DNA metabarcoding and morphological methods show complementary patterns in the metacommunity organization of lentic epiphytic diatoms

Genotyping by sequencing for estimating relative abundances of diatom taxa in mock communities

BACKGROUND

Diatoms are present in all waters and are highly sensitive to pollution gradients. Therefore, they are ideal bioindicators for water quality assessment. Current indices used in these applications are based on identifying diatom species and counting their abundances using traditional light microscopy. Several molecular techniques have been developed to help automate different steps of this process, but obtaining reliable estimates of diatom community composition and species abundance remains challenging.

RESULTS

Here, we evaluated a recently developed quantification method based on Genotyping by Sequencing (GBS) for the first time in diatoms to estimate the relative abundances within a species complex. For this purpose, a reference database comprised of thousands of genomic DNA clusters was generated from cultures of Nitzschia palea. The sequencing reads from calibration and mock samples were mapped against this database for parallel quantification. We sequenced 25 mock diatom communities containing up to five taxa per sample in different abundances. Taxon abundances in these communities were also quantified by a diatom expert using manual counting of cells on light microscopic slides. The relative abundances of strains across mock samples were over- or under-estimated by the manual counting method, and a majority of mock samples had stronger correlations using GBS. Moreover, one previously recognized putative hybrid had the largest number of false positive detections demonstrating the limitation of the manual counting method when morphologically similar and/or phylogenetically close taxa are analyzed.

CONCLUSIONS

Our results suggest that GBS is a reliable method to estimate the relative abundances of the N. palea taxa analyzed in this study and outperformed traditional light microscopy in terms of accuracy. GBS provides increased taxonomic resolution compared to currently available quantitative molecular approaches, and it is more scalable in the number of species that can be analyzed in a single run. Hence, this is a significant step forward in developing automated, high-throughput molecular methods specifically designed for the quantification of [diatom] communities for freshwater quality assessments.

Diatom eDNA metabarcoding and morphological methods for bioassessment of karstic river

Karst ecosystems play a unique role as exceptional natural habitats in sustaining biodiversity. This study focuses on diatoms, a diverse group of microeukaryotes in the periphytic community of a karstic river. In a multi-microhabitat study along the Krka River (Croatia), our goal was to obtain a detailed overview of diatom diversity and community structure using morphological and molecular approaches, and to assess the applicability of eDNA metabarcoding as a reliable tool for biomonitoring assessment. The results revealed a relatively low agreement in the diatom community composition between the two approaches, but also provided complementary information, with no differences in beta diversity detected between microhabitats. The SIMPER analysis underlined the importance of the molecular approach in identifying diatom community composition, due to errors in distinguishing between deposited diatom cells that occurred in the morphological analysis. In contrast, the morphological approach indicated a clear diatom community separation along the river with a strong location effect. Despite certain differences, both approaches provided a feasible assessment of the ecological status according to the relationship to environmental pressures, classifying the Krka River as High (morphological approach) or Good (molecular approach) throughout the most of its course. Moreover, diatom diversity based on both approaches provides a reliable dataset applicable in routine monitoring assessment and offers a deeper understanding of the presented ecological status. The incompleteness of a reference database presents one major drawback of the molecular approach, which needs further updating in order to improve routine diatom metabarcoding.

The Effects of Water Level Fluctuation on Zooplankton Communities in Shahu Lake Based on DNA Metabarcoding and Morphological Methods

Background: The water level of Poyang Lake (China) fluctuates seasonally. Shahu Lake, a smaller body of water connected to Poyang Lake during the wet season, is separated in the dry season. Due to a special fishing method termed ‘lake enclosed in autumn’, the water level is lowered and reaches its lowest point in January, which is <0.5 m deep in the middle of the lake. Our research investigated the effect of water level changes on the zooplankton community composition in Shahu Lake. Methods: We used both DNA metabarcoding method (MBC) (18S rRNA gene V4 region) and morphological method (MOI) to track the zooplankton community structure over four seasons in Shahu Lake (China). Results: Totals of 90 and 98 species of zooplankton were detected by MOI and MBC, respectively, with rotifers being the main zooplankton component. The α-diversity index of both methods increased from spring to summer and decreased from summer to autumn, reaching the lowest value in winter. NMDS and a cluster analysis showed that all zooplankton communities detected by MOI and MBC were significantly separated by season. The zooplankton community in winter was separated from that of the other three seasons, but the summer and autumn communities were more similar. Conclusions: Changes in the water level had significant effects on the zooplankton community composition. We found that MBC was more able to detect the differences in the zooplankton composition than MOI. MBC also had more advantages in copepod recognition. In our study, 37 species of copepods were detected by MBC, but only 11 species were detected by MOI. We concluded that MBC should be used to research the seasonal variations of zooplankton.