Microeukaryotic plankton evolutionary constraints in a subtropical river explained by environment and bacteria along differing taxonomic resolutions.

Microeukaryotic plankton communities are keystone components for keeping aquatic primary productivity. Currently, variations in microeukaryotic plankton diversity have often been explained by local ecological factors but not by evolutionary constraints. We used amplicon sequencing of 100 water samples across five years to investigate the ecological preferences of the microeukaryotic plankton community in a subtropical riverine ecosystem. We found that microeukaryotic plankton diversity was less associated with bacterial abundance (16S rRNA gene copy number) than bacterial diversity. Further, environmental effects exhibited a larger influence on microeukaryotic plankton community composition than bacterial community composition, especially at fine taxonomic levels. The evolutionary constraints of microeukaryotic plankton community increased with decreasing taxonomic resolution (from 97% to 91% similarity levels), but not significant change from 85% to 70% similarity levels. However, compared with the bacterial community, the evolutionary constraints were shown to be more affected by environmental variables. This study illustrated possible controlling environmental and bacterial drivers of microeukaryotic diversity and community assembly in a subtropical river, thereby indirectly reflecting on the quality status of the water environment by providing new clues on the microeukaryotic community assembly.

The impact of rainfall events on dissolved oxygen concentrations in a subtropical urban reservoir.

Understanding controls of dissolved oxygen (DO) concentrations in reservoirs is important as they are important for fisheries and a significant driver of greenhouse gas emissions. The latter is of global significance as IPCC inventories now require greenhouse gas emissions from artificial reservoirs to be included. Declines in dissolved oxygen (DO) concentrations in lakes and reservoirs have been linked to climate change and human activity. However, these effects can vary widely in any given region under various meteorological conditions. There is a clear need to know how changes in weather patterns affect DO in reservoirs by changing internal processes. Based on a six-year (2016-2021) high-frequency (twice a week) dataset from a shallow urban reservoir (Xinglinwan Reservoir) in subtropical China, the long-term (six years) and short-term (8-72-h) drivers of DO concentrations in surface waters were evaluated. Over the past six years, the concentration of DO has gradually decreased in the reservoir from 2016 to 2021. Multivariate adaptive regression spline (MARS) models were developed to identify the key factors explaining variability in DO and partial least squares path models (PLS-PM) were used to explore the short-term relationships between DO and environmental variables in rainy and dry (non-rain) periods, separately. We identified three key drivers operating on different time scales. First, the long-term decline of DO in Xinglinwan Reservoir from 2016 to 2021 was best explained by anthropogenic nutrient inputs. Second, rainy periods prior to sampling reduced DO concentrations indirectly by affecting the algal biomass and nutrient concentrations. This effect varied in complexity with the duration of the rainfall period. Third, water temperature best explained DO concentrations during dry periods, while wind reduced DO by reducing algal biomass. We conclude that anthropogenic nutrient and organic matter inputs drive long-term oxygen declines in urban subtropical reservoirs, while meteorological factors determine short-term variability in DO concentrations.

Eutrophication increases the similarity of cyanobacterial community features in lakes and reservoirs.

Eutrophication of inland waters is a mostly anthropogenic phenomenon impacting aquatic biodiversity worldwide, and might change biotic community structure and ecosystem functions. However, little is known about the patterns of cyanobacterial community variations and changes both on alpha and beta diversity levels in response to eutrophication. Here, we investigated cyanobacterial communities sampled at 140 sites from 59 lakes and reservoirs along a strong eutrophication gradient in eastern China through using CPC-IGS and 16S rRNA gene amplicon sequencing. We found that taxonomic diversity increased, but phylogenetic diversity decreased significantly along the eutrophication gradient. Both niche width and niche overlap of cyanobacteria significantly decreased from low- to high-nutrient waterbodies. Cyanobacterial community distance-decay relationship became weaker from mesotrophic to hypereutrophic waterbodies, while ecological uniqueness (i.e., local contributions to beta diversity) tended to increase in high-nutrient waterbodies. Latitude and longitude were more important in shaping cyanobacterial community structure than other environmental variables. These findings suggest that eutrophication affects alpha and beta diversity of cyanobacterial communities, leading to increasingly similar community structures in lakes and reservoirs with a higher level of eutrophication. Our work highlights how cyanobacterial communities respond to anthropogenic eutrophication and calls for an urgent need to develop conservation and management strategies to control lake eutrophication and protect freshwater biodiversity.

