American Chemical Society
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Improving the Quantification of Cyanotoxins Using a Mass Balance-Based Effective Concentration-Equivalent Concentration Approach

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journal contribution
posted on 2022-10-04, 18:06 authored by Ai Jia, Yingbo C. Guo, George D. Di Giovanni, Matthew D. Prescott, Wei L. Li, Eduardo A. Garcia
Two commonly used methods for cyanotoxin analysis are enzyme-linked immunosorbent assay (ELISA) and liquid chromatography–tandem mass spectrometry (LC-MS/MS). Each method has its advantages and disadvantages, and discrepancies are commonly observed between the two methods due to various factors including the ELISA antibody cross-reacting to different cyanotoxin congeners. However, reliable cyanotoxin monitoring methods and accurate interpretation of results are needed for water utilities to guide recreational water planning and drinking water treatment operations. In this study, we explored an innovative “effective concentration-equivalent concentration” (EC-EQ) approach to improve the interpretation of ELISA results and the comparison to LC-MS/MS results. The precision of ELISA results was first improved by reporting the sample ECs and EQs derived from their ELISA dose curves. Concentrations of each cyanotoxin as measured by LC-MS/MS were then combined with their respective ELISA cross-reactivities to calculate their theoretical ELISA responses. Finally, instead of comparing the results from the two methods directly, the equivalent concentration based on one single reference cyanotoxin was used for reporting and comparison. This integrated mass balance-based approach provides a more reliable interpretation of results by considering the reactivity differences between toxins as well as their mixture effects. This approach has been successfully applied to microcystin (one main group of cyanotoxins) standard mixtures and cyanobacterial bloom samples to interpret and compare their ELISA and LC-MS/MS detection results. The study provides guidance to utilities on how to obtain more accurate cyanotoxin monitoring results and better understand the discrepancy between the two methods.