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Necrotrophic and biotrophic pathogens are resisted by different plant defenses. While necrotrophic pathogens are sensitive to jasmonic acid (JA)-dependent resistance, biotrophic pathogens are resisted by salicylic acid (SA)- and reactive oxygen species (ROS)-dependent resistance. Although many pathogens switch from biotrophy to necrotrophy during infection, little is known about the signals triggering this transition. This study is based on the observation that the early colonization pattern and symptom development by the ascomycete pathogen Plectosphaerella cucumerina (P. cucumerina) vary between inoculation methods. Using the Arabidopsis (Arabidopsis thaliana) defense response as a proxy for infection strategy, we examined whether P. cucumerina alternates between hemibiotrophic and necrotrophic lifestyles, depending on initial spore density and distribution on the leaf surface. Untargeted metabolome analysis revealed profound differences in metabolic defense signatures upon different inoculation methods. Quantification of JA and SA, marker gene expression, and cell death confirmed that infection from high spore densities activates JA-dependent defenses with excessive cell death, while infection from low spore densities induces SA-dependent defenses with lower levels of cell death. Phenotyping of Arabidopsis mutants in JA, SA, and ROS signaling confirmed that P. cucumerina is differentially resisted by JA- and SA/ROS-dependent defenses, depending on initial spore density and distribution on the leaf. Furthermore, in situ staining for early callose deposition at the infection sites revealed that necrotrophy by P. cucumerina is associated with elevated host defense. We conclude that P. cucumerina adapts to early-acting plant defenses by switching from a hemibiotrophic to a necrotrophic infection program, thereby gaining an advantage of immunity-related cell death in the host.Plant pathogens are often classified as necrotrophic or biotrophic, depending on their infection strategy (Glazebrook, 2005; Nishimura and Dangl, 2010). Necrotrophic pathogens kill living host cells and use the decayed plant tissue as a substrate to colonize the plant, whereas biotrophic pathogens parasitize living plant cells by employing effector molecules that suppress the host immune system (Pel and Pieterse, 2013). Despite this binary classification, the majority of pathogenic microbes employ a hemibiotrophic infection strategy, which is characterized by an initial biotrophic phase followed by a necrotrophic infection strategy at later stages of infection (Perfect and Green, 2001). The pathogenic fungi Magnaporthe grisea, Sclerotinia sclerotiorum, and Mycosphaerella graminicola, the oomycete Phytophthora infestans, and the bacterial pathogen Pseudomonas syringae are examples of hemibiotrophic plant pathogens (Perfect and Green, 2001; Koeck et al., 2011; van Kan et al., 2014; Kabbage et al., 2015).Despite considerable progress in our understanding of plant resistance to necrotrophic and biotrophic pathogens (Glazebrook, 2005; Mengiste, 2012; Lai and Mengiste, 2013), recent debate highlights the dynamic and complex interplay between plant-pathogenic microbes and their hosts, which is raising concerns about the use of infection strategies as a static tool to classify plant pathogens. For instance, the fungal genus Botrytis is often labeled as an archetypal necrotroph, even though there is evidence that it can behave as an endophytic fungus with a biotrophic lifestyle (van Kan et al., 2014). The rice blast fungus Magnaporthe oryzae, which is often classified as a hemibiotrophic leaf pathogen (Perfect and Green, 2001; Koeck et al., 2011), can adopt a purely biotrophic lifestyle when infecting root tissues (Marcel et al., 2010). It remains unclear which signals are responsible for the switch from biotrophy to necrotrophy and whether these signals rely solely on the physiological state of the pathogen, or whether host-derived signals play a role as well (Kabbage et al., 2015).The plant hormones salicylic acid (SA) and jasmonic acid (JA) play a central role in the