Lake Ecosystem Robustness and Resilience Inferred from a Climate-Stressed Protistan Plankton Network

Unraveling the impact of climatic warming and wetting on eukaryotic microbial diversity and assembly mechanisms: A 10-year case study in Lake Bosten, NW China

Over the last six decades, northwest China has undergone a significant climatic shift from "warm-dry" to "warm-wet", profoundly impacting the structures and functions of lake ecosystem across the region. However, the influences of this climatic transition on the diversity patterns, co-occurrence network, and assembly processes of eukaryotic microbial communities in lake ecosystem, along with the underlying mechanisms, remain largely unexplored. To bridge this knowledge gap, our study focused on Lake Bosten, the largest inland freshwater body in China, conducting a comprehensive analysis. Firstly, we examined the dynamics of key water quality parameters in the lake based on long-term monitoring data (1992-2022). Subsequently, we collected 93 water samples spanning two distinctive periods: low water level (WL) and high total dissolved solids (TDS) (PerWLTDS; 2010-2011; attributed to "warm-dry" climate), and high WL and low TDS (PerTDSWL; 2021-2022; associated with "warm-wet" climate). Eukaryotic microorganisms were further investigated using 18S rRNA gene sequencing and various statistical methods. Our findings revealed that climatic warming and wetting significantly increased eukaryotic microbial α-diversity (all Wilcox. test: P<0.05), while simultaneously reducing β-diversity (all Wilcox. test: P<0.001) and network complexity. Through the two sampling periods, assembly mechanisms of eukaryotic microorganisms were predominantly influenced by dispersal limitation (DL) and drift (DR) within stochastic processes, alongside homogeneous selection (HoS) within deterministic processes. WL played a mediating role in eukaryotic microbial DL and HoS processes in the PerTDSWL, whereas water quality and α-diversity influenced the DL process in the PerWLTDS. Collectively, these results underscore the direct and indirect impacts of "warm-wet" conditions on the eukaryotic microorganisms within Lake Bosten. This study provides valuable insights into the evolutionary dynamics of lake ecosystems under such climatic conditions and aids in predicting the ecological ramifications of global climatic changes.

Depth significantly affects plastisphere microbial evenness, assembly and co-occurrence pattern but not richness and composition

Microplastics have become one of the hot concerns of global marine pollution. In recent years, diversity and abiotic influence factors of plastisphere microbial communities were well documented, but our knowledge of their assembly mechanisms and co-occurrence patterns remains unclear, especially the effects of depth on them. Here, we collected microorganisms on microplastics to investigate how ocean depth affects on microbial diversity, community composition, assembly processes and co-occurrence patterns. Our results indicated that there were similar microbial richness and community compositions but microbial evenness and unique microbes were obviously different in different ocean layers. Our findings also demonstrated that deterministic processes played dominant roles in the assembly of the mesopelagic plastisphere microbial communities, while the bathypelagic microbial community assembly was mainly shaped by stochastic processes. In addition, the co-occurrence networks suggested that the relationships between microorganisms in the mesopelagic layer were more complex and stable than those in the bathypelagic layer. Simultaneously, we also found that Proteobacteria and Actinobacteriota were the most abundant keystones which played important roles in microbial co-occurrence networks at both layers. This study enhanced our understanding of microbial diversity, assembly mechanism, and co-occurrence pattern on plastisphere surfaces, and provided useful insights into microorganisms capable of degrading plastics and microbial remediation.

The role of the core microorganisms in the microbial interactions in activated sludge

In order to gain a deeper understanding of the microbial interactions in wastewater treatment plants (WWTPs) in China and clarify the role of the core community in the microbial interactions in activated sludge (AS), this study used a molecular ecological network approach based on random matrix theory to construct co-occurrence networks of the core microorganisms (CoreN), the whole AS community (WholeN) and the microbial communities without the core microorganisms (OtherN), respectively. It was shown that the WholeN had more complex and tighter connections compared with the OtherN, because of its higher total number of nodes, higher average clustering coefficient, and shorter average geodesic distance. The proportions of positive links in the CoreN, WholeN and OtherN were gradually decreased, indicating that the core microorganisms promoted cooperation between AS microorganisms. Moreover, higher robustness after random removal of 50% of the nodes of the WholeN (0.2836 ± 0.0311) was observed than the robustness of the OtherN (0.1152 ± 0.0263). In addition, the vulnerability of OtherN (0.0514) is significantly higher than WholeN (0.0225). Meanwhile, the average ratio of negative/positive cohesion, was significantly decreased when the core microorganisms were removed. These results demonstrated that core community could strengthen the stability of the ecological network in AS. By discerning the key factors affecting ecological network, AS temperature was observed to have a strong correlation with all three networks. Moreover, pollutants in wastewater shown stronger correlations with the CoreN and WholeN, supporting the point that core community play a critical role in pollutant removal in WWTPs to a certain extent.

