AUTHOR=Tagliafierro Lidia , Bonawitz Kirsten , Glenn Omolara C. , Chiba-Falek Ornit TITLE=Gene Expression Analysis of Neurons and Astrocytes Isolated by Laser Capture Microdissection from Frozen Human Brain Tissues JOURNAL=Frontiers in Molecular Neuroscience VOLUME=9 YEAR=2016 URL=https://www.frontiersin.org/journals/molecular-neuroscience/articles/10.3389/fnmol.2016.00072 DOI=10.3389/fnmol.2016.00072 ISSN=1662-5099 ABSTRACT=

Different cell types and multiple cellular connections characterize the human brain. Gene expression analysis using a specific population of cells is more accurate than conducting analysis of the whole tissue homogenate, particularly in the context of neurodegenerative diseases, where a specific subset of cells is affected by the different pathology. Due to the difficulty of obtaining homogenous cell populations, gene expression in specific cell-types (neurons, astrocytes, etc.) has been understudied. To leverage the use of archive resources of frozen human brains in studies of neurodegenerative diseases, we developed and calibrated a method to quantify cell-type specific—neuronal, astrocytes—expression profiles of genes implicated in neurodegenerative diseases, including Parkinson's and Alzheimer's diseases. Archive human frozen brain tissues were used to prepare slides for rapid immunostaining using cell-specific antibodies. The immunoreactive-cells were isolated by Laser Capture Microdissection (LCM). The enrichment for a particular cell-type of interest was validated in post-analysis stage by the expression of cell-specific markers. We optimized the technique to preserve the RNA integrity, so that the RNA was suitable for downstream expression analyses. Following RNA extraction, the expression levels were determined digitally using nCounter Single Cell Gene Expression assay (NanoString Technologies®). The results demonstrated that using our optimized technique we successfully isolated single neurons and astrocytes from human frozen brain tissues and obtained RNA of a good quality that was suitable for mRNA expression analysis. We present here new advancements compared to previous reported methods, which improve the method's feasibility and its applicability for a variety of downstream molecular analyses. Our new developed method can be implemented in genetic and functional genomic research of neurodegenerative diseases and has the potential to significantly advance the field.