Proteomic analysis of extracellular vesicles derived from platelet concentrates treated with Mirasol® identifies biomarkers of platelet storage lesion

Journal Pre-proof Proteomic analysis of extracellular vesicles derived from platelet concentrates treated with Mirasol® identifies biomarkers of platelet storage lesion

Lidia Hermida-Nogueira, María N. Barrachina, Irene Izquierdo, María García-Vence, Serena Lacerenza, Susana Bravo, Azucena Castrillo, Ángel García PII:

S1874-3919(19)30301-X

DOI:

https://doi.org/10.1016/j.jprot.2019.103529

Reference:

JPROT 103529

To appear in:

Journal of Proteomics

Received date:

18 April 2019

Revised date:

4 September 2019

Accepted date:

16 September 2019

Please cite this article as: L. Hermida-Nogueira, M.N. Barrachina, I. Izquierdo, et al., Proteomic analysis of extracellular vesicles derived from platelet concentrates treated with Mirasol® identifies biomarkers of platelet storage lesion, Journal of Proteomics (2018), https://doi.org/10.1016/j.jprot.2019.103529

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© 2018 Published by Elsevier.

Journal Pre-proof Proteomic analysis of extracellular vesicles derived from platelet concentrates treated with Mirasol® identifies biomarkers of platelet storage lesion Lidia Hermida-Nogueira1 , María N. Barrachina1 , Irene Izquierdo1 , María García-Vence2 , Serena Lacerenza3 , Susana Bravo2 , Azucena Castrillo4 , Ángel García1 ,* [email protected] 1

Platelet Proteomics Group, Center for Research in Molecular Medicine and Chronic Diseases

(CIMUS),

Universidade

de Santiago

de Compostela, and Instituto de Investigación

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Proteomics Unit, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS),

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2

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Sanitaria(IDIS), Santiago de Compostela, Spain

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Santiago de Compostela, Spain

Department of Pharmacy, University of Pisa, Pisa, Italy

4

Axencia Galega de Sangue, Órganos e Tecidos, Galicia, Spain

*

Corresponding author at: Head of the Platelet Proteomics Group, Center for Research in

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3

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Molecular Medicine and Chronic Diseases (CIMUS)., Universidade de Santiago de Compostela., Avda. Barcelona s/n, 15782- Santiago de Compostela (Spain).

Journal Pre-proof Abstract In blood banks, platelets are stored until 7 days after a pathogen reduction technology (PRT) treatment, Mirasol® (vitamin B2 plus UVB light) in the present case. The storage time under these conditions may have an impact on platelets and their releasate leading to potential adverse reactions following transfusion to patients. The aim of this study was to analyze the proteome of extracellular vesicles generated by platelets at different storage days (2 and 7) to

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gain deeper information on the platelet concentrates state at those moments. EVs were

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isolated by a centrifugation-based approach and characterized by dynamic light scattering and

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transmission electron microscopy. Proteomic analysis was by LC-MS/MS and quantification

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by SWATH. In this way, 151 proteins were found up-regulated at day 7 of storage. This group includes CCL5 and Platelet Factor 4, chemokines with power to attract neutrophils and which

could

generate

transfusion

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monocytes,

adverse

reactions.

In

addition,

other

glycoproteins and platelet activation markers were also found elevated at day 7. Proteins

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related to glycolysis and lactate production were found altered with high fold changes,

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showing a deregulation of platelet metabolism at day 7. The obtained results provide novel

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information about possible effects of platelet-derived EVs on transfusion adverse reactions. Keywords: Extracellular vesicles; platelet concentrates; transfusion medicine; SWATH. Significance: We performed the first proteomic analysis of extracellular vesicles derived from platelets upon storage at different time points on blood bank conditions after Mirasol® treatment. We identified a high number of proteins related to platelet activation and platelet storage lesion that could have a role in possible transfusion adverse reactions.

