Abstract
Plant stress acclimation depends on metabolic changes. However, the knowledge concerning the modularity and robustness of plant metabolic networks under stress conditions remains fragmented. Here we carried out a multi-species/stress condition meta-analysis using previously published metabolite profiling data from plants under water deficit, cold, salt and nitrogen deprivation stress conditions. We carried out extensive network and multivariate analyses aiming to identify stress biomarkers and to investigate how plant metabolic network is altered in terms of topology and connectivity by stress conditions. Partial least squares discriminant analysis (PLS-DA) was effective in differentiating stressed from non-stressed plants at a metabolic level. However, no general pattern in both density and heterogeneity of the metabolic network was observed after stress imposition. Integrative analysis identified metabolic markers for multiple stresses in plants, including asparagine, shikimate, fructose and raffinose. This analysis further highlights that amino acid metabolism is a major hub for plant stress acclimation. This idea is supported by the fact that several amino acids related to photorespiration and that are used as substrates for alternative plant respiration pathways or the synthesis of secondary metabolites were found as key for the structure and modulation of the network under stress. Our results collectively suggest that stress-induced changes in metabolic network topology are species/stress level–specific. However, several hubs related to amino acid metabolism emerge as key nodes in the network when plants are subjected to stress conditions, highlighting that our approach can be used by systems-driven plant breeding programs toward plant stress tolerance improvement.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Albert R (2005) Scale-free networks in cell biology. J Cell Sci 118:4947–4957. https://doi.org/10.1242/jcs.02714
Albert R, Barabási A-L (2002) Statistical mechanics of complex networks. Rev Mod Phys 74:47–97. https://doi.org/10.1103/RevModPhys.74.47
Albert R, Jeong H, Barabasi A-L (2001) Error and attack tolerance of complex networks. Nature 409:542–542. https://doi.org/10.1038/35054111
Almaas E, Kovács B, Vicsek T, Oltvai ZN, Barabási AL (2004) Global organization of metabolic fluxes in the bacterium Escherichia coli. Nature 427:839–843. https://doi.org/10.1038/nature02289
Araújo WL, Ishizaki K, Nunes-Nesi A, Larson TR, Tohge T, Krahnert I, Witt S, Obata T, Schauer N, Graham IA, Leaver CJ, Fernie AR (2010) Identification of the 2-hydroxyglutarate and isovaleryl-CoA dehydrogenases as alternative electron donors linking lysine catabolism to the electron transport chain of Arabidopsis mitochondria. Plant Cell 22:1549–1563. https://doi.org/10.1105/tpc.110.075630
Araújo WL, Tohge T, Ishizaki K, Leaver CJ, Fernie AR (2011) Protein degradation - an alternative respiratory substrate for stressed plants. Trends Plant Sci 16:489–498. https://doi.org/10.1016/j.tplants.2011.05.008
Araújo WL, Nunes-Nesi A, Nikoloski Z, Sweetlove LJ, Fernie AR (2012) Metabolic control and regulation of the tricarboxylic acid cycle in photosynthetic and heterotrophic plant tissues. Plant, Cell Environ 35:1–21. https://doi.org/10.1111/j.1365-3040.2011.02332.x
