This work was supported by MIUR (Ministero Universit&#224; Ricerca, PRIN 2017 to MG) and by POR Calabria FESR 2014-2020, action 1.2.2, &#34;INNOPROST&#34;.

The study was approved by the Institutional Ethical Committee of the Magna Graecia University of Catanzaro, RP 41/2018. Written informed consent was obtained from all patients enrolled in the study.
1. Sample preparation
<ol>
	<li>Centrifuge EPS-urine samples within 2 h of collection at 2,100 x g for 10 minutes at room temperature (RT). Store the supernatant at -80 &#176;C until use.</li>
</ol>
2. Sample thawing
<ol>
	<li>Transfer the sample from -80 &#176;C to -20 &#176;C the day before digestion.</li>
	<li>Prior to sample processing, transfer the sample for 15-20 minutes at 4 &#176;C and then at RT.</li>
</ol>
3. Reagent preparation for FASP
<ol>
	<li>On the same day, prepare the following solutions: urea buffer, 50 mM iodoacetamide (IAA) in urea buffer, 50 mM triethylammonium bicarbonate and 500 mM dithiothreitol (DTT).</li>
	<li>Prepare urea buffer (urea 8 M, 100 mM Tris-HCl pH 8): for 10 mL, weigh 4,800 mg of urea and dissolve it in the appropriate amount of HPLC water after adding 1 mL of 1 M Tris pH 8. A volume of 800 &#181;L of urea is needed for each sample.</li>
	<li>Prepare 500 mM dithiothreitol (DTT): dissolve 38.5 mg of DTT in 500 &#181;L of HPLC water. For each sample, 66.7 &#181;L of DTT are needed.</li>
	<li>Prepare 50 mM IAA in Urea Buffer: dissolve 9.25 mg of IAA in 1 mL of urea buffer. For each sample 50 &#181;L of IAA are needed.</li>
	<li>Prepare 50 mM triethylammonium bicarbonate (TEAB). Add 150 &#181;L of 1 M TEAB to 2.85&#160;mL of HPLC water. For each sample 460 &#181;L of TEAB are needed.</li>
	<li>Prepare a solution of trypsin (100 ng/&#181;L) in HPLC water. This solution can be stored at -80 &#176;C and thawed immediately before use. For each sample, 2 &#181;L (200 ng) are needed.</li>
</ol>
4. Protein digestion by FASP
<ol>
	<li>Dilute 500 &#181;L of each EPS-urine sample with 66.7 &#181;L of 10% (w/v) sodium dodecyl sulfate (SDS), 66.7 &#181;L of 500 mM DTT and 33.3 &#181;L of 1 M Tris pH 8 to solubilize proteins and to reduce disulphide bonds. Incubate 10 minutes at 95 &#176;C with gentle shaking.</li>
	<li>Add 300 &#181;L of diluted EPS-urine sample on the filter unit (10 kDa) and centrifuge at 14,000 x g for 20 minutes.</li>
	<li>Add 200 &#181;L of urea buffer to the filter and centrifuge at 14,000 x g for 15 minutes. Repeat this step and then discard the flow-through.</li>
	<li>Add 50 &#181;L of IAA solution and centrifuge at 6,000 x g for 25 minutes.</li>
	<li>Add 200 &#181;L of urea buffer and centrifuge at 14,000 x g for 20 minutes. Repeat this step and then discard the flow-through.</li>
	<li>Add 200 &#181;L of 50 mM triethylammonium bicarbonate buffer (TEAB) and centrifuge at 14,000 x g for 20 minutes. Repeat this step.</li>
	<li>Transfer the filter unit into a new collection tube.</li>
	<li>Add 60 &#181;L of 50 mM TEAB buffer and 200 ng of trypsin and incubate the sample in a thermo-mixer at 37 &#176;C overnight. 
	NOTE: To avoid sample evaporation during overnight incubation, wrap each filter unit with a layer of aluminum foil and then a layer of parafilm.</li>
	<li>After trypsin incubation, add 140 &#181;L of water and centrifuge the vial at 14,000 x g for 25 minutes to collect the volume of digest (180-200 &#181;L).</li>
</ol>
5. Reagent preparation for SCX purification
<ol>
	<li>Prepare 1 mL of wash 1 (0.5% formic acid (FA) and 20% acetonitrile (ACN)) as follows: add 50 &#181;L of 10% FA and 200 &#181;L of 100% ACN to 750 &#181;L of HLPC water. For each sample, 100 &#181;L of wash 1 are needed.</li>
	<li>Prepare 1.5 mL of wash 2 (0.5% FA and 80% of ACN) as follows: add 75 &#181;L of 10 % FA and 1.2 mL of 100% ACN to 225 &#181;L of HPLC water. For each sample 190 &#181;L of wash 2 are needed.</li>
	<li>Prepare 100 &#181;L of eluting solution (500 mM ammonium acetate (AA) and 20% of ACN): add 25 &#181;L of 2 M AA and 20 &#181;L of 100% ACN to 55 &#181;L of HPLC water.</li>
	<li>Prepare StageTips as follows.
	<ol>
		<li>Pack a 200 &#181;L pipette tip with a layer of SCX resin using a blunt-ended syringe needle (gauge 16). Insert the StageTip into a microcentrifuge lid that has been previously pierced in order to accommodate the microcolumn.</li>
		<li>Assemble the lid onto a 2 mL microcentrifuge from which the original lid was removed. The micro-SPE centrifugal device just assembled should fit into a benchtop centrifuge. Since perforated lids are tedious to prepare, they can be utilized multiple times.</li>
	</ol>
	</li>
</ol>
6. SCX purification
<ol>
	<li>Dilute 30 &#181;L of each sample to 120 &#181;L using wash 2.</li>
	<li>Condition the StageTip by adding 50 &#181;L of wash 1 on top of the extraction resin and centrifuge at 400 x g for 2 minutes. Since flow resistance depends on how strongly the extraction resin was packed into the pipette tip, centrifuge speed may need to be adjusted in order to obtain a flow rate of 20-30 &#181;L/min. Try not to leave the tip dry during sample loading and washing.</li>
	<li>Equilibrate the StageTip with 50 &#181;L of wash 2 and centrifuge at 400 x g for 2 minutes.</li>
	<li>Load the diluted sample (120 &#181;L) using a lower spin speed.</li>
	<li>Wash the StageTip with 50 &#181;L of wash 2 and centrifuge at 400 x g for 2 minutes. Repeat with 50 &#181;L of wash 1. 
	NOTE: After this wash the resin must be completely dry.</li>
	<li>Elute peptide mixture with 7 &#181;L of eluate solution (500 mM ammonium acetate (AA) and 20% of ACN) slowly using a lower spin speed.</li>
	<li>Add 27 &#181;L of 0.1% FA to dilute AA and to obtain a sample for LC-MS/MS preliminary injection. The final dilution to 34 &#181;L will result into a 1:1 volumetric ratio between urine and peptide solution (1 &#181;L of purified digest will correspond to 1 &#181;L of original urine sample).</li>
</ol>
7. Protein quantification by external standard using DDA analysis (Figure 2)
<ol>
	<li>Determine protein amount in samples by injecting 2 &#181;L of the resulting peptide digest in LC-MS/MS and interpolating the resulting total peptide area with a calibration curve built as follows:</li>
	<li>Prepare five different HeLa digest solutions (1 ng/&#181;L, 2.5 ng/&#181;L, 7.5 ng/&#181;L, 25 ng/&#181;L, 75 ng/&#181;L) using a HeLa digest stock (100 &#181;g/&#181;L).</li>
	<li>Inject each Hela solution in duplicate (2 &#181;L).</li>
	<li>Set the LC-MS/MS method.
	<ol>
		<li>Inject 2 &#181;L of the five HeLa peptide mixtures and separate peptides through a linear gradient of 75 minutes at a flow rate of 230 nL/minute on a 15 cm, 75 &#181;m i.d column packed with 3 &#181;m C18 silica particles. Use a binary gradient constituted by mobile phase A (0.1% FA, 2% ACN) and mobile phase B (0.1% FA and 80% of ACN).</li>
