Introduction

Plants are under constant exposure to various pathogens. Different pathogens have evolved different strategies to obtain nutrients and to propagate, while plants have elaborate counter attack strategies to defend themselves (Nimchuk et al. 2003; Jones and Dangl 2006; Pieterse et al. 2012). During this ongoing battle, physiology and cellular metabolism of both host and pathogen get perturbed. Metabolism is the total sum of various biochemical processes that occur within a living organism; therefore, manipulation of such machinery is an ideal battlefield during plant–pathogen interactions (Duan et al. 2013). Alteration in photosynthetic machinery is most common amongst various pathogenic responses (Berger et al. 2007b). Various photosynthetic parameters such as Fv/Fm (maximum quantum efficiency of photosystem II), ETR (linear electron transport rate), ØPSII (operating efficiency of photosystem II) and NPQ (non-photochemical quenching) are found altered during pathogenesis (Scholes and Rolfe 1996; Petit et al. 2006; Rolfe and Scholes 2010). Various transcriptome studies have revealed photosynthesis-associated genes to be downregulated while respiratory processes, i.e., glycolysis, tricarboxylic acid cycle (TCA cycle) and mitochondrial electron transport chain to be upregulated in the infected tissues (Doehlemann et al. 2008; Parker et al. 2009; Chandran et al. 2010; Voll et al. 2011; Teixeira et al. 2014; Xu et al. 2015). Also various host secondary metabolites get induced during plant–pathogen interactions (Piasecka et al. 2015; Pusztahelyi et al. 2015). Interestingly, some of the plant secondary metabolites are known precursor of various phytohormones (such as salicylic acid, jasmonates) and defense-related (including phytoalexins) compounds (VanEtten et al. 1994; Dixon and Paiva 1995; Bolton 2009; Wojakowska et al. 2013; Piasecka et al. 2015; Pusztahelyi et al. 2015). Overall, reprogramming of host metabolism has emerged as a common theme during plant–pathogen interactions.

Previously, Berger et al. (2007b) and Bolton (2009) had reviewed the association of host primary metabolic changes during pathogenesis. However, with recent technological advancement, significant progress has been achieved towards dissecting the involvement of primary metabolic changes during plant–pathogen interactions. As sugars are core of primary metabolism, in this review we deliberate on current understanding, opportunities as well as available knowledge gaps about their dynamics and role during pathogenesis. We also prospect whether these changes are beneficial for the plant or the pathogen. For involvement of non-sugar primary metabolites (such as nitrogen), we refer readers to some of the recent reviews (Fagard et al. 2014; Rojas et al. 2014).

Changes in plant sugar metabolism: a common response during pathogenesis

Photosynthesis plays a vital role in management of biosynthesis and mobilization of various sugars. Alterations in photosynthesis as well as sugar metabolism play an important role during plant interactions with various pathogens including fungi (Table 1). For example, decreased photosynthetic activity is observed upon biotrophic fungal (Albugo candida, Golovinomyces orontii, Erysiphe cichoracearum) pathogen infection in Arabidopsis (Chou et al. 2000; Zimmerli et al. 2004; Chandran et al. 2010). Similarly, severe inhibition of photosynthesis is observed during pathogenesis of Botrytis cinerea (a necrotrophic fungal pathogen) in plants like Arabidopsis, tomato and lettuce (Berger et al. 2004; Windram et al. 2012; De Cremer et al. 2013; Smith et al. 2014). Moreover, the hemibiotrophic fungal pathogens like Colletotrichum lindemuthianum and Mycosphaerella graminicola are also known to inhibit photosynthesis during necrotrophic phase of their pathogenesis on beans and wheat, respectively (Lopes and Berger 2001; Meyer et al. 2001; Scholes and Rolfe 2009).

