Literature DB >> 23509975

A micro-silicon chip for in vivo cerebral imprint in monkey.

Affif Zaccaria1, Ali Bouamrani, Laurent Selek, Michelle El Atifi, Anne Marie Hesse, Aurélie Juhem, David Ratel, Herve Mathieu, Yohann Coute, Christophe Bruley, Jerome Garin, Alim L Benabid, Stephan Chabardes, Brigitte Piallat, François Berger.   

Abstract

Access to cerebral tissue is essential to better understand the molecular mechanisms associated with neurodegenerative diseases. In this study, we present, for the first time, a new tool designed to obtain molecular and cellular cerebral imprints in the striatum of anesthetized monkeys. The imprint is obtained during a spatially controlled interaction of a chemically modified micro-silicon chip with the brain tissue. Scanning electron and immunofluorescence microscopies showed homogeneous capture of cerebral tissue. Nano-liquid chromatography-tandem mass spectrometry (nano-LC-MS/MS) analysis of proteins harvested on the chip allowed the identification of 1158 different species of proteins. The gene expression profiles of mRNA extracted from the imprint tool showed great similarity to those obtained via the gold standard approach, which is based on post-mortem sections of the same nucleus. Functional analysis of the harvested molecules confirmed the spatially controlled capture of striatal proteins implicated in dopaminergic regulation. Finally, the behavioral monitoring and histological results establish the safety of obtaining repeated cerebral imprints in striatal regions. These results demonstrate the ability of our imprint tool to explore the molecular content of deep brain regions in vivo. They open the way to the molecular exploration of brain in animal models of neurological diseases and will provide complementary information to current data mainly restricted to post-mortem samples.

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Year:  2013        PMID: 23509975      PMCID: PMC3605817          DOI: 10.1021/cn300116g

Source DB:  PubMed          Journal:  ACS Chem Neurosci        ISSN: 1948-7193            Impact factor:   4.418


  34 in total

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10.  Towards standardization of RNA quality assessment using user-independent classifiers of microcapillary electrophoresis traces.

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