The authors would like to thank Prof. Tartaglia&#39;s and Dr. Cuomo&#39;s research group for the support offered. E.Z. received funding from the MINDED fellowship of the European Union&#39;s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No. 754490.

1. General methods and material
<ol>
	<li>Prepare the appropriate medium for the chosen mammalian cell culture and pre-warm it at 37 &#176;C for 20 min before use.</li>
	<li>Prepare the required material in advance, as described in the Table of Materials. Autoclave glassware, plasticware, and buffer stocks.</li>
	<li>Prepare the buffers as described in Table 1. Adjust the pH of the stock solutions using concentrated HCl or NaOH before diluting the components to their final volumes.</li>
</ol>
2. Mammalian cell line preparation
<ol>
	<li>Grow HEK 293T cells in Dulbecco&#39;s Modified Eagle Medium (DMEM) supplemented with 10% fetal bovine serum (FBS) and 100 &#181;g/mL penicillin/streptomycin solution. Incubate them at 37 &#176;C in a humidified incubator supplied with 5% CO2. Routinely split the cells.</li>
	<li>Before detaching, rinse the cells with enough phosphate-buffered saline (PBS) solution to cover the growing surface.</li>
	<li>Remove the PBS and add an ultra-thin layer of trypsin-EDTA solution.</li>
	<li>Incubate the cells at 37 &#176;C in a humidified incubator provided with 5% CO2 for 5 min, or until the cells are detached (they should look dispersed under microscopic observation).</li>
	<li>Dilute the trypsin-EDTA solution tenfold by adding complete DMEM to inactivate it and count the cells.</li>
	<li>Plate 1.5 x 105 cells/mL in 6-well plates, considering two wells/condition to test.</li>
	<li>Incubate the cells at 37 &#176;C for 48 h in a humidified incubator with 5% CO2. 
	NOTE: Check the manufacturer instructions for the type of medium and supplement apt for the cell line. Also, the amount and the incubation time of trypsin-EDTA depend on the cell line. Some cell types grow faster/slower than what was reported in this protocol; thus, seeding concentration should be tested beforehand.</li>
</ol>
3. Total protein harvest
<ol>
	<li>Remove medium from the wells where cells are growing.</li>
	<li>Wash each well of the 6-well plates with 1 mL of PBS.</li>
	<li>Discard the PBS.</li>
	<li>Move the plates on ice and either proceed with step 3.5 or freeze the dry plates at -80 &#176;C to facilitate lysis.</li>
	<li>Add 200 &#181;L of lysis buffer to each well.</li>
	<li>Use a cell scraper to detach and break the cells.</li>
	<li>Transfer the cell extract deriving from two wells into the same 1.5 mL tube.</li>
	<li>Place the tube containing the protein extract on ice for 30 min.</li>
	<li>Centrifuge the cell lysates at 17,000 x g for 15 min at 4 &#176;C.</li>
	<li>Transfer each supernatant into a pre-cooled tube. 
	NOTE: A total of 106-107 cells for each PD condition are recommended. Cell lysis and protein harvest should be performed with ice-cold buffers. Protease inhibitors should be added to the lysis buffer to prevent protein degradation.</li>
</ol>
4. Protein concentration determination
<ol>
	<li>Prepare Bradford reagent, as indicated by the producer, by diluting it fivefold in dH2O.</li>
	<li>Distribute 1 mL of reagent in a 1 cm cuvette, add 1 &#181;L of the sample, and mix by inversion.</li>
	<li>Incubate in the dark at room temperature for 5-10 min.</li>
	<li>Read the absorbance at 595 nm.</li>
	<li>Calculate the volume of protein extract corresponding to 1.5 mg of proteins and bring all the samples to a final volume of 600 &#181;L using lysis buffer.</li>
	<li>Keep the samples on ice until use. 
	NOTE: Any other protein concentration determination method can be used, following buffer compatibility recommendations. In any case, the lysis buffer should be used as a blank. Many reagents are not compatible with dithiothreitol (DTT). It is recommended to add DTT or other reducing agents only after protein quantification (DTT to a final concentration of 1 mM).</li>
</ol>
5. Bead preparation
<ol>
	<li>Mix the beads in their storage buffer by flicking the tube.</li>
	<li>Calculate 100 &#181;L of slurry medium/sample and place the volume into a magnetic rack.</li>
	<li>Bead wash
	<ol>
		<li>Remove the storage solution and wash the beads by adding 1 mL of lysis buffer/tube and invert it manually.</li>
		<li>Remove the buffer using the magnetic rack.</li>
		<li>Repeat the washing step.</li>
		<li>Add a volume of lysis buffer equal to the initial volume of slurry medium, mix by flicking the tube, and dispense the medium uniformly into as many 1.5 mL tubes as there are samples.</li>
	</ol>
	</li>
	<li>Bead blocking
	<ol>
		<li>Remove the buffer using the magnetic rack and add 600 &#181;L of a 0.25 mg/mL solution of yeast tRNA prepared in lysis buffer.</li>
		<li>Incubate for 1 h at room temperature on a rotating wheel.</li>
		<li>Remove the tRNA solution using the magnetic rack.</li>
		<li>Add 600 &#181;L of lysis buffer and wash by mixing manually.</li>
		<li>Repeat the washing step and discard the buffer.</li>
	</ol>
	</li>
</ol>
6. Bead loading
<ol>
	<li>Prepare 200 &#181;g of RNA oligonucleotide in 600 &#181;L of lysis buffer for each tube containing the initial 100 &#181;L slurry medium (now blocked beads).</li>
	<li>Add the oligo to the beads and incubate for 1 h at room temperature while rotating.</li>
	<li>Remove the solution, add 600 &#181;L of lysis buffer, and wash the beads twice by rotating the tubes for 5 min at room temperature.</li>
	<li>Discard the buffer. 
	&#8203;NOTE: Never vortex the beads, but flick instead. Limit the number of pipetting steps, unless necessary. When possible, use cut, 1 mL tips. The amount of bead slurry medium/sample depends on the binding capability of the beads and the starting amount of the total proteins. If the RNA oligo is predicted to have a significant amount of secondary structure, we recommend to first denature it at 80 &#176;C for 10 min and then cool it down slowly at room temperature or refold it by incubating it at 30 &#176;C for 1 h. It is suggested to recover the RNA oligo after bead loading and determine the concentration left, in order to optimize the amount required for loading and to evaluate the possibility of reusing the RNA.</li>
</ol>
7. Protein binding on beads
NOTE: From now on, when possible, perform the steps at 4 &#176;C.
<ol>
	<li>Take a 5% volume from the 600 &#181;L protein solution and keep it as INPUT (IN) for further analysis (1.5 mg of proteins are dissolved in 600 &#181;L, so 5% corresponds to 30 &#181;L and 75 &#181;g of proteins).</li>
	<li>Add the remaining protein mix to each tube of loaded beads and leave slowly rotating overnight at 4 &#176;C.</li>
</ol>
8. Washing of nonspecific binders
<ol>
	<li>Remove the unbound fraction using the magnetic rack. Save 5% of the volume and label it as FLOWTHROUGH (FT) (the unbound volume is ca. 600 &#181;L, so again keep 30 &#181;L for further analysis).</li>
	<li>Add 1 mL of wash buffer 1 to the beads and leave it rotating for 5 min at 4 &#176;C.</li>
	<li>Discard the buffer.</li>
	<li>Repeat steps 8.2 and 8.3.</li>
	<li>Add 1 mL of wash buffer 2 to the beads and leave it rotating for 5 min at 4 &#176;C.</li>
	<li>Discard the supernatant.</li>
</ol>
9. Elution of specific binders
<ol>
	<li>Add 100 &#181;L of elution buffer 1 or elution buffer 2 to the beads.</li>
	<li>Mix manually by flicking and incubate for 5 min at room temperature.</li>
	<li>Place the tubes in a thermomixer and shake vigorously for 5 min at 95 &#176;C.</li>
	<li>Place the tube into the magnetic rack and collect the eluted fraction into a clean tube.</li>
	<li>Quickly spin the beads with a bench centrifuge to maximize the recovery of the eluate.</li>
	<li>Save 5% of the total ELUATE (EL) volume for further analyses (total volume is 100 &#181;L, so separate 5 &#181;L into another tube).</li>
	<li>If needed, the protein concentration can be determined as in section 4, by using elution buffer as a blank. 
	NOTE: It is recommended to refrain from adding DTT to the elution buffer until protein concentration has been determined. If protein quantification is not required, or if reducing agent-compatible protein quantification kits are available, 1 mM DTT can be added to the elution buffer from the start. In this protocol, both elution buffer 1 (containing 1 M NaCl) and elution buffer 2 (with 2 M NaCl) were tested. No difference in the elution efficiency of the target protein was observed with increased ionic strength, but it is recommended to test both conditions before establishing the most appropriate buffer. If a high presence of salt in the elution buffer represents a limitation for further analysis, the very low amount of detergents in the elution buffer allows for buffer-exchange. As an alternative, the eluate can be diluted to reach the desired salt concentration.</li>
