Background
Despite evidence demonstrating that predictive immunological parameters may not be applicable across species, preclinical assessments of vaccines or vaccine adjuvants still typically rely on mouse models as the experimental tool of choice [
1,
2]. Significant differences have been demonstrated between mouse and human immune system development, activation and response to challenge [
2‐
5]. These differences have led to failure in clinical trials of formulations that appeared promising in preclinical studies [
2‐
6]. Because a mouse cannot be considered a “small human” the development of better methods for the study and analysis of human-based immune system models has been identified as an area of critical need in vaccinology. The need for human-based methods has begun to be filled with the continued development in vitro assays [
7,
8] and humanized mice (HM) that harbor a human immune system [
9,
10], both of which show promise but neither of which are currently widely used. Human-based in vitro models may not always replicate the entire immunomodulatory activity of an adjuvant or vaccine and are thus a logical complement to in vivo studies [
1]. This combination of in vitro and in vivo models offers the opportunity to identify cellular receptors and pathways that are conserved between mice and humans as well as species-specific differences in innate and adaptive immune response to vaccines and vaccine adjuvants.
New in vitro technologies for the pre-clinical assessment of innate response to vaccines or adjuvants have been developed. These include new human-based assays that utilize human monocytoid cell lines or primary immune cells to detect the innate response and safety profile of pyrogens, toxic compounds, adjuvants, and vaccines [
11‐
15]. One such model, the Modular Immune In vitro Construct (MIMIC®), models human innate and adaptive immunity in a sensitive, automated, and cost-effective manner [
16]. Two distinct modules of the MIMIC®, the Peripheral Tissue Equivalent model (PTE) and Transwell Peripheral Tissue Equivalent model (TW-PTE), are biomimetic modules designed to simulate innate immune response as it occurs in peripheral tissues such as the skin following an encounter with a vaccine or a pathogen, and can be used to examine human responses against vaccines or vaccine adjuvants. They utilize primary human immune cells coupled with naturally occurring signaling processes to replicate the development of cells responsible for much of the innate immune response. These modules have been shown to reflect appropriate cellular profiles (programmed death, cytokine production, and antigen presenting cell activation/maturation) following stimulation by a variety of test agents including monoclonal antibodies (e.g. TGN1412), seasonal influenza vaccines, immunomodulators and immunosuppressants such as TLR agonists and cyclosporine, respectively [
11,
13,
16‐
19]. Genome-wide transcriptome analysis represents an additional tool for the evaluation of innate response to vaccines or vaccine adjuvants, providing a signature of innate immune response to various challenges [
1,
20‐
22]. Molecular signatures in the blood of humans induced a few days after vaccination have been used to predict the magnitude of later immune responses to a vaccine and are beginning to yield insights about the nature of the innate and adaptive responses to vaccination [
23‐
25]. Additionally, in the vein of translational science, this technology can be applied to the evaluation of vaccine adjuvants in pre-clinical assessments including both in vivo models [e.g. murine, non-human primates (NHP)] and in vitro models (e.g. MIMIC®), the results of which have direct applications to later clinical evaluations in humans.
In recent years researchers have begun developing new classes of vaccine adjuvants which target natural innate response pathways in immune cells. These include compounds targeting pattern recognition receptors (PRRs) such as the TLRs and RLRs. PRR agonists have garnered considerable interest in recent years based on their ability to activate an immune response in a manner consistent with that triggered by invading pathogens. For example, the use of the synthetic ligand CpG (a TLR9 agonist) co-administered with various protein antigens has been investigated in a number of preclinical trials, and shown to induce potent antigen-specific responses [
26‐
29]. Activation of PRRs leads to downstream activation of transcription factors resulting in expression of various genes that drive immune cell maturation, expression of co-stimulatory molecules and production of cytokines and chemokines [
30‐
38]. Viral single-stranded RNA (ssRNA) and double-stranded RNA (dsRNA) are among the many PRR-selective agonists binding and activating TLRs, RLRs, and CLRs in cellular membranes, endosomal compartments, and inside the cell through cytoplasmic sensors [
32‐
34,
38]. Species-specific response to ssRNA from human immunodeficiency virus (HIV) has been demonstrated between mice and human, with murine TLR7 and human TLR8 mediating recognition of GU-rich ssRNA, respectively [
31,
33]. In both mouse and human, however, responses to ssRNA and dsRNA through TLRs and RLRs converge on NF-κB and mitogen-activated protein kinase signaling pathways, including the TLR, interleukin (IL)-1, and c-jun N-terminal kinase (JNK) pathways [
32]. Activation of these pathways in multiple immune cell subsets including pDCs, mDCs, monocytes, B-cells, and T-cells results in up-regulation of innate stimulation pathways [
30‐
37].
