Circulating pre- and postprandial extracellular vesicle proteomic profiles

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Garza, Elisa Wider-Eberspächer, Lorena Morton, Marco van Ham, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4426110/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Oct, 2024 Read the published version in Scientific Reports → Version 1 posted 12 You are reading this latest preprint version Abstract Extracellular vesicles (EVs) are key in intercellular communication, carrying biomolecules like nucleic acids, lipids, and proteins. This study investigated postprandial characteristics and proteomic profiles of circulating large extracellular vesicles (lEVs) in healthy individuals. Twelve participants fasted overnight before baseline assessments. After consuming a controlled isocaloric meal, lEVs were isolated for proteomic and flow cytometric analysis. Plasma triacylglyceride (TAG) levels confirmed fasting completion, while protein concentrations in plasma and lEVs were monitored for postprandial stability. Proteomic analysis identified upregulated proteins related to transport mechanisms and epithelial/endothelial functions postprandially, indicating potential roles in physiological responses to nutritional intake. Enrichment analyses revealed vesicle-related pathways and immune system processes. Flow cytometry showed increased expression of CD324 on medium-sized CD9 + CD63 + CD81 + EVs postprandially, suggesting an epithelial origin. These findings offer insights into postprandial lEV dynamics and their physiological significance, highlighting the need for stringent fasting guidelines in EV studies to account for postprandial effects on EV composition and function. Biological sciences/Chemical biology/Proteomics Health sciences/Biomarkers Postprandial extracellular vesicles plasma liquid biopsy proteomics fasting Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Extracellular vesicles (EVs) have garnered significant attention in the scientific community due to their critical roles in intercellular communication and their potential use as diagnostic and therapeutic agents 1 – 4 . These robust particles, released by various cell types, carry a diverse and mixed cargo of proteins, nucleic acids, and lipids, reflecting the physiological state of their parent cells 5 – 7 . EVs are found in various bodily fluids, including urine, saliva, amniotic fluid, cerebrospinal fluid, serum, and plasma 8 – 13 . Among these, blood and its derivatives are the most frequently utilized biofluids in research due to their ease of access through minimally invasive and well-established procedures 14 – 16 . The study of EV dynamic compositions in the context of physiological stimuli, such as fasting and postprandial states, is of considerable interest due to their physiological functions such as platelet biology, inflammation and immunity, the regulation and maintenance of blood pressure, regulation of water and salt levels in urine, pregnancy, fertilization and implantation among others, and potential clinical applications, particularly concerning liquid biopsies and cargo and delivering of therapeutic molecules 4 , 17 . Due to the influence of fasting on the isolation, composition, and abundance of EVs in the circulation 18 , 19 , a growing interest in the isolation and characterization of plasma-derived EV has been developed. Additionally, prior research acknowledged challenges entailed with EV separation from peripheral blood that are attributed to the presence of lipoproteins of similar size in blood after food consumption (Liang et al., 2021). Despite the recognized need, standardized guidelines regarding fasting status for the accurate isolation of plasma EVs are yet to be established. Various techniques for separating EVs offer unique strengths and limitations that vary based on the specific research objectives 22 . Recently, we have demonstrated the efficacy of using differential centrifugation to enrich lEVs in our samples, particularly when preparing samples for flow cytometry analyses (Garza et al., 2023). To study whether fasting is necessary before sample collection, we aimed in this study to investigate the impact of fasting status on (i) EV abundances and (ii) protein content and composition. This investigation is particularly pertinent given the challenges associated with implementing fasting in specific research contexts, potentially posing constraints within heterogeneous population samples, such as pediatric studies, and in individuals with metabolic conditions. Results No alteration in plasma and EV protein concentrations during the post-prandial state We examined the postprandial alterations in circulating EVs within a cohort of twelve healthy participants (median age 25 ± 3.6 years old, 6 females, median body mass index (BMI) 23.78 ± 2.7). Participants were instructed to undergo an overnight fasting period (median 13 ± 2.3 h) (Figure 1A), where plasma and circulating EVs) were isolated for baseline assessments (referred to as the “pre” group). Subsequently, an isocaloric meal was administered, and after a 75-min interval, a second round of blood sample collection (referred to as the “post” group) was conducted. After all samples were collected, EVs were applied for a comprehensive analysis utilizing proteomics and multicolor flow cytometry. This experimental setup (Figure 1B) aimed to discern the impact of a standardized meal on the compositional and quantitative aspects of EVs in the pre-and postprandial state, contributing to our understanding of the EV dynamic response to nutritional stimuli. Triacylglycerides (TAGs) are known to increase in the post-prandial state following an overnight fast, which we could validate with a significant increase in plasma TAG levels measured at 75 min postprandially (pre, 0.8008 ± 0.1472 mmol/L; post, 1.349 ± 0.3439 mmol/L, p = <0.0001) (Figure 1C). Subsequently, we assessed the protein concentrations in plasma and circulating EVs at both pre-and postprandial time points. The outcomes indicated that protein levels remained relatively stable between both conditions in plasma (pre, 73.96 ± 15.7 mg/mL; post, 73.96 ± 20.04 mg/mL, p = 0.9097) and EVs (pre, 0.2558 ± 0.1155 mg/mL; post, 0.3106 ± 0.1505 mg/mL, p = 0.3275), as depicted in Figure 1D. Given the variability in fasting durations among participants, we conducted a correlation analysis to investigate potential associations between fasting times and changes in protein levels. Our analysis revealed no significant correlation between fasting duration and the protein concentrations in circulating EVs in both pre- ( r = 0.1241, CI = -0.4843 to 0.6516, p = 0.7008) and postprandial (r = 0.0452, CI = -0.5427 to 0.6035, p = 0.8889) conditions (Figure 1E). Proteomic insights into postprandial extracellular vesicle dynamics To gain a comprehensive understanding of the protein composition within our EV samples, three participants were randomly selected to conduct an in-depth assessment of EV protein content utilizing proteomic techniques and mass spectrometry in pre- and post prandial conditions. This approach facilitated a detailed exploration into the protein distribution of 2230 proteins across samples, revealing consistent protein abundances in all samples (Figure 2A). Subsequently, we investigated differentially regulated proteins between pre- and postprandial states in healthy participants. For that, and to enhance robustness of our data, only proteins that were identified and quantified in all three samples of either the pre- or postprandial group were considered. Generally, we found more proteins to be enhanced in EVs at the postprandial time point (Figure 2B). Notably, several proteins implicated in epithelial and endothelial cell functions exhibited significant upregulation in the postprandial state, including EPPK1 (epiplakin), ITGA5 (integrin sub-unit alpha 5), SMTN (smoothelin), and ESAM (endothelial cell adhesion molecule) (Figure 2B), emphasizing their potential role in postprandial physiological processes. Due to the difficulties separating lipoproteins from EVs, we evaluated the main apolipoproteins associated with food intake (Figure 2C). We assessed the abundance of ApoB, ApoA1, ApoA4, ApoE, ApoA, ApoH, ApoOL1, ApoD, ApoC3, ApoA2, ApoC1, ApoC4 and ApoM and found similar levels between pre- and post conditions (Figure 2C). Additionally, considering the potential presence of platelet proteins in our sample, we examined 24 platelet proteins, of which we detected 17 (Figure 2D) 24 . Subsequently, we explored whether the presence of platelet proteins varied depending on fasting status. This analysis unvailed a significant upregulation of only one protein, protein kinase C beta type (PKCB), in the postprandial group (p = .0386). Notably, this protein plays a role in various biological processes, including B-cell activation and the regulation of endothelial cells in the brain microvasculature and its expression is not exclusive to platelets 25,26 . Enriched Gene Ontology (GO) and reactome pathways analysis. To identify prominent biological processes and pathways involved in lEV dynamics, we conducted protein enrichment analyses using the differently abundant EV proteins when comparing the pre- and postprandial states (Figure 3). First, utilizing differentially expressed proteins with regulation lower than -2 and/or higher than 2 and p value above 1.3 an in-depth network analysis of the interaction between the differentially expressed proteins utilizing the STRING database was performed, revealing significant enrichment within the "Extracellular exosome" network (Figure 3A). Further analysis of enriched reactome pathways and biological processes (GO) in our sample unveiled an expected emphasis on vesicle-related pathways, encompassing transport and membrane trafficking. Moreover, pathways and biological processes related to the immune system emerged prominently within the enriched pathways and processes (Figure 3B-C). Detailed examination of the proteins associated with these processes revealed a subset of proteins intricately involved in both epithelial and endothelial functions (Figure 2B). Increased EV surface expression of epithelial marker CD324 on postprandial lEVs Driven by the hypothesis that proteins identified in large EVs engage in communication with the endothelial and epithelium postprandially, we conducted multicolor flow cytometry to examine specific surface markers on lEVs related to these cell types (Figure 4A and B). We selected CD31 and CD106 as enriched expression markers on endothelial cells and CD44 and CD324 on epithelial cells. Our results showed no significant changes in the total concentration of EVs per microliter between the pre- and postprandial states (pre, 16890 ± 3630 lEVs/mL; post, 14003 ± 2834 lEVs/mL, p = .6878) showing a clear correlation with the protein levels assessed via colorimetric assay in which also no changes were present (Figure 1D). Indeed, we observed a significant increase in the postprandial expression of CD324 on EVs (tetraspanin + , size gate + ), a marker known for