Finding functional gaps: integrative analysis of VPAC1- and VPAC2-mediated signalling pathways in human lymphocytes

Finding functional gaps: integrative analysis of VPAC1- and VPAC2-mediated signalling pathways in human lymphocytes | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Finding functional gaps: integrative analysis of VPAC1- and VPAC2-mediated signalling pathways in human lymphocytes Alicia Cabrera-Martín, Paula Arribas-Castaño, David Castro-Vázquez, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9247309/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background Vasoactive Intestinal Peptide (VIP) is a pleiotropic neuropeptide regulating diverse cellular and physiological processes. Its functions are primarily mediated through two G protein–coupled receptors, VPAC1 and VPAC2. The aim of this study was to perform an integrative analysis of VPAC receptor signalling, encompassing receptor–G protein coupling, second messenger production, kinase activation and transcriptional responses in T cells. Experimental Approach : Receptor interactions with Gα subunits were analysed using BRET assays. Stable Jurkat T-cell lines overexpressing VPAC1 (J-OEV1) or VPAC2 (J-OEV2) were generated. VPAC-dependent intracellular signalling in these cells was assessed by measuring cAMP and Ca²⁺ levels, performing phospho-kinase arrays and Western blot analyses, and evaluating immune mediator expression, cell viability, and proliferation. Results VPAC1 showed interaction with both Gαs and Gαq subunits, whereas VPAC2 preferentially interacted with Gαs. In Jurkat cells, both receptors overexpression enhanced cAMP signalling, while increased Ca²⁺ responses were restricted to VPAC1. In both J-OEV1 and J-OEV2 cells, VIP treatment reduced phosphorylation of inflammatory kinase-associated proteins. Overexpression of either receptor induced distinct basal transcriptional profiles of transcription factors and cytokines, which were further modulated by CD3/CD28-activation and VIP. While proliferation was not altered with overexpression, J-OEV2 showed a reduced redox metabolism at 72h. Conclusion This study aimed to identify functional differences between VPAC1 and VPAC2 signalling and reveals reproducible subtype-specific differences at early signalling. In Jurkat cells, both receptors induce a shift in its basal state; however, changes do not persist during TCR-driven activation, resulting in largely convergent effector responses. Vasoactive Intestinal Peptide (VIP) VPAC receptors GPCR signalling pathways inflammatory mediators Jurkat T cell Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 INTRODUCTION Vasoactive Intestinal Peptide (VIP) is a 28-amino-acid neuropeptide ubiquitously distributed throughout the body. Initially described as an intestinal hormone, it is now recognized as a pleiotropic regulator involved in nervous system function, immune modulation, and bone and cartilage metabolism [ 1 – 3 ]. VIP exerts its biological activity primarily through two G protein-coupled receptors (GPCRs), VPAC1 and VPAC2, members of the secretin receptor family and share approximately 55% sequence homology [ 4 , 5 ]. Both receptors display comparable affinity for VIP (VPAC1 Kd ≈ 1 nM; VPAC2 Kd ≈ 5 nM) [ 5 , 6 ]. Like most class B1 GPCRs, VPAC receptors canonically signal through Gαs-dependent cAMP production with downstream activation of PKA and EPAC. In addition, VPAC1 consistently induces Ca²⁺ mobilization through Gαq and Gαi subunits and activates PKC in a cell context-dependent manner [ 1 , 7 , 8 ]. “G protein-independent” signalling has been described, including activation of PLD [ 9 ] and PI3K, which contribute to VIP-mediated regulation of prostate cancer progression via VPAC1 and breast tumour cell proliferation via VPAC2 [ 9 , 10 , 11 ]. At the downstream level, VIP signalling modulates kinase pathways such as MEK/ERK, p38, JNK, and survival-related kinases including mTOR [ 10 , 12 – 14 ]. Many VIP-regulated genes contain cAMP-responsive elements (CREs), such as CREB, which mediate VIP-dependent regulation of neuronal function, immune responses, and tumour biology [ 15 – 18 ]. VIP also influences the activity of additional transcription factors, including AP-1, IRF, NF-κB, and SP-1, particularly in immune cells [ 16 , 19 – 21 ]. Within the GPCR superfamily, shared ligands and overlapping signalling cascades often create context-dependent functional redundancy, strongly dependent on the physiological and cellular context, complicating the dissection of their distinct signalling mechanisms [ 22 ]. Although distinct signalling pathways for VPAC1 and VPAC2 have not been firmly defined, evidence suggests functional differences, with overlapping responses and receptor-specific modulation of signalling, that do not always translate into distinct physiological outcomes [ 23 , 24 ]. For instance, VPAC1 mediates hepatocyte proliferation [ 25 ], and its deficiency alters gut microbiota composition and metabolic homeostasis [ 26 ]. Alterations in VPAC2 expression have been associated with disrupted circadian rhythms, impaired neuronal maturation, and schizophrenia-related phenotypes linked to dopaminergic imbalance [ 17 – 29 ]. VPAC1 knockout mice exhibit resistance to experimental autoimmune encephalomyelitis, whereas VPAC2-deficient mice display an exacerbated pathological phenotype [ 30 , 31 ]. Regarding their immunomodulatory functions, in microglial cells, VPAC1 predominantly mediates inflammatory signalling, whereas VPAC2 contributes to survival and polarization responses [ 23 ]. In lymphocytes, VPAC1 is considered the main mediator of the anti-inflammatory actions of VIP, regulating cytokine production and T-cell activation [ 30 , 31 ]. However, depending on the degree of T-cell activation and differentiation, VPAC2 expression can be increased and contributes to anti-inflammatory responses [ 19 , 32 ], suggesting a dynamic and context-dependent balance between both receptors in immune regulation. Consistent with the redundancy observed in GPCR-mediated mechanisms, the immune system exemplifies biological redundancy. Cytokines and chemokines, often derived from gene duplication events [ 33 , 34 ], converge on shared signalling pathways modulated by cellular context. This functional overlap explains why blocking a single axis rarely abolishes inflammation [ 35 , 36 ]. This raises a central question: Do VPAC1 and VPAC2 mediate distinct context-dependent signalling and functional responses, or do they function as intrinsically redundant components of the same signalling network? In T CD4 + cells context, signalling mediated by VIP is strictly subordinate to TCR-driven signalling. It regulates CD4⁺ T-cell differentiation, shifting responses from Th1/Th17 toward Th2 and Treg phenotypes cells [ 17 , 37 ]. This regulation may be mediated by the expression pattern of its receptors, which display differential expression depending on the activation state of T lymphocytes [ 37 – 39 ]. Such differential receptor distribution suggests that VIP fine-tunes T-cell function through distinct, context-dependent signalling mechanisms. Jurkat cells, as a model of T cells, respond to a well-defined activating stimulus, the TCR engagement, that triggers a reproducible and extensively characterized signalling program. This makes them a suitable system to assess whether VPAC1 and VPAC2 generate distinct signalling effects and whether these differences persist within the established T-cell activation framework. We hypothesized that VPAC1 and VPAC2 differentially engage intracellular signalling pathways in T cells, leading to receptor-specific modulation of cellular responses and thereby contributing to the fine-tuning of immune signalling beyond simple functional redundancy. METHODS Cell culture Jurkat cells were maintained in RPMI medium (Cytiva), supplemented with 10% Fetal Bovine Serum (FBS), 1% peniciline/Streptomicine and 1% Stable L-Glutamine (PAN-Biotech) in T75 flask at a concentration of 0.3 × 10⁶ cells/mL. HEK293 cells were cultured in DMEM medium (Corning) supplemented with 10% FBS (Cytiva), 1% Peniciline/Streptomicine and 1% Stable L-Glutamine in 100mm dishes. The specific culture conditions for each assay are described in the corresponding section. In all cases, treatments were performed under low-serum conditions (0.5% FBS). Plasmids construction For every plasmid construction, GeneArt™ Gibson Assembly HiFi technology (ThermoScientific) was performed. For BRET assays, VIPR1 (VPAC1) and VIPR2 (VPAC2) human transcripts sequences were cloned into a Renilla Luciferase carrying vector (pRLuc-N1) [ 40 ] (supplementary Fig. 1A). Briefly, VIPR transcripts were amplified from human T cell cDNA samples by PCR. Subsequently, pRLucN1 vector was linearized with homologous ends to finally obtain two plasmids: pVIPR1_RLuc and pVIPR2_RLuc. For VPAC receptors overexpression, VIPR1 and VIPR2 human sequence were cloned into pRLuc-N1. RLUC transcript sequence was substituted by both VIPR sequences, to finally obtain pVIPR1 and pVIPR2 plasmids. Vectors were sequenced through the Sanger sequence method. Bioluminescence resonance energy transfer assay (BRET) The interaction between VIP receptors and different Gα proteins subunits was studied using the BRET technique (Bioluminescence Resonance Energy Transfer). To do so, specific miniG proteins, Gα subunits modified to improve the interaction with GPCRs, were used [ 41 ]. Four different proteins representing each main Gα subunit family were chosen Gs, Gq, Gi and G12, each fused to the Venus fluorescent protein (kindly provided by N. A. Lambert, Augusta University, Augusta, GA). HEK293 were co-transfected using Lipofectamine 2000 (Thermofisher) as a transfection reagent and OptiMEM (Thermofisher) as carrier medium, with either pVIPR1_RLuc or pVIPR2_RLuc along with the different miniG proteins carrying vectors. 8x10 4 cells/well were plated in 96 well white/clear flat bottom plate (Nunc, Thermofisher) with low glucose DMEM medium (Sigma-Aldrich, Merck) supplemented with 10% FBS. After 48 hours, cells were incubated with increasing concentrations of VIP (Bachem) diluted in Phosphate Buffered Saline (PBS), along with Renilla Luciferase substrate, Coelenterazine H 5µM (Thermofisher). After incubation at 37°C, luminescence (Rluc, 485 ± 10nm) and fluorescence (Venus, 530 ± 12) were detected in a Mithras LB 940 plate reader (Berthold Technologies). Results were analysed through a non-linear regression model 4PL, where the logarithm of the VIP concentration was plotted against the BRET ratio values (luminescence/fluorescence), corrected by the PBS condition. Electroporation of Jurkat Cells Jurkat cells were transformed by electroporation using 12µg of pVIPR1 or pVIPR2 plasmids to overexpress VPAC1 or VPAC2. Additionally, Jurkat cells were electroporated with 12µg of pR_LucN1 plasmid as a control. Briefly, 5x10 6 cells diluted in 100µl PBS/Hepes 1M were electroporated in a 4mm electroporation cuvette (Cell Project) using a Gene pulser Xcell Electroporation System (Bio-Rad) with the following conditions: 350 V, 50µF and 200Ω, immediately followed by a 1-minute ice incubation. Transformed cells were selected through antibiotic resistance, being treated with 700µg/ml of G418 (Gibco). Luminescence assays Jurkat cells transformed with pR_LucN1 were seeded at 12x10 5 cells/well on 96 well white/clear bottom plates (Nunc, Thermofisher) in PBS. Cells were exposed to Coelenterazine H 5µM and luminescence was measured using a Fluostar Omega plate reader (BMG LabTech) (Supplementary Fig. 1B). Gene expression by Real time PCR Total RNA was obtained using TriReagent (Invitrogen), and 2 µg were subsequently reverse transcribed using the High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems). VIP receptor gene expression was detected through semiquantitative RT-PCR, performed using TaqMan Gene Expression Master Mix (Thermofisher) and specific TaqMan probes for VIPR1 (Hs00270351_m1) and VIPR2 (Hs00173643_m1) genes. In order to study specific cytokines and transcription factors produced by Jurkat cells and Jurkat cells overexpressing each VPAC receptor, cells were cultured for 24 hours under the following conditions: untreated, treated with 25µl/ml ImmunoCult™ Human CD3/CD28 T Cell Activator (StemCell), VIP 10 − 8 M, or a combination, along with Jurkat expressing pR_LucN1 plasmid, used as a control. Semiquantitative RT-PCR was performed using GoTaq qPCR Master Mix (Promega), with specific sets of primers for each gene (Supplementary Fig. 2). Succinate dehydrogenase complex flavoprotein subunit A ( SDHA ) was used as a housekeeping gene, and each sample was normalized using the 2 −ΔCt formula. cAMP measurement cAMP production was measured using the HitHunter cAMP Assay for Small Molecules Kit (DiscoverX), measuring luminescence levels with a Fluostar Omega plate reader (BMG LabTech). Briefly, Jurkat cells and Jurkat cells overexpressing VPAC1 or VPAC2 were seeded at 1x10 6 cells/ml in OptiMEM / 2% FBS and treated with PBS or increasing concentrations of VIP, VPAC1 agonist [Lys 15 Arg 16 Leu 27 VIP (1–7) -GRF (8‐27)] or VPAC2 agonist (RO 25‐1553; Bachem) diluted in PBS for 30 minutes. Then, cells were lysated and produced cAMP was measured according to the manufacturer’s instructions. Finally, cAMP concentrations (nM) were calculated by interpolation from a standard curve. Determination of Ca influx To analyse the Calcium