Journal Pre-proof 1. Introduction Extracellular vesicles (EVs) are small particles that are the focus of interest nowadays as potential biomarkers for several diseases. There are three types of EVs which differ in size, markers and mechanism of formation [1,2]. Exosomes,

the smallest subpopulation (30-100 nm), are formed inside the cell in

multivesicular bodies. They contain large amounts of markers such as tetraspanins (CD9,

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CD63), which help to their characterization. Microvesicles (MVs) are bigger than exosomes (100-1000 nm) and are originated by budding of the cytoplasmic membrane. They are

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enriched in phosphatidylserine, one of the possible markers to detect them. Apoptotic bodies,

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the biggest group (1-5 μm), are generated in the last phase of cell apoptosis [3,4].

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EVs are secreted by many types of cells such as endothelial cells, megakaryocytes and different blood cells. In plasma the majority of EVs are derived from platelets (PEVs) [5].

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Platelets release EVs in response to agonist stimulation (e.g. ADP, thrombin) but also by

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other factors, for instance low temperatures or in pathological circumstances. In blood banks

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centres, platelet concentrates (PCs) are stored at room temperature (22°C) under agitation. Blood safety is a challenge in transfusion medicine; although strict screening criteria and nucleic acid testing (NAT) have significantly reduced the risk of transfusion-related infections, those strategies have not completely eliminated the threat related to newly emerging pathogens. To solve this problem, many companies have commercialized different pathogen reduction technologies (PRT), such as Mirasol® or Intercept™, based on the use of compounds that can be excited at a certain wavelength to trigger cross-linking or oxidative damage of nucleic acids to block DNA replication. Many publications have reported the efficacy of these technologies to inactivate a wide variety of viruses and bacteria [6-9]. Indeed

Journal Pre-proof their implementation has increased the safety of blood products with the extension of the storage time to up to 7 days. On the other hand, it is important to consider the potential negative impact of these technologies, and the storage time, on platelets and the possible adverse reactions that could cause on patients after transfusion. Schubert et al. [10] studied the impact of Mirasol® on PCs from buffy coats (PC-BC) during storage by different proteomic approaches discovering

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differential expression levels in proteins related to the maintenance of actin structure and the

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regulation of its dynamics, cytoskeleton and vesicle trafficking. Other investigators found

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changes in the expression of proteins associated with cytoskeleton organization and oxidative

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stress on buffy coats treated with Intercept™ [11,12]. Nonetheless, there are no studies that analyze in detail changes in the cargo of EVs released from platelets upon storage, and the

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functional impact of such changes. Various reports have investigated the relevance of EVs in many diseases such as cancer [13, 14] or obesity [15, 16] but there is no much knowledge

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about the influence of the storage time on the PEVs proteome. For this reason, the main goal of this study was to analyze the proteome of EVs derived from

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PCs stored at different time points on blood bank conditions after Mirasol® PRT treatment, in order to identify biomarkers related to the platelet state during storage. 2. Material and methods 2.1 Platelet free supernatant collection Whole blood (WB) units (450±45 mL) were collected at the Regional Blood Centre, Galicia (Spain), from volunteer donors meeting the criteria set out by the national law. Donors gave their informed consent before blood collection. The WB was processed for component separation and BC were pooled in additive solution PAS III-M (final PAS/plasma ratio was

Journal Pre-proof 60/40) to obtain PC. Platelets were inactivated with Mirasol® PRT and stored for 7 days at 22°C under continuous agitation. Platelet concentrate samples (n=9) were obtained at two time points of storage, days 2 and 7. Twelve millilitres per PC were collected and platelet free supernatant (PFS) was obtained following an established protocol based on serial centrifugations. Firstly, 5 µl of prostaglandin I2 1 mg/ml (Cayman Chemical) was added per 14 ml of PC to avoid platelet activation

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followed by low centrifugation at 200 g for 20 minutes to eliminate red blood cells as

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contaminants. Supernatant was centrifuged at 1000 g for 10 minutes for platelet depletion.

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Supernatant (platelet poor supernatant) was centrifuged at 1500 g for 10 minutes and followed

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which was aliquoted and frozen at - 80°C.