Table 1 Host metabolic alteration during plant–fungus interactions
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Besides fungal pathogens, decrease in photosynthesis is also observed during bacterial and viral infections in plants (Suppl. Table S1). For example, photosynthesis is significantly reduced during pathogenesis of Pseudomonas syringae on different hosts (Zou et al. 2005; Bonfig et al. 2006; Berger et al. 2007a). In a recent study, it has been observed that P. syringae utilizes effector molecules to disrupt photosystem II, inhibit photosynthetic CO2 assimilation and reprogram nuclear encoded chloroplast-targeted genes (NECGs) expression (de Torres Zabala et al. 2015). Repression of photosynthesis-associated genes is also observed during Bean Common Mosaic Virus (BCMV) infection on common bean (Martin et al. 2016). Besides this, downregulation of photosynthesis is also observed during plant–herbivore interactions (Zangerl et al. 2002; Tang et al. 2006). For example, repression of photosynthesis-related genes is observed in Nicotiana attenuate upon the attack of Manduca sexta, a moth (Hui et al. 2003). However, mirid bugs (Tupiocoris notatus) attack is found to enhance photosynthetic activity in N. attenuate (Halitschke et al. 2011). The authors had speculated that elevated CO2 assimilation might balance net photosynthesis in the mirid bugs affected leaves. Interestingly, the elevated rate of photosynthesis is also observed in the adjoining area of A. candida and B. cinerea infected regions of the leaves of Arabidopsis and tomato, respectively (Chou et al. 2000; Berger et al. 2004). Based on various studies, it has become apparent that during necrotrophic interaction, alteration in photosynthesis is rapid while during biotrophic interaction, such alterations are delayed, being observed after visible appearance of disease symptoms (Rolfe and Scholes 2010).

Besides photosynthesis, the host carbohydrate metabolism is also modulated by both biotrophic and necrotrophic pathogens (Table 1; Suppl. Table S1). For example, biotrophic fungal pathogen Ustilago maydis causes alteration in soluble sugar content in the infected maize leaves (Doehlemann et al. 2008; Horst et al. 2008). Notably, the defects in sugar accumulation (id1: indeterminate1; increased accumulation of sucrose) or starch metabolism (su1: sugary1; altered starch metabolism) impart tolerance against U. maydis infections in maize (Kretschmer et al. 2017). The adjustment in concentration of various sugars seems to play a determinative role in plant defense during necrotrophic interaction of B. cinerea and Sclerotinia sclerotiorum with tomato (Lecompte et al. 2013). A recent study has also suggested that relative proportion (but not the absolute concentration) of fructose amongst the pool of sugars (sucrose, glucose and fructose) plays a decisive role during tomato defense against B. cinerea (Lecompte et al. 2017). Several recent studies have suggested that alteration in host sugar metabolism is also important for the pathogenesis of soil-borne pathogens, such as Verticillium dahlia, Fusarium oxysporum, Phytophthora infestans and Rhizoctonia solani (Gyetvai et al. 2012; Buhtz et al. 2015; Kumar et al. 2016; Copley et al. 2017; Ghosh et al. 2017; Witzel et al. 2017).

Sugar mobilization in the battlefield

Plant tissues self-sufficient in producing sugars are known as source, while other tissues are called sink. Sink tissues require net sugar import (predominantly in the form of sucrose) via phloem and they are equipped to utilize sucrose as energy source (Kocal et al. 2008). When a pathogen attacks source tissues (such as leaves), a sink-type environment is created. Whereas when a pathogen colonizes sink tissues (such as developing leaves, meristems, etc.), the sink to source transition is arrested and sink status is retained at the site of infections (Teixeira et al. 2014; Dhandapani et al. 2017). The cascade of events including downregulation of photosynthetic genes, upregulation of respiratory genes and accumulation of hexose sugars facilitates creation of sink-type environment in the infected tissues (Fig. 1). Furthermore, sugar hydrolysis and uptake mechanism are modulated in the infected tissues (Fatima and Senthil-Kumar 2015; Oliva and Quibod 2017). Besides foliar pathogens, there are pathogens that infect non-aerial parts of the plants such as roots (sink tissue). The root knot nematode (Meloidogyne incognita) infection alters the primary metabolism during susceptible interaction but not during resistant interactions with tomato roots (Shukla et al. 2017). Recently, Zhao and colleagues have reported that root knot nematode (M. incognita) upregulates sugar transport-related genes and increases the sugar content in both roots as well as leaves of the infected tomato (Zhao et al. 2018). Overall, it seems that root pathogens can alter sugar mobilization in both foliar and non-foliar (root) tissues.

