Comparing Transcriptomic Points of Departure to Apical Effect Concentrations For Larval Fathead Minnow Exposed to Chemicals with Four Different Modes Of Action.

It is postulated that below a transcriptomic-based point of departure, adverse effects are unlikely to occur, thereby providing a chemical concentration to use in screening level hazard assessment. The present study extends previous work describing a high-throughput fathead minnow assay that can provide full transcriptomic data after exposure to a test chemical. One-day post-hatch fathead minnows were exposed to ten concentrations of three representatives of four chemical modes of action: organophosphates, ecdysone receptor agonists, plant photosystem II inhibitors, and estrogen receptor agonists for 24 h. Concentration response modeling was performed on whole body gene expression data from each exposure, using measured chemical concentrations when available. Transcriptomic points of departure in larval fathead minnow were lower than apical effect concentrations across fish species but not always lower than toxic effect concentrations in other aquatic taxa like crustaceans and insects. The point of departure was highly dependent on measured chemical concentration which were often lower than the nominal concentration. Differentially expressed genes between chemicals within modes of action were compared and often showed statistically significant overlap. In addition, reproducibility between identical exposures using a positive control chemical (CuSO4) and variability associated with the transcriptomic point of departure using in silico sampling were considered. Results extend a transcriptomic-compatible fathead minnow high-throughput assay for possible use in ecological hazard screening.

Pilot testing and optimization of a larval fathead minnow high throughput transcriptomics assay.

Concentrations at which global gene expression profiles in cells or animals exposed to a test substance start to differ significantly from those of controls have been proposed as an alternative point of departure for use in screening level hazard assessment. The present study describes pilot testing of a high throughput compatible transcriptomics assay with larval fathead minnows. One day post hatch fathead minnows were exposed to eleven different concentrations of three metals, three selective serotonin reuptake inhibitors, and four neonicotinoid-like compounds for 24 h and concentration response modeling was applied to whole body gene expression data. Transcriptomics-based points of departure (tPODs) were consistently lower than effect concentrations reported in apical endpoint studies in fish. However, larval fathead minnow-based tPODs were not always lower than concentrations reported to elicit apical toxicity in other aquatic organisms like crustaceans or insects. Random in silico subsampling of data from the pilot assays was used to evaluate various assay design and acceptance considerations such as transcriptome coverage, number of replicate individuals to sequence per treatment, and minimum number of differentially expressed genes to produce a reliable tPOD estimate. Results showed a strong association between the total number of genes for which a concentration response relationship could be derived and the overall variability in the resulting tPOD estimates. We conclude that, for our current assay design and analysis pipeline, tPODs based on fewer than 15 differentially expressed genes are likely to be unreliable for screening and that interindividual variability in gene expression profiles appears to be a more significant driver of tPOD variability than sample size alone. Results represent initial steps toward developing high throughput transcriptomics assays for use in ecological hazard screening.

Developing Indicators of Nutrient Pollution in Streams Using 16S rRNA Gene Metabarcoding of Periphyton-Associated Bacteria.

Indicators based on nutrient-biota relationships in streams can inform water quality restoration and protection programs. Bacterial assemblages could be particularly useful indicators of nutrient effects because they are species-rich, important contributors to ecosystem processes in streams, and responsive to rapidly changing conditions. Here, we sampled 25 streams weekly (12-14 times each) and used 16S rRNA gene metabarcoding of periphyton-associated bacteria to quantify the effects of total phosphorus (TP) and total nitrogen (TN). Threshold indicator taxa analysis identified assemblage-level changes and amplicon sequence variants (ASVs) that increased or decreased with increasing TP and TN concentrations (i.e., low P, high P, low N, and high N ASVs). Boosted regression trees confirmed that relative abundances of gene sequence reads for these four indicator groups were associated with nutrient concentrations. Gradient forest analysis complemented these results by using multiple predictors and random forest models for each ASV to identify portions of TP and TN gradients at which the greatest changes in assemblage structure occurred. Synthesized statistical results showed bacterial assemblage structure began changing at 24 µg TP/L with the greatest changes occurring from 110 to 195 µg/L. Changes in the bacterial assemblages associated with TN gradually occurred from 275 to 855 µg/L. Taxonomic and phylogenetic analyses showed that low nutrient ASVs were commonly Firmicutes, Verrucomicrobiota, Flavobacteriales, and Caulobacterales, Pseudomonadales, and Rhodobacterales of Proteobacteria, whereas other groups, such as Chitinophagales of Bacteroidota, and Burkholderiales, Rhizobiales, Sphingomonadales, and Steroidobacterales of Proteobacteria comprised the high nutrient ASVs. Overall, the responses of bacterial ASV indicators in this study highlight the utility of metabarcoding periphyton-associated bacteria for quantifying biotic responses to nutrient inputs in streams.

