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The maternal microbiome modulates fetal neurodevelopment in mice

Nature volume 586, pages 281–286 (2020)Cite this article

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Abstract

‘Dysbiosis’ of the maternal gut microbiome, in response to challenges such as infection1, altered diet2 and stress3 during pregnancy, has been increasingly associated with abnormalities in brain function and behaviour of the offspring4. However, it is unclear whether the maternal gut microbiome influences neurodevelopment during critical prenatal periods and in the absence of environmental challenges. Here we investigate how depletion and selective reconstitution of the maternal gut microbiome influences fetal neurodevelopment in mice. Embryos from antibiotic-treated and germ-free dams exhibited reduced brain expression of genes related to axonogenesis, deficient thalamocortical axons and impaired outgrowth of thalamic axons in response to cell-extrinsic factors. Gnotobiotic colonization of microbiome-depleted dams with a limited consortium of bacteria prevented abnormalities in fetal brain gene expression and thalamocortical axonogenesis. Metabolomic profiling revealed that the maternal microbiome regulates numerous small molecules in the maternal serum and the brains of fetal offspring. Select microbiota-dependent metabolites promoted axon outgrowth from fetal thalamic explants. Moreover, maternal supplementation with these metabolites abrogated deficiencies in fetal thalamocortical axons. Manipulation of the maternal microbiome and microbial metabolites during pregnancy yielded adult offspring with altered tactile sensitivity in two aversive somatosensory behavioural tasks, but no overt differences in many other sensorimotor behaviours. Together, our findings show that the maternal gut microbiome promotes fetal thalamocortical axonogenesis, probably through signalling by microbially modulated metabolites to neurons in the developing brain.

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Fig. 1: Depletion of the maternal microbiome impairs fetal thalamocortical axonogenesis.
Fig. 2: Colonization of the maternal microbiota prevents neurodevelopmental abnormalities induced by microbiome depletion.
Fig. 3: The maternal microbiota modulates maternal serum and fetal brain metabolites during pregnancy.
Fig. 4: The maternal microbiota modulates metabolites that promote fetal thalamocortical axonogenesis.

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Data availability

All data generated and analysed during this study are included in this published article and its Supplementary Information files. The 16S rRNA gene sequencing data that support the findings have also been deposited to the Qiita database (https://qiita.ucsd.edu/) with study IDs 13099, 13106 and 13107. Transcriptomic data that support the findings of this study have also been deposited to the Gene Expression Omnibus (GEO) repository with accession number GSE147183. Source data are provided with this paper.

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Acknowledgements

We thank members of the Hsiao lab for their critical review of the manuscript; T. Su for RNA sequencing advice; A. Oyler-Yaniv, J. Oyler-Yaniv and R. Wollman for assistance with initial light-sheet image acquisition; A. Rajbhandari and Irina Zhuravka of the UCLA Behavioral Testing Core for behavioural assay training; S. White for sharing ultrasonic vocalization equipment; and A. Collazo of the Caltech Beckman Institute Biological Imaging Facility for assistance with light-sheet image acquisition and analysis. Support for this research was provided by the Packard Fellowship in Science and Engineering and Klingenstein-Simons Award to E.Y.H.; UPLIFT: UCLA Postdocs’ Longitudinal Investment in Faculty Award (# K12 GM106996) and NICHD Pathway to Independence Award (#K99 HD101680) to H.E.V.; the Ruth L. Kirschstein National Research Service Awards (#F31 HD101270 to G.N.P. and #F30 DE025172 to D.W.W.), and the NSF Graduate Research Fellowship to E.J.L.C. E.Y.H. is a New York Stem Cell Foundation – Robertson Investigator. This research was supported in part by the New York Stem Cell Foundation.

