This study was supported by the National Heart, Lung, and Blood Institute (NHLBI) (HL169522).

The details of all the reagents and equipment used for the study are listed in the Table of Materials.
1. Plate reading spectrophotometer high-throughput assay
<ol>
	<li>Seeding HEK-293 cells with the cADDis BacMam vector in a 96-well plate (Day 1)
	<ol>
		<li>Split and infect cells in a viral hood.
		<ol>
			<li>Warm HEK media (Table 1) and 0.25% trypsin-EDTA in a 37 &#176;C water bath.</li>
			<li>Disinfect the hood and the materials by wiping them with EtOH-soaked tissues.</li>
			<li>Remove and discard HEK media from the flask with a serological pipette.</li>
			<li>Add 5 mL of Mg2+ and Ca2+ free DPBS (37 &#176;C) with a serological pipette. Tilt the flask back and forth to wash the bottom with DPBS. Remove and discard DPBS with a serological pipette.</li>
			<li>Trypsinize the cells by adding 3 mL of warmed 0.25% trypsin-EDTA with a serological pipette. Tilt the flask to ensure the reagent fully coats the bottom of the flask. Put the lid on the flask and let the reagent sit for 3-5 min to allow the cells to detach from the&#160;flask. 
			NOTE: This experiment is optimized for a 75 cm2 flask; volume adjustments for reagents may need to be made if a different-size culture apparatus is used.</li>
			<li>Draw 5 mL of fresh media containing antibiotics. Expel and draw the volume of the flask to wash the walls of the flask and physically detach cells.</li>
			<li>Collect the total volume of the flask (8 mL), and centrifuge (25 &#176;C) in a 15 mL tube at 200 x g for 5 min.</li>
			<li>After centrifuging, remove the supernatant with a serological pipette, careful not to disturb the pellet.</li>
			<li>To wash the cells without disturbing the pellet, add 500 &#181;L of DPBS without Mg2+ and Ca2+ DPBS to the side of the 15 mL tube. After gently adding the DPBS, remove and discard as much buffer as possible without disturbing the pellet. Repeat one&#160;more time.</li>
			<li>Count the cells and adjust to a cell density of 250,000 cells/mL cells.</li>
			<li>Make a master mix based on what reagent volumes are needed per well of a black, transparent bottom 96-well plate. This is referred to as the &#34;tissue plate.&#34; See volumes below: 
			NOTE: Example of 1 well (total volume 200 &#181;L): 40 &#181;L of the biosensor BacMam vector (stock of 2 x 1010 viral genes /mL), 2 &#181;L trichostatin A (stock of 100 &#181;M; final concentration 1 &#181;M), 158 &#181;L of 250,000 cells/mL cell density. Example of 10 wells (total volume 2 mL): 400 &#181;L of the biosensor BacMam vector (stock of 2 x 1010 viral genes /mL), 20 &#181;L of trichostatin A (stock of 100 &#181;M), 1,580 &#181;L media with 250,000 cells/mL cell density.</li>
			<li>Add 200 &#181;L of master mix per well. Incubate the cells at 37 &#176;C and 5% CO2 in an incubator for 24 h before running on the plate reading spectrophotometer.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Running on a plate reader
	<ol>
		<li>On a benchtop, carefully remove all media in each well and replace with 180 &#181;L of DPBS with Mg2+ and Ca2+ at 37 &#176;C.</li>
		<li>Inspect cells on a microscope to confirm cell health.</li>
		<li>Wrap the plate in aluminum foil and incubate at 37 &#176;C for 30 min-1 h.</li>
		<li>While incubating, prepare the drugs for the reading at 1:10 dilution (also called 10-fold) for the desired final dose. Thus, prepare 100 &#181;M forskolin and 100 nM isoproterenol.</li>
		<li>Add 60 &#181;L of each drug in a columnar fashion to a clear 96-well plate (referred to as the &#34;drug plate&#34;). 
		NOTE: With the proper drug dilution and to optimize the reading, the drugs are added to a clear 96-well plate, referred to as the &#34;drug plate&#34;, to be transferred at the time of the reading to the &#34;tissue plate&#34; using a 96-multi pipettor, allowing the drug to be added to all wells simultaneously and be rapidly read by the fluorescent spectrophotometer.</li>
	</ol>
	</li>
	<li>Fluorescence plate reader setup
	<ol>
		<li>Adjust the settings of the fluorescence plate reader.
		<ol>
			<li>Read Mode: fluorescence. Read Type: kinetic. Wavelengths reading: 494 nm and 522 nm.</li>
			<li>Reading time: Enter 3 min for the baseline fluorescent read and 7 min for the post-drug addition.&#34;Interval&#34; is entered as 00:00:30 for 30 s between each read. 
			NOTE: The reading time can be optimized and increased based on the required time.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Data acquisition
	<ol>
		<li>Remove the tissue plate from the incubator, remove the aluminum foil and the plate lid, and place the tissue plate in the plate reader. Close the reader drawer to allow the tissue plate to rest and equilibrate to the reader&#39;s temperature (37 &#176;C).</li>
		<li>Place the clear 96-well plate (drug plate) with the drug dilutions under the 96-multi pipette and practice drawing 20 &#181;L from the wells. Ensure that there is an even volume of drug pulled in the pipettor tips.</li>
		<li>Initiate a &#34;baseline&#34; measurement run. 
		NOTE: 40 RFU or above is considered viable data. If data is below this value, the experiment should be stopped and discarded.</li>
		<li>The tissue plate will eject from the reader at the end of the baseline run. Swiftly and carefully add 20 &#181;L from the clear drug plate to the black tissue plate. Then, quickly begin the &#34;treatment&#34; run. The tissue plate should not be out of the reader for more than 30 s after drugs are added. 
		NOTE: If the drug is added too quickly, the cells detach from the tissue plate, creating an unusable experiment. In addition, the cells are infected with a light-sensitive green fluorescent protein; thus, swiftly and promptly adding the drugs and beginning the second read is imperative to avoid missing the early part of the response.</li>
		<li>Once the second reading is complete, ensure that the tissue plate is ejected from the reader and data collection is concluded. 
		NOTE: Before disposing of the tissue plate, it is best practice to verify that the cells are still attached to the plate. Observe the cells under a microscope. If the cells detach, the results are invalid and should be discarded. The experiment will need to be repeated.</li>
		<li>Export the resulting data as an Excel file.</li>
		<li>Open the exported Excel readable data from the plate reader and copy and paste relevant information into the Excel conversion template. The data will transform from the plate reader set up to single well, column readouts to the right of the copied data. 
		NOTE: Columns of fluorescence for a well over time are listed at RFUs (titled column transformation) and as a decimal change relative to the RFU reading at initial reading (t0 titled Delta F). In the Excel template, the Delta F table is set to the last baseline reading before drug addition. This is the 6th data collection point.</li>
		<li>After data transformation, copy the data from Delta F and paste it into data analysis software as decay or relative decay in fluorescence over time.</li>