Synthetic nucleic acids vaccines are being investigated as alternatives to traditional vaccines. When used as vaccines nucleic acids have the potential to not only trigger an immunogenic response to the antigens they encode but also to trigger innate sensors of ribonucleic acid (RNA) or deoxyribonucleic acid (DNA) in immune cells. Although DNA-based vaccines have been investigated for use in molecular medicine and vaccinology, clinical applications have increasingly become compromised based on the efficacy and potential risks inherent in use of plasmid DNA. As an alternative to DNA, mRNA based vaccines have been developed to take advantage of the fact that mRNA molecules have the ability to transiently encode immunogenic antigens and also possess self-adjuvanting activity [
39]. A new class of mRNA vaccines, RNActive® vaccines, is based on conventional mRNA molecules that have been engineered and sequence-modified to optimize various aspects of the molecule, leading to enhanced mRNA half-life and protein expression [
40]. An important building block for the formulation of RNActive® vaccines is protamine, a cationic peptide that forms complexes with RNA. RNActive® vaccines containing protamine consists of an engineered mRNA, which in part is complexed with protamine. This formulation combines the strong expression profile of optimized mRNA with enhanced immune stimulation induced by protamine-complexed mRNA reported to activate the TLR7 receptor [
40‐
43]. This self-adjuvant activity has been investigated in pre-clinical animal studies as well as in clinical safety investigations for both therapeutic cancer and prophylactic vaccines [
40,
42‐
46].
In the present study, we applied a combined series of analytical techniques which constituted an original translational approach to a pre-clinical assessment of the basic mechanisms of self-adjuvantation from mRNA vaccines in an in vitro human model and in vivo in inbred mice. We used the in vitro model of the human immune system termed the MIMIC® to evaluate innate responses induced by distinct doses of the mRNA vaccine encoding influenza A hemagglutinin (HA). These responses were compared to profiles found in C57 BL/6-mice after intradermal injection. The murine samples were taken from two locations, at the injection site and in the draining lymph node (dLN). Phenotypic alterations of immune stimulatory cells and cytokine response in both the MIMIC® and in the mice were analyzed and compared. In each case an analysis of transcriptional changes was also performed, with activation pathways evaluated to compare gene expression profiles in both the human MIMIC® and the mouse after intradermal injection (ID) with mRNA vaccine.
Methods
Study design
This study was designed to evaluate the innate stimulatory profiles and basic mechanisms of self-adjuvantation of an mRNA-based vaccine encoding influenza A hemagglutinin in humans and inbred C57BL/6 mice. For all three phases of this study an mRNA vaccine encoding influenza A hemagglutinin of the pandemic strain H1N1pdm09 from the isolate A/Netherlands/602/2009 was used as the model [
43,
45]. The first study phase consisted of experiments on MIMIC®-PTE modules to assess the adjuvant properties of different concentrations of mRNA vaccine versus a benchmark vaccine (Fluzone®, Sanofi Pasteur) and the TLR7/8 agonist R848. These experiments were designed to test the immunostimulatory potential of these treatments in humans through the use of the human MIMIC® system to establish associated phenotypic and cytokine profiles. The second study phase was an analysis of transcriptome changes in humans in response to immunostimulation with the mRNA vaccine or R848 as a positive control of TLR7/8 activation. For this study the human MIMIC® Transwell-PTE module was used to generate RNA samples for use in full genome microarray analysis. The third and final phase of this work was performed in wild type mice to assess the mechanisms of self-adjuvantation from the mRNA vaccine by evaluation of cellular and molecular sensors at the injection site and in the dLN. To perform this analysis of gene expression patterns a full genome microarray analysis was performed on skin biopsies or the dLN after intradermal injection of the mRNA vaccine.