</ol>
10. Identification of protein binders by mass spectrometry
<ol>
	<li>Acetone precipitation
	<ol>
		<li>Concentrate the eluted proteins by diluting it fourfold in cold (-20 &#176;C) acetone.</li>
		<li>Vortex and incubate the tube at -20 &#176;C overnight.</li>
		<li>Spin at 17,000 x g for 30 min at 4 &#176;C.</li>
		<li>Gently remove the supernatant and allow the acetone to evaporate until the pellet has completely dried.</li>
	</ol>
	</li>
	<li>In-solution protein digestion
	<ol>
		<li>Dissolve the protein pellet by adding 50 &#181;L of denaturation buffer.</li>
		<li>Add DTT to a final concentration of 5 mM, allowing protein reduction for 30 min at 55 &#176;C.</li>
		<li>Cool down the samples at room temperature and proceed with the protein alkylation reaction, adding iodoacetamide (IAA) at a concentration of 10 mM for 15 min.</li>
		<li>Digest the proteins using a suitable enzyme (trypsin, LysC) and incubate the samples overnight at 37 &#176;C.</li>
		<li>Stop the digestion by adding 1 &#181;L of 10% trifluoroacetic acid (TFA).</li>
		<li>Clean up and concentrate the peptides on a custom reversed phase C18 micro-column, as previously described19.</li>
		<li>Elute peptides from the C18 tip with Buffer B.</li>
		<li>Remove the organic component using a vacuum centrifuge and resuspend the peptides in 5 &#181;L of 0.1% formic acid for further analysis. 
		NOTE: Alternatively, protein digestion can be performed &#34;on-beads&#34; immediately after washing nonspecific binders (steps 8.1-8.6), thus making the protocol faster. However, it is advisable to test the efficiency of the enzyme working &#34;on-beads&#34; immobilized-proteins compared to standard in solution digestion, in order to guarantee the optimal experimental protein sequence coverage.</li>
	</ol>
	</li>
	<li>Liquid chromatography-tandem mass spectrometry (LC-MS/MS)
	<ol>
		<li>Plug in the analytical column (C18-stationary phase) and keep it at 45 &#176;C during the time of the run.</li>
		<li>Connect the column to the outlet of a six-port rotary valve of the LC pump through a capillary finger-tight fitting (20 &#181;m x 550 mm) in a single-column configuration.</li>
		<li>Adjust the LC settings as follows:
		<ol>
			<li>Load the peptides under controlled pressure (980 bar) in Buffer A.</li>
			<li>Apply a 5%-20% Buffer B gradient at 300 nL/min over 59 min, followed by a 20%-30% Buffer B gradient over 15 min and a 30%-65% Buffer B gradient over 5 min.</li>
			<li>Add a wash step by increasing the concentration of Buffer B up to 95% over 5 min plus a 5 min isocratic step at 95% Buffer B.</li>
		</ol>
		</li>
		<li>Operate the mass spectrometer in data-dependent acquisition (DDA) mode to switch automatically between MS and MSMS events.</li>
		<li>Define a loop count equal to 15 using an automatic gain control (AGC) target value of 3 x 106 and 1 x 105 for the MS and MSMS events, respectively.</li>
		<li>Set the maximum allowed ion accumulation time to 20 ms for MS with a resolution of 60 K, and 100 ms for MSMS with a resolution of 15 K.</li>
		<li>Perform a high collision dissociation (HCD) fragmentation experiment using a normalized collision energy of 28%, with a dynamic exclusion time of 20 s.</li>
		<li>Operate the source parameters as follows: 
		Spray voltage: 1.7 kV 
		Capillary voltage: 275 &#176;C 
		Neither a sheath nor auxiliary gas used 
		NOTE: In this protocol, ultra-high performance liquid chromatography (UHPLC) mass spectrometric (MS) analysis has been specifically performed using an LC single column setup, coupled to a hybrid triple quadrupole orbitrap instrument (Table of Materials). Other LCMS systems can be used, but an adaption of parameters is recommended.</li>
	</ol>
	</li>
	<li>Data analysis
	<ol>
		<li>Use the Load button to import the raw files.</li>
		<li>Define the experiment names by clicking on the Set Experiment button.</li>
		<li>Enter the group-specific parameters section to specify all theparameters related to identification: 
		Enzyme used for digestion: Trypsin/P 
		Missed cleavages: up to three 
		Fixed modification: Carbamidomethylation 
		Variable modification: N-acetyl (Protein), Oxidation (M)</li>
		<li>Upload an updated FASTA file, available from public databases such as UniprotKB.</li>
		<li>Specify the correct parse rules according to the source of the chosen database.</li>
		<li>Define a parentage false discovery rate (FDR) value = 1 for both proteins and peptides.</li>
		<li>Add the label free quantification (LFQ) option in the Label Free Quantification tab.</li>
		<li>Keep the minimum LFQ ratio count at two. 
		NOTE: Here, we describe data analysis using MaxQuant24 and Perseus software25 to perform protein quantification and subsequent statistical analysis, respectively. However, data analysis can be performed with any other commercially available or free bioinformatic. FDR is estimated using a target-decoy database-based approach26. Peptide and protein FDR equal to 0.01 means that peptides and proteins identified are expected to contain 1% of false positives.</li>
	</ol>
	</li>
	<li>Statistical analysis
	<ol>
		<li>Load the proteingroups.txt file to perform statistical analysis at the protein level.</li>
		<li>Define the LFQ values as main columns.</li>
		<li>Remove &#34;reverse&#34; and &#34;contaminants&#34; by filtering rows based on the categorical column.</li>
		<li>Use the categorical annotation rows to group the different experimental conditions.</li>
		<li>Reduce the data matrix, selecting the number of valid values in each of the previously defined groups.</li>
		<li>Select the statistical test that better suits the experimental conditions (i.e., t-test, multiple sample test ANOVA).</li>
		<li>Determine a cut-off for significant hints with an FDR-based calculation. Typically, both 0.01 and 0.05 are accepted as thresholds for the adjusted p value.</li>
		<li>Visualize the results of differential analyses based on t-test statistics using a volcano plot representation.</li>
		<li>Export the final matrix in .txt format for further editing of the final result table. 
		NOTE: The configuration folder contains a FASTA file with proteins such as keratins that are considered common contaminants in global proteomic experiments, which are flagged with a + in the output table. In the present study, having two sample conditions, a t-test is used for the statistical analysis.</li>
	</ol>
	</li>
</ol>
11. Results validation by western blot
<ol>
	<li>Sample preparation
	<ol>
		<li>Add the appropriate volume of 4x sample loading buffer to each aliquot of IN, FT, and EL.</li>
		<li>Boil the samples for 5 min at 95&#176;C.</li>
		<li>Fast-spin to recover evaporated sample from the top of the tubes.</li>
	</ol>
	</li>
	<li>SDS-PAGE and gel transfer
	<ol>
		<li>Load samples on a 4%-12% denaturing polyacrylamide gel.</li>
		<li>Run the gel with MES SDS running buffer for 1.5 h at 120 V.</li>
		<li>Transfer the gel on a nitrocellulose membrane with a semi-dry transfer cassette, following the manufacturer instructions. We recommend a 10 min transfer at 15 V.</li>
	</ol>
	</li>
	<li>Immunodetection
	<ol>
		<li>Block the membrane with 10% bovine serum albumin (BSA) for 1 h at room temperature while gently agitating.</li>
		<li>Add the primary antibody prepared in 5% BSA in TBST, according to the manufacturer&#39;s instructions. Leave overnight at 4 &#176;C or for 1 h at room temperature under gentle agitation.</li>
		<li>Wash the membrane three times with TBST, each time for 5 min.</li>
		<li>Add the secondary antibody prepared in TBST for 1 h at room temperature under agitation.</li>
		<li>Wash the membrane three times with TBST, each time for 5 min.</li>
		<li>Visualize the results using a blot imager. 
		NOTE: For detecting TDP-43, a known binder of our RNA, recombinant rabbit monoclonal antibody was used and left with the membrane overnight at 4 &#176;C. As a secondary antibody, the anti-rabbit IgG horseradish peroxidase (HRP) was used, but a fluorescent secondary antibody would work as well. To visualize the antibodies on the membrane, the membrane was incubated with the Clarity Western ECL substrate for 1 min, before imaging with the ChemiDoc imaging system.</li>
	</ol>
	</li>
</ol>

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S., Juhas, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Recent+advances+in+aptamer+discovery+and+applications.">Recent advances in aptamer discovery and applications.</a> Molecules. 24 (5), 941 (2019).</li><li>UniProt Consortium. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=UniProt:+the+Universal+Protein+Knowledgebase+in+2023.">UniProt: the Universal Protein Knowledgebase in 2023.</a> Nucleic Acids Research. 51, 523-531 (2023).</li><li>Tyanova, S., Temu, T., Cox, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+MaxQuant+computational+platform+for+mass+spectrometry-based+shotgun+proteomics.">The MaxQuant computational platform for mass spectrometry-based shotgun proteomics.</a> Nature Protocols. 11 (12), 2301-2319 (2016).</li><li>Tyanova, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Perseus+computational+platform+for+comprehensive+analysis+of+(prote)omics+data.">The Perseus computational platform for comprehensive analysis of (prote)omics data.</a> Nature Methods. 13 (9), 731-740 (2016).</li><li>Rappsilber, J., Mann, M., Ishihama, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Protocol+for+micro-purification,+enrichment,+pre-fractionation+and+storage+of+peptides+for+proteomics+using+StageTips.">Protocol for micro-purification, enrichment, pre-fractionation and storage of peptides for proteomics using StageTips.</a> Nature Protocols. 2 (8), 1896-1906 (2007).</li><li>Bellucci, M., Agostini, F., Masin, M., Tartaglia, G. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Predicting+protein+associations+with+long+noncoding+RNAs.">Predicting protein associations with long noncoding RNAs.</a> Nature Methods. 8 (6), 444-445 (2011).</li><li>Gallo-Oller, G., Ordo&#241;ez, R., Dotor, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+new+background+subtraction+method+for+Western+blot+densitometry+band+quantification+through+image+analysis+software.">A new background subtraction method for Western blot densitometry band quantification through image analysis software.</a> Journal of Immunological Methods. 457, 1-5 (2018).</li><li>Weissinger, R., Heinold, L., Akram, S., Jansen, R. P., Hermesh, O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=RNA+proximity+labeling:+A+new+detection+tool+for+RNA-protein+interactions.">RNA proximity labeling: A new detection tool for RNA-protein interactions.</a> Molecules. 26 (8), 2270 (2021).</li><li>Hirsch, J. D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Easily+reversible+desthiobiotin+binding+to+streptavidin,+avidin,+and+other+biotin-binding+proteins:+Uses+for+protein+labeling,+detection,+and+isolation.">Easily reversible desthiobiotin binding to streptavidin, avidin, and other biotin-binding proteins: Uses for protein labeling, detection, and isolation.</a> Analytical Biochemistry. 308 (2), 343-357 (2002).</li><li>Sefah, K., Shangguan, D., Xiong, X., O'Donoghue, M. B., Tan, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Development+of+DNA+aptamers+using+cell-SELEX.">Development of DNA aptamers using cell-SELEX.</a> Nature Protocols. 5 (6), 1169-1185 (2010).</li></ol>

The authors have no competing financial interests or other conflicts of interest.

