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Analysis of Covalently Bound Microcystins in Sediments and Clam Tissue in the Sacramento–San Joaquin River Delta, California, USA

Harmful cyanobacterial blooms compromise human and environmental health, mainly due to the cyanotoxins they often produce. Microcystins (MCs) are the most commonly measured group of cyanotoxins and are hepatotoxic, neurotoxic, and cytotoxic. Due to MCs ability to covalently bind to proteins, quantif...

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Detalles Bibliográficos
Autores principales: Bolotaolo, Melissa, Kurobe, Tomofumi, Puschner, Birgit, Hammock, Bruce G, Hengel, Matt J., Lesmeister, Sarah, Teh, Swee J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7150880/
https://www.ncbi.nlm.nih.gov/pubmed/32183091
http://dx.doi.org/10.3390/toxins12030178
Descripción
Sumario:Harmful cyanobacterial blooms compromise human and environmental health, mainly due to the cyanotoxins they often produce. Microcystins (MCs) are the most commonly measured group of cyanotoxins and are hepatotoxic, neurotoxic, and cytotoxic. Due to MCs ability to covalently bind to proteins, quantification in complex matrices is difficult. To analyze bound and unbound MCs, analytical methods were optimized for analysis in sediment and clam tissues. A clean up step was incorporated to remove lipids, improving percent yield. This method was then applied to sediment and clam samples collected from the Sacramento–San Joaquin River Delta (Delta) in the spring and fall of 2017. Water samples were also tested for intracellular and extracellular MCs. These analyses were used to quantify the partitioning of MCs among sediment, clams, and water, and to examine whether MCs persist during non-summer months. Toxin analysis revealed that multiple sediment samples collected in the Delta were positive for MCs, with a majority of the positive samples from sites in the San Joaquin River, even while water samples from the same location were below detection limit. These data highlight the importance of analyzing MCs in complex matrices to accurately evaluate environmental risk.