We thank the engineers of the Microscopy-Rennes Imaging Center (MRic, BIOSIT, Rennes, France) for advice and help, and particularly X. Pinson for critical reading of the manuscript. MRic is member of the national infrastructure France-BioImaging supported by the French National Research Agency (ANR-10-INBS-04). This work was supported by the Centre National de la Recherche Scientifique (CNRS), the Ligue Contre le Cancer Comite&#769;s d&#8217;Ille et Vilaine, des Co&#770;tes d&#8217;Armor et du Finist&#232;re, and the Association pour la Recherche Contre le Cancer (ARC) to G.B.

NOTE: U2OS cells used in this protocol were purchased from American Type Culture Collection (ATCC, HTB-96), and they were tested free from mycoplasma. Step 2.1 to 2.7 should be performed under a laminar flow hood to keep cells and reagents sterile.
1. Choosing the donor/acceptor FRET pair
<ol>
	<li>Refer to the literature for the choice of the most suitable donor/acceptor FRET pairs. Useful examples can be found in20,21,22,23,24, although the final choice must be made according to the characteristics of the FRET/FLIM setup (available laser lines, filters, etc.). The following are some considerations on how to select a donor/acceptor pair.
	<ol>
		<li>Choosing the donor: refer to FP base (https://www.fpbase.org/) for a complete set of information on the available fluorescent proteins. This database is constantly updated with all the newly-developed fluorophores.</li>
		<li>Refer to the Fluorescent Biosensor Database (https://biosensordb.ucsd.edu/index.php) for more information on the biosensors already available in the literature, together with the respective fluorescent proteins used.</li>
		<li>As a general starting point, choose a bright donor fluorophore. Good candidates are cyan fluorescent proteins as mTFP1 or ECFP, or GFP variants as EGFP or mEGFP.</li>
		<li>Oligomers can affect protein localization and/or function25. Consider using monomeric mutants of CFP as mTurquoise226, or Aquamarine27,28. These variants also have good quantum yield and extinction coefficients, which make them good candidates as FRET donors.</li>
		<li>Give preference to fluorescent proteins (both as donor or acceptors) insensitive to environmental changes like intracellular pH23, or to photobleaching25, as FRET efficiency can be heavily affected by these parameters29. Nowadays, fluorophores like mTurquoise2 or mTFP1 are extensively used as donors, thanks to their good photostability22,25,26.</li>
	</ol>
	</li>
	<li>Choosing the acceptor: cyan donors are often paired with Yellow Fluorescent Protein (YFP) variants, as mVenus, Citrine, and YPet20,21,22,30. However, it should be noted that these proteins have a much greater sensitivity to pH, and globally display a poor photostability.
	<ol>
		<li>Consider using newly-developed, pH-insensitive yellow variants of YFP as pH-Lemon31, green fluorophores as mNeonGreen23 or red fluorophores as mScarlet-I23,32 as previously-validated fluorescent acceptors for mTurquoise2.</li>
		<li>Alternatively, consider using non-fluorescent/dark derivatives of YFP as ShadowG33 or ShadowY34, which were shown to behave as good acceptors for cyan-fluorescent donors in FRET/FLIM experiments.</li>
		<li>If using mEGFP as a donor, consider using monomeric red acceptors as mCherry.</li>
	</ol>
	</li>
	<li>Verify the spectral properties of the chosen donor/acceptor pair using the tools available on the FP base website. See Figure 1 for an example of the mEGFP/mCherry pair.
	<ol>
		<li>On the FP base website, select the Tools drop-down menu and select Spectra viewer.</li>
		<li>In the drop-down menus, enter the name of the fluorophore pair to visualize (e.g., mEGFP and mCherry).</li>
		<li>Simulate the properties of the donor/acceptor pair with a specific light source by selecting a given laser in the drop-down menu. Alternatively, enter a specific laser wavelength by selecting Add laser. Click on the Normalize emission to this option to adjust the fluorophore spectra to the desired wavelength. Here, the wavelength used to excite GFP is at 480 &#177; 10 nm.</li>
	</ol>
	</li>
	<li>Clone the selected donor/acceptor pair by adding one fluorophore at the N-terminus of the full-length sequence of AURKA, and one at the C-terminus. Follow the guidelines of the preferred cloning method to insert this construct in a mammalian expression vector of choice.</li>
</ol>
2. Cell culture, transfection and synchronization
<ol>
	<li>DAY 1. Prepare culture medium for U2OS cells: use Dulbecco&#8217;s Modified Eagle Medium (DMEM) supplemented with 10% Fetal Bovine Serum (FBS), 1% Penicillin-Streptomycin and 1% L-Glutamine (from here on, Complete growth media). Alternatively, DMEM with pre-supplemented L-Glutamine can also be used.</li>
	<li>If cells are frozen, thaw a vial at least 8 days prior to experiments (i.e., from point 2.5 on).</li>
	<li>Grow cells in an incubator dedicated to mammalian cell cultures at 37 &#176;C and with 5% CO2. Clean and sterilize the incubator regularly to avoid contaminations.</li>
	<li>When the cells reach ~80% confluence:
	<ol>
		<li>Wash them briefly with sterile 1x phosphate buffer saline (PBS) without Ca2+ and Mg2+.</li>
		<li>Trypsinize cells with sterile 0.05% Trypsin-EDTA according to manufacturer&#8217;s protocol and by placing cells in the incubator for 1-3 min.</li>
		<li>Inactivate trypsin by adding twice the volume of complete growth media; mix well.</li>
