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Shotgun proteomics of peach fruit reveals major metabolic pathways associated to ripening
BACKGROUND: Fruit ripening in Prunus persica melting varieties involves several physiological changes that have a direct impact on the fruit organoleptic quality and storage potential. By studying the proteomic differences between the mesocarp of mature and ripe fruit, it would be possible to highli...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7788829/ https://www.ncbi.nlm.nih.gov/pubmed/33413072 http://dx.doi.org/10.1186/s12864-020-07299-y |
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author | Nilo-Poyanco, Ricardo Moraga, Carol Benedetto, Gianfranco Orellana, Ariel Almeida, Andrea Miyasaka |
author_facet | Nilo-Poyanco, Ricardo Moraga, Carol Benedetto, Gianfranco Orellana, Ariel Almeida, Andrea Miyasaka |
author_sort | Nilo-Poyanco, Ricardo |
collection | PubMed |
description | BACKGROUND: Fruit ripening in Prunus persica melting varieties involves several physiological changes that have a direct impact on the fruit organoleptic quality and storage potential. By studying the proteomic differences between the mesocarp of mature and ripe fruit, it would be possible to highlight critical molecular processes involved in the fruit ripening. RESULTS: To accomplish this goal, the proteome from mature and ripe fruit was assessed from the variety O’Henry through shotgun proteomics using 1D-gel (PAGE-SDS) as fractionation method followed by LC/MS-MS analysis. Data from the 131,435 spectra could be matched to 2740 proteins, using the peach genome reference v1. After data pre-treatment, 1663 proteins could be used for comparison with datasets assessed using transcriptomic approaches and for quantitative protein accumulation analysis. Close to 26% of the genes that code for the proteins assessed displayed higher expression at ripe fruit compared to other fruit developmental stages, based on published transcriptomic data. Differential accumulation analysis between mature and ripe fruit revealed that 15% of the proteins identified were modulated by the ripening process, with glycogen and isocitrate metabolism, and protein localization overrepresented in mature fruit, as well as cell wall modification in ripe fruit. Potential biomarkers for the ripening process, due to their differential accumulation and gene expression pattern, included a pectin methylesterase inhibitor, a gibbellerin 2-beta-dioxygenase, an omega-6 fatty acid desaturase, a homeobox-leucine zipper protein and an ACC oxidase. Transcription factors enriched in NAC and Myb protein domains would target preferentially the genes encoding proteins more abundant in mature and ripe fruit, respectively. CONCLUSIONS: Shotgun proteomics is an unbiased approach to get deeper into the proteome allowing to detect differences in protein abundance between samples. This technique provided a resolution so that individual gene products could be identified. Many proteins likely involved in cell wall and sugar metabolism, aroma and color, change their abundance during the transition from mature to ripe fruit. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-020-07299-y. |
format | Online Article Text |
id | pubmed-7788829 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-77888292021-01-07 Shotgun proteomics of peach fruit reveals major metabolic pathways associated to ripening Nilo-Poyanco, Ricardo Moraga, Carol Benedetto, Gianfranco Orellana, Ariel Almeida, Andrea Miyasaka BMC Genomics Research Article BACKGROUND: Fruit ripening in Prunus persica melting varieties involves several physiological changes that have a direct impact on the fruit organoleptic quality and storage potential. By studying the proteomic differences between the mesocarp of mature and ripe fruit, it would be possible to highlight critical molecular processes involved in the fruit ripening. RESULTS: To accomplish this goal, the proteome from mature and ripe fruit was assessed from the variety O’Henry through shotgun proteomics using 1D-gel (PAGE-SDS) as fractionation method followed by LC/MS-MS analysis. Data from the 131,435 spectra could be matched to 2740 proteins, using the peach genome reference v1. After data pre-treatment, 1663 proteins could be used for comparison with datasets assessed using transcriptomic approaches and for quantitative protein accumulation analysis. Close to 26% of the genes that code for the proteins assessed displayed higher expression at ripe fruit compared to other fruit developmental stages, based on published transcriptomic data. Differential accumulation analysis between mature and ripe fruit revealed that 15% of the proteins identified were modulated by the ripening process, with glycogen and isocitrate metabolism, and protein localization overrepresented in mature fruit, as well as cell wall modification in ripe fruit. Potential biomarkers for the ripening process, due to their differential accumulation and gene expression pattern, included a pectin methylesterase inhibitor, a gibbellerin 2-beta-dioxygenase, an omega-6 fatty acid desaturase, a homeobox-leucine zipper protein and an ACC oxidase. Transcription factors enriched in NAC and Myb protein domains would target preferentially the genes encoding proteins more abundant in mature and ripe fruit, respectively. CONCLUSIONS: Shotgun proteomics is an unbiased approach to get deeper into the proteome allowing to detect differences in protein abundance between samples. This technique provided a resolution so that individual gene products could be identified. Many proteins likely involved in cell wall and sugar metabolism, aroma and color, change their abundance during the transition from mature to ripe fruit. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-020-07299-y. BioMed Central 2021-01-06 /pmc/articles/PMC7788829/ /pubmed/33413072 http://dx.doi.org/10.1186/s12864-020-07299-y Text en © The Author(s) 2021 Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Nilo-Poyanco, Ricardo Moraga, Carol Benedetto, Gianfranco Orellana, Ariel Almeida, Andrea Miyasaka Shotgun proteomics of peach fruit reveals major metabolic pathways associated to ripening |
title | Shotgun proteomics of peach fruit reveals major metabolic pathways associated to ripening |
title_full | Shotgun proteomics of peach fruit reveals major metabolic pathways associated to ripening |
title_fullStr | Shotgun proteomics of peach fruit reveals major metabolic pathways associated to ripening |
title_full_unstemmed | Shotgun proteomics of peach fruit reveals major metabolic pathways associated to ripening |
title_short | Shotgun proteomics of peach fruit reveals major metabolic pathways associated to ripening |
title_sort | shotgun proteomics of peach fruit reveals major metabolic pathways associated to ripening |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7788829/ https://www.ncbi.nlm.nih.gov/pubmed/33413072 http://dx.doi.org/10.1186/s12864-020-07299-y |
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