		<li>Change the X-title to &#34;time (s)&#34; and the Y-title to &#34;&#916;F/F0&#34; for relative decimal values.</li>
	</ol>
	</li>
</ol>
2. Single-cell assay using an inverted fluorescent microscope
<ol>
	<li>Seeding (HASM) cells with the cADDis BacMam vector in a 35 mm dish (Day 1)
	<ol>
		<li>Split and infect cells in a viral hood.
		<ol>
			<li>Warm HASM media (Table 1), 0.25% trypsin-EDTA in a 37 &#176;C water bath.</li>
			<li>Disinfect the hood and the materials and wipe the hood with EtOH-soaked tissues.</li>
			<li>Remove and discard HASM media from the flask with a serological pipette.</li>
			<li>Add 5 mL of Mg2+ and Ca2+ free DPBS (37 &#176;C) with a new serological pipette and tilt the flask to wash the bottom with the DPBS.</li>
			<li>Trypsinize cells by adding 3 mL of warmed 0.25% trypsin-EDTA with a serological pipette. Tilt the flask to ensure the reagent fully coats the bottom of the flask. Let the reagent sit for 3-5 min to allow the cells to detach from the flask.</li>
			<li>Draw 5 mL of fresh media containing antibiotics and expel the pipette to remove the cells from the bottom of the flask.</li>
			<li>Collect the total volume of the flask (8 mL) centrifuge in a centrifuge tube at 200 x g for 5 min.</li>
			<li>After centrifuging, remove the supernatant with a serological pipette, careful not to disturb the pellet.</li>
			<li>Without disturbing the pellet, add 500 &#181;L of DPBS without Mg2+ and Ca2+ DPBS to the side of the centrifuge tube. Remove and discard as much liquid as possible and repeat one more time. 
			NOTE: This experiment is optimized for a 75 cm2 flask; volume adjustments for reagents may need to be made if a different-size culture apparatus is used.</li>
			<li>Count cells and adjust to 40,000 cells/mL cell density.</li>
			<li>Make a master mix based on the reagent volume needed per well of a 35 mm dish. See volumes below: 
			NOTE: Example of 1 well (total volume 500 &#181;L): 20 &#181;L of the biosensor BacMam vector (stock of 2 x 1010 viral genes /mL), 5 &#181;L trichostatin A (stock of 100 &#181;M, final concentration 1 &#181;M), 500 &#181;L of 40,000 cells/mL cell density. Example for 4 wells (total volume 2 mL): 80 &#181;L of the biosensor BacMam vector (stock of viral genes /mL), 20 &#181;L of trichostatin A (stock of 100 &#181;M, final concentration 1 &#181;M), 2000 &#181;L media 40,000 cells/mL cell density.</li>
			<li>Add 500 &#181;L of master mix per well. Incubate the cells at 37 &#176;C and 5% CO2 for 24 h before continuing the experiment. 
			NOTE: The cell number may vary according to the cell line. To avoid overlapping cells for the analysis, use low cell numbers.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Preparing pharmacological agents (Day 2)
	<ol>
		<li>Carefully remove media in each well and replace with 450 &#181;L of DPBS with Mg2+ and Ca2+ at 37 &#176;C.</li>
		<li>Wrap the plate in aluminum foil and incubate the 35 mm disk at 37 &#176;C for 30 min-1 h.</li>
		<li>Inspect cells on a microscope to confirm cell health.</li>
		<li>In the meantime, prepare the drugs for the reading 1 log unit above the desired final concentration (10-fold greater). Thus, prepare 100 &#181;M forskolin and 100 nM isoproterenol.</li>
		<li>For log dose titers, prepare the drug at 10 mM and use serial dilutions to achieve 100 &#181;M of forskolin and 100 nM of isoproterenol.</li>
	</ol>
	</li>
	<li>Data acquisition 
	NOTE: The following settings are for a fluorescent inverted microscope. The software accompanying each microscope can differ; the general settings used in the current protocol are described here.
	<ol>
		<li>Turn on the central hub, then the inverted fluorescent microscope.</li>
		<li>Open the software that will be used for the capture and choose the time-lapse capture option.</li>
		<li>Place a 35 mm dish sample holder in the microscope stage.</li>
		<li>Set objective lens to x20.</li>
		<li>Use autofocus and get as clear a picture as possible. If it is difficult to find individual cells, start on a 4x objective, then move to 20x. Focus the sample manually if the microscope lacks an autofocus feature. 
		NOTE: The magnification of 40x can be used if more significant cell morphological detail is needed.</li>
		<li>Adjust the following settings for obtaining optimal data acquisition: Auto Brightness (exposure), Excitation Wavelength, Black Balance (to reduce background noise), Auto Focus.</li>
		<li>After finding an area of view with several cytoplasmic fluorescing cells, acquire data using time-lapse capture for 20 min every 30 s.</li>
		<li>Click on the go to begin the reading.</li>
		<li>Run for 3 min to collect baseline. As soon as the 3 min capture is taken, gently add 50 &#181;L of the drug to the appropriate well. When the drugs are added, the final concentration on the dish will be 10 &#181;M forskolin and 10 nM of isoproterenol. 
		NOTE: The drug must be added carefully; do not touch the plate with the pipette tip, as this may move the field of view made and make the sample unable to be analyzed.</li>
		<li>Leave the experiment to run for 17 more minutes with data capture every 30 s.</li>
		<li>Once the test is completed, ensure that the data is ready for analysis. 
		NOTE: While the current protocol does not incorporate a control for focal drift, it could be beneficial to include one in the experiment. For instance, the use of nuclear dyes can assist in managing focal drift during microscope analysis, especially when capturing images of live cells over prolonged durations. cADDis biosensors are typically distributed widely within the cell, making a broad focal plane the most effective capture and reducing the need for controlling focal drift9.</li>
	</ol>
	</li>
	<li>Analyzing the data 
	NOTE: The software accompanying each microscope can differ, so the general settings that should be used to analyze the captured images are described here.
	<ol>
		<li>Open the image files captured during the experiment.</li>
		<li>Use the polygon or circle tool to select the region of interest of each cell to perform the analysis. The analysis should give the brightness of each cell at each time point. 
		NOTE: Best practice is to select individual cells and not cells touching the wall of the dish or other cells. This ensures the best data collection possible. Select a minimum of 5 cells for analysis within each condition, and replicate the experiment at least three times.</li>
		<li>After analyzing the data, open the data in an Excel sheet and calculate the average brightness for each condition at each photo, starting at the picture just before adding the pharmacological agents or vehicle. In this example, at the 3 min mark or the 6th photo taken on the microscope, since each picture is taken every 30 s.</li>
		<li>Calculate &#916;F/F0 for each average value in each condition.</li>
		<li>Load into a statistical analysis software and plot &#916;F/F0 against time in s. 
		NOTE: Figure 1 provides a schematic overview of the major steps of the protocols.</li>
	</ol>
	</li>
</ol>