Core taxa drive microeukaryotic community stability of a deep subtropical reservoir after complete mixing.

Microeukaryotes are key for predicting the change of ecosystem processes in the face of a disturbance. However, their vertical responses to multiple interconnected factors caused by water mixing remain unknown. Here, we conducted a 12-month high-frequency study to compare the impacts of mixing disturbances on microeukaryotic community structure and stability over different depths in a stratified reservoir. We demonstrate that core and satellite microeukaryotic compositions and interactions in surface waters were not resistant to water mixing, but significantly recovered. This was because the water temperature rebounded to the pre-mixing level. Core microeukaryotes maintained community stability in surface waters with high recovery capacity after water mixing. In contrast, the changes in water temperature, chlorophyll-a, and nutrients resulted in steep and prolonged variations in the bottom core and satellite microeukaryotic compositions and interactions. Under low environmental fluctuation, the recovery of microbial communities did not affect nutrient cycling in surface waters. Under high environmental fluctuation, core and satellite microeukaryotic compositions in bottom waters were significantly correlated with the multi-nutrient cycling index. Our findings shed light on different mechanisms of plankton community resilience in reservoir ecosystems to a major disturbance over depths, highlighting the role of bottom microeukaryotes in nutrient cycling.

Tipping points of nitrogen use efficiency in freshwater phytoplankton along trophic state gradient.

Eutrophication and harmful algal blooms have severe effects on water quality and biodiversity in lakes and reservoirs. Ecological regime shifts of phytoplankton blooms are generally thought to be driven by the rapidly rising nutrient use efficiency of bloom-forming species over short periods, and often exhibit nonlinear dynamics. Regime shifts of trophic state, eutrophication, stratification, and clear or turbid waters are well-studied topics in aquatic ecology. However, information on the prevalence of regime shifts in relationships between trophic states and phytoplankton resource transfer efficiencies in ecosystems is still lacking. Here, we provided a first insight into regime shifts in nitrogen use efficiency of phytoplankton along the trophic state gradient. We explored the regime shifts of phytoplankton resource use efficiency and detected the tipping points by combining four temporal or spatial datasets from tropical to temperate zones in Asia and Europe. We first observed significant abrupt transitions (abruptness > 1) in phytoplankton nitrogen use efficiency along the trophic state gradient. The tipping point values were lower in subtropical/tropical waterbodies (mesotrophic states; TSIc: around 50) than those in temperate zones (eutrophic states; TSIc: 60-70). The regime shifts significantly reduced the primary production transfer efficiency via zooplankton (from 0.15 ± 0.03 to 0.03 ± 0.01; mean ± standard error) in the aquatic food web. Nitrogen-fixing filamentous cyanobacteria can drive eutrophication under mesotrophic state. Our findings imply that the time-window of opportunity for harmful algae prevention and control in lakes and reservoirs is earlier in subtropical/tropical regions.

Highly efficient atomic hydrogen-mediated electrochemical hydrodehalogenation of trichloroacetic acid on 3D hierarchical multi-transition metal selenides.

Halogenated organic compounds as highly focused emerging contaminants pose a long-lasting threat to human health and the aquatic environment due to their high toxicities and strong anti-biodegradation characteristics. Electrochemical hydrodehalogenation (ECHD) is a promising technology with a low-carbon footprint to remove halogenated organic compounds while suffering from a lack of efficient and robust earth-abundant electrocatalysts. Herein, by integrating two kinds of transition metal dichalcogenides (i.e., MoSe2 nanosheet and Ni3Se2 nanowire) into a conductive 3D porous network nickel foam, we obtained a hierarchical architecture (MoSe2/Ni3Se2@NF) that promises high surface area, fast charge transfer and efficient mass transfer. The interface-confined epitaxial growth of Ni3Se2 nanowires on nickel foam provides abundant sites for the vertical growth of MoSe2 nanosheets, which endows MoSe2 with maximal accessible active edge sites to participate in the ECHD process. Benefiting from such a hierarchical 3D porous configuration, trichloroacetic acid (5 mg/L) was removed over 95% by MoSe2/Ni3Se2@NF at - 1.2 V vs. SCE after 1 h, which dramatically outperformed that for NF (20%) and Ni3Se2@NF (53.2%). The major contributor to such boosted performance is the adsorbed atomic hydrogen (*H) generated during water splitting via suppressing hydrogen-hydrogen dimerization, as evidenced by radical quenching experiments and electron paramagnetic resonance spectroscopy. This study offers appealing opportunities for tailoring the catalytic performance of noble-metal-free heterogeneous catalysts for various applications that require noble-metal catalysts.

