Monitoring harmful microalgal species and their appearance in Tokyo Bay, Japan, using metabarcoding

Abstract

During the recent decade, high-throughput sequencing (HTS) techniques, in particular, DNA metabarcoding, have 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 throughout the sampling season (summer to autumn) and no structuring or succession patterns associated with the environmental conditions could be detected. Statistically significant (p < 0.05, rS ranging from −0.88 to 0.90) associations were found amongst the HAB species and other eukaryotic and prokaryotic species, including genera containing growth-limiting bacteria. However, significant correlations between species differed amongst the years, indicating that variability in environmental conditions between the years may have a stronger influence on the microalgal 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 microalgae monitoring, as it facilitates more precise species identification compared to light microscopy, as well as provides input for investigating potential interactions amongst different species/groups through simultaneous detection of multiple species/genera.

Eight years of weekly eDNA monitoring in the North‐Western Pacific

“…At the same time, we acknowledge that the number of OTUs is not directly comparable among different studies. On the other hand, the taxa associated with the highest number of OTUs is similar between this and other studies (De Vargas et al, 2015; Sildever et al, 2021, 2022) with the most species‐rich groups being Alveolata (especially dinoflagellates), Opisthokonta (metazoa and fungi), Stramenopiles (especially diatoms), and Rhizaria. In fungi, most of the OTUs were linked with Ascomycota and Basidiomycota as also reported for other marine environments around the world (Tisthammer et al, 2016; Zhang, Pavlovska et al, 2020b).…”

“…The high‐resolution dataset also facilitated the detection of statistically significant associations between different OTUs. Similar approaches have been used for investigating potential interactions across several trophic levels in the marine community (Djurhuus et al, 2020; Zhang, Pavlovska et al, 2020b) as well as between harmful algal species and bacteria (Sildever et al, 2022). The majority of the OTUs that were associated with a single species at ≥99% similarity based on 18S universal primer had more than one significant association with another OTU.…”

“…To capture marine fungi, the primers targeting ITS were also used (set 5: Table S1). Two‐step PCR for the construction of paired‐end libraries and HTS on the Illumina Miseq using the v3‐600 reagent kit (Illumina) followed the previously described approach (Sildever et al, 2022). Briefly, the first PCR was performed in a 25 μL reaction mixture containing 1.0 mL template DNA (<1 ng), 0.2 mM of each dNTP, 1 × PCR buffer, 1.5 mM Mg 2+ , 1.0 U KOD‐Plus‐ver.2 (Toyobo), and 1.0 mM of each primer.…”

“…Treatment of obtained sequences, selection of operational taxonomic units (OTUs), and taxonomic identification of OTUs were done according to the previously published workflow (Sildever et al, 2022). More specifically, the demultiplexing and trimming were performed using Trimmomatic version 0.35 (http://www.usadellab.org/cms/?page=trimmomatic).…”

“…Combining environmental monitoring with metabarcoding and the eDNA approach also advances the knowledge of the influence of abiotic parameters on community dynamics (Berry et al, 2019; Hirai et al, 2017; Jacobs‐Palmer et al, 2021; Robicheau et al, 2022). Also, the simultaneous detection of multiple taxa facilitates the understanding of potential interactions between species/groups (Djurhuus et al, 2020; Hirai et al, 2021; Sildever et al, 2022). Time series monitoring based on eDNA can be especially useful for determining the natural variability, fluctuations, and changes in community composition (Djurhuus et al, 2020).…”