| Literature DB >> 34867778 |
Amin Nozari1, Selena Do1, Vance L Trudeau1.
Abstract
Transgenic zebrafish models have been successfully used in biomonitoring and risk assessment studies of environmental pollutants, including xenoestrogens, pesticides, and heavy metals. We employed zebrafish larva (transgenic SR4G line) with a cortisol-inducible green fluorescence protein reporter (eGFP) as a model to detect stress responses upon exposure to compounds with environmental impact, including bisphenol A (BPA), vinclozolin (VIN), and fluoxetine (FLX). Cortisol, fluorescence signal, and mRNA levels of eGFP and 11 targeted genes were measured in a homogenized pool of zebrafish larvae, with six experimental replicates for each endpoint. Eleven targeted genes were selected according to their association with stress-axis and immediate early response class of genes. Hydrocortisone (CORT)and dexamethasone (DEX) were used as positive and negative controls, respectively. All measurements were done in two unstressed and stressed condition using standardized net handling as the stressor. A significant positive linear correlation between cortisol levels and eGFP mRNA levels was observed (r> 0.9). Based on eGFP mRNA levels in unstressed and stressed larvae two predictive models were trained (Random Forest and Logistic Regression). Both these models could correctly predict the blunted stress response upon exposure to BPA, VIN, FLX and the negative control, DEX. The negative predictive value (NPV) of these models were 100%. Similar NPV was observed when the predictive models trained based on the mRNA levels of the eleven assessed genes. Measurement of whole-body fluorescence intensity signal was not significant to detect blunted stress response. Our findings support the use of SR4G transgenic larvae as an in vivo biomonitoring model to screen chemicals for their stress-disrupting potentials. This is important because there is increasing evidence that brief exposures to environmental pollutants modify the stress response and critical coping behaviors for several generations.Entities:
Keywords: biomonitoring assay; endocrine-disrupting compounds; environmental toxicology; stress-axis; transgenic model; zebrafish
Mesh:
Substances:
Year: 2021 PMID: 34867778 PMCID: PMC8635770 DOI: 10.3389/fendo.2021.727777
Source DB: PubMed Journal: Front Endocrinol (Lausanne) ISSN: 1664-2392 Impact factor: 5.555
Figure 1The time-lapse fluorescence imaging captures the ubiquitous eGFP expression in 4dpf SR4G transgenic zebrafish line following the handling stress. Panel (A) shows the direct fluorescent imaging of 4dpf SR4G transgenic larva head at five different time-points after the handling stress. Panel (B) shows the quantified fluorescence intensity (mean grey value) after the handling stress in four different anatomical regions; diencephalon, telencephalon, left olfactory bulb and right olfactory bulb at five different time-points. Means (± SEM) marked with different letters (a, b) are significantly different within each anatomical position; p < 0.01; N=10.
Figure 2The correlation between whole-body cortisol and total eGFP mRNA levels in SR4G transgenic zebrafish larvae. Panel (A) shows normalized whole-body cortisol levels and panel (B) shows normalized whole-body eGFP mRNA levels in the two control groups, Ethanol and DMSO, under the two unstressed and stressed conditions. Two-way ANOVA was performed to evaluate the effect of treatments and stress conditions on whole-body cortisol levels and whole-body eGFP mRNA levels. Means (± SEM) marked by an asterisk (*) are significantly different within each category (whole-body cortisol or whole-body eGFP mRNA study); p ≤ 0.0001; N=6. Ethanol: overnight exposure to 0.005% ethanol; DMSO: overnight exposure to 0.001% DMSO. The time points,30 min or 60 min, show the time-lapsed following the handling stress before euthanizing the subjects for sample collection. Each sample contained a pool of 22-28 of 7dpf SR4G transgenic zebrafish larvae. The correlation coefficient between whole-body cortisol and whole-body eGFP mRNA determined by the Pearson test and a positive correlation with r=0.947 achieved.
