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      Robotic platform for microinjection into single cells in brain tissue

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          Abstract

          Microinjection into single cells in brain tissue is a powerful technique to study and manipulate neural stem cells. However, such microinjection requires expertise and is a low‐throughput process. We developed the “Autoinjector”, a robot that utilizes images from a microscope to guide a microinjection needle into tissue to deliver femtoliter volumes of liquids into single cells. The Autoinjector enables microinjection of hundreds of cells within a single organotypic slice, resulting in an overall yield that is an order of magnitude greater than manual microinjection. The Autoinjector successfully targets both apical progenitors ( APs) and newborn neurons in the embryonic mouse and human fetal telencephalon. We used the Autoinjector to systematically study gap‐junctional communication between neural progenitors in the embryonic mouse telencephalon and found that apical contact is a characteristic feature of the cells that are part of a gap junction‐coupled cluster. The throughput and versatility of the Autoinjector will render microinjection an accessible high‐performance single‐cell manipulation technique and will provide a powerful new platform for performing single‐cell analyses in tissue for bioengineering and biophysics applications.

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          Most cited references53

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          The molecular biology of memory storage: a dialogue between genes and synapses.

          E R Kandel (2001)
          One of the most remarkable aspects of an animal's behavior is the ability to modify that behavior by learning, an ability that reaches its highest form in human beings. For me, learning and memory have proven to be endlessly fascinating mental processes because they address one of the fundamental features of human activity: our ability to acquire new ideas from experience and to retain these ideas over time in memory. Moreover, unlike other mental processes such as thought, language, and consciousness, learning seemed from the outset to be readily accessible to cellular and molecular analysis. I, therefore, have been curious to know: What changes in the brain when we learn? And, once something is learned, how is that information retained in the brain? I have tried to address these questions through a reductionist approach that would allow me to investigate elementary forms of learning and memory at a cellular molecular level-as specific molecular activities within identified nerve cells.
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            The cell biology of neurogenesis.

            During the development of the mammalian central nervous system, neural stem cells and their derivative progenitor cells generate neurons by asymmetric and symmetric divisions. The proliferation versus differentiation of these cells and the type of division are closely linked to their epithelial characteristics, notably, their apical-basal polarity and cell-cycle length. Here, we discuss how these features change during development from neuroepithelial to radial glial cells, and how this transition affects cell fate and neurogenesis.
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              Regional differences in synaptogenesis in human cerebral cortex.

              The formation of synaptic contacts in human cerebral cortex was compared in two cortical regions: auditory cortex (Heschl's gyrus) and prefrontal cortex (middle frontal gyrus). Synapse formation in both cortical regions begins in the fetus, before conceptual age 27 weeks. Synaptic density increases more rapidly in auditory cortex, where the maximum is reached near postnatal age 3 months. Maximum synaptic density in middle frontal gyrus is not reached until after age 15 months. Synaptogenesis occurs concurrently with dendritic and axonal growth and with myelination of the subcortical white matter. A phase of net synapse elimination occurs late in childhood, earlier in auditory cortex, where it has ended by age 12 years, than in prefrontal cortex, where it extends to midadolescence. Synaptogenesis and synapse elimination in humans appear to be heterochronous in different cortical regions and, in that respect, appears to differ from the rhesus monkey, where they are concurrent. In other respects, including overproduction of synaptic contacts in infancy, persistence of high levels of synaptic density to late childhood or adolescence, the absolute values of maximum and adult synaptic density, and layer specific differences, findings in the human resemble those in rhesus monkeys.
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                Author and article information

                Contributors
                suhasabk@umn.edu
                elena_taverna@eva.mpg.de
                Journal
                EMBO Rep
                EMBO Rep
                10.1002/(ISSN)1469-3178
                EMBR
                embor
                EMBO Reports
                John Wiley and Sons Inc. (Hoboken )
                1469-221X
                1469-3178
                30 August 2019
                04 October 2019
                30 August 2019
                : 20
                : 10 ( doiID: 10.1002/embr.v20.10 )
                : e47880
                Affiliations
                [ 1 ] Department of Biomedical Engineering University of Minnesota Twin Cities MN USA
                [ 2 ] Department of Biomedical Engineering Duke University Durham NC USA
                [ 3 ] Max Planck Institute of Molecular Cell Biology and Genetics Dresden Germany
                [ 4 ] Department of Mechanical Engineering University of Minnesota Twin Cities MN USA
                [ 5 ] Max Planck Institute for Evolutionary Anthropology Leipzig Germany
                Author notes
                [*] [* ] Corresponding author. Tel: +1 612 301 1636; E‐mail: suhasabk@ 123456umn.edu

                Corresponding author. Tel: +49 341 3550; E‐mail: elena_taverna@ 123456eva.mpg.de

                [†]

                These authors contributed equally to this work

                Author information
                https://orcid.org/0000-0003-4143-7201
                https://orcid.org/0000-0002-7767-2644
                https://orcid.org/0000-0002-2430-4725
                Article
                EMBR201947880
                10.15252/embr.201947880
                6776899
                31469223
                07c23f53-648f-4435-a7f3-e4c03d2906cb
                © 2019 The Authors. Published under the terms of the CC BY 4.0 license

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 06 February 2019
                : 23 July 2019
                : 07 August 2019
                Page count
                Figures: 8, Tables: 0, Pages: 16, Words: 12058
                Funding
                Funded by: HHS | NIH | National Institute of Neurological Disorders and Stroke (NINDS)
                Award ID: 1R21NS103098‐01
                Funded by: HHS | National Institutes of Health (NIH)
                Award ID: 1R34NS111654‐01
                Funded by: UM | College of Science and Engineering, University of Minnesota (CSE, U of M)
                Funded by: MnDRIVE
                Funded by: EC | H2020 | H2020 Priority Excellent Science | H2020 European Research Council (ERC)
                Award ID: 250197
                Funded by: Deutsche Forschungsgemeinschaft (DFG)
                Award ID: SFB 655
                Award ID: A2
                Funded by: NOMIS Stiftung (NOMIS Foundation)
                Funded by: NSF | Directorate for Engineering (ENG)
                Funded by: IGERT
                Funded by: ERA‐NET NEURON (MicroKin)
                Categories
                Article
                Articles
                Custom metadata
                2.0
                embr201947880
                04 October 2019
                Converter:WILEY_ML3GV2_TO_NLMPMC version:5.7.0 mode:remove_FC converted:04.10.2019

                Molecular biology
                brain development,computer vision,neural stem cells,robotics,single cell manipulation,methods & resources,neuroscience

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