De Novo Assembly of the Nearly Complete Fathead Minnow Reference Genome Reveals a Repetitive but Compact Genome.

The fathead minnow is a widely used model organism in environmental toxicology. The lack of a high-quality fathead minnow reference genome, however, has severely hampered its uses in toxicogenomics. We present the de novo assembly and annotation of the fathead minnow genome using long PacBio reads, Bionano and Hi-C scaffolding data, and large RNA-sequencing data sets from different tissues and life stages. The new annotated fathead minnow reference genome has a scaffold N50 of 12.0 Mbp and a complete benchmarking universal single-copy orthologs score of 95.1%. The completeness of annotation for the new reference genome is comparable to that of the zebrafish GRCz11 reference genome. The fathead minnow genome, revealed to be highly repetitive and sharing extensive syntenic regions with the zebrafish genome, has a much more compact gene structure than the zebrafish genome. Particularly, comparative genomic analysis with zebrafish, mouse, and human showed that fathead minnow homologous genes are relatively conserved in exon regions but had strikingly shorter intron regions. The new fathead minnow reference genome and annotation data, publicly available from the National Center for Biotechnology Information and the University of California Santa Cruz genome browser, provides an essential resource for aquatic toxicogenomic studies in ecotoxicology and public health. Environ Toxicol Chem 2022;41:448-461. Published 2021. This article is a U.S. Government work and is in the public domain in the USA.

Evaluating the performance of DNA metabarcoding for assessment of zooplankton communities in Western Lake Superior using multiple markers.

For DNA metabarcoding to attain its potential as a community assessment tool, we need to better understand its performance versus traditional morphological identification and work to address any remaining performance gaps in incorporating DNA metabarcoding into community assessments. Using fragments of the 18S nuclear and 16S mitochondrial rRNA genes and two fragments of the mitochondrial COI marker, we examined the use of DNA metabarcoding and traditional morphological identification for understanding the diversity and composition of crustacean zooplankton at 42 sites across western Lake Superior. We identified 51 zooplankton taxa (genus or species, depending on the finest resolution of the taxon across all identification methods), of which 17 were identified using only morphological traits, 13 using only DNA and 21 using both methods. The taxa found using only DNA metabarcoding included four species and one genus-level identification not previously known to occur in Lake Superior, the presence of which still needs to be confirmed. A substantial portion of taxa that were identified to genus or species by morphological identification, but not identified using DNA metabarcoding, had zero ("no record") or ≤ 2 ("underrepresented records") reference barcodes in the BOLD or NCBI databases (63% for COI, 80% for 16S, 74% for 18S). The two COI marker fragments identified the most genus- and species-level taxa, whereas 18S was the only marker whose family-level percent sequence abundance patterns showed high correlation to composition patterns from morphological identification, based on a NMDS analysis of Bray-Curtis similarities. Multiple replicates were collected at a subset of sites and an occupancy analysis was performed, which indicated that rare taxa were more likely to be detected using DNA metabarcoding than traditional morphology. Our results support that DNA metabarcoding can augment morphological identification for estimating zooplankton diversity and composition of zooplankton over space and time, but may require use of multiple markers. Further addition of taxa to reference DNA databases will improve our ability to use DNA metabarcoding to identify zooplankton and other invertebrates in aquatic surveys.

Development of omics biomarkers for estrogen exposure using mRNA, miRNA and piRNAs.

The number of chemicals requiring risk evaluation exceeds our capacity to provide the underlying data using traditional methodology. This has led to an increased focus on the development of novel approach methodologies. This work aimed to expand the panel of gene expression-based biomarkers to include responses to estrogens, to identify training strategies that maximize the range of applicable concentrations, and to evaluate the potential for two classes of small non-coding RNAs (sncRNAs), microRNA (miRNA) and piwi-interacting RNA (piRNA), as biomarkers. To this end larval Pimephales promelas (96 hpf +/- 1h) were exposed to 5 concentrations of 17α- ethinylestradiol (0.12, 1.25, 2.5, 5.0, 10.0 ng/L) for 48 h. For mRNA-based biomarker development, RNA-seq was conducted across all concentrations. For sncRNA biomarkers, small RNA libraries were prepared only for the control and 10.0 ng/L EE2 treatment. In order to develop an mRNA classifier that remained accurate over the range of exposure concentrations, three different training strategies were employed that focused on 10 ng/L, 2.5 ng/L or a combination of both. Classifiers were tested against an independent test set of individuals exposed to the same concentrations used in training and subsequently against concentrations not included in model training. Both random forest (RF) and logistic regression with elastic net regularizations (glmnet) models trained on 10 ng/L EE2 performed poorly when applied to lower concentrations. RF models trained with either the 2.5 ng/L or combination (2.5 + 10 ng/L) treatments were able to accurately discriminate exposed vs. non-exposed across all but the lowest concentrations. glmnet models were unable to accurately classify below 5 ng/L. With the exception of the 10 ng/L treatment, few mRNA differentially expressed genes (DEG) were observed, however, there was marked overlap of DEGs across treatments. Overlapping DEGs have well established linkages to estrogen and several of the 81 DEGs identified in the 10 ng/L treatment have been previously utilized as estrogenic biomarkers (vitellogenin, estrogen receptor-ß). Following multiple test correction, no sncRNAs were found to be differentially expressed, however, both miRNA and piRNA classifiers were able to accurately discriminate control and 10 ng/L exposed organisms with AUCs of 0.83 and 1.0 respectively. We have developed a highly discriminative estrogenic mRNA biomarker that is accurate over a range of concentrations likely to be found in real-world exposures. We have demonstrated that both miRNA and piRNA are responsive to estrogenic exposure, suggesting the need to further investigate their regulatory roles in the estrogenic response.

Comparison of Larval Fish Detections Using Morphology-Based Taxonomy versus High-Throughput Sequencing for Invasive Species Early Detection.

When first introduced, invasive species typically evade detection; DNA barcoding coupled with high-throughput sequencing (HTS) may be more sensitive and accurate than morphology-based taxonomy, and thereby improve invasive (or rare) species detection. We quantified the relative error of species detection between morphology-based and HTS-based taxonomic identification of ichthyoplankton collections from the Port of Duluth, Minnesota, an aquatic non-native species introduction 'hot-spot' in the Laurentian Great Lakes. We found HTS-based taxonomy identified 28 species and morphology-based taxonomy 30 species, of which 27 were common to both. Among samples, 76% of family-level taxonomic assignments agreed; however, only 42% of species assignments agreed. Most errors were attributed to morphology-based taxonomy, whereas HTS-based taxonomy error was low. For this study system, for most non-native fishes, the detection probability by randomized survey for larvae was similar to that by a survey that is optimized for non-native species early detection of juveniles and adults. We conclude that classifying taxonomic errors by comparing HTS results against morphology-based taxonomy is an important step toward incorporating HTS-based taxonomy into biodiversity surveys.

Metabarcoding quantifies differences in accumulation of ballast water borne biodiversity among three port systems in the United States.

Characterizing biodiversity conveyed in ships' ballast water (BW), a global driver of biological invasions, is critically important for understanding risks posed by this key vector and establishing baselines to evaluate changes associated with BW management. Here we employ high throughput sequence (HTS) metabarcoding of the 18S small subunit rRNA to test for and quantify differences in the accumulation of BW-borne biodiversity among three distinct recipient port systems in the United States. These systems were located on three different coasts (Pacific, Gulf, and Atlantic) and chosen to reflect distinct trade patterns and source port biogeography. Extensive sampling of BW tanks (n = 116) allowed detailed exploration of molecular diversity accumulation. Our results indicate that saturation of introduced zooplankton diversity may be achieved quickly, with fewer than 25 tanks needed to achieve 95% of the total extrapolated diversity, if source biogeography is relatively limited. However, as predicted, port systems with much broader source geographies require more extensive sampling to estimate diversity, which continues to accumulate after sampling >100 discharges. The ability to identify BW sources using molecular indicators was also found to depend on the breadth of source biogeography and the extent to which sources had been sampled. These findings have implications both for the effort required to fully understand introduced diversity and for projecting risks associated with future changes to maritime traffic that may increase source biogeography for many recipient ports. Our data also suggest that molecular diversity may not decline significantly with BW age, indicating either that some organisms survive longer than recognized in previous studies or that nucleic acids from dead organisms persist in BW tanks. We present evidence for detection of potentially invasive species in arriving BW but discuss important caveats that preclude strong inferences regarding the presence of living representatives of these species in BW tanks.

Ballast Water Exchange and Invasion Risk Posed by Intracoastal Vessel Traffic: An Evaluation Using High Throughput Sequencing.

Ballast water remains a potent vector of non-native aquatic species introductions, despite increased global efforts to reduce risk of ballast water mediated invasions. This is particularly true of intracoastal vessel traffic, whose characteristics may limit the feasibility and efficacy of management through ballast water exchange (BWE). Here we utilize high throughput sequencing (HTS) to assess biological communities associated with ballast water being delivered to Valdez, Alaska from multiple source ports along the Pacific Coast of the United States. Our analyses indicate that BWE has a significant but modest effect on ballast water assemblages. Although overall richness was not reduced with exchange, we detected losses of some common benthic coastal taxa (e.g., decapods, mollusks, bryozoans, cnidaria) and gains of open ocean taxa (e.g., certain copepods, diatoms, and dinoflagellates), including some potentially toxic species. HTS-based metabarcoding identified significantly differentiated biodiversity signatures from individual source ports; this signal persisted, though weakened, in vessels undergoing BWE, indicating incomplete faunal turnover associated with management. Our analysis also enabled identification of taxa that may be of particular concern if established in Alaskan waters. While these results reveal a clear effect of BWE on diversity in intracoastal transit, they also indicate continued introduction risk of non-native and harmful taxa.

Sensitivity and accuracy of high-throughput metabarcoding methods for early detection of invasive fish species.

High-throughput DNA metabarcoding has gained recognition as a potentially powerful tool for biomonitoring, including early detection of aquatic invasive species (AIS). DNA based techniques are advancing, but our understanding of the limits to detection for metabarcoding complex samples is inadequate. For detecting AIS at an early stage of invasion when the species is rare, accuracy at low detection limits is key. To evaluate the utility of metabarcoding in future fish community monitoring programs, we conducted several experiments to determine the sensitivity and accuracy of routine metabarcoding methods. Experimental mixes used larval fish tissue from multiple "common" species spiked with varying proportions of tissue from an additional "rare" species. Pyrosequencing of genetic marker, COI (cytochrome c oxidase subunit I) and subsequent sequence data analysis provided experimental evidence of low-level detection of the target "rare" species at biomass percentages as low as 0.02% of total sample biomass. Limits to detection varied interspecifically and were susceptible to amplification bias. Moreover, results showed some data processing methods can skew sequence-based biodiversity measurements from corresponding relative biomass abundances and increase false absences. We suggest caution in interpreting presence/absence and relative abundance in larval fish assemblages until metabarcoding methods are optimized for accuracy and precision.

Genetic basis for rapidly evolved tolerance in the wild: adaptation to toxic pollutants by an estuarine fish species.

Atlantic killifish (Fundulus heteroclitus) residing in some urban and industrialized estuaries of the US eastern seaboard demonstrate recently evolved and extreme tolerance to toxic aryl hydrocarbon pollutants, characterized as dioxin-like compounds (DLCs). Here, we provide an unusually comprehensive accounting (69%) through quantitative trait locus (QTL) analysis of the genetic basis for DLC tolerance in killifish inhabiting an urban estuary contaminated with PCB congeners, the most toxic of which are DLCs. Consistent with mechanistic knowledge of DLC toxicity in fish and other vertebrates, the aryl hydrocarbon receptor (ahr2) region accounts for 17% of trait variation; however, QTL on independent linkage groups and their interactions have even greater explanatory power (44%). QTL interpreted within the context of recently available Fundulus genomic resources and shared synteny among fish species suggest adaptation via interacting components of a complex stress response network. Some QTL were also enriched in other killifish populations characterized as DLC-tolerant and residing in distant urban estuaries contaminated with unique mixtures of pollutants. Together, our results suggest that DLC tolerance in killifish represents an emerging example of parallel contemporary evolution that has been driven by intense human-mediated selection on natural populations.