Preparation of peripheral blood mononuclear cells for MIMIC®
Apheresis blood products were collected from 30 donors (phase 1 study: 24 donors; phase 2 study: 6 donors). The collections and study protocol were reviewed and approved by Chesapeake Research Review Inc (Columbia, Maryland) under IRB 0906009, “Development and testing of the MIMIC®”. All donors were screened and reported to be in good health. All blood products were received and confirmed to be negative for blood-borne pathogens as detected by standard blood bank screening assays.
Peripheral blood mononuclear cells (PBMCs) were enriched by Ficoll density gradient separation according to standard laboratory procedures [
47]. After washing, PBMCs were cryopreserved in dimethyl sulfoxide-containing freezing media for extended storage in liquid nitrogen. Donor PBMCs were chosen at random from our pool for inclusion in this study. In phase 1, 12 “Adult” donors of age <50 years and 12 “Elderly” donors of age ≥65 years were included. All donors for phase 2 were less than 50 years in age.
MIMIC® Peripheral Tissue Equivalent Assay (phase 1 study)
The PTE construct of the MIMIC® system is designed to replicate the early responses of innate immunity (cytokines and antigen presenting cell activation/maturation) in response to test agents [
11,
13,
16,
17]. The MIMIC® PTE module used in this study was built around our published manual technique but automation was used for cell and treatment application and washing steps [
13]. Briefly, endothelial cells were grown to a confluent layer atop a collagen matrix (PureCol; Advanced Biomatrix, San Diego, California). Thereafter, donor PBMCs were prepared from frozen stocks and applied to MIMIC® PTE assay wells. After an incubation period, non-migrated cells were washed away leaving only those cells that had transmigrated across the endothelial barrier into the collagen matrix. Over the course of a 48-h incubation period, antigen presenting cells (APCs), primarily differentiating immature dendritic cells, reverse-transmigrate back across the endothelial barrier (Additional file
1: Fig. S1). Test agents including mRNA vaccine were added to the constructs at the indicated concentrations 24 h prior to cell collection. MIMIC®-PTE modules were left untreated or treated with increasing concentrations of the mRNA vaccine (5–50 μg/10
6 cells), benchmark influenza vaccine (Fluzone® Trivalent 2012–13, FZ, 1:100), or the TLR7/8 agonist R848 (5 μg/ml). 24 human donors were assessed.
The reverse transmigrated cells were harvested after the 48-h incubation period for phenotyping analysis by flow cytometry. The cells were harvested, washed, and labeled for viability with LIVE/DEAD Aqua (Invitrogen, Eugene, Oregon). The cells were then labeled with a multicolor antibody panel specific for cluster of differentiation (CD) 14, human leukocyte antigen-DR, lymphocyte markers (CD3/CD19), and markers of immune cell activation/maturation (CD86, CD40, CCR7, CD25). All antibodies were purchased from eBiosciences (San Diego, California) or BD/Biosciences (San Jose, California). Data was acquired on a BD FORTESSA II flow cytometer (BD/Biosciences) and analyzed using FlowJo software (TreeStar Inc, Ashland, Oregon). Culture supernatants of MIMIC® PTE assays were also analyzed by multiplex bioplex analysis for cytokines and chemokines involved in innate immune cell activation and response [Millipore MILLIPLEX® human cytokine/chemokine kit(s)]. Levels of cytokines were measured in the pg/ml range, allowing for comparison of treated immune cell versus untreated control PTE wells.
MIMIC® Transwell Peripheral Tissue Equivalent Assay (phase 2 study)
As with the MIMIC® PTE construct, the MIMIC® Transwell PTE construct is also designed to replicate the early processes of innate immunity in response to test agents, albeit in a larger-scale manner [
47]. In this system, endothelial cells were grown to a confluent layer atop a transwell membrane. Thereafter, donor PBMCs were prepared from frozen stocks and applied to MIMIC® TW-PTE assay wells. After an incubation period the bucket containing the non-migrated cells was removed leaving only those cells that had transmigrated across the endothelial barrier into the bottom transwell bucket. As in the MIMIC® PTE constructs, these cells were primarily composed of differentiating immature dendritic cells and a small population of leukocytes comprised of B-cells (1–5%) and T-cells (15–20%) and were cultured for 48 h before collection. 24 h prior to collection the mRNA vaccine was added to the TW-PTE modules at 25 μg/10
6 cells. As a positive control, 5 μg/ml R848 was added to the constructs.
