Spatial and Temporal Variability of Saxitoxin-Producing Cyanobacteria in U.S. Urban Lakes

Abstract

Harmful cyanobacterial blooms (HCBs) are of growing global concern due to their production of toxic compounds, which threaten ecosystems and human health. Saxitoxins (STXs), commonly known as paralytic shellfish poison, are a neurotoxic alkaloid produced by some cyanobacteria. Although many field studies indicate a widespread distribution of STX, it is understudied relative to other cyanotoxins such as microcystins (MCs). In this study, we assessed eleven U.S. urban lakes using qPCR, sxtA gene-targeting sequencing, and 16S rRNA gene sequencing to understand the spatio-temporal variations in cyanobacteria and their potential role in STX production. During the blooms, qPCR analysis confirmed the presence of the STX-encoding gene sxtA at all lakes. In particular, the abundance of the sxtA gene had a strong positive correlation with STX concentrations in Big 11 Lake in Kansas City, which was also the site with the highest quantified STX concentration. Sequencing analysis revealed that potential STX producers, such as Aphanizomenon, Dolichospermum, and Raphidiopsis, were present. Further analysis targeting amplicons of the sxtA gene identified that Aphanizomenon and/or Dolichospermum are the primary STX producer, showing a significant correlation with sxtA gene abundances and STX concentrations. In addition, Aphanizomenon was associated with environmental factors, such as conductivity, sulfate, and orthophosphate, whereas Dolichospermum was correlated with temperature and pH. Overall, the results herein enhance our understanding of the STX-producing cyanobacteria and aid in developing strategies to control HCBs.

Keywords: cyanobacteria; harmful cyanobacterial blooms; paralytic shellfish toxins; qPCR; saxitoxin; sxtA.

Figure 1

Community composition and structure by 16S rRNA gene amplicon analysis. (A) Taxonomic classification (at phylum level) of collected samples from the studied urban lakes, (B) Analysis of alpha diversity based on Faith’s PD and Pielou’s Evenness, (C) NMDS ordination plot for bacterial community composition (stress = 0.18). Points represent the NMDS scores of each sample in the lakes and ellipses indicate the 95% confidence interval of the group centroids.

Figure 2

Relative abundances (%) of cyanobacterial genera identified at the studied urban lakes.

Figure 3

Analysis results of STX concentrations STX concentrations (shaded red area), sxtA gene copy numbers by qPCR (blue square), and sxtA gene abundances based on sxtA target sequencing (red circle) in the lakes of Kansas City, Cincinnati, and Denver. sxtA gene abundances were calculated by summing the counts of ASVs identified through the target sequencing. While the primers employed in the qPCR assay for the sxtA gene differ from those used in target sequencing, both sets of primers primarily target the sxtA gene in Aphanizomenon and Dolichospermum.

Figure 4

Heatmap showing Pearson correlation coefficients between STX concentrations and abundances of cyanobacteria (A), sxtA gene (qPCR) and the abundances of cyanobacteria (B) in the lakes. NA represents not available. The * indicates 0.01 < p-value < 0.05.and South Lake (R_pearson 0.72, p-values < 0.05). Planktothrix negatively correlated with the sxtA gene and STX in Big 11 Lake (R_pearson −0.77, p-values < 0.05), whereas a positive correlation was observed at Chaumiere lake (R_pearson 0.70, p-values < 0.05). The negative correlation was observed between the relative abundance of Planktothrix and the presence of the sxtA gene and STXs.

Figure 5

RDA plot linking the qPCR measurements and cyanotoxin concentrations with environmental variables (A), CCA plot linking the cyanobacteria species with environment variables (B), and heatmap showing Pearson correlation coefficients between the relative abundances of major cyanotoxin producers and environmental variables (C). The * and ** represent 0.01 < p < 0.05 and 0.0001 < p < 0.01, respectively.