We thank Dr. Mark E. Schurdak and University of Pittsburgh Drug Discovery Institute for providing the high-content imager and initial trainings. Dr. Krzysztof Palczewski (Case Western Reserve University) generously shared the 1D4 and B630 anti-rhodopsin antibodies. The plasmid containing the cDNA of mouse rhodopsin-Venus construct was shared by Dr. Nevin Lambert (Augusta University). This work was supported by the National Institute of Health grant EY024992 to YC and P30EY008098 from University of Pittsburgh Vision Research Core grant.

NOTE: The rhodopsin transport assay. 
1. Preparation and Culture of Cells
<ol>
	<li>Revive cryo-preserved U2OS stable cells expressing the wild type (WT) or mutant mouse rhodopsin-Venus fusion proteins. Thaw the cells at 37 &#176;C until only small ice crystals are left in the vial. 
	NOTE: The U2OS cells are used in this protocol because there is no photoreceptor cell line available for in vitro studies and the pre-ciliary biosynthesis of rhodopsin is regulated by similar molecular mechanisms in mammalian cells. Additionally, the U2OS cells attach tightly to the bottom of the plate and have large cell bodies, so they are ideal for the rhodopsin transport assay. Seven U2OS stable cells expressing the WT, T4R, P23H, P53R, C110Y, D190N and P267L rhodopsin mutants are used here as an example to show the quality and reliability of the assay. Stable cells expressing other rhodopsin mutants or other membrane proteins can be used, depending on the goal of the assay. Stable cells expressing human rhodopsin can be used in this assay if available. The mouse rhodopsin was used here because mouse and human rhodopsin proteins share 95% homology, and the compounds identified by this assay will be tested in vivo using a mouse adRP model carrying the rhodopsin P23H mutation8. The stable cells were generated as described previously19. The WT and mutant rhodopsin transcripts were quantified by q-PCR, and the clones of stable cells expressing similar levels of WT and mutant rhodopsin transcripts were selected for this assay. The expression of rhodopsin proteins was confirmed by immunoblot and immunostaining. The passage of cells used in this assay should be lower than 20.</li>
	<li>Transfer each line of cells into a 15 mL conical tube containing 10 mL of growth medium (high glucose Dulbecco&#39;s modified Eagle&#39;s medium (DMEM) with 10% fetal bovine serum (FBS) and 5 &#181;g/mL Plasmocin).</li>
	<li>Centrifuge the tube at 200 x g for 5 min. Discard the supernatant and resuspend the cell pellet with 5 mL of cell growth medium for each cell line. Transfer each line of cell suspension into a 60 mm tissue culture dish and incubate at 37 &#176;C with 5% CO2.</li>
	<li>Subculture the cells when the tissue culture dish reaches 90% confluence as described in reference12.</li>
</ol>
2. Seeding Cells at 5,000 cells per Well
NOTE: Perform the following procedures in a tissue culture hood.
<ol>
	<li>Treat the plate with poly-lysine.
	<ol>
		<li>One day before seeding the cells, treat a black-wall and clear bottom 384-well plate with 20 &#181;L/well of poly-lysine solution for 30 min.</li>
		<li>Aspirate the liquid and allow all wells to dry for 1 h. Put back the plate lid and store the plate at 4 &#176;C overnight for cell seeding.</li>
	</ol>
	</li>
	<li>Prepare the cell suspension.
	<ol>
		<li>Culture each cell line in growth medium in a 100 mm tissue culture dish until 90% confluence.</li>
		<li>Wash each dish with phosphate buffered saline (PBS) and detach the cells with 1 mL of 0.05% Trypsin at 37 &#176;C.</li>
		<li>Resuspend each line of cells in 10 mL of assay medium (high-glucose DMEM with 10% FBS, 100 units/mL penicillin and 100 &#956;g/mL streptomycin).</li>
		<li>Count the cells and dilute each line of cells to 1.25 x 105&#160;cells/mL with the assay medium.</li>
	</ol>
	</li>
	<li>Seed the cells.
	<ol>
		<li>Use an electronic multichannel pipette or an automated reagent dispenser to dispense 40 &#181;L/well of the cell suspension to three columns per cell line and fill columns 1-21 of the 384-well plate (Figure 2).</li>
		<li>Add 40 &#181;L/well of U2OS (P23H-Rhodopsin-Venus) to columns 22-23 and 40 &#181;L/well of U2OS (Rhodopsin-Venus) to column 24, as controls.</li>
		<li>Centrifuge the plate at 300 x g for 30 s to bring down all cells to the bottom of the 384-well plate. 
		NOTE: Avoid physical shock to the plate after cell seeding. Otherwise, cells will be crushed to one corner of each well, and the plate will not be suitable for high-content imaging.</li>
		<li>Incubate the 384-well plate at 37 &#176;C with 5% CO2 for 3 h for the cells to attach to the bottom of the plate.</li>
	</ol>
	</li>
</ol>
3. Treating the Cells with Compounds
<ol>
	<li>Generate a plate map with treatment conditions as shown in Figure 2.</li>
	<li>Prepare 300 &#181;L of 5x working solutions of up to 15 compounds in a 96-well plate.
	<ol>
		<li>Dilute cps 1 to 15 with the assay medium to five times of their final concentrations in wells A1 to G2 of the 96-well plate (Figure 2A). Add 300 &#181;L of assay medium in well H2. 
		NOTE: The final concentration of each compound is used at the most effective concentration for rescuing the transport of the P23H rhodopsin by the HTS12,13.</li>
		<li>Add 100 &#181;L per well of 2% dimethyl sulfoxide (DMSO) and 25 &#181;M 9-cis-retinal that are diluted in the assay medium to columns 11 and 12, respectively. Add 9-cis-retinal in dim light.</li>
	</ol>
	</li>
	<li>Adding 10 &#181;L per well of 5x working solutions to the 384-well plate cultured with the cells (Figure 2B).
	<ol>
		<li>Use an electronic multi-channel pipette to add compounds 1, 3, 5, 7, 9, 11, 13, and 15 to rows A, C, E, G, I, K, M, and O from columns 1 to 21 (Figure 2). Add compounds 2, 4, 6, 8, 10, 12, 14 and M to rows B, D, F, H, J, L, N, and P from columns 1 to 21.</li>
		<li>Add 10 &#181;L per well of 2% DMSO to columns 22 and 24. Add 10 &#181;L per well of 25 &#181;M 9-cis-retinal to column 23. 
		NOTE: DMSO is used as a vehicle control because all the compounds are initially dissolved in DMSO as stocks. Column 22 containing DMSO treated cells expressing the P23H rhodopsin is used as the 0% control. 9-Cis-retinal treated cells expressing the P23H rhodopsin is used as the 100% control.</li>
	</ol>
	</li>
	<li>Cover the 384-well plate with aluminum foil and incubate the plate at 37 &#176;C for 24 h.</li>
</ol>
4. Immunostaining without Membrane Permeabilization to Stain Rhodopsin Protein on the Cell Surface.
NOTE: Avoid any detergent in the entire immunostaining process to keep cell membrane intact.
<ol>
	<li>Prepare 4% paraformaldehyde (PFA) by diluting the 16% PFA with PBS in a 1:4 volume ratio in a chemical fume hood. Transfer the 4% PFA in a reagent reservoir.</li>