		<li>Centrifuge the cell suspension at 800 x g for 3-5 min.</li>
		<li>Count the cells using a hemocytometer and calculate the appropriate dilution for them to be at ~70-80% confluency in chamber slides the day after. Alternatively, similar supports for live cell imaging can also be used.</li>
		<li>Pipet the corresponding volume of cells in the chosen live cell imaging support, and place cells back in the incubator until the day after.</li>
	</ol>
	</li>
	<li>DAY 2. Proceed with transfection. Follow the guidelines of the preferred transient transfection method(s) to obtain an optimal transfection efficiency (~50/80%). No specific transfection method is required. Note that the transfection efficiency may vary according to the cell line used. Incubate for 48 h. 
	NOTE: Produce stable clones containing each of the three vectors to bypass the need of transient transfections. At this stage, two types of controls should be planned. First, a &#8220;donor-only&#8221; control is required to verify that the presence of full-length AURKA does not perturb the lifetime of mTurquoise2 per se. Second, a biosensor carrying a kinase-dead mutation should be used as a negative control where FRET is abolished or significantly lowered. Alternatively to a kinase-dead mutant, a chemical inhibitor of AURKA activation as the ATP analog MLN8237 can be used as a negative control.
	<ol>
		<li>Plan ahead three transfection conditions, each of them in an independent well: 
		The &#8220;donor-only&#8221; vector (e.g., AURKA-mTurquoise2) 
		The &#8220;biosensor&#8221; (e.g., superYFP-AURKA-mTurquoise2) 
		A kinase-dead/&#8221;K162M&#8221; biosensor (e.g., superYFP-AURKA K162M-mTurquoise2) or alternatively, an inhibitor of AURKA activation (e.g., MLN8237)</li>
		<li>Carry out three conditions for each independent donor/acceptor pair to compare.</li>
		<li>Consider doubling the number of transfected wells if comparing unsynchronized and G2/M-synchronized cells (see step 2.6).</li>
	</ol>
	</li>
	<li>DAY 3. Synchronize cells in G2/M. Add 100 ng/mL nocodazole dissolved in DMSO to each transfected well avoiding light exposure and incubate for 16 h (preferably overnight). If comparing unsynchronized and G2/M-synchronized cells, treat each transfection condition with nocodazole or with an equal volume of DMSO. For a better synchronization efficiency, prepare single-use aliquots of nocodazole in DMSO, store them at -20 &#176;C and discard them after use. 
	NOTE: Cell synchronization efficiency can vary among cell lines. The optimal concentration of nocodazole and its incubation time should be experimentally determined by flow cytometry approaches prior to FRET/FLIM experiments. For statistically relevant FRET/FLIM analyses, we recommend a synchronization efficiency in G2/M of at least 50% of the overall cell population.</li>
	<li>DAY 4. Nocodazole washout and FRET/FLIM imaging on mitotic cells
	<ol>
		<li>Remove the culture medium with a pipette and replace it with pre-warmed, sterile PBS. Avoid light exposure if possible. Gently rock the plate.</li>
		<li>Repeat the washing procedure, always avoiding light exposure.</li>
		<li>Remove the second PBS washing and replace it with pre-warmed, sterile Leibovitz L-15 medium, supplemented with 20% Fetal Bovine Serum (FBS) and 1% Penicillin-Streptomycin (from here on, imaging media). 
		NOTE: Imaging media should be purchased without pH indicators (e.g., phenol red) and medium components as riboflavin. These substances are a source of autofluorescence that could perturb lifetime values.</li>
		<li>Proceed with FRET/FLIM imaging. Minimize rapid changes in temperature and proceed to the imaging step (step 3) as fast as possible. Consider protecting the sample from light while transporting it to the microscope setup (i.e., by wrapping it in an aluminum foil or placing it in a box).&#160;</li>
	</ol>
	</li>
</ol>
3. FRET/FLIM acquisitions
NOTE: FRET/FLIM acquisitions in this protocol were performed on a custom-built setup, described in35 and equipped with a control solution as in15,17 (Figure 2). The setup is now commercialized by Inscoper and it is made of a spinning-disk microscope with a white laser for pulsed excitation, and a high-rate time-gated intensifier in front of the camera. Temporal gates of 2 ns in a time window of 10 ns are sequentially used to obtain a stack of five time-gated images. These images are then used to calculate the pixel-by-pixel mean fluorescence lifetime according to the following equation: &#964; = &#931;&#916;ti&#160;&#8226;&#160;&#921;i/&#931;&#921;i, where &#916;ti&#160;corresponds to the delay time of the of the ith gate while I indicates the pixel-by-pixel time-gated intensity image35,36. This method ensures rapid FLIM measurements: no fitting or binning steps are required, and lifetime can be calculated in an online mode, with minimal photon budget. The system also presents a user-friendly software interface. However, the same experiment can be performed under any other commercial microscope setup equipped for FLIM measurements.
<ol>
	<li>To ensure an optimal release of cells from the G2/M block into mitosis, perform experiments at 37 &#176;C. If possible, perform FRET/FLIM experiments with microscope setups equipped with a thermostatic chamber.</li>
	<li>Turn on the thermostatic chamber of the microscope at least 30 min to 1 h before the experiment.</li>
