Literature DB >> 19504245

Single-cell RT-PCR identification of genes expressed by human islet endocrine cells.

Dany Muller1, Peter M Jones, Shanta J Persaud.   

Abstract

Studies of gene expression by different islet endocrine cell populations can provide useful information about signal transduction cascades regulating alpha-, beta- and delta-cell function. Experiments on expression of beta-cell gene products are relatively easy to perform in rodent islets as these islets are readily isolated at high purities from the exocrine pancreas; beta-cells are the majority cell type and their autofluorescent properties allow them to be purified from non-beta-cells by fluorescence-activated cell sorting (FACS). However, the situation is rather more complicated when investigating human islet gene expression profiles as purities of collagenase-isolated human islets are generally less than those of mouse and rat islets; beta-cells are less abundant in human islets than they are in rodent islets and conventional FACS purification of human islet beta-cells is not possible because of their high background fluorescence. In addition, FACS does not provide pure alpha- or delta-cell populations from either rodent or human islets. We have developed single-cell RT-PCR protocols to allow identification of genes expressed by human islet alpha-, beta- and delta-cells. This chapter describes these protocols and appropriate steps that should be followed to minimise generation of false-positive amplicons.

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Year:  2009        PMID: 19504245     DOI: 10.1007/978-1-59745-448-3_7

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  1 in total

1.  Human CB1 Receptor Isoforms, present in Hepatocytes and β-cells, are Involved in Regulating Metabolism.

Authors:  Isabel González-Mariscal; Susan M Krzysik-Walker; Máire E Doyle; Qing-Rong Liu; Raffaello Cimbro; Sara Santa-Cruz Calvo; Soumita Ghosh; Łukasz Cieśla; Ruin Moaddel; Olga D Carlson; Rafal P Witek; Jennifer F O'Connell; Josephine M Egan
Journal:  Sci Rep       Date:  2016-09-19       Impact factor: 4.379

  1 in total

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