Abstract

BackgroundThe fight against grapevine diseases due to biotrophic pathogens usually requires the massive use of chemical fungicides with harmful environmental effects. An alternative strategy could be the use of compounds able to stimulate plant immune responses which significantly limit the development of pathogens in laboratory conditions. However, the efficiency of this strategy in natura is still insufficient to be included in pest management programs. To understand and to improve the mode of action of plant defense stimulators in the field, it is essential to develop reliable tools that describe the resistance status of the plant upon treatment.ResultsWe have developed a pioneering tool (“NeoViGen96” chip) based on a microfluidic dynamic array platform allowing the expression profiling of 85 defense-related grapevine genes in 90 cDNA preparations in a 4 h single run. Two defense inducers, benzothiadiazole (BTH) and fosetyl-aluminum (FOS), have been tested in natura using the “NeoViGen96” chip as well as their efficacy against downy mildew.BTH-induced grapevine resistance is accompanied by the induction of PR protein genes (PR1, PR2 and PR3), genes coding key enzymes in the phenylpropanoid pathway (PAL and STS), a GST gene coding an enzyme involved in the redox status and an ACC gene involved in the ethylene pathway.FOS, a phosphonate known to possess a toxic activity against pathogens and an inducing effect on defense genes provided a better grapevine protection than BTH. Its mode of action was probably strictly due to its fungicide effect at high concentrations because treatment did not induce significant change in the expression level of selected defense-related genes.ConclusionsThe NeoViGen96” chip assesses the effectiveness of plant defense inducers on grapevine in vineyard with an excellent reproducibility. A single run with this system (4 h and 1,500 €), corresponds to 180 qPCR plates with conventional Q-PCR assays (Stragene system, 270 h and 9,000 €) thus a throughput 60–70 times higher and 6 times cheaper. Grapevine responses after BTH elicitation in the vineyard were similar to those obtained in laboratory conditions, whereas our results suggest that the protective effect of FOS against downy mildew in the vineyard was only due to its fungicide activity since no activity on plant defense genes was observed. This tool provides better understanding of how the grapevine replies to elicitation in its natural environment and how the elicitor potential can be used to reduce chemical fungicide inputs.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3304-z) contains supplementary material, which is available to authorized users.

Highlights

  • The fight against grapevine diseases due to biotrophic pathogens usually requires the massive use of chemical fungicides with harmful environmental effects

  • Final steps correspond to the induction of defense genes, the production of secondary metabolites and the strengthening of cell walls, which all contribute to stopping the development of the pathogen [2, 3, 5]

  • We describe the construction of a new “NeoVigen96” chip allowing the detection of 85 defense markers and 11 genes used for standardization of expression on 95 Complementary Deoxynucleotidic acid (cDNA) preparations in a single run

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Summary

Results

We have developed a pioneering tool (“NeoViGen96” chip) based on a microfluidic dynamic array platform allowing the expression profiling of 85 defense-related grapevine genes in 90 cDNA preparations in a 4 h single run. Benzothiadiazole (BTH) and fosetyl-aluminum (FOS), have been tested in natura using the “NeoViGen96” chip as well as their efficacy against downy mildew. FOS, a phosphonate known to possess a toxic activity against pathogens and an inducing effect on defense genes provided a better grapevine protection than BTH. Its mode of action was probably strictly due to its fungicide effect at high concentrations because treatment did not induce significant change in the expression level of selected defense-related genes

Conclusions
Background
Methods

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