We thank S. Burkhart, C. Hofmann and Simone Gr&#228;&szlig;le for excellent technical assistance and are grateful to M. Ferg for help with data analysis. We also thank S. Rastegar for critical comments on the manuscript. We acknowledge funding by the Studienstiftung des deutschen Volkes (to MW), the DFG (DI913/4-1) and the Helmholtz Program BioInterfaces at KIT.

1. Prepare Working Dilution of Chemical Library
Predilute the compounds of the drug library to be tested (e.g. FDA approved drugs, ENZO Life Science) into E3 (5 mM NaCl, 0.17 mM KCl, 0.33 mM CaCl2) with a robotic liquid handling station (e.g. Multiprobe II, 8 needles with disposal tip adapter, PerkinElmer). Suitable concentrations are e.g. 40 &#956;g/ml in 3% DMSO, but this will depend on the type of library used. The Multiprobe II settings corresponding to the steps described below are indicated in Table 1. The protocol described in the table allows the preparation of four aliquot plates in parallel.
<ol>
	<li>Pipette 10 &#956;l aliquots of the stock library (2 mg/ml in DMSO) into deep well plates (e.g. 96-Well Storage Plate, Round Well, 0.8 ml, ABgene). Columns 1 and 12 should be left empty - these will receive the positive and negative within-plate controls.</li>
	<li>Dispense 490 &#956;l of E3 with 1% DMSO into the prepared aliquots of the library with the Multiprobe II. Dilution is performed with fixed needles without disposal tips.</li>
	<li>Add 10 &#956;l of DMSO into column 1 and 10 &#956;l of a 5 mM dexamethasone solution (in DMSO) to column 12 as within-plate controls. The concentration of DMSO in all wells is now 3%, the dexamethasone concentration in the positive control wells is 100 &#956;M in E3/3% DMSO.</li>
	<li>Seal the plate with DMSO resistant adhesive sealing sheets. Store the plates at -80 &#176;C until usage.</li>
</ol>
2. Breeding of Reporter Fish
Collect embryos from natural spawning of group matings between GRE:Luc transgenic fish. Raise embryos (not more than 60) in 9 cm Petri dishes containing E3 medium supplemented with 1 mg/ml of the fungicide methylene blue until 4 days post fertilization (dpf) in an incubator at 28 &#176;C. Change E3 medium regularly.
3. Preparation of Luciferase Medium (E3L)
Prepare an aqueous luciferin stock solution of 50 mM by adding dH2O to the vial containing the luciferin powder. This stock solution can be stored at -80 &#176;C for several months. Dilute the luciferin stock into E3 medium to a final concentration of 0.5 mM to obtain E3L medium.
4. Distribute Larvae into 96 Well Plates
<ol>
	<li>Prepare 1 ml pipette tips with wide bore by cutting off approximately 5 mm of the tip and briefly flaming the sharp edges.</li>
	<li>Pool larvae from several crosses by carefully pouring them from the Petri dishes into a beaker. Harvest about 50 larvae at a time by gently pouring them onto a sieve (pore size of 0.25 mm diameter) and immediately place the sieve into a small Petri dish (diameter 5.5 cm) filled with E3L medium.</li>
	<li>With a wide bore pipette tip, transfer 225 &#956;l of medium containing one larva each to the wells of a white 96 well plate (OptiPlate, PerkinElmer).</li>
	<li>Seal the plates with adhesive sealing sheets (e.g. TopSeal-A, PerkinElmer) and incubate them at 28 &#176;C overnight. This preincubation prevents recording of transient changes in bioluminescence immediately after addition of luciferin, a phenomenon that occurs also in cultured cells19.</li>
</ol>
5. Drug Treatment
<ol>
	<li>Remove the plate containing the working dilution of the library from the -80 &#176;C freezer about 4 hr before use. Gently vortex the plate and briefly spin it in a centrifuge to collect the liquid at the bottom of the plate.</li>
	<li>Remove adhesive sealing sheets from the larvae plates.</li>
	<li>With a hand-operated 96-channel pipetting device (e.g. Liquidator, Steinbrenner) pipette the drug solution up and down 3 times. Then aliquot 25 &#956;l of the working dilution of the chemical library into the wells containing the larvae (with the example above, this results in a final concentration of 4 &#956;g/ml in E3 with 0.3% DMSO). Prepare 10 (minimum: 5) replica plates with larvae per library plate.</li>
	<li>Seal the plates with the adhesive sealing sheets and label each plate with a barcode sticker.</li>
</ol>
6. Luminescence Recording
<ol>
	<li>Put the plates containing the larvae into the stacking units of an EnVision bioluminescence reader with enhanced luminescence sensitivity (PerkinElmer). Alternatively, use a robotized incubator system such as those employed for mammalian cell culture screening systems in combination with the reader.</li>
	<li>Record bioluminescence for two days using reader settings analogous to those described in Table 2 for the EnVision reader. Adapt the number of assay repeats to the number of plates in the run to match the required running time.</li>
	<li>After the end of the run, check the plates for the presence of dead larvae to evaluate general toxicity of the compounds.</li>
</ol>
7. Data Analysis
All data analysis is performed in the statistical programming environment R using custom scripts.
<ol>
	<li>AUC calculation 
	In order to identify compounds activating GC signaling regardless of their kinetic properties, determine the area under the curve (AUC) of the recorded luminescence traces (bioluminescence raw counts vs. time) as the screening parameter. AUCs are approximated with the trapezoidal rule (see Figures 2a and a&#39;).</li>
	<li>Normalization 
	Log transform the AUC values in order to ensure a higher normality of the data (Figures 2b and b&#39;). Then normalize the log transformed AUC values for each library plate with the robust Z-score method (see 20). This normalization results in values representing the number of standard deviations from the median of all data points. In this way, systematic errors, such as inter-run variability, are removed from the data. The data can now be visualized by plotting the mean robust Z-score of the replicas for each well (Figures 2c and c&#39;).</li>
	<li>Quality metrics
	<ol>
		<li>Heatmap 
		In order to visualize plate related effects, plot the data for each plate as a heatmap using e.g. the heatmap.2 function of the gplot package21. In this way, edge effects or compound carry-over can be easily detected (e.g. compare Figure 3a with 3b). Exclude sub-optimal plates from further analysis.</li>
		<li>ROC curve 
		To determine sensitivity and specificity of the assay, calculate a receiver operating characteristic (ROC) curve e.g. with the help of the ROC bioconductor package22 using the Z-score values determined in 7.2 (Figure 3c). Subsequently, determine the AUC of this curve. An AUC value close to 1 indicates high sensitivity and specificity of the assay.</li>
	</ol>
	</li>
	<li>Hit Identification 
	To optimize the cut-off value for the identification of active compounds, determine the Youden Index. To calculate the index, subtract the estimated true positive rate (TPR) from the false positive rate (FPR) of the ROC curve for increasing robust Z-score cut-off values. Take the robust Z-score with the highest Youden Index (TPR minus FPR) as the cut-off point. The TPR/FPR can be estimated by detection of positive control wells or of known active compounds within the library. When using positive control wells make sure that they match the anticipated hit strength.</li>
</ol>
8. Retesting
<ol>
	<li>Reevaluate positive hit compounds by treating larvae with serial dilutions of the compounds obtained from a different supplier, using the same recording set-up described above. True hits should induce luminescence also in this assay, ideally in a dose dependent manner.</li>
</ol>

