Proteomic profiling of the serological response to a chemically-inactivated nodavirus vaccine in European sea bass Dicentrarchus labrax

Proteomic profiling of the serological response to a chemically-inactivated nodavirus vaccine in European sea bass Dicentrarchus labrax | 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 Proteomic profiling of the serological response to a chemically-inactivated nodavirus vaccine in European sea bass Dicentrarchus labrax Nadia Chérif, Kais Ghedira, Houda Agrebi, Semah Najahi, Hiba Mejri, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5584738/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Analysing animal responses to immunization is pivotal in vaccine development by evaluating immune response, assessing vaccine safety and efficacy, and providing crucial insights into immune protection mechanisms. These insights are indispensable for advancing vaccines through trial stages and regulatory approval processes, as well as deciphering the molecular signatures of approved vaccines, which not only enhances our understanding of existing vaccines but also informs the rational design of new ones. This study aims to elucidate alterations in protein abundance patterns in the sera of European sea bass, Dicentrarchus labrax , following immunization with a chemically-inactivated nodavirus vaccine. The shotgun proteome comparison revealed that in vaccinated animals, compared to controls, there is a modulation of the redox balance favouring reactive oxygen species, an intricate interplay between coagulation and the immune system resulting in the under-abundance of hematopoiesis-related FLT3, and indications of functional adaptive immunity demonstrated by the under-abundance of pentraxin fusion protein-like and the over-abundance of myosins. To the best of our knowledge, this study represents the inaugural investigation of the immune response in fish using a proteomics approach, employing D. labrax as the host and nodavirus as the pathogen used for vaccination and challenge. Vaccine Development Adaptive immunity markers coagulation-immune interplay Dicentrarchus labrax hematopoiesis-related FLT3 nodavirus proteomic analysis reactive oxygen species sea bass immunization. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Highlights Modulation of redox balance in favour of reactive oxygen species. Interplay between coagulation and the immune system in favour of under-abundance of haematopoiesis-related FLT3. Functional adaptive immunity and insignificant alterations in immunoglobulin and complement protein levels. Introduction Viruses belonging to the Nodaviridae family, genus Betanodavirus , are non-enveloped single strand positive RNA viruses characterized by an extremely high resistance to chemical and physical agents [ 1 ]. Betanodavirus is a highly pathogenic virus able to evade the host’s protective systems and can either replicate and transmit progeny to other cells or remain latent. Betanodavirus is one of the most significant viral pathogens of finfish and represents a crucial bottleneck for development of mariculture in several countries [ 2 ]. Sea bass ( Dicentrarchus labrax ) is exposed to various pathogens during its life production cycle. One of these is red-spotted grouper nervous necrosis virus (RGNNV), which causes viral nervous necrosis (VNN) or viral encephalo- and retinopathy (VER). All stages of sea bass are highly sensitive to Betanodavirus but mortality can vary depending on the age and water temperature reaching mortalities up to 100% in larvae [ 3 ]. Infected fish often show flexing of the body, muscle tremors and abnormal swimming behaviour, which includes vertical positioning and spinning resulting from traumatic lesions [ 4 ]. Betanodavirus also causes hyperinflation of the swim bladder, with diseased fish present primarily at the surface. In adults, where the mortality rate can reach 50–60%, the most common clinical sign is abnormal swimming [ 5 ]. To date, the most common preventive strategies regarding husbandry and NNV-free brood stock selection appear to be inefficient at avoiding NNV outbreaks on fish farms due to the stability of the virus in the aquatic environment [ 1 , 6 ]. Therefore, vaccination remains the only cost-effective, innocuous, and sustainable strategy available to prevent NNV infections and severe disease episodes. Different strategies have been followed to design NNV vaccines tested in the laboratory and in the field such as inactivated virus, recombinant proteins, virus-like particles and DNA based vaccines, and their efficacy, based on relative percentage survival, has ranged from medium to high levels of protection to little or no protection [ 7 – 10 ]. It is also worth mentioning that at present, two commercial inactivated (formalin-killed) vaccines against the RGNNV genotype, Alpha ject micro 1Noda (Pharmaq) and Icthiovac VNN (Hipra) are available for sea bass vaccination in the Mediterranean marketplace. These vaccines were based on chemically inactivated viruses and were formulated with either a mineral or nonmineral oil adjuvant to enhance the immune response. Assessing immunogenicity and inflammatory responses is pivotal for vaccine quality evaluation. In contrast to infections, vaccine-induced inflammatory reactions need to be regulated to an acceptable level while promoting immune cell activation. Consequently, the comprehensive assessment of adaptive responses, particularly humoral and complement responses, along with innate immunity, constitutes a fundamental objective in the field of systems vaccinology [ 11 ]. Usually, the induced immune response is characterized through the detection of NNV reactive antibodies in the serum of vaccinated fish and by gene expression analysis of important immune genes in various tissues from vaccinated fish [ 12 ]. While plausible reasons for modulating the immune response are known or suspected, identification of markers of vaccine efficacy are still an area of active investigation. Several studies examined blood samples from vaccine recipients demonstrating that NNV infection in fish provokes a host immune response which is mediated by innate and adaptative response [ 13 , 14 ]. For example, an increase in the expression of T-cell marker genes (TRCb, CD4-2, CD4, CD8a, CB8b, Lck, NCCRP-1 and ZAP-70) has been reported in infected Atlantic halibut, European sea bass and gilthead sea bream [ 15 , 16 ]. More recently, the transcriptome analyses of different cell lines susceptible to NNV have provided useful information about the immune response elicited against viral infection. In SSN-1 cells infected with a RGNNV strain, the down-regulation of 1138 genes and the up-regulation of 2073 involved in different pathways related to viral pathogenesis was observed [ 17 ]. While few previous studies have investigated fish immune responses using a proteomics approach, none have specifically focused on D. labrax as the host species and nodavirus as the pathogen used for vaccination and challenge [ 18 ]. Interestingly, shotgun proteomics based on high-resolution tandem mass spectrometry can be efficiently performed on fishes based on database constructed with reference annotated genomes or closely related annotated genomes [ 19 , 20 ]. In order to expand our knowledge on D. labrax response to vaccination and capture novel biomarkers compared to those traditionally found by highly used conventional inflammatory panels impacting vaccine efficacy, we examined the abundance profiles of serum proteins from specimens recipient of a chemically-inactivated RGNNV vaccine using mass spectrometry-based proteomics and compared them to control specimens. Material and Methods Sample collection and on-chip protein electrophoresis Samples were obtained from European sea bass ( D. labrax ) farm performing a vaccination campaign against nodavirus in 2021. The local private hatchery (Tunisia) utilized a commercially available vaccine that was chemically inactivated and administered via intraperitoneal injection at the recommended dose. Blood samples were collected from the tail vein, allowed to clot at room temperature for 2 hours, and then centrifuged at 5,000 × g for 10 minutes to isolate the serum. This procedure was performed for two distinct cohorts. Following vaccination procedure, we analysed vaccinated fish specimens (n = 6), weighting at the mean of 40 g ± 2g after 37 days post vaccination (dpv), and control sera (n = 6) were obtained from unvaccinated specimens belonging to the same production cycle. Blood tubes were kept at + 4°C, centrifuged at 4000 × g for 10 min then blood sera were aliquoted 20 µL/tube) and stored at − 80°C for further analysis. The on-chip serum protein analysis was performed on the 2100 Bioanalyzer using Protein 80 kit, according to the guide instructions (Agilent Technologies). Fish serum samples (4 µl) were prepared in the presence of β-mercaptoethanol agent and directly analysed on the 2100 Bioanalyzer. Proteins migrate according to their molecular weights. Total protein concentration in serum was quantified using Bradford Assay with Bovine Serum Albumin (BSA) as standard protein. Briefly, diluted (1/10) serums were added to 96 well polystyrene plates (Nunc Maxi Sorb) in the presence of the Bradford reagent and incubated in darkness for 30 min, RT°C. Optical density (OD) was read at 595 nm. Serum levels were recorded as mg/mL (mean ± SD). This study was conducted in strict accordance with ethical standards for animal research. Specifically, the research (1) adhered to the guidelines outlined in the guide for the care and use of laboratory animals [ 21 ] and the guide to define and implement protocols for the welfare assessment of laboratory animals [ 22 ], and (2) complied with Directive 2010/63/EU on animal welfare, particularly articles 26 and 30. Efforts were made to minimize any potential distress to the animals, in accordance with articles 15 and 39 of the directive [ 23 ]. Ethical clearance was obtained from the National School of Veterinary Medicine of Tunis Ethics Committee. Proteome sample preparation and tandem mass spectrometry Twenty µL of serum (proteins) were dissolved in 25 µL of LDS buffer (26.5 mM Tris HCl, 35.25 mM Tris base, 0.5% LDS, 2.5% Glycerol, 0.13 mM EDTA, supplemented with 5% beta-mercaptoethanol). Samples were heated for 5 min at 99°C in a thermomixer (Eppendorf). For each sample, a volume of 20 µL (10 µg of proteins) was subjected to 5 min of denaturing electrophoresis on a NuPAGE 4–12% gradient gel with MES SDS as running buffer (50 mM MES (2-(N-morpholino) ethane sulfonic acid), 50 mM Tris Base, 0.1% SDS, 1 mM EDTA, pH 7.3). After electrophoresis, the gel was briefly washed with MilliQ water, and stained with SimplyBlue SafeStain (Thermo) for 5 min for visualizing proteins, then washed extensively with MilliQ water. Each proteome was extracted as a single polyacrylamide band of approximately 100 µL in volume. Each sample was subsequently processed as previously described (Rubiano-Labrador et al., 2014) and proteolyzed with trypsin Gold (Promega) in 50 mM NH4HCO3 in presence of ProteaseMax™ detergent (Promega). A volume of 10 µL of the resulting peptide mixture (45 µL) was injected in a nanoscale C18 PepMap100 capillary column (2 µm, 100 Å, 75 µm internal diameter × 50 cm length, LC Packings) mounted with a desalting pre-column and resolved with a 95-min gradient of acetonitrile (5–25% in 90 min followed by 25–40% in 5 min), 0.1% formic acid, at a flow rate of 0.25 µL/min. The peptides resolved by reverse phase chromatography with a NeoVanquish instrument (Thermo) were analyzed by tandem mass spectrometry with an Exploris 480 mass spectrometer (Thermo) connected directly to the column exit. The instrument was operated in data-dependent acquisition mode, with full scan of peptide ions acquired at a resolution of 120,000 from m/z 350 to 1500 and with a dynamic exclusion of 10 sec. Each MS scan was followed by high-energy collisional dissociation and MS/MS scans at a resolution of 15,000 on the 20 most abundant precursor ions identified within the full scan, selecting only ions with charge 2 + or 3+. Interpretation of MS/MS spectra was performed with the Mascot search engine, version 2.6.1 (Matrix