cAMP Analysis with cADDis: Single-Cell to High-Throughput Screening

<ol>
	<li>Krishna, G., Weiss, B., Brodie, B. B. <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,+sensitive+method+for+the+assay+of+adenyl+cyclase.">A simple, sensitive method for the assay of adenyl cyclase.</a> J Pharmacol Exp Ther. 163 (2), 379-385 (1968).</li><li>Post, S. R., Ostrom, R. S., Insel, P. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Biochemical+methods+for+detection+and+measurement+of+cyclic+amp+and+adenylyl+cyclase+activity.">Biochemical methods for detection and measurement of cyclic amp and adenylyl cyclase activity.</a> Methods Mol Biol. 126, 363-374 (2000).</li><li>Li, I. T., Pham, E., Truong, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Protein+biosensors+based+on+the+principle+of+fluorescence+resonance+energy+transfer+for+monitoring+cellular+dynamics.">Protein biosensors based on the principle of fluorescence resonance energy transfer for monitoring cellular dynamics.</a> Biotechnol Lett. 28 (24), 1971-1982 (2006).</li><li>Deal, J., Pleshinger, D. J., Johnson, S. C., Leavesley, S. J., Rich, T. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Milestones+in+the+development+and+implementation+of+fret-based+sensors+of+intracellular+signals:+A+biological+perspective+of+the+history+of+fret.">Milestones in the development and implementation of fret-based sensors of intracellular signals: A biological perspective of the history of fret.</a> Cell Signal. 75, 109769 (2020).</li><li>Leavesley, S. J., Rich, T. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Overcoming+limitations+of+fret+measurements.">Overcoming limitations of fret measurements.</a> Cytometry A. 89 (4), 325-327 (2016).</li><li>Zacharias, D. A., Violin, J. D., Newton, A. C., Tsien, R. Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Partitioning+of+lipid-modified+monomeric+GFPS+into+membrane+microdomains+of+live+cells.">Partitioning of lipid-modified monomeric GFPS into membrane microdomains of live cells.</a> Science. 296 (5569), 913-916 (2002).</li><li>Agarwal, S. R., 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=Compartmentalized+cAMP+signaling+associated+with+lipid+raft+and+non-raft+membrane+domains+in+adult+ventricular+myocytes.">Compartmentalized cAMP signaling associated with lipid raft and non-raft membrane domains in adult ventricular myocytes.</a> Front Pharmacol. 9, 332 (2018).</li><li>Tewson, P. H., Martinka, S., Shaner, N. C., Hughes, T. E., Quinn, A. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=New+dag+and+cAMP+sensors+optimized+for+live-cell+assays+in+automated+laboratories.">New dag and cAMP sensors optimized for live-cell assays in automated laboratories.</a> J Biomol Screen. 21 (3), 298-305 (2016).</li><li>Tewson, 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=Assay+for+detecting+Galphai-mediated+decreases+in+cAMP+in+living+cells.">Assay for detecting Galphai-mediated decreases in cAMP in living cells.</a> SLAS Discov. 23 (9), 898-906 (2018).</li><li>Nunez, F. J., 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=Glucocorticoids+rapidly+activate+cAMP+production+via+g(alphas)+to+initiate+non-genomic+signaling+that+contributes+to+one-third+of+their+canonical+genomic+effects.">Glucocorticoids rapidly activate cAMP production via g(alphas) to initiate non-genomic signaling that contributes to one-third of their canonical genomic effects.</a> FASEB J. 34 (2), 2882-2895 (2020).</li><li>Condreay, J. P., Witherspoon, S. M., Clay, W. C., Kost, T. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Transient+and+stable+gene+expression+in+mammalian+cells+transduced+with+a+recombinant+baculovirus+vector.">Transient and stable gene expression in mammalian cells transduced with a recombinant baculovirus vector.</a> Proc Natl Acad Sci U S A. 96 (1), 127-132 (1999).</li><li>Insel, P. A., 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=G+protein-coupled+receptor+(GPCR)+expression+in+native+cells:+&amp;#34;Novel&amp;#34;+endogpcrs+as+physiologic+regulators+and+therapeutic+targets.">G protein-coupled receptor (GPCR) expression in native cells: &amp;#34;Novel&amp;#34; endogpcrs as physiologic regulators and therapeutic targets.</a> Mol Pharmacol. 88 (1), 181-187 (2015).</li><li>Nunez, F. J., 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=Agonist-specific+desensitization+of+PGE(2)-stimulated+cAMP+signaling+due+to+upregulated+phosphodiesterase+expression+in+human+lung+fibroblasts.">Agonist-specific desensitization of PGE(2)-stimulated cAMP signaling due to upregulated phosphodiesterase expression in human lung fibroblasts.</a> Naunyn Schmiedebergs Arch Pharmacol. 393 (2), 843-856 (2020).</li><li>Ojiaku, C. A., 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=Transforming+growth+factor-beta1+decreases+beta(2)-agonist-induced+relaxation+in+human+airway+smooth+muscle.">Transforming growth factor-beta1 decreases beta(2)-agonist-induced relaxation in human airway smooth muscle.</a> Am J Respir Cell Mol Biol. 61 (2), 209-218 (2019).</li><li>Zuo, H., 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=Cigarette+smoke+up-regulates+pde3+and+pde4+to+decrease+cAMP+in+airway+cells.">Cigarette smoke up-regulates pde3 and pde4 to decrease cAMP in airway cells.</a> Br J Pharmacol. 175 (14), 2988-3006 (2018).</li><li>Cullum, S. A., Veprintsev, D. B., Hill, 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=Kinetic+analysis+of+endogenous+beta(2)+-adrenoceptor-mediated+cAMP+glosensor+responses+in+hek293+cells.">Kinetic analysis of endogenous beta(2) -adrenoceptor-mediated cAMP glosensor responses in hek293 cells.</a> Br J Pharmacol. 180 (2), 1304-1315 (2023).</li><li>Liu, X., Sun, S. Q., Ostrom, R. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fibrotic+lung+fibroblasts+show+blunted+inhibition+by+cAMP+due+to+deficient+cAMP+response+element-binding+protein+phosphorylation.">Fibrotic lung fibroblasts show blunted inhibition by cAMP due to deficient cAMP response element-binding protein phosphorylation.</a> J Pharmacol Exp Ther. 315 (2), 678-687 (2005).</li><li>Bogard, A. S., Birg, A. V., Ostrom, R. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Non-raft+adenylyl+cyclase+2+defines+a+cAMP+signaling+compartment+that+selectively+regulates+il-6+expression+in+airway+smooth+muscle+cells:+Differential+regulation+of+gene+expression+by+ac+isoforms.">Non-raft adenylyl cyclase 2 defines a cAMP signaling compartment that selectively regulates il-6 expression in airway smooth muscle cells: Differential regulation of gene expression by ac isoforms.</a> Naunyn Schmiedebergs Arch Pharmacol. 387 (4), 329-339 (2014).</li><li>Schmidt, M., Cattani-Cavalieri, I., Nunez, F. J., Ostrom, R. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Phosphodiesterase+isoforms+and+cAMP+compartments+in+the+development+of+new+therapies+for+obstructive+pulmonary+diseases.">Phosphodiesterase isoforms and cAMP compartments in the development of new therapies for obstructive pulmonary diseases.</a> Curr Opin Pharmacol. 51, 34-42 (2020).</li><li>Ostrom, K. F., 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=Physiological+roles+of+mammalian+transmembrane+adenylyl+cyclase+isoforms.">Physiological roles of mammalian transmembrane adenylyl cyclase isoforms.</a> Physiol Rev. 102 (2), 815-857 (2022).</li><li>Auld, D. 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=Characterization+of+chemical+libraries+for+luciferase+inhibitory+activity.">Characterization of chemical libraries for luciferase inhibitory activity.</a> J Med Chem. 51 (8), 2372-2386 (2008).</li><li>De Logu, F., 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=Schwann+cell+endosome+CGRP+signals+elicit+periorbital+mechanical+allodynia+in+mice.">Schwann cell endosome CGRP signals elicit periorbital mechanical allodynia in mice.</a> Nat Commun. 13 (1), 646 (2022).</li><li>Wray, N. H., Schappi, J. M., Singh, H., Senese, N. B., Rasenick, 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=NMDAR-independent,+cAMP-dependent+antidepressant+actions+of+ketamine.">NMDAR-independent, cAMP-dependent antidepressant actions of ketamine.</a> Mol Psychiatry. 24 (12), 1833-1843 (2019).</li><li>Thornquist, S. C., Pitsch, M. J., Auth, C. S., Crickmore, M. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Biochemical+evidence+accumulates+across+neurons+to+drive+a+network-level+eruption.">Biochemical evidence accumulates across neurons to drive a network-level eruption.</a> Mol Cell. 81 (4), 675-690 (2021).</li><li>Zhang, S. X., 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=Hypothalamic+dopamine+neurons+motivate+mating+through+persistent+cAMP+signalling.">Hypothalamic dopamine neurons motivate mating through persistent cAMP signalling.</a> Nature. 597 (7875), 245-249 (2021).</li><li>Lutas, A., Fernando, K., Zhang, S. X., Sambangi, A., Andermann, M. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=History-dependent+dopamine+release+increases+cAMP+levels+in+most+basal+amygdala+glutamatergic+neurons+to+control+learning.">History-dependent dopamine release increases cAMP levels in most basal amygdala glutamatergic neurons to control learning.</a> Cell Rep. 38 (4), 110297 (2022).</li><li>Zhang, 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=Area+postrema+cell+types+that+mediate+nausea-associated+behaviors.">Area postrema cell types that mediate nausea-associated behaviors.</a> Neuron. 109 (3), 461-472 (2021).</li></ol>

