4.7 Article

Development of a field-deployable qPCR assay for real-time pest monitoring in algal cultivation systems

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ELSEVIER
DOI: 10.1016/j.algal.2023.103194

Keywords

Pests; Diagnostics; qPCR; Nannochloropsis sp; Metagenomics

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Outdoor cultivation is commonly used for producing algal biomass for various bioproducts. However, it is susceptible to pest pressures, resulting in low productivity or even complete loss of the algal crop. In this study, a field deployable, low-cost qPCR assay was developed for detecting known and novel pests of Nannochloropsis sp., enabling rapid surveillance in remote field locations.
Outdoor cultivation is commonly used to produce algal biomass for a variety of bioproducts including food, feed, fuel, pharmaceuticals, and nutraceuticals. Outdoor cultivation ponds are highly susceptible to pest pressures that may lead to periods of low productivity or even entire loss of the algal crop. Therefore, there is a need for rapid, real-time tracking of pests for early intervention to mitigate crop loss. Herein, we describe the development of a field deployable, low-cost qPCR assay for detecting both known and novel pests of a farmed eukaryotic alga species, Nannochloropsis sp. We performed a proximity guided metagenome deconvolution approach (ProxiMetaTM) to discover novel pests that temporally correspond to periods of reduced pond productivity. This approach provided high-quality metagenome assemblies that were used to design qPCR probes to detect specific pests of interest. The portable qPCR assay, designed to be deployed at remote field locations, enables low-cost surveillance with a rapid (2 h) turn-around time. Frequent sampling allows for early detection and prompts intervention strategies to remedy infected ponds to minimize crop loss. The qPCR assay was used to successfully detect a known predatory bacterium within the order Bdellovibrionales both in the lab and at a remote field location. Furthermore, we assembled the genome of two novel, site-specific pests in the Saprospiraceae family and successfully designed qPCR probes that differentially detected their presence in two different pond locations. Ultimately, this assay has the potential to monitor multiple pests simultaneously and tailor targets to match likely pest infections that differ across geographical locations, helping to mitigate crop loss on a large scale.

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