Science) against the D. labrax protein sequence database as annotated in the GCF_905237075 genome assembly deposited in the NCBI repository on April 24, 2021 [ 24 ]. Proteins were confidently validated when detecting at least 2 peptides of different sequences, one being specific (unambiguous in the whole D. labrax database). Proteins were quantified based on their spectral counts. The normalized spectral abundance factor (NSAF) was calculated by dividing the spectral count for each observed protein by the polypeptide theoretical mass, as described previously [ 25 ] and is presented as a percentage of the NSAF sum considering all proteins. Proteome comparison between both conditions was done taking into account all the biological replicates based on standard normalisation with Tfold and t -test calculations, as previously described [ 26 ]. In this investigation, Tfold values were delineated from the locus tags using parentheses and commas, followed by the respective statistical class, unless specified otherwise. The blue class denotes identifications meeting both Tfold (> 1.5 or < − 1.5) and statistical ( p -value < 0.05) criteria. The orange class comprises identifications not meeting the fold criterion but warrant further scrutiny due to low p -values. The green class signifies identifications satisfying the fold criteria, possibly by chance, while the red class includes identifications not meeting both fold and p -value criteria. Differences were considered statistically significant for a p -value of less than 0.05 and statistically highly significant as a p ‐value < 0.001. Additional biological triplicates also allow for a quantitative assessment of differences between two conditions (non-vaccinated and vaccinated fish). Sequence similarity-based functional analysis Protein sequences belonging to the Blue Class proteins (eight proteins) were uploaded into Blast2GO tool [ 27 ]. Mapping against Swissprot, Uniprot database was performed using BLAST for protein annotation and GO mapping. Domains of proteins were predicted using the Simple Modular Architecture Research Tool (SMART) [ 28 ]. Orthologs were identified using the BLAST + tool suite through Galaxy [ 29 , 30 ]. Protein-protein interaction network The sequences corresponding to the eight proteins of D. labrax belonging to the PatternLab blue class (for which identifications satisfied both the fold (> 1.5) and statistical criteria ( p -value < 0.05)) were extracted and saved in a distinct multi-FASTA file. This file was then uploaded into the STRING database [ 31 ] and Danio rerio was chosen as a query microorganism. A total of eight hits with 100% identity were detected and their protein-protein interactions were predicted. Functional analysis and the identification of enriched biological processes and pathways was performed based on protein sequences. Results and Discussion In this study, we undertook a comprehensive exploration of the proteome landscape in fish, comparing the blood serum proteomes of unvaccinated and vaccinated D. labrax individuals. The choice of a 37-day sampling point in this study aligns with previous findings [ 32 , 33 ], aiming to capture a potentially sustained immune response. First, ten across 12 samples biochip-based electrophoretic profiles of total blood serum proteins (non-vaccinated S1–S6 and vaccinated sera S7–S10) were qualified and analysed. To enable proper comparison, same volume of serum was loaded on the biochip. Protein bands with varying migration time were observed in reduced conditions. Figure 1 .A shows the overlay of the ten different electropherogram traces in the corresponding gel-like image. Protein variations in serum individual samples could be partly attributed to the fish vaccination stress conditions, despite other chemical properties (glycosylation or phosphorylation patterns) that may influence protein interaction with the gel matrix during separation. High-resolution tandem mass spectrometry recorded a total of 951,230 MS/MS spectra that were interpreted against a database comprising the D. labrax annotated protein sequences. The number of peptide-to-spectrum matches, namely 304,176, shows a relatively good match between the analysed samples and the genome of reference, as the ratio of MS/MS spectra assignment is 32%. These assigned spectra enabled the identification of 6,967 distinct peptide sequences, which allowed to identify and label-free quantified 437 proteins (false discovery rate < 1%) across all samples. The mass spectrometry response was relatively homogeneous for all samples with an average of 26,646 (± 7%) spectral counts per sample. As illustrated in Fig. 1 .B, principal component analysis demonstrated that sample S4 (non-vaccinated) stands out as an outlier. Further detailed analysis shows an unusual level of hemoglobins (alpha and beta chains) representing 12.1% of the signal in this sample compared to 3.4% in average for all the other samples. This over-representation of hemoglobins impacted the quantitation of the other proteins. Henceforth, all analyses and data presented herein exclude outlier sample 4, unless explicitly stated otherwise. These analyses identified top protein hits based on fold change in abundances when comparing both fish groups (Table 1 ). Eight proteins showing at least a 50% difference in abundance and a p -value of less than 0.05 (Differential abundant proteins are labeled “blue-class” hereafter) were identified as differentially detected, all at lower abundance in sera from vaccinated compared to unvaccinated fish (Fig. 2 ). In light of the absence of IgG in fish and the predominance of IgM, IgD, and IgT/Z — for Teleost/Zebrafish [ 34 , 35 ], a BLAST-based analysis was conducted on the 437 proteins, resulting in the identification of best hits for IgM (XP_051244807.1 (1.08x, p -value = 0.51, E-value = 2e − 58 to AAK69167.1)), IgD (XP_051244806.1 (1.20x, p -value = 0.24, E-value = 0.0 to BAD34542.1 and AGR34025.1)), IgT/Z (XP_051250463.1 (1.82x, p -value = 0.14, E-value = 0.0 to ASK39431.1)), and immunoglobulin light chains (XP_051243640.1 (1.17x, p -value = 0.58, E-value = 7e − 46 to CAA33375.1), and XP_051243629.1 (− 1.02x, p -value = 0.94, E-value = 8e − 12 to XP_050924250.1)) [ 34 ]. Table 1 Top 10 hits based on fold change. Name Change Tfold p -value Class Description XP_051237425.1 Decreased −3.12 0.04 Blue Catalase XP_051244291.1 Decreased −2.57 0.17 Green Solute carrier family 4 member 1a (Diego blood group) isoform X1 XP_051239863.1 Decreased −2.40 0.00 Blue Peroxiredoxin-2 XP_051275475.1 Increased 2.37 0.06 Green Coagulation factor VIII XP_051244632.1 Decreased −2.28 0.33 Green Pentraxin fusion protein-like XP_051258241.1 Decreased −2.23 0.05 Blue Superoxide dismutase [Cu-Zn] XP_051270211.1 Increased 2.17 0.28 Green Myosin heavy chain, fast skeletal muscle-like XP_051243618.1 Increased 2.14 0.23 Green Myosin heavy chain, skeletal muscle, adult-like XP_051266112.1 Decreased −2.06 0.16 Green Receptor-type tyrosine-protein kinase FLT3 isoform X1 XP_051231594.1 Decreased −2.04 0.01 Blue Antithrombin-III Top protein hits based on fold change in abundances when comparing vaccinated to unvaccinated fish sera groups. Modulation of redox balance in favour of reactive oxygen species (ROS) Proteins like catalase, peroxiredoxin and superoxide dismutase are essential for maintaining the balance of ROS in cells. Of interest here is the strong decrease of the abundance in catalase (XP_051237425.1, − 3.12x, p -value = 0.04). Previously, a study on rainbow trout Oncorhynchus mykiss showed that vaccination against furunculosis led to decreased catalase activities in the muscles and gills of the vaccinated fish [ 36 ], indicating reduced capacity to scavenge hydrogen peroxide. The present results, shown in Table 1 , are in full accordance to these previous results [ 36 ]. The observed reduction in catalase activity within the tissues may be attributed to the generation of superoxide radicals induced by vaccination, during which these radicals can potentially inhibit catalase activity, as suggested by Kono and Fridovich [ 37 ]. Here, the abundance of catalase is shown to be lower after immunization inducing a lower activity, but demonstrating that the balance of synthesis of enzymes and degradation of the produced polypeptides is impacted. However, it is important to note that fish immunized with live theronts of Ichthyophthirius multifiliis showed elevated catalase levels in the liver [ 38 ], indicating also a potential positive influence of vaccination on catalase overabundance in the liver. Peroxiredoxins potentially serve as regulators of inflammation during pathogen infection and play a protective role against cell death, contributing to tissue repair following damage [ 39 , 40 ]. Here, a lower abundance of peroxiredoxin-2 (XP_051239863.1, − 2.40x, p -value = 0.00) is noted in vaccinated fish. This finding is in contradiction to a previous study which has suggested that, following exposure to an inactivated trivalent bacterial vaccine, three members of the peroxiredoxin family exhibited up-regulation [ 41 ]. Additionally, our results showing an under-abundance of superoxide dismutase (XP_051258241.1, − 2.23x, p -value = 0.05) is in contradiction to a prior study that proposed a significant increase in superoxide dismutase activity in head kidney lymphocytes of immunized Chinese breams exposed to an inactivated vaccine and recombinant Omp38 protein when compared to the control [ 42 ]. Furthermore, Tkachenko et al.'s study demonstrated a significant increase in superoxide dismutase activity within the muscles and liver of vaccinated O. mykiss [ 36 ]. ROS production contributes to elimination of pathogens and induces activation of immune defence mechanisms [ 43 ]. However, excessive ROS formation can induce oxidative stress, leading to cell damage and cell death may follow [ 44 ]. Furthermore, oxidative stress occurs when the critical balance between oxidants and antioxidants is disrupted due to the depletion of antioxidants or excessive accumulation of ROS, or both, which may lead to a series of biochemical and physiological changes, thus, altering normal body homeostasis and tissue injury [ 45 ]. Our results suggest that during an immune response, there could be a temporary shift in the redox balance which might allow for less need of antioxidant enzymes. This down-regulation can occur as a regulatory mechanism to fine-tune the immune response of the vaccinated fish. In this context, it is important to note that the integral involvement of macrophages in specific immune responses arises from their roles in lymphocyte activation and phagocytosis, facilitated by specific β-glucan receptors, leading to immunostimulants-induced increase of leukocytes' respiratory burst and subsequent generation of bactericidal ROS [ 46 , 47 ]. These results indicate that the modulation of the redox balance in favour of ROS represents a significant molecular mechanism linked to the immune response of European sea bass ( D. labrax ) following vaccination with chemically-inactivated nodavirus. Interplay between coagulation and the immune system in favour of lower abundance of haematopoiesis-related FLT3 Our findings (Table 1 ) suggest that vaccinated fish have an up-regulated coagulation factor VIII (XP_051275475.1, 2.37x, p -value > 0.05) and a down-regulated antithrombin-III (XP_051231594.1, − 2.04x, p -value = 0.01) and receptor-type tyrosine-protein kinase FLT3 isoform X1 (XP_051266112.1, − 2.06x, p -value > 0.05). Antithrombin-III functions as a pivotal serine protease inhibitor, contributing significantly to both the coagulation cascade and inflammatory response in fish [ 48 , 49 ]. Drawing upon the literature [ 50 ], the under-abundance of antithrombin-III in vaccinated fish, as identified in this study, is suggesting prevention of inactivating thrombin and activated factors. These findings may be somewhat limited by the prothrombin level (XP_051283059.1, 1.15x, p -value > 0.05) requiring further investigation due to its non-significant fold change and lack of statistical significance. The reduced presence of the FLT3 isoform X1, as indicated in Table 1 , implies that several cytoplasmic effector molecules in pathways involved