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Yu B, Liang Y, Qin Q, Zhao Y, Yang C, Liu R, Gan Y, Zhou H, Qiu Z, Chen L, Yan S, Cao B. Transcription Cofactor CsMBF1c Enhances Heat Tolerance of Cucumber and Interacts with Heat-Related Proteins CsNFYA1 and CsDREB2. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2024; 72:15586-15600. [PMID: 38949485 DOI: 10.1021/acs.jafc.4c02398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
Multiprotein bridging factor 1 (MBF1) is a very important transcription factor (TF) in plants, whose members influence numerous defense responses. Our study found that MBF1c in Cucurbitaceae was highly conserved. CsMBF1c expression was induced by temperature, salt stress, and abscisic acid (ABA) in cucumber. Overexpressed CsMBF1c enhanced the heat resistance of a cucumber, and the Csmbf1c mutant showed decreased resistance to high temperatures (HTs). CsMBF1c played an important role in stabilizing the photosynthetic system of cucumber under HT, and its expression was significantly associated with heat-related TFs and genes related to protein processing in the endoplasmic reticulum (ER). Protein interaction showed that CsMBF1c interacted with dehydration-responsive element binding protein 2 (CsDREB2) and nuclear factor Y A1 (CsNFYA1). Overexpression of CsNFYA1 in Arabidopsis improved the heat resistance. Transcriptional activation of CsNFYA1 was elevated by CsMBF1c. Therefore, CsMBF1c plays an important regulatory role in cucumber's resistance to high temperatures.
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Affiliation(s)
- Bingwei Yu
- Key Laboratory of Biology and Genetic Improvement of Horticultural Crops, Ministry of Agriculture and Rural Affairs/Guangdong Vegetable Engineering and Technology Research Center/Lingnan Guangdong Laboratory of Modern Agriculture, College of Horticulture, South China Agricultural University, Guangzhou 510642, China
- School of Biology and Agriculture, Shaoguan University, Shaoguan 512005, China
| | - Yonggui Liang
- Key Laboratory of Biology and Genetic Improvement of Horticultural Crops, Ministry of Agriculture and Rural Affairs/Guangdong Vegetable Engineering and Technology Research Center/Lingnan Guangdong Laboratory of Modern Agriculture, College of Horticulture, South China Agricultural University, Guangzhou 510642, China
| | - Qiteng Qin
- Key Laboratory of Biology and Genetic Improvement of Horticultural Crops, Ministry of Agriculture and Rural Affairs/Guangdong Vegetable Engineering and Technology Research Center/Lingnan Guangdong Laboratory of Modern Agriculture, College of Horticulture, South China Agricultural University, Guangzhou 510642, China
| | - Yafei Zhao
- Key Laboratory of Biology and Genetic Improvement of Horticultural Crops, Ministry of Agriculture and Rural Affairs/Guangdong Vegetable Engineering and Technology Research Center/Lingnan Guangdong Laboratory of Modern Agriculture, College of Horticulture, South China Agricultural University, Guangzhou 510642, China
| | - Chenyu Yang
- Key Laboratory of Biology and Genetic Improvement of Horticultural Crops, Ministry of Agriculture and Rural Affairs/Guangdong Vegetable Engineering and Technology Research Center/Lingnan Guangdong Laboratory of Modern Agriculture, College of Horticulture, South China Agricultural University, Guangzhou 510642, China
| | - Renjian Liu
- Key Laboratory of Biology and Genetic Improvement of Horticultural Crops, Ministry of Agriculture and Rural Affairs/Guangdong Vegetable Engineering and Technology Research Center/Lingnan Guangdong Laboratory of Modern Agriculture, College of Horticulture, South China Agricultural University, Guangzhou 510642, China
| | - Yuwei Gan
