Metabolomics of Solanum lycopersicum Infected with Phytophthora infestans Leads to Early Detection of Late Blight in Asymptomatic Plants

Rice-Magnaporthe oryzae interactions in resistant and susceptible rice cultivars under panicle blast infection based on defense-related enzyme activities and metabolomics

Rice blast, caused by rice blast fungus (Magnaporthe oryzae), is a global threat to food security, with up to 50% yield losses. Panicle blast is a severe form of rice blast, and disease responses vary between cultivars with different genotypes. Reactive oxygen species (ROS)-mediated signaling reactions and the phenylpropanoid pathway are important defense mechanisms involved in recognizing and resisting against fungal infection. To understand rice-M. oryzae interactions in resistant and susceptible cultivars, we determined dynamic changes in the activities of five defense-related enzymes in resistant cultivar jingsui 18 and susceptible cultivar jinyuan 899 infected with M. oryzae from 4 to 25 days after infection. We then performed untargeted metabolomics analyses to profile the metabolomes of the cultivars under infected and non-infected conditions. Dynamic changes in the activities of five defense-related enzymes were closely related to panicle blast resistance in rice. Metabolome data analysis identified 634 differentially accumulated metabolites (DAMs) between resistant and susceptible cultivars following infection, potentially explaining differences in disease response between varieties. The most enriched DAMs were associated with lipids and lipid-like molecules, phenylpropanoids and polyketides, organoheterocyclic compounds, organic acids and derivatives, and lignans, neolignans, and related compounds. Multiple metabolic pathways are involved in resistance to panicle blast in rice, including biosynthesis of other secondary metabolites, amino acid metabolism, lipid metabolism, phenylpropanoid biosynthesis, arachidonic acid metabolism, arginine biosynthesis, tyrosine metabolism, tryptophan metabolism, tyrosine and tryptophan biosynthesis, lysine biosynthesis, and oxidative phosphorylation.

Impact of Argemone mexicana L. on tomato plants infected with Phytophthora infestans

Background

Fungal diseases can cause significant losses in the tomato crop. Phytophthora infestans causes the late blight disease, which considerably affects tomato production worldwide. Weed-based plant extracts are a promising ecological alternative for disease control.

Methods

In this study, we analyzed the plant extract of Argemone mexicana L. using chromatography-mass spectrometry analysis (GC-MS). We evaluated its impact on the severity of P. infestans, as well as its effect on the components of the antioxidant defense system in tomato plants.

Results

The extract from A. mexicana contains twelve compounds most have antifungal and biostimulant properties. The findings of the study indicate that applying the A. mexicana extract can reduce the severity of P. infestans, increase tomato fruit yield, enhance the levels of photosynthetic pigments, ascorbic acid, phenols, and flavonoids, as well as decrease the biosynthesis of H2O2, malondialdehyde (MDA), and superoxide anion in the leaves of plants infected with this pathogen. These results suggest that using the extract from A. mexicana could be a viable solution to control the disease caused by P. infestans in tomato crop.

Steroidal Alkaloids from Food Waste of Tomato Processing Inhibit Neuroblastoma Cell Viability

Nowadays, there is considerable attention toward the use of food waste from food processing as possible sources of compounds with health properties, such as anticancer activity. An example is tomato processing, which is responsible for generating a remarkable amount of waste (leaves, peel, seeds). Therefore, our goal was to evaluate the potential anticancer property of tomato extracts, in particular "Datterino" tomato (DT) and "Piccadilly" tomato (PT), and to study their phytochemical composition. Liquid chromatography with tandem mass spectrometry (LC/MS-MS) results showed that these extracts are rich in alkaloids, flavonoids, fatty acids, lipids, and terpenes. Furthermore, their potential anticancer activity was evaluated in vitro by MTT assay. In particular, the percentage of cell viability was assessed in olfactory ensheathing cells (OECs), a particular glial cell type of the olfactory system, and in SH-SY5Y, a neuroblastoma cell line. All extracts (aqueous and ethanolic) did not lead to any significant change in the percentage of cell viability on OECs when compared with the control. Instead, in SH-SY5Y we observed a significant decrease in the percentage of cell viability, confirming their potential anticancer activity; this was more evident for the ethanolic extracts. In conclusion, tomato leaves extracts could be regarded as a valuable source of bioactive compounds, suitable for various applications in the food, nutraceutical, and pharmaceutical fields.

Novel nanotechnological approaches for managing Phytophthora diseases of plants

Members of the Phytophthora genus are soil-dwelling pathogens responsible for diseases of several important plants. Among these, Phytophthora infestans causes late blight of potatoes, which was responsible for the Irish potato famine during the mid-19th century. Various strategies have been applied to control Phytophthora, including integrated management programs (IMPs) and quarantine, but without successful full management of the disease. Thus, there is a need to search for alternative tools. Here, we discuss the emerging role of nanomaterials in the detection and treatment of Phytophthora species, including slow delivery of agrochemicals (microbicides and pesticides). We propose integrating these tools into an IMP, which could lead to a reduction in pesticide use and provide more effective and sustainable control of Phytophthora pathogens.

Can Metabolomic Approaches Become a Tool for Improving Early Plant Disease Detection and Diagnosis with Modern Remote Sensing Methods? A Review

The various areas of ultra-sensitive remote sensing research equipment development have provided new ways for assessing crop states. However, even the most promising areas of research, such as hyperspectral remote sensing or Raman spectrometry, have not yet led to stable results. In this review, the main methods for early plant disease detection are discussed. The best proven existing techniques for data acquisition are described. It is discussed how they can be applied to new areas of knowledge. The role of metabolomic approaches in the application of modern methods for early plant disease detection and diagnosis is reviewed. A further direction for experimental methodological development is indicated. The ways to increase the efficiency of modern early plant disease detection remote sensing methods through metabolomic data usage are shown. This article provides an overview of modern sensors and technologies for assessing the biochemical state of crops as well as the ways to apply them in synergy with existing data acquisition and analysis technologies for early plant disease detection.