Relic DNA obscures DNA-based profiling of multiple microbial taxonomic groups in a river-reservoir ecosystem.

Numerous studies have investigated the spatiotemporal variability in water microbial communities, yet the effects of relic DNA on microbial community profiles, especially microeukaryotes, remain far from fully understood. Here, total and active bacterial and microeukaryotic community compositions were characterized using propidium monoazide (PMA) treatment coupled with high-throughput sequencing in a river-reservoir ecosystem. Beta diversity analysis showed a significant difference in community composition between both the PMA untreated and treated bacteria and microeukaryotes; however, the differentiating effect was much stronger for microeukaryotes. Relic DNA only resulted in underestimation of the relative abundances of Bacteroidota and Nitrospirota, while other bacterial taxa exhibited no significant changes. As for microeukaryotes, the relative abundances of some phytoplankton (e.g. Chlorophyta, Dinoflagellata and Ochrophyta) and fungi were greater after relic DNA removal, whereas Cercozoa and Ciliophora showed the opposite trend. Moreover, relic DNA removal weakened the size and complexity of cross-trophic microbial networks and significantly changed the relationships between environmental factors and microeukaryotic community composition. However, there was no significant difference in the rates of temporal community turnover between the PMA untreated and treated samples for either bacteria or microeukaryotes. Overall, our results imply that the presence of relic DNA in waters can give misleading information of the active microbial community composition, co-occurrence networks and their relationships with environmental conditions. More studies of the abundance, decay rate and functioning of nonviable DNA in freshwater ecosystems are highly recommended in the future.

SARS-CoV-2 neutralising antibody therapies: Recent advances and future challenges.

The COVID-19 pandemic represents an unparalleled global public health crisis. Despite concerted research endeavours, the repertoire of effective treatment options remains limited. However, neutralising-antibody-based therapies hold promise across an array of practices, encompassing the prophylaxis and management of acute infectious diseases. Presently, numerous investigations into COVID-19-neutralising antibodies are underway around the world, with some studies reaching clinical application stages. The advent of COVID-19-neutralising antibodies signifies the dawn of an innovative and promising strategy for treatment against SARS-CoV-2 variants. Comprehensively, our objective is to amalgamate contemporary understanding concerning antibodies targeting various regions, including receptor-binding domain (RBD), non-RBD, host cell targets, and cross-neutralising antibodies. Furthermore, we critically examine the prevailing scientific literature supporting neutralising antibody-based interventions, and also delve into the functional evaluation of antibodies, with a particular focus on in vitro (vivo) assays. Lastly, we identify and consider several pertinent challenges inherent to the realm of COVID-19-neutralising antibody-based treatments, offering insights into potential future directions for research and development.

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Coronavirus disease 2019 (COVID-19) has continued to spread globally since late 2019, representing a formidable challenge to the world's healthcare systems, wreaking havoc, and spreading rapidly through human contact. With fever, fatigue, and a persistent dry cough being the hallmark symptoms, this disease threatened to destabilize the delicate balance of our global community. Rapid and accurate diagnosis of COVID-19 is a prerequisite for understanding the number of confirmed cases in the world or a region, and an important factor in epidemic assessment and the development of control measures. It also plays a crucial role in ensuring that patients receive the appropriate medical treatment, leading to optimal patient care. Reverse transcription-polymerase chain reaction (RT-PCR) technology is currently the most mature method for detecting viral nucleic acids, but it has many drawbacks. Meanwhile, a variety of COVID-19 detection methods, including molecular biological diagnostic, immunodiagnostic, imaging, and artificial intelligence methods have been developed and applied in clinical practice to meet diverse scenarios and needs. These methods can help clinicians diagnose and treat COVID-19 patients. This review describes the variety of such methods used in China, providing an important reference in the field of the clinical diagnosis of COVID-19.

