Cyanobacteria in an urban lake: hidden diversity revealed by metabarcoding

Abstract

The study and monitoring of communities within microbiomes is important as some organisms can synthesize toxic substances, such as cyanotoxins synthesized by cyanobacteria. Cyanobacteria is a large portion of the periphyton biomass and is responsible for toxic blooms in aquatic environments. This makes urban environments an interesting environment for observing cyanobacteria diversity, due to the disturbances from anthropic activities. As many classes of cyanobacteria are difficult to identify using traditional morphology methods, the use of molecular tools could complement periphyton community studies. Herein, we use the hypervariable V4 region of 16S rRNA gene to observe cyanobacteria diversity in the periphyton from an urban lake. After DNA extraction and metabarcoding analyses, the reads were classified according to the SILVA database, and the cyanobacteria operational taxonomic units (OTUs) were separated to compare with the GenBank database. Most of the cyanobacteria OTUs obtained in this study do not correspond to cyanobacteria previously found in this environment by traditional methods, and our GenBank comparison generated significantly improved taxonomic assignments. Metabarcoding is a useful tool and has allowed our first step toward understanding the true cyanobacteria diversity in the periphyton community of urban lakes.