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Metabolic profiling for dissection of late leaf spot disease resistance mechanism in groundnut

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Abstract

Late leaf spot (LLS) caused by fungi Passalora personata is generally more destructive and difficult to control than early leaf spot. The aim of this study was to decipher biochemical defense mechanism in groundnut genotypes against P. personata by identifying resistance specific biomarkers and metabolic pathways induced during host–pathogen interaction. Metabolomics of non-infected and infected leaves of moderately resistant (GPBD4 and ICGV86590), resistant (KDG128 and RHRG06083) and susceptible (GG20, JL24 and TMV2) genotypes was carried out at 5 days after infection (65 days after sowing). Non-targeted metabolite analysis using GC–MS revealed total 77 metabolites including carbohydrates, sugar alcohols, amino acids, fatty acids, polyamines, phenolics, terpenes and sterols. Variable importance in projection (VIP) measure of partial least squares-discriminant analysis (PLS-DA) showed that resistant and moderately resistant genotypes possessed higher intensities of ribonic acid, cinnamic acid, malic acid, squalene, xylulose, galactose, fructose, glucose, β-amyrin and hydroquinone while susceptible genotypes had higher amount of gluconic acid 2-methoxime, ribo-hexose-3-ulose and gluconic acid. Heat map analysis showed that resistant genotypes had higher intensities of β-amyrin, hydroquinone in non-infected and malic acid, squalene, putrescine and 2,3,4-trihydroxybutyric acid in infected leaves. Dendrogram analysis further separated resistant genotypes in the same cluster along with infected moderately resistant genotypes. The most significant pathways identified are: linoleic acid metabolism, flavone and flavonol biosynthesis, cutin, suberin and wax biosynthesis, pentose and glucuronate interconversions, starch and sucrose metabolism, stilbenoid biosynthesis and ascorbate and aldarate metabolism. Targeted metabolite analysis further confirmed that resistant genotypes possessed higher content of primary metabolites sucrose, glucose, fructose, malic acid and citric acid. Moreover, resistant genotypes possessed higher content of salicylic, coumaric, ferulic, cinnamic, gallic acid (phenolic acids) and kaempferol, quercetin and catechin (flavonols). Thus metabolites having higher accumulation in resistant genotypes can be used as biomarkers for screening of LSS resistant germplasm. These results unravel that higher amount of primary metabolites leads to stimulate the accumulation of more amounts of secondary metabolites such as phenolic acid, flavanols, stilbenes and terpenoids (squalene and β-amyrin) biosynthesis which are ultimately involved in defense mechanism against LLS pathogen.

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Acknowledgements

Authors are thankful to the Director, ICAR-Directorate of Groundnut Research, Junagadh, India for providing all the necessary facilities and support to completing this experiment.

Funding

This work was carried out under Institute Project. External funning was not received for this work.

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Authors and Affiliations

  1. ICAR-Directorate of Groundnut Research, Post Box No.5, Junagadh, 362001, Gujarat, India

    M. K. Mahatma, Lokesh Kumar Thawait, K. S. Jadon, P. P. Thirumalaisamy, S. K. Bishi, Aman Verma & Narendra Kumar

  2. ICAR-Central Arid Zone Research Institute, Jodhpur, India

    K. S. Jadon

  3. ICAR-Indian Institute of Agricultural Biotechnology, Ranchi, India

    S. K. Bishi

  4. Food Testing Laboratory, Department of Biotechnology, Junagadh Agricultural University, Junagadh, 362 001, India

    Khyati J. Rathod & B. A. Golakiya

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  1. M. K. Mahatma
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  2. Lokesh Kumar Thawait
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  3. K. S. Jadon
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  4. P. P. Thirumalaisamy
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  7. Aman Verma
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  9. B. A. Golakiya
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Contributions

MKM conceived the study, performed and designed the experiments and drafted the manuscript. LKT carried out sugar and organic acid measurements and phenolics and metabolite extraction. KSJ, TPP, and NK carried out the pot and field experiments to screen groundnut genotypes KSJ and TPP also performed inoculation of disease. KJR carried out untargeted metabolites analysis by GC–MS and phenolics profiling by LC–MS/MS and data processing, SKB and AV performed the statistical analysis and interpretation of results of targeted metabolites. BAG contributed to interpretation of the data and editing of the MS.

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Correspondence to M. K. Mahatma.

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Mahatma, M.K., Thawait, L.K., Jadon, K.S. et al. Metabolic profiling for dissection of late leaf spot disease resistance mechanism in groundnut. Physiol Mol Biol Plants 27, 1027–1041 (2021). https://doi.org/10.1007/s12298-021-00985-5

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