	<li>Take out the 384-well plate in a dark room with dim red light. Use an 8-channel aspirator connected to a vacuum collection bottle to gently aspirate the medium. Use an electronic multichannel pipette to add 20 &#181;L per well of freshly prepared 4% PFA to the entire 384-well plate and incubate for 20 min at room temperature. To avoid cell detachment, always point the tips of the aspirator to the same side of each well during aspirations. Do not touch the middle bottom area of each well. When taking images, select fields to avoid the region touched by the aspirator. For incubations longer than 10 min, cover the 384-well plate with its lid to avoid evaporation. 
	NOTE: Cells are fixed in a dark room to avoid photobleaching of the regenerated isorhodopsin that will affect the result of the 100% control. After fixation, the 384-well plate can be taken out under normal light.</li>
	<li>Use an 8-channel aspirator to aspirate the PFA in each well and use an electronic multi-channel pipette to add 50 &#956;L per well of PBS. Repeat two more times to perform three washes with PBS. 
	CAUTION: The waste liquid containing PFA are collected in a capped bottle and is to be disposed of as a hazardous chemical waste after the experiment.</li>
	<li>Block the cells by adding 20 &#181;L per well of 5% goat serum to the entire 384-well plate and incubate at room temperature for 30 min.</li>
	<li>Aspirate the 5% goat serum and add 15 &#181;L per well of 20 &#181;g mL-1 B6-30 anti-rhodopsin antibody in 1% goat serum to rows A to O. Add 15 &#181;L per well of 1% goat serum to row P for the secondary antibody-only control group.</li>
	<li>Incubate the 384-well plate at room temperature for 90 min or at 4 &#176;C overnight. Cover the 384-well plate with aluminum foil to avoid photobleaching of the fluorophores.</li>
	<li>Wash the plate 3 times with 50 &#181;L per well of PBS.</li>
	<li>Aspirate PBS and add 15 &#181;L per well of 5 &#181;g mL-1 Cy3-conjugated goat anti-mouse IgG antibody. Cover the 384-well plate with aluminum foil and incubate at room temperature for 1 h or at 4 &#176;C overnight.</li>
	<li>Wash the plate 3 times with 50 &#181;L per well of PBS. Add 50 &#181;L per well of PBS containing 1 &#181;g mL-1 Hoechst 33342 to stain nuclei at room temperature for 15 min.</li>
	<li>Seal the 384-well plate with a transparent film before imaging. Cover the 384-well plate with aluminum foil and store at 4 &#176;C for up to a week if images are taken immediately.</li>
</ol>
5. Imaging.
NOTE: This high-content imaging procedure is adapted to the imaging system listed in the Table of Material. Procedures can be different if using other high-content imaging systems.
<ol>
	<li>Remove the lid and put the 384-well plate into the high-content imager with A1 positioned on the top left corner of the plate.</li>
	<li>Open the image acquisition software to set up parameters for image acquisition.
	<ol>
		<li>Open the Plate Acquisition Setup window and create new setting or load an existing setup file.</li>
		<li>Select the 20x objective and set up pixel binning as 2 so the calibrated pixel size is 0.80 x 0.80 &#181;m. Set the scan lines as 2,000 and the image size (W x H) as 1,000 x 1,000 pixels (800.00 x 800.00 &#181;m) per site.</li>
		<li>Select the plate type to be imaged. Use the information provided by the manufacturer of the 384-well plate to fill in the plate dimensions.</li>
		<li>Select the wells to be imaged for the 384-well plate.</li>
		<li>Select four sites to be imaged per well. Avoid the side of the well touched by the aspiration tips.</li>
		<li>Select excitation lasers as 405, 488 and 561 nm. Select emission filters for DAPI, FITC and Texas Red channels. Optimize the laser power and gains of each channel to ensure the brightness of images taken from the positive control wells are less than the saturation threshold.</li>
		<li>Select well-to-well focus for autofocus. Select the first well acquired as the initial well for finding samples. Set site autofocus to all sites.</li>
		<li>Select four averages per line for each channel. Optimize the Z-offset value for each channel.</li>
		<li>Test 2-3 wells at the diagonal corners of the 384 well plate to make sure the images are on focus for all tested wells, images from all sites per well have cells with more than 40% confluence, and fluorescence intensities of all channels are about half saturated in the 100% control wells.</li>
		<li>Save the image acquisition method.</li>
	</ol>
	</li>
	<li>Run the entire plate. Watch the imager until it finishes capturing images from the first column of the plate to double-check the image quality before leaving the imager. Take the 384-well plate out and store at 4 &#176;C for future use. 
	NOTE: Depending on the number of sites selected per well and the channels taken, it takes 40 min to 3 h to finish imaging one 384-well plate.</li>
</ol>
6. Image Analysis.
<ol>
	<li>Pull out the image data using a high-content image analysis software. Select one of the 100% control wells (column 23) to set up parameters.</li>
	<li>Select the Multi-Wavelength Cell Scoring as the analysis method and start configuring settings.
	<ol>
		<li>Define the nuclei using images from the DAPI channel. Preview to make sure the defined nuclei shapes in the selected well fits well with the nuclei images.</li>
		<li>Define the shape of cell in the FITC channel where rhodopsin-Venus is imaged.</li>
		<li>Define the rhodopsin cell surface stain areas in the Texas Red channel.</li>
		<li>Test the current algorithm in 5 wells to determine if the settings are optimized. Save the settings and close the Configuration window.</li>
	</ol>
	</li>
	<li>Run all the wells with the optimized analysis method.</li>
	<li>Export Object Number as intact cell number. Export the Average Intensity of the FITC channel as Rhodopsin-Venus Intensity (Rhodopsin-Venus INT). Export the Average Intensity of the Texas Red channel as rhodopsin intensity on the cell surface (Rhodopsin INT on the cell surface).</li>
	<li>Open the exported data in a spreadsheet software. Divide the rhodopsin intensity on the cell surface by the rhodopsin-Venus INT as MEM-to-total ratio. Calculate the Z&#8217;-factors for each parameter to evaluate the assay quality. Z&#8242;=1&#8722;3X(STD100% control+STD0% control)/|Mean100% control&#8722;Mean0% control|. 
	NOTE: A Z&#8217;-factor higher than 0 indicates a moderate assay sufficient for a high-content screen, and a Z&#8217; factor between 0.5 and 1 suggests an outstanding assay required for a high-throughput screen20,21.</li>
	<li>Use the spreadsheet software to generate a two-color heat map for each parameter. Arrange the name of cell lines on the X-axis and the compounds on the Y-axis.</li>
</ol>