Figure 3Whole-body cortisol and eGFP mRNA levels in SR4G larvae exposed to different chemicals before and after handling stress. Panel (A) shows the whole-body cortisol (normalized pg/larvae) measured before and after the handling stress following exposure to different chemicals. The white bars represent cortisol levels in the unstressed condition (sacrificing subjects at 0 minutes before the handling stress) and the black bars represent cortisol levels 30 minutes after the handling stress. Panel (B) shows the eGFP mRNA levels (normalized fold change) measured before and after the handling stress following exposure to different chemicals. The white bars represent eGFP mRNA levels in the unstressed condition (sacrificing subjects at 0 minutes before the handling stress) and the gray bars represent eGFP mRNA levels 60 minutes after the handling stress. Two-way ANOVA was performed between each treatment group and its related control group in both unstressed and stressed state. No statistical comparison was performed between different treatment groups. Tukey’s post-hoc test followed the significant ANOVA results for pairwise comparisons. Means (± SEM) with different letters (a, b) are significantly different; p ≤ 0.05; N=6. Each sample contained a pool of 22-28 7dpf SR4G transgenic zebrafish larvae. Ethanol was used as the vehicle for FLX with a final concentration of 0.005%. DMSO was used as the vehicle for BPA, VIN, and DEX with a final concentration of 0.001%. The DMSO data in each graph is the same data portrayed for comparison purposes. FLX-O/N, overnight exposure to fluoxetine; FLX-6D, daily exposure to fluoxetine from 0 to 6 days post fertilization(dpf); Ethanol-O/N, overnight exposure to ethanol; Ethanol-6D, daily exposure to ethanol from 0dpf to 6dpf; BPA, overnight exposure to bisphenol A; VIN, overnight exposure to vinclozolin; DEX, overnight exposure to dexamethasone; DMSO, overnight exposure to DMSO. *Significantly different (p<0.05) compared to unstressed state but not significant in 2-way ANOVA.
Prediction of stress response based on the whole-body eGFP mRNA levels using regression random forest (RDF) and logistic regression (LOG) model trained by ethanol (control) group.
| Ethanol (control) | Predicted Stress Status | |||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| FLX_O/N | FLX-6D | DMSO | BPA | VIN | DEX | |||||||||||||||
| Samples | FC | Stress | FC | LOG | RDF | FC | LOG | RDF | FC | LOG | RDF | FC | LOG | RDF | FC | LOG | RDF | FC | LOG | RDF |
| Uns-1 | 2.05 | 0 | 9.33 | 1 | 1 | 0.23 |
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| 1.33 |
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| 0.16 |
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| 0.10 |
|
| 0.06 |
|
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| Uns-2 | 0.90 | 0 | 5.69 | 1 | 1 | 0.16 |
|
| 0.72 |
|
| 0.24 |
|
| 0.08 |
|
| 0.36 |
|
|
| Uns-3 | 0.64 | 0 | 1.27 |
|
| 0.39 |
|
| 0.93 |
|
| 0.37 |
|
| 0.04 |
|
| 0.10 |
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| Uns-4 | 0.27 | 0 | 0.74 |
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| 0.10 |
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| 1.09 |
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| 0.07 |
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| 0.06 |
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| 0.04 |
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| Uns-5 | 0.72 | 0 | 1.12 |
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| 0.24 |
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| 0.80 |
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| 0.16 |
|
| 0.00 |
|
| 0.07 |
|
|
| Uns-6 | 1.41 | 0 | 0.04 |
|
| 0.07 |
|
| 1.28 |
|
| 0.09 |
|
| 0.01 |
|
| 0.17 |
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| St-1 | 6.95 | 1 | 12.81 |
|
| 0.99 |
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| 3.93 |
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| 0.00 |
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| 0.55 |
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| 0.06 |
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| St-2 | 4.18 | 1 | 5.80 |
|
| 1.32 |
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| 0.84 | 0 | 0 | 0.00 |
|
| 0.58 |
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| 0.36 |
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| St-3 | 1.57 | 1 | 2.77 |
| 0 | 1.64 |
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| 1.24 | 0 | 0 | 1.01 |
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| 0.86 |
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| 0.10 |
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| St-4 | 2.89 | 1 | 2.80 |
| 0 | 1.55 |
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| 5.00 |
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| 0.79 |
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| 0.78 |
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| 0.04 |
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| St-5 | 5.32 | 1 | 3.60 |
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| 2.32 | 1 |
| 4.45 |
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| 0.01 |
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| 0.57 |
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| 0.07 |
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| St-6 | 5.74 | 1 | 5.60 |
|
| 1.65 |
|
| 3.30 |
|
| 0.94 |
|
| 0.92 |
|
| 0.17 |
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FC, fold change; FLX-6D, daily exposure to from 0 to 6 days post fertilization(dpf); FLX-O/N, BPA, VIN, DEX, CORT representing overnight exposure to fluoxetine, bis-phenol A, vinclozolin, dexamethasone, and cortisol, respectively. LOG, logistic regression, RFD, random forest. PPV, positive predictive value; NPV, negative predictive value. Uns, unstressed sample; St, stressed sample. (LOG; R2, 0.774) (RDF; OOB, 0.4).
N/A, not applicable, the PPV can not be calculated.
The correct predications (true) are shown by bold values (1 or 0).