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Authors and Affiliations

  1. Department of Integrative Biology and Physiology, University of California Los Angeles, Los Angeles, CA, USA

    Helen E. Vuong, Geoffrey N. Pronovost, Elena J. L. Coley, Emily L. Siegler, Austin Qiu, Maria Kazantsev, Chantel J. Wilson, Tomiko Rendon & Elaine Y. Hsiao

  2. Oral Immunity and Inflammation Section, NIDCR, NIH, Bethesda, MD, USA

    Drake W. Williams

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Contributions

H.E.V. led and performed all experiments; G.N.P. assisted with sample collection and data analysis for imaging, 16S rRNA gene sequencing and metabolomic experiments; D.W.W. assisted with CLARITY, microcomputed tomography and imaging experiments; E.J.L.C., E.L.S., A.Q., M.K. and C.J.W. assisted with axon outgrowth, behavioural, immunofluorescence staining and/or imaging experiments; T.R. generated gnotobiotic mice; E.Y.H. supervised the study; and H.E.V., G.N.P. and E.Y.H. wrote the manuscript.

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Correspondence to Helen E. Vuong.

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Competing interests

Findings regarding the manipulation of the maternal microbiome to influence fetal development and sensory behavior reported in the manuscript are the subject of provisional patent application US 62/844,503, owned by UCLA. The authors declare no competing interests.

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Peer review information Nature thanks Tianyi Mao and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data figures and tables

Extended Data Fig. 1 Network analysis and qPCR validation of fetal brain RNA-seq data.

a, Gene ontology analysis of differentially expressed genes from E14.5 brains from ABX versus SPF dams (one-tailed Fisher exact, q = 0.0125, 0.017, 0.017, 0.0383, 0.0745, 0.0745, 0.0745, 0.1002, n = 3 dams). b, Quantitative RT–PCR for Ntng1 and LRRC4C expression in E14.5 brains from offspring of SPF, ABX or GF dams (two-way ANOVA+Tukey’s, n = 9, 15, 10 dams). c, Protein interaction network of genes downregulated in E14.5 brains from offspring of ABX vs. SPF dams (Benjamini-Hochberg, q < 0.05, n = 3 dams). d, Protein interaction networks of genes upregulated in E14.5 brains from offspring of ABX vs. SPF dams (Benjamini-Hochberg, q < 0.05, n = 3 dams). Mean ± SEM. *P < 0.05, n.s. = not statistically significant.

Source Data

Extended Data Fig. 2 Netrin-G1a thalamocortical axons in E14.5 brains of offspring from gnotobiotic dams.

a, Reference diagrams of coronal rostral to caudal E14.5 brain sections. b–e, Netrin-G1a in four independent E14.5 brains from offspring of SPF (b), ABX (c), GF (d), and Sp (e) dams. Scale = 500 μm. Yellow lines = matched control ROI. f, Netrin-G1a fluorescence per control ROI in E14.5 brain sections of offspring from SPF, ABX, GF and Sp dams. SPF, ABX, GF and Sp data are as presented in Fig. 1c and 2d. (Two-way ANOVA+Tukey’s, n = 5 dams). g, Total brain area E14.5 brain section of offspring from SPF, ABX, GF and Sp dams. (Two-way ANOVA+Tukey’s, n = 5 dams). h, Netrin-G1a per matched control ROI, normalized by total brain area in E14.5 brain sections of offspring from SPF, ABX, GF and Sp dams. (Two-way ANOVA+Tukey’s, n = 5 dams). i, Area of Netrin-G1a in E14.5 brain sections of SPF, ABX, GF and Sp dams. (Two-way ANOVA+Tukey’s, n = 5 dams). j, Area of Netrin-G1a+ staining normalized by total brain area in E14.5 brain sections of offspring from SPF, ABX, GF and Sp dams. (Two-way ANOVA+ Tukey’s, n = 5 dams). k, Netrin-G1a fluorescence in area of Netrin-G1a+ staining of E14.5 brains from SPF, ABX, GF, and Sp dams. (Two-way ANOVA+Tukey’s, n = 5 dams). l, DAPI per matched control ROI, normalized by total brain area in E14.5 brain sections from SPF, ABX, GF and Sp dams. (Two-way ANOVA+Tukey’s, n = 5, 7, 4, 5 dams). m, DAPI+ cell per matched control ROI, normalized by total brain area in E14.5 brain sections from SPF, ABX, GF and Sp dams. (Two-way ANOVA+ Tukey’s, n = 5, 7, 4, 5 dams). Mean ± SEM. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, n.s. = not statistically significant.

