Development of biological recognition elements for the detection of the genome of cocoa swollen shoot virus

Monnier, Bertrand

Abstract

Cacao swollen shoot virus (CSSV) is the main threat to chocolate production in West Africa. Infection causes a decrease in bean production yield and can cause tree death within three years, causing socio-economic damage to small-holding farmers.

CSSV control measures relying on cutting out infected and surrounding trees have proven ineffective. Novel strategies are needed to stem the pathogen propagation in the endemic area by identifying and removing asymptomatic CSSV infected trees. This work assessed if a cost-effective easy to operate biosensor could be developed to detect CSSV DNA. Two biological recognition elements (BRE) deriving from CSSV, serving as an interface between the user and the targeted analyte, were designed, produced, and tested with CSSV-infected T. cacao extracts. First, a BRE based on a chimeric zinc finger protein targeting CSSV genome was functionally tested using an electrophoretic mobility shift assay, a double filter binding assay and a superparamagnetic particles pull-down assay. The second BRE was constructed with an oligonucleotide lattice following de novo sequencing of a CSSV UWE strain. Using these nucleotides, a temperature-independent, “cold”, hybridisation assay was developed and tested by high resolution melt and dot blotting. Simple DNA extraction methods were developed to isolate CSSV genome from tree and sap samples. Both DNA and protein based BREs were able to interact with the genome of CSSV with higher specificity observed with the oligonucleotide lattice. Successful simple CSSV DNA extraction was performed from leaves but also from vascular tissues. This combined with a cold hybridisation method could be integrated in a CSSV biosensing procedure.

A cost effective and user-friendly biosensor to detect CSSV in an area of low economic capital is feasible using the biological recognition elements, the DNA extractions and hybridisation assay developed in this project. The system could be adapted to monitor other analytes as indicators of tree health to help achieve sustainable agriculture targets.

• Thesis Type: Thesis
• Deposit Date: Sep 30, 2023
• Publicly Available Date: Aug 12, 2024
• Public URL: https://uwe-repository.worktribe.com/output/11145285
• Award Date: Aug 12, 2024