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The liver-clock coordinates rhythmicity of peripheral tissues in response to feeding

Nature Metabolism volume 3, pages 829–842 (2021)Cite this article

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Abstract

The mammalian circadian system consists of a central clock in the brain that synchronizes clocks in the peripheral tissues. Although the hierarchy between central and peripheral clocks is established, little is known regarding the specificity and functional organization of peripheral clocks. Here, we employ altered feeding paradigms in conjunction with liver-clock mutant mice to map disparities and interactions between peripheral rhythms. We find that peripheral clocks largely differ in their responses to feeding time. Disruption of the liver-clock, despite its prominent role in nutrient processing, does not affect the rhythmicity of clocks in other peripheral tissues. Yet, unexpectedly, liver-clock disruption strongly modulates the transcriptional rhythmicity of peripheral tissues, primarily on daytime feeding. Concomitantly, liver-clock mutant mice exhibit impaired glucose and lipid homeostasis, which are aggravated by daytime feeding. Overall, our findings suggest that, upon nutrient challenge, the liver-clock buffers the effect of feeding-related signals on rhythmicity of peripheral tissues, irrespective of their clocks.

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Fig. 1: Feeding differentially affects clocks in peripheral tissues.
Fig. 2: Daytime-restricted feeding affects the rhythmic transcriptome in a tissue-specific manner.
Fig. 3: The liver-clock does not affect clock rhythmicity in other peripheral tissues.
Fig. 4: The liver-clock modulates the response of the WAT and lung rhythmic transcriptomes to DF.
Fig. 5: The liver-clock affects the composition of lung and WAT rhythmic transcriptome.
Fig. 6: Impaired glucose homeostasis in liver-clock-deficient mice in response to DF.
Fig. 7: The liver-clock affects body weight and composition in response to DF.

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Data availability

The RNA-seq data are available from the GEO under accession no. GSE159135. Figures 1 and 3 and Extended Data Figs. 1 and 3 are associated with the statistical analysis available in Supplementary Data 1. In addition, the unprocessed blots of Fig. 1g are available as Source Data with this paper. Figures 2, 4, 5 and 6a and Extended Data Figs. 4 and 6 are associated with the RNA-seq data (raw and processed data accessible through the GEO) and with the statistical analysis available in Supplementary Data 2. Extended Data Figs. 2, 5 and 6c are associated with the complete results presented in Supplementary Data 3. Extended Data Fig. 4d,e is associated with the complete results presented in Supplementary Data 4. Extended Data Fig. 6d is associated with the complete results presented in Supplementary Data 5. All other data that support the findings of this study are available from the corresponding author upon request.

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Acknowledgements

We thank all the members of the Asher lab for their comments on the manuscript. We thank L. Flur and E. Elinav for their aid with plasma measurements and Y. Kuperman for her assistance with the metabolic cages. G.A. is supported by the European Research Council (ERC-2017 CIRCOMMUNICATION 770869), Abisch-Frenkel Foundation for the Promotion of Life Sciences, Adelis Foundation and Susan and Michael Stern. E.S. received a Martin Kushner Schnur and Armando and Maria Jinich postdoctoral fellowship for Mexican citizens.

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  1. Elizabeth Sabath

    Present address: Department of Medicine, Institute for transformative molecular medicine, Case Western Reserve University, Cleveland, OH, USA

Authors and Affiliations

  1. Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel

    Gal Manella, Elizabeth Sabath, Rona Aviram, Vaishnavi Dandavate, Saar Ezagouri, Marina Golik, Yaarit Adamovich & Gad Asher

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Contributions

G.M. and G.A. conceptualized the study. G.M., E.S., R.A., V.D., S.E., M.G. and Y.A. carried out the investigation. G.M. carried out the data visualization. G.M. curated the data. G.M. implemented the software. G.A. obtained the funding. G.M. and G.A. wrote, edited and reviewed the manuscript.

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Correspondence to Gad Asher.

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The authors declare no competing interests.

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Peer review information Nature Metabolism thanks Frederic Gachon and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: George Caputa.

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Extended data

Extended Data Fig. 1 Feeding differentially affects clocks in peripheral tissues.

Quantitative PCR results from mice (AlbCre) fed either ad libitum (AL) or exclusively during the light-phase (DF) for 30 days. Samples were collected at 2 h intervals for 24 h (n = 2 biologically independent mice per time point). Presented are representative clock genes from the (a) liver, (b) White Adipose Tissue (WAT), (c) lung, (d) quadriceps muscle, (e) kidney, and (f) heart. Dots mark individual measurements in each Zeitgeber Time (ZT). Significant rhythms according to JTK_CYCLE are denoted by cosine fit curve according to the captions, with a vertical line representing the phase; dashed curves represent non-significant (ns) rhythms. Note that the profiles for Arntl and Nr1d1 are re-plotted from Fig. 1a–f and are included here as well to enable side-by-side comparison with other clock genes in each tissue.

Extended Data Fig. 2 Daytime-restricted feeding affects the rhythmic transcriptome in a tissue-specific manner.

Gene Ontology (GO) Biological Processes (BP) enrichment analysis of rhythmic genes in mice fed either ad libitum (AL) or exclusively during the light-phase (DF) for 30 days in (a) liver, (b) WAT, and (c) lung (P < 0.05, over-representation test).

