The authors were supported by a Russian Science Foundation grant 20-74-00133.

1. Fluorescent protein labeling
<ol>
	<li>Material preparation
	<ol>
		<li>Prepare 1 M Sodium bicarbonate buffer, pH 9.0, store it at 4 &#176;C, and use it within one week.</li>
		<li>Prepare 1.5 M hydroxylamine hydrochloride buffer, pH 8.5, immediately before use.</li>
		<li>Prepare a 10 mg/mL solution of fluorescent dye (see the Table of Materials) in dimethylsulfoxide. 
		NOTE: This solution can be stored for a month at -20 &#176;C in the dark.</li>
		<li>Prepare solutions of purified antibodies or other proteins at 1-10 mg/mL. 
		NOTE: Avoid buffers containing ammonium ions or primary amines. Replace the buffers containing Tris or glycerol with phosphate-buffered saline (PBS) by dialysis. Neither sodium azide (&#8804;3 mM) nor thimerosal (&#8804;1 mM) will significantly affect the conjugation reaction.</li>
		<li>Incubate the gel filtration medium (see the Table of Materials) for protein purification in PBS overnight at room temperature or for 2 h at 60 &#176;C. Apply the gel filtration medium onto spin columns with 0.2 &#181;m membranes.</li>
	</ol>
	</li>
	<li>Calculate the amount of reactive dye to be used for each reaction according to the concentration of protein to be labeled by using Eq (1). 
	<img alt="Equation 1" src="/files/ftp_upload/63459/63459eq1v4.jpg" /> 
	Where Vdye is the volume of the dye stock solution; Cpr, Vpr and MWpr is the concentration, volume and molar weight of the protein; MWdye is the dye molar weight; 100 is a unit conversion factor; MR is the molar ratio of dye to protein in the reaction mixture. 
	NOTE: The following MRs are recommended for IgG labeling reactions: MR = 40 if the antibody is at 1-3 mg/mL or MR = 30 if the antibody is at 4-10 mg/mL. For coagulation factors, MR = 5 is usually used.</li>
	<li>Conjugation reaction
	<ol>
		<li>In a reaction tube, mix the protein solution with a 10x lower volume of 1 M bicarbonate solution.</li>
		<li>Add the required amount of fluorescent dye (see step 1.2) with continuous stirring.</li>
		<li>Incubate the reaction mixture at room temperature for approximately 1 h, protected from light and with continuous stirring.</li>
		<li>For each 200 &#181;L of protein solution, add 5 &#181;L of 1.5 M hydroxylamine hydrochloride.</li>
		<li>Incubate the reaction mixture at room temperature for approximately 30 min, protected from light and with continuous stirring.</li>
	</ol>
	</li>
	<li>Prepare the spin column.
	<ol>
		<li>Add 500 &#181;L of gel filtration medium for protein purification to a column. Centrifuge the column for 3 min at 1,000 &#215; g.</li>
		<li>Discard the buffer from the collection tube. If the column is not full, add more gel filtration medium, and centrifuge the column for 3 min at 1,000 &#215; g. Repeat this step until the column is full.</li>
	</ol>
	</li>
	<li>Purification
	<ol>
		<li>Centrifuge the reaction mixture (from step 1.3.5) for 5 min at 17,000 &#215; g and remove the precipitate.</li>
		<li>Transfer the supernatant to the spin column with gel filtration medium. Allow the solution to absorb into the gel bed.</li>
		<li>Use an empty collection tube for the spin column and centrifuge it for 5 min at 1,000 &#215; g. After centrifugation, collect the labeled protein from the collection tube.</li>
	</ol>
	</li>
	<li>Determination of the degree of labeling
	<ol>
		<li>Correct for the contribution of the dye to the absorbance at A280 by measuring the absorbance of free dye at 280 nm (A280) and the &#955;max for the dye (Amax) (see Eq (2)). 
		<img alt="Equation 2" src="/files/ftp_upload/63459/63459eq02.jpg" />&#160; &#160; (2)</li>
		<li>Measure the absorbance of the protein-dye conjugate at 280 nm (A280) and the &#955;max for the dye (Amax) and calculate the protein concetration using Eq (3). 
		<img alt="Equation 3" src="/files/ftp_upload/63459/63459eq3v2.jpg" />&#160; &#160; (3) 
		Where &#949;M is the molar extinction coefficient of the protein at 280 nm; d is the optical path length during the measurement of the absorbance; CF is the contribution of the dye to the absorbance at A280 (step 1.6.1).</li>
		<li>Calculate the degree of labeling (DOL) using Eq (4). 
		<img alt="Equation 4" src="/files/ftp_upload/63459/63459eq4v2.jpg" />&#160; &#160; (4) 
		Where &#949;M dye is the molar extinction coefficient of the dye at &#955;max nm; d is the optical path length during the measurement of the absorbance; Cprotein is the concentration of the protein (step 1.6.2).</li>
	</ol>
	</li>
</ol>
2. Preparation of phospholipid vesicles
<ol>
	<li>Preparation and storage of the lipid mixture
	<ol>
		<li>Combine the lipids in the appropriate ratio (phosphatidylserine/phosphatidylcholine&#160;at a ratio of 20 mol% to 80 mol%).</li>
		<li>Dry the lipid mixture after lyophilization or evaporation and store it under an inert atmosphere in glass ampules.</li>
	</ol>
	</li>
	<li>Lipid film production
	<ol>
		<li>Open the ampule, and resuspend the lipid mixture in a small amount (~100 &#181;L) of chloroform. 
		NOTE: Do not use too much chloroform as it does not evaporate completely.</li>
		<li>Add DiIC16(3) in ethanol at 0.2 mol%. Transfer the lipid mixture to a round bottom flask. Spread the mixture thinly over the sides of the flask by rotating it. Dry the lipid mix for 30 min under an argon stream.</li>
