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Expression microdissection isolation of enriched cell populations from archival brain tissue

Authors :
Heath, P.R.
Appleby-Mallinder, C.
Wyles, M.D.
Simpson, J.E.
Wharton, S.B.
Ince, P.G.
Publication Year :
2016
Publisher :
Elsevier, 2016.

Abstract

BACKGROUND:\ud Laser capture microdissection (LCM) is an established technique for the procurement of enriched cell populations that can undergo further downstream analysis, although it does have limitations. Expression microdissection (xMD) is a new technique that begins to address these pitfalls, such as operator dependence and contamination.\ud \ud NEW METHOD:\ud xMD utilises immunohistochemistry in conjunction with a chromogen to isolate specific cell types by extending the fundamental principles of LCM to create an operator-independent method for the procurement of specific CNS cell types.\ud \ud RESULTS:\ud We report how xMD enables the isolation of specific cell populations, namely neurones and astrocytes, from rat formalin fixed-paraffin embedded (FFPE) tissue. Subsequent reverse transcriptase-polymerase chain reaction (RT-PCR) analysis confirms the enrichment of these specific populations. RIN values after xMD indicate samples are sufficient to carry out further analysis.\ud \ud COMPARISON WITH EXISTING METHOD:\ud xMD offers a rapid method of isolating specific CNS cell types without the need for identification by an operator, reducing the amount of unintentional contamination caused by operator error, whilst also significantly reducing the time required by the current basic LCM technique.\ud \ud CONCLUSIONS:\ud xMD is a superior method for the procurement of enriched cell populations from post-mortem tissue, which can be utilised to create transcriptome profiles, aiding our understanding of the contribution of these cells to a range of neurological diseases. xMD also addresses the issues associated with LCM, such as reliance on an operator to identify target cells, which can cause contamination, as well as addressing the time consuming nature of LCM.

Details

Language :
English
ISSN :
01650270
Database :
OpenAIRE
Accession number :
edsair.core.ac.uk....5fd4744d7caa5b9ce89e01fd3e61ece5