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by other centrifugation at 15000 g for 2 minutes to obtain platelet free supernatant (PFS)

2.2 Extracellular vesicles isolation and characterization

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EVs were isolated by an ultracentrifugation-based protocol [15]. Transmission electron

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microscopy (TEM) and dynamic light scattering (DLS) were the techniques used to

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characterize EVs populations when standardizing the protocol for proteomic analysis. Both were performed on isolated vesicles, after the PBS washing ultracentrifugation step. Pellets were resuspended in 10% glutaraldehyde for TEM, and in 50 μl of PBS for DLS. For microscopy visualization (JEOL JEM-1011 microscope (JEOL, Inc., Peabody, MA)) one drop of sample was stained with 2% of uranyl acetate after being placed in a Cu grating and covered by a Formvar membrane. DLS analysis was performed on Zetasizer Nano-S (Malvern Instruments (UK)) to obtain sample populations distribution by intensity.

Journal Pre-proof 2.3 Protein identification by LC-MS/MS Isolated EVs were resuspended in 50 μl of sample buffer (65 mM CHAPS, 5 M urea, 2 M thiourea, 0.15 M NDSB-256, 30 mM Tris, 1 mM sodium vanadate, 0.1 mM sodium fluoride, and 1 mM benzamidine) for proteomic analysis. Protein concentration was measured using a standard colorimetric assay (Pierce Coomassie Plus (Thermo Scientific)). Following the above, 3 pools of 3 PCs per condition (each PC sampled at d2 and d7) were pooled together

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and 100 μg of protein per pool, solved in the above buffer, were supplemented with Laemmli

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sample buffer (2% w/v SDS, 5% v/v 2-mercaptoethanol, 10% v/v glycerol, 25 mM Tris, final

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concentrations, pH 6.8) and loaded on a 10% SDS-PAGE gel just to concentrate the protein

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sample in a gel band.

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Protein bands were excised from the gel and in-gel digestion was done with trypsin. Peptides were extracted carrying out three incubations of 20 minutes with 60% acetonitrile and 0.5%

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HCOOH. The resulting peptide extracts were pooled, concentrated and stored at −20 °C.

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Four micrograms of digested peptides were separated using Reverse Phase Chromatography.

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Gradient was created using a micro liquid chromatography system (Eksigent Technologies nanoLC 400, SCIEX) coupled to high speed Triple TOF 6600 mass spectrometer (SCIEX) with a micro flow source using a Data dependent workflow. The chosen analytical column was a silica-based reversed phase column YMC-TRIART C18 150 × 0.30 mm, 3 mm particle size and 120 Å pore size (YMC Technologies, Teknokroma). The trap column was a YMCTRIART C18 (YMC Technologies, Teknokroma with a 3 mm particle size and 120 Å pore size, switched on-line with the analytical column. The loading pump delivered a solution of 0.1% formic acid in water at 10 µl/min. The micro-pump generated a flow-rate of 5 µl/min and was operated under gradient elution conditions, using 0.1% formic acid in water as mobile phase A, and 0.1% formic acid in acetonitrile as mobile phase B. Peptides were

Journal Pre-proof separated using a 90 minutes gradient ranging from 2% to 90% mobile phase B (mobile phase A: 2% acetonitrile, 0.1% formic acid; mobile phase B: 100% acetonitrile, 0.1% formic acid). Injection volume was 4 µl. Data acquisition was performed in a TripleTOF 6600 System (SCIEX, Foster City, CA) using a Data dependent workflow (DDA). Source and interface conditions were the following: ionspray voltage floating (ISVF) 5500 V, curtain gas (CUR) 25, collision energy (CE) 10 and 1

(GS1)

25. Instrument was operated with Analyst TF 1.7.1 software

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ion source gas

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(SCIEX, USA). Switching criteria was set to ions greater than mass to charge ratio (m/z) 350

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and smaller than m/z 1400 with charge state of 2–5, mass tolerance 250ppm and an

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abundance threshold of more than 200 counts (cps). Former target ions were excluded for 15s.

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Peptide and protein identifications were performed with Protein Pilot software (version 5.0.1, Sciex) using a Human specific Uniprot database 2018_01, specifying iodoacetamide as

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variable and metionin oxidation as a fixed modifications. The false discovery rate (FDR) was

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set to 1% for both peptides and proteins.

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2.4 Relative quantification by SWATH acquisition Prior to protein quantification by SWATH, an MS/MS spectral library was constructed analyzing peptides by a shotgun data-dependent acquisition (DDA) approach by micro-LCMS/MS.