activation of plant defenses (Glazebrook, 2005; Pieterse et al., 2009, 2012). The first evidence that biotrophic and necrotrophic pathogens are resisted by different immune responses came from Thomma et al. (1998), who demonstrated that Arabidopsis (Arabidopsis thaliana) genotypes impaired in SA signaling show enhanced susceptibility to the biotrophic pathogen Hyaloperonospora arabidopsidis (formerly known as Peronospora parastitica), while JA-insensitive genotypes were more susceptible to the necrotrophic fungus Alternaria brassicicola. In subsequent years, the differential effectiveness of SA- and JA-dependent defense mechanisms has been confirmed in different plant-pathogen interactions, while additional plant hormones, such as ethylene, abscisic acid (ABA), auxins, and cytokinins, have emerged as regulators of SA- and JA-dependent defenses (Bari and Jones, 2009; Cao et al., 2011; Pieterse et al., 2012). Moreover, SA- and JA-dependent defense pathways have been shown to act antagonistically on each other, which allows plants to prioritize an appropriate defense response to attack by biotrophic pathogens, necrotrophic pathogens, or herbivores (Koornneef and Pieterse, 2008; Pieterse et al., 2009; Verhage et al., 2010).In addition to plant hormones, reactive oxygen species (ROS) play an important regulatory role in plant defenses (Torres et al., 2006; Lehmann et al., 2015). Within minutes after the perception of pathogen-associated molecular patterns, NADPH oxidases and apoplastic peroxidases generate early ROS bursts (Torres et al., 2002; Daudi et al., 2012; O’Brien et al., 2012), which activate downstream defense signaling cascades (Apel and Hirt, 2004; Torres et al., 2006; Miller et al., 2009; Mittler et al., 2011; Lehmann et al., 2015). ROS play an important regulatory role in the deposition of callose (Luna et al., 2011; Pastor et al., 2013) and can also stimulate SA-dependent defenses (Chaouch et al., 2010; Yun and Chen, 2011; Wang et al., 2014; Mammarella et al., 2015). However, the spread of SA-induced apoptosis during hyperstimulation of the plant immune system is contained by the ROS-generating NADPH oxidase RBOHD (Torres et al., 2005), presumably to allow for the sufficient generation of SA-dependent defense signals from living cells that are adjacent to apoptotic cells. Nitric oxide (NO) plays an additional role in the regulation of SA/ROS-dependent defense (Trapet et al., 2015). This gaseous molecule can stimulate ROS production and cell death in the absence of SA while preventing excessive ROS production at high cellular SA levels via S-nitrosylation of RBOHD (Yun et al., 2011). Recently, it was shown that pathogen-induced accumulation of NO and ROS promotes the production of azelaic acid, a lipid derivative that primes distal plants for SA-dependent defenses (Wang et al., 2014). Hence, NO, ROS, and SA are intertwined in a complex regulatory network to mount local and systemic resistance against biotrophic pathogens. Interestingly, pathogens with a necrotrophic lifestyle can benefit from ROS/SA-dependent defenses and associated cell death (Govrin and Levine, 2000). For instance, Kabbage et al. (2013) demonstrated that S. sclerotiorum utilizes oxalic acid to repress oxidative defense signaling during initial biotrophic colonization, but it stimulates apoptosis at later stages to advance necrotrophic colonization. Moreover, SA-induced repression of JA-dependent resistance not only benefits necrotrophic pathogens but also hemibiotrophic pathogens after having switched from biotrophy to necrotrophy (Glazebrook, 2005; Pieterse et al., 2009, 2012).Plectosphaerella
