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

Extracellular Vesicles Mimetic Design of Membrane Chimeric Nanovesicles for dsRNA Delivery in Spray-Induced Gene Silencing for Crop Protection

Spray-induced gene silencing (SIGS) presents a promising RNA interference (RNAi)-based crop protection strategy against eukaryotic phytopathogens. However, the application of SIGS faces challenges, such as the limited uptake of dsRNA by certain pathogens and the instability of dsRNA in the environment. This study introduces innovative biomimetic nanovesicles, called extracellular vesicle (EV) mimetic chimeric nanovesicles (ECNs), assembled from tomato leaf cell membranes and cationic sterosomes via the freeze-thaw method. Similar to the function of EVs in nucleic acid transport between cells, ECNs serve as a hybrid nanosystem to overcome the challenge of delivering exogenous dsRNA in Phytophthora infestans. When applied to SIGS, the superiority of ECNs in crop protection becomes more apparent, including high loading and protection of dsRNA, improved biosafety, and efficient internalization into pathogen and plant cells, all of which significantly enhance the efficacy of RNAi in preventing early infection of P. infestans to susceptible tomato plants. This study demonstrates that ECNs are promising RNA delivery vehicles and will promote the use of SIGS-based RNA pesticides in sustainable agricultural production.

Enhanced growth of wheat in contaminated fields via synthetic microbiome as revealed by genome-scale metabolic modeling

The relationship between plants and soil microbial communities is complex and subtle, with microbes playing a crucial role in plant growth. Autochthonous bioaugmentation and nutrient biostimulation are promising bioremediation methods for herbicides in contaminated agricultural soils, but how microbes interact to promote biodegradation and plant growth on barren fields, especially in response to the treatment of the herbicide bromoxynil after wheat seedlings, remains poorly understood. In this study, we explored the microbial community reassembly process from the three-leaf stage to the tillering stage of wheat and put forward the idea of using the overlapping results of three methods (network Zi-Pi analysis, LEfSe analysis, and Random Forest analysis) as keystones for the simplification and optimization of key microbial species in the soil. Then we used genome-scale metabolic models (GSMMs) to design a targeted synthetic microbiome for promoting wheat seedling growing. The results showed that carbon source was more helpful in enriching soil microbial diversity and promoting the role of functional microbial communities, which facilitated the degradation of bromoxynil. Designed a multifunctional synthetic consortium consisting of seven non-degraders which unexpectedly assisted in the degradation of indigenous bacteria, which increased the degradation rate of bromoxynil by 2.05 times, and when adding nutritional supplementation, it increased the degradation rate by 3.65 times. In summary, this study provides important insights for rational fertilization and precise microbial consortium management to improve plant seedling growth in contaminated fields.

Dual transcriptomic analysis reveals early induced Castanea defense-related genes and Phytophthora cinnamomi effectors

Phytophthora cinnamomi Rands devastates forest species worldwide, causing significant ecological and economic impacts. The European chestnut (Castanea sativa) is susceptible to this hemibiotrophic oomycete, whereas the Asian chestnuts (Castanea crenata and Castanea mollissima) are resistant and have been successfully used as resistance donors in breeding programs. The molecular mechanisms underlying the different disease outcomes among chestnut species are a key foundation for developing science-based control strategies. However, these are still poorly understood. Dual RNA sequencing was performed in C. sativa and C. crenata roots inoculated with P. cinnamomi. The studied time points represent the pathogen's hemibiotrophic lifestyle previously described at the cellular level. Phytophthora cinnamomi expressed several genes related to pathogenicity in both chestnut species, such as cell wall-degrading enzymes, host nutrient uptake transporters, and effectors. However, the expression of effectors related to the modulation of host programmed cell death (elicitins and NLPs) and sporulation-related genes was higher in the susceptible chestnut. After pathogen inoculation, 1,556 and 488 genes were differentially expressed by C. crenata and C. sativa, respectively. The most significant transcriptional changes occur at 2 h after inoculation (hai) in C. sativa and 48 hai in C. crenata. Nevertheless, C. crenata induced more defense-related genes, indicating that the resistant response to P. cinnamomi is controlled by multiple loci, including several pattern recognition receptors, genes involved in the phenylpropanoid, salicylic acid and ethylene/jasmonic acid pathways, and antifungal genes. Importantly, these results validate previously observed cellular responses for C. crenata. Collectively, this study provides a comprehensive time-resolved description of the chestnut-P. cinnamomi dynamic, revealing new insights into susceptible and resistant host responses and important pathogen strategies involved in disease development.