<ol>
	<li>Gregersen, N., Bross, P., Vang, S., Christensen, J. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Protein+misfolding+and+human+disease.">Protein misfolding and human disease.</a> Annual Review of Genomics and Human Genetics. 7, 103-124 (2006).</li><li>Daiger, S. P., Bowne, S. J., Sullivan, L. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Perspective+on+genes+and+mutations+causing+retinitis+pigmentosa.">Perspective on genes and mutations causing retinitis pigmentosa.</a> Archives of Ophthalmology. 125 (2), 151-158 (2007).</li><li>Daiger, S. P., Sullivan, L. S., Bowne, S. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genes+and+mutations+causing+retinitis+pigmentosa.">Genes and mutations causing retinitis pigmentosa.</a> Clinical Genetics. 84 (2), 132-141 (2013).</li><li>Stenson, P. D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Human+Gene+Mutation+Database:+towards+a+comprehensive+repository+of+inherited+mutation+data+for+medical+research,+genetic+diagnosis+and+next-generation+sequencing+studies.">The Human Gene Mutation Database: towards a comprehensive repository of inherited mutation data for medical research, genetic diagnosis and next-generation sequencing studies.</a> Human Genetics. 136 (6), 665-677 (2017).</li><li>Sung, C. H., Schneider, B. G., Agarwal, N., Papermaster, D. S., Nathans, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Functional+heterogeneity+of+mutant+rhodopsins+responsible+for+autosomal+dominant+retinitis+pigmentosa.">Functional heterogeneity of mutant rhodopsins responsible for autosomal dominant retinitis pigmentosa.</a> Proceedings of the National Academy of Sciences of the United States of America. 88 (19), 8840-8844 (1991).</li><li>Athanasiou, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+molecular+and+cellular+basis+of+rhodopsin+retinitis+pigmentosa+reveals+potential+strategies+for+therapy.">The molecular and cellular basis of rhodopsin retinitis pigmentosa reveals potential strategies for therapy.</a> Progress in Retinal and Eye Research. 62, 1-23 (2018).</li><li>Chiang, W. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Robust+Endoplasmic+Reticulum-Associated+Degradation+of+Rhodopsin+Precedes+Retinal+Degeneration.">Robust Endoplasmic Reticulum-Associated Degradation of Rhodopsin Precedes Retinal Degeneration.</a> Molecular Neurobiology. 52 (1), 679-695 (2015).</li><li>Sakami, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Probing+mechanisms+of+photoreceptor+degeneration+in+a+new+mouse+model+of+the+common+form+of+autosomal+dominant+retinitis+pigmentosa+due+to+P23H+opsin+mutations.">Probing mechanisms of photoreceptor degeneration in a new mouse model of the common form of autosomal dominant retinitis pigmentosa due to P23H opsin mutations.</a> Journal of Biological Chemistry. 286 (12), 10551-10567 (2011).</li><li>Dryja, T. P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mutations+within+the+rhodopsin+gene+in+patients+with+autosomal+dominant+retinitis+pigmentosa.">Mutations within the rhodopsin gene in patients with autosomal dominant retinitis pigmentosa.</a> New England Journal of Medicine. 323 (19), 1302-1307 (1990).</li><li>Sohocki, M. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Prevalence+of+mutations+causing+retinitis+pigmentosa+and+other+inherited+retinopathies.">Prevalence of mutations causing retinitis pigmentosa and other inherited retinopathies.</a> Human Mutation. 17 (1), 42-51 (2001).</li><li>Chen, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+novel+small+molecule+chaperone+of+rod+opsin+and+its+potential+therapy+for+retinal+degeneration.">A novel small molecule chaperone of rod opsin and its potential therapy for retinal degeneration.</a> Nature Communications. 9 (1), (2018).</li><li>Chen, Y., Tang, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-throughput+screening+assays+to+identify+small+molecules+preventing+photoreceptor+degeneration+caused+by+the+rhodopsin+P23H+mutation.">High-throughput screening assays to identify small molecules preventing photoreceptor degeneration caused by the rhodopsin P23H mutation.</a> Methods in Molecular Biology. 1271, 369-390 (2015).</li><li>Chen, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+High-Throughput+Drug+Screening+Strategy+for+Detecting+Rhodopsin+P23H+Mutant+Rescue+and+Degradation.">A High-Throughput Drug Screening Strategy for Detecting Rhodopsin P23H Mutant Rescue and Degradation.</a> Investigative Ophthalmology &amp; Visual Science. 56 (4), 2553-2567 (2015).</li><li>Noorwez, S. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Pharmacological+chaperone-mediated+in+vivo+folding+and+stabilization+of+the+P23H-opsin+mutant+associated+with+autosomal+dominant+retinitis+pigmentosa.">Pharmacological chaperone-mediated in vivo folding and stabilization of the P23H-opsin mutant associated with autosomal dominant retinitis pigmentosa.</a> Journal of Biological Chemistry. 278 (16), 14442-14450 (2003).</li><li>Saliba, R. S., Munro, P. M., Luthert, P. J., Cheetham, M. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+cellular+fate+of+mutant+rhodopsin:+quality+control,+degradation+and+aggresome+formation.">The cellular fate of mutant rhodopsin: quality control, degradation and aggresome formation.</a> Journal of Cell Science. 115, 2907-2918 (2002).</li><li>Kaushal, S., Khorana, H. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Structure+and+function+in+rhodopsin.+7.+Point+mutations+associated+with+autosomal+dominant+retinitis+pigmentosa.">Structure and function in rhodopsin. 7. Point mutations associated with autosomal dominant retinitis pigmentosa.</a> Biochemistry. 33 (20), 6121-6128 (1994).</li><li>Chen, Y., Brooks, M. J., Gieser, L., Swaroop, A., Palczewski, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Transcriptome+profiling+of+NIH3T3+cell+lines+expressing+opsin+and+the+P23H+opsin+mutant+identifies+candidate+drugs+for+the+treatment+of+retinitis+pigmentosa.">Transcriptome profiling of NIH3T3 cell lines expressing opsin and the P23H opsin mutant identifies candidate drugs for the treatment of retinitis pigmentosa.</a> Pharmacological Research. 115, 1-13 (2016).</li><li>Adamus, G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Anti-rhodopsin+monoclonal+antibodies+of+defined+specificity:+characterization+and+application.">Anti-rhodopsin monoclonal antibodies of defined specificity: characterization and application.</a> Vision Research. 31 (1), 17-31 (1991).</li><li>Goodson, H. V., Dzurisin, J. S., Wadsworth, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Generation+of+stable+cell+lines+expressing+GFP-tubulin+and+photoactivatable-GFP-tubulin+and+characterization+of+clones.">Generation of stable cell lines expressing GFP-tubulin and photoactivatable-GFP-tubulin and characterization of clones.</a> Cold Spring Harbor Protocols. 2010 (9), (2010).</li><li>Zhang, J. H., Chung, T. D., Oldenburg, K. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Simple+Statistical+Parameter+for+Use+in+Evaluation+and+Validation+of+High+Throughput+Screening+Assays.">A Simple Statistical Parameter for Use in Evaluation and Validation of High Throughput Screening Assays.</a> Journal of Biomolecular Screening. 4 (2), 67-73 (1999).</li><li>Bray, M. A., Carpenter, A., Sittampalam, G. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Advanced+Assay+Development+Guidelines+for+Image-Based+High+Content+Screening+and+Analysis.">Advanced Assay Development Guidelines for Image-Based High Content Screening and Analysis.</a> Assay Guidance Manual. , (2004).</li><li>Sung, C. H., Davenport, C. M., Nathans, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rhodopsin+mutations+responsible+for+autosomal+dominant+retinitis+pigmentosa.+Clustering+of+functional+classes+along+the+polypeptide+chain.">Rhodopsin mutations responsible for autosomal dominant retinitis pigmentosa. Clustering of functional classes along the polypeptide chain.</a> Journal of Biological Chemistry. 268 (35), 26645-26649 (1993).</li><li>Krebs, M. P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Molecular+mechanisms+of+rhodopsin+retinitis+pigmentosa+and+the+efficacy+of+pharmacological+rescue.">Molecular mechanisms of rhodopsin retinitis pigmentosa and the efficacy of pharmacological rescue.</a> Journal of Molecular Biology. 395 (5), 1063-1078 (2010).</li></ol>

The authors have nothing to disclose.

