© 2017. Published by The Company of Biologists Ltd.

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Inorganic Arsenic Causes Fatty Liver and Interacts with Ethanol to Cause Alcoholic Liver

Disease in Zebrafish

Kathryn Bambino1, Chi Zhang2, Christine Austin1, Chitra Amarasiriwardena1, Manish Arora1,

Jaime Chu3, Kirsten C. Sadler2*

1Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount

Sinai, New York, New York 10029

2Program in Biology, New York University Abu Dhabi, Saadiyat Island Campus, United Arab

Emirates

3Department of Pediatrics, Division of Pediatric Hepatology, Icahn School of Medicine at Mount

Sinai, New York, New York 10029

*Corresponding author. Email: Kirsten.Edepli@nyu.edu (K.C.S.)

Key terms: arsenic, ethanol, fatty liver disease, environmental exposure

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http://dmm.biologists.org/lookup/doi/10.1242/dmm.031575Access the most recent version at First posted online on 28 December 2017 as 10.1242/dmm.031575

Symbols and Abbreviations

ALD – alcoholic liver disease

dpf – days post fertilization

ER – endoplasmic reticulum

FLD – fatty liver disease

hpf – hours post fertilization

iAs – inorganic arsenic

ICP-MS – inductively-coupled plasma – mass spectroscopy

LA-ICP-MS – laser ablation – inductively-coupled plasma – mass spectroscopy

ORO – Oil Red O

ROS- reactive oxygen species

UPR – unfolded protein response

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Abstract

The rapid increase in fatty liver disease (FLD) incidence is attributed largely to genetic and life

style factors, however, environmental toxicants are a frequently overlooked factor that can

modify the effects of more common causes of FLD. Chronic exposure to inorganic arsenic (iAs)

is associated with liver disease in humans and animal models, but neither the mechanism of

action nor the combinatorial interaction with other disease causing factors has been fully

investigated. Here, we examined the contribution of iAs to FLD using zebrafish and tested the

interaction with ethanol to cause alcoholic liver disease (ALD). We report that zebrafish exposed

to iAs throughout development developed specific phenotypes beginning at 4 days post-

fertilization (dpf), including development of FLD in over 50% of larvae by 5 dpf. Comparative

transcriptomic analysis of livers from larvae exposed to either iAs or ethanol revealed oxidative

stress response and the unfolded protein response (UPR) caused by endoplasmic reticulum

(ER) stress as common pathways in both these models of FLD, suggesting they target similar

cellular processes. This was confirmed by our finding that arsenic is synthetically lethal with

both ethanol and a well-characterized ER stress inducing agent (tunicamycin), suggesting that

these exposures work together through UPR activation to cause iAs toxicity. Most significantly,

combined exposure to sub-toxic concentrations of iAs and ethanol potentiated the expression of

UPR-associated genes, cooperated to induce FLD, reduced the expression of the arsenic

metabolizing enzyme as3mt, and significantly increased the concentration of iAs in the liver.

This demonstrates that iAs exposure is sufficient to cause FLD and that low doses of iAs can

potentiate the effects of ethanol to cause liver disease.

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Introduction

Fatty liver disease (FLD) is the most common liver pathology in the world (Levene and

Goldin 2012). The dramatic rise in incidence in the past several decades has prompted intense

investigation into the biological basis for this observation. Diet (Adams and Lindor 2007),

genetics (Anstee and Day 2015; Liu et al. 2013), and alcohol abuse (Magdaleno et al. 2017) are

clear risk factors for FLD, but these risks alone do not account for the steep rise in FLD

incidence, nor do they provide an explanation for all FLD cases. Epidemiological studies have

shown that multiple environmental and anthropogenic toxins cause liver disease in humans

(Das et al. 2010; Islam et al. 2011; Mazumder 2005; Santra et al. 1999) and work in rodents

(Ditzel et al. 2016) and zebrafish (Cheng et al. 2016) have demonstrated a direct, causative

relationship between some environmental toxins and FLD (Al-Eryani et al. 2015; Wahlang et al.

2013). The combination of epidemiological and basic research on environmental toxins and

metabolic disease is rapidly advancing, yet the scope of the problem and the mechanisms of

toxicity are not yet clear.

Chronic exposure to inorganic arsenic (iAs) is a worldwide public health concern, as it is

associated with a broad range of health problems (Centeno et al. 2002; Naujokas et al. 2013).

iAs is a naturally-occurring element in the earth’s crust and both humans and wildlife are

exposed to iAs through food and water. Estimates of over 100 million people worldwide are

exposed to levels exceeding World Health Organization (WHO) established limits (Adams et al.

2016; Farzan et al. 2016; Yang et al. 2009). The first prospective cohort study of people

chronically exposed to arsenic has revealed an increase in all-cause and chronic disease

mortalities (Ahsan et al. 2006; Argos et al. 2010). Notably, frequent co-morbidities of FLD,

including diabetes (Kuo et al. 2015; Weijing Wang et al. 2014), cardiovascular disease (Moon et

al. 2013), and liver cancer (W. Wang et al. 2014) are significantly associated with iAs exposure.

A study in the arsenic endemic regions of Bangladesh and West Bengal, India where obesity

and alcohol abuse are low, chronic exposure to iAs via drinking water is associated with liver

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damage and fibrosis (Das et al. 2012; Islam et al. 2011). This was confirmed by the finding of a

high prevalence of FLD and other liver diseases in this same region (Das et al. 2010). Together,

the epidemiological data suggests that arsenic is a liver toxicant in humans. Whether it can

potentiate the effects of other causes of liver disease, such as alcohol abuse, remains to be

investigated.

Work using animal models have demonstrated that iAs can cause FLD. In some mouse

studies, chronic iAs exposure induces lipogenic gene expression in the liver (Adebayo et al.

2015) and FLD (Santra et al. 2000b). Strikingly, exposure to iAs in utero and post-weaning

leads to adults that have a higher rate of FLD when fed a high fat diet (Ditzel et al. 2016). In

zebrafish, arsenic exposure in embryos causes widespread developmental defects (Adeyemi et

al. 2015; Bambino and Chu 2017; Li et al. 2009; Li et al. 2012; Ma et al. 2015; McCollum et al.

2014; Wang et al. 2006) and exposing adult zebrafish causes a range of gene and protein

expression changes in the liver related to lipid metabolism (Carlson and Van Beneden 2014;

Hallauer et al. 2016; Li et al. 2016; Xu et al. 2013) and one study reported FLD in adult

zebrafish acutely exposed to iAs (Li et al. 2016). Thus, across species, iAs causes liver

damage. These data indicate that iAs alone causes FLD, and can also predispose to FLD

susceptibility and we propose that lower doses of iAs interact with more common risk factors to

promote FLD.

The importance of iAs as a toxicant has generated significant interest in deciphering how

iAs exposure causes disease. iAs metabolism via the arsenic 3 methyltransferase (AS3MT)

utilizes the same methyl donor that is used for DNA methylation (Hamdi et al. 2012; Thomas et

al. 2004) and iAs methylation reaction produces reactive oxygen species (ROS) (Jomova et al.