	<li>Switch on the laser, the camera, the microscope setup and the imaging software (Figure 2).</li>
	<li>Select the appropriate excitation and emission wavelengths for the donor fluorophore. Convenient wavelengths options are: &#955;ex 440/10 nm and &#955;em 483/35 nm for mTurquoise2 (Figure 3A); &#955;ex 488/10 nm and &#955;em 525/50 nm for GFP) (Figure 3B).</li>
	<li>Set the exposure time, generally between 30 and 100 ms (Figure 3). Beware that excessive laser power may result in induced phototoxic effects as photobleaching, which could in turn modify the fluorescence lifetime37. On the setup, validate the absence of photobleaching events by monitoring the fluorescence intensity of the first gate during time-lapse acquisitions. If variations in the fluorescence intensity are observable, discard the acquisition and adjust laser power. 
	NOTE: In the setup here, select an exposure time allowing at least 3000 gray levels in the first gate; otherwise the software will not calculate donor lifetime. This gray level value corresponds to the minimal photon budget necessary to obtain relevant lifetime values.</li>
	<li>Before launching FRET/FLIM acquisitions, ensure that cells have entered mitosis&#160;by waiting until the appearance of the bipolar spindle (~20/30 min in U2OS cells). Since mitotic AURKA localizes mainly at this structure, verify mitotic progression by screening the formation of the spindle in cells directly under the microscope, with an external light source (Figure 1). Note that the time required for mitotic progression might vary according to the cell line used.</li>
	<li>If treatment with MLN8237 is planned, place the cells under the microscope and allow them to reach metaphase (approx. 20 min after nocodazole washout). Add 250 nM MLN8237 dissolved in DMSO both to cells expressing the donor-only construct and to cells expressing the biosensor.
	<ol>
		<li>Control this condition on cells transfected as above and incubate with an equal volume of DMSO. For a better AURKA inhibition, prepare single-use aliquots of MLN8237 in DMSO, store them at -80 &#176;C. Thaw them by placing the aliquots on ice, and discard them after use.</li>
		<li>Incubate for 10 min. After this period, the mitotic spindle will shrink and only a single, intense dot is left. A similar phenotype is observed when K162M mutants are used.</li>
	</ol>
	</li>
	<li>For a better resolution of the mitotic spindle, use at least a 63x objective (Figure 3).</li>
	<li>Once found a cell in metaphase (see Figure 4 as an example of a cell in metaphase), adjust xyz coordinates to place it at the center of the field of view.</li>
	<li>For faster images, select one single z plane. Choose the plane where the mitotic spindle is more visible or intense.</li>
	<li>Start the recording. The acquisition time may vary according to the FLIM setup used (from few sec&#160;to min). The majority of the commercial setups available on the market will elaborate both the fluorescence micrograph and the pixel-by-pixel lifetime map. Save both images.</li>
	<li>Acquire at least 10 independent images from each transfection and/or treatment condition.</li>
</ol>
4. Calculation of &#916;Lifetime and comparison of FLIM values among donor/acceptor pairs
<ol>
	<li>Extract lifetime values from the whole pixel-by-pixel lifetime map (i.e., the entire mitotic spindle), or select regions of interest (ROIs) corresponding to specific subregions. 
	NOTE: According to the FRET/FLIM setup used, lifetime calculations may be performed directly on the acquisition software, or extracted with generic image processing solutions (e.g., Fiji/ImageJ: https://fiji.sc/). Software directly calculating lifetime values (also known as online mode) offer a more user-friendly solution, which is suitable for beginners and for microscopy users not fully familiar with FRET/FLIM. On the contrary, the extraction of lifetime values after acquisition often requires a fitting procedure. This option is less accessible to beginners, as some previous knowledge on mathematical models of fitting is necessary.</li>
	<li>Once visualized or extracted, calculate the mean lifetime of the cells expressing the &#8220;donor-only&#8221; vector (e.g., AURKA-mTurquoise2), hereby mean donor lifetime.</li>
	<li>Subtract each independent lifetime value calculated in step 4.1 from the mean donor lifetime. Repeating this step for all cells in all conditions analyzed will give the &#916;Lifetime for every condition.</li>
	<li>Compare &#916;Lifetime values for the &#8220;donor-only&#8221;, the &#8220;biosensor&#8221; and the &#8220;K162M&#8221;, or the DMSO and the MLN8237 conditions. 
	NOTE: For the &#8220;donor-only&#8221; condition, &#916;Lifetime should result in values close to zero and corresponding to the experimental fluctuations of lifetime values. For the &#8220;biosensor&#8221; condition, &#916;Lifetime values should yield the net difference between the two constructs (see Figure 4 for an illustrated example).</li>
	<li>Compare &#916;Lifetime values among different donor/acceptor pairs.
	<ol>
		<li>Compare the &#8220;biosensor&#8221; conditions: do they show similar &#916;Lifetime?</li>
		<li>Do the &#8220;K162M&#8221; or the MLN8237 conditions show similar &#916;Lifetime among them? Is their &#916;Lifetime similar to the &#8220;donor-only&#8221; condition?</li>
	</ol>
	</li>
</ol>