	</ol>
	</li>
	<li>Hydration of the lipid mixture
	<ol>
		<li>Add a suitably warm (~55 &#176;C) aqueous buffer (HEPES 20 mM, NaCl 140 mM, pH 7.4) in a volume corresponding to the expected lipid concentration to the flask with the lipid film. Incubate the mixture with vortexing at 55 &#176;&#1057; for 30 min for complete hydration.</li>
		<li>Placing the sample tube in a freezer or warm thermostat to make the lipid suspension undergo 3-5 freeze-thaw cycles.</li>
	</ol>
	</li>
	<li>Formation of lipid vesicles by extrusion
	<ol>
		<li>Prepare the extruder according to the manufacturer&#39;s instructions. Warm up all the extruder components to the phase transition temperature of the lipid mixture.</li>
		<li>Fill one of the extruder syringes with the hydrated lipid mixture. Wait for 5-10 min for the temperature of the lipid suspension to equilibrate with the temperature of the extruder.</li>
		<li>Extrude the lipid mixture through the membrane at least 10 times. For the final extrusion, place the lipid suspension in the alternate syringe and look for a change in appearance from a slightly nebulous to a clear solution.</li>
		<li>Store the resulting mixture of lipid vesicles at 4 &#176;C, preferably in an inert atmosphere of argon or nitrogen, for 3-4 days. Do not freeze.</li>
	</ol>
	</li>
</ol>
3. Isolation of platelets from whole blood
<ol>
	<li>Collect whole blood from healthy donors in tubes containing 3.2% sodium citrate.</li>
	<li>Add prostaglandin E1 (PGE1) (1 &#181;M) and apyrase (0.1 U/mL) to the blood, followed by centrifugation at room temperature at 100 &#215; g for 8 min.</li>
	<li>After centrifugation, take the platelet-rich plasma and add sodium citrate solution (106 mM, pH 5.5) to a plasma/citrate ratio of 3:1. Centrifuge the plasma at room temperature at 400 &#215; g for 5 min.</li>
	<li>Remove the supernatant, and resuspend the pellet in 300 &#181;L of Tyrode&#39;s buffer without BSA (20 mM HEPES, 150 mM NaCl, 2.7 mM KCl, 1 mM MgCl2, 0.4 mM NaH2PO4, 2.5 mM CaCl2, 5 mM glucose, pH 7.4). Purify the platelets from plasma proteins by gel chromatography on the gel filtration medium for platelet purification (see the Table of Materials).</li>
</ol>
4. Detection of protein - lipid interaction by flow cytometry
<ol>
	<li>Kinetic binding experiments
	<ol>
		<li>Dilute phospholipid vesicles (from step 2.4.4) in Tyrode&#39;s buffer (20 mM HEPES, 150 mM NaCl, 2.7 mM KCl, 1 mM MgCl2, 0.4 mM NaH2PO4, 2.5 mM CaCl2, 5 mM glucose, 0.5% BSA, pH 7.4) to a concentration of 1 &#181;M and total volume of 250 &#181;L.</li>
		<li>Mix fluorescent-labeled coagulation factor X (fX-fd) from step 1 at a concentration of 500 nM with the phospholipid vesicles from step 4.1.1 in a 1:1 ratio (final vesicle concentration 0.5 &#181;M, fX-fd concentration is 250 nM of fX) to a total volume of 500 &#181;L.</li>
		<li>Immediately inject the 500 &#181;L of the mixed suspension (~20 min for analysis with a low flowing rate) into the flow cytometer. Use a low flow rate and ensure that the threshold for channel FL2 (ex&#1089;itation 488 nm, emission filter 585/42 nm) is as value 200. Measure the mean fluorescence in channel FL4 (ex&#1089;itation 633 nm, emission filter 660/20) for the fluorescence dye from the Table of Materials. 
		NOTE: Choose a cytometer without an autosampler. This will speed up the process of injection of the sample into the measuring cell.</li>
		<li>When saturation of binding is achieved (no significant increase in fluorescence within 5 min), rapidly dilute the sample 20-fold with Tyrode&#39;s buffer, and monitor the dissociation until baseline fluorescence is reached (complete dissociation) or until a plateau is reached (no significant decrease in fluorescence within 5 min). 
		NOTE: As a control, add 10 &#181;M EDTA and monitor complete dissociation for 5 min.</li>
	</ol>
	</li>
	<li>Equilibrium binding experiments 
	NOTE: Use the kinetic curve of binding to determine the time to reach saturation; the time for saturation for fX-fd and artificial vesicles is 20 min.&#160;
	<ol>
		<li>Incubate artificial phospholipid vesicles (5 &#181;M) for the binding assay with different concentrations of fX-fd (from 0 to 1,000 nM) in Tyrode&#39;s buffer for 20 min.</li>
		<li>Dilute each sample from step 4.2.1&#160;by 20x to a final volume of 200 &#181;L with Tyrode&#39;s buffer. Immediately analyze the diluted sample by flow cytometry within 30 s. Use settings from step 4.1.3. 
		NOTE: As a control for nonspecific binding, use similar samples with EDTA (10 &#181;M) and incubate them for 5 min.</li>
	</ol>
	</li>
</ol>
5. Analysis of flow cytometry data
<ol>
	<li>Export experiments in FSC format from cytometry data acquisition software to cytometer software for data analysis (see the Table of Materials). Choose File | Export | FCS files. Open FSC files in cytometer software for data analysis by selecting the files on the computer and dragging them to the workspace of the program.</li>
	<li>For gating of the microvesicles, identify the region of microvesicles by the fluorescence of the lipophilic dye DiIC16(3). Use menu commands or plot button in the worksheet to create dot plot SSC from FL2 (dye DilC16(3)) in log coordinates. Choose the Rectangular Gate button to draw a gating region so that events from a sample without vesicles are not included in this region (Figure 1B,C).</li>
