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Maternal circadian rhythm disruption affects neonatal inflammation via metabolic reprograming of myeloid cells

Nature Metabolism (2024)Cite this article

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Abstract

Disruption of circadian rhythm during pregnancy produces adverse health outcomes in offspring; however, the role of maternal circadian rhythms in the immune system of infants and their susceptibility to inflammation remains poorly understood. Here we show that disruption of circadian rhythms in pregnant mice profoundly aggravates the severity of neonatal inflammatory disorders in both male and female offspring, such as necrotizing enterocolitis and sepsis. The diminished maternal production of docosahexaenoic acid (DHA) and the impaired immunosuppressive function of neonatal myeloid-derived suppressor cells (MDSCs) contribute to this phenomenon. Mechanistically, DHA enhances the immunosuppressive function of MDSCs via PPARγ-mediated mitochondrial oxidative phosphorylation. Transfer of MDSCs or perinatal supplementation of DHA relieves neonatal inflammation induced by maternal rhythm disruption. These observations collectively demonstrate a previously unrecognized role of maternal circadian rhythms in the control of neonatal inflammation via metabolic reprograming of myeloid cells.

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Fig. 1: Disruption of maternal rhythm aggravates neonatal inflammation.
Fig. 2: Effects of maternal rhythm disruption on neonatal inflammation is postnatally determined.
Fig. 3: Disruption of maternal rhythm dampens the function of neonatal MDSCs.
Fig. 4: Maternal-derived DHA enhances the function of neonatal MDSCs via mitochondrial function.
Fig. 5: PPARγ mediates the regulation of neonatal MDSCs by DHA.
Fig. 6: MDSCs transfer counteracts the effect of disrupted maternal rhythm on neonatal inflammation.
Fig. 7: Perinatal DHA supplementation alleviates neonatal inflammation in CRD model.

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Data availability

The bulk RNA-seq data generated in this study have been deposited in the Gene Expression Omnibus under accession code GSE233545. Image source data were deposited in Figshare (https://doi.org/10.6084/m9.figshare.25237708)60. No third-party materials were included in this study. Source data are provided with this paper.

Code availability

No custom codes were used in this study.

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Acknowledgements

This work was supported by grants from the National Natural Science Foundation of China (nos. 81925018 and 82130049 to J.Z.; 82321001 to Y.Y.; and 82225015 and 82171284 to Q.L.). This work was also supported by the New Cornerstone Science Foundation through the XPLORER PRIZE (to Q.L.), Natural Science Foundation of Tianjin (22JCQNJC01210 to H.X.).

Author information

Authors and Affiliations

  1. Tianjin Institute of Immunology, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, International Joint Laboratory of Ocular Diseases, Ministry of Education, State Key Laboratory of Experimental Hematology, Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China

    Zhaohai Cui, Haixu Xu, Jiale Chen, Lin Zhu, Jinhao Yang, Lijuan Zhang, Pan Zhou, Zhi Yao, Ying Yu, Qiang Liu & Jie Zhou

  2. Institute of Pediatric Health and Disease, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, Guangzhou, China

    Zhaohai Cui, Fan Wu & Chunhong Jia

  3. Department of Neonatology, Guangzhou Key Laboratory of Neonatal Intestinal Diseases, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China

    Fan Wu & Chunhong Jia

  4. Department of Cardiology, Jing’an District Central Hospital of Shanghai, Fudan University, Shanghai, China

    Zhuxia Shen

  5. Department of Bioinformatics, Tianjin, China

    Xianfu Yi & Mulin Jun Li

  6. Department of Pharmacology, Tianjin Key Laboratory of Inflammatory Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China

    Lu Zhu & Ying Yu

  7. Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang, China

    Shengzhong Duan

  8. Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China

    Qiang Liu

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  1. Zhaohai Cui
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Contributions

J.Z. conceived and supervised this study. Q.L. and Y.Y. jointly supervised this study. Z.C. performed the experiments, analysed the data and wrote the manuscript. H.X. participated in most of the experiments. X.Y. conducted bioinformatics analysis. F.W., J.C., Lin Zhu, Z. Shen, J.Y., C.J., L. Zhang and P.Z. participated in animal model and flow cytometry analysis. M.J.L., Lu Zhu, S.D. and Z.Y. provided suggestions in project design. J.Z. wrote the manuscript with inputs from all authors.