Here, we showed a high-content imaging assay used for characterizing hits identified from a HTS. The only automation involved in these protocols is the high-content imager. The immunostaining and fluorescence imaging of rhodopsin have been used commonly to characterize the localization of rhodopsin5,14,15,16. However, the quantification of images taken by the traditional imaging methods is limi...

Protein misfolding is involved in muscular dystrophy, neural degenerations, as well as blinding diseases, including retinitis pigmentosa (RP)1. RP is an inherited and progressive retinal degeneration associated with mutations in over 60 genes affecting the function and homeostasis of rod photoreceptors or the retinal pigmented epitheliums (RPEs)2,3. No effective treatment is currently available for RP. Rhodopsin mutations account for about 25-30% of autosomal dominant (ad) RP cases. Among the more than 150 rhodopsin mutations4 (Human Gene Mutation Database, http:/www.hgmd.cf.ac.uk/), the Class II mutations cause the structural instability of the rhodopsin protein that contributes to the rod photoreceptor death and vision loss5,6,7,8. The P23H is the most frequent rhodopsin mutation in North America, which is also a typical example of the Class II rhodopsin mutations9,10. Due to its inherent structural instability, the misfolded rhodopsin is accumulated in the endoplasmic reticulum (ER) in mammalian cells, whereas the wild type rhodopsin is located on the plasma membrane5. The misfolded rhodopsin P23H mutant exhibits dominant negative cytotoxicity that is not due to haploinsufficiency, but is related to the activation of ER associated protein degradation pathway and the interrupted rod outer segment organization. To alleviate rod photoreceptor cell stress, one strategy is to stabilize the native folding of the mutant rhodopsin using a pharmacological chaperone.
To achieve this goal, we performed a cell-based high-throughput screen (HTSs)11,12,13 using a &#946;-galactosidase fragment complementation assay to quantify the P23H rhodopsin mutant transported on the plasma membrane. The robust and simple protocol of this HTS assay enabled us to explore the activities of about 79,000 small molecules for each screen. However, because this HTS assay reads luminescence signals, false positives including the &#946;-gal inhibitors, colored or cytotoxic compounds are included in the hit list waiting to be identified by a secondary assay.
The traditional immunostaining and fluorescence imaging methods have been used for years to study the rhodopsin transport in mammalian cells5,14,15,16. However, these conventional methods cannot be used to quantify pharmacological effects of more than 10 compounds towards rhodopsin transport because a reliable imaging analysis requires a large number of images taken under a highly consistent condition, which is not amendable by the conventional imaging methods. Here, we developed an immunostaining based high-content imaging protocol as a secondary assay to quantify the cell surface transport of misfolded rhodopsin mutants11,13,17. To label rhodopsin on the plasma membrane, we skipped the step of cell membrane permeabilization and immunostained the rhodopsin mutants by a monoclonal (B6-30) anti-rhodopsin recognizing the N-terminal epitope of rhodopsin at the extracellular side of the cell membrane18. To visualize the mutant rhodopsin in the whole cell, we fused rhodopsin with the Venus fluorescence protein. By the quantification of the fluorescence intensities in different fluorescence channels, we are able to obtain multiple parameters from one single experiment including the total rhodopsin intensity in the whole cell, on the cell surface, and the ratio of rhodopsin fluorescence on the cell surface to that in the whole cell. Applying this method to stable cells expressing a total of six misfolded rhodopsin mutants, we can generate a pharmacological profile of multiple small molecule chaperones towards these mutants. In this protocol, all cells are immunostained in a 384-well plate and imaged using an automated imaging system under a highly consistent imaging condition. An image analysis is performed to each well, containing images of more than 600 cells to reduce variation due to the heterogeneity of the cells with varying cell shape and protein expression level. The workflow of this protocol is summarized in Figure 1. The advantage of this method is that we obtain high-resolution images as well as multi-parameter quantifications from the image-based analysis. In general, this protocol can be modified and applied to quantify the transport of any misfolded membrane protein of interest.