in apoptosis, proliferation, and differentiation of hematopoietic B-cell progenitors, myelomonocytic and dendritic cells, and pluripotent hematopoietic stem cells, may not undergo phosphorylation and consequently remain inactive [ 51 ]. Moreover, in an earlier investigation of the Yersinia ruckeri infection process in rainbow trout, proteome analysis unveiled the involvement of several proteins involved in the blood coagulation pathway [ 52 ]. We also found lower abundance of a solute carrier family 4 member 1A (SLC4A1, XP_051244291.1, − 2.57, p -value = 0.17) but this result was not validated statistically and should be taken cautiously. This protein is an important player found in red blood cells promoting the reversible exchange of bicarbonate ion for chloride ion and facilitating the efflux of osmolytes, including KCl and amino acids, a mechanism that is crucial in pH and cell volume regulation [ 53 – 55 ]. Hence, it could conceivably be hypothesised that the lower abundance of SLC4A1 is related to the conversion of prothrombin to its active form by the prothrombinase complex, comprising activated Factor X and Factor V in the presence of ions [56]. Previous studies indicated that coagulation, pathogen opsonization, recognition through pattern-recognition receptors, and cytokine-mediated inflammation collectively constitute the fundamental pillars of innate immunity of fish ([57] and references therein). Our results are aligned with these studies, thus confirming that the interconnection between blood clotting and the immune response is essential in safeguarding against microbial invasion, where clot formation functions to restrict pathogen dissemination, while immune cells actively strive to eradicate the infection. Certain clotting factors, in addition to their involvement in coagulation, exhibit immunomodulatory functions; for instance, thrombin, a pivotal component in the coagulation cascade, can impact inflammation by activating immune cells and regulating cytokine production [56]. Functional adaptive immunity and insignificant alterations in complement protein levels In addition to the modulation of the redox balance and the dynamic interaction between coagulation and the immune system, the findings presented in this work underscore the significance of host defence, inflammatory responses, and pathogen recognition. Pentraxins, constituting fluid phase pattern recognition molecules and demonstrating conservation across both fish and humans, play a crucial role in the innate immune defence [58]. These molecules represent a family of evolutionarily conserved proteins with diverse roles in host defence, encompassing their participation in inflammatory responses and pathogen recognition [59]. Pentraxins in fish have been identified in skin mucus, playing a pivotal role as the initial defence line against pathogens and external stressors [59]. Earlier findings proposed that short pentraxins exhibit heightened reactivity against viruses in the skin, and their overexpression appears to represent a compensatory mechanism for the diminished adaptive immunity [60]. Consequently, the observed lower abundance of pentraxin fusion protein-like (XP_051244632.1, − 2.28x, p -value > 0.05) in this study suggests a functional adaptive immunity in vaccinated fish. Moreover, the over-abundance of the myosin heavy chain, fast skeletal muscle-like (XP_051270211.1, 2.17x, p -value > 0.05) and the myosin heavy chain, skeletal muscle, adult-like (XP_051243618.1, 2.14x, p -value > 0.5) was observed. Myosins facilitate diverse cellular activities, encompassing muscle contraction, cell migration, intracellular transport, cell adhesion, and cell signalling [61]. Our findings are concordant with previous research indicating that, in immune cells, class I myosins are involved in the formation and maintenance of immunological synapse-related signalling [62]. Also, our results corroborate the previous findings suggesting that myosin-9 potentially enhances the immune response to Vibrio alginolyticus by positively influencing the phagocytosis rate of haemocytes [63]. For instance, to orchestrate an effective adaptive immune response, particularly involving T cells, the ability of leukocytes to migrate between the blood, secondary lymphoid organs, and sites of injury or infection is essential. The motility of T lymphocytes is intricately governed by the spatial distribution of specific proteins, including integrins. Notably, Mhc9 (class II myosin) has been identified as interacting with such molecules in crawling T cells. Beyond its role in regulating T cell motility, Mhc9, a highly versatile molecule, has also been implicated in various other immune processes, notably the formation of the immune synapse, a pivotal event in the adaptive immune response ([64] and references therein). In fish, within the realm of humoral components constituting innate immunity, the complement system comprises roughly 30 inactive circulating proteins alongside membrane-bound receptors ([65] and citations therein). Our study identified levels of 30 complement proteins (Supplementary Table S1), among which no significant difference in fold change nor statistical significance were observed. Notwithstanding, complement component 7b (XP_051267608.1) displayed a Tfold value of 1.63, indicative of a moderate increase in abundance, albeit without reaching statistical significance ( p -value = 0.16). Although these data must be interpreted with caution, it could conceivably be hypothesised, based on our overall observations, that the vaccinated host is in a stage of "adaptive immunity" rather than "innate immunity", as discussed in a prior review [65]. Differentially abundant proteins As illustrated in Fig. 3 , eight proteins were identified as differentially abundant proteins with stringent statistical validation ( p -value below 0.05). All exhibited lower abundance in vaccinated animals compared to unvaccinated: catalase (XP_051237425.1, − 5.30x), peroxiredoxin-2 (XP_051239863.1, − 4.19x), superoxide dismutase (XP_051258241.1, − 2.86x), antithrombin-III (XP_051231594.1, − 1.81x), tubulin beta-1 chain (XP_051270361.1, − 3.53x), carbonic anhydrase (XP_051267911.1, − 2.52x), thyroglobulin (XP_051255191.1, − 1.56x), and E-selectin (XP_051233011.1, − 1.48x). Among the most enriched biological processes linked to differentially abundant proteins (Tfold > 1.5 or < − 1.5 and p -value ≤ 0.05), as indicated in Fig. 4 , we found ROS metabolic process (GO:0072593), response to ROS (GO:0000302), removal of superoxide radicals (GO:0019430), cellular oxidant detoxification (GO:0098869), and response to inorganic substance (GO:0010035). The protein-protein interaction network of the aforementioned differentially abundant proteins confirms interactions among three proteins (Fig. 5 ). Additionally, GOChord plots of orange, green, and red-class proteins are presented in Supplementary Figure S1 (A, B, and C, respectively), with their interactions depicted in Supplementary Figure S2 (A, B, and C, respectively). In contrast to the COGs of orange, green, and red-class proteins shown in Supplementary Figure S3 (A, B, and C, respectively), all COGs of the blue-class proteins (Fig. 6 ) exclusively comprised under-abundant proteins, including the COG V (defence mechanisms). This observation aligns with findings in the literature [65] and with our previous observations, indicating that the vaccinated host is in a stage of "pathogen clearance" rather than "pathogen intrusion". Conclusion Our findings provide crucial insights into the molecular dynamics underpinning the vaccination process in fish. Some of these results should be further confirmed with larger cohort of animals, but the comparison of non-vaccinated and vaccinated groups and the subsequent identification of under- and over-abundant proteins, such as catalase, peroxiredoxin-2, and coagulation factor VIII, among others, unveils potential markers of immune modulation and sheds light on the biological processes influenced by vaccination. In essence, our study elucidates potential molecular mechanisms linked to both the immune response and the efficacy of chemically-inactivated vaccines. Declarations Acknowledgements We gratefully acknowledge the financial support provided by the Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture through the IAEA CRP 2296 (Project code: D3.20.37). This research was conducted under Contract Number 26187 (Immune2AquaVac-ir). Data availability statement The data that support the findings of this study are available in PRIDE at http://doi.org/10.6019/PXD051099. All mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository under the dataset identifiers PXD051099 and 10.6019/ PXD051099. Competing interests The authors declare no competing interests associated with the research presented in this article. No financial or non-financial conflicts of interest, including employment, consultancies, honoraria, stock ownership, or any other competing relationships, influenced the design, execution, or interpretation of the study. This work was conducted with scientific integrity, and the authors have no affiliations or involvements that may be perceived as biasing the content or outcomes of this research. Ethical statement All the animal handling and experimental procedures were approved by the National School of Veterinary Medicine of Tunis Ethics Committee — Approval Number: CEEA-ENMV 85/24. Authors' contributions Conceptualization, experimental design, HS, BBZ, NC, JA; in vivo and in vitro experiments, NC, HA; biochemical analyses, BBZ, SN; mass spectrometry experiments, MK; proteomics data analysis, JA, HS; bioinformatic analyses, KG, HS; original draft preparation, NC, HS; editing of the manuscript, KG, JA, RTK, VW, BBZ, coordination of financial and technical support, HS, RTK, VW. All authors read and approved the final manuscript. References I. Bandín, S. Souto, Betanodavirus and VER Disease: A 30-year Research Review, Pathogens (Basel, Switzerland), 9 (2020). A. Toffan, F. Pascoli, T. Pretto, V. Panzarin, M. Abbadi, A. Buratin, R. Quartesan, D. Gijón, F. Padrós, Viral nervous necrosis in gilthead sea bream ( Sparus aurata ) caused by reassortant betanodavirus RGNNV/SJNNV: an emerging threat for Mediterranean aquaculture, Sci Rep, 7 (2017) 46755. A. Toffan, V. Panzarin, M. Toson, K. Cecchettin, F. 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Zhu, The role of Astakine in Scylla paramamosain against Vibrio alginolyticus and white spot syndrome virus infection, Fish & shellfish immunology, 98 (2020) 236–244. J.L. Maravillas-Montero, L. Santos-Argumedo, The myosin family: unconventional roles of actin-dependent molecular motors in immune cells, Journal of leukocyte biology, 91 (2012) 35–46. M.E. Natnan, C.-F. Low, C.