Background: Phytoplankton diversity can be difficult to ascertain from morphological analyses, because of the existence of cryptic species and pico- and concealed phytoplankton. In-depth sequencing and metabarcoding can reveal microbial diversity, and identify novel diversity. However, there has been little comparison of metabarcoding and morphological datasets derived from the same samples, and metabarcoding studies covering total eukaryotic phytoplankton diversity are rare. In this study, the variable V7 region of the 18S rDNA gene was employed to explore eukaryotic phytoplankton diversity in 11 Chinese freshwater environments, and further compared with the dataset obtained through morphological identification. Results: Annotation by the evolutionary placement algorithm (EPA) rather than alignment with the SILVA database improved the taxonomic resolution, with 346 of 524 phytoplankton operational taxonomic units (OTUs) being assigned to the genus or species level. The number of unassigned OTUs was greatly reduced from 259 to 178 OTUs by using the EPA in place of the SILVA database. Metabarcoding detected 3.5 times more OTUs than the number of morphospecies revealed by morphological identification; furthermore, the number of species and the Shannon–Wiener index inferred from the two methods were correlated. A total of 34 genera were identified via both methods, while 31 and 123 genera were detected solely in the morphological or metabarcoding dataset, respectively. Conclusion: The dbRDA plot showed distinct separation of the phytoplankton communities between lakes and reservoirs according to the metabarcoding dataset. The same pattern was obtained on the basis of 10 environmental variables in the PCO ordination plot, while the separation of the populations based on morphological data was poor. However, 30 morphospecies contributed 70% of the community difference between lakes and reservoirs in the morphological dataset, while 11 morphospecies were not found by metabarcoding. Considering the limitations of each of the two methods, their combination could substantially improve phytoplankton community assessment.

Arsenic accumulation and biotransformation in algae was mostly carried out in a medium that contained far higher nutrient concentrations than that in natural freshwaters. The obtained results might have limited environmental validity and result in a failure to describe authentic arsenic biogeochemical cycles in natural freshwater systems. To validate the assumption, arsenic accumulation, and biotransformation in common bloom forming Microcystis wesenbergii was performed under a high nutrient concentration in BG11 medium (N = 250 mg/L, P = 7.13 mg/L), and adjusted low nutrients that mimicked values in natural freshwaters (N = 1.5 mg/L, P = 0.3 mg/L). The growth rate and maximum M. wesenbergii cell density were much lower in the high nutrient set, but more inhibition was shown with increasing ambient iAs(V) concentrations both in the high and low nutrient sets. The proportion of intracellular contents in total arsenicals decreased with increasing iAs(V) concentrations in both high and low nutrient sets but increased with incubation time. Intracellular iAs(III) was not found in the high nutrient set, while it formed high concentrations that could be comparable to that of an extracellular level in the low nutrient set. M. wesenbergii could methylate arsenic, and a higher proportion of organoarsenicals was formed in the low nutrient set. Lower intracellular MMA(V) and DMA(V) concentrations were found in the high nutrient set; contrarily, they presented a higher concentration that could be comparable to the extracellular ones in the low nutrient set. The results demonstrated that different nutrient regimes could affect arsenic accumulation and biotransformation in M. wesenbergii, and low nutrient concentrations could inhibit the excretion of iAs(III), MMA(V) and DMA(V) out of cells. Further investigations should be based on natural freshwater systems to obtain an authentic arsenic accumulation and biotransformation in cyanobacteria.

Three cyanobacterial strains (CB-4, GQSK-2, and LHH-2) with thin, simple filaments were isolated from freshwater habitats in China. In this study, a polyphasic approach, integrating 16S rRNA gene phylogenetic analyses, p-distance calculation, 16S-23S ITS secondary structures, and morphological and ecological observations, was employed to resolve the taxonomic status of these strains. The results confirmed the existence of two new species within a novel genus (Neoleptolyngbya) and one additional new species of Pseudoleptolyngbya (Leptolyngbyaceae): Neoleptolyngbya gaoqiuensis sp. nov. (strain GQSK-2), Neoleptolyngbya chanbaensis sp. nov. (strain CB-4), and Pseudoleptolyngbya wuhanensis sp. nov. (strain LHH-2). In the 16S rRNA phylogeny, strains GQSK-2 and CB-4 formed a well-supported, independent lineage sister to the Leptolyngbyopsis clade, while strain LHH-2 clustered with two recognized Pseudoleptolyngbya species in a distinct clade. Sequence similarity analyses revealed that the 16S rRNA gene sequences of GQSK-2 and CB-4 shared a maximum similarity of 94.2% with those of phylogenetically related established genera, and the 16S rRNA gene sequence of LHH-2 exhibited a maximum similarity of 95.7% with its closest Pseudoleptolyngbya relatives, both values below the threshold for cyanobacterial species/genus delineation. Furthermore, comparative analysis of the 16S–23S ITS secondary structures between the three strains and their respective reference strains revealed significant species-specific differences, providing additional evidence for their taxonomic novelty. The discovery of these novel taxa enriches the cyanobacterial diversity in China and lays a theoretical foundation for the conservation and sustainable utilization of algae resources.

Disentangling the relative contributions of deterministic and stochastic processes were critical to compressive understanding of underlying mechanism governing geographic pattern and assembly of phytoplankton community, while it was seldom performed in connected lakes under human pressure. Here, we investigated phytoplankton community pattern in relation to environmental and spatial factors over 81 lakes located in middle and lower reaches of Yangtze River (MLYR) floodplain, where many lakes suffered eutrophication and cyanobacterial blooms. A majority of MLYR lakes had higher phytoplankton abundance surpassing 10⁷ cells/L, and were dominated by common bloom-forming cyanobacterial genera, including Pseudanabaena, Microcystis, Merismopedia, Dolichospermum, Limnothrix, and Raphidiopsis. Phytoplankton community exhibited a striking geographical pattern both for taxonomic and functional compositions, while functional groups were less sensitive and disimmilarity in communities displayed no significant increases with increasing geographical distance. Further, species richness explained much higher percentage of community variations than species turnover, indicating a reduced effect of environmental filtering of phytoplankton species with tolerance to similar environments in connected MLYR lakes. Both deterministic and stochastic processes governed assembly and biogeographic of phytoplankton community. Variation partition analysis showed spatial factors exhibited greater influence on phytoplankton community compared to environmental variables. The stronger influence of spatial factors was further demonstrated by Mantel test and neutral community model. These findings indicate deterministic and stochastic processes exhibited similar biogeographic patterns for phytoplankton community in MLYR lakes, but stochastic process was overwhelmingly dominated. Moreover, a large proportion of unexplained variation implies complex interactions exist to shape assembly mechanism of phytoplankton community in MLYR lakes.