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Cyanobacteria are Gram-negative photosynthetic bacteria capable of producing toxins responsible for morbidity and mortality in humans and domestic animals. Many are capable of forming concentrated blooms that impact the environment by limiting the growth of sub-surface plants and phytoplankton. Harmful algal blooms (HABs) are also capable of producing multiple types of toxins, creating a potential hazard to recreational water users and animals drinking water from or near a bloom. Characterization of HABs is necessary to prevent these human and animal exposures and includes classifying of the type of cyanobacteria present and whether or not they are capable of toxin production, and the exact type of cyanotoxin that is actually present in bloom. Current methods used to classify cyanobacteria and cyanotoxins include microscopy, bioassays, ELISA, PCR, HPLC, and LC/MS. All of these methods, however, have limitations that include time, labor intensity, or cost. Fourier-Transform Infrared Spectroscopy (FTIR) is another potential tool for cyanobacterial classification that is not limited by these factors. To examine the practicality of this method, library screening with default software algorithms was performed on diagnostic samples received at the Kansas State University Veterinary Diagnostic Lab, followed by PCA of samples meeting minimum quality requirements to produce cluster analyses and dendrograms. Both spectrometers and software packages used were successful at distinguishing cyanobacteria from green algae in clean samples with 89.13% agreement. PCA resulted in clear classification of cyanobacteria or green algae demonstrated by a large order of magnitude difference produced by average Euclidian distance dendrograms. While this method is only capable of differentiating cyanobacteria from green algae or other aquatic environmental constituents, its simple, rapid use and low cost make it a beneficial screening tool when coupled with toxin-detection methods to characterize HABs. |
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