Structure-Based Mutational Analysis of eIF4E in Relation to sbm1 Resistance to Pea Seed-Borne Mosaic Virus in Pea

Background: Pea encodes eukaryotic translation initiation factor eIF4E (eIF4E(S)), which supports the multiplication of Pea seed-borne mosaic virus (PSbMV). In common with hosts for other potyviruses, some pea lines contain a recessive allele (sbm1) encoding a mutant eIF4E (eIF4E(R)) that fails to interact functionally with the PSbMV avirulence protein, VPg, giving genetic resistance to infection.

Multiplex Detection of Plant Pathogens Using a Microsphere Immunoassay Technology

Plant pathogens are a serious problem for seed export, plant disease control and plant quarantine. Rapid and accurate screening tests are urgently required to protect and prevent plant diseases spreading worldwide. A novel multiplex detection method was developed based on microsphere immunoassays to simultaneously detect four important plant pathogens: a fruit blotch bacterium Acidovorax avenae subsp. citrulli (Aac), chilli vein-banding mottle virus (CVbMV, potyvirus), watermelon silver mottle virus (WSMoV, tospovirus serogroup IV) and melon yellow spot virus (MYSV, tospovirus). An antibody for each plant pathogen was linked on a fluorescence-coded magnetic microsphere set which was used to capture corresponding pathogen. The presence of pathogens was detected by R-phycoerythrin (RPE)-labeled antibodies specific to the pathogens. The assay conditions were optimized by identifying appropriate antibody pairs, blocking buffer, concentration of RPE-labeled antibodies and assay time. Once conditions were optimized, the assay was able to detect all four plant pathogens precisely and accurately with substantially higher sensitivity than enzyme-linked immunosorbent assay (ELISA) when spiked in buffer and in healthy watermelon leaf extract. The assay time of the microsphere immunoassay (1 hour) was much shorter than that of ELISA (4 hours). This system was also shown to be capable of detecting the pathogens in naturally infected plant samples and is a major advancement in plant pathogen detection. © 2013 Charlermroj et al.