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MicroRNA-138 controls hippocampal interneuron function and short-term memory in mice

Daswani, Reetu, Gilardi, Carlotta, Soutschek, Michael, Nanda, Prakruti, Weiss, Kerstin, Bicker, Silvia, Fiore, Roberto, Dieterich, Christoph, Germain, Pierre-Luc, Winterer, Jochen, Schratt, Gerhard·2022·eLife

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Abstract

The proper development and function of neuronal circuits rely on a tightly regulated balance between excitatory and inhibitory (E/I) synaptic transmission, and disrupting this balance can cause neurodevelopmental disorders, for example, schizophrenia. MicroRNA-dependent gene regulation in pyramidal neurons is important for excitatory synaptic function and cognition, but its role in inhibitory interneurons is poorly understood. Here, we identify miR138-5p as a regulator of short-term memory and inhibitory synaptic transmission in the mouse hippocampus. Sponge-mediated miR138-5p inactivation specifically in mouse parvalbumin (PV)-expressing interneurons impairs spatial recognition memory and enhances GABAergic synaptic input onto pyramidal neurons. Cellular and behavioral phenotypes associated with miR138-5p inactivation are paralleled by an upregulation of the schizophrenia (SCZ)-associated Erbb4 , which we validated as a direct miR138-5p target gene. Our findings suggest that miR138-5p is a critical regulator of PV interneuron function in mice, with implications for cognition and SCZ. More generally, they provide evidence that microRNAs orchestrate neural circuit development by fine-tuning both excitatory and inhibitory synaptic transmission.

