Harmful algal blooms (HABs) have become a serious threat to freshwater and marine waters worldwide, impacting humans, animals, and aquatic ecosystems. In freshwater, many cyanobacterial blooms (cyanoHABs) produce neurotoxic, hepatotoxic, dermatotoxic, or other bioactive compounds. As a result, managers need rapid, sensitive methods that can accurately identify and enumerate harmful species in a water body, yet to date, no methods exist that can be used to enumerate multiple species in the same sample and that can be deployed in small, bench-top instruments or on moorings for automated detection. This proposed project employs an innovative approach to HAB cell enumeration – fiber optic genosensors. It builds from prior studies on marine HAB species, for which this technology is well advanced. Once the technology is adapted and refined for freshwater cyanobacteria, we will test them using a portable instrument designed for clinical use in human pathogen detection.
The overall project goal is to adapt and validate a rapid and accurate optical fiber-based technology for cyanoHAB cell detection and enumeration in both laboratory and field settings. Specific objectives are to:
This project addresses a significant constraint to freshwater monitoring and management – the critical need for methods that accelerate and simplify enumeration of potentially toxic cyanobacterial species. In this regard, we note several significant advantages of the proposed technology – it can analyze dozens of target species on a single optical fiber bundle using encoded beads, and the arrays are reusable hundreds of times. This multiplexing ability is of obvious importance in regions where multiple freshwater HAB species co-occur. The technology can readily be adapted to target other cyanoHAB species as well as microbial pathogens and microorganisms of many types. Furthermore, it is highly amenable to automation, bringing us closer to the goal of an early warning system utilizing laboratory-based flow-through systems, or remote, moored instruments capable of detecting and providing early warning of organisms that threaten public and ecosystem health.
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