To get a good representation of the peptides and proteins present in all samples,

pooled vials of samples from each group were prepared using equal mixtures of the original samples. 4 μL of each pool was separated into a micro-LC system Ekspert nLC425 (Eksigen, Dublin, CA, USA) using the same conditions as before. In this assay, the gradient run consisted of 5% to 95% B for 30 min, 5 min at 90% B and finally 5 min at 5% B for column equilibration, for a total run time of 40 min. When the peptides eluted, they were directly injected into a hybrid quadrupole-TOF mass spectrometer Triple TOF 6600 (Sciex, Redwood

Journal Pre-proof City, CA, USA) operated with a data-dependent acquisition system in positive ion mode. A Micro source (Sciex) was used for the interface between microLC and MS, with an application of 2600 V voltage. The acquisition mode consisted of a 250 ms survey MS scan from 400 to 1250 m/z followed by an MS/MS scan from 100 to 1500 m/z (25 ms acquisition time) of the top 65 precursor ions from the survey scan, for a total cycle time of 2.8 s. The fragmented precursors were then added to a dynamic exclusion list for 15 s; any singly charged ions were excluded from the MS/MS analysis. Peptide and protein identifications

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were performed with Protein Pilot software (version 5.0.1, Sciex) as described previously.

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Samples were analyzed using a data-independent acquisition (DIA) method making 3

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technical replicates per sample. Samples were analyzed by SWATH-MS acquisition method performed on a TripleTOF 6600 LC-MS/MS system (AB SCIEX). The method consisted of

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repeating a cycle that consisted of the acquisition of 65 TOF MS/MS scans (400 to 1500 m/z, high sensitivity mode, 50 ms acquisition time) of overlapping sequential precursor isolation

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windows of variable width (1 m/z overlap) covering the 400 to 1250 m/z mass range with a

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previous TOF MS scan (400 to 1500 m/z, 50 ms acquisition time) for each cycle. Total cycle

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time was 6.3 s. For each sample set, the width of the 65 variable windows was optimized according to the ion density found in the DDA runs using a SWATH variable window calculator worksheet from Sciex.

The targeted data extraction of the fragment ion chromatogram traces from the SWATH runs was performed by PeakView (version 2.2) using the SWATH Acquisition MicroApp (version 2.0). This application processed the data using the spectral library created from the DDA analysis. Up to ten peptides per protein and seven fragments per peptide were selected, based on signal intensity. Five minute windows and 30 ppm widths were used to extract the ion chromatograms. The retention times from the peptides that were selected for each protein were realigned in each run according to the calibration curve retention time (iRT). The

Journal Pre-proof extracted ion chromatograms were then generated for each selected fragment ion; the peak areas for the peptides were obtained by summing the peak areas from the corresponding fragment ions. PeakView computed an FDR and a score for each assigned peptide according to the chromatographic and spectra components; only peptides with an FDR below 1% were used for protein quantitation. Protein quantitation was calculated by adding the peak areas of the corresponding peptides.

The integrated peak areas were directly exported to the

MarkerView software (AB SCIEX) for relative quantitation following Student’s t-test. Fold

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change for each protein was calculated as follows: for each day and platelet concentrate sample the average of the summation of areas was calculated (the peak areas for the peptides

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were obtained by summing the peak areas from the corresponding fragment ions); this was

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done for the four platelet concentrate samples. The fold change was calculated dividing the

significant.

FunReach

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mean of the above values at day 7 by the mean at day 2. P-value less than 0.05 was considered (http://www.funrich.org/),

Reactome

(https://reactome.org/),

and

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Cytoscape (https://cytoscape.org/) tools were used for biological pathways and interaction

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networks analyses of proteins identified.

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All proteomic data are available via ProteomeXchange with identifier PXD014694.