Extended Data Fig. 3 The liver-clock does not affect clock-rhythmicity in other peripheral tissues.

Quantitative PCR results of clock gene expression of liver-clock mutant mice (BLKO), fed either ad libitum (AL, upper panels) or exclusively during the light-phase (DF, lower panels) for 30 days. Samples were collected at 2 h intervals for 24 h (n = 2 biologically independent mice per time point). Presented are representative clock genes from the (a) liver, (b) WAT, (c) lung, (d) quadriceps muscle, (e) kidney, and (f) heart. Dots mark individual measurements in each Zeitgeber Time (ZT). Significant rhythms according to JTK_CYCLE are denoted by cosine fit curve according to the captions, with a vertical line representing the phase; dashed curves represent non-significant (ns) rhythms.

Extended Data Fig. 4 The liver-clock affects the composition of lung and WAT rhythmic transcriptome.

a, The transcriptomic data of either WAT or lung was subdivided into 15 subsets, based on their rhythmicity in each of the four conditions (AlbCre AL, AlbCre DF, BLKO AL, BLKO DF). For each condition a gene is consider rhythmic if overall Qmin < 0.05, and PHR < 0.05 in this condition (JTK_CYCLE and Harmonic Regression, see also Methods section). Depicted is a tabular summary of all the subsets and categories (L-Bmal1 = Liver-Bmal1). (b, c) Bar plot representation of the size of each subset in WAT (b) and lung (c), with coloration according to the categories as in (a). (d, e) Ingenuity Upstream Regulators analysis for each category in WAT (d) and lung (e) (presented are transcriptional regulators, P < 0.001, and at least 20 targets in the category).

Extended Data Fig. 5 Enrichment analysis for functional annotations of the different rhythmic categories.

Gene Ontology (GO) Biological Processes (BP) enrichment analysis of rhythmic genes which either loss their rhythmicity in BLKO (‘Loss’), or gained rhythmicity in BLKO (‘Gain’), or where not affected by BLKO (‘Retain’) in (a) WAT and (b) lung. (P < 0.05, over-representation test).

Extended Data Fig. 6 Impaired glucose homeostasis in liver-clock deficient mice in response to day feeding.

(a-c) Around-the-clock transcriptomic analysis of livers from either AlbCre control mice or liver-clock deficient mice (BLKO) fed either ad libitum (AL) or exclusively during the light-phase (DF) for 30 days. (a) Pie chart representing the distribution of genes between the different rhythmicity categories (see Fig. S4 for details). (b) Bar-plot representing the sizes of each rhythmicity subset (see Fig. S4 for details). (c) Gene Ontology (GO) Biological Processes (BP) enrichment analysis of rhythmic genes from the RRNN subset (P < 0.05, over-representation test). (d) Phase Set Enrichment Analysis of GO terms in WAT of AlbCre (left panel) or BLKO (right panel) mice. Only terms that are significantly phase-enriched in both ad libitum (AL) and day fed animals (DF) are presented (P < 0.05, Kuiper test), and the phase differences between the two regimens are depicted.

Extended Data Fig. 7 Behavioral and metabolic characterization of control and liver-clock deficient mice.

(a) Intra-Peritoneal Glucose Tolerance Test (IPGTT) analysis AlbCre or BLKO mice fed ad libitum (AL), performed at ZT10 after 2 h of food deprivation (Circles - individual mice, lines - mean levels; 2-way ANOVA with repeated measures design; AlbCre n = 9 mice, BLKO n = 8 mice). (b) IPGTT results from day-fed (DF) AlbCre or BLKO mice, performed at ZT22 (due to the daytime feeding, these mice were food deprived for 10 h), (Circles - individual mice, lines - mean levels; 2-way ANOVA with repeated measures design; n = 7 mice per condition). (c) Area Under the glucose Curve (AUC), as calculated for the data in (a-b), (two-sided Student’s t-test, n as in (a) and (b); boxplots: middle line= median, box= 25th to 75th Inter Quantile Range (IQR), whiskers= the largest/smallest value no greater/smaller than 1.5*IQR, outlier points= measurements outside this range). (d-g) Mice fed either ad libitum (AL) or exclusively during the light-phase (DF) for 4 weeks and were analyzed in metabolic cages for three consecutive days under the same feeding regimens. (d) Food consumption, (e) activity, (f) Respiratory Exchange Rate (RER), and (g) Energy Expenditure (EE) are presented. The data is presented as average of individual mice (n = 3 mice per genotype in AL, n = 4 mice per genotype in DF), with 1 h binning of the data (original measurements were taken every 15 minutes).

Supplementary information

Reporting Summary

Supplementary Data 1

Rhythmicity analysis of qPCR data.

Supplementary Data 2

Summary tables of the statistical analyses.

Supplementary Data 3

GO term enrichment analyses.

Supplementary Data 4

Ingenuity upstream regulator analysis.

Supplementary Data 5

PSEA results.

Supplementary Table 1

qPCR primers.

Source data

Source Data Fig. 1

Unprocessed western blots.

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Manella, G., Sabath, E., Aviram, R. et al. The liver-clock coordinates rhythmicity of peripheral tissues in response to feeding. Nat Metab 3, 829–842 (2021). https://doi.org/10.1038/s42255-021-00395-7

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