<ol>
	<li>Norris, D. O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Vertebrate Endocrinology. , (2007).</li><li>Kassel, O., Herrlich, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Crosstalk+between+the+glucocorticoid+receptor+and+other+transcription+factors:+molecular+aspects.">Crosstalk between the glucocorticoid receptor and other transcription factors: molecular aspects.</a> Mol Cell Endocrinol. 275, 13-29 (2007).</li><li>Baschant, U., Tuckermann, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+role+of+the+glucocorticoid+receptor+in+inflammation+and+immunity.">The role of the glucocorticoid receptor in inflammation and immunity.</a> J Steroid Biochem Mol Biol. 120, 69-75 (2010).</li><li>Schacke, H., Docke, W. D., Asadullah, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mechanisms+involved+in+the+side+effects+of+glucocorticoids.">Mechanisms involved in the side effects of glucocorticoids.</a> Pharmacol Ther. 96, 23-43 (2002).</li><li>De Bosscher, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Selective+Glucocorticoid+Receptor+modulators.">Selective Glucocorticoid Receptor modulators.</a> J Steroid Biochem Mol Biol. 120, 96-104 (2010).</li><li>Kaufman, C. K., White, R. M., Zon, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chemical+genetic+screening+in+the+zebrafish+embryo.">Chemical genetic screening in the zebrafish embryo.</a> Nat Protoc. 4, 1422-1432 (2009).</li><li>Peal, D. S., Peterson, R. T., Milan, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Small+molecule+screening+in+zebrafish.">Small molecule screening in zebrafish.</a> J Cardiovasc Transl Res. 3, 454-460 (2010).</li><li>Casals-Casas, C., Desvergne, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Endocrine+disruptors:+from+endocrine+to+metabolic+disruption.">Endocrine disruptors: from endocrine to metabolic disruption.</a> Annu Rev Physiol. 73, 135-162 (2011).</li><li>Grun, F., Blumberg, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Minireview:+the+case+for+obesogens.">Minireview: the case for obesogens.</a> Mol Endocrinol. 23, 1127-1134 (2009).</li><li>Odermatt, A., Gumy, C., Atanasov, A. G., Dzyakanchuk, A. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Disruption+of+glucocorticoid+action+by+environmental+chemicals:+potential+mechanisms+and+relevance.">Disruption of glucocorticoid action by environmental chemicals: potential mechanisms and relevance.</a> J Steroid Biochem Mol Biol. 102, 222-231 (2006).</li><li>Odermatt, A., Gumy, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Glucocorticoid+and+mineralocorticoid+action:+why+should+we+consider+influences+by+environmental+chemicals.">Glucocorticoid and mineralocorticoid action: why should we consider influences by environmental chemicals.</a> Biochem Pharmacol. 76, 1184-1193 (2008).</li><li>Lohr, H., Hammerschmidt, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Zebrafish+in+endocrine+systems:+recent+advances+and+implications+for+human+disease.">Zebrafish in endocrine systems: recent advances and implications for human disease.</a> Annu Rev Physiol. 73, 183-211 (2011).</li><li>Schaaf, M. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Discovery+of+a+functional+glucocorticoid+receptor+beta-isoform+in+zebrafish.">Discovery of a functional glucocorticoid receptor beta-isoform in zebrafish.</a> Endocrinology. 149, 1591-1599 (2008).</li><li>Schaaf, M. J., Chatzopoulou, A., Spaink, H. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+zebrafish+as+a+model+system+for+glucocorticoid+receptor+research.">The zebrafish as a model system for glucocorticoid receptor research.</a> Comp Biochem Physiol A Mol Integr Physiol. 153, 75-82 (2009).</li><li>Alsop, D., Vijayan, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+zebrafish+stress+axis:+molecular+fallout+from+the+teleost-specific+genome+duplication+event.">The zebrafish stress axis: molecular fallout from the teleost-specific genome duplication event.</a> Gen Comp Endocrinol. 161, 62-66 (2009).</li><li>Alsop, D., Vijayan, M. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Molecular+programming+of+the+corticosteroid+stress+axis+during+zebrafish+development.">Molecular programming of the corticosteroid stress axis during zebrafish development.</a> Comp Biochem Physiol A Mol Integr Physiol. 153, 49-54 (2009).</li><li>Schoonheim, P. J., Chatzopoulou, A., Schaaf, M. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+zebrafish+as+an+in+vivo+model+system+for+glucocorticoid+resistance.">The zebrafish as an in vivo model system for glucocorticoid resistance.</a> Steroids. 75, 918-925 (2010).</li><li>Weger, B. D., Weger, M., Nusser, M., Brenner-Weiss, G., Dickmeis, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Chemical+Screening+System+for+Glucocorticoid+Stress+Hormone+Signaling+in+an+Intact+Vertebrate.">A Chemical Screening System for Glucocorticoid Stress Hormone Signaling in an Intact Vertebrate.</a> ACS Chem Biol. 7, (2012).</li><li>Hirota, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+chemical+biology+approach+reveals+period+shortening+of+the+mammalian+circadian+clock+by+specific+inhibition+of+GSK-3beta.">A chemical biology approach reveals period shortening of the mammalian circadian clock by specific inhibition of GSK-3beta.</a> Proc Natl Acad Sci U S A. 105, 20746-20751 (2008).</li><li>Birmingham, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Statistical+methods+for+analysis+of+high-throughput+RNA+interference+screens.">Statistical methods for analysis of high-throughput RNA interference screens.</a> Nat Methods. 6, 569-575 (2009).</li><li>Warnes, G. R., Bolker, B., Bonebakker, L., Gentleman, R., Liaw, W. H. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> gplots: Various R programming tools for plotting data. 2.11.0, (2012).</li><li>Carey, V., Redestig, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> ROC: utilities for ROC, with uarray focus. , (2013).</li><li>Fan, F., Wood, K. V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bioluminescent+assays+for+high-throughput+screening.">Bioluminescent assays for high-throughput screening.</a> Assay Drug Dev Technol. 5, 127-136 (2007).</li><li>Graf, S. F., Hotzel, S., Liebel, U., Stemmer, A., Knapp, H. 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We have nothing to disclose.