The authors have no competing financial interests.

Accurate and sensitive measurement of cAMP is crucial for understanding its role in various cellular processes and for studying the activity of cAMP-dependent signaling pathways. There are several methods commonly employed to measure cAMP levels, including ELISA, radioimmunoassay, FRET biosensors, and the GloSensor cAMP assay14,15,16,17,18. Each cAMP assay has...

Adenosine 3&#8242;,5&#8242;-cyclic monophosphate, cAMP, plays a central role in cellular communication and the coordination of various physiological processes. cAMP acts as a second messenger, relaying external signals from hormones, neurotransmitters, or other extracellular molecules to initiate a cascade of intracellular events1. Moreover, cAMP is intricately involved in various signaling pathways, including those associated with G-protein-coupled receptors (GPCRs) and adenylyl cyclases. Understanding the role of cAMP in cellular signaling is fundamental to unraveling the complex mechanisms that underlie normal cellular functions and the development of potential therapies for a wide range of medical conditions2.
In the past, various methods have been employed to measure cAMP directly or indirectly. These included radiolabeling of cellular ATP pools followed by column purification, HPLC, radioimmunoassays, and enzyme-linked immunoassays1,2. These legacy assays are limited by the fact that they are end-point measures, requiring a large number of samples to construct time-dependent responses. More recently, Fluorescence Resonance Energy Transfer (FRET) sensors were developed to create assays in living cells, producing real-time, dynamic data and allowing sensors to be targeted in different subcellular locations3. FRET leverages two fluorophores, one fluorescent donor, and one fluorescent acceptor that when in close proximity, the acceptor fluorophore will be excited by the donor fluorescent output. The two fluorophores most used are cyan fluorescent protein (CFP) and yellow fluorescent protein (YFP) since these have compatible excitation and emission properties. In addition to CFP and YFP, the utilization of the green fluorescent protein (GFP) and red fluorescent protein (RFP) is commonly used for FRET biosensors. cAMP FRET biosensors operate by having a donor and acceptor on opposite ends of the Epac2 cAMP binding protein. cAMP binding alters the confirmation of Epac and increases the distance between donor and acceptor fluorophores3,4. This conformational change is detected by a loss of FRET, that is, the excitation of the acceptor fluorophore by energy transferred from the donor fluorophore drops3. While a seemingly simple process, there are an abundance of limitations and issues with the FRET biosensor for cAMP research5. One of which is the selection of fluorescent proteins, for example, GFP, which can dimerize naturally, thus reducing sensitivity6. FRET-based cAMP biosensors have been targeted to specific microdomains7, but there may be limitations owing to the large size of a construct with two fluorophores6. Another significant issue is the low signal-to-noise ratio of FRET signals resulting from the overlap between excitation and emission of the fluorophore, resulting in high sampling frequency and complicating analysis of the results4,5.
Most recently, the novel biosensor (cAMP Difference Detector In Situ), cADDis has solved these and other limitations when it comes to studying the regulation of cAMP signaling8. One important improvement is the dependence on a single fluorophore. This allows for a rapid and efficient signal with a wider dynamic range and a high signal-to-noise ratio. As a result, there can be more accuracy as there is a less broad scope of wavelengths to comb through8. Like FRET probes, the biosensor has been targeted to subcellular locations, allowing research into the compartmentation theory and exploration in lipid rafts and non-rafts, and other subcellular domains9. Perhaps most important is the suitability of a single fluorophore biosensor for high-throughput screening, which has improved sensitivity and reproducibility over FRET-based biosensors. The biosensor is packaged into a BacMam vector for easy transduction of a wide array of cell types and precise control over protein expression.
Expression control via the BacMam vector can be particularly useful in assays using GPCR orthologs from different species to facilitate the interpretation of data from animal studies. Furthermore, control over receptor expression is critical for measuring the different degrees of drug efficacy (e.g., inverse agonists and partial agonists), and low levels of receptor expression are useful to mimic the low levels found in animal tissue. BacMam is a baculovirus vector that has been modified to transduce mammalian cells such as primary cell cultures and HEK-293 lines10. Dominant selectable markers allow for BacMam to provide more stability over traditional plasmid infections11. Such selective promoters allow for more efficient gene delivery and expression. In addition, adding trichostatin A (a histone deacetylase inhibitor) enhances the reporter protein levels11. Expression levels can be controlled via the titer of the BacMam virus used and should be optimized for each cell type. In the case of this biosensor, a red or green fluorescent protein is linked to the Epac at the N- and C-termini. When cAMP binds, a conformational change in the biosensor moves amino acids adjacent to the fluorescent protein. Such a shift moves the absorbance from the anionic state to the neutral state at 400 nm, thus decreasing the fluorescence.
There are 90-120 GPCRs expressed in a single cell that respond to a wide variety of neurohumoral signals12. Therefore, it can be hypothesized that at least several dozen GPCRs per cell can stimulate or inhibit cAMP through Gs or Gi coupling, respectively. While there has been progress in monitoring this second messenger in real-time, such as FRET, more efficient methods are needed. The methodology for monitoring the synthesis and degradation of cAMP signals using cADDis in real-time is presented here. The change in fluorescence can be monitored in real-time using a fluorescence plate reader for high throughput assays or using a fluorescent microscope for single-cell assays. These methods are useful for a wide array of biological questions regarding GPCR signaling via cAMP.