2011; Santra et al. 2000a; Shi et al. 2004; Xu et al. 2017). Thus, reduction in DNA methylation

and oxidative stress are two leading theories for the mechanism of iAs toxicity. A third possibility

is based on the finding that iAs impairs protein folding: iAs binds thiol groups, and it is well

established that the basis for acute arsenic poisoning is iAs acting as a reducing agent for

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sulfhydryl groups in key metabolic enzymes (Hughes 2002; Sattar et al. 2016). Similarly, at

lower doses, iAs acts to reduce sulfhydryl groups on cysteine residues in nascent peptides

which prevents disulfide bond formation (Jacobson et al. 2012; Ramadan et al. 2009) and

prevents accurate protein folding. In addition, ROS generated via arsenic metabolism can

disrupt the redox balance required for disulfide bond formation and protein folding in the

endoplasmic reticulum (ER). The finding that the unfolded protein response (UPR), the pathway

induced by ER stress, is activated with iAs treatment of some cell types (Doudican et al. 2012;

Weng et al. 2014) supports the hypothesis of ER stress is a mechanism for iAs induced toxicity.

The UPR is a central pathway in FLD pathophysiology across species (Goessling and

Sadler 2015; Wang and Kaufman 2014). A robust ER stress is sufficient to cause FLD in mice

and zebrafish (Cinaroglu et al. 2011; Ji et al. 2011; Ozcan et al. 2004; Thakur et al. 2011;

Vacaru et al. 2014; Yamamoto et al. 2010), and we have shown that activation of Atf6, a main

upstream player in the UPR, is necessary and sufficient to cause FLD (Cinaroglu et al. 2011;

Howarth et al. 2014). This provides a direct and mechanistic link between UPR activation and

fatty liver. ROS generated from ethanol metabolism is a central mechanism of alcoholic liver

disease (ALD) (Louvet and Mathurin 2015). ROS alone can induce the UPR, and we

(Tsedensodnom et al. 2013) and others (Lu and Cederbaum 2008) have shown that the UPR

activation and FLD caused by alcohol is mediated by ROS. Given that UPR activation is a

central mechanism of ALD (Cinaroglu et al. 2011; Howarth et al. 2012; Howarth et al. 2014)

we hypothesize that other toxicants which disrupt ER function, such as iAs, could collaborate

with ethanol to cause liver disease.

In this study, we use zebrafish to identify the mechanism by which iAs causes liver

disease and to investigate whether iAs exposure interacts with ethanol to induce ALD. We found

that iAs alone can cause FLD and that exposure to sub-toxic concentrations of iAs and ethanol

interact to induce the UPR and cause FLD. Transcriptomic analysis revealed that ER and

oxidative stress response are activated in the liver of larvae treated with either iAs or ethanol,

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but, strikingly, while a few UPR target genes were common to both, these two toxicants induced

unique UPR signatures. We found larvae exposed to iAs are sensitized to ethanol, showing an

increase in larval mortality and increased iAs concentration in the liver. Importantly, we show

that iAs and ethanol interact to cause FLD. This provides evidence that environmental toxicants

can modify the effect of more common risk factors for liver disease and thus may act as

coordinating events in the multistep process of progressive liver disease (Browning and Horton

2004; Day and James 1998; Dowman et al. 2010).

Results

Zebrafish are susceptible to arsenic toxicity

Multiple theories have been proposed to explain how chronic iAs causes disease,

however, none have yet been conclusively identified. Studies using zebrafish to investigate the

developmental toxicity (Li et al. 2009; Ma et al. 2015; Seok et al. 2007) and consequences of

iAs exposure in adults (Carlson and Van Beneden 2014; Hallauer et al. 2016; Lam et al. 2006;

Xu et al. 2013) have established this as an excellent model for investigating the mechanism of

iAs toxicity. We extended this work by establishing a protocol to expose zebrafish embryos to

iAs throughout development at a dose that would not impair liver development, to allow analysis

of liver disease in older larvae. Fertilized zebrafish embryos were exposed to a range of sodium

(meta)arsenite (iAs) concentrations beginning at 4 hpf and monitored daily for mortality.

Treatment with 2.0 mM (260 ppm) iAs resulted in death of all exposed fish by 6 dpf (n = 2

clutches, 80 embryos per condition) whereas concentrations <1.0 mM were well tolerated during

this time (Figure 1A, Table S3). Using this data, we calculated the concentration at which 50%

of exposed fish died by 6 dpf (LC50) to be 1.25 mM (Supplemental Figure 1A). Short term

exposure to 2 mM iAs prior to 48 hpf resulted in fewer developmental defects than longer

exposures (Supplemental Figure 1B), suggesting that the effects of iAs exposure during

development are cumulative. Exposure to the highest dose of iAs (2 mM) beginning at 72 or 96

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hpf until 120 hpf also resulted in significant abnormalities and larval death (data not shown),

raising the possibility that later developmental stages may also be susceptible, however, this

remains an area for further exploration.

Embryos exposed to concentrations of iAs which caused minimal lethality by 5 dpf (i.e.

<1.4 mM) developed a range of specific phenotypes by 5 dpf, including a shortened body

length, edema, clustering of pigment cells, under-consumption of yolk, and a small head

(arrows, Figure 1B). Of the larvae that survived exposure to 0.6 mM, 1.0 mM, 1.4 mM, and 2.0

mM iAs until 5 dpf, 19.6%, 37.1%, 64.1%, and 100% displayed at least one of these phenotypes

at 5 dpf (Figure 1C and Supplemental Figure 1C). These data are consistent with other studies

that show that iAs at concentrations of 1.0 mM and above caused developmental abnormalities,

whereas 0.5 mM was well tolerated by developing zebrafish embryos (Li et al. 2009).

Zebrafish metabolize iAs in the liver

Previous studies have demonstrated that zebrafish express aquaglyceroporins and the

trivalent arsenic specific methyltransferase (As3mt) (Hamdi et al. 2009; Hamdi et al. 2012),

enzymes required for the uptake and metabolism of iAs, respectively. We asked whether

zebrafish embryos expressed as3mt throughout development and determined whether, like in

mammals (Thomas et al. 2004; Tseng 2007), as3mt was enriched in the liver. Through both

qRT-PCR analysis and mining transcriptomic data from Array Express

(www.ebi.ac.uk/arrayexpress), it is clear that as3mt mRNA is maternally-contributed and

zygotically expressed (Figure 2A and Supplemental Figure 2), and at 5 dpf expression was

enriched by over 8-fold in the liver compared to the liver-less carcass (Figure 2A).