Source Data

Extended Data Fig. 3 Whole brain volume and L1+ thalamocortical axons in E14.5 brains of offspring from gnotobiotic dams.

a, Micro-computed tomography of E14.5 fetal brain. Scale bar = 2 mm. b, Whole fetal brain volume of E14.5 offspring from SPF, ABX, GF and Sp dams. (One-way ANOVA+Tukey’s, n = 10, 5, 8, 5 dams). c, Volume of Netrin-G1a axons, normalized to E14.5 SPF, ABX, GF, and Sp whole brain volume. (SPF v ABX: two-tailed Mann–Whitney, SPF v GF, GF v Sp, and ABX v Sp: One-way ANOVA+Tukey’s, n = 5 offspring from different dams). d, Length of Netrin-G1a axons, normalized to the cubic root of E14.5 SPF, ABX, GF, and Sp whole brain volume. (SPF v ABX and SPF v GF: One-way ANOVA+Tukey’s, Sp v ABX and Sp v GF: two-tailed Mann–Whitney, n = 5 offspring from different dams). e, Distance from rostral tip of Netrin-G1a axon to cortex, normalized to the cubic root of E14.5 SPF, ABX, GF, and Sp whole brain volume. (SPF v ABX and Sp v ABX: One-way ANOVA+Tukey’s, SPF v GF and Sp v GF: two-tailed Mann–Whitney, n = 5 offspring from different dams). f, Circumference of Netrin-G1a axonal bundle at the internal capsule (IC), normalized to the cubic root of E14.5 SPF, ABX, GF, and Sp whole brain volume. (One-way ANOVA+Tukey‘s, n = 5 offspring from different dams). g, Netrin-G1a (magenta) and L1 (cyan) in E14.5 SPF, ABX, GF and Sp brain sections. Scale = 500 μm. Yellow lines = matched control ROI. h, L1 per matched control ROI, normalized by total brain area in E14.5 SPF, ABX, GF and Sp brain sections. (Two-way ANOVA+Tukey’s, n = 5 dams). i, L1 per matched control ROI in E14.5 brain sections of offspring from SPF, ABX, GF and Sp dams. SPF, ABX, GF, and Sp data are as in Fig. 1d and 2e. (Two-way ANOVA+Tukey’s, n = 5 dams). Mean ± SEM, *P < 0.05, **P < 0.01, ****P < 0.0001, n.s. = not statistically significant.

Source Data

Extended Data Fig. 4 Thalamic explant monocultures and co-cultures with striatal and hypothalamic explants.

a, Axon outgrowth from monoculture of thalamic explants (Th) from E14.5 offspring of SPF, ABX, GF and Sp dams. Scale = 250 μm. In Th monocultures: b, axon number, and c, axon length (One-way ANOVA+Tukey’s, n = 26, 20, 21, 10 explants). d, Axon outgrowth from (i) SPF Th+SPF hypothalamic explant (Hy), (ii) ABX Th+ABX Hy, (iii) SPF Th+ABX Hy, (iv) ABX Th+SPF Hy. Scale = 250 μm. Proximal to Hy: e, axon number /200 μm2 surface area, normalized to Th monoculture, and f, axon length, normalized to Th monoculture. (One-way ANOVA+Tukey’s, n = 14, 20, 9, 10 explants). g, Axon outgrowth from GF Th+GF St. Scale bar = 250 μm. Proximal to St: h, axon number/200 μm2 surface area, normalized to Th monoculture, and i, axon length, normalized to Th monoculture. (One-way ANOVA+Tukey’s, n = 16 GF explants). j, Axon outgrowth from GF Th+GF Hy. Scale bar = 250 μm. Proximal to Hy: k, axon number/200 μm2 surface area, normalized to Th monoculture, and l, axon length, normalized to Th monoculture. (One-way ANOVA+Tukey’s, n = 14 GF explants). m, Axon outgrowth from (i) SPF Th+SPF St, (ii) ABX Th+ABX St, (iii) Sp Th+Sp St, (iv) Sp Th+ABX St. Scale = 250 μm. Proximal to St: n, axon number/200 μm2 surface area, normalized to Th monoculture, and o, axon length, normalized to Th monoculture. (One-way ANOVA+Tukey’s, n = 14, 20, 14, 6 explants.) p, Axon outgrowth from (i) SPF Th+SPF Hy, (ii) ABX Th+ABX Hy, (iii) Sp Th+Sp Hy, (iv) Sp Th+ABX Hy. Arrows = sparse short axons. Scale = 250 μm. Proximal to Hy: q, axon number/200 μm perimeter, normalized to Th monoculture, and r, axon length, normalized to Th monoculture. (One-way ANOVA+Tukey’s, n = 14, 20, 14, 6 explants). SPF and ABX data in g-i and m-o are in Fig. 1k, 1l. Mean ± SEM. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, n.s. = not statistically significant.

