Zebrafish as a Platform for Drug Screening

C H A P T E R

51 Zebrafish as a Platform for Drug Screening Tejia Zhang, Randall T. Peterson College of Pharmacy, University of Utah, Salt Lake City, UT, United States of America

Introduction Since the first demonstrated use of live zebrafish for chemical screening in 96-well format in 2000 (Peterson, Link, Dowling, & Schreiber, 2000), zebrafish chemical screens have expanded significantly to encompass a wide range of fish models, targeted pathways and phenotypic readouts (Rennekamp & Peterson, 2015). In the context of chemical screening, the zebrafish offers unique advantages, including rapid development, high fecundity, and small size, and optical transparency at the larval stage. These attributes allow highthroughput screening with larvae in 96- or 384-well plate format, and imaging-based readouts (Rennekamp & Peterson, 2015). In this chapter, we review chemical screening in the zebrafish model organism; we begin with a statistical overview of zebrafish chemical screens conducted since 2000, followed by more detailed discussions that address specific screens based on their areas of focus. We conclude by highlighting a few screens with significant clinical implications and bring to attention some of the current limitations and novel approaches toward addressing these limitations for future studies.

Zebrafish Chemical Screening, a Statistical Overview A survey of the existing literature between 2000 and June 2017 (Ncbi Resource Coordinators, 2017) uncovered 114 studies involving zebrafish chemical screening; while we highlight a number of these studies in this chapter, we do not claim this list to be exhaustive and apologize for any omissions made. Of the 114 studies identified, 56 focus on specific tissues to identify modulators of organogenesis or rescuers of tissue-specific pathologies (Fig. 51.1A and D) (Alvarez et al., 2009; Buckley et al., 2010; Chiu, Cunningham, Raible, Rubel, & Ou, 2008; Crawford et al., 2011; de Vrieze et al., 2015; The Zebrafish in Biomedical Research https://doi.org/10.1016/B978-0-12-812431-4.00051-8

Fleming, Sato, & Goldsmith, 2005; Hirose, Simon, & Ou, 2011; Huang, Lindgren, Wu, Liu, & Lin, 2012; Kitambi, McCulloch, Peterson, & Malicki, 2009; Lam et al., 2012; Lake, Tusheva, Graham, & Heuckeroth, 2013; Liang et al., 2015; Oppedal & Goldsmith, 2010; Papakyriakou et al., 2014; Sun, Dong, Khodabakhsh, Chatterjee, & Guo, 2012; Tran et al., 2007; Wang et al., 2010) (Asimaki et al., 2014; Choi et al., 2013; Coffin, Williamson, Mamiya, Raible, & Rubel, 2013; Gallardo et al., 2015; Kannan & Vincent, 2012; Leet et al., 2014; Liu et al., 2014; Milan, Peterson, Ruskin, Peterson, & MacRae, 2003; Namdaran, Reinhart, Owens, Raible, & Rubel, 2012; Ni et al., 2011; North et al., 2007; Ou et al., 2009; Owens et al., 2008; Peal et al., 2011; Shimizu et al., 2015; Tang, Xie, & Feng, 2015; Thomas et al., 2015; Vlasits, Simon, Raible, Rubel, & Owens, 2012; Yozzo, Isales, Raftery, & Volz, 2013; Yang et al., 2015), (Arulmozhivarman et al., 2016; Astin et al., 2014; Cao et al., 2009; Colanesi et al., 2012; de Groh et al., 2010; Garnaas et al., 2012; Hultman, Scott, & Johnson, 2008; Kawahara et al., 2011, 2014; Ko et al., 2016; Shafizadeh, Peterson, & Lin, 2004; Tamplin et al., 2015; Waugh et al., 2014; Westhoff et al., 2013; White et al., 2011; Yeh et al., 2009; Yeh & Munson, 2010; Yin, Evason, Maher, & Stainier, 2012; Zhen et al., 2013). Twelve studies use zebrafish in metabolic screens (Fig. 51.1A,B). The emergence of behaviors, such as eye movement, light response, and food seeking within the first week of development has enabled high-throughput behavioral screening in zebrafish larvae (Kalueff et al., 2013), and 10 such studies were identified by our search (Fig. 51.1B). Several screens have also been designed to target the inflammatory response (Hall et al., 2014; Liu et al., 2013; Robertson et al., 2014; Wang et al., 2014; Wittmann et al., 2015; Ye et al., 2017), toxin metabolism (Dimri et al., 2015; Jin et al., 2013; Legler et al., 2011; Nath et al., 2013; North et al., 2010; Padilla et al., 2012), and a diverse set of signaling pathways (Fig. 51.1A and C) (Gebruers et al., 2013; Hao et al., 2013; Le et al., 2013; Molina et al., 2009; Molina, Watkins, & Tsang, 2007;

659

© 2020 Elsevier Inc. All rights reserved.

660

51. Zebrafish as a Platform for Drug Screening

FIGURE 51.1 17 years of zebrafish chemical screening. (A) Zebrafish chemical screens by category, 2000e2017. (B) Metabolism-based zebrafish chemical screens. (C) Zebrafish chemical screens focusing on signaling pathways. (D) Tissue-specific zebrafish chemical screens.

Robertson et al., 2014; Torregroza, Evans, & Das, 2009; Weger, Weger, Nusser, Brenner-Weiss, & Dickmeis, 2012; Williams et al., 2015; Yu et al, 2008a, 2008b). Fifty five studies rely on wildtype zebrafish (Astin et al., 2014; Bouwmeester et al., 2016; Chiu et al., 2008; Coffin et al., 2013; Colanesi et al., 2012; Challal et al., 2014; Das, McCartin, Liu, Peterson, & Evans, 2010; de Groh et al., 2010; Fleming et al., 2005; Garnaas et al., 2012; Hirose et al., 2011; Kannan & Vincent, 2012; Kokel et al., 2010; Laggner et al., 2012; Lake et al., 2013; Li, Huang, Huang, Du, & Huang, 2012; Long et al., 2014; Lu et al., 2013; Maximino et al., 2014; Mendelsohn et al., 2006; Milan et al., 2003; Morash et al., 2011; Nath et al., 2015; North et al., 2007; Oppedal & Goldsmith, 2010; Ou et al., 2009; Owens et al., 2008; Peterson et al., 2000; Rahn et al., 2014; Rennekamp et al., 2016; Rihel et al., 2010; Sandoval et al., 2013; Sun et al., 2012; Tamplin et al., 2015; Tang et al., 2015; Thomas et al., 2015; Thorsteinson et al., 2009; Vlasits et al., 2012; Wang et al.,

2014; White et al., 2011; Zhen et al., 2013), 50 use transgenic lines (Alvarez et al., 2009; Andersson et al., 2012; Arulmozhivarman et al., 2016; Asimaki et al., 2014; Buckley et al., 2010; Choi et al., 2013; Crawford et al., 2011; de Vrieze et al., 2015; Gallardo et al., 2015; Gut et al., 2013; Gutierrez et al., 2014; Hall et al., 2014; Huang et al., 2012; Jimenez et al., 2016; Kitambi et al., 2009; Ko et al., 2016; Lam et al., 2012; Le et al., 2013; Leet et al., 2014; Li et al., 2015; Li et al., 2016; Li, Page-McCaw, & Chen, 2016; Liang et al., 2015; Liu et al., 2013; Liu et al., 2014; Molina et al., 2007; Molina et al., 2009; Namdaran et al., 2012; Ni et al., 2011; North et al., 2010; Papakyriakou et al., 2014; Raftery, Isales, Yozzo, & Volz, 2014; Robertson et al., 2014; Ridges et al., 2012; Rovira et al., 2011; Shafizadeh et al., 2004; Tran et al., 2007; Tsuji et al., 2014; Wang et al., 2010; Wang et al., 2014; Wang et al., 2015; Weger et al., 2012; Westhoff et al., 2013; Wittmann et al., 2015; Ye et al., 2017; Yeh & Munson, 2010; Yeh et al., 2009; Yin et al., 2012; Yozzo et al., 2013 ), and nine (Baraban, Dinday,

V. Scientific Research

Zebrafish Chemical Screening, a Statistical Overview

& Hortopan, 2013; Cao et al., 2009; Hultman et al., 2008; Kawahara et al., 2011; Kawahara et al., 2014; Paik, de Jong, Pugach, Opara, & Zon, 2010; Peal et al., 2011; Shimizu et al., 2015; Waugh et al., 2014) use mutant models (Fig. 51.2A), with the majority of studies focusing on larvae before eight days-post-fertilization (dpf), and four studies on adult zebrafish (Fig. 51.2B). (de Vrieze et al., 2015; Li et al., 2015; Maximino et al., 2014; Oppedal & Goldsmith, 2010). The majority of transgenic zebrafish encode fluorescent proteins (with GFP and its variants being the most common) for cell type-specific visualization: nine out of the nine angiogenesis screens use fli1or flik1-driven reporter lines that fluorescently label the entire vasculature (Alvarez et al., 2009; Crawford et al., 2011; Huang et al., 2012; Kitambi et al., 2009; Lam et al., 2012; Liang et al., 2015; Papakyriakou et al., 2014; Tran et al., 2007; Wang et al., 2010); and five out of the six

FIGURE 51.2 Zebrafish in chemical screening. (A) Types of zebrafish models for chemical screening, 2000e2017. (B) Age distribution of zebrafish screened. Studies with unclear or undesignated fish age were excluded; a few studies included screens in multiple age groups. t ¼ age of zebrafish.

661

inflammation screens use neutrophil-specific reporter lines with lyz- or mpx-driven fluorescence (Hall et al., 2014; Liu et al., 2013; Robertson et al., 2014; Ye et al., 2017; Wang et al., 2014). Three studies rely on luminescence (luciferase)-based reporters (Asimaki et al., 2014; de Vrieze et al., 2015; Weger et al., 2012). Five studies use zebrafish carrying human oncogenes or additional human mutations of interest (Asimaki et al., 2014; Gutierrez et al., 2014; Le et al., 2013; Yeh & Munson, 2010; Yeh et al., 2009), and two studies use nitroreductase-expressing systems for tissue-specific ablation (Andersson et al., 2012; Ko et al., 2016), with or without additional fluorescent or luminescent reporters to facilitate tissue visualization. All nine mutant zebrafish lines used in screening were identified from forward genetic screens (Baraban et al., 2013; Cao et al., 2009; Hultman et al., 2008; Kawahara et al., 2011; Kawahara et al., 2014; Paik et al., 2010; Peal et al., 2011; Shimizu et al., 2015; Waugh et al., 2014). While forward genetics has contributed significantly toward the availability of zebrafish mutants for chemical screening, recent advancements in genome editing technologies, such as TALENS (Hwang, Peterson, & Yeh, 2014; Zu et al., 2013) and CRISPR-Cas9 (Gagnon et al., 2014; Liu et al., 2017) in zebrafish point toward a likely rise in targeted model generation, and pave the way for future chemical screens in new models. Approximately half of the 114 screens use commercially available libraries, while another 20% rely on academic and government sources (Fig. 51.3A). Approximately 6% of screens are performed with extracts from plants, fungi or soil rather than purified compounds (Fig. 51.3A). 1000e2000 is the most widely used compound range, with the largest screens falling within the 10,000e30,000 range (Fig. 51.3B). A number of studies were conducted with a relatively small number of compounds (<25), and we have included these in our data as they often serve as proof-of-concept studies toward the execution of larger screens (Fig. 51.3B). The top 10 most frequently used screening libraries are listed in Fig. 51.3C, and include both commercial sources and collections from the NIH and EPA. The top three most commonly used libraries contain FDA-approved drugs, natural products, and additional pharmacologically relevant compounds, providing a wide range of structures for chemical screening (Rennekamp & Peterson, 2015). More category-based libraries, such as the Enzo SCREEN-WELL Nuclear Receptor Ligands library, could be selected for screens targeting specific pathways. It is also worth noting that many screening libraries have been formatted to include control wells and be compatible with robotic liquid handling systems, thus allowing direct transfer of contents into a working plate for screening.