Assenov Y, Ramírez F, Schelhorn S-E, Lengauer T, Albrecht M (2008) Computing topological parameters of biological networks. Bioinformatics 24:282–284. https://doi.org/10.1093/bioinformatics/btm554
Auler PA, Freire FBS, Lima VF, Daloso DM (2022) On the role of guard cells in sensing environmental signals and memorising stress periods. Theor Exp Plant Physiol. https://doi.org/10.1007/s40626-022-00250-4
Avin-Wittenberg T, Bajdzienko K, Wittenberg G, Alseekh S, Tohge T, Bock R, Giavalisco P, Fernie AR (2015) Global analysis of the role of autophagy in cellular metabolism and energy homeostasis in Arabidopsis seedlings under carbon starvation. Plant Cell Online 27:306–322. https://doi.org/10.1105/tpc.114.134205
Balfagón D, Gómez-Cadenas A, Rambla JL, Granell A, de Ollas C, Bassham DC, Mittler R, Zandalinas SI (2022) γ-Aminobutyric acid plays a key role in plant acclimation to a combination of high light and heat stress. Plant Physiol. https://doi.org/10.1093/plphys/kiac010
Barabási AL (2009) Scale-free networks: a decade and beyond. Science (80- ) 325:412–413. https://doi.org/10.1126/science.1173299
Barabási A, Dezso Z, Ravasz E (2003) Scale-free and hierarchical structures in complex networks. AIP Conf … 661:1–16. https://doi.org/10.1063/1.1571285
Barabási AL, Oltvai ZN (2004) Network biology: understanding the cell’s functional organization. Nat Rev Genet 5:101–113. https://doi.org/10.1038/nrg1272
Barros JAS, Cavalcanti JHF, Medeiros DB, Nunes-Nesi A, Avin-Wittenberg T, Fernie AR, Araújo WL (2017) Autophagy deficiency compromises alternative pathways of respiration following energy deprivation in Arabidopsis thaliana. Plant Physiol 175:62–76. https://doi.org/10.1104/pp.16.01576
Barros JAS, Siqueira JAB, Cavalcanti JHF, Araújo WL, Avin-Wittenberg T (2020) Multifaceted roles of plant autophagy in lipid and energy metabolism. Trends Plant Sci 1–13. https://doi.org/10.1016/j.tplants.2020.05.004
Basu S, Duren W, Evans CR, Burant CF, Michailidis G, Karnovsky A (2017) Systems Biology Sparse Network Modeling and Metscape-Based Visualization Methods for the Analysis of Large-Scale Metabolomics Data 33:1545–1553. https://doi.org/10.1093/bioinformatics/btx012
Batista VCV, Pereira IMC, de Paula-Marinho SO, Canuto KM, de Pereira RCA, Rodrigues THS, de Daloso DM, Gomes-Filho E, de Carvalho HH (2019) Salicylic acid modulates primary and volatile metabolites to alleviate salt stress-induced photosynthesis impairment on medicinal plant Egletes viscosa. Environ Exp Bot 167:103870. https://doi.org/10.1016/j.envexpbot.2019.103870
Batista-Silva W, Heinemann B, Rugen N, Nunes-Nesi A, Araújo WL, Braun H, Hildebrandt TM (2019) The role of amino acid metabolism during abiotic stress release. Plant Cell Environ 42:1630–1644. https://doi.org/10.1111/pce.13518
Bertolli SC, Mazzafera P, Souza GM (2014) Why is it so difficult to identify a single indicator of water stress in plants? A proposal for a multivariate analysis to assess emergent properties. Plant Biol 16:578–585. https://doi.org/10.1111/plb.12088
Birami B, Nägele T, Gattmann M, Preisler Y, Gast A, Arneth A, Ruehr NK (2020) Hot drought reduces the effects of elevated CO 2 on tree water-use efficiency and carbon metabolism. New Phytol 226:1607–1621. https://doi.org/10.1111/nph.16471
Bisbis MB, Gruda N, Blanke M (2018) Potential impacts of climate change on vegetable production and product quality – a review. J Clean Prod 170:1602–1620. https://doi.org/10.1016/j.jclepro.2017.09.224
