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Proteomic and metabolomic analysis of Nicotiana benthamiana under dark stress
Exposure to extended periods of darkness is a common source of abiotic stress that significantly affects plant growth and development. To understand how Nicotiana benthamiana responds to dark stress, the proteomes and metabolomes of leaves treated with darkness were studied. In total, 5763 proteins...
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Published in: | FEBS open bio 2022-01, Vol.12 (1), p.231-249 |
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description | Exposure to extended periods of darkness is a common source of abiotic stress that significantly affects plant growth and development. To understand how Nicotiana benthamiana responds to dark stress, the proteomes and metabolomes of leaves treated with darkness were studied. In total, 5763 proteins and 165 primary metabolites were identified following dark treatment. Additionally, the expression of autophagy‐related gene (ATG) proteins was transiently upregulated. Weighted gene coexpression network analysis (WGCNA) was utilized to find the protein modules associated with the response to dark stress. A total of four coexpression modules were obtained. The results indicated that heat‐shock protein (HSP70), SnRK1‐interacting protein 1, 2A phosphatase‐associated protein of 46 kDa (Tap46), and glutamate dehydrogenase (GDH) might play crucial roles in N. benthamiana’s response to dark stress. Furthermore, a protein–protein interaction (PPI) network was constructed and top‐degreed proteins were predicted to identify potential key factors in the response to dark stress. These proteins include isopropylmalate isomerase (IPMI), eukaryotic elongation factor 5A (ELF5A), and ribosomal protein 5A (RPS5A). Finally, metabolic analysis suggested that some amino acids and sugars were involved in the dark‐responsive pathways. Thus, these results provide a new avenue for understanding the defensive mechanism against dark stress at the protein and metabolic levels in N. benthamiana.
Exposure to prolonged periods of darkness can affect plant growth and development. In this study, the response of Nicotiana benthamiana to dark stress was investigated by analyzing changes to the proteome and metabolome across 13 time points. A number of hub proteins were filtered through weighted gene coexpression network analysis to identify potential key proteins involved in the dark stress response. |
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Exposure to prolonged periods of darkness can affect plant growth and development. In this study, the response of Nicotiana benthamiana to dark stress was investigated by analyzing changes to the proteome and metabolome across 13 time points. A number of hub proteins were filtered through weighted gene coexpression network analysis to identify potential key proteins involved in the dark stress response.</description><identifier>ISSN: 2211-5463</identifier><identifier>EISSN: 2211-5463</identifier><identifier>DOI: 10.1002/2211-5463.13331</identifier><identifier>PMID: 34792288</identifier><language>eng</language><publisher>England: John Wiley & Sons, Inc</publisher><subject>Amino acids ; Autophagy ; Chloroplasts ; Chromatography ; dark stress ; Gene Regulatory Networks ; Glutamate dehydrogenase ; Hsp70 protein ; Mass spectrometry ; Metabolism ; Metabolites ; Metabolome ; Metabolomics ; Nicotiana - genetics ; Nicotiana - metabolism ; Nicotiana benthamiana ; Phosphatase ; Plant Leaves - metabolism ; Proteins ; Proteome ; Proteomes ; proteomic ; Proteomics ; Scientific imaging ; Signal transduction ; Variance analysis ; weighted gene coexpression network analysis</subject><ispartof>FEBS open bio, 2022-01, Vol.12 (1), p.231-249</ispartof><rights>2021 The Authors. published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.</rights><rights>2021 The Authors. FEBS Open Bio published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.