- Key Laboratory of Biology and Genetic Improvement of Horticultural Crops, Ministry of Agriculture and Rural Affairs/Guangdong Vegetable Engineering and Technology Research Center/Lingnan Guangdong Laboratory of Modern Agriculture, College of Horticulture, South China Agricultural University, Guangzhou 510642, China
| | - Huoyan Zhou
- Key Laboratory of Biology and Genetic Improvement of Horticultural Crops, Ministry of Agriculture and Rural Affairs/Guangdong Vegetable Engineering and Technology Research Center/Lingnan Guangdong Laboratory of Modern Agriculture, College of Horticulture, South China Agricultural University, Guangzhou 510642, China
| | - Zhengkun Qiu
- Key Laboratory of Biology and Genetic Improvement of Horticultural Crops, Ministry of Agriculture and Rural Affairs/Guangdong Vegetable Engineering and Technology Research Center/Lingnan Guangdong Laboratory of Modern Agriculture, College of Horticulture, South China Agricultural University, Guangzhou 510642, China
| | - Letian Chen
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, College of Life Sciences, South China Agricultural University, Guangzhou 510642, China
| | - Shuangshuang Yan
- Key Laboratory of Biology and Genetic Improvement of Horticultural Crops, Ministry of Agriculture and Rural Affairs/Guangdong Vegetable Engineering and Technology Research Center/Lingnan Guangdong Laboratory of Modern Agriculture, College of Horticulture, South China Agricultural University, Guangzhou 510642, China
| | - Bihao Cao
- Key Laboratory of Biology and Genetic Improvement of Horticultural Crops, Ministry of Agriculture and Rural Affairs/Guangdong Vegetable Engineering and Technology Research Center/Lingnan Guangdong Laboratory of Modern Agriculture, College of Horticulture, South China Agricultural University, Guangzhou 510642, China
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Carrasco JL, Ambrós S, Gutiérrez PA, Elena SF. Adaptation of turnip mosaic virus to Arabidopsis thaliana involves rewiring of VPg-host proteome interactions. Virus Evol 2024; 10:veae055. [PMID: 39091990 PMCID: PMC11291303 DOI: 10.1093/ve/veae055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Revised: 05/23/2024] [Accepted: 07/16/2024] [Indexed: 08/04/2024] Open
Abstract
The outcome of a viral infection depends on a complex interplay between the host physiology and the virus, mediated through numerous protein-protein interactions. In a previous study, we used high-throughput yeast two-hybrid (HT-Y2H) to identify proteins in Arabidopsis thaliana that bind to the proteins encoded by the turnip mosaic virus (TuMV) genome. Furthermore, after experimental evolution of TuMV lineages in plants with mutations in defense-related or proviral genes, most mutations observed in the evolved viruses affected the VPg cistron. Among these mutations, D113G was a convergent mutation selected in many lineages across different plant genotypes, including cpr5-2 with constitutive expression of systemic acquired resistance. In contrast, mutation R118H specifically emerged in the jin1 mutant with affected jasmonate signaling. Using the HT-Y2H system, we analyzed the impact of these two mutations on VPg's interaction with plant proteins. Interestingly, both mutations severely compromised the interaction of VPg with the translation initiation factor eIF(iso)4E, a crucial interactor for potyvirus infection. Moreover, mutation D113G, but not R118H, adversely affected the interaction with RHD1, a zinc-finger homeodomain transcription factor involved in regulating DNA demethylation. Our results suggest that RHD1 enhances plant tolerance to TuMV infection. We also discuss our findings in a broad virus evolution context.