We next asked if iAs was metabolized in zebrafish using laser ablation-inductively

coupled plasma-mass spectroscopy (LA-ICP-MS) (Hare et al. 2012) and inductively coupled

plasma-mass spectroscopy (ICP-MS), highly sensitive microanalytical techniques used to detect

elements in biological or geological samples. ICP-MS is best suited to provide a highly sensitive

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quantitative measurement of iAs levels and LA-ICP-MS is used for mapping the tissues where

iAs accumulates (Sussulini et al. 2017). We found high concentrations of iAs in the skin, eye,

gut and, most notably, liver in larvae exposed to 1mM iAs from 4-120 hpf (Figure 2B). ICP-MS

performed on livers dissected from iAs exposed and control larvae showed a highly consistent,

dose-dependent increase in the amount of iAs with increasing exposure concentrations (Figure

2C). These data show that zebrafish larvae express the enzyme required to metabolize iAs in

the liver, and this is a site of iAs accumulation, suggesting this as a target tissue for iAs toxicity.

iAs causes fatty liver

Chronic exposure to iAs is associated with altered liver function and liver disease (Das et

al. 2012; Islam et al. 2011; Mazumder 2005; Santra et al. 1999; W. Wang et al. 2014). Previous

studies in both mice and adult zebrafish showed that arsenic exposure can cause steatosis

(Ditzel et al. 2016; Li et al. 2016; Tan et al. 2011), and can also sensitize mice to other factors

that cause FLD, such as a high fat diet (Tan et al. 2011). We tested the efficacy of iAs to directly

cause FLD in zebrafish larvae treated with 1.0 mM iAs from 4 to 120 hpf using oil red O (ORO),

which we have previously demonstrated is a straight forward means of assessing steatosis

incidence across multiple clutches of larvae (Passeri et al. 2009; Vacaru et al. 2014) (Figure

3A). The percent of control larvae with steatosis was an average of 15.2 ± 3.0% (ranging from 0

to 42% across 15 clutches; Figure 3B, Table S3). The incidence was significantly higher in the

iAs exposed larvae with a mean of 46.9 ± 5.2% (ranging from 16 to 85.7%, n = 15 clutches, p <

0.001) (Figure 3B, Table S3). These data show that iAs is sufficient to cause FLD in this model,

facilitating investigation of the cellular mechanisms of this phenotype.

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ER and oxidative stress responses are common pathways activated in response to either

iAs or ethanol

To identify cellular pathways activated in response to iAs and to gain insight into those

processes that contribute to iAs induced steatosis, we performed RNAseq analysis on livers

dissected from 3 clutches of 5 dpf Tg(fabp10a:nls-mCherrymss4Tg) larvae exposed to 1 mM iAs

from 4 hpf to 120 hpf and from unexposed controls. In total, 5,118 genes were differentially

expressed between iAs exposed and control siblings (padj < 0.05); 2,629 genes were

upregulated (537 log2 fold change > 2) and 2,489 genes were downregulated (412 log2 fold

change < -2) (Figure 4A, Table 1, Table S4). In addition, some genes with read counts greater

than or equal to 20 in one condition and less than or equal to 5 in the other were identified by

our analysis. We designated these as “on-off” genes, and found that 186 genes turned on and

214 genes turned off in the liver in response to iAs genes (Table 1). We identified pathways

induced in the liver by iAs exposure using Ingenuity Pathway Analysis (IPA) of the upregulated

genes in iAs samples. Metabolism (mitochondrial dysfunction and oxidative phosphorylation)

and Nrf2-mediated oxidative stress pathways were highly enriched in the livers of iAs exposed

larvae (Figure 4B), consistent with findings from other systems (Li et al. 2015; Sinha et al.

2013).

Reanalysis of an RNAseq dataset we previously generated from livers dissected from

Tg(fabp10a:nls-mCherrymss4Tg) zebrafish exposed to 2% ethanol from 96 – 132 hpf (Howarth et

al. 2014) was carried out to identify genes and pathways common to both iAs and ethanol

treatment. We found significantly fewer differentially expressed genes (1,094; padj < 0.05), with

619 genes upregulated (302 log2 fold change > 2) and 475 genes were downregulated (178

log2 fold change < -2), with 153 genes on and 65 genes off in only ethanol treated samples

(Figure 4C, Table 1, Table S4). IPA of all upregulated genes in the ethanol revealed that

cholesterol biosynthesis (Superpathway of Cholesterol Biosynthesis, Cholesterol Biosynthesis I,

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Mevalonate Pathway), oxidative stress and UPR/ER stress responses were among the most

significantly enriched processes (Figure 4D). This is consistent with our previous finding that

UPR activation and FLD in response to alcohol was mediated by oxidative stress (Howarth et al.

2014; Tsedensodnom et al. 2013).

We found high correlation between control samples in the two datasets, with correlation

coefficients ranging from 0.87-1.0 (Supplemental Figure 3A). This allowed us to compare these

two datasets to identify pathways that were commonly regulated. We identified 555 genes that

were significantly differentially expressed in both the iAs and ethanol datasets (Figure 4E, Table

1) of which 479 changed their expression in the same direction, with 215 genes upregulated and

264 genes downregulated in both datasets (Table 1, Table S4). IPA of the common upregulated

genes revealed that oxidative stress, ER stress, and UPR pathways as the most highly

represented (Figure 4F). Oxidative stress generated during iAs metabolism is a proposed

mechanism of arsenic toxicity (Huang et al. 2004; Santra et al. 2000a; Santra et al. 2007).

Decades of research in mammalian systems (Lu and Cederbaum 2008; Magdaleno et al. 2017)

and our work in zebrafish (Tsedensodnom et al. 2013) have shown that oxidative stress is also

a primary cellular mechanism of ALD. Interestingly, three of the commonly regulated pathways

(Pentose Phosphate Pathway, Glycolysis, and Gluconeogenesis) were previously found to be

induced in transcriptome or metabolomics analysis of livers from adult zebrafish acutely

exposed to iAs (Li et al. 2016; Xu et al. 2013).

Different stressors induce distinct UPRs (Vacaru et al. 2014) and each branch of the

UPR modulates protein folding in a unique way. We analyzed the iAs and ethanol RNAseq

datasets to determine if these toxins also activated distinct UPRs. We generated a list of 254

genes that are targets of the UPR or function in the UPR based on annotations in AmiGo and

NCBI. Of these UPR-associated genes, the majority (227 genes) were expressed in both the iAs

and ethanol RNAseq datasets and nearly half of these (103 genes) were significantly

differentially expressed in one or both datasets (Table S5), with 89 differentially expressed in

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the iAs dataset and 37 differentially expressed in the ethanol dataset. Interestingly, the pattern

of UPR gene expression was largely distinct in these two models as only 10% of all UPR-

associated genes and 20% of genes differentially expressed in one of the datasets showed a

shared expression pattern in both datasets. The UPR-associated genes affected by both

stressors include the bona fide UPR genes atf3, hspa5, hyou1, and dnajc3 as well as heat

shock related proteins (Figure 5B, Table S5). Additionally, 67 of the UPR-associated genes

were only changed in the iAs dataset and 15 genes were only changed in the ethanol dataset

(Figure 5A, Table S5). Since most of the UPR-associated transcripts were detected in both

datasets at similar levels based on FPKM values (Supplemental Figure 3B), we concluded that

the unique patterns of UPR gene expression in these two datasets reflect distinct types of UPRs

(i.e. UPR subclasses (Vacaru et al. 2014)). We used qRT-PCR to confirm that the UPR genes

we previously showed to be associated with FLD (xbp1, xbp1s, bip, chop, dnajc3, edem1, atf4,

and atf6 (Vacaru et al. 2014)) were upregulated in the liver of iAs exposed larvae, and found

that all except xbp1 and xbp1s were significantly induced (n = 9 clutches, p < 0.01)

(Supplemental Figure 4A). We functionally assessed the relevance of ER stress to iAs induced

toxicity by co-exposing larvae to iAs and tunicamycin, a well characterized and widely used ER

stressor which we have shown causes FLD in zebrafish (Cinaroglu et al. 2011; Howarth et al.