Bottcher A, Domingues-Junior AP, de Souza LP, Tohge T, Araújo WL, Fernie AR, Mazzafera P (2021) Sugarcane cell suspension reveals major metabolic changes under different nitrogen starvation regimes. Bragantia 80. https://doi.org/10.1590/1678-4499.2021-0009
Brito DS, Quinhones CGS, Neri-Silva R, Heinemann B, Schertl P, Cavalcanti JHF, Eubel H, Hildebrandt T, Nunes-Nesi A, Braun H-P, Araújo WL (2022) The role of the electron-transfer flavoprotein: ubiquinone oxidoreductase following carbohydrate starvation in Arabidopsis cell cultures. Plant Cell Rep 41:431–446. https://doi.org/10.1007/s00299-021-02822-1
Broido AD, Clauset A (2019) Scale-Free Networks are rare. Nat Commun 10:1–10. https://doi.org/10.1038/s41467-019-08746-5
Cattivelli L, Rizza F, Badeck FW, Mazzucotelli E, Mastrangelo AM, Francia E, Marè C, Tondelli A, Stanca AM (2008) Drought tolerance improvement in crop plants: an integrated view from breeding to genomics. F Crop Res 105:1–14. https://doi.org/10.1016/j.fcr.2007.07.004
Chong J, Soufan O, Li C, Caraus I, Li S, Bourque G, Wishart DS, Xia J (2018) MetaboAnalyst 4.0: towards more transparent and integrative metabolomics analysis. Nucleic Acids Res 46:W486–W494. https://doi.org/10.1093/nar/gky310
Choudhury FK, Devireddy AR, Azad RK, Shulaev V, Mittler R (2018) Local and systemic metabolic responses during light-induced rapid systemic signaling in Arabidopsis. Plant Physiol submitted. https://doi.org/10.1104/pp.18.01031
Daloso DM (2014) The ecological context of bilateral symmetry of organ and organisms. Nat Sci 6:184–190. https://doi.org/10.4236/ns.2014.64022
de Daloso DM, Antunes WC, Santana TA, Pinheiro DP, Ribas RF, Sachetto-Martins G, Loureiro ME (2014) Arabidopsis gun4 mutant have greater light energy transfer efficiency in photosystem II despite low chlorophyll content. Theor Exp Plant Physiol 26:177–187. https://doi.org/10.1007/s40626-014-0025-z
Domingues-Junior AP, de Daloso DM, Machado M, Rosado-Souza L, de Souza LP, Fernie AR, Mazzafera P (2019) A cold change: how short low temperature exposure affects primary metabolism in leaves and stems of two eucalyptus species. Theor Exp Plant Physiol 8:429–444. https://doi.org/10.1007/s40626-019-00156-8
Evans JR, Lawson T (2020) From green to gold: agricultural revolution for food security. J Exp Bot 71:2211–2215. https://doi.org/10.1093/jxb/eraa110
Fàbregas N, Fernie AR (2019) The metabolic response to drought. J Exp Bot 70:1077–1085. https://doi.org/10.1093/jxb/ery437
Fàbregas N, Lozano-Elena F, Blasco-Escámez D et al (2018) Overexpression of the vascular brassinosteroid receptor BRL3 confers drought resistance without penalizing plant growth. Nat Commun 9:1–13. https://doi.org/10.1038/s41467-018-06861-3
FAO F and AO (2017) The future of food and agriculture – trends and challenges. Rome
Fernie AR, Yan J (2019) De novo domestication: an alternative route toward new crops for the future. Mol Plant 12:615–631. https://doi.org/10.1016/j.molp.2019.03.016
Filippou P, Zarza X, Antoniou C, Obata T, Villarroel CA, Ganopoulos I, Harokopos V, Gohari G, Aidinis V, Madesis P, Christou A, Fernie AR, Tiburcio AF, Fotopoulos V (2021) Systems biology reveals key tissue-specific metabolic and transcriptional signatures involved in the response of Medicago truncatula plant genotypes to salt stress. Comput Struct Biotechnol J 19:2133–2147. https://doi.org/10.1016/j.csbj.2021.04.018
