Prototype of a nanostructured multi-epitope vaccine for the control of Piscirickettsiosis: Proof-of concept in salmonid cells

Prototype of a nanostructured multi-epitope vaccine for the control of Piscirickettsiosis: Proof-of concept in salmonid cells | 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 Prototype of a nanostructured multi-epitope vaccine for the control of Piscirickettsiosis : Proof-of concept in salmonid cells Paula This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5941909/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 The article focuses on the development of a nanostructured multi-epitope vaccine prototype to control Piscirickettsiosis, a serious bacterial infection caused by Piscirickettsia salmonis in salmonids. Piscirickettsiosis, one of the main causes of mortality in Chilean aquaculture, generates significant economic losses and extensive use of antibiotics, which represents risks to environmental and public health. Despite the existence of vaccines, their efficacy remains limited, especially under field conditions, where the genetic variability of the pathogen and other external factors compromise immunological protection. This research applies reverse vaccinology to identify specific antigenic epitopes of P. salmonis, particularly of the LF-89 and EM-90 genogroups, which are predominant in Chilean aquaculture. The study includes the design and production of four nanoparticles (NPs) with chimeric characteristics, called SkipZ, PulseJ, HopQ and Hoptech, derived from P. salmonis epitopes. These nanoparticles were expressed in Escherichia coli and purified for further immunogenic evaluation. The research analyses the uptake of these nanostructures by salmonid RTS-11 macrophage cells and their ability to induce antigen presentation and pro-inflammatory responses. The results show that the nanoparticles, especially SkipZ and HopQ, effectively stimulate the expression of key markers involved in antigen presentation, such as MHC-II, CD83 and CD86, as well as pro-inflammatory cytokines such as IL-1β and TNF-α, in a dose-dependent manner. These findings suggest that the selected epitopes are capable of enhancing immune responses in salmonid cells. This multi-epitope vaccine approach seeks to offer a more specific and effective strategy to control Piscirickettsiosis, potentially reducing the dependence on antibiotics and improving the long-term protection of salmonid populations. The work highlights the potential of using nanoparticle-based vaccines to induce robust cellular immunity, critical to combat intracellular pathogens such as P. salmonis. This proof-of-concept study paves the way for the development and optimization of vaccines tailored to the pathogen-specific genetic diversity in aquaculture environments. Animal Science recombinant protein cell line SRS Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction In recent years, Chile has established itself as a world leader in salmonid exports. In 2022, exports totaled 751,259 tons, generating a commercial value of US $ 6,606 million (Chile, 2022). However, salmon farming faces significant challenges, especially in relation to infectious diseases in farms. In particular, mortality caused by infectious factors is a critical problem, representing 26.9% of deaths in Atlantic salmon (SERNAPESCA, 2023 ). The main health challenge of the salmon farming industry in Chile is Salmon Rickettsial Syndrome (SRS) (Maisey et al., 2017 ); (SERNAPESCA, 2024 ) caused by the intracellular pathogen Piscirickettsia salmonis. This pathogen is responsible for 44.7% of deaths due to infectious causes, significantly affecting salmon in the fattening phase (SERNAPESCA, 2024 ). As the fish are close to the harvest period, the economic impact caused by P. salmonis is significant, resulting in estimated losses for the industry of around US $ 700 million annually. These economic losses related to mortality added to the cost of prophylactic treatments decrease the competitiveness of Chilean salmon compared to its main competitor, Norway (Maisey et al., 2017 ); (Caruffo et al., 2021 ). In 2023, more than 93.21% of the 338.9 tons of antimicrobial compounds used in marine waters were used to treat Piscirickettsiosis (SERNAPESCAb, 2023). Although the use of antibiotics mitigates the effects of this disease, its extensive use carries environmental, regulatory and public health risks (Cabello et al., 2013 ). Despite the decrease in the antibiotic consumption index in aquaculture (ICA) from 0.063% in 2015 to 0.031% in 2023, equivalent to 338.9 tons of antibiotics compared to 1,107,109 tons of harvested biomass, these figures are still alarmingly high (SERNAPESCA b, 2023 ). Although vaccines have been considered essential for the development of salmon farming worldwide (Sommerset et al., 2005 ), their effectiveness against P. salmonis has been limited (Caruffo et al., 2021 ). In Chile, there are approximately 17 provisionally registered vaccines authorized for commercialization against Piscirickettsiosis (SAG, 2024 ). However, recent evidence suggests persistent susceptibility to the disease, possibly due to decreased vaccine-induced immunity and/or immunological compromise associated with co-infections and stress (Figueroa et al., 2017 ) (Figueroa et al., 2020 ); (Valenzuela-Aviles et al., 2022 ). Despite the sustained use of P. salmonis vaccines, the consensus within the industry is that the long-term protection provided by them remains low (Rozas-Serri et al., 2023 ); (Tobar et al., 2015 ). In the last nine years, an average of 1.1 billion doses of vaccines have been administered in Chilean aquaculture, of which approximately 50% were used to prevent Piscirickettsiosis (Valenzuela-Aviles et al., 2022 ). Currently marketed SRS vaccines include bacterins with inactivated or attenuated live pathogens, as well as subunit vaccines, which manage to delay the onset of infection but do not effectively prevent the continuous outbreaks affecting fish farms (Martinez et al., 2018 ). The high mortality rates observed in the field can be explained by a combination of intrinsic and extrinsic factors. Intrinsic factors include inherent biological characteristics such as family group, sex, and population variations, which directly affect the efficacy of vaccines due to the wide heritable genetic diversity in fish (Figueroa et al., 2017 ; Figueroa et al., 2020 ). On the other hand, extrinsic factors include environmental and ecological conditions such as temperature, salinity, sea lion attacks, algal blooms, co-infections with ectoparasites, and the variable virulence of the different genogroups of Piscirickettsia salmonis. These external factors are often not adequately considered in the design and development of current vaccines, which negatively impacts their effectiveness under real-life culture conditions (Figueroa et al., 2020 ; Valenzuela-Avilés et al., 2022). Pangenomic analyses have revealed the existence of two predominant genogroups of P. salmonis, LF-89-like and EM-90-like (Ramirez et al., 2015 ); (Nourdin-Galindo et al., 2017 ); (Saavedra et al., 2017 ); (Aravena et al., 2020 ), which have shown a variable spatiotemporal distribution in farms in southern Chile during the last years. These two genogroups, in addition to a variable distribution, present different surface antigenic structures and virulence; therefore, genetic surveillance has been defined as crucial to define effective vaccination strategies against Salmon Rickettsiosis Syndrome (Rozas-Serri et al., 2023 ); (Rozas-Serri et al., 2024 ); (Carril et al., 2023 ). Current vaccination in the salmon industry relies on formulations based mainly on isolates of the EM-90-like genogroup, such as the live attenuated vaccine introduced in 2016 and the pentavalent bacterin adopted since 2017 (Rozas-Serri et al., 2024 ). However, the combination of both vaccines has shown significant deficiencies in protection against infections by the LF-89-like genogroup, which has increased its prevalence to become the dominant genogroup in 2023, with an estimated rate of 94% (Rozas-Serri et al., 2024 ). These vaccine formulations, although they manage to stimulate a temporary and limited humoral response, do not generate a sufficiently strong or long-lasting cellular immune response (CMI) to effectively control SRS (Rozas-Serri et al., 2019 ); (Figueroa et al., 2020 ); (Vargas et al., 2021). The absence of complete cross-protection between the LF-89-like and EM-90-like genogroups highlights the need to develop new vaccines that incorporate representative antigenic sequences from both genogroups. In this sense, reverse vaccinology is positioned as a key tool to identify conserved and specific antigens from each genogroup, allowing the design of multivalent vaccines with greater protection potential. This strategy would not only address the genetic diversity of P. salmonis, but would also mitigate the limitations of current vaccines, improving their efficacy against co-infections and the increasing infection pressure from the LF-89-like genogroup. Based on this challenge, the present work includes the development of a multi-epitope nanostructured vaccine prototype, using antigens from the most relevant P. salmonis genogroups for salmonids on the Chilean coasts. This strategy is based on reverse vaccinology, which allows the identification of specific antigenic sequences from the pathogen genome and their subsequent use as vaccine candidates. Multi-epitope vaccines will be designed as structured nanoparticles, composed of high concentrations of antigenic