<table><tbody><tr><td>96-well plate (clear)</td><td>Fisherbrand</td><td>21-377-203</td><td></td></tr><tr><td>35 mm dish</td><td>Greiner Bio-One</td><td>627870</td><td>Cell culture dishes with glass bottom</td></tr><tr><td>96-well plate&amp;nbsp;</td><td>Corning</td><td>3904</td><td>Black with clear flat bottom</td></tr><tr><td>Antibiotic-Antimycotic (100x)</td><td>Gibco</td><td>15240062</td><td>For HEK and HASM media</td></tr><tr><td>BZ-X fluorescence microscope</td><td>Keyence</td><td></td><td></td></tr><tr><td>Calcium chloride (IM)</td><td>Quality Biological Inc</td><td>E506</td><td>For HASM media</td></tr><tr><td>Centrifuge tube (15 mL)</td><td>Thermo Scientific</td><td>339651</td><td></td></tr><tr><td>DMEM (1x)</td><td>Gibco</td><td>11965092</td><td>HEK media</td></tr><tr><td>DPBS with Mg&lt;sup&gt;2+&lt;/sup&gt; and Ca&lt;sup&gt;2+&lt;/sup&gt;&amp;nbsp;</td><td>Gibco</td><td>14040-133</td><td></td></tr><tr><td>DPBS without Mg&lt;sup&gt;2+&lt;/sup&gt; and Ca&lt;sup&gt;2+&lt;/sup&gt;</td><td>Corning</td><td>14040-133</td><td></td></tr><tr><td>Fetal Bovine Serum (FBS)</td><td>R&amp;amp;D systems</td><td>S11195</td><td>For HEK and HASM media</td></tr><tr><td>Forskolin</td><td>Millipore</td><td>344270</td><td>Drug</td></tr><tr><td>Green Down cADDis cAMP Assay Kit</td><td>Montana Molecular</td><td>#D0200G</td><td>Reagent</td></tr><tr><td>Ham&#039;s F-12K&amp;nbsp;</td><td>Gibco</td><td>21127022</td><td>For HASM media</td></tr><tr><td>HEPES (1M)</td><td>Gibco</td><td>15630080</td><td>For HASM media</td></tr><tr><td>Isoproterenol</td><td>Sigma</td><td>I6504</td><td>Drug</td></tr><tr><td>L-glutamine 200 mM (100x)</td><td>Gibco</td><td>25030-081</td><td>For HASM media</td></tr><tr><td>Microcentrifuge tube (2 mL)</td><td>Eppendorf</td><td>22363352</td><td></td></tr><tr><td>Primocin</td><td>Invitrogen</td><td>ant-pm-1</td><td>Antibiotic for HASM media</td></tr><tr><td>RNAse away</td><td>Thermo Scientific</td><td>700511</td><td>Reagent</td></tr><tr><td>Sodium hydroxide solution</td><td>Sigma</td><td>S2770</td><td>For HASM media</td></tr><tr><td>Spectrmax M5 plate reader</td><td>Molecular Devices</td><td></td><td></td></tr><tr><td>Trichostatin A</td><td>TCI America</td><td>T2477</td><td>Reagent</td></tr><tr><td>Trypsin EDTA</td><td>Gibco</td><td>25200-056</td><td>Reagent</td></tr></tbody></table>

real-time camp dynamics in live cells using the fluorescent camp difference detector in situ

cAMP Difference Detector In Situ (cADDis) is a novel biosensor that allows for the continuous measurement of cAMP levels in living cells. The biosensor is created from a circularly permuted fluorescent protein linked to the hinge region of Epac2. This creates a single fluorophore biosensor that displays either increased or decreased fluorescence upon binding of cAMP. The biosensor exists in red and green upward versions, as well as green downward versions, and several red and green versions targeted to subcellular locations. To illustrate the effectiveness of the biosensor, the green downward version, which decreases in fluorescence upon cAMP binding, was used. Two protocols using this sensor are demonstrated: one utilizing a 96-well plate reading spectrophotometer&#160;compatible with high-throughput screening and another utilizing single-cell imaging on a fluorescent microscope. On the plate reader, HEK-293 cells cultured in 96-well plates were stimulated with 10 &#181;M forskolin or 10 nM isoproterenol, which induced rapid and large decreases in fluorescence in the green downward version. The biosensor was used to measure cAMP levels in individual human airway smooth muscle (HASM) cells monitored under a fluorescent microscope. The green downward biosensor displayed similar responses to populations of cells when stimulated with forskolin or isoproterenol. This single-cell assay allows visualization of the biosensor location at 20x and 40x magnification. Thus, this cAMP biosensor is sensitive and flexible, allowing real-time measurement of cAMP in both immortalized and primary cells, and with single cells or populations of cells. These attributes make cADDis a valuable tool for studying cAMP signaling dynamics in living cells.

The present study validated the cytosolic biosensor in both plate reader and microscope assays. Once cells expressed the biosensor, they were stimulated with either 10 &#181;M forskolin (a direct activator of adenylyl cyclase), 10 nM isoproterenol (an agonist at &#223;1AR and &#223;2AR), or vehicle (Figure 1). The subsequent changes in fluorescence, indicative of cAMP production, were captured every 30 s.
The data was transformed as the chang...

