26 research outputs found

    Connecting gut microbiome changes with fish health conditions in juvenile Atlantic cod (Gadus morhua) exposed to dispersed crude oil

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    Polycyclic aromatic hydrocarbons found in crude oil can impair fish health following sublethal exposure. However, the dysbiosis of microbial communities within the fish host and influence it has on the toxic response of fish following exposure has been less characterized, particularly in marine species. To better understand the effect of dispersed crude oil (DCO) on juvenile Atlantic cod (Gadus morhua) microbiota composition and potential targets of exposure within the gut, fish were exposed to 0.05 ppm DCO for 1, 3, 7, or 28 days and 16 S metagenomic and metatranscriptomic sequencing on the gut and RNA sequencing on intestinal content were conducted. In addition to assessing species composition, richness, and diversity from microbial gut community analysis and transcriptomic profiling, the functional capacity of the microbiome was determined. Mycoplasma and Aliivibrio were the two most abundant genera after DCO exposure and Photobacterium the most abundant genus in controls, after 28 days. Metagenomic profiles were only significantly different between treatments after a 28-day exposure. The top identified pathways were involved in energy and the biosynthesis of carbohydrates, fatty acids, amino acids, and cellular structure. Biological processes following fish transcriptomic profiling shared common pathways with microbial functional annotations such as energy, translation, amide biosynthetic process, and proteolysis. There were 58 differently expressed genes determined from metatranscriptomic profiling after 7 days of exposure. Predicted pathways that were altered included those involved in translation, signal transduction, and Wnt signaling. EIF2 signaling was consistently dysregulated following exposure to DCO, regardless of exposure duration, with impairments in IL-22 signaling and spermine and spermidine biosynthesis in fish after 28 days. Data were consistent with predictions of a potentially reduced immune response related to gastrointestinal disease. Herein, transcriptomic-level responses helped explain the relevance of differences in gut microbial communities in fish following DCO exposure.publishedVersio

    Evaluation of Microbiome-Host Relationships in the Zebrafish Gastrointestinal System Reveals Adaptive Immunity Is a Target of Bis(2-ethylhexyl) Phthalate (DEHP) Exposure

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    To improve physical characteristics of plastics such as flexibility and durability, producers enrich materials with phthalates such as di-2-(ethylhexyl) phthalate (DEHP). DEHP is a high production volume chemical associated with metabolic and immune disruption in animals and humans. To reveal mechanisms implicated in phthalate-related disruption in the gastrointestinal system, male and female zebrafish were fed DEHP (3 ppm) daily for two months. At the transcriptome level, DEHP significantly upregulated gene networks in the intestine associated with helper T cells' (Th1, Th2, and Th17) specific pathways. The activation of gene networks associated with adaptive immunity was linked to the suppression of networks for tight junction, gap junctional intercellular communication, and transmembrane transporters, all of which are precursors for impaired gut integrity and performance. On a class level, DEHP exposure increased Bacteroidia and Gammaproteobacteria and decreased Verrucomicrobiae in both the male and female gastrointestinal system. Further, in males there was a relative increase in Fusobacteriia and Betaproteobacteria and a relative decrease in Saccharibacteria. Predictive algorithms revealed that the functional shift in the microbiome community, and the metabolites they produce, act to modulate intestinal adaptive immunity. This finding suggests that the gut microbiota may contribute to the adverse effects of DEHP on the host by altering metabolites sensed by both intestinal and immune Th cells. Our results suggest that the microbiome-gut-immune axis can be modified by DEHP and emphasize the value of multiomics approaches to study microbiome-host interactions following chemical perturbations

    Tissue-Based Mapping of the Fathead Minnow (Pimephales promelas) Transcriptome and Proteome

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    Omics approaches are broadly used to explore endocrine and toxicity-related pathways and functions. Nevertheless, there is still a significant gap in knowledge in terms of understanding the endocrine system and its numerous connections and intricate feedback loops, especially in non-model organisms. The fathead minnow (Pimephales promelas) is a widely used small fish model for aquatic toxicology and regulatory testing, particularly in North America. A draft genome has been published, but the amount of available genomic or transcriptomic information is still far behind that of other more broadly studied species, such as the zebrafish. Here, we used a proteogenomics approach to survey the tissue-specific proteome and transcriptome profiles in adult male fathead minnow. To do so, we generated a draft transcriptome using short and long sequencing reads from liver, testis, brain, heart, gill, head kidney, trunk kidney, and gastrointestinal tract. We identified 30,378 different putative transcripts overall, with the assembled contigs ranging in size from 264 to over 9,720 nts. Over 17,000 transcripts were >1,000 nts, suggesting a robust transcriptome that can be used to interpret RNA sequencing data in the future. We also performed RNA sequencing and proteomics analysis on four tissues, including the telencephalon, hypothalamus, liver, and gastrointestinal tract of male fish. Transcripts ranged from 0 to 600,000 copies per gene and a large portion were expressed in a tissue-specific manner. Specifically, the telencephalon and hypothalamus shared the most expressed genes, while the gastrointestinal tract and the liver were quite distinct. Using protein profiling techniques, we identified a total of 4,045 proteins in the four tissues investigated, and their tissue-specific expression pattern correlated with the transcripts at the pathway level. Similarly to the findings with the transcriptomic data, the hypothalamus and telencephalon had the highest degree of similarity in the proteins detected. The main purpose of this analysis was to generate tissue-specific omics data in order to support future aquatic ecotoxicogenomic and endocrine-related studies as well as to improve our understanding of the fathead minnow as an ecological model

    A multistate assessment of population normalization factors for wastewater-based epidemiology of COVID-19.