-M. Chong, H. Bunawan, S.N. Baharum, Integration of Omics Tools for Understanding the Fish Immune Response Due to Microbial Challenge, 8 (2021). Additional Declarations The authors declare no competing interests. Supplementary Files CIREP2024CherifetalSupplementaryData.docx Supplementary data Supplementary Figure S1.A. GOChord plot showing assignment of orange-class proteins to their most enriched biological processes. Orange-class proteins from the European sea bass (on the left) are linked to enriched GO terms (on the right) by chords. Coloured rectangles denote fold change. Supplementary Figure S1.B. GOChord plot showing assignment of green-class proteins to their most enriched biological processes. Green-class proteins from the European sea bass (on the left) are linked to enriched GO terms (on the right) by chords. Coloured rectangles denote fold change. Supplementary Figure S1.C. GOChord plot showing assignment of red-class proteins to their most enriched biological processes. Red-class proteins from the European sea bass (on the left) are linked to enriched GO terms (on the right) by chords. Coloured rectangles denote fold change. Supplementary Figure S2.A. Protein-protein interaction (PPI) network of orange-class proteins. Edge widths represent the strength of the interaction, while node colours indicate the fold change. Supplementary Figure S2.B. Protein-protein interaction (PPI) network of green-class proteins. Edge widths represent the strength of the interaction, while node colours indicate the fold change. Supplementary Figure S2.C. Protein-protein interaction (PPI) network of red-class proteins. Edge widths represent the strength of the interaction, while node colours indicate the fold change. Supplementary Figure S3.A. Predicted COG classes of European sea bass orange-class proteins based on a Tfold comparison "vaccinated" versus "non-vaccinated". Over- and under-abundant COG classes in green and indigo colours, respectively. A: RNA processing and modification, B: Chromatin structure and dynamics, C: Energy production and conversion, D: Cell cycle control and mitosis, F: Nucleotide metabolism and transport, I: Lipid metabolism, J: Translation, ribosomal structure and biogenesis, M: Cell wall/membrane/envelope biogenesis, O: Post-translational modification, protein turnover, chaperone functions, P: Inorganic ion transport and metabolism, Q: Secondary metabolites biosynthesis, transport and catabolism, S: Function unknown, T: Signal transduction mechanisms, V: Defence mechanisms, U: Intracellular trafficking, secretion, and vesicular transport, and Z: Cytoskeleton. Supplementary Figure S3.B. Predicted COG classes of European sea bass green-class proteins based on a Tfold comparison "vaccinated" versus "non-vaccinated". Over- and under-abundant COG classes in green and indigo colours, respectively. B: Chromatin structure and dynamics, C: Energy production and conversion, E: Amino acid transport and metabolism, F: Nucleotide metabolism and transport, G: Carbohydrate transport and metabolism, I: Lipid metabolism, K: Transcription, L: Replication, recombination and repair, O: Post-translational modification, protein turnover, chaperone functions, M: Cell wall/membrane/envelope biogenesis, W: Extracellular structures, P: Inorganic ion transport and metabolism, S: Function unknown, T: Signal transduction mechanisms, V: Defence mechanisms, and Z: Cytoskeleton. Supplementary Figure S3.C. Predicted COG classes of European sea bass red-class proteins based on a Tfold comparison "vaccinated" versus "non-vaccinated". Over- and under-abundant COG classes in green and indigo colours, respectively. A: RNA processing and modification, B: Chromatin structure and dynamics, C: Energy production and conversion, D: Cell cycle control, cell division, chromosome partitioning, E: Amino acid transport and metabolism, F: Nucleotide metabolism and transport, G: Carbohydrate transport and metabolism, I: Lipid metabolism, J: Translation, ribosomal structure and biogenesis, M: Cell wall/membrane/envelope biogenesis, W: Extracellular structures, O: Post-translational modification, protein turnover, chaperone functions, P: Inorganic ion transport and metabolism, Q: Secondary metabolites biosynthesis, transport and catabolism, S: Function unknown, T: Signal transduction mechanisms, V: Defence mechanisms, Z: Cytoskeleton, and U: Intracellular trafficking, secretion, and vesicular transport. Supplementary Table S1. Summary of complement-related proteins identified from the Tfold comparison "vaccinated" versus "non-vaccinated" of Dicentrarchus labrax . 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Sghaier","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABJUlEQVRIie2RMWvCQBiGvyDocuJ6QzF/4UJA23/zHR2yaBGyODgkBHSRZj3I0F9Q6NQ5Rch04JpyRQwO3UpBKE7ipUVq26AdC71nOF6+47nvhQMwGP4gDKyg9hEJAAK0f6OE0aHi6mQF74P6PnxXwPpUNDw4pXQbs8lqMLoHO759eF0OF16cTJ5XA1hcdW+Chg4/uJjyMBKZApa/XFKUfl88SScS4PtnmS4gKoqlWiF1rVDJKB9j/472rIgAcqGLRaRCmRda2SqwhXQ3fIseo15xXMn1luZYAcynHcoDREbROaEUYdK8VoTlpHOOGToi7zkJYaXCw6SymLdckzfVtmPpPm5GaLdEORlqpTZL1xXKHgIUvzxVHpXfckArPX5vMBgM/5cdyt9qXW6n+WcAAAAASUVORK5CYII=","orcid":"","institution":"National Center for Nuclear Sciences and Technology","correspondingAuthor":true,"prefix":"","firstName":"Haitham","middleName":"","lastName":"Sghaier","suffix":""}],"badges":[],"createdAt":"2024-12-05 07:46:15","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":true,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":true},"doi":"10.21203/rs.3.rs-5584738/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5584738/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":70910524,"identity":"4bd681cd-3e94-4f0d-934b-8c1c75e92d79","added_by":"auto","created_at":"2024-12-09 07:19:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":416123,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Electrophoresis profiles and protein chip analysis of serum samples from vaccinated and non-vaccinated fish.\u003c/p\u003e\n\u003cp\u003eElectrophoresis profiles and protein biochip analysis with the Protein 80 kit (Bioanalyzer 2100 Agilent Technologies, Inc.) of the serum samples (4 ml) collected from non-vaccinated (S1–S6) (lines 1–6) and vaccinated fishes (S7–S10) (lines 7–12) (in the presence of reducing agent b-mercaptoethanol). Gel-like image shows differentials in serum protein abondance, recorded from vaccinated and non-vaccinated fishes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(B) PCA analysis of proteins confidently identified by tandem mass spectrometry.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5584738/v1/6b409c8eb80b8ff9ca4d5b15.png"},{"id":70908230,"identity":"011789df-1a36-4929-bf68-e74e3ee35ce4","added_by":"auto","created_at":"2024-12-09 06:55:35","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":75153,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVolcano plot (effect (Tfold) \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eversus\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003esignificance (\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e-value)) based on proteomics data.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5584738/v1/4d37341d3c0351efe442e62f.png"},{"id":70908253,"identity":"20e04880-1573-4be3-befd-eb9693b914ae","added_by":"auto","created_at":"2024-12-09 06:55:36","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":101302,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferential abundant proteins.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Normalized Spectral Abundance Factor (NSAF), enabling to identify the most abundant proteins, is on the right side. XP_051231594.1: antithrombin-III, XP_051233011.1: E-selectin, XP_051237425.1: catalase, XP_051239863.1: peroxiredoxin-2, XP_051255191.1: LOW QUALITY PROTEIN: thyroglobulin, XP_051258241.1: superoxide dismutase [Cu-Zn], XP_051267911.1: carbonic anhydrase, and XP_051270361.1: tubulin beta-1 chain.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5584738/v1/071afc3299571583e5d71e37.jpg"},{"id":70908232,"identity":"dd328c9c-9153-4f77-824c-a13e37b3da5a","added_by":"auto","created_at":"2024-12-09 06:55:35","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":499995,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGOChord plot showing assignment of blue-class proteins to their most enriched biological processes.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDifferentially abundant blue-class proteins from the European sea bass (on the left) are linked to enriched GO terms (on the right) by chords. Coloured rectangles denote fold change. XP_051237425: catalase, XP_051239863: peroxiredoxin-2, and XP_051258241: superoxide dismutase [Cu-Zn].\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5584738/v1/b08ae551ea289563b3f4bfc2.png"},{"id":70908245,"identity":"fcf18330-8ab7-4aef-bb8d-f560c1b5572c","added_by":"auto","created_at":"2024-12-09 06:55:35","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":66278,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProtein-protein interaction (PPI) network of differentially abundant blue-class proteins.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEdge widths represent the strength of the interaction, while node colours indicate the fold change. XP_051237425.1: catalase, XP_051258241.1: superoxide dismutase [Cu-Zn], and XP_051239863.1: peroxiredoxin-2.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5584738/v1/c795347fd65c60af501a6235.png"},{"id":70908806,"identity":"c48d5fcf-db61-4505-a660-601607301141","added_by":"auto","created_at":"2024-12-09 07:03:36","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":56336,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePredicted COG classes of differentially abundant European sea bass blue-class proteins based on a Tfold comparison \"vaccinated\" \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eversus\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e \"non-vaccinated\".\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll COG classes are under-abundant (in indigo colour). I: Lipid transport and metabolism, O: Posttranslational modification, protein turnover, chaperones, P: Inorganic ion transport and metabolism, T: Signal transduction mechanisms, V: Defence mechanisms, and Z: Cytoskeleton.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-5584738/v1/6053d3cf0a5d7e31378e83a5.png"},{"id":70911774,"identity":"3ffc9328-4266-4f2a-a7a2-e8ad3d938afa","added_by":"auto","created_at":"2024-12-09 07:27:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1874356,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5584738/v1/39487190-bfef-4b0a-97f5-62cbea29f368.pdf"},{"id":70908256,"identity":"1fc2b886-1a1f-4782-bd34-e65566e288c9","added_by":"auto","created_at":"2024-12-09 06:55:37","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1907995,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary data\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Figure S1.A. GOChord plot showing assignment of orange-class proteins to their most enriched biological processes.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOrange-class proteins from the European sea bass (on the left) are linked to enriched GO terms (on the right) by chords. Coloured rectangles denote fold change.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Figure S1.B. GOChord plot showing assignment of green-class proteins to their most enriched biological processes.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGreen-class proteins from the European sea bass (on the left) are linked to enriched GO terms (on the right) by chords. Coloured rectangles denote fold change.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Figure S1.C. GOChord plot showing assignment of red-class proteins to their most enriched biological processes.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRed-class proteins from the European sea bass (on the left) are linked to enriched GO terms (on the right) by chords. Coloured rectangles denote fold change.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Figure S2.A. Protein-protein interaction (PPI) network of orange-class proteins.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEdge widths represent the strength of the interaction, while node colours indicate the fold change.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Figure S2.B. Protein-protein interaction (PPI) network of green-class proteins.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEdge widths represent the strength of the interaction, while node colours indicate the fold change.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Figure S2.C. Protein-protein interaction (PPI) network of red-class proteins.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEdge widths represent the strength of the interaction, while node colours indicate the fold change.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Figure S3.A. Predicted COG classes of European sea bass orange-class proteins based on a Tfold comparison \"vaccinated\" \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eversus\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e\"non-vaccinated\".\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOver- and under-abundant COG classes in green and indigo colours, respectively. A: RNA processing and modification, B: Chromatin structure and dynamics, C: Energy production and conversion, D: Cell cycle control and mitosis, F: Nucleotide metabolism and transport, I: Lipid metabolism, J: Translation, ribosomal structure and biogenesis, M: Cell wall/membrane/envelope biogenesis, O: Post-translational modification, protein turnover, chaperone functions, P: Inorganic ion transport and metabolism, Q: Secondary metabolites biosynthesis, transport and catabolism, S: Function unknown, T: Signal transduction mechanisms, V: Defence mechanisms, U: Intracellular trafficking, secretion, and vesicular transport, and Z: Cytoskeleton.