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Julien BOUREL




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2 publication(s) since Janvier 2018:


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11/08/2020 | Neuropsychopharmacology   IF 6.8
Maternal dietary omega-3 deficiency worsens the deleterious effects of prenatal inflammation on the gut-brain axis in the offspring across lifetime.
Leyrolle Q, Decoeur F, Briere G, Amadieu C, Quadros ARAA, Voytyuk I, Lacabanne C, Benmamar-Badel A, Bourel J, Aubert A, Sere A, Chain F, Schwendimann L, Matrot B, Bourgeois T, Gregoire S, Leblanc JG, De Moreno De Leblanc A, Langella P, Fernandes GR, Bretillon L, Joffre C, Uricaru R, Thebault P, Gressens P, Chatel JM, Laye S, Nadjar A

Abstract:
Maternal immune activation (MIA) and poor maternal nutritional habits are risk factors for the occurrence of neurodevelopmental disorders (NDD). Human studies show the deleterious impact of prenatal inflammation and low n-3 polyunsaturated fatty acid (PUFA) intake on neurodevelopment with long-lasting consequences on behavior. However, the mechanisms linking maternal nutritional status to MIA are still unclear, despite their relevance to the etiology of NDD. We demonstrate here that low maternal n-3 PUFA intake worsens MIA-induced early gut dysfunction, including modification of gut microbiota composition and higher local inflammatory reactivity. These deficits correlate with alterations of microglia-neuron crosstalk pathways and have long-lasting effects, both at transcriptional and behavioral levels. This work highlights the perinatal period as a critical time window, especially regarding the role of the gut-brain axis in neurodevelopment, elucidating the link between MIA, poor nutritional habits, and NDD. Fig. 1 EFFECT OF N-3 PUFA DEFICIENCY ON MIA-INDUCED BEHAVIORAL DEFICITS IN NEONATES AND IN ADULT OFFSPRING.: All graphs show Means +/- SEM. a Experimental setup. b Average time spent by pups to achieve the Fox battery tests (negative geotaxis and righting reflex; 3 trials per day from PND4 to PND6). N = 14-19. Two-way ANOVA: MIA effect, F(1,62) = 11.67, p = 0.0011. c Average vocalization time (15-min sessions at PND7-8). N = 14-19. Kruskal-Wallis test followed by Mann-Whitney comparison; n-3 sufficient-Saline vs n-3 sufficient-LPS, **p < 0.01. d Neonate average locomotion measured as the distance traveled (in cm/min) during 1 min-session from PND5 to PND8. N = 14-19. Kruskal-Wallis test followed by Mann-Whitney comparison; n-3 sufficient-Saline vs n-3 deficient-saline, **p = 0.009, n-3 deficient-Saline vs n-3 deficient-LPS, ***p < 0.001. e Time course of locomotor activity of newborns from PND5 to PND8. N = 14-19. Two-way ANOVA on repeated measures followed by Bonferroni's multiple comparisons test: n-3 deficient-Saline vs n-3 deficient-LPS, *p = 0.02. f Time course of the distance traveled in the Morris Water Maze during the learning phase (in cm). N = 10. Two-way ANOVA on repeated measures: diet effect, F(1,36) = 9.22, p = 0.004. g Percentage of time spent in the target quadrant. N = 10. One-sample t test; n-3 sufficient-Saline, ***p < 0.001; n-3 sufficient-LPS, **p = 0.004; n-3 deficient-saline, ***p < 0.001; n-3 deficient-LPS, p = 0.11. h. Time course of the distance traveled in the Morris Water Maze during the reversal learning phase (in cm). N = 10. Two-way ANOVA on repeated measures: MIA effect, F(1,36) = 3.27, p = 0.008; time effect, F(1,36) = 19, p < 0.001. i Basal locomotor activity (in cm). N = 12. Kruskal-Wallis test followed by Mann-Whitney comparison; n-3 deficient-Saline vs