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Journal of Extracellular Vesicles logoLink to Journal of Extracellular Vesicles
. 2024 Jul 25;13(7):e12485. doi: 10.1002/jev2.12485

Normothermic liver perfusion derived extracellular vesicles have concentration‐dependent immunoregulatory properties

Heather Jennings 1, Stacey McMorrow 1, Peter Chlebeck 1, Grace Heise 1, Mia Levitsky 1, Bret Verhoven 1, John A Kink 2, Kristin Weinstein 1, Seungpyo Hong 3, David P Al‐Adra 1,✉
PMCID: PMC11270586  PMID: 39051751

Abstract

Extracellular vesicles (EVs) are major contributors to immunological responses following solid organ transplantation. Donor derived EVs are best known for their role in transplant rejection through transferring donor major histocompatibility complex proteins to recipient antigen presenting cells, a phenomenon known as ‛cross‐decoration’. In contrast, donor liver‐derived EVs are associated with organ tolerance in small animal models. Therefore, the cellular source of EVs and their cargo could influence their downstream immunological effects. To investigate the immunological effects of EVs released by the liver in a physiological and transplant‐relevant model, we isolated EVs being produced during normothermic ex vivo liver perfusion (NEVLP), a novel method of liver storage prior to transplantation. We found EVs were produced by the liver during NEVLP, and these EVs contained multiple anti‐inflammatory miRNA species. In terms of function, liver‐derived EVs were able to cross‐decorate allogeneic cells and suppress the immune response in allogeneic mixed lymphocyte reactions in a concentration‐dependent fashion. In terms of cytokine response, the addition of 1 × 109 EVs to the mixed lymphocyte reactions significantly decreased the production of the inflammatory cytokines TNF‐α, IL‐10 and IFN‐γ. In conclusion, we determined physiologically produced liver‐derived EVs are immunologically regulatory, which has implications for their role and potential modification in solid organ transplantation.

Keywords: anti‐inflammatory, cross‐decoration, extracellular vesicles, liver‐derived, normothermic liver perfusion, organ tolerance, organ transplantation

1. INTRODUCTION

Donor‐derived extracellular vesicles (EVs) have garnered interest in transplantation due to their capacity to deliver their contents and subsequently modify the cellular activities of recipient cells (Conde‐Vancells et al., 2008; Montecalvo et al., 2012; Valadi et al., 2007; Vallabhajosyula et al., 2017). As membrane‐bound particles, EVs are secreted by a variety of cell types into body tissues and fluids (Yuana et al., 2013). EVs are known to carry a cargo of proteins, nucleic acids, lipids and immunological factors, reflecting the status of the cells of origin, demonstrating their vital role in cell–cell or organ–organ communication (Abels & Breakefield, 2016; Conde‐Vancells et al., 2008; Lee et al., 2021; Montecalvo et al., 2012; Pitt et al., 2016; Valadi et al., 2007). In solid organ transplantation, EVs derived from the donor organ, parenchymal cells or passenger antigen presenting cells (APCs), have been identified as having a key role in the initiation of acute allograft rejection (Zeng et al., 2021). The key component of this type of EV‐mediated rejection is due to their ability to transport donor major histocompatibility complexes (MHC) to recipient APCs (Liu et al., 2016). When donor MHC molecules from donor EVs become present on recipient APCs (a phenomenon known as cross‐decoration) it activates the recipient immune system via the semi‐direct pathway of allorecognition, which is a major contributor to clinical organ rejection (Benichou et al., 2020; Liu et al., 2016; Marino et al., 2016).

Although EVs are primarily associated with transplant rejection, they have also been shown to be a driver of tolerance in some transplant models (Ono et al., 2018) and clinical settings (Lema et al., 2022; Mastoridis et al., 2021). For example, in a small animal model of liver transplantation, cross‐decoration of recipient APCs by donor EVs is associated with a significant increase in the expression of programmed death ligand 1 (PD‐L1), an immune inhibitory protein, on these recipient cells (Ono et al., 2018). This cross‐decoration is thought to be the driving force behind the transplant tolerance seen in this model. Furthermore, EVs isolated from cultured hepatocytes or mechanical separation of livers have restorative properties, particularly after liver tissue damage (Lee et al., 2021; Nojima et al., 2016). In the clinical setting, we have shown that after liver transplantation, donor liver‐derived EVs are capable of cross‐decorating recipient cells and these cells express higher amounts of PD‐L1 (Lema et al., 2022). Mastoridis et al. (2021) further show that donor liver‐derived EVs are capable of cross decoration in vitro and create immunoregulatory recipient cells. Taken together, these data suggest that depending on the cellular source, and cargo, donor‐derived EVs can promote tolerance. However, the animal in vitro models do not adequately represent the physiological secretion of EVs, and clinical studies lack mechanistic details of how cross‐decorating donor EVs create tolerogenic recipient cells.

To investigate donor liver‐derived EVs in a physiological transplant model, we employed normothermic ex vivo liver perfusion (NEVLP), a clinically relevant contemporary technique used for organ preservation (Chapman et al., 2023). During NEVLP, the liver is housed at a physiological temperature whilst providing a continuous supply of nutrients, oxygen and medications. This technique allows the isolation and characterisation of liver‐derived EVs produced in a physiological fashion. Combined with our recent research demonstrating the acellular (and EV‐free) oxygen carrier, Oxyglobin, is a viable alternative to packed red blood cells in NEVLP (Jennings et al., 2022), we can specifically isolate EVs produced by the liver.

2. METHODS

2.1. Animals

Male Lewis (LEW) and Brown Norway rats (BN) aged 8–16 weeks were used in all experiments (both from Charles River Laboratories, Wilmington, MA). Animals were housed in specific pathogen‐free conditions in animal care facilities at the University of Wisconsin (UW)‐Madison in accordance with institutional guidelines. The study (protocol #B0007) was approved by the Institutional Animal Care and Use Committee at UW‐Madison, and all animals were treated ethically.