its role in cell-cell adhesion, mobility, and proliferation of epithelial cells (Figure 4C-D) (pre, 45.03 % ± 2.102; post, 46.64 % ± 2.45; p = .0294). In conclusion, our findings demonstrate a significant increase in postprandial expression of the epithelial marker CD324 on lEVs, supporting the hypothesis of their engagement in communication with epithelial cells following food intake. Discussion In this study, plasma concentrations and the molecular composition of EVs were assessed in postprandial states of healthy individuals. Our results provide a novel insight into the proteomic landscape and changes in specific surface markers on EVs in response to nutritional intake with further consequences for biomarker research. Previous results using flow cytometry indicate increased concentration of plasma EVs postprandially 27 . In our study, we evaluated the possible differences via colorimetric assay and found similar protein concentrations in plasma and EVs in both fasting and postprandial samples. Upon targeted flow cytometry evaluation of lEVs, no alteration was detected in the total number of lEVs. Furthermore, our analysis revealed that EVs maintain a consistent protein concentration, regardless of the fasting duration, and indicate a tightly controlled homeostatic mechanism with no significant effect in response to short-term changes in nutritional status. From a physiological perspective, the stability of EV protein levels despite fasting states emphasizes the EVs potential to serve as stable carriers of biological signals, of particular importance in the context of diagnostic biomarker development, where EVs can provide a reliable snapshot of biological states independent of a fasting period. For clinicians and researchers, it suggests that EV-derived biomarkers may not require strict controls for fasting duration, simplifying the sample collection protocol and expanding the applicability of EV-based diagnostics. It is recommended that studies involving plasma-derived EVs report fasting status if known, along with the duration of the fasting period 28 . Our present results demonstrate that quantitatively via flow cytometry using specific identification markers, there are no significant fluctuations observed in EVs concerning fasting status. While our results revealed that the overall protein concentrations in plasma and circulating EVs remained relatively stable, it is crucial to distinguish this overall stability from the changes observed at the proteomic level. A notable challenge in isolating EVs from plasma is the presence of large lipoproteins, such as low-density lipoprotein (LDL), which share physical characteristics with EVs 21 . LDL predominantly comprises Apolipoprotein B (ApoB). Thus, we evaluated its presence, along with various other apolipoproteins, in our EV sample, and our findings revealed no significant changes between the two conditions, indicating the minimal impact of fasting on EVs at the proteomic level. Another potential concern in EV isolation is contamination with platelets. To address this, we evaluated to methods of isolating PPP, assessed platelet presence via flow cytometry, and observed no significant differences in platelet quantity between the two methods (Supplementary Fig. 1). It is worth highlighting that various protocols exist for PPP isolation, with Method 2 (2x, 2500g for 20 min) being the most widely accepted within the EV community 29 , 30 . Although our results did not show significant changes, a discernible trend suggest the presence of platelets, which could potentially affect downstream analyses. Therefore, for consistency and reproducibility, we recommend adhering to the Method 2 and the general guidelines outlined by the International Society for Extracelluar Vesicles (ISEV) 22 . Our proteomic data indicates the enrichment of an "Extracellular Exosome" network, affirming the effectiveness of our isolation method in yielding a sample enriched with EVs. Further, our proteomic analysis revealed a distinct landscape of EV protein composition, characterized by a significant postprandial upregulation of proteins associated with transport mechanisms, as well as proteins integral to epithelial and endothelial cell functions. This upregulation indicates that, although the total protein content may remain unchanged, the proportion of specific types of proteins within the EVs and the prevalence of certain EV subpopulations is altered in response to food intake. These findings suggest a selective enrichment or mobilization of EVs carrying proteins crucial for postprandial physiological processes, reflecting an adaptive response to such a metabolic state. Recent studies have delved into the multifaceted roles of EVs across physiological and pathological processes, indicating their critical function in nucleic acid and protein transfer, receptor sequestration, interaction with the extracellular matrix (ECM), and their emerging role in endocrinology and tissue repair 31 , 32 . Other omics approaches, such as lipidomics, have also proven helpful in the understanding of EV function in homeostasis and metabolic changes 33 . These studies elucidate the mechanism through which EVs promote intercellular signaling and are consistent with our findings of postprandial EV dynamics where we have observed a marked increase in proteins linked to transport and cellular communication. The identification of enriched gene ontology (GO) and Reactome pathways related to vesicle-mediated transport, membrane trafficking, and immune system processes further emphasizes the complex involvement of EVs in systemic physiological responses. The analysis of proteins implicated in enriched networks revealed heightened levels of endothelial and epithelial-related proteins. This finding holds particular significance given the pivotal roles of both intestinal and vascular barriers in mediating inter-system communication, particularly in the context of gut-periphery interactions during physiological processes 34 . Notably, the coordinated postprandial upregulation of epiplakin (EPPK1), a protein predominantly expressed in epithelial and glandular cells that are also present in the gastrointestinal tract, and integrin sub-unit alpha 5 (ITGA5), an integrin primarily expressed in intestinal tissue and endothelial cells, suggests a coordinated gastrointestinal response detectable in lEV composition 35 , 36 . Similarly, the postprandial upregulation of smoothelin (SMTN) and endothelial cell adhesion molecule (ESAM) postprandially underscores the potential involvement of EV-mediated communication between the digestive system and peripheral tissues 37 – 39 . These observations hint at an unexplored mechanism of communication facilitated by EVs following food intake involving endothelial and epithelial, affirming further investigation. For this purpose, we evaluated the surface expression of epithelial and endothelial markers on lEVs via flow cytometry. Our results revealed increased surface expression of the epithelial marker CD324 on lEVs postprandially. This could involve epithelial cells in the gut that release EVs in response to direct contact with nutrients and may contribute to regulating the intestinal barrier and nutrient absorption. The postprandial gut feedback, where intestinal epithelial cells release molecules such as peptides and hormones, has been previously described 40 , 41 . Similarly, exploring EV interactions with the ECM 42 complements our findings of increased epithelial and endothelial marker expressions following food consumption, suggesting a distinct role for EVs in modulating tissue responses to nutritional intake. Additionally, the capabilities of EV cargo in clinical diagnostics, as discussed by Qian et al. 43 , parallels our detection of specific postprandial alterations in EV protein composition, highlighting the diagnostic and therapeutic potential of understanding EV protein shift in response to food intake. The growing body of evidence regarding EVs and their role in intercellular communication further corroborates the importance of our findings, suggesting that postprandial EV profiles may be crucial in systemic metabolic regulation and intercellular communication 44 , 45 . Collectively, our results further unravel EV behavior and their physiological adaptation in postprandial states. By directly addressing previously identified gaps in the literature regarding the influence of fasting on EV phenotypes 28 , our results improve EV research methodologies and their physiological relevance. Our study employs a comprehensive approach to investigate the effects of fasting on plasma concentrations and molecular composition of EVs encompassing analytical techniques such as flow cytometry and proteomics. We also addressed the current gap in the literature about the stability of plasma and EV protein concentrations in response to nutritional intake and shed light on the changes in EVs during fasting and postprandial states and informing future research guidelines. We also describe which EV-derived markers and proteins are differentially expressed in two conditions during homeostasis, thereby possibly simplifying sample collection protocols and expanding the applicability of EV-based diagnostics. However, our study is limited by a relatively small sample size, which may affect the generalizability of our findings. A larger cohort would enhance the statistical power and robustness of the results. While this study employs established EV isolation protocols and identification techniques, such as differential centrifugation and flow cytometry and mass spectrometry, there may be inherent methodological limitations associated with each approach, which could impact the accuracy and reproducibility of the results. Overall, while this study provides valuable insights into the effects of fasting on EV proteomics, its findings should be interpreted cautiously considering the aforementioned limitations. Methods Experimental setup and blood withdrawal. Twelve young, healthy participants (6 females, 6 males, mean age ± SEM: 26,42 ± 1,05 years, range: 23–32 years) were prospectively recruited at the Medical Faculty of the Otto von Guericke University in Magdeburg, Germany. The experimental procedure was approved by the guidelines of the local committee of the Medical Faculty, Otto-von-Guericke Magdeburg (No 07/17). Inclusion criteria were age over 18 years, overnight fast of ≥ 12 hours (no alcohol, sugar-containing beverages, and food consumption). Exclusion criteria were acute diseases, chronic conditions (cardiovascular, neurological, psychiatric), uncontrolled metabolic disease, pregnancy, current or recent smoking, and alcohol abuse. Every participant gave written informed consent. To determine the effects of fasting, peripheral blood was collected in the fasting state (pre-group) to establish an individual baseline, after which a standardized meal was provided. The meal was approximately 915 kcal, consisting of 34.8% fat, 55.42% carbohydrates, and 9.78% protein. The second studied time point was 75 min postprandial (post). Blood