Source Data

Extended Data Fig. 5 Effects of maternal antibiotic treatment and gestational conventionalization on the faecal microbiota.

a, Bacterial load of the maternal faecal microbiota in response to antibiotic (ANVM = ampicillin, neomycin, vancomycin, metronidazole) treatment and conventionalization with SPF microbiota. Yellow line = Ct of germ-free control. (n = 5 cages). b, Principal coordinate analysis of 16S rRNA gene sequencing data (weighted Unifrac distances) for maternal faecal microbiota before antibiotic treatment (pre-ABX), on Day 2, 4, or 6 after ABX treatment, and on Day 0 (E14.5), 4 (E18.5), 6 (P2) and 8 (P4) after exposure to SPF bedding. (n = 5, 5, 5, 5, 3 cages). c, Class-level taxonomic diversity of maternal faecal microbiota pre-ABX and on Day 0 (E14.5), 4 (E18.5), 6 (P2) and 8 (P4) after exposure to SPF bedding. (n = 5, 5, 5, 5, 3 cages).

Source Data

Extended Data Fig. 6 Effects of the maternal microbiome on behaviours.

a, Maternal Sp colonization and SPF conventionalization. b, Force filament to induce 50% paw withdrawal (One-way ANOVA+Tukey’s, n = 38, 24, 45, 25 offspring). c, Latency to contact the adhesive, and d, latency to remove adhesive after first contact (One-way ANOVA+Tukey’s, n = 35, 19, 45, 38 offspring). e, f, Pairwise data for latency to contact and remove adhesive. (Two-way ANOVA+Sidak’s, n = 6, 6, 7, 7 dams). g, Force filament to induce 50% paw withdrawal by sex, per litter or individual (Two-way ANOVA+Tukey’s, n = 5, 7, 7, 7 dams). h, Latency to contact and i, remove adhesive after first contact (Two-way ANOVA+Tukey’s, n = 6, 6, 7, 11 dams). j, Latency to withdraw from hot plate (One-way ANOVA+Tukey’s; n = 37, 19, 45, 25 offspring). k, Habituation to acoustic tone (Two-way ANOVA+Tukey’s; n = 45, 25, 45, 52 offspring). l, Inhibitory effect of prepulse on startle (Two-way ANOVA+Tukey’s; n = 45, 25, 45, 52 offspring). m, Time on rotarod (One-way ANOVA+Tukey’s; n = 45, 20, 45, 50 offspring). n, Visual depth discrimination. y = 0.05, equal instances of exiting safe vs. cliff zone. (One-way ANOVA+Tukey’s; n = 38, 19, 45, 52 offspring). o, Percent time investigating novel texture (One-way ANOVA+Tukey’s; n = 20, 15, 29, 18 offspring). p, 4-MM treatment and SPF conventionalization. q, Force filament to induce 50% paw withdrawal (One-way ANOVA+Tukey’s, n = 10, 23, 15, 21 offspring). r, Latency to contact and s, remove adhesive after first contact (One-way ANOVA+Tukey’s, n = 25, 19, 15, 22 offspring). t, Pairwise data for latency to contact and remove adhesive. (Two-way ANOVA+Sidak’s, n = 5, 5 dams). u, Force filament to induce 50% paw withdrawal by sex, per litter or individual (Two-way ANOVA+Tukey’s, n = 5, 7, 5, 5 dams). v, Latency to contact and w, remove adhesive after first contact. (Two-way ANOVA+Tukey’s, n = 6, 6, 5, 5 dams). Data for SPF and ABX in u–w are as in g–i. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. n.s. = not statistically significant. Number of dams, sex of offspring per group and behavioural task are detailed in Supplementary Table 3.

