Jishu Xu, Michaela Hörner, Maike Nagel, Perwin Perhat, Milena Korneck, Marvin Noß, Stefan Hauser, Ludger Schöls, Jakob Admard, Nicolas Casadei, Rebecca Schüle
{"title":"揭示轴突转录景观:iPSC 衍生皮质神经元的启示及对运动神经元退化的影响","authors":"Jishu Xu, Michaela Hörner, Maike Nagel, Perwin Perhat, Milena Korneck, Marvin Noß, Stefan Hauser, Ludger Schöls, Jakob Admard, Nicolas Casadei, Rebecca Schüle","doi":"10.1101/2024.03.26.586780","DOIUrl":null,"url":null,"abstract":"<p><p>Neuronal function and pathology are deeply influenced by the distinct molecular profiles of the axon and soma. Traditional studies have often overlooked these differences due to the technical challenges of compartment specific analysis. In this study, we employ a robust RNA-sequencing (RNA-seq) approach, using microfluidic devices, to generate high-quality axonal transcriptomes from iPSC-derived cortical neurons (CNs). We achieve high specificity of axonal fractions, ensuring sample purity without contamination. Comparative analysis revealed a unique and specific transcriptional landscape in axonal compartments, characterized by diverse transcript types, including protein-coding mRNAs, RNAs encoding ribosomal proteins (RPs), mitochondrial-encoded RNAs, and long non-coding RNAs (lncRNAs). Previous works have reported the existence of transcription factors (TFs) in the axon. Here, we detect a set of TFs specific to the axon and indicative of their active participation in transcriptional regulation. To investigate transcripts and pathways essential for central motor neuron (MN) degeneration and maintenance we analyzed <i>KIF1C-knockout (KO)</i> CNs, modeling hereditary spastic paraplegia (HSP), a disorder associated with prominent length-dependent degeneration of central MN axons. We found that several key factors crucial for survival and health were absent in <i>KIF1C-KO</i> axons, highlighting a possible role of these also in other neurodegenerative diseases. Taken together, this study underscores the utility of microfluidic devices in studying compartment-specific transcriptomics in human neuronal models and reveals complex molecular dynamics of axonal biology. The impact of <i>KIF1C</i> on the axonal transcriptome not only deepens our understanding of MN diseases but also presents a promising avenue for exploration of compartment specific disease mechanisms.</p>","PeriodicalId":72407,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10996649/pdf/","citationCount":"0","resultStr":"{\"title\":\"Unraveling Axonal Transcriptional Landscapes: Insights from iPSC-Derived Cortical Neurons and Implications for Motor Neuron Degeneration.\",\"authors\":\"Jishu Xu, Michaela Hörner, Maike Nagel, Perwin Perhat, Milena Korneck, Marvin Noß, Stefan Hauser, Ludger Schöls, Jakob Admard, Nicolas Casadei, Rebecca Schüle\",\"doi\":\"10.1101/2024.03.26.586780\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Neuronal function and pathology are deeply influenced by the distinct molecular profiles of the axon and soma. Traditional studies have often overlooked these differences due to the technical challenges of compartment specific analysis. In this study, we employ a robust RNA-sequencing (RNA-seq) approach, using microfluidic devices, to generate high-quality axonal transcriptomes from iPSC-derived cortical neurons (CNs). We achieve high specificity of axonal fractions, ensuring sample purity without contamination. Comparative analysis revealed a unique and specific transcriptional landscape in axonal compartments, characterized by diverse transcript types, including protein-coding mRNAs, RNAs encoding ribosomal proteins (RPs), mitochondrial-encoded RNAs, and long non-coding RNAs (lncRNAs). Previous works have reported the existence of transcription factors (TFs) in the axon. Here, we detect a set of TFs specific to the axon and indicative of their active participation in transcriptional regulation. To investigate transcripts and pathways essential for central motor neuron (MN) degeneration and maintenance we analyzed <i>KIF1C-knockout (KO)</i> CNs, modeling hereditary spastic paraplegia (HSP), a disorder associated with prominent length-dependent degeneration of central MN axons. We found that several key factors crucial for survival and health were absent in <i>KIF1C-KO</i> axons, highlighting a possible role of these also in other neurodegenerative diseases. Taken together, this study underscores the utility of microfluidic devices in studying compartment-specific transcriptomics in human neuronal models and reveals complex molecular dynamics of axonal biology. The impact of <i>KIF1C</i> on the axonal transcriptome not only deepens our understanding of MN diseases but also presents a promising avenue for exploration of compartment specific disease mechanisms.</p>\",\"PeriodicalId\":72407,\"journal\":{\"name\":\"bioRxiv : the preprint server for biology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10996649/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"bioRxiv : the preprint server for biology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1101/2024.03.26.586780\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"bioRxiv : the preprint server for biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.03.26.586780","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Unraveling Axonal Transcriptional Landscapes: Insights from iPSC-Derived Cortical Neurons and Implications for Motor Neuron Degeneration.
Neuronal function and pathology are deeply influenced by the distinct molecular profiles of the axon and soma. Traditional studies have often overlooked these differences due to the technical challenges of compartment specific analysis. In this study, we employ a robust RNA-sequencing (RNA-seq) approach, using microfluidic devices, to generate high-quality axonal transcriptomes from iPSC-derived cortical neurons (CNs). We achieve high specificity of axonal fractions, ensuring sample purity without contamination. Comparative analysis revealed a unique and specific transcriptional landscape in axonal compartments, characterized by diverse transcript types, including protein-coding mRNAs, RNAs encoding ribosomal proteins (RPs), mitochondrial-encoded RNAs, and long non-coding RNAs (lncRNAs). Previous works have reported the existence of transcription factors (TFs) in the axon. Here, we detect a set of TFs specific to the axon and indicative of their active participation in transcriptional regulation. To investigate transcripts and pathways essential for central motor neuron (MN) degeneration and maintenance we analyzed KIF1C-knockout (KO) CNs, modeling hereditary spastic paraplegia (HSP), a disorder associated with prominent length-dependent degeneration of central MN axons. We found that several key factors crucial for survival and health were absent in KIF1C-KO axons, highlighting a possible role of these also in other neurodegenerative diseases. Taken together, this study underscores the utility of microfluidic devices in studying compartment-specific transcriptomics in human neuronal models and reveals complex molecular dynamics of axonal biology. The impact of KIF1C on the axonal transcriptome not only deepens our understanding of MN diseases but also presents a promising avenue for exploration of compartment specific disease mechanisms.