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      Mitochondrial proteins encoded by the 22q11.2 neurodevelopmental locus regulate neural stem and progenitor cell proliferation

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          Abstract

          Microdeletion of a 3Mb region encompassing 45 protein-coding genes at chromosome 22q11.2 (22q11.2DS) predisposes individuals to multiple neurodevelopmental disorders and is one of the greatest genetic risk factors for schizophrenia. Defective mitochondrial function has been hypothesized to contribute to 22q11.2DS pathogenesis; however, which of the six mitochondrial genes contribute to neurodevelopmental phenotypes and their underlying mechanisms remain unresolved. To systematically test 22q11.2DS genes for functional roles in neurodevelopment and behavior, we generated genetic mutants for each of the 37 conserved zebrafish orthologs and performed high throughput behavioral phenotyping using seven behavioral assays. Through this unbiased approach, we identified five single-gene mutants with partially overlapping behavioral phenotypes. Two of these genes, mrpl40 and prodha, encode for mitochondrial proteins and, similar to what we observed in mrpl40 and prodha mutants, pharmacologic inhibition of mitochondrial function during development results in microcephaly. Single mutant analysis shows that both mrpl40 and prodha mutants display aberrant neural stem and progenitor cell proliferation, with each gene regulating distinct cell populations. Finally, double mutants for both mrpl40 and prodha display aggravated behavioral phenotypes and neural stem and progenitor cell analysis reveals a previously unrecognized partially redundant role for mrpl40 and prodha in regulating radial glia-like cell proliferation. Combined, our results demonstrate a critical role for mitochondrial function in neural stem and progenitor cell populations in the developing vertebrate brain and provide compelling evidence that mitochondrial dysfunction during neurodevelopment is linked to brain volume and behavioral phenotypes observed in models of 22q11.2DS.

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          Most cited references63

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          Ensembl 2022

          Ensembl ( https://www.ensembl.org ) is unique in its flexible infrastructure for access to genomic data and annotation. It has been designed to efficiently deliver annotation at scale for all eukaryotic life, and it also provides deep comprehensive annotation for key species. Genomes representing a greater diversity of species are increasingly being sequenced. In response, we have focussed our recent efforts on expediting the annotation of new assemblies. Here, we report the release of the greatest annual number of newly annotated genomes in the history of Ensembl via our dedicated Ensembl Rapid Release platform ( http://rapid.ensembl.org ). We have also developed a new method to generate comparative analyses at scale for these assemblies and, for the first time, we have annotated non-vertebrate eukaryotes. Meanwhile, we continually improve, extend and update the annotation for our high-value reference vertebrate genomes and report the details here. We have a range of specific software tools for specific tasks, such as the Ensembl Variant Effect Predictor (VEP) and the newly developed interface for the Variant Recoder. All Ensembl data, software and tools are freely available for download and are accessible programmatically.
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            MitoCarta3.0: an updated mitochondrial proteome now with sub-organelle localization and pathway annotations

            Abstract The mammalian mitochondrial proteome is under dual genomic control, with 99% of proteins encoded by the nuclear genome and 13 originating from the mitochondrial DNA (mtDNA). We previously developed MitoCarta, a catalogue of over 1000 genes encoding the mammalian mitochondrial proteome. This catalogue was compiled using a Bayesian integration of multiple sequence features and experimental datasets, notably protein mass spectrometry of mitochondria isolated from fourteen murine tissues. Here, we introduce MitoCarta3.0. Beginning with the MitoCarta2.0 inventory, we performed manual review to remove 100 genes and introduce 78 additional genes, arriving at an updated inventory of 1136 human genes. We now include manually curated annotations of sub-mitochondrial localization (matrix, inner membrane, intermembrane space, outer membrane) as well as assignment to 149 hierarchical ‘MitoPathways’ spanning seven broad functional categories relevant to mitochondria. MitoCarta3.0, including sub-mitochondrial localization and MitoPathway annotations, is freely available at http://www.broadinstitute.org/mitocarta and should serve as a continued community resource for mitochondrial biology and medicine.
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              Impaired hippocampal-prefrontal synchrony in a genetic mouse model of schizophrenia.