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Figure S3.B. Predicted COG classes of European sea bass green-class proteins based on a Tfold comparison \"vaccinated\" \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eversus\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e\"non-vaccinated\".\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOver- and under-abundant COG classes in green and indigo colours, respectively. B: Chromatin structure and dynamics, C: Energy production and conversion, E: Amino acid transport and metabolism, F: Nucleotide metabolism and transport, G: Carbohydrate transport and metabolism, I: Lipid metabolism, K: Transcription, L: Replication, recombination and repair, O: Post-translational modification, protein turnover, chaperone functions, M: Cell wall/membrane/envelope biogenesis, W: Extracellular structures, P: Inorganic ion transport and metabolism, S: Function unknown, T: Signal transduction mechanisms, V: Defence mechanisms, and Z: Cytoskeleton.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Figure S3.C. Predicted COG classes of European sea bass red-class proteins based on a Tfold comparison \"vaccinated\" \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eversus\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e\"non-vaccinated\".\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOver- and under-abundant COG classes in green and indigo colours, respectively. A: RNA processing and modification, B: Chromatin structure and dynamics, C: Energy production and conversion, D: Cell cycle control, cell division, chromosome partitioning, E: Amino acid transport and metabolism, F: Nucleotide metabolism and transport, G: Carbohydrate transport and metabolism, I: Lipid metabolism, J: Translation, ribosomal structure and biogenesis, M: Cell wall/membrane/envelope biogenesis, W: Extracellular structures, O: Post-translational modification, protein turnover, chaperone functions, P: Inorganic ion transport and metabolism, Q: Secondary metabolites biosynthesis, transport and catabolism, S: Function unknown, T: Signal transduction mechanisms, V: Defence mechanisms, Z: Cytoskeleton, and U: Intracellular trafficking, secretion, and vesicular transport.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Table S1. \u003c/strong\u003eSummary of complement-related proteins identified from the Tfold comparison \"vaccinated\" \u003cem\u003eversus\u003c/em\u003e \"non-vaccinated\" of \u003cem\u003eDicentrarchus labrax\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"CIREP2024CherifetalSupplementaryData.docx","url":"https://assets-eu.researchsquare.com/files/rs-5584738/v1/590d1b71bb874eda45a0710d.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eProteomic profiling of the serological response to a chemically-inactivated nodavirus vaccine in European sea bass \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eDicentrarchus labrax\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e","fulltext":[{"header":"Highlights","content":"\u003cul\u003e\n \u003cli\u003eModulation of redox balance in favour of reactive oxygen species.\u003c/li\u003e\n \u003cli\u003eInterplay between coagulation and the immune system in favour of under-abundance of haematopoiesis-related FLT3.\u003c/li\u003e\n \u003cli\u003eFunctional adaptive immunity and insignificant alterations in immunoglobulin and complement protein levels.\u0026nbsp;\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Introduction","content":"\u003cp\u003eViruses belonging to the \u003cem\u003eNodaviridae\u003c/em\u003e family, genus \u003cem\u003eBetanodavirus\u003c/em\u003e, are non-enveloped single strand positive RNA viruses characterized by an extremely high resistance to chemical and physical agents [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. \u003cem\u003eBetanodavirus\u003c/em\u003e is a highly pathogenic virus able to evade the host\u0026rsquo;s protective systems and can either replicate and transmit progeny to other cells or remain latent. \u003cem\u003eBetanodavirus\u003c/em\u003e is one of the most significant viral pathogens of finfish and represents a crucial bottleneck for development of mariculture in several countries [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Sea bass (\u003cem\u003eDicentrarchus labrax\u003c/em\u003e) is exposed to various pathogens during its life production cycle. One of these is red-spotted grouper nervous necrosis virus (RGNNV), which causes viral nervous necrosis (VNN) or viral encephalo- and retinopathy (VER). All stages of sea bass are highly sensitive to \u003cem\u003eBetanodavirus\u003c/em\u003e but mortality can vary depending on the age and water temperature reaching mortalities up to 100% in larvae [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Infected fish often show flexing of the body, muscle tremors and abnormal swimming behaviour, which includes vertical positioning and spinning resulting from traumatic lesions [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. \u003cem\u003eBetanodavirus\u003c/em\u003e also causes hyperinflation of the swim bladder, with diseased fish present primarily at the surface. In adults, where the mortality rate can reach 50\u0026ndash;60%, the most common clinical sign is abnormal swimming [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. To date, the most common preventive strategies regarding husbandry and NNV-free brood stock selection appear to be inefficient at avoiding NNV outbreaks on fish farms due to the stability of the virus in the aquatic environment [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Therefore, vaccination remains the only cost-effective, innocuous, and sustainable strategy available to prevent NNV infections and severe disease episodes.\u003c/p\u003e \u003cp\u003eDifferent strategies have been followed to design NNV vaccines tested in the laboratory and in the field such as inactivated virus, recombinant proteins, virus-like particles and DNA based vaccines, and their efficacy, based on relative percentage survival, has ranged from medium to high levels of protection to little or no protection [\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. It is also worth mentioning that at present, two commercial inactivated (formalin-killed) vaccines against the RGNNV genotype, Alpha ject micro 1Noda (Pharmaq) and Icthiovac VNN (Hipra) are available for sea bass vaccination in the Mediterranean marketplace. These vaccines were based on chemically inactivated viruses and were formulated with either a mineral or nonmineral oil adjuvant to enhance the immune response.\u003c/p\u003e \u003cp\u003eAssessing immunogenicity and inflammatory responses is pivotal for vaccine quality evaluation. In contrast to infections, vaccine-induced inflammatory reactions need to be regulated to an acceptable level while promoting immune cell activation. Consequently, the comprehensive assessment of adaptive responses, particularly humoral and complement responses, along with innate immunity, constitutes a fundamental objective in the field of systems vaccinology [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Usually, the induced immune response is characterized through the detection of NNV reactive antibodies in the serum of vaccinated fish and by gene expression analysis of important immune genes in various tissues from vaccinated fish [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. While plausible reasons for modulating the immune response are known or suspected, identification of markers of vaccine efficacy are still an area of active investigation. Several studies examined blood samples from vaccine recipients demonstrating that NNV infection in fish provokes a host immune response which is mediated by innate and adaptative response [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. For example, an increase in the expression of T-cell marker genes (TRCb, CD4-2, CD4, CD8a, CB8b, Lck, NCCRP-1 and ZAP-70) has been reported in infected Atlantic halibut, European sea bass and gilthead sea bream [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. More recently, the transcriptome analyses of different cell lines susceptible to NNV have provided useful information about the immune response elicited against viral infection. In SSN-1 cells infected with a RGNNV strain, the down-regulation of 1138 genes and the up-regulation of 2073 involved in different pathways related to viral pathogenesis was observed [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. While few previous studies have investigated fish immune responses using a proteomics approach, none have specifically focused on \u003cem\u003eD. labrax\u003c/em\u003e as the host species and nodavirus as the pathogen used for vaccination and challenge [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Interestingly, shotgun proteomics based on high-resolution tandem mass spectrometry can be efficiently performed on fishes based on database constructed with reference annotated genomes or closely related annotated genomes [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn order to expand our knowledge on \u003cem\u003eD. labrax\u003c/em\u003e response to vaccination and capture novel biomarkers compared to those traditionally found by highly used conventional inflammatory panels impacting vaccine efficacy, we examined the abundance profiles of serum proteins from specimens recipient of a chemically-inactivated RGNNV vaccine using mass spectrometry-based proteomics and compared them to control specimens.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSample collection and on-chip protein electrophoresis\u003c/h2\u003e \u003cp\u003eSamples were obtained from European sea bass (\u003cem\u003eD. labrax\u003c/em\u003e) farm performing a vaccination campaign against nodavirus in 2021. The local private hatchery (Tunisia) utilized a commercially available vaccine that was chemically inactivated and administered \u003cem\u003evia\u003c/em\u003e intraperitoneal injection at the recommended dose. Blood samples were collected from the tail vein, allowed to clot at room temperature for 2 hours, and then centrifuged at 5,000 \u0026times; g for 10 minutes to isolate the serum. This procedure was performed for two distinct cohorts. Following vaccination procedure, we analysed vaccinated fish specimens (n\u0026thinsp;=\u0026thinsp;6), weighting at the mean of 40 g\u0026thinsp;\u0026plusmn;\u0026thinsp;2g after 37 days post vaccination (dpv), and control sera (n\u0026thinsp;=\u0026thinsp;6) were obtained from unvaccinated specimens belonging to the same production cycle. Blood tubes were kept at +\u0026thinsp;4\u0026deg;C, centrifuged at 4000 \u0026times; g for 10 min then blood sera were aliquoted 20 \u0026micro;L/tube) and stored at \u0026minus;\u0026thinsp;80\u0026deg;C for further analysis. The on-chip serum protein analysis was performed on the 2100 Bioanalyzer using Protein 80 kit, according to the guide instructions (Agilent Technologies). Fish serum samples (4 \u0026micro;l) were prepared in the presence of β-mercaptoethanol agent and directly analysed on the 2100 Bioanalyzer. Proteins migrate according to their molecular weights. Total protein concentration in serum was quantified using Bradford Assay with Bovine Serum Albumin (BSA) as standard protein. Briefly, diluted (1/10) serums were added to 96 well polystyrene plates (Nunc Maxi Sorb) in the presence of the Bradford reagent and incubated in darkness for 30 min, RT\u0026deg;C. Optical density (OD) was read at 595 nm. Serum levels were recorded as mg/mL (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD). This study was conducted in strict accordance with ethical standards for animal research. Specifically, the research (1) adhered to the guidelines outlined in the guide for the care and use of laboratory animals [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] and the guide to define and implement protocols for the welfare assessment of laboratory animals [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], and (2) complied with Directive 2010/63/EU on animal welfare, particularly articles 26 and 30. Efforts were made to minimize any potential distress to the animals, in accordance with articles 15 and 39 of the directive [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Ethical clearance was obtained from the National School of Veterinary Medicine of Tunis Ethics Committee.