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  1. Agarwal, 2015, Predicting effective microRNA target sites in mammalian mRNAs, eLife, 4, 10.7554/eLife.05005 · DOI · Paper page
  2. Bartel, 2018, Metazoan MicroRNAs, Cell, 173, 20, 10.1016/j.cell.2018.03.006 · DOI · Paper page
  3. Beveridge, 2010, Schizophrenia is associated with an increase in cortical microRNA biogenesis, Molecular Psychiatry, 15, 1176, 10.1038/mp.2009.84 · DOI
  4. Boscher, 2020, MicroRNA-138 Overexpression Alters Abeta42 Levels and Behavior in Wildtype Mice, Frontiers in Neuroscience, 14, 10.3389/fnins.2020.591138 · DOI
  5. Cheng, 2018, Partial loss of psychiatric risk gene Mir137 in mice causes repetitive behavior and impairs sociability and learning via increased Pde10a, Nature Neuroscience, 21, 1689, 10.1038/s41593-018-0261-7 · DOI
  6. Christensen, 2010, Recombinant Adeno-Associated Virus-Mediated microRNA Delivery into the Postnatal Mouse Brain Reveals a Role for miR-134 in Dendritogenesis in Vivo, Frontiers in Neural Circuits, 3, 10.3389/neuro.04.016.2009 · DOI
  7. Crowell, 2020, muscat detects subpopulation-specific state transitions from multi-sample multi-condition single-cell transcriptomics data, Nature Communications, 11, 10.1038/s41467-020-19894-4 · DOI · Paper page
  8. Del Pino, 2018, Neural circuit dysfunction in mouse models of neurodevelopmental disorders, Current Opinion in Neurobiology, 48, 174, 10.1016/j.conb.2017.12.013 · DOI
  9. Ebert, 2010, MicroRNA sponges: progress and possibilities, RNA (New York, N.Y.), 16, 2043, 10.1261/rna.2414110 · DOI · Paper page
  10. Fuchs, 2007, Recruitment of parvalbumin-positive interneurons determines hippocampal function and associated behavior, Neuron, 53, 591, 10.1016/j.neuron.2007.01.031 · DOI · Paper page
  11. Giusti, 2014, MicroRNA-9 controls dendritic development by targeting REST, eLife, 3, 10.7554/eLife.02755 · DOI · Paper page
  12. Hájos, 2004, Spike timing of distinct types of GABAergic interneuron during hippocampal gamma oscillations in vitro, The Journal of Neuroscience, 24, 9127, 10.1523/JNEUROSCI.2113-04.2004 · DOI
  13. Konopka, 2010, MicroRNA loss enhances learning and memory in mice, The Journal of Neuroscience, 30, 14835, 10.1523/JNEUROSCI.3030-10.2010 · DOI · Paper page
  14. Korotkevich, 2021, Fast Gene Set Enrichment Analysis, 10.1101/060012 · DOI
  15. Kumar, 2010, A de novo 1p34.2 microdeletion identifies the synaptic vesicle gene RIMS3 as a novel candidate for autism, Journal of Medical Genetics, 47, 81, 10.1136/jmg.2008.065821 · DOI
  16. Lackinger, 2019, A placental mammal-specific microRNA cluster acts as a natural brake for sociability in mice, EMBO Reports, 20, 10.15252/embr.201846429 · DOI
  17. Leger, 2013, Object recognition test in mice, Nature Protocols, 8, 2531, 10.1038/nprot.2013.155 · DOI · Paper page
  18. Lovett-Barron, 2014, Dendritic inhibition in the hippocampus supports fear learning, Science (New York, N.Y.), 343, 857, 10.1126/science.1247485 · DOI · Paper page
  19. Markram, 2004, Interneurons of the neocortical inhibitory system, Nature Reviews. Neuroscience, 5, 793, 10.1038/nrn1519 · DOI · Paper page
  20. McNeill, 2012, MicroRNAs shape the neuronal landscape, Neuron, 75, 363, 10.1016/j.neuron.2012.07.005 · DOI · Paper page
  21. Moreau, 2011, Altered microRNA expression profiles in postmortem brain samples from individuals with schizophrenia and bipolar disorder, Biological Psychiatry, 69, 188, 10.1016/j.biopsych.2010.09.039 · DOI · Paper page
  22. Murray, 2011, Parvalbumin-positive CA1 interneurons are required for spatial working but not for reference memory, Nature Neuroscience, 14, 297, 10.1038/nn.2751 · DOI
  23. Nicodemus, 2006, Further evidence for association between ErbB4 and schizophrenia and influence on cognitive intermediate phenotypes in healthy controls, Molecular Psychiatry, 11, 1062, 10.1038/sj.mp.4001878 · DOI
  24. Pouille, 2001, Enforcement of temporal fidelity in pyramidal cells by somatic feed-forward inhibition, Science (New York, N.Y.), 293, 1159, 10.1126/science.1060342 · DOI · Paper page
  25. Qiu, 2020, microRNA Deficiency in VIP+ Interneurons Leads to Cortical Circuit Dysfunction, Cerebral Cortex (New York, N.Y, 30, 2229, 10.1093/cercor/bhz236 · DOI
  26. Que, 2021, Transcriptional and morphological profiling of parvalbumin interneuron subpopulations in the mouse hippocampus, Nature Communications, 12, 10.1038/s41467-020-20328-4 · DOI