2013; Vacaru et al. 2014) and found them to be synergistically lethal (Supplemental Figure 4B),

suggesting they act through shared mechanisms to cause lethality.

Together, these data indicate that (1) similar pathways are deregulated by iAs and

ethanol, or ethanol alone, including oxidative stress and the UPR, (2) both iAs and ethanol

induce the UPR and that (3) a subset of UPR genes are targeted by both iAs and ethanol and

also that (4) each of these toxicants induces a unique UPR signature, extending our previous

findings of distinct UPR subclasses in response to other ER stressors (Vacaru et al. 2014). We

speculate that the subset of UPR genes deregulated in response to both stressors reflects some

commonality in their mechanism of UPR induction.

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Ethanol potentiates iAs toxicity, ER stress, and fatty liver

Our finding that there are shared pathways targeted by both ethanol and iAs suggests

that combined exposure may interact to cause liver disease. To test this, embryos were treated

with a range of concentrations of iAs (0.1 mM, 0.5 mM, 1.0 mM) starting at 4 hpf and

subsequently exposed at 96 hpf to a range of ethanol concentrations (0.5%, 1.0%, 1.5%) which

we have previously shown are below and above the threshold for causing lethality and FLD

(Tsedensodnom et al. 2013). We found that iAs significantly reduced survival of larvae exposed

to ethanol concentrations that were otherwise well-tolerated on their own (n = 3 clutches, p <

0.001) (Figure 6A), showing that they synergize to cause lethality and suggesting this results

from their convergence on the same pathways.

To investigate the nature of this interaction, we reduced exposure concentrations to

ensure survival of co-exposed larvae to allow further analysis. qPCR analysis of samples from

larvae exposed to 0.5% ethanol or 0.5 mM iAs alone or in combination revealed that co-

exposure enhanced expression of bip, chop, and atf6, compared to that in samples treated with

either toxicant alone (Figure 6B). This demonstrates that exposure to a dose of iAs which does

not cause any morphological or gene expression changes can predispose to a dramatic

response to a low dose of ethanol. This is important as it suggests that co-exposure to sub-toxic

concentrations of these two toxicants can cause disease.

We next tested our hypothesis that a potential mechanism by which iAs and ethanol

could interact would be via altered expression of the enzymes responsible for iAs metabolism

and clearance. We found that as3mt expression was significantly reduced in fish treated with

iAs and ethanol compared to those exposed to either toxicant alone (n = 5 clutches, 0.5%

ethanol vs. 0.5 mM iAs + 0.5% ethanol p = 0.0013, 0.5 mM iAs vs. 0.5 mM iAs + 0.5% ethanol p

= 0.0158) (Figure 6C). Since reduced expression of as3mt can impair clearance of iAs from the

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liver, we hypothesized that ethanol exposure would increase the iAs levels in the liver. ICP-MS

analysis showed that iAs levels were significantly higher in the livers of larvae exposed to 0.5

mM iAs, 0.5% ethanol than in larvae exposed to 0.5 mM iAs alone (n = 6 clutches, p =0.0003)

(Figure 6D). This demonstrates that the clearance of arsenic from the liver is hindered upon co-

exposure to these two toxicants.

We next hypothesized that accumulation of iAs can increase the toxic sequelae of iAs

exposure, including exacerbating ER stress and potentially increasing FLD incidence. To test

this, we exposed zebrafish to each toxicant alone or in combination at doses which, when given

independently, do not cause steatosis. Zebrafish embryos were treated with 0.5 mM iAs at 4

hpf, followed by addition of either 0% or 0.5% ethanol at 96 hpf and collected at 120 hpf for

ORO staining. We found that the incidence of steatosis was significantly higher in larvae

exposed to both toxicants compared to either agent alone (n = 7 clutches, 0.5% ethanol vs. 0.5

mM iAs + 0.5% ethanol p = 0.0025; 0.5 mM iAs vs. 0.5 mM iAs + 0.5% ethanol p = 0.0172)

(Figure 6E, Table S6). To determine whether we could detect an interaction between iAs and

ethanol in the development of steatosis, we modeled the risk difference between the exposure

conditions. The combined incidence of steatosis across all seven clutches was determined by

dividing the number of larvae with steatosis in each group by the total population of that group.

This yielded a background incidence of steatosis of 20.45% (27/132) in control larvae, 19.85%

(27/136) in larvae exposed to 0.5% ethanol alone, 25.19% (33/131) in larvae exposed to 0.5

mM iAs alone, and 48.97% (71/145) in larvae co-exposed to 0.5 mM iAs + 0.5% ethanol (Figure

6E and Table S6). Controlling for the fact that some of the larvae were from the same clutch,

neither exposure to 0.5% ethanol nor 0.5 mM iAs alone significantly increased the risk of

developing steatosis relative to control (0.5% ethanol p = 0.98, 0.5 mM iAs p = 0.36). However,

co-exposure to 0.5 mM iAs + 0.5% ethanol resulted in an increased risk of developing steatosis

at an alpha of 0.1, commonly used to assess the risk of interaction in epidemiological studies (p

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= 0.08). These data support the conclusion that iAs and ethanol interact to increase the

concentration of iAs in the liver, aggravate ER stress and enhance FLD (Figure 7).

Discussion

Genetic and lifestyle factors are assumed to be primary causes of FLD, however,

environmental toxicants can serve important disease-modifying roles by targeting cellular

pathways or processes that render them more susceptible to other stimuli. Here we show that

high doses of iAs causes FLD and can modify the risk of ALD. Importantly, the interaction

between iAs and ethanol is observed at doses of these toxins which alone do not cause any

detectable phenotypic or cellular changes. This suggests that exposure to a sub-toxic level of

iAs could serve as a risk factor for more common causes of liver disease, such as ALD.

Additionally, our unbiased approach to identify pathways that serve as a nexus for these

toxicants revealed oxidative and ER stress as points of convergence. We hypothesize that

these cellular stress responses are the mechanisms for the increased toxicity we observe in the

presence of iAs and ethanol. Finally, we present mechanistic data demonstrating that ethanol

acts to decrease as3mt expression, thereby reducing iAs metabolism, leading to sustained, high

concentrations of iAs and potentiating its toxic impact.

Oxidative stress is a major cause of hepatic injury caused by alcohol, as ROS are

generated from alcohol metabolism by the Cytochrome P450 system (CYP2E1) (Cederbaum

2010; Lu and Cederbaum 2008). Previous work from our lab and others has shown that ROS

generated during ethanol metabolism leads to ER stress (Ashraf and Sheikh 2015; Cederbaum

2010). Protein folding in the ER is dependent on a delicate redox balance in order to form the

disulfide bonds which are required for proper protein structure. By altering the redox balance in

the ER, oxidative protein folding is impaired (Hudson et al. 2015), leading to UPR induction to

mitigate the accumulation of unfolded proteins (Malhotra and Kaufman 2007). An important

insight into arsenic mediated pathology is the finding that iAs and its metabolic derivatives act

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as strong inhibitors of oxidative protein folding (Jacobson et al. 2012; O'Connell et al. 2014;

Sapra et al. 2015), bind to unfolded proteins (Ramadan et al. 2009), and that trivalent iAs

species directly prevent the proper folding of nascent peptides due to strong affinity for thiol

groups on cysteine residues (Ramadan et al. 2009; Watanabe and Hirano 2013). Our working

model (Figure 7) proposes that iAs exposure increases the unfolded protein load in the ER by

directly acting as a reducing agent, and indirectly by disrupting the redox balance in the ER

through ROS generated during iAs metabolism by As3mt. Given that our RNAseq analysis

found that a CYP450 enzyme that metabolizes ethanol in zebrafish (cyp2y3 (Tsedensodnom et

al. 2013)) is downregulated in response to iAs, it is unlikely that iAs treatment potentiates

ethanol metabolism; if anything, it may reduce it.