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eProteome sample preparation and tandem mass spectrometry\u003c/h3\u003e\n\u003cp\u003eTwenty \u0026micro;L of serum (proteins) were dissolved in 25 \u0026micro;L of LDS buffer (26.5 mM Tris HCl, 35.25 mM Tris base, 0.5% LDS, 2.5% Glycerol, 0.13 mM EDTA, supplemented with 5% beta-mercaptoethanol). Samples were heated for 5 min at 99\u0026deg;C in a thermomixer (Eppendorf). For each sample, a volume of 20 \u0026micro;L (10 \u0026micro;g of proteins) was subjected to 5 min of denaturing electrophoresis on a NuPAGE 4\u0026ndash;12% gradient gel with MES SDS as running buffer (50 mM MES (2-(N-morpholino) ethane sulfonic acid), 50 mM Tris Base, 0.1% SDS, 1 mM EDTA, pH 7.3). After electrophoresis, the gel was briefly washed with MilliQ water, and stained with SimplyBlue SafeStain (Thermo) for 5 min for visualizing proteins, then washed extensively with MilliQ water. Each proteome was extracted as a single polyacrylamide band of approximately 100 \u0026micro;L in volume. Each sample was subsequently processed as previously described (Rubiano-Labrador et al., 2014) and proteolyzed with trypsin Gold (Promega) in 50 mM NH4HCO3 in presence of ProteaseMax\u0026trade; detergent (Promega). A volume of 10 \u0026micro;L of the resulting peptide mixture (45 \u0026micro;L) was injected in a nanoscale C18 PepMap100 capillary column (2 \u0026micro;m, 100 \u0026Aring;, 75 \u0026micro;m internal diameter \u0026times; 50 cm length, LC Packings) mounted with a desalting pre-column and resolved with a 95-min gradient of acetonitrile (5\u0026ndash;25% in 90 min followed by 25\u0026ndash;40% in 5 min), 0.1% formic acid, at a flow rate of 0.25 \u0026micro;L/min. The peptides resolved by reverse phase chromatography with a NeoVanquish instrument (Thermo) were analyzed by tandem mass spectrometry with an Exploris 480 mass spectrometer (Thermo) connected directly to the column exit. The instrument was operated in data-dependent acquisition mode, with full scan of peptide ions acquired at a resolution of 120,000 from \u003cem\u003em/z\u003c/em\u003e 350 to 1500 and with a dynamic exclusion of 10 sec. Each MS scan was followed by high-energy collisional dissociation and MS/MS scans at a resolution of 15,000 on the 20 most abundant precursor ions identified within the full scan, selecting only ions with charge 2\u0026thinsp;+\u0026thinsp;or 3+.\u003c/p\u003e \u003cp\u003eInterpretation of MS/MS spectra was performed with the Mascot search engine, version 2.6.1 (Matrix Science) against the \u003cem\u003eD. labrax\u003c/em\u003e protein sequence database as annotated in the GCF_905237075 genome assembly deposited in the NCBI repository on April 24, 2021 [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Proteins were confidently validated when detecting at least 2 peptides of different sequences, one being specific (unambiguous in the whole \u003cem\u003eD. labrax\u003c/em\u003e database). Proteins were quantified based on their spectral counts. The normalized spectral abundance factor (NSAF) was calculated by dividing the spectral count for each observed protein by the polypeptide theoretical mass, as described previously [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] and is presented as a percentage of the NSAF sum considering all proteins. Proteome comparison between both conditions was done taking into account all the biological replicates based on standard normalisation with Tfold and \u003cem\u003et\u003c/em\u003e-test calculations, as previously described [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In this investigation, Tfold values were delineated from the locus tags using parentheses and commas, followed by the respective statistical class, unless specified otherwise. The blue class denotes identifications meeting both Tfold (\u0026gt;\u0026thinsp;1.5 or \u0026lt;\u0026thinsp;\u0026minus;\u0026thinsp;1.5) and statistical (\u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05) criteria. The orange class comprises identifications not meeting the fold criterion but warrant further scrutiny due to low \u003cem\u003ep\u003c/em\u003e-values. The green class signifies identifications satisfying the fold criteria, possibly by chance, while the red class includes identifications not meeting both fold and \u003cem\u003ep\u003c/em\u003e-value criteria. Differences were considered statistically significant for a \u003cem\u003ep\u003c/em\u003e-value of less than 0.05 and statistically highly significant as a \u003cem\u003ep\u003c/em\u003e‐value\u0026thinsp;\u0026lt;\u0026thinsp;0.001. Additional biological triplicates also allow for a quantitative assessment of differences between two conditions (non-vaccinated and vaccinated fish).\u003c/p\u003e\n\u003ch3\u003eSequence similarity-based functional analysis\u003c/h3\u003e\n\u003cp\u003eProtein sequences belonging to the Blue Class proteins (eight proteins) were uploaded into Blast2GO tool [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Mapping against Swissprot, Uniprot database was performed using BLAST for protein annotation and GO mapping. Domains of proteins were predicted using the Simple Modular Architecture Research Tool (SMART) [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Orthologs were identified using the BLAST\u0026thinsp;+\u0026thinsp;tool suite through Galaxy [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eProtein-protein interaction network\u003c/h3\u003e\n\u003cp\u003eThe sequences corresponding to the eight proteins of \u003cem\u003eD. labrax\u003c/em\u003e belonging to the PatternLab blue class (for which identifications satisfied both the fold (\u0026gt;\u0026thinsp;1.5) and statistical criteria (\u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05)) were extracted and saved in a distinct multi-FASTA file. This file was then uploaded into the STRING database [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] and \u003cem\u003eDanio rerio\u003c/em\u003e was chosen as a query microorganism. A total of eight hits with 100% identity were detected and their protein-protein interactions were predicted. Functional analysis and the identification of enriched biological processes and pathways was performed based on protein sequences.\u003c/p\u003e\n"},{"header":"Results and Discussion","content":"\u003cp\u003eIn this study, we undertook a comprehensive exploration of the proteome landscape in fish, comparing the blood serum proteomes of unvaccinated and vaccinated \u003cem\u003eD. labrax\u003c/em\u003e individuals. The choice of a 37-day sampling point in this study aligns with previous findings [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], aiming to capture a potentially sustained immune response. First, ten across 12 samples biochip-based electrophoretic profiles of total blood serum proteins (non-vaccinated S1\u0026ndash;S6 and vaccinated sera S7\u0026ndash;S10) were qualified and analysed. To enable proper comparison, same volume of serum was loaded on the biochip. Protein bands with varying migration time were observed in reduced conditions. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003e.A shows the overlay of the ten different electropherogram traces in the corresponding gel-like image. Protein variations in serum individual samples could be partly attributed to the fish vaccination stress conditions, despite other chemical properties (glycosylation or phosphorylation patterns) that may influence protein interaction with the gel matrix during separation.\u003c/p\u003e \u003cp\u003eHigh-resolution tandem mass spectrometry recorded a total of 951,230 MS/MS spectra that were interpreted against a database comprising the \u003cem\u003eD. labrax\u003c/em\u003e annotated protein sequences. The number of peptide-to-spectrum matches, namely 304,176, shows a relatively good match between the analysed samples and the genome of reference, as the ratio of MS/MS spectra assignment is 32%. These assigned spectra enabled the identification of 6,967 distinct peptide sequences, which allowed to identify and label-free quantified 437 proteins (false discovery rate\u0026thinsp;\u0026lt;\u0026thinsp;1%) across all samples. The mass spectrometry response was relatively homogeneous for all samples with an average of 26,646 (\u0026plusmn;\u0026thinsp;7%) spectral counts per sample. As illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003e.B, principal component analysis demonstrated that sample S4 (non-vaccinated) stands out as an outlier. Further detailed analysis shows an unusual level of hemoglobins (alpha and beta chains) representing 12.1% of the signal in this sample compared to 3.4% in average for all the other samples. This over-representation of hemoglobins impacted the quantitation of the other proteins. Henceforth, all analyses and data presented herein exclude outlier sample 4, unless explicitly stated otherwise. These analyses identified top protein hits based on fold change in abundances when comparing both fish groups (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Eight proteins showing at least a 50% difference in abundance and a \u003cem\u003ep\u003c/em\u003e-value of less than 0.05 (Differential abundant proteins are labeled \u0026ldquo;blue-class\u0026rdquo; hereafter) were identified as differentially detected, all at lower abundance in sera from vaccinated compared to unvaccinated fish (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In light of the absence of IgG in fish and the predominance of IgM, IgD, and IgT/Z \u0026mdash; for Teleost/Zebrafish [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], a BLAST-based analysis was conducted on the 437 proteins, resulting in the identification of best hits for IgM (XP_051244807.1 (1.08x, \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;=\u0026thinsp;0.51, E-value\u0026thinsp;=\u0026thinsp;2e\u0026thinsp;\u0026minus;\u0026thinsp;58 to AAK69167.1)), IgD (XP_051244806.1 (1.20x, \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;=\u0026thinsp;0.24, E-value\u0026thinsp;=\u0026thinsp;0.0 to BAD34542.1 and AGR34025.1)), IgT/Z (XP_051250463.1 (1.82x, \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;=\u0026thinsp;0.14, E-value\u0026thinsp;=\u0026thinsp;0.0 to ASK39431.1)), and immunoglobulin light chains (XP_051243640.1 (1.17x, \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;=\u0026thinsp;0.58, E-value\u0026thinsp;=\u0026thinsp;7e\u0026thinsp;\u0026minus;\u0026thinsp;46 to CAA33375.1), and XP_051243629.1 (\u0026minus;\u0026thinsp;1.02x, \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;=\u0026thinsp;0.94, E-value\u0026thinsp;=\u0026thinsp;8e\u0026thinsp;\u0026minus;\u0026thinsp;12 to XP_050924250.1)) [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTop 10 hits based on fold change.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eName\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChange\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTfold\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eClass\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDescription\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eXP_051237425.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDecreased\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;3.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBlue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCatalase\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eXP_051244291.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDecreased\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;2.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGreen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSolute carrier family 4 member 1a (Diego blood group) isoform X1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eXP_051239863.