2.5 Western blotting

Western blot was performed following an established protocol [17] in an independent cohort of 4 PCs against CD9, ACTN1 and ITGA2B to validate the results obtained by the proteomic SWATH-based approach. The primary antibodies used were: rabbit anti-CD9 antibody (sc9148, Santa Cruz Biotechnology) dilution 1/1000; rabbit anti-ITGA2B antibody (sc-15328, Santa Cruz Biotechnology) dilution 1/500; and mouse anti-ACTN1 antibody (MAB1501,

Journal Pre-proof Merck Millipore) dilution 1/1000. Before immunoblotting, proteins were separated in 11% SDS-PAGE gels; 10 g of protein was loaded per lane. 2.6 Flow cytometry Flow cytometry was used to quantify platelet-derived microvesicles on PCs.

The protocol

used was based on that described by Cointe et al. [18] for MVs measurement in a

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FACSCalibur cytometer (BD bioscience).

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3. Results

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3.1 Characterization of EVs present in platelet concentrates: microvesicles and

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exosomes

A serial ultracentrifugation-based protocol was applied in order to isolate EVs. Some

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drawbacks of this method are that it does not permit the separation of MVs and exosomes.

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Before processing samples for proteomic analyses, the protocol was carefully established and

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validated for platelet concentrates. To characterize the samples during this protocol standardization phase, different approaches were used to identify vesicle subpopulations. By performing DLS, we found two populations of EVs: one related to exosomes, which are between 30-100 nm, and a bigger main population (100-1,000 nm) that correspond to MVs (Fig. 1). Moreover, by TEM the presence of both EVs populations was confirmed. Exosomes had a mean size around 60 nm and MVs bigger than 100 nm (Fig. 1).

Journal Pre-proof 3.2 Extracellular vesicles proteomic profile in platelet concentrates: Protein markers related to the platelet storage time For the proteomic analysis, firstly a qualitative analysis was done to characterize the proteome profile of the EVs from the PCs. For that, EVs from three PCs were pooled and analyzed individually by LC-MS/MS at different days of storage, 2 and 7. A total of 785 proteins were successfully identified, 535 proteins at day 2 of storage versus 709 proteins identified at day

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was reasonable since they belonged to the same sample.

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7. Four hundred and fifty nine proteins were overlapped between time conditions; this issue

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FunRich analysis [19] revealed that the majority of proteins identified in both days had

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exosomes as principal cellular component, confirming the presence of many proteins related

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to this subpopulation in platelet concentrates. Identifications at day 2 contained 72.6% of genes in this subcellular location versus a 66.4% present at day 7. Regarding biological

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pathways in which the identified proteins were involved, haemostasis, complement cascade

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and platelet activation and signaling were the principal routes where the vast majority of proteins detected in both conditions participate (days 2 and 7). We would like to highlight

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protein S100A9 that was suggested as marker for “young” platelets [20]. Indeed this protein was only identified in PEVs at the second day of storage. In contrast, the collagen receptor glycoprotein VI (GPVI) is on the list of proteins only identified at day 7. The majority of proteins only identified at day 2 are immunoglobulins and HLA proteins, being immune system the principal biological pathway identified by FunRich software. On the other hand, FunRich identified platelet activation, signaling and aggregation, as the most enriched biological pathway related to proteins only identified at day 7. The complete list of all proteins identified is shown in Supplementary Table 1.

Journal Pre-proof 3.3 SWATH analysis: up-regulation of platelet activation and metabolism markers at day 7 of storage In order to know protein differences between time points of storage, a relative quantification was done in an independent analysis by LC-MS/MS with SWATH acquisition. MarkerView, a data-independent method of quantitation, was used for SWATH-MS data analysis following Student’s t-test analysis for comparison among the samples based on the averaged area sums

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distinguishes the two groups, reported as a p-value.

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of all the transitions derived for each protein. The t-test indicates how well each variable

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A total of 415 proteins were identified when doing the differential analysis, but only proteins

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with p-value <0.05 and fold change ≥2 were selected as relevant. In that way we found 151

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proteins up-regulated and 3 down regulated at day 7 in PEVs derived from platelets (Supplementary Table 2). Moreover, up-regulated proteins at day 7 were analyzed by the

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Reactome software [21]. Regarding the most important biological pathways related to the

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differentially regulated proteins identified, many of them reveal the physiological state of the PC (involved in platelet activation, carbohydrate metabolism and cellular response to stress),

