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Protamine Characterization by Top-Down Proteomics: Boosting Proteoform Identification with DBSCAN
Protamines replace histones as the main nuclear protein in the sperm cells of many species and play a crucial role in compacting the paternal genome. Human spermatozoa contain protamine 1 (P1) and the family of protamine 2 (P2) proteins. Alterations in protamine PTMs or the P1/P2 ratio may be associ...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8162566/ https://www.ncbi.nlm.nih.gov/pubmed/33946530 http://dx.doi.org/10.3390/proteomes9020021 |
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author | Arauz-Garofalo, Gianluca Jodar, Meritxell Vilanova, Mar de la Iglesia Rodriguez, Alberto Castillo, Judit Soler-Ventura, Ada Oliva, Rafael Vilaseca, Marta Gay, Marina |
author_facet | Arauz-Garofalo, Gianluca Jodar, Meritxell Vilanova, Mar de la Iglesia Rodriguez, Alberto Castillo, Judit Soler-Ventura, Ada Oliva, Rafael Vilaseca, Marta Gay, Marina |
author_sort | Arauz-Garofalo, Gianluca |
collection | PubMed |
description | Protamines replace histones as the main nuclear protein in the sperm cells of many species and play a crucial role in compacting the paternal genome. Human spermatozoa contain protamine 1 (P1) and the family of protamine 2 (P2) proteins. Alterations in protamine PTMs or the P1/P2 ratio may be associated with male infertility. Top-down proteomics enables large-scale analysis of intact proteoforms derived from alternative splicing, missense or nonsense genetic variants or PTMs. In contrast to current gold standard techniques, top-down proteomics permits a more in-depth analysis of protamine PTMs and proteoforms, thereby opening up new perspectives to unravel their impact on male fertility. We report on the analysis of two normozoospermic semen samples by top-down proteomics. We discuss the difficulties encountered with the data analysis and propose solutions as this step is one of the current bottlenecks in top-down proteomics with the bioinformatics tools currently available. Our strategy for the data analysis combines two software packages, ProSight PD (PS) and TopPIC suite (TP), with a clustering algorithm to decipher protamine proteoforms. We identified up to 32 protamine proteoforms at different levels of characterization. This in-depth analysis of the protamine proteoform landscape of normozoospermic individuals represents the first step towards the future study of sperm pathological conditions opening up the potential personalized diagnosis of male infertility. |
format | Online Article Text |
id | pubmed-8162566 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-81625662021-05-29 Protamine Characterization by Top-Down Proteomics: Boosting Proteoform Identification with DBSCAN Arauz-Garofalo, Gianluca Jodar, Meritxell Vilanova, Mar de la Iglesia Rodriguez, Alberto Castillo, Judit Soler-Ventura, Ada Oliva, Rafael Vilaseca, Marta Gay, Marina Proteomes Article Protamines replace histones as the main nuclear protein in the sperm cells of many species and play a crucial role in compacting the paternal genome. Human spermatozoa contain protamine 1 (P1) and the family of protamine 2 (P2) proteins. Alterations in protamine PTMs or the P1/P2 ratio may be associated with male infertility. Top-down proteomics enables large-scale analysis of intact proteoforms derived from alternative splicing, missense or nonsense genetic variants or PTMs. In contrast to current gold standard techniques, top-down proteomics permits a more in-depth analysis of protamine PTMs and proteoforms, thereby opening up new perspectives to unravel their impact on male fertility. We report on the analysis of two normozoospermic semen samples by top-down proteomics. We discuss the difficulties encountered with the data analysis and propose solutions as this step is one of the current bottlenecks in top-down proteomics with the bioinformatics tools currently available. Our strategy for the data analysis combines two software packages, ProSight PD (PS) and TopPIC suite (TP), with a clustering algorithm to decipher protamine proteoforms. We identified up to 32 protamine proteoforms at different levels of characterization. This in-depth analysis of the protamine proteoform landscape of normozoospermic individuals represents the first step towards the future study of sperm pathological conditions opening up the potential personalized diagnosis of male infertility. MDPI 2021-04-30 /pmc/articles/PMC8162566/ /pubmed/33946530 http://dx.doi.org/10.3390/proteomes9020021 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Arauz-Garofalo, Gianluca Jodar, Meritxell Vilanova, Mar de la Iglesia Rodriguez, Alberto Castillo, Judit Soler-Ventura, Ada Oliva, Rafael Vilaseca, Marta Gay, Marina Protamine Characterization by Top-Down Proteomics: Boosting Proteoform Identification with DBSCAN |
title | Protamine Characterization by Top-Down Proteomics: Boosting Proteoform Identification with DBSCAN |
title_full | Protamine Characterization by Top-Down Proteomics: Boosting Proteoform Identification with DBSCAN |
title_fullStr | Protamine Characterization by Top-Down Proteomics: Boosting Proteoform Identification with DBSCAN |
title_full_unstemmed | Protamine Characterization by Top-Down Proteomics: Boosting Proteoform Identification with DBSCAN |
title_short | Protamine Characterization by Top-Down Proteomics: Boosting Proteoform Identification with DBSCAN |
title_sort | protamine characterization by top-down proteomics: boosting proteoform identification with dbscan |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8162566/ https://www.ncbi.nlm.nih.gov/pubmed/33946530 http://dx.doi.org/10.3390/proteomes9020021 |
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