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDecreased\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;2.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBlue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePeroxiredoxin-2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eXP_051275475.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIncreased\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGreen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCoagulation factor VIII\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eXP_051244632.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDecreased\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;2.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGreen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePentraxin fusion protein-like\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eXP_051258241.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDecreased\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;2.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBlue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSuperoxide dismutase [Cu-Zn]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eXP_051270211.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIncreased\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGreen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMyosin heavy chain, fast skeletal muscle-like\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eXP_051243618.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIncreased\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGreen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMyosin heavy chain, skeletal muscle, adult-like\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eXP_051266112.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDecreased\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;2.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGreen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eReceptor-type tyrosine-protein kinase FLT3 isoform X1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eXP_051231594.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDecreased\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;2.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBlue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAntithrombin-III\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTop protein hits based on fold change in abundances when comparing vaccinated to unvaccinated fish sera groups.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eModulation of redox balance in favour of reactive oxygen species (ROS)\u003c/h2\u003e \u003cp\u003eProteins like catalase, peroxiredoxin and superoxide dismutase are essential for maintaining the balance of ROS in cells. Of interest here is the strong decrease of the abundance in catalase (XP_051237425.1, \u0026minus;\u0026thinsp;3.12x, \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;=\u0026thinsp;0.04). Previously, a study on rainbow trout \u003cem\u003eOncorhynchus mykiss\u003c/em\u003e showed that vaccination against furunculosis led to decreased catalase activities in the muscles and gills of the vaccinated fish [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], indicating reduced capacity to scavenge hydrogen peroxide. The present results, shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, are in full accordance to these previous results [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The observed reduction in catalase activity within the tissues may be attributed to the generation of superoxide radicals induced by vaccination, during which these radicals can potentially inhibit catalase activity, as suggested by Kono and Fridovich [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Here, the abundance of catalase is shown to be lower after immunization inducing a lower activity, but demonstrating that the balance of synthesis of enzymes and degradation of the produced polypeptides is impacted. However, it is important to note that fish immunized with live theronts of \u003cem\u003eIchthyophthirius multifiliis\u003c/em\u003e showed elevated catalase levels in the liver [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], indicating also a potential positive influence of vaccination on catalase overabundance in the liver.\u003c/p\u003e \u003cp\u003ePeroxiredoxins potentially serve as regulators of inflammation during pathogen infection and play a protective role against cell death, contributing to tissue repair following damage [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Here, a lower abundance of peroxiredoxin-2 (XP_051239863.1, \u0026minus;\u0026thinsp;2.40x, \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;=\u0026thinsp;0.00) is noted in vaccinated fish. This finding is in contradiction to a previous study which has suggested that, following exposure to an inactivated trivalent bacterial vaccine, three members of the peroxiredoxin family exhibited up-regulation [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Additionally, our results showing an under-abundance of superoxide dismutase (XP_051258241.1, \u0026minus;\u0026thinsp;2.23x, \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;=\u0026thinsp;0.05) is in contradiction to a prior study that proposed a significant increase in superoxide dismutase activity in head kidney lymphocytes of immunized Chinese breams exposed to an inactivated vaccine and recombinant Omp38 protein when compared to the control [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Furthermore, Tkachenko et al.'s study demonstrated a significant increase in superoxide dismutase activity within the muscles and liver of vaccinated \u003cem\u003eO. mykiss\u003c/em\u003e [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eROS production contributes to elimination of pathogens and induces activation of immune defence mechanisms [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. However, excessive ROS formation can induce oxidative stress, leading to cell damage and cell death may follow [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Furthermore, oxidative stress occurs when the critical balance between oxidants and antioxidants is disrupted due to the depletion of antioxidants or excessive accumulation of ROS, or both, which may lead to a series of biochemical and physiological changes, thus, altering normal body homeostasis and tissue injury [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Our results suggest that during an immune response, there could be a temporary shift in the redox balance which might allow for less need of antioxidant enzymes. This down-regulation can occur as a regulatory mechanism to fine-tune the immune response of the vaccinated fish. In this context, it is important to note that the integral involvement of macrophages in specific immune responses arises from their roles in lymphocyte activation and phagocytosis, facilitated by specific β-glucan receptors, leading to immunostimulants-induced increase of leukocytes' respiratory burst and subsequent generation of bactericidal ROS [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. These results indicate that the modulation of the redox balance in favour of ROS represents a significant molecular mechanism linked to the immune response of European sea bass (\u003cem\u003eD. labrax\u003c/em\u003e) following vaccination with chemically-inactivated nodavirus.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eInterplay between coagulation and the immune system in favour of lower abundance of haematopoiesis-related FLT3\u003c/h3\u003e\n\u003cp\u003eOur findings (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) suggest that vaccinated fish have an up-regulated coagulation factor VIII (XP_051275475.1, 2.37x, \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026gt;\u0026thinsp;0.05) and a down-regulated antithrombin-III (XP_051231594.1, \u0026minus;\u0026thinsp;2.04x, \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;=\u0026thinsp;0.01) and receptor-type tyrosine-protein kinase FLT3 isoform X1 (XP_051266112.1, \u0026minus;\u0026thinsp;2.06x, \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Antithrombin-III functions as a pivotal serine protease inhibitor, contributing significantly to both the coagulation cascade and inflammatory response in fish [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Drawing upon the literature [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], the under-abundance of antithrombin-III in vaccinated fish, as identified in this study, is suggesting prevention of inactivating thrombin and activated factors. These findings may be somewhat limited by the prothrombin level (XP_051283059.1, 1.15x, \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026gt;\u0026thinsp;0.05) requiring further investigation due to its non-significant fold change and lack of statistical significance. The reduced presence of the FLT3 isoform X1, as indicated in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, implies that several cytoplasmic effector molecules in pathways involved in apoptosis, proliferation, and differentiation of hematopoietic B-cell progenitors, myelomonocytic and dendritic cells, and pluripotent hematopoietic stem cells, may not undergo phosphorylation and consequently remain inactive [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMoreover, in an earlier investigation of the \u003cem\u003eYersinia ruckeri\u003c/em\u003e infection process in rainbow trout, proteome analysis unveiled the involvement of several proteins involved in the blood coagulation pathway [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. We also found lower abundance of a solute carrier family 4 member 1A (SLC4A1, XP_051244291.1, \u0026minus;\u0026thinsp;2.57, \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;=\u0026thinsp;0.17) but this result was not validated statistically and should be taken cautiously. This protein is an important player found in red blood cells promoting the reversible exchange of bicarbonate ion for chloride ion and facilitating the efflux of osmolytes, including KCl and amino acids, a mechanism that is crucial in pH and cell volume regulation [\u003cspan additionalcitationids=\"CR54\" citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Hence, it could conceivably be hypothesised that the lower abundance of SLC4A1 is related to the conversion of prothrombin to its active form by the prothrombinase complex, comprising activated Factor X and Factor V in the presence of ions [56].\u003c/p\u003e \u003cp\u003ePrevious studies indicated that coagulation, pathogen opsonization, recognition through pattern-recognition receptors, and cytokine-mediated inflammation collectively constitute the fundamental pillars of innate immunity of fish ([57] and references therein). Our results are aligned with these studies, thus confirming that the interconnection between blood clotting and the immune response is essential in safeguarding against microbial invasion, where clot formation functions to restrict pathogen dissemination, while immune cells actively strive to eradicate the infection. Certain clotting factors, in addition to their involvement in coagulation, exhibit immunomodulatory functions; for instance, thrombin, a pivotal component in the coagulation cascade, can impact inflammation by activating immune cells and regulating cytokine production [56].