Modelling metabolic fluxes of tomato stems reveals that nitrogen shapes central metabolism for defence against Botrytis cinerea

Among plant pathogens, the necrotrophic fungus Botrytis cinerea is one of the most prevalent, leading to severe crop damage. Studies related to its colonization of different plant species have reported variable host metabolic responses to infection. In tomato, high N availability leads to decreased susceptibility. Metabolic flux analysis can be used as an integrated method to better understand which metabolic adaptations lead to effective host defence and resistance. Here, we investigated the metabolic response of tomato infected by B. cinerea in symptomless stem tissues proximal to the lesions for 7 d post-inoculation, using a reconstructed metabolic model constrained by a large and consistent metabolic dataset acquired under four different N supplies. An overall comparison of 48 flux solution vectors of Botrytis- and mock-inoculated plants showed that fluxes were higher in Botrytis-inoculated plants, and the difference increased with a reduction in available N, accompanying an unexpected increase in radial growth. Despite higher fluxes, such as those involved in cell wall synthesis and other pathways, fluxes related to glycolysis, the tricarboxylic acid cycle, and amino acid and protein synthesis were limited under very low N, which might explain the enhanced susceptibility. Limiting starch synthesis and enhancing fluxes towards redox and specialized metabolism also contributed to defence independent of N supply.

Infection of Phytophthora palmivora Isolates on Arabidopsis thaliana

Phytophthora palmivora, a hemibiotrophic oomycete, causes diseases in several economically important tropical crops, such as oil palm, which it is responsible for a devastating disease called bud rot (BR). Despite recent progress in understanding host resistance and virulence mechanisms, many aspects remain unknown in P. palmivora isolates from oil palm. Model pathosystems are useful for understanding the molecular interactions between pathogens and hosts. In this study, we utilized detached leaves and whole seedlings of Arabidopsis thaliana Col-0 to describe and evaluate the infection process of three P. palmivora isolates (CPPhZC-05, CPPhZC-04, CPPhZOC-01) that cause BR in oil palm. Two compatible isolates (CPPhZC-05 and CPPhZOC-01) induced aqueous lesions at 72 h post-inoculation (hpi), with microscopic visualization revealing zoospore encysting and appressorium penetration at 3 hpi, followed by sporangia generation at 72 hpi. In contrast, an incompatible isolate (CPPhZC-04) exhibited cysts that could not penetrate tissue, resulting in low leaf colonization. Gene expression of ten P. palmivora infection-related genes was quantified by RT-qPCR, revealing overexpression in compatible isolates, but not in the incompatible isolate. Additionally, key genes associated with salicylic acid (SA), jasmonic acid (JA), and ethylene (ET) in Arabidopsis exhibited regulation during interaction with the three isolates. These findings demonstrate that P. palmivora can infect Arabidopsis Col-0, and variability is observed in the interaction between Arabidopsis-Col-0 and P. palmivora isolates. Establishing this pathosystem is expected to enhance our understanding of P. palmivora's pathology and physiology.

Extracellular niche establishment by plant pathogens

The plant extracellular space, referred to as the apoplast, is inhabited by a variety of microorganisms. Reflecting the crucial nature of this compartment, both plants and microorganisms seek to control, exploit and respond to its composition. Upon sensing the apoplastic environment, pathogens activate virulence programmes, including the delivery of effectors with well-established roles in suppressing plant immunity. We posit that another key and foundational role of effectors is niche establishment - specifically, the manipulation of plant physiological processes to enrich the apoplast in water and nutritive metabolites. Facets of plant immunity counteract niche establishment by restricting water, nutrients and signals for virulence activation. The complex competition to control and, in the case of pathogens, exploit the apoplast provides remarkable insights into the nature of virulence, host susceptibility, host defence and, ultimately, the origin of phytopathogenesis. This novel framework focuses on the ecology of a microbial niche and highlights areas of future research on plant-microorganism interactions.