production, Fluo-4 AM (Invitrogen) was used. 12x10 5 cells of each condition were incubated on 96 well black/clear bottom plates (Ibidi) in HBSS w/o Ca 2+ / Mg 2+ (Gibco), supplemented with 5µM of Fluo-4 AM at 37°C. Afterward, cells were wash with fresh medium to remove excess staining and incubated for another 30 minutes. Finally, emission was measured at 520nm for 8 minutes, using a Fluostar Omega plate reader (BMG LabTech), in the presence of PBS or 100nM of VIP, VPAC1 agonist or VPAC2 agonist diluted in PBS. Values are expressed as ΔF/F₀, calculated as the fluorescence at each time point (F) divided by the basal fluorescence (F₀) and normalized to the PBS control. Phospo-Kinase array Jurkat cells and Jurkat cells overexpressing VPAC1 or VPAC2 receptors were cultured overnight with OptiMEM/2%FBS at 1x10 6 cells/mL. The following day, cells were incubated with PBS, with 25µl/ml ImmunoCult™ Human CD3/CD28 T Cell Activator (StemCell) or VIP 10 − 8 M for 15 minutes. Afterwards, 200µg protein lysates were used to perform the Proteome Profiler™ Human Phospho-Kinase Array Kit (R&D Systems), following the manufacturer’s instructions. The results were densitometred using ImageJ software (V1.54k) and corrected using PBS spot values. Untreated results are represented as the mean pixel intensity of both spots that belong to each phosphorylated protein. The effect of activation or VIP treatment is represented as a volcano plot where the log2 of the fold change is plotted against the -log10 of the q-value obtained using a one-way ANOVA test. Protein analysis by Western Blot Jurkat cells and Jurkat cells overexpressing each VPAC receptor were cultured overnight with OptiMEM/2%FBS at 1x10 6 cell/ml, follow by a 5- or 15-minutes treatment under the following conditions: untreated, treated with 25µl/ml ImmunoCult™ Human CD3/CD28 T Cell Activator (StemCell), VIP 10 − 8 M, or a combination. The optimal treatment duration was determined in advance for each protein (Supplementary Fig. 3). Protein extracts were obtained using ice-cold radio-immunoprecipitation assay buffer (Thermofisher) and quantified using a QuantiPro BCA Assay kit (Sigma Aldrich). Protein extracts were subjected to SDS-PAGE, using different protein quantities and acrylamide gel percentages depending on the protein of study (Supplementary Fig. 4), and then transferred to a nitrocellulose membrane (0.45 µm). Each membrane was blocked 1 hour with 5% Bovine Serum Albumin and incubated overnight at 4°C with primary antibodies (Supplementary Fig. 4). Anti-rabbit (1:5000) or anti-mouse (1:10000) HRP-conjugated secondary antibodies (Invitrogen) were used, and proteins were detected using SuperSignal West Pico PLUS Chemiluminiscent Substrate (Thermofisher). Results were analysed using Bio-Rad Quantity One Program. The measurement of phosphorylated protein was then normalised against the quantity of unphosphorylated protein or GAPDH expression. Cell viability and proliferation Viability was determined through mitochondrial metabolism by the Cell Proliferation Reagent WST-1(Roche). Jurkat cells and Jurkat cells overexpressing each VPAC receptor were cultured in a 96 well round bottom plate at a density of 10.000 cells per well in RPMI plus 2% FBS and treated as described in previous section for 72 hours. At 0, 24, 48 and 72 hours, WST-1 was added at a 1/10 ratio (v/v) and incubated in at 37°C incubator for 30 minutes. Supernatant was then moved to a 96 well flat bottom plate and read at 450nm. Cell proliferation was studied using Tag-it Violet (BioLegend). 3x10 6 cells of Jurkat cells and Jurkat cells overexpressing each VPAC receptor, previously washed with PBS (Phosphate Buffer Saline), were incubated with 2µM Tag-it Violet diluted in PBS during 20 minutes at 37°C in the dark. Afterwards, excess staining was quenched with RPMI /10%FBS, centrifuged and incubated during 10 minutes in RPMI/10%FBS. Each condition was then treated for 72 hours in RPMI/2%FBS under the same conditions described in previous sections. At 0, 24, 48 and 72 hours cells were stained with 7-AAD (Invitrogen) and acquired on a FACSymphony A1 flow cytometer (BD Life Sciences), results were analysed using FlowJo™ Software (version 10, BD Life Sciences). Statistical analysis All data were analysed using GraphPad Prism 8.0. For BRET concentration–response curves, data were fitted using a 4-parameter logistic (4PL) non-linear regression model. For experiments with two groups, an unpaired Student’s t-test was used. For experiments with three or more groups, one-way ANOVA or a Kruskal-Wallis test followed by Dunn’s post-hoc test was applied, unless otherwise specified. Data are presented as mean ± SEM, and the number of independent biological replicates (n) is indicated in the figure legends. Differences were considered statistically significant at p < 0.05. For volcano plots, significance thresholds are described in the corresponding figure legends. RESULTS Interaction of VPAC receptors with different G proteins. To study the interaction of each receptor with different G proteins, HEK293 cells were co-transfected with VPAC1-RLuc or VPAC2-RLuc constructs together with Venus-tagged miniG proteins, and BRET responses were measured following VIP stimulation. HEK293 cells were preferred over Jurkat cells, since these cells provide a controlled, efficient and reproducible system to characterize VPAC receptor-G protein interactions, with inflammatory relevance later confirmed in Jurkat T cells. Stimulation of transfected cells with VIP led to a time-dependent increase in the BRET ratio for the VPAC1 receptor with Gs, Gq, and to a lesser extent, Gi and G12 (Fig. 1 A). Dose-response analysis showed that VPAC1 exhibited the highest potency for Gs coupling (EC₅₀ = 1.87 nM), followed by Gq (EC₅₀ = 8.97 nM), whereas Gi showed lower efficacy and G12 induced minimal responses (Fig. 1 B). In contrast, for the VPAC2 receptor, VIP promoted a time-dependent increase in BRET ratio only with Gs, while the response with Gq was linear and without defined activation kinetics, and no interaction was detected with Gi or G12 (Fig. 1 C). Moreover, the potency of Gs interaction with VPAC2 was lower than with VPAC1 (EC50 9.9 nM), being the potency of Gq even lower (EC50 27.5 nM) (Fig. 1 D). Functional characterization of VPAC signalling in Jurkat cells overexpressing VPAC receptors. After identifying differences in G protein activation, we further examined VPAC receptor signalling in depth. Given the importance of VIP in the immune system and the previously described differences in VPAC receptor expression among Th cells [ 2 , 16 , 36 , 42 ], we investigated signalling in Jurkat cells, which express non-functional VPAC receptors (Fig. 2 A). We generated Jurkat cell lines overexpressing either the VPAC1 or VPAC2 receptor by transfection with plasmids encoding the respective receptors (supplementary Fig. 1A). As shown in Fig. 2 A, VPAC1 overexpressing cells (J-OEV1) exhibited a six-fold increase in VPAC1 expression, while VPAC2-overexpressing cells (J-OEV2) showed a seven-fold increase in VPAC2 expression compared with parental Jurkat cells. To assess receptor functionality, we measured cAMP production, modulated by Gs proteins, and cytosolic Ca 2+ influx, mediated by Gq proteins. VIP stimulation significantly increased intracellular cAMP levels in J-OEV1 and J-OEV2, whereas no effect was observed in untransfected Jurkat cells (Fig. 2 B). Selective VPAC1 and VPAC2 agonists increased cAMP production only in cells overexpressing the corresponding receptor. Using the calcium sensor Fluo-4 AM, we detected an increase in cytosolic Ca 2+ in J-OEV1 cells upon stimulation with VIP or the VPAC1 agonist (Fig. 2 C). In Jurkat and J-OEV2 cells, the calcium response to VIP was small and transient, and no effect was observed upon stimulation with the VPAC2 agonist. Effect of Jurkat-VPAC overexpression and activation on protein phosphorylation dynamics To investigate signalling pathways regulated by VPAC receptors, phosphorylation profiles were analysed using a phospho-kinase array. We observed higher phosphorylation levels of some kinases in untransfected Jurkat cells. Compared with control Jurkat cells, overexpression of either receptor increased phosphorylation of CREB, ERK1/2, JNK, Lck, Lyn, Src, Akt, PRAS40, STAT3 and Hsp60, with differences in the intensity (Fig. 3 ). For example, CREB and ERK phosphorylation were higher in J-OEV1 whereas in J-OEV2, the greater phosphorylation was found in Lck, Lyn, Src, Akt, PRAS40 and Hsp60. VIP stimulation did not alter kinase phosphorylation in control Jurkat cells (Fig. 4 ). In contrast, VIP reduced phosphorylation of several kinases in receptor-overexpressing cells. In J-OEV1 cells, VIP induced a decrease in the phosphorylation of 8 out of the 43 kinases assessed, with p53, PRAS40 and eNOS showing the strongest reduction. The effect was more pronounced in J-OEV2 cells, where 12 kinases displayed decreased phosphorylation in response to VIP, among these, STAT2, PDGF, FGR, Lck, eNOS and Hsp27 exhibited the greatest reductions in phosphorylation levels. Additionally, Jurkat control cells were briefly stimulated with anti-CD3/anti-CD28 antibodies to assess rapidly activated pathways. As shown in Fig. 5, stimulation increased phosphorylation of several proteins, with ERK, CREB, RSK and Hsp27 showing the strongest responses, alongside lower-level phosphorylation of 11 additional proteins. Based on above previous results and on the analysis of key signalling pathways involved in inflammation, survival and proliferation in T lymphocytes, we selected several kinases for further examination by Western blotting. We focused on those affected by VIP treatment or by anti-CD3/anti-CD28 antibodies activation, and considering the differential responses associated with the overexpression of VPAC1 and VPAC2 receptors. Since phosphorylation of some kinases is highly time-dependent, we performed a preliminary time-course analysis to select the optimal time point for each protein (Supplementary Fig. 4). Within the signalling pathway of Gs-coupled GPCRs, CREB acts as a key transcription factor in the cAMP-mediated response and is a phosphorylation-dependent transcription factor that plays a crucial role in T cell activation, proliferation, survival and differentiation. Its phosphorylation can also be promoted by kinases such as RSK2, which is linked to the MAPK/ERK signalling pathway [ 43 ]. Jurkat untransfected and VPAC overexpressed activation resulted in enhanced CREB phosphorylation, which was further increased following VIP treatment in both untransfected and J-OEV1 cells (Fig. 6 ). In J-OEV2 VIP treatment maintained the phosphorylation levels of CREB observed after activation. The MAPK pathway, which can be activated through the TCR, cytokines, and other stimuli, integrates external signals to coordinate activation, proliferation, and survival. In this pathway, two key downstream components are ERK and p38α [ 44 ]. As expected, activation of Jurkat cells, both untransfected and transfected, stimulated ERK1/2 phosphorylation, however VIP treatment maintained ERK phosphorylation level following activation in every Jurkat condition tested. p38α activity is essential for normal immune and inflammatory responses and is activated in T cells by several inflammatory mediators. Consistently, TCR activation increased p38α phosphorylation in both untransfected and transfected Jurkat cells, and this effect was downregulated by VIP, particularly in J-OEV1 cells. PLCγ1 is recruited and activated as a key step in TCR-mediated T cells activation [ 45 ]; however, in our experimental conditions, we observed little (Jurkat, J-OEV1) to no (J-OEV2) phosphorylation of this protein. The presence of VIP appears to decline the phosphorylation of this protein in J-OEV1. PRAS40 is a component of the mTOR complex 1 (mTORC1), and its phosphorylation, mainly mediated by Akt, activates mTORC1, that acts as a key regulator of lymphocyte survival [ 46 ]. Anti-CD3/anti-CD28 activation induced strong phosphorylation of PRAS40 in untransfected and VPAC overexpressed cells, which was decreased by VIP, especially in J-OEV1 cells. Lck belongs to the Src family of kinases, and its activity constitutes the initial step in TCR signalling [ 47 ]; therefore, it is not surprising that its phosphorylation increases upon anti-CD3/anti-CD28 activation, a phenomenon observed in control Jurkat cells as well as in J-OEV1 and J-OEV2. VIP preserved the activation-induced Lck phosphorylation level in all cases. VPAC modulation of cytokines and transcription factors relevant for T cells To evaluate the functional consequences of VPAC receptor expression, transcription factors and cytokines associated with T cell responses were analysed. We observed a similar expression pattern for TBX21 ( T-bet), RORC (RORγt) and GATA3 in Jurkat, J-OEV1 and J-OEV2 cells, being GATA3 the most highly expressed followed by RORC and TBX21 (Supplementary Fig. 5A). Regarding cytokine expression, IL10 (IL-10) was the most abundantly expressed cytokine in all cell lines tested. Nevertheless, the relative expression pattern of other cytokines changed upon VPAC receptor overexpression. Both, J-OEV1 and J-OEV2 cells, expressed more TNF (TNFα) than IL2 (IL-2), and in J-OEV2 the expression of IFNG (IFNγ) and IL4 (IL-4) was reversed compared with that in untransfected cells (Supplementary Fig. 5B). When we