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Extended Data Fig. 7 Maternal gut microbiota and fetal thalamocortical axons in dams colonized with a consortium of spore-forming bacteria or Bacteroides.

Faecal microbiota of E14.5 SPF and Sp dams (n = 4 dams): a, rarefaction curves of observed operational taxonomic units (OTUs). b, Principal coordinate analysis of weighted sequencing data, and c, order-level taxonomic diversity. d, Genes commonly differentially expressed in E14.5 brains from offspring of SPF and Sp vs. ABX dams (two-tailed Wald, n = 3 dams). Data for SPF and ABX are as in Fig. 1. Red indicates axonogenesis-related genes. e, PRR12 expression in E14.5 brains from offspring of SPF, ABX, and Sp dams (one-way ANOVA+Tukey’s; n = 11, 15, 8 offspring). f, g, Expression of axonogenesis-related genes in E14.5 brains from SPF, ABX, and Sp dams (Two-way ANOVA+Tukey’s; n = 11, 16, 8 offspring). Faecal microbiota of E14.5 SPF and BD dams (n = 4, 5 dams): h, rarefaction curves of the observed OTUs, i, principal coordinate analysis of weighted data, and j, order-level taxonomic diversity. k, Netrin-G1a (magenta) and L1 (cyan) in E14.5 brain sections of BD dams. Scale = 500 μm. Yellow lines = matched control ROI. l, L1 per matched control ROI, un-normalized (right) and normalized (left) by total brain area of E14.5 brain sections of SPF, ABX, and BD dams. Data for SPF and ABX are as in Figs. 1d and 2e, Extended Data Fig. 3g-i. (Two-way ANOVA+Tukey’s, n = 5 dams). m, Netrin-G1a per matched control ROI, un-normalized (middle) and normalized by total area of E14.5 brain sections (left). Netrin-G1a in area of Netrin-G1a+ staining in E14.5 brain sections (right). Data for SPF and ABX are as in Figs. 1c and 2d, Extended Data Fig. 2. (Two-way ANOVA+Tukey’s, n = 5 dams). Mean ± SEM. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, n.s. = not statistically significant.

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Extended Data Fig. 8 Maternal serum and fetal brain metabolomic profiles from gnotobiotic dams.

a, Unsupervised hierarchical clustering of 753 maternal serum metabolites (n = 6 dams). b, Amino acid, lipid and xenobiotic metabolites dysregulated in E14.5 fetal brains of offspring from ABX vs. SPF dams (left) and ABX vs. Sp dams (right) (q<0.05; One-way ANOVA, n = 6 embryos from different dams). c, Amino acid, lipid and xenobiotic metabolites significantly dysregulated in E14.5 fetal brains of offspring from GF dams vs. SPF controls (left) and GF dams vs. Sp dams (right) (q<0.05; One-way ANOVA, n = offspring from 6 dams per group). d, Random Forest classification of top 30 metabolites in maternal serum that discriminate between SPF and Sp vs. ABX and GF dams. (n = 6 dams). e, Relative concentrations of N,N,N-trimethyl-5-aminovalerate (TMAV), trimethylamine N-oxide (TMAO), imidazole propionate (IP), hippurate (HIP), and 3-indoxyl-sulfate (3-IS) in maternal sera of SPF, ABX, GF, and Sp dams (One-way ANOVA with FDR contrasts; n = 6 dams). Mean ± SEM. *q<0.05, **q<0.01, ***q<0.001, ****q<0.0001, n.s. = not statistically significant.