Read this Scientific Article Protocol about Author Spotlight: Advancing Real-Time cAMP Detection in Cells Using cADDis Biosensor at JoVE.com

Author Spotlight: Advancing Real-Time cAMP Detection in Cells Using cADDis Biosensor

The protocol presented in this study illustrates the effectiveness of the cAMP Difference Detector In Situ in measuring cAMP through two methods. One method utilizes a 96-well plate reading spectrophotometer with HEK-293 cells. The other method demonstrates individual HASM cells under a fluorescent microscope.

Real-Time cAMP Dynamics in Live Cells Using the Fluorescent cAMP Difference Detector In Situ

cAMP Difference Detector In Situ (cADDis) is a novel biosensor that allows for the continuous measurement of cAMP levels in living cells. The biosensor is ...

real-time-camp-dynamics-live-cells-using-fluorescent-camp-difference

Research

JoVE Journal

Biochemistry

759 Views.  Chapman University School of Pharmacy. The protocol presented in this study illustrates the effectiveness of the cAMP Difference Detector In Situ in measuring cAMP through two methods. One method utilizes a 96-well plate reading spectrophotometer with HEK-293 cells. The other method demonstrates individual HASM cells under a fluorescent microscope.

Video: Author Spotlight: Advancing Real-Time cAMP Detection in Cells Using cADDis Biosensor

Live-cell Imaging of Migrating Cells Expressing Fluorescently-tagged Proteins in a Three-dimensional Matrix

Traditionally, cell migration has been studied on two-dimensional, stiff plastic surfaces. However, during important biological processes such as wound healing, tissue regeneration, and cancer metastasis, cells must navigate through complex, three-dimensional extracellular tissue. To better understand the mechanisms behind these biological processes, it is important to examine the roles of the proteins responsible for driving cell migration. Here, we outline a protocol to study the mechanisms of cell migration using the epithelial cell line (MDCK), and a three-dimensional, fibrous, self-polymerizing matrix as a model system. This optically clear extracellular matrix is easily amenable to live-cell imaging studies and better mimics the physiological, soft tissue environment. This report demonstrates a technique for directly visualizing protein localization and dynamics, and deformation of the surrounding three-dimensional matrix. 
Examination of protein localization and dynamics during cellular processes provides key insight into protein functions. Genetically encoded fluorescent tags provide a unique method for observing protein localization and dynamics. Using this technique, we can analyze the subcellular accumulation of key, force-generating cytoskeletal components in real-time as the cell maneuvers through the matrix. In addition, using multiple fluorescent tags with different wavelengths, we can examine the localization of multiple proteins simultaneously, thus allowing us to test, for example, whether different proteins have similar or divergent roles. Furthermore, the dynamics of fluorescently tagged proteins can be quantified using Fluorescent Recovery After Photobleaching (FRAP) analysis. This measurement assays the protein mobility and how stably bound the proteins are to the cytoskeletal network.
By combining live-cell imaging with the treatment of protein function inhibitors, we can examine in real-time the changes in the distribution of proteins and morphology of migrating cells. Furthermore, we also combine live-cell imaging with the use of fluorescent tracer particles embedded within the matrix to visualize the matrix deformation during cell migration. Thus, we can visualize how a migrating cell distributes force-generating proteins, and where the traction forces are exerted to the surrounding matrix. Through these techniques, we can gain valuable insight into the roles of specific proteins and their contributions to the mechanisms of cell migration.

Cellular processes such as cell migration have traditionally been studied on two-dimensional, stiff plastic surfaces. This report describes a technique for directly visualizing protein localization and analyzing protein dynamics in cells migrating in a more physiologically relevant, three-dimensional matrix.

Traditionally, cell migration has been studied on two-dimensional, stiff plastic surfaces. However, during important biological processes such as wound ...

Bioengineering

An Optogenetic Method to Control and Analyze Gene Expression Patterns in Cell-to-cell Interactions

Cells should respond properly to temporally changing environments, which are influenced by various factors from surrounding cells. The Notch signaling pathway is one of such essential molecular machinery for cell-to-cell communications, which plays key roles in normal development of embryos. This pathway involves a cell-to-cell transfer of oscillatory information with ultradian rhythms, but despite the progress in molecular biology techniques, it has been challenging to elucidate the impact of multicellular interactions on oscillatory gene dynamics. Here, we present a protocol that permits optogenetic control and live monitoring of gene expression patterns in a precise temporal manner. This method successfully revealed that intracellular and intercellular periodic inputs of Notch signaling entrain intrinsic oscillations by frequency tuning and phase shifting at the single-cell resolution. This approach is applicable to the analysis of the dynamic features of various signaling pathways, providing a unique platform to test a functional significance of dynamic gene expression programs in multicellular systems.

Here, we present a protocol to analyze cell-to-cell transfer of oscillatory information by optogenetic control and live monitoring of gene expression. This approach provides a unique platform to test a functional significance of dynamic gene expression programs in multicellular systems.

Cells should respond properly to temporally changing environments, which are influenced by various factors from surrounding cells. The Notch signaling ...

Genetics

Real-time Live Imaging of T-cell Signaling Complex Formation

Protection against infectious diseases is mediated by the immune system 1,2. T lymphocytes are the master coordinators of the immune system, regulating the activation and responses of multiple immune cells 3,4. T-cell activation is dependent on the recognition of specific antigens displayed by antigen presenting cells (APCs). The T-cell antigen receptor (TCR) is specific to each T-cell clone and determines antigen specificity 5. The binding of the TCR to the antigen induces the phosphorylation of components of the TCR complex. In order to promote T-cell activation, this signal must be transduced from the membrane to the cytoplasm and the nucleus, initiating various crucial responses such as recruitment of signaling proteins to the TCR;APC site (the immune synapse), their molecular activation, cytoskeletal rearrangement, elevation of intracellular calcium concentration, and changes in gene expression 6,7. The correct initiation and termination of activating signals is crucial for appropriate T-cell responses. The activity of signaling proteins is dependent on the formation and termination of protein-protein interactions, post translational modifications such as protein phosphorylation, formation of protein complexes, protein ubiquitylation and the recruitment of proteins to various cellular sites 8. Understanding the inner workings of the T-cell activation process is crucial for both immunological research and clinical applications.
Various assays have been developed in order to investigate protein-protein interactions; however, biochemical assays, such as the widely used co-immunoprecipitation method, do not allow protein location to be discerned, thus precluding the observation of valuable insights into the dynamics of cellular mechanisms. Additionally, these bulk assays usually combine proteins from many different cells that might be at different stages of the investigated cellular process. This can have a detrimental effect on temporal resolution. The use of real-time imaging of live cells allows both the spatial tracking of proteins and the ability to temporally distinguish between signaling events, thus shedding light on the dynamics of the process 9,10. We present a method of real-time imaging of signaling-complex formation during T-cell activation. Primary T-cells or T-cell lines, such as Jurkat, are transfected with plasmids encoding for proteins of interest fused to monomeric fluorescent proteins, preventing non-physiological oligomerization 11. Live T cells are dropped over a coverslip pre-coated with T-cell activating antibody 8,9, which binds to the CD3/TCR complex, inducing T-cell activation while overcoming the need for specific activating antigens. Activated cells are constantly imaged with the use of confocal microscopy. Imaging data are analyzed to yield quantitative results, such as the colocalization coefficient of the signaling proteins.