This work reports the optimization of a PD protocol performed with biotinylated RNA oligonucleotides to capture their protein interactors. The protocol described here is simple to perform, requires little material, and produces highly reliable results. Importantly, the most novel aspects of this protocol consist of the use of an RNA bait designed fully in silico and specific for the protein target, and the elution of all proteins bound to the RNA bait by directly disrupting their interactions with a high-salt solution, rather than by dissociating the streptavidin from the biotin with detergent and high temperature treatment.
This protocol takes advantage of the strength of the bond between biotin and streptavidin29,30. According to the chosen streptavidin beads, loading of the biotinylated RNA must be tested and quantified before proceeding. Also, the RNA tri-dimensional folding might affect the loading efficiency on the beads, since it might limit the exposure of the biotin to the streptavidin. Blocking the beads with non-biotinylated tRNA improves the cleanliness of the results by limiting nonspecific interactions with the beads. The loading buffer and the elution buffer must be chosen depending on the downstream applications. Here, very mild conditions, suitable to the majority of the applications and developed to preserve potential protein complexes, were proposed. This method is however highly adaptable; the user can choose any cell line and any RNA size, and could decide to repeat the protocol after folding/unfolding of the RNA to determine the effect of the structure on the binding properties.
Another original aspect of this protocol is the use of in silico prediction tools to ensure the correctness of the results20. Knowing in advance which proteins should be identified as interactors of the RNA of interest gives the unprecedented advantage of validating the technical aspects of the protocol. For example, using a simple WB analysis, it is possible to verify the presence of a known protein target in the samples derived from the different steps of the protocol before proceeding with the MS analysis, which requires specialized instrumentation and is more costly. In addition, a method to use catRAPID20, an in-house protein-RNA prediction algorithm, to design de novo RNA specific for a target protein was recently reported. Until recently, the only available pipeline to design DNA/RNA aptamers for a target protein was the SELEX (systematic evolution of ligands by exponential enrichment) approach31. The in silico method enables for a much faster and cost-effective design of RNA aptamers.
The main limitations of this method are associated with the need of working in nuclease-free buffers and tools. Moreover, if it is considered necessary to confirm in vitro the binding between a de novo-designed RNA and a target protein prior PD, the protein needs to be produced and purified and the binding determined with biophysical approaches. This is a limitation that is shared with the production of monoclonal antibodies.
Despite these minor issues, reliable methods to map RNA-protein interactions, such as the one presented here, can bring scientists closer to unveil macromolecular networks and complex main actors of many physiological and pathological mechanisms, such as the ones involved in cancer, cardiomyopathies, diabetes, microbial infections, and genetic and neurodegenerative disorders.

RNA-binding proteins (RBPs) have emerged as crucial players in transcriptional and post-transcriptional gene regulation, since they are involved in processes such as mRNA splicing, RNA cellular localization, translation, modification, and degradation1,2,3. Such interactions between the two macromolecules are highly coordinated, precisely balanced, and essential for the formation of functional and processing hubs. Variations or dysregulations within these hubs have the potential of disrupting the finely regulated protein-RNA networks and are increasingly associated with a variety of human diseases, including cancer4,5 and neurodegenerative disorders6,7,8. The interactions between RNA molecules and their protein binding partners can be either stable and easy to validate experimentally, or highly dynamic, transient, and more difficult to characterize.
In recent years, intensive efforts have been undertaken to understand these interactions. Among the most established methods, protein pull-down assays (PDs) are probably the most appreciated and commonly used approaches to unravel the main players constituting ribonucleoprotein (RNP) complexes and other protein-RNA interaction networks3,9,10. PDs include a broad umbrella of informative techniques, such as the immunoprecipitation of either the RNA (RIP)11,12 or the protein (CLIP)13,14 of interest. Some of these RNA-PD protocols employ a known RNA as bait for proteins15, most frequently by taking advantage of high affinity tags such as biotin. In this instance, the interaction partners of a biotinylated RNA can be detected by anchoring the RNA on streptavidin-coated beads, enabling efficient isolation of the RNPs. The main limitations of these approaches are usually the design of the biotinylated probes and the testing of their ability to bind target proteins. For this purpose, it could be useful to rely on published CLIP data of the protein of interest, if available, since they reveal, with high precision, the short RNA regions that correspond to peaks of interactions with the target protein13,16. These same regions could be used to develop probes for PDs. An alternative method to design such RNA baits might be the systematic evolution of ligands by exponential enrichment (SELEX)17, which enable the design of aptamers through in vitro selection, starting from a comprehensive randomized library and via a series of PCR-driven optimization cycles. However, SELEX is complex and time consuming, and the final results are highly dependent on the initial library. To select the RNA bait to use in the protocol presented here, yet another approach was exploited, consisting of using an RNA bait designed de novo by means of the computational power of the algorithm catRAPID, which predicts the preferential binding of a given protein toward certain RNA sequences18,19,20.