cucumerina ((P. cucumerina, anamorph Plectosporum tabacinum) anamorph Plectosporum tabacinum) is a filamentous ascomycete fungus that can survive saprophytically in soil by decomposing plant material (Palm et al., 1995). The fungus can cause sudden death and blight disease in a variety of crops (Chen et al., 1999; Harrington et al., 2000). Because P. cucumerina can infect Arabidopsis leaves, the P. cucumerina-Arabidopsis interaction has emerged as a popular model system in which to study plant defense reactions to necrotrophic fungi (Berrocal-Lobo et al., 2002; Ton and Mauch-Mani, 2004; Carlucci et al., 2012; Ramos et al., 2013). Various studies have shown that Arabidopsis deploys a wide range of inducible defense strategies against P. cucumerina, including JA-, SA-, ABA-, and auxin-dependent defenses, glucosinolates (Tierens et al., 2001; Sánchez-Vallet et al., 2010; Gamir et al., 2014; Pastor et al., 2014), callose deposition (García-Andrade et al., 2011; Gamir et al., 2012, 2014; Sánchez-Vallet et al., 2012), and ROS (Tierens et al., 2002; Sánchez-Vallet et al., 2010; Barna et al., 2012; Gamir et al., 2012, 2014; Pastor et al., 2014). Recent metabolomics studies have revealed large-scale metabolic changes in P. cucumerina-infected Arabidopsis, presumably to mobilize chemical defenses (Sánchez-Vallet et al., 2010; Gamir et al., 2014; Pastor et al., 2014). Furthermore, various chemical agents have been reported to induce resistance against P. cucumerina. These chemicals include β-amino-butyric acid, which primes callose deposition and SA-dependent defenses, benzothiadiazole (BTH or Bion; Görlach et al., 1996; Ton and Mauch-Mani, 2004), which activates SA-related defenses (Lawton et al., 1996; Ton and Mauch-Mani, 2004; Gamir et al., 2014; Luna et al., 2014), JA (Ton and Mauch-Mani, 2004), and ABA, which primes ROS and callose deposition (Ton and Mauch-Mani, 2004; Pastor et al., 2013). However, among all these studies, there is increasing controversy about the exact signaling pathways and defense responses contributing to plant resistance against P. cucumerina. While it is clear that JA and ethylene contribute to basal resistance against the fungus, the exact roles of SA, ABA, and ROS in P. cucumerina resistance vary between studies (Thomma et al., 1998; Ton and Mauch-Mani, 2004; Sánchez-Vallet et al., 2012; Gamir et al., 2014).This study is based on the observation that the disease phenotype during P. cucumerina infection differs according to the inoculation method used. We provide evidence that the fungus follows a hemibiotrophic infection strategy when infecting from relatively low spore densities on the leaf surface. By contrast, when challenged by localized host defense to relatively high spore densities, the fungus switches to a necrotrophic infection program. Our study has uncovered a novel strategy by which plant-pathogenic fungi can take advantage of the early immune response in the host plant. 相似文献
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Holliday junctions (HJs) are physical links between homologous DNA molecules that arise as central intermediary structures during homologous recombination and repair in meiotic and somatic cells. It is necessary for these structures to be resolved to ensure correct chromosome segregation and other functions. In eukaryotes, including plants, homologs of a gene called XPG-like endonuclease1 (GEN1) have been identified that process HJs in a manner analogous to the HJ resolvases of phages, archaea, and bacteria. Here, we report that Arabidopsis (Arabidopsis thaliana), a eukaryotic organism, has two functional GEN1 homologs instead of one. Like all known eukaryotic resolvases, AtGEN1 and Arabidopsis single-strand DNA endonuclease1 both belong to class IV of the Rad2/XPG family of nucleases. Their resolvase activity shares the characteristics of the Escherichia coli radiation and UV sensitive C paradigm for resolvases, which involves resolving HJs by symmetrically oriented incisions in two opposing strands. This leads to ligatable products without the need for further processing. The observation that the sequence context influences the cleavage by the enzymes can be interpreted as a hint for the existence of sequence specificity. The two Arabidopsis paralogs differ in their preferred sequences. The precise cleavage positions observed for the resolution of mobile nicked HJs suggest that these cleavage positions are determined by both the substrate structure and the sequence context at the junction point.To counter the effects of endogenous and exogenous factors that threaten the genome integrity, efficient mechanisms have evolved to ensure the faithful