	<li>Analyze the kinetic experiments.
	<ol>
		<li>Create a dot-plot using the coordinates of fluorescence (FL4) over time for the region of the vesicles (double-click in the region of vesicles in step 5.2)</li>
		<li>Export the data on the change in fluorescence over time in csv format. Choose Sample | Right-click | Export | Choose FL4 and Time in Parameters | Select directory for saving | Select CSV format | Export.</li>
		<li>Open the CSV file in any statistical software (see the Table of Materials). Calculate a simple moving average of fluorescence and time for every 1,000 events.</li>
		<li>Approximate a graph of the dependence of the simple moving average fluorescence on time under the assumption of exponential dependence (Analysis &#62; Fitting &#62;Nonlinear Curve Fit) and use this to calculate the kinetic association constant using Eq (5). 
		<img alt="Equation 5" src="/files/ftp_upload/63459/63459eq05v2.jpg" />&#160; &#160; (5) 
		Where [XB] is the bound factor concentration at each moment of time (user-defined units) according to the simple moving average from step 5.3.3; [X] is the added factor concentration; [X]max is the maximum bound factor concentration; k is the association constant; t is the time.</li>
		<li>Repeat the same set of actions (5.3.1-5.3.4) to calculate the kinetic dissociation constant using Eq (6). 
		<img alt="Equation 6" src="/files/ftp_upload/63459/63459eq06v2.jpg" />&#160; &#160; (6) 
		Where [XB] is the bound factor concentration at each moment of time; [X]0 is the bound factor concentration at the initial moment of time; k is the dissociation constant; t is the time.</li>
	</ol>
	</li>
	<li>Equilibrium binding assay
	<ol>
		<li>Determine the average fluorescence of fX-fd in the region of the vesicles for each selected concentration of fX-fd.</li>
		<li>Approximate the dependence of the bound factor fluorescence from the concentration of the added factor in the assumption of simple single-site binding. Calculate the average binding parameters using Eq (7) from three independent repeats at a minimum. 
		<img alt="Equation 7" src="/files/ftp_upload/63459/63459eq07v2.jpg" />&#160; &#160; (7) 
		Where [XB] is the bound factor concentration; [X] is the added factor concentration; nx&#160;is the apparent number of binding sites per vesicle; Kd is the apparent dissociation constant.</li>
	</ol>
	</li>
</ol>
6. Converting fluorescence intensity to the mean number of binding sites
<ol>
	<li>Prepare calibrated beads.
	<ol>
		<li>Incubate gel-filtered platelets (see step 3.3) with A23187 (10 &#181;M) in the presence of CaCl2 (2.5 mM) for 10 min at room temperature.</li>
		<li>Add to the activated platelets the various concentrations of fX-fd (0 to 1,000 nM). Add 2% v/v formaldehyde and incubate for 1 h. Stop the reaction by incubating the platelets with 3 M glycine and 5% BSA for 30 min at room temperature.</li>
		<li>Purify the mixture from the unreacted dye. Centrifuge the platelets for 5 min at 400 &#215; g, remove the supernatant, and resuspend the pellet in Tyrode&#39;s buffer (containing 0.5% BSA). 
		NOTE: Repeat step 6.1.3 three times.</li>
	</ol>
	</li>
	<li>Measure the fluorescence level of the calibration beads in each sample first using a spectrofluorometer (for fluorescent dye from the Table of Materials, excitation 633 nm, emission 670 nm) and then using the flow cytometer (in channel FL4: excitation 633 nm, emission filter 660/20). Using a cell counter, determine the number of beads in each sample.</li>
	<li>Convert the fluorescence intensity of each respective bead sample to the concentration of soluble fluorescent dye using a spectrofluorometer. Recalculate the fluorescent dye concentration for the number of fluorophore molecules using Eq (8). 
	<img alt="Equation 8" src="/files/ftp_upload/63459/63459eq08.jpg" />&#160; &#160;(8) 
	Where Nx is the number of fluorophore molecules; C is the fluorescent dye concentration; NA&#160;is Avogadro constant; NA = 6.02214076&#215;1023 mol -1.</li>
	<li>Create a dependence graph of the average fluorescence of the beads in a flow cytometer (step 6.2) on the number of fluorophore molecules (see step 6.3) for each sample using any statistical software (see the Table of Materials). Approximate this dependence by line proportionality (Analysis | Fitting | Fit linear). From the approximation in Eq (9), calculate the conversion factor of the mean fluorescence to binding sites. 
	<img alt="Equation 9" src="/files/ftp_upload/63459/63459eq09.jpg" />&#160; &#160; (9) 
	Where MF is the mean fluorescence of beads by flow cytometry; Nx is the number of fluorophore molecules per bead; CF represents the conversion factor of the mean fluorescence to binding sites. CF and b are obtained from the results of fitting the graph by linear proportionality.</li>
	<li>Calculate the apparent number of binding sites per vesicle of interest using Eq (10). 
	<img alt="Equation 10" src="/files/ftp_upload/63459/63459eq10.jpg" />&#160; &#160; (10) 
	Where nx is the apparent number of binding sites per vesicle of interest; MF is the mean fluorescence of the vesicles of interest by flow cytometry; CF and b are conversion factors from the Eq (8).</li>
</ol>

