Metagenomic Sequencing for Identification of Xylella fastidiosa from Leaf Samples.

Xylella fastidiosa () is a globally distributed plant-pathogenic bacterium. The primary control strategy for diseases is eradicating infected plants; therefore, timely and accurate detection is necessary to prevent crop losses and further pathogen dispersal. Conventional diagnostics primarily relies on quantitative PCR (qPCR) assays. However, these methods do not consider new or emerging variants due to pathogen genetic recombination and sensitivity limitations. We developed and tested a metagenomics pipeline using in-house short-read sequencing as a complementary approach for affordable, fast, and highly accurate detection. We used metagenomics to identify to the strain level in single- and mixed-infected plant samples at concentrations as low as 1 pg of bacterial DNA per gram of tissue. We also tested naturally infected samples from various plant species originating from Europe and the United States. We identified subspecies in samples previously considered inconclusive with real-time PCR (quantification cycle [], >35). Overall, we showed the versatility of the pipeline by using different plant hosts and DNA extraction methods. Our pipeline provides taxonomic and functional information for diagnostics without extensive knowledge of the disease. This pipeline demonstrates that metagenomics can be used for early detection of and incorporated as a tool to inform disease management strategies. Destructive Xylella fastidiosa () outbreaks in Europe highlight this pathogen's capacity to expand its host range and geographical distribution. The current disease diagnostic approaches are limited by a multiple-step process, biases to known sequences, and detection limits. We developed a low-cost, user-friendly metagenomic sequencing tool for detection. In less than 3 days, we were able to identify subspecies and strains in field-collected samples. Overall, our pipeline is a diagnostics tool that could be easily extended to other plant-pathogen interactions and implemented for emerging plant threat surveillance.