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      Trpm4 ion channels in pre-Bötzinger complex interneurons are essential for breathing motor pattern but not rhythm

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          Abstract

          Inspiratory breathing movements depend on pre-Bötzinger complex (preBötC) interneurons that express calcium (Ca 2+)-activated nonselective cationic current ( I CAN) to generate robust neural bursts. Hypothesized to be rhythmogenic, reducing I CAN is predicted to slow down or stop breathing; its contributions to motor pattern would be reflected in the magnitude of movements (output). We tested the role(s) of I CAN using reverse genetic techniques to diminish its putative ion channels Trpm4 or Trpc3 in preBötC neurons in vivo. Adult mice transduced with Trpm4-targeted short hairpin RNA (shRNA) progressively decreased the tidal volume of breaths yet surprisingly increased breathing frequency, often followed by gasping and fatal respiratory failure. Mice transduced with Trpc3-targeted shRNA survived with no changes in breathing. Patch-clamp and field recordings from the preBötC in mouse slices also showed an increase in the frequency and a decrease in the magnitude of preBötC neural bursts in the presence of Trpm4 antagonist 9-phenanthrol, whereas the Trpc3 antagonist pyrazole-3 (pyr-3) showed inconsistent effects on magnitude and no effect on frequency. These data suggest that Trpm4 mediates I CAN, whose influence on frequency contradicts a direct role in rhythm generation. We conclude that Trpm4-mediated I CAN is indispensable for motor output but not the rhythmogenic core mechanism of the breathing central pattern generator.

          Author summary

          Breathing behavior consists of periodic movements of the chest and airways that ventilate the lungs. The brain must generate a rhythm and form a motor output pattern to make breathing movements happen. Here, we address the ion channel–level neural origins of breathing, particularly the role of a class of transient receptor potential (Trp) channels hypothesized to be rhythmogenic. Using genetic techniques to knockdown these channels in a specialized brainstem site known for its respiratory rhythmogenic role, we surprisingly did not find the expected changes in breathing frequency. Rather, we measured progressive attenuation of breath magnitude, which in some cases led to fatal breathing pathologies. Therefore, the importance of this ion channel class is not respiratory rhythm generation per se but rather governing the motor output pattern. These results cause us to re-evaluate whether rhythm and pattern are discrete neural processes or instead inextricably linked in microcircuits of the central nervous system that generate and control motor behaviors.

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          Most cited references97

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          TRP channels.

          The TRP (Transient Receptor Potential) superfamily of cation channels is remarkable in that it displays greater diversity in activation mechanisms and selectivities than any other group of ion channels. The domain organizations of some TRP proteins are also unusual, as they consist of linked channel and enzyme domains. A unifying theme in this group is that TRP proteins play critical roles in sensory physiology, which include contributions to vision, taste, olfaction, hearing, touch, and thermo- and osmosensation. In addition, TRP channels enable individual cells to sense changes in their local environment. Many TRP channels are activated by a variety of different stimuli and function as signal integrators. The TRP superfamily is divided into seven subfamilies: the five group 1 TRPs (TRPC, TRPV, TRPM, TRPN, and TRPA) and two group 2 subfamilies (TRPP and TRPML). TRP channels are important for human health as mutations in at least four TRP channels underlie disease.
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            TRP channels as cellular sensors.

            TRP channels are the vanguard of our sensory systems, responding to temperature, touch, pain, osmolarity, pheromones, taste and other stimuli. But their role is much broader than classical sensory transduction. They are an ancient sensory apparatus for the cell, not just the multicellular organism, and they have been adapted to respond to all manner of stimuli, from both within and outside the cell.
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              Decoding the organization of spinal circuits that control locomotion.

              Ole Kiehn (2016)
              Unravelling the functional operation of neuronal networks and linking cellular activity to specific behavioural outcomes are among the biggest challenges in neuroscience. In this broad field of research, substantial progress has been made in studies of the spinal networks that control locomotion. Through united efforts using electrophysiological and molecular genetic network approaches and behavioural studies in phylogenetically diverse experimental models, the organization of locomotor networks has begun to be decoded. The emergent themes from this research are that the locomotor networks have a modular organization with distinct transmitter and molecular codes and that their organization is reconfigured with changes to the speed of locomotion or changes in gait.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: InvestigationRole: ValidationRole: Writing – review & editing
                Role: Formal analysisRole: InvestigationRole: ValidationRole: Writing – review & editing
                Role: Formal analysisRole: Investigation
                Role: InvestigationRole: Visualization
                Role: InvestigationRole: Visualization
                Role: MethodologyRole: ResourcesRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: Formal analysisRole: InvestigationRole: MethodologyRole: ResourcesRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: Methodology
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ResourcesRole: SupervisionRole: ValidationRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: Academic Editor
                Journal
                PLoS Biol
                PLoS Biol
                plos
                plosbiol
                PLoS Biology
                Public Library of Science (San Francisco, CA USA )
                1544-9173
                1545-7885
                21 February 2019
                February 2019
                21 February 2019
                : 17
                : 2
                : e2006094
                Affiliations
                [1 ] Department of Applied Science, Integrated Science Center, William & Mary, Williamsburg, Virginia, United States of America
                [2 ] Biological Sciences, Louisiana State University, Baton Rouge, Louisiana, United States of America
                [3 ] Signalisation, Electrophysiologie et Imagerie des Lésions d’Ischémie-Reperfusion Myocardique, Normandie Université, UNICAEN, Caen, France
                [4 ] Department of Cell Biology and Anatomy, Chicago Medical School, Rosalind Franklin University, Chicago, Illinois, United States of America
                [5 ] Department of Biology, Integrated Science Center, William & Mary, Williamsburg, Virginia, United States of America
                Université de Montréal, Canada
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-7848-8224
                Article
                pbio.2006094
                10.1371/journal.pbio.2006094
                6400419
                30789900
                70c4bc71-4643-4d27-bd7b-8d8aa52d8b9e
                © 2019 Picardo et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 20 March 2018
                : 5 February 2019
                Page count
                Figures: 8, Tables: 1, Pages: 30
                Funding
                National Institutes of Health (NIH) (grant number R01-HL104127). Received by CADN. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. National Science Foundation (NSF) (grant number 1257895). Received by MSS. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. National Institutes of Health (NIH) (grant number R15-HD077624 and R15-HD096415). Received by MSS. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. National Institutes of Health (NIH) (grant number R01-NS097492). Received by KK. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. National Institutes of Health (NIH) (grant number R21-HD097565 and R01-HL115208). Received by RT. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
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                Custom metadata
                vor-update-to-uncorrected-proof
                2019-03-05
                The original data used to analyze the transcriptome of Dbx1-derived and non-Dbx1-derived pre-Bötzinger complex interneurons ( Fig 1) are publicly available in the NCBI Gene Expression Omnibus database, https://www.ncbi.nlm.nih.gov/geo/, accession number GSE100356. Those data include FASTQ files (raw nucleotide sequences and quality scores) as well as processed data files (sequenced reads subsequently aligned and normalized to the mouse reference genome). All of the relevant data plotted in Figs 48, S3, S5 and S7 are available as ascii text files in Supporting information S1 Data.

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