Fig. 1
figure 1

A simplified overview of source to sink transition during plant–pathogen interactions. During pathogen attack, source tissues (such as leaves) undergo extensive metabolic changes. The source-specific genes are repressed and sink-specific ones are induced. This leads to increase in hexose to sucrose ratio in the infected tissues and causes source to sink transition. Generally, sugars are transported from source tissues to various other parts of the plants (black arrow) while upon pathogen attack, sugars get translocated to infected zones (blue arrow). During pathogenesis, hexose transporters are upregulated in the infected tissues to facilitate sugar uptake from the host. RbcS ribulose-1,5-bisphosphate carboxylase, Cab chlorophyll a, b binding protein, INVs invertases, HXTs hexose transporters, SWEETs Sugars Will Eventually be Exported Transporters

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Sink-related enzymes

In most cases, sucrose is not readily available to pathogen and it needs to be broken down into more accessible form, i.e., glucose for utilization (Paul et al. 2008). Invertases (INVs) present in sink tissue assist in hydrolyzing sucrose into glucose and fructose (reviewed in Tauzin and Giardina 2014). They influence sucrose level, sink strength as well as sucrose: hexose ratio. The host cell wall invertases upregulated during pathogen infection are known to increase the hexose to sucrose ratio in the infected tissues (Chou et al. 2000; Fotopoulos et al. 2003; Hayes et al. 2010). Also there are reports which suggest that some phytopathogens upregulate their own invertase(s) to promote host colonization (Voegele et al. 2006; Chang et al. 2017). Besides invertases, sucrose synthases (plant/pathogen origin) which are involved in breakdown of sucrose into fructose and UDP-glucose are also upregulated in some pathosystems (Hren et al. 2009; Brzin et al. 2011; Cabello et al. 2014). The upregulation of these sucrose synthases can also alter sucrose:hexose ratio in the infected tissues.

Sink-related transporters

Generally, membrane transporters are upregulated at the site of infection to promote uptake of sugars from the infected tissues (Table 2). For example, hexose transporters (HXTs) of either plant or pathogen origins are upregulated in various pathosystems and facilitate uptake of hexoses. Recently, the HXT1 of U. maydis has been shown to be required for its pathogenesis on maize (Schuler et al. 2015). Interestingly, different paralogs of HXT1 transporters of C. graminicola are differentially regulated during different phases of its pathogenesis on maize (Lingner et al. 2011). The CgHXT1 and CgHXT3 are induced during biotrophic phase while the CgHXT2 and CgHXT5 are induced during necrotrophic phase. Besides HXTs, induction of another hexose transporter, i.e., mfs1 (major facilitator superfamily), has been observed during necrotrophic phase of anthracnose disease causing fungal (C. lindemuthianum) infection in common bean (Pereira et al. 2013). In general, the HXTs are co-regulated with cell wall invertases, suggesting that they might be functioning to facilitate sugar uptake in a coordinated fashion (Sutton et al. 2007; Essmann et al. 2008). For example, both invertase (UfINV1) and hexose transporter (UfHXT1) are upregulated in the haustoria of Uromyces fabae (a biotrophic pathogen) and promote hexose uptake from the host during its pathogenesis on broad bean (Voegele et al. 2001, 2006).