The protocol introduced here is a version of an RNA-PD optimized to elute specific protein partners in near-to-physiological conditions, without the use of detergent, denaturing agents, or high temperatures. It relies on nano-superparamagnetic beads covalently coated with highly purified streptavidin and the use of a specific in silico designed biotinylated RNA as a bait. This protocol provides a rapid and efficient method to isolate the binding partners of biotinylated RNA molecules in native conditions, offering the potential for a wide range of downstream applications. To test this protocol, a 10-nucleotide single stranded RNA aptamer sequence, previously designed to bind the protein TAR DNA-binding protein 43 (TDP-43) with high affinity and specificity, was used20. Starting from HEK 293T cell lysates, the interactors of the biotinylated RNA aptamer were identified by means of mass-spectrometry analysis performed on samples detached from the RNA bait using a hypertonic buffer. This analysis confirmed&#160;the successful identification and quantification of TDP-43 as preferred binder.
This protocol enables the successful identification of protein interactors using only a short, in vitro synthesized RNA oligonucleotide. Moreover, the use of in silico designed RNA aptamers as PD probes21,22 guarantees specificity for the targets at significantly reduced costs.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>6-well tissue culture plates&#160;</td>
			<td>VWR</td>
			<td>10861-554</td>
			<td>CELLS</td>
		</tr>
		<tr>
			<td>Cell scrapers</td>
			<td>BIOSIGMA&#160;</td>
			<td>10153</td>
			<td>CELLS</td>
		</tr>
		<tr>
			<td>Dulbecco&#8242;s Modified Eagle&#8242;s Medium&#160; (DMEM)</td>
			<td>Thermo Fisher Scientfic</td>
			<td>11995065</td>
			<td>CELLS</td>
		</tr>
		<tr>
			<td>Fetal Bovine Serum, qualified, heat inactivated, Brazil</td>
			<td>Thermo Fisher Scientfic</td>
			<td>10500064</td>
			<td>CELLS</td>
		</tr>
		<tr>
			<td>Phosphate Buffer Saline (PBS, Waltham, MA)</td>
			<td>Thermo Fisher Scientfic</td>
			<td>14190169</td>
			<td>CELLS</td>
		</tr>
		<tr>
			<td>Trypsin (0.25%), phenol red</td>
			<td>Thermo Fisher Scientfic</td>
			<td>15050065</td>
			<td>CELLS</td>
		</tr>
		<tr>
			<td>Anti-rabbit IgG horseradish peroxidase (HRP)</td>
			<td>Cellsignal</td>
			<td>7070</td>
			<td>PD</td>
		</tr>
		<tr>
			<td>Biotinylated RNA</td>
			<td>Eurofins</td>
			<td>Custom RNA oligonucleotides</td>
			<td>PD</td>
		</tr>
		<tr>
			<td>Bovine serum albumin</td>
			<td>Sigma-Aldrich</td>
			<td>A9418</td>
			<td>PD</td>
		</tr>
		<tr>
			<td>Clarity Western ECL Substrate, 500 ml</td>
			<td>Biorad</td>
			<td>1705061</td>
			<td>PD</td>
		</tr>
		<tr>
			<td>cOmplete, EDTA-free Protease Inhibitor Cocktail</td>
			<td>Merck - Sigma Aldrich</td>
			<td>5056489001</td>
			<td>PD</td>
		</tr>
		<tr>
			<td>NuPAGE 4 to 12%, Bis-Tris, 1.0 mm, Mini Protein Gel, 10-well</td>
			<td>Invitrogen</td>
			<td>NP0321BOX</td>
			<td>PD</td>
		</tr>
		<tr>
			<td>Recombinant anti-TDP43 antibody</td>
			<td>Abcam</td>
			<td>ab109535</td>
			<td>PD</td>
		</tr>
		<tr>
			<td>Ribonucleic acid, transfer from baker&#39;s yeast (S.&#160;cerevisiae)</td>
			<td>Merck - Sigma Aldrich</td>
			<td>R5636-1ML</td>
			<td>PD</td>
		</tr>
		<tr>
			<td>Streptavidin Mag Sepharose</td>
			<td>Merck - Sigma Aldrich</td>
			<td>GE28-9857-99</td>
			<td>PD</td>
		</tr>
		<tr>
			<td>Trans-Blot Turbo RTA Mini 0.2 &#181;m PVDF Transfer Kit</td>
			<td>Biorad</td>
			<td>1704272</td>
			<td>PD</td>
		</tr>
		<tr>
			<td>Acetone</td>
			<td>Thermo Fisher Scientfic</td>
			<td>022928.K2</td>
			<td>MS</td>
		</tr>
		<tr>
			<td>C18 cartridge</td>
			<td>Thermo Fisher Scientfic</td>
			<td>13-110-018</td>
			<td>MS</td>
		</tr>
		<tr>
			<td>Dithiothreitol&#160; (DTT)</td>
			<td>Thermo Fisher Scientfic</td>
			<td>20290</td>
			<td>MS</td>
		</tr>
		<tr>
			<td>EASY-Spray HPLC Columns</td>
			<td>Thermo Scientific</td>
			<td>ES902</td>
			<td>MS</td>
		</tr>
		<tr>
			<td>iodoacetamide (IAA)&#160;</td>
			<td>Sigma Aldrich S.r.l.</td>
			<td>I6125</td>
			<td>MS</td>
		</tr>
		<tr>
			<td>Lys-C/Trypsin</td>
			<td>Promega</td>
			<td>V5073</td>
			<td>MS</td>
		</tr>
		<tr>
			<td>Trifluoroacetic acid (TFA)</td>
			<td>Thermo Fisher Scientfic</td>
			<td>28904</td>
			<td>MS</td>
		</tr>
		<tr>
			<td>Urea</td>
			<td>Thermo Fisher Scientfic</td>
			<td>J75826.A7</td>
			<td>MS</td>
		</tr>
		<tr>
			<td>Equipment</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>ChemiDoc imaging system</td>
			<td>Bio-Rad</td>
			<td></td>
			<td>CELLS</td>
		</tr>
		<tr>
			<td>Dyna Mag -2 , Magnetic rack</td>
			<td>Invitrogen</td>
			<td></td>
			<td>CELLS</td>
		</tr>
		<tr>
			<td>Forma Series 3 water jacketed C02 incubator</td>
			<td>Thermo Scientific</td>
			<td></td>
			<td>PD</td>
		</tr>
		<tr>
			<td>PROTEAN II xi cell , power supply for PAGE applications</td>
			<td>Bio-Rad</td>
			<td></td>
			<td>PD</td>
		</tr>
		<tr>
			<td>Rotating wheel, rotator SB3</td>
			<td>Stuart</td>
			<td></td>
			<td>PD</td>
		</tr>
		<tr>
			<td>Water bath set at 37 &#176;C</td>
			<td>VWR</td>
			<td></td>
			<td>PD</td>
		</tr>
		<tr>
			<td>XCell SureLock Mini-Cell electrophoresis system</td>
			<td>ThermoFisher Scientific</td>
			<td></td>
			<td>MS</td>
		</tr>
		<tr>
			<td>Easy-nLC 1200 UHPLC</td>
			<td>Thermo Scientific</td>
			<td></td>
			<td>MS</td>
		</tr>
		<tr>
			<td>Q exactive Mass Spectrometer</td>
			<td>Thermo Scientific</td>
			<td></td>
			<td>MS</td>
		</tr>
		<tr>
			<td>Software</td>
			<td>Version</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>MaxQuant</td>
			<td>2.0.3.0</td>
			<td></td>
			<td>MS</td>
		</tr>
		<tr>
			<td>Perseus</td>
			<td>1.6.14.0</td>
			<td></td>
			<td>MS</td>
		</tr>
	</tbody>
</table>