Flexas J (2016) Genetic improvement of leaf photosynthesis and intrinsic water use efficiency in C3plants: why so much little success? Plant Sci 251:155–161. https://doi.org/10.1016/j.plantsci.2016.05.002
Fonseca-Pereira P, Daloso DM, Gago J, De Oliveira Silva FM, Condori-Apfata JA, Florez-Sarasa I, Tohge T, Reichheld JP, Nunes-Nesi A, Fernie AR, Arajo WL (2019) The mitochondrial thioredoxin system contributes to the metabolic responses under drought episodes in Arabidopsis. Plant Cell Physiol 60:213–229. https://doi.org/10.1093/pcp/pcy194
Freire FBS, Bastos RLG, Bret RSC, Cândido-Sobrinho SA, Medeiros DB, Antunes WC, Fernie AR, Daloso DM (2021) Mild reductions in guard cell sucrose synthase 2 expression leads to slower stomatal opening and decreased whole plant transpiration in Nicotiana tabacum L. Environ Exp Bot 184:104370. https://doi.org/10.1016/j.envexpbot.2020.104370
Friso G (2015) van Wijk KJ (2015) Update: post-translational protein modifications in plant metabolism. Plant Physiol 169:01378. https://doi.org/10.1104/pp.15.01378
Gago J, Fernie AR, Nikoloski Z, Tohge T, Martorell S, Escalona JM, Ribas-Carbó M, Flexas J, Medrano H (2017) Integrative field scale phenotyping for investigating metabolic components of water stress within a vineyard. Plant Methods 13:1–14. https://doi.org/10.1186/s13007-017-0241-z
Gago J, Daloso DM, Carriquí M, Nadal M, Morales M, Araújo WL, Nunes-Nesi A, Perera-Castro AV, Clemente-Moreno MJ, Flexas J (2020) The photosynthesis game is in the “inter-play”: mechanisms underlying CO2 diffusion in leaves. Environ Exp Bot 178:104174. https://doi.org/10.1016/j.envexpbot.2020.104174
Galviz Y, Souza GM, Lüttge U (2022) The biological concept of stress revisited: relations of stress and memory of plants as a matter of space–time. Theor Exp Plant Physiol 34:239–264
Gaufichon L, Rothstein SJ, Suzuki A (2016) Asparagine metabolic pathways in arabidopsis. Plant Cell Physiol 57:675–689. https://doi.org/10.1093/pcp/pcv184
Geigenberger P, Thormählen I, Daloso DM, Fernie AR (2017) The unprecedented versatility of the plant thioredoxin system. Trends Plant Sci 22:249–262. https://doi.org/10.1016/j.tplants.2016.12.008
Gomes Silveira JA, De Almeida VR, Almeida Da Rocha IM, De Oliveira Monteiro Moreira AC, De Azevedo Moreira RD, Abreu Oliveira JT (2003) Proline accumulation and glutamine synthetase activity are increased by salt-induced proteolysis in cashew leaves. J Plant Physiol 160:115–123. https://doi.org/10.1078/0176-1617-00890
Guilherme EA, Carvalho FEL, Daloso DM, Silveira JAG (2019) Increase in assimilatory nitrate reduction and photorespiration enhances CO2 assimilation under high light-induced photoinhibition in cotton. Environ Exp Bot 159:66–74. https://doi.org/10.1016/j.envexpbot.2018.12.012
Gutiérrez AR, Lejay LV, Dean A, Chiaromonte F, Shasha DE, Coruzzi GM (2007) Qualitative network models and genome-wide expression data define carbon/nitrogen-responsive molecular machines in Arabidopsis. Genome Biol 8:R7. https://doi.org/10.1186/gb-2007-8-1-r7
Hildebrandt TM (2018) Synthesis versus degradation: directions of amino acid metabolism during Arabidopsis abiotic stress response. Plant Mol Biol 98:121–135. https://doi.org/10.1007/s11103-018-0767-0