Our model suggests that iAs induces FLD by activating a pathological or “stressed” UPR

subclass (Howarth et al. 2014; Tsedensodnom et al. 2013; Vacaru et al. 2014; Wang and

Kaufman 2016). We speculate that some aspects of this stressed UPR are shared with the

response to ethanol. We demonstrated that Atf6 is necessary and sufficient for fatty liver in

zebrafish (Cinaroglu et al. 2011; Howarth et al. 2014), and since atf6 is one of the few genes

that is targeted by both iAs and ethanol, we speculate that FLD caused by iAs is mediated by

Atf6 activation. However, it is also possible that the unique aspects of the UPR which are

induced by iAs and by ethanol could create unique proteostatic environments that are only

minimally overlapping, as found in mammalian cells in culture (Shoulders et al. 2013).

Other work has suggested that iAs impacts mitochondrial function (Luz et al. 2016;

Santra et al. 2007), and our RNAseq analysis also highlighted mitochondrial dysfunction as a

response to iAs exposure. It is possible that mitochondrial damage in hepatocytes could reduce

lipid oxidation and cause lipid accumulation. Another interesting possibility is that

communication between the mitochondria and ER could impair the function of both of these

organelles if one is damaged. We found that ero1a, a component of mitochondrial-associated

ER membranes (MAMs) and a regulator of oxidative protein folding and ER redox homeostasis

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(Anelli et al. 2011; Benham et al. 2013; Seervi et al. 2013), is among the genes that are

significantly upregulated in both iAs and ethanol datasets. MAMs are key signaling centers that

act at the interface of mitochondria and the ER and are linked by their key functions in redox

homeostasis and calcium storage (Carreras-Sureda et al. 2017). Thus, it is possible that defects

in the function of multiple organelles contribute both to the ER stress and FLD phenotypes

caused by iAs exposure.

Other mechanisms proposed to mediate iAs toxicity – namely changes in DNA

methylation (Huang et al. 2004; Hughes 2002; Kile et al. 2012; Mauro et al. 2016) – were not

identified by our studies in zebrafish (not shown). In fact, there is nearly no overlap in the gene

expression changes induced by iAs and by mutants which have a defect in DNA methylation

(Chernyavskaya et al. 2017; Jacob et al. 2015) and our preliminary studies found neither an

impact on global DNA methylation nor synergy with mutants that have DNA methylation loss

(not shown). Thus, we conclude that oxidative and ER stress are the major mechanisms of iAs

hepatotoxicity.

By comparing the iAs and ethanol RNAseq datasets, we found several additional

enriched pathways that may contribute to the development of FLD. Both glycolysis and

gluconeogenesis pathways were enriched in both datasets and these pathways have previously

been demonstrated to be induced by iAs in the liver of guinea pigs and adult zebrafish (Li et al.

2016; Reichl et al. 1988). We speculate that these pathways are important for maintaining the

energetic balance required for efficient protein folding and hepatic metabolism, and that the

accumulation of lipids in hepatocytes of toxin-stressed cells may serve as an adaptive function

to store energy.

While our RNAseq analysis and other data provide evidence that iAs and ethanol are

converging on the same cellular pathways, it is important to note that there are differences in

the gene expression profiles in response to the two toxicants. It is therefore possible that the

cumulative effects of independent cellular responses are converging to yield the phenotypes

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analyzed in this study (i.e. FLD and death). The same zebrafish line Tg(fabp10a:nls-

mCherrymss4Tg) was used to generate both RNAseq datasets and consistency across sample

maintenance (i.e. light:dark cycle, culture conditions and time of collection) were maintained to

provide a basis for comparison. Moreover, qPCR analysis of additional clutches which were

treated in parallel confirmed that the gene expression changes detected by RNAseq were

reproducible.

An important finding from our work is that co-exposure to iAs and ethanol reduces the

expression of as3mt, which catalyzes the methylation of iAs, and results in an increase in the

total accumulation of arsenic in the liver. Polymorphisms in the human AS3MT gene are

predictive of arsenic metabolism across multiple study populations (Engstrom et al. 2011;

Engstrom et al. 2013). Indeed, reduced capacity for arsenic methylation has previously been

shown to correlate with adverse outcomes following arsenic exposure (Chen et al. 2013; Das et

al. 2016). Human genome wide association studies for mutations promoting arsenic

susceptibility identified an AS3MT haplotype that leads to reduced expression of AS3MT and

increased toxicity (Das et al. 2016). Recently it was shown that C57BL/6J mice are more

susceptible to arsenic-induced oxidative liver injury than 129X1/SvJ mice, and that this

difference is related to their reduced capacity for arsenic methylation (Wu et al. 2017). In

addition, one study found that alcohol use may decrease methylation of iAs (Hopenhayn-Rich et

al. 1996; Tseng 2009). Future research will seek to determine the mechanisms by which ethanol

reduces expression of as3mt.

While zebrafish are at the forefront of toxicology research (Bambino and Chu 2017;

Garcia et al. 2016), there are some limitations in the extension of this study to understanding the

effects of arsenic and alcohol on liver disease in humans. As with other experimental models,

translation of the results to the effects of human exposures are complicated by differences in

arsenic metabolism (Vahter 1999) and the doses used under laboratory conditions (States et al.

2011). The concentration of iAs used here surpasses the levels that are associated with disease

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in humans, suggesting that in this system where animals are immersed in iAs, low levels are not

acutely toxic, but instead may have an impact over longer term exposures. We have used

exposures on the low parts per million (ppm) range, whereas humans are typically exposed to

arsenic concentrations in the parts per billion (ppb) range, with a WHO standard of 10 ppb.

However, samples of drinking water from Argentina, Bangladesh, China, Taiwan, and the United

States have all been found to contain iAs at concentrations greater than 2mg L-1 (2 ppm)

(Naujokas et al. 2013), indicating the possibility of exposure at levels higher than previously

presumed. We examined the effect of arsenic exposure beginning just prior to gastrulation to

mimic the effects of early-life exposure; however, this does not completely recapitulate the

predominant route of human exposure, as the zebrafish do not begin to swallow water until 3

dpf.

Collectively, these data demonstrate that combined exposure to iAs and ethanol led to a

reduced survival of zebrafish larvae, enhanced induction of the UPR, and an increase in the risk

of fatty liver disease. Given the high conservation of common disease-related genes and

pathways required for disease between zebrafish and humans (Goessling and Sadler 2015), we

hypothesize that the mechanism of iAs-induced FLD and the cellular pathways targeted by both

toxicants will also be conserved. With the increasing global incidence of liver disease, the risk of

liver damage caused by iAs exposure may be more significant than previously presumed.