Genome-wide identification and expression profiles of the Phytophthora infestans responsive CYPome (cytochrome P450 complement) in Solanum tuberosum

Cytochrome P450s represent one of the largest protein families across all domains of life. In plants, biotic stress can regulate the expression of some P450 genes. However, the CYPome (cytochrome P450 complement) in Solanum tuberosum and its response to Phytophthora infestans infection remains unrevealed. In this study, 488 P450 genes were identified from potato genome, which can be divided into 41 families and 57 subfamilies. Responding to the infection of P. infestans, 375 potato P450 genes were expressed in late blight resistant or susceptible cultivars. A total of 14 P450 genes were identified as resistant related candidates, and 81 P450 genes were identified as late blight responsive candidates. Several phytohormone biosynthesis, brassinosteroid biosynthesis, and phenylpropanoid biosynthesis involved P450 genes were differentially expressed during the potato-pathogen interactions. This study firstly reported the CYPome in S. tuberosum, and characterized the expression patterns of these P450 genes during the infection of P. infestans.

The lncRNA20718-miR6022-RLPs module regulates tomato resistance to Phytophthora infestans

KEY MESSAGE

Sl-lncRNA20718 acts as an eTM of Sl-miR6022 regulating its expression thereby affecting SlRLP6/10 expression. SlRLP6/10 regulate PRs expression, ROS accumulation, and JA/ET content thereby affecting tomato resistance to P. infestans. Tomato (Solanum lycopersicum) is an important horticultural and cash crop whose yield and quality can be severely affected by Phytophthora infestans (P. infestans). Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) are widely involved in plant defense responses against pathogens. The involvement of Sl-lncRNA20718 and Sl-miR6022 in tomato resistance to P. infestans as well as the targeting of Sl-miR6022 to receptor-like protein genes (RLPs) were predicted in our previous study. However, uncertainty exists regarding their potential interaction as well as the molecular processes regulating tomato resistance. Here, we found that Sl-lncRNA20718 and Sl-miR6022 are positive and negative regulators of tomato resistance to P. infestans by gain- and loss-of-function experiments, respectively. Overexpression of Sl-lncRNA20718 decreased the expression of Sl-miR6022, induced the expression of PRs, reduced the diameter of lesions (DOLs), thereby enhanced disease resistance. A six-point mutation in the binding region of Sl-lncRNA20718 to Sl-miR6022 disabled the interaction, indicating that Sl-lncRNA20718 acts as an endogenous target mimic (eTM) of Sl-miR6022. We demonstrated that Sl-miR6022 cleaves SlRLP6/10. Overexpression of Sl-miR6022 decreases the expression levels of SlRLP6/10, induces the accumulation of reactive oxygen species (ROS) and reduces the content of JA and ET, thus inhibiting tomato resistance to P. infestans. In conclusion, our study provides detailed information on the lncRNA20718-miR6022-RLPs module regulating tomato resistance to P. infestans by affecting the expression of disease resistance-related genes, the accumulation of ROS and the phytohormone levels, providing a new reference for tomato disease resistance breeding.

Deciphering the underlying immune network of the potato defense response inhibition by Phytophthora infestans nuclear effector Pi07586 through transcriptome analysis

Phytophthora infestans, a highly destructive plant oomycete pathogen, is responsible for causing late blight in potatoes worldwide. To successfully infect host cells and evade immunity, P. infestans secretes various effectors into host cells and exclusively targets the host nucleus. However, the precise mechanisms by which these effectors manipulate host gene expression and reprogram defenses remain poorly understood. In this study, we focused on a nuclear-targeted effector, Pi07586, which has been implicated in immune suppression. Quantitative real-time PCR (qRT-PCR) analysis showed Pi07586 was significant up-regulation during the early stages of infection. Agrobacterium-induced transient expression revealed that Pi07586 localized in the nucleus of leaf cells. Overexpression of Pi07586 resulted in increased leaf colonization by P. infestans. RNA-seq analysis revealed that Pi07586 effectively suppressed the expression of PR-1C-like and photosynthetic antenna protein genes. Furthermore, high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS) analysis indicated that Pi07586 overexpression led to a substantial decrease in abscisic acid (ABA), jasmonic acid (JA), and jasmonoyl-isoleucine (JA-Ile) levels, while not affecting salicylic acid (SA) and indole-3-acetic acid (IAA) production. These findings shed new light on the modulation of plant immunity by Pi07586 and enhance our understanding of the intricate relationship between P. infestans and host plants.

