Lake-depth related pattern of genetic and morphological diatom diversity in boreal Lake Bolshoe Toko, Eastern Siberia

Spatio-temporal changes of small protist and free-living bacterial communities in a temperate dimictic lake: insights from metabarcoding and machine learning

Microbial communities, which include prokaryotes and protists, play an important role in aquatic ecosystems and influence ecological processes. To understand these communities, metabarcoding provides a powerful tool to assess their taxonomic composition and track spatio-temporal dynamics in both marine and freshwater environments. While marine ecosystems have been extensively studied, there is a notable research gap in understanding eukaryotic microbial communities in temperate lakes. Our study addresses this gap by investigating the free-living bacteria and small protist communities in Lake Roś (Poland), a dimictic temperate lake. Metabarcoding analysis revealed that both the bacterial and protist communities exhibit distinct seasonal patterns that are not necessarily shaped by dominant taxa. Furthermore, machine learning and statistical methods identified crucial amplicon sequence variants (ASVs) specific to each season. In addition, we identified a distinct community in the anoxic hypolimnion. We have also shown that the key factors shaping the composition of analysed community are temperature, oxygen, and silicon concentration. Understanding these community structures and the underlying factors is important in the context of climate change potentially impacting mixing patterns and leading to prolonged stratification.

Taxonomic composition, community structure and molecular novelty of microeukaryotes in a temperate oligomesotrophic lake as revealed by metabarcoding

Microbial eukaryotes are diverse and ecologically important organisms, yet sampling constraints have hindered the understanding of their distribution and diversity in freshwater ecosystems. Metabarcoding has provided a powerful complement to traditional limnological studies, revealing an unprecedented diversity of protists in freshwater environments. Here, we aim to expand our knowledge of the ecology and diversity of protists in lacustrine ecosystems by targeting the V4 hypervariable region of the 18S rRNA gene in water column, sediment and biofilm samples collected from Sanabria Lake (Spain) and surrounding freshwater ecosystems. Sanabria is a temperate lake, which are relatively understudied by metabarcoding in comparison to alpine and polar lakes. The phylogenetic diversity of microbial eukaryotes detected in Sanabria spans all currently recognized eukaryotic supergroups, with Stramenopiles being the most abundant and diverse supergroup in all sampling sites. Parasitic microeukaryotes account for 21% of the total protist ASVs identified in our study and were dominated by Chytridiomycota, both in terms of richness and abundance, in all sampling sites. Sediments, biofilms and water column samples harbour distinct microbial communities. Phylogenetic placement of poorly assigned and abundant ASVs indicates molecular novelty inside Rhodophyta, Bigyra, early-branching Nucletmycea and Apusomonadida. In addition, we report the first freshwater incidence of the previously exclusively marine genera Abeoforma and Sphaeroforma. Our results contribute to a deeper understanding of microeukaryotic communities in freshwater ecosystems, and provide the first molecular reference for future biomonitoring surveys in Sanabria Lake.

Depth diversity gradients of macrophytes: Shape, drivers, and recent shifts

Investigating diversity gradients helps to understand biodiversity drivers and threats. However, one diversity gradient is rarely assessed, namely how plant species distribute along the depth gradient of lakes. Here, we provide the first comprehensive characterization of depth diversity gradient (DDG) of alpha, beta, and gamma species richness of submerged macrophytes across multiple lakes. We characterize the DDG for additive richness components (alpha, beta, gamma), assess environmental drivers, and address temporal change over recent years. We take advantage of yet the largest dataset of macrophyte occurrence along lake depth (274 depth transects across 28 deep lakes) as well as of physiochemical measurements (12 deep lakes from 2006 to 2017 across Bavaria), provided publicly online by the Bavarian State Office for the Environment. We found a high variability in DDG shapes across the study lakes. The DDGs for alpha and gamma richness are predominantly hump-shaped, while beta richness shows a decreasing DDG. Generalized additive mixed-effect models indicate that the depth of the maximum richness (D max) is influenced by light quality, light quantity, and layering depth, whereas the respective maximum alpha richness within the depth gradient (R max) is significantly influenced by lake area only. Most observed DDGs seem generally stable over recent years. However, for single lakes we found significant linear trends for R max and D max going into different directions. The observed hump-shaped DDGs agree with three competing hypotheses: the mid-domain effect, the mean-disturbance hypothesis, and the mean-productivity hypothesis. The DDG amplitude seems driven by lake area (thus following known species-area relationships), whereas skewness depends on physiochemical factors, mainly water transparency and layering depth. Our results provide insights for conservation strategies and for mechanistic frameworks to disentangle competing explanatory hypotheses for the DDG.

Lake Sedimentary DNA Research on Past Terrestrial and Aquatic Biodiversity: Overview and Recommendations

The use of lake sedimentary DNA to track the long-term changes in both terrestrial and aquatic biota is a rapidly advancing field in paleoecological research. Although largely applied nowadays, knowledge gaps remain in this field and there is therefore still research to be conducted to ensure the reliability of the sedimentary DNA signal. Building on the most recent literature and seven original case studies, we synthesize the state-of-the-art analytical procedures for effective sampling, extraction, amplification, quantification and/or generation of DNA inventories from sedimentary ancient DNA (sedaDNA) via high-throughput sequencing technologies. We provide recommendations based on current knowledge and best practises.

A new insight into acute lymphoblastic leukemia in children: influences of changed intestinal microfloras

Background

Previous studies have shown that changes in intestinal microfloras are associated with both gastrointestinal (GI) and non-GI tumors. It is not clear whether there is an association between GI microflora changes and hematological malignancies.

Methods

In the current study, we used 16S rDNA gene sequencing techniques to profile the GI microbiome in children with lymphoblastic leukemia (ALL, n = 18) and matched healthy control (n = 18). Using multiple specialized software [Heatmap, Principal coordinates analysis (PCoA), Claster and Metastates], we analyzed the sequencing data for microfloral species classification, abundance and diversity.

Results

A total of 27 genera between the ALL and control groups (FDR ≤ 0.05 and/or P ≤ 0.05) showed significantly different abundance between ALL patients and healthy controls: 12 of them were predominant in healthy group and other 15 species were significantly higher in ALL group. In addition, we compared the abundance and diversity of microfloral species in ALL patients prior to and during remission stage after chemotherapy, and no significant difference was detected.

Conclusions

Compared to healthy controls, ALL patient showed significant changes of GI microfloras. Further explorations of the intestinal micro-ecology in ALL patients may provide important information to understand relationship between microfloras and ALL.