Callose is a polysaccharide of β-1,3-glucan which is a naturally occurring compound found in the cell walls of a variety of higher plants. Callose is synthesized by callose synthases (CalS) and degraded by β-(1,3)-glucanases1,2,3. It is involved in several biological processes, including growth and development and response to abiotic and biotic stresses4,5,6. During pathogen infection, the increase in callose deposition in the papillae helps to prevent further microbial colonization, acting as a permeability barrier between the neighboring plant cells2,4,7,8,9,10,11,12. By slowing down pathogen invasion in the attacked tissue, callose deposition allows time for the induction of additional defense responses13. Accurate spatiotemporal quantification of callose in the plant tissues is essential for understanding its role in the various physiological processes. However, the current methods of callose quantification from plant tissues, which include epifluorescence microscopy, immunofluorescence microscopy, and fluorescence spectrophotometry, possess significant limitations and quantification challenges. Therefore, there is a pressing need to explore alternative methods for callose quantification to overcome these drawbacks. It was hypothesized that immunofluorescence spectrophotometry or enzyme-linked immunosorbent assay (ELISA) could offer a more efficient method of callose quantification in plant samples, which includes high specificity, sensitivity, reliability, reproducibility and offers a high-throughput method.
The gold standard method for callose quantification involves imaging of aniline blue-stained callose particles by epifluorescence microscopy14,15,16,17. The aniline blue-stained callose when exposed to blue or UV light excitation appears as yellow fluorescent particles, which can either be manually counted for the number of fluorescing callose particles14,15 or counted by automated callose counting software. Manual counting of callose particles is laborious, time-consuming, and subjective to the researcher18, whereas automated counting requires acquiring software resources and a considerable technical skills. Some of the software used for automated callose counting include ImageJ19,20,21,22, photoshop23, CalloseMeasurer24, Icy18,25 and Ilastik26. The aniline blue-stained callose may also be quantified using fluorescence spectrophotometry17,19,27,28,29. However, the high background/autofluorescence associated with epifluorescence microscopy and fluorescence spectrophotometry make these methods difficult and unreliable due to low signal to noise ratio26. Moreover, aniline blue can stain other β-1,3-glucans besides callose30, making both epifluorescence microscopy and fluorescence spectrophotometry methods of callose detection and quantification partially non-specific and unreliable. A method of immunofluorescence microscopy for callose quantification which is based on callose-specific antibodies has also been used in several studies31,32,33. Although this method shares a few disadvantages with epifluorescence microscopy of aniline blue-stained callose, it has the advantage of being callose-specific due to the antibodies used here. Callose quantification has also been performed using enzyme activity-based methods. Enzyme activity-based methods for callose quantification include assessment of callose synthase (CalS)20,33 and β-(1,3)-glucanase activities34,35. The enzyme activity-based methods have several disadvantages as compared to epifluorescence microscopy, immunofluorescence microscopy and fluorescence spectrophotometry. These include indirect estimation of callose, the difficulty of enzyme extraction and enzyme activity assays, and lack of even distribution of callose in the plant tissues.
Due to the disadvantages of the current methods of callose quantification which include epifluorescence microscopy, immunofluorescence microscopy, fluorescence spectrophotometry, CalS and β-(1,3)-glucanase assays, there was need to come up with a new method of callose quantification that would offer a number of advantages which include, 1) high specificity, sensitivity, reliability and reproducibility, and 2) easier callose quantification with high-throughput ability. The use of immunofluorescence spectrophotometry for callose quantification has not been explored. Here, a new method of callose quantification based on immunofluorescence spectrophotometry, more specifically, Enzyme-Linked Immunosorbent Assay (ELISA), is reported. The method can be optimized for the quantification of callose in different plants or their tissues with a good degree of specificity to callose, precision, reproducibility, and a high-throughput experimental capability. This method can also be modified to quantify any plant-based analyte if the antibody against that analyte is available. To ensure accurate, efficient, and reliable spatiotemporal distribution of callose in plant tissues, it is recommended that different methods of callose quantification are used simultaneously which include the microscopy, spectrophotometry and enzyme activity-based methods. Consequently, this will accurately and efficiently allow the understanding of the role of callose in various physiological and stress responses.