Hildebrandt TM, Nunes Nesi A, Araújo WL, Braun HP (2015) Amino acid catabolism in plants. Mol Plant 8:1563–1579. https://doi.org/10.1016/j.molp.2015.09.005
Jeong H, Mason SP, Barabási AL, Oltvai ZN (2001) Lethality and centrality in protein networks. Nature 411:41–42. https://doi.org/10.1038/35075138
Jones H (1998) Stomatal control of photosynthesis and transpiration. J Exp Bot 49:387–398. https://doi.org/10.1093/jexbot/49.suppl_1.387
Jones AM, Xuan Y, Xu M et al (2014) Border control - a membrane-linked interactome of Arabidopsis. Science 344:711–716. https://doi.org/10.1126/science.1251358 ((80))
Kopka J, Schauer N, Krueger S, Birkemeyer C, Usadel B, Bergmüller E, Dörmann P, Weckwerth W, Gibon Y, Stitt M, Willmitzer L, Fernie AR, Steinhauser D (2005) GMD@CSB.DB: the Golm metabolome database. Bioinformatics 21:1635–1638. https://doi.org/10.1093/bioinformatics/bti236
Kranner I, Minibayeva FV, Beckett RP, Seal CE (2010) What is stress? Concepts, definitions and applications in seed science. New Phytol 188:655–673. https://doi.org/10.1111/j.1469-8137.2010.03461.x
Kubis A, Bar-Even A (2019) Synthetic biology approaches for improving photosynthesis. J Exp Bot 70:1425–1433. https://doi.org/10.1093/jxb/erz029
Kuhalskaya A, Ahchige MW, de Souza LP, Vallarino J, Brotman Y, Alseekh S (2020) Network analysis provides insight into tomato lipid metabolism. Metabolites 10. https://doi.org/10.3390/metabo10040152
Leitch AR, Leitch IJ (2008) Genomic plasticity and the diversity of polyploid plants. Science 320:481–483. https://doi.org/10.1126/science.1153585 ((80- ))
Lichtenthaler HK (1998) The stress concept in plants: an introduction. Ann N Y Acad Sci 851:187–198. https://doi.org/10.1111/j.1749-6632.1998.tb08993.x
Lima VF, Medeiros DB, Dos Anjos L, Gago J, Fernie AR, Daloso DM (2018) Toward multifaceted roles of sucrose in the regulation of stomatal movement. Plant Signal Behav 0:1–8. https://doi.org/10.1080/15592324.2018.1494468
Lisec J, Schauer N, Kopka J, Willmitzer L, Fernie AR (2006) Gas chromatography mass spectrometry–based metabolite profiling in plants. Nat Protoc 1:387–396. https://doi.org/10.1038/nprot.2006.59
Liu YY, Slotine JJ, Barabási AL (2011) Controllability of complex networks. Nature 473:167–173. https://doi.org/10.1038/nature10011
Long SP, Marshall-Colon A, Zhu XG (2015) Meeting the global food demand of the future by engineering crop photosynthesis and yield potential. Cell 161:56–66. https://doi.org/10.1016/j.cell.2015.03.019
Lozano-Elena F, Fàbregas N, Coleto-Alcudia V, Caño-Delgado AI (2022) Analysis of metabolic dynamics during drought stress in Arabidopsis plants. Sci Data 9:1–12. https://doi.org/10.1038/s41597-022-01161-4
Luedemann A, Strassburg K, Erban A, Kopka J (2008) TagFinder for the quantitative analysis of gas chromatography - mass spectrometry (GC-MS)-based metabolite profiling experiments. Bioinformatics 24:732–737. https://doi.org/10.1093/bioinformatics/btn023
Lüttge U (2021) Integrative emergence in contrast to separating modularity in plant biology: views on systems biology with information, signals and memory at scalar levels from molecules to the biosphere. Theor Exp Plant Physiol 33:1–13. https://doi.org/10.1007/s40626-021-00198-x
Merchant A, Richter AA (2011) Polyols as biomarkers and bioindicators for 21st century plant breeding. Funct Plant Biol 38:934–940. https://doi.org/10.1071/FP11105
