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Sandwich Enzyme-Linked Immunosorbent Assay for Quantification of Callose

The existing methods of callose quantification include epifluorescence microscopy and fluorescence spectrophotometry of aniline blue-stained callose particles, immuno-fluorescence microscopy and indirect assessment of both callose synthase and β-(1,3)-glucanase enzyme activities. Some of these metho...

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Detalles Bibliográficos
Autores principales: Mustafa, Abubakar S., Ssenku, Jamilu E., Ssemanda, Paul, Ntambi, Saidi, Dinesh-Kumar, Savithramma P., Tugume, Arthur K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9326611/
https://www.ncbi.nlm.nih.gov/pubmed/35893580
http://dx.doi.org/10.3390/mps5040054
Descripción
Sumario:The existing methods of callose quantification include epifluorescence microscopy and fluorescence spectrophotometry of aniline blue-stained callose particles, immuno-fluorescence microscopy and indirect assessment of both callose synthase and β-(1,3)-glucanase enzyme activities. Some of these methods are laborious, time consuming, not callose-specific, biased and require high technical skills. Here, we describe a method of callose quantification based on Sandwich Enzyme-Linked Immunosorbent Assay (S-ELISA). Tissue culture-derived banana plantlets were inoculated with Xanthomonas campestris pv. musacearum (Xcm) bacteria as a biotic stress factor inducing callose production. Banana leaf, pseudostem and corm tissue samples were collected at 14 days post-inoculation (dpi) for callose quantification. Callose levels were significantly different in banana tissues of Xcm-inoculated and control groups except in the pseudostems of both banana genotypes. The method described here could be applied for the quantification of callose in different plant species with satisfactory level of specificity to callose, and reproducibility. Additionally, the use of 96-well plate makes this method suitable for high throughput callose quantification studies with minimal sampling and analysis biases. We provide step-by-step detailed descriptions of the method.