n-3 deficient-LPS, **p = 0.008. j Time spent in the light box (anxiogenic area) of the light-dark test. N = 11. Kruskal-Wallis test followed by Mann-Whitney comparison. k Percentage of time spent in the center of the open-field arena (anxiogenic area). N = 8-11. Kruskal-Wallis test followed by Mann-Whitney comparison. Fig. 2 DIETARY N-3 PUFA DEFICIENCY EXACERBATES MIA-INDUCED ALTERATIONS OF THE HIPPOCAMPAL LIPID AND TRANSCRIPTIONAL PROFILES IN ADULTHOOD.: Quantification of the levels of total PUFAs (a), n-6 PUFAs (b), DTA n-6 (c) or DPAn-6 (d) in the hippocampus of adult mice, expressed as the percentage of total fatty acids. All graphs show Means +/- SEM. N = 6. Two-way ANOVA followed by Bonferroni's multiple comparisons test: Total PUFAs: n-3 sufficient-Saline vs n-3 deficient-Saline, ***p = 0.0001; n-3 deficient-Saline vs n-3 deficient-LPS, *p = 0.0156; n-3 deficient-Saline vs n-3 sufficient-LPS, ***p = 0.0003. Total n-6 PUFAs: n-3 sufficient-Saline vs n-3 deficient-Saline, ***p < 0.0001; n-3 deficient-Saline vs n-3 deficient-LPS, **p = 0.0055; n-3 deficient-Saline vs n-3 sufficient-LPS, ***p < 0.0001; n-3 sufficient-Saline vs n-3 deficient LPS, ***p < 0.0001; n-3 deficient-LPS vs n-3 sufficient-LPS, ***p < 0.0001. DTA n-6: n-3 sufficient-Saline vs n-3 deficient-Saline, ***p < 0.0001; n-3 deficient-Saline vs n-3 deficient-LPS, **p = 0.0013; n-3 deficient-Saline vs n-3 sufficient-LPS, ***p < 0.0001; n-3 sufficient-Saline vs n-3 deficient LPS, ***p = 0.0004; n-3 deficient-LPS vs n-3 sufficient-LPS, *p = 0.0158. DPA n-6: n-3 sufficient-Saline vs n-3 deficient-Saline, ***p < 0.0001; n-3 deficient-Saline vs n-3 deficient-LPS, **p = 0.0045; n-3 deficient-Saline vs n-3 sufficient-LPS, ***p < 0.0001; n-3 sufficient-Saline vs n-3 deficient LPS, ***p < 0.0001; n-3 deficient-LPS vs n-3 sufficient-LPS, ***p < 0.0001. e Venn diagram highlighting the number of genes that were modulated by MIA in the hippocampi of adult n-3 sufficient (blue) or n-3 deficient (red) mice. Lower panel: Number of genes that were up- or down-regulated in n-3 sufficient and n-3 deficient mice. Representation of the 20 most significantly dysregulated genes in n-3 sufficient (f) and n-3 deficient (g) mice. Genes that appear in both n-3 sufficient and n-3 deficient mice are bold. h PCA analysis of MIA-induced differentially expressed genes (DEG) in both dietary groups. Confidence ellipses appear around each group. i, j Gene Ontology analysis of DEGs (light red and blue: up-regulated genes; dark red and blue: down-regulated genes). Fig. 3 EFFECT OF N-3 PUFA DEFICIENCY AND MIA ON MICROGLIA-NEURON CROSSTALK PATHWAYS, SPINE DENSITY, OLIGODENDROCYTE AND MYELIN PROTEIN EXPRESSION.: All graphs show Means +/- SEM. a Colocalization of Iba-1 and PSD95 proteins immunoreactivity in the CA1 region of the hippocampus of PND14 pups. Representative confocal image of Iba-1 (green) PSD95 (red) costaining (Top panel: scale bar = 10 microm) and Imaris 3D reconstruction (Bottom panel, scale bar = 1 microm). N = 72-122. Kruskal-Wallis test followed by Mann-Whitney comparisons; n-3 deficient-Saline vs n-3 sufficient-Saline, ***p < 0.0001; n-3 deficient-LPS vs n-3 sufficient-LPS, ***p < 0.0001. b qRT-PCR quantification of microglia-neuron interaction mRNA markers in the hippocampus of PND14 mice (data normalized to the saline group, dotted line). N = 4-6. Kruskal-Wallis test followed by Mann-Whitney comparisons; *p < 0.05, **p < 0.01 (all comparisons in Table S2). c Quantification and representative images of Golgi staining spine density in the CA1 region of the hippocampus at PND28. N = 