compared cells overexpressing the receptors with untransfected cells to assess whether receptor overexpression alters the expression levels of transcription factors and cytokines (Fig. 7 ), we observed that J-OEV1 and J-OEV2 exhibited lower expressions of IL2, IL10 and IFNG compared with Jurkat cells. Additionally, J-OEV2 expressed less TBX21 , IL4 and more TNF than Jurkat cells. The differences observed in transfected cells were attributable to receptor overexpression as empty plasmid transfection caused no changes in the transcription factors or cytokines analyzed (Supplementary Fig. 6). Upon activation with anti-CD3/anti-CD28 antibodies, we observed changes in both transcription factor and cytokine expression (Fig. 8 ). RORC expression decreased, with significant reduction in J-OEV1 and J-OEV2 cells, whereas TBX21 and GATA3 expression were upregulated following activation, reaching significance in J-OEV2 cells for TBX21 and in J-OEV1 cells for GATA3 . Regarding cytokines, all of them, except IL10 , showed a trend towards upregulation. IL2 expression increased significantly in J-OEV1 cells, IL4 in J-OEV2 cells, and TNF showed a significant increase in all three Jurkat-derived cell lines. Overall, the observed changes indicate that activation promotes a mainly Th1/Th2-oriented differentiation profile. When cells activated with anti-CD3/anti-CD28 antibodies were exposed to VIP, we detected alterations in both cytokine and transcription factor expression. Notably, VIP induced a significant increase in IL2 expression in J-OEV1 cells, while both J-OEV1 and J-OEV2 cells displayed a tendency to a higher IL10 levels in response to VIP, not observed in activated Jurkat cells, which may suggest that the presence of VIP could favours an anti-inflammatory profile in these cells through both VPAC receptors. Effect of VPAC receptors on Human T Cell Proliferation and Survival Since all the signalling pathways analysed were related to proliferation and survival, we next examined the proliferation of untransfected and transfected Jurkat cells. First, cell viability was assessed using a WST-1 assay which measures metabolic activity that correlates with the number of viable cells in culture (Fig. 9 A). Jurkat, J-OEV1 and J-OEV2 cells exhibited similar viability under untreated conditions, after activation with anti-CD3/anti-CD28 antibodies, and following VIP treatment at 24h and 48h. After 72h, VPAC2 overexpression reduced cell viability independently of VIP treatment. Second, cell proliferation was measured using Tag-it Violet labeling. Proliferation of Jurkat cells and cells overexpressing each receptor was comparable across all conditions. Subsequently, proliferation assays were performed under basal conditions, following activation with anti-CD3/anti-CD28 antibodies, and in the presence or absence of VIP (Fig. 9 B). In all cases, the same proliferation pattern was observed across the different experimental conditions, with a tendency toward increased proliferation upon overexpression of either receptor, independent of activation of VIP treatment. DISCUSSION Contemporary models of GPCR signalling emphasize that receptor function reflects the integration of ligand-dependent activation with receptor-specific basal activity and cellular context. Here, we provide a comparative pharmacological analysis of VPAC1 and VPAC2 in a T-cell model, integrating proximal receptor–G protein coupling with second messenger generation, kinase activation and transcriptional outputs. Our findings indicate that although both receptors are activated by VIP, they impose distinct proximal signalling signatures that are progressively buffered at downstream functional levels. VPAC receptors have traditionally been classified as prototypical Gαs-coupled GPCRs based on their robust stimulation of cAMP production [ 1 , 7 ]. However, accumulating evidence suggests that class B1 GPCRs can engage multiple G-protein families in a context-dependent manner. Using miniG-BRET biosensors to directly assess receptor–G protein engagement, we demonstrate that VPAC1 exhibits broader coupling flexibility than VPAC2, recruiting Gαs and Gαq robustly and displaying a transient interaction with Gαi. These findings refine previous conclusions based on downstream assays and are consistent with models suggesting that ligand binding stabilizes receptor conformations that determine selective G-protein coupling [ 48 , 49 ]. The functional translation of these coupling differences was evident at the level of second messengers. Ca²⁺ mobilisation was selectively enhanced in VPAC1-overexpressing cells, consistent with its preferential Gαq. This recruitment has been previously described in several cellular systems and is commonly linked to PLC activation downstream of Gαq [ 8 ]. Notably, despite this divergence in Ca²⁺ signalling, no amplification of downstream transcriptional or proliferative responses was observed. As emphasized in the GPCR literature, biased signalling reflects both receptor properties and the cellular system in which signalling occurs [ 50 ]. Early differences may be buffered by downstream network integration, and signal persistence depends on the duration of receptor–transducer interactions [ 51 ]. For instance, VPAC1 has been shown to internalize independently of β-arrestins while maintaining endosomal Gs-dependent cAMP signalling, suggesting that β-arrestins contribute to the temporal organization of cAMP responses rather than being strictly required for signal generation. Such mechanisms illustrate how receptor-specific regulatory features can contribute to signalling bias without necessarily producing distinct functional outcomes [ 52 ]. In T cells, where TCR signalling dominates the integration of activation signals, subtype-specific VPAC coupling differences may therefore remain confined to early signalling layers and fail to generate distinct functional outcomes. Beyond ligand-induced signalling, an additional layer emerged at the basal level. A central observation of this study is that receptor expression alone remodels basal signalling states. Numerous GPCRs exhibit basal or constitutive signalling activity that is independent of ligand engagement, commonly referred to as ligand-free signalling [ 53 ]. In addition, GPCRs can interact with downstream transducers, including heterotrimeric G proteins, in pre-assembled or pre-coupled states prior to ligand binding, described for several GPCRs as PAR1, β2AR, Muscarinic M3R and CB1R [ 54 – 56 ]. In this context, changes in receptor abundance, such as those resulting from receptor overexpression, may promote basal signalling gain through these mechanisms. A case in point is that elevated expression of GPR35 is sufficient to induce functionally relevant ligand-free signalling [ 57 ]. In our model, overexpression of either VPAC subtype increased phosphorylation of Src family kinases and MAPK components, together with kinases associated with metabolic regulation such as AKT and PRAS40. These findings are consistent with tonic signalling phenomena described in T cells, where basal phosphorylation contributes to a poised state even in the absence of antigenic stimulation [ 58 ]. At the transcriptional level, however, a distinct pattern emerged. Interestingly, this enhanced basal kinase activity coexisted with reduced basal expression of canonical effector genes, including IL2, IL4 and IFNG. Rather than reflecting a simple linear relationship between kinase activation and transcription, this dissociation likely illustrates the complexity of signal integration in T cells. Jurkat cells establish both autocrine and paracrine feedback loops, including cytokines and immunomodulatory metabolites, which can influence transcriptional outputs [ 59 ]. In addition, basal signalling history is known to recalibrate responsiveness, as illustrated during thymocyte selection, primary T cell activation or T cell differentiation [ 60 ]. In Naïve T cells, strong tonic TCR signals maintain quiescence and restrain effector activation, while constitutive mTORC1 activity shapes baseline translation without driving differentiation [ 61 , 62 ]. By analogy, increased proximal kinase activity in our model may similarly adjust the signalling set point, allowing enhanced basal phosphorylation to coexist with reduced basal effector gene expression until a strong activating stimulus is encountered. To determine whether these basal differences persisted under activating conditions, we examined the response to CD3/CD28 co-stimulation, which elicits a robust activation programme in Jurkat cells. This response is accompanied by a broad phosphorylation profile consistent with classical TCR-associated pathways and culminates in the coordinated induction of effector-related genes across all conditions, underscoring the integrity of the core TCR signalling [ 63 ]. Within this framework, VIP did not substantially modify activation-induced transcriptional programme. However, the tendency toward increased IL2 expression (together with a similar, non-significant trend for IL10) suggests that VIP signalling may selectively influence specific components of the activation response. The concurrent modulation of these mediators is consistent with the established immunomodulatory and anti-inflammatory role of VIP, whose impact depends on cellular context, activation state, and signalling thresholds [ 8 , 17 ]. Thus, the VIP/VPAC axis mainly adjusts basal signalling tone, while activation-dependent transcription remains constrained by dominant TCR-driven integration. Given the observed changes in kinase pathways linked to metabolic regulation, we next assessed cellular metabolic activity. Our results indicate a receptor subtype-specific modulation of redox metabolism, with J-OEV2 cells exhibiting a reduced basal redox output after three days in culture, both under resting conditions and upon stimulation. This profile is observed in parallel with increased phosphorylation of kinases involved in metabolic regulation and stress adaptation, including AKT and PRAS40 [ 64 ]. Notably, this phenotype emerges only after prolonged culture, consistent with progressive changes in static culture microenvironments, such as nutrient depletion and altered oxygen availability, which influence cellular redox balance over time [ 65 ]. In parallel, Tag-it proliferation tracking revealed only a slightly, non-significant increase in cell division in both J-OEV1 and J-OEV2 populations, indicating that the observed metabolic changes reflect an adjustment of basal metabolic tone rather than altered proliferative capacity. While these findings provide mechanistic insight, several limitations should be acknowledged. Receptor overexpression was used to resolve subtype-specific signalling, which may enhance basal signalling beyond physiological receptor expression levels. Jurkat cells, although a widely used T-cell model, are transformed and genomically heterogeneous, limiting direct extrapolation to primary CD4⁺ T cells. In addition, receptor–G protein coupling was assessed using miniG BRET biosensors in HEK293 cells, a heterologous system that allows robust analysis of proximal interactions but does not fully capture the T-cell signalling environment. Consequently, while the coupling profiles likely reflect intrinsic receptor properties, their quantitative impact on downstream signalling may depend on cell-type specific factors. CONCLUSIONS This study presents a comparative pharmacological analysis of VPAC1 and VPAC2 signalling in a T-cell model. We identify reproducible subtype-specific differences in proximal G-protein coupling and basal signalling that are largely buffered at the transcriptional level under dominant TCR stimulation. These findings indicate that VPAC receptors primarily modulate basal immune tone rather than directly governing T-cell activation, which may be relevant for strategies that aim to fine-tune immune responses without broadly suppressing T-cell function. Declarations Ethics approval and consent to participate: Not applicable Consent for publication: Not applicable Availability of data and materials: The data that support the findings of this study are available from the corresponding author upon reasonable request. Competing interests: The authors have no relevant financial or non-financial interests to disclose Funding : This work was supported by grants RD21/0002/004 and RD24/0007/0014 from the Ministerio de Economía y Competitividad (Instituto de Salud Carlos III) and co‐funded by European regional development fund (ERDF), as well as by UCM grants PR12/24-31572 and PR12/24-31568, and Comunidad de Madrid grant PR17/24-31935. This work was also supported by CNRS (Centre National de la Recherche Scientifique) and FEDER (Fonds Européen de Développement Régional) through the GioMab project, and by the EMBO Fellowship Programme (STF 8993). Authors' contributions: RVR, IGC and YJ conceptualized the study. IGC, RVR, ACM and SML developed the methodology. ACM, RVR, IGC, PAC, KT, SPG and CE performed the investigation. ACM, DCV and RVR conducted formal analysis. YJ, IGC, RVR, SML and CM supervised the project. RVR, IGC, YJ and ACM wrote the original draft of the manuscript. PAC, DCV, KT, SPG, CM, CE and SML contributed to writing, review and editing. YJ, CM, SPG and RVR acquired funding. All authors reviewed and approved the final version of the manuscript. Acknowledgements: We acknowledge the support of the CAI of Biological Techniques of the Complutense University of Madrid (UCM), particularly the Genomics Unit. Authors' information (optional) ORCID CODES: Alicia Cabrera-Martín: 0000-0001-5697-6967 Paula Arribas-Castaño: 0009-0006-6390-6952 David Castro-Vázquez: 0000-0003-2446-5075 Karolina Tecza: 0009-0003-1660-1222 Selene Pérez-García: 0000-0002-4500-8132 Carmen Martínez: 0000-0003-3541-0571 Chayma El Kamlichi : 0000-0003-4796-8169 Séverine Morisset-López : 0000-0002-9930-7824 Yasmina Juarranz: 0000-0001-5886-8273 Irene Gutiérrez-Cañas: 0000-0003-0678-3619 Raúl Villanueva-Romero: 0000-0002-9001-2413 References Harmar AJ, Fahrenkrug J, Gozes I, Laburthe M, May V, Pisegna JR, Vaudry D, Vaudry H, Waschek JA, Said SI. 