		<li>Perform gradient elution by increasing mobile phase B content from 6% to 42% in 60 minutes and from 42% to 100% in additional 8 minutes. Maintain for 5 minutes 100% B and then move back to 0% B in two minutes.</li>
		<li>Operate in DDA mode using a top-12 method and set MS full scan range at 350-1800 m/z, resolution 70,000, ACG target 1e6 and maximum injection time 50 ms. Set the mass window for precursor ion isolation at 1.6 m/z, resolution 35,000, ACG target 1e5, maximum injection time 120 ms, HCD fragmentation at of 25 NCE (normalized collision energy) and dynamic exclusion 15 seconds.</li>
	</ol>
	</li>
	<li>Analyze raw files using Sequest as search engine, and the HUMAN Uniprot Complete protein sequence as the database. In the experiments presented here, the database was downloaded on March 2016 and contained 42.013 sequences.
	<ol>
		<li>Use the following settings: MS tolerance 15 ppm, MS/MS tolerance 0.02 Da, trypsin as enzyme by setting two missed cleavage sites. Set the carbamidomethylation of lysine, serine, threonine, tyrosine (+57.021) and the oxidation of methionines as dynamic modifications and the carbamidomethylation of cysteines (+57.021) as static modifications. Use the cut-off of false discovery rate (FDR) for peptides and proteins identification to 0.01 and filter out by percolator.</li>
		<li>Calculate the peak area for all MS1 peptide signals. Calculate the total area of the peptides.</li>
	</ol>
	</li>
	<li>Inject 2 &#181;L of peptide mixtures obtained from EPS-urine samples using the same LC-MS/MS method used for the HeLa samples and analyze the raw file using the same parameters used for HeLa data processing.</li>
	<li>Calculate total intensity of peptide signals by summing up area values of all identified peptides and interpolate the external standard curve. This will provide an acceptable estimation of peptide amount present in the EPS-urine protein digest.</li>
</ol>
8. Reagent preparation for C18 StageTip protocol
<ol>
	<li>Prepare 500 &#181;L of solution A (0.1% Trifluoroacetic acid (TFA), 50% ACN): add 250 &#181;L of 100% ACN and 10 &#181;L of 5% TFA to 240 &#181;L of HPLC water.</li>
	<li>Prepare 2 mL of solution B (0.1 % TFA): add 40 &#181;L of 5% TFA to 1960 &#181;L of HPLC water.</li>
	<li>Prepare 100 &#181;L of eluting solution (0.1% FA, 50% ACN): add 1 &#181;L of 10% FA and 50 &#181;L of 100% ACN to 49 &#181;L of HPLC water.</li>
	<li>Prepare StageTips as previously described. In this case, C18 extraction disks are used.</li>
</ol>
9. SCX/C18 StageTip protocol
NOTE: Purify EPS-urine digests by C18 StageTip protocol to remove salts.
<ol>
	<li>Start from 2 &#181;g of peptides (as quantified by the preliminary injection). Dilute the digest solution 4-fold in wash 2 SCX and proceed as described above (in section &#34;SCX purification&#34;). Elute the peptide mixture with 7 &#181;L of eluate solution (500 mM ammonium acetate (AA) and 20% of ACN) slowly using a lower spin speed (5 &#181;L/min flow rate).</li>
	<li>Acidify the SCX eluate with 150 &#181;L of 0.1% of trifluoroacetic acid (TFA) in order to achieve a pH lower than 3 and a concentration of organic solvent below 5%.</li>
	<li>Condition the C18 StageTip with 50 &#181;L of solution A and centrifuge at 400 x g for 2 minutes. Equilibrate C18 StageTip with 50 &#181;L of solution B and centrifuge at 400 x g for 2 minutes.</li>
	<li>Load the sample on the stage-tip slowly using a lower spin speed.</li>
	<li>Wash C18 StageTip with 50 &#181;L of solution B and centrifuge.</li>
	<li>Slowly elute the peptide mixture with 10 &#181;L of elution solution using a lower spin speed.</li>
	<li>Dry the eluate (10 &#181;L) at 30 &#176;C in in a vacuum centrifuge for 3 minutes. Add 47 &#181;L of 0.1% FA. Expected peptide concentration will be 40 ng/ &#181;L. Analyze by LC-MS/MS in DIA mode.</li>
</ol>
10. DIA Analysis (Figure 3)
<ol>
	<li>nanoLC separation: Separate the peptide mixture using a linear gradient of 140 minutes at a flow rate of 230 nL/min on a 15 cm, 75 &#181;m ID column packed with 3 &#181;m C18 silica particles.
	<ol>
		<li>Perform gradient elution at 230 nL/minute flow rate and increase mobile phase B content from 3% to 25% in 90 minutes, then from 25% to 40% in 30 minutes and finally from 40% to 100% in 8 minutes.</li>
		<li>After 10 minutes at 100% B, equilibrate the column with mobile phase A for 15 min.</li>
	</ol>
	</li>
	<li>Mass spectrometric parameters: perform DIA analysis using a method employing the following scan cycle: (i) a full scan MS event at a resolution of 17,500 (AGC target 1e6, maximum injection time 50 ms) followed by (ii) 20 windows at 20 m/z isolation width, starting from m/z 350, (ii) 5 windows at 50 m/z isolation width and (iv) 1 window at 200 m/z isolation width, ending the scan range of DIA at 1200 m/z. Perform DIA scans at resolution 35,000 (AGC target 5e5, maximum injection time 120 ms and 25 NCE).</li>
</ol>
11. High- pH reversed phase C18 fractionation for library generation
NOTE: Pool EPS-urine representative samples in an amount of higher than 10 &#181;g in order to build a data-dependent library for DIA analysis by the following procedure:
<ol>
	<li>Acidify the peptide mixture (11 &#181;g) by 0.2% of TFA and load the resulting solution onto a C18 StageTip packed with two layers of extraction disks to allow higher capacity. We estimated the loading capacity of a single micro disk (from a 16 gauge syringe needle) to be in the 5-10 &#181;g range.</li>
	<li>Condition and equilibrate stationary phase as already described for C18 purification.</li>
	<li>Carry out peptide fractionation by stepwise elution (n=10) from high pH reversed phase C18 using elution solutions containing 0.2% of ammonium hydroxide, 10 mM TEAB, and increasing v/v concentrations of ACN (4%, 8%, 12%, 16%, 20%, 24%, 28%, 32%, 40%, 80%).</li>
	<li>Analyze the 10 fractions using the same chromatographic parameters of the DIA method. Operate the mass spectrometer in DDA mode using the settings previously adopted for the preliminary analysis (see &#34;Protein quantification by external standard using DDA analysis&#34;).</li>
</ol>
12. Data analysis
<ol>
	<li>Generate the spectral library by importing the protein identification results obtained from the DDA LC-MS/MS experiments of high-reversed phase C18 fractionation in a software dedicated to DIA analysis.</li>
	<li>Set the minimum and maximum number of fragment ions used for identification and quantification to 3 and 6, respectively. Filter the obtained results by a Q-value of 0.01.</li>
	<li>Import DIA raw files and associate to each raw file the same FASTA file used for creating the spectral library.</li>
	<li>Set the minimum and maximum number of unique peptides used for protein quantification to 1 and 10, respectively.</li>
	<li>Calculate the intensity for each protein by summing fragment ion peak area.</li>
	<li>Generate a matrix with the intensity of the quantified proteins in each sample.</li>
</ol>