Merchant A, Tausz M, Arndt SK, Adams MA (2006) Cyclitols and carbohydrates in leaves and roots of 13 Eucalyptus species suggest contrasting physiological responses to water deficit. Plant, Cell Environ 29:2017–2029. https://doi.org/10.1111/j.1365-3040.2006.01577.x
Mesquita RO, Coutinho FS, Vital CE, Nepomuceno AL, Rhys Williams TC, de Oliveira J, Ramos H, Loureiro ME (2020) Physiological approach to decipher the drought tolerance of a soybean genotype from Brazilian savanna. Plant Physiol Biochem 151:132–143. https://doi.org/10.1016/j.plaphy.2020.03.004
Mitchell M (2006) Complex systems: network thinking. Artif Intell 170:1194–1212. https://doi.org/10.1016/j.artint.2006.10.002
Murashige T, Skoog F (1962) A revised medium for rapid growth and bio assays with tobacco tissue cultures. Physiol Plant 15:473–497. https://doi.org/10.1111/j.1399-3054.1962.tb08052.x
Neto MCL, Carvalho FEL, Souza GM, Silveira JAG (2021) Understanding photosynthesis in a spatial–temporal multiscale: the need for a systemic view. Theor Exp Plant Physiol 33:113–124. https://doi.org/10.1007/s40626-021-00199-w
O’Leary B, Plaxton WC (2020) Multifaceted functions of post-translational enzyme modifications in the control of plant glycolysis. Curr Opin Plant Biol 55:28–37. https://doi.org/10.1016/j.pbi.2020.01.009
Obata T, Fernie AR (2012) The use of metabolomics to dissect plant responses to abiotic stresses. Cell Mol Life Sci 69:3225–3243. https://doi.org/10.1007/s00018-012-1091-5
Obata T, Witt S, Lisec J, Palacios-Rojas N, Florez-Sarasa I, Yousfi S, Araus JL, Cairns JE, Fernie AR (2015) Metabolite profiles of maize leaves in drought, heat, and combined stress field trials reveal the relationship between metabolism and grain yield. Plant Physiol 169:2665–2683. https://doi.org/10.1104/pp.15.01164
Pang Z, Chong J, Zhou G, De Lima Morais DA, Chang L, Barrette M, Gauthier C, Jacques PÉ, Li S, Xia J (2021) MetaboAnalyst 5.0: narrowing the gap between raw spectra and functional insights. Nucleic Acids Res 49:W388–W396. https://doi.org/10.1093/nar/gkab382
Pires MV, Pereira Júnior AA, Medeiros DB, Daloso DM, Pham PA, Barros KA, Engqvist MKM, Florian A, Krahnert I, Maurino VG, Araújo WL, Fernie AR (2016) The influence of alternative pathways of respiration that utilize branched-chain amino acids following water shortage in Arabidopsis. Plant Cell Environ 39:1304–1319. https://doi.org/10.1111/pce.12682
Razaghi-Moghadam Z, Nikoloski Z (2021) GeneReg: a constraint-based approach for design of feasible metabolic engineering strategies at the gene level. Bioinformatics 37:1717–1723. https://doi.org/10.1093/bioinformatics/btaa996
Rosenzweig C, Elliott J, Deryng D et al (2014) Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison. Proc Natl Acad Sci U S A 111:3268–3273. https://doi.org/10.1073/pnas.1222463110
Saito K, Yonekura-Sakakibara K, Nakabayashi R, Higashi Y, Yamazaki M, Tohge T, Fernie AR (2013) The flavonoid biosynthetic pathway in Arabidopsis: structural and genetic diversity. Plant Physiol Biochem 72:21–34. https://doi.org/10.1016/j.plaphy.2013.02.001
Shannon P, Markiel A, Owen Ozier 2, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 2498–2504. https://doi.org/10.1101/gr.1239303.metabolite