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    Wastewater-based epidemiology (WBE) has become a valuable tool for monitoring SARS-CoV-2 infection trends throughout the COVID-19 pandemic. Population biomarkers that measure the relative human fecal contribution to normalize SARS-CoV-2 wastewater concentrations are needed for improved analysis and interpretation of community infection trends. The Centers for Disease Control and Prevention National Wastewater Surveillance System (CDC NWSS) recommends using the wastewater flow rate or human fecal indicators as population normalization factors. However, there is no consensus on which normalization factor performs best. In this study, we provided the first multistate assessment of the effects of flow rate and human fecal indicators (crAssphage, F+ Coliphage, and PMMoV) on the correlation of SARS-CoV-2 wastewater concentrations and COVID-19 cases using the CDC NWSS dataset of 182 communities across six U.S. states. Flow normalized SARS-CoV-2 wastewater concentrations produced the strongest correlation with COVID-19 cases. The correlation from the three human fecal indicators were significantly lower than flow rate. Additionally, using reverse transcription droplet digital polymerase chain reaction (RT-ddPCR) significantly improved correlation values over samples that were analyzed with real-time reverse transcription quantitative polymerase chain reaction (rRT-qPCR). Our assessment shows that utilizing flow normalization with RT-ddPCR generate the strongest correlation between SARS-CoV-2 wastewater concentrations and COVID-19 cases

    Transcriptomic Analysis of the Differential Nephrotoxicity of Diverse Brominated Flame Retardants in Rat and Human Renal Cells

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    Brominated flame retardants (BFRs) are environmentally persistent, are detected in humans, and some have been banned due to their potential toxicity. BFRs are developmental neurotoxicants and endocrine disruptors; however, few studies have explored their potential nephrotoxicity. We addressed this gap in the literature by determining the toxicity of three different BFRs (tetrabromobisphenol A (TBBPA), hexabromocyclododecane (HBCD), and tetrabromodiphenyl ether (BDE-47)) in rat (NRK 52E) and human (HK-2 and RPTEC) tubular epithelial cells. All compounds induced time- and concentration-dependent toxicity based on decreases in MTT staining and changes in cell and nuclear morphology. The toxicity of BFRs was chemical- and cell-dependent, and human cells were more susceptible to all three BFRs based on IC50s after 48 h exposure. BFRs also had chemical- and cell-dependent effects on apoptosis as measured by increases in annexin V and PI staining. The molecular mechanisms mediating this toxicity were investigated using RNA sequencing. Principal components analysis supported the hypothesis that BFRs induce different transcriptional changes in rat and human cells. Furthermore, BFRs only shared nine differentially expressed genes in rat cells and five in human cells. Gene set enrichment analysis demonstrated chemical- and cell-dependent effects; however, some commonalities were also observed. Namely, gene sets associated with extracellular matrix turnover, the coagulation cascade, and the SNS-related adrenal cortex response were enriched across all cell lines and BFR treatments. Taken together, these data support the hypothesis that BFRs induce differential toxicity in rat and human renal cell lines that is mediated by differential changes in gene expression

    Dynamism of Stimuli-Responsive Nanohybrids: Environmental Implications

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    Nanomaterial science and design have shifted from generating single passive nanoparticles to more complex and adaptive multi-component nanohybrids. These adaptive nanohybrids (ANHs) are designed to simultaneously perform multiple functions, while actively responding to the surrounding environment. ANHs are engineered for use as drug delivery carriers, in tissue-engineered templates and scaffolds, adaptive clothing, smart surface coatings, electrical switches and in platforms for diversified functional applications. Such ANHs are composed of carbonaceous, metallic or polymeric materials with stimuli-responsive soft-layer coatings that enable them to perform such switchable functions. Since ANHs are engineered to dynamically transform under different exposure environments, evaluating their environmental behavior will likely require new approaches. Literature on polymer science has established a knowledge core on stimuli-responsive materials. However, translation of such knowledge to environmental health and safety (EHS) of these ANHs has not yet been realized. It is critical to investigate and categorize the potential hazards of ANHs, because exposure in an unintended or shifting environment could present uncertainty in EHS. This article presents a perspective on EHS evaluation of ANHs, proposes a principle to facilitate their identification for environmental evaluation, outlines a stimuli-based classification for ANHs and discusses emerging properties and dynamic aspects for systematic EHS evaluation

    Correlation coefficients of the SARS-CoV-2 wastewater concentrations and the sewershed-level COVID-19 cases for each study site.

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    This range includes the correlation coefficient using each of the four normalization categories used in the analysis.</p

    Spearman correlation coefficient analysis of the fecal indicator raw wastewater concentration (Log10GC/L), fecal indicator flow normalized wastewater concentration (Log10GC/Day), and flow rate (L/Day) with the estimated population served across each study site.

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    Spearman correlation coefficient analysis of the fecal indicator raw wastewater concentration (Log10GC/L), fecal indicator flow normalized wastewater concentration (Log10GC/Day), and flow rate (L/Day) with the estimated population served across each study site.</p
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