<ol>
	<li>H&#252;ttenhain, R., Soste, M., Selevsek, 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=Reproducible+quantification+of+cancer-associated+proteins+in+body+fluids+using+targeted+proteomics.">Reproducible quantification of cancer-associated proteins in body fluids using targeted proteomics.</a> Sci Transl Med. 4 (142), 10 (2013).</li><li>Roobol, M. J., Carlsson, S. V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Risk+stratification+in+prostate+cancer+screening.">Risk stratification in prostate cancer screening.</a> Nature Reviews Urology. 10 (1), 38-48 (2013).</li><li>Principe, 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=Identification+of+prostate-enriched+proteins+by+in-depth+proteomic+analyses+of+expressed+prostatic+secretions+in+urine.">Identification of prostate-enriched proteins by in-depth proteomic analyses of expressed prostatic secretions in urine.</a> Journal of Proteome Research. 11 (4), 2386-2396 (2012).</li><li>Kim, 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=Targeted+proteomics+identifies+liquid-biopsy+signatures+for+extracapsular+prostate+cancer.">Targeted proteomics identifies liquid-biopsy signatures for extracapsular prostate cancer.</a> Nature Communications. 7, 1-10 (2016).</li><li>Drake, R. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Clinical+collection+and+protein+properties+of+expressed+prostatic+secretions+as+a+source+for+biomarkers+of+prostatic+disease.">Clinical collection and protein properties of expressed prostatic secretions as a source for biomarkers of prostatic disease.</a> Journal of Proteomics. 72 (6), 907-917 (2009).</li><li>Macklin, A., Khan, S., Kislinger, T. <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+mass+spectrometry+based+clinical+proteomics:+Applications+to+cancer+research.">Recent advances in mass spectrometry based clinical proteomics: Applications to cancer research.</a> Clinical Proteomics. 17 (1), 1-25 (2020).</li><li>Berger, S. T., 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=MStern+blotting-high+throughput+polyvinylidene+fluoride+(PVDF)+membrane-based+proteomic+sample+preparation+for+96-well+plates.">MStern blotting-high throughput polyvinylidene fluoride (PVDF) membrane-based proteomic sample preparation for 96-well plates.</a> Molecular and Cellular Proteomics. 14 (10), 2814-2823 (2015).</li><li>Zougman, A., Selby, P. J., Banks, R. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Suspension+trapping+(STrap)+sample+preparation+method+for+bottom-up+proteomics+analysis.">Suspension trapping (STrap) sample preparation method for bottom-up proteomics analysis.</a> Proteomics. 14 (9), 1006 (2014).</li><li>Hughes, C. 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=Ultrasensitive+proteome+analysis+using+paramagnetic+bead+technology.">Ultrasensitive proteome analysis using paramagnetic bead technology.</a> Molecular Systems Biology. 10 (10), 757 (2014).</li><li>Kulak, N. A., Pichler, G., Paron, I., Nagaraj, N., Mann, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Minimal,+encapsulated+proteomic-sample+processing+applied+to+copy-number+estimation+in+eukaryotic+cells.">Minimal, encapsulated proteomic-sample processing applied to copy-number estimation in eukaryotic cells.</a> Nature Methods. 11 (3), 319-324 (2014).</li><li>Wi&#347;niewski, J. R., Zougman, A., Nagaraj, N., Mann, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Universal+sample+preparation+method+for+proteome+analysis.">Universal sample preparation method for proteome analysis.</a> Nature Methods. 6 (5), 359-362 (2009).</li><li>Ding, H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Urine+Proteomics:+Evaluation+of+Different+Sample+Preparation+Workflows+for+Quantitative,+Reproducible,+and+Improved+Depth+of+Analysis.">Urine Proteomics: Evaluation of Different Sample Preparation Workflows for Quantitative, Reproducible, and Improved Depth of Analysis.</a> Journal of Proteome Research. 19 (4), 1857-1862 (2020).</li><li>Zhao, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+comprehensive+analysis+and+annotation+of+human+normal+urinary+proteome.">A comprehensive analysis and annotation of human normal urinary proteome.</a> Scientific Reports. 7 (1), 1-13 (2017).</li><li>Wi&#347;niewski, J. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+Evaluation+of+Filter+Aided+Sample+Preparation+(FASP)+and+Multienzyme+Digestion+FASP+Protocols.">Quantitative Evaluation of Filter Aided Sample Preparation (FASP) and Multienzyme Digestion FASP Protocols.</a> Analytical Chemistry. 88 (10), 5438-5443 (2016).</li><li>Wi&#347;niewski, J. R., Zielinska, D. F., Mann, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparison+of+ultrafiltration+units+for+proteomic+and+N-glycoproteomic+analysis+by+the+filter-aided+sample+preparation+method.">Comparison of ultrafiltration units for proteomic and N-glycoproteomic analysis by the filter-aided sample preparation method.</a> Analytical Biochemistry. 410 (2), 307-309 (2011).</li><li>Yu, 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=Urine+sample+preparation+in+96-well+filter+plates+for+quantitative+clinical+proteomics.">Urine sample preparation in 96-well filter plates for quantitative clinical proteomics.</a> Analytical Chemistry. 86 (11), (2014).</li><li>Gillet, L. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Targeted+data+extraction+of+the+MS/MS+spectra+generated+by+data-independent+acquisition:+A+new+concept+for+consistent+and+accurate+proteome+analysis.">Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: A new concept for consistent and accurate proteome analysis.</a> Molecular and Cellular Proteomics. 11 (6), 1-17 (2012).</li><li>Liu, Y., H&#252;ttenhain, R., Collins, B., Aebersold, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mass+spectrometric+protein+maps+for+biomarker+discovery+and+clinical+research.">Mass spectrometric protein maps for biomarker discovery and clinical research.</a> Expert Review of Molecular Diagnostics. 13 (8), 811-825 (2013).</li><li>Gallien, S., Duriez, E., Demeure, K., Domon, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Selectivity+of+LC-MS/MS+analysis:+Implication+for+proteomics+experiments.">Selectivity of LC-MS/MS analysis: Implication for proteomics experiments.</a> Journal of Proteomics. 81, 148-158 (2013).</li><li>Muntel, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Advancing+Urinary+Protein+Biomarker+Discovery+by+Data-Independent+Acquisition+on+a+Quadrupole-Orbitrap+Mass+Spectrometer.">Advancing Urinary Protein Biomarker Discovery by Data-Independent Acquisition on a Quadrupole-Orbitrap Mass Spectrometer.</a> Journal of Proteome Research. 14 (11), 4752-4762 (2015).</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>Kim, 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=Identification+of+Differentially+Expressed+Proteins+in+Direct+Expressed+Prostatic+Secretions+of+Men+with+Organ-confined+Versus+Extracapsular+Prostate+Cancer.">Identification of Differentially Expressed Proteins in Direct Expressed Prostatic Secretions of Men with Organ-confined Versus Extracapsular Prostate Cancer.</a> Molecular &amp; Cellular Proteomics. 11 (12), 1870-1884 (2012).</li><li>Decramer, 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=Urine+in+clinical+proteomics.">Urine in clinical proteomics.</a> Molecular and Cellular Proteomics. 7 (10), 1850-1862 (2008).</li><li>Thongboonkerd, V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Practical+points+in+urinary+proteomics.">Practical points in urinary proteomics.</a> Journal of Proteome Research. 6 (10), 3881-3890 (2007).</li><li>Konvalinka, A., Scholey, J. W., Diamandis, E. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Searching+for+new+biomarkers+of+renal+diseases+through+proteomics.">Searching for new biomarkers of renal diseases through proteomics.</a> Clinical Chemistry. 58 (2), 353-365 (2012).</li><li>Drake, R. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In-Depth+Proteomic+Analyses+of+Direct+Expressed+Prostatic+Secretions.">In-Depth Proteomic Analyses of Direct Expressed Prostatic Secretions.</a> Journal of Proteome Research. 9 (5), 2109-2116 (2010).</li></ol>

