Virus Infection of a Freshwater Cyanobacterium Contributes Significantly to the Release of Toxins Through Cell Lysis

Toxic algal-bloom-forming cyanobacteria are a persistent problem globally for many aquatic environments. Their occurrence is attributed to eutrophication and rising temperatures due to climate change. The result of these blooms is often the loss of biodiversity, economic impacts on tourism and fishe...

Full description

Saved in:
Bibliographic Details
Main Authors: Victoria Lee, Isaac Meza-Padilla, Jozef I. Nissimov
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Microorganisms
Subjects:
Online Access:https://www.mdpi.com/2076-2607/13/3/486
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Toxic algal-bloom-forming cyanobacteria are a persistent problem globally for many aquatic environments. Their occurrence is attributed to eutrophication and rising temperatures due to climate change. The result of these blooms is often the loss of biodiversity, economic impacts on tourism and fisheries, and risks to human and animal health. Of emerging interest is the poorly understood interplay between viruses and toxic species that form blooms. This is because recent studies have suggested that viruses may exacerbate the harmful effects of these blooms by contributing to the release of toxins into a dissolved phase upon cell lysis. However, to date, there is no experimental evidence that explicitly implicates viruses in microcystin release. Here, we show experimentally that a virus infection of the toxin-producing, harmful, algal-bloom-forming cyanobacterium <i>Microcystis aeruginosa</i> results in a 4-fold increase in the toxin microcystin-LR two days post-infection (dpi). We also show that the concentrations of microcystin remain high after culture discoloration and host cell lysis. Collectively, our results directly implicate viruses as major contributors to microcystin release from cyanobacteria and emphasize the importance of taking viruses into account in predictive models and in the assessment of water quality and safety.
ISSN:2076-2607