<ol>
	<li>Hoffman, M., Monroe, D. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+cell-based+model+of+hemostasis.">A cell-based model of hemostasis.</a> Thrombosis and haemostasis. 85 (6), 958-965 (2001).</li><li>Roberts, H. R., Hoffman, M., Monroe, D. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+cell-based+model+of+thrombin+generation.">A cell-based model of thrombin generation.</a> Seminars in Thrombosis and Hemostasis. 32, 32-38 (2006).</li><li>Panteleev, M. A., Dashkevich, N. M., Ataullakhanov, F. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hemostasis+and+thrombosis+beyond+biochemistry:+roles+of+geometry,+flow+and+diffusion.">Hemostasis and thrombosis beyond biochemistry: roles of geometry, flow and diffusion.</a> Thrombosis Research. 136 (4), 699-711 (2015).</li><li>Podoplelova, N. 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=Hysteresis-like+binding+of+coagulation+factors+X/Xa+to+procoagulant+activated+platelets+and+phospholipids+results+from+multistep+association+and+membrane-dependent+multimerization.">Hysteresis-like binding of coagulation factors X/Xa to procoagulant activated platelets and phospholipids results from multistep association and membrane-dependent multimerization.</a> Biochimica et Biophysica Acta. 1858 (6), 1216-1227 (2016).</li><li>Panteleev, M. A., Ananyeva, N. M., Greco, N. J., Ataullakhanov, F. I., Saenko, E. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Two+subpopulations+of+thrombin-activated+platelets+differ+in+their+binding+of+the+components+of+the+intrinsic+factor+X-activating+complex.">Two subpopulations of thrombin-activated platelets differ in their binding of the components of the intrinsic factor X-activating complex.</a> Journal of Thrombosis and Haemostasis. 3 (11), 2545-2553 (2005).</li><li>Kotova, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Binding+of+coagulation+factor+XIII+zymogen+to+activated+platelet+subpopulations:+roles+of+integrin+&#945;IIb&#946;3+and+fibrinogen.">Binding of coagulation factor XIII zymogen to activated platelet subpopulations: roles of integrin &#945;IIb&#946;3 and fibrinogen.</a> Thrombosis and Haemostasis. 119 (6), 906-915 (2019).</li><li>Fay, S. P., Posner, R. G., Swann, W. N., Sklar, L. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Real-time+analysis+of+the+assembly+of+ligand,+receptor,+and+G+protein+by+quantitative+fluorescence+flow+cytometry.">Real-time analysis of the assembly of ligand, receptor, and G protein by quantitative fluorescence flow cytometry.</a> Biochemistry. 30 (20), 5066-5075 (2002).</li><li>Nolan, J. P., Shen, B., Park, M. S., Sklar, L. A. <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+human+flap+endonuclease-1+by+flow+cytometry.">Kinetic analysis of human flap endonuclease-1 by flow cytometry.</a> Biochemistry. 35 (36), 11668-11676 (1996).</li><li>Sarvazyan, N. A., Lim, W. K., Neubig, R. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fluorescence+analysis+of+receptor&#8722;G+protein+interactions+in+cell+membranes.">Fluorescence analysis of receptor&#8722;G protein interactions in cell membranes.</a> Biochemistry. 41 (42), 12858-12867 (2002).</li><li>Sarvazyan, N. A., Neubig, R. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+of+molecular+assemblies+by+flow+cytometry:+determinants+of+Gi1+and+by+binding.">Analysis of molecular assemblies by flow cytometry: determinants of Gi1 and by binding.</a> Advances in Optical Biophysics. 3256, 122-131 (1998).</li><li>De Franceschi, N., 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=ProLIF+-+Quantitative+integrin+protein-protein+interactions+and+synergistic+membrane+effects+on+proteoliposomes.">ProLIF - Quantitative integrin protein-protein interactions and synergistic membrane effects on proteoliposomes.</a> Journal of Cell Science. 132 (4), (2018).</li></ol>