V. Scientific Research

662

51. Zebrafish as a Platform for Drug Screening

Peterson, 2015). While the lack of target information could prove detrimental toward compound optimization for therapeutic development, correlation of compoundinduced phenotypes with those of established mutant lines may aid in elucidation of the mechanism of action (Mendelsohn et al., 2006; Sandoval et al., 2013). Additional biochemical and analytical approaches, such as affinity-based pull-down, crosslinking, and proteomics could also shed light on the pathways perturbed by the compound of interest (Rennekamp & Peterson, 2015). We highlight the examples of zebrafish chemical screens in the following sections.

Metabolic Screens

FIGURE 51.3 Chemical screening libraries. (A) Compound libraries by category, 2000e2017. (B) Distribution of number of compounds tested in screens; a number of studies employed multiple libraries, studies with ambiguous or undesignated compound source were excluded. s ¼ number of compounds used in screen. (C) Top 10 most frequently used compound libraries.

Zebrafish Chemical Screens by Category Zebrafish chemical screens have evolved over the past 17 years to encompass a wide range of biological processes (Fig. 51.1A). (Rennekamp & Peterson, 2015) The vast majority of these studies are phenotypedriven rather than target-driven, where hit compounds are identified based on downstream biological responses in the live, vertebrate zebrafish; this approach confers several advantages, such as the ability to identify hits even in the absence of known target or mechanism of action, and the inclusion of multiple targets that could boost the efficiency of drug discovery (Rennekamp &

Implementation of zebrafish in metabolic studies is aided by conservation of key nodes of metabolic regulation across zebrafish and mammals (Keatinge et al., 2015; Peal et al., 2011; Seth, Stemple, & Barroso, 2013). While the poikilothermic nature and still undiscovered existence of brown adipose tissue in zebrafish limit the study of thermogenesis in this organism, the preservation of key aspects of appetite regulation, lipid storage and insulin-sensitive tissues, has contributed to a wealth of studies in these areas (Schlegel & Gut, 2015; Seth et al., 2013). The zebrafish pancreas, compartmentalized into endocrine and exocrine portions, is one of the most extensively studied organs in the context of metabolism, which is also reflected in the focus of the majority of zebrafish metabolic screens on pancreatic b-cells (Fig. 51.1B) (Seth et al., 2013; Schlegel & Gut, 2015). Zebrafish metabolic screens employ a noteworthy set of fluorescent reporters. The Tg(tp1:hmgb1-mCherry); Tg(pax6b:GFP) line was used in one of the earliest zebrafish b-cell screens (Rovira et al., 2011). This doubly transgenic system, consisting of mCherry-labeled Notch-responsive cells and GFP-labeled endocrine cells, enabled screening for inducers of secondary islet formation while also monitoring for potential adverse effects on Notch signaling (Rovira et al., 2011). This approach identified six candidate compounds, with mechanisms of action, including inhibition of GTP production and retinoic acid biosynthesis (Rovira et al., 2011). Another labeling technology implemented in zebrafish screens is the fluorescent ubiquitination-based cell cycle indicator (FUCCI), which uses dual fluorescent probes of oscillating cell cycle regulatory proteins to track phasespecific proliferation (Zielke & Edgar, 2015). Zebrafish larvae expressing mAG-zGeminin (fluorescent S/G2/M phase marker) under the insulin promoter has been used to screen for enhancers of b-cell proliferation (Tsuji et al., 2014). Importantly, it is also possible to incorporate additional dietary manipulations into transgenic larvae

V. Scientific Research

Zebrafish Chemical Screens by Category

prior to chemical screening; Li et al. established an overnutrition model in b-cell-specific transgenic zebrafish by feeding the larvae chicken egg yolk to induce compensatory b-cell proliferation; screening in this model identified FGF1 signaling as a key component of the overnutrition-induced b-cell proliferation response (Li et al., 2016). Additional transgenic models for metabolic screening include the nitroreductase system (Andersson et al., 2012), and a transgenic reporter for gluconeogenesis (Gut et al., 2013). In the Tg(ins:CFP-NTR); Tg(ins:Kaede) line, insulin promoter drives expression of nitroreductase and Kaede fluorescent protein, allowing b-cell-specific ablation by metronidazole, and screening for enhancers of b-cell regeneration via increased Kaede fluorescence (Andersson et al., 2012). This approach identified the small molecule NECA as a promoter of b-cell regeneration through the adenosine receptor A2aa, an effect that was replicated in mice (Andersson et al., 2012). The transgenic zebrafish Tg(pck1:Luc2) expresses luciferase under the promoter of the fasting-inducible gluconeogenesis gene pck1; chemical screening in this model identified two compounds that raised pck1 expression while lowering glucose, one of which improved the metabolic parameters in diet-induced obese mice (Gut et al., 2013). As zebrafish chemical screens become fine-tuned to address increasingly complex biological questions, a similar development has taken place in highthroughput technologies for the examination of downstream phenotypic outputs. As an example, a 2016 screen conducted by Wang et al. to identify modulators of b-cell mass automated the entire screening process through automated reporter quantification in vivo (ARQiv), which included a microplate reader setup for high-throughput fluorescence quantification in live larvae, real-time data analysis, and robotic liquid handling and sorting systems for larva and compound transfer (Wang et al., 2015). Additional bioenergetic profiling methods, such as colorimetric detection of acid secretion from individual larva (Makky, Duvnjak, Pramanik, Ramchandran, & Mayer, 2008), and measurement of larval oxygen consumption rate via flux analyzer (Stackley, Beeson, Rahn, & Chan, 2011; Kumar et al., 2016), have been achieved for either 96- or additional multiwell formats. Fluorescence-based glucose detection kit has been used in a zebrafish chemical screen for modulators of glucose level (Nath et al., 2015), and the rise in omics-based technologies, such as high-throughput metabolomics supports a widening in the repertoire of measurable endpoints to include metabolic profiles in addition to imaging-based readouts (Li et al., 2016; Wang et al., 2017). Efforts have also been directed toward optimization of fluorescent chemical probes to track metabolite uptake to complement the rich set of transgenic zebrafish models

663

for metabolic screening. Two of the probes optimized for zebrafish larvae are the BOPIDY-labeled C5 fatty acid analog PED-6 (Clifton et al., 2010) and the fluorescent glucose analog 2-NBDG (Lee et al., 2013). Incubation with compounds followed by PED-6 addition in a chemical screen identified inhibitors of intestinal lipid absorption with potential pharmacological applications in cardiovascular disease (Clifton et al., 2010). 2-NBDG is taken up by zebrafish larvae in a time-dependent manner as visualized by increased fluorescence in the GLUT receptor-rich eye (Lee et al., 2013); this model was screened against selected compounds and plant-based fractions, leading to discovery of a triazine-based compound as a potential insulin-mimetic (Lee et al., 2013). Additional zebrafish metabolic screens have focused on metal homeostasis (Li et al., 2016; Mendelsohn et al., 2006; Sandoval et al., 2013). Iron homeostasis in vertebrates is regulated by the hepcidin/ferroportin axis, defects in which cause iron deficiency or overload (Li et al., 2016). A recent zebrafish screen identified three steroids that lowered ferroportin level by increasing hepcidin biosynthesis, an effect that was recapitulated in mice and humans (Li et al., 2016). A screen for modulators of copper homeostasis identified the copper chelator neocuproine, which caused progressive appearance of phenotypes from pigmentation loss to wavy notochord and enlarged brain ventricle with increasing treatment time or dosage, supporting a role for copper metabolism in notochord development; a forward genetic screen identified the mutant calamity that phenocopied these copper deficiency-induced defects (Mendelsohn et al., 2006). Importantly, a separate chemical screen conducted several years later revealed that treatment of zebrafish larvae with kalihinol F, a diterpenoid originally isolated from a marine sponge, resulted in calamity-like phenotypes, and led to the discovery of kalihinol F’s mechanism of action as a copper chelator (Sandoval et al., 2013). These studies demonstrate the ability to identify novel biological pathways and mechanisms of action for tested compounds through a combination of chemical and forward genetic screens.

Behavioral Screens Zebrafish larvae have proven to be highly amenable to behavioral screening due to small size and early emergence of screenable behaviors (Kalueff et al., 2013). Within the first week of development, zebrafish larvae display a range of environment-triggered behaviors, such as eye tracking, threat responses, and food seeking (Kalueff et al., 2013). Zebrafish between 30 and 42 hpf demonstrate a reproducible pattern of mobile and immobile behaviors in response to pulses of light, a phenomenon termed the photomotor response (PMR)

V. Scientific Research

664

51. Zebrafish as a Platform for Drug Screening

(Kokel & Peterson, 2011). While the purpose of the PRM is undefined, the reproducibility, detectability, and scalability associated with this behavior have resulted in its inclusion in several screens (Kokel & Peterson, 2011). A chemical screen in seven dpf larvae was conducted by Rennekamp et al. to identify modifiers of freezing behavior in response to a strobe light, yielding three candidate classes of compounds that shifted freezing to escape (Rennekamp et al., 2016). In vitro binding and CRISPR-Cas9 knockout studies identified s1 receptor binding as the mechanism of action for the finazine class of compounds, and impaired freezing was also detected in a finazine-treated mouse fear model (Rennekamp et al., 2016). These findings implicate novel pathways underlying the decision between passive and active threat responses and suggests potential therapeutic targets for psychiatric disorders, in which, these responses are dysregulated (Rennekamp et al., 2016). While the study of behavior in zebrafish may still be considered as an emerging field, past and recent findings of the ability of zebrafish to develop addiction (Bosse´ & Peterson, 2017), respond to psychotropic drugs, and navigate behavioral assays support conservation of key aspects of neurocircuitry between zebrafish and mammalian models (Kalueff, Stewart, & Gerlai, 2014). Treatment of zebrafish larvae with the common convulsant and GABAA antagonist pentylenetetrazol (PTZ) leads to behavioral and biochemical changes consistent with rodent seizure models (Baraban, Taylor, Castro, & Baier, 2005). Chemical screens in the zebrafish PTZ model have yielded several compounds, including vitamin K3 derivatives (Rahn et al., 2014), and plant and marine natural products (Challal et al., 2014; Long et al., 2014) as potential anticonvulsants. A zebrafish model of epilepsy was discovered in a chemical mutagenesis screen (Schoonheim, Arrenberg, Del Bene, & Baier, 2010), and carries a mutation in the sodium-gated ion channel Nav1.1 (scn1Lab) (Baraban et al., 2013). Small molecule screening in scn1Lab zebrafish identified clemizole as a seizure suppressant (Baraban et al., 2013), and paved the way for testing of the compound lorcaserin in a clinical trial (Griffin et al., 2017). Given the multidimensionality of zebrafish behaviors in response to characterized and uncharacterized compounds, behavior barcoding has emerged as a method for behavior categorization and target prediction (Rennekamp & Peterson, 2015). By monitoring larval behaviors in a chemical screen, and performing hierarchical clustering of the recorded behavioral barcode corresponding to each tested compound, it was shown that compounds with similar biological targets often fall into the same phenocluster, thus making it possible to predict targets for uncharacterized compounds clustering with those with known modes of action (Kokel et al., 2010; Rihel et al., 2010). This approach was adapted by

Rihel et al. (2010) and Kokel et al. (2010) toward sleep/ wake and PMR behavioral data in response to psychotropic compounds. Hierarchical clustering yielded phenoclusters of compounds with similar known targets and identified previously unknown protein functions and novel small molecule modulators of known pathways (Kokel et al., 2010; Rihel et al., 2010). Clustering analysis has since been adapted toward additional screens with various behavioral outputs and compound types (Maximino et al., 2014; Wang et al., 2014). In a significant expansion of previous behavioral readouts, Bruni et al. tested 10 acoustic and/or visual stimulus-based behaviors against 14 antipsychotic, antidepressant or anxiolytic drugs, with data clustering demonstrating class-specific effects (Bruni et al., 2016). The behavioral signature from the antipsychotic haloperidol was further screened against 24,760 compounds, identifying a number of hits with haloperidol-like phenotypic profiles and in vitro receptor binding properties; the compound finazine reduced locomotion in a psychostimulantinduced schizophrenia mouse model (Bruni et al., 2016). This last study is worth noting for its demonstration of the resolution of complex zebrafish behavior barcodes in distinguishing different psychotropic drugs and recalling compounds with potentially shared mechanisms of action; this approach could prove useful toward the identification of novel psychotropics as therapeutics.