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and others could be related to transfusion adverse reactions (haemostasis and immune system). Linked to the latter, CCL5, also known as RANTES, was the protein identified with the highest fold change, 10. This protein is released from platelets upon activation and, together with PF4 and several glycoproteins - also found up-regulated in platelet-derived EVs at day 7 of storage (Table 1) - suggest a higher activation state of platelets during storage. Among the 151 proteins up-regulated at day 7 upon storage, many of them are indicative of the high cellular stress that platelets were suffering at that moment (Table 1). Regarding carbohydrate metabolism, glycolysis was the principal pathway affected, involving proteins that transport glucose inside cells (SLC2A3) and enzymes that regulate the last steps to lactate

Journal Pre-proof production (Fig. 2). At mitochondrial level, platelets are also affected because differential regulated proteins that are related to reactive oxygen species detoxification, such as glutathione enzymes, were found up-regulated at day 7. Many cytoskeleton proteins were also found up-regulated at day 7 (Table 1), such as DSTN and CFL1, with a fold change of 7.2 and 6.8, respectively. These cytoskeleton proteins are related to microvesicle shedding through actin depolymerisation and integrin αIIb.

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3.4 ITGA2B and CD9 are up-regulated in PEVs at days 4 and 7 of storage

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Some of the proteins identified up-regulated at day 7 of storage in the proteomic analysis were validated by western blot in independent cohorts of samples. In this case, we included an

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intermediate storage time point of 4 days. We chose ACTN1 (the most important cytoskeleton

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component), CD9 (as an exosome marker) and ITGA2B (platelet receptor essential for aggregation and marker of PEVs). The above proteins were validated on isolated PEVs

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derived from four independent units of PCs. Western blot analysis showed an enrichment of

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these proteins in PCs upon storage, reaching the maximum at day 7 of storage, in line with the

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proteomic data obtained by SWATH approach (Fig. 3). 3.5 The number of MVs is affected by inter-individual variability Flow cytometry was used to corroborate if in addition to the proteomic results, which showed many proteins up-regulated at day 7 of storage, there was also a higher number of MVs at these time point of storage. MVs of up to 160 nm and double positive to annexin V and CD41 were quantified in PFS from 7 PCs, three of them used for proteomic analysis and four used for validation studies. There was a high variability in the number of MVs per microliter (MVs/μl) between samples and storage time conditions (Fig. 4), probably due to the fact that every PC is a pool of different donors. In addition, it is important to point out that this method does not permit the visualization of exosomes because of their small size.

Journal Pre-proof 4. Discussion In the transfusion medicine field there is currently a debate about the best choice to storage platelets. Indeed one of the most challenging issues in this field is to avoid platelet activation, which could cause EVs release. During the last decades, PRT such as Mirasol® or Intercept™, have made safer PCs, avoiding bacterial growth and allowing extending platelet storage times. However, these methods are not totally innocuous on platelets and have an

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impact on the platelet proteome [10, 11, 22-26]. Nonetheless, PRT have a slight impact on

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platelets at proteome level compared with the storage time [20, 27-31]. The variables

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mentioned above, PRT and storage time, have an impact on platelet function leading to the so

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called platelet storage lesion (PSL), which is characterize by EVs release among other factors.

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There are some reports describing the impact of different platelet agonists on the EVs proteome and releasate [4, 32] but none of them focused on the proteome of EVs derived

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from resting platelets in PCs.

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In the present study we analyzed for the first time the proteome of PEVs derived from

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platelets upon storage at different time points on blood bank conditions after Mirasol® treatment. Different time points were chosen in order to identify biomarkers related to the platelet state during storage. The day 2 condition was chosen since it is the first day for transfusion of PCs after treatment with Mirasol whereas the day 7 condition was chosen because is the top limit for transfusion of treated PCs. Isolation of EVs was the first step to analyze them and for that, we applied an ultracentrifugation-based protocol because it allowed a good characterization of both EVs subpopulations (MVs and exosomes) by DLS and TEM and achieving a good protein yield. Focusing on the proteomic study, we firstly carried out a qualitative analysis to know about the proteome profile of EVs in PCs, and then an independent SWATH-based quantitative