We present here the workflow and data analysis for a chemical screen measuring GC activity in vivo using the GRIZLY assay18. The assay has quality control characteristics and performance measures that are comparable with conventional cell based screens, an important advantage for its use in high-throughput settings. In addition, however, the in vivo assay detects also compounds that are not accessible to in vitro screens. This is exemplified by the presence of the prohormone pregnenolone among the hits. Thus, the GRIZLY assay extends the scope of screens aimed at GC signaling activity.
The importance of the detection of in vivo effects with our assay is also illustrated by results we obtained with the organotin pollutants DBT and TBT18. DBT, but not TBT, has been shown to inhibit GC signaling in mammalian cell culture, and we observed the same in zebrafish cell cultures expressing the GRE:Luc reporter. Importantly however, in the GRIZLY assay, TBT showed inhibitory activity on the GC pathway, as it can be converted to DBT by the larval metabolism. This inhibition was observed already at environmentally relevant concentrations of TBT. These results further illustrate the potential of the GRIZLY assay in detecting compound effects based on inter-organ cross-talk and metabolic modifications of the compounds in the living animal. They also highlight the application potential of the GRIZLY assay for environmental monitoring. Thus, endocrine disruptor effects can be studied at the level of receptor signaling, where the disruptor interferes with GC signaling activity induced by a GR agonist such as dexamethasone. Another possibility is to study compound effects on pregnenolone-stimulated GC synthesis. The high throughput quality of the assay should permit the rapid screening of environmental sample libraries.
The use of luciferase as a reporter gene allows for a high dynamic range of detection of signaling activity23. Indeed, the sensitivity of the assay makes it possible to detect osmotic stress-induced GC production from single larvae18. The high temporal resolution achieved with the luciferase reporter allows us to follow signaling activities over time, which makes it possible to analyze also the kinetics of the data.
A potential drawback for some applications is the limited suitability for spatial monitoring of this reporter system. Fluorescent reporter systems might be better suited for assays that require monitoring of certain areas of the larvae. However, such assays might suffer from lower sensitivities due to background effects caused by the excitation light, which also poses limits on the detection of fluorescent compounds. Additionally, they might provide less kinetic resolution because of the generally higher stability of fluorescent proteins23. Furthermore, they present challenges in terms of imaging equipment, data analysis and data storage that might limit their use for smaller research labs.
The set-up of the GRIZLY assay as a microtiter plate based assay allows for easy integration into typical screening workflows. The assay is easily applicable also in smaller research labs due to its simple handling and data analysis. At the same time, it allows for a substantial degree of automation, e.g. automated drug application by pipetting robots or automated distribution of embryos by embryo sorting devices24,25. The simple readout does not require automated screening microscopes or sophisticated image analysis software, yet provides a rich set of data on temporal and quantitative aspects of the studied signaling pathway.
In summary, we present a step-by-step protocol for a relatively inexpensive, robust and easy-to-handle chemical screening assay for GC signaling activity in vivo and in real time. The assay allows the determination of in vivo effects of compounds on GC signaling not detectable in cell culture based assays. Among the many applications for the assay are e.g. the determination of genetic effects on glucocorticoid signaling, environmental monitoring of endocrine disruptor effects on glucocorticoid synthesis and signaling activity, and the screening of compounds for unwanted effects on GC signaling or for novel in vivo modulators of this important signaling pathway.

Glucocorticoids (GCs) are steroid hormones produced by the adrenal gland which play important roles during the stress response and in the regulation of metabolism1. GCs bind cytoplasmic glucocorticoid receptors (GRs) of the nuclear receptor superfamily which, upon binding, translocate into the nucleus2. Here, they can for example repress transcription by interfering with other transcription factors (transrepression) or activate gene transcription via glucocorticoid response elements (GREs, transactivation). Due to their anti-inflammatory properties, both natural and artificial GCs are widely used drugs in the treatment of a number of diseases, such as asthma or arthritis3. However, especially long-term use of GCs can lead to severe side effects, including diabetes and glaucoma4. Therefore, novel compounds targeting GC signaling with potentially more beneficial treatment efficiency and tolerability are highly sought after. Importantly, ligand effects observed in cultured cells can differ from those seen in vivo5. Such effects might bias results obtained with conventional cell culture based pharmaceutical screening assays. Chemical in vivo screening as enabled by the zebrafish model has recently come into focus, as it allows the determination of effects not detectable in cell culture6,7.
Hormonal signaling pathways can also be affected by environmental pollutants. So-called endocrine disrupting chemicals (EDCs) affect various hormone regulated processes8. Thus, reproduction and sexual differentiation of aquatic organisms can be modulated by substances with estrogen-like activities. Recently, concerns have been raised that metabolic disorders might be linked to EDCs in the environment9. One pathway targeted by such &#34;metabolic disruption&#34; is the glucocorticoid pathway, which has also been implicated in xenobiotics effects on development and immune function10,11. However, compared with the large amount of information available on compounds interfering with sex steroid hormone action, relatively little is known about endocrine disruption effects mediated via the GR. Therefore, tools are needed that allow monitoring pollutant effects on GC signaling in vivo.
The zebrafish has long been a popular model in developmental biology and has more recently also attracted researchers from other fields, including endocrinology12. Compared with other teleosts, the GC signaling system of zebrafish is more similar to that of mammals, since the zebrafish genome contains only one GR gene as opposed to the duplicated receptors in many other fish species13-15. In addition, the hypothalamic-pituitary-adrenal axis is already functional in 5 day old zebrafish larvae, which increase endogenous GC production in response to stressors14,16-18.
We have recently generated a transgenic zebrafish line, GRE:Luc, which allows for the monitoring of GC signaling activity in vivo and in real-time18. The line carries a luciferase reporter gene construct under control of a minimal TATA box promoter and four concatemerized GREs (Figure 1a). GC induced bioluminescence can be measured from single GRE:Luc larvae in 96 well microtiter plates in vivo over prolonged periods of time. This GRIZLY assay (for &#34;Glucocorticoid Responsive In vivo Zebrafish Luciferase activitY&#34;) can be used in a number of different research fields, such as stress research, environmental monitoring, and pharmacological screens18. We were able to detect the endogenous rise in cortisol after osmotic stress from single larvae and could follow the maturation of the response during development. Furthermore, we could monitor the effects on GC signaling of organotins that require metabolization by the larva. Importantly, the line was able to detect these effects at environmentally relevant concentrations. Finally, in a pilot screen the assay sensitively and specifically detected compounds with GC activity from a chemical library, including one compound that stimulated endogenous cortisol production in the larvae. Here, we describe a detailed protocol for chemical screens using the GRIZLY assay.

