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Functional proteomics screen enables enrichment of distinct cell types from human pancreatic islets.


ABSTRACT: The current world-wide epidemic of diabetes has prompted attempts to generate new sources of insulin-producing cells for cell replacement therapy. An inherent challenge in many of these strategies is the lack of cell-surface markers permitting isolation and characterization of specific cell types from differentiating stem cell populations. Here we introduce an iterative proteomics procedure allowing tag-free isolation of cell types based on their function. Our method detects and associates specific cell-surface markers with particular cell functionality by coupling cell capture on antibody arrays with immunofluorescent labeling. Using this approach in an iterative manner, we discovered marker combinations capable of enriching for discrete pancreatic cell subtypes from human islets of Langerhans: insulin-producing beta cells (CD9high/CD56+), glucagon-producing alpha cells (CD9-/CD56+) and trypsin-producing acinar cells (CD9-/CD56-). This strategy may assist future beta cell research and the development of diagnostic tools for diabetes. It can also be applied more generally for function-based purification of desired cell types from other limited and heterogeneous biological samples.

SUBMITTER: Sharivkin R 

PROVIDER: S-EPMC4338300 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Functional proteomics screen enables enrichment of distinct cell types from human pancreatic islets.

Sharivkin Revital R   Walker Michael D MD   Soen Yoav Y  

PloS one 20150223 2


The current world-wide epidemic of diabetes has prompted attempts to generate new sources of insulin-producing cells for cell replacement therapy. An inherent challenge in many of these strategies is the lack of cell-surface markers permitting isolation and characterization of specific cell types from differentiating stem cell populations. Here we introduce an iterative proteomics procedure allowing tag-free isolation of cell types based on their function. Our method detects and associates speci  ...[more]

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