2.2. Surgery and liver procurement

Donor surgeries were performed under inhaled 5% isoflurane (Phoenix, St. Joseph, MO) anaesthesia for induction and 2%–3% isoflurane maintenance. After disinfection with betadine (Purdue Products L.P., Stamford, CT), the abdominal cavity was opened by midline and transverse incisions and the portal vein was exposed. The common bile duct was cannulated with a 24‐gauge angiocath (BD, Sandy, Utah), and the hepatic artery and gastrosplenic and duodenopancreatic branches of the portal vein were isolated and ligated. Heparin (400 U, Fresenius Kabi, Lake Zurich, IL) was injected through the inferior vena cava and allowed to circulate for 5 min. The portal vein was then cannulated with a 1.3 mm mini ball cannula with a basket tip (Harvard Apparatus, Holliston, MA) and flushed with 20 mL of ice cold 0.9% saline (Baxter, Deerfield, IL). Livers were then explanted, weighed and connected to the perfusion machine with minimal cold ischemic time (<5 min).

2.3. Perfusate composition

The perfusate was made up of 50 mL William's E Medium (Quality Biological, Gaithersburg, MD), 3250 U of each penicillin/streptomycin (Life Technologies Corporation, Grand Island, NY), 0.65 mM sodium pyruvate (Sigma‐Aldrich, St. Louis, MO), 1.30 mM l‐glutamine (Sigma‐Aldrich), 1% human albumin (Baxter), 500 U heparin, 15 mg papaverine (American Regent, Inc., Shirley, NY), 1 mg insulin (Sigma—Aldrich), 1.25 mg hydrocortisone (Pfizer, New York, NY) and 46 mL of Oxyglobin (generously provided by Hemoglobin Oxygen Therapeutics LLC).

2.4. Machine perfusion

Ex vivo machine perfusion was performed as described previously (Jennings et al., 2022) and the experimental design shown in Figure 1. Briefly, warmed, oxygenated perfusate is delivered through the portal vein of LEW or BN livers at 1.8 mL/min/g liver by a peristaltic pump. Temperature, pressure, flow rate and oxygen saturation were monitored throughout perfusion (Hugo Sachs Elektronic, Harvard Apparatus). The oxygenator was supplied by 95% O2 / 5% CO2 gas to maintain > 95% saturation of the perfusate, and the temperature of the liver was maintained at 37°C.

FIGURE 1.

FIGURE 1

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Experimental schematic. The schematic of the experimental procedures in this study. A rat liver produced EVs during NEVLP. EVs were isolated from samples taken every hour during the perfusion and from the remaining perfusate at the end of the perfusion. The isolated EVs were characterised and tested for functionality.

An i‐STAT point‐of‐care analyser (CG4+ and CHEM8+ cartridges, Abbott Point of Care Inc., Abbott Park, IL) was used for hourly inflow perfusate testing. Perfusate samples (1 mL) were collected at baseline (hour 0) and after 1 h of perfusion and immediately stored at −80°C until further processing. These time points were selected to minimise perfusate solution loss early in the perfusion. At the end of the 4 h perfusion, all remaining perfusion solution was collected (end perfusate) and immediately stored at −80°C until further processing. At the end of perfusion, the liver was partitioned for histological analysis and liver‐resident APCs isolation, as described previously (Nojima et al., 2016).

2.5. EV isolation

EVs were handled and stored in accordance with the Minimal information for studies of extracellular vesicles (MISEV2023) guidelines (Welsh et al., 2024). EVs were isolated from perfusate samples taken at hour 0, 1 and 4 using Izon qEV original 35 nm Gen2 size exclusion chromatography (SEC) columns (IZON Sciences Ltd., Christchurch, New Zealand) according to the manufacturers protocol. EVs from the end perfusate were isolated using a two‐step centrifugation process as described by Thery et al. (2006). Briefly, the perfusate was first centrifuged at a low‐speed spin (2000 × g at 4°C for 20 min) to remove any cell debris and/or aggregates. The supernatant was then collected and placed in 30 mL conical polypropylene ultracentrifuge tubes (Beckman Coulter Inc, Brea, CA, USA), and centrifuged at 100,000 × g average at 4°C for 2 h using the Optima™ L‐80XP Ultracentrifuge (Beckman Coulter Inc.) in an SW‐28 rotor (Beckman Coulter Inc.). The supernatant was removed by aspiration, and tubes inverted to drain the excess fluid from the EV pellet. EVs were then re‐suspended in PBS at a volume proportional to the starting perfusate material (100 µL of PBS per 30 mL of perfusate) and stored at −80°C. To obtain the higher EV concentrations used in dose titrations for both cross‐decoration and mixed lymphocyte reaction (MLR) experiments, end perfusate ultracentrifuged (UC) samples from three sequential NEVLP experiments were combined.

2.6. Western blotting

Due to the dilute amount of protein in each sample, an acetone protein precipitation was performed on the ultracentrifuge isolated EV samples to concentrate the protein. SDS sample buffer was added to each of the dried samples, then boiled at 95°C for 10 min. Liver APCs were lysed in cold RIPA lysis buffer system (Cat #sc‐24948, Santa Cruz Biotechnology, Dallas, TX, USA) with 1 nM Na3VO4 5 mM NaF, and 1× protease inhibitor cocktail (Cat #11836153001, Roche, Basel, Switzerland). The cell lysate was then sonicated at 15% amplitude for 15 s. After sonication, the cell lysate was eluted with SDS sample buffer, boiled at 95°C for 10 min. For immunoblotting, 5–20 µg of protein was loaded and the samples were run through a standard SDS‐PAGE protocol using 12% precast gels (Cat # 4561043, Bio‐Rad, Hercules, CA, USA), then transferred to PVDF membrane (Cat #IPVH00010, MilliporeSigma, Burlington, MA, USA). The membrane was blocked with 1% BSA and then incubated at 4°C overnight in either anti‐TSG101 (T5701, MilliporeSigma) or anti CD63 (AD1, BD Pharmingen, Franklin Lakes, NJ, USA) antibodies, both diluted at a 1:1000 ratio. The membrane was washed three times with PBST for 10 min each time the following day. The secondary antibodies used were anti‐mouse IgG (7076P2, Cell Signaling, Danvers, MA, USA), and anti‐rabbit IgG (7074P2, Cell Signaling) at 1:5000 dilutions, corresponding to the respective primary antibody utilised. The membrane was incubated at room temperature for 3 h, washed with PBST 3 times for 10 min each time. Immunoblots were developed using an odyssey imaging system (Li‐Cor Biosciences) controlled with Image Studio v15.2.