<table><tbody><tr><td>U2OS (rhodopsin-Venus) cells</td><td>NA</td><td>NA</td><td>Stable cells generated from U2OS cells</td></tr><tr><td>U2OS (T4R-rhodopsin-Venus) cells</td><td>NA</td><td>NA</td><td>Stable cells generated from U2OS cells</td></tr><tr><td>U2OS (P23H-rhodopsin-Venus) cells</td><td>NA</td><td>NA</td><td>Stable cells generated from U2OS cells</td></tr><tr><td>U2OS (P53R-rhodopsin-Venus) cells</td><td>NA</td><td>NA</td><td>Stable cells generated from U2OS cells</td></tr><tr><td>U2OS (C110Y-rhodopsin-Venus) cells</td><td>NA</td><td>NA</td><td>Stable cells generated from U2OS cells</td></tr><tr><td>U2OS (D190N-rhodopsin-Venus) cells</td><td>NA</td><td>NA</td><td>Stable cells generated from U2OS cells</td></tr><tr><td>U2OS (P267L-rhodopsin-Venus) cells</td><td>NA</td><td>NA</td><td>Stable cells generated from U2OS cells</td></tr><tr><td>DMEM high glucose</td><td>Genesee Scientific</td><td>25-500</td><td>With L-Glutamine, sodium pyruvate</td></tr><tr><td>Fetal bovine serum (FBS)</td><td>Gibco</td><td>16140071</td><td>Heat inactivated</td></tr><tr><td>Plasmocin</td><td>InvivoGen</td><td>ant-mpt</td><td>Mycoplasma elimination reagent</td></tr><tr><td>Penicillin-Streptomycin (100X)</td><td>Gibco</td><td>15140122</td><td>100X concentrated antibiotic solutions to prevent bacteria contamination of cell cultures</td></tr><tr><td>Trypsin-EDTA</td><td>Genesee Scientific</td><td>25-510</td><td>0.25%, 1mM EDTA in HBSS without calcium and magnesium</td></tr><tr><td>Poly-L-lysine solution</td><td>Sigma-Aldrich</td><td>P4707-50ML</td><td>Mol wt 70,000-150,000, 0.01%, sterile-filtered, BioReagent, suitable for cell culture</td></tr><tr><td>CellCarrier-384 Ultra Microplates</td><td>PerkinElmer</td><td>6057300</td><td>384-well tissue culutre-treated microplates with black well walls and an optically -clear cyclic olefin bottom for imaging cells in high content analysis</td></tr><tr><td>Sterile 96-well plate</td><td>Eppendorf</td><td>30730119</td><td>Tissue culture treated with lid flat bottom, sterile, free of detectable pyrogens, Rnase, DNase and DNA. Non-cytotoxic</td></tr><tr><td>Phosphate Buffered Sailine (PBS)</td><td>Invitrogen</td><td>AM9625</td><td>10 x PBS Buffer, pH 7.4</td></tr><tr><td>DMSO</td><td>Sigma-Aldrich</td><td>D4540</td><td>&gt;99.5%, cell culture tested</td></tr><tr><td>9-&lt;em&gt;cis&lt;/em&gt;-retinal</td><td>Sigma-Aldrich</td><td>R5754</td><td></td></tr><tr><td>Compounds tested</td><td>Selleckchem/Life Chemicals/Custom synthesized</td><td>NA</td><td>Compounds were purchased from different vendors or custom synthesized</td></tr><tr><td>B6-30 anti-rhodopsin antibody</td><td>Novus</td><td>NBP2-25160</td><td>Gift from Dr. Krzysztof Palczewski</td></tr><tr><td>Cy3-conjugated goat anti-mouse secondary antibody</td><td>Jackson ImmunoResearch Laboratories, Inc</td><td>115-165-146</td><td></td></tr><tr><td>16% paraformaldehyde</td><td>Thermo Fisher Scientific</td><td>28908</td><td>Methanol-free</td></tr><tr><td>10% Normal Goat Serum</td><td>Thermo Fisher Scientific</td><td>50062Z</td><td>Blocking buffer</td></tr><tr><td>Hoechst 33342, Trihydroch</td><td>Invitrogen</td><td>H3570</td><td>Nuclear staining solution</td></tr><tr><td>High-content imager</td><td>Molecular Devices</td><td>ImageXpress</td><td>ImageXpress&amp;reg; Micro Confocal High-Content Imaging System</td></tr><tr><td>MetaXpress high-content image acquisition and analysis software</td><td>Molecular Devices</td><td>MetaXpress</td><td>High-content image acquisition and analysis software</td></tr><tr><td>Multichannel pipette (0.5-10 &amp;micro;L)</td><td>Rainin</td><td>17013802</td><td>Manual 8-channel pipette, 0.5-10 &amp;micro;L</td></tr><tr><td>Multichannel pipette (0.5-10c</td><td>Rainin</td><td>17013805</td><td>Manual 8-channel pipette, 20-200 &amp;micro;L</td></tr><tr><td>Electronic multichannel pipette (10-200 &amp;mu;L)</td><td>Thermo Scientific</td><td>14-3879-56BT</td><td>Electronic multichanenel pipette for 96- and 384-well microplate pipetting tasks</td></tr><tr><td>50ml Reagent Reservoir</td><td>Genesee Scientific</td><td>28-125</td><td>Reagent reservior for multichannel pippte dispensing</td></tr><tr><td>8-Channel aspirator</td><td>ABC Scientific</td><td>EV503</td><td>8-Channel stainless steel adaptor for aspirating liquids from 96- or 384-well plates</td></tr><tr><td>Excel spreadsheet software</td><td>Microsoft</td><td>Excel2016</td><td>The spreadsheet software for data analysis and heatmap generation</td></tr><tr><td>Origin2018 scientific data analysis and graphing software</td><td>OriginLab</td><td>Origin2018</td><td>The data analysis software for generating the dose response curves</td></tr></tbody></table>

a rhodopsin transport assay by high-content imaging analysis

Rhodopsin misfolding mutations lead to rod photoreceptor death that is manifested as autosomal dominant retinitis pigmentosa (RP), a progressive blinding disease that lacks effective treatment. We hypothesize that the cytotoxicity of the misfolded rhodopsin mutant can be alleviated by pharmacologically stabilizing the mutant rhodopsin protein. The P23H mutation, among the other Class II rhodopsin mutations, encodes a structurally unstable rhodopsin mutant protein that is accumulated in the endoplasmic reticulum (ER), whereas the wild type rhodopsin is transported to the plasma membrane in mammalian cells. We previously performed a luminescence-based high-throughput screen (HTS) and identified a group of pharmacological chaperones that rescued the transport of the P23H rhodopsin from ER to the plasma membrane. Here, using an immunostaining method followed by a high-content imaging analysis, we quantified the mutant rhodopsin protein amount in the whole cell and on the plasma membrane. This method is informative and effective to identify true hits from false positives following HTS. Additionally, the high-content image analysis enabled us to quantify multiple parameters from a single experiment to evaluate the pharmacological properties of each compound. Using this assay, we analyzed the effect of 11 different compounds towards six RP associated rhodopsin mutants, obtaining a 2-D pharmacological profile for a quantitative and qualitative understanding about the structural stability of these rhodopsin mutants and efficacy of different compounds towards these mutants.

We characterized the rhodopsin transport with three parameters: the rhodopsin-Venus intensity in the whole cell (Rhodopsin-Venus INT), the immunostaining intensity of rhodopsin on the plasma membrane (Rhodopsin INT on the cell surface), and the ratio of rhodopsin stain on the cell surface to rhodopsin-Venus intensity in the whole cell (MEM-Total Ratio). A representative result of the rhodopsin transport assay is shown in Figure 3 and Figu...

Watch this Scientific Journal Video about A Rhodopsin Transport Assay by High-Content Imaging Analysis at JoVE.com

A Rhodopsin Transport Assay by High-Content Imaging Analysis

Here, we described a high-content imaging method to quantify the transport of rhodopsin mutants associated with retinitis pigmentosa. A multiple-wavelength scoring analysis was used to quantify rhodopsin protein on the cell surface or in the whole cell.

Rhodopsin misfolding mutations lead to rod photoreceptor death that is manifested as autosomal dominant retinitis pigmentosa (RP), a progressive blinding ...

a-rhodopsin-transport-assay-by-high-content-imaging-analysis

Research

JoVE Journal

Chemistry

6.4K Views.  University of Pittsburgh. Here, we described a high-content imaging method to quantify the transport of rhodopsin mutants associated with retinitis pigmentosa. A multiple-wavelength scoring analysis was used to quantify rhodopsin protein on the cell surface or in the whole cell.