FISHing for ciliates: Catalyzed reporter deposition fluorescence in situ hybridization for the detection of planktonic freshwater ciliates

Planktonic ciliate species form multiple trophic guilds and are central components of freshwater food webs. Progress in molecular analytical tools has opened new insight into ciliate assemblages. However, high and variable 18S rDNA copy numbers, typical for ciliates, make reliable quantification by amplicon sequencing extremely difficult. For an exact determination of abundances, the classical morphology-based quantitative protargol staining is still the method of choice. Morphotype analyses, however, are time consuming and need specific taxonomic expertise. Catalyzed reporter deposition fluorescence in situ hybridization (CARD-FISH) may represent a promising tool for the analysis of planktonic ciliates by combining molecular identification with microscopic quantification. We tested the applicability of CARD-FISH using nine cultured ciliate species. Eight species- and three genus-specific oligonucleotide probes were designed based on their 18S rRNA genes. The CARD-FISH protocol was adapted and the specificity of probes was established. We subsequently examined the precision of quantitation by CARD-FISH on single cultures and mock assemblages. Successful tests on lake water samples proved that planktonic ciliates could be identified and quantified in field samples by CARD-FISH. Double hybridizations allowed studying interspecific predator prey interactions between two ciliate species. In summary, we demonstrate that CARD-FISH with species-specific probes can facilitate studies on the population dynamics of closely related, small sized or cryptic species at high sampling frequencies.

Droplet microfluidics-based high-throughput bacterial cultivation for validation of taxon pairs in microbial co-occurrence networks

Co-occurrence networks inferred from the abundance data of microbial communities are widely applied to predict microbial interactions. However, the high workloads of bacterial isolation and the complexity of the networks themselves constrained experimental demonstrations of the predicted microbial associations and interactions. Here, we integrate droplet microfluidics and bar-coding logistics for high-throughput bacterial isolation and cultivation from environmental samples, and experimentally investigate the relationships between taxon pairs inferred from microbial co-occurrence networks. We collected Potamogeton perfoliatus plants (including roots) and associated sediments from Beijing Olympic Park wetland. Droplets of series diluted homogenates of wetland samples were inoculated into 126 96-well plates containing R2A and TSB media. After 10 days of cultivation, 65 plates with > 30% wells showed microbial growth were selected for the inference of microbial co-occurrence networks. We cultivated 129 bacterial isolates belonging to 15 species that could represent the zero-level OTUs (Zotus) in the inferred co-occurrence networks. The co-cultivations of bacterial isolates corresponding to the prevalent Zotus pairs in networks were performed on agar plates and in broth. Results suggested that positively associated Zotu pairs in the co-occurrence network implied complicated relations including neutralism, competition, and mutualism, depending on bacterial isolate combination and cultivation time.

Temperature mediated the balance between stochastic and deterministic processes and reoccurrence of microbial community during treating aniline wastewater

Seasonal temperature changes significantly affect microbial community diversity, composition, and performance in wastewater treatment plants. However, the community assembly mechanisms under seasonal temperature variations remain unclear. Here, we carried out temperature cycling experiments (30 °C, 35 °C, 37 °C, 40 °C, 42 °C, 45 °C, 40 °C, and 30 °C) to investigate how temperature impacts microbial performance and co-occurrence network and how assembly processes determine the structure and function of microbial communities during treating aniline wastewater. During the 195-day operation, the system achieved an efficient and stable aniline removal of 99%. Interestingly, α-diversity and network complexity were negatively correlated with temperature but could be recovered when the temperature was returned to 30 °C. The results showed that functional redundancy was probably responsible for the excellent microbial performance during the whole process. Null model analyses presented that deterministic process dominated the community when the temperature was 30 °C, and stochasticity dominated the assembly process when the temperature was over 30 °C. Overall, the balance between stochastic and deterministic processes in the treatment of aniline wastewater mediated the reoccurrence of microbial community and co-occurrence network at different temperatures. This study provides new insights into microbial community reoccurrence under seasonal temperature changes and a theoretical basis for regulating microbial communities in wastewater treatment plants.