transmission of genetic information (Tuteja et al., 2001). Double-strand breaks, induced by conditions such as ionizing radiation or replication fork (RF) stalling, are among the most deleterious lesions (Jackson and Bartek, 2009). To protect the genome from consequences of these lesions, the cells have ancient double-strand break repair mechanisms, including the homologous recombination (HR) pathway. The HR mechanism is also of great importance in the intentional genetic recombination during sexual reproduction. A key intermediate in HR is the so-called Holliday junction (HJ), a structure that was first suggested in the context of a gene conversion model in fungi (Holliday, 1964) and later shown to arise in somatic and meiotic cells (Szostak et al., 1983; Schwacha and Kleckner, 1995; Cromie et al., 2006; Bzymek et al., 2010).HJs are structures consisting of four DNA strands of two homologous DNA helices (e.g. homologous chromosomes or sister chromatids). They arise through invasion of one single strand from each of two helices into the other double strand. This results in two continuous strands (one per helix) and two strands that cross from one helix into the other. Schematics often depict the HJs with a parallel orientation of the helices, in which the crossing strands cross each other as was originally postulated (Holliday, 1964). However, HJs based on oligonucleotides have been shown to adopt an antiparallel conformation (for review, see Lilley, 2000). In this configuration, the junction resembles the letter H in a lateral view, and the crossing strands actually perform U turns. The crossing strands represent physical links between the two DNA strands involved. If a RF is restored by HR-mediated repair during mitosis, the resulting HJ usually involves the two sister chromatids of one chromosome (Li and Heyer, 2008). In meiosis, the physical links in the shape of HJs arise because of meiotic crossover between homologous chromosomes. In either case, these links must be resolved to ensure unperturbed cell survival.The importance of resolving the HJs for the survival of cells and organisms is highlighted by the phenotypes described for mutants defective for the known pathways of HJ resolution. One of these pathways is the resolution by canonical HJ resolvases, enzymes that cleave the two opposing strands of a HJ in perfectly symmetric positions relative to the junction point, which results in readily ligatable nicked duplex (nD) products (Svendsen and Harper, 2010). This property distinguishes the canonical HJ resolvases from the noncanonical resolvases (see below).The main resolvase of Escherichia coli is radiation and UV sensitive C (RuvC), which is part of the E. coli resolvasome (RuvABC complex; Otsuji et al., 1974; Sharples et al., 1990, 1999). In this complex, a HJ is sandwiched between two RuvA tetramers (Panyutin and Hsieh, 1994). Two RuvB complexes form ATP-dependent motors of branch migration, with two opposing helical arms of the junction threaded through their central openings. For the resolution of the HJ, one RuvA tetramer is replaced by a RuvC homodimer. This homodimer positions two active sites at the center of the junction that are poised to cleave the junction point if a preferred consensus sequence of the form 5′-(A/T)TT↓(G/C)-3′ is encountered. The requirement for this correct sequence is quite strict; even a single base change can lead to a drastic reduction of the cleavage efficiency (Shah et al., 1994). Isolated EcRuvC is also active in vitro and binds only HJ structures with high specificity. This binding is independent of the sequence context, but the cleavage depends on the specific sequence (Iwasaki et al., 1991; Benson and West, 1994; Dunderdale et al., 1994). The exact cleavage position has been determined to be either one nucleotide 3′ or 5′ from the junction or at the junction point (Bennett and West, 1996; Shida et al., 1996; Osman et al., 2009). The well-characterized EcRuvC is often referred to as a paradigm of canonical HJ resolution.Eukaryotes have evolved a more complex interplay of different HJ resolution pathways (Schwartz and Heyer, 2011; Zakharyevich