G.B. performed the experiments, wrote and reviewed the manuscript, and provided funding, M.T. reviewed the manuscript and provided support. M.T. is a scientific advisor and shareholder of the Inscoper company (France), which produces the solutions for rapid FLIM measurements shown in this manuscript. Inscoper partially supported the Open Access publication of the manuscript. Inscoper was not involved in experimental design, data handling, nor in the writing of the manuscript.

Genetically-encoded FRET biosensors are reliable tools to measure the activation of single proteins or of entire signaling pathways41. Particularly, the AURKA FRET biosensor constitutes a preferential way to explore the activation of the kinase in time and space. However, some elements deserve special attention when designing or optimizing a FRET biosensor, not only in general terms but more specifically for AURKA.
First, the nature and the relative position of the donor/acceptor FRET pair can be adapted for specific functions of this kinase. AURKA is greatly enriched at the mitotic spindle during mitosis, but it is present throughout the cell cycle and at different subcellular locations (e.g., centrosomes, the nucleus, and mitochondria)1,2. If the biosensor is to be used in specific compartments like mitochondria, which can reach acidic pH, the choice of a pH-insensitive donor-acceptor FRET pair as mTurquoise2/shadowG should be made. Moreover, placing the FRET donor at the C-terminus could allow a better visualization of the biosensor at this subcellular compartment, and potentially even optimize FRET detection given that AURKA N-terminus was shown to partially cleave off at mitochondria16,42.
Second, a yet unexplored way of optimizing the AURKA FRET biosensor would require a more careful design of linkers between full-length AURKA and the donor/acceptor pair. Not only the distance between the fluorescent pair, but also the properties of the linker itself were shown to be key factors to improve FRET efficiency43,44,45,46. In this light, increasing the rigidity or the flexibility of the linker could either be detrimental to FRET efficiency, or further improve it.
Third, it is known that the overexpression of AURKA induces mitotic spindle abnormalities in a significant proportion of cells2. It would be interesting to compare &#916;Lifetime obtained by expressing the same FRET construct under a strong promoter like cytomegalovirus (CMV) &#8211; one of the most common promoters found in mammalian expression vectors &#8211; or under the AURKA minimal promoter sequence (CTTCCGG)14,47. This promoter was previously shown to rescue monopolar or multipolar spindles arising after the knock-down of the kinase, and its use did not induce cell cycle perturbations per se14,47. Although FLIM is insensitive to protein expression levels and relative concentrations in the cell11, benefiting from a thorough comparison of the two promoters on the same biosensor setup would broaden the understanding of the pool of activated AURKA at any given location. In addition, it would provide novel insights on how AURKA activation may change upon overexpression, which is relevant for epithelial and hematologic cancer paradigms.
Last, the downstream FRET application should also be taken into account. A future perspective in the field of AURKA would be to cumulate the kinase conformational biosensor with a substrate-based biosensor. Analyzing the FRET behavior of two biosensors simultaneously &#8211; a process known as multiplex FRET &#8211; requires a dark acceptor on the first biosensor to avoid spectral bleed through in the second donor channel. In the context of AURKA, this would open up the exciting new perspective of detecting the activation of the kinase with the first biosensor, and its enzymatic activity towards a given substrate with the second one. Recent developments in multiplexing now allow to cumulate up to three biosensors at a time48. Applying a similar method in the context of AURKA could represent a very promising strategy not only to test the activation-activity interplay of the kinase, but also to explore AURKA signaling cascades with unprecedented spatiotemporal resolution.
In conclusion, FRET/FLIM is a convenient way to deepen the knowledge on protein activity. On one hand, it allows to visualize the localization of a given protein in live cells, thanks to at least one fluorescent moiety. On the other hand, it can unravel protein conformational changes, which could be informative on protein activation and/or activity. Therefore, FRET/FLIM and conformational FRET biosensors have the potential of becoming widespread methods to follow signaling pathways in live cells, and with exquisite spatiotemporal resolution.

Aurora kinase A/AURKA is a multifunctional serine/threonine kinase, active throughout the cell cycle and at different subcellular compartments1. Understanding its broad spatiotemporal activation is particularly important in cancer, as AURKA is often overexpressed in epithelial and hematological malignancies, with patients showing poor responsiveness to the currently available therapies2.
Structural studies revealed that AURKA undergoes two steps to convert from an inactive to an active kinase. First, the autophosphorylation of Thr288 changes the conformation of the kinetic pocket of the kinase and activates it3,4,5,6. This step increases the catalytic activity of AURKA in human cells and in Xenopus laevis3,6,7, priming the kinase for full activity. Once activated, the interaction of AURKA with the targeting protein for Xklp2 (TPX2) induces a second conformational change5. This further modification allows AURKA to reach full enzymatic activity towards its substrates in the cell5,8,9,10.
For nearly two decades, insights on the activation and activity of AURKA were obtained mainly through a combination of biochemical approaches. These include the detection of phosphorylated Thr288 in cells or in vivo as a hallmark of AURKA activation, crystallographic analyses, and in vitro or in cellulo kinase assays to probe the activity of AURKA1. However, the spatiotemporal resolution of these approaches is poor or absent, and novel solutions were needed to broaden the knowledge of the dynamics of these two events.
The development of fluorescent probes in the last few years facilitated the monitoring of AURKA in live cells, allowing the following of its activation with greater spatiotemporal resolution. The most specific sensors for AURKA developed so far rely on the FRET principle (F&#246;rster&#8217;s Resonance Energy Transfer)11 to discriminate between inactive and active AURKA. The first sensor developed was a substrate-based biosensor of AURKA kinase activity. Substrate-based biosensors are constituted by a short aminoacidic sequence targeted by a given kinase for phosphorylation, and inserted within a donor/acceptor FRET pair and a binding domain recognizing the phosphorylated residue, which helps the folding of the biosensor for an efficient FRET process12. In the case of AURKA, a 14-aminoacid fragment of KIF2C targeted by phosphorylation was inserted between a CFP-YFP donor/acceptor pair13. However, this sensor has some major drawbacks. First, the KIF2C sequence used in this probe can be targeted both by AURKA and the closely-related kinase AURKB, thereby decreasing the specificity of this biosensor. Second, the sensor relies on the endogenous kinase for phosphorylation. Therefore, FRET efficiency can be undetectable or not significant if the quantities of the kinase are limiting (e.g., in subcellular compartments or cell cycle phases). To overcome these limitations, a new class of AURKA sensor was created known as &#8220;conformational sensors&#8221;. In these probes, the full-length sequence of AURKA was inserted within a donor fluorophore at the N-terminus, and an acceptor fluorophore at the C-terminus. Inactive AURKA presents an &#8220;open&#8221; conformation, which brings the N- and C-termini of the kinase away from each other. With such distance between the two termini (&#62; 10 nm), the donor/acceptor pair are in a non-permissive configuration for FRET. On the contrary, autophosphorylated AURKA adopts a &#8220;closed&#8221; conformation, with the two protein termini and the two fluorophores in proximity. This was shown to allow FRET between the donor and the acceptor, which can be measured using the variations in the donor lifetime14,15. Such probes present several advantages. First, they are genetically-encoded, and they can be used to replace the endogenous kinase in the cell. Second, they rescue the phenotypes induced by the knockdown of AURKA, indicating that they are functional in the cell. Third, they allow to follow the activation of the kinase at different subcellular compartments and throughout the cell cycle. The probes detected the activation of AURKA at locations where the kinase is known to be activated (i.e. centrosomes and the mitotic spindle), and also participated in discovering the activation of AURKA at the mitochondria16. Last, these sensors allowed high-content screenings based on FRET/FLIM, where the conformational changes of AURKA were used to identify novel pharmacological inhibitors17.
In the present work, we describe a procedure to visualize AURKA activation in cultured cells. First, we will make an insight on potential fluorophore pairs for FRET. The choice of the most suitable donor/acceptor pair will be made according to the available microscope setup, or a particular downstream application as multiplex FRET18,19. Then, we propose a pipeline to explore the behavior of the biosensor(s) chosen in a rapid FRET/FLIM microscope setup. This pipeline will extend from cell culture and synchronization procedures to FLIM acquisition and data analysis. Last, we will discuss the potential advantages of this protocol, as an analogous strategy for biosensor design could be applied to other kinases, and it may also be used with other FRET-based imaging systems.