was collected to two sterile acid citrate dextrose (ACD) BD Vacutainer tubes containing 1 ml of ACD, and one lithium heparin coated (LH PST™ II) BD Vacutainer from a cubital vein at both time points. Tubes were inverted twice to ensure the incorporation of the agents and whole blood. All samples were processed within 1 hour of collection. Triacylglycerides measurement. Blood collected in lithium heparin-coated tubes was centrifuged within one hour at 1.5 x 10 3 g for 10 min at 4°C. Plasma was transferred to sterile tubes and stored at -80°C until further processing. Samples were sent to and measured by the Institute of Clinical Chemistry at the Medical Faculty of Otto von Guericke University. Extracellular vesicle isolation. First, two methods were investigated in order to obtain platelet-poor plasma (PPP). Method 1 consisted of two centrifugation steps of the ACD blood at 1,5 x 10 3 g for 10 min at room temperature (RT). Method 2 consisted of two steps of ACD blood centrifugation at 2,5 x 10 3 g for 20 min at RT. Further, lEVs were enriched as previously described (Garza et al., 2023; Pospichalova et al., 2015). PPP from both methods was then transferred to fresh clean tubes and centrifuged at 14 x 10 3 g for 70 min at 4°C. Further, the supernatant was carefully removed, and the pellet was resuspended in 0.22 µm filtered phosphate-buffered saline (PBS) without Ca2 + and Mg2+ (fPBS-/-) and vortexed to ensure the solution of the previously formed pellet. This step was followed by another round of centrifugation 14 x 10 3 g for 70 min at 4°C, after which the supernatant was removed, and the pellet was reconstituted in fPBS −/− . Samples were stored at -80°C until further experiments. Protein concentration measurement. Heparin plasma and EVs were thawed on ice and vortexed before further processing. Bio-Rad protein assay 48 was performed according to instructions provided by the manufacturer (500-0006 Bio-Rad). Briefly, EVs were diluted 1:100 and plasma was diluted 1:4000 both in distilled water. Bovine serum albumin (BSA, BioRad Laboratories, USA) 1mg/ml was used to determine the standard curve. Bradford reagent was mixed 1:5 with the respective sample and added to a 96-well plate. Samples were measured at 595 nm using a SpectraMax M5e microplate reader (Molecular Devices LLC). Each sample and standard were measured as technical triplicates and averages were calculated for further analysis. Flow cytometry. Aliquots of EVs were thawed on ice and vortexed to ensure a homogenous sample. 50 µl per sample were added to a 96-well plate with 35 µl of fPBS −/− per well. Diluted samples were stained with labelled tetraspanin marker-specific antibodies CD9, CD63, CD81 (Allophycocyanin, BioLegend), hyaluronic acid receptor CD44 (Alexa Fluor 700), CD324 (Peridinin chlorophyll protein-Cyanine 5.5, BioLegend) and endothelial markers CD106 (Phycoerythrin, BioLegend), CD31 (Fluorescein isothiocyanate, BioLegend) and for 30 min at 4°C. Following this, samples were washed and resuspended in fPBS-/-. To confirm the presence and purity of EVs samples were prepared as described above and lysed for 10 min with 0.1% Triton X solution. To identify the events on the size range of EVs, 300 nm to 1000 nm size reference silica beads (CD Bioparticles) were used. For quantification of events, AccuCheck counting beads (Invitrogen) were added to each sample and calculations were performed following the manufacturer’s instructions. Samples were acquired using the AttuneNxT flow cytometer (ThermoFisher) equipped with a small particle side scatter filter. Sample acquisition speed was set to 25 µl per min, SSC-threshold was set to 0.18 x 10 3 and FSC-threshold was set to 0.15 x 10 3 . Each sample measurement was followed by 10% bleach and filtered distilled water to prevent carryover from the previous sample. Data were transferred to FlowJo 10.9.0 and gated on tetraspanin positivity and FSC and SSC utilizing the previously established size gate (Fig. 4 A). Further, plots were generated using t-distributed stochastic neighbor embedding (t-SNE) algorithm for which events were down sampled using the DownSample plug-in. 6,700 size and tetraspanin positive events per sample were used and concatenated followed by tSNE utilizing all compensated parameters for 1,000 iterations and perplexity of 20, approximate random projection forest (ANNOY) as KNN (k-nearest neighbor) and FFT (Fast Fourier Transformation) interpolation as gradient algorithm. Further statistical analyses were performed using GraphPad Prism 10.1.1. Data was assessed for normality of distribution using D’Agostino & Pearson and Shapiro-Wilk tests, and paired t-tests or Wilcoxon tests were performed accordingly. Proteomics. EVs were suspended in 200 µl PBS and stored for further proteomic analyses. For protein recovery, protein digestion and peptide clean-up, a slightly adapted SP3 protocol was applied 49 . For that, extracellular vesicle samples were diluted in lysis buffer to final concentrations of 2 %sodium dodecyl-sulfate (SDS), 100mM NaCl and 250mM triethylammonium bicarbonate (TEAB), and were supplemented with complete protease inhibitor cocktail (Roche). Lysis was increased by sonication using 10 cycles of a standard 30 seconds on/off Bioruptor protocol (Diagenode). Proteins were reduced for 1 hour at 55°C using a final concentration of 5 mM Tris(2-carboxyethyl)phosphine P(CH 2 CH 2 COOH) 3 (TCEP) followed by reduction for 30 min at room temperature using a final concentration of 10 mM s-Methyl methanethiosulfonate (MMTS). Carboxylate beads (20 µl) were added, and proteins were allowed to bind overnight upon acetonitrile (ACN) addition to a final concentration between 50 and 60 % Beads were washed twice with 80 %ethanol and once with 100 %ACN and allowed to dry on air. Beads were suspended in 50 µl 200 mM TEAB containing 5 mM TCEP and 10 mM MMTS. Trypsin was added in a ratio of 1 µg trypsin to 30 µg protein and proteins were digested overnight at 37°C while shaking. Peptides were allowed to bind overnight upon ACN addition to a final concentration of at least 90 % Beads were spun down and supernatants transferred to LoBind Eppendorf tubes and stored for further analyses. Beads were washed three times with 100 %ACN. Peptides were eluted by using first 20 µl 2 %Dimethyl sulfoxide (DMSO) followed by a second step with 20 µl Millipore H 2 O. Purified peptides were vacuum dried, and pellets were suspended in 40 µl 0.1 %formic acid. For liquid chromatography–mass spectrometry (LC-MS/MS) analyses, all samples were measured as triplicates on a Evosep One HPLC (Evosep) connected to a TimsTOFPro mass spectrometer (Bruker) equiped with PaSER Version 2022c (Bruker) for real-time database searches. Samples were applied onto C18 Evotips (EV-2001; Evosep) according to manufacturer’s protocol. The Evosep One HPLC was operated with the standard 60 sample per day method (21 min gradient at a flow rate of 1.0 µl/min; buffer A: 0.1 %formic acid, buffer B: 0.1 %formic acid in acetonitrile). For the TimsTOFPro mass spectrometer, the standard MSMS Bruker method “DDA PASEF method for short gradients with 0.5 s cycletime” was employed. MS settings were: scan begin 100 m/z; scan end 1700 m/z; ion polarity: positive; scan mode: PASEF. Tims settings were: mode custom; number of PASEF ramps: 4; charge minimum: 0; charge maximum: 5; 1/K0 start 0.75 V*s/cm2; 1/K0 end 1.4 V*s/cm2; ramp time: 100.0 ms; MS average: 1. For protein and peptide identification and quantification, raw data files were loaded and run on the PEAKS software (PEAKS studio Xpro, Bioinformatics Solutions) using following settings; parent mass error tolerance: 20.0 ppm; fragment mass error tolerance: 0.03 Da; enzyme: trypsin; max missed cleavages: 2; peptide length range: 6–45; fixed modifications: beta-methylthiolation (C) + 45.99; variable modifications: oxidation (M) + 15.99; database: human release 15 November 2021. Downstream analyses, data presentation and statistical analyses were performed using Perseus V2.0.9.0, STRING database version 12.0 and GraphPad Prism 9.3.1. Abbreviations ACD, acid citrate dextrose; ACN, acetonitrile; ANNOY, approximate random projection forest; Apo, apolipoprotein; BMI, body mass index; DMSO, dimethyl sulfoxide; ECM, extracellular matrix; EPPK1, epiplakin 1; ESAM, endothelial cell adhesion molecule; EV, extracellular vesicle; FFT, fast fourier transformation; fPBS, filtered PBS; GO, gene ontology; ITGA5, integrin sub-unit alpha 5; KNN, k-nearest neighbor; LC-MS/MS, liquid chromatography–mass spectrometry; LDL, low-density lipoprotein; lEV, large extracellular vesicle; LH, lithium heparin; MMTS, s-Methyl methanethiosulfonate; PBS, phosphate-buffered saline; PKCB, protein kinase C beta type; PPP, platelet-poor plasma; RT, room temperature; SDS, sodium dodecyl-sulfate; SEM, standard error of the mean; SMTN, smoothelin; t-SNE, ). t-distributed stochastic neighbor embedding; TAG, triacylglycerides; TCEP, tris(2-carboxyethyl)phosphine P(CH 2 CH 2 COOH) 3 ; TEAB, triethylammonium bicarbonate. Declarations Author contributions IRD conceived the presented idea, designed the study, supervised analyses and edited the manuscript. IRD, LJ and EB were responsible for supervision, project administration and manuscript revisions. EWE recruited the participants and carried out experiments and analyses of plasma-derived lEVs, wrote and edited this manuscript. APG performed the experiments, data analyses, data interpretation, performed data visualization and wrote the manuscript. LM contributed to sample preparation, measurements, analyses and edited the manuscript. MVH carried out the proteomics experiments, analyses, and data visualization. EP read and edited the manuscript. All authors approved the submitted version. Competing interests The authors declare no competing interests Data availability The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Ethics declarations This study adhered to the ethical principles outlined in the Declaration of Helsinki. Prior to participation, written informed consent was obtained from all participants in accordance with institutional guidelines and ethical standards. Confidentiality and anonymity of participants were rigorously maintained throughout the study duration. Competing interests The authors declare that they have no competing interests Funding This work was supported by the following grants: DZPG-CIRC, NVKP_16-1-2016-0004, VEKOP-2.3.2-16-2016-00002, VEKOP-2.3.3-15-2017-00016, TKP2021-EGA-23, RRF-2.3.1-21-2022-00003 and 2019-2.1.7-ERA-NET-2021-00015, and EU’s Horizon 2020 grant No. 739593. References Kumar, M. A. et al. Extracellular vesicles as tools and targets in therapy for diseases. Signal Transduction and Targeted Therapy 2024 9:1 9 , 1–41 (2024). Shah, R., Patel, T. & Freedman, J. E. Circulating Extracellular Vesicles in Human Disease. 