Selected Tissue-Specific Screens 56 out of the 114 zebrafish chemical screens focus on specific tissues and rely heavily on fluorescence or luminescence-based reporters for visualization following compound treatment. We highlight screens on heart, lateral line, and tissue-specific disease models in the following sections. Heart The zebrafish heart is a two-chambered organ consisting of a single atrium and ventricle (Asnani & Peterson, 2014). Electrophysiological studies demonstrate close resemblance in the shape of zebrafish ventricle action potentials to those of humans, with a conserved plateau phase that is not recapitulated in mice (Nemtsas, Wettwer, Christ, Weidinger, & Ravens, 2010; Vornanen & Hassinen, 2016). Compounds that are known to induce repolarization defects in humans also consistently cause bradycardia in zebrafish (Milan et al., 2003). In the context of chemical screening, the zebrafish heart confers several advantages, including small size, fairly rapid development, and optical transparency that allows high-throughput imaging and quantification of cardiac parameters (Asnani & Peterson, 2014; Rennekamp & Peterson, 2015). Zebrafish larvae are able to oxygenate

V. Scientific Research

Zebrafish Chemical Screens by Category

through diffusion alone during early development, and adult zebrafish heart regenerates following partial ventricle amputation (Zhao et al., 2014); these unique qualities allow regeneration studies and modeling of severe cardiomyopathy phenotypes that would otherwise be embryonically lethal (Asnani & Peterson, 2014). Cardiovascular screens in the zebrafish employ a number of disease models (Asimaki et al., 2014; Peal et al., 2011; Shimizu et al., 2015). The zebrafish Kcnh2 mutant (breakdance) faithfully reproduces key aspects of human genetic long QT syndrome, a life-threatening disorder of prolonged cardiac repolarization caused predominantly by failed membrane trafficking of KCHN2 ion channel proteins (Milan et al., 2003; Peal et al., 2011). A small-molecule screen in this model identified flurandrenolide, a steroid that suppressed prolonged cardiac repolarization by acting through the glucocorticoid receptor, a mechanism distinct from trafficking rescue of defective ion channels (Peal et al., 2011). A zebrafish model of arrhythmogenic cardiomyopathy (ACM) bearing a known human mutation demonstrated progressive cardiomyopathy mirroring human pathologies (Asimaki et al., 2014). Combination of ACM zebrafish with the cardiomyocyte stress reporter line Tg(nppb: luciferase) allowed chemical screening for suppressors of ACM phenotypes and identified a compound that normalized ACM-associated action potential defects in mammalian and zebrafish myocytes (Asimaki et al., 2014). A zebrafish model for cardiac fibrillation, tremblor, exhibited uncoordinated heart contractions due to a defect in calcium extrusion (Shimizu et al., 2015); a chemical screening of tremblor larvae identified the small molecule efsevin, which bind to the mitochondrial channel protein VDAC2 and increase mitochondrial calcium uptake (Shimizu et al., 2015). As mentioned previously, zebrafish have the remarkable capability of regenerating a number of tissues following injury, including portions of fins, heart, and brain (Gemberling et al., 2013); partial heart ventricle resection in adult zebrafish activates signaling cascades that drive formation of new cardiac wall typically by 30 days postinjury (Gemberling et al., 2013). While the non-high-throughput nature of heart surgery and size of adult zebrafish present challenges for chemical screening in adult models of heart injury, heart-specific transgenic larvae have been used in screens for modulators of cardiomyocyte proliferation with the potential to alter pathways involved in heart regeneration (Choi et al., 2013). Choi et al. used FUCCI to distinguish populations of proliferating and nonproliferating cardiomyocytes in developing larvae (Choi et al., 2013); combination of a larval chemical screen and adult heart-injury studies revealed involvement of hedgehog, insulin-like growth factor and transforming growth factor b signaling in cardiomyocyte proliferation

665

postinjury (Choi et al., 2013). In a separate study, cardiomyocyte-specific transgenic larvae (Tg(cmlc2: EGFP)) were screened to identify the small molecules cardionogen-1, -2 and -3, which caused an enlarged heart phenotype via expansion of cardiac progenitor cells (Ni et al., 2011). In the clinical setting, doxorubicin is a potent chemotherapeutic with a broad application but restricted use due to acute and/or delayed cardiotoxicity (Liu et al., 2014). Chemical screening in a zebrafish model of doxorubicin-induced cardiotoxicity identified the small molecules visnagin and diphenylurea, which rescued doxorubicin-induced cardiotoxicity in zebrafish and mice; visnagin bound to mitochondrial malate dehydrogenase (MDH2), and several MDH2 inhibitors exhibited similar cardioprotective effects, supporting visnagin and modulators of MDH2 activity as potential options for treating doxorubicin-induced cardiotoxicty in patients (Liu et al., 2014). For carrying out further cardiac function-focused screens, there exists a need for imaging technologies with adequate throughput and speed for monitoring cardiac parameters in real time; this has been addressed in several studies that employ automated imaging systems to quantify body length, circulation, pericardial area, heart rate and/or intersegmental vessel area in live, fluorescent larvae (Asnani & Peterson, 2014; Liu et al., 2014; Lin, Chang, Lai, & Liau, 2014). Notably, Lin et al. used confocal laser-scanning microscopy to generate time-lapse images of live zebrafish heart at different depths, from which, a pseudodynamic 3D reconstruction of the cardiac cycle could be achieved (Lin et al., 2014). Availability of disease models and continued improvements in live imaging are likely to pave the way for additional heart-specific screens (Asnani & Peterson, 2014). Lateral Line The zebrafish lateral line is a sensory system on the surface of the fish that allows detection of changes in water flow and contributes to predator/prey sensing, shoaling, and mating behaviors (Chitnis, Nogare, & Matsuda, 2012; ZFIN). The lateral line is comprised of neuromasts, clusters of mechanosensory hair cells anatomically similar to those found in the human inner ear (Owens et al., 2008; ZFIN). Given the implication of hair cell loss in deafness and balance disorders, and challenge of accessing the inner ear in mammals (Ou, Santos, Raible, Simon, & Rubel, 2010), several zebrafish chemical screens have been designed with a focus on ototoxicity (Chiu et al., 2008; Coffin et al., 2013; Hirose et al., 2011; Namdaran et al., 2012; Ou et al., 2009; Ou et al., 2010; Ou, Simon, Rubel, & Raible, 2012; Ou et al., 2012; Owens et al., 2008; Thomas et al., 2015; Vlasits et al., 2012); an additional screen identifies inhibitors

V. Scientific Research

666

51. Zebrafish as a Platform for Drug Screening

of posterior lateral line primordium migration during development (Gallardo et al., 2015). Ototoxicity-based screens fall into two categories: identification of toxic agents (Chiu et al., 2008; Coffin et al., 2013; Hirose et al., 2011) and identification of modulators of hair cell response to known ototoxins (Namdaran et al., 2012; Ou et al., 2009; Owens et al., 2008; Thomas et al., 2015; Vlasits et al., 2012). The vital DNA dye YO-PRO-1 is often used to fluorescently label hair cell nuclei (Coffin et al., 2010). A high-throughput ototoxicity screen was conducted in 2008 by Chiu et al., using wildtype larvae and 1040 compounds from NINDS Custom Collection 2 (Chiu et al., 2008). This screen identified seven known and 14 previously unknown ototoxins; two of the unknown compounds were further examined to show ototoxic effects in mouse utricle explant cultures (Chiu et al., 2008). Another ototoxicity screen was performed with 88 anticancer compounds from the NCI Approved Oncology Drugs Set, identifying four out of five known, four out of seven suspected, and five potentially novel ototoxins (Hirose et al., 2011). Additional ototoxicitybased screens identified modulators of hair cell response to known ototoxins, such as the aminoglycosides neomycin, gentamicin, and kanamycin, and the anticancer drug, cisplatin (Namdaran et al., 2012; Ou et al., 2009; Owens et al., 2008; Thomas et al., 2015; Vlasits et al., 2012). While some hit compounds reduce hair cell death by blocking ototoxin uptake (Thomas et al., 2015; Vlasits et al., 2012), others function via additional mechanisms, such as stimulating hair cell precursor division (Namdaran et al., 2012). One screen focused on the posterior lateral line primordium (pLLP), a cluster of around a 100 cells, a large portion of which migrates posteriorly under the skin and periodically deposits neuromasts along the trunk of the developing larva (Chitnis et al., 2012). In a chemical screen with the pLLP reporter line Tg(cldnb:EGFP) (Haas & Gilmour, 2006), Gallardo et al. identified 165 inhibitors of pLLP migration (Gallardo et al., 2015). Three of the hit compounds were Src inhibitors, and CRISPR-Cas9 targeting of src or its downstream target tks5 inhibited or delayed pLLP migration in injected larvae (Gallardo et al., 2015). The Src inhibitor SU6656 also exhibited antimetastatic activity in a mouse tumor model (Gallardo et al., 2015). These findings taken together, suggest that high-throughput screening in zebrafish, complemented by genome-editing technology and orthogonal secondary assays, could facilitate identification of compounds with high therapeutic potential. Tissue-Specific Disease Models Several screens were conducted with focus on specific diseases. Duchenne muscular dystrophy (DMD) is an X-linked neuromuscular disorder due to loss-offunction mutations in the protein dystrophin; patients

experience progressive muscle weakening and often early death from cardiac and/or respiratory failure (Waugh et al., 2014). A dystrophin-null zebrafish DMD model, sapje, was identified from the large-scale 1996 Tuebingen mutagenesis screen by its reduced muscle birefringence (Guyon et al., 2007; Granato et al., 1996), while a similar model, sapje-like, was generated by early-pressure screen (Guyon et al., 2009); both models lack dystrophin expression and exhibit muscle degeneration within a few days of development (Guyon et al., 2007; Guyon et al., 2009). In a chemical screen in sapje and sapje-like larvae with birefringence as readout, Kawahara et al. identified seven compounds that decreased the proportion of affected fish without altering dystrophin expression (Kawahara et al., 2011). In particular, prolonged treatment with the phosphodiesterase (PDE) inhibitor aminophylline normalized muscle structure as observed at 30 dpf (Kawahara et al., 2011). Protein kinase A (PKA) activity was upregulated in treated fish, suggesting that the cAMP-dependent PKA axis is likely involved in a compound activity (Kawahara et al., 2011). Several additional candidates were identified in subsequent screens, including modulators of heme oxygenase signaling (Kawahara et al., 2014) and the serotonin pathway (Waugh et al., 2014); the PDE5 inhibitor sildenafil was efficacious in a mouse DMD model (Adamo et al., 2010). Two zebrafish models for polycystic kidney disease (PKD), pkd2hi4166 and ift172hi2211, were identified from mutagenesis screens. Known association between PKD and body curvature/left-right symmetry defects in zebrafish larvae enabled screening of PKD modulators with body curvature and laterality as readout (Cao et al., 2009; Sun et al., 2004). Chemical screening with pkd2hi4166 and ift172hi2211 embryos identified trichostatin A, a pan-HDAC inhibitor that rescued body curvature defects in pkd2hi4166 larvae; excessive body curvature was also suppressed by hdac1 knockdown or the class I-specific HDAC inhibitor valproic acid (VPA), and VPA slowed disease progression in a mouse PKD model (Cao et al., 2009). One study focused on Hirschsprung’s disease, a common birth defect characterized by failure of nerve cells to colonize the distal bowel (aganglionosis), leading to growth failure, intestinal blockage and life-threatening infections (Hirschsprung Disease; Lake et al., 2013). Lake et al. identified nine inhibitors of enteric nervous system development in a chemical screen with wildtype zebrafish larvae (Lake et al., 2013). Among these compounds, the immunosuppression drug mycophenolate caused aganglionosis in zebrafish and mice via GTP depletion from proliferating enteric neural crestderived cells (Lake et al., 2013). Given partial penetrance and overall unclear etiology associated with this disease, the authors’ findings hint at additional factors, such as

V. Scientific Research

Limitations and Potential Solutions

medication and perturbed nucleotide homeostasis as potential contributors toward disease phenotype (Lake et al., 2013).