Use of the larger-scale MIMIC® TW-PTE system allowed for the collection of enough cells for RNA isolation and purification for use in full genome microarray analysis, all while retaining the cell populations and innate response profile found in MIMIC® PTE modules.
Biopsy of mouse injection sites (phase 3 study)
The mRNA vaccine was applied via intradermal injection, distributed to two sites on the backs of C57BL/6 mice. 2 × 50 μl of mRNA vaccine dissolved in Ringer’s lactate solution were injected, for a total amount of 80 μg of mRNA vaccine. Biopsies were collected 6 or 24 h post treatment from the injection site (two approx. 1 cm2 pieces per mouse) and the dLN (axillary and brachial, four dLN in total). The time points of analysis were selected so that earlier (6 h) and later (24 h) effects could be measured. Animals treated with buffer served as controls. Untreated mice were used as an additional control to exclude the possibility of unspecific effects induced by the injection of the buffer. The animal protocol (CUR6-12) was approved by the regional council in Tuebingen, Germany.
RNA samples from MIMIC® TW-PTE (phase 2 full genome microarray analysis)
24 h after treatment, MIMIC® TW-PTE donor samples (n = 18) were collected and the cells were counted. Briefly, following harvest from the PTE at least 1 × 106 immune cells, composed primarily of immature dendritic cells with a small subset of T-cells and B-cells, were lysed in Buffer RLT (QIAGEN) with freshly added 2-mercaptoethanol and stored at −80 °C. After all time points were collected, the samples were thawed, and the RNA isolation proceeded according to the manufacturer’s protocol (QIAGEN). Total RNA sample quality was evaluated by spectrophotometer to determine quantity, protein contamination and organic solvent contamination, and an Agilent 2200 Tapestation was used to check for RNA degradation. Two-round in vitro transcription amplification and labeling was performed starting with 50 ng intact, uncontaminated total RNA per sample, following the Affymetrix protocol. After hybridization on Human U133 Plus 2.0 Arrays for 16 h at 45 °C and 60 r.p.m. in a Hybridization Oven 640 (Affymetrix), slides were washed and stained with a Fluidics Station 450 (Affymetrix). Scanning was performed on a seventh-generation GeneChip Scanner 3000 (Affymetrix), and Affymetrix GCOS software was used to perform image analysis and generate raw intensity data. Initial data quality was assessed by background level, 3′ labeling bias, and pairwise correlation among samples. For this analysis, we used Affymetrix Human Genome U133 Plus 2.0 Array, but instead of using Affymetrix’s sequence clusters to define genes, which is based on the UniGene database build 133, 20 April 2001, gene sequence clusters were based on the updated UniGene build 199, 16 January 2007, to yield a list of 20,078 genes.
Microarray analysis (phase 2 full genome microarray analysis)
Gene expression data was analyzed using Array Studio (Omicsoft, V7.2). The data was normalized and a MAS5 report was generated for QC assessment. The ArrayStudio (V7.2), Ingenuity Pathway Analysis (IPA,
http://www.ingenuity.com) and GeneGo (Thomson Reuters, MetaCore version 6.19, build 65960) packages were used to identify differentially expressed genes (pFDR < 0.05; fold change >1.3 and <−1.3) compared with mock condition.
Data processing and statistical analysis (phase 2 full genome microarray analysis)
Initial quality control of the microarray signal intensity data was performed using the lumi Bioconductor package [
48] in the R programming language. Regression and ANOVA were carried out in R. Further analysis was carried out using ArrayStudio. Array Studio, Array Viewer and Array Server and all other Omicsoft products or service names are registered trademarks or trademarks of Omicsoft Corporation, Research Triangle Park, NC, USA. Statistical analysis was performed using the SAS environment package JMP® (JMP®,Version 10. SAS Institute Inc., Cary, NC, 1989–2007).
