Anthropogenic activities cause disruption to natural ecosystems, which can in turn impact the functioning of human societies. To ensure long-term societal well being, the monitoring of living organisms is becoming increasingly critical in a variety of domains from pathogens and pest detection to stock assessment and biodiversity protection. A critical challenge is to develop efficient data collection methods of potential biotic concerns that will allow informed management decisions. However, current methods for detecting micro and macroorganisms in their environment are expensive and time intensive rendering large scale applications infeasible.
The increasing availability of information on species occurrences and genomes means it is now possible to develop tailored diagnostics for environmental monitoring with CRISPR-Cas biotechnology for specific organisms. Engineered CRISPR-Cas reagents associated with a readout system are reported to allow the diagnosis of pathogens in medical samples. In the proposed project, we will generate a programmable approach for CRISPR-Cas to harness this technology and achieve organism detection in environmental DNA samples (eDNA), allowing fast and cost-effective tracking of multiple species’ occupancy overtime at multiple sites.
Building on our expertise in machine learning, eDNA and CRISPR-Cas applications, we will develop a flexible and adaptable strategy for organism detection in water samples. We will first investigate whether organisms of concern have a unique genomic signature in eDNA that can be tracked in the environment using CRISPR-Cas, and for which the generation of target DNA regions can be automatized using machine learning. The project will deliver both a software and low-cost assay kit facilitating analysis of many samples. We will demonstrate the application of the technology to support phytosanitary service, the monitoring of problematic pathogens in wildlife, and the management of animal populations. Our project will offer an attractive service for government and private industries to respond to increasing demands for biological monitoring. Overall, the technology emerging from this project will provide the paradigm shift needed to vastly change the cost, speed and scale with which organisms can be surveyed through time allowing a commercial solution.
Last updated:31.10.2022
