Case Study: Metabolomic Analysis of Tomato Plant Infections

Tomato plants are frequently infected by a variety of pathogens, which can significantly impact their growth and yield. Metabolomics, a comprehensive discipline that studies metabolites in biological samples, has become an important tool for understanding plant responses to disease. In this case study, we explore how metabolomics analysis can be used to study infections in tomato plants, particularly those caused by bacterial and fungal pathogens.

Case Study 1: Tomato SlS5H-Mediated Pathogen-Specific Salicylic Acid Homeostasis Regulation Mechanism

Plants rely on a complex defense signaling network in their interactions with pathogens, with salicylic acid (SA) being a core hormone mediating disease resistance responses. SA homeostasis (synthesis, metabolism, and transformation) directly affects defense gene expression and disease resistance; however, its regulatory mechanisms vary depending on the pathogen type (e.g., viruses, bacteria, fungi), leaving unexplored areas of "pathogen-specific" regulation.

This case study uses the tomato SlS5H gene as the research object. Through multi-technology integration (metabolics + gene function verification + pathogen interaction analysis), it reveals the SlS5H-mediated pathogen-specific SA homeostasis regulation mechanism, providing a new perspective for understanding the flexibility of plant-pathogen interactions.

Experimental Design

• Targeted Metabolomics: HPLC was used to quantify SA and its hydroxylated product gentioic acid (GA), analyzing the dynamic changes under different pathogen infections and SlS5H silencing.
• Untargeted Metabolomics: UPLC-ESI-QTOF-MS was used to comprehensively analyze the metabolic network, combined with XCMS pretreatment and SIMCA-P principal component analysis (PCA) to identify differentially expressed metabolites (e.g., glycosylated SA in CEVd infection and phenolic substances in Pst infection).
• Quality Control: Random injection, QC samples (pooled samples), and blank injection were used to ensure data reliability.
• Mechanism Validation: By analyzing changes in SA metabolic flux (glycosylated SA, phenolic substances) in RNAi_SlS5H plants, combined with HPLC/UPLC-MS data, it was confirmed that SlS5H influences metabolic reprogramming by regulating SA hydroxylation (generating GA), ultimately determining the pathogen-specific defense phenotype.
• Mechanism linkage: Metabolomics data combined with phenotype confirm that SlS5H determines pathogen-specific resistance by regulating SA→GA conversion and metabolic reprogramming (glycosylation/phenolic conversion).

Key Findings

• SlS5H is a key enzyme in the hydroxylation of SA to GA. Silencing SlS5H in tomatoes reprograms SA metabolism—SA accumulates via glycosylation under CEVd infection, and redirects to phenolic substances (such as ferulic acid derivatives) under Pst infection. Both enhance disease resistance, but the mechanisms vary depending on the pathogen.
• Different pathogens induce different levels of SlS5H expression (strong induction by CEVd, weak induction by Pst), resulting in pathogen-specific SA homeostasis regulation: CEVd depends on SA glycosylation, while Pst depends on SA conversion to phenols.

Studies have shown that plants regulate SA metabolic flux through SlS5H to adapt to the defense needs of different pathogens, revealing the flexibility and pathogen specificity of SA homeostasis in plant-pathogen interactions.

Figure 1: Evolution of free and glycosylated SA (A) and GA (B) accumulation in different genotypes tomato plants (Payá, C et al., 2022)

For more information on the role of plant metabolomics in plant-microbe interactions, please refer to our resource article on Plant Metabolomics in Plant–Microbe Interactions.

Case 2: Functional Analysis of Tomato Twi1 Glycosyltransferase in Plant Defense

Plants rely on secondary metabolites (such as coumarins and flavonoids) as antibacterial and antioxidant defense weapons when responding to biotic stress (such as pathogen infection). Most secondary metabolites accumulate as glycoconjugates, and their glycosylation modification is catalyzed by glycosyltransferases (GTs), which are key to regulating metabolite activity, stability, and transport. The tomato Twi1 gene has been annotated as "wound and SA-induced UGT (uridine diphosphate glycosyltransferase)," but its substrate specificity, physiological function, and role in defense remain unknown. This study aims to elucidate the function of Twi1 and reveal its role in plant secondary metabolite glycosylation and defense.