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.

To verify the validity of the proposed protocol, the PD experiments presented here were performed with a biotinylated RNA aptamer designed in silico to specifically bind TDP-4320. This RNA binds its protein target with high binding affinity (Kd = 90 nM)20. Here, this RNA, of sequence 5&#39;-CGGUGUUGCU-3&#39;, is referred to with the name &#34;+RNA&#34;. As a negative control, the reverse complementary sequence of +RNA, which is here called &#34;-RNA&#34;, was used. Its sequence is 5&#39;-AGCAACACCG-3&#39;. -RNA shows a significantly lower binding affinity toward TDP-43 (Kd = 1.5 &#181;M)19. For the purpose of the protocol described here, these RNA oligonucleotides have been purchased conjugated to a biotin molecule, to allow binding to the streptavidin beads. +RNA was purchased with a biotin-TEG at its 3&#39; end, which includes a 15-atom triethylene glycol spacer between the biotin and the phosphate group of the nucleic acid; -RNA instead had a biotin at its 5&#39; end, conjugated to the nucleic acid via an amino-C6 linker. However, if the design of the RNA bait is robust, and as long as there is no structural or chemical interference between the linker and the RNA, other positions for the biotin conjugation and other linker lengths could be employed.
Knowing the identity of the main protein to be found bound to the +RNA probe after the PD enabled the validation of the protocol by identification of TDP-43 in the eluate, using both mass spectrometry (MS) and western blot (WB) (Figure 1).
MS analysis was carried out on four PD replicates performed using either +RNA or -RNA (Figure 2). The identification of the interactomes of +RNA and -RNA is beyond the scope of this protocol, however some results that validate the accuracy of the protocol are reported. Of note, plotting the significantly enriched proteins in a volcano plot revealed that the total protein content and the enriched proteins eluted from +RNA was significantly higher that what was recovered from -RNA (Figure 2). This means that, despite having the same length and structural content (linear), +RNA can establish a higher number of specific interactions, which are retained up to the elution step with high salt. It is likely that -RNA instead establishes a higher number of nonspecific contacts that are disrupted during the washing steps. As expected, TDP-43 was identified as a unique interactor of +RNA20; the average label-free quantification (LFQ) for the four PD replicates performed with +RNA is 31.96 &#177; 0.56, while the protein is not identified among the interactors of -RNA. In addition, among all unique interactors of +RNA, TDP-43 was found to be the most abundantly enriched protein.
To further validate the protocol, the in-house algorithm catRAPID18,19 was used to computationally predict which other proteins would specifically bind either +RNA or -RNA. In particular, interaction scores for +RNA and -RNA with the proteins composing the human proteome were computed using the catRAPID &#39;interaction propensity&#39; feature, as defined in our previous work27. Among the proteins scored with high confidence, HNRNPH3 was predicted to bind selectively +RNA (+RNA interaction score = 1.01; -RNA interaction score = 0.21) and PCBP2 to interact specifically with -RNA (+RNA interaction score = -0.5; -RNA interaction score = 0.31) (Figure 3A). In addition, the protein RBM41 was predicted to be promiscuous for both RNA oligonucleotides (+RNA interaction score = 0.4; -RNA interaction score = 0.39) (Figure 3A). The MS analysis indeed confirmed the presence of HNRNPH3 and PCBP2 in the PD of +RNA and -RNA respectively, while RBM41 was found interacting with both (Figure 3B).
WB was used to detect the presence of TDP-43 to further confirm the results and during protocol optimization (Figure 4). In the procedure described here, different samples were collected at different stages. The input sample (IN) consisted of the total proteins diluted in lysis buffer. The flowthrough (FT) was obtained after an overnight incubation of the total proteins with the streptavidin beads pre-coated with the biotinylated RNA, representing the fraction of proteins that did not bind the RNA. Finally, the eluate (EL) contained all the proteins that recognized specifically the RNA under investigation, since between the FT and the EL steps three washing steps with 150 mM salt and 0.1% triton-X should have removed the weakest interactions.
For each replicate, the same amount (5% v/v) of IN, FT, and EL was run in parallel on an SDS-PAGE and stained with an anti-TDP-43 antibody (Figure 4). In the case of +RNA, the band of TDP-43 was observed in IN and in EL, indicating that the protein, present from the start in the total protein extract, is retained by +RNA during the washing steps and is only eluted at the end with a high salt buffer. TDP-43 was also present in IN for -RNA, however the band corresponding to the protein is also visible in FT, indicating that this RNA does not bind TDP-43. The absence of the TDP-43 band in EL confirms this result.
During the optimization of the protocol, the elution of the proteins specifically bound to the RNA sequences was probed both with an elution buffer containing 1 M NaCl (EB1) and with an elution buffer complete with 2 M NaCl (EB2) (Figure 4). Eluates obtained with either EB were compared on an SDS-PAGE and blotted with the anti-TDP-43 antibody. The images obtained were then analyzed with ImageJ28 to quantify any difference in TDP-43 amount eluted with the two buffers. Overall, no significant difference was observed, and we concluded that, within these assays, 1 M salt is sufficient to disrupt even the strongest protein-RNA interactions.
Overall, the results reported here for MS and WBs demonstrate that this protocol is efficient in capturing the protein interactors of a given RNA in a specific manner, and that it enables the elution in buffers compatible with downstream analysis.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/64923/64923fig01.jpg" /> 
Figure 1: Sketch of the experimental pipeline used in the proposed protocol. (A) The biotinylated RNA oligonucleotide is prepared in lysis buffer at the appropriate concentration. (B) Magnetic streptavidin beads are washed, blocked with yeast tRNA, and loaded with the biotinylated RNA. (C) Total protein extract derived from cultured mammalian cell lines are added to the beads-RNA mixture. (D) Multiple washes are performed to remove nonspecific interactions. (E) The specific protein interactors are detached from the RNA with a hypertonic solution. (F) The identity of the interactors is revealed by mass spectrometry, and specific cases are validated by western blot. <a href="https://www.jove.com/files/ftp_upload/64923/64923fig01large.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/64923/64923fig02.jpg" /> 
Figure 2: Analytical strategy for label-free MS-based protein quantification. (A) Eluted proteins are precipitated in cold acetone overnight. Proteins are then denatured, and an in-solution digestion is performed. Proteolytic peptides are concentrated and desalted. (B) Peptides are analyzed via LC-MS/MS using a &#34;shotgun approach&#34;. (C) Raw data processing and analysis is performed using MaxQuant and Perseus software, respectively. (D) Statistically significant enriched proteins are displayed in a volcano plot. <a href="https://www.jove.com/files/ftp_upload/64923/64923fig02large.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/64923/64923fig03.jpg" /> 
Figure 3: Correlation between predicted interaction propensities and experimentally determined interactions of +RNA and -RNA. (A) catRAPID interaction scores relative to HNRNPH3, PCBP2, and RBM41, indicating preferential binding of HNRNPH3 for +RNA and of PCBP2 for -RNA, while RBM41 is predicted to indiscriminately bind both RNA sequences. (B)&#160;Label-free quantification averages determined by mass-spectrometry analysis from the pull-downs performed with +RNA and -RNA. The analysis confirms that HNRNPH3 solely binds +RNA, PCBP2 solely binds -RNA, and RBM41 binds both equally. <a href="https://www.jove.com/files/ftp_upload/64923/64923fig03large.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/64923/64923fig04.jpg" /> 
Figure 4: Western blot validation of the presence/absence of TDP-43 among the interactors of chosen RNA sequences. The WB membrane has been treated with anti-TDP-43 antibody. IN = input; FT = flow-through; EL (EB1) = elution with elution buffer 1; EL (EB2) = elution with elution buffer 2; the sign &#34;+&#34; indicates samples derived from the pull-down performed with +RNA; the sign &#34;-&#34; indicates samples derived from the pull-down performed with -RNA; lane 1 contains a protein ladder. TDP-43 is indicated by an arrow. The WB indicates that TDP-43 is found among +RNA interactors but not among -RNA interactors. <a href="https://www.jove.com/files/ftp_upload/64923/64923fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td colspan="3">Buffer Name</td>
			<td colspan="3">Composition</td>
			<td></td>
		</tr>
		<tr>
			<td colspan="3">10x Tranfer buffer</td>
			<td colspan="3">250 mM tris, 1.92 M glycine, 1% SDS, 20% methanol. Dilute 10 folds prior use</td>
			<td rowspan="9">PD</td>
		</tr>
		<tr>
			<td colspan="3">20X MES SDS running buffer</td>
			<td colspan="3">1 M MES, 1 M tris, 2% SDS , 20 mM EDTA. Adjust pH to 7.3. Dilute 20 folds prior use</td>
		</tr>
		<tr>
			<td colspan="3">4x Sample loading buffer</td>
			<td colspan="3">0.25 M Tris base, 0.28 M SDS, 40% glycerol, 20% 2-mercapto-ethanol, 4 mg/ml bromphenol blue</td>
		</tr>
		<tr>
			<td colspan="3">Elution buffer 1</td>
			<td colspan="3">20 mM phosphate pH 7.5, 1 M NaCl, 0.5 mM EDTA, 0.1 % Triton X-100, 1 mM DTT (to be added after quantification)&#160;</td>
		</tr>
		<tr>
			<td colspan="3">Elution buffer 2</td>
			<td colspan="3">20 mM phosphate pH 7.5, 2 M NaCl, 0.5 mM EDTA, 0.1 % Triton X-100, 1 mM DTT (to be added after quantification)</td>
		</tr>
		<tr>
			<td colspan="3">Lysis buffer</td>
			<td colspan="3">10 mM Tris-HCl pH 7.4, 150 mM NaCl, 0.5 mM EDTA, 0.1 % Triton X-100, 1 mM DTT and protease inhibitors&#160;</td>
		</tr>
		<tr>
			<td colspan="3">Tris-buffered saline with Tween-20</td>
			<td colspan="3">1 M Tris-HCl pH 7.4, 3 M NaCl, 2.0% Tween-20</td>
		</tr>
		<tr>
			<td colspan="3">Wash buffer 1</td>
			<td colspan="3">10 mM Tris-HCl pH 7.4, 150 mM NaCl, 0.5 mM EDTA, 0.1 % Triton TM X-100, 1 mM DTT and protease inhibitors</td>
		</tr>
		<tr>
			<td colspan="3">Wash buffer 2&#160;</td>
			<td colspan="3">25 mM Hepes pH 8, 150 mM NaCl, 0.5 mM EDTA, 0.1 % Triton X-100, 1 mM DTT and protease inhibitors&#160;</td>
		</tr>
		<tr>
			<td colspan="3">Buffer A&#160;</td>
			<td colspan="3">0.1% formic acid&#160;</td>
			<td rowspan="3">MS</td>
		</tr>
		<tr>
			<td colspan="3">Buffer B&#160;</td>
			<td colspan="3">60% acetonitrile, 0.1% formic acid</td>
		</tr>
		<tr>
			<td colspan="3">Denaturation buffer&#160;</td>
			<td colspan="3">8M urea, 50 mM Tris-HCl</td>
		</tr>
	</tbody>
</table>
Table 1:&#160;PD and MS buffers. Names and composition of the buffers used for either the pull-down experiments (PD) or for the mass-spectrometry analysis (MS).