<table>
	<tbody>
		<tr>
			<td>Alisertib (MLN8237)</td>
			<td>SelleckChem</td>
			<td>S1133</td>
			<td>Use at a 250 nM final dilution</td>
		</tr>
		<tr>
			<td>Dulbecco&#39;s Modified Eagle Medium (DMEM)</td>
			<td>ThermoFischer Scientific 
			Brand: Gibco</td>
			<td>41966052</td>
			<td>High glucose + L-glutamine + Sodium pyruvate</td>
		</tr>
		<tr>
			<td>Fetal Bovine Serum (FBS)</td>
			<td>ThermoFischer Scientific 
			Brand: Gibco</td>
			<td>10270106</td>
			<td></td>
		</tr>
		<tr>
			<td>L15</td>
			<td>ThermoFischer Scientific 
			Brand: Gibco</td>
			<td>21083027</td>
			<td>Leibovitz&#39;s L15 medium + L-glutamine, no Phenol red</td>
		</tr>
		<tr>
			<td>LabTek</td>
			<td>Nunc</td>
			<td>2515380</td>
			<td></td>
		</tr>
		<tr>
			<td>Nocodazole</td>
			<td>Merck 
			Brand: Sigma-Aldrich</td>
			<td>M1404</td>
			<td>Use at a 100 ng/mL final dilution</td>
		</tr>
		<tr>
			<td>Penicillin/Streptomycin</td>
			<td>ThermoFischer Scientific 
			Brand: Gibco</td>
			<td>15140122</td>
			<td>Penicillin-Streptomycin 10,000 U/mL (100x)</td>
		</tr>
		<tr>
			<td>Phosphate Buffer Saline (PBS)</td>
			<td>ThermoFischer Scientific 
			Brand: Gibco</td>
			<td>14190169</td>
			<td>DPBS, no calcium, no magnesium</td>
		</tr>
		<tr>
			<td>Trypsin/EDTA</td>
			<td>ThermoFischer Scientific 
			Brand: Gibco</td>
			<td>25300096</td>
			<td>Trypsin-EDTA 0.05%, Phenol Red (1x)</td>
		</tr>
	</tbody>
</table>

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.