2.7. Nanosight tracking analysis

The NS300 Nanosight Tracking Analysis (NTA) instrument (Malvern Panalytical Ltd., Worcestershire, UK) was used to examine diluted solutions of exosomes. A 532 nm laser was utilised in this analysis. For each sample, 3 videos lasting 45 or 60 s each were obtained and evaluated using the Nanosight 3.0 software. During the analysis, the camera level was established at 14, and the detection threshold was set at 5.

2.8. Cryo‐electron microscopy

Cryo‐Electron Microscopy (cryo‐EM) was performed as follows: CF200 Cu grids (Electron Microscopy Sciences, PA, USA) were glow‐discharged for 30 s with 15 mA current in a Pelco EasiGlow (Ted Pella, Inc., CA, USA). A 3 µL aliquot of the concentrated aqueous sample solution was applied to the carbon side of the grids for 60 s, washed twice in 20 µL of PBS buffer, washed once in 20 µL nanoWTM (Nanoprobes, NY, USA), and then floated on 20 µL nanoWTM for 60 s. Grids were manually blotted with Whatman 1 filter paper (Cytiva, MA, USA) following sample application, each wash, and final staining. The stained grids were dried and stored in a desiccator until imaged in a Talos L120C 120 kV TEM (Thermo Fisher Scientific, OR, USA).

Quantifoil R1.2/1.3 Cu 200 mesh grids (Quantifoil Micro Tools GmbH, Germany) were glow‐discharged for 60 s with 20 mA current in a GloQube (Quorum Technologies, ES, United Kingdom). A 3 µL aliquot of the aqueous sample solution was applied to the carbon side of the grid, incubated for 10 s, and manually blotted with filter paper before one or two additional rounds of sample application and blotting. After the final sample application, the grid was loaded into a Vitrobot Mark IV (chamber humidity 95%, 4◦C) (Thermo Fisher Scientific Hillsboro, OR, USA) and blotted for 2.0 or 3.0 s using the Vitrobot blotters before plunge‐freezing into liquid ethane. Cryo‐preserved samples were stored in liquid nitrogen until imaged.

Cryo‐electron microscopy (cryo‐EM) data collection was performed on a Talos Arctica TEM (Thermo Fisher Scientific Hillsboro, OR, USA) operated at 200 kV. Images were acquired on a Gatan K3 camera equipped with a BioQuantum energy filter (Gatan—Ametek, Inc., CA, USA). Images were collected with a defocus of −2 µm and an energy filter silt width of 20 eV at 24,000× (3.7 Å/pixel, dose of 20 e/ Å2) and 79,000× (1.1 Å/pixel, dose of 48 e/ Å2) using the SerialEM software package (v.3.8.8).

2.9. miRNA isolation and sequencing

miRNA was isolated from 250 µL of SEC‐isolated EV samples using the Qiagen miRNeasy mini kit (Qiagen, Germantown, MD, USA) according to the manufacturer‘s instructions. Bioinformatic analysis of transcriptomic data adhere to recommended ENCODE guidelines and best practices for mRNA‐Seq (Encode Consortium, 2016). cDNA libraries were constructed following the QIAseq miRNA Library Kit (Qiagen, Germantown, MD, USA) protocol using purified total RNA as input. Libraries were sequenced at the University of Wisconsin Gene Expression Center on an Illumina NovaSeq 6000 instrument and initially filtered from reads failing to meet default quality thresholds. Reads were then exported to FASTQ format (bcl2fastq v2.2.0) with corresponding base quality scores. Quality control of the remaining reads was evaluated with fastp (v0.23.2) (Chen et al., 2018). To evaluate expression of known miRNAs, candidate reads were first identified with and filtered from the 3′ Qiagen adapter sequence (5′‐AACTGTAGGCACCATCAAT‐3′) using CutAdapt (v1.3) (Martin, 2011). Next, the reads were aligned with bowtie (v1.1.2) (Langmead et al., 2009) to the Rnor_6.0 reference genome (assembly accession GCA_000001895.4). The software featureCounts (v1.5.1) (Liao et al., 2014) was used to assign read counts to miRNA features defined by miRbase v22.1 (Kozomara et al., 2019). To test for differential gene expression among individual groups, read counts were used as input into edgeR (v3.16.5) (Robinson et al., 2010). Inter‐sample normalisation was achieved with the trimmed mean of M‐values (TMM) method (Robinson & Oshlack, 2010). Statistical significance of the negative‐binomial regression test was adjusted with a Benjamini‐Hochberg False Discovery Rate (FDR) correction at the 5% level (Reiner et al., 2003). Prior to statistical analysis with edgeR, independent filtering was applied and required genes to have a count‐per‐million above k in n samples, where k is determined by minimum read count (10 reads) and by the sample library sizes where n is determined by the number of biological replicates in each group.

As the EV samples were sequenced in two different overlapping batches, the GLM in edgeR included a batch factor in the design matrix to account for any additive batch effect due to the two sequencing runs. Heatmaps of the Pearson correlation difference and expression levels along with a multi‐dimensional scaling (MDS) ordination of gene expression were created using library‐normalised data converted with a regularised logarithm variance‐stabilising transform (rlog) (Love et al., 2014) and plotted with R (v4.2.2) (Core Team, 2020). These plots are presented with batch variation removed, which was achieved with limma (v3.54.0) function removeBatchEffect (Ritchie et al., 2015).