8-21. Kruskal-Wallis test followed by Mann-Whitney comparisons; n-3 deficient-Saline vs n-3 deficient-LPS, ***p < 0.0001; n-3 deficient-Saline vs n-3 sufficient-Saline, **p = 0.001; n-3 deficient-LPS vs n-3 sufficient-LPS, *p = 0.025. d Western blot-based quantification and representative images of PSD95 protein expression in the hippocampus of PND28 mice. N = 4-8. Kruskal-Wallis test followed by Mann-Whitney comparisons; n-3 deficient-Saline vs n-3 deficient-LPS, **p = 0.004; n-3 deficient-LPS vs n-3 sufficient-LPS, *p = 0.03. Quantification of Olig2 (e), PLP (f), APC (g), MAG (h) and MBP (i) immunoreactivity in the hippocampus of PND14 mice. N = 4-7. Two-way ANOVA. Olig2: diet effect, F(1,20) = 3.48, p = 0.08; MIA effect, F(1,20) = 4.78, p = 0.041. PLP: MIA effect, F(1,22) = 5.01, p = 0.036. APC: diet effect, F(1,17) = 4.96, p = 0.0397. Fig. 4 EFFECT OF N-3 PUFA DEFICIENCY AND MIA ON GUT MICROBIOTA COMPOSITION AT PND14 AND PND21.: All graphs show Means +/- SEM. a 16S rRNA-sequencing-based alpha diversity analysis of the microbiota, measured by Shannon index in PND14 mice. N = 8-12. Two-way ANOVA: diet effect, F(1,39) = 12.76, p < 0.001; MIA effect, F(1,39) = 5.39, p = 0.026. Bacteria phyla (b) and family (c) observed in all experimental groups at PND14. d PCA of all subjects at PND14. Confidence ellipses appear around each group. e 16S rRNA-sequencing-based alpha diversity analysis, measured by Shannon index in PND21 mice. N=8-13. Two-way ANOVA: n-3 sufficient-Saline vs n-3 sufficient-LPS, ***p = 0.0005; n-3 sufficient-LPS vs n-3 deficient-LPS, *p = 0.019; n-3 sufficient-Saline vs n-3 deficient-Saline, **p = 0.0078. Bacteria phyla (f) and family (g) observed in all experimental groups at PND21. h PCA of all subjects at PND14. Confidence ellipses appear around each group. Quantification of MLN lymphocytes cytokine release measured by ELISA at PND14 (i) and PND21 (j). N = 6-15; Kruskal-Wallis test followed by Mann-Whitney comparisons; *p < 0.05, **p < 0.01, ***p < 0.001 (all comparisons in Table S2). Z-score of T cells inflammatory reactivity in PND14 (k) and PND21 (l) mice. N = 7-15. Kruskal-Wallis test followed by Mann-Whitney comparisons; PND14: n-3 deficient-Saline vs n-3 deficient-LPS, ***p < 0.001. PND21: n-3 sufficient-Saline vs n-3 sufficient-LPS, **p = 0.0011, n-3 sufficient-LPS vs n-3 deficient-LPS, ***p = <0.0004. Fig. 5 CORRELATIONS BETWEEN MICROBIAL MODIFICATIONS, GUT INFLAMMATION, AND NEUROBIOLOGICAL PARAMETERS.: a Spearman's correlation matrix between gut immune cells reactivity (e.g cytokine release after T-cells stimulation) and bacterial genera in PND14 mice (*p = 0.05). b Spearman's correlation matrix between neurobiological measurements (PLP, Olig2, Iba-1 and MAP2) and bacterial genera in PND14 mice (*p = 0.05). c Spearman's correlation matrix between gut immune cells reactivity (e.g cytokine release after T-cells stimulation) and bacterial genera in PND21 mice (*p = 0.05). d Spearman's correlation matrix between neurobiological measurements (PLP, Olig2, Iba-1, and MAP2) and bacterial genera in PND21 mice (*p = 0.05). e Spearman's correlation between gut immune cells reactivity (e.g released cytokines after stimulation) and neurobiological parameters in PND21 mice (*p = 0.05). N = 20-22. Escherichia-Shig: Escherichia-Shigella; Eubacterium copro: Eubacterium coprostanoligenes group; Lachno NK4A136: Lachnospiraceae NK4A136 group; Lachno UCG-008: Lachnospiraceae UCG-008; Prevo UCG-001: Prevotellaceae UCG-001; Rikenellaceae RC9: Rikenellaceae RC9 gut group; Ruminococcus gg: Ruminococcus gnavus group. f Schematic summarizing the main findings. Exposure of n-3 PUFA deficient dams to MIA alters the gut microbiota composition and increases the inflammatory reactivity of the gut T-lymphocytes in the offspring during the post-natal period. This is correlated with an impairment in microglia-neuron crosstalk during this phase, with consequences on hippocampus function and memory abilities later in life.




