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      The maternal microbiome modulates fetal neurodevelopment in mice

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          Summary

          “Dysbiosis” of the maternal gut microbiome, in response to challenges such as infection 1 , altered diet 2 and stress 3 during pregnancy, has been increasingly associated with abnormalities in offspring brain function and behavior 4 . However, whether the maternal gut microbiome influences neurodevelopment during critical prenatal periods and in the absence of environmental challenge is poorly understood. 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 exhibit reduced expression of genes related to axonogenesis, deficient thalamocortical axons and impaired thalamic axon outgrowth in response to cell-extrinsic factors. Gnotobiotic colonization of microbiota-depleted dams with a limited consortium of bacteria prevents abnormalities in fetal brain gene expression and thalamocortical axonogenesis. Metabolomic profiling reveals that the maternal microbiota regulates numerous small molecules in the maternal serum and brains of fetal offspring. Select microbiota-dependent metabolites promote axon outgrowth from fetal thalamic explants. Moreover, maternal supplementation with the metabolites abrogates deficiencies in fetal thalamocortical axons. Manipulation of the maternal microbiome and microbial metabolites during pregnancy yields adult offspring with altered tactile sensitivity in two aversive somatosensory behavioral tasks, with no overt differences in many other sensorimotor behaviors. Altogether, these findings reveal that the maternal gut microbiome promotes fetal thalamocortical axonogenesis, likely by signaling of microbially modulated metabolites to neurons in the developing brain.

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          Most cited references63

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          Is Open Access

          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            Fiji: an open-source platform for biological-image analysis.

            Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.
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              HISAT: a fast spliced aligner with low memory requirements.

              HISAT (hierarchical indexing for spliced alignment of transcripts) is a highly efficient system for aligning reads from RNA sequencing experiments. HISAT uses an indexing scheme based on the Burrows-Wheeler transform and the Ferragina-Manzini (FM) index, employing two types of indexes for alignment: a whole-genome FM index to anchor each alignment and numerous local FM indexes for very rapid extensions of these alignments. HISAT's hierarchical index for the human genome contains 48,000 local FM indexes, each representing a genomic region of ∼64,000 bp. Tests on real and simulated data sets showed that HISAT is the fastest system currently available, with equal or better accuracy than any other method. Despite its large number of indexes, HISAT requires only 4.3 gigabytes of memory. HISAT supports genomes of any size, including those larger than 4 billion bases.
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                Author and article information

                Journal
                0410462
                6011
                Nature
                Nature
                Nature
                0028-0836
                1476-4687
                4 September 2020
                23 September 2020
                October 2020
                23 March 2021
                : 586
                : 7828
                : 281-286
                Affiliations
                [1 ]Department of Integrative Biology & Physiology, University of California Los Angeles, Los Angeles, CA 90095, USA
                [2 ]Oral Immunity and Inflammation Section, NIDCR, NIH, Bethesda, MD 20892, USA.
                Author notes

                Author 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.C., E.L.S., A.Q., M.K. and C.J.W. assisted with axon outgrowth assays, behavioral, 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.

                [* ]Correspondence to: hvuong2323@ 123456ucla.edu
                Article
                NIHMS1623239
                10.1038/s41586-020-2745-3
                7554197
                32968276
                f254475d-9187-4fc7-8211-04d59f782607

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