Video: A Rhodopsin Transport Assay by High-Content Imaging Analysis

High Content Screening in Neurodegenerative Diseases

The functional annotation of genomes, construction of molecular networks and novel drug target identification, are important challenges that need to be addressed as a matter of great urgency1-4. Multiple complementary 'omics' approaches have provided clues as to the genetic risk factors and pathogenic mechanisms underlying numerous neurodegenerative diseases, but most findings still require functional validation5. For example, a recent genome wide association study for Parkinson's Disease (PD), identified many new loci as risk factors for the disease, but the underlying causative variant(s) or pathogenic mechanism is not known6, 7. As each associated region can contain several genes, the functional evaluation of each of the genes on phenotypes associated with the disease, using traditional cell biology techniques would take too long. 
	There is also a need to understand the molecular networks that link genetic mutations to the phenotypes they cause. It is expected that disease phenotypes are the result of multiple interactions that have been disrupted. Reconstruction of these networks using traditional molecular methods would be time consuming. Moreover, network predictions from independent studies of individual components, the reductionism approach, will probably underestimate the network complexity8. This underestimation could, in part, explain the low success rate of drug approval due to undesirable or toxic side effects. Gaining a network perspective of disease related pathways using HT/HC cellular screening approaches, and identifying key nodes within these pathways, could lead to the identification of targets that are more suited for therapeutic intervention.
	High-throughput screening (HTS) is an ideal methodology to address these issues9-12. but traditional methods were one dimensional whole-well cell assays, that used simplistic readouts for complex biological processes. They were unable to simultaneously quantify the many phenotypes observed in neurodegenerative diseases such as axonal transport deficits or alterations in morphology properties13, 14. This approach could not be used to investigate the dynamic nature of cellular processes or pathogenic events that occur in a subset of cells. To quantify such features one has to move to multi-dimensional phenotypes termed high-content screening (HCS)4, 15-17. HCS is the cell-based quantification of several processes simultaneously, which provides a more detailed representation of the cellular response to various perturbations compared to HTS. 
	HCS has many advantages over HTS18, 19, but conducting a high-throughput (HT)-high-content (HC) screen in neuronal models is problematic due to high cost, environmental variation and human error. In order to detect cellular responses on a 'phenomics' scale using HC imaging one has to reduce variation and error, while increasing sensitivity and reproducibility. 
	Herein we describe a method to accurately and reliably conduct shRNA screens using automated cell culturing20 and HC imaging in neuronal cellular models. We describe how we have used this methodology to identify modulators for one particular protein, DJ1, which when mutated causes autosomal recessive parkinsonism21. 
	Combining the versatility of HC imaging with HT methods, it is possible to accurately quantify a plethora of phenotypes. This could subsequently be utilized to advance our understanding of the genome, the pathways involved in disease pathogenesis as well as identify potential therapeutic targets.

We describe a methodology combining automated cell culturing with high-content imaging to visualize and quantify multiple cellular processes and structures, in a high-throughput manner. Such methods can aid in the further functional annotation of genomes as well as identify disease gene networks and potential drug targets.

The functional annotation of genomes, construction of molecular networks and novel drug target identification, are important challenges that need to be ...

Medicine

Strategic Screening and Characterization of the Visual GPCR-mini-G Protein Signaling Complex for Successful Crystallization

The key to determining crystal structures of membrane protein complexes is the quality of the sample prior to crystallization. In particular, the choice of detergent is critical, because it affects both the stability and monodispersity of the complex. We recently determined the crystal structure of an active state of bovine rhodopsin coupled to an engineered G protein, mini-Go, at 3.1 &#197; resolution. Here, we detail the procedure for optimizing the preparation of the rhodopsin&#8211;mini-Go complex. Dark-state rhodopsin was prepared in classical and neopentyl glycol (NPG) detergents, followed by complex formation with mini-Go under light exposure. The stability of the rhodopsin was assessed by ultraviolet-visible (UV-VIS) spectroscopy, which monitors the reconstitution into rhodopsin of the light-sensitive ligand, 9-cis retinal. Automated size-exclusion chromatography (SEC) was used to characterize the monodispersity of rhodopsin and the rhodopsin&#8211;mini-Go complex. SDS-polyacrylamide electrophoresis (SDS-PAGE) confirmed the formation of the complex by identifying a 1:1 molar ratio between rhodopsin and mini-Go after staining the gel with Coomassie blue. After cross-validating all this analytical data, we eliminated unsuitable detergents and continued with the best candidate detergent for large-scale preparation and crystallization. An additional problem arose from the heterogeneity of N-glycosylation. Heterologously-expressed rhodopsin was observed on SDS-PAGE to have two different N-glycosylated populations, which would probably have hindered crystallogenesis. Therefore, different deglycosylation enzymes were tested, and endoglycosidase F1 (EndoF1) produced rhodopsin with a single species of N-glycosylation. With this strategic pipeline for characterizing protein quality, preparation of the rhodopsin&#8211;mini-Go complex was optimized to deliver the crystal structure. This was only the third crystal structure of a GPCR&#8211;G protein signaling complex. This approach can also be generalized for other membrane proteins and their complexes to facilitate sample preparation and structure determination.

This report describes screening of different detergents for preparing the visual GPCR, rhodopsin, and its complex with mini-Go. Biochemical methods characterizing the quality of the complex at different stages during purification are demonstrated. This protocol can be generalized to other membrane protein complexes for their future structural studies.

The key to determining crystal structures of membrane protein complexes is the quality of the sample prior to crystallization. In particular, the choice ...

Biochemistry

A "Dual-Addition" Calcium Fluorescence Assay for the High-Throughput Screening of Recombinant G Protein-Coupled Receptors

G protein-coupled receptors (GPCRs) represent the largest superfamily of receptors and are the targets of numerous human drugs. High-throughput screening (HTS) of random small molecule libraries against GPCRs is used by the pharmaceutical industry for target-specific drug discovery. In this study, an HTS was employed to identify novel small-molecule ligands of invertebrate-specific neuropeptide GPCRs as probes for physiological studies of vectors of deadly human and veterinary pathogens.
The invertebrate-specific kinin receptor was chosen as a target because it regulates many important physiological processes in invertebrates, including diuresis, feeding, and digestion. Furthermore, the pharmacology of many invertebrate GPCRs is poorly characterized or not characterized at all; therefore, the differential pharmacology of these groups of receptors with respect to the related GPCRs in other metazoans, especially humans, adds knowledge to the structure-activity relationships of GPCRs as a superfamily. An HTS assay was developed for cells in 384-well plates for the discovery of ligands of the kinin receptor from the cattle fever tick, or southern cattle tick, Rhipicephalus microplus. The tick kinin receptor was stably expressed in CHO-K1 cells.
The kinin receptor, when activated by endogenous kinin neuropeptides or other small molecule agonists, triggers Ca2+ release from calcium stores into the cytoplasm. This calcium fluorescence assay combined with a &#34;dual-addition&#34; approach can detect functional agonist and antagonist &#34;hit&#34; molecules in the same assay plate. Each assay was conducted using drug plates carrying an array of 320 random small molecules. A reliable Z&#39; factor of 0.7 was obtained, and three agonist and two antagonist hit molecules were identified when the HTS was at a 2 &#181;M final concentration. The calcium fluorescence assay reported here can be adapted to screen other GPCRs that activate the Ca2+ signaling cascade.

In this work, a high-throughput, intracellular calcium fluorescence assay for 384-well plates to screen small molecule libraries on recombinant G protein-coupled receptors (GPCRs) is described. The target, the kinin receptor from the cattle fever tick, Rhipicephalus microplus, is expressed in CHO-K1 cells. This assay identifies agonists and antagonists using the same cells in one "dual-addition" assay.

G protein-coupled receptors (GPCRs) represent the largest superfamily of receptors and are the targets of numerous human drugs. High-throughput screening ...

