Developmental Toxicity of PEDOT:PSS in Zebrafish: Effects on Morphology, Cardiac Function, and Intestinal Health.

Poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) is a conductive polymer commonly used in various technological applications. However, its impact on aquatic ecosystems remains largely unexplored. In this study, we investigated the toxicity effects of PEDOT:PSS on zebrafish. We first determined the lethal concentration (LC50) of PEDOT:PSS in zebrafish and then exposed AB-type zebrafish embryos to different concentrations of PEDOT:PSS for 120 h. Our investigation elucidated the toxicity effects of zebrafish development, including morphological assessments, heart rate measurements, behavioral analysis, transcriptome profiling, and histopathological analysis. We discovered that PEDOT:PSS exhibited detrimental effects on the early developmental stages of zebrafish, exacerbating the oxidative stress level, suppressing zebrafish activity, impairing cardiac development, and causing intestinal cell damage. This study adds a new dimension to the developmental toxicity of PEDOT:PSS in zebrafish. Our findings contribute to our understanding of the ecological repercussions of PEDOT:PSS and highlight the importance of responsible development and application of novel materials in our rapidly evolving technological landscape.

Biogeographic patterns of meio- and micro-eukaryotic communities in dam-induced river-reservoir systems.

Although the Three Gorges Dam (TGD) is the world's largest hydroelectric dam, little is known about the spatial-temporal patterns and community assembly mechanisms of meio- and micro-eukaryotes and its two subtaxa (zooplankton and zoobenthos). This knowledge gap is particularly evident across various habitats and during different water-level periods, primarily arising from the annual regular dam regulation. To address this inquiry, we employed mitochondrial cytochrome c oxidase I (COI) gene-based environmental DNA (eDNA) metabarcoding technology to systematically analyze the biogeographic pattern of the three communities within the Three Gorges Reservoir (TGR). Our findings reveal distinct spatiotemporal characteristics and complementary patterns in the distribution of meio- and micro-eukaryotes. The three communities showed similar biogeographic patterns and assembly processes. Notably, the diversity of these three taxa gradually decreased along the river. Their communities were less shaped by stochastic processes, which gradually decreased along the longitudinal riverine-transition-lacustrine gradient. Hence, deterministic factors, such as seasonality, environmental, and spatial variables, along with species interactions, likely play a pivotal role in shaping these communities. Environmental factors primarily drive seasonal variations in these communities, while hydrological conditions, represented as spatial distance, predominantly influence spatial variations. These three communities followed the distance-decay pattern. In winter, compared to summer, both the decay and species interrelationships are more pronounced. Taken together, this study offers fresh insights into the composition and diversity patterns of meio- and micro-eukaryotes at the spatial-temporal level. It also uncovers the mechanisms behind community assembly in various environmental niches within the dam-induced river-reservoir systems. KEY POINTS: • Distribution and diversity of meio- and micro-eukaryotes exhibit distinct spatiotemporal patterns in the TGR. • Contribution of stochastic processes in community assembly gradually decreases along the river. • Deterministic factors and species interactions shape meio- and micro-eukaryotic community.

Supervised machine learning improves general applicability of eDNA metabarcoding for reservoir health monitoring.

Effective and standardized monitoring methodologies are vital for successful reservoir restoration and management. Environmental DNA (eDNA) metabarcoding sequencing offers a promising alternative for biomonitoring and can overcome many limitations of traditional morphological bioassessment. Recent attempts have even shown that supervised machine learning (SML) can directly infer biotic indices (BI) from eDNA metabarcoding data, bypassing the cumbersome calculation process of BI regardless of the taxonomic assignment of eDNA sequences. However, questions surrounding the general applicability of this taxonomy-free approach to monitoring reservoir health remain unclear, including model stability, feature selection, algorithm choice, and multi-season biomonitoring. Here, we firstly developed a novel biological integrity index (Me-IBI) that integrates multitrophic interactions and environmental information, based on taxonomy-assigned eDNA metabarcoding data. The Me-IBI can better distinguish the actual health status of the Three Gorges Reservoir (TGR) than physicochemical assessments and have a clear response to human activity. Then, taking this reliable Me-IBI as a supervised label, we compared the impact of selecting different numbers of features and SML algorithms on the stability and predictive performance of the model for predicting ecological conditions in multiple seasons using taxonomy-free eDNA metabarcoding data. We discovered that even with a small number of features, different SML algorithms can establish a stable model and obtain excellent predictive performance. Finally, we proposed a four-step strategy for standardized routine biomonitoring using SML tools. Our study firstly explores the general applicability problem of the taxonomy-free eDNA-SML approach and establishes a solid foundation for the large-scale and standardized biomonitoring application.