The relationship between land cover and microbial community composition in European lakes

Microbes are essential for element cycling and ecosystem functioning. However, many questions central to understanding the role of microbes in ecology are still open. Here, we analyze the relationship between lake microbiomes and the lakes' land cover. By applying machine learning methods, we quantify the covariance between land cover categories and the microbial community composition recorded in the largest amplicon sequencing dataset of European lakes available to date. Our results show that the aggregation of environmental features or microbial taxa before analysis can obscure ecologically relevant patterns. We observe a comparatively high covariation of the lakes' microbial community with herbaceous and open spaces surrounding the lake; nevertheless, the microbial covariation with land cover categories is generally lower than the covariation with physico-chemical parameters. Combining land cover and physico-chemical bioindicators identified from the same amplicon sequencing dataset, we develop analytical data structures that facilitate insights into the ecology of the lake microbiome. Among these, a list of the environmental parameters sorted by the number of microbial bioindicators we have identified for them points towards apparent environmental drivers of the lake microbial community composition, such as the altitude, conductivity, and area covered herbaceous vegetation surrounding the lake. Furthermore, the response map, a similarity matrix calculated from the Jaccard similarity of the environmental parameters' lists of bioindicators, allows us to study the ecosystem's structure from the standpoint of the microbiome. More specifically, we identify multiple clusters of highly similar and possibly functionally linked ecological parameters, including one that highlights the importance of the calcium-bicarbonate equilibrium for lake ecology. Taken together, we demonstrate the use of machine learning approaches in studying the interplay between microbial diversity and environmental factors and introduce novel approaches to integrate environmental molecular diversity into monitoring and water quality assessments.

Destabilization of the Bacterial Interactome Identifies Nutrient Restriction-Induced Dysbiosis in Insect Guts

Stress-associated dysbiosis of microbiome can have several configurations that, under an energy landscape conceptual framework, can change from one configuration to another due to different alternating selective forces. It has been proposed-according to the Anna Karenina Principle-that in stressed individuals the microbiome are more dispersed (i.e., with a higher within-beta diversity), evidencing the grade of dispersion as indicator of microbiome dysbiosis. We hypothesize that although dysbiosis leads to different microbial communities in terms of beta diversity, these are not necessarily differently dispersed (within-beta diversity), but they form disrupted networks that make them less resilient to stress. To test our hypothesis, we select nutrient restriction (NR) stress that impairs host fitness but does not introduce overt microbiome selectors, such as toxic compounds and pathogens. We fed the polyphagous black soldier fly, Hermetia illucens, with two NR diets and a control full-nutrient (FN) diet. NR diets were dysbiotic because they strongly affected insect growth and development, inducing significant microscale changes in physiochemical conditions of the gut compartments. NR diets established new configurations of the gut microbiome compared to FN-fed guts but with similar dispersion. However, these new configurations driven by the deterministic changes induced by NR diets were reflected in rarefied, less structured, and less connected bacterial interactomes. These results suggested that while the dispersion cannot be considered a consistent indicator of the unhealthy state of dysbiotic microbiomes, the capacity of the community members to maintain network connections and stability can be an indicator of the microbial dysbiotic conditions and their incapacity to sustain the holobiont resilience and host homeostasis. IMPORTANCE Changes in diet play a role in reshaping the gut microbiome in animals, inducing dysbiotic configurations of the associated microbiome. Although studies have reported on the effects of specific nutrient contents on the diet, studies regarding the conditions altering the microbiome configurations and networking in response to diet changes are limited. Our results showed that nutrient poor diets determine dysbiotic states of the host with reduction of insect weight and size, and increase of the times for developmental stage. Moreover, the poor nutrient diets lead to changes in the compositional diversity and network interaction properties of the gut microbial communities. Our study adds a new component to the understanding of the ecological processes associated with dysbiosis, by disentangling consequences of diets on microbiome dysbiosis that is manifested with the disruption of microbiome networking properties rather than changes in microbiome dispersion and beta diversity.