<table border="1">
	<tbody>
		<tr>
			<td>Name</td>
			<td>Company</td>
			<td>Catalog Number</td>
			<td>Comments</td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td></td>
			<td>Buffer composition + reagents</td>
		</tr>
		<tr>
			<td>Dimethyl sulphoxide (DMSO)</td>
			<td>Carl Roth GmbH &#38; Co KG</td>
			<td>A994.2</td>
			<td></td>
		</tr>
		<tr>
			<td>FDA approved drug library</td>
			<td>Enzo Life Sciences</td>
			<td>BML-2841-0100</td>
			<td></td>
		</tr>
		<tr>
			<td>Luciferin</td>
			<td>Biosynth</td>
			<td>L-8220</td>
			<td></td>
		</tr>
		<tr>
			<td>Dexamethasone</td>
			<td>Sigma-Aldrich</td>
			<td>D4902</td>
			<td></td>
		</tr>
		<tr>
			<td>Methylene Blue</td>
			<td>Sigma-Aldrich</td>
			<td>M9140</td>
			<td></td>
		</tr>
		<tr>
			<td>E3</td>
			<td>N/A</td>
			<td>N/A</td>
			<td>5 mM NaCl, 0.17 mM KCl, 0.33 mM CaCl2</td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td></td>
			<td>Instruments</td>
		</tr>
		<tr>
			<td>Multiprobe II</td>
			<td>PerkinElmer</td>
			<td></td>
			<td>8 channel, equipped with disposable tip adaptor</td>
		</tr>
		<tr>
			<td>Liquidator 96</td>
			<td>Steinbrenner Laborsysteme</td>
 <td></td>
			<td>hand-operated 96-channel pipette</td>
		</tr>
		<tr>
			<td>EnVision XCite Multilabel Plate Reader</td>
			<td>PerkinElmer</td>
			<td></td>
			<td>Equipped with stacker automation, temperature control, barcode reader and enhanced luminescence detector</td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td></td>
			<td>Plasticware + consumables</td>
		</tr>
		<tr>
			<td>96-Well Storage Plate</td>
			<td>ABgene</td>
			<td>AB-0765</td>
			<td>round well, 0.8 ml</td>
		</tr>
		<tr>
			<td>Cover films,</td>
			<td>ratiolab</td>
			<td>6018412</td>
			<td>self adhesive, DMSO resistent</td>
		</tr>
		<tr>
			<td>Pipette tips</td>
			<td>Steinbrenner Laborsysteme</td>
			<td>LRF-200L</td>
			<td>for liquidator 96, 200 &#956;l, low retention</td>
		</tr>
		<tr>
			<td>TopSeal-A</td>
			<td>PerkinElmer</td>
			<td>6005185</td>
			<td></td>
		</tr>
		<tr>
			<td>OptiPlate-96</td>
			<td>PerkinElmer</td>
			<td>6005299</td>
			<td>white opaque 96-well microplate</td>
		</tr>
		<tr>
			<td>Barcode Labels</td>
			<td>PerkinElmer</td>
			<td>1608182</td>
			<td></td>
		</tr>
		<tr>
			<td>filtered polypropylene IsoTip pipette tips</td>
			<td>Corning</td>
			<td>S058.4809</td>
			<td></td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td></td>
			<td>Animals</td>
		</tr>
		<tr>
			<td>GRE:Luc fish</td>
			<td>N/A</td>
			<td>ZDB-TGCONSTRCT-120920-1</td>
			<td>available at the European Zebrafish Resource Centre EZRC, Karlsruhe</td>
		</tr>
	</tbody>
</table>

a chemical screening procedure for glucocorticoid signaling with a zebrafish larva luciferase reporter system

Glucocorticoid stress hormones and their artificial derivatives are widely used drugs to treat inflammation, but long-term treatment with glucocorticoids can lead to severe side effects. Test systems are needed to search for novel compounds influencing glucocorticoid signaling in vivo or to determine unwanted effects of compounds on the glucocorticoid signaling pathway. We have established a transgenic zebrafish assay which allows the measurement of glucocorticoid signaling activity in vivo and in real-time, the GRIZLY assay (Glucocorticoid Responsive In vivo Zebrafish Luciferase activitY). The luciferase-based assay detects effects on glucocorticoid signaling with high sensitivity and specificity, including effects by compounds that require metabolization or affect endogenous glucocorticoid production. We present here a detailed protocol for conducting chemical screens with this assay. We describe data acquisition, normalization, and analysis, placing a focus on quality control and data visualization. The assay provides a simple, time-resolved, and quantitative readout. It can be operated as a stand-alone platform, but is also easily integrated into high-throughput screening workflows. It furthermore allows for many applications beyond chemical screening, such as environmental monitoring of endocrine disruptors or stress research.