  27. Rico, 2011, Neuregulin signaling, cortical circuitry development and schizophrenia, Current Opinion in Genetics & Development, 21, 262, 10.1016/j.gde.2010.12.010 · DOI
  28. Robinson, 2010, A scaling normalization method for differential expression analysis of RNA-seq data, Genome Biology, 11, 10.1186/gb-2010-11-3-r25 · DOI · Paper page
  29. Schratt, 2009, microRNAs at the synapse, Nature Reviews. Neuroscience, 10, 842, 10.1038/nrn2763 · DOI · Paper page
  30. Schröder, 2014, MicroRNA-138 is a potential regulator of memory performance in humans, Frontiers in Human Neuroscience, 8, 10.3389/fnhum.2014.00501 · DOI
  31. Siegel, 2009, A functional screen implicates microRNA-138-dependent regulation of the depalmitoylation enzyme APT1 in dendritic spine morphogenesis, Nature Cell Biology, 11, 705, 10.1038/ncb1876 · DOI · Paper page
  32. Siegert, 2015, The schizophrenia risk gene product miR-137 alters presynaptic plasticity, Nature Neuroscience, 18, 1008, 10.1038/nn.4023 · DOI · Paper page
  33. Sohal, 2019, Excitation-inhibition balance as a framework for investigating mechanisms in neuropsychiatric disorders, Molecular Psychiatry, 24, 1248, 10.1038/s41380-019-0426-0 · DOI · Paper page
  34. Takada, 2015, Rab3 interacting molecule 3 mutations associated with autism alter regulation of voltage-dependent Ca(2)(+) channels, Cell Calcium, 58, 296, 10.1016/j.ceca.2015.06.007 · DOI
  35. Tan, 2013, MicroRNA-128 governs neuronal excitability and motor behavior in mice, Science (New York, N.Y.), 342, 1254, 10.1126/science.1244193 · DOI · Paper page
  36. Tatro, 2013, Short-term recognition memory correlates with regional CNS expression of microRNA-138 in mice, The American Journal of Geriatric Psychiatry, 21, 461, 10.1016/j.jagp.2012.09.005 · DOI
  37. Tian, 2017, Down-Regulation of Neuregulin1/ErbB4 Signaling in the Hippocampus Is Critical for Learning and Memory, Molecular Neurobiology, 54, 3976, 10.1007/s12035-016-9956-5 · DOI
  38. Tian, 2018, MiR-138/SIRT1 axis is implicated in impaired learning and memory abilities of cerebral ischemia/reperfusion injured rats, Experimental Cell Research, 367, 232, 10.1016/j.yexcr.2018.03.042 · DOI · Paper page
  39. Tuncdemir, 2015, miRNAs are Essential for the Survival and Maturation of Cortical Interneurons, Cerebral Cortex (New York, N.Y, 25, 1842, 10.1093/cercor/bht426 · DOI
  40. Valluy, 2015, A coding-independent function of an alternative Ube3a transcript during neuronal development, Nature Neuroscience, 18, 666, 10.1038/nn.3996 · DOI
  41. Walgrave, 2021, Restoring miR-132 expression rescues adult hippocampal neurogenesis and memory deficits in Alzheimer’s disease, Cell Stem Cell, 28, 1805, 10.1016/j.stem.2021.05.001 · DOI · Paper page
  42. Wang, 2018, Genetic recovery of ErbB4 in adulthood partially restores brain functions in null mice, PNAS, 115, 13105, 10.1073/pnas.1811287115 · DOI · Paper page
  43. Watanabe, 2014, A rare MIR138-2 gene variation is associated with schizophrenia in a Japanese population, Psychiatry Research, 215, 801, 10.1016/j.psychres.2013.12.029 · DOI
  44. Wen, 2010, Neuregulin 1 regulates pyramidal neuron activity via ErbB4 in parvalbumin-positive interneurons, PNAS, 107, 1211, 10.1073/pnas.0910302107 · DOI
  45. Winterer, 2019, Single-cell RNA-Seq characterization of anatomically identified OLM interneurons in different transgenic mouse lines, The European Journal of Neuroscience, 50, 3750, 10.1111/ejn.14549 · DOI
  46. Zerbi, 2019, Rapid Reconfiguration of the Functional Connectome after Chemogenetic Locus Coeruleus Activation, Neuron, 103, 702, 10.1016/j.neuron.2019.05.034 · DOI

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Metadata

Authors
Daswani, R., Gilardi, C., Soutschek, M., Nanda, P., Weiss, K., Bicker, S., Fiore, R., Dieterich, C., Germain, P.-L., Winterer, J., & Schratt, G.
Affiliations
  • Lab of Systems Neuroscience, Institute for Neuroscience, Department of Health Science and Technology, Swiss Federal Institute of Technology ETH
  • Institute for Physiological Chemistry, Biochemical-Pharmacological Center Marburg, Philipps-University of Marburg
  • Section of Bioinformatics and Systems Cardiology, Department of Internal Medicine III and Klaus Tschira Institute for Integrative Computational Cardiology, University of Heidelberg
Venue
eLife
Published
2022-03-15
Volume
11
ISSN
2050-084X
Cited by
38
References
9
Language
en
Funders
  • Deutsche Forschungsgemeinschaft (SCHR 1136/4-2)
  • Eidgenössische Technische Hochschule Zürich (24 18-2 (NeuroSno))

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