The authors have no conflicts of interest to disclose.

The proposed method can be adapted for a rough characterization of the interaction of proteins with phospholipid membranes from various sources and compositions. The quantitative flow cytometry described here concedes to surface plasmon resonance (SPR) in several parameters. In particular, it has a lower sensitivity and time resolution and requires fluorescent labeling of proteins. Fluorescent labeling can lead to a change in conformation and loss of activity for many proteins and therefore requires careful control. Howe...

Biomembranes separate the inner contents of animal cells and extracellular space. Note that membranes also surround microvesicles formed during the cell&#39;s life cycle and organelles. The cell membrane is predominantly composed of lipids and proteins. Membrane proteins perform signaling, structural, transport, and adhesive functions. However, the lipid bilayer is also essential for the interrelation of the animal cell with the extracellular space. This paper proposes a method for studying the peripheral interaction of external proteins with the lipid membrane.
The most striking example of reactions occurring on the outer membrane layer of an animal cell is the blood coagulation reaction. An important feature of blood coagulation is that all the main reactions proceed on the phospholipid membranes of cells and microvesicles arising from these cells and not in the plasma1,2,3. Membrane-dependent reactions include the process of starting coagulation (on the cell membranes of the subendothelium, inflamed endothelium, or activated immune cells, with the participation of a tissue factor), all reactions of the main cascade-activation of factors IX, X, prothrombin; activation of factor XI by thrombin (on the membranes of activated platelets, erythrocytes, lipoproteins, and microvesicles); reactions of the protein C pathway; inactivation of coagulation enzymes (on the membranes of endothelial cells with the participation of thrombomodulin cofactors, endothelial protein C receptor, heparan sulfate); and contact pathway reactions (on membranes of platelets and some microvesicles with the participation of unknown cofactors). Thus, it is impossible to investigate blood coagulation without studying the interaction of various plasma proteins with the membrane of blood cells.
This paper describes a flow-cytometry-based method for characterizing the interaction of proteins with lipid membranes of cells or microvesicles. This approach was initially proposed to study the interaction of blood plasma with platelets and artificial phospholipid vesicles. Moreover, most of the studied proteins interact directly with negatively charged membrane phospholipids, particularly with phosphatidylserine4,5. Additionally, there are proteins whose interaction with the membrane is mediated by special receptors6.
An important ability of flow cytometry is discriminating between free and bound ligands without additional separation. This feature of cytometry allows the study of ligand equilibrium binding at the endpoint and helps perform continuous kinetic measurements. The technique is unsophisticated and does not require complex sample preparation. Flow cytometry is actively used to quantitatively study the dynamics of interaction between fluorescent peptides, receptors, and G-proteins in intact and detergent-permeable neutrophils7. This approach is also applicable for exploring protein-DNA interactions and the kinetics of endonuclease activity in real time8. Over time, this method was used to quantitatively study high-affinity protein-protein interactions with purified lipid vesicles9, or, more generally, with membrane proteins expressed in a highly efficient Sf9 cell expression system10. Quantitative methods have also been described for characterizing protein-liposome interactions using flow cytometry for transmembrane proteins11.
This technique uses self-made calibration beads to avoid using commercially available beads7. The calibration beads used previously7 were intended to work with fluorescein, which substantively restricted the assortment of accessible fluorescent ligands on the proteins. In addition, this paper offers a new way to acquire and analyze kinetic data for reasonable time resolution. Although this method is described for artificial phospholipid vesicles, there are no obvious limitations for its adaptability to cells, natural vesicles, or artificial phospholipid vesicles with a different lipid composition. The method described herein allows the estimation of the parameters of interaction (kon, koff) and equilibrium (Kd) and facilitates quantitative characterization of the number of protein binding sites on the membrane. Note that this technique provides an approximate estimate of the number of binding sites. The advantages of the method are its relative simplicity, accessibility, and adaptability to native cells and natural and artificial microvesicles.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>A23187</td>
			<td>Sigma Aldrich</td>
			<td>C7522-10MG</td>
			<td></td>
		</tr>
		<tr>
			<td>Alexa Fluor 647 NHS Ester (Succinimidyl Ester)</td>
			<td>Thermo Fisher Scientific</td>
			<td>A37573</td>
			<td>fluorescent dye</td>
		</tr>
		<tr>
			<td>Apyrase from potatoes</td>
			<td>Sigma Aldrich</td>
			<td>A2230</td>
			<td></td>
		</tr>
		<tr>
			<td>BD FACSCantoII</td>
			<td>BD Bioscience</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>bovine serum albumin</td>
			<td>VWR Life Science AMRESCO</td>
			<td>Am-O332-0.1</td>
			<td></td>
		</tr>
		<tr>
			<td>Calcium chloride, anhydrous, powder, &#8805;97%</td>
			<td>Sigma Aldrich</td>
			<td>C4901-100G</td>
			<td></td>
		</tr>
		<tr>
			<td>Cary Eclipse Fluorescence Spectrometer</td>
			<td>Agilent</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>D-(+)-Glucose</td>
			<td>Sigma Aldrich</td>
			<td>G7528-1KG</td>
			<td></td>
		</tr>
		<tr>
			<td>DiIC16(3) (1,1&#39;-Dihexadecyl-3,3,3&#39;,3&#39;-Tetramethylindocarbocyanine Perchlorate)</td>
			<td>Thermo Fisher Scientific</td>
			<td>D384</td>
			<td></td>
		</tr>
		<tr>
			<td>DMSO</td>
			<td>Sigma Aldrich</td>
			<td>D8418</td>
			<td></td>
		</tr>
		<tr>
			<td>EDTA disodium salt</td>
			<td>VWR Life Science AMRESCO</td>
			<td>Am-O105B-0.1</td>
			<td></td>
		</tr>
		<tr>
			<td>FACSDiva</td>
			<td>BD Bioscience</td>
			<td></td>
			<td>cytometry data acquisition software</td>
		</tr>
		<tr>
			<td>FlowJo</td>
			<td>Tree Star</td>
			<td></td>
			<td>cytometer software for data analysis</td>
		</tr>
		<tr>
			<td>HEPES</td>
			<td>Sigma Aldrich</td>
			<td>H4034-500G</td>
			<td></td>
		</tr>
		<tr>
			<td>Human Factor X</td>
			<td>Enzyme research</td>
			<td>HFX 1010</td>
			<td></td>
		</tr>
		<tr>
			<td>Hydroxylamine hydrochloride</td>
			<td>Panreac</td>
			<td>141914.1209</td>
			<td></td>
		</tr>
		<tr>
			<td>L-&#945;-phosphatidylcholine (Brain, Porcine)</td>
			<td>Avanti Polar Lipids</td>
			<td>840053P</td>
			<td></td>
		</tr>
		<tr>
			<td>L-&#945;-phosphatidylserine (Brain, Porcine) (sodium salt)</td>
			<td>Avanti Polar Lipids</td>
			<td>840032P</td>
			<td></td>
		</tr>
		<tr>
			<td>Magnesium chloride</td>
			<td>Sigma Aldrich</td>
			<td>M8266-100G</td>
			<td></td>
		</tr>
		<tr>
			<td>Mini-Extruder</td>
			<td>Avanti Polar Lipids</td>
			<td>610020-1EA</td>
			<td></td>
		</tr>
		<tr>
			<td>OriginPro 8 SR4 v8.0951</td>
			<td>OriginLab Corporation</td>
			<td></td>
			<td>Statistical software</td>
		</tr>
		<tr>
			<td>Phosphate Buffered Saline (PBS) Tablets, Biotechnology Grade</td>
			<td>VWR Life Science AMRESCO</td>
			<td>97062-732</td>
			<td></td>
		</tr>
		<tr>
			<td>Potassium chloride</td>
			<td>Sigma Aldrich</td>
			<td>P9541-500G</td>
			<td></td>
		</tr>
		<tr>
			<td>Prostaglandin E1</td>
			<td>Cayman Chemical</td>
			<td>13010</td>
			<td></td>
		</tr>
		<tr>
			<td>Sephadex G25</td>
			<td>GE Healthcare</td>
			<td>GE17-0033-01</td>
			<td>gel filtration medium for protein purification</td>
		</tr>
		<tr>
			<td>Sepharose CL-2B</td>
			<td>Sigma Aldrich</td>
			<td>CL2B300-500ML</td>
			<td>gel filtration medium for platelet purification</td>
		</tr>
		<tr>
			<td>Sodium bicarbonate</td>
			<td>Corning</td>
			<td>61-065-RO</td>
			<td></td>
		</tr>
		<tr>
			<td>Sodium chloride</td>
			<td>Sigma Aldrich</td>
			<td>S3014-500G</td>
			<td></td>
		</tr>
		<tr>
			<td>Sodium phosphate monobasic</td>
			<td>Sigma Aldrich</td>
			<td>S3139-250G</td>
			<td></td>
		</tr>
		<tr>
			<td>Spin collumns with membrane 0.2 &#181;m</td>
			<td>Sartorius</td>
			<td>VS0171</td>
			<td></td>
		</tr>
		<tr>
			<td>Trisodium citrate dihydrate</td>
			<td>Sigma Aldrich</td>
			<td>S1804-1KG</td>
			<td></td>
		</tr>
	</tbody>
</table>

analyzing the interaction of fluorescent-labeled proteins with artificial phospholipid microvesicles using quantitative flow cytometry

In the human body, most of the major physiologic reactions involved in the immune response and blood coagulation proceed on the membranes of cells. An important first step in any membrane-dependent reaction is binding of protein on the phospholipid membrane. An approach to studying protein interaction with lipid membranes has been developed using fluorescently labeled proteins and flow cytometry. This method allows the study of protein-membrane interactions using live cells and natural or artificial phospholipid vesicles. The advantage of this method is the simplicity and availability of reagents and equipment. In this method, proteins are labeled using fluorescent dyes. However, both self-made and commercially available, fluorescently labeled proteins can be used. After conjugation with a fluorescent dye, the proteins are incubated with a source of the phospholipid membrane (microvesicles or cells), and the samples are analyzed by flow cytometry. The obtained data can be used to calculate the kinetic constants and equilibrium Kd. In addition, it is possible to estimate the approximate number of protein binding sites on the phospholipid membrane using special calibration beads.