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02dpqcy73)","correspondingAuthor":false,"prefix":"","firstName":"Severine","middleName":"","lastName":"Morisset-López","suffix":""},{"id":635393280,"identity":"4c66ff5b-e4a5-4999-80a8-759f8043da5f","order_by":8,"name":"Yasmina Juarranz","email":"","orcid":"","institution":"Complutense University of Madrid (ROR 02p0gd045)","correspondingAuthor":false,"prefix":"","firstName":"Yasmina","middleName":"","lastName":"Juarranz","suffix":""},{"id":635393281,"identity":"a10c55ae-5cd0-44ff-9b19-d694ace33bb6","order_by":9,"name":"Irene Gutiérrez-Cañas","email":"","orcid":"","institution":"Complutense University of Madrid (ROR 02p0gd045)","correspondingAuthor":false,"prefix":"","firstName":"Irene","middleName":"","lastName":"Gutiérrez-Cañas","suffix":""},{"id":635393282,"identity":"7f6d89d7-383c-4967-99af-8ad37c39ec63","order_by":10,"name":"Raúl Villanueva-Romero","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAr0lEQVRIiWNgGAWjYJCCAw8KGBj4SdOSYMDAINlAkh6QFoMDxKo2bz9jCLTFLs/4RvLTDQwVdYS1yJzJMQBqSS42u5FmdoPhzGHCWiQY0hKAWpgTt93IYbvB2EaE8yT4n4G01CdungHS8o8Ih0lIJB8AajmcuEECpKWBmRgtj0FajifOOPPM7EbCMWL8wp/Y/OFDRXVif3vysxsfaohwGCpIIFXDKBgFo2AUjALsAADufDz9nZe8dwAAAABJRU5ErkJggg==","orcid":"","institution":"Complutense University of Madrid (ROR 02p0gd045)","correspondingAuthor":true,"prefix":"","firstName":"Raúl","middleName":"","lastName":"Villanueva-Romero","suffix":""}],"badges":[],"createdAt":"2026-03-27 17:38:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9247309/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9247309/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108807597,"identity":"b28818a6-7af6-4f25-b539-77f28eab2d7c","added_by":"auto","created_at":"2026-05-08 15:30:55","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":534224,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAnalysis of VPAC receptor coupling to mini Gs, Gi, Gq, and G12 through BRET technique. \u003c/strong\u003e\u003cem\u003eUpper panels\u003c/em\u003e: BRET signal kinetics following co-transfection of VPAC1–RLuc (A) and VPAC2-Rluc (C) with each Gα–Venus subunit in the presence of 30 nM ligand. \u003cem\u003eLower panels\u003c/em\u003e: concentration–response curves derived from BRET values measured after 30 min incubation in the presence of VIP for VPAC1 (B) and VPAC2 (D) receptor. Data were analysed through a non-linear regression model 4PL and normalised to basal BRET values recorded in the presence of PBS. Data represent the medium (A and C) and the medium ± SEM (B and D) from six independent experiments performed by triplicate.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9247309/v1/fc530900142e6d1e5dbc9964.png"},{"id":108807635,"identity":"5240f1c7-05f7-4c2f-859d-b377837792f9","added_by":"auto","created_at":"2026-05-08 15:30:59","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":471516,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCharacterisation of VPAC expression levels and functional signalling (cAMP and Ca\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e+2\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e responses) in Jurkat-overexpressing cells\u003c/strong\u003e. \u003cstrong\u003e(A) \u003c/strong\u003emRNA expression of the VPAC1 (\u003cem\u003eVIPR1\u003c/em\u003e) and VPAC2 (\u003cem\u003eVIPR2\u003c/em\u003e) was determined by real-time PCR analysis in Jurkat cells (Jurkat), VPAC1 overexpressed Jurkat cells (J-OEV1) and VPAC2 overexpressed Jurkat cells (J-OEV2). Data were normalized with SDHA mRNA expression and are shown as the percentage of Jurkat cells values (2\u003csup\u003e-ΔΔCt\u003c/sup\u003e). Data represent three experiments performed by triplicate. \u003cstrong\u003e(B)\u003c/strong\u003e Intracellular levels of cAMP under increased concentrations of VIP, VPAC1 agonist or VPAC2 agonist after 30min was measured in Jurkat, J-OV1 and J-OV2 cells. Ligand concentration values (nM) are expressed relative to the basal condition (above basal). Data are the mean ± SEM of triplicate determination of five different experiments (*p \u0026lt; 0.05, **p \u0026lt;0.01, ***p \u0026lt;0.001). \u003cstrong\u003e(C)\u003c/strong\u003e Cells were loaded with the Ca²⁺-sensitive dye Fluo-4 AM, and fluorescence was recorded over time following stimulation with PBS (control), 100 nM VIP, VPAC1 agonist or VPAC2 agonist. Values are expressed as ΔF/F₀, calculated as the fluorescence at each time point (F) divided by the basal fluorescence (F₀) and normalized to the PBS control (horizontal dashed line). The vertical dashed line indicates the time point at which the stimuli were added. Figures show representative traces of Ca²⁺ responses over time. Data are the mean from three independent experiments performed by triplicate.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9247309/v1/f4554a130b34c8c09f45ba6f.png"},{"id":108759271,"identity":"ac5ad6fa-3667-469d-b715-8fec72a9c0d6","added_by":"auto","created_at":"2026-05-08 06:17:19","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":326917,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePhospho-kinase profiling of signalling pathways in Jurkat cells following VPAC receptors overexpression. (A) \u003c/strong\u003eRepresentative membranes from the Human Phospho-Kinase Array showing phosphorylated kinases in Jurkat vs J-OEV1 and J-OEV2 cells. Highlighted spots indicate kinases showing increased phosphorylation levels or overexpression-dependent changes, and the corresponding kinases are listed in the figure. \u003cstrong\u003e(B)\u003c/strong\u003e Quantification of relative spot intensities for selected kinases, normalized to negative spots and expressed as mean pixel density.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-9247309/v1/90f8a1df7bc2337d96f95ac4.png"},{"id":108806218,"identity":"71690240-f5c1-4ee2-ae7d-34887982ea95","added_by":"auto","created_at":"2026-05-08 15:28:02","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":567190,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVIP effect in the phosphorylation profile of intracellular signalling proteins in Jurkat and Jurkat-overexpressing cells\u003c/strong\u003e. Volcano plot of differentially phosphorylated kinases between VIP-stimulated over unstimulated in Jurkat cells \u003cstrong\u003e(A),\u003c/strong\u003e in J-OEV1 \u003cstrong\u003e(B)\u003c/strong\u003e and J-OEV2 \u003cstrong\u003e(C)\u003c/strong\u003e, based on data from the Proteome Profiler™ Human Phospho-Kinase Array (R\u0026amp;D Systems), are shown. Spot intensities were quantified by densitometry, background-subtracted, and normalized to internal reference spots. Log₂ fold change (x-axis) and −log₁₀ q-value (y-axis) are shown. Kinases displaying increased phosphorylation are highlighted in red (dashed lines denote the significance thresholds (p \u0026lt; 0.1 and |log₂FC| \u0026gt; 0.5), while non-significant changes are represented in black. A representative experiment is shown. Tables detailing the most significantly altered phosphorylated proteins in J-OEV1 and J-OEV2 are also shown, including the −log₁₀ (q-value) associated with each kinase.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-9247309/v1/022c8837c272de364b6f4475.png"},{"id":108807185,"identity":"5d47283e-6c9e-459b-b18a-8170f5355eed","added_by":"auto","created_at":"2026-05-08 15:30:17","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":336065,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eActivation-dependent alterations in the phosphorylation profile of intracellular signalling proteins in Jurkat cell\u003c/strong\u003e. \u003cstrong\u003e(A)\u003c/strong\u003e Volcano plot of differentially phosphorylated kinases between antiCD3/antiCD28-activated and non-activated Jurkat cells, based on data from the Proteome Profiler™ Human Phospho-Kinase Array (R\u0026amp;D Systems), is shown. Spot intensities were quantified by densitometry, background-subtracted, and normalized to internal reference spots. Log₂ fold change (x-axis) and −log₁₀ q-value (y-axis) are shown. Kinases displaying increased phosphorylation are highlighted in blue (dashed lines denote the significance thresholds (p \u0026lt; 0.05 and |log₂FC| \u0026gt; 0.5), while non-significant changes are represented in black. A representative experiment is shown. \u003cstrong\u003e(B)\u003c/strong\u003e A table detailing the most significantly altered phosphorylated proteins is also shown, including the −log₁₀ (q-value) associated with each kinase.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-9247309/v1/3022f612afb8b2a20726bbf5.png"},{"id":108759273,"identity":"5bb8ce7b-83ec-4cf9-99d1-0ce313c0c91b","added_by":"auto","created_at":"2026-05-08 06:17:19","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":571132,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVIP-induced modulation of the phosphorylation profile of intracellular kinases in activated Jurkat cells\u003c/strong\u003e. \u003cstrong\u003e(A)\u003c/strong\u003e Protein levels of signalling kinases in untransfected Jurkat cells and in cells overexpressing VPAC1 (J-OEV1) or VPAC2 (J-OEV2) were analysed after 5 min (CREB, ERK, p38α, and PRAS40) or 15 min (PLCγ and Lck) of anti-CD3/anti-CD28 activation, in the presence or absence of 100 nM VIP, by Western blotting. Levels of the corresponding unphosphorylated proteins or GADPH levels were used as a loading control. A representative experiment is shown. \u003cstrong\u003e(B)\u003c/strong\u003e Protein bands were quantified by densitometric analysis and normalized to the intensity of unphosphorylated protein or GADPH. Asterisks indicate significative differences towards the untreated condition. Data represent the mean ± SEM of three independent experiments.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-9247309/v1/2d4e80f363a915c66e79c04b.png"},{"id":108806116,"identity":"7b071b59-18f6-4d5b-bbad-2a13765bb39e","added_by":"auto","created_at":"2026-05-08 15:27:43","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":235884,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTranscription factors and cytokines mRNA expression in Jurkat cells and changes observed after VPAC overexpression. \u003c/strong\u003emRNA expression of \u003cem\u003eTBX21, RORC and GATA3\u003c/em\u003e transcription factors and \u003cem\u003eIL2, IL4, IL10, IFNG and TNFA\u003c/em\u003e cytokines was determined by semiquantitative real-time PCR analysis in Jurkat, J-OEV1 and J-OEV2 cells. Results are expressed as relative mRNA levels (normalized to SDHA mRNA levels, 2\u003csup\u003e−ΔCt\u003c/sup\u003e) and relativized with respect to each mRNA expression in Jurkat cells (2\u003csup\u003e−ΔΔCt\u003c/sup\u003e) (dashed line). The mean ± SEM of triplicate determination from five independent experiments are shown. Asterisks indicate differences between untransfected Jurkat cells and VPAC overexpressed cells (*p \u0026lt; 0.05, **p \u0026lt;0.01).\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-9247309/v1/d046764d150f87b7fa60d424.png"},{"id":108759275,"identity":"b40433f9-d741-4ba7-83fc-6b9d2079d4f7","added_by":"auto","created_at":"2026-05-08 06:17:19","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":476369,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eActivation-depended changes in transcription factors and cytokines mRNA expression levels and VIP effect. \u003c/strong\u003emRNA expression of \u003cem\u003eTBX21, RORC and GATA3\u003c/em\u003e transcription factors \u003cstrong\u003e(A)\u003c/strong\u003e and \u003cem\u003eIL2, IL4, IL10, IFNG and TNF\u003c/em\u003e cytokines \u003cstrong\u003e(B)\u003c/strong\u003e was determined by semiquantitative real-time PCR analysis in Jurkat, J-OEV1 and J-OEV2 cells. Results are expressed as relative mRNA levels (normalized to SDHA mRNA levels, 2\u003csup\u003e−ΔCt\u003c/sup\u003e) and relativized with respect to each mRNA expression in untreated condition. \u003cstrong\u003e(C)\u003c/strong\u003e mRNA expression of transcription factor and cytokine was tested in J-OEV1 and J-OEV2 cells, in the presence of 100 nM VIP after one day of cell culture activation. The fold change expression in the presence of VIP versus anti-CD3/anti-CD28 activated cells is represented. The mean ± SEM of triplicate determination from five independent experiments are shown. Asterisks indicate differences between untreated Jurkat cells and anti-CD3/anti-CD28 activation (*p \u0026lt; 0.05, **p \u0026lt;0.01).