BackgroundArgonaute (AGO) proteins bind to small-interfering (si)RNAs and micro (mi)RNAs to target RNA silencing against viruses, transgenes and in regulation of mRNAs. Plants encode multiple AGO proteins but, in Arabidopsis, only AGO1 is known to have an antiviral role.Methodology/Principal FindingsTo uncover the roles of specific AGOs in limiting virus accumulation we inoculated turnip crinkle virus (TCV) to Arabidopsis plants that were mutant for each of the ten AGO genes. The viral symptoms on most of the plants were the same as on wild type plants although the ago2 mutants were markedly hyper-susceptible to this virus. ago2 plants were also hyper-susceptible to cucumber mosaic virus (CMV), confirming that the antiviral role of AGO2 is not specific to a single virus. For both viruses, this phenotype was associated with transient increase in virus accumulation. In wild type plants the AGO2 protein was induced by TCV and CMV infection.Conclusions/SignificanceBased on these results we propose that there are multiple layers to RNA-mediated defense and counter-defense in the interactions between plants and their viruses. AGO1 represents a first layer. With some viruses, including TCV and CMV, this layer is overcome by viral suppressors of silencing that can target AGO1 and a second layer involving AGO2 limits virus accumulation. The second layer is activated when the first layer is suppressed because AGO2 is repressed by AGO1 via miR403. The activation of the second layer is therefore a direct consequence of the loss of the first layer of defense.
Maize, a staple food in many African countries including Kenya, is often contaminated by toxic and carcinogenic fungal secondary metabolites such as aflatoxins and fumonisins. This study evaluated the potential use of a low-cost, multi-spectral sorter in identification and removal of aflatoxin-and fumonisin-contaminated single kernels from a bulk of mature maize kernels. The machine was calibrated by building a mathematical model relating reflectance at nine distinct wavelengths (470-1,550 nm) to mycotoxin levels of single kernels collected from small-scale maize traders in open-air markets and from inoculated maize field trials in Eastern Kenya. Due to the expected skewed distribution of mycotoxin contamination, visual assessment of putative risk factors such as discoloration, moldiness, breakage, and fluorescence under ultraviolet light (365 nm), was used to enrich for mycotoxin-positive kernels used for calibration. Discriminant analysis calibration using both infrared and visible spectra achieved 77% sensitivity and 83% specificity to identify kernels with aflatoxin > 10 ng g-1 and fumonisin > 1,000 ng g-1 , respectively (measured by ELISA or UHPLC). In subsequent sorting of 46 market maize samples previously tested for mycotoxins, 0-25% of sample mass was rejected from samples that previously tested toxin-positive and 0-1% was rejected for previously toxin-negative samples. In most cases where mycotoxins were detected in sorted maize streams, accepted maize had lower mycotoxin levels than the rejected maize (21/25 accepted maize streams had lower aflatoxin than rejected streams, 25/27 accepted maize streams had lower fumonisin than rejected streams). Reduction was statistically significant (p<0.001), achieving an 83% mean reduction in each toxin. With further development, this technology could be used to sort maize at local hammer mills to reduce human mycotoxin exposure in Kenya, and elsewhere in the world, while at once reducing food loss, and improving food safety and nutritional status.
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