We describe a live-cell imaging method that provides insight into protein dynamics during the T-cell activation process. We demonstrate the combined usage of the T-cell spreading assay, confocal microscopy and imaging analysis to yield quantitative results to follow signaling complex formation throughout T-cell activation.

Protection against infectious diseases is mediated by the immune system 1,2. T lymphocytes are the master coordinators of the immune system, regulating ...

Immunology and Infection

Dual-Color Fluorescence Cross-Correlation Spectroscopy to Study Protein-Protein Interaction and Protein Dynamics in Live Cells

We present a protocol and workflow to perform live cell dual-color fluorescence cross-correlation spectroscopy (FCCS) combined with F&#246;rster Resonance Energy transfer (FRET) to study membrane receptor dynamics in live cells using modern fluorescence labeling techniques. In dual-color FCCS, where the fluctuations in fluorescence intensity represent the dynamic &#34;fingerprint&#34; of the respective fluorescent biomolecule, we can probe co-diffusion or binding of the receptors. FRET, with its high sensitivity to molecular distances, serves as a well-known &#34;nanoruler&#34; to monitor intramolecular changes. Taken together, conformational changes and key parameters such as local receptor concentrations and mobility constants become accessible in cellular settings.
Quantitative fluorescence approaches are challenging in cells due to high noise levels and the vulnerability of the sample. Here we show how to perform this experiment, including the calibration steps using dual-color labeled &#946;2-adrenergic receptor (&#946;2AR) labeled with eGFP and SNAP-tag-TAMRA. A step-by-step data analysis procedure is provided using open-source software and templates that are easy to customize.
Our guideline enables researchers to unravel molecular interactions of biomolecules in live cells in situ with high reliability despite the limited signal-to-noise levels in live cell experiments. The operational window of FRET and particularly FCCS at low concentrations allows quantitative analysis at near-physiological conditions.

We present an experimental protocol and data analysis workflow to perform live cell dual-color fluorescence cross correlation spectroscopy (FCCS) combined with F&#246;rster Resonance Energy transfer (FRET) to study membrane receptor dynamics in live cells using modern fluorescence labeling techniques.

We present a protocol and workflow to perform live cell dual-color fluorescence cross-correlation spectroscopy (FCCS) combined with F&#246;rster Resonance ...

Monitoring Kinase and Phosphatase Activities Through the Cell Cycle by Ratiometric FRET

F&ouml;rster resonance energy transfer (FRET)-based reporters1 allow the assessment of endogenous kinase and phosphatase activities in living cells. Such probes typically consist of variants of CFP and YFP, intervened by a phosphorylatable sequence and a phospho-binding domain. Upon phosphorylation, the probe changes conformation, which results in a change of the distance or orientation between CFP and YFP, leading to a change in FRET efficiency (Fig 1). Several probes have been published during the last decade, monitoring the activity balance of multiple kinases and phosphatases, including reporters of PKA2, PKB3, PKC4, PKD5, ERK6, JNK7, Cdk18, Aurora B9 and Plk19. Given the modular design, additional probes are likely to emerge in the near future10. 
Progression through the cell cycle is affected by stress signaling pathways 11. Notably, the cell cycle is regulated differently during unperturbed growth compared to when cells are recovering from stress12.Time-lapse imaging of cells through the cell cycle therefore requires particular caution. This becomes a problem particularly when employing ratiometric imaging, since two images with a high signal to noise ratio are required to correctly interpret the results. Ratiometric FRET imaging of cell cycle dependent changes in kinase and phosphatase activities has predominately been restricted to sub-sections of the cell cycle8,9,13,14.
Here, we discuss a method to monitor FRET-based probes using ratiometric imaging throughout the human cell cycle. The method relies on equipment that is available to many researchers in life sciences and does not require expert knowledge of microscopy or image processing.

FRET-based reporters are increasingly used to monitor kinase and phosphatase activities in live cells. Here we describe a method on how to use FRET-based reporters to assess cell cycle-dependent changes in target phosphorylation.

F&ouml;rster resonance energy transfer (FRET)-based reporters1 allow the assessment of endogenous kinase and phosphatase activities in living cells. Such ...

Biology

FRET Microscopy for Real-time Monitoring of Signaling Events in Live Cells Using Unimolecular Biosensors

F&ouml;rster resonance energy transfer (FRET) microscopy continues to gain increasing interest as a technique for real-time monitoring of biochemical and signaling events in live cells and tissues. Compared to classical biochemical methods, this novel technology is characterized by high temporal and spatial resolution. FRET experiments use various genetically-encoded biosensors which can be expressed and imaged over time in situ or in vivo1-2. Typical biosensors can either report protein-protein interactions by measuring FRET between a fluorophore-tagged pair of proteins or conformational changes in a single protein which harbors donor and acceptor fluorophores interconnected with a binding moiety for a molecule of interest3-4. Bimolecular biosensors for protein-protein interactions include, for example, constructs designed to monitor G-protein activation in cells5, while the unimolecular sensors measuring conformational changes are widely used to image second messengers such as calcium6, cAMP7-8, inositol phosphates9 and cGMP10-11. Here we describe how to build a customized epifluorescence FRET imaging system from single commercially available components and how to control the whole setup using the Micro-Manager freeware. This simple but powerful instrument is designed for routine or more sophisticated FRET measurements in live cells. Acquired images are processed using self-written plug-ins to visualize changes in FRET ratio in real-time during any experiments before being stored in a graphics format compatible with the build-in ImageJ freeware used for subsequent data analysis. This low-cost system is characterized by high flexibility and can be successfully used to monitor various biochemical events and signaling molecules by a plethora of available FRET biosensors in live cells and tissues. As an example, we demonstrate how to use this imaging system to perform real-time monitoring of cAMP in live 293A cells upon stimulation with a &beta;-adrenergic receptor agonist and blocker.

F&#246;rster resonance energy transfer (FRET) microscopy is a powerful technique for real-time monitoring of signaling events in live cells using various biosensors as reporters. Here we describe how to build a customized epifluorescence FRET imaging system from commercially available components and how to use it for FRET experiments.

F&ouml;rster resonance energy transfer (FRET) microscopy  continues to gain increasing interest as a technique for real-time monitoring  of biochemical ...