Watch this Scientific Journal Video about An Optimized Quantitative Pull-Down Analysis of RNA-Binding Proteins Using Short Biotinylated RNA at JoVE.com

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

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 ...

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JoVE Journal

Biochemistry

3.0K Views.  Italian Institute of Technology (IIT). 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. 

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

Isolation of High-density Lipoproteins for Non-coding Small RNA Quantification

The diversity of small non-coding RNAs (sRNA) is rapidly expanding and their roles in biological processes, including gene regulation, are emerging. Most interestingly, sRNAs are also found outside of cells and are stably present in all biological fluids. As such, extracellular sRNAs represent a novel class of disease biomarkers and are likely involved in cell signaling and intercellular communication networks. To assess their potential as biomarkers, sRNAs can be quantified in plasma, urine, and other fluids. Nevertheless, to fully understand the impact of extracellular sRNAs as endocrine signals, it is important to determine which carriers are transporting and protecting them in biological fluids (e.g., plasma), which cells and tissues contribute to extracellular sRNA pools, and cells and tissues capable of accepting and utilizing extracellular sRNA. To accomplish these goals, it is critical to isolate highly pure populations of extracellular carriers for sRNA profiling and quantification. We have previously demonstrated that lipoproteins, particularly high-density lipoproteins (HDL), transport functional microRNAs (miRNA) between cells and HDL-miRNAs are significantly altered in disease. Here, we detail a new protocol that utilizes tandem HDL isolation with density-gradient ultracentrifugation (DGUC) and fast-protein-liquid chromatography (FPLC) to obtain highly pure HDL for downstream profiling and quantification of all sRNAs, including miRNAs, using both high-throughput sequencing and real-time PCR approaches. This protocol will be a valuable resource for the investigation of sRNAs on HDL.

This protocol describes the isolation and quantification of high-density lipoprotein small RNAs.

The diversity of small non-coding RNAs (sRNA) is rapidly expanding and their roles in biological processes, including gene regulation, are emerging. Most ...

An Optimized Protocol for Electrophoretic Mobility Shift Assay Using Infrared Fluorescent Dye-labeled Oligonucleotides

Electrophoretic Mobility Shift Assays (EMSA) are an instrumental tool to characterize the interactions between proteins and their target DNA sequences. Radioactivity has been the predominant method of DNA labeling in EMSAs. However, recent advances in fluorescent dyes and scanning methods have prompted the use of fluorescent tagging of DNA as an alternative to radioactivity for the advantages of easy handling, saving time, reducing cost, and improving safety. We have recently used fluorescent EMSA (fEMSA) to successfully address an important biological question. Our fEMSA analysis provides mechanistic insight into the effect of a missense mutation, G73E, in the highly conserved HMG transcription factor SOX-2 on olfactory neuron type diversification. We found that mutant SOX-2G73E protein alters specific DNA binding activity, thereby causing olfactory neuron identity transformation. Here, we present an optimized and cost-effective step-by-step protocol for fEMSA using infrared fluorescent dye-labeled oligonucleotides containing the LIM-4/SOX-2 adjacent target sites and purified SOX-2 proteins (WT and mutant SOX-2G73E proteins) as a biological example.

We describe here an optimized protocol of fluorescent Electrophoretic Mobility Shift Assays (fEMSA) using purified SOX-2 proteins together with infrared fluorescent dye-labeled DNA probes as a case study to tackle an important biological question.

Electrophoretic Mobility Shift Assays (EMSA) are an instrumental tool to characterize the interactions between proteins and their target DNA sequences. ...

An Efficient Method for the Isolation of Highly Purified RNA from Seeds for Use in Quantitative Transcriptome Analysis

Plant seeds accumulate large amounts of storage reserves comprising biodegradable organic matter. Humans rely on seed storage reserves for food and as industrial materials. Gene expression profiles are powerful tools for investigating metabolic regulation in plant cells. Therefore, detailed, accurate gene expression profiles during seed development are required for crop breeding. Acquiring highly purified RNA is essential for producing these profiles. Efficient methods are needed to isolate highly purified RNA from seeds. Here, we describe a method for isolating RNA from seeds containing large amounts of oils, proteins, and polyphenols, which have inhibitory effects on high-purity RNA isolation. Our method enables highly purified RNA to be obtained from seeds without the use of phenol, chloroform, or additional processes for RNA purification. This method is applicable to Arabidopsis, rapeseed, and soybean seeds. Our method will be useful for monitoring the expression patterns of low level transcripts in developing and mature seeds.

We have succeeded in establishing a method for RNA isolation from plant seeds containing large amounts of oils, proteins, and polyphenols, which have inhibitory effects on high-purity RNA isolation. Our method is suitable for monitoring the expression of genes with low level transcripts in seeds.

Plant seeds accumulate large amounts of storage reserves comprising biodegradable organic matter. Humans rely on seed storage reserves for food and as ...

Purification of Biotinylated Cell Surface Proteins from Rhipicephalus microplus Epithelial Gut Cells

Rhipicephalus microplus &#8211; the cattle tick &#8211; is the most significant ectoparasite in terms of economic impact on livestock as a vector of several pathogens. Efforts have been dedicated to the cattle tick control to diminish its deleterious effects, with focus on the discovery of vaccine candidates, such as BM86, located on the surface of the tick gut epithelial cells. Current research focuses upon the utilization of cDNA and genomic libraries, to screen for other vaccine candidates. The isolation of tick gut cells constitutes an important advantage in investigating the composition of surface proteins upon the tick gut cells membrane. This paper constitutes a novel and feasible method for the isolation of epithelial cells, from the tick gut contents of semi-engorged R. microplus. This protocol utilizes TCEP and EDTA to release the epithelial cells from the subepithelial support tissues and a discontinuous density centrifugation gradient to separate epithelial cells from other cell types. Cell surface proteins were biotinylated and isolated from the tick gut epithelial cells, using streptavidin-linked magnetic beads allowing for downstream applications in FACS or LC-MS/MS-analysis.