2.10. miRNA pathway analysis

Differentially expressed miRNAs (FDR ≤ 0.05, up to 10 differentially expressed miRNAs) were used to perform transcriptome‐wide miRNA target prediction with MirTarget (Liu & Wang, 2019) as implemented in miRDB (Chen & Wang, 2020) using the rat transcript model. Gene targets predicted by MirTarget were ranked by a calculated target score, which reflects the statistical assessment of the prediction accuracy. Genes exhibiting scores ≥ 95 were selected and used to evaluate evidence for enrichment in KEGG pathway and GO:MF databases (Ge et al., 2020).

2.11. Cross‐decoration of splenocyte APCs

5 × 105 BN spleen APCs were freshly isolated and cultured in EV‐free RPMI 1640 (Biological industries, Watertown, MA) with 10% exosome‐depleted Foetal Bovine Serum (Gibco, Thermo Fisher Scientific Inc., Waltham, MA), with NEVLP‐derived EVs added to select wells. After 24 h, the cells were examined for cross‐decoration frequency using flow cytometry with an Attune Flow Cytometer (ThermoFisher Scientific). Fluorochrome‐labelled monoclonal antibodies used are listed in Table S1. Cross‐decoration efficiency percentages were calculated following subtraction of negative control values for each set.

2.12. Mixed lymphocyte reaction

For the MLR, freshly isolated BN lymph node cells and LEW splenocytes were used as responder and stimulator cells, respectively. In phosphate buffered saline (PBS), at a concentration of 1×106 cells/mL, responders were labelled with a 1:10,000 dilution of Cell Trace Far Red (CTFR; Thermo Fisher Scientific, Waltham, MA, USA). Stimulator cells received 20 grey irradiation prior to culture. In a 96‐well plate, 2×105 responders were plated with 0.5×105 irradiated stimulators in RPMI media supplemented with 10% foetal bovine serum. Pooled end‐perfusate EVs isolated by ultracentrifugation were added to select wells at various concentrations. Negative controls were established using both labelled and unlabelled BN lymphocytes. Non‐specific stimulation using activating plate‐bound anti‐CD3 (1 µg/mL; BD Biosciences) and soluble anti‐CD28 (1 µg/mL; BD Biosciences) served as positive controls. All experimental conditions were performed in quintuplicates. After 4 days of culture at 37°C, cells and supernatant were collected, and flow cytometry data were acquired using an Attune Flow Cytometer (ThermoFisher Scientific). Data analysis was performed using FlowJo software (Tree Star, San Carlos, CA, USA).

2.13. Cytokine analysis

LEGENDplex™ Rat Inflammation Panel (BioLegend, San Diego, CA, USA) was used according to the manufacturer's recommendations to detect IL‐1a, IL‐1b, IL‐6, IL‐10, IL‐12p70, IL‐17A, IL‐18, IL‐33, CXCL1, CCL2 [Monocyte Chemoattractant Protein‐1 (MCP‐1)], granulocyte macrophage colony‐stimulating factor (GM‐CSF), interferon (IFN‐g), tumour necrosis factor (TNF‐a), from the supernatant of MLR wells. Data were acquired on a BD FACS Calibur and analysed in LEGENDplex™ software package v7.1.21.

2.14. Statistical analysis

Statistical analyses (aside from the above‐described miRNA statistical analysis) were performed in GraphPad Prism v.8.3.1. Holm Šídák t‐test was used to analyse the MLR experiments and the LEGENDplex™ experiment was analysed with a one‐way ANOVA test followed by Fisher's Least Significant Difference test.

3. RESULTS

3.1. NEVLP

Liver function and perfusion quality were assessed throughout each NEVLP experiment. All livers demonstrated uniform perfusion and were free of gross ischemia (Figure S1A). The perfusion lactate concentrations were measured hourly and the rate of lactate clearance was calculated between each subsequent hour of perfusion (Figure S1B). Total bile collection was measured at the conclusion of each experiment (Figure S1C) with no significant difference between groups. Histopathological analysis of liver architectural damage after NEVLP was scored according to the Suzuki criteria (Suzuki et al., 1993) (Figure S1D,E). These results indicate that livers undergoing sustained minimal architectural damage and was similar between LEW and BN livers.

3.2. Liver‐derived EV isolation and characterisation

Successful isolation of EVs from the end perfusate from the hourly samples by SEC and the end perfusate after 4 h of NEVLP by UC was confirmed by Cryo‐EM, Western blot and NTA. Cryo‐EM images were captured from samples obtained at two time points: before the liver was connected to the machine (T0) and after 4 h of NEVLP (T4) (Figure 2a). Images of the T0 perfusate show no EVs, whereas the T4 samples demonstrate the presence of EVs, suggesting EVs are being produced by the liver during NEVLP. Western blot images (Figure 2b) indicate the presence of EV‐associated tetraspanin proteins CD63 and TSG101. NTA was performed on EVs collected at distinct time points: prior to liver connection to the machine (T0), 1 h into the perfusion (T1), and after 4 h of NEVLP (T4). Additionally, NTA was performed on the ultracentrifuged perfusate solution obtained at T0 and T4 (Figure 2c). The mode size of particles did not significantly differ depending on the method of EV isolation at the end of NEVLP (Figure 2d). The concentration of particles increased between T0 and T4 in both NEVLP groups (Figure 2e).

FIGURE 2.

FIGURE 2

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Characterisation of EVs produced by the liver during NEVLP. (a) Representative cryogenic electron microscopy images of the perfusate samples indicate the presence and the expected morphology of the EVs at T4 as well as the lack of EVs at T0. Scalebar: 100 nm; inset 50 nm. (b) The purified liver EVs and liver cell lysates (5–20 µg) were loaded to detect EV markers, TSG101 and CD63 via western blot analysis. (c) Representative nanosight tracking analysis (NTA) data showing the size and concentration of EV isolates from their respective groups, D) the mode size distribution of EVs isolated from each group and (e) the particle concentrations at T0, T1 and T4, indicating that the concentration of EVs throughout the perfusion.