Souza GM, Lüttge U (2015) Stability as a phenomenon emergent from plasticity–complexity–diversity in eco-physiology. In: Lüttge U, Beyschlag W (eds) Progress in Botany, 1st edn. Springer-Verlag, Berlin, pp 211–239
Souza GM, Ribeiro RV, Pincus SM (2004) Changes in network connectance and temporal dynamics of gas exchange in Citrus sinensis under different evaporative demands. Brazilian J Plant Physiol 16:119–130. https://doi.org/10.1590/S1677-04202004000300001
Souza GM, Pincus SM, Monteiro JAF (2005) The complexity-stability hypothesis in plant gas exchange under water deficit. Brazilian J Plant Physiol 17:363–373. https://doi.org/10.1590/S1677-04202005000400004
Souza GM, Ribeiro RV, De ORF, Machado EC (2005) Network connectance and autonomy analyses of the photosynthetic apparatus in tropical tree species from different successional groups under contrasting irradiance conditions. Rev Bras Botânica 28:47–59. https://doi.org/10.1590/S0100-84042005000100005
Souza GM, Ribeiro RV, Prado CHBA, Damineli DSC, Sato AM, Oliveira MS (2009) Using network connectance and autonomy analyses to uncover patterns of photosynthetic responses in tropical woody species. Ecol Complex 6:15–26. https://doi.org/10.1016/j.ecocom.2008.10.002
Souza GM, Prado CHBA, Ribeiro RV, Barbosa JPRAD, Gonçalves AN, Habermann G (2016) Toward a systemic plant physiology. Theor Exp Plant Physiol 28:341–346. https://doi.org/10.1007/s40626-016-0071-9
Souza PVL, Lima-Melo Y, Carvalho FE, Reichheld JP, Fernie AR, Silveira JAG, Daloso DM (2019) Function and compensatory mechanisms among the components of the chloroplastic redox network. CRC Crit Rev Plant Sci 38:1–28. https://doi.org/10.1080/07352689.2018.1528409
Sweetlove LJ, Fernie AR (2005) Regulation of metabolic networks: understanding metabolic complexity in the systems biology era. New Phytol 168:9–24. https://doi.org/10.1111/j.1469-8137.2005.01513.x
Sweetlove LJ, Fernie AR (2013) The spatial organization of metabolism within the plant cell. Annu Rev Plant Biol 64:723–746. https://doi.org/10.1146/annurev-arplant-050312-120233
Sweetlove LJ, Obata T, Fernie AR (2014) Systems analysis of metabolic phenotypes: what have we learnt? Trends Plant Sci 19:222–230. https://doi.org/10.1016/j.tplants.2013.09.005
Sweetlove LJ, Nielsen J, Fernie AR (2017) Engineering central metabolism – a grand challenge for plant biologists. Plant J 90:749–763. https://doi.org/10.1111/tpj.13464
Timm S, Hagemann M (2020) Photorespiration – how is it regulated and regulates overall plant metabolism? J Exp Bot. https://doi.org/10.1016/j.ijbiomac.2015.10.079
Todaka D, Zhao Y, Yoshida T et al (2017) Temporal and spatial changes in gene expression, metabolite accumulation and phytohormone content in rice seedlings grown under drought stress conditions. Plant J 90:61–78. https://doi.org/10.1111/tpj.13468
Trisos CH, Merow C, Pigot AL (2020) The projected timing of abrupt ecological disruption from climate change. Nature. https://doi.org/10.1038/s41586-020-2189-9
Valladares F, Balaguer L, Martinez-Ferri E, Perez-Corona E, Manrique E (2002) Plasticity, instability and canalization: is the phenotypic variation in seedlings of sclerophyll oaks consistent with the environmental unpredictability of Mediterranean ecosystems? New Phytol 156:457–467. https://doi.org/10.1046/j.1469-8137.2002.00525.x
