Characterising and predicting cyanobacterial blooms in an 8-year amplicon sequencing time course.

ABSTRACT: Cyanobacterial blooms occur in lakes worldwide, producing toxins that pose a serious public health threat. Eutrophication caused by human activities and warmer temperatures both contribute to blooms, but it is still difficult to predict precisely when and where blooms will occur. One reason that prediction is so difficult is that blooms can be caused by different species or genera of cyanobacteria, which may interact with other bacteria and respond to a variety of environmental cues. Here we used a deep 16S amplicon sequencing approach to profile the bacterial community in eutrophic Lake Champlain over time, to characterise the composition and repeatability of cyanobacterial blooms, and to determine the potential for blooms to be predicted based on time course sequence data. Our analysis,

SUBMITTER: Tromas N 

PROVIDER: S-EPMC5520043 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature