Responses of juvenile fathead minnow (Pimephales promelas) gut microbiota to a chronic dietary exposure of benzo[a]pyrene

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Tracking ID under eDNA project: UofS-eDNA-dataset-metadata-3

These data are collected from juvenile fathead minnows (Pimephales promelas) that were exposed to benzo[a]pyrene (BaP) as well as fish exposed to a solvent control for two weeks via the diet. The samples were sterilely collected from whole fathead minnow guts and stored at -80?C until DNA and RNA extraction. The guts were used for 16S rRNA sequencing to analyze the impact of BaP on gut microbial communities. Each fish was analyzed independently (samples were not pooled). The results of this study showed a significant effect of BaP exposure on gut microbial community.

The gut microbiota of animals has been described as an additional host ?organ' with beneficial roles. However, little is known about the impact of chemical exposures on the structure and function of gut microbiota of fishes. The purpose of this project was to assess the implications of dietary exposure of benzo[a]pyrene (BaP) on the gut microbial communities of juvenile fathead minnows (Pimephales promelas).

This study sought to determine the effects of an aqueous BaP exposure on fathead minnow gut microbial communities. Benzo[a]pyrene is used as a model compound to simulate the exposure that might occur following an oil spill because it is a single compound, and therefore easier to study in the laboratory. The gut microbiome is a relatively new area of research in toxicology. It is believed that several toxicant can impair the gut bacteria and result in decreased health of an organism, which is why this study wanted to look at how BaP impacts the gut bacteria.

DeBofsky, A., Xie, Y., Challis, J., Brinkmann, M., Hecker, M., Giesy, J. (2020). Responses of juvenile fathead minnow (Pimephales promelas) gut microbiota to a chronic dietary exposure of benzo[a]pyrene [Dataset]. Federated Research Data Repository. https://doi.org/10.20383/101.0247

DeBofsky, A., Xie, Y., Challis, J. K., Jain, N., Brinkmann, M., Jones, P. D., Giesy, J. (2021). Responses of juvenile fathead minnow (Pimephales promelas) gut microbiome to a chronic dietary exposure of benzo[a]pyrene. Environmental Pollution 278: 116821. https://doi.org/10.1016/j.envpol.2021.116821

University of Saskatchewan Aquatic Toxicology Research Facility (ATRF)
https://toxicology.usask.ca/atrf/facilities-and-equipment.php

1. Description of methods used for collection/generation of data:
Intestinal samples were collected from fathead minnows exposed to BaP via a dietary route. Fish were exposed to either a solvent control, 1, 10, 100, or 1000 ?g/g BaP. All samples were collected with sterile dissection tools, and samples were immediately placed on ice prior to being transferred to a -80C freezer for long-term storage.

16s amplicon sequencing
Total genomic DNA was extracted from guts using the DNeasy PowerSoil Kit (Qiagen Inc., Mississauga, ON). Concentrations were measured using a Qubit 4 Fluorometer and dsDNA HS assay kit (ThermoFisher Scientific, Waltham, MA). The V3-V4 variable region of the 16S rRNA gene was amplified using the Bact-0341 forward primer (CCTACGGGNGGCWGCAG) (Klindworth et al., 2013) and the Bact-806 reverse primer (GGACTACNVGGGTWTCTAAT) (Apprill et al., 2015). Samples were dual indexed to increase throughput of sequencing (Fadrosh et al., 2014). Samples were amplified with a 50 ?L PCR reaction including Phusion green polymerase (ThermoFisher Scientific) using a SimpliAmp thermal cycler (ThermoFisher Scientific) under the following conditions: initial denaturation at 98?C for 30s, followed by 25 cycles of 98?C for 30s, 58?C for 30s, and 72?C for 30s, with a final extension at 72?C for 10 min. PCR products were assessed for size and specificity using electrophoresis on a 1.2% w/v agarose gel and purified using the Qiagen QIAquick PCR Purification Kit (Qiagen Inc.). All purified products were quantified with the Qubit dsDNA HS assay kit and concentrations were adjusted to 1 ng/ ?L with molecular-grade water. Purified products were pooled, and libraries were constructed using the NEBNext? DNA Library Prep Master Mix Set for Illumina? (New England BioLabs Inc., Whitby, ON). Libraries were quantified prior to sequencing using the NEBNext? Library Quant Kit for Illumina?. Sequencing was performed on an Illumina? MiSeq instrument (Illumina, San Diego, CA) using a 2x300 base pair kit.

2. Methods for processing the data:
Sequences were trimmed, cleaned, and demultiplexed using a combination of Trimmomatic (Bolger et al., 2014), USEARCH v11 (Edgar 2010), and QIIME1 (Caporaso et al., 2010). Paired-end sequences were merged with DADA2 (Callahan et al., 2016) in QIIME2 (Bolyen et al., 2019) after truncating the forward read to 280 nucleotides and the reverse read to 240 nucleotides in order to ensure maximum quality and percentage of reads retained. The DADA2 package generates sequence variants (SVs) that are used to infer different bacterial species. Chimeric sequences were subsequently removed, and SVs were compared to the Silva rRNA database release 132 for taxonomic identification in QIIME2. Statistical analyses were performed in R (R Core Team, 2013).

3. Instrument- or software-specific information needed to interpret the data:
User defined. These are fastq files. They can be analyzed in QIIME2 or R.

4. Environmental/experimental conditions:
Adult fathead minnows were obtained from an in-house stock population of the Aquatic Toxicology Research Facility at University of Saskatchewan. Fish were acclimated at a density of 10 fish per 5 gallon tank in aerated, pretreated facility water held at 25 ? 1 ?C. Approximately two-thirds of the water in each tank were siphoned and renewed daily, and fish were held with a 16h-light: 8h-dark photoperiod. Fish were fed EWOS? Micro Crumble trout chow (Cargill Inc., Wayzata, MN), with solvent plus the corresponding concentration of BaP, two times daily on a maintenance food ration (5% of their average wet body mass (bm) per day).

5. Describe any quality-assurance procedures performed on the data:
Quality was visualized with fastqc. Trimmomatic was used to trim low-quality bases out of the dataset prior to demultiplexing. DADA2 then filters, denoises, and merges the paired end reads. DADA2 also removes chimeras from the data.

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https://doi.org/10.20383/101.0247