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      Astrocytes regulate brain extracellular pH via a neuronal activity-dependent bicarbonate shuttle

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          Abstract

          Brain cells continuously produce and release protons into the extracellular space, with the rate of acid production corresponding to the levels of neuronal activity and metabolism. Efficient buffering and removal of excess H + is essential for brain function, not least because all the electrogenic and biochemical machinery of synaptic transmission is highly sensitive to changes in pH. Here, we describe an astroglial mechanism that contributes to the protection of the brain milieu from acidification. In vivo and in vitro experiments conducted in rodent models show that at least one third of all astrocytes release bicarbonate to buffer extracellular H + loads associated with increases in neuronal activity. The underlying signalling mechanism involves activity-dependent release of ATP triggering bicarbonate secretion by astrocytes via activation of metabotropic P2Y 1 receptors, recruitment of phospholipase C, release of Ca 2+ from the internal stores, and facilitated outward HCO 3 transport by the electrogenic sodium bicarbonate cotransporter 1, NBCe1. These results show that astrocytes maintain local brain extracellular pH homeostasis via a neuronal activity-dependent release of bicarbonate. The data provide evidence of another important metabolic housekeeping function of these glial cells.

          Abstract

          Several mechanisms contribute to the maintenance of constant extracellular pH, essential for normal brain function. Here the authors show that astrocytes help to control local brain pH via a neuronal activity-dependent release of bicarbonate by the electrogenic sodium bicarbonate cotransporter 1.

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          Comprehensive Integration of Single-Cell Data

          Single-cell transcriptomics has transformed our ability to characterize cell states, but deep biological understanding requires more than a taxonomic listing of clusters. As new methods arise to measure distinct cellular modalities, a key analytical challenge is to integrate these datasets to better understand cellular identity and function. Here, we develop a strategy to "anchor" diverse datasets together, enabling us to integrate single-cell measurements not only across scRNA-seq technologies, but also across different modalities. After demonstrating improvement over existing methods for integrating scRNA-seq data, we anchor scRNA-seq experiments with scATAC-seq to explore chromatin differences in closely related interneuron subsets and project protein expression measurements onto a bone marrow atlas to characterize lymphocyte populations. Lastly, we harmonize in situ gene expression and scRNA-seq datasets, allowing transcriptome-wide imputation of spatial gene expression patterns. Our work presents a strategy for the assembly of harmonized references and transfer of information across datasets.
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            Integrating single-cell transcriptomic data across different conditions, technologies, and species

            Computational single-cell RNA-seq (scRNA-seq) methods have been successfully applied to experiments representing a single condition, technology, or species to discover and define cellular phenotypes. However, identifying subpopulations of cells that are present across multiple data sets remains challenging. Here, we introduce an analytical strategy for integrating scRNA-seq data sets based on common sources of variation, enabling the identification of shared populations across data sets and downstream comparative analysis. We apply this approach, implemented in our R toolkit Seurat (http://satijalab.org/seurat/), to align scRNA-seq data sets of peripheral blood mononuclear cells under resting and stimulated conditions, hematopoietic progenitors sequenced using two profiling technologies, and pancreatic cell 'atlases' generated from human and mouse islets. In each case, we learn distinct or transitional cell states jointly across data sets, while boosting statistical power through integrated analysis. Our approach facilitates general comparisons of scRNA-seq data sets, potentially deepening our understanding of how distinct cell states respond to perturbation, disease, and evolution.
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              A robust and high-throughput Cre reporting and characterization system for the whole mouse brain

              The Cre/lox system is widely used in mice to achieve cell-type-specific gene expression. However, a strong and universal responding system to express genes under Cre control is still lacking. We have generated a set of Cre reporter mice with strong, ubiquitous expression of fluorescent proteins of different spectra. The robust native fluorescence of these reporters enables direct visualization of fine dendritic structures and axonal projections of the labeled neurons, which is useful in mapping neuronal circuitry, imaging and tracking specific cell populations in vivo. Using these reporters and a high-throughput in situ hybridization platform, we are systematically profiling Cre-directed gene expression throughout the mouse brain in a number of Cre-driver lines, including novel Cre lines targeting different cell types in the cortex. Our expression data are displayed in a public online database to help researchers assess the utility of various Cre-driver lines for cell-type-specific genetic manipulation.
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                Author and article information

                Contributors
                a.gourine@ucl.ac.uk
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                8 October 2020
                8 October 2020
                2020
                : 11
                : 5073
                Affiliations
                [1 ]GRID grid.83440.3b, ISNI 0000000121901201, Centre for Cardiovascular and Metabolic Neuroscience, Neuroscience, Physiology and Pharmacology, , University College London, ; London, UK
                [2 ]GRID grid.418237.b, ISNI 0000 0001 0378 7310, Centro de Estudios Científicos (CECs), ; Valdivia, Chile
                [3 ]GRID grid.83440.3b, ISNI 0000000121901201, Institute of Neurology, , University College London, ; London, UK
                Author information
                http://orcid.org/0000-0002-3921-3674
                http://orcid.org/0000-0002-1086-1424
                http://orcid.org/0000-0002-6514-3980
                http://orcid.org/0000-0001-9539-9947
                http://orcid.org/0000-0002-6623-4833
                http://orcid.org/0000-0003-3068-491X
                Article
                18756
                10.1038/s41467-020-18756-3
                7545092
                33033238
                f216909b-3dd4-41a2-b2f4-f9e6de4fda15
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 24 October 2019
                : 9 September 2020
                Funding
                Funded by: FundRef https://doi.org/10.13039/100004440, Wellcome Trust (Wellcome);
                Award ID: 212251
                Award ID: 200893
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                neurochemistry,astrocyte,neuronal physiology
                Uncategorized
                neurochemistry, astrocyte, neuronal physiology

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