Vital CE, Giordano A, de Almeida SE, Rhys Williams TC, Mesquita RO, Vidigal PMP, de Santana LA, Pacheco TG, Rogalski M, de Oliveira Ramos HJ, Loureiro ME (2017) An integrative overview of the molecular and physiological responses of sugarcane under drought conditions. Plant Mol Biol 94:577–594. https://doi.org/10.1007/s11103-017-0611-y
Worley B, Powers R (2015) Multivariate analysis in metabolomics Bradley. Curr Metabolomics 1:92–107. https://doi.org/10.2174/2213235X11301010092.Multivariate
Wurtzel ET, Vickers CE, Hanson AD, Millar AH, Cooper M, Voss-Fels KP, Nikel PI, Erb TJ (2019) Revolutionizing agriculture with synthetic biology. Nat Plants 5:1207–1210. https://doi.org/10.1038/s41477-019-0539-0
Xia J, Wishart DS (2011) Web-based inference of biological patterns, functions and pathways from metabolomic data using MetaboAnalyst. Nat Protoc 6:743–760. https://doi.org/10.1038/nprot.2011.319
Xia J, Broadhurst DI, Wilson M, Wishart DS (2013) Translational biomarker discovery in clinical metabolomics: an introductory tutorial. Metabolomics 9:280–299. https://doi.org/10.1007/s11306-012-0482-9
Ye CY, Fan L (2021) Orphan crops and their wild relatives in the genomic era. Mol Plant 14:27–39. https://doi.org/10.1016/j.molp.2020.12.013
Yoshida T, Yamaguchi-Shinozaki K (2021) Metabolic engineering: towards water deficiency adapted crop plants. J Plant Physiol 258–259:153375. https://doi.org/10.1016/j.jplph.2021.153375
Zandalinas SI, Mittler R (2022) Plant responses to multifactorial stress combination. New Phytol. https://doi.org/10.1111/nph.18087
Zandalinas SI, Fritschi FB, Mittler R (2021) Global warming, climate change, and environmental pollution: recipe for a multifactorial stress combination disaster. Trends Plant Sci 26:588–599. https://doi.org/10.1016/j.tplants.2021.02.011
Zandalinas SI, Balfagón D, Gómez-Cadenas A, Mittler R (2022) Responses of plants to climate change: metabolic changes during abiotic stress combination in plants. J Exp Bot. https://doi.org/10.1093/jxb/erac073
Zsögön A, Čermák T, Naves ER, Notini MM, Edel KH, Weinl S, Freschi L, Voytas DF, Kudla J, Peres LEP (2018) De novo domestication of wild tomato using genome editing. Nat Biotechnol 36:1211–1216. https://doi.org/10.1038/nbt.4272
Funding
This work was made possible through financial support from the National Council for Scientific and Technological Development (CNPq, Grant 404817/2021–1). We also received the research fellowship granted by CNPq to DMD (303709/2020–0) and the scholarships granted by CNPq to FBSF and by Fundação Cearense de Apoio ao Desenvolvimento Cientifico e Tecnológico (FUNCAP) to LLC.
Author information
Authors and Affiliations
Contributions
DMD idealized the work. LLC and FBSF performed the analysis, with supervision of DMD. Data analysis and interpretation and the establishment of the figures were carried out by LLC, FBSF and DMD. All authors contributed to writing the manuscript. DMD obtained funding and is responsible for this article.
Corresponding author
Ethics declarations
Conflict of Interest
The authors declare no competing interests.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Cardoso, L.L., Freire, F.B.S. & Daloso, D.M. Plant Metabolic Networks Under Stress: a Multi-species/Stress Condition Meta-analysis. J Soil Sci Plant Nutr 23, 4–21 (2023). https://doi.org/10.1007/s42729-022-01032-2
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s42729-022-01032-2