@inbook{e8d4a87dd3f143de9b3585bf21a9bd0c,
title = "Mass spectrometry-based identification of extracellular domains of cell surface N-glycoproteins: defining the accessible surfaceome for immunophenotyping stem cells and their derivatives",
abstract = "Human stem cells and their progeny are valuable for a variety of research applications and have the potential to revolutionize approaches to regenerative medicine. However, we currently have limited tools to permit live isolation of homogeneous populations of cells apt for mechanistic studies or cellular therapies. While these challenges can be overcome through the use of immunophenotyping based on accessible cell surface markers, the success of this process depends on the availability of reliable antibodies and well-characterized markers, which are lacking for most stem cell lineages. This chapter outlines an iterative process for the development of new cell surface marker barcodes for identifying and selecting stem cell derived progeny of specific cell types, subtypes, and maturation stages, where antibody-independent identification of cell surface proteins is achieved using a modern chemoproteomic approach to specifically identify N-glycoproteins localized to the cell surface. By taking advantage of a large repository of available cell surfaceome data, proteins that are unlikely to confer cell type specificity can be rapidly eliminated from consideration. Subsequently, targeted quantitation by mass spectrometry can be used to refine candidates of interest, and a bioinformatic visualization tool is key to mapping experimental data to candidate protein sequences for the purpose of epitope selection during the antibody development phase. Overall, the process of developing cell surface barcodes for immunophenotyping is iterative and can include multiple rounds of discovery, refinement, and validation depending on the phenotypic resolution required.",
keywords = "Barcode, Cell surface, Cell surface protein atlas, Epitope selection, Extracellular domain, Immunophenotyping, Mass spectrometry, N-glycoproteins, Proteomics",
author = "Fujinaka, {Chelsea M.} and Matthew Waas and Gundry, {Rebekah L.}",
note = "Funding Information: This work was supported by National Institutes of Health grants R01HL126785 and R01HL134010 and the Paul G. Allen Family Foundation (Grant Award 11715). Publisher Copyright: {\textcopyright} Springer Science+Business Media, LLC 2018.",
year = "2018",
doi = "10.1007/978-1-4939-7553-2_4",
language = "English (US)",
series = "Methods in Molecular Biology",
publisher = "Humana Press Inc.",
pages = "57--78",
booktitle = "Methods in Molecular Biology",
}