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      A model of human neural networks reveals NPTX2 pathology in ALS and FTLD

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          Abstract

          Human cellular models of neurodegeneration require reproducibility and longevity, which is necessary for simulating age-dependent diseases. Such systems are particularly needed for TDP-43 proteinopathies 1 , which involve human-specific mechanisms 25 that cannot be directly studied in animal models. Here, to explore the emergence and consequences of TDP-43 pathologies, we generated induced pluripotent stem cell-derived, colony morphology neural stem cells (iCoMoNSCs) via manual selection of neural precursors 6 . Single-cell transcriptomics and comparison to independent neural stem cells 7 showed that iCoMoNSCs are uniquely homogenous and self-renewing. Differentiated iCoMoNSCs formed a self-organized multicellular system consisting of synaptically connected and electrophysiologically active neurons, which matured into long-lived functional networks (which we designate iNets). Neuronal and glial maturation in iNets was similar to that of cortical organoids 8 . Overexpression of wild-type TDP-43 in a minority of neurons within iNets led to progressive fragmentation and aggregation of the protein, resulting in a partial loss of function and neurotoxicity. Single-cell transcriptomics revealed a novel set of misregulated RNA targets in TDP-43-overexpressing neurons and in patients with TDP-43 proteinopathies exhibiting a loss of nuclear TDP-43. The strongest misregulated target encoded the synaptic protein NPTX2, the levels of which are controlled by TDP-43 binding on its 3′ untranslated region. When NPTX2 was overexpressed in iNets, it exhibited neurotoxicity, whereas correcting NPTX2 misregulation partially rescued neurons from TDP-43-induced neurodegeneration. Notably, NPTX2 was consistently misaccumulated in neurons from patients with amyotrophic lateral sclerosis and frontotemporal lobar degeneration with TDP-43 pathology. Our work directly links TDP-43 misregulation and NPTX2 accumulation, thereby revealing a TDP-43-dependent pathway of neurotoxicity.

          Abstract

          A neural stem cell culture system derived from induced pluripotent stem cells forms a network of synaptically connected and electrophysiologically active neurons that were used as a model system to identify a mechanism of TDP-43-induced neurodegeneration.

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          Fiji: an open-source platform for biological-image analysis.

          Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.
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            STAR: ultrafast universal RNA-seq aligner.

            Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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              edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

              Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org). Contact: mrobinson@wehi.edu.au
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                Author and article information

                Contributors
                magdalini.polymenidou@uzh.ch
                Journal
                Nature
                Nature
                Nature
                Nature Publishing Group UK (London )
                0028-0836
                1476-4687
                14 February 2024
                14 February 2024
                2024
                : 626
                : 8001
                : 1073-1083
                Affiliations
                [1 ]Department of Quantitative Biomedicine, University of Zurich, ( https://ror.org/02crff812) Zurich, Switzerland
                [2 ]Department of Molecular Life Sciences, University of Zurich, ( https://ror.org/02crff812) Zurich, Switzerland
                [3 ]GRID grid.7400.3, ISNI 0000 0004 1937 0650, SIB Swiss Institute of Bioinformatics, , University of Zurich, ; Zurich, Switzerland
                [4 ]Department of Biosystems Science and Engineering, ETH Zürich, ( https://ror.org/05a28rw58) Basel, Switzerland
                [5 ]Brain Research Institute, University of Zurich, ( https://ror.org/02crff812) Zurich, Switzerland
                [6 ]Department of Histology and Embryology, Faculty of Medicine, Masaryk University Brno, ( https://ror.org/02j46qs45) Brno, Czech Republic
                [7 ]Department of Chemistry, Biochemistry and Pharmaceutical Sciences, University of Bern, ( https://ror.org/02k7v4d05) Bern, Switzerland
                [8 ]NCCR RNA and Disease Technology Platform, Bern, Switzerland
                [9 ]Institute of Neuropathology, University of Zurich, ( https://ror.org/02crff812) Zurich, Switzerland
                [10 ]Queen Square Brain Bank for Neurological diseases, Department of Movement Disorders, UCL Institute of Neurology, ( https://ror.org/048b34d51) London, UK
                [11 ]GRID grid.83440.3b, ISNI 0000000121901201, Department of Neurodegenerative Disease, , UCL Institute of Neurology, ; London, UK
                [12 ]Present Address: MaxWell Biosystems AG, Zurich, Switzerland
                Author information
                http://orcid.org/0000-0002-9253-4362
                http://orcid.org/0000-0001-8223-4588
                http://orcid.org/0000-0001-5041-6205
                http://orcid.org/0000-0002-2853-7526
                http://orcid.org/0000-0001-9189-3390
                http://orcid.org/0000-0002-0753-5505
                http://orcid.org/0000-0002-6151-2363
                http://orcid.org/0000-0001-9064-9724
                http://orcid.org/0000-0002-9538-6668
                http://orcid.org/0000-0003-0566-9005
                http://orcid.org/0000-0001-6675-6968
                http://orcid.org/0000-0002-0945-8857
                http://orcid.org/0000-0002-0344-6708
                http://orcid.org/0000-0001-7389-0348
                http://orcid.org/0000-0002-3267-6254
                http://orcid.org/0000-0003-1624-6761
                http://orcid.org/0000-0002-3838-2468
                http://orcid.org/0000-0003-1271-9445
                Article
                7042
                10.1038/s41586-024-07042-7
                10901740
                38355792
                f4fe22f0-1ec4-4975-b982-dc4f52c657b4
                © The Author(s) 2024

                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
                : 28 September 2021
                : 8 January 2024
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                © Springer Nature Limited 2024

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                amyotrophic lateral sclerosis,neurodegeneration
                Uncategorized
                amyotrophic lateral sclerosis, neurodegeneration

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