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Extended Data Fig. 9 Effects of microbiome-dependent metabolites on thalamocortical axon outgrowth from GF explant co-cultures.

a, Axon number and b, axon length per 200 μm2 surface area proximal to striatal explant (St) and from (i) SPF thalamic explant (Th)+SPF St (ii) ABX Th+ABX St, and (iii) ABX Th+ABX St, supplemented with 1 nM, 100 nM, 10 μM of metabolites: trimethylamine N-oxide (TMAO), 5-aminovalerate (5-AV), imidazole propionate (IP), 3-indoxyl-sulfate (3-IS) or hippurate (HIP). (One-way ANOVA+Tukey’s, n = 14, 13, TMAO: 7, 6, 7, 5-AV: 3, 5, 7, IP: 5, 7, 7, 3-IS: 3, 7, 7, HIP: 6, 7, 8 explants). c, Axon number, and d, axon length per 200 μm2 surface area proximal to hypothalamic explant (Hy) from (i) SPF Th+SPF Hy), (ii) ABX Th+ABX Hy, and (iii) ABX Th+ABX Hy, supplemented with metabolites. (One-way ANOVA+Tukey’s, n = 14, 10, TMAO: 6, 6, 7, 5-AV: 3, 5, 7, IP: 3, 6, 7, 3-IS: 3, 7, 5, HIP: 5, 7, 8 explants). e, E14.5 GF Th proximal to GF St treated with metabolites. Scale = 250 μm. f, g, Axon number and h, i, axon length per 200 μm perimeter proximal to St (f, h) and Hy (g, i). (One-way ANOVA+Tukey’s, n = 14, 15, 14, 13, 12, 12, 16 explants). Mean ± SEM. *P < 0.05, **P < 0.01, ****P < 0.0001.

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Extended Data Fig. 10 Microbiome-dependent metabolites in E14.5 brains after maternal supplementation with 4-MM or SCFA and effects on netrin-G1a thalamocortical axons.

a, Netrin-G1a in four independent E14.5 brains from offspring of ABX+vehicle and ABX+4-MM dams. Scale = 500 μm, b, Netrin-G1a in area of Netrin-G1a+ staining in E14.5 brains from ABX+vehicle and ABX+4-MM dams. (Two-way ANOVA+Tukey’s, n = 8 dams). c, Area of Netrin-G1a+ staining in E14.5 brain sections. (Two-way ANOVA+Tukey’s, n = 8 dams). d, DAPI counts per matched ROI (yellow lines) normalized by total brain area. (Two-way ANOVA+Tukey’s, n = 4 dams). e, Levels of the metabolites (i) imidazole propionate (IP), (ii) trimethylamine oxide (TMAO), (iii) 3-indoxyl-sulfate (3-IS), (iv) hippurate (HIP) and (v) N, N, N-trimethyl-5-aminovalerate (TMAV) in E14.5 brain lysates from antibiotic-treated dams supplemented with 4-MM or vehicle (One-way ANOVA, n = 5 (ABX+vehicle), 3, 3, 5, 3, 5 (ABX+4-MM) dams). f, Levels of IP, TMAO, 3-IS, HIP, and TMAV in E14.5 brain lysates from BD dams. (One-way ANOVA+Tukey’s, n = 6, 6, 5 dams). g, SCFA administration. h, Netrin-G1a in four independent E14.5 brain sections from offspring of ABX and ABX+SCFA dams. Scale = 500 μm, i, Netrin-G1a and L1 in E14.5 brain sections from offspring of ABX and ABX+SCFA dams. j, Netrin-G1a per matched control ROI, normalized by total brain area. (Two-way ANOVA+Tukey’s, n = 4, 7 dams). k, Netrin-G1a in area of Netrin-G1a+ staining. (Two-way ANOVA+Tukey’s, n = 4, 7 dams). l, Area of Netrin-G1a+ staining. (Two-way ANOVA+Tukey’s, n = 4, 7 dams). m, L1 per matched control ROI, normalized by total brain area. (Two-way ANOVA+Tukey’s, n = 4, 7 dams). n, DAPI count per matched ROI, normalized by total brain area. (Two-way ANOVA+Tukey’s, n = 4, 7 dams). Mean ± SEM. *P < 0.05, **P < 0.01, ***P < 0.001, n.s. = not statistically significant.

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Supplementary Discussion: Discussion of effects of the gut microbiota on axonogenesis and potential mechanisms of microbially modulated metabolites.

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This file contains Supplementary Tables 1-8.

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Vuong, H.E., Pronovost, G.N., Williams, D.W. et al. The maternal microbiome modulates fetal neurodevelopment in mice. Nature 586, 281–286 (2020). https://doi.org/10.1038/s41586-020-2745-3

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