\u003c/p\u003e\n\u003ch3\u003eFunctional adaptive immunity and insignificant alterations in complement protein levels\u003c/h3\u003e\n\u003cp\u003eIn addition to the modulation of the redox balance and the dynamic interaction between coagulation and the immune system, the findings presented in this work underscore the significance of host defence, inflammatory responses, and pathogen recognition. Pentraxins, constituting fluid phase pattern recognition molecules and demonstrating conservation across both fish and humans, play a crucial role in the innate immune defence [58]. These molecules represent a family of evolutionarily conserved proteins with diverse roles in host defence, encompassing their participation in inflammatory responses and pathogen recognition [59]. Pentraxins in fish have been identified in skin mucus, playing a pivotal role as the initial defence line against pathogens and external stressors [59]. Earlier findings proposed that short pentraxins exhibit heightened reactivity against viruses in the skin, and their overexpression appears to represent a compensatory mechanism for the diminished adaptive immunity [60]. Consequently, the observed lower abundance of pentraxin fusion protein-like (XP_051244632.1, \u0026minus;\u0026thinsp;2.28x, \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026gt;\u0026thinsp;0.05) in this study suggests a functional adaptive immunity in vaccinated fish. Moreover, the over-abundance of the myosin heavy chain, fast skeletal muscle-like (XP_051270211.1, 2.17x, \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026gt;\u0026thinsp;0.05) and the myosin heavy chain, skeletal muscle, adult-like (XP_051243618.1, 2.14x, \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026gt;\u0026thinsp;0.5) was observed. Myosins facilitate diverse cellular activities, encompassing muscle contraction, cell migration, intracellular transport, cell adhesion, and cell signalling [61].\u003c/p\u003e \u003cp\u003eOur findings are concordant with previous research indicating that, in immune cells, class I myosins are involved in the formation and maintenance of immunological synapse-related signalling [62]. Also, our results corroborate the previous findings suggesting that myosin-9 potentially enhances the immune response to \u003cem\u003eVibrio alginolyticus\u003c/em\u003e by positively influencing the phagocytosis rate of haemocytes [63]. For instance, to orchestrate an effective adaptive immune response, particularly involving T cells, the ability of leukocytes to migrate between the blood, secondary lymphoid organs, and sites of injury or infection is essential. The motility of T lymphocytes is intricately governed by the spatial distribution of specific proteins, including integrins. Notably, Mhc9 (class II myosin) has been identified as interacting with such molecules in crawling T cells. Beyond its role in regulating T cell motility, Mhc9, a highly versatile molecule, has also been implicated in various other immune processes, notably the formation of the immune synapse, a pivotal event in the adaptive immune response ([64] and references therein).\u003c/p\u003e \u003cp\u003eIn fish, within the realm of humoral components constituting innate immunity, the complement system comprises roughly 30 inactive circulating proteins alongside membrane-bound receptors ([65] and citations therein). Our study identified levels of 30 complement proteins (Supplementary Table S1), among which no significant difference in fold change nor statistical significance were observed. Notwithstanding, complement component 7b (XP_051267608.1) displayed a Tfold value of 1.63, indicative of a moderate increase in abundance, albeit without reaching statistical significance (\u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;=\u0026thinsp;0.16). Although these data must be interpreted with caution, it could conceivably be hypothesised, based on our overall observations, that the vaccinated host is in a stage of \"adaptive immunity\" rather than \"innate immunity\", as discussed in a prior review [65].\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eDifferentially abundant proteins\u003c/h2\u003e \u003cp\u003eAs illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003e, eight proteins were identified as differentially abundant proteins with stringent statistical validation (\u003cem\u003ep\u003c/em\u003e-value below 0.05). All exhibited lower abundance in vaccinated animals compared to unvaccinated: catalase (XP_051237425.1, \u0026minus;\u0026thinsp;5.30x), peroxiredoxin-2 (XP_051239863.1, \u0026minus;\u0026thinsp;4.19x), superoxide dismutase (XP_051258241.1, \u0026minus;\u0026thinsp;2.86x), antithrombin-III (XP_051231594.1, \u0026minus;\u0026thinsp;1.81x), tubulin beta-1 chain (XP_051270361.1, \u0026minus;\u0026thinsp;3.53x), carbonic anhydrase (XP_051267911.1, \u0026minus;\u0026thinsp;2.52x), thyroglobulin (XP_051255191.1, \u0026minus;\u0026thinsp;1.56x), and E-selectin (XP_051233011.1, \u0026minus;\u0026thinsp;1.48x). Among the most enriched biological processes linked to differentially abundant proteins (Tfold\u0026thinsp;\u0026gt;\u0026thinsp;1.5 or \u0026lt;\u0026thinsp;\u0026minus;\u0026thinsp;1.5 and \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026le;\u0026thinsp;0.05), as indicated in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003e, we found ROS metabolic process (GO:0072593), response to ROS (GO:0000302), removal of superoxide radicals (GO:0019430), cellular oxidant detoxification (GO:0098869), and response to inorganic substance (GO:0010035). The protein-protein interaction network of the aforementioned differentially abundant proteins confirms interactions among three proteins (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Additionally, GOChord plots of orange, green, and red-class proteins are presented in Supplementary Figure S1 (A, B, and C, respectively), with their interactions depicted in Supplementary Figure S2 (A, B, and C, respectively). In contrast to the COGs of orange, green, and red-class proteins shown in Supplementary Figure S3 (A, B, and C, respectively), all COGs of the blue-class proteins (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e6\u003c/span\u003e) exclusively comprised under-abundant proteins, including the COG V (defence mechanisms). This observation aligns with findings in the literature [65] and with our previous observations, indicating that the vaccinated host is in a stage of \"pathogen clearance\" rather than \"pathogen intrusion\".\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur findings provide crucial insights into the molecular dynamics underpinning the vaccination process in fish. Some of these results should be further confirmed with larger cohort of animals, but the comparison of non-vaccinated and vaccinated groups and the subsequent identification of under- and over-abundant proteins, such as catalase, peroxiredoxin-2, and coagulation factor VIII, among others, unveils potential markers of immune modulation and sheds light on the biological processes influenced by vaccination. In essence, our study elucidates potential molecular mechanisms linked to both the immune response and the efficacy of chemically-inactivated vaccines.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe gratefully acknowledge the financial support provided by the Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture through the IAEA CRP 2296 (Project code: D3.20.37). This research was conducted under Contract Number 26187 (Immune2AquaVac-ir).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available in PRIDE at http://doi.org/10.6019/PXD051099. All mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium \u003cem\u003evia\u003c/em\u003e the PRIDE partner repository under the dataset identifiers PXD051099 and 10.6019/ PXD051099.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests associated with the research presented in this article. No financial or non-financial conflicts of interest, including employment, consultancies, honoraria, stock ownership, or any other competing relationships, influenced the design, execution, or interpretation of the study. This work was conducted with scientific integrity, and the authors have no affiliations or involvements that may be perceived as biasing the content or outcomes of this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the animal handling and experimental procedures were approved by the National School of Veterinary Medicine of Tunis Ethics Committee \u0026mdash; Approval Number: CEEA-ENMV 85/24.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization, experimental design, HS, BBZ, NC, JA; \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003ein vitro\u003c/em\u003e experiments, NC, HA; biochemical analyses, BBZ, SN; mass spectrometry experiments, MK; proteomics data analysis, JA, HS; bioinformatic analyses, KG, HS; original draft preparation, NC, HS;\u003c/p\u003e\n\u003cp\u003eediting of the manuscript, KG, JA, RTK, VW, BBZ, coordination of financial and technical support, HS, RTK, VW. All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eI. Band\u0026iacute;n, S. Souto, Betanodavirus and VER Disease: A 30-year Research Review, Pathogens (Basel, Switzerland), 9 (2020).\u003c/li\u003e\n\u003cli\u003eA. Toffan, F. Pascoli, T. Pretto, V. Panzarin, M. Abbadi, A. Buratin, R. Quartesan, D. Gij\u0026oacute;n, F. Padr\u0026oacute;s, Viral nervous necrosis in gilthead sea bream (\u003cem\u003eSparus aurata\u003c/em\u003e) caused by reassortant betanodavirus RGNNV/SJNNV: an emerging threat for Mediterranean aquaculture, Sci Rep, 7 (2017) 46755.\u003c/li\u003e\n\u003cli\u003eA. Toffan, V. Panzarin, M. Toson, K. Cecchettin, F. Pascoli, Water temperature affects pathogenicity of different betanodavirus genotypes in experimentally challenged \u003cem\u003eDicentrarchus labrax\u003c/em\u003e, Diseases of aquatic organisms, 119 (2016) 231\u0026ndash;238.\u003c/li\u003e\n\u003cli\u003eB.L.M.K.J.G.M.J.G. 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Baharum, Integration of Omics Tools for Understanding the Fish Immune Response Due to Microbial Challenge, 8 (2021).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":" International Atomic Energy Agency","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Adaptive immunity markers, coagulation-immune interplay, Dicentrarchus labrax, hematopoiesis-related FLT3, nodavirus, proteomic analysis, reactive oxygen species, sea bass immunization.","lastPublishedDoi":"10.21203/rs.3.rs-5584738/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5584738/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAnalysing animal responses to immunization is pivotal in vaccine development by evaluating immune response, assessing vaccine safety and efficacy, and providing crucial insights into immune protection mechanisms. These insights are indispensable for advancing vaccines through trial stages and regulatory approval processes, as well as deciphering the molecular signatures of approved vaccines, which not only enhances our understanding of existing vaccines but also informs the rational design of new ones. This study aims to elucidate alterations in protein abundance patterns in the sera of European sea bass, \u003cem\u003eDicentrarchus labrax\u003c/em\u003e, following immunization with a chemically-inactivated nodavirus vaccine. The shotgun proteome comparison revealed that in vaccinated animals, compared to controls, there is a modulation of the redox balance favouring reactive oxygen species, an intricate interplay between coagulation and the immune system resulting in the under-abundance of hematopoiesis-related FLT3, and indications of functional adaptive immunity demonstrated by the under-abundance of pentraxin fusion protein-like and the over-abundance of myosins. To the best of our knowledge, this study represents the inaugural investigation of the immune response in fish using a proteomics approach, employing \u003cem\u003eD. labrax\u003c/em\u003e as the host and nodavirus as the pathogen used for vaccination and challenge.\u003c/p\u003e","manuscriptTitle":"Proteomic profiling of the serological response to a chemically-inactivated nodavirus vaccine in European sea bass Dicentrarchus labrax","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-09 06:55:30","doi":"10.21203/rs.3.rs-5584738/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ab7527ea-f727-4fe4-b878-45598001f62f","owner":[],"postedDate":"December 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":41186541,"name":"Vaccine Development"}],"tags":[],"updatedAt":"2024-12-09T06:55:30+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-09 06:55:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5584738","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5584738","identity":"rs-5584738","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}