All authors declare no conflict of interest.

In this work, a strategy for analyzing EPS-urine samples is presented. The FASP protocol is an ideal choice for urinary proteomics because it allows sample concentration before enzymatic digestion. In fact, using this workflow, several hundreds of microliters of urine can be loaded on a single filter and processed. Moreover, on-filter digestion offers relative freedom in the choice of denaturation conditions. In our work, protein denaturation is achieved by diluting urine samples in a buffer containing Tris, SDS and DTT (final concentration: 50 mM Tris, 1% SDS, 50 mM DTT). Proteins are efficiently denatured immediately after thawing the sample, in order to avoid unwanted degradation by active proteases. The original FASP protocol has been improved by increasing the volume of washes from 100 &#181;L to 200 &#181;L. In this way, better removal of residues, especially detergents from the filter, is achieved.
After enzymatic digestion, protein estimation by external standard using a fast LC-MS/MS, data-dependent method is performed before the last steps of the protocol, which comprise double StageTip purification and LC-MS/MS analysis in DIA mode, on equal starting material for all samples (2 &#181;g).
The versatility of FASP is associated with the DIA approach, a sensitive method providing a low number of missing values17. In our work, 2387 proteins were identified and quantified, thus enabling a detailed proteomic profile of EPS-urine to be drawn. The identification and quantification of 2387 proteins was possible through the generation of a rich spectral library, obtained via high-pH reversed fractionation of peptides, and by our DIA method, directed at a wide m/z precursor range. This workflow identified over 80% of proteins previously found in direct-EPS analysis, demonstrating that a considerable fraction of the EPS-urinary proteome is indeed derived from expressed prostatic secretions, thus is a rich source of prostate tissue-specific proteins26.
In conclusion, our experimental design couples the versatility of FASP with the sensitivity of DIA in order to obtain a rich map of the urinary proteome. This strategy is recommended for analyzing EPS-urine samples, but its use can be extended to urinary proteomics in general, or even to other sample types.