Clinical Implications Several screens have led to additional investigations toward therapeutic development. Dorsomorphin is a bone morphogenic protein (BMP) signaling inhibitor identified in a zebrafish chemical screen, where it triggered dorsalization of the developing embryo (Yu et al, 2008a, 2008b). Follow-up studies revealed dorsomorphin inhibited type I BMP receptors, leading to reduced transcription of BMP-responsive genes, such as the iron transport regulator hepcidin (Yu et al, 2008a, 2008b). Dysregulated BMP signaling is implicated in a number of diseases, including anemia of chronic inflammation (AI) and fibrodysplasia ossificans progressiva (FOP), in which progressive ossification of muscle and connective tissues leads to restrained movement and early mortality (Rennekamp & Peterson, 2015). A dorsomorphin derivative alleviated disease symptoms in mouse models of AI (Steinbicker et al., 2011) and FOP (Yu et al, 2008a, 2008b), and derivatives of dorsomorphin are being investigated as potential FOP therapeutics under NIH’s Therapeutics for Rare and Neglected Diseases (TRND) program (Bone Morphogenetic Protein). A screen in wildtype zebrafish larvae for modulators of the hematopoietic stem cell (HSC) pool identified a role for prostaglandin agonists and antagonists in increasing and decreasing HSC number, respectively (North et al., 2007). PGE2 synthesis was required for HSC formation, and pre-ex vivo treatment of donor mouse whole bone marrow with a long-acting PGE2 derivative significantly increased HSC repopulation frequency in recipient mice (North et al., 2007). Results from this study have contributed to the testing of ProHema (Fate Therapeutics) in human patients to assess its effect on neutrophil engraftment from blood cord hematopoietic cell transplantation (HCT) (Rennekamp & Peterson, 2015). In addition to these findings, the ability to model oncogene-driven leukemia (Yeh et al., 2009) and perform HCT (Li et al., 2015) in zebrafish provides valuable tools in the study of transplantation biology and hematologic malignancies. More recently, chemical screening in a zebrafish epilepsy model was directly translated into a clinical trial (Griffin et al., 2017). Mutations in SCN1A are the primary monogenic cause of Dravet syndrome, pediatric epilepsy with impaired development and severe seizures (Baraban et al., 2013; Griffin et al., 2017). Chemical screening in scn1Lab zebrafish identified the antihistamine clemizole as a seizure suppressant (Baraban et al., 2013). Clemizole exhibited a binding affinity for serotonin

667

receptors, and several additional modulators of serotonin signaling also suppressed seizure events in zebrafish (Griffin et al., 2017). These findings led to a clinical trial with the FDA-approved serotonin agonist lorcaserin in five Dravet syndrome patients, with initial results demonstrating a reduction in seizure severity and/or frequency (Griffin et al., 2017). Chemical screens in zebrafish models of doxorubicin cardiotoxicity (Liu et al., 2014) and long QT syndrome (Peal et al., 2011) have also yielded candidate compounds with promising therapeutic potential. Structural activity relationship studies are currently underway for visnagin. Dexamethasone, an approved drug structurally similar to the long QT rescue candidate flurandrenolide, is under investigation for its potential effects on long QT syndrome (Rennekamp & Peterson, 2015). While testing and approval of new compounds require significant time (Lo B), drug repositioning, the process of screening, either experimentally or computationally, previously approved drugs to identify additional therapeutic targets, could improve speed along the drug discovery pipeline given availability of data, such as mechanism of action, bioavailability, and toxicity (Ashburn & Thor, 2004; Brown & Patel, 2016; Lotfi Shahreza, Ghadiri, Mousavi, Varshosaz, & Green, 2017).

Limitations and Potential Solutions While small larval size, high fecundity, and optic transparency of zebrafish confer distinct advantages in the realm of chemical screening, there also exist limitations unique to this model organism (Rennekamp & Peterson, 2015). Approximately 70% of human genes have at least one ortholog in zebrafish, with over 3100 genes having at least two zebrafish orthologs, a likely consequence of teleost-specific genome duplication (Howe et al., 2013; Vornanen & Hassinen, 2016). While this overlap supports conservation of the associated biological pathways, duplicates arising from genomic duplication could undergo loss and/or change of a function over time, thus creating additional downstream variability (Howe et al., 2013). The human and zebrafish genomes also contain a few thousand genes with no mutual orthologs, thereby placing some restrictions over a model generation; notable examples include the absence of identifiable zebrafish orthologs for human IL6 and BRCA1 (Howe et al., 2013). Evolutionary divergence of the teleost lineage from other vertebrates has also resulted in significant physiological differences. As an aquatic organism, the zebrafish does not possess lungs, and therefore, would not be suitable for modeling pulmonary diseases. The poikilothermic nature of zebrafish hinders the study of thermogenesis, and the existence of brown adipose tissue in this

V. Scientific Research

668

51. Zebrafish as a Platform for Drug Screening

organism remains unexplored (Seth et al., 2013). Additional differences from mammals include location of hematopoietic tissue, and organization of pancreatic cells and hepatocytes (Menke, Spitsbergen, Wolterbeek, & Woutersen, 2011), though similarities in the types and functions of these cells have enabled studies of metabolic disorders and hematopoiesis (Rennekamp & Peterson, 2015; Seth et al., 2013). In addition to differences in biology, chemical screening in zebrafish faces its unique technical challenges. The aquatic nature of zebrafish necessitates compound addition into an aqueous buffer, thus limiting testing of compounds with high hydrophobicity; when possible, synthesis of water-soluble analogs could improve solubility, though at the risk of potentially altering compound activity (Dang et a., 2016). In place of water or aqueous buffer, organic solvents, such as dimethylsulfoxide and alcohols, could be used as carrier solvents, though only low concentrations (typically averaging at around 1% volume/volume) are tolerable by live larvae (Maes et al., 2012). When available, partition coefficients (logP) could be used as a guide in the selection of compounds with a greater chance of solubility in the zebrafish environment (Savjani, Gajjar, & Savjani, 2012). Another issue is compound uptake, which could vary depending on the developmental stage due to differences in the maturity of the gills, mouth, and/or skin (Dang et al., 2016). Zebrafish larvae hatch sporadically, typically on the third day of development, with most larvae hatched by the end of the fourth day (Kimmel, Ballard, Kimmel, Ullmann, & Schilling, 1995); this difference in hatching rate even within the same clutch could introduce inconsistencies in compound absorption, as the chorion may in some cases be a physical barrier to compound entry (Zhang, Qin, Zhang, & Hu, 2015). While manual and mechanical chorion removal is time-intensive, chemical methods, such as pronase have routinely been used on large numbers of embryos without lowering survival; an automated approach, combining pronase treatment with automated mechanical agitation followed by dechorionated larva placement into well plates, has also been developed (Mandrell et al., 2012). As has been encountered in most mammalian models, increased size and opacity of adult zebrafish hinders high-throughput screening (Rennekamp & Peterson, 2015). While rapid development of zebrafish enables the study of many key aspects of behavior, metabolism, and organogenesis at the larval stage (Kimmel et al., 1995; Rennekamp & Peterson, 2015), it is difficult to integrate a high-throughput screening platform into aging, adult tissue regeneration, and some behavioral assays (Rennekamp & Peterson, 2015). Despite the unfeasibility of a 96-well format, it still remains possible to screen adult fish using smaller, custom compound

collections, as was demonstrated in a study by Maximino et al., in which a panel of anxiolytic and anxiogenic drugs was screened in adult zebrafish to identify modifiers of anxiety-like behavior (Maximino et al., 2014). Generation of the highly optically transparent Casper zebrafish, which lack melanocytes and iridophores in all stages of life, has enabled imaging-based readout in adult fish (Li et al., 2015; Rennekamp & Peterson, 2015; White et al., 2008). As more complex behavioral assays, such as opioid self-administration (Bosse´ & Peterson, 2017) and maze learning (Roberts, Bill, & Glanzman, 2013) become optimized for adult zebrafish, it is likely that behavior-based chemical screens will also expand alongside these novel setups. The availability of automated, motion-tracking instruments and software, such as ZebraBox (ViewPoint Behavior Technology) and ActualTrack (Actual Analytics) have also facilitated behavior monitoring in both multiwell and single-fish formats. Given the frequent use of fluorescent zebrafish reporter lines and imaging-based readouts, it is crucial for some screens that larval orientation remains consistent across all wells (Rennekamp & Peterson, 2015). Following swim bladder inflation around five dpf (Kimmel et al., 1995), zebrafish larvae typically take on a dorsal-ventral orientation when viewed from top, while larvae prior to swim bladder inflation tend to orient more laterally if undisturbed; differences in timeframe of swim bladder inflation, coupled with emergence of movement-related behaviors within the first few days of development, can lead to inconsistent larval orientation, with use of anesthesia not a guarantee for consistent orientation in all larvae. Two major approaches toward improving larval positioning include modifications of the screening plate and design of automated systems (Rennekamp & Peterson, 2015). Rovira et al., in their screen for enhancers of b-cell differentiation, designed a 96-well SideView plate in which prisms adjacent to wells refract excitation and emission light, allowing consistent lateral visualization of fluorescent larvae (Rovira et al., 2011). A second approach by Wittbrodt et al. used a desktop 3D printer to create orientation tools that could be used as molds for generating cavities in agarose-filled multiwells, enabling positioning and imaging of larvae in either dorsal-ventral or lateral view in the resulting plate (Wittbrodt, Liebel, & Gehrig, 2014). An automated, capillary-based larva orientation and imaging system (VAST BioImager Platform) has been designed by Union Biometrica based on technology from the Yanik research group (Chang, Pardo-Martin, Allalou, Wahlby, & Yanik, 2012; Pardo-Martin et al., 2010; Pardo-Martin et al., 2013; Union Biometrica); a single larva is loaded and positioned in a capillary until reaching the desired view, the resulting instrument parameters can then be

V. Scientific Research

Conclusion

rapidly replicated in each additional larva until all larvae are imaged (Union Biometrica). As previously mentioned, Wang et al., in their screen for modulators of b-cell mass, fully automated the screening process from larva transfer to data analysis, relying on the COPAS-XL system (Union Biometrica) for dispensing of larvae into individual wells of a 96-well plate (Wang et al., 2015). While the manual transfer of larva and compound has traditionally been one of the major bottlenecks of zebrafish chemical screens, it is likely solvable through advancements in automation. While whole-organism phenotypic screens are more adept than cell-based approaches at capturing systemlevel responses and more suited toward discovery of novel drug targets than target-based methods, their limitation lies in the challenge of target identification (Hart, 2005). As the availability of target information is crucial for compound optimization, a number of target discovery methodologies have been explored. Two major approaches are direct methods, such as affinity chromatography and microarrays that examine compoundtarget interactions, and indirect methods that compare compound-induced biological changes against those associated with known compounds or chemical/genetic modulations (Hart, 2005). Affinity chromatography identified an interaction between visnagin and mitochondrial malate dehydrogenase (Liu et al., 2014), while comparison of kalihinol F-induced larval phenotypes against those of the established calamity model revealed kalihinol F’s role as a copper chelator (Sandoval et al., 2013); however, it is worth noting that both of these approaches also carry limitations, such as challenge of maintaining compound activity in the former, and model availability in the latter (Hart, 2005). Ultimately, the choice of target identification methods will depend on compound structure, model organism, and availability of additional reference data.