Table 2 Modulation of sink-related transporters during plant–pathogen interactions
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It is noteworthy that some host origin hexose transporters such as sugar transport proteins (STPs) are also modulated during plant–pathogen interactions. Moore and colleagues had reported that a mutation in the wheat STP13 (lr67) gene imparts resistance against multiple biotrophic pathogens (Moore et al. 2015). Similarly, Arabidopsis STP13 is known to provide basal resistance against B. cinerea (Lemonnier et al. 2014). Upregulation of pathogen encoded sucrose transporters at infection site suggests that they might facilitate the pathogen to directly uptake sucrose from the host (Table 2). Srt1 is the first characterized pathogen origin sucrose transporter which is involved in the virulence of U. maydis on maize (Wahl et al. 2010). Interestingly, during the C. graminicola infection in maize another type of sucrose transporter, i.e., SUT1 has been upregulated (Vargas et al. 2012). In recent years, new types of sugar transporters (commonly referred to as SWEETs) have been found to facilitate glucose and sucrose efflux into the plant apoplast. These host origin SWEET transporters are induced upon pathogen invasion and it has been thought that pathogens induce them to promote uptake of sugars from their host (Chen et al. 2010). For example, Xanthomonas oryzae pv. oryzae utilizes transcriptional activator-like (TAL) effectors, i.e., PthXo1 and PthXo2 to induce rice OsSWEET11 (sucrose uniporter) and OsSWEET13 genes, respectively, during infection process (Chen et al. 2010; Zhou et al. 2015). Similarly, the pathogen (X. oryzae pv. oryzae) uses AvrXa7 and PthXo3 effectors to induce the OsSWEET14 (Os11N3) gene to promote susceptibility (Antony et al. 2010). Cassava sugar transporter MeSWEET10a is also induced by TAL20Xam668 effector from causal agent of bacterial blight disease, i.e., X. axonopodis (Cohn et al. 2014). Similarly, the X. citri ssp. citri was found to modulate the CsSWEET1 gene in citrus by TAL effectors (PthA4 and PthAw) (Hu et al. 2014).

Besides bacterial pathogens, fungal pathogens such as Golovinomyces cichoracearum and B. cinerea are also known to modulate host SWEET genes to promote pathogenesis (Ferrari et al. 2007; Chen et al. 2010). The host sweet gene (VvSWEET4) has been found upregulated during pathogenesis of B. cinerea in Vitis vinifera (Chong et al. 2014). Overall it seems that most of the foliar pathogens induce host SWEET transporters to facilitate infections (Chen et al. 2010; Cohn et al. 2014). However, the SWEET transporters seem to have different role during pathogenesis of soil-borne pathogens. For example, loss of host vacuolar SWEET2 transporter promotes enhanced susceptibility against a common root pathogen, Pythium irregulare infection in Arabidopsis (Chen et al. 2015). Similarly, overexpression of IbSWEET10 gene of sweet potato enhances host resistance to F. oxysporum infections (Li et al. 2017).

Sugars as regulators of plant defense—a stone unturned

In recent years, a pivotal role of various sugars like glucose, sucrose and trehalose in regulating the defense-related metabolic pathways has become apparent (Fig. 2) (Rolland et al. 2006; Wind et al. 2010; Bolouri Moghaddam and Van den Ende 2012). Glucose-mediated induction of defense-related secondary metabolites such as chalcone synthase and phenylalanine ammonia-lyase (Dao et al. 2011; Kim and Hwang 2014; Tonnessen et al. 2014) has been demonstrated (Xiao et al. 2000). Furthermore, sucrose can promote host defense response by enhancing the expression of anthocyanin biosynthesis genes and stimulating accumulation of isoflavonoids (Morkunas et al. 2005; Solfanelli et al. 2006).