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Impact of preanalytical conditions on plasma concentration and size distribution of extracellular vesicles using Nanoparticle Tracking Analysis. Sci Rep 8 , (2018). Nasu, M., Khadka, V. S., Jijiwa, M., Kobayashi, K. & Deng, Y. Exploring Optimal Biomarker Sources: A Comparative Analysis of Exosomes and Whole Plasma in Fasting and Non-Fasting Conditions for Liquid Biopsy Applications. Int J Mol Sci 25 , 371 (2023). Liang, Y., Lehrich, B. M., Zheng, S. & Lu, M. Emerging methods in biomarker identification for extracellular vesicle-based liquid biopsy. J Extracell Vesicles 10 , e12090 (2021). Sódar, B. W. et al. Low-density lipoprotein mimics blood plasma-derived exosomes and microvesicles during isolation and detection. Sci Rep 6 , (2016). Welsh, J. A. et al. Minimal information for studies of extracellular vesicles (MISEV2023): From basic to advanced approaches. J Extracell Vesicles 13 , e12404 (2024). Garza, A. P. et al. Initial and ongoing tobacco smoking elicits vascular damage and distinct inflammatory response linked to neurodegeneration. Brain Behav Immun Health 28 , 100597 (2023). Burkhart, J. M. et al. The first comprehensive and quantitative analysis of human platelet protein composition allows the comparative analysis of structural and functional pathways. Blood 120 , e73–e82 (2012). Kadir, R. R. A., Alwjwaj, M. & Bayraktutan, U. Protein kinase C-β distinctly regulates blood-brain barrier-forming capacity of Brain Microvascular endothelial cells and outgrowth endothelial cells. Metab Brain Dis 37 , 1815 (2022). Newton, A. C. Protein Kinase C: Structure, Function, and Regulation (*). (1995) doi:10.1074/jbc.270.48.28495. Mørk, M. et al. Postprandial Increase in Blood Plasma Levels of Tissue Factor-Bearing (and Other) Microvesicles Measured by Flow Cytometry: Fact or Artifact? 2 , 147–157 (2018). Lucien, F. et al. MIBlood-EV: Minimal information to enhance the quality and reproducibility of blood extracellular vesicle research. J Extracell Vesicles 12 , (2023). Fortunato, D. et al. Selective isolation of extracellular vesicles from minimally processed human plasma as a translational strategy for liquid biopsies. Biomark Res 10 , 1–24 (2022). Pospichalova, V. et al. Simplified protocol for flow cytometry analysis of fluorescently labeled exosomes and microvesicles using dedicated flow cytometer. J Extracell Vesicles (2015) doi:10.3402/jev.v4.25530. Yates, A. G. et al. In sickness and in health: The functional role of extracellular vesicles in physiology and pathology in vivo: Part I: Health and Normal Physiology. J Extracell Vesicles 11 , (2022). Staufer, O. et al. Vesicle Induced Receptor Sequestration: Mechanisms behind Extracellular Vesicle-Based Protein Signaling. Advanced Science 9 , 2200201 (2022). Klemetti, M. M. et al. Lipid profile of circulating placental extracellular vesicles during pregnancy identifies foetal growth restriction risk. J Extracell Vesicles 13 , 12413 (2024). Chang, X. et al. Extracellular Vesicles with Possible Roles in Gut Intestinal Tract Homeostasis and IBD. Mediators Inflamm 2020 , (2020). Maltseva, D. V., Poloznikov, A. A. & Artyushenko, V. G. Selective changes in expression of integrin α-subunits in the intestinal epithelial caco-2 cells under conditions of hypoxia and microcirculation. Bulletin of Russian State Medical University 23–30 (2020) doi:10.24075/BRSMU.2020.078. Spazierer, D. et al. Epiplakin Gene Analysis in Mouse Reveals a Single Exon Encoding a 725-kDa Protein with Expression Restricted to Epithelial Tissues. Journal of Biological Chemistry 278 , 31657–31666 (2003). Niessen, P. et al. Smoothelin-A Is Essential for Functional Intestinal Smooth Muscle Contractility in Mice. Gastroenterology 129 , 1592–1601 (2005). Isayama, K., Rini, D. M., Yamamoto, Y. & Suzuki, T. Propionate regulates tight junction barrier by increasing endothelial-cell selective adhesion molecule in human intestinal Caco-2 cells. Exp Cell Res 425 , 113528 (2023). Scalise, A. A., Kakogiannos, N., Zanardi, F., Iannelli, F. & Giannotta, M. The blood–brain and gut–vascular barriers: from the perspective of claudins. Tissue Barriers 9 , (2021). Kong, S., Zhang, Y. H. & Zhang, W. Regulation of Intestinal Epithelial Cells Properties and Functions by Amino Acids. Biomed Res Int 2018 , (2018). Wachsmuth, H. R., Weninger, S. N. & Duca, F. A. Role of the gut–brain axis in energy and glucose metabolism. Experimental & Molecular Medicine 2022 54:4 54 , 377–392 (2022). Al Halawani, A., Mithieux, S. M., Yeo, G. C., Hosseini-Beheshti, E. & Weiss, A. S. Extracellular Vesicles: Interplay with the Extracellular Matrix and Modulated Cell Responses. International Journal of Molecular Sciences 2022, Vol. 23, Page 3389 23 , 3389 (2022). Qian, F. et al. Analysis and Biomedical Applications of Functional Cargo in Extracellular Vesicles. ACS Nano 16 , 19980–20001 (2022). Salomon, C. et al. Extracellular Vesicles and Their Emerging Roles as Cellular Messengers in Endocrinology: An Endocrine Society Scientific Statement. Endocr Rev 43 , 441–468 (2022). Zhang, X. et al. Extracellular vesicles in the treatment and diagnosis of breast cancer: a status update. Front Endocrinol (Lausanne) 14 , 1202493 (2023). Pospichalova, V. et al. Simplified protocol for flow cytometry analysis of fluorescently labeled exosomes and microvesicles using dedicated flow cytometer. J Extracell Vesicles 4 , 1–15 (2015). Garza, A. P. et al. Initial and ongoing tobacco smoking elicits vascular damage and distinct inflammatory response linked to neurodegeneration. Brain Behav Immun Health 28 , (2023). Bradford, M. M. A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem 72 , 248–254 (1976). Hughes, C. S. et al. Single-pot, solid-phase-enhanced sample preparation for proteomics experiments. Nat Protoc 14 , 68–85 (2019). Additional Declarations No competing interests reported. Supplementary Files GarzaFastingFigure5.pdf Supplementary Figure 1. Comparison of platelet presence in two isolation methods. Method 1 involved two centrifugation steps of the ACD blood at 1,5 x 10 3 g for 10 min at room temperature (RT), while method 2 entailed two centrifugation steps of ACD blood centrifugation at 2,5 x 10 3 g for 20 min at RT. Both methods were followed by two centrifugation steps of 14 x 10 3 g for 70 min at 4 °C. n=4, all samples were measured in technical duplicates. Statistical analyses were performed using paired t-test. Cite Share Download PDF Status: Published Journal Publication published 03 Oct, 2024 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 28 Jun, 2024 Reviews received at journal 28 Jun, 2024 Reviews received at journal 18 Jun, 2024 Reviewers agreed at journal 03 Jun, 2024 Reviews received at journal 03 Jun, 2024 Reviewers agreed at journal 31 May, 2024 Reviewers agreed at journal 29 May, 2024 Reviewers invited by journal 22 May, 2024 Editor assigned by journal 22 May, 2024 Editor invited by journal 22 May, 2024 Submission checks completed at journal 20 May, 2024 First submitted to journal 15 May, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4426110","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":308082988,"identity":"3282ddfa-9b9f-4081-8aa3-90ed8c32f975","order_by":0,"name":"Alejandra P. Garza","email":"","orcid":"","institution":"Otto-von-Guericke University Magdeburg","correspondingAuthor":false,"prefix":"","firstName":"Alejandra","middleName":"P.","lastName":"Garza","suffix":""},{"id":308082989,"identity":"f3c4e8e6-a3f4-4e5e-ae84-c3a51076ba59","order_by":1,"name":"Elisa Wider-Eberspächer","email":"","orcid":"","institution":"Otto-von-Guericke University Magdeburg","correspondingAuthor":false,"prefix":"","firstName":"Elisa","middleName":"","lastName":"Wider-Eberspächer","suffix":""},{"id":308082990,"identity":"2883a35a-31ff-45a8-a28a-ba794abca197","order_by":2,"name":"Lorena Morton","email":"","orcid":"","institution":"Otto-von-Guericke University Magdeburg","correspondingAuthor":false,"prefix":"","firstName":"Lorena","middleName":"","lastName":"Morton","suffix":""},{"id":308082991,"identity":"ddc3d47f-383d-4a5e-88eb-ac2638110e99","order_by":3,"name":"Marco van Ham","email":"","orcid":"","institution":"Helmholtz Centre for Infection Research","correspondingAuthor":false,"prefix":"","firstName":"Marco","middleName":"van","lastName":"Ham","suffix":""},{"id":308082992,"identity":"82cf73ff-8e95-4316-a5df-2a81e4d3da64","order_by":4,"name":"Éva Pállinger","email":"","orcid":"","institution":"Semmelweis University","correspondingAuthor":false,"prefix":"","firstName":"Éva","middleName":"","lastName":"Pállinger","suffix":""},{"id":308082993,"identity":"4d6be52d-bfd1-420f-900c-423176727c35","order_by":5,"name":"Edit I. Buzás","email":"","orcid":"","institution":"Semmelweis University","correspondingAuthor":false,"prefix":"","firstName":"Edit","middleName":"I.","lastName":"Buzás","suffix":""},{"id":308082994,"identity":"2f9938e0-cf07-4d5b-ab1c-6af42be55893","order_by":6,"name":"Lothar Jänsch","email":"","orcid":"","institution":"Helmholtz Centre for Infection Research","correspondingAuthor":false,"prefix":"","firstName":"Lothar","middleName":"","lastName":"Jänsch","suffix":""},{"id":308082995,"identity":"d8bafb29-ed32-4b80-aa90-c1c95d441ba9","order_by":7,"name":"Ildiko Rita Dunay","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/0lEQVRIiWNgGAWjYBACNnYGg4MNDAyMDSDeBxiDgYEZtxZmJC2MM4jRApQyYIRpYeYhRgsfM/PGgzMqGGQ33G5+Jm2bYyPbwN5j/JqHwVoOt8PYCg5uOMNgvOHOMTPp3G1pxg08Z8yseRjSjXFr4TE4+LCNIXHDjQSQlsOJDRJpacY8DEAGYS3p36Qtt/2Ha6nHq2UjWEuOmTTjtgNALcmHHwO1JOD1y4wzEsYzb+QUW/ZuSzZu4zl8jHGOQbohLlvk25s3f+ypsJHtu5G+8cbPbXay/eyNzR/eVFjL47IFCiRABAuYZAMiCQYDAhqggPkDOmMUjIJRMApGAQgAABiHV561SFQLAAAAAElFTkSuQmCC","orcid":"","institution":"Otto-von-Guericke University Magdeburg","correspondingAuthor":true,"prefix":"","firstName":"Ildiko","middleName":"Rita","lastName":"Dunay","suffix":""}],"badges":[],"createdAt":"2024-05-15 15:17:04","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4426110/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4426110/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-74228-4","type":"published","date":"2024-10-03T15:56:55+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":57722584,"identity":"3cf945e1-e664-4875-a3e7-97193c4db75c","added_by":"auto","created_at":"2024-06-04 19:09:31","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":92251,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExperimental design and pre-requisites for assessing postprandial changes in healthy individuals. \u003c/strong\u003eDetailed demographic information of the healthy participants\u003cstrong\u003e (A). \u003c/strong\u003eSchematic representation of the experimental setup, wherein blood samples were collected from healthy participants before and 75 min after consumption of an isocaloric meal. Samples were then processed to obtain plasma and plasma lEVs, of which the later were used for detailed characterization by proteomics and flow cytometry (B). Bar chart illustrating the triacylglycerides levels in plasma before and after food intake, indicating postprandial changes (C). Bar plots displaying total protein concentrations in plasma and plasma-EVs, both pre- and postprandially (D). Correlation plot demonstrating no correlation between fasting time and total protein concentration in EV samples both in pre- and postprandial time points (E). n=12, all samples were measured in technical triplicates. Statistical analyses were performed using paired t-test (C-D) and Pearson correlation (E), respectively. \u003cem\u003eP\u003c/em\u003e values: * for \u003cem\u003ep\u003c/em\u003e ≤ 0.05; ** for \u003cem\u003ep\u003c/em\u003e ≤ 0.001; *** for \u003cem\u003ep\u003c/em\u003e ≤ 0.0001.