et al., 2012). A defined complex, consisting of a recombination deficiency Q (RecQ) helicase (AtRECQ4A in Arabidopsis [Arabidopsis thaliana], Bloom syndrome protein in human, and Slow growth suppression1 (Sgs1) in yeast [Saccharomyces cerevisiae]), a type IA topoisomerase (DNA topoisomerase 3-alpha [TOP3A] in Arabidopsis, HsTOPOIIIα in human, and ScTop3 in yeast), and the structural protein RecQ-mediated genome instability1 (AtRMI1 in Arabidopsis, HsRMI1 in human, and ScRmi1 in yeast; RTR complex), mediates the so-called dissolution pathway. The crossing points of a double HJ are brought together by branch migration catalyzed by the helicase followed by decatenation catalyzed by the topoisomerase (Wu and Hickson, 2003; Hartung et al., 2007a, 2008; Mankouri and Hickson, 2007; Yang et al., 2010). In addition to the catalytic activities, a functional RTR complex also requires structural functions based on protein-protein interactions, for which RMI1 plays an essential role (Mullen et al., 2005; Chen and Brill, 2007; Bonnet et al., 2013; Schröpfer et al., 2014). Dissolution leads to noncross-over products and therefore, is a major mechanism in somatic yeast cells (Gangloff et al., 1994; Ira et al., 2003; Matos et al., 2011). In Arabidopsis, the loss of RTR component function leads to elevated rates of HR as well as sensitivity to UV light and methylmethane sulfonate (MMS; Bagherieh-Najjar et al., 2005; Hartung et al., 2007a; Bonnet et al., 2013). Mutants of AtRMI1 and AtTOP3A exhibit severe and unique meiotic phenotypes (Chelysheva et al., 2008; Hartung et al., 2008). This meiosis I arrest is dependent on HR, but the exact nature of the recombination intermediates that are involved remains unclear (Li et al., 2004; Hartung et al., 2007b; Knoll et al., 2014).Dissolution acts in parallel with a second pathway mediated by the structure-specific endonuclease MMS and UV-sensitive protein81 (MUS81) as shown by the fact that the additional mutation of ScSgs1/AtRECQ4A leads to synthetic lethality (Mullen et al., 2001; Hartung et al., 2006; Mannuss et al., 2010). Single mutants of MUS81 in yeast, human, Drosophila melanogaster, and Arabidopsis are sensitive to DNA-damaging agents that perturb RFs and show reduced HR after induction of double-strand breaks (Boddy et al., 2001; Hanada et al., 2006; Hartung et al., 2006). The MUS81 homologs form heterodimers with the noncatalytic subunit essential meiotic endonuclease1 (EME1; ScMms4 in S. cerevisiae). SpMus81-Eme1 was, to our knowledge, the first nuclear endonuclease reported to be capable of resolving HJs (Boddy et al., 2001). The Arabidopsis complexes can be formed with the two different subunits: AtEME1A or AtEME1B (Geuting et al., 2009). AtMUS81-EME1A/B, like the fission yeast ortholog, preferentially cleaves nicked Holliday junctions (nHJs) and 3′-flaps but also shows weaker activity on intact HJs in vitro (Boddy et al., 2001; Osman et al., 2003; Geuting et al., 2009; Schwartz and Heyer, 2011). MUS81 homologs are key players in meiotic cross-over generation (Osman et al., 2003; Berchowitz et al., 2007; Higgins et al., 2008). Although cross-over formation is solely dependent on SpMus81 in fission yeast, this function was shown to be shared with ScYen1 in budding yeast (Osman et al., 2003; Blanco et al., 2010; Ho et al., 2010; Tay and Wu, 2010). Tightly regulated by cell division cycle5-dependent hyperphosphorylation at the end of prophase I, the main activity of ScMus81-Mms4 is timed to coordinate with the formation of chiasmata and HJs that link the homologous chromosomes. This role in meiosis I is shown by the failure of chromosome segregation at the end of meiosis I in ScMus81 mutants (Matos et al., 2011). Interestingly, the chromosomes could be segregated at the end of meiosis II because of the presence of ScYen1. In contrast to canonical HJ resolvases, the hallmark of the MUS81-EME1 cleavage mechanism is the asymmetry of the second incision relative to either a first incision or a preexisting nick. This difference classifies MUS81-EME1 as a noncanonical resolvase. Its products need additional processing by gap-filling or flap-cleaving enzymes