Fig. 2
figure 2

Generalized overview of sugar signaling associated with metabolic reprogramming during plant–pathogen interactions. Repression of photosynthesis and activation of host cellular respiration and secondary metabolism are most common responses that occur during pathogen attack. Different sugars and sugar-related enzymes seem to control various aspects of these host metabolic changes to govern fate of interactions (green lines). SUS sucrose synthases, SPS sucrose-phosphate synthase, AGPase ADP-glucose pyrophosphorylase, SnRK1 SNF1-related kinase 1, bZIP11 basic region-leucine zipper transcription factor 11, TPS trehalose-6-phosphate synthase, TPP trehalose-6-phosphate phosphatase, TCA cycle tricarboxylic acid cycle

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In addition, various sugar-related enzymes, transporters and signaling molecules that are induced during pathogen invasion can regulate the plant defense processes. For example, cell wall invertases can play a pivotal role in integrating sugar and defense signaling (Proels and Hückelhoven 2014). An increased invertase activity in the infected host tissue causes generation of sugar signals via modulation of sucrose/hexose ratio. Some sucrose transporters such as SUC2 and SUT1 might also function as sugar sensors (Lalonde et al. 1999). It is possible that sugar transporters that are upregulated during formation of secondary sink in the infected tissue might also be participating in defense response associated signaling processes (Sutton et al. 2007; Bezrutczyk et al. 2018). Similarly, various sugar signaling molecules such as hexokinase (HXK) and trehalose-6-phosphate (T6P) can also potentially regulate plant defense (Moore et al. 2003; Rolland et al. 2006; Paul et al. 2008; Sheen 2014). The HXKs are the best studied sugar sensors which are ascribed to be associated with glucose-mediated repression of photosynthetic genes (chlorophyll a/b binding protein and plastocyanin) (Sheen 1990; Moore et al. 2003; Cho et al. 2006). Also, HSKs potentially promote degradation of ETHYLENE-INSENSITIVE3 (EIN3), a key transcriptional regulator in ethylene signaling (Yanagisawa et al. 2003; Karve et al. 2012). The transcriptional de-repression of EIN3 is known to facilitate synergy between various plant defense hormone (jasmonate and ethylene) signaling pathways (Zhu et al. 2011). In addition, ethylene can also influence the photosynthesis and sugar partitioning (recently reviewed in Ceusters and Van de Poel 2018). Several other studies have also revealed interconnection between sugar and phytohormone signaling (León and Sheen 2003; Heil et al. 2012; Bolouri Moghaddam and Van den Ende 2012). Arabidopsis G-signaling protein AtRGS1 (regulator of G-protein signaling protein 1) has also been proven as a glucose sensor and it is known to influence the sugar-mediated gene regulation (Chen and Jones 2004; Grigston et al. 2008). Although the G-protein signaling has been known to play a pivotal role during plant–pathogen interactions (Urano et al. 2013), still the role of AtRGS1 in plant disease susceptibility or resistance remains to be analyzed. Establishing the links of sugar-hormone and sugar-G-protein signaling with plant pathogenesis is naive areas of research and largely remains unexplored.