Conclusion In this book chapter, we provide an overview of zebrafish chemical screening over the past 17 years, highlighting key examples in metabolism, behavior, and organogenesis. Our literature search (Ncbi Resource Coordinators, 2017) yielded 114 examples of zebrafish chemical screens, approximately half of which were tissue-specific, focusing on modulators of organogenesis or rescuers of tissue-specific pathologies. The next largest categories were metabolism, signaling, and behavior, with additional screens covering a wide range

669

of topics, such as inflammation, toxicology, and epigenetics. 55 studies use wildtype zebrafish, 50 use transgenic lines and nine use genetic mutants, with the majority of studies focusing on larvae before eight dpf, and four studies using adult zebrafish. The top three most frequently selected compound libraries were Prestwick Chemical Library, Spectrum Collection and Sigma LOPAC1280. While the optical transparency, high fecundity, rapid development and small size of the larval zebrafish confer clear advantages in the realm of high-throughput chemical screening, we also note limitations, including imperfectly conserved biology, challenge of target identification, difficulty of high-throughput screening in adult fish, compound insolubility, undefined absorption profile, and inconsistent larval orientation (Rennekamp & Peterson, 2015). However, continued improvements in automation suggest that some of the aforementioned limitations are likely to be solvable issues in future screens. We also bring to attention chemical screens with significant clinical impact. While the rise in number of zebrafish screens in recent years supports a corresponding increase in the number of compounds with therapeutic potential, the fairly large span (10 to 15 years) (Lo B) between hit identification and drug approval suggests that additional time is needed before one could fully evaluate the impact of zebrafish screening in the realm of approved drugs and make comparisons with other drug discovery approaches. As zebrafish chemical screening looks toward the future, we conclude the current chapter by proposing the following as potential rising trends in this evolving field: (1) Optimization of more complex behavioral assays in adult zebrafish is likely to promote development of behavior-based chemical screens capable of accommodating these novel setups as well as older fish. (2) Improved efficiency and availability of genomeediting technologies have contributed to an increase in targeted disease model generation in zebrafish, which could translate into a rise in disease-focused screening in these models. (3) Advancements in high-throughput quantification of biological parameters (i.e., metabolomics) could broaden the range of phenotypic readouts. (4) Improved automation in all aspects of the zebrafish screening platform is likely to significantly reduce experiment time and lead to an overall increase in the number of future screens.

V. Scientific Research

670

51. Zebrafish as a Platform for Drug Screening

References Adamo, C. M., et al. (2010). Sildenafil reverses cardiac dysfunction in the mdx mouse model of Duchenne muscular dystrophy. Proceedings of the National Academy of Sciences of the United States of America, 107, 19079e19083. https://doi.org/10.1073/ pnas.1013077107. Alvarez, Y., et al. (2009). Selective inhibition of retinal angiogenesis by targeting PI3 kinase. PLoS One, 4, e7867. https://doi.org/10.1371/ journal.pone.0007867. Andersson, O., et al. (2012). Adenosine signaling promotes regeneration of pancreatic b cells in vivo. Cell Metabolism, 15, 885e894. https://doi.org/10.1016/j.cmet.2012.04.018. Arulmozhivarman, G., et al. (2016). In vivo chemical screen in zebrafish embryos identifies regulators of hematopoiesis using a semiautomated imaging assay. Journal of Biomolecular Screening, 21, 956e964. https://doi.org/10.1177/1087057116644163. Ashburn, T. T., & Thor, K. B. (2004). Drug repositioning: Identifying and developing new uses for existing drugs. Nature Reviews Drug Discovery, 3, 673. https://doi.org/10.1038/nrd1468. Asimaki, A., et al. (2014). Identification of a new modulator of the intercalated disc in a zebrafish model of arrhythmogenic cardiomyopathy. Science Translational Medicine, 6. https://doi.org/ 10.1126/scitranslmed.3008008, 240ra274-240ra274. Asnani, A., & Peterson, R. T. (2014). The zebrafish as a tool to identify novel therapies for human cardiovascular disease. Disease Models and Mechanisms, 7, 763e767. https://doi.org/10.1242/ dmm.016170. Astin, J. W., et al. (2014). An in vivo antilymphatic screen in zebrafish identifies novel inhibitors of mammalian lymphangiogenesis and lymphatic-mediated metastasis. Molecular Cancer Therapeutics, 13, 2450e2462. https://doi.org/10.1158/1535-7163.mct-14-0469-t. Baraban, S. C., Dinday, M. T., & Hortopan, G. A. (2013). Drug screening in Scn1a zebrafish mutant identifies clemizole as a potential Dravet Syndrome treatment. Nature Communications, 4. https://doi.org/ 10.1038/ncomms3410, 2410-2410. Baraban, S. C., Taylor, M. R., Castro, P. A., & Baier, H. (2005). Pentylenetetrazole induced changes in zebrafish behavior, neural activity and c-fos expression. Neuroscience, 131, 759e768. https://doi.org/ 10.1016/j.neuroscience.2004.11.031. Bone morphogenetic protein inhibitors to treat fibrodysplasia ossificans progressiva. NIH Therapeutics for Rare and Neglected Diseases (TRND) program. https://ncats.nih.gov/trnd/projects/ active/protein-inhibitors-fibrodysplasia. Bosse´, G. D., & Peterson, R. T. (2017). Development of an opioid selfadministration assay to study drug seeking in zebrafish. Behavioural Brain Research, 335, 158e166. https://doi.org/10.1016/j.bbr.2017. 08.001. Bouwmeester, M. C., et al. (2016). Zebrafish embryos as a screen for DNA methylation modifications after compound exposure. Toxicology and Applied Pharmacology, 291, 84e96. https://doi.org/10. 1016/j.taap.2015.12.012. Brown, A. S., & Patel, C. J. (2016). A review of validation strategies for computational drug repositioning. Briefings in Bioinformatics. https://doi.org/10.1093/bib/bbw110. bbw110-bbw110. Bruni, G., et al. (2016). Zebrafish behavioral profiling identifies multitarget antipsychotic-like compounds. Nature Chemical Biology, 12, 559e566. https://doi.org/10.1038/nchembio.2097. supplementaryinformation. http://www.nature.com/nchembio/journal/v12/n7 /abs/nchembio.2097.html. Buckley, C. E., et al. (2010). Drug reprofiling using zebrafish identifies novel compounds with potential pro-myelination effects. Neuropharmacology, 59, 149e159. https://doi.org/10.1016/j. neuropharm.2010.04.014. Cao, Y., et al. (2009). Chemical modifier screen identifies HDAC inhibitors as suppressors of PKD models. Proceedings of the National

Academy of Sciences, 106, 21819e21824. https://doi.org/10.1073/ pnas.0911987106. Challal, S., et al. (2014). Zebrafish bioassay-guided microfractionation identifies anticonvulsant steroid glycosides from the Philippine medicinal plant solanum torvum. ACS Chemical Neuroscience, 5, 993e1004. https://doi.org/10.1021/cn5001342. Chang, T.-Y., Pardo-Martin, C., Allalou, A., Wahlby, C., & Yanik, M. F. (2012). Fully automated cellular-resolution vertebrate screening platform with parallel animal processing. Lab on a Chip, 12, 711e716. https://doi.org/10.1039/C1LC20849G. Chitnis, A. B., Nogare, D. D., & Matsuda, M. (2012). Building the posterior lateral line system in zebrafish. Developmental Neurobiology, 72, 234e255. https://doi.org/10.1002/dneu.20962. Chiu, L. L., Cunningham, L. L., Raible, D. W., Rubel, E. W., & Ou, H. C. (2008). Using the zebrafish lateral line to screen for ototoxicity. JARO: Journal of the Association for Research in Otolaryngology, 9, 178e190. https://doi.org/10.1007/s10162-008-0118-y. Choi, W.-Y., et al. (2013). In vivo monitoring of cardiomyocyte proliferation to identify chemical modifiers of heart regeneration. Development, 140, 660e666. https://doi.org/10.1242/dev.088526. Clifton, J. D., et al. (2010). Identification of novel inhibitors of dietary lipid absorption using zebrafish. PLoS One, 5, e12386. https:// doi.org/10.1371/journal.pone.0012386. Coffin, A. B., et al. (2010). Chemical screening for hair cell loss and protection in the zebrafish lateral line. Zebrafish, 7, 3e11. https:// doi.org/10.1089/zeb.2009.0639. Coffin, A. B., Williamson, K. L., Mamiya, A., Raible, D. W., & Rubel, E. W. (2013). Profiling drug-induced cell death pathways in the zebrafish lateral line. Apoptosis, 18, 393e408. https:// doi.org/10.1007/s10495-013-0816-8. Colanesi, S., et al. (2012). Small molecule screening identifies targetable zebrafish pigmentation pathways. Pigment Cell and Melanoma Research, 25, 131e143. https://doi.org/10.1111/j.1755148X.2012.00977.x. Crawford, A. D., et al. (2011). Zebrafish bioassay-guided natural product discovery: Isolation of angiogenesis inhibitors from East African medicinal plants. PLoS One, 6, e14694. https://doi.org/10.1371/ journal.pone.0014694. Dang, M., et al. (2016). Identifying novel cancer therapies using chemical genetics and zebrafish. In D. M. Langenau (Ed.), Cancer and zebrafish e mechanisms, techniques, and models Advances in Experimental Medicine and Biology, 916 pp. 103e124. Cham: Springer. https://doi.org/10.1007/978-3-319-30654-4_5. Das, B. C., McCartin, K., Liu, T.-C., Peterson, R. T., & Evans, T. (2010). A forward chemical screen in zebrafish identifies a retinoic acid derivative with receptor specificity. PLoS One, 5, e10004. https:// doi.org/10.1371/journal.pone.0010004. Dimri, M., et al. (2015). Prilocaine hydrochloride protects zebrafish from lethal effects of ionizing radiation: Role of hematopoietic cell expansion. Tokai Journal of Experimental and Clinical Medicine, 40, 8e15. Fleming, A., Sato, M., & Goldsmith, P. (2005). High-throughput in vivo screening for bone anabolic compounds with zebrafish. Journal of Biomolecular Screening, 10, 823e831. https://doi.org/10.1177/ 1087057105279952. Gagnon, J. A., et al. (2014). Efficient mutagenesis by Cas9 proteinmediated oligonucleotide insertion and large-scale assessment of single-guide RNAs. PLoS One, 9, e98186. https://doi.org/ 10.1371/journal.pone.0098186. Gallardo, V. E., et al. (2015). Phenotype-driven chemical screening in zebrafish for compounds that inhibit collective cell migration identifies multiple pathways potentially involved in metastatic invasion. Disease Models and Mechanisms, 8, 565e576. https:// doi.org/10.1242/dmm.018689.