Corresponding authors

Correspondence to Ying Yu, Qiang Liu or Jie Zhou.

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Nature Metabolism thanks Lindsey Devisscher, Christoph Scheiermann and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Ashley Castellanos-Jankiewicz, in collaboration with the Nature Metabolism team.

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Extended data

Extended Data Fig. 1 General effects of maternal rhythm disruption on dams and pups.

(a) Corticosterone content in serum non-targeted metabolomics at day 7 postpartum of dams in control and circadian rhythm disorder groups (n = 3). (b) The contents of melatonin in the serum of dams were measured by ELISA (n = 3/time point). (c) Average food intake per day of control and CRD dams (n = 5). (d) Body weights of pups were evaluated at birth (n = 8). (e) Milk consumption of 7-day-old was assessed (Ctrl: n = 7; CRD: n = 8). (f) The proportions of Th17 and Treg in small intestine were evaluated by flow cytometry after NEC induction (n = 3). (g) The survival rate of NEC mice at ZT0 and ZT6 (Ctrl-ZT0: n = 15; Ctrl-ZT6: n = 16; CRD-ZT0: n = 19; CRD-ZT6: n = 20). (h) Representative H&E staining and inflammation score of intestinal (scale bars: 100 μm, ZT0-Ctrl: n = 6; ZT6-Ctrl: n = 12; ZT0-CRD: n = 3; ZT6-CRD: n = 4). Data are representative of two independent experiments. Mean ± SEM were shown. Two-tailed unpaired Student’s t test for a, c, d, e, f, h. Log-rank (Mantel-Cox) test was used for g. Ns, not significant, *p < 0.05; **p < 0.01, exact P values are provided in the source data.

Source data

Extended Data Fig. 2 Effects of maternal rhythm disruption on neonatal MDSCs.

(a-c) WT pups cross-fostered by Bmal1fl/flWAPcre (n = 8) or Bmal1fl/fl (n = 8) mother were subjected to NEC induction. (a) The survival rate of pups. (b) Representative H&E staining of intestine and the Inflammation scores. scale bars, 100 μm (n = 3-6). (c) The expression of the pro-inflammation genes Il6 and Il1β in intestine was determined by qRT–PCR (n = 3-6). (d-e) The frequencies and absolute numbers of indicated immune cell types in spleen of 7-day-old pups were analysed by flow cytometry (n = 5). (f) The immunosuppressive function of splenic M-MDSC of pups (n = 3-5). (g) The immunosuppressive activity of neonatal PMN-MDSCs from control and CRD groups at different time points (n = 3/time point). (h) The mRNA expression of clock genes Cry2, Per3 and Nr1d2 in PMN-MDSCs from pups were determined by qRT–PCR (n = 3). Data are representative of two independent experiments. Mean ± SEM were shown. Log-rank (Mantel-Cox) test for a. Two-tailed unpaired Student’s t test for b, c, e, f and two-way ANOVA followed by Bonferroni’s multiple comparisons test for g. *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001, exact P values are provided in the source data.

Source data

Extended Data Fig. 3 Effects of maternal rhythm disruption on the transcriptome of neonatal MDSCs.