Experimental Design

Following the main line of "gene function verification - metabolomics analysis - pathogen interaction phenotype," this study uses in vitro biochemical assays, transgenic silent lines, and multidimensional metabolomics analysis to clarify the substrate profile and defensive functions of Twi1.

• Targeted metabolomics (HPLC fluorescence quantification): Analysis of flavonoids (scopoletin, esculetin, umbelliferone), phenolic acids (2,4-DHBA), etc., using a Waters 470 fluorescence detector (λ excitation 313nm/emission 405nm), quantified using external standard method.
• Untargeted metabolomics (UPLC-PDA-Q-ToF-MS): Analysis of flavonoids (quercetin, kaempferol), phenylpropanoids (p-coumaric acid, caffeic acid, etc.), using an ACQUITY UPLC-PDA system coupled with Q-ToF mass spectrometry, data acquisition in negative ESI mode, preprocessing on an XCMS online platform (chromatographic alignment, peak extraction), and partial least squares analysis (PLS) using SIMCA-P software to screen for differentially expressed metabolites.
• Quality control: Parallel sample and standard calibration, extraction recovery monitoring (50%-80%), ensuring data reliability.
• Gene manipulation: Full-length Twi1 cDNA was amplified by RT-PCR, and pGWB8-Twi1 (transient expression) and pART27-Twi1 (RNAi silencing) vectors were constructed. These vectors were transformed into Agrobacterium and then used to infect tobacco (transient expression) or tomato (silencing line RNAi_Twi1).
• Functional validation: Recombinant Twi1 protein was purified in vitro (Ni column affinity chromatography), and glycosyltransferase activity was measured (UDP-glucose/xylose as substrates). Twi1 expression was detected by qRT-PCR. Phenotypic analysis of transgenic lines was performed (virus symptom score, morbidity).

Key Findings

• In vitro biochemical assays confirmed that Twi1 can catalyze the glycosylation of coumarins (scopoletin, umbelliferone, esculetin) and flavonoids (quercetin, kaempferol) to generate stable glycoside products, with a substrate profile far exceeding the previous hypothesis of a "single UGT".
• Metabolomics analysis revealed a significant increase in the accumulation of Twi1 substrates (coumarins, quercetin, and kaempferol) and a decrease in their glycosylation products in RNAi_Twi1 transgenic tomatoes, indicating that Twi1 is a key enzyme regulating the homeostasis of these metabolites.
• Tomatoes with silenced Twi1 showed enhanced susceptibility to TSWV virus (more severe symptoms and higher morbidity), confirming that Twi1 enhances plant antiviral capabilities through glycosylation of secondary metabolites (such as flavonoids).
• Combining metabolomics (providing a comprehensive analysis of metabolite changes) with in vitro and in vivo experiments overcomes the limitations of traditional "sequence alignment predicting function," providing an efficient paradigm for functional annotation of UGT family members.

This case study, through "metabolomics + gene function verification," reveals that tomato Twi1 glycosyltransferase enhances plant antiviral capabilities by regulating the glycosylation of key defense metabolites such as coumarins and flavonoids, providing an important example for understanding plant secondary metabolic regulatory networks and UGT function research.

Figure 2：PLS analysis was performed on metabolites from leaves infected with Tomato Spot Virus (TSWV) (Campos, L et al., 2019)

Case 3: Metabolomics Analysis of Flagellin Recipient Sensing in Tomato and Regulation of Defense Metabolism

Plant innate immunity depends on the sensing of pathogen-derived molecules (such as flagellin-derived molecular patterns, MAMPs), activating signal cascades and synthesizing defense-related metabolites. As a model plant, the metabolic response mechanism of tomato to flagellin inducers (such as Flg22 and FlgII-28) is not fully understood. This study focuses on the dynamic changes in the metabolome of tomato plants after sensing Flg22/FlgII-28. Through untargeted metabolomics analysis of the MAMP-induced defense metabolic network, it reveals the signal transduction divergence and downstream metabolic reorganization patterns of different flagellin inducers, providing a new perspective for understanding plant immune metabolic regulation.