Review of therapeutic mechanisms and applications based on SARS-CoV-2 neutralizing antibodies.

COVID-19 pandemic is a global public health emergency. Despite extensive research, there are still few effective treatment options available today. Neutralizing-antibody-based treatments offer a broad range of applications, including the prevention and treatment of acute infectious diseases. Hundreds of SARS-CoV-2 neutralizing antibody studies are currently underway around the world, with some already in clinical applications. The development of SARS-CoV-2 neutralizing antibody opens up a new therapeutic option for COVID-19. We intend to review our current knowledge about antibodies targeting various regions (i.e., RBD regions, non-RBD regions, host cell targets, and cross-neutralizing antibodies), as well as the current scientific evidence for neutralizing-antibody-based treatments based on convalescent plasma therapy, intravenous immunoglobulin, monoclonal antibodies, and recombinant drugs. The functional evaluation of antibodies (i.e., in vitro or in vivo assays) is also discussed. Finally, some current issues in the field of neutralizing-antibody-based therapies are highlighted.

Remote Synergy between Heterogeneous Single Atoms and Clusters for Enhanced Oxygen Evolution.

Integrating single atoms and clusters into one system is a novel strategy to achieve desired catalytic performances. Compared with homogeneous single-atom cluster catalysts, heterogeneous ones combine the merits of different species and therefore show greater potential. However, it is still challenging to construct single-atom cluster systems of heterogeneous species, and the underlying mechanism for activity improvement remains unclear. In this work, we developed a heterogeneous single-atom cluster catalyst (ConIr1/N-C) for efficient oxygen evolution. The Ir single atoms worked in synergy with the Co clusters at a distance of about 8 Å, which optimized the configuration of the key intermediates. Consequently, the oxygen evolution activity was significantly improved on ConIr1/N-C relative to the Co cluster catalyst (Con/N-C), exhibiting an overpotential lower by 107 mV than that of Con/N-C at 10 mA cm-2 and a turnover frequency 50.9 times as much as that of Con/N-C at an overpotential of 300 mV.

Planktonic ciliate community driven by environmental variables and cyanobacterial blooms: A 9-year study in two subtropical reservoirs.

It is well-established that environmental variability and cyanobacterial blooms have major effects on the assembly and functioning of bacterial communities in both marine and freshwater habitats. It remains unclear, however, how the ciliate community responds to such changes over the long-term, particularly in subtropical lake and reservoir ecosystems. We analysed 9-year planktonic ciliate data series from the surface water of two subtropical reservoirs to elucidate the role of cyanobacterial bloom and environmental variabilities on the ciliate temporal dynamics. We identified five distinct periods of cyanobacterial succession in both reservoirs. Using multiple time-scale analyses, we found that the interannual variability of ciliate communities was more strongly related to cyanobacterial blooms than to other environmental variables or to seasonality. Moreover, the percentage of species turnover across cyanobacterial bloom and non-bloom periods increased significantly with time over the 9-year period. Phylogenetic analyses further indicated that 84 %-86 % of ciliate community turnover was governed by stochastic dispersal limitation or undominated processes, suggesting that the ciliate communities in subtropical reservoirs were mainly controlled by neutral processes. However, short-term blooms increased the selection pressure and drove 30 %-53 % of the ciliate community turnover. We found that the ciliate community composition was influenced by environmental conditions with nutrients, cyanobacterial biomass and microzooplankton having direct and/or indirect significant effects on the ciliate taxonomic or functional community dynamics. Our results provide new insights into the long-term temporal dynamics of planktonic ciliate communities under cyanobacterial bloom disturbance.

Interaction between Raphidiopsis raciborskii and rare bacterial species revealed by dilution-to-extinction experiments.

