Rapid cyanobacteria species identification with high sensitivity using native mass spectrometry

Dataset

Description

The data comprises 1) native mass spectra of phycobiliproteins extracted from cyanobacteria. 2) UV-vis spectroscopy data on cyanobacteria protein extracts and on pure phycobiliproteins 3) Cell counting data and microscopy images of different cyanobacterial species The data is supplemental to the manuscript entitled "Rapid cyanobacteria species identification with high sensitivity using native mass spectrometry" by Sound et al. The abstract from this is detailed below. ABSTRACT: Cyanobacteria have evolved over billions of years to adapt and survive in diverse climates. Environmentally, this presents a huge challenge, since cyanobacteria can now rapidly form algae blooms that are detrimental to aquatic life. In addition, many cyanobacteria produce toxins, making them hazardous to the animals and humans that they encounter. Rapid identification of cyanobacteria is essential to monitor and prevent toxic algae blooms. Here, we show for the first time how native mass spectrometry can quickly and precisely identify cyanobacteria from diverse aquatic environments. By monitoring phycobiliproteins, abundant protein complexes within cyanobacteria, simple, easy-to-understand mass spectral ‘fingerprints’ were created that were unique to each species. Moreover, our method is 10-fold more sensitive than the current MALDI-TOF mass spectrometric methods, meaning that cyanobacteria can be monitored using this technology far prior to bloom formation. Together, the data show great promise for the simultaneous detection and identification of co-existing cyanobacteria in situ.
Date made available29 Sep 2021
PublisherUniversity of Birmingham

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