Pathway enrichment and content analysis (phase 2 full genome microarray analysis)
The gene ontology vocabulary used was obtained from the GO Web site (
http://www.geneontology.org, 2014 build). Genes that had shown to be significantly modulated by vaccination, as determined by the microarray analysis were further analyzed for pathway enrichment. Briefly, we used ArrayStudio to analyze the microarray data by pairwise scatter analysis and identify significantly differentially regulated genes. The differentially expressed genes were defined in terms of the log2-fold change for treatment over mock. To limit the detection of false positives, the array data was set with thresholds including p values adjusted by the Benjamini and Hochberg false-discovery-rate method with a cutoff of 0.05. Gene lists were analyzed using GenGo MetaCore analysis software (Thompson Reuters), Ingenuity Pathway Analysis software (Ingenuity Systems) and DAVID Ontology (
http://www.david.abcc.ncifcrf.gov) to identify significantly associated pathways and generate pathway maps.
Phase 3 full genome microarray analyses from mouse tissue biopsies
Total RNA was isolated from RNAlater-preserved biopsy tissues with commercially available kits and gene expression analysis was performed by the service provider MFT Tuebingen, Germany. For this purpose 100 ng of total RNA was amplified per array with the Ambion WT expression kit according to the manufacturer instructions and labeled. The samples were then hybridized and stained on the Affymetrix WT Mouse Gene-2.1-ST GeneChip Array using the Affymetrix hybridization, wash, and stain kit. The arrays were scanned with the Affymetrix GCS3000 reader. The raw data were read in the AGCC 3.0 software and converted to intensity values. Further analysis of the data was performed in R 2.15.1 on various Bioconductor packages. Some arrays did not meet the quality control criteria (one skin sample from group 4, one skin sample from group 5 and one dLN sample from group 3 and were excluded from further analysis. Since at least four replicates per condition were still available, the impact on the statistical analysis should be considered as very low.
To identify differentially expressed transcripts the arrays were normalized via RMA (Robust Multichip Average) [
49]. All subsequent steps were separated by tissue. For the calculation of differentially expressed transcripts a linear model was created for the comparisons of the mRNA vaccine treated groups and the respective buffer controls. Before fitting the model control probes were removed and a non-specific variance filter was applied to eliminate non informative transcripts. Subsequently, the coefficients of the linear model that describes the expression profile of the corresponding gene were calculated based on the experimental design [
50]. The relevant comparisons were defined as a contrast matrix and the F-statistic was calculated for all comparisons, with the standard error moderated through an empirical Bayesian model [
51]. Subsequently, to receive a statement about the significance of the comparisons the p value resulting from the F-statistic was determined and corrected via “Benjamini–Hochberg” for multiple testing for all transcripts followed by a decision matrix [
52]. Similarly, the strength of the change in expression (M value) was determined. The M value is the log2 of the fold change. Because many transcripts were differentially regulated only transcripts with a corrected p value less than 0.01 and a log2 fold change greater than 0.9 (fold change greater than 1.87) were taken into account for the subsequent analysis.
Statistical analysis
All statistical analyses and graphics were prepared using GraphPad InStat version 46.00 (GraphPad Software Inc, San Diego, California). One-way analysis of variance (ANOVA) and Bonferroni posttest analyses were employed to determine statistical significance; p values <0.05 were considered statistically significant.
Discussion
In this study, we evaluated the innate immunostimulatory potential of an mRNA vaccine encoding influenza A hemagglutinin, a vaccine that previously demonstrated protective immunity to influenza A virus infections in mice and pigs [
45]. This evaluation was performed in an in vitro model of human innate immunity and in vivo in mice after intradermal injection. To evaluate the self-adjuvant properties of this novel vaccine a translational approach was undertaken to correlate phenotypic and cytokine/chemokine responses in immune cell populations to transcriptional responses in those same cells. In the human MIMIC® strong correlation was demonstrated in phenotypic, cytokine, and transcriptional response between the TLR7/8 agonist R848 and the mRNA vaccine indicating that at least a part of the signaling involved these TLR receptors. However, there were some noteworthy differences in transcript up-regulation. Both
il-
27 and
il-
8 were down-regulated following treatment with mRNA vaccine and up-regulated by R848.