Comparing predicted estrogen concentrations with measurements in US waters.

The range of exposure rates to the steroidal estrogens estrone (E1), beta-estradiol (E2), estriol (E3), and ethinyl estradiol (EE2) in the aquatic environment was investigated by modeling estrogen introduction via municipal wastewater from sewage plants across the US. Model predictions were compared to published measured concentrations. Predictions were congruent with most of the measurements, but a few measurements of E2 and EE2 exceed those that would be expected from the model, despite very conservative model assumptions of no degradation or in-stream dilution. Although some extreme measurements for EE2 may reflect analytical artifacts, remaining data suggest concentrations of E2 and EE2 may reach twice the 99th percentile predicted from the model. The model and bulk of the measurement data both suggest that cumulative exposure rates to humans are consistently low relative to effect levels, but also suggest that fish exposures to E1, E2, and EE2 sometimes substantially exceed chronic no-effect levels.

Comparative fecal metagenomics unveils unique functional capacity of the swine gut.

BACKGROUND: Uncovering the taxonomic composition and functional capacity within the swine gut microbial consortia is of great importance to animal physiology and health as well as to food and water safety due to the presence of human pathogens in pig feces. Nonetheless, limited information on the functional diversity of the swine gut microbiome is available. RESULTS: Analysis of 637, 722 pyrosequencing reads (130 megabases) generated from Yorkshire pig fecal DNA extracts was performed to help better understand the microbial diversity and largely unknown functional capacity of the swine gut microbiome. Swine fecal metagenomic sequences were annotated using both MG-RAST and JGI IMG/M-ER pipelines. Taxonomic analysis of metagenomic reads indicated that swine fecal microbiomes were dominated by Firmicutes and Bacteroidetes phyla. At a finer phylogenetic resolution, Prevotella spp. dominated the swine fecal metagenome, while some genes associated with Treponema and Anareovibrio species were found to be exclusively within the pig fecal metagenomic sequences analyzed. Functional analysis revealed that carbohydrate metabolism was the most abundant SEED subsystem, representing 13% of the swine metagenome. Genes associated with stress, virulence, cell wall and cell capsule were also abundant. Virulence factors associated with antibiotic resistance genes with highest sequence homology to genes in Bacteroidetes, Clostridia, and Methanosarcina were numerous within the gene families unique to the swine fecal metagenomes. Other abundant proteins unique to the distal swine gut shared high sequence homology to putative carbohydrate membrane transporters. CONCLUSIONS: The results from this metagenomic survey demonstrated the presence of genes associated with resistance to antibiotics and carbohydrate metabolism suggesting that the swine gut microbiome may be shaped by husbandry practices.

Expression profiles during dedifferentiation in newt lens regeneration revealed by expressed sequence tags.

PURPOSE: The adult newt can regenerate lens from pigmented epithelial cells (PECs) of the dorsal iris via dedifferentiation. The purpose of this research is to obtain sequence resources for a newt lens regeneration study and to obtain insights of dedifferentiation at the molecular level. METHODS: mRNA was purified from iris during dedifferentiation and its cDNA library was constructed. From the cDNA library 10,449 clones were sequenced and analyzed. RESULTS: From 10,449 reads, 780 contigs and 1,666 singlets were annotated. The presence of several cancer- and apoptosis-related genes during newt dedifferentiation was revealed. Moreover, several candidate genes, which might participate in reprogramming during dedifferentiation, were also found. CONCLUSIONS: The expression of cancer- and apoptosis-related genes could be hallmarks during dedifferentiation. The expression sequence tag (EST) resource is useful for the future study of newt dedifferentiation, and the sequence information is available in GenBank (accession numbers; FS290155-FS300559).