Imaging Ca2+ Dynamics in Cone Photoreceptor Axon Terminals of the Mouse Retina

Retinal cone photoreceptors (cones) serve daylight vision and are the basis of color discrimination. They are subject to degeneration, often leading to blindness in many retinal diseases. Calcium (Ca2+), a key second messenger in photoreceptor signaling and metabolism, has been proposed to be indirectly linked with photoreceptor degeneration in various animal models. Systematically studying these aspects of cone physiology and pathophysiology has been hampered by the difficulties of electrically recording from these small cells, in particular in the mouse where the retina is dominated by rod photoreceptors. To circumvent this issue, we established a two-photon Ca2+ imaging protocol using a transgenic mouse line that expresses the genetically encoded Ca2+ biosensor TN-XL exclusively in cones and can be crossbred with mouse models for photoreceptor degeneration. The protocol described here involves preparing vertical sections (&#8220;slices&#8221;) of retinas from mice and optical imaging of light stimulus-evoked changes in cone Ca2+ level. The protocol also allows &#8220;in-slice measurement&#8221; of absolute Ca2+ concentrations; as the recordings can be followed by calibration. This protocol enables studies into functional cone properties and is expected to contribute to the understanding of cone Ca2+ signaling as well as the potential involvement of Ca2+ in photoreceptor death and retinal degeneration.

Imaging Ca2+ Dynamics in Cone Photoreceptor Axon Terminals of the Mouse Retina

We describe a protocol to monitor Ca2+ dynamics in the axon terminals of cone photoreceptors using an ex-vivo&#160;slice preparation of the mouse retina. This protocol allows comprehensive studies of cone Ca2+ signaling in an important mammalian model system, the mouse.

Retinal cone photoreceptors (cones) serve daylight vision and are the basis of color discrimination. They are subject to degeneration, often leading to ...

Neuroscience

Investigating Vitamin A Receptor Kinetics and Function for Retinoid Homeostasis

Methodology for Studying Interactions of Vitamin A Membrane Receptors and Opsin Protein with their Ligands in Generating the Retinylidene Protein

Distribution of dietary vitamin A/all-trans retinol (ROL) throughout the body is critical for maintaining retinoid function in peripheral tissues and generating the retinylidene protein for visual function. RBP4-ROL is the complex of ROL with retinol-binding protein 4 (RBP4), which is present in the blood. Two membrane receptors, Retinol Binding Protein 4 Receptor 2 (RBPR2) in the liver and STimulated by Retinoic Acid 6 Retinol (STRA6) in the eye, bind circulatory RBP4 and this mechanism is critical for internalizing ROL into cells. Establishing methods to investigate receptor-ligand kinetics is essential in understanding the physiological function of vitamin A receptors for retinoid homeostasis. Using Surface Plasmon Resonance (SPR) assays, we can analyze the binding affinities and kinetic parameters of vitamin A membrane receptors with its physiological ligand RBP4. 
These methodologies can reveal new structural and biochemical information of RBP4-binding motifs in RBPR2 and STRA6, which are critical for understanding pathological states of vitamin A deficiency. In the eye, internalized ROL is metabolized to 11-cis retinal, the visual chromophore that binds to opsin in photoreceptors to form the retinylidene protein, rhodopsin. The absorbance of light causes the cis-to-trans isomerization of 11-cis retinal, inducing conformational changes in rhodopsin and the subsequent activation of the phototransduction cascade. Decreased concentrations of serum and ocular ROL can impact retinylidene protein formation, which in turn can cause rhodopsin mislocalization, apoprotein opsin accumulation, night blindness, and photoreceptor outer segment degeneration, leading to Retinitis Pigmentosa or Leber Congenital Amaurosis. 
Therefore, spectrophotometric methodologies to quantify the G protein-coupled receptor opsin-11-cis retinal complex in the retina are critical for understanding mechanisms of retinal cell degeneration in the above-mentioned pathological states. With these comprehensive methodologies, investigators will be able to better assess dietary vitamin A supply in maintaining systemic and ocular retinoid homeostasis, which is critical for generating and maintaining retinylidene protein concentrations in photoreceptors, which is critical for sustaining visual function in humans.

Author Spotlight: Unraveling Vitamin A Transport Mechanisms &#8212; Linking Liver Receptors to Vision Health Through RBPR2 and RBP4 Interactions

Here, we describe two quantitative methods for studying the protein-ligand interactions of vitamin A membrane receptors and photoreceptor opsin with their respective physiological ligands.

Distribution of dietary vitamin A/all-trans retinol (ROL) throughout the body is critical for maintaining retinoid function in peripheral tissues and ...

A High-content Assay for Monitoring AMPA Receptor Trafficking

Postsynaptic trafficking of receptors to and from the cell surface is an important mechanism by which neurons modulate their responsiveness to different stimuli. The &#945;-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors, which are responsible for fast excitatory synaptic transmission in neurons, are trafficked to and from the postsynaptic surface to dynamically alter neuronal excitability. AMPA receptor trafficking is essential for synaptic plasticity and can be disrupted in neurological disease. However, prevalent approaches for quantifying receptor trafficking ignore entire receptor pools, are overly time- and labor-intensive, or potentially disrupt normal trafficking mechanisms and therefore complicate the interpretation of resulting data. We present a high-content assay for the quantification of both surface and internal AMPA receptor populations in cultured primary hippocampal neurons using dual fluorescent immunolabeling and a near-infrared fluorescent 96-well microplate scanner. This approach facilitates the rapid screening of bulk internalized and surface receptor densities while minimizing sample material. However, our method has limitations in obtaining single-cell resolution or conducting live cell imaging. Finally, this protocol may be amenable to other receptors and different cell types, provided proper adjustments and optimization.

Neuronal excitability can be modulated through a dynamic process of endo- and exocytosis of excitatory ionotropic glutamate receptors. Described here is an accessible, high-content assay for quantifying surface and internal receptor population pools.

Postsynaptic trafficking of receptors to and from the cell surface is an important mechanism by which neurons modulate their responsiveness to different ...

Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software

Advances in understanding the control mechanisms governing the behavior of cells in adherent mammalian tissue culture models are becoming increasingly dependent on modes of single-cell analysis. Methods which deliver composite data reflecting the mean values of biomarkers from cell populations risk losing subpopulation dynamics that reflect the heterogeneity of the studied biological system. In keeping with this, traditional approaches are being replaced by, or supported with, more sophisticated forms of cellular assay developed to allow assessment by high-content microscopy. These assays potentially generate large numbers of images of fluorescent biomarkers, which enabled by accompanying proprietary software packages, allows for multi-parametric measurements per cell. However, the relatively high capital costs and overspecialization of many of these devices have prevented their accessibility to many investigators.
Described here is a universally applicable workflow for the quantification of multiple fluorescent marker intensities from specific subcellular regions of individual cells suitable for use with images from most fluorescent microscopes. Key to this workflow is the implementation of the freely available Cell Profiler software1&#160;to distinguish individual cells in these images, segment them into defined subcellular regions and deliver fluorescence marker intensity values specific to these regions. The extraction of individual cell intensity values from image data is the central purpose of this workflow and will be illustrated with the analysis of control data from a siRNA screen for G1 checkpoint regulators in adherent human cells. However, the workflow presented here can be applied to analysis of data from other means of cell perturbation (e.g., compound screens) and other forms of fluorescence based cellular markers and thus should be useful for a wide range of laboratories.