Materials and Methods

Zebrafish maintenance and treatment of embryos

Procedures were performed in accordance with the Icahn School of Medicine at Mount

Sinai Institutional Animal Care and Use Committee (IACUC). Adult wild type (WT; AB, Tab14

and TAB5) and Tg(fabp10a:nls-mCherrymss4Tg) (Mudbhary et al. 2014), fish were maintained on

a 14:10 light:dark cycle at 28oC. Fertilized embryos from natural spawning of group matings

were collected and cultured in embryo water (0.6 g/L Crystal Sea MarineMix; Marine Enterprises

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International, Baltimore, MD) containing Methylene Blue at 28oC. Embryos were treated with

sodium (meta)arsenite (Sigma, S7400) beginning at 4 hours post fertilization (hpf). Sodium

(meta)arsenite and/or ethanol were diluted from stock solutions in 10 mL of embryo water. After

addition of exposure medium, 35 mm dishes were sealed with Parafilm and returned to the

incubator. Medium was not replaced during the exposure period unless otherwise noted. For co-

exposures, sodium (meta)arsenite was removed and replaced with embryo water containing

sodium (meta)arsenite and tunicamycin at 72 hpf or sodium (meta)arsenite and ethanol at 96

hpf at the indicated concentrations. Images of anesthetized larvae were taken by mounting in

3% methyl cellulose using a Nikon SMZ1500 stereomicroscope.

Gene expression analysis by qRT-PCR

Livers were microdissected in from anesthetized 5 dpf zebrafish larvae that were

immobilized in 3% methyl cellulose using 30 gauge needles, and collected in 20 µL RLT Buffer

(Qiagen) and RNA was isolated by extraction in TRIzol Reagent (Life Technologies) as

described (Passeri et al. 2009). RNA (250 ng) was reverse transcribed using the SuperScript

cDNA synthesis kit (Quanta) per the manufacturer’s instructions. Quantitative Real Time PCR

(qRT-PCR) was performed using PerfeCTa SYBR Green Fast Mix (Quanta). Samples were run

in triplicate on the Roche LightCycler 480 (Roche), with least three independent samples

analyzed for each experiment. Target gene expression normalized to ribosomal protein large P0

(rplp0) using the comparative threshold cycle (ΔΔCt) method. Expression in treated animals

was normalized to untreated controls from the same clutch. Primer sequences are listed in

Table S1.

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mRNA sequencing (RNAseq)

Total RNA was extracted from livers dissected from 5 dpf Tg(fabp10a:nls-mCherrymss4Tg)

zebrafish larvae using the Zymo Quick-RNA Micro Kit (R1050, Zymo Research) per the

manufacturer’s instructions. RNA quality was determined by Agilent 2100 BioAnalyzer. RNAseq

libraries were prepared according to Illumina TruSeq RNA sample preparation version 2

protocol, and library quality was analyzed on the Agilent 2100 Bioanalyzer. cDNA libraries were

sequenced on the Illumina Hiseq 2500 platform to obtain 100-base pair paired-end reads.

Sequencing quality was assessed by using FASTQC (Andrews 2010) and reads were quality

trimmed using Trimmomatic (Bolger et al. 2014) to remove low Q scores, adapter contamination

and systematic sequencing errors. Reads were aligned to the Danio rerio GRCz10 reference

genome assembly with Tophat 2.0.9 (Trapnell et al. 2009). To estimate gene expression, read

counts were calculated by HTSeq with ensemble annotation (Aken et al. 2016; Anders et al.

2015; Trapnell et al. 2009). Normalization and test of differential expression using a generalized

linear model were implemented in DESeq2 (Gentleman et al. 2004; Love et al. 2014). Adjusted

p-value (FDR) <0.05 was treated as significantly different expression. We established a method

to identify “on-off” genes as those that were expressed in controls, but not in the experimental

condition or vice versa. These were designated as genes with read counts greater than or equal

to 20 in one condition and less than or equal to 5 in the other. RNAseq datasets were submitted

to Gene Expression Omnibus (GEO) with the access number GSE104953. RNAseq from livers

of Tg(fabp10a:nls-mCherrymss4Tg) larvae exposed to 2% ethanol from 96-132 hpf was previously

described ((Howarth et al. 2014); GSE56498) as were the unexposed 5 dpf controls,

GSE52605; (Mudbhary et al. 2014)). The data was realigned and reanalyzed for this study.

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Qualitative and quantitative assessment of iAs content in zebrafish larvae

Total iAs analysis was carried out by Inductively Coupled Plasma-Mass Spectrometry

(ICP-MS) on pools of 20 dissected livers from 5 dpf larvae in 20 μL deionized water followed by

0.5 ml of concentrated double distilled nitric acid. After an overnight digestion at room

temperature, samples were diluted to 5 mL and analyzed using ICP-MS (Agilent 8800-QQQ,

Wilmington, DE). iAs concentration was measured in MS/MS mode using oxygen as the cell gas

and tellurium as the internal standard. Quality control (QC) and quality assurance procedures

included analyses of procedural blanks and QC standards. Lab recovery rates for QC standards

with this method were 90 to 110% and <5% precision (given as %RSD). The limit of detection

for arsenic was 0.02 ng ml-1.

For tissue mapping by laser ablation (LA)-ICP-MS, larvae were washed with embryo

water and fixed in 4% paraformaldehyde (PFA) in phosphate buffered saline (PBS) overnight at

4°C. They were transferred to 30% sucrose in PBS and embedded in a 2:1 mixture OCT (Tissue

Tek):30% sucrose. Ten-micron thick cryosections sections were cut on a Leica CM3050S

cryostat and were thawed and warmed to room temperature prior to analysis.

A New Wave Research NWR-193 (ESI, USA) laser ablation unit equipped with a 193nm

ArF excimer laser was connected to an Agilent Technologies 8800 triple-quad ICP-MS (Agilent

Technologies, USA). Helium was used as carrier gas from the laser ablation cell and mixed with

argon via Y-piece before introduction to the ICP-MS. The system was tuned daily using NIST

SRM 612 (trace elements in glass) to monitor sensitivity (maximum analyte ion counts), oxide

formation (232Th16O+/232Th+, < 0.3%) and fractionation (232Th+/238U+, 100 ± 5%). The

laser was scanned across the tissue sections at 20 μm spot size, 40μm/s scan speed, 40Hz

repetition rate and approximately 0.2 J cm2 power. ICP-MS integration times for analytes were

adjusted so that total scan time was 0.5 seconds, maintaining the dimensions of the tissue in

data analysis. LA-ICP-MS operating parameters are given in Table S2.

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Lipid staining

Larvae were fixed in 4% PFA overnight at 4oC and stained with Oil Red O as previously

described (Passeri et al. 2009; Vacaru et al. 2014). Samples were blinded before scoring as

positive (presence of 3 or more lipid droplets per liver) or negative for steatosis. The average

steatosis incidence was calculated for at least 3 clutches per condition and on average, 15-20

larvae per condition per experiment were scored (Tables S3 and S6).