3.3. Liver‐derived EVs contain multiple anti‐inflammatory miRNAs

miRNA isolated from LEW liver‐derived EVs was sequenced at the University of Wisconsin Gene Expression Center. Analysis of miRNAs isolated prior to the liver being placed into the circuit (T0) and after 4 h of perfusion (T4) demonstrate distinct populations in the MDS ordination plot (Figure 3a). Pearson correlation differences of miRNA expression levels were used to create a heatmap to demonstrate significant changes between T0 and T4 samples (Figure 3b). Last, a volcano plot was created to showcase differentially expressed miRNAs between T0 and T4 samples (Figure 3c). There were 28 differentially upregulated miRNAs between the T0 and T4 samples with a FDR of < 0.05. These miRNAs were classified as either inflammatory, anti‐inflammatory, pleotropic or no inflammatory function in Table 1. The majority of the upregulated miRNAs were anti‐inflammatory.

FIGURE 3.

FIGURE 3

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Liver‐derived EVs contain multiple anti‐inflammatory miRNAs. (a) The MDS plot indicates that the levels of miRNAs isolated from the T0 samples differ from those of the T4 samples. (b) The heat map indicates the changes in miRNA expression between the two groups and (c) the volcano plot indicates the miRNAs most upregulated over the course of the perfusion.

TABLE 1.

Functional description of significantly upregulated miRNAs categorised by their inflammatory nature.

Anti‐inflammatory
miRNA Description FDR
rno‐miR‐378a‐3p Protective effects on renal allografts to prevent IRI during kidney transplantation (Xiong et al., 2020) 1.27758E‐14
rno‐miR‐142‐5p Reduced pulmonary oedema, neutrophil infiltration, and TNF‐α and IL‐6 levels, in a septic acute lung injury model (Zhu et al., 2022) 1.08322E‐05
rno‐miR‐30d‐5p Immunomodulatory role in type 1 diabetes (Gomez‐Muñoz et al., 2023) 4.68875E‐05
rno‐miR‐24‐3p Attenuates T cell function, inflammation and the expression of pro‐inflammatory mediators (Oladejo et al., 2022) 6.12614E‐05
rno‐miR‐126a‐3p Represses inflammation by targeting VCAM‐1 and S1PR2 (Cantaluppi et al., 2012; Yu et al., 2020) 9.51196E‐05
rno‐miR‐126a‐5p Represses inflammation by targeting VCAM‐1 and S1PR2 (Cantaluppi et al., 2012; Yu et al., 2020) 0.000253251
rno‐let‐7d‐5p Suppresses inflammatory response in neonatal rats with necrotising enterocolitis via LGALS3‐mediated TLR4/NF‐κB signaling pathway (Sun et al., 2020) 0.000433788
rno‐let‐7 g‐5p Inhibiting Th17 cell differentiation (Yang et al., 2020) 0.000898906
rno‐miR‐26b‐5p Inhibits inflammatory response and oxidative stress in ischemia‐reperfusion injury (Jia et al., 2022) 0.001215039
rno‐miR‐23b‐3p Regulates multiple inflammatory cytokine pathways (Hu & O'Connell, 2012; Zhu et al., 2012) 0.001296686
rno‐miR‐191a‐5p Inhibit inflammatory cytokine productions and apoptotic protein levels in septic rats (Qin et al., 2019) 0.002889784
rno‐miR‐153‐3p Decreases inflammatory cytokine production in spinal cord and myocardial ischemia models (Qiu et al., 2021; Zhou et al., 2022) 0.003867883
rno‐miR‐22‐3p Suppresses inflammatory response in sepsis model (Wang et al., 2020) 0.004636318
rno‐miR‐26a‐5p Suppresses inflammatory response in sepsis‐induced model (Chen et al., 2022) 0.004936964
rno‐miR‐27b‐3p Alleviates fibrosis and IRI (Bai et al., 2021; Cheng et al., 2023; Gao et al., 2023) 0.004936964
rno‐let‐7i‐5p Reduces oxidation and inflammation, and promotes the polarisation of macrophages towards the M2 phenotype (Zhao et al., 2018) 0.027192264
Pro‐inflammatory
miRNA Description FDR
rno‐miR‐122‐5p Promote lipid accumulation, inflammation and oxidative stress in the liver in response to high fat diets (Hu et al., 2022) 3.67247E‐17
rno‐miR‐30e‐5p Targets multiple negative regulators of innate immune signaling and enhances immune responses(Mishra et al., 2020) 0.001298911
rno‐miR‐151‐5p Upregulated in adipose tissue during induced allergic reaction in rats (Szczepankiewicz et al., 2020) 0.004636318
rno‐miR‐192‐5p Associated with liver injury and subsequent inflammation (Lv et al., 2021; Motawi et al., 2018) 0.00539276
rno‐miR‐125b‐5p Promotes generation of M1 phenotype in macrophages, driving M1 macrophage inflammation(Harrell et al., 2019; Huang et al., 2019) 0.028949514
rno‐miR‐423‐5p Contributes to LPS‐induced NF‐κB activation (Wang et al., 2017) 0.032231178
Pleotropic
miRNA Description FDR
rno‐miR‐29a‐3p Promotes DC maturation, migration and alloreactive T cell proliferation also promotes tendon healing and alleviates steatotic liver ischemia‐reperfusion injury (Li et al., 2022; Ranganathan et al., 1950) 8.98091E‐08
rno‐miR‐27a‐3p Targets GLP1R to accelerate inflammatory response in osteoblasts also downregulating TICAM‐2 of the TLR4 signaling pathway (Li et al., 2015; Zeng et al., 2022) 0.016175554
rno‐miR‐21‐5p Targets TLR4 downstream, promoting expression of inflammatory factors. Also polarizes macrophages to M2 phenotype to reduce inflammation (Shen & He, 2021) 0.02315642
No inflammatory function
miRNA Description FDR
rno‐miR‐30a‐5p Tumour suppressor (Jiang et al., 2018) 8.98091E‐08
rno‐miR‐1b Maintenance of cardiac tissue, Bone marrow mesenchymal stem cells (Safa et al., 2020) 0.006003391
rno‐miR‐184 Essential role in apoptosis, neurological development (Li et al., 2011) 0.015957702
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Next, we conducted pathway analysis of differentially expressed miRNA's between the T0 and T4 time points using the KEGG and GO:MF databases. KEGG analysis revealed ‛Protein digestion and absorption’ and ‛MicroRNAs in cancer’ pathway enrichment (Figure 4a), whereas GO:BP identified ‛Poly(G) binding’ and ‛Dynein complex binding’ as the top pathways that were enriched (Figure 4b).