Presented is a flexible informatics workflow enabling multiplexed image-based analysis of fluorescently labeled cells. The workflow quantifies nuclear and cytoplasmic markers and computes marker translocation between these compartments. Procedures are provided for perturbation of cells using siRNA and reliable methodology for marker detection by indirect immunofluorescence in 96-well formats.

Advances in understanding the control mechanisms governing the behavior of cells in adherent mammalian tissue culture models are becoming increasingly ...

Biology

Open Source High Content Analysis Utilizing Automated Fluorescence Lifetime Imaging Microscopy

We present an open source high content analysis instrument utilizing automated fluorescence lifetime imaging (FLIM) for assaying protein interactions using F&#246;rster resonance energy transfer (FRET) based readouts of fixed or live cells in multiwell plates. This provides a means to screen for cell signaling processes read out using intramolecular FRET biosensors or intermolecular FRET of protein interactions such as oligomerization or heterodimerization, which can be used to identify binding partners. We describe here the functionality of this automated multiwell plate FLIM instrumentation and present exemplar data from our studies of HIV Gag protein oligomerization and a time course of a FRET biosensor in live cells. A detailed description of the practical implementation is then provided with reference to a list of hardware components and a description of the open source data acquisition software written in &#181;Manager. The application of FLIMfit, an open source MATLAB-based client for the OMERO platform, to analyze arrays of multiwell plate FLIM data is also presented. The protocols for imaging fixed and live cells are outlined and a demonstration of an automated multiwell plate FLIM experiment using cells expressing fluorescent protein-based FRET constructs is presented. This is complemented by a walk-through of the data analysis for this specific FLIM FRET data set.

We present an open source high content analysis (HCA) instrument utilizing automated fluorescence lifetime imaging (FLIM) for assaying protein interactions using F&#246;rster resonance energy transfer (FRET) based readouts. Data acquisition for this openFLIM-HCA instrument is controlled by software written in &#181;Manager and data analysis is undertaken in FLIMfit.

We present an open source high content analysis instrument utilizing automated fluorescence lifetime imaging (FLIM) for assaying protein interactions ...

Cellular Redox Profiling Using High-content Microscopy

Reactive oxygen species (ROS) regulate essential cellular processes including gene expression, migration, differentiation and proliferation. However, excessive ROS levels induce a state of oxidative stress, which is accompanied by irreversible oxidative damage to DNA, lipids and proteins. Thus, quantification of ROS provides a direct proxy for cellular health condition. Since mitochondria are among the major cellular sources and targets of ROS, joint analysis of mitochondrial function and ROS production in the same cells is crucial for better understanding the interconnection in pathophysiological conditions. Therefore, a high-content microscopy-based strategy was developed for simultaneous quantification of intracellular ROS levels, mitochondrial membrane potential (&#916;&#936;m) and mitochondrial morphology. It is based on automated widefield fluorescence microscopy and image analysis of living adherent cells, grown in multi-well plates, and stained with the cell-permeable fluorescent reporter molecules CM-H2DCFDA (ROS) and TMRM (&#916;&#936;m and mitochondrial morphology). In contrast with fluorimetry or flow-cytometry, this strategy allows quantification of subcellular parameters at the level of the individual cell with high spatiotemporal resolution, both before and after experimental stimulation. Importantly, the image-based nature of the method allows extracting morphological parameters in addition to signal intensities. The combined feature set is used for explorative and statistical multivariate data analysis to detect differences between subpopulations, cell types and/or treatments. Here, a detailed description of the assay is provided, along with an example experiment that proves its potential for unambiguous discrimination between cellular states after chemical perturbation.

This paper presents a high-content microscopy workflow for simultaneous quantification of intracellular ROS levels, as well as mitochondrial membrane potential and morphology &#8211; jointly referred to as mitochondrial morphofunction &#8211; in living adherent cells using the cell-permeant fluorescent reporter molecules 5-(and-6)-chloromethyl-2&#39;,7&#39;-dichlorodihydrofluorescein diacetate, acetyl ester (CM-H2DCFDA) and tetramethylrhodamine methylester (TMRM).

Reactive oxygen species (ROS) regulate essential cellular processes including gene expression, migration, differentiation and proliferation. However, ...

Quantifying Retinal Pigment Epithelial Phagocytosis and Lipofuscin Accumulation

Improved Lipofuscin Models and Quantification of Outer Segment Phagocytosis Capacity in Highly Polarized Human Retinal Pigment Epithelial Cultures

The daily phagocytosis of photoreceptor outer segments by the retinal pigment epithelium (RPE) contributes to the accumulation of an intracellular aging pigment termed lipofuscin. The toxicity of lipofuscin is well established in Stargardt's disease, the most common inherited retinal degeneration, but is more controversial in age-related macular degeneration (AMD), the leading cause of irreversible blindness in the developed world. Determining lipofuscin toxicity in humans has been difficult, and animal models of Stargardt's have limited toxicity. Thus, in vitro models that mimic human RPE in vivo are needed to better understand lipofuscin generation, clearance, and toxicity. The majority of cell culture lipofuscin models to date have been in cell lines or have involved feeding RPE a single component of the complex lipofuscin mixture rather than fragments/tips of the entire photoreceptor outer segment, which generates a more complete and physiologic lipofuscin model. Described here is a method to induce the accumulation of lipofuscin-like material (termed undigestible autofluorescence material, or UAM) in highly differentiated primary human pre-natal RPE (hfRPE) and induced pluripotent stem cell (iPSC) derived RPE. UAM accumulated in cultures by repeated feedings of ultraviolet light-treated OS fragments taken up by the RPE via phagocytosis. The key ways that UAM approximates and differs from lipofuscin in vivo are also discussed. Accompanying this model of lipofuscin-like accumulation, imaging methods to distinguish the broad autofluorescence spectrum of UAM granules from concurrent antibody staining are introduced. Finally, to assess the impact of UAM on RPE phagocytosis capacity, a new method for quantifying outer segment fragment/tips uptake and breakdown has been introduced. Termed "Total Consumptive Capacity", this method overcomes potential misinterpretations of RPE phagocytosis capacity inherent in classic outer segment "pulse-chase" assays. The models and techniques introduced here can be used to study lipofuscin generation and clearance pathways and putative toxicity.

Author Spotlight: Improved Lipofuscin Models and Quantification of Outer Segment Phagocytosis Capacity in Highly Polarized Human Retinal Pigment Epithelial Cultures  

This protocol describes a lipofuscin accumulation model in highly differentiated and polarized human retinal pigment epithelial (RPE) cultures and an improved outer segment (OS) phagocytosis assay to detect the total OS consumption/degradation capacity of the RPE. These methods overcome the limitations of previous lipofuscin models and classical pulse-chase outer segment phagocytosis assays.

The daily phagocytosis of photoreceptor outer segments by the retinal pigment epithelium (RPE) contributes to the accumulation of an intracellular aging ...