              Abnormalities in functional connectivity between brain areas have been postulated as an important pathophysiological mechanism underlying schizophrenia. In particular, macroscopic measurements of brain activity in patients suggest that functional connectivity between the frontal and temporal lobes may be altered. However, it remains unclear whether such dysconnectivity relates to the aetiology of the illness, and how it is manifested in the activity of neural circuits. Because schizophrenia has a strong genetic component, animal models of genetic risk factors are likely to aid our understanding of the pathogenesis and pathophysiology of the disease. Here we study Df(16)A(+/-) mice, which model a microdeletion on human chromosome 22 (22q11.2) that constitutes one of the largest known genetic risk factors for schizophrenia. To examine functional connectivity in these mice, we measured the synchronization of neural activity between the hippocampus and the prefrontal cortex during the performance of a task requiring working memory, which is one of the cognitive functions disrupted in the disease. In wild-type mice, hippocampal-prefrontal synchrony increased during working memory performance, consistent with previous reports in rats. Df(16)A(+/-) mice, which are impaired in the acquisition of the task, showed drastically reduced synchrony, measured both by phase-locking of prefrontal cells to hippocampal theta oscillations and by coherence of prefrontal and hippocampal local field potentials. Furthermore, the magnitude of hippocampal-prefrontal coherence at the onset of training could be used to predict the time it took the Df(16)A(+/-) mice to learn the task and increased more slowly during task acquisition. These data suggest how the deficits in functional connectivity observed in patients with schizophrenia may be realized at the single-neuron level. Our findings further suggest that impaired long-range synchrony of neural activity is one consequence of the 22q11.2 deletion and may be a fundamental component of the pathophysiology underlying schizophrenia.
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                Author and article information

                Contributors
                granatom@pennmedicine.upenn.edu
                Journal
                Mol Psychiatry
                Mol Psychiatry
                Molecular Psychiatry
                Nature Publishing Group UK (London )
                1359-4184
                1476-5578
                4 October 2023
                4 October 2023
                2023
                : 28
                : 9
                : 3769-3781
                Affiliations
                [1 ]GRID grid.25879.31, ISNI 0000 0004 1936 8972, Department of Psychiatry, Perelman School of Medicine, , University of Pennsylvania, ; Philadelphia, PA 19104 USA
                [2 ]GRID grid.25879.31, ISNI 0000 0004 1936 8972, Department of Cell and Developmental Biology, Perelman School of Medicine, , University of Pennsylvania, ; Philadelphia, PA 19104 USA
                [3 ]Department of Neurobiology, University of Alabama at Birmingham, ( https://ror.org/008s83205) Birmingham, AL 35294 USA
                Author information
                http://orcid.org/0000-0001-7292-0197
                http://orcid.org/0000-0003-3878-9468
                Article
                2272
                10.1038/s41380-023-02272-z
                10730408
                37794116
                6cad7494-cfee-4d6b-b162-cfa39268b33f
                © The Author(s) 2023

                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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 22 February 2023
                : 7 September 2023
                : 13 September 2023
                Funding
                Funded by: FundRef https://doi.org/10.13039/100000065, U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke (NINDS);
                Award ID: R01NS118921
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100000025, U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH);
                Award ID: T32MH019112
                Award ID: R25MH119043
                Award ID: R00MH110603
                Award Recipient :
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH)
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH)
                Categories
                Article
                Custom metadata
                © Springer Nature Limited 2023

                Molecular medicine
                neuroscience,cell biology,genetics,autism spectrum disorders,schizophrenia
                Molecular medicine
                neuroscience, cell biology, genetics, autism spectrum disorders, schizophrenia

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