A systematic assessment of matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) application for rapid identification of pathogenic microbes that affect food crops: delivered and future deliverables

MALDI-TOF MS has decades of experience in the detection and identification of microbial pathogens. This has now become a valuable analytical tool when it comes to the identification and detection of clinical microbial pathogens. This review gives a brief synopsis of what has been achieved using MALDI-TOF MS in clinical microbiology. The major focus, however, is on summarizing and highlighting the effectiveness of MALDI-TOF MS as a novel tool for rapid identification of food crop microbial pathogens. The methods used and the sample preparation methodologies reported thus far have been highlighted and the challenges and gaps and recommendations for fine tuning the technique have been put forth. In an era where anything close to the health and welfare of humanity has been considered as the top priority, this review pitches on one such relevant research topics.

Untargeted Metabolomics Using UHPLC-HRMS Reveals Metabolic Changes of Fresh-Cut Potato during Browning Process

Surface browning plays a major role in the quality loss of fresh-cut potatoes. Untargeted metabolomics were used to understand the metabolic changes of fresh-cut potato during the browning process. Their metabolites were profiled by ultra-high performance liquid chromatography coupled with high resolution mass spectrometry (UHPLC-HRMS). Data processing and metabolite annotation were completed by Compound Discoverer 3.3 software. Statistical analysis was applied to screen the key metabolites correlating with browning process. Fifteen key metabolites responsible for the browning process were putatively identified. Moreover, after analysis of the metabolic causes of glutamic acid, linolenic acid, glutathione, adenine, 12-OPDA and AMP, we found that the browning process of fresh-cut potatoes was related to the structural dissociation of the membrane, oxidation and reduction reaction and energy shortage. This work provides a reference for further investigation into the mechanism of browning in fresh-cut products.

Metabolomics-Driven Mining of Metabolite Resources: Applications and Prospects for Improving Vegetable Crops

Vegetable crops possess a prominent nutri-metabolite pool that not only contributes to the crop performance in the fields, but also offers nutritional security for humans. In the pursuit of identifying, quantifying and functionally characterizing the cellular metabolome pool, biomolecule separation technologies, data acquisition platforms, chemical libraries, bioinformatics tools, databases and visualization techniques have come to play significant role. High-throughput metabolomics unravels structurally diverse nutrition-rich metabolites and their entangled interactions in vegetable plants. It has helped to link identified phytometabolites with unique phenotypic traits, nutri-functional characters, defense mechanisms and crop productivity. In this study, we explore mining diverse metabolites, localizing cellular metabolic pathways, classifying functional biomolecules and establishing linkages between metabolic fluxes and genomic regulations, using comprehensive metabolomics deciphers of the plant’s performance in the environment. We discuss exemplary reports covering the implications of metabolomics, addressing metabolic changes in vegetable plants during crop domestication, stage-dependent growth, fruit development, nutri-metabolic capabilities, climatic impacts, plant-microbe-pest interactions and anthropogenic activities. Efforts leading to identify biomarker metabolites, candidate proteins and the genes responsible for plant health, defense mechanisms and nutri-rich crop produce are documented. With the insights on metabolite-QTL (mQTL) driven genetic architecture, molecular breeding in vegetable crops can be revolutionized for developing better nutritional capabilities, improved tolerance against diseases/pests and enhanced climate resilience in plants.

Both Constitutive and Infection-Responsive Secondary Metabolites Linked to Resistance against Austropuccinia psidii (Myrtle Rust) in Melaleuca quinquenervia

Austropuccinia psidii is a fungal plant pathogen that infects species within the Myrtaceae, causing the disease myrtle rust. Myrtle rust is causing declines in populations within natural and managed ecosystems and is expected to result in species extinctions. Despite this, variation in response to A. psidii exist within some species, from complete susceptibility to resistance that prevents or limits infection by the pathogen. Untargeted metabolomics using Ultra Performance Liquid Chromatography with Ion Mobility followed by analysis using MetaboAnalyst 3.0, was used to explore the chemical defence profiles of resistant, hypersensitive and susceptible phenotypes within Melaleuca quinquenervia during the early stages of A. psidii infection. We were able to identify three separate pools of secondary metabolites: (i) metabolites classified structurally as flavonoids that were naturally higher in the leaves of resistant individuals prior to infection, (ii) organoheterocyclic and carbohydrate-related metabolites that varied with the level of host resistance post-infection, and (iii) metabolites from the terpenoid pathways that were responsive to disease progression regardless of resistance phenotype suggesting that these play a minimal role in disease resistance during the early stages of colonization of this species. Based on the classes of these secondary metabolites, our results provide an improved understanding of key pathways that could be linked more generally to rust resistance with particular application within Melaleuca.

Response of Transgenic Potato Plants Expressing Heterologous Genes of ∆9- or ∆12-Acyl-lipid Desaturases to Phytophthora infestans Infection

Late blight is one of the most economically important diseases affecting potato and causing a significant loss in yield. The development of transgenic potato plants with enhanced resistance to infection by Phytophthora infestans may represent a possible approach to solving this issue. A comparative study of the leaf response in control potato plants (S.tuberosum L. cultivar Skoroplodnyi), control transgenic plants expressing the reporter gene of thermostable lichenase (transgenic licBM3 line) and transgenic plants expressing cyanobacterial hybrid genes ∆9-acyl-lipid desaturase (transgenic desC lines) and ∆12-acyl-lipid desaturase (transgenic desA lines) to infection with P. infestans has been performed. The expression of desaturase genes in potato plants enhanced their tolerance to potato late blight agents as compared with the control. The lipid peroxidation level raised in the leaves of the control and transgenic desA plants on third day after inoculation with P. infestans zoospores and remained the same in the transgenic desC plants. The number of total phenolic compounds was increased as early as on the second day after infection in all studied variants and continued to remain the same, except for transgenic desC plants. Accumulation of flavonoids, the main components of the potato leaf phenolic complex, raised on the second day in all studied variants, remained unchanged on the third day in the control plants and decreased in most transgenic plants expressing desaturase genes. The results obtained in our study demonstrate that the expression of genes of Δ9- and Δ12-acyl-lipid desaturases in potato plants enhanced their resistance to P. infestans as compared with the control non-transgenic plants due to concomitant accumulation of phenolic compounds, including flavonoids, in the leaves. All these changes were more pronounced in transgenic desC plants, which indicates that the Δ9-acyllipid desaturase gene appears to be a potential inducer of the production of biological antioxidants in plant cells.

Root infection by the nematode Meloidogyne incognita modulates leaf antiherbivore defenses and plant resistance to Spodoptera exigua

Studies on plant-mediated interactions between root parasitic nematodes and aboveground herbivores are rapidly increasing. However, outcomes for the interacting organisms vary, and the mechanisms involved remain ambiguous. We hypothesized that the impact of root infection by the root-knot nematode Meloidogyne incognita on the performance of the aboveground caterpillar Spodoptera exigua is modulated by the nematode's infection cycle. We challenged root-knot nematode-infected tomato plants with caterpillars when the nematode's infection cycle was at the invasion, galling, and reproduction stages. We found that M. incognita root infection enhanced S. exigua performance during the galling stage, while it did not affect the caterpillar's performance at the invasion and reproduction stages. Molecular and chemical analyses performed at the different stages of the nematode infection cycle revealed that M. incognita root infection systemically affected the jasmonic acid-, salicylic acid-, and abscisic acid-related responses, as well as the changes in the leaf metabolome triggered during S. exigua feeding. The M. incognita-induced leaf responses varied over the nematode's root infection cycle. These findings suggest that specific leaf responses triggered systemically by the nematode at its different life-cycle stages underlie the differential impact of M. incognita on plant resistance against the caterpillar S. exigua.

Non-Targeted Metabolite Profiling Reveals Host Metabolomic Reprogramming during the Interaction of Black Pepper with Phytophthora capsici

Phytophthora capsici is one of the most destructive pathogens causing quick wilt (foot rot) disease in black pepper (Piper nigrum L.) to which no effective resistance has been defined. To better understand the P. nigrum-P. capsici pathosystem, we employed metabolomic approaches based on flow-infusion electrospray-high-resolution mass spectrometry. Changes in the leaf metabolome were assessed in infected and systemic tissues at 24 and 48 hpi. Principal Component Analysis of the derived data indicated that the infected leaves showed a rapid metabolic response by 24 hpi whereas the systemic leaves took 48 hpi to respond to the infection. The major sources of variations between infected leaf and systemic leaf were identified, and enrichment pathway analysis indicated, major shifts in amino acid, tricarboxylic acid cycle, nucleotide and vitamin B6 metabolism upon infection. Moreover, the individual metabolites involved in defensive phytohormone signalling were identified. RT-qPCR analysis of key salicylate and jasmonate biosynthetic genes indicated a transient reduction of expression at 24 hpi but this increased subsequently. Exogenous application of jasmonate and salicylate reduced P. capsici disease symptoms, but this effect was suppressed with the co-application of abscisic acid. The results are consistent with abscisic acid reprogramming, salicylate and jasmonate defences in infected leaves to facilitate the formation of disease. The augmentation of salicylate and jasmonate defences could represent an approach through which quick wilt disease could be controlled in black pepper.

Metabolite mass spectrometry profiling of cacao genotypes reveals contrasting resistances to Ceratocystis cacaofunesta phytopathogen

Ceratocystis wilt is a lethal disease of cacao, and the search for resistant genotypes may provide the best way to deal with the disease. Resistance or susceptibility behavior of some cacao genotypes when infected by Ceratocystis cacaofunesta is not yet understood. Herein, we report an LC-MS metabolomic screening analysis based on high-resolution MS to obtain comprehensive metabolic profile associated with multivariate data analysis of PLS-DA, which was effective to classify CCN-51 and TSH-1188 as resistant genotypes to C. cacaofunesta fungus, while CEPEC2002 was classified as a susceptible one. Using reversed-phase LC method, electrospray interface, and high-resolution tandem MS by the quadrupole-TOF analyzer, the typical profiles of metabolites, such as phenylpropanoids, flavonoids, lipids, alkaloids, and amino acids, were obtained. Untargeted metabolite profiles were used to construct discriminant analysis by partial least squares (PLS-DA)-derived loading plots, which placed the cacao genotypes into two major clusters related to susceptible or resistant groups. Linolenic, linoleic, oleic, stearic, arachidonic, and asiatic acids were annotated metabolites of infected, susceptible, and resistant genotypes, while methyl jasmonate, jasmonic acid, hydroxylated jasmonic acid, caffeine, and theobromine were annotated as constituents of the resistant genotypes. Trends of these typical metabolites levels revealed that CCN51 is susceptible, CEPEC2002 is moderately susceptible, and TSH1188 is resistant to C. cacaofunesta. Therefore, profiles of major metabolites as screened by LC-MS offer an efficient tool to reveal the level of resistance of cacao genotypes to C. cacaofunesta present in any farm around the world.

