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Untargeted and Targeted LC-MS and Data Processing Workflow for the Comprehensive Analysis of Oligopeptides from Cyanobacteria.

CHEMOSPHERE(2023)

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摘要
Cyanobacteria produce a plethora of structurally diverse bioactive secondary metabolites, including cyanotoxins which pose a serious threat to humans and other living organisms worldwide. Currently, a wide variety of mass spectrometry-based methods for determination of microcystins (MCs), the most commonly occurring and studied class of cyanotoxins, have been developed and employed for research and monitoring purposes. The scarcity of commercially available reference materials, together with the ever-growing range of mass spectrometers and analytical approaches, make the accuracy of quantitative analyses a critical point to be carefully investigated in view of a reliable risk evaluation. This study reports, a comparative investigation of the qualitative and quantitative MCs profile obtained using targeted and untargeted liquid chromatography-mass spectrometry approaches for the analyses of cyanobacterial biomass from Lake Kastoria, Greece. Comparison of the total MCs content measured by the two approaches showed good correlation, with variations in the range of 3.8-13.2%. In addition, the implementation of an analytical workflow on a hybrid linear ion trap/orbitrap mass spectrometer is described, based on combining data-dependent acquisition and a powerful database of cyanobacterial metabolites (CyanoMetDB) for the annotation of known and discovery of new cyanopeptides. This untargeted strategy proved highly effective for the identification of MCs, microginins, anabaenopeptins, and micropeptins. The systematic interpretation of the acquired fragmentation patterns allowed the elucidation of two new MC structural variants, MC-PrhcysR and MC-Prhcys(O)R, and proposal of structures for two new microginins, isomeric cyanostatin B and MG 821A, and three isomeric micropeptins at m/z 846.4715, 846.4711 and 846.4723.
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关键词
Microcystins,Cyanotoxins,Cyanopeptides,Untargeted LC-HRMS,Targeted LC-MS,MS,Data-dependent acquisition
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