\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-9247309/v1/72d7c628893d2185a8d46705.png"},{"id":108807140,"identity":"0d698ef0-aa1b-4a94-a7cf-affa78f33658","added_by":"auto","created_at":"2026-05-08 15:30:12","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":334243,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVPAC modulation of T Cell Metabolism and Proliferation in activated-Jurkat cells. (A). \u003c/strong\u003eCell viability was assessed using the WST-1 assay in Jurkat, J-OEV1, and J-OEV2 cells under different stimulation conditions at 24, 48 and 72h. Cells were left untreated (left panel), stimulated with αCD3/αCD28 (middle panel), or stimulated with αCD3/αCD28 in the presence of 10nM VIP (right panel). Data are presented as fold change relative to 0 hours of treatment for each cell type. Values represent the mean ± SEM of three independent experiments performed in triplicate. Asterisks indicate differences between J-OEV and Jurkat cells (*p \u0026lt; 0.05). \u003cstrong\u003e(B)\u003c/strong\u003e Cell proliferation was assessed using Tag-it Violet dye. Jurkat, J-OEV1 and J-OEV2 cells were cultured under three conditions: untreated, αCD3/αCD28 stimulation in the presence or absence of 10 nM VIP. Proliferation is expressed as the loss of fluorescence, normalized to Jurkat cells. Data are shown as mean ± SEM.\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-9247309/v1/ee2c2a09d733622d408ddaec.png"},{"id":108976999,"identity":"f176b606-29a7-448d-9004-073648e06c26","added_by":"auto","created_at":"2026-05-11 11:29:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4248217,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9247309/v1/d4d979e3-3b30-43c3-912a-4d8f63c96a88.pdf"},{"id":108759268,"identity":"f6a2e40c-43fd-448a-8a84-5749d5a158d9","added_by":"auto","created_at":"2026-05-08 06:17:19","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":1171832,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryData.docx","url":"https://assets-eu.researchsquare.com/files/rs-9247309/v1/1a6628e9cef55cbb55dab353.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Finding functional gaps: integrative analysis of VPAC1- and VPAC2-mediated signalling pathways in human lymphocytes","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eVasoactive Intestinal Peptide (VIP) is a 28-amino-acid neuropeptide ubiquitously distributed throughout the body. Initially described as an intestinal hormone, it is now recognized as a pleiotropic regulator involved in nervous system function, immune modulation, and bone and cartilage metabolism [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eVIP exerts its biological activity primarily through two G protein-coupled receptors (GPCRs), VPAC1 and VPAC2, members of the secretin receptor family and share approximately 55% sequence homology [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Both receptors display comparable affinity for VIP (VPAC1 Kd\u0026thinsp;\u0026asymp;\u0026thinsp;1 nM; VPAC2 Kd\u0026thinsp;\u0026asymp;\u0026thinsp;5 nM) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Like most class B1 GPCRs, VPAC receptors canonically signal through Gαs-dependent cAMP production with downstream activation of PKA and EPAC. In addition, VPAC1 consistently induces Ca\u0026sup2;⁺ mobilization through Gαq and Gαi subunits and activates PKC in a cell context-dependent manner [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. \u0026ldquo;G protein-independent\u0026rdquo; signalling has been described, including activation of PLD [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] and PI3K, which contribute to VIP-mediated regulation of prostate cancer progression via VPAC1 and breast tumour cell proliferation via VPAC2 [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAt the downstream level, VIP signalling modulates kinase pathways such as MEK/ERK, p38, JNK, and survival-related kinases including mTOR [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Many VIP-regulated genes contain cAMP-responsive elements (CREs), such as CREB, which mediate VIP-dependent regulation of neuronal function, immune responses, and tumour biology [\u003cspan additionalcitationids=\"CR16 CR17\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. VIP also influences the activity of additional transcription factors, including AP-1, IRF, NF-κB, and SP-1, particularly in immune cells [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWithin the GPCR superfamily, shared ligands and overlapping signalling cascades often create context-dependent functional redundancy, strongly dependent on the physiological and cellular context, complicating the dissection of their distinct signalling mechanisms [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Although distinct signalling pathways for VPAC1 and VPAC2 have not been firmly defined, evidence suggests functional differences, with overlapping responses and receptor-specific modulation of signalling, that do not always translate into distinct physiological outcomes [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. For instance, VPAC1 mediates hepatocyte proliferation [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], and its deficiency alters gut microbiota composition and metabolic homeostasis [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Alterations in VPAC2 expression have been associated with disrupted circadian rhythms, impaired neuronal maturation, and schizophrenia-related phenotypes linked to dopaminergic imbalance [\u003cspan additionalcitationids=\"CR18 CR19 CR20 CR21 CR22 CR23 CR24 CR25 CR26 CR27 CR28\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. VPAC1 knockout mice exhibit resistance to experimental autoimmune encephalomyelitis, whereas VPAC2-deficient mice display an exacerbated pathological phenotype [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Regarding their immunomodulatory functions, in microglial cells, VPAC1 predominantly mediates inflammatory signalling, whereas VPAC2 contributes to survival and polarization responses [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In lymphocytes, VPAC1 is considered the main mediator of the anti-inflammatory actions of VIP, regulating cytokine production and T-cell activation [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. However, depending on the degree of T-cell activation and differentiation, VPAC2 expression can be increased and contributes to anti-inflammatory responses [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], suggesting a dynamic and context-dependent balance between both receptors in immune regulation.\u003c/p\u003e \u003cp\u003eConsistent with the redundancy observed in GPCR-mediated mechanisms, the immune system exemplifies biological redundancy. Cytokines and chemokines, often derived from gene duplication events [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], converge on shared signalling pathways modulated by cellular context. This functional overlap explains why blocking a single axis rarely abolishes inflammation [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. This raises a central question: \u003cem\u003eDo VPAC1 and VPAC2 mediate distinct context-dependent signalling and functional responses, or do they function as intrinsically redundant components of the same signalling network?\u003c/em\u003e In T CD4\u003csup\u003e+\u003c/sup\u003e cells context, signalling mediated by VIP is strictly subordinate to TCR-driven signalling. It regulates CD4⁺ T-cell differentiation, shifting responses from Th1/Th17 toward Th2 and Treg phenotypes cells [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. This regulation may be mediated by the expression pattern of its receptors, which display differential expression depending on the activation state of T lymphocytes [\u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Such differential receptor distribution suggests that VIP fine-tunes T-cell function through distinct, context-dependent signalling mechanisms. Jurkat cells, as a model of T cells, respond to a well-defined activating stimulus, the TCR engagement, that triggers a reproducible and extensively characterized signalling program. This makes them a suitable system to assess whether VPAC1 and VPAC2 generate distinct signalling effects and whether these differences persist within the established T-cell activation framework.\u003c/p\u003e \u003cp\u003eWe hypothesized that VPAC1 and VPAC2 differentially engage intracellular signalling pathways in T cells, leading to receptor-specific modulation of cellular responses and thereby contributing to the fine-tuning of immune signalling beyond simple functional redundancy.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCell culture\u003c/h2\u003e \u003cp\u003eJurkat cells were maintained in RPMI medium (Cytiva), supplemented with 10% Fetal Bovine Serum (FBS), 1% peniciline/Streptomicine and 1% Stable L-Glutamine (PAN-Biotech) in T75 flask at a concentration of 0.3 \u0026times; 10⁶ cells/mL. HEK293 cells were cultured in DMEM medium (Corning) supplemented with 10% FBS (Cytiva), 1% Peniciline/Streptomicine and 1% Stable L-Glutamine in 100mm dishes. The specific culture conditions for each assay are described in the corresponding section. In all cases, treatments were performed under low-serum conditions (0.5% FBS).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePlasmids construction\u003c/h3\u003e\n\u003cp\u003eFor every plasmid construction, GeneArt\u0026trade; Gibson Assembly HiFi technology (ThermoScientific) was performed. For BRET assays, \u003cem\u003eVIPR1\u003c/em\u003e (VPAC1) and \u003cem\u003eVIPR2\u003c/em\u003e (VPAC2) human transcripts sequences were cloned into a Renilla Luciferase carrying vector (pRLuc-N1) [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] (supplementary Fig.\u0026nbsp;1A). Briefly, VIPR transcripts were amplified from human T cell cDNA samples by PCR. Subsequently, pRLucN1 vector was linearized with homologous ends to finally obtain two plasmids: pVIPR1_RLuc and pVIPR2_RLuc. For VPAC receptors overexpression, VIPR1 and VIPR2 human sequence were cloned into pRLuc-N1. \u003cem\u003eRLUC\u003c/em\u003e transcript sequence was substituted by both VIPR sequences, to finally obtain pVIPR1 and pVIPR2 plasmids. Vectors were sequenced through the Sanger sequence method.\u003c/p\u003e\n\u003ch3\u003eBioluminescence resonance energy transfer assay (BRET)\u003c/h3\u003e\n\u003cp\u003eThe interaction between VIP receptors and different Gα proteins subunits was studied using the BRET technique (Bioluminescence Resonance Energy Transfer). To do so, specific miniG proteins, Gα subunits modified to improve the interaction with GPCRs, were used [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Four different proteins representing each main Gα subunit family were chosen Gs, Gq, Gi and G12, each fused to the Venus fluorescent protein (kindly provided by N. A. Lambert, Augusta University, Augusta, GA).\u003c/p\u003e \u003cp\u003eHEK293 were co-transfected using Lipofectamine 2000 (Thermofisher) as a transfection reagent and OptiMEM (Thermofisher) as carrier medium, with either pVIPR1_RLuc or pVIPR2_RLuc along with the different miniG proteins carrying vectors. 8x10\u003csup\u003e4\u003c/sup\u003e cells/well were plated in 96 well white/clear flat bottom plate (Nunc, Thermofisher) with low glucose DMEM medium (Sigma-Aldrich, Merck) supplemented with 10% FBS. After 48 hours, cells were incubated with increasing concentrations of VIP (Bachem) diluted in Phosphate Buffered Saline (PBS), along with Renilla Luciferase substrate, Coelenterazine H 5\u0026micro;M (Thermofisher). After incubation at 37\u0026deg;C, luminescence (Rluc, 485\u0026thinsp;\u0026plusmn;\u0026thinsp;10nm) and fluorescence (Venus, 530\u0026thinsp;\u0026plusmn;\u0026thinsp;12) were detected in a Mithras LB 940 plate reader (Berthold Technologies).\u003c/p\u003e \u003cp\u003eResults were analysed through a non-linear regression model 4PL, where the logarithm of the VIP concentration was plotted against the BRET ratio values (luminescence/fluorescence), corrected by the PBS condition.\u003c/p\u003e\n\u003ch3\u003eElectroporation of Jurkat Cells\u003c/h3\u003e\n\u003cp\u003eJurkat cells were transformed by electroporation using 12\u0026micro;g of pVIPR1 or pVIPR2 plasmids to overexpress VPAC1 or VPAC2. Additionally, Jurkat cells were electroporated with 12\u0026micro;g of pR_LucN1 plasmid as a control. Briefly, 5x10\u003csup\u003e6\u003c/sup\u003e cells diluted in 100\u0026micro;l PBS/Hepes 1M were electroporated in a 4mm electroporation cuvette (Cell Project) using a Gene pulser Xcell Electroporation System (Bio-Rad) with the following conditions: 350 V, 50\u0026micro;F and 200Ω, immediately followed by a 1-minute ice incubation. Transformed cells were selected through antibiotic resistance, being treated with 700\u0026micro;g/ml of G418 (Gibco).\u003c/p\u003e\n\u003ch3\u003eLuminescence assays\u003c/h3\u003e\n\u003cp\u003eJurkat cells transformed with pR_LucN1 were seeded at 12x10\u003csup\u003e5\u003c/sup\u003e cells/well on 96 well white/clear bottom plates (Nunc, Thermofisher) in PBS. Cells were exposed to Coelenterazine H 5\u0026micro;M and luminescence was measured using a Fluostar Omega plate reader (BMG LabTech) (Supplementary Fig.\u0026nbsp;1B).