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Exploiting the endogenous yeast nuclear proteome to identify short linear motifs in vivo
Peptide-domain interactions mediated by short linear motifs (SLiMs) play crucial roles in cellular biology. The simplicity of SLiMs poses challenges in their computational identification. Existing high-throughput methods for discovering SLiMs lack cellular context as they are typically performed in ...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10694487/ https://www.ncbi.nlm.nih.gov/pubmed/37949066 http://dx.doi.org/10.1016/j.crmeth.2023.100637 |
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author | Tessier, Tanner M. King, Cason R. Mymryk, Joe S. |
author_facet | Tessier, Tanner M. King, Cason R. Mymryk, Joe S. |
author_sort | Tessier, Tanner M. |
collection | PubMed |
description | Peptide-domain interactions mediated by short linear motifs (SLiMs) play crucial roles in cellular biology. The simplicity of SLiMs poses challenges in their computational identification. Existing high-throughput methods for discovering SLiMs lack cellular context as they are typically performed in vitro. We developed a functional selection method using yeast to identify peptides that interact with the endogenous yeast nuclear proteome. Remarkably, peptides selected for in yeast also mediated nuclear import in human cells. Notably, the identified peptides did not resemble classical nuclear localization sequences. This platform has the potential to identify and investigate motifs that interact with the nuclear proteome of yeast and human and to aid in the identification and understanding of alternative protein nuclear import mechanisms. |
format | Online Article Text |
id | pubmed-10694487 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-106944872023-12-05 Exploiting the endogenous yeast nuclear proteome to identify short linear motifs in vivo Tessier, Tanner M. King, Cason R. Mymryk, Joe S. Cell Rep Methods Report Peptide-domain interactions mediated by short linear motifs (SLiMs) play crucial roles in cellular biology. The simplicity of SLiMs poses challenges in their computational identification. Existing high-throughput methods for discovering SLiMs lack cellular context as they are typically performed in vitro. We developed a functional selection method using yeast to identify peptides that interact with the endogenous yeast nuclear proteome. Remarkably, peptides selected for in yeast also mediated nuclear import in human cells. Notably, the identified peptides did not resemble classical nuclear localization sequences. This platform has the potential to identify and investigate motifs that interact with the nuclear proteome of yeast and human and to aid in the identification and understanding of alternative protein nuclear import mechanisms. Elsevier 2023-11-09 /pmc/articles/PMC10694487/ /pubmed/37949066 http://dx.doi.org/10.1016/j.crmeth.2023.100637 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Report Tessier, Tanner M. King, Cason R. Mymryk, Joe S. Exploiting the endogenous yeast nuclear proteome to identify short linear motifs in vivo |
title | Exploiting the endogenous yeast nuclear proteome to identify short linear motifs in vivo |
title_full | Exploiting the endogenous yeast nuclear proteome to identify short linear motifs in vivo |
title_fullStr | Exploiting the endogenous yeast nuclear proteome to identify short linear motifs in vivo |
title_full_unstemmed | Exploiting the endogenous yeast nuclear proteome to identify short linear motifs in vivo |
title_short | Exploiting the endogenous yeast nuclear proteome to identify short linear motifs in vivo |
title_sort | exploiting the endogenous yeast nuclear proteome to identify short linear motifs in vivo |
topic | Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10694487/ https://www.ncbi.nlm.nih.gov/pubmed/37949066 http://dx.doi.org/10.1016/j.crmeth.2023.100637 |
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