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Quantitative isoform-profiling of highly diversified recognition molecules
Complex biological systems rely on cell surface cues that govern cellular self-recognition and selective interactions with appropriate partners. Molecular diversification of cell surface recognition molecules through DNA recombination and complex alternative splicing has emerged as an important prin...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4489214/ https://www.ncbi.nlm.nih.gov/pubmed/25985086 http://dx.doi.org/10.7554/eLife.07794 |
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author | Schreiner, Dietmar Simicevic, Jovan Ahrné, Erik Schmidt, Alexander Scheiffele, Peter |
author_facet | Schreiner, Dietmar Simicevic, Jovan Ahrné, Erik Schmidt, Alexander Scheiffele, Peter |
author_sort | Schreiner, Dietmar |
collection | PubMed |
description | Complex biological systems rely on cell surface cues that govern cellular self-recognition and selective interactions with appropriate partners. Molecular diversification of cell surface recognition molecules through DNA recombination and complex alternative splicing has emerged as an important principle for encoding such interactions. However, the lack of tools to specifically detect and quantify receptor protein isoforms is a major impediment to functional studies. We here developed a workflow for targeted mass spectrometry by selected reaction monitoring that permits quantitative assessment of highly diversified protein families. We apply this workflow to dissecting the molecular diversity of the neuronal neurexin receptors and uncover an alternative splicing-dependent recognition code for synaptic ligands. DOI: http://dx.doi.org/10.7554/eLife.07794.001 |
format | Online Article Text |
id | pubmed-4489214 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-44892142015-07-07 Quantitative isoform-profiling of highly diversified recognition molecules Schreiner, Dietmar Simicevic, Jovan Ahrné, Erik Schmidt, Alexander Scheiffele, Peter eLife Cell Biology Complex biological systems rely on cell surface cues that govern cellular self-recognition and selective interactions with appropriate partners. Molecular diversification of cell surface recognition molecules through DNA recombination and complex alternative splicing has emerged as an important principle for encoding such interactions. However, the lack of tools to specifically detect and quantify receptor protein isoforms is a major impediment to functional studies. We here developed a workflow for targeted mass spectrometry by selected reaction monitoring that permits quantitative assessment of highly diversified protein families. We apply this workflow to dissecting the molecular diversity of the neuronal neurexin receptors and uncover an alternative splicing-dependent recognition code for synaptic ligands. DOI: http://dx.doi.org/10.7554/eLife.07794.001 eLife Sciences Publications, Ltd 2015-05-18 /pmc/articles/PMC4489214/ /pubmed/25985086 http://dx.doi.org/10.7554/eLife.07794 Text en © 2015, Schreiner et al http://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Cell Biology Schreiner, Dietmar Simicevic, Jovan Ahrné, Erik Schmidt, Alexander Scheiffele, Peter Quantitative isoform-profiling of highly diversified recognition molecules |
title | Quantitative isoform-profiling of highly diversified recognition molecules |
title_full | Quantitative isoform-profiling of highly diversified recognition molecules |
title_fullStr | Quantitative isoform-profiling of highly diversified recognition molecules |
title_full_unstemmed | Quantitative isoform-profiling of highly diversified recognition molecules |
title_short | Quantitative isoform-profiling of highly diversified recognition molecules |
title_sort | quantitative isoform-profiling of highly diversified recognition molecules |
topic | Cell Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4489214/ https://www.ncbi.nlm.nih.gov/pubmed/25985086 http://dx.doi.org/10.7554/eLife.07794 |
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