(a) Principal component analysis (PCA) of neonatal PMN-MDSCs transcriptome between control and CRD groups (n = 3). (b) Heat map of immunosuppressive related genes in PMN-MDSCs (n = 3). (c) WT pups were cross-fostered by Bmal1fl/fl or Bmal1fl/fl WAPcre (WT → Bmal1fl/fl: n = 3; WT → Bmal1fl/fl WAPcre: n = 3). The proliferation of CD8+ T from OT-I spleen were stimulated with OVA257-264 in the presence of neonatal PMN-MDSCs were shown. (d) Heat map of anti-bacterial, phagocytosis and chemokine related genes in PMN-MDSCs (n = 3). (e) The effect of DHA on the migration of PMN-MDSCs was evaluated in vitro by transwell migration assay (n = 5). Neonatal PMN-MDSCs from the spleens from the indicated group were seeded on the upper chamber of transwell. Medium containing chemokine CXCL1 was added to the bottom layer of the transwell. After 1 hour incubation, cells were counted at the bottom chamber. Data are representative of two independent experiments. Two-tailed unpaired Student’s t test for c, and one-way ANOVA followed by Bonferroni’s multiple comparisons test for e. *p < 0.05; **p < 0.01, exact P values are provided in the source data.

Source data

Extended Data Fig. 4 Effect of DHA supplementation on neonatal MDSCs.

(a) Principal component analysis (PCA) of non-targeted metabolomics from breast milk between CRD and control dams (n = 3). (b) Volcano plot showing changed metabolites in breast milk between two groups (n = 3). (c) Heat map displaying altered proteins in breast milk between control and CRD dams. (d) Breast milk was collected from control dams at different time points, followed by targeted metabolomics to evaluate the amounts of DHA (n = 3). (e) The expression of Elovl2 and Elovl5 mRNA in liver of dams at different time points was assessed by qRT–PCR (n = 3). (f) The mRNA expression of DHA synthesis genes in dams’ liver was evaluated by qRT–PCR (n = 3). (g) DHA was orally administered to CRD dams, the proportions of M-MDSC and PMN-MDSC in the spleen of pups were evaluated by flow cytometry (n = 6-7). (h-j) 2-day-old CRD-delivered pups were injected intraperitoneally with DHA at 20 mg/kg/day for 5 days. (i). The proportions of M-MDSC and PMN-MDSC in the spleen were evaluated by flow cytometry (n = 7). (j). The immunosuppressive function of total MDSCs was was evaluated T cell coculture experiment, T cell proliferation was indicated by CFSE labelling (n = 4-7). Data are representative of two independent experiments. Mean ± SEM were shown. Two-tailed unpaired Student’s t test for f, and one-way ANOVA followed by Bonferroni’s multiple comparisons test for g, i, j. Ns, not significant, p > 0.05; *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001, exact P values are provided in the source data.

Source data

Extended Data Fig. 5 Effects of maternal rhythm disruption on PPARγ signalling and mitochondrial function in neonatal PMN-MDSCs.

(a) Heat map of genes related to oxidative phosphorylation in PMN-MDSCs (n = 3). (b) Diurnal mRNA expression of genes involved in mitochondrial dynamics in PMN-MDSCs from control and CRD groups was determined by qRT–PCR (n = 3/time point). (c) Heat map of PPARγ pathway related genes in PMN-MDSCs (n = 3). (d) qRT–PCR analysis of mitochondrial related genes in PMN-MDSCs from pups of PPARγfl/fl and PPARγfl/fl Lysmcre (n = 3). Data are representative of two independent experiments. Mean ± SEM were shown. Two-tailed unpaired Student’s t test for d. *p < 0.05; ***p < 0.001, exact P values are provided in the source data.

Source data

Extended Data Fig. 6 Gating strategies for this paper.

(a) Gating strategy for MDSC. (b) The gating strategy for MDSC subsets. (c) Gating strategy for macrophage, natural killer cell, B cell, T cell and dendritic cell.

Supplementary information

Reporting Summary

Supplementary Data 1–4

1. Antibodies used for flow cytometry in this study. 2. Non-targeted metabolomics of dams. 3. Non-targeted metabolomics of neonates. 4. Primer sequences.

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Cui, Z., Xu, H., Wu, F. et al. Maternal circadian rhythm disruption affects neonatal inflammation via metabolic reprograming of myeloid cells. Nat Metab (2024). https://doi.org/10.1038/s42255-024-01021-y

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