FIGURE 4.

FIGURE 4

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miRNA pathway enrichment. (a) KEGG pathway enrichment and (b) GO‐BP pathway enrichment for differentially expressed miRNAs between the start and the end of perfusion.

3.4. Cross‐decorating efficiency

Given cross‐decoration of allogeneic cells is the first step in the semi‐direct pathway of allorecognition, the ability of liver‐derived EVs isolated after NEVLP to cross‐decorate allogeneic cells was investigated. To accomplish this, various concentrations of LEW liver‐derived EVs were added to BN splenocytes and cultured for 24 h (Figure 5a). To determine if the liver‐derived EVs that were doing the cross‐decorating of BN APCs originated from immune or parenchymal cells within the liver, we assessed for the expression of LEW MHC class I and II. More cross‐decorating occurred with 5 × 109 than 5 × 108 LEW EVs as shown in Figure 5b with a net 9.8% versus 5.5%, respectively, indicating cross‐decorating is concentration dependent. These experiments also show that the majority of BN cross‐decorated cells express LEW MHC class II, whether alone or in combination with MHC class I. No BN APCs demonstrated cross‐decorating with LEW MHC class I only. These findings suggest liver‐derived EVs generated during NEVLP arise primarily from immune (MHC class II positive) cells.

FIGURE 5.

FIGURE 5

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Cross‐decorating efficiency of liver‐derived EVs is concentration dependent. (a) Representative flow cytometry plots of BN splenocytes with the addition of either BN or various concentrations of LEW liver‐derived EVs. The antibody clones B5 and OX3 are specific for LEW class I and II major histocompatibility complexes, respectively. The BN APC gating strategy is shown in Figure S2. (b) Bar graph summary of each quadrant of the flow plots in A, with data being presented as percent change relative to 0 EV control following background subtraction of negative (BN EV) control.

3.5. Mixed cellular reaction and cytokine profile

To determine the immunological function of liver‐derived EVs, MLRs were performed with various amounts of LEW EVs. MLR results demonstrate similar BN responder cell proliferation when comparing the control (no EVs added) to the group with 5×107 EVs added (Figure 6a). At higher concentrations of EVs added (5 × 108 and 5 × 109) there was a significant decrease in proliferation response when compared to the control and 5 × 107 EV groups. Samples of supernatant from the MLR cultures on day 4 then underwent cytokine analysis. Of the 13 cytokines detected in the LEGENDplex™ Rat Inflammation kit, IL‐1b, IL‐18, IL‐1a, IL‐12p70, IL‐33 and CXCL1 were below the level of detection for all samples (data not shown). Results for the remaining cytokines are shown in Figure 6b. Similar to the observed MLR proliferation response, when 5 × 107 EVs were added, all measurable cytokines were comparable to the control; except for a significant increase in TNF‐α. The addition of 5 × 108 EVs statistically decreased the level of IL‐6 and increased the level of GM‐CSF. The trend of decreasing cytokine response continued when 5 × 109 EVs were added to the MLR, with all measured cytokines statistically decreased compared to the control.

FIGURE 6.

FIGURE 6

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Liver‐derived EVs can decrease an allogenic proliferation response. (a) Relative proliferation of BN lymph node cells stimulated with irradiated LEW splenocytes 4:1 and treated with LEW EVs at various concentrations. The non‐specific proliferation response (positive control) showed that all cells are capable of proliferation (data not shown). (b) MLR supernatant was collected and cytokines were measured. Data are presented as percent change relative to the 0 EV control following background subtraction of negative control. Asterisks indicate p values as follows: *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.

4. DISCUSSION

EVs have a central role in the immunological response post‐solid organ transplantation and mitigating this response could decrease rates of organ rejection. Rejection of a transplanted liver is a major cause of morbidity and can lead to loss of the organ and death (Levitsky et al., 2017; Palmer et al., 2018). Since the cellular source and cargo contained within EVs can influence whether EVs stimulate or regulate the immune system (Marino et al., 2016; Ono et al., 2018), we characterised the immunological effects of liver derived‐EVs. By utilising clinically relevant NEVLP methods, we were able to evaluate EVs being produced specifically by the liver in a physiological setting. We determined EVs are produced by the liver during NEVLP and are detectable in the perfusion solution after the first hour of perfusion (Figure 2e). Between hours one and four, the concentration of EVs did not change significantly, which may be due to EVs only being released during the initial phase of NEVLP, or more likely, reaching a steady state of release and degradation. Determining if the phenotype of EVs change during NEVLP is the subject of ongoing experiments.