Statistical analysis

Data were analyzed using GraphPad Prism 7 software and interaction between iAs and

ethanol in steatosis was modeled in SAS version 9.4 (SAS Institute Inc., Cary, NC). Data are

expressed as mean ± standard deviation (SD). Differences between experimental groups were

analyzed by unpaired Student t test (with correction for multiple comparisons where applicable),

or by one-way analysis of variance (ANOVA) followed by Dunnet’s or Tukey post-hoc correction

when more than two groups were compared. P values <0.05 were considered statistically

significant unless otherwise noted. Differentially expressed genes from RNAseq data were

analyzed using a package DESeq2 in Bioconductor (Gentleman et al., 2004, Love MI 2014),

which embedded a generalized linear model for test of differential expression. Adjusted p-value

(FDR) <0.05 was treated as significantly differential expression.

Author Contributions

KB designed the study, performed experiments, analyzed data, and wrote the

manuscript. C Austin, C Amarasiriwardena, and CZ performed experiments, analyzed data, and

wrote the manuscript. MA supervised the research and edited the manuscript. JC designed the

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study, supervised the research, and edited the manuscript. KCS designed the study, supervised

the research, analyzed the data, and wrote the manuscript.

Acknowledgements

The authors would like to thank members of the Sadler and Chu laboratories for their close

reading of this manuscript and Dr. Jeanette Stingone for statistical expertise, Shikha Nayar,

Liam Gordon, Leonore Wunsche, and Priyanka Lakhiani for technical assistance, and Jill

Gregory for graphic design of our working model. We thank Dr. Christoph Buettner, Dr. Scott L.

Friedman, and Dr. Robert O. Wright for scientific input. We thank the CCMS staff at Icahn

School of Medicine at Mount Sinai for zebrafish facility maintenance.

Competing Interests

The authors have no competing or financial interests to disclose.

Funding

This work was funded by 5RO1AA018886 to KCS. T32 HD049311-09 and

P30ES023515 supported KB.

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Figures

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Figure 1. Exposure to iAs is toxic to zebrafish embryos. A) Survival analysis of zebrafish

treated with iAs from 4 hpf through 6 dpf. Fish were scored daily for mortality (n ≥ 2 clutches,

>80 embryos per condition, Table S3). Red arrow indicates addition of iAs. Concentration of iAs

used throughout the manuscript highlighted in red. B) Bright field images of representative wild

type control (top) and arsenic-exposed (bottom) 5 dpf zebrafish larvae. Arrows indicate arsenic-

induced phenotypes, including shortened body length, edema, clustering of pigment cells, under

consumption of yolk, and a small head (black arrows). Scale bar = 1000μm. C) Exposure to

increasing doses of iAs from 4 hpf to 5 dpf led to an accumulation of phenotypes. The

proportion of surviving embryos at 5 dpf that were affected increased with increasing

concentrations of iAs (n = 2 clutches exposed to 0.1 mM or 0.3 mM, n = 3 clutches exposed to

0.6 mM, 1.0 mM, or 1.4 mM, > 30 fish exposed per treatment condition, Table S3). hpf = hours

post fertilization, dpf = days post fertilization, iAs = inorganic arsenic.

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Figure 2. Zebrafish are capable of arsenic metabolism and accumulate iAs in their

tissues. A) Expression of the zas3mt transcript is dynamic during zebrafish development, as

determined by quantitative RT-PCR. zas3mt is maternally provided. Expression is enriched in

the liver at 120 hpf. Error bars correspond to mean +/- standard deviation. B) Representative

images of LA-ICP-MS analysis of 10 μm sections of control and iAs exposed larvae. Following

exposure from 4 hpf – 120 hpf, iAs accumulated in the eye (white arrows, white circle in

enlarged image), liver (yellow arrows, yellow circle in enlarged image), and in the gut (green

arrows, green circle in the enlarged image). Refer to Table S2 for operating parameters. C)

Quantification of total arsenic content in the livers of 5 dpf larvae by ICP-MS. Livers dissected

from larvae exposed to 0, 0.1, 0.5, and 1.0 mM iAs from 4 – 120 hpf showed a dose-dependent

increase in the total arsenic content per liver (n = 3 clutches). Error bars correspond to mean +/-

standard deviation. hpf = hours post fertilization; L = liver; C = carcass; LA-ICP-MS = laser

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ablation inductively-coupled plasma mass spectroscopy; iAs = inorganic arsenic; ICP-MS =

inductively-coupled plasma mass spectroscopy.

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Figure 3. Exposure to iAs causes steatosis in zebrafish larvae. A) Representative bright

field images of 5 dpf Oil Red O-stained control and iAs exposed (1.0 mM from 4 – 120 hpf). The

area around the liver (outlined in black) is enlarged. B) The percent of larvae with steatosis

analyzed by ORO staining of 15 clutches, with an average of 20 lavae per treatment per clutch.

The total number of larvae analyzed in each clutch is listed in Table S3. Statistical significance

was determined by unpaired, 2-tailed Student’s t test (n = 15 clutches, p < 0.001, Table S3).

Error bars correspond to mean +/- standard deviation.

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Figure 4. Exposure to iAs induces expression of genes involved in metabolic processes

and the UPR. MA plot of normalized gene expression in livers from larvae exposed to 1.0 mM

iAs from 4 - 120 hpf compared to unexposed siblings (A) and in livers from larvae exposed to

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2% ethanol from 96 - 132 hpf compared to unexposed siblings (B). p-values and fold-changes

for all significantly differentially expressed genes is included in Table S3. B) IPA analysis of

biological processes based on upregulated genes identified through RNAseq analysis. C) MA

plot of normalized gene expression in D) IPA of biological processes based on upregulated

genes identified through RNAseq analysis. E) Plot of genes significantly upregulated in both iAs

and ethanol datasets (upper right quadrant), upregulated in iAs dataset and downregulated in

ethanol dataset (lower right quadrant), downregulated in both iAs and ethanol datasets (lower

left quadrant), and upregulated in ethanol dataset and downregulated in iAs dataset (upper left

quadrant). F) IPA of biological processes based on upregulated genes in both iAs and ethanol

RNAseq datasets. iAs = inorganic arsenic; IPA = Ingenuity Pathway Analysis.

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Figure 5. Arsenic and ethanol regulate common cellular pathways. A) Plot of UPR-

associated genes expression in iAs and ethanol RNAseq datasets. B) Heat map of expression

of 103 significantly differentially regulated UPR genes. Refer to Table S4 for p-values and fold-

changes. iAs = inorganic arsenic.

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Figure 6. Arsenic potentiates alcohol-induced liver disease in zebrafish larvae. A) Survival

of zebrafish larvae at 120 hpf. Zebrafish larvae were exposed to a range of concentrations of

iAs and/or ethanol. Survival was assessed at 120 hpf. Statistical significance was determined by

unpaired, 2-tailed Student’s t test, correcting for multiple comparisons (n = 3 clutches, p <

0.001). Data are presented as mean +/- standard deviation. B) Quantitative real-time

polymerase chain reaction data from liver cDNA. Data are presented as fold-change versus

control. Statistical significance was determined by one-way ANOVA (n = 5 clutches, bip: 0.5%

ethanol vs. 0.5 mM iAs + 0.5% ethanol p = 0.0072, 0.5 mM iAs vs. 0.5 mM iAs + 0.5% ethanol p

= 0.078; chop: 0.5% ethanol vs. 0.5 mM iAs + 0.5% ethanol p = 0.0021, 0.5 mM iAs vs. 0.5 mM

iAs + 0.5% ethanol p = 0.0008; atf6: 0.5% ethanol vs. 0.5 mM iAs + 0.5% ethanol p = 0.0205,

0.5 mM iAs vs. 0.5 mM iAs + 0.5% ethanol p = 0.0241). C) Quantitative real-time polymerase

chain reaction data from liver cDNA. Data are presented as fold-change versus control.

