Phytoplasma, a plant pathogen that threatens plant health, can induce diseases such as yellow wilt, virescence, phyllody, and witches’ broom. Although early detection methods using polyclonal and monoclonal antibodies have been developed, synthetic peptides offer advantages such as higher titers, predictable antigenic characteristics and superior sensitivity and specificity. Epitope mapping plays a key role in designing peptide antigens and includes gene synthesis, transformation, expression assessment, large-scale production, and purification. A study using New Zealand male White rabbits was conducted to generate antibodies against phytoplasma. The SecA (395–470) sequence, obtained from the preprotein translocase meets the criteria of being non-homologous, nonallergic, and antigenic. The three-dimensional structure of SecA (395–470) has a sequential similarity of 77–97% with certain phytoplasma types, and the protein purity exceeds 90%. The production of polyclonal antibodies was successful, achieving titers greater than 1:512,000. The SWISS model was used to predict the 3D structure of SecA in phytoplasma species, revealing structural homology with other phytoplasma species. The recombinant protein antigen SecA was able to induce high-titer antibody formation (>1:512.000). The developed lateral flow immunoassay (LFA) detects phytoplasma in plants using purified and conjugated antibodies. The peptide design, derived from Aster yellows witches-broom (SrI), effectively detects phytoplasma from various groups, especially Cactus witches’ broom phytoplasma (SrII-C) and Peanut witches’ broom phytoplasma (SrII-A). The SrI group phytoplasma was chosen as a reference sequence due to its` ability to infect plants across the broadest host range. LFIA was tested on samples from both phytoplasma-infected and healthy plants using nested PCR. The SecA sequence was successfully produced and used as an immunogen candidate against phytoplasmas.
                        
                        
                        
                        
                            
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