Experimental Design

The experimental design followed a main line of "flagellin inducer treatment - dynamic metabolomics monitoring - multivariate statistical analysis - metabolite functional annotation," combined with ROS detection (oxidative burst) to verify immune activation. Untargeted metabolomics was used to provide a comprehensive analysis of the tomato defense metabolic response.

• Untargeted metabolomics (UHPLC-HDMS): Analysis of dynamic changes in the full spectrum of metabolites.
• Analysis: UHPLC-HDMS (Acquity HSS T3 column, acetonitrile-0.1% formic acid gradient elution; SYNAPT G1 qTOF-MS, ESI source, positive and negative ion mode, m/z 50-1500, MSE fragmentation).
• Data Processing: MarkerLynx XS preprocessing (peak detection, alignment, normalization) → SIMCA 14.1 multivariate statistics (PCA unsupervised clustering, OPLS-DA supervised classification, VIP>1.0 for differential variables screening) → Database (Metlin, KEGG, MoTo) annotation (MSI level 2).
• Quality Control: Parallel samples (3 biological replicates), blank samples (50% methanol), QC samples (randomly inserted mixed samples), sample randomization, extraction recovery monitoring (50%-80%), ensuring data reliability.
• Gene Manipulation: No gene editing, immune response activated by treatment with exogenous flagellin peptides.
• ROS detection: DAB staining (H₂O₂ staining, brown precipitate) and fluorescence analysis (luminol-horseradish peroxidase luminescence, Synergy HT microplate reader, measured every 2 minutes, area under the curve ∑) were used to verify the oxidative burst kinetics.
• Phenotype analysis: Leaf symptoms (yellowing, necrosis) were recorded, and the incidence rate (percentage of infected leaves) was calculated to assess the strength of the defense response.

Key findings

• Oxidative burst and metabolic reprogramming: Both Flg22 and FlgII-28 induced ROS bursts (Flg22 responded faster), with significant perturbations in the metabolite profile within 16-32 hours (co-changing primary/secondary metabolism).
• Common defense metabolic characteristics: Activation of tyrosine metabolism, producing hydroxycinnamic acid conjugates (HCAAs) (such as feruloyltyramine and dopamine derivatives, with antioxidant/antibacterial activity); glutathione-S-caffeoylquinic acid conjugates appeared after 24 hours (scavenging oxidative damage).
• Signal transduction divergence: Differences in downstream metabolic remodeling between Flg22 and FlgII-28 (such as different steroid glycoalkaloid and lipid accumulation patterns) reflect inducer-specific regulation.
• Methodological value: Non-targeted metabolomics combined with multivariate statistics efficiently captures MAMP-induced "subtle metabolic perturbations," providing a paradigm for plant immune metabolism research.

Figure 3：PCA and HiCA models of UHPLC-MS ESI(–) data of extracts from tomato leaves (Zeiss, D.R et al., 2021)

Conclusion

The metabolomics changes following infection in tomato plants provide valuable insights into plant metabolic responses to pathogens. By identifying specific metabolites associated with resistance, researchers can develop targeted strategies to enhance the disease resistance of tomato crops.

Furthermore, metabolomics offers a more comprehensive perspective on plant-pathogen interactions, capturing complex changes across various metabolic pathways. This approach can also be extended to studying other crops and their responses to different pathogens, thus contributing to more sustainable agricultural practices.

References

1. Payá C, Minguillón S, Hernández M, Miguel SM, Campos L, Rodrigo I, Bellés JM, López-Gresa MP, Lisón P. SlS5H silencing reveals specific pathogen-triggered salicylic acid metabolism in tomato. BMC Plant Biol. 2022 Nov 29;22(1):549.
2. Campos L, López-Gresa MP, Fuertes D, Bellés JM, Rodrigo I, Lisón P. Tomato glycosyltransferase Twi1 plays a role in flavonoid glycosylation and defence against virus. BMC Plant Biol. 2019 Oct 26;19(1):450.
3. Zeiss DR, Steenkamp PA, Piater LA, Dubery IA. Altered metabolomic states elicited by Flg22 and FlgII-28 in Solanum lycopersicum: intracellular perturbations and metabolite defenses. BMC Plant Biol. 2021 Sep 21;21(1):429.