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eGene expression by Real time PCR\u003c/h2\u003e \u003cp\u003eTotal RNA was obtained using TriReagent (Invitrogen), and 2 \u0026micro;g were subsequently reverse transcribed using the High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems). VIP receptor gene expression was detected through semiquantitative RT-PCR, performed using TaqMan Gene Expression Master Mix (Thermofisher) and specific TaqMan probes for \u003cem\u003eVIPR1\u003c/em\u003e (Hs00270351_m1) and \u003cem\u003eVIPR2\u003c/em\u003e (Hs00173643_m1) genes.\u003c/p\u003e \u003cp\u003eIn order to study specific cytokines and transcription factors produced by Jurkat cells and Jurkat cells overexpressing each VPAC receptor, cells were cultured for 24 hours under the following conditions: untreated, treated with 25\u0026micro;l/ml ImmunoCult\u0026trade; Human CD3/CD28 T Cell Activator (StemCell), VIP 10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003eM, or a combination, along with Jurkat expressing pR_LucN1 plasmid, used as a control. Semiquantitative RT-PCR was performed using GoTaq qPCR Master Mix (Promega), with specific sets of primers for each gene (Supplementary Fig.\u0026nbsp;2). Succinate dehydrogenase complex flavoprotein subunit A (\u003cem\u003eSDHA\u003c/em\u003e) was used as a housekeeping gene, and each sample was normalized using the 2\u003csup\u003e\u0026minus;ΔCt\u003c/sup\u003e formula.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ecAMP measurement\u003c/h3\u003e\n\u003cp\u003ecAMP production was measured using the HitHunter cAMP Assay for Small Molecules Kit (DiscoverX), measuring luminescence levels with a Fluostar Omega plate reader (BMG LabTech). Briefly, Jurkat cells and Jurkat cells overexpressing VPAC1 or VPAC2 were seeded at 1x10\u003csup\u003e6\u003c/sup\u003ecells/ml in OptiMEM / 2% FBS and treated with PBS or increasing concentrations of VIP, VPAC1 agonist [Lys\u003csup\u003e15\u003c/sup\u003eArg\u003csup\u003e16\u003c/sup\u003eLeu\u003csup\u003e27\u003c/sup\u003eVIP (1\u0026ndash;7) -GRF (8‐27)] or VPAC2 agonist (RO 25‐1553; Bachem) diluted in PBS for 30 minutes. Then, cells were lysated and produced cAMP was measured according to the manufacturer\u0026rsquo;s instructions. Finally, cAMP concentrations (nM) were calculated by interpolation from a standard curve.\u003c/p\u003e\n\u003ch3\u003eDetermination of Ca influx\u003c/h3\u003e\n\u003cp\u003eTo analyse the Calcium production, Fluo-4 AM (Invitrogen) was used. 12x10\u003csup\u003e5\u003c/sup\u003e cells of each condition were incubated on 96 well black/clear bottom plates (Ibidi) in HBSS w/o Ca\u003csup\u003e2+\u003c/sup\u003e/ Mg\u003csup\u003e2+\u003c/sup\u003e (Gibco), supplemented with 5\u0026micro;M of Fluo-4 AM at 37\u0026deg;C. Afterward, cells were wash with fresh medium to remove excess staining and incubated for another 30 minutes. Finally, emission was measured at 520nm for 8 minutes, using a Fluostar Omega plate reader (BMG LabTech), in the presence of PBS or 100nM of VIP, VPAC1 agonist or VPAC2 agonist diluted in PBS. Values are expressed as ΔF/F₀, calculated as the fluorescence at each time point (F) divided by the basal fluorescence (F₀) and normalized to the PBS control.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePhospo-Kinase array\u003c/h2\u003e \u003cp\u003eJurkat cells and Jurkat cells overexpressing VPAC1 or VPAC2 receptors were cultured overnight with OptiMEM/2%FBS at 1x10\u003csup\u003e6\u003c/sup\u003ecells/mL. The following day, cells were incubated with PBS, with 25\u0026micro;l/ml ImmunoCult\u0026trade; Human CD3/CD28 T Cell Activator (StemCell) or VIP 10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003eM for 15 minutes. Afterwards, 200\u0026micro;g protein lysates were used to perform the Proteome Profiler\u0026trade; Human Phospho-Kinase Array Kit (R\u0026amp;D Systems), following the manufacturer\u0026rsquo;s instructions. The results were densitometred using ImageJ software (V1.54k) and corrected using PBS spot values. Untreated results are represented as the mean pixel intensity of both spots that belong to each phosphorylated protein. The effect of activation or VIP treatment is represented as a volcano plot where the log2 of the fold change is plotted against the -log10 of the q-value obtained using a one-way ANOVA test.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eProtein analysis by Western Blot\u003c/h2\u003e \u003cp\u003eJurkat cells and Jurkat cells overexpressing each VPAC receptor were cultured overnight with OptiMEM/2%FBS at 1x10\u003csup\u003e6\u003c/sup\u003ecell/ml, follow by a 5- or 15-minutes treatment under the following conditions: untreated, treated with 25\u0026micro;l/ml ImmunoCult\u0026trade; Human CD3/CD28 T Cell Activator (StemCell), VIP 10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003eM, or a combination. The optimal treatment duration was determined in advance for each protein (Supplementary Fig.\u0026nbsp;3). Protein extracts were obtained using ice-cold radio-immunoprecipitation assay buffer (Thermofisher) and quantified using a QuantiPro BCA Assay kit (Sigma Aldrich). Protein extracts were subjected to SDS-PAGE, using different protein quantities and acrylamide gel percentages depending on the protein of study (Supplementary Fig.\u0026nbsp;4), and then transferred to a nitrocellulose membrane (0.45 \u0026micro;m). Each membrane was blocked 1 hour with 5% Bovine Serum Albumin and incubated overnight at 4\u0026deg;C with primary antibodies (Supplementary Fig.\u0026nbsp;4). Anti-rabbit (1:5000) or anti-mouse (1:10000) HRP-conjugated secondary antibodies (Invitrogen) were used, and proteins were detected using SuperSignal West Pico PLUS Chemiluminiscent Substrate (Thermofisher). Results were analysed using Bio-Rad Quantity One Program. The measurement of phosphorylated protein was then normalised against the quantity of unphosphorylated protein or GAPDH expression.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eCell viability and proliferation\u003c/h2\u003e \u003cp\u003eViability was determined through mitochondrial metabolism by the Cell Proliferation Reagent WST-1(Roche). Jurkat cells and Jurkat cells overexpressing each VPAC receptor were cultured in a 96 well round bottom plate at a density of 10.000 cells per well in RPMI plus 2% FBS and treated as described in previous section for 72 hours. At 0, 24, 48 and 72 hours, WST-1 was added at a 1/10 ratio (v/v) and incubated in at 37\u0026deg;C incubator for 30 minutes. Supernatant was then moved to a 96 well flat bottom plate and read at 450nm.\u003c/p\u003e \u003cp\u003eCell proliferation was studied using Tag-it Violet (BioLegend). 3x10\u003csup\u003e6\u003c/sup\u003e cells of Jurkat cells and Jurkat cells overexpressing each VPAC receptor, previously washed with PBS (Phosphate Buffer Saline), were incubated with 2\u0026micro;M Tag-it Violet diluted in PBS during 20 minutes at 37\u0026deg;C in the dark. Afterwards, excess staining was quenched with RPMI /10%FBS, centrifuged and incubated during 10 minutes in RPMI/10%FBS. Each condition was then treated for 72 hours in RPMI/2%FBS under the same conditions described in previous sections. At 0, 24, 48 and 72 hours cells were stained with 7-AAD (Invitrogen) and acquired on a FACSymphony A1 flow cytometer (BD Life Sciences), results were analysed using FlowJo\u0026trade; Software (version 10, BD Life Sciences).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll data were analysed using GraphPad Prism 8.0. For BRET concentration\u0026ndash;response curves, data were fitted using a 4-parameter logistic (4PL) non-linear regression model. For experiments with two groups, an unpaired Student\u0026rsquo;s t-test was used. For experiments with three or more groups, one-way ANOVA or a Kruskal-Wallis test followed by Dunn\u0026rsquo;s post-hoc test was applied, unless otherwise specified.\u003c/p\u003e \u003cp\u003eData are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM, and the number of independent biological replicates (n) is indicated in the figure legends. Differences were considered statistically significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. For volcano plots, significance thresholds are described in the corresponding figure legends.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003e \u003cb\u003eInteraction of VPAC receptors with different G proteins.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo study the interaction of each receptor with different G proteins, HEK293 cells were co-transfected with VPAC1-RLuc or VPAC2-RLuc constructs together with Venus-tagged miniG proteins, and BRET responses were measured following VIP stimulation. HEK293 cells were preferred over Jurkat cells, since these cells provide a controlled, efficient and reproducible system to characterize VPAC receptor-G protein interactions, with inflammatory relevance later confirmed in Jurkat T cells. Stimulation of transfected cells with VIP led to a time-dependent increase in the BRET ratio for the VPAC1 receptor with Gs, Gq, and to a lesser extent, Gi and G12 (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eA). Dose-response analysis showed that VPAC1 exhibited the highest potency for Gs coupling (EC₅₀ = 1.87 nM), followed by Gq (EC₅₀ = 8.97 nM), whereas Gi showed lower efficacy and G12 induced minimal responses (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eB). In contrast, for the VPAC2 receptor, VIP promoted a time-dependent increase in BRET ratio only with Gs, while the response with Gq was linear and without defined activation kinetics, and no interaction was detected with Gi or G12 (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eC). Moreover, the potency of Gs interaction with VPAC2 was lower than with VPAC1 (EC50 9.9 nM), being the potency of Gq even lower (EC50 27.5 nM) (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eFunctional characterization of VPAC signalling in Jurkat cells overexpressing VPAC receptors.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAfter identifying differences in G protein activation, we further examined VPAC receptor signalling in depth. Given the importance of VIP in the immune system and the previously described differences in VPAC receptor expression among Th cells [\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e42\u003c/span\u003e], we investigated signalling in Jurkat cells, which express non-functional VPAC receptors (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA). We generated Jurkat cell lines overexpressing either the VPAC1 or VPAC2 receptor by transfection with plasmids encoding the respective receptors (supplementary Fig.\u0026nbsp;1A). As shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA, VPAC1 overexpressing cells (J-OEV1) exhibited a six-fold increase in VPAC1 expression, while VPAC2-overexpressing cells (J-OEV2) showed a seven-fold increase in VPAC2 expression compared with parental Jurkat cells.\u003c/p\u003e \u003cp\u003eTo assess receptor functionality, we measured cAMP production, modulated by Gs proteins, and cytosolic Ca\u003csup\u003e2+\u003c/sup\u003e influx, mediated by Gq proteins. VIP stimulation significantly increased intracellular cAMP levels in J-OEV1 and J-OEV2, whereas no effect was observed in untransfected Jurkat cells (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eB). Selective VPAC1 and VPAC2 agonists increased cAMP production only in cells overexpressing the corresponding receptor. Using the calcium sensor Fluo-4 AM, we detected an increase in cytosolic Ca\u003csup\u003e2+\u003c/sup\u003e in J-OEV1 cells upon stimulation with VIP or the VPAC1 agonist (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eC). In Jurkat and J-OEV2 cells, the calcium response to VIP was small and transient, and no effect was observed upon stimulation with the VPAC2 agonist.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eEffect of Jurkat-VPAC overexpression and activation on protein phosphorylation dynamics\u003c/h2\u003e \u003cp\u003eTo investigate signalling pathways regulated by VPAC receptors, phosphorylation profiles were analysed using a phospho-kinase array. We observed higher phosphorylation levels of some kinases in untransfected Jurkat cells. Compared with control Jurkat cells, overexpression of either receptor increased phosphorylation of CREB, ERK1/2, JNK, Lck, Lyn, Src, Akt, PRAS40, STAT3 and Hsp60, with differences in the intensity (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). For example, CREB and ERK phosphorylation were higher in J-OEV1 whereas in J-OEV2, the greater phosphorylation was found in Lck, Lyn, Src, Akt, PRAS40 and Hsp60.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eVIP stimulation did not alter kinase phosphorylation in control Jurkat cells (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). In contrast, VIP reduced phosphorylation of several kinases in receptor-overexpressing cells. In J-OEV1 cells, VIP induced a decrease in the phosphorylation of 8 out of the 43 kinases assessed, with p53, PRAS40 and eNOS showing the strongest reduction. The effect was more pronounced in J-OEV2 cells, where 12 kinases displayed decreased phosphorylation in response to VIP, among these, STAT2, PDGF, FGR, Lck, eNOS and Hsp27 exhibited the greatest reductions in phosphorylation levels. Additionally, Jurkat control cells were briefly stimulated with anti-CD3/anti-CD28 antibodies to assess rapidly activated pathways.\u003c/p\u003e \u003cp\u003eAs shown in Fig. 5, stimulation increased phosphorylation of several proteins, with ERK, CREB, RSK and Hsp27 showing the strongest responses, alongside lower-level phosphorylation of 11 additional proteins.