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Affiliation(s)
- José L Carrasco
- Instituto de Biología Integrativa de Sistemas (CSIC—Universitat de València), Catedratico Agustin Escardino 9, Paterna, València 46182, Spain
| | - Silvia Ambrós
- Instituto de Biología Integrativa de Sistemas (CSIC—Universitat de València), Catedratico Agustin Escardino 9, Paterna, València 46182, Spain
| | - Pablo A Gutiérrez
- Laboratorio de Microbiología Industrial, Facultad de Ciencias, Universidad Nacional de Colombia, Carrera 65 Nro. 59A - 110, Medellín, Antioquia 050034, Colombia
| | - Santiago F Elena
- Instituto de Biología Integrativa de Sistemas (CSIC—Universitat de València), Catedratico Agustin Escardino 9, Paterna, València 46182, Spain
- The Santa Fe Institute, 1399 Hyde Park Rd, Santa Fe, NM 87501, United States
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3
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Sukko N, Kalapanulak S, Saithong T. Trehalose metabolism coordinates transcriptional regulatory control and metabolic requirements to trigger the onset of cassava storage root initiation. Sci Rep 2023; 13:19973. [PMID: 37968317 PMCID: PMC10651926 DOI: 10.1038/s41598-023-47095-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Accepted: 11/09/2023] [Indexed: 11/17/2023] Open
Abstract
Cassava storage roots (SR) are an important source of food energy and raw material for a wide range of applications. Understanding SR initiation and the associated regulation is critical to boosting tuber yield in cassava. Decades of transcriptome studies have identified key regulators relevant to SR formation, transcriptional regulation and sugar metabolism. However, there remain uncertainties over the roles of the regulators in modulating the onset of SR development owing to the limitation of the widely applied differential gene expression analysis. Here, we aimed to investigate the regulation underlying the transition from fibrous (FR) to SR based on Dynamic Network Biomarker (DNB) analysis. Gene expression analysis during cassava root initiation showed the transition period to SR happened in FR during 8 weeks after planting (FR8). Ninety-nine DNB genes associated with SR initiation and development were identified. Interestingly, the role of trehalose metabolism, especially trehalase1 (TRE1), in modulating metabolites abundance and coordinating regulatory signaling and carbon substrate availability via the connection of transcriptional regulation and sugar metabolism was highlighted. The results agree with the associated DNB characters of TRE1 reported in other transcriptome studies of cassava SR initiation and Attre1 loss of function in literature. The findings help fill the knowledge gap regarding the regulation underlying cassava SR initiation.
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Affiliation(s)
- Nattavat Sukko
- Bioinformatics and Systems Biology Program, School of Bioresources and Technology and School of Information Technology, King Mongkut's University of Technology Thonburi (Bang Khun Thian), Bangkok, 10150, Thailand
| | - Saowalak Kalapanulak
- Bioinformatics and Systems Biology Program, School of Bioresources and Technology and School of Information Technology, King Mongkut's University of Technology Thonburi (Bang Khun Thian), Bangkok, 10150, Thailand.
- School of Bioresources and Technology, King Mongkut's University of Technology Thonburi (Bang Khun Thian), Bangkok, 10150, Thailand.
- Center for Agricultural Systems Biology, Systems Biology and Bioinformatics Research Group, Pilot Plant Development and Training Institute, King Mongkut's University of Technology Thonburi (Bang Khun Thian), Bangkok, 10150, Thailand.
| | - Treenut Saithong
- Bioinformatics and Systems Biology Program, School of Bioresources and Technology and School of Information Technology, King Mongkut's University of Technology Thonburi (Bang Khun Thian), Bangkok, 10150, Thailand.
- School of Bioresources and Technology, King Mongkut's University of Technology Thonburi (Bang Khun Thian), Bangkok, 10150, Thailand.
- Center for Agricultural Systems Biology, Systems Biology and Bioinformatics Research Group, Pilot Plant Development and Training Institute, King Mongkut's University of Technology Thonburi (Bang Khun Thian), Bangkok, 10150, Thailand.
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Mäkinen K, Aspelin W, Pollari M, Wang L. How do they do it? The infection biology of potyviruses. Adv Virus Res 2023; 117:1-79. [PMID: 37832990 DOI: 10.1016/bs.aivir.2023.07.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2023]
Affiliation(s)
- Kristiina Mäkinen
- Department of Agricultural Sciences, Viikki Plant Science Centre, University of Helsinki, Helsinki, Finland.
| | - William Aspelin
- Department of Agricultural Sciences, Viikki Plant Science Centre, University of Helsinki, Helsinki, Finland
| | - Maija Pollari
- Department of Agricultural Sciences, Viikki Plant Science Centre, University of Helsinki, Helsinki, Finland
| | - Linping Wang
- Department of Agricultural Sciences, Viikki Plant Science Centre, University of Helsinki, Helsinki, Finland
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Cohen AA, Leung DL, Legault V, Gravel D, Blanchet FG, Côté AM, Fülöp T, Lee J, Dufour F, Liu M, Nakazato Y. Synchrony of biomarker variability indicates a critical transition: Application to mortality prediction in hemodialysis. iScience 2022; 25:104385. [PMID: 35620427 PMCID: PMC9127602 DOI: 10.1016/j.isci.2022.104385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Revised: 03/22/2022] [Accepted: 05/05/2022] [Indexed: 12/03/2022] Open
Abstract
Critical transition theory suggests that complex systems should experience increased temporal variability just before abrupt state changes. We tested this hypothesis in 763 patients on long-term hemodialysis, using 11 biomarkers collected every two weeks and all-cause mortality as a proxy for critical transitions. We find that variability-measured by coefficients of variation (CVs)-increases before death for all 11 clinical biomarkers, and is strikingly synchronized across all biomarkers: the first axis of a principal component analysis on all CVs explains 49% of the variance. This axis then generates powerful predictions of mortality (HR95 = 9.7, p < 0.0001, where HR95 is a scale-invariant metric of hazard ratio; AUC up to 0.82) and starts to increase markedly ∼3 months prior to death. Our results provide an early warning sign of physiological collapse and, more broadly, a quantification of joint system dynamics that opens questions of how system modularity may break down before critical transitions.
