[Biogeographic Distribution Patterns and Ecological Mechanisms of Benthic Eukaryotic Microorganisms in Jinsha River]

Eukaryotic microbial communities play an important role in biogeochemical cycling and maintaining the health and stability of ecosystems. However, little is known about the geographical distribution patterns, key driving mechanisms, and interspecific interactions of eukaryotic microorganisms in large rivers. This study investigated the geographical distribution characteristics, influencing factors, and interspecific interactions of eukaryotic microorganisms in sediments from the Jinsha River, a cascade hydropower development river in southwest China. The results showed that the α-diversity indices of benthic eukaryotic microorganisms in the Jinsha River increased first and then decreased. The community structure and relative abundance of dominant genera of benthic eukaryotic microorganisms differed significantly among different reaches. The results of distance decay analysis showed that the community assembly of benthic eukaryotic microorganisms in the Jinsha River was influenced by environmental selection and dispersal limitation. The results of variance partitioning analysis and neutral model further demonstrated that the geographical distribution pattern was mainly driven by dispersal limitation. The co-occurrence network analysis revealed that the interspecific competition and network connectivity of the cascade dam reach were weaker than those of the upstream natural reach, indicating that the interactions of benthic eukaryotic microorganisms were stronger in the upstream natural reach. This study supplemented the lack of data on the diversity and geographical distribution of benthic eukaryotic microorganisms in the river of southwest China and provided data support for the ecological response of benthic eukaryotic microorganisms in the river of cascade hydropower development.

Robust cross-cohort gut microbiome associations with COVID-19 severity

Although many recent studies have examined associations between the gut microbiome and COVID-19 disease severity in individual patient cohorts, questions remain on the robustness across international cohorts of the biomarkers they reported. Here, we performed a meta-analysis of eight shotgun metagenomic studies of COVID-19 patients (comprising 1,023 stool samples) and 23 > 16S rRNA gene amplicon sequencing (16S) cohorts (2,415 total stool samples). We found that disease severity (as defined by the WHO clinical progression scale) was associated with taxonomic and functional microbiome differences. This alteration in gut microbiome configuration peaks at days 7-30 post diagnosis, after which the gut microbiome returns to a configuration that becomes more similar to that of healthy controls over time. Furthermore, we identified a core set of species that were consistently associated with disease severity across shotgun metagenomic and 16S cohorts, and whose abundance can accurately predict disease severity category of SARS-CoV-2 infected subjects, with Actinomyces oris abundance predicting population-level mortality rate of COVID-19. Additionally, we used relational diet-microbiome databases constructed from cohort studies to predict microbiota-targeted diet patterns that would modulate gut microbiota composition toward that of healthy controls. Finally, we demonstrated the association of disease severity with the composition of intestinal archaeal, fungal, viral, and parasitic communities. Collectively, this study has identified robust COVID-19 microbiome biomarkers, established accurate predictive models as a basis for clinical prognostic tests for disease severity, and proposed biomarker-targeted diets for managing COVID-19 infection.

Different distribution patterns of microorganisms between aquaculture pond sediment and water

Aquatic microorganisms in the sediment and water column are closely related; however, their distribution patterns between these two habitats still remain largely unknown. In this study, we compared sediment and water microeukaryotic and bacterial microorganisms in aquaculture ponds from different areas in China, and analyzed the influencing environmental factors as well as the inter-taxa relationships. We found that bacteria were significantly more abundant than fungi in both sediment and water, and the bacterial richness and diversity in sediment were higher than in water in all the sampling areas, but no significant differences were found between the two habitats for microeukaryotes. Bacterial taxa could be clearly separated through cluster analysis between the sediment and water, while eukaryotic taxa at all classification levels could not. Spirochaetea, Deltaproteobacteria, Nitrospirae, Ignavibacteriae, Firmicutes, Chloroflexi, and Lentimicrobiaceae were more abundantly distributed in sediment, while Betaproteobacteria, Alphaproteobacter, Cyanobacteria, Roseiflexaceae, Dinghuibacter, Cryomorphaceae, and Actinobacteria were more abundant in water samples. For eukaryotes, only Cryptomonadales were found to be distributed differently between the two habitats. Microorganisms in sediment were mainly correlated with enzymes related to organic matter decomposition, while water temperature, pH, dissolved oxygen, and nutrient levels all showed significant correlation with the microbial communities in pond water. Intensive interspecific relationships were also found among eukaryotes and bacteria. Together, our results indicated that eukaryotic microorganisms are distributed less differently between sediment and water in aquaculture ponds compared to bacteria. This study provides valuable data for evaluating microbial distributions in aquatic environments, which may also be of practical use in aquaculture pond management.

Heavy metal whole-cell biosensors using eukaryotic microorganisms: an updated critical review

This review analyzes the advantages and disadvantages of using eukaryotic microorganisms to design whole-cell biosensors (WCBs) for monitoring environmental heavy metal pollution in soil or aquatic habitats. Basic considerations for designing a eukaryotic WCB are also shown. A comparative analysis of the promoter genes used to design WCBs is carried out, and the sensitivity and reproducibility of the main reporter genes used is also reviewed. Three main eukaryotic taxonomic groups are considered: yeasts, microalgae, and ciliated protozoa. Models that have been widely analyzed as potential WCBs are the Saccharomyces cerevisiae model among yeasts, the Tetrahymena thermophila model for ciliates and Chlamydomonas model for microalgae. The advantages and disadvantages of each microbial group are discussed, and a ranking of sensitivity to the same type of metal pollutant from reported eukaryotic WCBs is also shown. General conclusions and possible future developments of eukaryotic WCBs are reported.

Eukaryotic microorganisms in cold environments: examples from Pyrenean glaciers

Little is known about the viability of eukaryotic microorganisms preserved in icy regions. Here we report on the diversity of microbial eukaryotes in ice samples derived from four Pyrenean glaciers. The species composition of eukaryotic communities in these glaciers is unknown mostly because of the presence of a multi-year ice cap, and it is not clear whether they harbor the same populations. The recent deglaciation of these areas is allowing an easy access to glacial layers that correspond to the “Little Ice Age” although some isolated deposits are attributed to previous glacial cycles. In this study, we use molecular 18S rRNA-based approaches to characterize some of the microbial eukaryotic populations associated with Pyrenean glaciers. Firstly, we performed a chemical and microscopical characterization of ice samples. Secondly, molecular analyses revealed interesting protist genetic diversity in glaciers. In order to understand the microbial composition of the ice samples the eukaryotic communities resident in the glacial samples were examined by amplifying community DNA and constructing clone libraries with 18S rRNA primers. After removal of potential chimeric sequences and dereplication of identical sequences, phylogenetic analysis demonstrated that several different protists could be identified. Protist diversity was more phylum rich in Aneto and Monte Perdido glaciers. The dominant taxonomic groups across all samples (>1% of all sequences) were Viridiplantae and Rhizaria. Significant variations in relative abundances of protist phyla between higher and lower glaciers were observed. At the genus level, significant differences were also recorded for the dominant genera Chloromonas, Raphidonema, Heteromita, Koliella, and Bodomorpha. In addition, protist community structure showed significant differences between glaciers. The relative abundances of protist groups at different taxonomic levels correlated with the altitude and area of glaciers and with pH of ice, but little or no relationships to other chemical characteristics were found.