ddx58 (RIG-1),
ifih1 (MDA-5), and
tlr3 were all up-regulated by the mRNA vaccine to a much greater degree than from R848. These differences support the notion that the vaccine does not act solely through stimulation of the TLR7/8 pathway. The adjuvant effect of mRNA vaccine in humans (MIMIC®) and mice acts through similar cellular RNA sensors found in endosomal compartments as well as within the cytoplasm of immune cells. Transcriptional analysis demonstrated up-regulation of TLR3, 7, and 8 in humans, TLR 3 and 7 in mice, and RLRs such as RIG-I, MDA-5, and inflammasome components in both species. Sixty-five of the 81 “innate” immune-related genes identified in this study demonstrated correlative transcriptional regulation in human MIMIC® modules and at the injection site in mice 6 h after treatment. The most significant immune pathways induced in response to the mRNA vaccine include the TLR, IL-1, and JNK pathways. Results from the phenotypic analysis of immune cell populations and cytokine/chemokine levels of treated human MIMIC® modules and ID injected mice confirmed the immunostimulatory capacity of the mRNA vaccine. Phenotyping revealed immune cell maturation and activation of APCs and B-cells. Cytokine/chemokine analysis indicated production of factors in both systems that could attract and activate key players of the innate and adaptive immune system.
Similarities and differences have been demonstrated between mice and humans in immune system development, activation, and response to challenge [
2‐
6]. The relevance of any study in mice into the effects that immunostimulatory agents and adjuvants to the human response depends upon whether those stimuli target pathways that are conserved or convergent between mice and humans and whether it is realistic to single out particular genes for analysis. In this study the focus was on predicting the innate response in humans following treatment with an mRNA vaccine using two model systems, a human in vitro model and a murine model. The mRNA vaccine largely drove consistent responses in the two despite some species-specific differences in cell populations, differences in RNA sensors between the species, and fundamental differences between in vitro models and in vivo testing. When comparing mice and humans, some differences have been noted in the principle ssRNA sensors present in immune cell populations. In mice, dendritic cells typically express TLR7 whereas in humans TLR8 is present on myeloid-derived DCs (which predominate in our system) while TLR7 can be found on plasmacytoid DCs and B-cells (subsets also found in the MIMIC®) [
31,
32,
56]. Based on the transcriptional profile measured in both humans and mice, genes for RLRs [
ddx58 (RIG-1) and
ifih1 (MDA-5)], TLRs (
tlr3,
tlr7, and
tlr8-
human only), and CLRs (
clec4gp1,
clec2d,
cledl1) were all significantly up-regulated by the mRNA vaccine. The up-regulation of TLR8 and TLR7 points to the involvement of both mDCs and pDCs in the innate response to the mRNA vaccine in humans. The induced production of IFNα from the mRNA vaccine suggests that pDCs present in MIMIC® were activated. TLR3 and RLRs were activated in the mouse and the human MIMIC ® indicating the probability of double-stranded structure in the mRNA vaccine that effectively amplifies the adjuvant effect of the vaccine. These endosomal and cytoplasmic sensors of dsRNA do not typically respond to R848 and while gene families for both are up-regulated slightly by R848 the mRNA vaccine triggered much greater up-regulation of these sensors and activation of relevant downstream pathways. This overlap of results between the mouse and human models highlight the relevance of each for studying a subset of conserved gene families when evaluating the adjuvant effects of this vaccine. The models complement each other to highlight receptors that are conserved between species and known to generate innate responses following challenge with RNA. In some cases, however, transcriptional differences were observed between the mouse and human, likely due to different patterns of cellular sensors on innate immune cell populations. The gene for
il-
27 is up-regulated early in the injection site but is down-regulated late in the injection site and in the MIMIC® possibly due to differences in the pattern of response between the mouse and human, specifically in TLR7/8 activation. This is supported by the up-regulation of
il-
27 in the MIMIC® from R848 which activates TLR7 but down-regulation from the mRNA vaccine which appears to activate TLR8 in mDCs.