In a previous publication18, we screened a library of 640 FDA approved drugs in a pilot screen to evaluate the performance of the GRIZLY assay. This library contained 12 bona fide GCs, thereby allowing us to determine quality measures for sensitivity and specificity of the assay.
Figure 2 shows typical examples of the raw data analysis and normalization taken from this screen. A typical result from a dexamethasone control well is depicted in Figure 2a, illustrating the temporal information given by the data. A peak in bioluminescence that occurs at about 12 hr after the treatment slowly decreases over the following 36 hr of measurement. Figure 2a&#39; highlights the approximation of the AUC value using the trapezoidal method. This calculation is carried out for all wells and each technical repeat. The result of the log transformation is shown in Figures 2b and b&#39;. Here the mean of the positive controls are plotted in a normal Q-Q plot. Log transformation leads to a greater approximation of the data points to the theoretical normally distributed values indicated by the red diagonals. A transformation to achieve normality of the data increases the statistical power of the subsequent analyses. Finally, Figures 2c and 2c&#39; show the effect of robust Z-score normalization on plate-to-plate variability: The different baseline values obtained with different plates (Figure 2c) are normalized in the robust Z-score plot in Figure 2c&#39;.
The robust Z-score values can be used to identify systematic errors in the data by visualizing the distribution of the hits across the plates. Figure 3a shows one example of a heatmap of a library plate, in which the robust Z-score values are plotted color-coded into the well positions. One easily identifies column 12 with the in-plate positive controls. Positive scoring library compounds are seen in well F8 and, albeit weaker, E2. Figure 3b shows a plate in which a systematic error is present. One observes a series of compounds with decreasing Z-score values in rows A and E over several columns. None of the compounds in these wells was tested positive in the re-test. Since the wells with this decreasing GRIZLY test activity are placed along the path the pipetting robot takes when aliquoting the library plates, this pattern is indicative of carry-over of a positive compound during the automated pipetting process.
The robust Z-score normalization together with the presence of known GCs in the library also enabled us to calculate a receiver operating characteristic (ROC) curve for the screen18. Figure 3c shows a plot of the estimated true positive rate against the estimated false positive rate for different robust Z-score cut-off values. The estimated true positive rate is defined as the percentage of true positive hits (here, the known glucocorticoids present in the library) that are found at a given robust Z-score cut-off value. The corresponding estimated false positive rate indicates the percentage of non-positive compounds hit at this cut-off value. The AUC of this curve is 0.95, indicating a high sensitivity and specificity of the screen and excellent assay performance. The AUC curve was also used to estimate the optimal cut-off value for hit identification by calculating the Youden index for different robust Z-scores. We identified the robust Z-score of 1.49 as having the highest Youden index. This cut-off value is indicated in Figure 2c&#39; as a black line separating the hits from the bulk of the compounds.
In our screen18, we were able to identify nearly all known GCs present in the library. Only three of the 12 bona fide GCs were not detected. In the case of melengestrol acetate, this was a false negative finding, since this compound tested positive in the re-test at a higher concentration than the one used in the library. The other two GCs were negative also in the re-test. Corticosterone is the major GC in rodents, but not in fish or humans1, while the prodrug prednisone might not be metabolized well by the larval system. Interestingly, also two drugs not annotated as GCs were identified in the screen, of which one could not be confirmed in the re-test (spironolactone, a mineralocorticoid receptor antagonist). The other compound, pregnenolone, is a precursor in steroid biosynthesis, which is converted to cortisol by the adrenal gland. Indeed, treatment with pregnenolone stimulated cortisol production in the larvae18. All these results confirm the high performance of the assay: only one false negative and one false positive compound were among the primary screen results, and 10 of the 11 confirmed compounds with GC signaling stimulating activity were already identified in the primary screen.
<img alt="Figure 1" fo:content-width="6in" src="/files/ftp_upload/50439/50439fig1.jpg" /> 
Figure 1. General principle of the assay and work flow of the screening procedure. a) Scheme of the GRIZLY assay reporter construct. Luciferase (yellow) expression is controlled by a minimal promoter (Pmin, orange) and four concatemerized GRE elements ((GRE)4, white), which are bound by ligand-activated GR homodimers (GR, blue). Red boxes indicate Tol2 transposase sites that facilitate integration of the construct into the genome. The pink box represents a poly-adenylation site (pA). Transgenic larvae carrying this construct are placed in opaque 96 well microtiter plates for bioluminescence measurements. b) Scheme of the luciferase reaction. Luciferase catalyzes the oxidation of luciferin to oxyluciferin, which leads to light emission (h&#957;). The reaction requires also ATP and Mg2+, which is provided by the larva. PPi, pyrophosphate. c) Workflow of the screen. Working stock dilutions are prepared from an FDA approved drug library in 96 well plates, one column containing a negative within-plate control (DMSO only, green) and one column containing a positive control (Dexamethasone, red) (library design). GRE:Luc larvae are distributed in 96 well plates (5-11 replicates) and treated with the library compounds (drug application). Bioluminescence traces are recorded with a bioluminescence reader for two days (data collection). Bioluminescence traces are integrated (AUC calculations), log transformed and robust Z-score normalized (normalization). Normalized data are used for determining quality metrics and for hit identification (data analysis). Chosen hits are retested for dose-dependent activity in the assay (retest). <a href="https://www.jove.com/files/ftp_upload/50439/50439fig1large.jpg" target="_blank"> Click here to view larger figure</a>.
<img alt="Figure 2" fo:content-width="6in" src="/files/ftp_upload/50439/50439fig2.jpg" /> 
Figure 2. Data analysis illustrated with data from a screen of a FDA approved drug library. a) Representative trace from a positive control well. a&#39;) The area under the curve (AUC) is approximated with the trapezoid rule. The trapezoids used for the calculation are shown in different shades of red. b) Normal Q-Q plot of raw AUC values of the positive control wells (y-axis) vs. a standard normal population (x-axis) before log transformation. b&#39;) Normal Q-Q plot of the AUC values after log transformation. A normal distribution is indicated by the linearity of the log transformed data points. c) Plot of log transformed raw data for all compounds tested in the screen. Blue, bona fide glucocorticoids; grey, all other compounds. c&#39;) Plot of screen data after robust Z-score normalization. Systematic errors such as inter-plate variations have been removed from the data. Red lines indicate the mean &#177; s.e.m. of positive within-plate controls. Black line: hit identification cut-off value as determined by Youden-Index optimization (Figure 3). Reproduced with permission from14, 2012 ACS. <a href="https://www.jove.com/files/ftp_upload/50439/50439fig2large.jpg" target="_blank"> Click here to view larger figure</a>.
<img alt="Figure 3" fo:content-width="4.5in" src="/files/ftp_upload/50439/50439fig3.jpg" /> 
Figure 3. Screen results. a) Heatmap of screen results. Robust Z-score values of library compounds are plotted into the respective well positions. The positive controls in column 12 as well as two positive hit compounds in wells F8 and E2 are visible. b) Heatmap of a plate showing carry-over of a positive compound during library preparation with a pipetting robot. A gradient of activity is visible along the pipetting path taken by the robot. c) Receiver operating characteristic (ROC) curve for the screen. The estimated true positive rates (left-hand y-axis) and false positive rates (x-axis) are plotted for increasing robust Z-score cut-off values (color coded, right-hand y-axis). The AUC value of the resulting curve is close to 1, indicating good assay performance. Reproduced with permission from 14, 2012 ACS. d) Table showing compounds active (yellow) or inactive (blue) in the primary screen (prim.) or in the retest. Bona fide glucocorticoids were not always retested (white). Redrawn with permission from14, 2012 ACS. <a href="https://www.jove.com/files/ftp_upload/50439/50439fig3large.jpg" target="_blank"> Click here to view larger figure</a>.
<table border="1" fo:keep-together.within-page="always">
	<tbody>
		<tr>
			<td colspan="4">General settings: </td>
		</tr>
		<tr>
			<td colspan="4">Step 1.1</td>
		</tr>
		<tr>
			<td>Procedure </td>
			<td>type:</td>
			<td colspan="2">single liquid</td>
		</tr>
		<tr>
			<td> </td>
			<td>mode:</td>
			<td colspan="2">blow out</td>
		</tr>
		<tr>
			<td> </td>
			<td>dispenses per aspirate:</td>
			<td colspan="2">1</td>
		</tr>
		<tr>
			<td> </td>
			<td>optimize for speed:</td>
			<td colspan="2">Yes</td>
		</tr>
		<tr>
			<td> </td>
			<td>air gaps system:</td>
			<td colspan="2">10 &#956;l</td>
		</tr>
		<tr>
			<td> </td>
			<td>transport:</td>
			<td colspan="2">0</td>
		</tr>
		<tr>
			<td>Flush/Wash </td>
			<td colspan="3" width="426">No </td>
		</tr>
		<tr>
			<td>Aspirate </td>
			<td>Type of setting </td>
			<td>Value </td>
			<td>remarks </td>
		</tr>
		<tr>
			<td> </td>
			<td>Position</td>
			<td>B7, B10, B13, B16</td>
			<td> </td>
		</tr>
		<tr>
			<td> </td>
			<td>Aspirate Vol.</td>
			<td>10 &#956;l</td>
			<td> </td>
		</tr>
		<tr>
			<td> </td>
			<td>Speed</td>
			<td>200 &#956;l/sec</td>
			<td> </td>
		</tr>
		<tr>
			<td> </td>
			<td>Liquid tracking</td>
			<td>60%</td>
			<td> </td>
		</tr>
		<tr>
			<td> </td>
			<td>Aspirate Height</td>
			<td>Labware default</td>
			<td>22.28</td>
		</tr>
		<tr>
			<td>Dispense </td>
			<td>Type of setting </td>
			<td>Value </td>
			<td>remarks </td>
		</tr>
		<tr>
			<td> </td>
			<td>Positions</td>
			<td>D7, D10, D13, D16</td>
			<td> </td>
		</tr>
		<tr>
			<td> </td>
			<td>Dispense Vol.</td>
			<td>10 &#956;l</td>
			<td> </td>
		</tr>
		<tr>
			<td> </td>
			<td>Speed</td>
			<td>200 &#956;l/sec</td>
			<td> </td>
		</tr>
		<tr>
			<td> </td>
			<td>Liquid tracking</td>
			<td>100 &#956;l</td>
			<td> </td>
		</tr>
		<tr>
			<td> </td>
			<td>Dispense Height</td>
			<td>Labware default</td>
			<td>17.01</td>
		</tr>
		<tr>
			<td colspan="4">Step 1.2 </td>
		</tr>
		<tr>
			<td>Procedure </td>
			<td>type: </td>
			<td colspan="2">reagent </td>
		</tr>
		<tr>
			<td> </td>
			<td>mode:</td>
			<td colspan="2">waste</td>
		</tr>
		<tr>
			<td> </td>
			<td>dispenses per aspirate:</td>
			<td colspan="2">3</td>
		</tr>
		<tr>
			<td> </td>
			<td>optimize for speed:</td>
			<td colspan="2">Yes</td>
		</tr>
		<tr>
			<td> </td>
			<td>air gaps system:</td>
			<td colspan="2">15 &#956;l</td>
		</tr>
		<tr>
			<td> </td>
			<td>transport:</td>
			<td colspan="2">0</td>
		</tr>
		<tr>
			<td colspan="2">Flush/Wash </td>
			<td colspan="2">No </td>
		</tr>
		<tr>
			<td>Aspirate </td>
			<td>Type of setting </td>
			<td>Value </td>
			<td>remarks </td>
		</tr>
		<tr>
			<td> </td>
			<td>Position</td>
			<td>A4</td>
			<td> </td>
		</tr>
		<tr>
			<td> </td>
			<td>Aspirate Vol.</td>
			<td>3 x 490 &#956;l</td>
			<td> </td>
		</tr>
		<tr>
			<td> </td>
			<td>Air gaps</td>
			<td>15 and 0</td>
			<td> </td>
		</tr>
		<tr>
			<td> </td>
			<td>Speed</td>
			<td>200 &#956;l/sec</td>
			<td> </td>
		</tr>
		<tr>
			<td> </td>
			<td>Liquid tracking</td>
			<td>400%</td>
			<td> </td>
		</tr>
		<tr>
			<td> </td>
			<td>Aspirate Height</td>
			<td>Liquid surface</td>
			<td> </td>
		</tr>
		<tr>
			<td>Dispense </td>
			<td>Type of setting </td>
			<td>Value </td>
			<td>remarks </td>
		</tr>
		<tr>
			<td> </td>
			<td>Position</td>
			<td>D7, D10, D13, D16</td>
			<td> </td>
		</tr>
		<tr>
			<td> </td>
			<td>Dispense Vol.</td>
			<td>490 &#956;l</td>
			<td> </td>
		</tr>
		<tr>
			<td> </td>
			<td>Air gaps</td>
			<td>15 and 0</td>
			<td> </td>
		</tr>
		<tr>
			<td> </td>
			<td>Speed</td>
			<td>200 &#956;l/sec</td>
			<td> </td>
		</tr>
		<tr>
			<td> </td>
			<td>Liquid tracking</td>
			<td>100%</td>
			<td> </td>
		</tr>
		<tr>
			<td> </td>
			<td>Dispense Height</td>
			<td>Labware default</td>
			<td>17.01</td>
		</tr>
	</tbody>
</table>
Table 1. Settings for Multiprobe II. The protocol in Table 1 describes the preparation of 4 plates (each 96 wells). The plates are located on plate adapters in the working area at positions specified by the robot (e.g. B7, B10, B13, B16).
<table border="1" fo:keep-together.within-page="always">
	<tbody>
		<tr>
			<td colspan="4">General settings:</td>
		</tr>
		<tr>
			<td colspan="2">Number of assay repeats </td>
			<td colspan="2">dependent on the length of the run </td>
		</tr>
		<tr>
			<td colspan="2">Number of plates</td>
			<td colspan="2">unlimited</td>
		</tr>
		<tr>
			<td colspan="2">Temperature control</td>
			<td colspan="2">28 &#176;C</td>
		</tr>
		<tr>
			<td colspan="2">Protocol </td>
			<td colspan="2">Calculations </td>
		</tr>
		<tr>
			<td> </td>
			<td colspan="3">US Lum 96 (cps) read</td>
		</tr>
		<tr>
			<td> </td>
			<td>Measurement time</td>
			<td>2.5 sec</td>
			<td rowspan="3">Crosstalk correction</td>
		</tr>
		<tr>
			<td> </td>
			<td>Distance between plate and detector</td>
			<td>0 mm</td>
		</tr>
		<tr>
			<td> </td>
			<td>Glow (CT2) correction factor</td>
			<td>0 %</td>
		</tr>
	</tbody>
</table>
Table 2. EnVision settings used for the screen.

