Abstract
Sugarcane smut disease, caused by the biotrophic fungus Sporisorium scitamineum, is characterized by the development of a whip-like structure from the plant meristem. The disease causes negative effects on sucrose accumulation, fiber content and juice quality. The aim of this study was to exam whether the transcriptomic changes already described during the infection of sugarcane by S. scitamineum result in changes at the metabolomic level. To address this question, an analysis was conducted during the initial stage of the interaction and through disease progression in a susceptible sugarcane genotype. GC-TOF-MS allowed the identification of 73 primary metabolites. A set of these compounds was quantitatively altered at each analyzed point as compared with healthy plants. The results revealed that energetic pathways and amino acid pools were affected throughout the interaction. Raffinose levels increased shortly after infection but decreased remarkably after whip emission. Changes related to cell wall biosynthesis were characteristic of disease progression and suggested a loosening of its structure to allow whip growth. Lignin biosynthesis related to whip formation may rely on Tyr metabolism through the overexpression of a bifunctional PTAL. The altered levels of Met residues along with overexpression of SAM synthetase and ACC synthase genes suggested a role for ethylene in whip emission. Moreover, unique secondary metabolites antifungal-related were identified using LC-ESI-MS approach, which may have potential biomarker applications. Lastly, a putative toxin was the most important fungal metabolite identified whose role during infection remains to be established.
Highlights
Sugarcane (Saccharum spp.) has long been recognized as one of the world’s most efficient crops in converting solar energy into harvestable chemical energy, storing exceptionally high concentrations of sucrose, which can achieve 25% of fresh weight under favorable conditions (Chandra, 2011)
The meristem region was analyzed at four time points during sugarcane-smut interaction: two representing the limits of the colonization process (5 and 120 days after inoculation (DAI)), as studied in previous experiments (Taniguti et al, 2015; Schaker et al, 2016); and two representing intermediate steps of the infection process (65 and 100 DAI)
Growing concentrations of the pathogen from 5 to 65 DAI were observed in inoculated plants using qPCR with DNA from the same samples used in metabolomic analysis
Summary
Sugarcane (Saccharum spp.) has long been recognized as one of the world’s most efficient crops in converting solar energy into harvestable chemical energy, storing exceptionally high concentrations of sucrose, which can achieve 25% of fresh weight under favorable conditions (Chandra, 2011). The carbon partitioning is directly related to the Metabolomics of Sugarcane Smut Disease well-established concept of source (photosynthetic) and sink (non-photosynthetic) tissues systems (McCormick et al, 2009), where sucrose is synthesized in source tissues, transported via phloem and distributed via apoplast (Robinson-Beers and Evert, 1991) and symplast (Rae et al, 2005). In mature tissues of sugarcane, the carbon skeletons are converted to sucrose and stored in cellular vacuoles, whereas, in younger tissues, they are used for building proteins and synthesizing cell wall fibers (Bindon and Botha, 2002; Rae et al, 2005). Carbon is partitioned into several compounds including organic acids, amino acids, proteins, cell wall components and secondary metabolites (Botha and Whittaker, 1997; Wang et al, 2013). Many studies have been carried out to identify the molecular basis of this disease, including changes in gene expression, protein accumulation and specific cell wall components, that can be used as determinants of resistance (Legaz et al, 1998; Piñon et al, 1999; Heinze et al, 2001; Fontaniella et al, 2002; Borrás-Hidalgo et al, 2005; Millanes et al, 2005; Lao et al, 2008; Santiago et al, 2009, 2010, 2012; Que et al, 2011; You-Xiong et al, 2011; Su et al, 2013; Wu et al, 2013; Esh, 2014; Huang et al, 2015; Barnabas et al, 2016; Peters, 2016; Schaker et al, 2016)
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