V. Scientific Research

References

Garnaas, M. K., et al. (2012). Rargb regulates organ laterality in a zebrafish model of right atrial isomerism. Developmental Biology, 372, 178e189. https://doi.org/10.1016/j.ydbio.2012.09.001. Gebruers, E., et al. (2013). A phenotypic screen in zebrafish identifies a novel small-molecule inducer of ectopic tail formation suggestive of alterations in non-canonical wnt/PCP signaling. PLoS One, 8, e83293. https://doi.org/10.1371/journal.pone.0083293. Gemberling, M., Bailey, T. J., Hyde, D. R., & Poss, K. D. (2013). The zebrafish as a model for complex tissue regeneration. Trends in Genetics, 29, 611e620. https://doi.org/10.1016/j.tig.2013.07.003. Granato, M., et al. (1996). Genes controlling and mediating locomotion behavior of the zebrafish embryo and larva. Development, 123, 399e413. Griffin, A., et al. (2017). Clemizole and modulators of serotonin signalling suppress seizures in Dravet syndrome. Brain, 140, 669e683. https://doi.org/10.1093/brain/aww342. de Groh, E. D., et al. (2010). Inhibition of histone deacetylase expands the renal progenitor cell population. Journal of the American Society of Nephrology, 21, 794e802. https://doi.org/10.1681/asn.2009080851. Gut, P., et al. (2013). Whole-organism screening for gluconeogenesis identifies activators of fasting metabolism. Nature Chemical Biology, 9, 97e104. supplementary-information. http://www. nature.com/nchembio/journal/v9/n2/abs/nchembio.1136.html. Gutierrez, A., et al. (2014). Phenothiazines induce PP2A-mediated apoptosis in T cell acute lymphoblastic leukemia. The Journal of Clinical Investigation, 124, 644e655. https://doi.org/10.1172/ JCI65093. Guyon, J. R., et al. (2007). Modeling human muscle disease in zebrafish. Biochimica et Biophysica Acta (BBA) e Molecular Basis of Disease, 1772, 205e215. https://doi.org/10.1016/j.bbadis.2006.07.003. Guyon, J. R., et al. (2009). Genetic isolation and characterization of a splicing mutant of zebrafish dystrophin. Human Molecular Genetics, 18, 202e211. https://doi.org/10.1093/hmg/ddn337. Haas, P., & Gilmour, D. (2006). Chemokine signaling mediates self-organizing tissue migration in the zebrafish lateral line. Developmental Cell, 10, 673e680. https://doi.org/10.1016/j.devcel. 2006.02.019. Hall, C. J., et al. (2014). Repositioning drugs for inflammatory disease e fishing for new anti-inflammatory agents. Disease Models and Mechanisms, 7, 1069e1081. https://doi.org/10.1242/dmm.016873. Hao, J., et al. (2013). Selective small molecule targeting b-catenin function discovered by in vivo chemical genetic screen. Cell Reports, 4, 898e904. https://doi.org/10.1016/j.celrep.2013.07.047. Hart, C. P. (2005). Finding the target after screening the phenotype. Drug Discovery Today, 10, 513e519. https://doi.org/10.1016/ S1359-6446(05)03415-X. Hirose, Y., Simon, J. A., & Ou, H. C. (2011). Hair cell toxicity in anticancer drugs: Evaluating an anti-cancer drug library for independent and synergistic toxic effects on hair cells using the zebrafish lateral line. Journal of the Association for Research in Otolaryngology, 12, 719e728. https://doi.org/10.1007/s10162-011-0278-z. Hirschsprung Disease. NIDDK. https://www.niddk.nih.gov/healthinformation/digestive-diseases/hirschsprung-disease. Howe, K., et al. (2013). The zebrafish reference genome sequence and its relationship to the human genome. Nature, 496, 498e503. https://doi.org/10.1038/nature12111. Huang, H., Lindgren, A., Wu, X., Liu, N.-A., & Lin, S. (2012). Highthroughput screening for bioactive molecules using primary cell culture of transgenic zebrafish embryos. Cell Reports, 2, 695e704. https://doi.org/10.1016/j.celrep.2012.08.015. Hultman, K. A., Scott, A. W., & Johnson, S. L. (2008). Small molecule modifier screen for kit-dependent functions in zebrafish embryonic melanocytes. Zebrafish, 5, 279e287. https://doi.org/10.1089/ zeb.2008.0542.

671

Hwang, W. Y., Peterson, R. T., & Yeh, J.-R. J. (2014). Methods for targeted mutagenesis in zebrafish using TALENs. Methods, 69, 76e84. https://doi.org/10.1016/j.ymeth.2014.04.009. Jimenez, L., et al. (2016). Phenotypic chemical screening using a zebrafish neural crest EMT reporter identifies retinoic acid as an inhibitor of epithelial morphogenesis. Disease Models and Mechanisms, 9, 389e400. https://doi.org/10.1242/dmm.021790. Jin, S., et al. (2013). An in vivo zebrafish screen identifies organophosphate antidotes with diverse mechanisms of action. Journal of Biomolecular Screening, 18, 108e115. https://doi.org/10.1177/ 1087057112458153. Kalueff, A. V., et al. (2013). Towards a comprehensive catalog of zebrafish behavior 1.0 and beyond. Zebrafish, 10, 70e86. https://doi.org/ 10.1089/zeb.2012.0861. Kalueff, A. V., Stewart, A. M., & Gerlai, R. (2014). Zebrafish as an emerging model for studying complex brain disorders. Trends in Pharmacological Sciences, 35, 63e75. https://doi.org/10.1016/ j.tips.2013.12.002. Kannan, R. R., & Vincent, S. G. P. (2012). Cynodon dactylon and Sida acuta extracts impact on the function of the cardiovascular system in zebrafish embryos. Journal of Biomedical Research, 26, 90e97. https://doi.org/10.1016/S1674-8301(12)60017-7. Kawahara, G., et al. (2011). Drug screening in a zebrafish model of Duchenne muscular dystrophy. Proceedings of the National Academy of Sciences, 108, 5331e5336. https://doi.org/10.1073/ pnas.1102116108. Kawahara, G., et al. (2014). Dystrophic muscle improvement in zebrafish via increased heme oxygenase signaling. Human Molecular Genetics, 23, 1869e1878. https://doi.org/10.1093/hmg/ddt579. Keatinge, M., et al. (2015). Glucocerebrosidase 1 deficient Danio rerio mirror key pathological aspects of human Gaucher disease and provide evidence of early microglial activation preceding alphasynuclein-independent neuronal cell death. Human Molecular Genetics, 24, 6640e6652. https://doi.org/10.1093/hmg/ddv369. Kimmel, C. B., Ballard, W. W., Kimmel, S. R., Ullmann, B., & Schilling, T. F. (1995). Stages of embryonic development of the zebrafish. Developmental Dynamics, 203, 253e310. https://doi.org/ 10.1002/aja.1002030302. Kitambi, S. S., McCulloch, K. J., Peterson, R. T., & Malicki, J. J. (2009). Small molecule screen for compounds that affect vascular development in the zebrafish retina. Mechanisms of Development, 126, 464e477. https://doi.org/10.1016/j.mod.2009.01.002. Ko, S., et al. (2016). Bromodomain and extraterminal (BET) proteins regulate biliary-driven liver regeneration. Journal of Hepatology, 64, 316e325. https://doi.org/10.1016/j.jhep.2015.10.017. Kokel, D., et al. (2010). Rapid behavior-based identification of neuroactive small molecules in the zebrafish. Nature Chemical Biology, 6, 231e237. http://www.nature.com/nchembio/journal/v6/n3/ suppinfo/nchembio.307_S1.html. Kokel, D., & Peterson, R. T. (2011). Using the zebrafish photomotor response for psychotropic drug screening. Methods in Cell Biology, 105, 517e524. https://doi.org/10.1016/B978-0-12-3813206.00022-9. Kumar, M. G., et al. (2016). Altered glycolysis and mitochondrial respiration in a zebrafish model of Dravet syndrome. eNeuro, 3, 0008e0016. https://doi.org/10.1523/ENEURO.0008-16.2016. ENEURO. Laggner, C., et al. (2012). Chemical informatics and target identification in a zebrafish phenotypic screen. Nature Chemical Biology, 8, 144e146. supplementary-information. http://www.nature.com/ nchembio/journal/v8/n2/abs/nchembio.732.html. Lake, J. I., Tusheva, O. A., Graham, B. L., & Heuckeroth, R. O. (2013). Hirschsprung-like disease is exacerbated by reduced de novo GMP synthesis. The Journal of Clinical Investigation, 123, 4875e4887. https://doi.org/10.1172/JCI69781.

V. Scientific Research

672

51. Zebrafish as a Platform for Drug Screening

Lam, I. K., et al. (2012). In vitro and in vivo structure and activity relationship analysis of polymethoxylated flavonoids: Identifying sinensetin as a novel antiangiogenesis agent. Molecular Nutrition and Food Research, 56, 945e956. https://doi.org/10.1002/ mnfr.201100680. Le, X., et al. (2013). A novel chemical screening strategy in zebrafish identifies common pathways in embryogenesis and rhabdomyosarcoma development. Development, 140, 2354e2364. https://doi.org/ 10.1242/dev.088427. Lee, J., et al. (2013). Development of a highly visual, simple, and rapid test for the discovery of novel insulin mimetics in living vertebrates. ACS Chemical Biology, 8, 1803e1814. https://doi.org/10.1021/ cb4000162. Leet, J. K., et al. (2014). High-content screening in zebrafish embryos identifies butafenacil as a potent inducer of anemia. PLoS One, 9, e104190. https://doi.org/10.1371/journal.pone.0104190. Legler, J., et al. (2011). Effect-directed analysis of municipal landfill soil reveals novel developmental toxicants in the zebrafish Danio rerio. Environmental Science and Technology, 45, 8552e8558. https:// doi.org/10.1021/es201099s. Li, C., et al. (2016). Metabolomic characterizations of liver injury caused by acute arsenic toxicity in zebrafish. PLoS One, 11, e0151225. https://doi.org/10.1371/journal.pone.0151225. Li, L., et al. (2016). In vivo screening using transgenic zebrafish embryos reveals new effects of hdac inhibitors trichostatin a and valproic acid on organogenesis. PLoS One, 11, e0149497. https:// doi.org/10.1371/journal.pone.0149497. Li, P., et al. (2015). Epoxyeicosatrienoic acids enhance embryonic haematopoiesis and adult marrow engraftment. Nature, 523, 468. https://doi.org/10.1038/nature14569. supplementaryinformation www.nature.com/articles/nature14569. Li, X., et al. (2016). Progesterone receptor membrane component-1 regulates hepcidin biosynthesis. The Journal of Clinical Investigation, 126, 389e401. https://doi.org/10.1172/JCI83831. Li, M., Page-McCaw, P., & Chen, W. (2016). FGF1 mediates overnutrition-induced compensatory b-cell differentiation. Diabetes, 65, 96e109. https://doi.org/10.2337/db15-0085. Li, Y., Huang, W., Huang, S., Du, J., & Huang, C. (2012). Screening of anti-cancer agent using zebrafish: Comparison with the MTT assay. Biochemical and Biophysical Research Communications, 422, 85e90. https://doi.org/10.1016/j.bbrc.2012.04.110. Liang, F., et al. (2015). Kaempferol identified by zebrafish assay and fine fractionations strategy from Dysosma versipellis inhibits angiogenesis through VEGF and FGF pathways (Vol. 5, p. 14468). https://doi.org/10.1038/srep14468. supplementary-information. http://dharmasastra.live.cf.private.springer.com/articles/ srep14468 Lin, K.-Y., Chang, W.-T., Lai, Y.-C., & Liau, I. (2014). Toward functional screening of cardioactive and cardiotoxic drugs with zebrafish in vivo using pseudodynamic three-dimensional imaging. Analytical Chemistry, 86, 2213e2220. https://doi.org/10.1021/ac403877h. Liu, J., et al. (2017). CRISPR/Cas9 in zebrafish: An efficient combination for human genetic diseases modeling. Human Genetics, 136, 1e12. https://doi.org/10.1007/s00439-016-1739-6. Liu, Y., et al. (2014). Visnagin protects against doxorubicin-induced cardiomyopathy through modulation of mitochondrial malate dehydrogenase. Science Translational Medicine, 6. https://doi.org/ 10.1126/scitranslmed.3010189. 266ra170-266ra170. Liu, Y.-J., et al. (2013). Cannabinoid receptor 2 suppresses leukocyte inflammatory migration by modulating the JNK/c-Jun/Alox5 pathway. Journal of Biological Chemistry, 288, 13551e13562. https://doi.org/10.1074/jbc.M113.453811. Lo B, F. M. Conflict of interest in medical research, education, and practice. Washington (DC): National Academies Press (US). Institute of Medicine (US) Committee on Conflict of Interest in Medical Research, Education, and Practice: The Pathway from Idea to

