Abstract
The widespread distribution of cyanobacteria in the aquatic environment is increasing the risk of water pollution caused by cyanotoxins, which poses a serious threat to human health. However, the structural characterization, distribution and identification techniques of cyanotoxins have not been comprehensively reviewed in previous studies. This paper aims to elaborate the existing information systematically on the diversity of cyanotoxins to identify valuable research avenues. According to the chemical structure, cyanotoxins are mainly classified into cyclic peptides, alkaloids, lipopeptides, nonprotein amino acids and lipoglycans. In terms of global distribution, the amount of cyanotoxins are unbalanced in different areas. The diversity of cyanotoxins is more obviously found in many developed countries than that in undeveloped countries. Moreover, the threat of cyanotoxins has promoted the development of identification and detection technology. Many emerging methods have been developed to detect cyanotoxins in the environment. This communication provides a comprehensive review of the diversity of cyanotoxins, and the detection and identification technology was discussed. This detailed information will be a valuable resource for identifying the various types of cyanotoxins which threaten the environment of different areas. The ability to accurately identify specific cyanotoxins is an obvious and essential aspect of cyanobacterial research.
Highlights
Cyanobacteria, which have existed for about 3.5 billion years, are believed to be the oldest creatures on Earth
Ultra-high-performance liquid chromatography (HPLC) (UHPLC) tandem mass spectrometry (MS) becomes the preferred technique for quantitative analysis and detection of cyanotoxins in water bodies, cyanobacteria and shellfish, due to its high efficiency and high-sensitivity [17]
liquid chromatography (LC)-MS has been proven to be an ideal method for discovering trace CYNs in water samples because of its sensitivity and specificity, and it has been established as the standard method for CYNs detection [64]
Summary
Xingde Du 1 , Haohao Liu 1 , Le Yuan 1 , Yueqin Wang 1 , Ya Ma 1 , Rui Wang 1 , Xinghai Chen 2 , Michael D. Losiewicz 2 , Hongxiang Guo 3, * and Huizhen Zhang 1, *. College of Life Sciences, Henan Agricultural University, Zhengzhou 450002, China. Received: 27 August 2019; Accepted: 9 September 2019; Published: 12 September 2019
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