The constant evolution of proteomic technologies promises to have a considerable impact in helping disease diagnosis and prediction of response to treatment by providing high resolution maps of key molecular effectors present in a wide variety of samples such as tissues and biofluids. From an analytical point of view, urine offers several advantages such as ease of collection and major stability of the proteome with respect to others biofluids1. Proteomic analysis of urine is of special interest in biomarker discovery studies on urological cancers, since it allows noninvasive sampling in proximity to the tissues of interest2. In particular, a sample that seems to be promising for studying prostate-related pathologies is the EPS-urine3,4 (i.e., a urine sample collected after a digital rectal exam (DRE)). This latter operation prior to sample collection enriches urine with prostate specific proteins. EPS-urine is a good candidate to investigate disorders related to the prostate gland5 including prostate cancer (PCa), since through DRE, proteins secreted by the tumor can be poured into the urine sample, increasing the chance of detecting cancer tissue-specific proteins.
A crucial role in allowing detection and quantification of potential protein biomarkers is played by mass spectrometry (MS). Over the last two decades, MS-based protocols for proteomic analysis have allowed an ever-increasing number of proteins to be detected in a single LC-MS/MS run thanks to continuous improvements in MS instrumentation and in data analysis software6.
MS-based proteomic sample preparation generally involves enzymatic digestion of the protein mixture, which can be achieved via a wide variety of protocols such as: in-solution digestion, MStern blotting7, suspension trapping (S-trap)8, solid-phase-enhanced sample preparation (SP3)9, in-StageTip digestion10 and filter aided sample preparation (FASP)11. All protocols can be used for urinary proteomics, even though results may vary with respect to the number of identified proteins and peptides and in terms of reproducibility12.
In this work, our attention was focused on the analysis of EPS-urine by the FASP protocol. The FASP protocol was originally designed to analyze proteins extracted from tissues and cell cultures, but its use was then expanded to the analysis of other sample types, such as urine13. With respect to straightforward in-solution digestion FASP is a more flexible proteomic approach14, since by achieving effective removal of detergents and other contaminants such as salts from the protein mixture before enzymatic digestion15, it allows the choice of optimal protein solubilization conditions. Moreover, an additional characteristic of FASP is that it provides a means for sample concentration. This is of particular interest for urinary proteomic analysis, because it allows to start from relatively large sample volumes (hundreds of microliters). In the light of the potential of the FASP protocol, several studies have focused the attention on workflow automation, with the aim of reducing experimental variability and processing an elevated number of samples in parallel16.
In our workflow, FASP is followed by LC-MS/MS acquisition in data-independent analysis (DIA), which provides high proteome coverage, good quantitative precision and low incidence of missing values. The DIA approach is a sensitive method where all ions are selected for MS/MS events, opposite to what happens in data-dependent analysis (DDA) where only ions with the highest intensity are fragmented. The mass spectrometer, operating in DIA mode, performs scan cycles with different isolation width covering the whole m/z precursor range. This approach allows to reproducibly detect a high number of peptides per unit time, providing a proteomics snapshot of the sample17. Moreover, data generated by DIA have another interesting characteristic: the possibility of a posteriori analysis18. DIA data are more complex than those obtained by DDA, because MS/MS spectra in DIA result from the co-isolation of several precursor ions within each m/z window19. Disentangling the composite MS/MS spectra into distinct and specific peptide signals is achieved by using two fundamental elements: a spectral library and a dedicated software for data analysis. The spectral library is generated by a data-dependent experiment, usually involving peptide fractionation to maximize proteome coverage, which provides a list of thousands of experimentally determined precursor ions and MS/MS spectra of peptides detectable in the sample under consideration. The data analysis software, instead, uses the information contained in the spectral library to interpret the DIA data by generating specific extracted ion chromatograms which allow peptide detection and quantification. While library-free DIA data analysis is now feasible, library-based DIA still provides better results in terms of proteome coverage20.
The sample preparation protocol here described (Figure 1) consists of the following steps: a centrifugation step (to remove cell debris), FASP digestion, StageTip purification21, quantification of proteins and DIA analysis. This protocol has been designed for the analysis of EPS-urine in the context of prostate cancer biomarker discovery, but it can be applied to proteomic analysis of any urine sample.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>1 M Tris HCL pH 8.0</td>
			<td>Lonza</td>
			<td>51238</td>
			<td></td>
		</tr>
		<tr>
			<td>2-iodoacetamide for synthesis</td>
			<td>Merck</td>
			<td>8047440100</td>
			<td></td>
		</tr>
		<tr>
			<td>Acetonitrile for HPLC LC-MS grade</td>
			<td>VWR</td>
			<td>83640.290</td>
			<td></td>
		</tr>
		<tr>
			<td>Ammonium acetate</td>
			<td>Fluka</td>
			<td>9690</td>
			<td></td>
		</tr>
		<tr>
			<td>ammonium hydroxide solution</td>
			<td>Sigma</td>
			<td>30501</td>
			<td></td>
		</tr>
		<tr>
			<td>ammonium hydroxide volumetric standard, 5N solution in water</td>
			<td>Merck</td>
			<td>318612-500ML</td>
			<td></td>
		</tr>
		<tr>
			<td>Dithiothreitol</td>
			<td>Amresco</td>
			<td>0281-25G</td>
			<td></td>
		</tr>
		<tr>
			<td>Empore Cation 47mm Extraction Disks</td>
			<td>Microcolumn</td>
			<td>2251</td>
			<td></td>
		</tr>
		<tr>
			<td>Empore Disk C18</td>
			<td>Varian</td>
			<td>12145004</td>
			<td></td>
		</tr>
		<tr>
			<td>Formic acid optima</td>
			<td>Fisher Scientific</td>
			<td>A117-50</td>
			<td></td>
		</tr>
		<tr>
			<td>Hela Protein Digest Standard</td>
			<td>Fisher Scientific</td>
			<td>88329</td>
			<td></td>
		</tr>
		<tr>
			<td>Microcon-10kDa Centrifugal Filter Unit with Ultracel-10 membrane</td>
			<td>MERCK</td>
			<td>MRCPRT010</td>
			<td></td>
		</tr>
		<tr>
			<td>sodium dodecyl sulfate solution</td>
			<td>Merck</td>
			<td>71736-500ML</td>
			<td></td>
		</tr>
		<tr>
			<td>Thiethylammonium bicarbonate buffer</td>
			<td>Merck</td>
			<td>T7408-100ML</td>
			<td></td>
		</tr>
		<tr>
			<td>trifluoroacetic acid</td>
			<td>Riedel-de Ha&#235;n</td>
			<td>34957</td>
			<td></td>
		</tr>
		<tr>
			<td>Trypsin from porcine pancreas</td>
			<td>Merck</td>
			<td>T6567-1MG</td>
			<td></td>
		</tr>
		<tr>
			<td>Urea</td>
			<td>Merck</td>
			<td>U6504-500G</td>
			<td></td>
		</tr>
		<tr>
			<td>Water HPLC gradient grade</td>
			<td>Fisher Scientific</td>
			<td>W/0106/17</td>
			<td></td>
		</tr>
		<tr>
			<td>Proteome Discoverer 1,4</td>
			<td>Thermo Fisher Scientific</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Spectronaut 14.0</td>
			<td>Biognosys</td>
			<td></td>
			<td></td>
		</tr>
	</tbody>
</table>

proteomic profile of eps-urine through fasp digestion and data-independent analysis

Filter-aided sample protocol (FASP) is widely used for proteomics sample preparation because it allows to concentrate diluted samples and it is compatible with a wide variety of detergents. Bottom-up proteomics workflows like FASP increasingly rely on LC-MS/MS methods performed in data-independent analysis (DIA) mode, a scanning method that allows deep proteome coverage and low incidence of missing values. 
In this report, we will provide the details of a workflow that combines a FASP protocol, a double StageTip purification step and LC-MS/MS in DIA mode for urinary proteome mapping. As a model sample, we analyzed expressed prostatic secretions (EPS)-urine, a sample collected after a digital rectal exam (DRE), which is of interest in prostate cancer biomarker discovery studies.