Regulatory Approval: Examples for Drug Development. https:// www.ncbi.nlm.nih.gov/books/NBK22930/. Long, S.-M., et al. (2014). Identification of marine neuroactive molecules in behaviour-based screens in the larval zebrafish. Marine Drugs, 12, 3307. Lotfi Shahreza, M., Ghadiri, N., Mousavi, S. R., Varshosaz, J., & Green, J. R. (2017). A review of network-based approaches to drug repositioning. Briefings in Bioinformatics. https://doi.org/ 10.1093/bib/bbx017. bbx017-bbx017. Lu, J., et al. (2013). A novel anti-tumor inhibitor identified by virtual screen with PLK1 structure and zebrafish assay. PLoS One, 8, e53317. https://doi.org/10.1371/journal.pone.0053317. Maes, J., et al. (2012). Evaluation of 14 organic solvents and carriers for screening applications in zebrafish embryos and larvae. PLoS One, 7, e43850. https://doi.org/10.1371/journal.pone.0043850. Makky, K., Duvnjak, P., Pramanik, K., Ramchandran, R., & Mayer, A. N. (2008). A whole-animal microplate Assay for metabolic rate using zebrafish. Journal of Biomolecular Screening, 13, 960e967. https://doi.org/10.1177/1087057108326080. Mandrell, D., et al. (2012). Automated zebrafish chorion removal and single embryo placement: Optimizing throughput of zebrafish developmental toxicity screens. Journal of Laboratory Automation, 17, 66e74. https://doi.org/10.1177/2211068211432197. Maximino, C., et al. (2014). Fingerprinting of psychoactive drugs in zebrafish anxiety-like behaviors. PLoS One, 9, e103943. https:// doi.org/10.1371/journal.pone.0103943. Mendelsohn, B. A., et al. (2006). Atp7a determines a hierarchy of copper metabolism essential for notochord development. Cell Metabolism, 4, 155e162. https://doi.org/10.1016/j.cmet.2006.05.001. Menke, A. L., Spitsbergen, J. M., Wolterbeek, A. P. M., & Woutersen, R. A. (2011). Normal anatomy and histology of the adult zebrafish. Toxicologic Pathology, 39, 759e775. https://doi.org/ 10.1177/0192623311409597. Milan, D. J., Peterson, T. A., Ruskin, J. N., Peterson, R. T., & MacRae, C. A. (2003). Drugs that induce repolarization abnormalities cause bradycardia in zebrafish. Circulation, 107, 1355e1358. https://doi.org/10.1161/01.cir.0000061912.88753.87. Molina, G., et al. (2009). Zebrafish chemical screening reveals an inhibitor of Dusp6 that expands cardiac cell lineages. Nature Chemical Biology, 5, 680e687. http://www.nature.com/nchembio/journal/ v5/n9/suppinfo/nchembio.190_S1.html. Molina, G. A., Watkins, S. C., & Tsang, M. (2007). Generation of FGF reporter transgenic zebrafish and their utility in chemical screens. BMC Developmental Biology, 7, 62. https://doi.org/10.1186/1471-213x-7-62. Morash, M. G., et al. (2011). The zebrafish embryo as a tool for screening and characterizing pleurocidin host-defense peptides as anti-cancer agents. Disease Models and Mechanisms, 4, 622e633. https://doi.org/10.1242/dmm.007310. Namdaran, P., Reinhart, K. E., Owens, K. N., Raible, D. W., & Rubel, E. W. (2012). Identification of modulators of hair cell regeneration in the zebrafish lateral line. The Journal of Neuroscience, 32, 3516e3528. https://doi.org/10.1523/jneurosci.3905-11.2012. Nath, A. K., et al. (2013). Chemical and metabolomic screens identify novel biomarkers and antidotes for cyanide exposure. The FASEB Journal, 27, 1928e1938. https://doi.org/10.1096/fj.12-225037. Nath, A. K., et al. (2015). PTPMT1 inhibition lowers glucose through phosphorylation of SDH. Cell Reports, S2211e1247(2215), 00023e00026. https://doi.org/10.1016/j.celrep.2015.01.010, 00010.01016/j.celrep.02015.00001.00010. Ncbi Resource Coordinators. (2017). Database resources of the national center for biotechnology information. Nucleic Acids Research, 45, D12eD17. https://doi.org/10.1093/nar/gkw1071. Nemtsas, P., Wettwer, E., Christ, T., Weidinger, G., & Ravens, U. (2010). Adult zebrafish heart as a model for human heart? An electrophysiological study. Journal of Molecular and Cellular Cardiology, 48, 161e171. https://doi.org/10.1016/j.yjmcc.2009.08.034.

V. Scientific Research

References

Ni, Terri, T., et al. (2011). Discovering small molecules that promote cardiomyocyte generation by modulating wnt signaling. Chemistry and Biology, 18, 1658e1668. https://doi.org/10.1016/j.chembiol. 2011.09.015. North, T. E., et al. (2007). Prostaglandin E2 regulates vertebrate haematopoietic stem cell homeostasis. Nature, 447, 1007e1011. http:// www.nature.com/nature/journal/v447/n7147/suppinfo/ nature05883_S1.html. North, T. E., et al. (2010). PGE2-regulated wnt signaling and Nacetylcysteine are synergistically hepatoprotective in zebrafish acetaminophen injury. Proceedings of the National Academy of Sciences, 107, 17315e17320. https://doi.org/10.1073/ pnas.1008209107. Oppedal, D., & Goldsmith, M. I. (2010). A chemical screen to identify novel inhibitors of fin regeneration in zebrafish. Zebrafish, 7, 53e60. https://doi.org/10.1089/zeb.2009.0633. Ou, H. C., et al. (2009). Identification of FDA-approved drugs and bioactives that protect hair cells in the zebrafish (Danio rerio) lateral line and mouse (Mus musculus) utricle. Journal of the Association for Research in Otolaryngology, 10, 191e203. https://doi.org/10.1007/ s10162-009-0158-y. Ou, H. C., et al. (2012). Quinoline ring derivatives protect against aminoglycoside-induced hair cell death in the zebrafish lateral line. Journal of the Association for Research in Otolaryngology, 13, 759e770. https://doi.org/10.1007/s10162-012-0353-0. Ou, H. C., Santos, F., Raible, D. W., Simon, J. A., & Rubel, E. W. (2010). Drug screening for hearing loss: Using the zebrafish lateral line to screen for drugs that prevent and cause hearing loss. Drug Discovery Today, 15, 265e271. https://doi.org/10.1016/j.drudis.2010.01.001. Ou, H., Simon, J. A., Rubel, E. W., & Raible, D. W. (2012). Screening for chemicals that affect hair cell death and survival in the zebrafish lateral line. Hearing Research, 288, 58e66. https://doi.org/10. 1016/j.heares.2012.01.009. Owens, K. N., et al. (2008). Identification of genetic and chemical modulators of zebrafish mechanosensory hair cell death. PLoS Genetics, 4, e1000020. https://doi.org/10.1371/journal.pgen.1000020. Padilla, S., et al. (2012). Zebrafish developmental screening of the ToxCastÔ Phase I chemical library. Reproductive Toxicology, 33, 174e187. https://doi.org/10.1016/j.reprotox.2011.10.018. Paik, E. J., de Jong, J. L. O., Pugach, E., Opara, P., & Zon, L. I. (2010). A chemical genetic screen in zebrafish for pathways interacting with cdx4 in primitive hematopoiesis. Zebrafish, 7, 61e68. https://doi.org/10.1089/zeb.2009.0643. Papakyriakou, A., et al. (2014). A zebrafish in vivo phenotypic assay to identify 3-aminothiophene-2-carboxylic acid-based angiogenesis inhibitors. ASSAY and Drug Development Technologies, 12, 527e535. https://doi.org/10.1089/adt.2014.606. Pardo-Martin, C., et al. (2010). High-throughput in vivo vertebrate screening. Nature Methods, 7, 634. https://doi.org/10.1038/nmeth. 1481. supplementary-information. www.nature.com/articles/nme th.1481 Pardo-Martin, C., et al. (2013). High-throughput hyperdimensional vertebrate phenotyping. Nature Communications, 4, 1467. https:// doi.org/10.1038/ncomms2475. supplementary-information. www. nature.com/articles/ncomms2475 Peal, D. S., et al. (2011). Novel chemical suppressors of long QT syndrome identified by an in vivo functional screen. Circulation, 123, 23e30. https://doi.org/10.1161/circulationaha.110.003731. Peterson, R. T., Link, B. A., Dowling, J. E., & Schreiber, S. L. (2000). Small molecule developmental screens reveal the logic and timing of vertebrate development. Proceedings of the National Academy of Sciences, 97, 12965e12969. https://doi.org/10.1073/ pnas.97.24.12965.

673

Raftery, T. D., Isales, G. M., Yozzo, K. L., & Volz, D. C. (2014). Highcontent screening assay for identification of chemicals impacting spontaneous activity in zebrafish embryos. Environmental Science and Technology, 48, 804e810. https://doi.org/10.1021/es404322p. Rahn, J. J., et al. (2014). Novel Vitamin K analogs suppress seizures in zebrafish and mouse models of epilepsy. Neuroscience, 259, 142e154. https://doi.org/10.1016/j.neuroscience.2013.11.040. Rennekamp, A. J., et al. (2016). [sigma]1 receptor ligands control a switch between passive and active threat responses. Nature Chemical Biology, 12, 552e558. https://doi.org/10.1038/nchembio.2089. supplementary-information. http://www.nature.com/nchembio/ journal/v12/n7/abs/nchembio.2089.html Rennekamp, A. J., & Peterson, R. T. (2015). 15 years of zebrafish chemical screening. Current Opinion in Chemical Biology, 24, 58e70. https://doi.org/10.1016/j.cbpa.2014.10.025. Ridges, S., et al. (2012). Zebrafish screen identifies novel compound with selective toxicity against leukemia. Blood, 119, 5621e5631. https://doi.org/10.1182/blood-2011-12-398818. Rihel, J., et al. (2010). Zebrafish behavioral profiling links drugs to biological targets and rest/wake regulation. Science (New York, N.Y.), 327, 348e351. https://doi.org/10.1126/science.1183090. Roberts, A. C., Bill, B. R., & Glanzman, D. L. (2013). Learning and memory in zebrafish larvae. Frontiers in Neural Circuits, 7, 126. https:// doi.org/10.3389/fncir.2013.00126. Robertson, A. L., et al. (2014). A zebrafish compound screen reveals modulation of neutrophil reverse migration as an antiinflammatory mechanism. Science Translational Medicine, 6. https://doi.org/10.1126/scitranslmed.3007672, 225ra229-225ra229. Robertson, J. K., et al. (2014). Targeting the Wnt pathway in zebrafish as a screening method to identify novel therapeutic compounds. Experimental Biology and Medicine, 239, 169e176. https://doi.org/ 10.1177/1535370213514322. Rovira, M., et al. (2011). Chemical screen identifies FDA-approved drugs and target pathways that induce precocious pancreatic endocrine differentiation. Proceedings of the National Academy of Sciences, 108, 19264e19269. https://doi.org/10.1073/pnas.1113081108. Sandoval, Imelda, T., et al. (2013). Juxtaposition of chemical and mutation-induced developmental defects in zebrafish reveal a copper-chelating activity for kalihinol F. Chemistry and Biology, 20, 753e763. https://doi.org/10.1016/j.chembiol.2013.05.008. Savjani, K. T., Gajjar, A. K., & Savjani, J. K. (2012). Drug solubility: Importance and enhancement techniques. ISRN Pharmaceutics, 195727. https://doi.org/10.5402/2012/195727. Schlegel, A., & Gut, P. (2015). Metabolic insights from zebrafish genetics, physiology, and chemical biology. Cellular and Molecular Life Sciences, 72, 2249e2260. https://doi.org/10.1007/s00018-0141816-8. Schoonheim, P. J., Arrenberg, A. B., Del Bene, F., & Baier, H. (2010). Optogenetic localization and genetic perturbation of saccadegenerating neurons in zebrafish. The Journal of Neuroscience, 30, 7111e7120. https://doi.org/10.1523/JNEUROSCI.5193-09.2010. Seth, A., Stemple, D. L., & Barroso, I. (2013). The emerging use of zebrafish to model metabolic disease. Disease Models and Mechanisms, 6, 1080e1088. https://doi.org/10.1242/dmm.011346. Shafizadeh, E., Peterson, R. T., & Lin, S. (2004). Induction of reversible hemolytic anemia in living zebrafish using a novel small molecule. Comparative Biochemistry and Physiology Part C: Toxicology and Pharmacology, 138, 245e249. https://doi.org/10.1016/j.cca.2004. 05.003. Shimizu, H., et al. (2015). Mitochondrial Ca2þ uptake by the voltagedependent anion channel 2 regulates cardiac rhythmicity. eLife, 4, e04801. https://doi.org/10.7554/eLife.04801.