to allow religation (Boddy et al., 2001; Geuting et al., 2009).In very recent studies, HsMUS81-EME1 was found to constitute an essential canonical HJ resolvase with HsSLX1-SLX4 (SLX for synthetic lethal of unknown function), in which a first incision is made by HsSLX1-SLX4 followed by the enhanced action of the HsMUS81-EME1 subunits on the resulting nHJ (Garner et al., 2013; Wyatt et al., 2013). HsSLX1-SLX4 had previously been described as a canonical resolvase, albeit producing only a low level of symmetrically cut ligatable products (Fekairi et al., 2009).In addition to the mechanisms described above, an activity resembling that of EcRuvC had long been known to be present in mammalian cell-free extracts. In 2008, the group of Steven C. West succeeded in identifying, to their knowledge, the first nuclear proteins analogous to the EcRuvC paradigm: ScYen1 and Homo sapiens XPG-like endonuclease1 (HsGEN1; Ip et al., 2008). These proteins are members of the large and well-characterized Rad2/XPG family of nucleases. The Rad2/XPG family consists of the Xeroderma pigmentosum group G-complementing protein (XPG) endonucleases of the nucleotide excision repair (class I), the flap endonuclease1 (FEN1) replication-associated flap endonucleases (class II), the exodeoxyribonuclease1 (EXO1) exonucleases of recombination and repair (class III), and class IV (containing the [putative] eukaryotic HJ resolvases). This last class was introduced after the identification of the rice (Oryza sativa) single-strand DNA endonuclease1 (OsSEND-1) based on sequence homology. The class IV members show a domain composition homologous to FEN1 and EXO1, with no spacer region between their N-terminal XPG (XPG-N) and internal XPG (XPG-I) domains, whereas the primary structure of these domains is more similar to the sequence of the nuclease domain of XPG (Furukawa et al., 2003).Although all Rad2/XPG homologs share a common cleavage mechanism as observed for the typical 5′-flap substrate (Tsutakawa et al., 2011; Tsutakawa and Tainer, 2012), the striking evolutionary difference between classes I, II, and III on the one hand and the HJ resolvases (class IV) on the other hand is the ability of class IV members to form homodimers in vitro at their preferred substrate, the HJs (Rass et al., 2010). The homodimer configuration ensures the presence of two active sites positioned on the opposing strands of the HJ, which is necessary for resolution. The mode of eukaryotic HJ resolution is largely similar to the bacterial paradigm: (1) cleavage occurs one nucleotide in the 3′ direction of a static junction point (equivalent to the main cleavage site on 5′-flaps), (2) the incisions occur with almost perfect point symmetry, (3) the incisions result in readily ligatable nDs, and (4) certain sites within a migratable HJ core are preferred, providing evidence for a (yet to be determined) sequence specificity (Ip et al., 2008; Bailly et al., 2010; Rass et al., 2010; Yang et al., 2012).In the absence of MUS81-EME1/Mms4, the proteins HsGEN1, ScYen1, and CeGEN-1 have been shown to play a role in response to replication-associated perturbations, such as MMS- and UV-induced DNA damage (Bailly et al., 2010; Blanco et al., 2010; Tay and Wu, 2010; Gao et al., 2012; Muñoz-Galván et al., 2012). It is also likely that these proteins provide a backup mechanism in mitosis and meiosis, ensuring proper chromosome segregation after a failure of other mechanisms, including MUS81-EME1/Mms4 (Blanco et al., 2010; Matos et al., 2011).Although canonical HJ resolvases in animals and fungi are a current topic of great interest, very little is known about these proteins in plants. In rice, two members of the Rad2/XPG class IV have been described: OsSEND-1 (the founding member) and OsGEN-like (OsGEN-L). OsSEND-1 was shown to digest single-stranded circular DNA, and its expression is induced on MMS-induced genotoxic stress, whereas OsGEN-L is implicated in late spore development (Furukawa et al., 2003; Moritoh et al., 2005). Both studies (Furukawa et al., 2003; Moritoh et al., 2005) proposed putative homologs in other plants, and the gene locus At1g01880 of