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Proteomic and Metabolomic Evaluation of Insect- and Herbicide-Resistant Maize Seeds

Label-free quantitative proteomic (LFQ) and widely targeted metabolomic analyses were applied in the safety evaluation of three genetically modified (GM) maize varieties, BBL, BFL-1, and BFL-2, in addition to their corresponding non-GM parent maize. A total of 76, 40, and 25 differentially expressed...

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Autores principales: Liu, Weixiao, Meng, Lixia, Zhao, Weiling, Wang, Zhanchao, Miao, Chaohua, Wan, Yusong, Jin, Wujun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9696663/
https://www.ncbi.nlm.nih.gov/pubmed/36355161
http://dx.doi.org/10.3390/metabo12111078
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author Liu, Weixiao
Meng, Lixia
Zhao, Weiling
Wang, Zhanchao
Miao, Chaohua
Wan, Yusong
Jin, Wujun
author_facet Liu, Weixiao
Meng, Lixia
Zhao, Weiling
Wang, Zhanchao
Miao, Chaohua
Wan, Yusong
Jin, Wujun
author_sort Liu, Weixiao
collection PubMed
description Label-free quantitative proteomic (LFQ) and widely targeted metabolomic analyses were applied in the safety evaluation of three genetically modified (GM) maize varieties, BBL, BFL-1, and BFL-2, in addition to their corresponding non-GM parent maize. A total of 76, 40, and 25 differentially expressed proteins (DEPs) were screened out in BBL, BFL-1, and BFL-2, respectively, and their abundance compared was with that in their non-GM parents. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed that most of the DEPs participate in biosynthesis of secondary metabolites, biosynthesis of amino acids, and metabolic pathways. Metabolomic analyses revealed 145, 178, and 88 differentially accumulated metabolites (DAMs) in the BBL/ZH58, BFL-1/ZH58, and BFL-2/ZH58×CH72 comparisons, respectively. KEGG pathway enrichment analysis showed that most of the DAMs are involved in biosynthesis of amino acids, and in arginine and proline metabolism. Three co-DEPs and 11 co-DAMs were identified in the seeds of these GM maize lines. The proteomic profiling of seeds showed that the GM maize varieties were not dramatically different from their non-GM control. Similarly, the metabolomic profiling of seeds showed no dramatic changes in the GM/non-GM maize varieties compared with the GM/GM and non-GM/non-GM maize varieties. The genetic background of the transgenic maize was found to have some influence on its proteomic and metabolomic profiles.
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spelling pubmed-96966632022-11-26 Proteomic and Metabolomic Evaluation of Insect- and Herbicide-Resistant Maize Seeds Liu, Weixiao Meng, Lixia Zhao, Weiling Wang, Zhanchao Miao, Chaohua Wan, Yusong Jin, Wujun Metabolites Article Label-free quantitative proteomic (LFQ) and widely targeted metabolomic analyses were applied in the safety evaluation of three genetically modified (GM) maize varieties, BBL, BFL-1, and BFL-2, in addition to their corresponding non-GM parent maize. A total of 76, 40, and 25 differentially expressed proteins (DEPs) were screened out in BBL, BFL-1, and BFL-2, respectively, and their abundance compared was with that in their non-GM parents. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed that most of the DEPs participate in biosynthesis of secondary metabolites, biosynthesis of amino acids, and metabolic pathways. Metabolomic analyses revealed 145, 178, and 88 differentially accumulated metabolites (DAMs) in the BBL/ZH58, BFL-1/ZH58, and BFL-2/ZH58×CH72 comparisons, respectively. KEGG pathway enrichment analysis showed that most of the DAMs are involved in biosynthesis of amino acids, and in arginine and proline metabolism. Three co-DEPs and 11 co-DAMs were identified in the seeds of these GM maize lines. The proteomic profiling of seeds showed that the GM maize varieties were not dramatically different from their non-GM control. Similarly, the metabolomic profiling of seeds showed no dramatic changes in the GM/non-GM maize varieties compared with the GM/GM and non-GM/non-GM maize varieties. The genetic background of the transgenic maize was found to have some influence on its proteomic and metabolomic profiles. MDPI 2022-11-07 /pmc/articles/PMC9696663/ /pubmed/36355161 http://dx.doi.org/10.3390/metabo12111078 Text en © 2022 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
Liu, Weixiao
Meng, Lixia
Zhao, Weiling
Wang, Zhanchao
Miao, Chaohua
Wan, Yusong
Jin, Wujun
Proteomic and Metabolomic Evaluation of Insect- and Herbicide-Resistant Maize Seeds
title Proteomic and Metabolomic Evaluation of Insect- and Herbicide-Resistant Maize Seeds
title_full Proteomic and Metabolomic Evaluation of Insect- and Herbicide-Resistant Maize Seeds
title_fullStr Proteomic and Metabolomic Evaluation of Insect- and Herbicide-Resistant Maize Seeds
title_full_unstemmed Proteomic and Metabolomic Evaluation of Insect- and Herbicide-Resistant Maize Seeds
title_short Proteomic and Metabolomic Evaluation of Insect- and Herbicide-Resistant Maize Seeds
title_sort proteomic and metabolomic evaluation of insect- and herbicide-resistant maize seeds
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9696663/
https://www.ncbi.nlm.nih.gov/pubmed/36355161
http://dx.doi.org/10.3390/metabo12111078
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