Monitoring harmful algal bloom species and their appearance in Tokyo Bay, Japan, using metabarcoding and high-throughput sequencing approach
During the recent decade, metabarcoding and high-throughput sequencing (HTS) has facilitated increased detection of biodiversity, including harmful algal bloom (HAB) species. In this study, the presence of HAB species and their appearance patterns were investigated by employing molecular and light microscopy-based monitoring in Tokyo Bay, Japan. The potential co-appearance patterns between the HAB species as well as with other eukaryotes and prokaryotes were investigated using correlation and association rule-based time-series analysis. In total, 40 unique HAB species were detected, including 12 toxin-producing HAB species previously not reported from the area. More than half of the HAB species were present from summer to autumn, and no structuring or succession patterns associated with the environmental conditions could be detected. Statistically significant (p < 0.05) associations were found among the HAB species and other eukaryotic and prokaryotic species, including genera containing growth-limiting bacteria. However, significant correlations between species differed among the years, indicating that variability in environmental conditions between the years may have a stronger influence on the phytoplankton community structure and interspecies interactions, than the variability during the sampling season. The association rule-based time-series analysis allowed the detection of a previously reported negative relationship between Synechococcus sp. and Skeletonema sp. in nature. Overall, the results support the applicability of metabarcoding and HTS-based phytoplankton monitoring, as it facilitates more precise species identification compared to light microscopy as well as provides input for investigating potential interactions among different species/groups through simultaneous detection of multiple species/genera.