The flow cytometry method described herein is used to characterize the binding of plasma coagulation proteins to activated platelets. In addition, phospholipid vesicles PS:PC 20:80 were applied as a model system. This paper mainly focuses on artificial phospholipid vesicles as an example. The parameters of the cytometer, in particular, the photomultiplier tube (PMT) voltage and the compensation must be selected for each specific device, the object of study (cells, artificial or natural microvesicles), and the dyes used. ...

Watch this Scientific Journal Video about Analyzing the Interaction of Fluorescent-Labeled Proteins with Artificial Phospholipid Microvesicles using Quantitative Flow Cytometry at JoVE.com

Analyzing the Interaction of Fluorescent-Labeled Proteins with Artificial Phospholipid Microvesicles using Quantitative Flow Cytometry

Here, we describe a set of methods for characterizing the interaction of proteins with membranes of cells or microvesicles.

In the human body, most of the major physiologic reactions involved in the immune response and blood coagulation proceed on the membranes of cells. An ...

analyzing-interaction-fluorescent-labeled-proteins-with-artificial

Research

JoVE Journal

Biochemistry

2.3K Views.  Russian Academy of Sciences. Here, we describe a set of methods for characterizing the interaction of proteins with membranes of cells or microvesicles.

Video: Analyzing the Interaction of Fluorescent-Labeled Proteins with Artificial Phospholipid Microvesicles using Quantitative Flow Cytometry

Mimicking the Function of Signaling Proteins: Toward Artificial Signal Transduction Therapy

Signal transduction pathways, which control the response of cells to various environmental signals, are mediated by the function of signaling proteins that interact with each other and activate one other with high specificity. Synthetic agents that mimic the function of these proteins might therefore be used to generate unnatural signal transduction steps and consequently, alter the cell's function. We present guidelines for designing 'chemical transducers' that can induce artificial communication between native proteins. In addition, we present detailed protocols for synthesizing and testing a specific 'transducer', which can induce communication between two unrelated proteins: platelet-derived growth-factor (PDGF) and glutathione-S-transferase (GST). The way by which this unnatural PDGF-GST communication could be used to control the cleavage of an anticancer prodrug is also presented, indicating the potential for using such systems in 'artificial signal transduction therapy'. This work is intended to facilitate developing additional 'transducers' of this class, which may be used to mediate intracellular protein-protein communication and consequently, to induce artificial cell signaling pathways.

We present guidelines for developing synthetic 'chemical transducers' that can induce communication between naturally unrelated proteins. In addition, detailed protocols are presented for synthesizing and testing a specific 'transducer' that enables a growth factor to activate a detoxifying enzyme and consequently, to regulate the cleavage of an anticancer prodrug.

Signal transduction pathways, which control the response of cells to various environmental signals, are mediated by the function of signaling proteins ...

A Fluorescence-based Assay of Phospholipid Scramblase Activity

Scramblases translocate phospholipids across the membrane bilayer bidirectionally in an ATP-independent manner. The first scramblase to be identified and biochemically verified was opsin, the apoprotein of the photoreceptor rhodopsin. Rhodopsin is a G protein-coupled receptor localized in rod photoreceptor disc membranes of the retina where it is responsible for the perception of light. Rhodopsin&#39;s scramblase activity does not depend on its ligand 11-cis-retinal, i.e., the apoprotein opsin is also active as a scramblase. Although constitutive and regulated phospholipid scrambling play an important role in cell physiology, only a few phospholipid scramblases have been identified so far besides opsin. Here we describe a fluorescence-based assay of opsin&#39;s scramblase activity. Opsin is reconstituted into large unilamellar liposomes composed of phosphatidylcholine, phosphatidylglycerol and a trace quantity of fluorescent NBD-labeled PC (1-palmitoyl-2-{6-[7-nitro-2-1,3-benzoxadiazole-4-yl)amino]hexanoyl}-sn-glycero-3-phosphocholine). Scramblase activity is determined by measuring the extent to which NBD-PC molecules located in the inner leaflet of the vesicle are able to access the outer leaflet where their fluorescence is chemically eliminated by a reducing agent that cannot cross the membrane. The methods we describe have general applicability and can be used to identify and characterize scramblase activities of other membrane proteins.

We describe a fluorescence-based assay to measure phospholipid scrambling in large unilamellar liposomes reconstituted with opsin.

Scramblases translocate phospholipids across the membrane bilayer bidirectionally in an ATP-independent manner. The first scramblase to be identified and ...

DNA Polymerase Activity Assay Using Near-infrared Fluorescent Labeled DNA Visualized by Acrylamide Gel Electrophoresis

For any enzyme, robust, quantitative methods are required for characterization of both native and engineered enzymes. For DNA polymerases, DNA synthesis can be characterized using an in vitro DNA synthesis assay followed by polyacrylamide gel electrophoresis. The goal of this assay is to quantify synthesis of both natural DNA and modified DNA (M-DNA). These approaches are particularly useful for resolving oligonucleotides with single nucleotide resolution, enabling observation of individual steps during enzymatic oligonucleotide synthesis. These methods have been applied to the evaluation of an array of biochemical and biophysical properties such as the measurement of steady-state rate constants of individual steps of DNA synthesis, the error rate of DNA synthesis, and DNA binding affinity. By using modified components including, but not limited to, modified nucleoside triphosphates (NTP), M-DNA, and/or mutant DNA polymerases, the relative utility of substrate-DNA polymerase pairs can be effectively evaluated. Here, we detail the assay itself, including the changes that must be made to accommodate nontraditional primer DNA labeling strategies such as near-infrared fluorescently labeled DNA. Additionally, we have detailed crucial technical steps for acrylamide gel pouring and running, which can often be technically challenging.

This protocol describes the characterization of DNA polymerase synthesis of modified DNA through observation of changes to near-infrared fluorescently labeled DNA using gel electrophoresis and gel imaging. Acrylamide gels are used for high resolution imaging of the separation of short nucleic acids, which migrate at different rates depending on size.

For any enzyme, robust, quantitative methods are required for characterization of both native and engineered enzymes. For DNA polymerases, DNA synthesis ...