Journal Pre-proof analysis. Regarding the former, we successfully identified by LC-MS/MS more than 700 proteins, many of them described in different platelet scenarios and by different proteomic approaches [32, 33]. Data analysis points out exosomes as the principal cellular component and platelet activation and signaling as one of the most relevant pathways related to proteins identified in both time conditions. Focusing on the proteins only identified on EVs at the beginning of the storage, protein

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S100A9 was suggested by Rijkers and collaborators [20] as a marker for “young” platelets

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because its presence in platelets decline significantly at day 5 of storage compared to days 1

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and 2; the latter is therefore in line with our data. On the other hand, the collagen receptor

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GPVI was only present in samples at day 7, which is in line with the results obtained by Hosseini et al. [34], who suggest this receptor as a valid marker of PSL due to its shedding

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rise following time storage. For the overall analysis it is also interesting to consider the possibility raised by Salunkhe and colleagues of the presence of a population of “naturally

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old” platelets in the PCs that may have some impact in the population of EVs that are released

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at the beginning of storage, especially during the first day [27].

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Regarding the results obtained by SWATH-based differential analysis, many proteins were identified up-regulated at day 7, which provides a considerable amount of information about PSL. One example is CCL5, which is the protein with the highest up-regulated fold change identified. CCL5 is reported as a marker of platelet activation together with PF4 [35], also increased at the last day of storage. Both proteins are able to chemoattract monocytes, eosinophil and neutrophils, which could generate transfuse adverse reactions. Indeed, changes in glycoproteins expression on the platelet surface are another signal of platelet activation [35], which is corroborated by our results.

Journal Pre-proof Interestingly, many EVs proteins increased at day 7 of platelet storage shed light on the metabolic state of platelets during storage. Thus, the majority of enzymes that take part in the glycolysis pathway were found increased at day 7, deriving in lactate production and increased levels of bicarbonate to buffer the pH of the medium. CA2, one of these proteins, is known to be the enzyme responsible for the dissociation of bicarbonate in CO 2 and water. The data obtained supports the evidence of higher levels of H2 CO 3 and lactate after 7 days of storage, corresponding to a dysfunction on platelet carbohydrate metabolism. Furthermore, an

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up-regulation of glycolysis generates metabolic stress and production of reaction oxygen species, which are detoxified by different enzymes, such as glutathione enzymes, highly

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expressed in EVs at day 7 of storage.

Finally, cytoskeleton proteins, such as CAPN1, GSN, TLN1, DSTN and CFL1were also

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found up-regulated in EVs after 7 days of storage. The two first promote MVs shedding by cleaving and removing actin capping after increased levels of cytosolic calcium [36]. The

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three latter are associated with ITGA2B, receptor implicated in MVs shedding in resting

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platelets by cytoskeleton destabilization [37].

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Validation assays were made by western blot to corroborate the results described above. Three principal proteins thoroughly described on PEVs were selected and found up-regulated at day 7 of storage in line with the proteomic data. Two of them CD9, and ITGA2B, were selected for being markers of exosomes and MVs respectively. Indeed, ITGA2B is a platelet receptor essential for aggregation and related to EVs release in absence of stimulus [37]. The third protein selected was ACTN1 because cytoskeleton reorganization is related to MVs shedding. The three proteins were successfully found highly expressed in an independent cohort of PCs,

validating the results previously found by SWATH-based analysis.

Interestingly, the levels of the three validated proteins are already increased in PEVs from

Journal Pre-proof PCs after 4 days of storage. Given this is a common time limit for transfusion of PCs in blood banks, our overall results should be taken in consideration by the transfusion medicine field. In addition to the above, we also analyzed the number of MVs released during storage to see whether there was some sort of parallelism with the proteomic data. We did the analysis by flow cytometry using annexin V and CD41 as markers and we observed that the numbers between days and samples were very variable. This variability could be explained because

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every PC is a pool of buffy coats from different donors. Moreover, PCs were made as buffy

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coats from men and women and it is known that gender, among other variables, could have an

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impact on MVs count [38, 39]. In addition, it should be pointed out that exosomes were not

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detected by flow cytometry.

