9
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      The microbiota regulate neuronal function and fear extinction learning

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Multicellular organisms have co-evolved with complex consortia of viruses, bacteria, fungi and parasites, collectively referred to as the microbiota. In mammals, changes in the composition of the microbiota can influence a wide range of physiologic processes (including development, metabolism, and immune cell function) and are associated with susceptibility to multiple diseases. Alterations in the microbiota can also modulate host behaviors such as social activity, stress, and anxiety-related responses that are linked to diverse neuropsychiatric disorders. However, the mechanisms through which the microbiota influence neuronal activity and host behavior remain poorly defined. Here we demonstrate that manipulation of the microbiota in either antibiotic-treated or germ-free adult mice results in significant deficits in fear extinction learning. Single nucleus RNA-sequencing of the medial prefrontal cortex of the brain revealed significant alterations in gene expression in multiple cell types including excitatory neurons and glial cells. Transcranial two-photon imaging following deliberate manipulation of the microbiota demonstrated that extinction learning deficits were associated with defective learning-related remodeling of postsynaptic dendritic spines and reduced activity in cue-encoding neurons in the medial prefrontal cortex. In addition to effects of manipulating the microbiota on behavior in adult mice, selective re-establishment of the microbiota revealed a limited neonatal developmental window in which microbiota-derived signals can restore normal extinction learning in adulthood. Lastly, unbiased metabolomic analysis identified four metabolites that were significantly downregulated in germ-free mice and were previous reported to be related to human and mouse models of neuropsychiatric disorders, suggesting that microbiota-derived compounds may directly affect brain function and behavior. Together, these data indicate that fear extinction learning requires microbiota-derived signals during both early postnatal neurodevelopment and in adult mice, with implications for our understanding of how diet, infection, and lifestyle influence brain health and subsequent susceptibility to neuropsychiatric disorders.

          Related collections

          Most cited references29

          • Record: found
          • Abstract: found
          • Article: not found

          XCMS Online: a web-based platform to process untargeted metabolomic data.

          Recently, interest in untargeted metabolomics has become prevalent in the general scientific community among an increasing number of investigators. The majority of these investigators, however, do not have the bioinformatic expertise that has been required to process metabolomic data by using command-line driven software programs. Here we introduce a novel platform to process untargeted metabolomic data that uses an intuitive graphical interface and does not require installation or technical expertise. This platform, called XCMS Online, is a web-based version of the widely used XCMS software that allows users to easily upload and process liquid chromatography/mass spectrometry data with only a few mouse clicks. XCMS Online provides a solution for the complete untargeted metabolomic workflow including feature detection, retention time correction, alignment, annotation, statistical analysis, and data visualization. Results can be browsed online in an interactive, customizable table showing statistics, chromatograms, and putative METLIN identities for each metabolite. Additionally, all results and images can be downloaded as zip files for offline analysis and publication. XCMS Online is available at https://xcmsonline.scripps.edu.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Imaging large-scale neural activity with cellular resolution in awake, mobile mice.

            We report a technique for two-photon fluorescence imaging with cellular resolution in awake, behaving mice with minimal motion artifact. The apparatus combines an upright, table-mounted two-photon microscope with a spherical treadmill consisting of a large, air-supported Styrofoam ball. Mice, with implanted cranial windows, are head restrained under the objective while their limbs rest on the ball's upper surface. Following adaptation to head restraint, mice maneuver on the spherical treadmill as their heads remain motionless. Image sequences demonstrate that running-associated brain motion is limited to approximately 2-5 microm. In addition, motion is predominantly in the focal plane, with little out-of-plane motion, making the application of a custom-designed Hidden-Markov-Model-based motion correction algorithm useful for postprocessing. Behaviorally correlated calcium transients from large neuronal and astrocytic populations were routinely measured, with an estimated motion-induced false positive error rate of <5%.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Automated analysis of cellular signals from large-scale calcium imaging data.

              Recent advances in fluorescence imaging permit studies of Ca(2+) dynamics in large numbers of cells, in anesthetized and awake behaving animals. However, unlike for electrophysiological signals, standardized algorithms for assigning optically recorded signals to individual cells have not yet emerged. Here, we describe an automated sorting procedure that combines independent component analysis and image segmentation for extracting cells' locations and their dynamics with minimal human supervision. In validation studies using simulated data, automated sorting significantly improved estimation of cellular signals compared to conventional analysis based on image regions of interest. We used automated procedures to analyze data recorded by two-photon Ca(2+) imaging in the cerebellar vermis of awake behaving mice. Our analysis yielded simultaneous Ca(2+) activity traces for up to >100 Purkinje cells and Bergmann glia from single recordings. Using this approach, we found microzones of Purkinje cells that were stable across behavioral states and in which synchronous Ca(2+) spiking rose significantly during locomotion.
                Bookmark

                Author and article information

                Journal
                0410462
                6011
                Nature
                Nature
                Nature
                0028-0836
                1476-4687
                14 September 2019
                23 October 2019
                October 2019
                23 April 2020
                : 574
                : 7779
                : 543-548
                Affiliations
                [1 ]Jill Roberts Institute for Research in Inflammatory Bowel Disease, Weill Cornell Medicine, Cornell University, New York, NY, USA.
                [2 ]Friedman Center for Nutrition and Inflammation, Joan and Sanford I. Weill Department of Medicine, Department of Microbiology and Immunology, Weill Cornell Medicine, Cornell University, New York, NY, USA.
                [3 ]Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, Cornell University, New York, NY, USA.
                [4 ]Department of Psychiatry, Weill Cornell Medicine, Cornell University, New York, NY, USA.
                [5 ]Sackler Institute for Developmental Psychobiology, Weill Cornell Medicine, Cornell University, New York, NY, USA.
                [6 ]Department of Pharmacology, Weill Cornell Medicine, Cornell University, New York, NY, USA.
                [7 ]Boyce Thompson Institute and Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY, USA.
                [8 ]Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
                [9 ]Howard Hughes Medical Institute, Koch Institute of Integrative Cancer Research, Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA.
                [10 ]Center for Biomedical Science and Bioelectronic Medicine, Feinstein Institute for Medical Research, Northwell Health, Manhasset, NY, USA.
                [11 ]Elmezzi Graduate School, Feinstein Institute for Medical Research, Northwell Health, Manhasset, NY, USA.
                [12 ]Department of Surgery, Northshore University Hospital, Northwell Health, 300 Community Drive, Manhasset, NY, USA
                [13 ]Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA.
                Author notes

                Contributions

                C.C. carried out most of the experiments and analyzed the data. M.H.M., D.J., T.W., H.C., A.M.K., T.T., M.E.A., L.Z., N.J.B., R.R.Y., S.M., C.N.P., A.L., H.C.M., F.T., S.S.C., K.J.T., A.R., F.C.S. and F.S.L. helped with experiments. H.C. and A.R. performed snRNA-seq and analysis. G.G.P. performed bulk RNA-seq and 16S rDNA-seq analysis. D.A., C.L. and C.C. conceived the project, analyzed data, and wrote the manuscript with input from all co-authors.

                Corresponding authors: Correspondence to D.A. ( dartis@ 123456med.cornell.edu ) or C.L. ( col2004@ 123456med.cornell.edu ).
                Article
                NIHMS1539231
                10.1038/s41586-019-1644-y
                6818753
                31645720
                2168f170-233e-4953-9a03-6760e3f1d80e

                Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms

                History
                Categories
                Article

                Uncategorized
                Uncategorized

                Comments

                Comment on this article