Interactions between heterotrophic bacteria and cyanobacteria regulate the structure and function of aquatic ecosystems and are thus crucial for the prediction and management of cyanobacterial blooms in relation to water security. Currently, abundant bacterial species are of primary concern, while the role of more diverse and copious rare species remains largely unknown. Using a dilution-to-extinction approach, rare bacterial species from reservoir water were co-cultured with the bloom-forming cyanobacterium Raphidiopsis raciborskii in the lab to explore their interactions by using Phyto-PAM and 16S rRNA gene high-throughput sequencing. We found that a ≤1000-fold bacterial dilution led to bacteria control of the growth and photosynthesis of R. raciborskii. Moreover, the bacterial community compositions in the low-dilution groups were clearly diverged from the high-dilution groups. Importantly, rare species changed dramatically in the low-dilution groups, resulting in lower phylogenetic diversity and narrower niche width. The network complexity and compositional stability of bacterial communities decreased in the low-dilution groups. Collectively, our results suggest that rare bacterial species inhibit R. raciborskii growth and photosynthesis through microbial interactions mediated by species coexistence and interaction mechanisms. Our study provides new knowledge of the ecological role of rare bacteria and offers new perspectives for understanding the outbreak and regression of R. raciborskii blooms.

Adenylate cyclase activity of TIR1/AFB auxin receptors in plants.

The phytohormone auxin is the major coordinative signal in plant development1, mediating transcriptional reprogramming by a well-established canonical signalling pathway. TRANSPORT INHIBITOR RESPONSE 1 (TIR1)/AUXIN-SIGNALING F-BOX (AFB) auxin receptors are F-box subunits of ubiquitin ligase complexes. In response to auxin, they associate with Aux/IAA transcriptional repressors and target them for degradation via ubiquitination2,3. Here we identify adenylate cyclase (AC) activity as an additional function of TIR1/AFB receptors across land plants. Auxin, together with Aux/IAAs, stimulates cAMP production. Three separate mutations in the AC motif of the TIR1 C-terminal region, all of which abolish the AC activity, each render TIR1 ineffective in mediating gravitropism and sustained auxin-induced root growth inhibition, and also affect auxin-induced transcriptional regulation. These results highlight the importance of TIR1/AFB AC activity in canonical auxin signalling. They also identify a unique phytohormone receptor cassette combining F-box and AC motifs, and the role of cAMP as a second messenger in plants.

Development and validation of a nomogram to predict the 30-day mortality risk of patients with intracerebral hemorrhage.

Background: Intracerebral hemorrhage (ICH) is a stroke syndrome with an unfavorable prognosis. Currently, there is no comprehensive clinical indicator for mortality prediction of ICH patients. The purpose of our study was to construct and evaluate a nomogram for predicting the 30-day mortality risk of ICH patients. Methods: ICH patients were extracted from the MIMIC-III database according to the ICD-9 code and randomly divided into training and verification cohorts. The least absolute shrinkage and selection operator (LASSO) method and multivariate logistic regression were applied to determine independent risk factors. These risk factors were used to construct a nomogram model for predicting the 30-day mortality risk of ICH patients. The nomogram was verified by the area under the receiver operating characteristic curve (AUC), integrated discrimination improvement (IDI), net reclassification improvement (NRI), and decision curve analysis (DCA). Results: A total of 890 ICH patients were included in the study. Logistic regression analysis revealed that age (OR = 1.05, P < 0.001), Glasgow Coma Scale score (OR = 0.91, P < 0.001), creatinine (OR = 1.30, P < 0.001), white blood cell count (OR = 1.10, P < 0.001), temperature (OR = 1.73, P < 0.001), glucose (OR = 1.01, P < 0.001), urine output (OR = 1.00, P = 0.020), and bleeding volume (OR = 1.02, P < 0.001) were independent risk factors for 30-day mortality of ICH patients. The calibration curve indicated that the nomogram was well calibrated. When predicting the 30-day mortality risk, the nomogram exhibited good discrimination in the training and validation cohorts (C-index: 0.782 and 0.778, respectively). The AUCs were 0.778, 0.733, and 0.728 for the nomogram, Simplified Acute Physiology Score II (SAPSII), and Oxford Acute Severity of Illness Score (OASIS), respectively, in the validation cohort. The IDI and NRI calculations and DCA analysis revealed that the nomogram model had a greater net benefit than the SAPSII and OASIS scoring systems. Conclusion: This study identified independent risk factors for 30-day mortality of ICH patients and constructed a predictive nomogram model, which may help to improve the prognosis of ICH patients.

RALF1 peptide triggers biphasic root growth inhibition upstream of auxin biosynthesis.