V. Scientific Research

674

51. Zebrafish as a Platform for Drug Screening

Stackley, K. D., Beeson, C. C., Rahn, J. J., & Chan, S. S. L. (2011). Bioenergetic profiling of zebrafish embryonic development. PLoS One, 6, e25652. https://doi.org/10.1371/journal.pone.0025652. Steinbicker, A. U., et al. (2011). Inhibition of bone morphogenetic protein signaling attenuates anemia associated with inflammation. Blood, 117, 4915e4923. https://doi.org/10.1182/blood-2010-10-313064. Sun, Y., Dong, Z., Khodabakhsh, H., Chatterjee, S., & Guo, S. (2012). Zebrafish chemical screening reveals the impairment of dopaminergic neuronal survival by cardiac glycosides. PLoS One, 7, e35645. https://doi.org/10.1371/journal.pone.0035645. Sun, Z., et al. (2004). A genetic screen in zebrafish identifies cilia genes as a principal cause of cystic kidney. Development, 131, 4085e4093. https://doi.org/10.1242/dev.01240. Tamplin, Owen, J., et al. (2015). Hematopoietic stem cell arrival triggers dynamic remodeling of the perivascular niche. Cell, 160, 241e252. https://doi.org/10.1016/j.cell.2014.12.032. Tang, C., Xie, D., & Feng, B. (2015). Zebrafish as a new model for phenotype-based screening of positive inotropic agents. Chemical Biology and Drug Design, 85, 253e258. https://doi.org/10.1111/ cbdd.12389. Thomas, A. J., et al. (2015). Identification of small molecule inhibitors of cisplatin-induced hair cell death: Results of a 10,000 compound screen in the zebrafish lateral line. Otology and Neurotology, 36, 519e525. https://doi.org/10.1097/mao.0000000000000487. Thorsteinson, N., et al. (2009). In silico identification of anthropogenic chemicals as ligands of zebrafish sex hormone binding globulin. Toxicology and Applied Pharmacology, 234, 47e57. https://doi.org/ 10.1016/j.taap.2008.07.014. Torregroza, I., Evans, T., & Das, B. C. (2009). A forward chemical screen using zebrafish embryos with novel 2-substituted 2H-chromene derivatives. Chemical Biology and Drug Design, 73, 339e345. https://doi.org/10.1111/j.1747-0285.2009.00782.x. Tran, T. C., et al. (2007). Automated, quantitative screening assay for antiangiogenic compounds using transgenic zebrafish. Cancer Research, 67, 11386e11392. https://doi.org/10.1158/00085472.can-07-3126. Tsuji, N., et al. (2014). Whole organism high content screening identifies stimulators of pancreatic beta-cell proliferation. PLoS One, 9, e104112. https://doi.org/10.1371/journal.pone.0104112. Union Biometrica. VAST BioImagerÔ. http://www.unionbio.com/ vast/. Vlasits, A. L., Simon, J. A., Raible, D. W., Rubel, E. W., & Owens, K. N. (2012). Screen of FDA-approved drug library reveals compounds that protect hair cells from aminoglycosides and cisplatin. Hearing Research, 294, 153e165. https://doi.org/10.1016/j.heares.2012.08. 002. Vornanen, M., & Hassinen, M. (2016). Zebrafish heart as a model for human cardiac electrophysiology. Channels, 10, 101e110. https:// doi.org/10.1080/19336950.2015.1121335. de Vrieze, E., Zethof, J., Schulte-Merker, S., Flik, G., & Metz, J. R. (2015). Identification of novel osteogenic compounds by an ex-vivo sp7: luciferase zebrafish scale assay. Bone, 74, 106e113. https://doi. org/10.1016/j.bone.2015.01.006. Wang, C., et al. (2010). Rosuvastatin, identified from a zebrafish chemical genetic screen for antiangiogenic compounds, suppresses the growth of prostate cancer. European Urology, 58, 418e426. https:// doi.org/10.1016/j.eururo.2010.05.024. Wang, G., et al. (2015). First quantitative high-throughput screen in zebrafish identifies novel pathways for increasing pancreatic b-cell mass. eLife, 4, e08261. https://doi.org/10.7554/eLife.08261. Wang, X., et al. (2014). Inhibitors of neutrophil recruitment identified using transgenic zebrafish to screen a natural product library. Disease Models and Mechanisms, 7, 163e169. https://doi.org/10.1242/ dmm.012047.

Wang, Y., et al. (2017). 1H NMR-based metabolomics analysis of adult zebrafish (Danio rerio) after exposure to diniconazole as well as its bioaccumulation behavior. Chemosphere, 168, 1571e1577. https:// doi.org/10.1016/j.chemosphere.2016.11.157. Wang, Y.-N., et al. (2014). Behavioural screening of zebrafish using neuroactive traditional Chinese medicine prescriptions and biological targets, 4 p. 5311). https://doi.org/10.1038/srep05311. supplementaryinformation http://dharmasastra.live.cf.private.springer.com/ articles/srep05311. Waugh, T. A., et al. (2014). Fluoxetine prevents dystrophic changes in a zebrafish model of Duchenne muscular dystrophy. Human Molecular Genetics, 23, 4651e4662. https://doi.org/10.1093/hmg/ddu185. Weger, B. D., Weger, M., Nusser, M., Brenner-Weiss, G., & Dickmeis, T. (2012). A chemical screening system for glucocorticoid stress hormone signaling in an intact vertebrate. ACS Chemical Biology, 7, 1178e1183. https://doi.org/10.1021/cb3000474. Westhoff, J. H., et al. (2013). Development of an automated imaging pipeline for the analysis of the zebrafish larval kidney. PLoS One, 8, e82137. https://doi.org/10.1371/journal.pone.0082137. White, R. M., et al. (2008). Transparent adult zebrafish as a tool for in vivo transplantation analysis. Cell Stem Cell, 2, 183e189. https://doi.org/10.1016/j.stem.2007.11.002. White, R. M., et al. (2011). DHODH modulates transcriptional elongation in the neural crest and melanoma. Nature, 471, 518e522. supplementary-information. http://www.nature.com/nature/ journal/v471/n7339/abs/10.1038-nature09882-unlocked.html Williams, Charles, H., et al. (2015). An in vivo chemical genetic screen identifies phosphodiesterase 4 as a pharmacological target for hedgehog signaling inhibition. Cell Reports, 11, 43e50. https:// doi.org/10.1016/j.celrep.2015.03.001. Wittbrodt, J. N., Liebel, U., & Gehrig, J. (2014). Generation of orientation tools for automated zebrafish screening assays using desktop 3D printing. BMC Biotechnology, 14, 36. https://doi.org/10.1186/ 1472-6750-14-36. Wittmann, C., et al. (2015). A zebrafish drug-repurposing screen reveals sGC-dependent and sGC-independent pro-inflammatory activities of nitric oxide. PLoS One, 10, e0137286. https://doi.org/ 10.1371/journal.pone.0137286. Yang, R., et al. (2015). Antimalarial drug artemisinin depletes erythrocytes by activating apoptotic pathways in zebrafish. Experimental Hematology, 43, 331e341. e338 https://doi.org/10.1016/j.exphem. 2014.11.012. Ye, B., et al. (2017). Meisoindigo, but not its core chemical structure indirubin, inhibits zebrafish interstitial leukocyte chemotactic migration. Pharmaceutical Biology, 55, 673e679. https://doi.org/ 10.1080/13880209.2016.1238949. Yeh, J.-R. J., et al. (2009). Discovering chemical modifiers of oncogeneregulated hematopoietic differentiation. Nat Chem Biol, 5, 236e243. http://www.nature.com/nchembio/journal/v5/n4/suppinfo/ nchembio.147_S1.html. Yeh, J.-R. J., & Munson, K. M. (2010). In S. Ding (Ed.), Cellular programming and reprogramming: Methods and protocols (pp. 317e327). Humana Press. Yin, C., Evason, K. J., Maher, J. J., & Stainier, D. Y. R. (2012). The basic helix-loop-helix transcription factor, heart and neural crest derivatives expressed transcript 2, marks hepatic stellate cells in zebrafish: Analysis of stellate cell entry into the developing liver. Hepatology, 56, 1958e1970. https://doi.org/10.1002/hep.25757. Yozzo, K. L., Isales, G. M., Raftery, T. D., & Volz, D. C. (2013). Highcontent screening assay for identification of chemicals impacting cardiovascular function in zebrafish embryos. Environmental Science and Technology, 47, 11302e11310. https://doi.org/10.1021/ es403360y.

V. Scientific Research

References

Yu, P. B., et al. (2008). BMP type I receptor inhibition reduces heterotopic ossification. Nature Medicine, 14, 1363e1369. http://www.nature. com/nm/journal/v14/n12/suppinfo/nm.1888_S1.html. Yu, P. B., et al. (2008). Dorsomorphin inhibits BMP signals required for embryogenesis and iron metabolism. Nature Chemical Biology, 4, 33e41. http://www.nature.com/nchembio/journal/v4/n1/suppinfo /nchembio.2007.54_S1.html. ZFIN. Zebrafish anatomy dictionary. https://zfin.org/zf_info/ anatomy/dict/lat_line/lat_line.html. Zhang, F., Qin, W., Zhang, J.-P., & Hu, C.-Q. (2015). Antibiotic toxicity and absorption in zebrafish using liquid chromatography-tandem mass spectrometry. PLoS One, 10, e0124805. https://doi.org/ 10.1371/journal.pone.0124805. Zhao, L., et al. (2014). Notch signaling regulates cardiomyocyte proliferation during zebrafish heart regeneration. Proceedings of the

675

National Academy of Sciences, 111, 1403e1408. https://doi.org/ 10.1073/pnas.1311705111. Zhen, A. W., et al. (2013). The small molecule, genistein, increases hepcidin expression in human hepatocytes. Hepatology, 58, 1315e1325. https://doi.org/10.1002/hep.26490. Zielke, N., & Edgar, B. A. (2015). FUCCI sensors: Powerful new tools for analysis of cell proliferation. Wiley Interdisciplinary Reviews: Developmental Biology, 4, 469e487. https://doi.org/10.1002/ wdev.189. Zu, Y., et al. (2013). TALEN-mediated precise genome modification by homologous recombination in zebrafish. Nature Methods, 10, 329. https://doi.org/10.1038/nmeth.2374. supplementary-information. www.nature.com/articles/nmeth.2374

V. Scientific Research