Sparking a sulfur war between plants and pathogens

The biochemical versatility of sulfur (S) lends itself to myriad roles in plant-pathogen interactions. This review evaluates the current understanding of mechanisms by which pathogens acquire S from their plant hosts and highlights new evidence that plants can limit S availability during the immune responses. We discuss the discovery of host disease-susceptibility genes related to S that can be genetically manipulated to create new crop resistance. Finally, we summarize future research challenges and propose a research agenda that leverages systems biology approaches for a holistic understanding of this important element's diverse roles in plant disease resistance and susceptibility.

Analysis of QTLs and Candidate Genes for Tassel Symptoms in Maize Infected with Sporisorium reilianum

Heat smut is a fungal soil-borne disease caused by Sporisorium reilianum, and affects the development of male and female tassels. Our previous research found that the tassel symptoms in maize infected with Sporisorium reilianum significantly differed in inbred lines with Sipingtou blood, and exhibited stable heredity over time at multiple locations. In this study, cytological analysis demonstrated that the cellular organization structures of three typical inbred lines (Huangzao4, Jing7, and Chang7-2) showed significant discrepancies at the VT stage. QTLs that control the different symptoms of maize tassels infected with Sporisorium reilianum were located in two F₂ populations, which were constructed using three typical inbred lines. The BSA (bulked segregation analysis) method was used to construct mixed gene pools based on typical tassel symptoms. The QTLs of different symptoms of maize tassels infected with Sporisorium reilianum were detected with 869 SSR markers covering the whole maize genome. The mixed gene pools were screened with polymorphic markers between the parents. Additional SSR markers were added near the above marker to detect genotypes in partially single plants in F₂ populations. The QTL controlling tassel symptoms in the Huangzao4 and Jing7 lines was located on the bin 1.06 region, between the markers of umc1590 and bnlg1598, and explained 21.12% of the phenotypic variation with an additive effect of 0.6524. The QTL controlling the tassel symptoms of the Jing7 and Chang7-2 lines was located on the bin 2.07 region, between the markers of umc1042 and bnlg1335, and explained 11.26% phenotypic variation with an additive effect of 0.4355. Two candidate genes (ZmABP2 and Zm00001D006403) were identified by a conjoint analysis of label-free quantification proteome sequencings.

Comparative Metabolomic Profiling of Compatible and Incompatible Interactions Between Potato and Phytophthora infestans

Late blight is one of the main biological stresses limiting the potato yield; however, the biochemical mechanisms underlying the infection process of Phytophthora infestans remain unrevealed. In this study, the late blight-resistant potato cultivar Ziyun No.1 (R) and the susceptible cultivar Favorita (S) were inoculated with P. infestans. Untargeted metabolomics was used to study the changes of metabolites in the compatible and incompatible interactions of the two cultivars and the pathogen at 0, 48, and 96 h postinoculation (hpi). A total of 819 metabolites were identified, and the metabolic differences mainly emerged after 48 hpi. There were 198 and 115 differentially expressed metabolites (DEMs) in the compatible and incompatible interactions. These included 147 and 100 upregulated metabolites during the compatible and incompatible interactions, respectively. Among them, 73 metabolites were identified as the P. infestans-responsive DEMs. Furthermore, the comparisons between the two cultivars identified 57 resistance-related metabolites. Resistant potato cultivar had higher levels of salicylic acid and several upstream phenylpropanoid biosynthesis metabolites, triterpenoids, and hydroxycinnamic acids and their derivatives, such as sakuranetin, ferulic acid, ganoderic acid Mi, lucidenic acid D2, and caffeoylmalic acid. These metabolites play crucial roles in cell wall thickening and have antibacterial and antifungal activities. This study reports the time-course metabolomic responses of potatoes to P. infestans. The findings reveal the responses involved in the compatible and incompatible interactions of potatoes and P. infestans.