Localization of SUMO-modified Proteins Using Fluorescent Sumo-trapping Proteins

Here we are presenting a novel method to study the sumoylation of proteins and their sub-cellular localization in mammalian cells and nematode oocytes. This method utilizes a recombinant modified SUMO-trapping protein fragment, kmUTAG, derived from the Ulp1 SUMO protease of the stress-tolerant budding yeast Kluyveromyces marxianus. We have adapted the properties of the kmUTAG for the purpose of studying sumoylation in a variety of model systems without the use of antibodies. For the study of SUMO, KmUTAG has several advantages when compared to antibody-based approaches. This stress-tolerant SUMO-trapping reagent is produced recombinantly, it recognizes native SUMO isoforms from many species, and unlike commercially available antibodies it shows reduced affinity for free, unconjugated SUMO. Representative results shown here include the localization of SUMO conjugates in mammalian tissue culture cells and nematode oocytes.

SUMO is an essential and highly conserved, small ubiquitin-like modifier protein. In this protocol we are describing the use of a stress-tolerant recombinant SUMO-trapping protein (kmUTAG) to visualize native, untagged SUMO conjugates and their localization in a variety of cell types.

Here we are presenting a novel method to study the sumoylation of proteins and their sub-cellular localization in mammalian cells and nematode oocytes. ...

Quantitative Analysis of the Cellular Lipidome of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry

Lipids are structurally diverse amphipathic molecules that are insoluble in water. Lipids are essential contributors to the organization and function of biological membranes, energy storage and production, cellular signaling, vesicular transport of proteins, organelle biogenesis, and regulated cell death. Because the budding yeast Saccharomyces cerevisiae is a unicellular eukaryote amenable to thorough molecular analyses, its use as a model organism helped uncover mechanisms linking lipid metabolism and intracellular transport to complex biological processes within eukaryotic cells. The availability of a versatile analytical method for the robust, sensitive, and accurate quantitative assessment of major classes of lipids within a yeast cell is crucial for getting deep insights into these mechanisms. Here we present a protocol to use liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) for the quantitative analysis of major cellular lipids of S. cerevisiae. The LC-MS/MS method described is versatile and robust. It enables the identification and quantification of numerous species (including different isobaric or isomeric forms) within each of the 10 lipid classes. This method is sensitive and allows identification and quantitation of some lipid species at concentrations as low as 0.2 pmol/&#181;L. The method has been successfully applied to assessing lipidomes of whole yeast cells and their purified organelles. The use of alternative mobile phase additives for electrospray ionization mass spectrometry in this method can increase the efficiency of ionization for some lipid species and can be therefore used to improve their identification and quantitation.

Quantitative Analysis of the Cellular Lipidome of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry

We present a protocol using liquid chromatography coupled with tandem mass spectrometry to identify and quantify major cellular lipids in Saccharomyces cerevisiae. The described method for a quantitative assessment of major lipid classes within a yeast cell is versatile, robust, and sensitive.

Lipids are structurally diverse amphipathic molecules that are insoluble in water. Lipids are essential contributors to the organization and function of ...

Transverse Sectioning of Mature Rice (Oryza sativa L.) Kernels for Scanning Electron Microscopy Imaging Using Pipette Tips as Immobilization Support

Starch granules (SGs) exhibit different morphologies depending on the plant species, especially in the endosperm of the Poaceae family. Endosperm phenotyping can be used to classify genotypes based on SG morphotype using scanning electron microscopic (SEM) analysis. SGs can be visualized using SEM by slicing through the kernel (pericarp, aleurone layers, and endosperm) and exposing the organellar contents. Current methods require the rice kernel to be embedded in plastic resin and sectioned using a microtome or embedded in a truncated pipette tip and sectioned by hand using a razor blade. The former method requires specialized equipment and is time-consuming, while the latter introduces a new host of problems depending on rice genotype. Chalky rice varieties, particularly, pose a problem for this type of sectioning due to the friable nature of their endosperm tissue. Presented here is a technique for preparing translucent and chalky rice kernel sections for microscopy, requiring only pipette tips and a scalpel blade. Preparing the sections within the confines of a pipette tip prevents rice kernel endosperm from shattering (for translucent or &#8216;vitreous&#8217; phenotypes) and crumbling (for chalky phenotypes). Using this technique, endosperm cell patterning and the structure of intact SGs can be observed.

Transverse Sectioning of Mature Rice Oryza sativa L. Kernels for Scanning Electron Microscopy Imaging Using Pipette Tips as Immobilization Support

This protocol allows for the preparation of transverse sections of cereal seeds (e.g., rice) for the analysis of endosperm and starch granule morphology using scanning electron microscopy.

Starch granules (SGs) exhibit different morphologies depending on the plant species, especially in the endosperm of the Poaceae family. Endosperm ...

Quantitative Metabolomics of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry

Metabolomics is a methodology used for the identification and quantification of many low-molecular-weight intermediates and products of metabolism within a cell, tissue, organ, biological fluid, or organism. Metabolomics traditionally focuses on water-soluble metabolites. The water-soluble metabolome is the final product of a complex cellular network that integrates various genomic, epigenomic, transcriptomic, proteomic, and environmental factors. Hence, the metabolomic analysis directly assesses the outcome of the action for all these factors in a plethora of biological processes within various organisms. One of these organisms is the budding yeast Saccharomyces cerevisiae, a unicellular eukaryote with the fully sequenced genome. Because S. cerevisiae is amenable to comprehensive molecular analyses, it is used as a model for dissecting mechanisms underlying many biological processes within the eukaryotic cell. A versatile analytical method for the robust, sensitive, and accurate quantitative assessment of the water-soluble metabolome would provide the essential methodology for dissecting these mechanisms. Here we present a protocol for the optimized conditions of metabolic activity quenching in and water-soluble metabolite extraction from S. cerevisiae cells. The protocol also describes the use of liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) for the quantitative analysis of the extracted water-soluble metabolites. The LC-MS/MS method of non-targeted metabolomics described here is versatile and robust. It enables the identification and quantification of more than 370 water-soluble metabolites with diverse structural, physical, and chemical properties, including different structural isomers and stereoisomeric forms of these metabolites. These metabolites include various energy carrier molecules, nucleotides, amino acids, monosaccharides, intermediates of glycolysis, and tricarboxylic cycle intermediates. The LC-MS/MS method of non-targeted metabolomics is sensitive and allows the identification and quantitation of some water-soluble metabolites at concentrations as low as 0.05 pmol/&#181;L. The method has been successfully used for assessing water-soluble metabolomes of wild-type and mutant yeast cells cultured under different conditions.