We followed the procedure described above to record the autophosphorylation of AURKA on Thr288 using two biosensors with different spectral properties. We compared the initial GFP-AURKa-mCherry probe14 with two biosensors with different spectral properties. These two probes rely on the fluorescent donor mTurquoise2 and on a non-fluorescent acceptor (ShadowG) in one case, or a yellow acceptor (superYFP) in a second case. We then inserted the full-length sequence of AURKA within each donor/acceptor pair. To have a negative control for AURKA activation, two strategies can be pursued. First, the use a small ATP-analog (MLN8237) interferes with the binding of ATP in the kinetic pocket of the kinase and prevents its activation38. Second, the mutation of Lys162 into Met (K162M), creates a kinase-dead version of each biosensor incapable of activating14,15,39. This mutation induces the disruption of a salt bridge normally established between Lys162 and Glu181, which results in a stable opening of the kinetic pocket of the kinase and triggers its overall inactivation40. As a negative control for FRET, we used an acceptor-devoid construct (GFP-AURKA or AURKA-mTurquoise2).
After synchronizing cells in G2/M and releasing them into mitosis, we measured the lifetime of all the transfected constructs at the mitotic spindle (Figure 4). Of note, this structure was considered as a whole, and no ROIs within the spindle were analyzed. We then calculated &#916;Lifetime for all conditions. As expected, the lifetime of GFP-AURKA or AURKA-mTurquoise2 (the &#8220;donor-only&#8221; conditions) was close to 0, indicating that the values measured for these constructs fluctuated around the mean value (Figure 4A,4B). Conversely, the &#916;Lifetime values for GFP-AURKA-mCherry were statistically different from the donor-only condition, with &#916;Lifetime increasing of ~130 ps (Figure 4A). Similar observations were made for shadowG-AURKA-mTurquoise2 and for superYFP-AURKA-mTurquoise2, with &#916;Lifetime increasing of ~150 and ~220 ps from the donor-only condition, respectively (Figure 4B,4C). These data can be easily visualized in single cells with a pseudocolor Lookup Table (LUT). In this case, values of &#916;Lifetime around 0 are pseudocolored yellow, while more significant differences are pseudocolored red/purple. Indeed, the pixel-by-pixel LUT was closer to yellow in cells expressing the donor-only constructs, while it was more in the red/purple spectrum in cells expressing either biosensor (Figure 4A,4B). This was also observed when the GFP-AURKA-mCherry biosensor was treated with the pharmacological inhibitor MLN8237.
We then analyzed the &#916;Lifetime of kinase-dead biosensors. These constructs showed intermediate &#916;Lifetime values: &#916;Lifetime was significantly higher when compared to the donor-only condition (Figure 4B,4C), but it was also significantly lower than their normal counterparts (Figure 4B,4D). The comparisons with cells treated with MLN8237 or expressing kinase-dead biosensors are necessary to estimate whether &#916;Lifetime variations for each donor/acceptor pair are solely linked to the activation of AURKA. In the case of GFP-AURKA-mCherry, &#916;Lifetime variations are abolished when an AURKA-specific inhibitor is used. Conversely, &#916;Lifetime variations are mostly, but not exclusively linked to AURKA activation in the case of shadowG-AURKA-mTurquoise2 and of superYFP-AURKA-mTurquoise2.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/61611/61611fig01.jpg" /> 
Figure 1: GFP (donor) and mCherry (acceptor) excitation and emission spectra. 
Spectra were obtained and adapted from the FP base website (https://www.fpbase.org/), and adjusted to a 480 nm-laser excitation. <a href="https://www.jove.com/files/ftp_upload/61611/61611fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/61611/61611fig02.jpg" /> 
Figure 2: Image of the experimental workspace. 
(1) The control solution; (2) white laser source; (3) CCD camera; (4) microscope setup; (5) external light source/lamp for ocular screening of the sample. <a href="https://www.jove.com/files/ftp_upload/61611/61611fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/61611/61611fig03.jpg" /> 
Figure 3: Representative images of the software for FLIM acquisition. 
(A, B) (1) excitation and emission parameters for the donor (CFP in A, or GFP in B); (2) exposure time; (3) selection of the objective. <a href="https://www.jove.com/files/ftp_upload/61611/61611fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/61611/61611fig04v3.jpg" /> 
Figure 4: Representative images of AURKA FRET biosensors and their negative controls. 
(A) (Micrographs) Fluorescence (green channel) and corresponding pixel-by-pixel &#916;Lifetime (donor only &#8211; biosensor) of U2OS cells expressing GFP-AURKA or GFP-AURKA-mCherry, synchronized at G2/M, released until the bipolar spindle is visible and then treated with DMSO or with MLN8237. &#916;Lifetime is illustrated with a pseudocolor scale (&#8220;Fire&#8221; lookup table). (Graph) Corresponding quantification and two-way ANOVA analysis for the indicated conditions. (B) (Micrographs) Fluorescence (cyan channel) and corresponding pixel-by-pixel &#916;Lifetime (donor only &#8211; biosensor) of U2OS cells expressing shadowG-AURKA-mTurquoise2 (upper panel) or superYFP-AURKA-mTurquoise2 (lower panel), synchronized at G2/M and released until the bipolar spindle is visible. &#916;Lifetime is illustrated with a pseudocolor scale (&#8220;Fire&#8221; lookup table). (Graph) Corresponding quantification and one-way ANOVA analysis of conditions represented in the above micrographs. (C) (Micrographs) Images of AURKA-mTurquoise2 (upper panel), shadowG-AURKA K162M-mTurquoise2 (middle panel) and superYFP-AURKA K162M-mTurquoise2 acquired and represented as in the micrographs. (Graph) Two-way ANOVA analysis for the indicated transfection conditions. The bar in boxplots represents the median; whiskers extend from the min to the max. n = 10 cells per condition of one representative experiment (of three). Individual values are represented as dots. Scale bar: 10 &#181;m. *P &#60; 0.05, **P &#60; 0.01, ***P &#60; 0.001 against each indicated condition in (A) the &#8220;AURKA-mTurquoise2&#8221; condition in (B), and against each indicated condition in (C). NS: not significant. <a href="https://www.jove.com/files/ftp_upload/61611/61611fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Real-Time Monitoring of Aurora kinase A Activation using Conformational FRET Biosensors in Live Cells at JoVE.com

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

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 ...

real-time-monitoring-aurora-kinase-activation-using-conformational

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JoVE Journal

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3.0K Views.  Univ Rennes, CNRS, IGDR (Genetics and Development Institute of Rennes), UMR 6290, F-35000 Rennes, France. 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.

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

Combining QD-FRET and Microfluidics to Monitor DNA Nanocomplex Self-Assembly in Real-Time

Advances in genomics continue to fuel the development of therapeutics that can target pathogenesis at the cellular and molecular level. Typically functional inside the cell, nucleic acid-based therapeutics require an efficient intracellular delivery system. One widely adopted approach is to complex DNA with a gene carrier to form nanocomplexes via electrostatic self-assembly, facilitating cellular uptake of DNA while protecting it against degradation. The challenge lies in the rational design of efficient gene carriers, since premature dissociation or overly stable binding would be detrimental to the cellular uptake and therapeutic efficacy. Nanocomplexes synthesized by bulk mixing showed a diverse range of intracellular unpacking and trafficking behavior, which was attributed to the heterogeneity in size and stability of nanocomplexes. Such heterogeneity hinders the accurate assessment of the self-assembly kinetics and adds to the difficulty in correlating their physical properties to transfection efficiencies or bioactivities. We present a novel convergence of nanophotonics (i.e. QD-FRET) and microfluidics to characterize the real-time kinetics of the nanocomplex self-assembly under laminar flow. QD-FRET provides a highly sensitive indication of the onset of molecular interactions and quantitative measure throughout the synthesis process, whereas microfluidics offers a well-controlled microenvironment to spatially analyze the process with high temporal resolution (~milliseconds). For the model system of polymeric nanocomplexes, two distinct stages in the self-assembly process were captured by this analytic platform. The kinetic aspect of the self-assembly process obtained at the microscale would be particularly valuable for microreactor-based reactions which are relevant to many micro- and nano-scale applications. Further, nanocomplexes may be customized through proper design of microfludic devices, and the resulting QD-FRET polymeric DNA nanocomplexes could be readily applied for establishing structure-function relationships. 

