represented by average log-transformed normalized abundances, and transcriptome levels are represented using average log-transformed FPKM within each group (b) Functional processes and pathways altered by changes in transcriptome and proteome abundances at IF12 (Benjamini-Hochberg FDR <0.05, 2-D annotation enrichment using MANOVA test). Each dot on the plot represents a modulation in a pathway or process. The scores are indicative of abundance changes of transcriptome or proteome levels over AL. Upregulation and downregulation of components are denoted by positive and negative scores, respectively. (c) EOD induced fold changes in mRNA (x-axis) and protein abundances of enzymes (y-axis) in comparison to AL.

Figure 2—figure supplement 3
Analysis of the core clock components genes.

Differentially expressed mRNAs for clock genes in the three IF groups compared to the AL group (heat map). Most of the clock gene transcripts displayed differential expression profile compared to the AL control group irrespective of the different fasting regimens (Wald test as implemented in DESeq). IF12 and IF16 groups showed similar trend and did not particularly differ from the EOD fasting group. Red border denotes increased expression, and blue border denotes decreased expression compared to AL.

Figure 3 with 4 supplements
Network mapping of IF-responsive proteins.

(a) Proteins with significantly altered abundance in response to IF are overlaid on consensus protein-protein interaction network constructed using all IF-responsive proteins. The proteins that sequentially show differential modulation are indicated with different colors as yellow (IF12), blue (IF16), and red (EOD). (b) The top densely connected functional protein clusters are shown (one-sided Mann-Whitney U test as implemented in Cluster ONE). The color of each node indicates the IF regimen for which the protein was differentially expressed. Yellow, blue, and red indicate IF12, IF16, and EOD regimens, respectively. The heat maps show proteome changes for the proteins in the respective clusters. Red denotes increased expression, and blue denotes decreased expression. (c) Transcription factors significantly enriched across the different IF groups. n=4–5 mice in each experimental group.

Figure 3—figure supplement 1
Network mapping of IF-responsive proteins across different regimens.

Proteins that showed significantly altered protein abundance in response to (a) IF12 (yellow), (b) IF16 (blue), and (c) EOD (red) regimen are overlaid on the consensus protein-protein interaction network constructed using all IF-responsive proteins.

Figure 3—figure supplement 2
Functional clusters enriched in IF-modulated network.

Close-knit protein clusters spanning different functional processes from the IF-responsive protein network are shown. The color of each node indicates the IF regimen at which the protein was differentially expressed. Yellow, blue, and red indicate IF12, IF16, and EOD regimens, respectively.

Figure 3—figure supplement 3
Association perturbations across different IF regimens.

(a) Proteins with altered functional network associations (colored nodes) against a background protein association network assembled from positive and negative co-regulation analysis of all quantified proteins (p≤0.05, hypergeometric test). Only those protein co-regulations that were significant (Benjamini-Hochberg adjusted p≤0.01, correlation test) were included in the background protein association network. The functional involvement of perturbed proteins across different IF regimens is shown below. (b) Proteins showing regimen-specific association perturbations in selected biological processes.

Figure 3—figure supplement 4
A mitochondrial association network.

(a) Increased representation of mitochondrial proteins among all association perturbed proteins (radar plot). Numbers represent significant of enrichment (negative log10 adjusted p value). (b) Association network of mitochondrial proteins impacted by IF in the heart. The perturbed proteins specific to each IF or AL regimen are indicated by yellow (AL), green (IF12), blue (IF16), and pink (EOD) nodes. Perturbations inferred from positive associations are indicated as red edges, and those from negative associations are shown as blue edges. All gray nodes denote proteins sharing association perturbation with the indicated mitochondrial proteins. Colored borders around the nodes are representative of pathways or processes.

Figure 4 with 1 supplement
Phosphoproteome landscape of IF-induced changes in heart.

(a) Phosphorylation sites showing significant changes in the hearts of mice in the IF12, IF16, and EOD. Phosphorylation changes observed on structural sarcomere organization proteins are highlighted. (b) Hierarchical clustering of differentially altered phosphopeptides showing increased (red) and decreased (blue) phosphosite abundance. Kinase motifs enriched (p<0.05) in representative clusters are shown (Fisher’s exact test for enrichment). (c) Pathways significantly enriched (p-value ≤0.05) among the differentially altered phosphoproteins across the three IF regimens are visualized as a heatmap (Fisher’s exact test for enrichment). The color scale represents negative log10-transformed p values. (d) Temporal alteration of specific IF-responsive phosphorylation sites in AMPK and cGMP-PKG signaling. n=3 mice in each experimental group.

Figure 4—figure supplement 1
Site-specific alteration of IF-responsive phosphoproteins.

Temporal alteration of specific IF-responsive phosphorylation sites in insulin signaling (a), lipid metabolism (b), regulation of heartbeat (c), and heart structural remodeling/development (d). Red indicates increased phosphosite abundance, and blue denotes decreased phosphosite abundance. The overall trend among the diet groups based on the phosphoproteome landscape is indicated as brown triangles.

Immunoblot validation of the selected proteins in IF-modulated pathways.