Watch this Scientific Journal Video about A Chemical Screening Procedure for Glucocorticoid Signaling with a Zebrafish Larva Luciferase Reporter System at JoVE.com

A Chemical Screening Procedure for Glucocorticoid Signaling with a Zebrafish Larva Luciferase Reporter System | Biology  | Video

A Chemical Screening Procedure for Glucocorticoid Signaling with a Zebrafish Larva Luciferase Reporter System

We describe the procedure and data analysis of a chemical screening system for glucocorticoid stress hormone signaling using zebrafish larvae: the Glucocorticoid Responsive In vivo Zebrafish Luciferase activitY (GRIZLY) assay. The assay sensitively and specifically detects effects on glucocorticoid signaling by compounds that require metabolization or affect endogenous glucocorticoid production.

Glucocorticoid stress hormones and their artificial derivatives are widely used drugs to treat inflammation, but long-term treatment with glucocorticoids ...

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11.8K Views.  Karlsruhe Institute of Technology - Campus North. We describe the procedure and data analysis of a chemical screening system for glucocorticoid stress hormone signaling using zebrafish larvae: the Glucocorticoid Responsive In vivo Zebrafish Luciferase activitY (GRIZLY) assay. The assay sensitively and specifically detects effects on glucocorticoid signaling by compounds that require metabolization or affect endogenous glucocorticoid production.

Video: A Chemical Screening Procedure for Glucocorticoid Signaling with a Zebrafish Larva Luciferase Reporter System

Studying Membrane Biogenesis with a Luciferase-Based Reporter Gene Assay

To study the coordination of different lipid synthesis pathways during membrane biogenesis it is useful to work with an experimental system where membrane biogenesis occurs rapidly and in an inducible manner. We have found that phagocytosis of latex beads is practical for these purposes as cells rapidly synthesize membrane lipids to replenish membrane pools lost as  wrapping material  during particle engulfment. Here, we describe procedures for studying changes in phagocytosis-induced gene expression with a luciferase-based reporter gene approach using the Dual-Glo  Luciferase Assay System from Promega.

Here, we describe procedures for studying changes in phagocytosis-induced gene expression with a luciferase-based reporter gene approach using the Dual-GloTM Luciferase Assay System from Promega.

To study the coordination of different lipid synthesis pathways during membrane biogenesis it is useful to work with an experimental system where membrane ...

Development of automated imaging and analysis for zebrafish chemical screens.

We demonstrate the application of image-based high-content screening (HCS) methodology to identify small molecules that can modulate the FGF/RAS/MAPK pathway in zebrafish embryos. The zebrafish embryo is an ideal system for in vivo high-content chemical screens. The 1-day old embryo is approximately 1mm in diameter and can be easily arrayed into 96-well plates, a standard format for high throughput screening. During the first day of development, embryos are transparent with most of the major organs present, thus enabling visualization of tissue formation during embryogenesis. The complete automation of zebrafish chemical screens is still a challenge, however, particularly in the development of automated image acquisition and analysis. We previously generated a transgenic reporter line that expresses green fluorescent protein (GFP) under the control of FGF activity and demonstrated their utility in chemical screens 1. To establish methodology for high throughput whole organism screens, we developed a system for automated imaging and analysis of zebrafish embryos at 24-48 hours post fertilization (hpf) in 96-well plates 2. In this video we highlight the procedures for arraying transgenic embryos into multiwell plates at 24hpf and the addition of a small molecule (BCI) that hyperactivates FGF signaling 3. The plates are incubated for 6 hours followed by the addition of tricaine to anesthetize larvae prior to automated imaging on a Molecular Devices ImageXpress Ultra laser scanning confocal HCS reader. Images are processed by Definiens Developer software using a Cognition Network Technology algorithm that we developed to detect and quantify expression of GFP in the heads of transgenic embryos. In this example we highlight the ability of the algorithm to measure dose-dependent effects of BCI on GFP reporter gene expression in treated embryos.