This protocol for urinary proteomic analysis includes the following steps: FASP digestion, estimation of protein amount via external standard calibration, double StageTip purification (SCX and C18), and LC-MS/MS analysis in DIA mode.
After protein digestion, preliminary injections are performed after StageTip SCX purification of the resulting peptides. LC-MS/MS raw files are processed to obtain the number of identified peptides, the number of identified proteins and the area of detected peptides. The total area obtained by summing up all identified peptides is used to estimate protein content via interpolation to an external standard: a HeLa protein digest injected at five different amounts (2, 5, 15, 50, 150 ng, respectively). The protein amount for the six samples analyzed in this study varied from sample to sample, showing an average value of 78 ng/&#181;L.
After protein estimation, 2 &#181;g of digested proteins from each sample are purified by sequential SCX and C18 StageTip before DIA analysis. The spectral library for searching DIA data is created after high-pH reversed-phase fractionation and DDA LC-MS/MS analysis of a representative sample (e.g., a sample pool). Using the parameters described above, we have identified and quantified, cumulatively, 2387 protein groups in the six EPS-urine samples under consideration (Supplementary Table 1 and Figure 4).
In order to evaluate from a qualitative point of view the relevance of the list of identified and quantified proteins, the obtained matrix was compared to a list of 624 proteins previously identified in direct- EPS22, a sample collected in a more invasive procedure, which has proven to be a source of interesting candidate prostate cancer biomarkers. In total, 508 out of 624 proteins were successfully detected by our FASP/DIA protocol on EPS-urine.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/62512/62512fig01.jpg" /> 
Figure 1: Proteomic workflow. <a href="https://www.jove.com/files/ftp_upload/62512/62512fig01large.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/62512/62512fig02.jpg" /> 
Figure 2: Representation of our experimental design for protein quantification based on external standard (HeLa digest). <a href="https://www.jove.com/files/ftp_upload/62512/62512fig02large.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/62512/62512fig03.jpg" /> 
Figure 3: Key steps of DIA analysis: (i) elaboration of the spectral library through high-pH reversed-phase fractionation and DDA analysis, (ii) sample analysis using the DIA approach, (iii) data analysis by Spectronaut. <a href="https://www.jove.com/files/ftp_upload/62512/62512fig03large.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/62512/62512fig04.jpg" /> 
Figure 4: Ranked plot for the detected EPS-urinary proteins. A few selected hits are labelled. <a href="https://www.jove.com/files/ftp_upload/62512/62512fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Supplementary Table 1: Representative table of quantified proteins in six EPS-urine samples in Spectronaut. <a href="https://www.jove.com/files/ftp_upload/62512/Supplementary Table 1.xls" target="_blank">Please click here to download this Table.</a>

Watch this Scientific Journal Video about Proteomic Profile of EPS-Urine through FASP Digestion and Data-Independent Analysis at JoVE.com

Proteomic Profile of EPS-Urine through FASP Digestion and Data-Independent Analysis

Here, we present an optimized on-filter digestion protocol with detailed information about the following: protein digestion, peptide purification and data independent acquisition analysis. This strategy is applied to the analysis of expressed prostatic secretions-urine samples and allows high proteome coverage and low missing value label-free profiling of the urinary proteome.

Filter-aided sample protocol (FASP) is widely used for proteomics sample preparation because it allows to concentrate diluted samples and it is compatible ...

proteomic-profile-eps-urine-through-fasp-digestion-data-independent

Research

JoVE Journal

Biochemistry

6.7K Views.  Magna Graecia University of Catanzaro. Here, we present an optimized on-filter digestion protocol with detailed information about the following: protein digestion, peptide purification and data independent acquisition analysis. This strategy is applied to the analysis of expressed prostatic secretions-urine samples and allows high proteome coverage and low missing value label-free profiling of the urinary proteome. 

Video: Proteomic Profile of EPS-Urine through FASP Digestion and Data-Independent Analysis

Resolving Affinity Purified Protein Complexes by Blue Native PAGE and Protein Correlation Profiling

Most proteins act in association with others; hence, it is crucial to characterize these functional units in order to fully understand biological processes. Affinity purification coupled to mass spectrometry (AP-MS) has become the method of choice for identifying protein-protein interactions. However, conventional AP-MS studies provide information on protein interactions, but the organizational information is lost. To address this issue, we developed a strategy to unravel the distinct functional assemblies a protein might be involved in, by resolving affinity-purified protein complexes prior to their characterization by mass spectrometry. Protein complexes isolated through affinity purification of a bait protein using an epitope tag and competitive elution are separated through blue native electrophoresis. Comparison of protein migration profiles through correlation profiling using quantitative mass spectrometry allows assignment of interacting proteins to distinct molecular entities. This method is able to resolve protein complexes of close molecular weights that might not be resolved by traditional chromatographic techniques such as gel filtration. With little more work than conventional AP-geLC-MS/MS, we demonstrate this strategy may in many cases be adequate for obtaining protein complex topological information concomitantly to identifying protein interactions.

Here we present protocols for affinity purification of protein complexes and their separation by blue native PAGE, followed by protein correlation profiling using label free quantitative mass spectrometry. This method is useful to resolve interactomes into distinct protein complexes.

Most proteins act in association with others; hence, it is crucial to characterize these functional units in order to fully understand biological ...

Dissection of Human Retina and RPE-Choroid for Proteomic Analysis

The human retina is composed of the sensory neuroretina and the underlying retinal pigmented epithelium (RPE), which is firmly complexed to the vascular choroid layer. Different regions of the retina are anatomically and molecularly distinct, facilitating unique functions and demonstrating differential susceptibility to disease. Proteomic analysis of each of these regions and layers can provide vital insights into the molecular process of many diseases, including Age-Related Macular Degeneration (AMD), diabetes mellitus, and glaucoma. However, separation of retinal regions and layers is essential before quantitative proteomic analysis can be accomplished. Here, we describe a method for dissection and collection of the foveal, macular, and peripheral retinal regions and underlying RPE-choroid complex, involving regional punch biopsies and manual removal of tissue layers from a human eye.One-dimensional SDS-PAGE as well as downstream proteomic analysis, such as liquid chromatography-tandem mass spectrometry (LC-MS/MS), can be used to identify proteins in each dissected retinal layer, revealing molecular biomarkers for retinal disease.