We present a novel and powerful integration of nanophotonics (QD-FRET) and microfluidics to investigate the formation of polyelectrolyte polyplexes, which is expected to provide better control and synthesis of uniform and customizable polyplexes for future nucleic acid-based therapeutics.

Advances in genomics continue to fuel the development of therapeutics that can target pathogenesis at the cellular and molecular level. Typically ...

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 ...

Real-time Monitoring of Ligand-receptor Interactions with Fluorescence Resonance Energy Transfer

FRET is a process whereby energy is non-radiatively transferred from an excited donor molecule to a ground-state acceptor molecule through long-range dipole-dipole interactions1. In the present sensing assay, we utilize an interesting property of PDA: blue-shift in the UV-Vis electronic absorption spectrum of PDA (Figure 1) after an analyte interacts with receptors attached to PDA2,3,4,7. This shift in the PDA absorption spectrum provides changes in the spectral overlap (J) between PDA (acceptor) and rhodamine (donor) that leads to changes in the FRET efficiency. Thus, the interactions between analyte (ligand) and receptors are detected through FRET between donor fluorophores and PDA. In particular, we show the sensing of a model protein molecule streptavidin. We also demonstrate the covalent-binding of bovine serum albumin (BSA) to the liposome surface with FRET mechanism. These interactions between the bilayer liposomes and protein molecules can be sensed in real-time. The proposed method is a general method for sensing small chemical and large biochemical molecules. Since fluorescence is intrinsically more sensitive than colorimetry, the detection limit of the assay can be in sub-nanomolar range or lower8. Further, PDA can act as a universal acceptor in FRET, which means that multiple sensors can be developed with PDA (acceptor) functionalized with donors and different receptors attached on the surface of PDA liposomes.

We demonstrate FRET between conjugated polymer polydiacetylene (PDA) and fluorophore attached to the surface of PDA liposomes for the sensing of biomolecules. PDA liposomes also contained receptor molecules on their surfaces for biomolecules to be used as probes. Ligand-receptor interactions lead to changes in the FRET efficiency between the fluorophore and PDA which is the basis of the sensing mechanism.

FRET is a process  whereby energy is non-radiatively transferred from an excited donor molecule to  a ground-state acceptor molecule through long-range ...

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 ...

Autonomously Bioluminescent Mammalian Cells for Continuous and Real-time Monitoring of Cytotoxicity

Mammalian cell-based in vitro assays have been widely employed as alternatives to animal testing for toxicological studies but have been limited due to the high monetary and time costs of parallel sample preparation that are necessitated due to the destructive nature of firefly luciferase-based screening methods. This video describes the utilization of autonomously bioluminescent mammalian cells, which do not require the destructive addition of a luciferin substrate, as an inexpensive and facile method for monitoring the cytotoxic effects of a compound of interest. Mammalian cells stably expressing the full bacterial bioluminescence (luxCDABEfrp) gene cassette autonomously produce an optical signal that peaks at 490 nm without the addition of an expensive and possibly interfering luciferin substrate, excitation by an external energy source, or destruction of the sample that is traditionally performed during optical imaging procedures. This independence from external stimulation places the burden for maintaining the bioluminescent reaction solely on the cell, meaning that the resultant signal is only detected during active metabolism. This characteristic makes the lux-expressing cell line an excellent candidate for use as a biosentinel against cytotoxic effects because changes in bioluminescent production are indicative of adverse effects on cellular growth and metabolism. Similarly, the autonomous nature and lack of required sample destruction permits repeated imaging of the same sample in real-time throughout the period of toxicant exposure and can be performed across multiple samples using existing imaging equipment in an automated fashion.

Mammalian cells expressing the bacterial bioluminescence gene cassette (lux) produce light autonomously. The resulting bioluminescent dynamics upon chemical exposure have been demonstrated to reflect the treatment effects on cellular growth and metabolism, making these cells an inexpensive, continuous, real-time toxicity screening tool that can easily be adapted for high-throughput automation.

Mammalian  cell-based in vitro assays have been  widely employed as alternatives to animal testing for toxicological studies but  have been limited due to ...

Real-time Imaging of Single Engineered RNA Transcripts in Living Cells Using Ratiometric Bimolecular Beacons

The growing realization that both the temporal and spatial regulation of gene expression can have important consequences on cell function has led to the development of diverse techniques to visualize individual RNA transcripts in single living cells. One promising technique that has recently been described utilizes an oligonucleotide-based optical probe, ratiometric bimolecular beacon (RBMB), to detect RNA transcripts that were engineered to contain at least four tandem repeats of the RBMB target sequence in the 3&#8217;-untranslated region. RBMBs are specifically designed to emit a bright fluorescent signal upon hybridization to complementary RNA, but otherwise remain quenched. The use of a synthetic probe in this approach allows photostable, red-shifted, and highly emissive organic dyes to be used for imaging. Binding of multiple RBMBs to the engineered RNA transcripts results in discrete fluorescence spots when viewed under a wide-field fluorescent microscope. Consequently, the movement of individual RNA transcripts can be readily visualized in real-time by taking a time series of fluorescent images. Here we describe the preparation and purification of RBMBs, delivery into cells by microporation and live-cell imaging of single RNA transcripts.

Ratiometric bimolecular beacons (RBMBs) can be used to image single engineered RNA transcripts in living cells. Here, we describe the preparation and purification of RBMBs, delivery of RBMBs into cells by microporation and fluorescent imaging of single RNA transcripts in real-time.