Single-molecule Imaging of Gene Regulation In vivo Using Cotranslational Activation by Cleavage (CoTrAC)

We describe a fluorescence microscopy method, Co-Translational Activation by Cleavage (CoTrAC) to image the production of protein molecules in live cells with single-molecule precision without perturbing the protein's functionality. This method makes it possible to count the numbers of protein molecules produced in one cell during sequential, five-minute time windows. It requires a fluorescence microscope with laser excitation power density of ~0.5 to 1 kW/cm2, which is sufficiently sensitive to detect single fluorescent protein molecules in live cells. The fluorescent reporter used in this method consists of three parts: a membrane targeting sequence, a fast-maturing, yellow fluorescent protein and a protease recognition sequence. The reporter is translationally fused to the N-terminus of a protein of interest. Cells are grown on a temperature-controlled microscope stage. Every five minutes, fluorescent molecules within cells are imaged (and later counted by analyzing fluorescence images) and subsequently photobleached so that only newly translated proteins are counted in the next measurement.
Fluorescence images resulting from this method can be analyzed by detecting fluorescent spots in each image, assigning them to individual cells and then assigning cells to cell lineages. The number of proteins produced within a time window in a given cell is calculated by dividing the integrated fluorescence intensity of spots by the average intensity of single fluorescent molecules. We used this method to measure expression levels in the range of 0-45 molecules in single 5 min time windows. This method enabled us to measure noise in the expression of the &lambda; repressor CI, and has many other potential applications in systems biology.

Single-molecule Imaging of Gene Regulation In vivo Using Cotranslational Activation by Cleavage CoTrAC

We describe a fluorescence microscopy method, Co-Translational Activation by Cleavage (CoTrAC), to image the production of protein molecules in live cells with single-molecule precision without perturbing the protein's functionality. This method has been used to follow the stochastic expression dynamics of a transcription factor, the &lambda; repressor CI 1.

We describe a fluorescence microscopy method, Co-Translational Activation by Cleavage (CoTrAC) to image the production of protein molecules in live cells ...

Temporal Quantification of MAPK Induced Expression in Single Yeast Cells

The quantification of gene expression at the single cell level uncovers novel regulatory mechanisms obscured in measurements performed at the population level. Two methods based on microscopy and flow cytometry are presented to demonstrate how such data can be acquired. The expression of a fluorescent reporter induced upon activation of the high osmolarity glycerol MAPK pathway in yeast is used as an example. The specific advantages of each method are highlighted. Flow cytometry measures a large number of cells (10,000) and provides a direct measure of the dynamics of protein expression independent of the slow maturation kinetics of the fluorescent protein. Imaging of living cells by microscopy is by contrast limited to the measurement of the matured form of the reporter in fewer cells. However, the data sets generated by this technique can be extremely rich thanks to the combinations of multiple reporters and to the spatial and temporal information obtained from individual cells. The combination of these two measurement methods can deliver new insights on the regulation of protein expression by signaling pathways.

Two complementary methods based on flow cytometry and microscopy are presented which enable the quantification, at the single cell level, of the dynamics of gene expression induced by the activation of a MAPK pathway in yeast.

The quantification of gene expression at the  single cell level uncovers novel regulatory mechanisms obscured in measurements  performed at the population ...

Live Cell Fluorescence Microscopy to Observe Essential Processes During Microbial Cell Growth

Core cellular processes such as DNA replication and segregation, protein synthesis, cell wall biosynthesis, and cell division rely on the function of proteins which are essential for bacterial survival. A series of target-specific dyes can be used as probes to better understand these processes. Staining with lipophilic dyes enables the observation of membrane structure, visualization of lipid microdomains, and detection of membrane blebs. Use of fluorescent-d-amino acids (FDAAs) to probe the sites of peptidoglycan biosynthesis can indicate potential defects in cell wall biogenesis or cell growth patterning. Finally, nucleic acid stains can indicate possible defects in DNA replication or chromosome segregation. Cyanine DNA stains label living cells and are suitable for time-lapse microscopy enabling real-time observations of nucleoid morphology during cell growth. Protocols for cell labeling can be applied to protein depletion mutants to identify defects in membrane structure, cell wall biogenesis, or chromosome segregation. Furthermore, time-lapse microscopy can be used to monitor morphological changes as an essential protein is removed and can provide additional insights into protein function. For example, the depletion of essential cell division proteins results in filamentation or branching, whereas the depletion of cell growth proteins may cause cells to become shorter or rounder. Here, protocols for cell growth, target-specific labeling, and time-lapse microscopy are provided for the bacterial plant pathogen Agrobacterium tumefaciens. Together, target-specific dyes and time-lapse microscopy enable characterization of essential processes in A. tumefaciens. Finally, the protocols provided can be readily modified to probe essential processes in other bacteria.

Understanding the function of essential processes in bacteria is challenging. Fluorescence microscopy with target-specific dyes can provide key insights into microbial cell growth and cell cycle progression. Here, Agrobacterium tumefaciens is used as a model bacterium to highlight methods for live cell imaging for characterization of essential processes.

Core cellular processes such as DNA replication and segregation, protein synthesis, cell wall biosynthesis, and cell division rely on the function of ...

Real-Time Monitoring of Aurora kinase A Activation using Conformational FRET Biosensors in Live Cells

Epithelial cancers are often hallmarked by the overexpression of the Ser/Thr kinase Aurora A/AURKA. AURKA is a multifunctional protein that activates upon its autophosphorylation on Thr288. AURKA abundance peaks in mitosis, where it controls the stability and the fidelity of the mitotic spindle, and the overall efficiency of mitosis. Although well characterized at the structural level, a consistent monitoring of the activation of AURKA throughout the cell cycle is lacking. A possible solution consists in using genetically-encoded F&#246;rster&#8217;s Resonance Energy Transfer (FRET) biosensors to gain insight into the autophosphorylation of AURKA with sufficient spatiotemporal resolution. Here, we describe a protocol to engineer FRET biosensors detecting Thr288 autophosphorylation, and how to follow this modification during mitosis. First, we provide an overview of possible donor/acceptor FRET pairs, and we show possible cloning and insertion methods of AURKA FRET biosensors in mammalian cells. Then, we provide a step-by-step analysis for rapid FRET measurements by fluorescence lifetime imaging microscopy (FLIM) on a custom-built setup. However, this protocol is also applicable to alternative commercial solutions available. We conclude by considering the most appropriate FRET controls for an AURKA-based biosensor, and by highlighting potential future improvements to further increase the sensitivity of this tool.

The activation of the multifunctional Ser/Thr kinase AURKA is hallmarked by its autophosphorylation on Thr288. Fluorescent probes relying on FRET can discriminate between its inactive and activated states. Here, we illustrate some strategies for probe engineering, together with a rapid FRET protocol to follow the kinase activation throughout mitosis.

Epithelial cancers are often hallmarked by the overexpression of the Ser/Thr kinase Aurora A/AURKA. AURKA is a multifunctional protein that activates upon ...