Metabolomic and Physiological Changes in Fagus sylvatica Seedlings Infected with Phytophthora plurivora and the A1 and A2 Mating Types of P. ×cambivora

Phytophthora infections are followed by histological alterations, physiological and metabolomic adjustments in the host but very few studies contemplate these changes simultaneously. Fagus sylvatica seedlings were inoculated with A1 and A2 mating types of the heterothallic P. ×cambivora and with the homothallic P. plurivora to identify plant physiological and metabolomic changes accompanying microscope observations of the colonization process one, two and three weeks after inoculation. Phytophthora plurivora-infected plants died at a faster pace than those inoculated with P. ×cambivora and showed higher mortality than P. ×cambivora A1-infected plants. Phytophthora ×cambivora A1 and A2 caused similar progression and total rate of mortality. Most differences in the physiological parameters between inoculated and non-inoculated plants were detected two weeks after inoculation. Alterations in primary and secondary metabolites in roots and leaves were demonstrated for all the inoculated plants two and three weeks after inoculation. The results indicate that P. plurivora is more aggressive to Fagus sylvatica seedlings than both mating types of P. ×cambivora while P. ×cambivora A1 showed a slower infection mode than P. ×cambivora A2 and led to minor plant metabolomic adjustments.

Chickpea Roots Undergoing Colonisation by Phytophthora medicaginis Exhibit Opposing Jasmonic Acid and Salicylic Acid Accumulation and Signalling Profiles to Leaf Hemibiotrophic Models

Hemibiotrophic pathogens cause significant losses within agriculture, threatening the sustainability of food systems globally. These microbes colonise plant tissues in three phases: a biotrophic phase followed by a biotrophic-to-necrotrophic switch phase and ending with necrotrophy. Each of these phases is characterized by both common and discrete host transcriptional responses. Plant hormones play an important role in these phases, with foliar models showing that salicylic acid accumulates during the biotrophic phase and jasmonic acid/ethylene responses occur during the necrotrophic phase. The appropriateness of this model to plant roots has been challenged in recent years. The need to understand root responses to hemibiotrophic pathogens of agronomic importance necessitates further research. In this study, using the root hemibiotroph Phytophthora medicaginis, we define the duration of each phase of pathogenesis in Cicer arietinum (chickpea) roots. Using transcriptional profiling, we demonstrate that susceptible chickpea roots display some similarities in response to disease progression as previously documented in leaf plant–pathogen hemibiotrophic interactions. However, our transcriptomic results also show that chickpea roots do not conform to the phytohormone responses typically found in leaf colonisation by hemibiotrophs. We found that quantified levels of salicylic acid concentrations in root tissues decreased significantly during biotrophy while jasmonic acid concentrations were significantly induced. This study demonstrated that a wider spectrum of plant species should be investigated in the future to understand the physiological changes in plants during colonisation by soil-borne hemibiotrophic pathogens before we can better manage these economically important microbes.

Comparison of the Distinct, Host-Specific Response of Three Solanaceae Hosts Induced by Phytophthora infestans

Three Solanaceae hosts (TSHs), S. tuberosum, N. benthamiana and S. lycopersicum, represent the three major phylogenetic clades of Solanaceae plants infected by Phytophthora infestans, which causes late blight, one of the most devastating diseases seriously affecting crop production. However, details regarding how different Solanaceae hosts respond to P. infestans are lacking. Here, we conducted RNA-seq to analyze the transcriptomic data from the TSHs at 12 and 24 h post P. infestans inoculation to capture early expression effects. Macroscopic and microscopic observations showed faster infection processes in S. tuberosum than in N. benthamiana and S. lycopersicum under the same conditions. Analysis of the number of genes and their level of expression indicated that distinct response models were adopted by the TSHs in response to P. infestans. The host-specific infection process led to overlapping but distinct in GO terms and KEGG pathways enriched for differentially expressed genes; many were tightly linked to the immune response in the TSHs. S. tuberosum showed the fastest response and strongest accumulation of reactive oxygen species compared with N. benthamiana and S. lycopersicum, which also had similarities and differences in hormone regulation. Collectively, our study provides an important reference for a better understanding of late blight response mechanisms of different Solanaceae host interactions.