Purification of Biotinylated Cell Surface Proteins from Rhipicephalus microplus Epithelial Gut Cells

A modified density centrifugation gradient-based methodology was utilized to isolate epithelial cells from Rhipicephalus microplus gut tissue. Surface-bound proteins were biotinylated and purified through streptavidin magnetic beads for utilization in downstream applications.

Rhipicephalus microplus &#8211; the cattle tick &#8211; is the most significant ectoparasite in terms of economic impact on livestock as a vector of ...

Optimized Protocol for the Extraction of Proteins from the Human Mitral Valve

Analysis of the cellular proteome can help to elucidate the molecular mechanisms underlying diseases due to the development of technologies that permit the large-scale identification and quantification of the proteins present in complex biological systems.The knowledge gained from a proteomic approach can potentially lead to a better understanding of the pathogenic mechanisms underlying diseases, allowing for the identification of novel diagnostic and prognostic disease markers, and, hopefully, of therapeutic targets. However, the cardiac mitral valve represents a very challenging sample for proteomic analysis because of the low cellularity in proteoglycan and collagen-enriched extracellular matrix. This makes it challenging to extract proteins for a global proteomic analysis. This work describes a protocol that is compatible with subsequent protein analysis, such as quantitative proteomics and immunoblotting. This can allow for the correlation of data concerning protein expression with data on quantitative mRNA expression and non-quantitative immunohistochemical analysis. Indeed, these approaches, when performed together, will lead to a more comprehensive understanding of the molecular mechanisms underlying diseases, from mRNA to post-translational protein modification. Thus, this method can be relevant to researchers interested in the study of cardiac valve physiopathology.

The protein composition of the human mitral valve is still partially unknown, because its analysis is complicated by low cellularity and therefore by low protein biosynthesis. This work provides a protocol to efficiently extract protein for the analysis of the mitral valve proteome.

Analysis of the cellular proteome can help to elucidate the molecular mechanisms underlying diseases due to the development of technologies that permit ...

Sample Preparation for Mass Spectrometry-based Identification of RNA-binding Regions

Noncoding RNAs play important roles in several nuclear processes, including regulating gene expression, chromatin structure, and DNA repair. In most cases, the action of noncoding RNAs is mediated by proteins whose functions are in turn regulated by these interactions with noncoding RNAs. Consistent with this, a growing number of proteins involved in nuclear functions have been reported to bind RNA and in a few cases the RNA-binding regions of these proteins have been mapped, often through laborious, candidate-based methods.
Here, we report a detailed protocol to perform a high-throughput, proteome-wide unbiased identification of RNA-binding proteins and their RNA-binding regions. The methodology relies on the incorporation of a photoreactive uridine analog in the cellular RNA, followed by UV-mediated protein-RNA crosslinking, and mass spectrometry analyses to reveal RNA-crosslinked peptides within the proteome. Although we describe the procedure for mouse embryonic stem cells, the protocol should be easily adapted to a variety of cultured cells.

We describe a protocol to identify RNA-binding proteins and map their RNA-binding regions in live cells using UV-mediated photocrosslinking and mass spectrometry.

Noncoding RNAs play important roles in several nuclear processes, including regulating gene expression, chromatin structure, and DNA repair. In most ...

Capture and Identification of RNA-binding Proteins by Using Click Chemistry-assisted RNA-interactome Capture (CARIC) Strategy

A comprehensive identification of RNA-binding proteins (RBPs) is key to understanding the posttranscriptional regulatory network in cells. A widely used strategy for RBP capture exploits the polyadenylation [poly(A)] of target RNAs, which mostly occurs on eukaryotic mature mRNAs, leaving most binding proteins of non-poly(A) RNAs unidentified. Here we describe the detailed procedures of a recently reported method termed click chemistry-assisted RNA-interactome capture (CARIC), which enables the transcriptome-wide capture of both poly(A) and non-poly(A) RBPs by combining the metabolic labeling of RNAs, in vivo UV cross-linking, and bioorthogonal tagging.

Capture and Identification of RNA-binding Proteins by Using Click Chemistry-assisted RNA-interactome Capture CARIC Strategy

A detailed protocol for applying the click chemistry-assisted RNA-interactome capture (CARIC) strategy to identify proteins binding to both coding and noncoding RNAs is presented.

A comprehensive identification of RNA-binding proteins (RBPs) is key to understanding the posttranscriptional regulatory network in cells. A widely used ...

PeptiQuick, a One-Step Incorporation of Membrane Proteins into Biotinylated Peptidiscs for Streamlined Protein Binding Assays

Membrane proteins, including transporters, channels, and receptors, constitute nearly one-fourth of the cellular proteome and over half of current drug targets. Yet, a major barrier to their characterization and exploitation in academic or industrial settings is that most biochemical, biophysical, and drug screening strategies require these proteins to be in a water-soluble state. Our laboratory recently developed the peptidisc, a membrane mimetic offering a &#8220;one-size-fits-all&#8221; approach to the problem of membrane protein solubility. We present here a streamlined protocol that combines protein purification and peptidisc reconstitution in a single chromatographic step. This workflow, termed PeptiQuick, allows for bypassing dialysis and incubation with polystyrene beads, thereby greatly reducing exposure to detergent, protein denaturation, and sample loss. When PeptiQuick is performed with biotinylated scaffolds, the preparation can be directly attached to streptavidin-coated surfaces. There is no need to biotinylate or modify the membrane protein target. PeptiQuick is showcased here with the membrane receptor FhuA and antimicrobial ligand colicin M, using biolayer interferometry to determine the precise kinetics of their interaction. It is concluded that PeptiQuick is a convenient way to prepare and analyze membrane protein-ligand interactions within one&#160;day in a detergent-free environment.

We present a method that combines membrane protein purification and reconstitution into peptidiscs in a single chromatographic step. Biotinylated scaffolds are used for direct surface attachment and measurement of protein-ligand interactions via biolayer interferometry.

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Ubiquitin Chain Analysis by Parallel Reaction Monitoring

Assessment of the global profile of ubiquitin chain topologies within a proteome is of interest to answer a wide range of biological questions. The protocol outlined here takes advantage of the di-glycine (-GG) modification left after the tryptic digestion of ubiquitin incorporated in a chain. By quantifying these topology-characteristic peptides the relative abundance of each ubiquitin chain topology can be determined. The steps required to quantify these peptides by a parallel reaction monitoring experiment are reported taking into consideration the stabilization of ubiquitin chains. Preparation of heavy controls, cell lysis, and digestion are described along with the appropriate mass spectrometer setup and data analysis workflow. An example data set with perturbations in ubiquitin topology is presented, accompanied by examples of how optimization of the protocol can affect results. By following the steps outlined, a user will be able to perform a global assessment of the ubiquitin topology landscape within their biological context.

This method describes the assessment of global changes in ubiquitin chain topology. The assessment is performed by the application of a mass spectrometry-based targeted proteomics approach.

Assessment of the global profile of ubiquitin chain topologies within a proteome is of interest to answer a wide range of biological questions. The ...

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.