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Affiliation(s)
- Alan A. Cohen
- PRIMUS Research Group, Department of Family Medicine, University of Sherbrooke, Sherbrooke, Quebec J1H 5N4, Canada
- Research Center on Aging, Sherbrooke, Quebec J1H 4C4, Canada
- Research Center of Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, Quebec J1H 5N4, Canada
| | - Diana L. Leung
- PRIMUS Research Group, Department of Family Medicine, University of Sherbrooke, Sherbrooke, Quebec J1H 5N4, Canada
| | - Véronique Legault
- PRIMUS Research Group, Department of Family Medicine, University of Sherbrooke, Sherbrooke, Quebec J1H 5N4, Canada
| | - Dominique Gravel
- Département de Biologie, Université de Sherbrooke, Sherbrooke, Quebec J1K 2R1, Canada
| | - F. Guillaume Blanchet
- Research Center on Aging, Sherbrooke, Quebec J1H 4C4, Canada
- Département de Biologie, Université de Sherbrooke, Sherbrooke, Quebec J1K 2R1, Canada
- Département de mathématique, Université de Sherbrooke, Sherbrooke, Québec J1K 2R1, Canada
- Département des Sciences de la Santé Communautaires, Université de Sherbrooke, Sherbrooke, Québec J1H 5N4, Canada
| | - Anne-Marie Côté
- Department of Medicine, Nephrology Division, University of Sherbrooke, Sherbrooke, Quebec J1H 5N4, Canada
| | - Tamàs Fülöp
- Research Center on Aging, Sherbrooke, Quebec J1H 4C4, Canada
- Department of Medicine, Geriatric Division, University of Sherbrooke, Sherbrooke, Quebec J1H 5N4, Canada
| | - Juhong Lee
- InfoCentre, Centre intégré universitaire de santé et de services sociaux de l’Estrie – Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, Quebec J1H 5N4, Canada
| | - Frédérik Dufour
- PRIMUS Research Group, Department of Family Medicine, University of Sherbrooke, Sherbrooke, Quebec J1H 5N4, Canada
- Département de Biologie, Université de Sherbrooke, Sherbrooke, Quebec J1K 2R1, Canada
| | - Mingxin Liu
- PRIMUS Research Group, Department of Family Medicine, University of Sherbrooke, Sherbrooke, Quebec J1H 5N4, Canada
| | - Yuichi Nakazato
- Division of Nephrology, Hakuyukai Medical Corporation, Yuai Nisshin Clinic, 2-1914-6 Nisshin-cho, Kita-ku, Saitama-City, Saitama 331-0823, Japan
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Lin S, Lin Y, Wu K, Wang Y, Feng Z, Duan M, Liu S, Fan Y, Huang L, Zhou F. FeCO3, constructing the network biomarkers using the inter-feature correlation coefficients and its application in detecting high-order breast cancer biomarkers. Curr Bioinform 2022. [DOI: 10.2174/1574893617666220124123303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Aims:
This study aims to formulate the inter-feature correlation as the engineered features.
Background:
Modern biotechnologies tend to generate a huge number of characteristics of a sample, while an OMIC dataset usually has a few dozens or hundreds of samples due to the high costs of generating the OMIC data. So many bio-OMIC studies assumed the inter-feature independence and selected a feature with a high phenotype-association.
Objective:
However, many features are closely associated with each other due to their physical or functional interactions, which may be utilized as a new view of features.