We report the development of a system for automated imaging and analysis of zebrafish transgenic embryos in multiwell plates. This demonstrates the ability to measure dose dependent effects of a small molecule, BCI, on Fibroblast Growth Factor reporter gene expression and provide technology for establishing high-throughput zebrafish chemical screens.

We demonstrate the application of image-based high-content screening (HCS) methodology to identify small molecules that can modulate the FGF/RAS/MAPK ...

Lineage Labeling of Zebrafish Cells with Laser Uncagable Fluorescein Dextran

A central problem in developmental biology is to deduce the origin of the myriad cell types present in vertebrates as they arise from undifferentiated precursors. Researchers have employed various methods of lineage labeling, such as DiI labeling1 and pressure injection of traceable enzymes2 to ascertain cell fate at later stages of development in model systems. The first fate maps in zebrafish (Danio rerio) were assembled by iontophoretic injection of fluorescent dyes, such as rhodamine dextran, into single cells in discrete regions of the embryo and tracing the labeled cell's fate over time3-5. While effective, these methods are technically demanding and require specialized equipment not commonly found in zebrafish labs. Recently, photoconvertable fluorescent proteins, such as Eos and Kaede, which irreversibly switch from green to red fluorescence when exposed to ultraviolet light, are seeing increased use in zebrafish6-8. The optical clarity of the zebrafish embryo and the relative ease of transgenesis have made these particularily attractive tools for lineage labeling and to observe the migration of cells in vivo7. Despite their utility, these proteins have some disadvantages compared to dye-mediated lineage labeling methods. The most crucial is the difficulty we have found in obtaining high 3-D resolution during photoconversion of these proteins. In this light, perhaps the best combination of resolution and ease of use for lineage labeling in zebrafish makes use of caged fluorescein dextran, a fluorescent dye that is bound to a quenching group that masks its fluorescence9. The dye can then be "uncaged" (released from the quenching group) within a specific cell using UV light from a laser or mercury lamp, allowing visualization of its fluorescence or immunodetection. Unlike iontophoretic methods, caged fluorescein can be injected with standard injection apparatuses and uncaged with an epifluorescence microscope equipped with a pinhole10. In addition, antibodies against fluorescein detect only the uncaged form, and the epitope survives fixation well11. Finally, caged fluorescein can be activated with very high 3-D resolution, especially if two-photon microscopy is employed 12,13. This protocol describes a method of lineage labeling by caged fluorescein and laser uncaging. Subsequenctly, uncaged fluorescein is detected simultaneously with other epitopes such as GFP by labeling with antibodies.

This protocol delineates a way to label and trace the fate of small groups of cells zebrafish embryos using UV-uncaging of caged fluorescein, followed by whole mount immunolabeling to amplify the signal from the uncaged fluorescein.

A central problem in developmental biology is to deduce the origin of the myriad cell types present in vertebrates as they arise from undifferentiated ...

Identifying Targets of Human microRNAs with the LightSwitch Luciferase Assay System using 3'UTR-reporter Constructs and a microRNA Mimic in Adherent Cells

MicroRNAs (miRNAs) are important regulators of gene expression and play a role in many biological processes. More than 700 human miRNAs have been identified so far with each having up to hundreds of unique target mRNAs. Computational tools, expression and proteomics assays, and chromatin-immunoprecipitation-based techniques provide important clues for identifying mRNAs that are direct targets of a particular miRNA. In addition, 3'UTR-reporter assays have become an important component of thorough miRNA target studies because they provide functional evidence for and quantitate the effects of specific miRNA-3'UTR interactions in a cell-based system. To enable more researchers to leverage 3'UTR-reporter assays and to support the scale-up of such assays to high-throughput levels, we have created a genome-wide collection of human 3'UTR luciferase reporters in the highly-optimized LightSwitch Luciferase Assay System. The system also includes synthetic miRNA target reporter constructs for use as positive controls, various endogenous 3'UTR reporter constructs, and a series of standardized experimental protocols.
Here we describe a method for co-transfection of individual 3'UTR-reporter constructs along with a miRNA mimic that is efficient, reproducible, and amenable to high-throughput analysis.

Identifying Targets of Human microRNAs with the LightSwitch Luciferase Assay System using 3&#039;UTR-reporter Constructs and a microRNA Mimic in Adherent Cells

MicroRNAs (miRNAs) are important regulators of gene expression and have been shown to play a role in numerous biological processes. To better understand miRNA-UTR interactions, we have created a genome-wide collection of 3 UTR luciferase reporters paired with a novel luciferase gene and assay reagent, the LightSwitch system.

MicroRNAs (miRNAs) are important regulators of gene expression and play a role in many biological processes.  More than 700 human miRNAs have been ...

RNAi Screening to Identify Postembryonic Phenotypes in C. elegans

C. elegans has proven to be a valuable model system for the discovery and functional characterization of many genes and gene pathways1. More sophisticated tools and resources for studies in this system are facilitating continued discovery of genes with more subtle phenotypes or roles. 
Here we present a generalized protocol we adapted for identifying C. elegans genes with postembryonic phenotypes of interest using RNAi2. This procedure is easily modified to assay the phenotype of choice, whether by light or fluorescence optics on a dissecting or compound microscope. This screening protocol capitalizes on the physical assets of the organism and molecular tools the C. elegans research community has produced. As an example, we demonstrate the use of an integrated transgene that expresses a fluorescent product in an RNAi screen to identify genes required for the normal localization of this product in late stage larvae and adults. First, we used a commercially available genomic RNAi library with full-length cDNA inserts. This library facilitates the rapid identification of multiple candidates by RNAi reduction of the candidate gene product. Second, we generated an integrated transgene that expresses our fluorecently tagged protein of interest in an RNAi-sensitive background. Third, by exposing hatched animals to RNAi, this screen permits identification of gene products that have a vital embryonic role that would otherwise mask a post-embryonic role in regulating the protein of interest. Lastly, this screen uses a compound microscope equipped for single cell resolution.

RNAi Screening to Identify Postembryonic Phenotypes in C. elegans

We describe a sensitized method to identify postembryonic regulators of protein expression and localization in C. elegans using an RNAi-based genomic screen and an integrated transgene that expresses a functional, fluorescently tagged protein.

C. elegans has proven to be a valuable model system for the discovery and functional characterization of many genes and gene pathways1. More sophisticated ...