Arabidopsis, coding for the protein AtGEN1, is considered the ortholog of HsGEN1 and ScYen1 (Ip et al., 2008). However, currently, only OsGEN-L has been further investigated and described to possess in vitro properties similar to both Rad2/XPG nucleases and EcRuvC. This protein shows a well-defined 5′-flap activity as well as a poorly characterized ability, similar to that of EcRuvC, to resolve mobile HJs (Yang et al., 2012).Thus, of two members of Rad2/XPG class IV of plants, only one member has so far been analyzed with respect to a possible HJ resolvase activity. However, Arabidopsis expression data show that both proteins are expressed in plants and do not reveal marked differences (Laubinger et al., 2008). In this study, the goal was, therefore, to characterize the in vitro activities of not only AtGEN1 but also, AtSEND1, focusing on the idea that Arabidopsis and (seed) plants in general might encode not one but actually two HJ resolvases with functional homology to EcRuvC. 相似文献
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Eva Grafahrend-Belau Astrid Junker André Eschenr?der Johannes Müller Falk Schreiber Bj?rn H. Junker 《Plant physiology》2013,163(2):637-647
Plant metabolism is characterized by a unique complexity on the cellular, tissue, and organ levels. On a whole-plant scale, changing source and sink relations accompanying plant development add another level of complexity to metabolism. With the aim of achieving a spatiotemporal resolution of source-sink interactions in crop plant metabolism, a multiscale metabolic modeling (MMM) approach was applied that integrates static organ-specific models with a whole-plant dynamic model. Allowing for a dynamic flux balance analysis on a whole-plant scale, the MMM approach was used to decipher the metabolic behavior of source and sink organs during the generative phase of the barley (Hordeum vulgare) plant. It reveals a sink-to-source shift of the barley stem caused by the senescence-related decrease in leaf source capacity, which is not sufficient to meet the nutrient requirements of sink organs such as the growing seed. The MMM platform represents a novel approach for the in silico analysis of metabolism on a whole-plant level, allowing for a systemic, spatiotemporally resolved understanding of metabolic processes involved in carbon partitioning, thus providing a novel tool for studying yield stability and crop improvement.Plants are of vital significance as a source of food (Grusak and DellaPenna, 1999; Rogalski and Carrer, 2011), feed (Lu et al., 2011), energy (Tilman et al., 2006; Parmar et al., 2011), and feedstocks for the chemical industry (Metzger and Bornscheuer, 2006; Kinghorn et al., 2011). Given the close connection between plant metabolism and the usability of plant products, there is a growing interest in understanding and predicting the behavior and regulation of plant metabolic processes. In order to increase crop quality and yield, there is a need for methods guiding the rational redesign of the plant metabolic network (Schwender, 2009).Mathematical modeling of plant metabolism offers new approaches to understand, predict, and modify complex plant metabolic processes. In plant research, the issue of metabolic modeling is constantly gaining attention, and different modeling approaches applied to plant metabolism exist, ranging from highly detailed quantitative to less complex qualitative approaches (for review, see Giersch, 2000; Morgan and Rhodes, 2002; Poolman et al., 2004; Rios-Estepa and Lange, 2007).A widely used modeling approach is flux balance analysis (FBA), which allows the prediction of metabolic capabilities and steady-state fluxes under different environmental and genetic backgrounds using (non)linear optimization (Orth et al., 2010). Assuming steady-state conditions, FBA has the advantage of not requiring the knowledge of kinetic parameters and, therefore, can be applied to model detailed, large-scale systems. In recent years, the FBA approach has been applied to several different plant species, such as maize (Zea mays; Dal’Molin et al., 2010; Saha et al., 2011), barley (Hordeum vulgare; Grafahrend-Belau et