Plant cell growth responds rapidly to various stimuli, adapting architecture to environmental changes. Two major endogenous signals regulating growth are the phytohormone auxin and the secreted peptides rapid alkalinization factors (RALFs). Both trigger very rapid cellular responses and also exert long-term effects [Du et al., Annu. Rev. Plant Biol. 71, 379-402 (2020); Blackburn et al., Plant Physiol. 182, 1657-1666 (2020)]. However, the way, in which these distinct signaling pathways converge to regulate growth, remains unknown. Here, using vertical confocal microscopy combined with a microfluidic chip, we addressed the mechanism of RALF action on growth. We observed correlation between RALF1-induced rapid Arabidopsis thaliana root growth inhibition and apoplast alkalinization during the initial phase of the response, and revealed that RALF1 reversibly inhibits primary root growth through apoplast alkalinization faster than within 1 min. This rapid apoplast alkalinization was the result of RALF1-induced net H+ influx and was mediated by the receptor FERONIA (FER). Furthermore, we investigated the cross-talk between RALF1 and the auxin signaling pathways during root growth regulation. The results showed that RALF-FER signaling triggered auxin signaling with a delay of approximately 1 h by up-regulating auxin biosynthesis, thus contributing to sustained RALF1-induced growth inhibition. This biphasic RALF1 action on growth allows plants to respond rapidly to environmental stimuli and also reprogram growth and development in the long term.

The scale-dependence of spatial distribution of reservoir plankton communities in subtropical and tropical China.

Distance-decay relationships (DDRs) represent a very useful approach to describing the spatial distribution of biological communities. However, plankton DDR patterns and community assembly mechanisms are still poorly understood at different spatial scales in reservoir ecosystems. We collected phytoplankton, zooplankton and water samples in 24 reservoirs from subtropical and tropical China from July to August 2018. We examined DDR patterns across three distinct spatial scales, i.e., within-reservoir, within-drainage (but between reservoirs) and between drainages. We tested whether the rate of change (i.e., slope) of DDRs is consistent across different spatial scales. We assessed the relative importance of spatial and environmental variables in shaping the community distribution of plankton and quantitatively distinguished the community assembly mechanisms. We observed significant DDR curves in phytoplankton and zooplankton communities, in which slopes of the DDRs were steepest at the smallest spatial scale. Both spatial and environmental factors had significant impacts on DDR and dispersal assembly was a slightly stronger process in reservoir phytoplankton and zooplankton community assembly than niche-based process. We conclude that DDRs of reservoir phytoplankton and zooplankton vary with spatial scale. Our data shed light on how spatial and environmental variables contribute to plankton community assembly together. However, we revealed that dispersal process contributes to the biogeography of reservoir plankton slightly more strongly than environmental filtering. Collectively, this study enhances the understanding of plankton biogeography and distribution at multiple spatial scales.

Community assembly of microbial habitat generalists and specialists in urban aquatic ecosystems explained more by habitat type than pollution gradient.

Urban freshwater ecosystems have important ecosystem functions, provide habitats for diverse microbial communities and are susceptible to multiple interconnected factors such as environmental pollution. Despite the ecological significance of bacteria and microeukaryotes, little is known about how their community assembly responds to various environmental factors across water and sediment habitats and ecological processes shaping them. Here, environmental DNA-based approaches were used to investigate the community assembly processes of bacteria and microeukaryotes (including habitat generalists and specialists) in urban water and sediment across an urban-pollution gradient in Wuhan, central China. The diversity, community composition and potential function of bacteria and microeukaryotes showed significantly stronger variation between water and sediment than across an urban pollution gradient. Although, bacterial and microeukaryotic community assemblies were dominated by strong selection processes in both water and sediment habitats, but a contrasting community assembly mechanism was identified between habitat generalists and specialists. Bacterial and microeukaryotic communities showed a greater response to physicochemical variability in water, while a strong distance-decay relationship was found in sediment. Further, cross-kingdom microbial network analysis revealed strong modular associations of bacteria and microeukaryotes, meanwhile, microeukaryotic habitat specialists might be keystone, but generalists have higher proportion of connections in the networks. This study provides significant insights into the response of bacteria and microeukaryotes to different urban pollutions between water and sediment, and the ecological processes structuring microbial community dynamics across habitat types under anthropogenic disturbances.