Metabolomic Evaluation of Tissue-Specific Defense Responses in Tomato Plants Modulated by PGPR-Priming against Phytophthora capsici Infection

Plant growth-promoting rhizobacteria (PGPR) can stimulate disease suppression through the induction of an enhanced state of defense readiness. Here, untargeted ultra-high performance liquid chromatography–mass spectrometry (UHPLC–MS) and targeted ultra-high performance liquid chromatography coupled to triple-quadrupole mass spectrometry (UHPLC–QqQ-MS) were used to investigate metabolic reprogramming in tomato plant tissues in response to priming by Pseudomonas fluorescens N04 and Paenibacillus alvei T22 against Phytophthora capsici. Roots were treated with the two PGPR strains prior to stem inoculation with Ph. capsici. Metabolites were methanol-extracted from roots, stems and leaves at two–eight days post-inoculation. Targeted analysis by UHPLC–QqQ-MS allowed quantification of aromatic amino acids and phytohormones. For untargeted analysis, UHPLC–MS data were chemometrically processed to determine signatory biomarkers related to priming against Ph. capsici. The aromatic amino acid content was differentially reprogrammed in Ps. fluorescens and Pa. alvei primed plants responding to Ph. capsici. Furthermore, abscisic acid and methyl salicylic acid were found to be major signaling molecules in the tripartite interaction. LC–MS metabolomics analysis showed time-dependent metabolic changes in the primed-unchallenged vs. primed-challenged tissues. The annotated metabolites included phenylpropanoids, benzoic acids, glycoalkaloids, flavonoids, amino acids, organic acids, as well as oxygenated fatty acids. Tissue-specific reprogramming across diverse metabolic networks in roots, stems and leaves was also observed, which demonstrated that PGPR priming resulted in modulation of the defense response to Ph. capsici infection.

MALDI-TOF MS as a method for rapid identification of Phytophthora de Bary, 1876

The number of described species of the oomycete genus Phytophthora is growing rapidly, highlighting the need for low-cost, rapid tools for species identification. Here, a collection of 24 Phytophthora species (42 samples) from natural as well as anthropogenic habitats were genetically identified using the internal transcribed spacer (ITS) and cytochrome c oxidase subunit I (COI) regions. Because genetic identification is time consuming, we have created a complementary method based on by matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). Both methods were compared and hypothesis that the MALDI-TOF MS method can be a fast and reliable method for the identification of oomycetes was confirmed. Over 3500 mass spectra were acquired, manually reviewed for quality control, and consolidated into a single reference library using the Bruker MALDI Biotyper platform. Finally, a database containing 144 main spectra (MSPs) was created and published in repository. The method presented in this study will facilitate the use of MALDI-TOF MS as a complement to existing approaches for fast, reliable identification of Phytophthora isolates.

Deciphering Prunus Responses to PPV Infection: A Way toward the Use of Metabolomics Approach for the Diagnostic of Sharka Disease

Sharka disease, caused by Plum pox virus (PPV), induces several changes in Prunus. In leaf tissues, the infection may cause oxidative stress and disrupt the photosynthetic process. Moreover, several defense responses can be activated after PPV infection and have been detected at the phytohormonal, transcriptomic, proteomic, and even translatome levels. As proposed in this review, some responses may be systemic and earlier to the onset of symptoms. Nevertheless, these changes are highly dependent among species, variety, sensitivity, and tissue type. In the case of fruit tissues, PPV infection can modify the ripening process, induced by an alteration of the primary metabolism, including sugars and organic acids, and secondary metabolism, including phenolic compounds. Interestingly, metabolomics is an emerging tool to better understand Prunus–PPV interactions mainly in primary and secondary metabolisms. Moreover, through untargeted metabolomics analyses, specific and early candidate biomarkers of PPV infection can be detected. Nevertheless, these candidate biomarkers need to be validated before being selected for a diagnostic or prognosis by targeted analyses. The development of a new method for early detection of PPV-infected trees would be crucial for better management of the outbreak, especially since there is no curative treatment.

Metabolomic Response of Tomatoes (Solanum lycopersicum L.) against Bacterial Wilt (Ralstonia solanacearum) Using 1H-NMR Spectroscopy

Ralstonia solanacearum is the pathogen responsible for wilting, yield losses, and death in tomato plants. The use of resistant cultivars has been proven as the most appropriate solution to controlling this pathogen. Therefore, further study of host-plant resistance mechanisms in tomatoes is urgently needed. ¹H-NMR (nuclear magnetic resonance) spectroscopy combined with multivariate data analysis has been used to identify the biochemical compounds that play a crucial role in the defense mechanisms of tomato against bacterial wilt. Eleven metabolites consisting of amino acids, sugars and organic acids were identified and presented at different concentrations in each cultivar. Leucine and valine were determined as distinguishable metabolites of resistant and susceptible cultivars. Permata and Hawaii 7996 as resistant cultivars had a significant decrease of valine after inoculation about 1.5-2 times compared to the susceptible cultivar (GM2). Meanwhile, the resistant cultivars had a higher level of leucine, about 1.3-1.5 times compared to the susceptible ones. Synthesis of leucine and valine are linked as a member of the pyruvate family. Therefore, the decrease in valine may be related to the higher need for leucine to form the leucine-rich receptor, which plays a role in the plant's immune system against the bacterial wilt.