al., 2009b; Melkus et al., 2011; Rolletschek et al., 2011), rice (Oryza sativa; Lakshmanan et al., 2013), Arabidopsis (Arabidopsis thaliana; Poolman et al., 2009; de Oliveira Dal’Molin et al., 2010; Radrich et al., 2010; Williams et al., 2010; Mintz-Oron et al., 2012; Cheung et al., 2013), and rapeseed (Brassica napus; Hay and Schwender, 2011a, 2011b; Pilalis et al., 2011), as well as algae (Boyle and Morgan, 2009; Cogne et al., 2011; Dal’Molin et al., 2011) and photoautotrophic bacteria (Knoop et al., 2010; Montagud et al., 2010; Boyle and Morgan, 2011). These models have been used to study different aspects of metabolism, including the prediction of optimal metabolic yields and energy efficiencies (Dal’Molin et al., 2010; Boyle and Morgan, 2011), changes in flux under different environmental and genetic backgrounds (Grafahrend-Belau et al., 2009b; Dal’Molin et al., 2010; Melkus et al., 2011), and nonintuitive metabolic pathways that merit subsequent experimental investigations (Poolman et al., 2009; Knoop et al., 2010; Rolletschek et al., 2011). Although FBA of plant metabolic models was shown to be capable of reproducing experimentally determined flux distributions (Williams et al., 2010; Hay and Schwender, 2011b) and generating new insights into metabolic behavior, capacities, and efficiencies (Sweetlove and Ratcliffe, 2011), challenges remain to advance the utility and predictive power of the models.Given that many plant metabolic functions are based on interactions between different subcellular compartments, cell types, tissues, and organs, the reconstruction of organ-specific models and the integration of these models into interacting multiorgan and/or whole-plant models is a prerequisite to get insight into complex plant metabolic processes organized on a whole-plant scale (e.g. source-sink interactions). Almost all FBA models of plant metabolism are restricted to one cell type (Boyle and Morgan, 2009; Knoop et al., 2010; Montagud et al., 2010; Cogne et al., 2011; Dal’Molin et al., 2011), one tissue or one organ (Grafahrend-Belau et al., 2009b; Hay and Schwender, 2011a, 2011b; Pilalis et al., 2011; Mintz-Oron et al., 2012), and only one model exists taking into account the interaction between two cell types by specifying the interaction between mesophyll and bundle sheath cells in C4 photosynthesis (Dal’Molin et al., 2010). So far, no model representing metabolism at the whole-plant scale exists.Considering whole-plant metabolism raises the problem of taking into account temporal and environmental changes in metabolism during plant development and growth. Although classical static FBA is unable to predict the dynamics of metabolic processes, as the network analysis is based on steady-state solutions, time-dependent processes can be taken into account by extending the classical static FBA to a dynamic flux balance analysis (dFBA), as proposed by Mahadevan et al. (2002). The static (SOA) and dynamic optimization approaches introduced in this work provide a framework for analyzing the transience of metabolism by integrating kinetic expressions to dynamically constrain exchange fluxes. Due to the requirement of knowing or estimating a large number of kinetic parameters, so far dFBA has only been applied to a plant metabolic model once, to study the photosynthetic metabolism in the chloroplasts of C3 plants by a simplified model of five biochemical reactions (Luo et al., 2009). Integrating a dynamic model into a static FBA model is an alternative approach to perform dFBA.In this study, a multiscale metabolic modeling (MMM) approach was applied with the aim of achieving a spatiotemporal resolution of cereal crop plant metabolism. To provide a framework for the in silico analysis of the metabolic dynamics of barley on a whole-plant scale, the MMM approach integrates a static multiorgan FBA model and a dynamic whole-plant multiscale functional plant model (FPM) to perform dFBA. The performance of the novel whole-plant MMM approach was tested by studying source-sink interactions during the seed developmental phase of barley plants. 相似文献
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