Uncovering the Role of Metabolism in Oomycete-Host Interactions Using Genome-Scale Metabolic Models

Metabolism is the set of biochemical reactions of an organism that enables it to assimilate nutrients from its environment and to generate building blocks for growth and proliferation. It forms a complex network that is intertwined with the many molecular and cellular processes that take place within cells. Systems biology aims to capture the complexity of cells, organisms, or communities by reconstructing models based on information gathered by high-throughput analyses (omics data) and prior knowledge. One type of model is a genome-scale metabolic model (GEM) that allows studying the distributions of metabolic fluxes, i.e., the "mass-flow" through the network of biochemical reactions. GEMs are nowadays widely applied and have been reconstructed for various microbial pathogens, either in a free-living state or in interaction with their hosts, with the aim to gain insight into mechanisms of pathogenicity. In this review, we first introduce the principles of systems biology and GEMs. We then describe how metabolic modeling can contribute to unraveling microbial pathogenesis and host-pathogen interactions, with a specific focus on oomycete plant pathogens and in particular Phytophthora infestans. Subsequently, we review achievements obtained so far and identify and discuss potential pitfalls of current models. Finally, we propose a workflow for reconstructing high-quality GEMs and elaborate on the resources needed to advance a system biology approach aimed at untangling the intimate interactions between plants and pathogens.

Function identification of miR394 in tomato resistance to Phytophthora infestans

MiR394 plays a negative role in tomato resistance to late blight. The lncRNA40787 severing as an eTM for miR394 to regulate LCR and exerting functions in tomato resistance. Tomato (Solanum lycopersicum), which was used as model species for studying the mechanism of plant disease defense, is susceptible to multiple pathogens. Non-coding RNA (ncRNA) has a pivotal role in plants response to biological stresses. It has previously been observed that the expression level of miR394 changed significantly after the infection of various pathogens. However, there has been no detailed investigation of the accumulated or suppressed mechanism of miR394. Our previous study predicted three lncRNAs (lncRNA40787, lncRNA27177, and lncRNA42566) that contain miR394 endogenous target mimics (eTM), which may exist as the competitive endogenous RNAs (ceRNAs) of miR394. In our study, the transcription levels of these three lncRNAs were strongly up-regulated in tomato upon infection with P. infestans. In contrast with the three lncRNAs, the accumulation of miR394 was significantly suppressed. Based on the expression pattern, and value of minimum free energy (mfes) that represents the binding ability between lncRNA and miRNA, lncRNA40787 was chosen for further investigation. Results showed that overexpression of lncRNA40787 reduced the expression of miR394 along with decreased lesion area and enhanced disease resistance. Overexpression of miR394, however, decreased the expression of its target gene Leaf Curling Responsiveness (LCR), and suppressed the synthesis components genes of jasmonic acid (JA), depressing the resistance of tomato to P. infestans infection. Taken together, our findings indicated that miR394 can be decoyed by lncRNA40787, and negatively regulated the expression of LCR to enhance tomato susceptibility under P. infestans infection. Our study provided detailed information on the lncRNA40787-miR394-LCR regulatory network and serves as a reference for future research.

Unravelling Plant Responses to Stress-The Importance of Targeted and Untargeted Metabolomics

Climate change and an increasing population, present a massive global challenge with respect to environmentally sustainable nutritious food production. Crop yield enhancements, through breeding, are decreasing, whilst agricultural intensification is constrained by emerging, re-emerging, and endemic pests and pathogens, accounting for ~30% of global crop losses, as well as mounting abiotic stress pressures, due to climate change. Metabolomics approaches have previously contributed to our knowledge within the fields of molecular plant pathology and plant-insect interactions. However, these remain incredibly challenging targets, due to the vast diversity in metabolite volatility and polarity, heterogeneous mixtures of pathogen and plant cells, as well as rapid rates of metabolite turn-over. Unravelling the systematic biochemical responses of plants to various individual and combined stresses, involves monitoring signaling compounds, secondary messengers, phytohormones, and defensive and protective chemicals. This demands both targeted and untargeted metabolomics approaches, as well as a range of enzymatic assays, protein assays, and proteomic and transcriptomic technologies. In this review, we focus upon the technical and biological challenges of measuring the metabolome associated with plant stress. We illustrate the challenges, with relevant examples from bacterial and fungal molecular pathologies, plant-insect interactions, and abiotic and combined stress in the environment. We also discuss future prospects from both the perspective of key innovative metabolomic technologies and their deployment in breeding for stress resistance.

