Exploiting the endogenous yeast nuclear proteome to identify short linear motifs in vivo
Summary: 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 perf...
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Format: | Article |
Language: | English |
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Elsevier
2023-11-01
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Series: | Cell Reports: Methods |
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Online Access: | http://www.sciencedirect.com/science/article/pii/S2667237523003089 |
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author | Tanner M. Tessier Cason R. King Joe S. Mymryk |
author_facet | Tanner M. Tessier Cason R. King Joe S. Mymryk |
author_sort | Tanner M. Tessier |
collection | DOAJ |
description | Summary: 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. Motivation: Methodologies for identifying short linear motifs have several limitations. Typically, these approaches are limited by scale, making testing of bait and prey libraries in a “many-to-many” fashion impractical. These limitations are further compounded by their in vitro nature and therefore lack functional context. To address these limitations, we have exploited the endogenously expressed yeast nuclear proteome as prey to screen libraries of genetically encoded peptides in an in vivo setting to identify peptide-mediated interactions. This approach capitalizes on the observation that many nuclear proteins lack an identifiable nuclear localization sequence (NLS) and are co-transported into the nucleus via interaction with proteins containing a true NLS. |
first_indexed | 2024-03-10T09:26:01Z |
format | Article |
id | doaj.art-c35a7d060ef843c0a19ec493ec20de9d |
institution | Directory Open Access Journal |
issn | 2667-2375 |
language | English |
last_indexed | 2024-03-10T09:26:01Z |
publishDate | 2023-11-01 |
publisher | Elsevier |
record_format | Article |
series | Cell Reports: Methods |
spelling | doaj.art-c35a7d060ef843c0a19ec493ec20de9d2023-11-22T04:49:27ZengElsevierCell Reports: Methods2667-23752023-11-01311100637Exploiting the endogenous yeast nuclear proteome to identify short linear motifs in vivoTanner M. Tessier0Cason R. King1Joe S. Mymryk2Department of Microbiology and Immunology, Western University, London, ON, CanadaDepartment of Microbiology and Immunology, Western University, London, ON, CanadaDepartment of Microbiology and Immunology, Western University, London, ON, Canada; Department of Oncology, Western University, London, ON, Canada; Department of Otolaryngology, Western University, London, ON, Canada; London Regional Cancer Program, Lawson Health Research Institute, London, ON, Canada; Corresponding authorSummary: 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. Motivation: Methodologies for identifying short linear motifs have several limitations. Typically, these approaches are limited by scale, making testing of bait and prey libraries in a “many-to-many” fashion impractical. These limitations are further compounded by their in vitro nature and therefore lack functional context. To address these limitations, we have exploited the endogenously expressed yeast nuclear proteome as prey to screen libraries of genetically encoded peptides in an in vivo setting to identify peptide-mediated interactions. This approach capitalizes on the observation that many nuclear proteins lack an identifiable nuclear localization sequence (NLS) and are co-transported into the nucleus via interaction with proteins containing a true NLS.http://www.sciencedirect.com/science/article/pii/S2667237523003089CP: Cell biologyCP: Molecular biology |
spellingShingle | Tanner M. Tessier Cason R. King Joe S. Mymryk Exploiting the endogenous yeast nuclear proteome to identify short linear motifs in vivo Cell Reports: Methods CP: Cell biology CP: Molecular biology |
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 | CP: Cell biology CP: Molecular biology |
url | http://www.sciencedirect.com/science/article/pii/S2667237523003089 |
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