Quantitative Metabolomics of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry

We present a protocol for the identification and quantitation of major classes of water-soluble metabolites in the yeast Saccharomyces cerevisiae. The described method is versatile, robust, and sensitive. It allows the separation of structural isomers and stereoisomeric forms of water-soluble metabolites from each other.

Metabolomics is a methodology used for the identification and quantification of many low-molecular-weight intermediates and products of metabolism within ...

A Robust Single-Particle Cryo-Electron Microscopy (cryo-EM) Processing Workflow with cryoSPARC, RELION, and Scipion

Recent advances in both instrumentation and image processing software have made single-particle cryo-electron microscopy (cryo-EM) the preferred method for structural biologists to determine high-resolution structures of a wide variety of macromolecules. Multiple software suites are available to new and expert users for image processing and structure calculation, which streamline the same basic workflow: movies acquired by the microscope detectors undergo correction for beam-induced motion and contrast transfer function (CTF) estimation. Next, particle images are selected and extracted from averaged movie frames for iterative 2D and 3D classification, followed by 3D reconstruction, refinement, and validation. Because various software packages employ different algorithms and require varying levels of expertise to operate, the 3D maps they generate often differ in quality and resolution. Thus, users regularly transfer data between a variety of programs for optimal results. This paper provides a guide for users to navigate a workflow across the popular software packages: cryoSPARC v3, RELION-3, and Scipion 3 to obtain a near-atomic resolution structure of the adeno-associated virus (AAV). We first detail an image processing pipeline with cryoSPARC v3, as its efficient algorithms and easy-to-use GUI allow users to quickly arrive at a 3D map. In the next step, we use PyEM and in-house scripts to convert and transfer particle coordinates from the best quality 3D reconstruction obtained in cryoSPARC v3 to RELION-3 and Scipion 3 and recalculate 3D maps. Finally, we outline steps for further refinement and validation of the resultant structures by integrating algorithms from RELION-3 and Scipion 3. In this article, we describe how to effectively utilize three processing platforms to create a single and robust workflow applicable to a variety of data sets for high-resolution structure determination.

A Robust Single-Particle Cryo-Electron Microscopy cryo-EM Processing Workflow with cryoSPARC, RELION, and Scipion

This article describes how to effectively utilize three cryo-EM processing platforms, i.e., cryoSPARC v3, RELION-3, and Scipion 3, to create a single and robust workflow applicable to a variety of single-particle data sets for high-resolution structure determination.

Recent advances in both instrumentation and image processing software have made single-particle cryo-electron microscopy (cryo-EM) the preferred method ...

Rapid Assessment of Membrane Protein Quality by Fluorescent Size Exclusion Chromatography

During membrane protein structural elucidation and biophysical characterization, it is common to trial numerous protein constructs containing different tags, truncations, deletions, fusion partner insertions, and stabilizing mutations to find one that is not aggregated after extraction from the membrane. Furthermore, buffer screening to determine the detergent, additive, ligand, or polymer that provides the most stabilizing condition for the membrane protein is an important practice. The early characterization of membrane protein quality by fluorescent size exclusion chromatography provides a powerful tool to assess and rank different constructs or conditions without the requirement for protein purification, and this tool also minimizes the sample requirement. The membrane proteins must be fluorescently tagged, commonly by expressing them with a GFP tag or similar. The protein can be solubilized directly from whole cells and then crudely clarified by centrifugation; subsequently, the protein is passed down a size exclusion column, and a fluorescent trace is collected. Here, a method for running FSEC and representative FSEC data on the GPCR targets sphingosine-1-phosphate receptor (S1PR1) and serotonin receptor (5HT2AR) are presented.

The present protocol describes a procedure to perform fluorescent size exclusion chromatography (FSEC) on membrane proteins to assess their quality for downstream functional and structural analysis. Representative FSEC results collected for several G-protein coupled receptors (GPCRs) under detergent-solubilized and detergent-free conditions are presented.

During membrane protein structural elucidation and biophysical characterization, it is common to trial numerous protein constructs containing different ...

An Optimized Quantitative Pull-Down Analysis of RNA-Binding Proteins Using Short Biotinylated RNA

Protein-RNA interactions regulate gene expression and cellular functions at transcriptional and post-transcriptional levels. For this reason, identifying the binding partners of an RNA of interest remains of high importance to unveil the mechanisms behind many cellular processes. However, RNA molecules might interact transiently and dynamically with some RNA-binding proteins (RBPs), especially with non-canonical ones. Hence, improved methods to isolate and identify such RBPs are greatly needed.
To identify the protein partners of a known RNA sequence efficiently and quantitatively, we developed a method based on the pull-down and characterization of all interacting proteins, starting from cellular total protein extract. We optimized the protein pull-down using biotinylated RNA pre-loaded on streptavidin-coated beads. As a proof of concept, we employed a short RNA sequence known to bind the neurodegeneration-associated protein TDP-43 and a negative control of a different nucleotide composition but the same length. After blocking the beads with yeast tRNA, we loaded the biotinylated RNA sequences on the streptavidin beads and incubated them with the total protein extract from HEK 293T cells. After incubation and several washing steps to remove nonspecific binders, we eluted the interacting proteins with a high-salt solution, compatible with the most commonly used protein quantification reagents and with sample preparation for mass spectrometry. We quantified the enrichment of TDP-43 in the pull-down performed with the known RNA binder compared to the negative control by mass spectrometry. We used the same technique to verify the selective interactions of other proteins computationally predicted to be unique binders of our RNA of interest or of the control. Finally, we validated the protocol by western blot via the detection of TDP-43 with an appropriate antibody. 
This protocol will allow the study of the protein partners of an RNA of interest in near-to-physiological conditions, helping uncover unique and unpredicted protein-RNA interactions.

Here, we present an optimized in vitro method to uncover, quantify, and validate protein interactors of specific RNA sequences, using total protein extract from human cells, streptavidin beads coated with biotinylated RNA, and mass spectrometry analysis.

Protein-RNA interactions regulate gene expression and cellular functions at transcriptional and post-transcriptional levels. For this reason, identifying ...