Method:
This study proposed a feature engineering algorithm based on the correlation coefficients (FeCO3) by utilizing the correlations between a given sample and a few reference samples. A comprehensive evaluation was carried out for the proposed FeCO3 network features using 24 bio-OMIC datasets.
Result:
The experimental data suggested that the newly calculated FeCO3 network features tended to achieve better classification performances than the original features, using the same popular feature selection and classification algorithms. The FeCO3 network features were also consistently supported by the literature. FeCO3 was utilized to investigate the high-order engineered biomarkers of breast cancer, and detected the PBX2 gene (Pre-B-Cell Leukemia Transcription Factor 2) as one of the candidate breast cancer biomarkers. Although the two methylated residues cg14851325 (Pvalue=8.06e-2) and cg16602460 (Pvalue=1.19e-1) within PBX2 did not have statistically significant association with breast cancers, the high-order inter-feature correlations showed a significant association with breast cancers.
Conclusion:
The proposed FeCO3 network features calculated the high-order inter-feature correlations as novel features, and may facilitate the investigations of complex diseases from this new perspective. The source code is available in FigShare at 10.6084/m9.figshare.13550051 or the web site http://www.healthinformaticslab.org/supp/ .
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Affiliation(s)
- Shenggeng Lin
- College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin 130012, China
- State Key Laboratory of Microbial Metabolism, and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Yuqi Lin
- College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin 130012, China
| | - Kexin Wu
- College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin 130012, China
| | - Yueying Wang
- College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin 130012, China
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, Jilin Province, China
| | - Zixuan Feng
- College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin 130012, China
| | - Meiyu Duan
- College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin 130012, China
| | - Shuai Liu
- College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin 130012, China
| | - Yusi Fan
- College of Software, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin 130012, China
| | - Lan Huang
- College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin 130012, China
| | - Fengfeng Zhou
- College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin 130012, China
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Solé R, Sardanyés J, Elena SF. Phase transitions in virology. REPORTS ON PROGRESS IN PHYSICS. PHYSICAL SOCIETY (GREAT BRITAIN) 2021; 84:115901. [PMID: 34584031 DOI: 10.1088/1361-6633/ac2ab0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Accepted: 09/28/2021] [Indexed: 06/13/2023]
Abstract
Viruses have established relationships with almost every other living organism on Earth and at all levels of biological organization: from other viruses up to entire ecosystems. In most cases, they peacefully coexist with their hosts, but in most relevant cases, they parasitize them and induce diseases and pandemics, such as the AIDS and the most recent avian influenza and COVID-19 pandemic events, causing a huge impact on health, society, and economy. Viruses play an essential role in shaping the eco-evolutionary dynamics of their hosts, and have been also involved in some of the major evolutionary innovations either by working as vectors of genetic information or by being themselves coopted by the host into their genomes. Viruses can be studied at different levels of biological organization, from the molecular mechanisms of genome replication, gene expression and encapsidation, to global pandemics. All these levels are different and yet connected through the presence of threshold conditions allowing for the formation of a capsid, the loss of genetic information or epidemic spreading. These thresholds, as occurs with temperature separating phases in a liquid, define sharp qualitative types of behaviour. Thesephase transitionsare very well known in physics. They have been studied by means of simple, but powerful models able to capture their essential properties, allowing us to better understand them. Can the physics of phase transitions be an inspiration for our understanding of viral dynamics at different scales? Here we review well-known mathematical models of transition phenomena in virology. We suggest that the advantages of abstract, simplified pictures used in physics are also the key to properly understanding the origins and evolution of complexity in viruses. By means of several examples, we explore this multilevel landscape and how minimal models provide deep insights into a diverse array of problems. The relevance of these transitions in connecting dynamical patterns across scales and their evolutionary and clinical implications are outlined.