(a) Immunoblots that show the effects of IF16 on the expression of selected proteins p-AMPKα/AMPKα, PKG-1, MYPT1, PPARγ, p-GSKαβ/GSKαβ, AKT, p-IRS1/IRS-1 and Insulin receptor β compared to AL group. Data are represented as mean ± S.E.M. n=6 mice in each experimental group. *p<0.05 compared with young sham; **p<0.01 compared with AL group.

Figure 6 with 5 supplements
Echocardiographic analyses of IF on cardiac stress adaptation.

(a) Dobutamine stress tests for ability of the heart to adapt to stress under IF. Heart rate and ejection fraction following administration of dobutamine were measured. Values are the mean ± SD; n=10 each; *p<0.05 (Unpaired t-test). Representative images of long axis M-Mode raw data before and after dobutamine-induced stress are shown in the right panel. (b) Contractility in hearts of IF16 mice compared with AL mice as illustrated by global longitudinal strain (GLS) (upper panel) and radial strain (lower panel). Values are the mean ± SD (n=10 in each experimental group; **p<0.01, ***p<0.001) before and after dobutamine (one-way ANOVA with Tukey’s multiple comparisons test). Representative images of myocardial movement (upper panel) and radial strain (lower panel) before and after dobutamine-induced stress.

Figure 6—figure supplement 1
Echocardiographic analyses.

(a) Reduced mitral E/A ratio (left panel) and increased deceleration time (right panel) in hearts of IF16 compared to AL mice suggest that IF enhances diastolic function. Values are the mean ± SD; n=10 each; *p<0.05, ***p<0.001. Representative images of mitral pulse waves are shown in the middle panel (Unpaired t-test). (b) Comparison of heart weight:body weight ratio between AL and IF16 groups. Values are the mean ± SEM; ****p<0.0001; n=36–40 each.

Figure 6—video 1
Baseline ad libitum echocardiographic measurements.
Figure 6—video 2
Baseline intermittent fasting echocardiographic measurements.
Figure 6—video 3
Dobutamine stress ad libitum echocardiographic measurements.
Figure 6—video 4
Dobutamine stress intermittent fasting echocardiographic measurements.

Additional files

Supplementary file 1

List of all identified proteins in heart tissues of different dietary groups.

https://cdn.elifesciences.org/articles/89214/elife-89214-supp1-v1.xlsx
Supplementary file 2

IF-responsive differentially expressed proteins in heart tissues among different dietary groups.

https://cdn.elifesciences.org/articles/89214/elife-89214-supp2-v1.xlsx
Supplementary file 3

Functional processes and pathways enriched among different IF groups.

https://cdn.elifesciences.org/articles/89214/elife-89214-supp3-v1.xlsx
Supplementary file 4

RNA-seq based transcriptome profiling for heart tissues obtained from mice in different IF regimens.

https://cdn.elifesciences.org/articles/89214/elife-89214-supp4-v1.xlsx
Supplementary file 5

Functional processes and pathways differentially enriched in proteome and transcriptome.

https://cdn.elifesciences.org/articles/89214/elife-89214-supp5-v1.xlsx
Supplementary file 6

Node properties of time-resolved IF protein network.

https://cdn.elifesciences.org/articles/89214/elife-89214-supp6-v1.xlsx
Supplementary file 7

Perturbation of protein association co-regulation in different dietary groups.

https://cdn.elifesciences.org/articles/89214/elife-89214-supp7-v1.xlsx
Supplementary file 8

Quantitative phosphoproteome of heart tissues across different dietary groups.

https://cdn.elifesciences.org/articles/89214/elife-89214-supp8-v1.xlsx
Supplementary file 9

Echocardiographic assessment of myocardial functional and cardiac dynamics.

https://cdn.elifesciences.org/articles/89214/elife-89214-supp9-v1.xlsx
MDAR checklist
https://cdn.elifesciences.org/articles/89214/elife-89214-mdarchecklist1-v1.pdf

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  1. Thiruma V Arumugam
  2. Asfa Alli-Shaik
  3. Elisa A Liehn
  4. Sharmelee Selvaraji
  5. Luting Poh
  6. Vismitha Rajeev
  7. Yoonsuk Cho
  8. Yongeun Cho
  9. Jongho Kim
  10. Joonki Kim
  11. Hannah LF Swa
  12. David Tan Zhi Hao
  13. Chutima Rattanasopa
  14. David Yang-Wei Fann
  15. David Castano Mayan
  16. Gavin Yong-Quan Ng
  17. Sang-Ha Baik
  18. Karthik Mallilankaraman
  19. Mathias Gelderblom
  20. Grant R Drummond
  21. Christopher G Sobey
  22. Brian K Kennedy
  23. Roshni R Singaraja
  24. Mark P Mattson
  25. Dong-Gyu Jo
  26. Jayantha Gunaratne
(2023)
Multiomics analyses reveal dynamic bioenergetic pathways and functional remodeling of the heart during intermittent fasting
eLife 12:RP89214.
https://doi.org/10.7554/eLife.89214.2