Sucrose is known to translationally inhibit the expression of a particular group (S) of bZIP (basic region leucine zipper) transcription factor, i.e., ATB2/AtbZIP11 (Rook et al. 1998; Wiese et al. 2004, 2005). During sugar limiting condition, the bZIP11 is regulated by SnRK1 (SNF1-related kinase 1), a Ser/Thr kinase which acts as a metabolite sensor to regulate sugar and energy metabolism. Interestingly, the role of SnRK1 and bZIP transcription factors during plant–pathogen interactions has also been established (Alves et al. 2013; Morkunas and Ratajczak 2014; Hulsmans et al. 2016). Another sugar sensor, i.e., trehalose-6-phosphate (T6P, an intermediate of trehalose metabolism) is known to inhibit SnRK1 and influence bZIP11-SnRK1 regulatory pathway (Delatte et al. 2011; O’Hara et al. 2013; Nunes et al. 2013). T6P can also promote redox activation of ADP-glucose pyrophosphorylase (AGPase), which is involved in starch synthesis (Kolbe et al. 2005). Interestingly, the alterations of host starch metabolism (turnover) can also influence the outcome of the interaction (Engelsdorf et al. 2013). Besides host, trehalose biosynthetic pathway of the pathogens do play an important role during pathogenesis. For example, the T6P synthase (Tps1) deletion mutant of Magnaporthe oryzae exhibits reduced pathogenicity in rice (Foster et al. 2003; Wilson et al. 2007). The trehalose produced by X. citri subsp. citri acts as an important virulence determinant during pathogenesis in citrus (Piazza et al. 2015). Overall, it is being envisaged that by altering host SnRK1 activity, the pathogen origin trehalose as well as T6P modulates host metabolism and defense responses. In summary, the notion that sugars play a crucial role during plant defense response is emerging (Bolouri Moghaddam and Van den Ende 2012; Morkunas and Ratajczak 2014). A new term, sweet immunity has been coined to describe sugar-mediated induction of plant immune responses (Bolouri Moghaddam and Van Den Ende 2013). Various sugars like fructans and sucrose can also serve as damage-associated molecular patterns (DAMPs) which hallmark the pathogen infection (Duran-Flores and Heil 2016; Versluys et al. 2017) and are known to prime plant defense response against various pathogens (Duran-Flores and Heil 2016).

Metabolic shift—favoring plant or pathogen

It is apparent that metabolic shift occurs during both susceptible (compatible) and resistant (incompatible) interactions. The downregulation of photosynthesis and alteration in carbohydrate metabolism have been a common response during both types of interactions (Swarbrick et al. 2006; Fu et al. 2016; Li et al. 2016). However, the dynamics of gene expression has been found to be qualitatively similar but quantitatively different during compatible and incompatible interactions (Tao et al. 2003; Wang et al. 2010). For example, the photosynthesis and CO2 fixation-related genes are highly abundant amongst differentially regulated genes during compatible compared to incompatible interactions of P. infestans with potato (Gyetvai et al. 2012). The presence of high level of extracellular sugar at infection site is another common response during both susceptible and resistant interactions (Essmann et al. 2008; Siemens et al. 2011; Sun et al. 2014). However, a recent report has shown that bidirectional sugar transporters are upregulated only during colonization of a pathogenic isolate of F. oxysporum (Lanubile et al. 2015).

Interestingly, the timing of modulation of photosynthesis and sugar metabolism-related genes do vary between compatible and incompatible interactions (Fofana et al. 2007; Pérez-Bueno et al. 2015; Stare et al. 2015). The photosynthesis-related genes are transiently upregulated at early stage (before viral multiplication) of Potato Virus Y (PVY) infection in tolerant potato but subsequently they get downregulated (Stare et al. 2015). However, in case of the sensitive tomato (SA-deficient transgenic plants) the photosynthesis-related genes are consistently downregulated. How such temporal regulation of sugar metabolism as well as photosynthesis, influences the outcome of susceptible or resistant interaction, remain largely unanswered.