The growing realization that both the temporal and spatial regulation of gene expression can have important consequences on cell function has led to the ...

Identification of Kinase-substrate Pairs Using High Throughput Screening

We have developed a screening platform to identify dedicated human protein kinases for phosphorylated substrates which can be used to elucidate novel signal transduction pathways. Our approach features the use of a library of purified GST-tagged human protein kinases and a recombinant protein substrate of interest. We have used this technology to identify MAP/microtubule affinity-regulating kinase 2 (MARK2) as the kinase for a glucose-regulated site on CREB-Regulated Transcriptional Coactivator 2 (CRTC2), a protein required for beta cell proliferation, as well as the Axl family of tyrosine kinases as regulators of cell metastasis by phosphorylation of the adaptor protein ELMO. We describe this technology and discuss how it can help to establish a comprehensive map of how cells respond to environmental stimuli.

Protein phosphorylation is a central feature of how cells interpret and respond to information in their extracellular milieu. Here, we present a high throughput screening protocol using kinases purified from mammalian cells to rapidly identify kinases that phosphorylate a substrate(s) of interest.


We have developed a screening platform to identify dedicated human protein kinases for phosphorylated substrates which can be used to elucidate novel ...

Detection of Intracellular Gene Expression in Live Cells of Murine, Human and Porcine Origin Using Fluorescence-labeled Nanoparticles

The reprogramming of somatic cells to induced pluripotent stem cells (iPS) has successfully been performed in different mammalian species including mouse, rat, human, pig and others. The verification of iPS clones mainly relies on the detection of the endogenous expression of different pluripotency genes. These genes mostly represent transcription factors which are located in the cell nucleus. Traditionally, the proof of their endogenous expression is supplied by immunohistochemical staining after fixation of the cells. This approach requires replicate cultures of each clone at this early stage to preserve validated clones for further experiments. The present protocol describes an approach with gene-specific nanoparticles which allows the evaluation of intracellular gene expression directly in live cells by fluorescence. The nanoparticles consist of a central gold particle coupled to a capture strand carrying a sequence complementary to the target mRNA as well as a quenched reporter strand. These nanoparticles are actively endocytosed and the target mRNA displaces the reporter strand which then start to fluoresce. Therefore, specific target gene expression can be detected directly under the microscope. In addition, the emitted fluorescence allows the identification, isolation and enrichment of cells expressing a specific gene by flow cytometry. This method can be applied directly to live cells in culture without any manipulation of the target cells.

This manuscript describes a novel technique which allows the detection of intracellular gene expression after endocytosis of fluorescence-labeled nanoparticles directly in live cells. The method does not require manipulation of the cells and is not restricted with respect to the target gene or species.

The reprogramming of somatic cells to induced pluripotent stem cells (iPS) has successfully been performed in different mammalian species including mouse, ...

G Protein-selective GPCR Conformations Measured Using FRET Sensors in a Live Cell Suspension Fluorometer Assay

F&#1255;rster resonance energy transfer (FRET)-based studies have become increasingly common in the investigation of GPCR signaling. Our research group developed an intra-molecular FRET sensor to detect the interaction between G&#945; subunits and GPCRs in live cells following agonist stimulation. Here, we detail the protocol for detecting changes in FRET between the &#946;2-adrenergic receptor and the G&#945;s C-terminus peptide upon treatment with 100 &#181;M isoproterenol hydrochloride as previously characterized1. Our FRET sensor is a single polypeptide consisting serially of a full-length GPCR, a FRET acceptor fluorophore (mCitrine), an ER/K SPASM (systematic protein affinity strength modulation) linker, a FRET donor fluorophore (mCerulean), and a G&#945; C-terminal peptide. This protocol will detail cell preparation, transfection conditions, equipment setup, assay execution, and data analysis. This experimental design detects small changes in FRET indicative of protein-protein interactions, and can also be used to compare the strength of interaction across ligands and GPCR-G protein pairings. To enhance the signal-to-noise in our measurements, this protocol requires heightened precision in all steps, and is presented here to enable reproducible execution.

Simple methods to detect the selective activation of G proteins by G protein-coupled receptors remain an outstanding challenge in cell signaling. Here, F&#1255;rster resonance energy transfer (FRET) biosensors have been developed by pairwise tethering a GPCR to G protein peptides to probe conformational changes at controlled concentrations in live cells.

F&#1255;rster resonance energy transfer (FRET)-based studies have become increasingly common in the investigation of GPCR signaling. Our research group ...

A Graphical User Interface for Software-assisted Tracking of Protein Concentration in Dynamic Cellular Protrusions

Filopodia are dynamic, finger-like cellular protrusions associated with migration and cell-cell communication. In order to better understand the complex signaling mechanisms underlying filopodial initiation, elongation and subsequent stabilization or retraction, it is crucial to determine the spatio-temporal protein activity in these dynamic structures. To analyze protein function in filopodia, we recently developed a semi-automated tracking algorithm that adapts to filopodial shape-changes, thus allowing parallel analysis of protrusion dynamics and relative protein concentration along the whole filopodial length. Here, we present a detailed step-by-step protocol for optimized cell handling, image acquisition and software analysis. We further provide instructions for the use of optional features during image analysis and data representation, as well as troubleshooting guidelines for all critical steps along the way. Finally, we also include a comparison of the described image analysis software with other programs available for filopodia quantification. Together, the presented protocol provides a framework for accurate analysis of protein dynamics in filopodial protrusions using image analysis software.

We present a software solution for semi-automated tracking of relative protein concentration along the length of dynamic cellular protrusions.

Filopodia are dynamic, finger-like cellular protrusions associated with migration and cell-cell communication. In order to better understand the complex ...