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Affiliation(s)
- Ricard Solé
- ICREA-Complex Systems Lab, Universitat Pompeu Fabra-PRBB, Dr Aiguader 80, 08003 Barcelona, Spain
- Institut de Biologia Evolutiva, CSIC-Universitat Pompeu Fabra, Passeig Maritim de la Barceloneta 37, 08003 Barcelona, Spain
- Santa Fe Institute, 1399 Hyde Park Road, Santa Fe NM 87501, United States of America
| | - Josep Sardanyés
- Centre de Recerca Matemàtica (CRM), Edifici C, Campus de Bellaterra, Cerdanyola del Vallès, 08193 Barcelona, Spain
- Dynamical Systems and Computational Virology, CSIC Associated Unit, Institute for Integrative Systems Biology (I2SysBio)-CRM, Spain
| | - Santiago F Elena
- Santa Fe Institute, 1399 Hyde Park Road, Santa Fe NM 87501, United States of America
- Evolutionary Systems Virology Lab (I2SysBio), CSIC-Universitat de València, Catedrático Agustín Escardino 9, Paterna, 46980 València, Spain
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German-Retana S, Mäkinen K. Special Issue: "The Complexity of the Potyviral Interaction Network". Viruses 2020; 12:E874. [PMID: 32796503 PMCID: PMC7472181 DOI: 10.3390/v12080874] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Accepted: 07/23/2020] [Indexed: 11/17/2022] Open
Abstract
Many potyvirus species are among the most economically-significant plant viruses as they cause substantial yield losses to crop plants globally [...].
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Affiliation(s)
- Sylvie German-Retana
- UMR 1332 Biologie du Fruit et Pathologie, INRAE, Univ. Bordeaux, 71 Av. E. Bourlaux, CS 20032, 33882 Villenave d’Ornon Cedex, France
| | - Kristiina Mäkinen
- Department of Microbiology and Viikki Plant Science Centre, University of Helsinki, 00014 Helsinki, Finland
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9
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Cai J, Wang D, Liang S, Peng J, Zhao F, Liu J. Excessive supply of glucose elicits an NF-κB2-dependent glycolysis in lactating goat mammary glands. FASEB J 2020; 34:8671-8685. [PMID: 32359096 DOI: 10.1096/fj.201903088r] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2019] [Revised: 03/30/2020] [Accepted: 04/18/2020] [Indexed: 11/11/2022]
Abstract
During lactation, an improper glucose supply often threatens mammary gland (MG) health. However, information is limited on the metabolic trajectories and molecules that regulate lactating MGs with an excessive glucose supply. Based on the network analysis of transcriptome and microRNAs, we found that the oversupply of glucose-induced severe glucose metabolic disorders in MGs of lactating goats, shifting lactose synthesis to acute fermentative glycolysis which caused increased flux of glucose metabolism into lactate. Moreover, NF-κB2 played a key role in regulating glycolysis, exhibiting a metabolic shift when MGs had an excessive supply of glucose. In primary mammary epithelial cells, fermentative glycolysis, and intracellular concentration of reactive oxygen species (ROS) were reduced by ganoderic acid A through blocking NF-κB2, while activation of NF-κB2 with phorbol myristate acetate (PMA) upregulated fermentative glycolysis and increased cellular ROS accumulation under excessive glucose. Thus, we established an NF-κB2-targeting method to reform the metabolic shift toward glycolysis caused by glucose oversupply by integrating NF-κB2 blockade and intracellular ROS scavenging.
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Affiliation(s)
- Jie Cai
- Ministry of Education Key Laboratory of Molecular Animal Nutrition, Institute of Dairy Science, College of Animal Sciences, Zhejiang University, Hangzhou, Zhejiang, China
| | - Diming Wang
- Ministry of Education Key Laboratory of Molecular Animal Nutrition, Institute of Dairy Science, College of Animal Sciences, Zhejiang University, Hangzhou, Zhejiang, China
| | - Shulin Liang
- Ministry of Education Key Laboratory of Molecular Animal Nutrition, Institute of Dairy Science, College of Animal Sciences, Zhejiang University, Hangzhou, Zhejiang, China
| | - Jinrong Peng
- Ministry of Education Key Laboratory of Molecular Animal Nutrition, Institute of Dairy Science, College of Animal Sciences, Zhejiang University, Hangzhou, Zhejiang, China
| | - Fengqi Zhao
- Ministry of Education Key Laboratory of Molecular Animal Nutrition, Institute of Dairy Science, College of Animal Sciences, Zhejiang University, Hangzhou, Zhejiang, China.,Department of Animal and Veterinary Sciences, University of Vermont, Burlington, VT, USA
| | - Jianxin Liu
- Ministry of Education Key Laboratory of Molecular Animal Nutrition, Institute of Dairy Science, College of Animal Sciences, Zhejiang University, Hangzhou, Zhejiang, China
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