Signaling in the Tomato Immunity against Fusarium oxysporum

New strategies of control need to be developed with the aim of economic and environmental sustainability in plant and crop protection. Metabolomics is an excellent platform for both understanding the complex plant-pathogen interactions and unraveling new chemical control strategies. GC-MS-based metabolomics, along with a phytohormone analysis of a compatible and incompatible interaction between tomato plants and Fusarium oxysporum f. sp. lycopersici, revealed the specific volatile chemical composition and the plant signals associated with them. The susceptible tomato plants were characterized by the over-emission of methyl- and ethyl-salicylate as well as some fatty acid derivatives, along with an activation of salicylic acid and abscisic acid signaling. In contrast, terpenoids, benzenoids, and 2-ethylhexanoic acid were differentially emitted by plants undergoing an incompatible interaction, together with the activation of the jasmonic acid (JA) pathway. In accordance with this response, a higher expression of several genes participating in the biosynthesis of these volatiles, such as MTS1, TomloxC,TomloxD, and AOS, as well as JAZ7, a JA marker gene, was found to be induced by the fungus in these resistant plants. The characterized metabolome of the immune tomato plants could lead to the development of new resistance inducers against Fusarium wilt treatment.

Magnaporthe oryzae systemic defense trigger 1 (MoSDT1)-mediated metabolites regulate defense response in Rice

BACKGROUND

Some of the pathogenic effector proteins play an active role in stimulating the plant defense system to strengthen plant resistance.

RESULTS

In this study, ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC/Q-TOF-MS) was implemented to identify altered metabolites in transgenic rice containing over-expressed M. oryzae Systemic Defense Trigger 1 (MoSDT1) that was infected at three-time points. The characterized dominating metabolites were organic acids and their derivatives, organic oxygen compounds, lipids, and lipid-like molecules. Among the identified metabolites, shikimate, galactinol, trehalose, D-mannose, linolenic acid, dopamine, tyramine, and L-glutamine are precursors for the synthesis of many secondary defense metabolites Carbohydrate, as well as amino acid metabolic, pathways were revealed to be involved in plant defense responses and resistance strengthening.

CONCLUSION

The increasing salicylic acid (SA) and jasmonic acid (JA) content enhanced interactions between JA synthesis/signaling gene, SA synthesis/receptor gene, raffinose/fructose/sucrose synthase gene, and cell wall-related genes all contribute to defense response in rice. The symptoms of rice after M. oryzae infection were significantly alleviated when treated with six identified metabolites, i.e., galactol, tyramine, L-glutamine, L-tryptophan, α-terpinene, and dopamine for 72 h exogenously. Therefore, these metabolites could be utilized as an optimal metabolic marker for M. oryzae defense.

Concurrent Metabolic Profiling and Quantification of Aromatic Amino Acids and Phytohormones in Solanum lycopersicum Plants Responding to Phytophthora capsici

Pathogenic microorganisms account for large production losses in the agricultural sector. Phytophthora capsici is an oomycete that causes blight and fruit rot in important crops, especially those in the Solanaceae family. P. capsici infection is difficult to control due to genetic diversity, arising from sexual reproduction, and resistant spores that remain dormant in soil. In this study, the metabolomics of tomato plants responding to infection by P. capsici were investigated. Non-targeted metabolomics, based on liquid chromatography coupled to mass spectrometry (LC-MS), were used with multivariate data analyses to investigate time-dependent metabolic reprogramming in the roots, stems, and leaves of stem-infected plants, over an 8 day period. In addition, phytohormones and amino acids were determined using quantitative LC-MS. Methyl salicylate and 1-aminocyclopropane-1-carboxylate were detected as major signalling molecules in the defensive response to P. capsici. As aromatic amino acid precursors of secondary metabolic pathways, both phenylalanine and tryptophan showed a continuous increase over time in all tissues, whereas tyrosine peaked at day 4. Non-targeted metabolomic analysis revealed phenylpropanoids, benzoic acids, glycoalkaloids, flavonoids, amino acids, organic acids, and fatty acids as the major classes of reprogrammed metabolites. Correlation analysis showed that metabolites derived from the same pathway, or synthesised by different pathways, could either have a positive or negative correlation. Furthermore, roots, stems, and leaves showed contrasting time-dependent metabolic reprogramming, possibly related to the biotrophic vs. necrotrophic life-stages of the pathogen, and overlapping biotic and abiotic stress signaling. As such, the targeted and untargeted approaches complemented each other, to provide a detailed view of key time-dependent metabolic changes, occurring in both the asymptomatic and symptomatic stages of infection.

Tomato Metabolic Changes in Response to Tomato-Potato Psyllid (Bactericera cockerelli) and Its Vectored Pathogen Candidatus Liberibacter solanacearum

The bacterial pathogen ‘Candidatus Liberibacter solanacearum’ (Lso) is transmitted by the tomato potato psyllid (TPP), Bactericera cockerelli, to solanaceous crops. In the present study, the changes in metabolic profiles of insect-susceptible (cv CastleMart) and resistant (RIL LA3952) tomato plants in response to TPP vectoring Lso or not, were examined after 48 h post infestation. Non-volatile and volatile metabolites were identified and quantified using headspace solid-phase microextraction equipped with a gas chromatograph-mass spectrometry (HS-SPME/GC-MS) and ultra-high pressure liquid chromatography coupled to electrospray quadrupole time-of-flight mass spectrometry (UPLC/ESI-HR-QTOFMS), respectively. Partial least squares-discriminant analysis (PLS-DA) was used to define the major uncorrelated metabolite components assuming the treatments as the correlated predictors. Metabolic changes in various classes of metabolites, including volatiles, hormones, and phenolics, were observed in resistant and susceptible plants in response to the insects carrying the pathogen or not. The results suggest the involvement of differentially regulated and, in some cases, implicates antagonistic metabolites in plant defensive signaling. Upon validation, the identified metabolites could be used as markers to screen and select breeding lines with enhanced resistance to reduce economic losses due to the TPP-Lso vector-pathogen complex in Solanaceous crops.