Statistical significance was determined by one-way ANOVA (n = 5 clutches, 0.5% ethanol vs.

0.5 mM iAs + 0.5% ethanol p = 0.0013, 0.5 mM iAs vs. 0.5 mM iAs + 0.5% ethanol p = 0.0158).

D) Quantification of total arsenic content in the livers of 5 dpf larvae by liquid ICP-MS. Statistical

significance was determined by one-way ANOVA (n = 6 clutches, 0.5 mM iAs vs. 0.5 mM iAs +

0.5% ethanol p = 0.0003). E) Steatosis incidence in 120 hpf larvae exposed to 0.5 mM iAs,

0.5% ethanol, and 0.5 mM iAs + 0.5% ethanol. Statistical significance was determined by one-

way ANOVA (n = 7 clutches, 0.5% ethanol vs. 0.5 mM iAs + 0.5% ethanol p = 0.0025; 0.5 mM

iAs vs. 0.5 mM iAs + 0.5% ethanol p = 0.0172). Error bars in all panels correspond to mean +/-

standard deviation.

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Figure 7. Model of the mechanism of iAs and ethanol interacting to cause ER stress.

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Table 1. Summary of gene expression changes in RNAseq datasets.

1.0 mM iAs vs. control up regulated genes down regulated genes Total

padj<0.05&LFC2>0 2629 2489 5118

padj<0.05&LFC2>2 537 412 949

on-off 186 on in iAs 214 on in siblings

2% ethanol vs. control up regulated genes down regulated genes Total

padj<0.05&LFC2>0 619 475 1094

padj<0.05&LFC2>2 302 178 480

on-off 153 on in 2%ethanol 65 on in 0%ethanol

Overlap up regulated genes down regulated genes Total

padj<0.05&LFC2>0 215 264 479

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Table S1. qRT-PCR primer sequences.

Primer Name Forward Sequence (5’ 3’) Reverse Primer (5’ 3’)

zrplp0 CTGAACATCTCGCCCTTCTC TAGCCGATCTGCAGACACAC

zbip AAGAGGCCGAAGAGAAGGAC AGCAGCAGAGCCTCGAAATA

zchop AAGGAAAGTGCAGGAGCTGA TCACGCTCTCCACAAGAAGA

zdnajc3 TCCCATGGATCCTGAGAGTC CTCCTGTGTGTGAGGGGTCT

zedem1 ATCCAAAGAAGATCGCATGG TCTCTCCCTGAAACGCTGAT

zatf4 TTAGCGATTGCTCCGATAGC GCTGCGGTTTTATTCTGCTC

zatf6 CTGTGGTGAAACCTCCACCT CATGGTGACCACAGGAGATG

zxbp1s TGTTGCGAGACAAGACGA CCTGCACCTGCTGCGGACT

zxbp1t GGGTTGGATACCTTGGAAA AGGGCCAGGGCTGTGAGTA

zas3mt ACTTTATGGGGCGAGTGCCT AGAGTCGGTATGTGGCAGAC

Table S2. LA-ICP-MS operating parameters.

NWR-193 Laser Conditions Agilent 8800 ICP-MS Conditions

Wavelength (nm) 193 RF power (W) 1350

Helium carrier flow (L min-1) 0.8 Argon carrier flow (L min-1) 0.6

Fluence (J cm-2) 0.2 Plasma gas flow (L min-1) 15

Repetition rate (Hz) 40 Sample Depth (mm) 4.0

Spot size (μm) 20 Scan mode Peak hopping

Scan speed (μm s-1) 40 Integration time (ms) 50 – 55

Disease Models & Mechanisms 11: doi:10.1242/dmm.031575: Supplementary information

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Table S3. Number of larvae analyzed per experiment for Figures 1 through 3.

Table S4. Gene expression analysis from livers of 120 hpf larvae exposed to 1 mM iAs or 2% EtOH. All genes identified in the iAs and EtOH RNA-seq datasets with those significantly overexpressed (red) or downregulated (blue) compared to unexposed siblings highlighted.

Table S5. UPR gene expression analysis from livers of 120 hpf larvae exposed to 1 mM iAs or 2% EtOH. All genes identified in the iAs and EtOH RNA-seq datasets with those significantly overexpressed or downregulated compared to unexposed siblings in one or both datasets.

Table S6. Number of larvae analyzedfor steatosis

Click here to Download Table S3

Click here to Download Table S4

Click here to Download Table S5

Click here to Download Table S6

Disease Models & Mechanisms 11: doi:10.1242/dmm.031575: Supplementary information

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Disease Models & Mechanisms 11: doi:10.1242/dmm.031575: Supplementary information

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Supplemental Figure 1. Early-life exposure to iAs causes toxicity in zebrafish. A)

Calculation of LC50 at 6 dpf. B) Time course of removal of 2.0 mM iAs. C) The proportion

of surviving embryos at 5 dpf that were affected increased with increasing

concentrations of iAs (n = 2 clutches exposed to 0.1 mM or 0.3 mM, n = 3 clutches

exposed to 0.6 mM, 1.0 mM, or 1.4 mM, > 30 fish exposed per treatment condition,

Table S3). Data from individual clutches presented in Figure 1C.

Disease Models & Mechanisms 11: doi:10.1242/dmm.031575: Supplementary information

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Supplemental Figure 2. Zebrafish embryos and larvae express the trivalent arsenic

specific methyltransferase. A) Expression of the as3mt transcript is dynamic during

zebrafish development, as determined by reverse-transcription polymerase chain

reaction. zas3mt is maternally provided and zygotic expression begins by 24 hpf.

Expression is enriched in the liver at 120 hpf. B) Expression of as3mt during the first five

days of zebrafish development was mined from Array Express.

Disease Models & Mechanisms 11: doi:10.1242/dmm.031575: Supplementary information

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Supplemental Figure 3. Comparison of iAs and ethanol RNAseq datasets. A)

Correlation between control samples in iAs and ethanol RNAseq show high similarity in

gene expression between these two datasets. B) Expression levels of UPR genes are

normally and uniformly distributed in iAs and ethanol RNAseq datasets.

Disease Models & Mechanisms 11: doi:10.1242/dmm.031575: Supplementary information

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Supplemental Figure 4. Exposure to iAs induces the UPR. A) Quantitative real-time polymerase chain reaction data from liver cDNA. Statistical significance was determined by unpaired, 2-tailed Student’s t test (n = 9 clutches, p < 0.01). Data are presented as mean, with minimum to maximum. B) Survival of zebrafish larvae at 120 hpf. Zebrafish larvae were exposed to iAs and a dose curve of tunicamycin (0, 1, 2, 3 µg/mL). Survival was assessed at 120 hpf. UPR = unfolded protein response; hpf = hours post fertilization; iAs = inorganic arsenic.

Disease Models & Mechanisms 11: doi:10.1242/dmm.031575: Supplementary information

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