From genes to toxins: Profiling Prymnesium parvum during a riverine harmful algal bloom.

Blooms of Prymnesium parvum, a unicellular alga globally distributed in marine and brackish environments, frequently result in massive fish kills due to the production of toxins called prymnesins by this haptophyte. In August 2022, a harmful algal bloom (HAB) of this species occurred in the lower Oder River (Poland and Germany), which caused mass mortalities of fish and other organisms. This HAB was linked to low discharge of the Oder and mining activities that caused a significant increase in salinity. In this context, we report on the molecular detection and screening of this haptophyte and its toxins in environmental samples and clonal cultures derived thereof. Both conventional PCR and droplet digital PCR assays reliably detected P. parvum in environmental samples. eDNA metabarcoding using the V4 region of the 18S rRNA gene revealed a single Prymnesium sequence variant, but failed to identify it to species level. Four clonal cultures established from environmental samples were unambiguously identified as P. parvum by molecular phylogenetics (near full-length 18S rRNA gene) and light microscopy. Phylogenetic analysis (ITS1-5.8S-ITS2 marker region) placed the cultured phylotype within a clade containing other P. parvum strains known to produce B-type prymnesins. Toxin-screening of the cultures using liquid chromatography-electrospray ionization - time of flight mass spectrometry identified B-type prymnesins, which were also detected in extracts of filter residues from water samples of the Oder collected during the HAB. Overall, our investigation provides a detailed characterization of P. parvum, including their prymnesins, during this HAB in the Oder River, contributing valuable insights into this ecological disaster. In addition, the droplet digital PCR assay established here will be useful for future monitoring of low levels of P. parvum on the Oder River or any other salt-impacted and brackish water bodies.

Diatom DNA metabarcoding for ecological assessment: Comparison among bioinformatics pipelines used in six European countries reveals the need for standardization.

Ecological assessment of lakes and rivers using benthic diatom assemblages currently requires considerable taxonomic expertise to identify species using light microscopy. This traditional approach is also time-consuming. Diatom metabarcoding is a promising alternative and there is increasing interest in using this approach for routine assessment. However, until now, analysis protocols for diatom metabarcoding have been developed and optimised by research groups working in isolation. The diversity of existing bioinformatics methods highlights the need for an assessment of the performance and comparability of results of different methods. The aim of this study was to test the correspondence of outputs from six bioinformatics pipelines currently in use for diatom metabarcoding in different European countries. Raw sequence data from 29 biofilm samples were treated by each of the bioinformatics pipelines, five of them using the same curated reference database. The outputs of the pipelines were compared in terms of sequence unit assemblages, taxonomic assignment, biotic index score and ecological assessment outcomes. The three last components were also compared to outputs from traditional light microscopy, which is currently accepted for ecological assessment of phytobenthos, as required by the Water Framework Directive. We also tested the performance of the pipelines on the two DNA markers (rbcL and 18S-V4) that are currently used by the working groups participating in this study. The sequence unit assemblages produced by different pipelines showed significant differences in terms of assigned and unassigned read numbers and sequence unit numbers. When comparing the taxonomic assignments at genus and species level, correspondence of the taxonomic assemblages between pipelines was weak. Most discrepancies were linked to differential detection or quantification of taxa, despite the use of the same reference database. Subsequent calculation of biotic index scores also showed significant differences between approaches, which were reflected in the final ecological assessment. Use of the rbcL marker always resulted in better correlation among molecular datasets and also in results closer to these generated using traditional microscopy. This study shows that decisions made in pipeline design have implications for the dataset's structure and the taxonomic assemblage, which in turn may affect biotic index calculation and ecological assessment. There is a need to define best-practice bioinformatics parameters in order to ensure the best representation of diatom assemblages. Only the use of similar parameters will ensure the compatibility of data from different working groups. The future of diatom metabarcoding for ecological assessment may also lie in the development of new metrics using, for example, presence/absence instead of relative abundance data.

Epilithic diatom communities of selected streams from the Lerma-Chapala Basin, Central Mexico, with the description of two new species.

The Lerma-Chapala Basin, in Central Mexico, is geologically heterogeneous, climatically diverse and boasts high biodiversity, lying within two Biodiversity Hotspots, namely Mesoamerica and the Madrean Pine-Oak Woodlands. Epilithon and water samples were collected in the basin from 14 sampling sites three times each, two sampling campaigns during the rainy season and one in the dry season. A total of 274 infrageneric taxa in 48 genera were recorded. The taxonomic composition observed was dominated by taxa from the genera Nitzschia, Gomphonema, Pinnularia, Navicula, Sellaphora and Eunotia. About a third of the taxa found could not be identified to the species level. From those unidentified morphodemes, two are described as new species, namely Brachysira altepetlensis and Sellaphora queretana. Furthermore, Eolimna rhombica is transferred to Sellaphora. Canonical Correspondence Analysis (CCA) revealed that specific conductivity and pH were the main environmental factors driving the community composition observed. Three groups of samples were identified after the CCA: 1) characterized by acidic waters and low conductivity; 2) with circumneutral waters, low specific conductivity and high temperature and phosphorous concentrations; and 3) characterized by circumneutral waters, high conductivity and low nitrogen concentrations. The indicator value method (IndVal), based on the relative abundance and relative frequency of the most abundant taxa was calculated based on the groups observed in the CCA, identifying the characteristic taxa for each of the three groups.