Untargeted Metabolomics of Alternaria solani-Challenged Wild Tomato Species Solanum cheesmaniae Revealed Key Metabolite Biomarkers and Insight into Altered Metabolic Pathways

受到链格孢菌攻击的野生番茄品种 Solanum cheesmaniae 的非靶向代谢组学揭示了关键代谢物生物标志物并深入了解了改变的代谢途径

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作者:Dhananjaya Pratap Singh, Mansi Singh Bisen, Ratna Prabha, Sudarshan Maurya, Suresh Reddy Yerasu, Renu Shukla, Jagesh Kumar Tiwari, Krishna Kumar Chaturvedi, Md Samir Farooqi, Sudhir Srivastava, Anil Rai, Birinchi Kumar Sarma, Nagendra Rai, Prabhakar Mohan Singh, Tusar Kanti Behera, Mohamed A Farag

Abstract

Untargeted metabolomics of moderately resistant wild tomato species Solanum cheesmaniae revealed an altered metabolite profile in plant leaves in response to Alternaria solani pathogen. Leaf metabolites were significantly differentiated in non-stressed versus stressed plants. The samples were discriminated not only by the presence/absence of specific metabolites as distinguished markers of infection, but also on the basis of their relative abundance as important concluding factors. Annotation of metabolite features using the Arabidopsis thaliana (KEGG) database revealed 3371 compounds with KEGG identifiers belonging to biosynthetic pathways including secondary metabolites, cofactors, steroids, brassinosteroids, terpernoids, and fatty acids. Annotation using the Solanum lycopersicum database in PLANTCYC PMN revealed significantly upregulated (541) and downregulated (485) features distributed in metabolite classes that appeared to play a crucial role in defense, infection prevention, signaling, plant growth, and plant homeostasis to survive under stress conditions. The orthogonal partial least squares discriminant analysis (OPLS-DA), comprising a significant fold change (≥2.0) with VIP score (≥1.0), showed 34 upregulated biomarker metabolites including 5-phosphoribosylamine, kaur-16-en-18-oic acid, pantothenate, and O-acetyl-L-homoserine, along with 41 downregulated biomarkers. Downregulated metabolite biomarkers were mapped with pathways specifically known for plant defense, suggesting their prominent role in pathogen resistance. These results hold promise for identifying key biomarker metabolites that contribute to disease resistive metabolic traits/biosynthetic routes. This approach can assist in mQTL development for the stress breeding program in tomato against pathogen interactions.

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