NMR Metabolomics Applied on the Discrimination of Variables Influencing Tomato (Solanum lycopersicum)

Tomato composition and nutritional value are attracting increasing attention and interest from both consumers and producers. The interest in enhancing fruits' quality with respect to beneficious nutrients and flavor/aroma components is based not only in their economic added value but also in their implications involving organoleptic and healthy properties and has generated considerable research interest among nutraceutical and horticultural industries. The present article reviews up to March 2020 some of the most relevant studies based on the application of NMR coupled to multivariate statistical analysis that have addressed the investigation on tomato (Solanum lycopersicum). Specifically, the NMR untargeted technique in the agri-food sector can generate comprehensive data on metabolic networks and is paving the way towards the understanding of variables affecting tomato crops and composition such as origin, variety, salt-water irrigation, cultivation techniques, stage of development, among many others. Such knowledge is helpful to improve fruit quality through cultural practices that divert the metabolism towards the desired pathways and, probably more importantly, drives further efforts towards the differentiation of those crops developed under controlled and desired agronomical conditions.

The impact of Spodoptera exigua herbivory on Meloidogyne incognita-induced root responses depends on the nematodes' life cycle stages

Induced responses to above-ground and below-ground herbivores may interact via systemic signalling in plants. We investigated whether the impact of above-ground herbivory on root-knot nematode-induced responses depends on the nematode's life cycle stages. Tomato plants were infected with the nematode (Meloidogyne incognita) for 5, 15 or 30 days before receiving Spodoptera exigua caterpillars above-ground. We collected root materials after 24 h of caterpillar feeding. We investigated phytohormones and α-tomatine levels, and the expression of defence and glycoalkaloid metabolism (GAME) marker genes in tomato roots. Nematode infection alone increased the endogenous root levels of jasmonic acid (JA), salicylic acid (SA), abscisic acid (ABA), α-tomatine and the expression of the GLYCOALKALOID METABOLISM 1 (GAME1) gene mostly at 30 days post-nematode inoculation. Caterpillar feeding alone upregulated Lipoxygenase D and downregulated Basic-β-1-glucanase and GAME1 expression in roots. On nematode-infected plants, caterpillar feeding decreased JA levels, but it increased the expression of Leucine aminopeptidase A. The induction patterns of ABA and SA suggest that caterpillars cause cross-talk between the JA-signalling pathway and the SA and ABA pathways. Our results show that caterpillar feeding attenuated the induction of the JA pathway triggered by nematodes, mostly in the nematodes' reproduction stage. These results generate a better understanding of the molecular and chemical mechanisms underlying frequent nematode-plant-caterpillar interactions in natural and agricultural ecosystems.

Investigating potato late blight physiological differences across potato cultivars with spectroscopy and machine learning

Understanding plant disease resistance is important in the integrated management of Phytophthora infestans, causal agent of potato late blight. Advanced field-based methods of disease detection that can identify infection before the onset of visual symptoms would improve management by greatly reducing disease potential and spread as well as improve both the financial and environmental sustainability of potato farms. In-vivo foliar spectroscopy offers the capacity to rapidly and non-destructively characterize plant physiological status, which can be used to detect the effects of necrotizing pathogens on plant condition prior to the appearance of visual symptoms. Here, we tested differences in spectral response of four potato cultivars, including two cultivars with a shared genotypic background except for a single copy of a resistance gene, to inoculation with Phytophthora infestans clonal lineage US-23 using three statistical approaches: random forest discrimination (RF), partial least squares discrimination analysis (PLS-DA), and normalized difference spectral index (NDSI). We find that cultivar, or plant genotype, has a significant impact on spectral reflectance of plants undergoing P. infestans infection. The spectral response of four potato cultivars to infection by Phytophthora infestans clonal lineage US-23 was highly variable, yet with important shared characteristics that facilitated discrimination. Early disease physiology was found to be variable across cultivars as well using non-destructively derived PLS-regression trait models. This work lays the foundation to better understand host-pathogen interactions across a variety of genotypic backgrounds, and establishes that host genotype has a significant impact on spectral reflectance, and hence on biochemical and physiological traits, of plants undergoing pathogen infection.