High-throughput Functional Screening using a Homemade Dual-glow Luciferase Assay

We present a rapid and inexpensive high-throughput screening protocol to identify transcriptional regulators of alpha-synuclein, a gene associated with Parkinson&#39;s disease. 293T cells are transiently transfected with plasmids from an arrayed ORF expression library, together with luciferase reporter plasmids, in a one-gene-per-well microplate format. Firefly luciferase activity is assayed after 48 hr to determine the effects of each library gene upon alpha-synuclein transcription, normalized to expression from an internal control construct (a hCMV promoter directing Renilla luciferase). This protocol is facilitated by a bench-top robot enclosed in a biosafety cabinet, which performs aseptic liquid handling in 96-well format. Our automated transfection protocol is readily adaptable to high-throughput lentiviral library production or other functional screening protocols requiring triple-transfections of large numbers of unique library plasmids in conjunction with a common set of helper plasmids. We also present an inexpensive and validated alternative to commercially-available, dual luciferase reagents which employs PTC124, EDTA, and pyrophosphate to suppress firefly luciferase activity prior to measurement of Renilla luciferase. Using these methods, we screened 7,670 human genes and identified 68 regulators of alpha-synuclein. This protocol is easily modifiable to target other genes of interest.

We present a rapid and inexpensive screening method for identifying transcriptional regulators using high-throughput robotic transfections and a homemade dual-glow luciferase assay. This protocol rapidly generates direct side-by-side functional data for thousands of genes and is easily modifiable to target any gene of interest.

We present a rapid and inexpensive high-throughput screening protocol to identify transcriptional regulators of alpha-synuclein, a gene associated with ...

RNA Catalyst as a Reporter for Screening Drugs against RNA Editing in Trypanosomes

Substantial progress has been made in determining the mechanism of mitochondrial RNA editing in trypanosomes. Similarly, considerable progress has been made in identifying the components of the editosome complex that catalyze RNA editing. However, it is still not clear how those proteins work together. Chemical compounds obtained from a high-throughput screen against the editosome may block or affect one or more steps in the editing cycle. Therefore, the identification of new chemical compounds will generate valuable molecular probes for dissecting the editosome function and assembly. In previous studies, in vitro editing assays were carried out using radio-labeled RNA. These assays are time consuming, inefficient and unsuitable for high-throughput purposes. Here, a homogenous fluorescence-based &#8220;mix and measure&#8221; hammerhead ribozyme in vitro reporter assay to monitor RNA editing, is presented. Only as a consequence of RNA editing of the hammerhead ribozyme a fluorescence resonance energy transfer (FRET) oligoribonucleotide substrate undergoes cleavage. This in turn results in separation of the fluorophore from the quencher thereby producing a signal. In contrast, when the editosome function is inhibited, the fluorescence signal will be quenched. This is a highly sensitive and simple assay that should be generally applicable to monitor in vitro RNA editing or high throughput screening of chemicals that can inhibit the editosome function.

A highly sensitive ribozyme-based assay, applicable to high-throughput screening of chemicals targeting the unique process of RNA editing in trypanosomatid pathogens, is described in this paper. Inhibitors can be used as tools for hypothesis-driven analysis of the RNA editing process and ultimately as therapeutics.

Substantial progress has been made in determining the mechanism of mitochondrial RNA editing in trypanosomes. Similarly, considerable progress has been ...

High-throughput Screening for Chemical Modulators of Post-transcriptionally Regulated Genes

Both transcriptional and post-transcriptional regulation have a profound impact on genes expression. However, commonly adopted cell-based screening assays focus on transcriptional regulation, being essentially aimed at the identification of promoter-targeting molecules. As a result, post-transcriptional mechanisms are largely uncovered by gene expression targeted drug development. Here we describe a cell-based assay aimed at investigating the role of the 3&#39; untranslated region (3&#8217; UTR) in the modulation of the fate of its mRNA, and at identifying compounds able to modify it. The assay is based on the use of a luciferase reporter construct containing the 3&#8217; UTR of a gene of interest stably integrated into a disease-relevant cell line. The protocol is divided into two parts, with the initial focus on the primary screening aimed at the identification of molecules affecting luciferase activity after 24 hr of treatment. The second part of the protocol describes the counter-screening necessary to discriminate compounds modulating luciferase activity specifically through the 3&#8217; UTR. In addition to the detailed protocol and representative results, we provide important considerations about the assay development and the validation of the hit(s) on the endogenous target. The described cell-based reporter gene assay will allow scientists to identify molecules modulating protein levels via post-transcriptional mechanisms dependent on a 3&#8217; UTR.

Here we describe a cell-based reporter gene assay as a valuable tool to screen chemical libraries for compounds modulating post-transcriptional control mechanisms exerted through 3&#8217; UTR.

Both transcriptional and post-transcriptional regulation have a profound impact on genes expression. However, commonly adopted cell-based screening assays ...

Transfecting RAW264.7 Cells with a Luciferase Reporter Gene

Transfection of desired genetic materials into cells is an inevitable procedure in biomedical research studies. While numerous methods have been described, certain types of cells are resistant to many of these methods and yield low transfection efficiency1, potentially hindering research in those cell types. In this protocol, we present an optimized transfection procedure to introduce luciferase reporter genes as a plasmid DNA into the RAW264.7 macrophage cell line. Two different types of transfection reagents (lipid-based and polyamine-based) are described, and important notes are given throughout the protocol to ensure that the RAW264.7 cells are minimally altered by the transfection procedure and any experimental data obtained are the direct results of the experimental treatment. While transfection efficiency may not be higher compared to other transfection methods, the described procedure is robust enough for detecting luciferase signal in RAW264.7 without changing the physiological response of the cells to stimuli.

Transfection into the macrophage cell line, RAW264.7, is difficult due to the cell&#8217;s natural response against foreign materials. We described here a gentle yet robust procedure for transfecting luciferase reporter genes into RAW264.7 cells.

Transfection of desired genetic materials into cells is an inevitable procedure in biomedical research studies. While numerous methods have been ...

Multi-enzyme Screening Using a High-throughput Genetic Enzyme Screening System

The recent development of a high-throughput single-cell assay technique enables the screening of novel enzymes based on functional activities from a large-scale metagenomic library1. We previously proposed a genetic enzyme screening system (GESS) that uses dimethylphenol regulator activated by phenol or p-nitrophenol. Since a vast amount of natural enzymatic reactions produce these phenolic compounds from phenol deriving substrates, this single genetic screening system can be theoretically applied to screen over 200 different enzymes in the BRENDA database. Despite the general applicability of GESS, applying the screening process requires a specific procedure to reach the maximum flow cytometry signals. Here, we detail the developed screening process, which includes metagenome preprocessing with GESS and the operation of a flow cytometry sorter. Three different phenolic substrates (p-nitrophenyl acetate, p-nitrophenyl-&#946;-D-cellobioside, and phenyl phosphate) with GESS were used to screen and to identify three different enzymes (lipase, cellulase, and alkaline phosphatase), respectively. The selected metagenomic enzyme activities were confirmed only with the flow cytometry but DNA sequencing and diverse in vitro analysis can be used for further gene identification.

This work presents a method of high-throughput screening using a universal genetic enzyme screening system that can be theoretically applied to over 200 enzymes. Here, the single screening system identifies three different enzymes (lipase, cellulase, and alkaline phosphatase) by simply changing the substrate used (p-nitrophenyl acetate, p-nitrophenyl-&#946;-D-cellobioside, and phenyl phosphate).

The recent development of a high-throughput single-cell assay technique enables the screening of novel enzymes based on functional activities from a ...