The impact of fluoxetine on the gut microbiome of Pimephales promelas

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This data is supplementary information regarding the effects of fluoxetine on the gut microbiome of Fathead Minnows when aqueously exposed to the compound. After a 28-day exposure to three different concentrations of fluoxetine; 0.01, 10 and 100 µg/L, or control (0 µg/L), fish were euthanized, and gut contents was collected. Using DNA extraction methods, PCR amplification and sequencing, bioinformatics was then performed to interpret the metagenomic data. All tests and data were collected between September 2019 and January 2021 at the University of Saskatchewan, Saskatoon, SK, Canada. This data was generated to better understand how pharmaceuticals found downstream of wastewater treatment plants may impact the gut microbiome of aquatic organisms.

The symbiotic relationship between the microbiome and the host in which it lives has only recently been recognized as an important aspect of ecotoxicology. The microbiome plays an essential role in host health, with the ability to detoxify and activate toxicants as well as crosstalk with the immune and nervous systems. With recent insights into the microbiome-gut-brain-axis, such as its ability to manipulate neurochemicals further impacting host behavior, and the ability for bacteria to synthesize and transport biogenic amines such as serotonin, it is valuable to understand how pharmaceuticals that heavily impact serotonin and its transporters may influence the microbiome and in turn, the host. Selective serotonin reuptake inhibitors (SSRIs) have received attention in ecotoxicology for the potential impacts of these pharmaceuticals on vertebrate and invertebrate behavior, reproduction, and development. However, no ecotoxicological work thus far has been conducted on identifying the effects SSRIs may have on the microbiome. At high concentrations, the SSRI fluoxetine, can impede the growth of bacteria cultured from the guts of fathead minnows, Pimephales promelas. Therefore, it is expected that bacteria will be affected in-vivo. A sub-acute exposure was performed on adult male and female P. promelas to understand if fluoxetine can impact the microbiome. A 28-day, static renewal test was performed with fluoxetine concentrations of 0.01, 1, 10, 100 µg/L. Using 16S rRNA amplicon sequencing of the V3/V4 region, bacterial communities of the intestine will be analyzed. Alpha and beta diversity will be used to explore shifts among the gut-associated microflora related to fluoxetine concentrations and PICRUSt2 will be used to determine presumptive functional annotation of the bacteria identified. This research will provide an understanding of how a prominent pharmaceutical may impact fish gut microbiota, emphasizing the importance of the microbiome as a functioning organ within the body and stressing the need to incorporate it into toxicological studies.

This study was run in order to better understand how an antidepressant, fluoxetine, which can be found downstream of wastewater treatment plants may impact the gut microbiome of the fish species, Fathead minnows.

Weber, A., Xie, Y., Challis, J., DeBofsky, A., Ankley, P., Hecker, M., Jones, P., Giesy, J. (2021). The impact of fluoxetine on the gut microbiome of Pimephales promelas [Dataset]. Federated Research Data Repository. https://doi.org/10.20383/102.0412

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

1. Description of collection methods and generation of data:
Gut content of Fathead minnows was collected after a 28-day exposure to fluoxetine at varying concentrations (100, 10, & 0.01, 0.00 µg/L).

2. 16s amplicon sequencing:
DNA was extracted from intestines using DNeasy PowerSoil Kit (Qiagen Inc., Mississauga, ON). DNA quantification was measured using a Quibt 4 Fluorometer and dsDNA HS assay kit (ThermoFisher Scientific, Waltham, MA). The V3-V4 variable region of the 16S rRNA gene was amplified using polymerase chain reaction (PCR) with dual-tagged primers, 341F (5'-tag- CCTACGGGNGGCWGCAG-3') and 806R (5'-tag- GGACTACNVGGGTWTCTAAT-3'). SimpliAmp thermal cycler (ThermoFisher Scientific) was used to perform PCR and conditions were set at; initial denaturation: 98°C for 30s, followed by 26 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 then verified using gel electrophoresis and purified using the Qiagen QIAquick PCR Purification Kit (Qiagen Inc.). After purification, products were then pooled and libraries were constructed using the NEBNext DNA Library Prep Master Mix set for Illumina ® (New England BioLabs Inc., Whitby, ON). After quantification of the libraries, sequencing was run on the Illumina ® MiSeq instrument (Illumina, San Diego, CA).

3. Methods for processing the data:
Sequences were trimmed, cleaned, demultiplexed and merged using fastq_multx 9 (Aronesty, 2013) and DADA2 (Callahan et al., 2016) within QIIME2 (Boylen et al., 2019). To maximize quality of reads, forward reads were truncated at 260bp and reverse reads at 220bp. Using VSEARCH (Rognes et al., 2016) against the reference database, SILVA 132 (Bokulich et al., 2018; Quast et al., 2013), taxonomy was assigned. All nonbacterial ASVs and low frequency reads were removed, and alpha rarefaction was performed at a depth of 11,125 to maximize the depth threshold. 73 samples survived after rarefaction and 377 ASVs. Statistical analysis were then conducted in R Statistical language v 4.0.3 (R Core Team, 2020).

4. Instrument- or software-specific information needed to interpret the data:
Fastq files can be analyzed in QIIME2 and R.

5. Environmental/experimental conditions:
Adult fathead minnows were exposed to select concentrations of fluoxetine treated water as a static renewal 28-day exposure. Fish were randomly assigned a tank where there were 5 tanks per concentration, 5 fish per tank and 4 different exposure groups (control, 0.01, 10, and 100 µg/L). Fish were fed twice a day with blood worms and average temperature for tanks was 22 ºC. Ammonia, pH, and dissolved oxygen were checked weekly. Light to dark ratio was 16:8 according to the OECD 229 guidelines (OECD, 2009).

6. Describe any quality-assurance procedures performed on the data:
Fasq_multx was used for quality assurance by trimming and cleaning low quality bases and removing them from the dataset. DADA2 was used to filter, denoise and remove chimeras from data.

Creative Commons Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/

Data available at: https://doi.org/10.20383/102.0412