Computational Biology and Machine Learning Approaches to Understand Mechanistic Microbiome-Host Interactions

The microbiome, by virtue of its interactions with the host, is implicated in various host functions including its influence on nutrition and homeostasis. Many chronic diseases such as diabetes, cancer, inflammatory bowel diseases are characterized by a disruption of microbial communities in at least one biological niche/organ system. Various molecular mechanisms between microbial and host components such as proteins, RNAs, metabolites have recently been identified, thus filling many gaps in our understanding of how the microbiome modulates host processes. Concurrently, high-throughput technologies have enabled the profiling of heterogeneous datasets capturing community level changes in the microbiome as well as the host responses. However, due to limitations in parallel sampling and analytical procedures, big gaps still exist in terms of how the microbiome mechanistically influences host functions at a system and community level. In the past decade, computational biology and machine learning methodologies have been developed with the aim of filling the existing gaps. Due to the agnostic nature of the tools, they have been applied in diverse disease contexts to analyze and infer the interactions between the microbiome and host molecular components. Some of these approaches allow the identification and analysis of affected downstream host processes. Most of the tools statistically or mechanistically integrate different types of -omic and meta -omic datasets followed by functional/biological interpretation. In this review, we provide an overview of the landscape of computational approaches for investigating mechanistic interactions between individual microbes/microbiome and the host and the opportunities for basic and clinical research. These could include but are not limited to the development of activity- and mechanism-based biomarkers, uncovering mechanisms for therapeutic interventions and generating integrated signatures to stratify patients.

Late blight in tomato: insights into the pathogenesis of the aggressive pathogen Phytophthora infestans and future research priorities

This review provides insights into the molecular interactions between Phytophthora infestans and tomato and highlights research gaps that need further attention. Late blight in tomato is caused by the oomycota hemibiotroph Phytophthora infestans, and this disease represents a global threat to tomato farming. The pathogen is cumbersome to control because of its fast-evolving nature, ability to overcome host resistance and inefficient natural resistance obtained from the available tomato germplasm. To achieve successful control over this pathogen, the molecular pathogenicity of P. infestans and key points of vulnerability in the host plant immune system must be understood. This review primarily focuses on efforts to better understand the molecular interaction between host pathogens from both perspectives, as well as the resistance genes, metabolomic changes, quantitative trait loci with potential for improvement in disease resistance and host genome manipulation via transgenic approaches, and it further identifies research gaps and provides suggestions for future research priorities.

Reconstruction and analysis of a genome-scale metabolic model for Agrobacterium tumefaciens

The plant pathogen Agrobacterium tumefaciens causes crown gall disease and is a widely used tool for generating transgenic plants owing to its virulence. The pathogenic process involves a shift from an independent to a living form within a host plant. However, comprehensive analyses of metabolites, genes, and reactions contributing to this complex process are lacking. To gain new insights about the pathogenicity from the viewpoints of physiology and cellular metabolism, a genome-scale metabolic model (GSMM) was reconstructed for A. tumefaciens. The model, referred to as iNX1344, contained 1,344 genes, 1,441 reactions, and 1,106 metabolites. It was validated by analyses of in silico cell growth on 39 unique carbon or nitrogen sources and the flux distribution of carbon metabolism. A. tumefaciens metabolic characteristics under three ecological niches were modelled. A high capacity to access and metabolize nutrients is more important for rhizosphere colonization than in the soil, and substantial metabolic changes were detected during the shift from the rhizosphere to tumour environments. Furthermore, by integrating transcriptome data for tumour conditions, significant alterations in central metabolic pathways and secondary metabolite metabolism were identified. Overall, the GSMM and constraint-based analysis could decode the physiological and metabolic features of A. tumefaciens as well as interspecific interactions with hosts, thereby improving our understanding of host adaptation and infection mechanisms.

Interactions of tagatose with the sugar metabolism are responsible for Phytophthora infestans growth inhibition

Tagatose is a rare sugar metabolised by a limited number of microorganisms that inhibits a large spectrum of phytopathogens. In particular, tagatose inhibited Phytophthora infestans growth and negatively affected mitochondrial processes. However, the possible effects of tagatose on P. infestans metabolism have not yet been investigated. The aim of this study was to analyse the impact of this rare sugar on the sugar metabolism in P. infestans, in order to better understand its mode of action. Tagatose inhibited the growth of P. infestans with a precise reprogramming of the carbohydrate metabolism that involved a decrease of glucose, glucose-1-phosphate and mannose content and β-glucosidase activity. The combination of tagatose with common sugars led to three different responses and highlighted antagonistic interactions. In particular, glucose partially attenuated the inhibitory effects of tagatose, while fructose fully impaired tagatose-mediated growth inhibition and metabolite changes. Moreover, sucrose did not attenuate tagatose effects, suggesting that the inhibition of sucrose catabolism and the alteration of glucose-related pathways contributed to the growth inhibition caused by tagatose to P. infestans. The interactions of tagatose with the common sugar metabolism were found to be a key mode of action against P. infestans growth, which may represent the basis for the further development of tagatose as an eco-friendly fungicide.