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5. Conclusion

As a conclusion, the present study constitutes the first proteomic analysis of EVs derived

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from PCs stored on blood bank conditions. The study presents information about PSL by the

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analysis of EVs, indicating a higher platelet activation state in PCs treated with Mirasol®

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upon storage, with differences already evident after 4 days of storage. Proteins up-regulated on EVs at day 7 of storage could be suggested as biomarkers of PSL. Overall, our results open a new field of research to focus on the physiological role of PEVs in PCs and in transfusion adverse reactions. Acknowledgements The authors would like to thank the technical staff from the Center for Research in Biological Chemistry and Molecular Materials (CiQUS), Universidade de Santiago de Compostela, for their support for EVs isolation.

Journal Pre-proof Funding This work was supported by the Consellería de Cultura, Educación e Ordenación Universitaria, Xunta de Galicia [predoctoral grant 2018 Call; Centro Singular de investigación de Galicia accreditation 2016-2019, ED431G/05; and GRC Call, GRC2014/011). Co-funding by the European Regional Development Fund (ERDF) is also gratefully acknowledged. Conflict of interest

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The authors declare no conflict of interest.

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[39] Nielsen MH, Beck-Nielsen H, Andersen MN, Handberg A. A flow cytometric method for characterization of circulating cell-derived microparticles in plasma. J Extracell Vesicles 2014; 3(1):20795.

Journal Pre-proof Table 1: Selection of proteins found up-regulated in platelet-derived extracellular vesicles at day 7 of storage versus day 2 (fold change ≥2). Fold change

CCL5

10

ITGB3

4.2

ITGA2B

4.2

GP1BB

3.8

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Platelet receptors/signaling/secreted proteins

3.8

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GP9

3.6

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CLEC1B

3.6

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ITGA6 CD36

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LYN

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ITGA2

PF4 GP1BA Proteins

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CSK

related

to

reactive

2.7 2.6 2.5

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ITGB1

3.3

2.4 2.3 2.0 oxygen

species

detoxification PRDX6

4.2

GSTP1

3.9

GSTO1

3.9

Cytoskeleton proteins DSTN

7.2

CFL1

6.8

VCL

4.5

TLN1

4.2

CAPN1

3.1

FLNA

2.7

ACTN1

2.6

GSN

2.6

MSN

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2.1

Journal Pre-proof Figure legends Figure 1: Characterization of PEVs sub-population: microvesicles and exosomes. A) DLS analysis. Diagram of size distribution by intensity is shown. Two populations were identified, exosomes between 30-100 nm and MVs between 100-1,000 nm. Blue, red and green lines represent triplicates. B) Characterization by transmission electron microscopy: MVs (size > 100 nm) and exosomes (around 50 nm). Enlarged images of representative MVs

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and exosomes are shown. Figure 2: Cytoscape-Wikipathways analysis: PEVs proteins involved in glycolysis and

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gluconeogenesis pathway provides clues about the platelet metabolism state upon

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storage. Many proteins taking part in this pathway were found up-regulated in EVs at day 7

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of storage (in blue), especially enzymes that regulate the last steps to produce lactate. Figure 3: Western blot analysis confirms CD9, ACTN1 and ITGA2B are up-regulated at

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days 4 and 7 of storage. A) Validation analysis of the SWATH approach. A new cohort of 4

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independent PCs samples was analyzed at days 2 and 7; B) Validation analysis in an

means “day”.

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independent cohort of PCs samples, including an intermediate storage time point, day 4. “d”

Figure 4: FACS analysis confirms variability in the number of platelet MVs between samples and storage time conditions. The number of MVs per microliter, CD41 and annexin V positive, at different storage days is shown. Data is represented by mean ± SD. Supplementary Table legends Supplementary Table 1. Qualitative analysis: Proteins identified by LC-MS/MS in all samples.

Journal Pre-proof Supplementary Table 2. Quantitative analysis: Summary of proteins identified, and differences in abundances, following SWATH analysis. A fold change (FC) above 1 indicates that the variation is favorable to day 7. Significant differences are those with a p

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value lower than 0.05.

Journal Pre-proof Highlights

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  

More than 700 proteins were identified in EVs from platelet concentrates at different days of storage. SWATH analysis revealed an up-regulation of 151 proteins at day 7 of storage. Platelet activation and glycolysis among the most up-regulated pathways. High variability in the number of EVs between samples and days of storage.

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