The human retina is composed of functionally and molecularly distinct regions, including the fovea, macula, and peripheral retina. Here, we describe a method using punch biopsies and manual removal of tissue layers from a human eye to dissect and collect these distinct retinal regions for downstream proteomic analysis.

The human retina is composed of the sensory neuroretina and the underlying retinal pigmented epithelium (RPE), which is firmly complexed to the vascular ...

Utilizing a Comprehensive Immunoprecipitation Enrichment System to Identify an Endogenous Post-translational Modification Profile for Target Proteins

It is now well-appreciated that post-translational modifications (PTMs) play an integral role in regulating a protein&#39;s structure and function, which may be essential for a given protein&#39;s role both physiologically and pathologically. Enrichment of PTMs is often necessary when investigating the PTM status of a target protein, because PTMs are often transient and relatively low in abundance. Many pitfalls are encountered when enriching for a PTM of a target protein, such as buffer incompatibility, the target protein antibody is not IP-compatible, loss of PTM signal, and others. The degree of difficulty is magnified when investigating multiple PTMs like acetylation, ubiquitination, SUMOylation 2/3, and tyrosine phosphorylation for a given target protein. Studying a combination of these PTMs may be necessary, as crosstalk between PTMs is prevalent and critical for protein regulation. Often, these PTMs are studied in different lysis buffers and with unique inhibitor compositions. To simplify the process, a unique denaturing lysis system was developed that effectively isolates and preserves these four PTMs; thus, enabling investigation of potential crosstalk in a single lysis system. A unique filter system was engineered to remove contaminating genomic DNA from the lysate, which is a problematic by-product of denaturing buffers. Robust affinity matrices targeting each of the four PTMs were developed in concert with the buffer system to maximize the enrichment and detection of the endogenous states of these four PTMs. This comprehensive PTM detection toolset streamlines the process of obtaining critical information about whether a protein is modified by one or more of these PTMs.

Investigating multiple, endogenous post-translational modifications for a target protein can be extremely challenging. Techniques described here utilize an optimized lysis buffer and filter system developed with specific PTM-targeting, affinity matrices to detect the acetylation, ubiquitination, SUMOylation 2/3, and tyrosine phosphorylation modifications for a target protein using a single, streamlined system.

It is now well-appreciated that post-translational modifications (PTMs) play an integral role in regulating a protein&#39;s structure and function, which ...

Protein Digestion, Ultrafiltration, and Size Exclusion Chromatography to Optimize the Isolation of Exosomes from Human Blood Plasma and Serum

Exosomes, a type of nanovesicle released from all cell types, can be isolated from any bodily fluid. The contents of exosomes, including proteins and RNAs, are unique to the cells from which they are derived and can be used as indicators of disease. Several common enrichment protocols, including ultracentrifugation, yield exosomes laden with soluble protein contaminants. Specifically, we have found that the most abundant proteins within blood often co-purify with exosomes and can confound downstream proteomic studies, thwarting the identification of low abundance biomarker candidates. Of additional concern is irreproducibility of exosome protein quantification due to inconsistent representation of non-exosomal protein levels. The protocol detailed here was developed to remove non-exosomal proteins that co-purify along with exosomes, adding rigor to the exosome purification process. Five methods were compared using paired blood plasma and serum from five donors. Analysis using nanoparticle tracking analysis and micro bicinchoninic acid protein assay revealed that a combined protocol utilizing ultrafiltration and size exclusion chromatography yielded the optimal vesicle enrichment and soluble protein removal. Western blotting was used to verify that the expected abundant blood proteins, including albumin and apolipoproteins, were depleted.

Here, we present a protocol to purify exosomes from both plasma and serum with reduced co-purification of non-exosomal blood proteins. The optimized protocol includes ultrafiltration, protease treatment, and size exclusion chromatography. Enhanced purification of exosomes benefits downstream analyses, including more accurate quantification of vesicles and proteomic characterization.

Exosomes, a type of nanovesicle released from all cell types, can be isolated from any bodily fluid. The contents of exosomes, including proteins and ...

Split-BioID &#8212; Proteomic Analysis of Context-specific Protein Complexes in Their Native Cellular Environment

To complement existing affinity purification (AP) approaches for the identification of protein-protein interactions (PPI), enzymes have been introduced that allow the proximity-dependent labeling of proteins in living cells. One such enzyme, BirA* (used in the BioID approach), mediates the biotinylation of proteins within a range of approximately 10 nm. Hence, when fused to a protein of interest and expressed in cells, it allows the labeling of proximal proteins in their native environment. As opposed to AP that relies on the purification of assembled protein complexes, BioID detects proteins that have been marked within cells no matter whether they are still interacting with the protein of interest when they are isolated. Since it biotinylates proximal proteins, one can moreover capitalize on the exceptional affinity of streptavidin for biotin to very efficiently isolate them. While BioID performs better than AP for identifying transient or weak interactions, both AP- and BioID-mass spectrometry approaches provide an overview of all possible interactions a given protein may have. However, they do not provide information on the context of each identified PPI. Indeed, most proteins are typically part of several complexes, corresponding to distinct maturation steps or different functional units. To address this common limitation of both methods, we have engineered a protein-fragments complementation assay based on the BirA* enzyme. In this assay, two inactive fragments of BirA* can reassemble into an active enzyme when brought in close proximity by two interacting proteins to which they are fused. The resulting split-BioID assay thus allows the labeling of proteins that assemble around a pair of interacting proteins. Provided these two only interact in a given context, split-BioID then allows the analysis of specific context-dependent functional units in their native cellular environment. Here, we provide a step-by-step protocol to test and apply split-BioID to a pair of interacting proteins.

Split-BioID &amp;#8212; Proteomic Analysis of Context-specific Protein Complexes in Their Native Cellular Environment

We provide a step-by-step protocol for split-BioID, a protein fragments-complementation assay based on the proximity-labeling technique BioID. Activated on the interaction of two given proteins, it allows the proteomics analysis of context-dependent protein complexes in their native cellular environment. The method is simple, cost-effective and only requires standard laboratory equipment.

To complement existing affinity purification (AP) approaches for the identification of protein-protein interactions (PPI), enzymes have been introduced ...

