Resistance associated metabolite profiling of Aspergillus leaf spot in cotton through non-targeted metabolomics

Abstract

Aspergillus tubingensis is an important pathogen of economically important crops. Different biotic stresses strongly influence the balance of metabolites in plants. The aim of this study was to understand the function and response of resistance associated metabolites which, in turn are involved in many secondary metabolomics pathways to influence defense mechanism of cotton plant. Analysis of non-targeted metabolomics using ultra high performance liquid chromatography-mass spectrometry (UPLC-MS) revealed abundant accumulation of key metabolites including flavonoids, phenylpropanoids, terpenoids, fatty acids and carbohydrates, in response to leaf spot of cotton. The principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA) and partial least squares discriminant analysis (PLS-DA) score plots illustrated the evidences of variation between two varieties of cotton under mock and pathogen inoculated treatments. Primary metabolism was affected by the up regulation of pyruvate and malate and by the accumulation of carbohydrates like cellobiose and inulobiose. Among 241 resistance related (RR) metabolites, 18 were identified as resistance related constitutive (RRC) and 223 as resistance related induced (RRI) metabolites. Several RRI metabolites, identified in the present study were the precursors for many secondary metabolic pathways. These included phenylpropanoids (stilbenes and furanocoumarin), flavonoids (phlorizin and kaempferol), alkaloids (indolizine and acetylcorynoline) and terpenoids (azelaic acid and oleanolic acid). Our results demonstrated that secondary metabolism, primary metabolism and energy metabolism were more active in resistant cultivar, as compared to sensitive cultivar. Differential protein and fatty acid metabolism was also depicted in both cultivars. Accumulation of these defense related metabolites in resistant cotton cultivar and their suppression in susceptible cotton cultivar revealed the reason of their respective tolerance and susceptibility against A. tubingensis.

WITHDRAWN: RNA-Seq based exploration of differentially expressed genes (DEGs) in cotton(Gossypium hirsutum. L) upon infection with Aspergillus tubingensis

“…Consistent with our metabolomics data, in which primary metabolites (sugar, amino acids, fatty acids) and secondary metabolites (alkaloids, terpenoids, pheylpropanoid) exhibited higher accumulation in resistant cultivar 17 .…”

“…Furthermore, transcription factors such as ethylene response factors (ERFs) and WRKYs can be triggered by MAPKs, and are involved in modulating plant defense 15 . A. tubingensis has been reported as a causal agent of leaf spot of cotton in Pakistan 16. Non-targeted metabolomics profiling of G. hirsutum infected with A. tubingensis has depicted ample accumulation of significant metabolites like carbohydrates, flavonoids, fatty acids, phenylpropanoids organic acids, terpenoids and fatty acids in tolerant cultivar 17 .…”

Genome Sequencing and Analysis Reveal the Mechanism of Terpenoids Biosynthesis in Deep-See-Derived Fungus Aspergillus Tubingensis

“…Secondary metabolites isolated from marine fungi have been found to have many important biological activities, such as anti-tumor, antibacterial, antioxidant, antiviral, anti-adhesion and so on (Moghadamtousi et al 2015). Although terpenoids account for about 20% of the total active ingredients in A. tubingensis, they play an important role because of their antitumor, antiviral and anti-in ammatory activities (Khizar et al 2020). Unfortunately, few studies have investigated the biosynthetic pathway of terpenoid, and the hereditary information or functional genes of A. tubingensis by omics sequencing technology is becoming more and more urgent to be investigated.…”

Endosphere Microbiome and Metabolic Differences Between the Spots and Green Parts of Tricyrtis macropoda Leaves

“…Plant microbiota, which is often called the second or extended genome of the host, may directly affect the metabolic activity of plants ( Khan et al, 2011 ; Brader et al, 2014 ; Huang et al, 2018 ), and it provides plants with a large number of functional capabilities that can aid in the metabolic processes of host plants encoded by their genomes ( Berendsen et al, 2012 ; Berg et al, 2014 ; Chen H. H. et al, 2018 ; Huang et al, 2018 ). In addition, some microorganisms may infect leaves, thus leading to the formation of plant leaf spots that are often harmful to plants ( Khizar et al, 2020 ; Lin et al, 2020 ). For example, Pseudocercospora fuligena will cause tomato leaves to show melatonin spots ( Kang et al, 2019 ).…”