It is important to identify specific cells within the liver that contribute to its tolerogenic exploit their therapeutic potential (Carlson et al., 2020). For example, EVs derived from mature dendritic cells induced effector T cells that led to skin graft rejection, however, EVs from immature dendritic cells delayed rejection (Segura et al., 2005). Since EVs play a major role in immune system stimulation or regulation, identifying the cells capable of producing tolerogenic EVs may allow engineering of the parent cells to enrich production of their EVs (Sailliet et al., 2022). Although the factors that control tolerogenicity of EVs have not been determined, we found the cargo within liver‐derived EVs to contain large amounts of anti‐inflammatory miRNAs (Table 1). However, the most upregulated miRNA, miR‐122‐5p, is likely inflammatory (Hu et al., 2022). miR‐122‐5p has been previously isolated from EVs generated from cultured hepatocytes in experiments demonstrating the tolerogenic effects of liver‐derived EVs (Holman et al., 2019). Therefore, future studies will be required to determine if the miRNA cargo is the primary driver of immune regulation. In a study by Tapparo et al. EVs enriched with one of three ‛regenerative’ miRNAs (miR‐127, miR‐10a or miR‐486) were unable to improve kidney function in model of acute kidney injury (Tapparo et al., 2019). Perhaps the miRNAs loaded in these EVs were unable to improve kidney function because multiple different miRNAs are required to create an effect. Regardless, the modification of parent cells to create an EV containing a specific miRNA holds promise for generating tolerogenic EVs. Since miRNAs regulate post‐transcriptional gene expression, a comprehensive analysis of their function also requires proteomic profiling of their target genes in future studies.

The transfer of cell surface MHC protein complexes between donor and recipient (cross‐decorating) that is mediated EVs has been shown to be responsible for rejection in solid organ transplantation (Marino et al., 2016). The semi‐direct mechanism of immunological rejection is through the presentation of donor peptides in the context of both self‐ and foreign‐MHC complexes on a recipient APC to recipient T cells (Herrera et al., 1950). This mechanism is a parsimonious solution for the requirement that for a CD4 T cell to ‛help’ a CD8 T cell initiate an immune response, the CD4 T cell must recognise a donor peptide on the same APC that is also directly interacting with the CD8 T cell (Carnel et al., 2023). However, in certain situations, the cross‐decorated cells can mediate tolerance. Indeed, this was determined in a tolerogenic mouse liver transplant model, where graft infiltrating APCs were highly cross‐decorated with donor MHC (Ono et al., 2018). These cross‐decorated cells also expressed high amounts of PD‐L1, a co‐inhibitory signalling protein capable of decreasing an immune response. Although immune‐inhibitory, it is unclear if PD‐L1 expression required for tolerance in this model. In this experimental model, cross‐decoration efficiency was location dependent with the highest levels in the transplanted liver and lower levels in the spleen or blood. In agreement with these results, in the clinical setting, we found that cross‐decorated recipient APC isolated after liver transplant contained significantly more PD‐L1 than non‐cross‐decorated cells (Lema et al., 2022). In the current study, we determined liver‐derived EVs are capable of cross‐decorating allogeneic cells, in a concentration‐dependent fashion (Figure 4). However, the frequency of cross‐decorated cells is lower than in prior studies, where in vitro cross‐decoration can be seen as high as 20% with a similar number of EVs (Mastoridis et al., 2021). This could be a difference in human versus animal models of in vitro cross‐decorating, however, these levels are close to what we found clinically 3 years after liver transplantation (Lema et al., 2022). Despite the low levels of cross‐decorating of donor APCs, these are likely the cells mediating the alloresponse, as EVs themselves may not have a significant direct effect on T cells (Prunevieille et al., 2021). Interestingly, most cross‐decorated allogeneic cells in our study obtained mostly donor MHC class II, with or without MHC I proteins (Figure 4b). This suggests the origin of the cross‐decorating EV are cells within the liver that contain MHC class II, which are primarily immune cells. However, under physiological stress, liver vasculature endothelium, biliary endothelium and hepatocytes can be induced to express MHC class II (Hübscher et al., 1990; Steinhoff et al., 1988). Our results contrast with the findings of Ono et al. (2018), where the cellular source of the cross‐decorating EVs were primarily from hepatocytes. Therefore, the cellular origin of the EVs in our system requires further investigation.

Although factors controlling the immune effects of EV are not known, we determined EVs produced by the liver during NEVLP can decrease an allogeneic immune response in a MLR (Figure 5a). The regulatory immune effect of liver‐derived EVs was concentration‐dependent, only becoming apparent when 5 × 108 or more EVs were added to the MLR. In concordance with the lower proliferation response, the culture supernatant collected from the MLR, showed lower levels of inflammatory cytokines, when more than 5×108 EVs were added (Figure 5b). These results are similar to Mastoridis et al. (2021), where they demonstrated EVs isolated after clinical liver transplantation are capable of cross‐decorating allogeneic cells and these cells generated a lower proliferation response in MLR. The similarity of our functional ex vivo results with the clinical setting inspires confidence that our model system is capturing clinically relevant EVs and will be a system to study the mechanism of the immunological effects of liver‐derived EVs. Our experimental system may be valuable for research into the mechanisms of EV uptake and presentation by allogeneic cells, which would further understanding of cell‐cell communication.

Prior studies have demonstrated the anti‐inflammatory and reparative effects of liver derived EVs. In one study, EVs isolated from cultured primary human hepatocytes were able to decrease the inflammatory effect LPS had on monocytes in vitro (Holman et al., 2019). Specifically, they showed a reduction in IL‐1b and IL‐8 and were able to identify some of the RNA cargo that may be mediating the immune effects. In another study, primary mouse hepatocyte‐derived EVs, but not Kupffer cell‐ or sinusoidal endothelial cell‐derived EVs, were associated with liver regeneration in a dose‐dependent fashion (Nojima et al., 2016). Mechanistic investigations revealed hepatocyte derived EVs transferred sphingosine kinase 2 to target hepatocytes which increased synthesis of the proliferation factor, sphingosine‐1‐phospahate. In an alternative approach, Lee et al. (2021) isolated EVs after mechanical digestion of fresh liver tissue and administered these EVs to mice in an acute liver injury model. They found these EVs could accelerate liver recovery by increasing the levels of hepatocyte growth factor present in the liver. However, in each of these experimental systems, the EVs were not produced in a physiological fashion and may not reflect EVs secreted naturally by the liver. NEVLP provides the opportunity to isolate the liver and specifically collect EVs being produced in a physiological fashion that is near to homeostasis. Furthermore, with the advent of normothermic machine perfusion strategies for multiple organs (liver, lung, heart, kidney), we now have the unique opportunity to study EVs in an organ‐specific fashion and can also attempt to modify the organ prior to transplantation. To this end, we have begun characterising the immunological effects of EVs produced by the liver during NEVLP in the clinical liver transplantation setting. EVs are currently a subject of intense interest in the field of transplantation, where EVs released by kidney grafts during normothermic machine perfusion are being investigated as a biomarker for assessing kidney functional status before transplantation (Woud et al., 2022). In addition, there are growing number of reports examining donor organ EVs as markers for organ rejection (Gunasekaran et al., 2017; Sharma et al., 2020; Vallabhajosyula et al., 2017).