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-4426110/v1/94d69a89e7caaa1013735792.png"},{"id":57722194,"identity":"9613eae7-4b1d-45b9-90be-8bcea2f5c649","added_by":"auto","created_at":"2024-06-04 19:01:31","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":54566,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProteomic analyses of fasted and postprandial isolated extracellular vesicles. \u003c/strong\u003eDistribution of relative protein abundances (log2) in isolated EV samples (A). Volcano plots showing protein regulations (-log10) in lEVs isolated post- vs preprandially (B). Protein abundances of apolipoproteins (log2) in EV samples comparing pre- and postprandial conditions (C). Platelet protein abundances (log2) in EV samples comparing pre- and postprandial conditions (D). n=3, all samples were measured in technical triplicates; \u003cem\u003eP\u003c/em\u003e values are given in -log10, and statistical analyses were performed using paired students t-test.\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-4426110/v1/28494880a8cda026f7a02af1.png"},{"id":57722195,"identity":"b41d996b-7091-4bd9-a1de-7fbf18a85412","added_by":"auto","created_at":"2024-06-04 19:01:31","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":91273,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEnrichment analyses of significantly regulated proteins. \u003c/strong\u003eNetwork analysis showing proteins annotated as “Extracellular exosome” in red, names are given in bold (A). Enrichment analyses showing enriched Reactome Pathways and Biological Processes (GO) analyses revealed multiple enriched biological processes (\u003cem\u003ep\u003c/em\u003e-values given in -log2) in postprandial EVs. Size of the dots indicate number of proteins; color of the dots indicates strength of the enriched processes and pathways (B-C). Analyses were performed using the STRING database.\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-4426110/v1/5c6dc040789b5088b0e485f2.png"},{"id":57722197,"identity":"b195dd68-6ba2-4649-a4df-6dff4b8f9e52","added_by":"auto","created_at":"2024-06-04 19:01:31","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":163423,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlow cytometry of plasma extracellular vesicles. \u003c/strong\u003eRepresentative gating strategy of plasma derived lEVs showing first counting beads as reference (left graph). Selection of events positive for tetraspanin markers (CD9, CD63 and CD81) was followed by selection of events based on a size gate established with silica beads (A). Bar charts showing absolute number of lEVs per microliter comparing pre- and postprandial timepoints (B). Violin plots showing the frequency of positive events for CD31 and CD106 (endothelial markers) as well as CD44 and CD324 (epithelial markers) in pre- vs postprandial states (C). t-distributed stochastic neighbor embedding (t-SNE) plots showing the mean fluorescence intensity of CD31, CD106, CD44, and CD324 in a total of 80,400 positive events (based on CD9+, CD63+ CD81+ events and size) in each pre- and postprandial states (D). n=12, all samples were measured in technical duplicates. Statistical analyses were performed using paired t-test. \u003cem\u003eP\u003c/em\u003e values: * for \u003cem\u003ep\u003c/em\u003e ≤ 0.05; ** for \u003cem\u003ep\u003c/em\u003e ≤ 0.001; *** for \u003cem\u003ep\u003c/em\u003e ≤ 0.0001.).\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-4426110/v1/fad95e63bfadcae14d7fbb70.png"},{"id":66097086,"identity":"e5484670-7450-4ec3-80c3-b683d8db97e9","added_by":"auto","created_at":"2024-10-07 16:13:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1004632,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4426110/v1/a53156d0-37a5-4a88-8dcd-d28c6ac32c12.pdf"},{"id":57722196,"identity":"7ec79397-4a69-4ced-ae7e-04cc24db5482","added_by":"auto","created_at":"2024-06-04 19:01:31","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1518267,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure 1.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparison of platelet presence in two isolation methods. \u003c/strong\u003eMethod 1 involved two centrifugation steps of the ACD blood at 1,5 x 10\u003csup\u003e3 \u003c/sup\u003e\u003cem\u003eg\u003c/em\u003e for 10 min at room temperature (RT), while method 2 entailed two centrifugation steps of ACD blood centrifugation at 2,5 x 10\u003csup\u003e3 \u003c/sup\u003e\u003cem\u003eg\u003c/em\u003e for 20 min at RT. Both methods were followed by two centrifugation steps of 14 x 10\u003csup\u003e3\u003c/sup\u003e \u003cem\u003eg\u003c/em\u003e for 70 min at 4 °C. n=4, all samples were measured in technical duplicates. Statistical analyses were performed using paired t-test.\u003c/p\u003e","description":"","filename":"GarzaFastingFigure5.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4426110/v1/92d829b6a087e2a31b5e065d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Circulating pre- and postprandial extracellular vesicle proteomic profiles","fulltext":[{"header":"Introduction","content":"\u003cp\u003eExtracellular vesicles (EVs) have garnered significant attention in the scientific community due to their critical roles in intercellular communication and their potential use as diagnostic and therapeutic agents \u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. These robust particles, released by various cell types, carry a diverse and mixed cargo of proteins, nucleic acids, and lipids, reflecting the physiological state of their parent cells \u003csup\u003e\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. EVs are found in various bodily fluids, including urine, saliva, amniotic fluid, cerebrospinal fluid, serum, and plasma \u003csup\u003e\u003cspan additionalcitationids=\"CR9 CR10 CR11 CR12\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Among these, blood and its derivatives are the most frequently utilized biofluids in research due to their ease of access through minimally invasive and well-established procedures \u003csup\u003e\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe study of EV dynamic compositions in the context of physiological stimuli, such as fasting and postprandial states, is of considerable interest due to their physiological functions such as platelet biology, inflammation and immunity, the regulation and maintenance of blood pressure, regulation of water and salt levels in urine, pregnancy, fertilization and implantation among others, and potential clinical applications, particularly concerning liquid biopsies and cargo and delivering of therapeutic molecules \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Due to the influence of fasting on the isolation, composition, and abundance of EVs in the circulation \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e, a growing interest in the isolation and characterization of plasma-derived EV has been developed. Additionally, prior research acknowledged challenges entailed with EV separation from peripheral blood that are attributed to the presence of lipoproteins of similar size in blood after food consumption (Liang et al., 2021). Despite the recognized need, standardized guidelines regarding fasting status for the accurate isolation of plasma EVs are yet to be established.\u003c/p\u003e \u003cp\u003eVarious techniques for separating EVs offer unique strengths and limitations that vary based on the specific research objectives \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Recently, we have demonstrated the efficacy of using differential centrifugation to enrich lEVs in our samples, particularly when preparing samples for flow cytometry analyses (Garza et al., 2023). To study whether fasting is necessary before sample collection, we aimed in this study to investigate the impact of fasting status on (i) EV abundances and (ii) protein content and composition. This investigation is particularly pertinent given the challenges associated with implementing fasting in specific research contexts, potentially posing constraints within heterogeneous population samples, such as pediatric studies, and in individuals with metabolic conditions.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eNo alteration in plasma and EV protein concentrations during the post-prandial state\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe examined the postprandial alterations in circulating EVs within a cohort of twelve healthy participants (median age 25 \u0026plusmn; 3.6 years old, 6 females, median body mass index (BMI) 23.78 \u0026plusmn; 2.7). Participants were instructed to undergo an overnight fasting period (median 13 \u0026plusmn; 2.3 h) (Figure 1A), where plasma and circulating EVs) were isolated for baseline assessments (referred to as the \u0026ldquo;pre\u0026rdquo; group). Subsequently, an isocaloric meal was administered, and after a 75-min interval, a second round of blood sample collection (referred to as the \u0026ldquo;post\u0026rdquo; group) was conducted. After all samples were collected, EVs were applied for a comprehensive analysis utilizing proteomics and multicolor flow cytometry. This experimental setup (Figure 1B) aimed to discern the impact of a standardized meal on the compositional and quantitative aspects of EVs in the pre-and postprandial state, contributing to our understanding of the EV dynamic response to nutritional stimuli. Triacylglycerides (TAGs) are known to increase in the post-prandial state following an overnight fast, which we could validate with a significant increase in plasma TAG levels measured at 75 min postprandially (pre, 0.8008 \u0026plusmn; 0.1472 mmol/L; post, 1.349 \u0026plusmn; 0.3439 mmol/L, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e= \u0026lt;0.0001) (Figure 1C).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSubsequently, we assessed the protein concentrations in plasma and circulating EVs at both pre-and postprandial time points. The outcomes indicated that protein levels remained relatively stable between both conditions in plasma (pre, 73.96 \u0026plusmn; 15.7 mg/mL; post, 73.96 \u0026plusmn; 20.04 mg/mL, \u003cem\u003ep\u003c/em\u003e = 0.9097) and EVs (pre, 0.2558 \u0026plusmn; 0.1155 mg/mL; post, 0.3106 \u0026plusmn; 0.1505 mg/mL, \u003cem\u003ep\u003c/em\u003e = 0.3275), as depicted in Figure 1D. Given the variability in fasting durations among participants, we conducted a correlation analysis to investigate potential associations between fasting times and changes in protein levels. Our analysis revealed no significant correlation between fasting duration and the protein concentrations in circulating EVs in both pre- (\u003cem\u003er\u003c/em\u003e = 0.1241, CI = -0.4843 to 0.6516, \u003cem\u003ep\u003c/em\u003e = 0.7008) and postprandial (r = 0.0452, CI = -0.5427 to 0.6035, \u003cem\u003ep\u003c/em\u003e = 0.8889) conditions (Figure 1E). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProteomic insights into postprandial extracellular vesicle dynamics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo gain a comprehensive understanding of the protein composition within our EV samples, three participants were randomly selected to conduct an in-depth assessment of EV protein content utilizing proteomic techniques and mass spectrometry in pre- and post prandial conditions. This approach facilitated a detailed exploration into the protein distribution of 2230 proteins across samples, revealing consistent protein abundances in all samples (Figure 2A). Subsequently, we investigated differentially regulated proteins between pre- and postprandial states in healthy participants. For that, and to enhance robustness of our data, only proteins that were identified and quantified in all three samples of either the pre- or postprandial group were considered. Generally, we found more proteins to be enhanced in EVs at the postprandial time point (Figure 2B). Notably, several proteins implicated in epithelial and endothelial cell functions exhibited significant upregulation in the postprandial state, including EPPK1 (epiplakin), ITGA5 (integrin sub-unit alpha 5), SMTN (smoothelin), and ESAM (endothelial cell adhesion molecule) (Figure 2B), emphasizing their potential role in postprandial physiological processes. Due to the difficulties separating lipoproteins from EVs, we evaluated the main apolipoproteins associated with food intake (Figure 2C). We assessed the abundance of ApoB, ApoA1, ApoA4, ApoE, ApoA, ApoH, ApoOL1, ApoD, ApoC3, ApoA2, ApoC1, ApoC4 and ApoM and found similar levels between pre- and post conditions (Figure 2C). Additionally, considering the potential presence of platelet proteins in our sample, we examined 24 platelet proteins, of which we detected 17 (Figure 2D) \u003csup\u003e24\u003c/sup\u003e. Subsequently, we explored whether the presence of platelet proteins varied depending on fasting status. This analysis unvailed a significant upregulation of only one protein, protein kinase C beta type (PKCB), in the postprandial group (p = .0386). Notably, this protein plays a role in various biological processes, including B-cell activation and the regulation of endothelial cells in the brain microvasculature and its expression is not exclusive to platelets \u003csup\u003e25,26\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEnriched Gene Ontology (GO) and reactome pathways analysis.\u0026nbsp;\u003c/strong\u003eTo identify prominent biological processes and pathways involved in lEV dynamics, we conducted protein enrichment analyses using the differently abundant EV proteins when comparing the pre- and postprandial states (Figure 3). First, utilizing differentially expressed proteins with regulation lower than -2 and/or higher than 2 and \u003cem\u003ep\u003c/em\u003e value above 1.3 an in-depth network analysis of the interaction between the differentially expressed proteins utilizing the STRING database was performed, revealing significant enrichment within the \u0026quot;Extracellular exosome\u0026quot; network (Figure 3A). Further analysis of enriched reactome pathways and biological processes (GO) in our sample unveiled an expected emphasis on vesicle-related pathways, encompassing transport and membrane trafficking. Moreover, pathways and biological processes related to the immune system emerged prominently within the enriched pathways and processes (Figure 3B-C). Detailed examination of the proteins associated with these processes revealed a subset of proteins intricately involved in both epithelial and endothelial functions (Figure 2B).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIncreased EV surface expression of epithelial marker CD324 on postprandial lEVs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDriven by the hypothesis that proteins identified in large EVs engage in communication with the endothelial and epithelium postprandially, we conducted multicolor flow cytometry to examine specific surface markers on lEVs related to these cell types (Figure 4A and B). We selected CD31 and CD106 as enriched expression markers on endothelial cells and CD44 and CD324 on epithelial cells. Our results showed no significant changes in the total concentration of EVs per microliter between the pre- and postprandial states (pre, 16890 \u0026plusmn; 3630 lEVs/mL; post, 14003 \u0026plusmn; 2834 lEVs/mL, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e= .6878) showing a clear correlation with the protein levels assessed via colorimetric assay in which also no changes were present (Figure 1D). Indeed, we observed a significant increase in the postprandial expression of CD324 on EVs (tetraspanin\u003csup\u003e+\u003c/sup\u003e, size gate\u003csup\u003e+\u003c/sup\u003e), a marker known for its role in cell-cell adhesion, mobility, and proliferation of epithelial cells (Figure 4C-D) (pre, 45.03 % \u0026plusmn; 2.102; post, 46.64 % \u0026plusmn; 2.45; \u003cem\u003ep\u003c/em\u003e = .0294). In conclusion, our findings demonstrate a significant increase in postprandial expression of the epithelial marker CD324 on lEVs, supporting the hypothesis of their engagement in communication with epithelial cells following food intake.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, plasma concentrations and the molecular composition of EVs were assessed in postprandial states of healthy individuals. Our results provide a novel insight into the proteomic landscape and changes in specific surface markers on EVs in response to nutritional intake with further consequences for biomarker research.\u003c/p\u003e \u003cp\u003ePrevious results using flow cytometry indicate increased concentration of plasma EVs postprandially \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. In our study, we evaluated the possible differences via colorimetric assay and found similar protein concentrations in plasma and EVs in both fasting and postprandial samples. Upon targeted flow cytometry evaluation of lEVs, no alteration was detected in the total number of lEVs. Furthermore, our analysis revealed that EVs maintain a consistent protein concentration, regardless of the fasting duration, and indicate a tightly controlled homeostatic mechanism with no significant effect in response to short-term changes in nutritional status. From a physiological perspective, the stability of EV protein levels despite fasting states emphasizes the EVs potential to serve as stable carriers of biological signals, of particular importance in the context of diagnostic biomarker development, where EVs can provide a reliable snapshot of biological states independent of a fasting period. For clinicians and researchers, it suggests that EV-derived biomarkers may not require strict controls for fasting duration, simplifying the sample collection protocol and expanding the applicability of EV-based diagnostics. It is recommended that studies involving plasma-derived EVs report fasting status if known, along with the duration of the fasting period \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Our present results demonstrate that quantitatively via flow cytometry using specific identification markers, there are no significant fluctuations observed in EVs concerning fasting status.\u003c/p\u003e \u003cp\u003eWhile our results revealed that the overall protein concentrations in plasma and circulating EVs remained relatively stable, it is crucial to distinguish this overall stability from the changes observed at the proteomic level. A notable challenge in isolating EVs from plasma is the presence of large lipoproteins, such as low-density lipoprotein (LDL), which share physical characteristics with EVs \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. LDL predominantly comprises Apolipoprotein B (ApoB). Thus, we evaluated its presence, along with various other apolipoproteins, in our EV sample, and our findings revealed no significant changes between the two conditions, indicating the minimal impact of fasting on EVs at the proteomic level. Another potential concern in EV isolation is contamination with platelets. To address this, we evaluated to methods of isolating PPP, assessed platelet presence via flow cytometry, and observed no significant differences in platelet quantity between the two methods (Supplementary Fig.\u0026nbsp;1). It is worth highlighting that various protocols exist for PPP isolation, with Method 2 (2x, 2500g for 20 min) being the most widely accepted within the EV community \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Although our results did not show significant changes, a discernible trend suggest the presence of platelets, which could potentially affect downstream analyses. Therefore, for consistency and reproducibility, we recommend adhering to the Method 2 and the general guidelines outlined by the International Society for Extracelluar Vesicles (ISEV) \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOur proteomic data indicates the enrichment of an \"Extracellular Exosome\" network, affirming the effectiveness of our isolation method in yielding a sample enriched with EVs. Further, our proteomic analysis revealed a distinct landscape of EV protein composition, characterized by a significant postprandial upregulation of proteins associated with transport mechanisms, as well as proteins integral to epithelial and endothelial cell functions. This upregulation indicates that, although the total protein content may remain unchanged, the proportion of specific types of proteins within the EVs and the prevalence of certain EV subpopulations is altered in response to food intake. These findings suggest a selective enrichment or mobilization of EVs carrying proteins crucial for postprandial physiological processes, reflecting an adaptive response to such a metabolic state. Recent studies have delved into the multifaceted roles of EVs across physiological and pathological processes, indicating their critical function in nucleic acid and protein transfer, receptor sequestration, interaction with the extracellular matrix (ECM), and their emerging role in endocrinology and tissue repair \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Other omics approaches, such as lipidomics, have also proven helpful in the understanding of EV function in homeostasis and metabolic changes \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. These studies elucidate the mechanism through which EVs promote intercellular signaling and are consistent with our findings of postprandial EV dynamics where we have observed a marked increase in proteins linked to transport and cellular communication. The identification of enriched gene ontology (GO) and Reactome pathways related to vesicle-mediated transport, membrane trafficking, and immune system processes further emphasizes the complex involvement of EVs in systemic physiological responses.