\u003c/p\u003e \u003cp\u003eBased on above previous results and on the analysis of key signalling pathways involved in inflammation, survival and proliferation in T lymphocytes, we selected several kinases for further examination by Western blotting. We focused on those affected by VIP treatment or by anti-CD3/anti-CD28 antibodies activation, and considering the differential responses associated with the overexpression of VPAC1 and VPAC2 receptors. Since phosphorylation of some kinases is highly time-dependent, we performed a preliminary time-course analysis to select the optimal time point for each protein (Supplementary Fig.\u0026nbsp;4). Within the signalling pathway of Gs-coupled GPCRs, CREB acts as a key transcription factor in the cAMP-mediated response and is a phosphorylation-dependent transcription factor that plays a crucial role in T cell activation, proliferation, survival and differentiation. Its phosphorylation can also be promoted by kinases such as RSK2, which is linked to the MAPK/ERK signalling pathway [\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e]. Jurkat untransfected and VPAC overexpressed activation resulted in enhanced CREB phosphorylation, which was further increased following VIP treatment in both untransfected and J-OEV1 cells (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e). In J-OEV2 VIP treatment maintained the phosphorylation levels of CREB observed after activation. The MAPK pathway, which can be activated through the TCR, cytokines, and other stimuli, integrates external signals to coordinate activation, proliferation, and survival. In this pathway, two key downstream components are ERK and p38α [\u003cspan class=\"CitationRef\"\u003e44\u003c/span\u003e]. As expected, activation of Jurkat cells, both untransfected and transfected, stimulated ERK1/2 phosphorylation, however VIP treatment maintained ERK phosphorylation level following activation in every Jurkat condition tested. p38α activity is essential for normal immune and inflammatory responses and is activated in T cells by several inflammatory mediators. Consistently, TCR activation increased p38α phosphorylation in both untransfected and transfected Jurkat cells, and this effect was downregulated by VIP, particularly in J-OEV1 cells. PLCγ1 is recruited and activated as a key step in TCR-mediated T cells activation [\u003cspan class=\"CitationRef\"\u003e45\u003c/span\u003e]; however, in our experimental conditions, we observed little (Jurkat, J-OEV1) to no (J-OEV2) phosphorylation of this protein. The presence of VIP appears to decline the phosphorylation of this protein in J-OEV1. PRAS40 is a component of the mTOR complex 1 (mTORC1), and its phosphorylation, mainly mediated by Akt, activates mTORC1, that acts as a key regulator of lymphocyte survival [\u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e]. Anti-CD3/anti-CD28 activation induced strong phosphorylation of PRAS40 in untransfected and VPAC overexpressed cells, which was decreased by VIP, especially in J-OEV1 cells. Lck belongs to the Src family of kinases, and its activity constitutes the initial step in TCR signalling [\u003cspan class=\"CitationRef\"\u003e47\u003c/span\u003e]; therefore, it is not surprising that its phosphorylation increases upon anti-CD3/anti-CD28 activation, a phenomenon observed in control Jurkat cells as well as in J-OEV1 and J-OEV2. VIP preserved the activation-induced Lck phosphorylation level in all cases.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eVPAC modulation of cytokines and transcription factors relevant for T cells\u003c/h2\u003e \u003cp\u003eTo evaluate the functional consequences of VPAC receptor expression, transcription factors and cytokines associated with T cell responses were analysed. We observed a similar expression pattern for \u003cem\u003eTBX21 (\u003c/em\u003eT-bet), \u003cem\u003eRORC\u003c/em\u003e (RORγt) and \u003cem\u003eGATA3\u003c/em\u003e in Jurkat, J-OEV1 and J-OEV2 cells, being GATA3 the most highly expressed followed by \u003cem\u003eRORC\u003c/em\u003e and \u003cem\u003eTBX21\u003c/em\u003e (Supplementary Fig.\u0026nbsp;5A). Regarding cytokine expression, \u003cem\u003eIL10\u003c/em\u003e (IL-10) was the most abundantly expressed cytokine in all cell lines tested. Nevertheless, the relative expression pattern of other cytokines changed upon VPAC receptor overexpression. Both, J-OEV1 and J-OEV2 cells, expressed more \u003cem\u003eTNF\u003c/em\u003e (TNFα) than \u003cem\u003eIL2\u003c/em\u003e (IL-2), and in J-OEV2 the expression of \u003cem\u003eIFNG\u003c/em\u003e (IFNγ) and \u003cem\u003eIL4\u003c/em\u003e (IL-4) was reversed compared with that in untransfected cells (Supplementary Fig.\u0026nbsp;5B). When we compared cells overexpressing the receptors with untransfected cells to assess whether receptor overexpression alters the expression levels of transcription factors and cytokines (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e), we observed that J-OEV1 and J-OEV2 exhibited lower expressions of \u003cem\u003eIL2, IL10\u003c/em\u003e and \u003cem\u003eIFNG\u003c/em\u003e compared with Jurkat cells. Additionally, J-OEV2 expressed less \u003cem\u003eTBX21\u003c/em\u003e, \u003cem\u003eIL4\u003c/em\u003e and more \u003cem\u003eTNF\u003c/em\u003e than Jurkat cells. The differences observed in transfected cells were attributable to receptor overexpression as empty plasmid transfection caused no changes in the transcription factors or cytokines analyzed (Supplementary Fig.\u0026nbsp;6).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eUpon activation with anti-CD3/anti-CD28 antibodies, we observed changes in both transcription factor and cytokine expression (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e). \u003cem\u003eRORC\u003c/em\u003e expression decreased, with significant reduction in J-OEV1 and J-OEV2 cells, whereas \u003cem\u003eTBX21\u003c/em\u003e and \u003cem\u003eGATA3\u003c/em\u003e expression were upregulated following activation, reaching significance in J-OEV2 cells for \u003cem\u003eTBX21\u003c/em\u003e and in J-OEV1 cells for \u003cem\u003eGATA3\u003c/em\u003e. Regarding cytokines, all of them, except \u003cem\u003eIL10\u003c/em\u003e, showed a trend towards upregulation. \u003cem\u003eIL2\u003c/em\u003e expression increased significantly in J-OEV1 cells, \u003cem\u003eIL4\u003c/em\u003e in J-OEV2 cells, and \u003cem\u003eTNF\u003c/em\u003e showed a significant increase in all three Jurkat-derived cell lines. Overall, the observed changes indicate that activation promotes a mainly Th1/Th2-oriented differentiation profile. When cells activated with anti-CD3/anti-CD28 antibodies were exposed to VIP, we detected alterations in both cytokine and transcription factor expression. Notably, VIP induced a significant increase in \u003cem\u003eIL2\u003c/em\u003e expression in J-OEV1 cells, while both J-OEV1 and J-OEV2 cells displayed a tendency to a higher \u003cem\u003eIL10\u003c/em\u003e levels in response to VIP, not observed in activated Jurkat cells, which may suggest that the presence of VIP could favours an anti-inflammatory profile in these cells through both VPAC receptors.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eEffect of VPAC receptors on Human T Cell Proliferation and Survival\u003c/h2\u003e \u003cp\u003eSince all the signalling pathways analysed were related to proliferation and survival, we next examined the proliferation of untransfected and transfected Jurkat cells. First, cell viability was assessed using a WST-1 assay which measures metabolic activity that correlates with the number of viable cells in culture (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003eA). Jurkat, J-OEV1 and J-OEV2 cells exhibited similar viability under untreated conditions, after activation with anti-CD3/anti-CD28 antibodies, and following VIP treatment at 24h and 48h. After 72h, VPAC2 overexpression reduced cell viability independently of VIP treatment.\u003c/p\u003e \u003cp\u003eSecond, cell proliferation was measured using Tag-it Violet labeling. Proliferation of Jurkat cells and cells overexpressing each receptor was comparable across all conditions. Subsequently, proliferation assays were performed under basal conditions, following activation with anti-CD3/anti-CD28 antibodies, and in the presence or absence of VIP (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003eB). In all cases, the same proliferation pattern was observed across the different experimental conditions, with a tendency toward increased proliferation upon overexpression of either receptor, independent of activation of VIP treatment.\u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eContemporary models of GPCR signalling emphasize that receptor function reflects the integration of ligand-dependent activation with receptor-specific basal activity and cellular context. Here, we provide a comparative pharmacological analysis of VPAC1 and VPAC2 in a T-cell model, integrating proximal receptor–G protein coupling with second messenger generation, kinase activation and transcriptional outputs. Our findings indicate that although both receptors are activated by VIP, they impose distinct proximal signalling signatures that are progressively buffered at downstream functional levels.\u003c/p\u003e\u003cp\u003eVPAC receptors have traditionally been classified as prototypical Gαs-coupled GPCRs based on their robust stimulation of cAMP production [\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e]. However, accumulating evidence suggests that class B1 GPCRs can engage multiple G-protein families in a context-dependent manner. Using miniG-BRET biosensors to directly assess receptor–G protein engagement, we demonstrate that VPAC1 exhibits broader coupling flexibility than VPAC2, recruiting Gαs and Gαq robustly and displaying a transient interaction with Gαi. These findings refine previous conclusions based on downstream assays and are consistent with models suggesting that ligand binding stabilizes receptor conformations that determine selective G-protein coupling [\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e49\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe functional translation of these coupling differences was evident at the level of second messengers. Ca²⁺ mobilisation was selectively enhanced in VPAC1-overexpressing cells, consistent with its preferential Gαq. This recruitment has been previously described in several cellular systems and is commonly linked to PLC activation downstream of Gαq [\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e]. Notably, despite this divergence in Ca²⁺ signalling, no amplification of downstream transcriptional or proliferative responses was observed. As emphasized in the GPCR literature, biased signalling reflects both receptor properties and the cellular system in which signalling occurs [\u003cspan class=\"CitationRef\"\u003e50\u003c/span\u003e]. Early differences may be buffered by downstream network integration, and signal persistence depends on the duration of receptor–transducer interactions [\u003cspan class=\"CitationRef\"\u003e51\u003c/span\u003e]. For instance, VPAC1 has been shown to internalize independently of β-arrestins while maintaining endosomal Gs-dependent cAMP signalling, suggesting that β-arrestins contribute to the temporal organization of cAMP responses rather than being strictly required for signal generation. Such mechanisms illustrate how receptor-specific regulatory features can contribute to signalling bias without necessarily producing distinct functional outcomes [\u003cspan class=\"CitationRef\"\u003e52\u003c/span\u003e]. In T cells, where TCR signalling dominates the integration of activation signals, subtype-specific VPAC coupling differences may therefore remain confined to early signalling layers and fail to generate distinct functional outcomes.\u003c/p\u003e\u003cp\u003eBeyond ligand-induced signalling, an additional layer emerged at the basal level. A central observation of this study is that receptor expression alone remodels basal signalling states. Numerous GPCRs exhibit basal or constitutive signalling activity that is independent of ligand engagement, commonly referred to as ligand-free signalling [\u003cspan class=\"CitationRef\"\u003e53\u003c/span\u003e]. In addition, GPCRs can interact with downstream transducers, including heterotrimeric G proteins, in pre-assembled or pre-coupled states prior to ligand binding, described for several GPCRs as PAR1, β2AR, Muscarinic M3R and CB1R [\u003cspan class=\"CitationRef\"\u003e54\u003c/span\u003e–\u003cspan class=\"CitationRef\"\u003e56\u003c/span\u003e]. In this context, changes in receptor abundance, such as those resulting from receptor overexpression, may promote basal signalling gain through these mechanisms. A case in point is that elevated expression of GPR35 is sufficient to induce functionally relevant ligand-free signalling [\u003cspan class=\"CitationRef\"\u003e57\u003c/span\u003e]. In our model, overexpression of either VPAC subtype increased phosphorylation of Src family kinases and MAPK components, together with kinases associated with metabolic regulation such as AKT and PRAS40. These findings are consistent with tonic signalling phenomena described in T cells, where basal phosphorylation contributes to a poised state even in the absence of antigenic stimulation [\u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAt the transcriptional level, however, a distinct pattern emerged. Interestingly, this enhanced basal kinase activity coexisted with reduced basal expression of canonical effector genes, including IL2, IL4 and IFNG. Rather than reflecting a simple linear relationship between kinase activation and transcription, this dissociation likely illustrates the complexity of signal integration in T cells. Jurkat cells establish both autocrine and paracrine feedback loops, including cytokines and immunomodulatory metabolites, which can influence transcriptional outputs [\u003cspan class=\"CitationRef\"\u003e59\u003c/span\u003e]. In addition, basal signalling history is known to recalibrate responsiveness, as illustrated during thymocyte selection, primary T cell activation or T cell differentiation [\u003cspan class=\"CitationRef\"\u003e60\u003c/span\u003e]. In Naïve T cells, strong tonic TCR signals maintain quiescence and restrain effector activation, while constitutive mTORC1 activity shapes baseline translation without driving differentiation [\u003cspan class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e62\u003c/span\u003e]. By analogy, increased proximal kinase activity in our model may similarly adjust the signalling set point, allowing enhanced basal phosphorylation to coexist with reduced basal effector gene expression until a strong activating stimulus is encountered.