Metabolic Profiling of PGPR-Treated Tomato Plants Reveal Priming-Related Adaptations of Secondary Metabolites and Aromatic Amino Acids

Plant growth–promoting rhizobacteria (PGPR) are beneficial microbes in the rhizosphere that can directly or indirectly stimulate plant growth. In addition, some can prime plants for enhanced defense against a broad range of pathogens and insect herbivores. In this study, four PGPR strains (Pseudomonas fluorescens N04, P. koreensis N19, Paenibacillus alvei T19, and Lysinibacillus sphaericus T22) were used to induce priming in Solanum lycopersicum (cv. Moneymaker) plants. Plants were inoculated with each of the four PGPRs, and plant tissues (roots, stems, and leaves) were harvested at 24 h and 48 h post-inoculation. Methanol-extracted metabolites were analyzed by ultra-high performance liquid chromatography mass spectrometry (UHPLC-MS). Chemometric methods were applied to mine the data and characterize the differential metabolic profiles induced by the PGPR. The results revealed that all four strains induced defense-related metabolic reprogramming in the plants, characterized by dynamic changes to the metabolomes involving hydroxycinnamates, benzoates, flavonoids, and glycoalkaloids. In addition, targeted analysis of aromatic amino acids indicated differential quantitative increases or decreases over a two-day period in response to the four PGPR strains. The metabolic alterations point to an altered or preconditioned state that renders the plants primed for enhanced defense responses. The results contribute to ongoing efforts in investigating and unraveling the biochemical processes that define the PGPR priming phenomenon.

Contact Reflectance Spectroscopy for Rapid, Accurate, and Nondestructive Phytophthora infestans Clonal Lineage Discrimination

Populations of Phytophthora infestans, the oomycete causal agent of potato late blight in the United States, are predominantly asexual, and isolates are characterized by clonal lineage or asexual descendants of a single genotype. Current tools for clonal lineage identification are time consuming and require laboratory equipment. We previously found that foliar spectroscopy can be used for high-accuracy pre- and postsymptomatic detection of P. infestans infections caused by clonal lineages US-08 and US-23. In this work, we found subtle but distinct differences in spectral responses of potato foliage infected by these clonal lineages in both growth-chamber time-course experiments (12- to 24-h intervals over 5 days) and naturally infected samples from commercial production fields. In both settings, we measured continuous visible to shortwave infrared reflectance (400 to 2,500 nm) on leaves using a portable spectrometer with contact probe. We consistently discriminated between infections caused by the two clonal lineages across all stages of disease progression using partial least squares (PLS) discriminant analysis, with total accuracies ranging from 88 to 98%. Three-class random forest differentiation between control, US-08, and US-23 yielded total discrimination accuracy ranging from 68 to 76%. Differences were greatest during presymptomatic infection stages and progressed toward uniformity as symptoms advanced. Using PLS-regression trait models, we found that total phenolics, sugar, and leaf mass per area were different between lineages. Shortwave infrared wavelengths (>1,100 nm) were important for clonal lineage differentiation. This work provides a foundation for future use of hyperspectral sensing as a nondestructive tool for pathovar differentiation.

Omics applications: towards a sustainable protection of tomato

Transcriptome data and gene expression analysis have a huge potential in the study of multiple relationships involving plants, pathogens, and pests, including the interactions with beneficial microorganisms such as endophytes or other functional groups. Next-generation sequencing (NGS) and other recent long-read-based sequencing approaches (i.e., nanopore and others) provide unprecedented tools allowing the fast identification of plant information processing systems, in situ and in real time, fundamental for crop management and pest regulation. Other -omics approaches such as metagenomics and metatranscriptomics allow high-resolution insights on the rhizosphere ecology. They may highlight key factors affecting belowground biodiversity or processes, modulating the expression of stress-responsive pathways. The application of miRNAs and other small RNAs is a relatively new field of application, with enormous potential for the selective activation of defense pathways. However, limitations concerning the stability of the RNA molecules and their effective delivery must be overcome.

Metabolomic applications for understanding complex tripartite plant-microbes interactions: Strategies and perspectives

Phytopathogens from the Alternaria sp., Fusarium sp., Penicillium sp., and Pseudomonas sp. and their toxigenic metabolites - alternariol, fumonisin, citrinin, and coronatine respectively, negatively impact crop yields and sales by eliciting plant diseases and/or causing human and veterinary toxicoses upon the consumption of contaminated food. These phytopathogens and their associated toxins, however, are present and most likely in undetectable concentrations pre-harvest and post-harvest of many major staple crops. Metabolomic approaches have been used extensively for better characterizing and diagnosing human disease, plant disease and, their etiological agents. Their use in agro-industrial research focusing specifically on tripartite (plant - toxicogenic microbe - beneficial microbe) interactions is, however, limited. Since new approaches for eradicating food-borne pathogens, increasing crop productivity and improving agro-international trade are being sought worldwide, the consequent integration of metabolomic approaches and perspectives in crop protection strategies for better understanding plant - toxicogenic microbe - beneficial microbe interaction in tandem is discussed.

Hyperspectral Measurements Enable Pre-Symptomatic Detection and Differentiation of Contrasting Physiological Effects of Late Blight and Early Blight in Potato

In-vivo foliar spectroscopy, also known as contact hyperspectral reflectance, enables rapid and non-destructive characterization of plant physiological status. This can be used to assess pathogen impact on plant condition both prior to and after visual symptoms appear. Challenging this capacity is the fact that dead tissue yields relatively consistent changes in leaf optical properties, negatively impacting our ability to distinguish causal pathogen identity. Here, we used in-situ spectroscopy to detect and differentiate Phytophthora infestans (late blight) and Alternaria solani (early blight) on potato foliage over the course of disease development and explored non-destructive characterization of contrasting disease physiology. Phytophthora infestans, a hemibiotrophic pathogen, undergoes an obligate latent period of two–seven days before disease symptoms appear. In contrast, A. solani, a necrotrophic pathogen, causes symptoms to appear almost immediately when environmental conditions are conducive. We found that respective patterns of spectral change can be related to these differences in underlying disease physiology and their contrasting pathogen lifestyles. Hyperspectral measurements could distinguish both P. infestans-infected and A. solani-infected plants with greater than 80% accuracy two–four days before visible symptoms appeared. Individual disease development stages for each pathogen could be differentiated from respective controls with 89–95% accuracy. Notably, we could distinguish latent P. infestans infection from both latent and symptomatic A. solani infection with greater than 75% accuracy. Spectral features important for late blight detection shifted over the course of infection, whereas spectral features important for early blight detection remained consistent, reflecting their different respective pathogen biologies. Shortwave infrared wavelengths were important for differentiation between healthy and diseased, and between pathogen infections, both pre- and post-symptomatically. This proof-of-concept work supports the use of spectroscopic systems as precision agriculture tools for rapid and early disease detection and differentiation tools, and highlights the importance of careful consideration of underlying pathogen biology and disease physiology for crop disease remote sensing.