Recent updates and ongoing quest

With recent advent of transcriptomics, metabolomics, or proteomics-based approaches, exploring the complexity of metabolic alterations during plant–pathogen interactions has become feasible (Aliferis and Jabaji 2012; Hong et al. 2012; Yang et al. 2013; Teixeira et al. 2014; Aliferis et al. 2014). Nowadays, dual omics approaches are being adopted to solve this unfolded mystery. Studying interactions of M. oryzae and Oryza sativa (Kawahara et al. 2012), Hemileia vastatrix and Coffea arabica (Fernandez et al. 2012), Leptosphaeria maculans and Brassica napus (Lowe et al. 2014), Moniliophthora perniciosa and Theobroma cacao (Teixeira et al. 2014) are some of the recent examples wherein dual transcriptomics approach has been explored to understand the intricacies of plant–pathogen interactions. Also metabolomics/proteomics techniques, such as gas chromatography–mass spectrometry (GC–MS), liquid chromatography–mass spectrometry (LC–MS), and NMR spectroscopy, are being used to understand metabolic perturbations during pathogen infections (Botanga et al. 2012; Cevallos-Cevallos et al. 2012; Hong et al. 2012; Prezelj et al. 2016). In addition, targeted (having prior knowledge of the compounds of interest) or non-targeted MS analysis is also being explored (Heuberger et al. 2014). The limitation of distinguishing the plant or pathogen origin metabolites/proteins from the mixed pool is being resolved by in vitro co-culturing of the plant and pathogen cells and thereafter separating them to precisely identify the origin of metabolites/proteins (Allwood et al. 2010, 2012). However, such methodology is unsuitable for most of the pathosystems, as it is performed under in vitro condition and only partially mimics the changes that occur during pathogenesis in plants. The uses of the laser microdissection (LMD) to separate the host/pathogen cells in the infected tissues are a good alternative to understand the spatio-temporal regulation (Chandran et al. 2010). However, intimate association of the invading pathogen with the plant and presence of pathogen origin secreted proteins/metabolites in the host apoplast adds further complexity in data analysis. Considering such limitations, in recent years integrative approaches by combining more than one omics tools are being explored to unravel the complexity (Fig. 3). For example, simultaneous measurement of transcripts and/or proteins has been attempted to identify secreted effectors of Acyrthosiphon pisum (aphid) and P. infestans (fungus) during pathogenesis on pea and potato, respectively (Carolan et al. 2011; Ali et al. 2014). Similarly combined genome-wide RNAseq and global LC–MS and/or GC–MS-based metabolome analysis are being conducted to understand the metabolic alterations during plant–pathogen interactions (Rudd et al. 2015; Copley et al. 2017; Ghosh et al. 2017).

Fig. 3
figure 3

A diagrammatic overview of dual or integrative omic approaches to understand the plant–pathogen interaction. Either entire tissues or laser-assisted precise sampling of infected tissues is analyzed to study the transcriptional dynamics during infection process. Through in silico analysis, the host and pathogen origin transcripts are filtered out from the mixed transcriptome and they are analyzed separately. The observed changes in the host as well as pathogen transcripts might influence individually or cumulatively the outcome of the interactions. Besides this, the proteomics and metabolomics approaches are being integrated with transcriptome studies nowadays to understand the intricacies of plant–pathogen interactions. The accolade (in blue) on the right side of the picture represents such integrative approaches

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In conclusion, with the advent of new technologies, systematic and holistic understanding of metabolic perturbation during host–pathogen interactions is becoming possible. Sugar metabolism and mobilization have emerged as important players, which decide the fate of ongoing battle between plant and pathogen during infection process. However, in spite of various recent advancements, the metabolic signatures and their regulatory nodes, which decide the susceptible or resistant responses, remain poorly understood. The host metabolic signature that favors plant or pathogen remains a major ongoing quest for future research. In addition, metabolic signatures that are associated with diverse lifestyle (biotrophic, necrotrophic and hemibiotrophic) as well as different modes of colonization (foliar, soil-borne, etc.) of the pathogen are yet to be established. We have summarized the current understanding and important unanswered quests about sugar metabolic alterations during plant–pathogen interactions in Fig. 4.

Fig. 4
figure 4

Understanding sugar metabolic shift: an ongoing quest with future implications. A model showing the major contributions (blue arrow) and the open questions/information gap (green arrow) in understanding host sugar metabolic signature during plant–pathogen interaction. Also, it remains to be established how host sugar metabolism is affected by various modes of pathogen colonization (question marks). In conclusion, despite recent advances, it is still not clear how host metabolic changes (depicted as wheel in the figure) favor the plant or the pathogen (depicted as direction of wheel) during their interaction. If the metabolic signature is properly understood, one can exploit it to develop disease-resistant plants

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Author contribution statement

PK and GJ designed the outline of the article. PK designed the figures and tables. PK and GJ have written and edited the manuscript.