\u003c/p\u003e\u003cp\u003eTo determine whether these basal differences persisted under activating conditions, we examined the response to CD3/CD28 co-stimulation, which elicits a robust activation programme in Jurkat cells. This response is accompanied by a broad phosphorylation profile consistent with classical TCR-associated pathways and culminates in the coordinated induction of effector-related genes across all conditions, underscoring the integrity of the core TCR signalling [\u003cspan class=\"CitationRef\"\u003e63\u003c/span\u003e]. Within this framework, VIP did not substantially modify activation-induced transcriptional programme. However, the tendency toward increased IL2 expression (together with a similar, non-significant trend for IL10) suggests that VIP signalling may selectively influence specific components of the activation response. The concurrent modulation of these mediators is consistent with the established immunomodulatory and anti-inflammatory role of VIP, whose impact depends on cellular context, activation state, and signalling thresholds [\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e]. Thus, the VIP/VPAC axis mainly adjusts basal signalling tone, while activation-dependent transcription remains constrained by dominant TCR-driven integration.\u003c/p\u003e\u003cp\u003eGiven the observed changes in kinase pathways linked to metabolic regulation, we next assessed cellular metabolic activity. Our results indicate a receptor subtype-specific modulation of redox metabolism, with J-OEV2 cells exhibiting a reduced basal redox output after three days in culture, both under resting conditions and upon stimulation. This profile is observed in parallel with increased phosphorylation of kinases involved in metabolic regulation and stress adaptation, including AKT and PRAS40 [\u003cspan class=\"CitationRef\"\u003e64\u003c/span\u003e]. Notably, this phenotype emerges only after prolonged culture, consistent with progressive changes in static culture microenvironments, such as nutrient depletion and altered oxygen availability, which influence cellular redox balance over time [\u003cspan class=\"CitationRef\"\u003e65\u003c/span\u003e]. In parallel, Tag-it proliferation tracking revealed only a slightly, non-significant increase in cell division in both J-OEV1 and J-OEV2 populations, indicating that the observed metabolic changes reflect an adjustment of basal metabolic tone rather than altered proliferative capacity.\u003c/p\u003e\u003cp\u003eWhile these findings provide mechanistic insight, several limitations should be acknowledged. Receptor overexpression was used to resolve subtype-specific signalling, which may enhance basal signalling beyond physiological receptor expression levels. Jurkat cells, although a widely used T-cell model, are transformed and genomically heterogeneous, limiting direct extrapolation to primary CD4⁺ T cells. In addition, receptor–G protein coupling was assessed using miniG BRET biosensors in HEK293 cells, a heterologous system that allows robust analysis of proximal interactions but does not fully capture the T-cell signalling environment. Consequently, while the coupling profiles likely reflect intrinsic receptor properties, their quantitative impact on downstream signalling may depend on cell-type specific factors.\u003c/p\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eThis study presents a comparative pharmacological analysis of VPAC1 and VPAC2 signalling in a T-cell model. We identify reproducible subtype-specific differences in proximal G-protein coupling and basal signalling that are largely buffered at the transcriptional level under dominant TCR stimulation. These findings indicate that VPAC receptors primarily modulate basal immune tone rather than directly governing T-cell activation, which may be relevant for strategies that aim to fine-tune immune responses without broadly suppressing T-cell function.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eThe authors have no relevant financial or non-financial interests to disclose\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: This work was supported by grants RD21/0002/004 and RD24/0007/0014 from the Ministerio de Econom\u0026iacute;a y Competitividad (Instituto de Salud Carlos III) and co‐funded by European regional development fund (ERDF), as well as by UCM grants PR12/24-31572 and PR12/24-31568, and Comunidad de Madrid grant PR17/24-31935. This work was also supported by CNRS (Centre National de la Recherche Scientifique) and FEDER (Fonds Europ\u0026eacute;en de D\u0026eacute;veloppement R\u0026eacute;gional) through the GioMab project, and by the EMBO Fellowship Programme (STF 8993).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions:\u0026nbsp;\u003c/strong\u003eRVR, IGC and YJ conceptualized the study. IGC, RVR, ACM and SML developed the methodology. ACM, RVR, IGC, PAC, KT, SPG and CE performed the investigation. ACM, DCV and RVR conducted formal analysis. YJ, IGC, RVR, SML and CM supervised the project. RVR, IGC, YJ and ACM wrote the original draft of the manuscript. PAC, DCV, KT, SPG, CM, CE and SML contributed to writing, review and editing. YJ, CM, SPG and RVR acquired funding. All authors reviewed and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eWe acknowledge the support of the CAI of Biological Techniques of the Complutense University of Madrid (UCM), particularly the Genomics Unit.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; information (optional)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eORCID CODES:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAlicia Cabrera-Mart\u0026iacute;n:\u0026nbsp;\u003c/strong\u003e0000-0001-5697-6967\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePaula Arribas-Casta\u0026ntilde;o:\u0026nbsp;\u003c/strong\u003e0009-0006-6390-6952\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDavid Castro-V\u0026aacute;zquez:\u003c/strong\u003e 0000-0003-2446-5075\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKarolina Tecza:\u0026nbsp;\u003c/strong\u003e0009-0003-1660-1222\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSelene P\u0026eacute;rez-Garc\u0026iacute;a:\u003c/strong\u003e 0000-0002-4500-8132\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCarmen Mart\u0026iacute;nez:\u0026nbsp;\u003c/strong\u003e0000-0003-3541-0571\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eChayma El Kamlichi\u0026nbsp;:\u003c/strong\u003e 0000-0003-4796-8169\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eS\u0026eacute;verine Morisset-L\u0026oacute;pez :\u003c/strong\u003e 0000-0002-9930-7824\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eYasmina Juarranz:\u0026nbsp;\u003c/strong\u003e0000-0001-5886-8273\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIrene Guti\u0026eacute;rrez-Ca\u0026ntilde;as:\u003c/strong\u003e 0000-0003-0678-3619\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRa\u0026uacute;l Villanueva-Romero:\u003c/strong\u003e 0000-0002-9001-2413\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHarmar AJ, Fahrenkrug J, Gozes I, Laburthe M, May V, Pisegna JR, Vaudry D, Vaudry H, Waschek JA, Said SI. 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Int J Mol Sci. 2023;24(3):2717. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijms24032717\u003c/span\u003e\u003cspan address=\"10.3390/ijms24032717\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cell-and-bioscience","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cbio","sideBox":"Learn more about [Cell \u0026 Bioscience](http://cellandbioscience.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/cbio/default.aspx","title":"Cell \u0026 Bioscience","twitterHandle":"@OACellBiology","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Vasoactive Intestinal Peptide (VIP), VPAC receptors, GPCR, signalling pathways, inflammatory mediators, Jurkat T cell","lastPublishedDoi":"10.21203/rs.3.rs-9247309/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9247309/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eVasoactive Intestinal Peptide (VIP) is a pleiotropic neuropeptide regulating diverse cellular and physiological processes. Its functions are primarily mediated through two G protein\u0026ndash;coupled receptors, VPAC1 and VPAC2. The aim of this study was to perform an integrative analysis of VPAC receptor signalling, encompassing receptor\u0026ndash;G protein coupling, second messenger production, kinase activation and transcriptional responses in T cells.\u003c/p\u003e\u003ch2\u003eExperimental Approach\u003c/h2\u003e \u003cp\u003e: Receptor interactions with Gα subunits were analysed using BRET assays. Stable Jurkat T-cell lines overexpressing VPAC1 (J-OEV1) or VPAC2 (J-OEV2) were generated. VPAC-dependent intracellular signalling in these cells was assessed by measuring cAMP and Ca\u0026sup2;⁺ levels, performing phospho-kinase arrays and Western blot analyses, and evaluating immune mediator expression, cell viability, and proliferation.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eVPAC1 showed interaction with both Gαs and Gαq subunits, whereas VPAC2 preferentially interacted with Gαs. In Jurkat cells, both receptors overexpression enhanced cAMP signalling, while increased Ca\u0026sup2;⁺ responses were restricted to VPAC1. In both J-OEV1 and J-OEV2 cells, VIP treatment reduced phosphorylation of inflammatory kinase-associated proteins. Overexpression of either receptor induced distinct basal transcriptional profiles of transcription factors and cytokines, which were further modulated by CD3/CD28-activation and VIP. While proliferation was not altered with overexpression, J-OEV2 showed a reduced redox metabolism at 72h.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis study aimed to identify functional differences between VPAC1 and VPAC2 signalling and reveals reproducible subtype-specific differences at early signalling. In Jurkat cells, both receptors induce a shift in its basal state; however, changes do not persist during TCR-driven activation, resulting in largely convergent effector responses.\u003c/p\u003e","manuscriptTitle":"Finding functional gaps: integrative analysis of VPAC1- and VPAC2-mediated signalling pathways in human lymphocytes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-08 06:17:15","doi":"10.21203/rs.3.rs-9247309/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-06T09:59:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"83922960536030488893079303484321459406","date":"2026-04-29T10:16:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"310685357717529505362984255602816158097","date":"2026-04-28T21:06:13+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-28T16:57:02+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-31T18:30:16+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-31T18:29:29+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cell \u0026 Bioscience","date":"2026-03-27T17:30:46+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cell-and-bioscience","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cbio","sideBox":"Learn more about [Cell \u0026 Bioscience](http://cellandbioscience.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/cbio/default.aspx","title":"Cell \u0026 Bioscience","twitterHandle":"@OACellBiology","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8ea259b2-1d77-464e-bef5-4d3737ed9f33","owner":[],"postedDate":"May 8th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-06T09:59:09+00:00","index":21,"fulltext":""},{"type":"reviewerAgreed","content":"83922960536030488893079303484321459406","date":"2026-04-29T10:16:43+00:00","index":18,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-08T06:17:15+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-08 06:17:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9247309","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9247309","identity":"rs-9247309","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}