\u003c/p\u003e \u003cp\u003eThe analysis of proteins implicated in enriched networks revealed heightened levels of endothelial and epithelial-related proteins. This finding holds particular significance given the pivotal roles of both intestinal and vascular barriers in mediating inter-system communication, particularly in the context of gut-periphery interactions during physiological processes \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Notably, the coordinated postprandial upregulation of epiplakin (EPPK1), a protein predominantly expressed in epithelial and glandular cells that are also present in the gastrointestinal tract, and integrin sub-unit alpha 5 (ITGA5), an integrin primarily expressed in intestinal tissue and endothelial cells, suggests a coordinated gastrointestinal response detectable in lEV composition \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Similarly, the postprandial upregulation of smoothelin (SMTN) and endothelial cell adhesion molecule (ESAM) postprandially underscores the potential involvement of EV-mediated communication between the digestive system and peripheral tissues \u003csup\u003e\u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. These observations hint at an unexplored mechanism of communication facilitated by EVs following food intake involving endothelial and epithelial, affirming further investigation.\u003c/p\u003e \u003cp\u003eFor this purpose, we evaluated the surface expression of epithelial and endothelial markers on lEVs via flow cytometry. Our results revealed increased surface expression of the epithelial marker CD324 on lEVs postprandially. This could involve epithelial cells in the gut that release EVs in response to direct contact with nutrients and may contribute to regulating the intestinal barrier and nutrient absorption. The postprandial gut feedback, where intestinal epithelial cells release molecules such as peptides and hormones, has been previously described \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. Similarly, exploring EV interactions with the ECM \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e complements our findings of increased epithelial and endothelial marker expressions following food consumption, suggesting a distinct role for EVs in modulating tissue responses to nutritional intake. Additionally, the capabilities of EV cargo in clinical diagnostics, as discussed by Qian et al. \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e, parallels our detection of specific postprandial alterations in EV protein composition, highlighting the diagnostic and therapeutic potential of understanding EV protein shift in response to food intake.\u003c/p\u003e \u003cp\u003eThe growing body of evidence regarding EVs and their role in intercellular communication further corroborates the importance of our findings, suggesting that postprandial EV profiles may be crucial in systemic metabolic regulation and intercellular communication \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. Collectively, our results further unravel EV behavior and their physiological adaptation in postprandial states. By directly addressing previously identified gaps in the literature regarding the influence of fasting on EV phenotypes \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e, our results improve EV research methodologies and their physiological relevance.\u003c/p\u003e \u003cp\u003eOur study employs a comprehensive approach to investigate the effects of fasting on plasma concentrations and molecular composition of EVs encompassing analytical techniques such as flow cytometry and proteomics. We also addressed the current gap in the literature about the stability of plasma and EV protein concentrations in response to nutritional intake and shed light on the changes in EVs during fasting and postprandial states and informing future research guidelines. We also describe which EV-derived markers and proteins are differentially expressed in two conditions during homeostasis, thereby possibly simplifying sample collection protocols and expanding the applicability of EV-based diagnostics. However, our study is limited by a relatively small sample size, which may affect the generalizability of our findings. A larger cohort would enhance the statistical power and robustness of the results. While this study employs established EV isolation protocols and identification techniques, such as differential centrifugation and flow cytometry and mass spectrometry, there may be inherent methodological limitations associated with each approach, which could impact the accuracy and reproducibility of the results. Overall, while this study provides valuable insights into the effects of fasting on EV proteomics, its findings should be interpreted cautiously considering the aforementioned limitations.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cb\u003eExperimental setup and blood withdrawal.\u003c/b\u003e Twelve young, healthy participants (6 females, 6 males, mean age\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM: 26,42\u0026thinsp;\u0026plusmn;\u0026thinsp;1,05 years, range: 23\u0026ndash;32 years) were prospectively recruited at the Medical Faculty of the Otto von Guericke University in Magdeburg, Germany. The experimental procedure was approved by the guidelines of the local committee of the Medical Faculty, Otto-von-Guericke Magdeburg (No 07/17). Inclusion criteria were age over 18 years, overnight fast of \u0026ge;\u0026thinsp;12 hours (no alcohol, sugar-containing beverages, and food consumption). Exclusion criteria were acute diseases, chronic conditions (cardiovascular, neurological, psychiatric), uncontrolled metabolic disease, pregnancy, current or recent smoking, and alcohol abuse. Every participant gave written informed consent. To determine the effects of fasting, peripheral blood was collected in the fasting state (pre-group) to establish an individual baseline, after which a standardized meal was provided. The meal was approximately 915 kcal, consisting of 34.8% fat, 55.42% carbohydrates, and 9.78% protein. The second studied time point was 75 min postprandial (post). Blood was collected to two sterile acid citrate dextrose (ACD) BD Vacutainer tubes containing 1 ml of ACD, and one lithium heparin coated (LH PST\u0026trade; II) BD Vacutainer from a cubital vein at both time points. Tubes were inverted twice to ensure the incorporation of the agents and whole blood. All samples were processed within 1 hour of collection.\u003c/p\u003e \u003cp\u003e \u003cb\u003eTriacylglycerides measurement.\u003c/b\u003e Blood collected in lithium heparin-coated tubes was centrifuged within one hour at 1.5 x 10\u003csup\u003e3\u003c/sup\u003e \u003cem\u003eg\u003c/em\u003e for 10 min at 4\u0026deg;C. Plasma was transferred to sterile tubes and stored at -80\u0026deg;C until further processing. Samples were sent to and measured by the Institute of Clinical Chemistry at the Medical Faculty of Otto von Guericke University.\u003c/p\u003e \u003cp\u003e\u003cb\u003eExtracellular vesicle isolation.\u003c/b\u003e First, two methods were investigated in order to obtain platelet-poor plasma (PPP). Method 1 consisted of two centrifugation steps of the ACD blood at 1,5 x 10\u003csup\u003e3\u003c/sup\u003e\u003cem\u003eg\u003c/em\u003e for 10 min at room temperature (RT). Method 2 consisted of two steps of ACD blood centrifugation at 2,5 x 10\u003csup\u003e3\u003c/sup\u003e\u003cem\u003eg\u003c/em\u003e for 20 min at RT. Further, lEVs were enriched as previously described (Garza et al., 2023; Pospichalova et al., 2015). PPP from both methods was then transferred to fresh clean tubes and centrifuged at 14 x 10\u003csup\u003e3\u003c/sup\u003e\u003cem\u003eg\u003c/em\u003e for 70 min at 4\u0026deg;C. Further, the supernatant was carefully removed, and the pellet was resuspended in 0.22 \u0026micro;m filtered phosphate-buffered saline (PBS) without Ca2\u0026thinsp;+\u0026thinsp;and Mg2+ (fPBS-/-) and vortexed to ensure the solution of the previously formed pellet. This step was followed by another round of centrifugation 14 x 10\u003csup\u003e3\u003c/sup\u003e\u003cem\u003eg\u003c/em\u003e for 70 min at 4\u0026deg;C, after which the supernatant was removed, and the pellet was reconstituted in fPBS\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e. Samples were stored at -80\u0026deg;C until further experiments.\u003c/p\u003e \u003cp\u003e \u003cb\u003eProtein concentration measurement.\u003c/b\u003e Heparin plasma and EVs were thawed on ice and vortexed before further processing. Bio-Rad protein assay \u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e was performed according to instructions provided by the manufacturer (500-0006 Bio-Rad). Briefly, EVs were diluted 1:100 and plasma was diluted 1:4000 both in distilled water. Bovine serum albumin (BSA, BioRad Laboratories, USA) 1mg/ml was used to determine the standard curve. Bradford reagent was mixed 1:5 with the respective sample and added to a 96-well plate. Samples were measured at 595 nm using a SpectraMax M5e microplate reader (Molecular Devices LLC). Each sample and standard were measured as technical triplicates and averages were calculated for further analysis.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFlow cytometry.\u003c/b\u003e Aliquots of EVs were thawed on ice and vortexed to ensure a homogenous sample. 50 \u0026micro;l per sample were added to a 96-well plate with 35 \u0026micro;l of fPBS\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e per well. Diluted samples were stained with labelled tetraspanin marker-specific antibodies CD9, CD63, CD81 (Allophycocyanin, BioLegend), hyaluronic acid receptor CD44 (Alexa Fluor 700), CD324 (Peridinin chlorophyll protein-Cyanine 5.5, BioLegend) and endothelial markers CD106 (Phycoerythrin, BioLegend), CD31 (Fluorescein isothiocyanate, BioLegend) and for 30 min at 4\u0026deg;C. Following this, samples were washed and resuspended in fPBS-/-. To confirm the presence and purity of EVs samples were prepared as described above and lysed for 10 min with 0.1% Triton X solution. To identify the events on the size range of EVs, 300 nm to 1000 nm size reference silica beads (CD Bioparticles) were used. For quantification of events, AccuCheck counting beads (Invitrogen) were added to each sample and calculations were performed following the manufacturer\u0026rsquo;s instructions. Samples were acquired using the AttuneNxT flow cytometer (ThermoFisher) equipped with a small particle side scatter filter. Sample acquisition speed was set to 25 \u0026micro;l per min, SSC-threshold was set to 0.18 x 10\u003csup\u003e3\u003c/sup\u003e and FSC-threshold was set to 0.15 x 10\u003csup\u003e3\u003c/sup\u003e. Each sample measurement was followed by 10% bleach and filtered distilled water to prevent carryover from the previous sample. Data were transferred to FlowJo 10.9.0 and gated on tetraspanin positivity and FSC and SSC utilizing the previously established size gate (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Further, plots were generated using t-distributed stochastic neighbor embedding (t-SNE) algorithm for which events were down sampled using the DownSample plug-in. 6,700 size and tetraspanin positive events per sample were used and concatenated followed by tSNE utilizing all compensated parameters for 1,000 iterations and perplexity of 20, approximate random projection forest (ANNOY) as KNN (k-nearest neighbor) and FFT (Fast Fourier Transformation) interpolation as gradient algorithm. Further statistical analyses were performed using GraphPad Prism 10.1.1. Data was assessed for normality of distribution using D\u0026rsquo;Agostino \u0026amp; Pearson and Shapiro-Wilk tests, and paired t-tests or Wilcoxon tests were performed accordingly.