</rights><rights>2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c6011-cc1ec71789600a6a031d814f67a6b4ec97c81bf88d373fb4b38f9a24e7f097703</citedby><cites>FETCH-LOGICAL-c6011-cc1ec71789600a6a031d814f67a6b4ec97c81bf88d373fb4b38f9a24e7f097703</cites><orcidid>0000-0003-3852-1293</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2616512138/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2616512138?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,11562,25753,27924,27925,37012,37013,44590,46052,46476,53791,53793,75126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34792288$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Shen, Juan‐Juan</creatorcontrib><creatorcontrib>Chen, Qian‐Si</creatorcontrib><creatorcontrib>Li, Ze‐Feng</creatorcontrib><creatorcontrib>Zheng, Qing‐Xia</creatorcontrib><creatorcontrib>Xu, Ya‐Long</creatorcontrib><creatorcontrib>Zhou, Hui‐Na</creatorcontrib><creatorcontrib>Mao, Hong‐Yan</creatorcontrib><creatorcontrib>Shen, Qi</creatorcontrib><creatorcontrib>Liu, Ping‐Ping</creatorcontrib><title>Proteomic and metabolomic analysis of Nicotiana benthamiana under dark stress</title><title>FEBS open bio</title><addtitle>FEBS Open Bio</addtitle><description>Exposure to extended periods of darkness is a common source of abiotic stress that significantly affects plant growth and development. To understand how Nicotiana benthamiana responds to dark stress, the proteomes and metabolomes of leaves treated with darkness were studied. In total, 5763 proteins and 165 primary metabolites were identified following dark treatment. Additionally, the expression of autophagy‐related gene (ATG) proteins was transiently upregulated. Weighted gene coexpression network analysis (WGCNA) was utilized to find the protein modules associated with the response to dark stress. A total of four coexpression modules were obtained. The results indicated that heat‐shock protein (HSP70), SnRK1‐interacting protein 1, 2A phosphatase‐associated protein of 46 kDa (Tap46), and glutamate dehydrogenase (GDH) might play crucial roles in N. benthamiana’s response to dark stress. Furthermore, a protein–protein interaction (PPI) network was constructed and top‐degreed proteins were predicted to identify potential key factors in the response to dark stress. These proteins include isopropylmalate isomerase (IPMI), eukaryotic elongation factor 5A (ELF5A), and ribosomal protein 5A (RPS5A). Finally, metabolic analysis suggested that some amino acids and sugars were involved in the dark‐responsive pathways. Thus, these results provide a new avenue for understanding the defensive mechanism against dark stress at the protein and metabolic levels in N. benthamiana.
Exposure to prolonged periods of darkness can affect plant growth and development. In this study, the response of Nicotiana benthamiana to dark stress was investigated by analyzing changes to the proteome and metabolome across 13 time points. A number of hub proteins were filtered through weighted gene coexpression network analysis to identify potential key proteins involved in the dark stress response.</description><subject>Amino acids</subject><subject>Autophagy</subject><subject>Chloroplasts</subject><subject>Chromatography</subject><subject>dark stress</subject><subject>Gene Regulatory Networks</subject><subject>Glutamate dehydrogenase</subject><subject>Hsp70 protein</subject><subject>Mass spectrometry</subject><subject>Metabolism</subject><subject>Metabolites</subject><subject>Metabolome</subject><subject>Metabolomics</subject><subject>Nicotiana - genetics</subject><subject>Nicotiana - metabolism</subject><subject>Nicotiana benthamiana</subject><subject>Phosphatase</subject><subject>Plant Leaves - metabolism</subject><subject>Proteins</subject><subject>Proteome</subject><subject>Proteomes</subject><subject>proteomic</subject><subject>Proteomics</subject><subject>Scientific imaging</subject><subject>Signal transduction</subject><subject>Variance analysis</subject><subject>weighted gene coexpression network