Prospects for the use of the tomato genetic collection of the FSBSI ARRIBPP to develop varieties with group resistance to Alternaria sp. and Phytophthora infestans (Mont.) de Bary

The resistance of mutant tomato lines to the main diseases upon the provocative infectious background was assessed. We used as experimental material 22 lines of the tomato genetic collection of the FSBSI ARRIBPP, Krasnodar. According to the results of assessing the damage by Alternaria sp. in the field it was found that line 41 exhibitted high resistance, there were no signs of disease damage. Mutant lines 80, 387, 434, 568, 620 showed resistance, the degree of the disease development varied within 1–8 %. Lines 172, 467, 509, 518 with a degree of development of 12–23 % were characterized by semi-resistance. Lines 41, 387 showed high resistance to P. infestans. No visible signs of damage by P. infestans were detected in these genotypes. Lines 341, 509, 518, 568 had semi-resistance to the pathogen, the degree of development varied from 10 to 18 %. The genotypes Mo 41 and 387 that showed high and relatively high resistance to Alternaria sp. and P. infestans are of the greatest interest for breeding and genetic work as sources of group resistance.

Hydrophilic Interaction Liquid Chromatography Coupled to Mass Spectrometry and Multivariate Analysis of the De Novo Pyrimidine Pathway Metabolites

In this study, we describe the optimization of a Hydrophilic Interaction Liquid Chromatography coupled to mass spectrometry (HILIC-MS) method for the evaluation of 14 metabolites related to the de novo synthesis of pyrimidines (dnSP) while using multivariate analysis, which is the metabolic pathway for pyrimidine nucleotide production. A multivariate design was used to set the conditions of the column temperature, flow of the mobile phase, additive concentration, gradient rate, and pH of the mobile phase in order to attain higher peak resolution and ionization efficiency in shorter analysis times. The optimization process was carried out while using factorial fractional designs, Box–Behnken design and central composite design while using two zwitterionic columns, ZIC-p-HILIC and ZIC-HILIC, polymeric, and silica-based columns, respectively. The factors were evaluated while using resolution (R), retention factor (k), efficiency of the column (N), and peak height (h) as the response variables. The best optimized conditions were found with the ZIC-p-HILIC column: elution gradient rate 2 min, pH 7.0, temperature 45 °C, mobile phase flow of 0.35 mL min⁻¹, and additive (ammonium acetate) concentration of 6 mM. The total analysis time was 28 min. The ZIC-p-HILIC LC-MS method yielded satisfactory results for linearity of calibration curves, limit of detection (LOD), and limit of quantification (LOQ). The method has been shown to be appropriate for the analysis of dnSP on samples of tomato plants that were infected with Phytophthora infestans.

Metabolic Model of the Phytophthora infestans-Tomato Interaction Reveals Metabolic Switches during Host Colonization

The oomycete pathogen Phytophthora infestans causes potato and tomato late blight, a disease that is a serious threat to agriculture. P. infestans is a hemibiotrophic pathogen, and during infection, it scavenges nutrients from living host cells for its own proliferation. To date, the nutrient flux from host to pathogen during infection has hardly been studied, and the interlinked metabolisms of the pathogen and host remain poorly understood. Here, we reconstructed an integrated metabolic model of P. infestans and tomato (Solanum lycopersicum) by integrating two previously published models for both species. We used this integrated model to simulate metabolic fluxes from host to pathogen and explored the topology of the model to study the dependencies of the metabolism of P. infestans on that of tomato. This showed, for example, that P. infestans, a thiamine auxotroph, depends on certain metabolic reactions of the tomato thiamine biosynthesis. We also exploited dual-transcriptome data of a time course of a full late blight infection cycle on tomato leaves and integrated the expression of metabolic enzymes in the model. This revealed profound changes in pathogen-host metabolism during infection. As infection progresses, P. infestans performs less de novo synthesis of metabolites and scavenges more metabolites from tomato. This integrated metabolic model for the P. infestans-tomato interaction provides a framework to integrate data and generate hypotheses about in planta nutrition of P. infestans throughout its infection cycle.IMPORTANCE Late blight disease caused by the oomycete pathogen Phytophthora infestans leads to extensive yield losses in tomato and potato cultivation worldwide. To effectively control this pathogen, a thorough understanding of the mechanisms shaping the interaction with its hosts is paramount. While considerable work has focused on exploring host defense mechanisms and identifying P. infestans proteins contributing to virulence and pathogenicity, the nutritional strategies of the pathogen are mostly unresolved. Genome-scale metabolic models (GEMs) can be used to simulate metabolic fluxes and help in unravelling the complex nature of metabolism. We integrated a GEM of tomato with a GEM of P. infestans to simulate the metabolic fluxes that occur during infection. This yields insights into the nutrients that P. infestans obtains during different phases of the infection cycle and helps in generating hypotheses about nutrition in planta.