Environment-coupled models of leaf metabolism

The plant leaf is the main site of photosynthesis. This process converts light energy and inorganic nutrients into chemical energy and organic building blocks for the biosynthesis and maintenance of cellular components and to support the growth of the rest of the plant. The leaf is also the site of gas–water exchange and due to its large surface, it is particularly vulnerable to pathogen attacks. Therefore, the leaf's performance and metabolic modes are inherently determined by its interaction with the environment. Mathematical models of plant metabolism have been successfully applied to study various aspects of photosynthesis, carbon and nitrogen assimilation and metabolism, aided suggesting metabolic intervention strategies for optimized leaf performance, and gave us insights into evolutionary drivers of plant metabolism in various environments. With the increasing pressure to improve agricultural performance in current and future climates, these models have become important tools to improve our understanding of plant–environment interactions and to propel plant breeders efforts. This overview article reviews applications of large-scale metabolic models of leaf metabolism to study plant–environment interactions by means of flux-balance analysis. The presented studies are organized in two ways — by the way the environment interactions are modelled — via external constraints or data-integration and by the studied environmental interactions — abiotic or biotic.

Genome-scale metabolic reconstruction of the symbiosis between a leguminous plant and a nitrogen-fixing bacterium

The mutualistic association between leguminous plants and endosymbiotic rhizobial bacteria is a paradigmatic example of a symbiosis driven by metabolic exchanges. Here, we report the reconstruction and modelling of a genome-scale metabolic network of Medicago truncatula (plant) nodulated by Sinorhizobium meliloti (bacterium). The reconstructed nodule tissue contains five spatially distinct developmental zones and encompasses the metabolism of both the plant and the bacterium. Flux balance analysis (FBA) suggests that the metabolic costs associated with symbiotic nitrogen fixation are primarily related to supporting nitrogenase activity, and increasing N2-fixation efficiency is associated with diminishing returns in terms of plant growth. Our analyses support that differentiating bacteroids have access to sugars as major carbon sources, ammonium is the main nitrogen export product of N2-fixing bacteria, and N2 fixation depends on proton transfer from the plant cytoplasm to the bacteria through acidification of the peribacteroid space. We expect that our model, called 'Virtual Nodule Environment' (ViNE), will contribute to a better understanding of the functioning of legume nodules, and may guide experimental studies and engineering of symbiotic nitrogen fixation.

Metabolomics to Exploit the Primed Immune System of Tomato Fruit

Tomato is a major crop suffering substantial yield losses from diseases, as fruit decay at a postharvest level can claim up to 50% of the total production worldwide. Due to the environmental risks of fungicides, there is an increasing interest in exploiting plant immunity through priming, which is an adaptive strategy that improves plant defensive capacity by stimulating induced mechanisms. Broad-spectrum defence priming can be triggered by the compound ß-aminobutyric acid (BABA). In tomato plants, BABA induces resistance against various fungal and bacterial pathogens and different methods of application result in durable protection. Here, we demonstrate that the treatment of tomato plants with BABA resulted in a durable induced resistance in tomato fruit against Botrytis cinerea, Phytophthora infestans and Pseudomonas syringae. Targeted and untargeted metabolomics were used to investigate the metabolic regulations that underpin the priming of tomato fruit against pathogenic microbes that present different infection strategies. Metabolomic analyses revealed major changes after BABA treatment and after inoculation. Remarkably, primed responses seemed specific to the type of infection, rather than showing a common fingerprint of BABA-induced priming. Furthermore, top-down modelling from the detected metabolic markers allowed for the accurate prediction of the measured resistance to fruit pathogens and demonstrated that soluble sugars are essential to predict resistance to fruit pathogens. Altogether, our results demonstrate that metabolomics is particularly insightful for a better understanding of defence priming in fruit. Further experiments are underway in order to identify key metabolites that mediate broad-spectrum BABA-induced priming in tomato fruit.