analysis</subject><issn>2211-5463</issn><issn>2211-5463</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNqFkc1vFCEYh4nR2Kb27M1M4sXLtnwtMBcTbVptUj8OeiZ8vLSsM0OFGc3-9zI766b1Ihfg5eHJCz-EXhJ8RjCm55QSslpzwc4IY4w8QceHytMH6yN0WsoG1yEwERg_R0eMy5ZSpY7Rp685jZD66Boz-KaH0djU7fem25ZYmhSaz9GlMdZKY2EY70y_W0-Dh9x4k380ZcxQygv0LJiuwOl-PkHfry6_XXxc3Xz5cH3x7mblagtk5RwBJ4lUbW3HCIMZ8YrwIKQRloNrpVPEBqU8kyxYbpkKraEcZMCtlJidoOvF65PZ6Psce5O3Opmod4WUb7XJY3QdaCOdVZ57ySXhnlnVSgWcChEYgA2z6-3iup9sD97V92XTPZI-Phninb5Nv7SSVLZ8FrzZC3L6OUEZdR-Lg64zA6SpaLpuWywVYzP6-h90k6Zc_7lSgog1oYSpSp0vlMuplAzh0AzBek5ez9nqOVu9S77eePXwDQf-b84VEAvwO3aw_Z9PX12-54v5D-KGt5M</recordid><startdate>202201</startdate><enddate>202201</enddate><creator>Shen, Juan‐Juan</creator><creator>Chen, Qian‐Si</creator><creator>Li, Ze‐Feng</creator><creator>Zheng, Qing‐Xia</creator><creator>Xu, Ya‐Long</creator><creator>Zhou, Hui‐Na</creator><creator>Mao, Hong‐Yan</creator><creator>Shen, Qi</creator><creator>Liu, Ping‐Ping</creator><general>John Wiley & Sons, Inc</general><general>John Wiley and Sons Inc</general><general>Wiley</general><scope>24P</scope><scope>WIN</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FH</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>LK8</scope><scope>M7P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0003-3852-1293</orcidid></search><sort><creationdate>202201</creationdate><title>Proteomic and metabolomic analysis of Nicotiana benthamiana under dark stress</title><author>Shen, Juan‐Juan ; 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To understand how Nicotiana benthamiana responds to dark stress, the proteomes and metabolomes of leaves treated with darkness were studied. In total, 5763 proteins and 165 primary metabolites were identified following dark treatment. Additionally, the expression of autophagy‐related gene (ATG) proteins was transiently upregulated. Weighted gene coexpression network analysis (WGCNA) was utilized to find the protein modules associated with the response to dark stress. A total of four coexpression modules were obtained. The results indicated that heat‐shock protein (HSP70), SnRK1‐interacting protein 1, 2A phosphatase‐associated protein of 46 kDa (Tap46), and glutamate dehydrogenase (GDH) might play crucial roles in N. benthamiana’s response to dark stress. Furthermore, a protein–protein interaction (PPI) network was constructed and top‐degreed proteins were predicted to identify potential key factors in the response to dark stress. These proteins include isopropylmalate isomerase (IPMI), eukaryotic elongation factor 5A (ELF5A), and ribosomal protein 5A (RPS5A). Finally, metabolic analysis suggested that some amino acids and sugars were involved in the dark‐responsive pathways. Thus, these results provide a new avenue for understanding the defensive mechanism against dark stress at the protein and metabolic levels in N. benthamiana.
Exposure to prolonged periods of darkness can affect plant growth and development. In this study, the response of Nicotiana benthamiana to dark stress was investigated by analyzing changes to the proteome and metabolome across 13 time points. A number of hub proteins were filtered through weighted gene coexpression network analysis to identify potential key proteins involved in the dark stress response.</abstract><cop>England</cop><pub>John Wiley & Sons, Inc</pub><pmid>34792288</pmid><doi>10.1002/2211-5463.13331</doi><tpages>249</tpages><orcidid>https://orcid.org/0000-0003-3852-1293</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Amino acids Autophagy Chloroplasts Chromatography dark stress Gene Regulatory Networks Glutamate dehydrogenase Hsp70 protein Mass spectrometry Metabolism Metabolites Metabolome Metabolomics Nicotiana - genetics Nicotiana - metabolism Nicotiana benthamiana Phosphatase Plant Leaves - metabolism Proteins Proteome Proteomes proteomic Proteomics Scientific imaging Signal transduction Variance analysis weighted gene coexpression network analysis |
title | Proteomic and metabolomic analysis of Nicotiana benthamiana under dark stress |
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