In addition to consistent transcriptional responses between the mice and the human subjects evaluated in this study, mRNA vaccination resulted in phenotypic and cytokine/chemokine responses that were similar between the two species and reflected the transcriptional profile. Elevated expression of genes for CD69 and CD40 was detected early upon mRNA vaccine injection in mice indicating specific activation of immune cells in the skin. Increased surface expression of CD86 was measured in human MIMIC®-PTE APCs and B-cells and also in migratory dendritic cells and B-cells in the draining lymph nodes of mice, all suggesting activation of antigen presenting cells. However in the PTE module at this time point
cd86 gene activity dropped in the mRNA vaccine treated cells versus no antigen control. This decline may have been due to an initial burst in
cd86 activity followed by a subsequent decline since the dose used in the transwell experiments (25 μg) was higher than that showing optimal immune cell activation on the APC population from the PTE (10 μg). Another possibility to explain the discrepancy between phenotype and gene expression of CD86 is that there exists an intracellular reservoir of CD86 in dendritic cells [
57]. These intracellular reservoirs can cycle CD86 to the cellular membrane rapidly in response to cell activation. mRNA vaccine mediated cell activation may trigger this cycling with no requirement for gene activation. Transcript analysis at a time point earlier than 24 h would help to elucidate the kinetics of the
cd86 gene. In contrast to
cd86, the transcriptional response profiles for CD14, CD40, and CCR7 following treatment with the mRNA vaccine matched the protein expression profiles detected by flow cytometry in the PTE derived cells. Administration of the mRNA vaccine also led to significant induction of chemokines and cytokines locally at the injection site in mice and in MIMIC®-PTE modules. In the mice, the CXCR3-ligands CXCL9, CXCL10 and CXCL11 whose pleiotropic functions include stimulation of monocytes/macrophages, T cells, NK cells, and dendritic cells migration showed the most pronounced up-regulation among the chemokines, up-regulation that was reflected in the transcriptional analysis of human MIMIC® modules. In the human MIMIC® sentinel markers for immune cell activation were all up-regulated, including IL-12(p40), IL-12(p70), IFN-α, and TNF-α.
When comparing responses to the mRNA vaccine between MIMIC®-PTE modules and mice after intradermal injection there is a fundamental difference between the two that must be addressed. After innate stimulation immune cells and specifically dendritic cells in vivo capture and process antigen, mature and are activated, and migrate to the lymph node to prime the adaptive immune system. Consequently the gene signature of activation will gradually be lost in the injection site and appear in the draining lymph node. In the MIMIC® immune cells, which consist primarily of antigen presenting cells, respond to stimuli like mRNA vaccines to activate and mature in place because migration is not possible in this system. When evaluating the MIMIC®-PTE modules responding APCs are examined 24 h after treatment. Consequently MIMIC®-PTE modules may demonstrate innate response characteristics found in both the skin and in the dLN of the mouse model. Overall, however, while there is some correlation between the MIMIC® dataset and the mouse datasets, specifically the injection site 6 h post-injection and the dLN 24 h post injection, differences are evident and may be driven by the species tested, the in vitro versus in vivo models, or unidentified reasons.
Conclusions
The translational approach used in this pre-clinical assessment into the basic mechanisms of self-adjuvantation from the mRNA vaccine allowed the identification of the mechanism of action by which the vaccine exerts its effect in humans and mice. In both species the vaccine acts through cellular RNA sensors, driving maturation and activation of immune cells as well as production of cytokines and chemokines known to attract and activate key players of the innate and adaptive immune system. In addition, because this approach could simultaneously be applied to both the in vitro human MIMIC® and in vivo mouse studies, correlative or divergent responses between the two species and two types of models were identified. Based on consistency between the two species in phenotypic, cytokine/chemokine, and transcriptional response to mRNA vaccine treatment, the mechanism of action of the adjuvant activity of this mRNA vaccine appears to be relatively conserved or at least convergent between the two species indicating that the innate immune stimulation from mRNA vaccines seen in mice translates to the human system. In addition, the results demonstrate that the MIMIC® system can be useful in preclinical evaluations of innate immune response to mRNA vaccines, with the potential identification of relevant pathways only evident in humans while demonstrating great similarity in the overall activation profile found in mouse studies.
Authors’ contributions
DE performed all MIMIC studies, generated and analyzed phenotypic and cytokine response data, and wrote all parts of the manuscript except methods and results sections relating to mouse assessments. EJ wrote methods and results sections relating to mouse studies. EJ, NH, MFM, and BP designed, ran, and analyzed studies in mice. DE, HY, and VW designed all MIMIC experiments. BS and TG ran and analyzed transcriptome studies. All authors read and approved the final manuscript.