\u003c/p\u003e \u003cp\u003e \u003cb\u003eProteomics.\u003c/b\u003e EVs were suspended in 200 \u0026micro;l PBS and stored for further proteomic analyses. For protein recovery, protein digestion and peptide clean-up, a slightly adapted SP3 protocol was applied \u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. For that, extracellular vesicle samples were diluted in lysis buffer to final concentrations of 2 %sodium dodecyl-sulfate (SDS), 100mM NaCl and 250mM triethylammonium bicarbonate (TEAB), and were supplemented with complete protease inhibitor cocktail (Roche). Lysis was increased by sonication using 10 cycles of a standard 30 seconds on/off Bioruptor protocol (Diagenode). Proteins were reduced for 1 hour at 55\u0026deg;C using a final concentration of 5 mM Tris(2-carboxyethyl)phosphine P(CH\u003csub\u003e2\u003c/sub\u003eCH\u003csub\u003e2\u003c/sub\u003eCOOH)\u003csub\u003e3\u003c/sub\u003e (TCEP) followed by reduction for 30 min at room temperature using a final concentration of 10 mM s-Methyl methanethiosulfonate (MMTS). Carboxylate beads (20 \u0026micro;l) were added, and proteins were allowed to bind overnight upon acetonitrile (ACN) addition to a final concentration between 50 and 60 % Beads were washed twice with 80 %ethanol and once with 100 %ACN and allowed to dry on air. Beads were suspended in 50 \u0026micro;l 200 mM TEAB containing 5 mM TCEP and 10 mM MMTS. Trypsin was added in a ratio of 1 \u0026micro;g trypsin to 30 \u0026micro;g protein and proteins were digested overnight at 37\u0026deg;C while shaking. Peptides were allowed to bind overnight upon ACN addition to a final concentration of at least 90 % Beads were spun down and supernatants transferred to LoBind Eppendorf tubes and stored for further analyses. Beads were washed three times with 100 %ACN. Peptides were eluted by using first 20 \u0026micro;l 2 %Dimethyl sulfoxide (DMSO) followed by a second step with 20 \u0026micro;l Millipore H\u003csub\u003e2\u003c/sub\u003eO. Purified peptides were vacuum dried, and pellets were suspended in 40 \u0026micro;l 0.1 %formic acid. For liquid chromatography\u0026ndash;mass spectrometry (LC-MS/MS) analyses, all samples were measured as triplicates on a Evosep One HPLC (Evosep) connected to a TimsTOFPro mass spectrometer (Bruker) equiped with PaSER Version 2022c (Bruker) for real-time database searches. Samples were applied onto C18 Evotips (EV-2001; Evosep) according to manufacturer\u0026rsquo;s protocol. The Evosep One HPLC was operated with the standard 60 sample per day method (21 min gradient at a flow rate of 1.0 \u0026micro;l/min; buffer A: 0.1 %formic acid, buffer B: 0.1 %formic acid in acetonitrile). For the TimsTOFPro mass spectrometer, the standard MSMS Bruker method \u0026ldquo;DDA PASEF method for short gradients with 0.5 s cycletime\u0026rdquo; was employed. MS settings were: scan begin 100 m/z; scan end 1700 m/z; ion polarity: positive; scan mode: PASEF. Tims settings were: mode custom; number of PASEF ramps: 4; charge minimum: 0; charge maximum: 5; 1/K0 start 0.75 V*s/cm2; 1/K0 end 1.4 V*s/cm2; ramp time: 100.0 ms; MS average: 1. For protein and peptide identification and quantification, raw data files were loaded and run on the PEAKS software (PEAKS studio Xpro, Bioinformatics Solutions) using following settings; parent mass error tolerance: 20.0 ppm; fragment mass error tolerance: 0.03 Da; enzyme: trypsin; max missed cleavages: 2; peptide length range: 6\u0026ndash;45; fixed modifications: beta-methylthiolation (C)\u0026thinsp;+\u0026thinsp;45.99; variable modifications: oxidation (M)\u0026thinsp;+\u0026thinsp;15.99; database: human release 15 November 2021. Downstream analyses, data presentation and statistical analyses were performed using Perseus V2.0.9.0, STRING database version 12.0 and GraphPad Prism 9.3.1.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eACD, acid citrate dextrose; ACN, acetonitrile; ANNOY, approximate random projection forest; Apo, apolipoprotein; BMI, body mass index; DMSO, dimethyl sulfoxide; ECM, extracellular matrix; EPPK1, epiplakin 1; ESAM, endothelial cell adhesion molecule; EV, extracellular vesicle; FFT, fast fourier transformation; fPBS, filtered PBS; GO, gene ontology; ITGA5, integrin sub-unit alpha 5; KNN, k-nearest neighbor; LC-MS/MS,\u0026nbsp;liquid chromatography\u0026ndash;mass spectrometry; LDL, low-density lipoprotein; lEV, large extracellular vesicle; LH, lithium heparin; MMTS,\u0026nbsp;s-Methyl methanethiosulfonate; PBS, phosphate-buffered saline; PKCB, protein kinase C beta type; PPP, platelet-poor plasma; RT, room temperature; SDS,\u0026nbsp;sodium dodecyl-sulfate; SEM, standard error of the mean; SMTN, smoothelin; t-SNE, ). t-distributed stochastic neighbor embedding; TAG, triacylglycerides; TCEP,\u0026nbsp;tris(2-carboxyethyl)phosphine P(CH\u003csub\u003e2\u003c/sub\u003eCH\u003csub\u003e2\u003c/sub\u003eCOOH)\u003csub\u003e3\u003c/sub\u003e; TEAB, triethylammonium bicarbonate.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIRD conceived the presented idea, designed the study, supervised analyses and edited the manuscript. IRD, LJ and EB were responsible for supervision, project administration and manuscript revisions. EWE recruited the participants and carried out experiments and analyses of plasma-derived lEVs, wrote and edited this manuscript. APG performed the experiments, data analyses, data interpretation, performed data visualization and wrote the manuscript. LM contributed to sample preparation, measurements, analyses and edited the manuscript. MVH carried out the proteomics experiments, analyses, and data visualization. EP read and edited the manuscript. All authors approved the submitted version.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study adhered to the ethical principles outlined in the Declaration of Helsinki. Prior to participation, written informed consent was obtained from all participants in accordance with institutional guidelines and ethical standards. Confidentiality and anonymity of participants were rigorously maintained throughout the study duration.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the following grants: DZPG-CIRC, NVKP_16-1-2016-0004, VEKOP-2.3.2-16-2016-00002, VEKOP-2.3.3-15-2017-00016, TKP2021-EGA-23, RRF-2.3.1-21-2022-00003 and 2019-2.1.7-ERA-NET-2021-00015, and EU\u0026rsquo;s Horizon 2020 grant No. 739593.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKumar, M. 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S. \u003cem\u003eet al.\u003c/em\u003e Single-pot, solid-phase-enhanced sample preparation for proteomics experiments. \u003cem\u003eNat Protoc\u003c/em\u003e \u003cstrong\u003e14\u003c/strong\u003e, 68\u0026ndash;85 (2019).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Postprandial, extracellular vesicles, plasma, liquid biopsy, proteomics, fasting","lastPublishedDoi":"10.21203/rs.3.rs-4426110/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4426110/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eExtracellular vesicles (EVs) are key in intercellular communication, carrying biomolecules like nucleic acids, lipids, and proteins. This study investigated postprandial characteristics and proteomic profiles of circulating large extracellular vesicles (lEVs) in healthy individuals. Twelve participants fasted overnight before baseline assessments. After consuming a controlled isocaloric meal, lEVs were isolated for proteomic and flow cytometric analysis. Plasma triacylglyceride (TAG) levels confirmed fasting completion, while protein concentrations in plasma and lEVs were monitored for postprandial stability. Proteomic analysis identified upregulated proteins related to transport mechanisms and epithelial/endothelial functions postprandially, indicating potential roles in physiological responses to nutritional intake. Enrichment analyses revealed vesicle-related pathways and immune system processes. Flow cytometry showed increased expression of CD324 on medium-sized CD9\u003csup\u003e+\u003c/sup\u003eCD63\u003csup\u003e+\u003c/sup\u003eCD81\u003csup\u003e+\u003c/sup\u003e EVs postprandially, suggesting an epithelial origin. These findings offer insights into postprandial lEV dynamics and their physiological significance, highlighting the need for stringent fasting guidelines in EV studies to account for postprandial effects on EV composition and function.\u003c/p\u003e","manuscriptTitle":"Circulating pre- and postprandial extracellular vesicle proteomic profiles","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-04 19:01:26","doi":"10.21203/rs.3.rs-4426110/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-06-28T09:43:35+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-28T07:53:00+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-18T21:04:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"303120431911525039333907008003793822357","date":"2024-06-04T03:46:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-03T14:27:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"69257990822936740366990016781198244536","date":"2024-06-01T01:20:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"150884208543888573181119071029524063187","date":"2024-05-29T07:54:40+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-05-22T11:36:28+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-22T11:13:15+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-05-22T09:46:08+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-20T05:24:11+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-05-15T15:15:44+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0cfa0ccc-6d43-4de9-b80f-f42933bfe447","owner":[],"postedDate":"June 4th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":32542174,"name":"Biological sciences/Chemical biology/Proteomics"},{"id":32542175,"name":"Health sciences/Biomarkers"}],"tags":[],"updatedAt":"2024-10-07T16:06:57+00:00","versionOfRecord":{"articleIdentity":"rs-4426110","link":"https://doi.org/10.1038/s41598-024-74228-4","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-10-03 15:56:55","publishedOnDateReadable":"October 3rd, 2024"},"versionCreatedAt":"2024-06-04 19:01:26","video":"","vorDoi":"10.1038/s41598-024-74228-4","vorDoiUrl":"https://doi.org/10.1038/s41598-024-74228-4","workflowStages":[]},"version":"v1","identity":"rs-4426110","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4426110","identity":"rs-4426110","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}