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A High Output Method to Isolate Cerebral Pericytes from Mouse

Abstract : In recent years, cerebral pericytes have become the focus of extensive research in vascular biology and pathology. The importance of pericytes in blood brain barrier formation and physiology is now demonstrated but its molecular basis remains largely unknown. As the pathophysiological role of cerebral pericytes in neurological disorders is intriguing and of great importance, the in vitro models are not only sufficiently appropriate but also able to incorporate different techniques for these studies. Several methods have been proposed as in vitro models for the extraction of cerebral pericytes, although an antibiotic-free protocol with high output is desirable. Most importantly, a method that has increased output per extraction reduces the usage of more animals. Here, we propose a simple and efficient method for extracting cerebral pericytes with sufficiently high output. The mouse brain tissue homogenate is mixed with a BSA-dextran solution for the separation of the tissue debris and microvascular pellet. We propose a three-step separation followed by filtration to obtain a microvessel rich filtrate. With this method, the quantity of microvascular fragments obtained from 10 mice is sufficient to seed 9 wells (9.6 cm2 each) of a 6-well plate. Most interestingly with this protocol, the user can obtain 27 pericyte rich wells (9.6 cm2 each) in passage 2. The purity of the pericyte cultures are confirmed with the expression of classical pericyte markers: NG2, PDGFR-β and CD146. This method demonstrates an efficient and feasible in vitro tool for physiological and pathophysiological studies on pericytes.
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Contributor : Virginie Justin-Labonne <>
Submitted on : Tuesday, April 7, 2020 - 5:46:29 PM
Last modification on : Wednesday, April 8, 2020 - 1:47:10 AM




Anupriya Mehra, Lucie Dehouck, Elodie Vandenhaute, Marc Fatar, Laurence Fenart, et al.. A High Output Method to Isolate Cerebral Pericytes from Mouse. Journal of visualized experiments : JoVE, JoVE, 2020, ⟨10.3791/60588⟩. ⟨hal-02535814⟩



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