Dynamic Proteomic and miRNA Analysis of Polysomes from Isolated Mouse Heart After Langendorff Perfusion

Studies in dynamic changes in protein translation require specialized methods. Here we examined changes in newly-synthesized proteins in response to ischemia and reperfusion using the isolated perfused mouse heart coupled with polysome profiling. To further understand the dynamic changes in protein translation, we characterized the mRNAs that were loaded with cytosolic ribosomes (polyribosomes or polysomes) and also recovered mitochondrial polysomes and compared mRNA and protein distribution in the high-efficiency fractions (numerous ribosomes attached to mRNA), low-efficiency (fewer ribosomes attached) which also included mitochondrial polysomes, and the non-translating fractions. miRNAs can also associate with mRNAs that are being translated, thereby reducing the efficiency of translation, we examined the distribution of miRNAs across the fractions. The distribution of mRNAs, miRNAs, and proteins was examined under basal perfused conditions, at the end of 30 min of global no-flow ischemia, and after 30 min of reperfusion. Here we present the methods used to accomplish this analysis&#8212;in particular, the approach to optimization of protein extraction from the sucrose gradient, as this has not been described before&#8212;and provide some representative results.

Here we present a protocol to perform polysome profiling on the isolated perfused mouse heart. We describe methods for heart perfusion, polysome profiling, and analysis of the polysome fractions with respect to mRNAs, miRNAs, and the polysome proteome.

Studies in dynamic changes in protein translation require specialized methods. Here we examined changes in newly-synthesized proteins in response to ...

Proteomic Analysis of Human Macrophage Polarization Under a Low Oxygen Environment

Macrophages are innate immune cells involved in a number of physiological functions ranging from responses to infectious pathogens to tissue homeostasis. The various functions of these cells are related to their activation states, which is also called polarization. The precise molecular description of these various polarizations is a priority in the field of macrophage biology. It is currently acknowledged that a multidimensional approach is necessary to describe how polarization is controlled by environmental signals. In this report, we describe a protocol designed to obtain the proteomic signature of various polarizations in human macrophages. This protocol is based on a label-free quantification of macrophage protein expression obtained from in-gel fractionated and Lys C/trypsin-digested cellular lysis content. We also provide a protocol based on in-solution digestion and isoelectric focusing fractionation to use as an alternative. Because oxygen concentration is a relevant environmental parameter in tissues, we use this protocol to explore how atmospheric composition or a low oxygen environment affects the classification of macrophage polarization.

We present a protocol to obtain proteomic signatures of human macrophages and apply this to determination of the impact of a low oxygen environment on macrophage polarization.

Macrophages are innate immune cells involved in a number of physiological functions ranging from responses to infectious pathogens to tissue homeostasis. ...

Identification of Functional Protein Regions Through Chimeric Protein Construction

The goal of this protocol encompasses the design of chimeric proteins in which distinct regions of a protein are replaced by their corresponding sequences in a structurally similar protein, in order to determine the functional importance of these regions. Such chimeras are generated by means of a nested PCR protocol using overlapping DNA fragments and adequately designed primers, followed by their expression within a mammalian system to ensure native secondary structure and post-translational modifications. 
The functional role of a distinct region is then indicated by a loss of activity of the chimera in an appropriate readout assay. In consequence, regions harboring a set of critical amino acids are identified, which can be further screened by complementary techniques (e.g. site-directed mutagenesis) to increase molecular resolution. Although limited to cases in which a structurally related protein with differing functions can be found, chimeric proteins have been successfully employed to identify critical binding regions in proteins such as cytokines and cytokine receptors. This method is particularly suitable in cases in which the protein's functional regions are not well defined, and constitutes a valuable first step in directed evolution approaches to narrow down the regions of interest and reduce the screening effort involved.

Structurally related proteins frequently exert distinct biological functions. The exchange of equivalent regions of these proteins in order to create chimeric proteins constitutes an innovative approach to identify critical protein regions that are responsible for their functional divergence.

The goal of this protocol encompasses the design of chimeric proteins in which distinct regions of a protein are replaced by their corresponding sequences ...

Evaluation of Protein&#8211;Protein Interactions using an On-Membrane Digestion Technique

Numerous intracellular proteins physically interact in accordance with their intracellular and extracellular circumstances. Indeed, cellular functions largely depend on intracellular protein&#8211;protein interactions. Therefore, research regarding these interactions is indispensable to facilitating the understanding of physiologic processes. Co-precipitation of associated proteins, followed by mass spectrometry (MS) analysis, enables the identification of novel protein interactions. In this study, we have provided details of the novel technique of immunoprecipitation-liquid chromatography (LC)-MS/MS analysis combined with on-membrane digestion for the analysis of protein&#8211;protein interactions. This technique is suitable for crude immunoprecipitants and can improve the throughput of proteomic analyses. Tagged recombinant proteins were precipitated using specific antibodies; next, immunoprecipitants blotted onto polyvinylidene difluoride membrane pieces were subjected to reductive alkylation. Following trypsinization, the digested protein residues were analyzed using LC-MS/MS. Using this technique, we were able to identify several candidate associated proteins. Thus, this method is convenient and useful for the characterization of novel protein&#8211;protein interactions.

Here, we present a protocol for an on-membrane digestion technique for the preparation of samples for mass spectrometry. This technique facilitates the convenient analysis of protein&#8211;protein interactions.

Numerous intracellular proteins physically interact in accordance with their intracellular and extracellular circumstances. Indeed, cellular functions ...

Ex Vivo Hepatic Perfusion Through the Portal Vein in Mouse

Metabolic diseases such as diabetes, pre-diabetes, non-alcoholic fatty liver disease (NAFLD), and nonalcoholic steatohepatitis (NASH) are becoming increasingly common. Ex vivo liver perfusions allow for a comprehensive analysis of liver metabolism using nuclear magnetic resonance (NMR), in nutritional conditions that can be rigorously controlled. As in silico simulations remain a primarily theoretical means of assessing hormone actions and the effects of pharmaceutical intervention, the perfused liver remains one of the most valuable test beds for understanding hepatic metabolism. As these studies guide basic insights into hepatic physiology, results must be accurate and reproducible. The greatest factor in the reproducibility of ex vivo hepatic perfusion is the quality of surgery. Therefore, we have introduced an organized and streamlined method to perform ex vivo mouse liver perfusions in the context of in situ NMR experiments. We also describe a unique application and discuss common issues encountered in these studies. The overall purpose is to provide an uncomplicated guide to a technique we have refined over several years that we deem the golden standard for obtaining reproducible results in hepatic resections and perfusions in the context of in situ NMR experiments. The distance to the center of the field for the magnet as well as the inaccessibility of the tissue to intervention during the NMR experiment makes our methods novel.

Ex Vivo Hepatic Perfusion Through the Portal Vein in Mouse

The protocol describes a straightforward method of resectioning an intact mouse liver for metabolic studies through portal vein perfusion.