Probiotics mitigate kidney damage after exposure to Sri Lanka's local groundwater from chronic kidney disease with uncertain etiology (CKDu) prevalent area in zebrafish.

Groundwater in Sri Lanka, contaminated with environmental toxins, is suspected to potentially induce chronic kidney disease of uncertain etiology (CKDu) in humans. This study aims to elucidate the potential mitigating effects of probiotics on kidney damage induced by exposure to this local groundwater (LW) in zebrafish. We used zebrafish as a model organism and exposed them to local groundwater to evaluate the risk of CKDu. Probiotics were then added at a concentration of 108 colony-forming units per milliliter (CFU/mL). Our findings revealed that exposure to local groundwater resulted in abnormalities, such as tail deletion and spinal curvature in zebrafish larvae. However, the addition of probiotics mitigated these effects, improving the hatching rate, heart rate, length, weight, deformity rate, survival rate, and abnormal behavior of zebrafish. It also positively influenced the differential expression levels of kidney development and immunity-related genes (dync2h1, foxj1, pkd2, gata3, slc20a1, il1ß, and lyso). Furthermore, exposure to LW decreased both the diversity and abundance of microbiota in zebrafish larvae. However, treatment with probiotics, such as L. plantarum and L. rhamnosus partially restored the disrupted gut microbiota and significantly impacted the cellular process pathways of the microbial community, as determined by KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis. In conclusion, this study highlights the risks associated with Sri Lanka's local groundwater from a CKDu prevalent area and confirms the beneficial effects of different probiotics. These findings may provide new insights into bacterial function in host kidney health.

Ultra-sensitive detection of ecologically rare fish from eDNA samples based on the RPA-CRISPR/Cas12a technology.

Environmental DNA (eDNA) research holds great promise for improving biodiversity science and conservation efforts by enabling worldwide species censuses in near real-time. Current eDNA methods face challenges in detecting low-abundance ecologically important species. In this study, we used isothermal recombinase polymerase amplification (RPA)-CRISPR/Cas detection to test Ctenopharyngodon idella. RPA-CRISPR-Cas12a detected 6.0 eDNA copies/µL within 35 min. Ecologically rare species were identified in the Three Gorges Reservoir Area (TGRA) using functional distinctiveness and geographical restrictiveness, with seven fish species (9%) classified as potentially ecologically rare including three species in this investigation. RPA-CRISPR/Cas12a-FQ outperformed high-throughput sequencing (HTS) and qPCR in detecting low-abundance eDNA (AUC = 0.883∗∗). A significant linear correlation (R2 = 0.682∗∗) between RPA-CRISPR/Cas12a-FQ and HTS quantification suggests its potential for predicting species abundance and enhancing eDNA-based fish biodiversity monitoring. This study highlights the value of RPA-CRISPR/Cas12a-FQ as a tool for advancing eDNA research and conservation efforts.

Engineering bacteriophages for enhanced host range and efficacy: insights from bacteriophage-bacteria interactions.

Bacteriophages, the most abundant organisms on earth, have the potential to address the rise of multidrug-resistant bacteria resulting from the overuse of antibiotics. However, their high specificity and limited host range can hinder their effectiveness. Phage engineering, through the use of gene editing techniques, offers a means to enhance the host range of bacteria, improve phage efficacy, and facilitate efficient cell-free production of phage drugs. To engineer phages effectively, it is necessary to understand the interaction between phages and host bacteria. Understanding the interaction between the receptor recognition protein of bacteriophages and host receptors can serve as a valuable guide for modifying or replacing these proteins, thereby altering the receptor range of the bacteriophage. Research and development focused on the CRISPR-Cas bacterial immune system against bacteriophage nucleic acids can provide the necessary tools to promote recombination and counter-selection in engineered bacteriophage programs. Additionally, studying the transcription and assembly functions of bacteriophages in host bacteria can facilitate the engineered assembly of bacteriophage genomes in non-host environments. This review highlights a comprehensive summary of phage engineering methods, including in-host and out-of-host engineering, and the use of high-throughput methods to understand their role. The main aim of these techniques is to harness the intricate interactions between bacteriophages and hosts to inform and guide the engineering of bacteriophages, particularly in the context of studying and manipulating the host range of bacteriophages. By employing advanced high-throughput methods to identify specific bacteriophage receptor recognition genes, and subsequently introducing modifications or performing gene swapping through in-host recombination or out-of-host synthesis, it becomes possible to strategically alter the host range of bacteriophages. This capability holds immense significance for leveraging bacteriophages as a promising therapeutic approach against antibiotic-resistant bacteria.