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Deep thermal profiling for detection of functional proteoform groups
The complexity of the functional proteome extends considerably beyond the coding genome, resulting in millions of proteoforms. Investigation of proteoforms and their functional roles is important to understand cellular physiology and its deregulation in diseases but challenging to perform systematic...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group US
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10374440/ https://www.ncbi.nlm.nih.gov/pubmed/36941476 http://dx.doi.org/10.1038/s41589-023-01284-8 |
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author | Kurzawa, Nils Leo, Isabelle Rose Stahl, Matthias Kunold, Elena Becher, Isabelle Audrey, Anastasia Mermelekas, Georgios Huber, Wolfgang Mateus, André Savitski, Mikhail M. Jafari, Rozbeh |
author_facet | Kurzawa, Nils Leo, Isabelle Rose Stahl, Matthias Kunold, Elena Becher, Isabelle Audrey, Anastasia Mermelekas, Georgios Huber, Wolfgang Mateus, André Savitski, Mikhail M. Jafari, Rozbeh |
author_sort | Kurzawa, Nils |
collection | PubMed |
description | The complexity of the functional proteome extends considerably beyond the coding genome, resulting in millions of proteoforms. Investigation of proteoforms and their functional roles is important to understand cellular physiology and its deregulation in diseases but challenging to perform systematically. Here we applied thermal proteome profiling with deep peptide coverage to detect functional proteoform groups in acute lymphoblastic leukemia cell lines with different cytogenetic aberrations. We detected 15,846 proteoforms, capturing differently spliced, cleaved and post-translationally modified proteins expressed from 9,290 genes. We identified differential co-aggregation of proteoform pairs and established links to disease biology. Moreover, we systematically made use of measured biophysical proteoform states to find specific biomarkers of drug sensitivity. Our approach, thus, provides a powerful and unique tool for systematic detection and functional annotation of proteoform groups. [Image: see text] |
format | Online Article Text |
id | pubmed-10374440 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group US |
record_format | MEDLINE/PubMed |
spelling | pubmed-103744402023-07-29 Deep thermal profiling for detection of functional proteoform groups Kurzawa, Nils Leo, Isabelle Rose Stahl, Matthias Kunold, Elena Becher, Isabelle Audrey, Anastasia Mermelekas, Georgios Huber, Wolfgang Mateus, André Savitski, Mikhail M. Jafari, Rozbeh Nat Chem Biol Article The complexity of the functional proteome extends considerably beyond the coding genome, resulting in millions of proteoforms. Investigation of proteoforms and their functional roles is important to understand cellular physiology and its deregulation in diseases but challenging to perform systematically. Here we applied thermal proteome profiling with deep peptide coverage to detect functional proteoform groups in acute lymphoblastic leukemia cell lines with different cytogenetic aberrations. We detected 15,846 proteoforms, capturing differently spliced, cleaved and post-translationally modified proteins expressed from 9,290 genes. We identified differential co-aggregation of proteoform pairs and established links to disease biology. Moreover, we systematically made use of measured biophysical proteoform states to find specific biomarkers of drug sensitivity. Our approach, thus, provides a powerful and unique tool for systematic detection and functional annotation of proteoform groups. [Image: see text] Nature Publishing Group US 2023-03-20 2023 /pmc/articles/PMC10374440/ /pubmed/36941476 http://dx.doi.org/10.1038/s41589-023-01284-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Kurzawa, Nils Leo, Isabelle Rose Stahl, Matthias Kunold, Elena Becher, Isabelle Audrey, Anastasia Mermelekas, Georgios Huber, Wolfgang Mateus, André Savitski, Mikhail M. Jafari, Rozbeh Deep thermal profiling for detection of functional proteoform groups |
title | Deep thermal profiling for detection of functional proteoform groups |
title_full | Deep thermal profiling for detection of functional proteoform groups |
title_fullStr | Deep thermal profiling for detection of functional proteoform groups |
title_full_unstemmed | Deep thermal profiling for detection of functional proteoform groups |
title_short | Deep thermal profiling for detection of functional proteoform groups |
title_sort | deep thermal profiling for detection of functional proteoform groups |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10374440/ https://www.ncbi.nlm.nih.gov/pubmed/36941476 http://dx.doi.org/10.1038/s41589-023-01284-8 |
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