Molecular Data Reveal a Cryptic Diversity in the Genus Urotricha (Alveolata, Ciliophora, Prostomatida), a Key Player in Freshwater Lakes, With Remarks on Morphology, Food Preferences, and Distribution

Species of the ciliate genus Urotricha are key players in freshwater plankton communities. In the pelagial of lakes, about 20 urotrich species occur throughout an annual cycle, some of which play a pivotal role in aquatic food webs. For example, during the phytoplankton spring bloom, they consume a remarkable proportion of the algal production. In ecological studies, urotrich ciliates are usually merely identified to genus rank and grouped into size classes. This is unsatisfying considering the distinct autecological properties of individual species and their specific spatial and temporal distribution patterns. As a basis for future research, we characterized in detail four common urotrich morphotypes, i.e., specimens identified as U. furcata and tentatively as U. agilis, U. pseudofurcata, and U. castalia, using state-of-the-art methods. We used an integrative polyphasic approach, in which morphological studies (in vivo observation, silver staining methods, scanning electron microscopy) were linked with a molecular approach exploiting four different gene fragments as taxonomic DNA barcodes with different resolution potential (SSU rDNA, ITS-1, ITS-2, hypervariable V4 and V9 regions of the SSU rDNA). We shed light on the diversity of urotrich ciliates as well as on their global distribution patterns, and annual cycles. Additionally, we coupled individual species occurrences and environmental parameters, and subsequently modeled the distribution and occurrence, using logistic regressions. Furthermore, for one strain putatively identified as U. castalia, we ascertained the optimal cultivation media and food preferences. Thereby, our comprehensive view on these important freshwater ciliates that frequently occur in environmental high throughput sequencing datasets worldwide will allow future studies to better exploit protistan plankton data from lakes.

Long-term dynamics of the human oral microbiome during clinical disease progression

BACKGROUND

Oral microbiome dysbiosis is linked to overt inflammation of tooth-supporting tissues, leading to periodontitis, an oral condition that can cause tooth and bone loss. Microbiome dysbiosis has been described as a disruption in the symbiotic microbiota composition's stability that could adversely affect the host's health status. However, the precise microbiome dynamics that lead to dysbiosis and the progression of the disease are largely unknown. The objective of our study was to investigate the long-term dynamics of periodontitis progression and its connection to dysbiosis.

RESULTS

We studied three different teeth groups: sites that showed disease progression, sites that remained stable during the study, and sites that exhibited a cyclic deepening followed by spontaneous recovery. Time-series analysis revealed that communities followed a characteristic succession of bacteria clusters. Stable and fluctuating sites showed high asynchrony in the communities (i.e., different species responding dissimilarly through time) and a reordering of the communities where directional changes dominated (i.e., sample distance increases over time) in the stable sites but not in the fluctuating sites. Progressing sites exhibited low asynchrony and convergence (i.e., samples distance decreases over time). Moreover, new species were more likely to be recruited in stable samples if a close relative was not recruited previously. In contrast, progressing and fluctuating sites followed a neutral recruitment model, indicating that competition between closely related species is a significant component of species-species interactions in stable samples. Finally, periodontal treatment did not select similar communities but stabilized α-diversity, centered the abundance of different clusters to the mean, and increased community rearrangement.

CONCLUSIONS

Here, we show that ecological principles can define dysbiosis and explain the evolution and outcomes of specific microbial communities of the oral microbiome in periodontitis progression. All sites showed an ecological succession in community composition. Stable sites were characterized by high asynchrony, a reordering of the communities where directional changes dominated, and new species were more likely to be recruited if a close relative was not recruited previously. Progressing sites were characterized by low asynchrony, community convergence, and a neutral model of recruitment. Finally, fluctuating sites were characterized by high asynchrony, community convergence, and a neutral recruitment model.

Detection of the Deep-Sea Plankton Community in Marine Ecosystem with Underwater Robotic Platform

Variations in the quantity of plankton impact the entire marine ecosystem. It is of great significance to accurately assess the dynamic evolution of the plankton for monitoring the marine environment and global climate change. In this paper, a novel method is introduced for deep-sea plankton community detection in marine ecosystem using an underwater robotic platform. The videos were sampled at a distance of 1.5 m from the ocean floor, with a focal length of 1.5-2.5 m. The optical flow field is used to detect plankton community. We showed that for each of the moving plankton that do not overlap in space in two consecutive video frames, the time gradient of the spatial position of the plankton are opposite to each other in two consecutive optical flow fields. Further, the lateral and vertical gradients have the same value and orientation in two consecutive optical flow fields. Accordingly, moving plankton can be accurately detected under the complex dynamic background in the deep-sea environment. Experimental comparison with manual ground-truth fully validated the efficacy of the proposed methodology, which outperforms six state-of-the-art approaches.