Limitations of our study include using SEC for isolation of the hourly samples. This was done due to the low volumes of perfusate collected during the perfusion. Although SEC offers advantages in being reproducible and able to isolate EVs from low volumes, this method may not correspond to the UC methods used to isolate EV at the end of NEVLP, despite the similar NTA data. Second, we conducted our experiments in the rat because it is an established model of NEVLP and liver transplantation, however, there are few rat antibodies against common EV markers that are commercially available. The lack of anti‐rat antibodies limited our ability to characterise the surface proteins present on liver‐derived EVs. We attempted to overcome this barrier by using both human and mouse EV identification kits and assessing for cross‐reactivity to the rat, however, the results were inconclusive (results not shown). Third, in this study we focused only on miRNA because these RNA species are known to be prominent in EV signalling (Valadi et al., 2007). However, many other RNA types are present in EVs, including long noncoding RNA, ribosomal RNA and messenger RNA, and studies will be required to determine the immune effects of these other types of RNA (O'Brien et al., 2020). Next, a difficulty in the study of EVs is demonstrated by the discordance between NTA and Cryo‐EM data. NTA routinely counted over 1 × 107 particles with heterogeneous sizes in the T0 samples (perfusate prior to the liver being placed on the circuit), yet EVs are not visible in any T0 Cryo‐EM images (Figure 2). According to the NanoSight NS300 manual, ‛the instrument can work with particle concentrations in the range of ∼107–109 particles/mL’, therefore, at lower concentrations, artifacts are likely being counted. This may make quantifying EV numbers and concentrations difficult to compare across experimental systems. Last, there were a limited number of experimental replicants in the cross‐decorating and MLR experiments due to the high number of EVs required for these tests. Ideally, these experiments would be conducted across other rat strains that reject Lewis cells, however, we were not able to conduct these experiments due to challenges with acquiring these rat strains.

In this study, NEVLP was used as a tool to evaluate liver‐derived EVs, however, NEVLP also creates an opportunity for organ evaluation and treatment prior to transplantation. Therefore, future studies will investigate whether the quality of the donor liver influences the EVs being produced and if treatments during NEVLP can modify the types of EVs being produced to be made more tolerogenic. The current study can act as a reference point for testing interventions aimed at EV modification during NEVLP (Figure 6).

AUTHOR CONTRIBUTIONS

Heather Jennings: Data curation; formal analysis; investigation; methodology; writing—original draft; writing—review and editing. Stacey McMorrow: Data curation; formal analysis; investigation. Peter Chlebeck: Data curation; formal analysis; investigation; methodology; writing—original draft. Grace Heise: Data curation; formal analysis; writing—review and editing. Mia Levitsky: Data curation; formal analysis; writing—review and editing. Bret Verhoven: Data curation; formal analysis; investigation; methodology; writing—original draft. John A. Kink: Investigation; methodology; writing—original draft; writing—review and editing. Kristin Weinstein: Formal analysis; investigation; methodology. Seungpyo Hong: Formal analysis; investigation; methodology; project administration. David P. Al‐Adra: Conceptualization; formal analysis; funding acquisition; investigation; methodology; project administration; supervision; writing—original draft; writing—review and editing.

CONFLICT OF INTEREST STATEMENT

The authors declare no conflicts of interest.

Supporting information

Supporting Information

JEV2-13-e12485-s001.jpg (1.1MB, jpg)

Supporting Information

JEV2-13-e12485-s002.jpg (386.4KB, jpg)

Supporting Information

JEV2-13-e12485-s003.docx (14.1KB, docx)

ACKNOWLEDGEMENTS

We would like to thank Matt Brown, Mo Chen, Noah Carrillo, Michael Poellmann, Richard Anderson, Narendra Thapa and Mark Berres for experimental assistance. We also thank the generous contributions from the labs of Christian Capitini and Wei Xu. We thank the University of Wisconsin—Madison Biotechnology Gene Expression Center (Research Resource Identifier—RRID:SCR_017757) for RNA library preparation and the DNA Sequencing Facility (RRID:SCR_017759) for sequencing. We also thank the University of Wisconsin Carbone Cancer Center Flow Cytometry Laboratory, supported by P30 CA014520, for use of its facilities and services. Some of this work was performed in the Cryo‐EM Research Center (CEMRC) in the Department of Biochemistry at the University of Wisconsin‐Madison. Last, we thank Hemoglobin Oxygen Therapeutics LLC for supplying the Oxyglobin used in NEVLP. David Al‐Adra is supported by the National Institute of Allergy and Infectious Diseases under Grant K08AI155816 and by the University of Wisconsin Office of the Vice Chancellor for Research.

Jennings, H. , McMorrow, S. , Chlebeck, P. , Heise, G. , Levitsky, M. , Verhoven, B. , Kink, J. A. , Weinstein, K. , Hong, S. , & Al‐Adra, D. P. (2024). Normothermic liver perfusion derived extracellular vesicles have concentration‐dependent immunoregulatory properties. Journal of Extracellular Vesicles, 13, e12485. 10.1002/jev2.12485

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author, DA, upon reasonable request.

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Supplementary Materials

Supporting Information

JEV2-13-e12485-s001.jpg (1.1MB, jpg)

Supporting Information

JEV2-13-e12485-s002.jpg (386.4KB, jpg)

Supporting Information

JEV2-13-e12485-s003.docx (14.1KB, docx)

Data Availability Statement

The data that support the findings of this study are available from the corresponding author, DA, upon reasonable request.

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