Universal method for the gentle isolation of intact microvessels from frozen tissue: a multiomic investigation into the neurovasculature

التفاصيل البيبلوغرافية
العنوان: Universal method for the gentle isolation of intact microvessels from frozen tissue: a multiomic investigation into the neurovasculature
المؤلفون: Marina Wakid, Daniel Almeida, Zahia Aouabed, Reza Rahimian, Maria Antonietta Davoli, Volodymyr Yerko, Elena Leonova-Erko, Vincent Richard, René Zahedi, Christoph Borchers, Gustavo Turecki, Naguib Mechawar
بيانات النشر: Cold Spring Harbor Laboratory, 2023.
سنة النشر: 2023
الوصف: The neurovascular unit (NVU), comprised of endothelial cells, pericytes, smooth muscle cells, astrocytic endfeet and microglia together with neurons, is paramount for the proper function of the central nervous system. The NVU gatekeeps blood-brain barrier (BBB) properties which, as a system, experiences impairment in several neurological and psychiatric diseases, and contributes to pathogenesis. To better understand function and dysfunction at the NVU, isolation and characterization of the NVU is needed. Here, we describe a singular, standardized protocol to enrich and isolate microvessels from archived snap-frozen human and frozen mouse cerebral cortex using mechanical homogenization and centrifugation-separation that preserves the structural integrity and multicellular composition of microvessel fragments. For the first time, microvessels are isolated from postmortem vmPFC tissue and are comprehensively investigated using both RNA sequencing and Liquid Chromatography with tandem mass spectrometry (LC-MS-MS). Both the transcriptome and proteome are elucidated and compared, demonstrating that the isolated brain microvessel is a robust model for the NVU and can be used to generate highly informative datasets in both physiological and disease contexts.
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::5f7118aee21dfbfc350f11e3e346a094Test
https://doi.org/10.1101/2023.05.10.540076Test
رقم الانضمام: edsair.doi...........5f7118aee21dfbfc350f11e3e346a094
قاعدة البيانات: OpenAIRE