30/01/2018 | Neuroimage   IF 5.4
Deciphering the microstructure of hippocampal subfields with in vivo DTI and NODDI: Applications to experimental multiple sclerosis.
Crombe A, Planche V, Raffard G, Bourel J, Dubourdieu N, Panatier A, Fukutomi H, Dousset V, Oliet S, Hiba B, Tourdias T

Abstract:
The hippocampus contains distinct populations of neurons organized into separate anatomical subfields and layers with differential vulnerability to pathological mechanisms. The ability of in vivo neuroimaging to pinpoint regional vulnerability is especially important for better understanding of hippocampal pathology at the early stage of neurodegenerative disorders and for monitoring future therapeutic strategies. This is the case for instance in multiple sclerosis whose neurodegenerative component can affect the hippocampus from the early stage. We challenged the capacity of two models, i.e. the classical diffusion tensor imaging (DTI) model and the neurite orientation dispersion and density imaging (NODDI) model, to compute quantitative diffusion MRI that could capture microstructural alterations in the individual hippocampal layers of experimental-autoimmune encephalomyelitis (EAE) mice, the animal model of multiple sclerosis. To achieve this, the hippocampal anatomy of a healthy mouse brain was first explored ex vivo with high resolution DTI and NODDI. Then, 18 EAE mice and 18 control mice were explored 20 days after immunization with in vivo diffusion MRI prior to sacrifice for the histological quantification of neurites and glial markers in each hippocampal layer. Fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD) maps were computed from the DTI model while the orientation dispersion index (ODI), the neurite density index (NDI) and the volume fraction of isotropic diffusivity (isoVF) maps were computed from the NODDI model. We first showed in control mice that color-coded FA and ODI maps can delineate three main hippocampal layers. The quantification of FA, AD, RD, MD, ODI, NDI and isoVF presented differences within these 3 layers, especially within the molecular layer of the dentate gyrus which displayed a specific signature based on a combination of AD (or MD), ODI and NDI. Then, the comparison between EAE and control mice showed a decrease of AD (p=0.036) and of MD (p=0.033) selectively within the molecular layer of EAE mice while NODDI indices did not present any difference between EAE and control mice in any layer. Histological analyses confirmed the differential vulnerability of the molecular layer of EAE mice that exhibited decreased dendritic length and decreased dendritic complexity together with activated microglia. Dendritic length and intersections within the molecular layer were independent contributors to the observed decrease of AD (R(2)=0.37 and R(2)=0.40, p<0.0001) and MD (R(2)=0.41 and R(2)=0.42, p<0.0001). We therefore identified that NODDI maps can help to highlight the internal microanatomy of the hippocampus but NODDI still presents limitations in grey matter as it failed to capture selective dendritic alterations occurring at early stages of a neurodegenerative disease such as multiple sclerosis, whereas DTI maps were significantly altered.