proteins and presenting various degrees of packaging (de Marco et al., 2019 ). These nanoparticles assemble in the form of interdigitated amyloid and non-amyloid fibers (de Marco et al., 2019 ), and can incorporate variable amounts of the protein of interest in their secondary structure, depending on the production conditions (Gupta et al., 2013 ); (de Marco, 2013 ); (Seras-Franzoso et al., 2016 ). These nanoparticles could play a key role as natural vehicles for the delivery of therapeutic proteins in vaccine development, due to their highly desirable characteristics, such as mechanical and biological stability (Torrealba et al., 2016 ), low production cost (Thwaite et al., 2018 ); (Lopez-Cano et al., 2023); scalability (Torrealba et al.,2024); cell penetration capacity through endocytosis (Vazquez et al. 2012); (Seras-Franzoso et al. 2016 ), immunostimulatory trace drag (Thwaite et al., 2020 ), and sustained release over time (Lopez-cano et al., 2023) Recent advances have highlighted the transformative potential of reverse vaccinology in vaccine development and the identification of therapeutic targets (Alsowayeh & Albutti, 2022 ; Moxon et al., 2019 ; Solanki et al., 2019 ). This approach, based on the exploitation of genomic data through bioinformatics tools, has demonstrated its efficacy against various pathogens, such as Acinetobacter baumannii, where in silico analysis has allowed the identification of promising vaccine candidates from the bacterial proteome. For example, Alsowayeh et al. (2022) applied this strategy to design a multi-epitopic vaccine against Burkholderia cepacia, selecting highly conserved surface proteins and assembling immunogenic epitopes into an optimized construct, thus validating the ability of reverse vaccinology to generate specific and effective immunogens. In this context, we propose to use reverse vaccinology to preselect immunogenic epitopes of Piscirickettsia salmonis belonging to the LF-89-like and EM-90-like genogroups, with the aim of developing nanostructured vaccine prototypes based on multiple epitopes. This design would integrate key antigens from both genogroups, providing a more precise and effective approach for the control of Salmon Rickettsial Septicemia (SRS) in salmon. The present study seeks to establish new prophylactic strategies that respond to the growing need for innovative tools to confront this endemic disease in the aquaculture industry. 2. Materials and Methods 2.1 Design of multi-epitope amino acid sequences Through the application of the reverse vaccinology technique, key antigenic epitopes of Piscirickettsia salmonis, EM.90 and LF89, were identified. Based on these sequences, the amino acid sequence of four selected multi-epitope nanoparticle prototypes was designed. Using the subtractive proteomics approach, proteins that declared a predicted antigenic potential for vaccine development were selected. For this purpose, the BLAST tool of the SEED Viewer version 2.0 platform (Overbeek et al., 2014 ) was first used on the RAST server (Aziz et al., 2008 ), which allowed a search for sequences corresponding to these proteins to perform an alignment with the P. salmonis genogroups: strain LF-89 and strain EM-90. The antigenic property of all selected proteins was determined using the VaxiJen v2.0 web server ( http://www.ddg-pharmfac.net/vaxijen/VaxiJen/VaxiJen.html ) (Doytchinova & Flower, 2007 ). To determine the physicochemical characteristics of the selected proteins, the ProtParam tool ( https://web.expasy.org/protparam/ ) (Gasteiger et al., 2003 ) and the Protter tool ( http://wlab.ethz.ch/protter/start/ ) (Omasits et al., 2014 ) were used to predict the subcellular localization. Subsequently, the predicted proteins were modeled in their 3D structure by homology using the Phyre2 platforms ( http://www.sbg.bio.ic.ac.uk/phyre2/html/page.cgi?id=index ) (Kelley et al., 2015 ); SwissModel ( https://swissmodel.expasy.org/ ) (Waterhouse et al., 2018 ); ITASSER ( https://zhanggroup.org/I-TASSER/ ) (Yang & Zhang, 2015 ) and RaptorX ( http://raptorx.uchicago.edu/ ) (Källberg et al., 2012 ). The degree of homology between the models was determined with the QMEAN tool ( https://swissmodel.expasy.org/qmean/ ) of the SwissModel platform, which allows the quality of protein models to be assessed by considering the Z-score, a value that indicates the overall quality of the model and measures the deviation of the total energy of the structure with respect to an energy distribution derived from random conformations (Wiederstein & Sippl, 2007 ). Next, multi-epitope prediction was performed. For this, the predictions of the major histocompatibility complex class I and class II epitopes (MHC-I and MHC-II) were made by the RANKPEP server ( http://imed.med.ucm.es/Tools/rankpep.html ) (Reche et al., 2002 ). From the Rankpep server, those possible epitopes that presented an optimal score of > 20% were selected. The B cell epitope predictions were made with the BCPREDS online server ( https://webs.iiitd.edu.in/raghava/bcepred/index.html ) (Saha & Raghava, 2004 ). The prediction accuracy for models based on the combination of four amino acid properties (hydrophilicity, flexibility, polarity and exposed surface) reached 58.70%. Once the list of possible epitopes from both platforms (Rankpep and BCPREDS) was obtained, a comparative visual analysis was performed to identify matching amino acid sequences in both lists. Subsequently, using the VaxiJen 2.0 server (Doytchinova & Flower, 2007 ), the predicted antigenic level of the previously selected matching sequences was determined. Then, using the MHC I immunogenicity prediction tool, the IEDB server (Calis et al., 2012 ), the following were predicted: 1) the P4-6 positions of a presented peptide, which are more important for immunogenicity than other amino acids; 2) prediction of large and aromatic side chains of amino acids that are associated with immunogenicity. Therefore, according to these parameters, the epitopes that, according to the immunogenicity prediction, gave positive values were selected (Calis et al., 2013 ). Finally, the level of toxicity was analyzed using the ToxinPred server (Gupta et al., 2013 ). To continue, the visualization and structural characterization of the epitopes was carried out using the PyMOL server ( https://pymol.org/2/ ) (Schrodinger, 2015 ), and the peptide sequences were located in an alpha helix, a beta fold or a loop on the surface of the predicted proteins. Once the peptide sequences with chimeric characteristics were created, they were entered into the QUARK server ( https://zhanggroup.org/QUARK/ ) (from the Zhang Lab at the University of Michigan) for analysis and modeling (Xu and Zhang, 2012). The same chimeric sequences were entered into the ToxinPred platform to analyze the level of toxicity ( https://webs.iiitd.edu.in/raghava/toxinpred/protein.php ) (Gupta et al., 2013 ). Additionally, the level of antigenicity was evaluated using the VaxiJen v2.0 server (Gasteiger et al., 2003 ), ensuring that the selected chimeric proteins had an antigenic potential with a threshold ≥ 0.5. Subsequently, the SOLpro program ( http://scratch.proteomics.ics.uci.edu/ ) (Magnan et al., 2009 ), to predict the propensity of the primary structure of multi-epitope sequences to be soluble or insoluble after overexpression in Escherichia coli (E. coli). Additionally, the functional characterization of the chimeras was performed using the Expasy ProtParam server ( http://expasy.org/cgi-bin/protpraram ) (Gasteiger et al., 2003 ), determining the number of amino acids, the molecular weight, the isoelectric point (pI), the estimated half-life, the aliphatic index and the hydropathicity values (GRAVY). The latter was calculated using the hydropathy values of Kyte and Doolittle (Kyte & Doolittle, 1982 ) and adjusted to guarantee positive values that ensure an adequate hydrophobicity, contributing to the stability and functionality of the proteins. Based on these characteristics, four chimeric constructs were selected for production: Hoptech, SkipZ, PulseJ and HopQ. 2.2 Production and purification of nanostructured chimeric sequences. All designed constructs were fused at the C-terminus to a six-histidine (H6)-tag for subsequent protein purification. The codons of the sequences were optimized for overexpression in E. coli by GenScript (Hong Kong, China) and cloned into pET22b (ampR). Competent E. coli BL21 (DE3) bacteria were transformed by heat shock with pET22b (ampR) with the chimeric nucleotide sequences of each construct. Once transformed, E. coli BL21 was cultured in 500 mL with Luria Bertani (LB) medium supplemented with 50 µg/mL ampicillin (Winkler Ltda., Santiago, Chile), aerobically at 37°C with constant shaking (250 rpm) in the Labtech LSI-3016R0 incubator (Labtech, Namyangju, Korea). When reaching OD600nm between 0.6 and 0.9, it was induced with 1 mM IPTG (Merck, Darmstadt, Germany), for 3 hours. The culture was then centrifuged at 6,000 x g at 4°C for 15 min, the supernatant was decanted, and the pellet was resuspended in 10% of the final volume of lysis buffer (50 mM TrisHCl (pH 8.1), 100 mM NaCl and 1 mM EDTA) and stored at -80°C overnight. After thawing the cells at room temperature, 0.1 mg/mL lysozyme (Winkler Ltda, Santiago, Chile) and 0.5 mM phenylmethanesulfonylfluoride (PMSF, Roche Diagnostic, Mannheim, Germany) were added for 2 h at 37°C at 250 rpm. The mixture was then placed on ice and sonicated for 3 min (10 sec on, 10 sec off at 30% amplitude; Ultrasonic processor GE505) and then Triton X-100 (0.2% (v/v) (Winkler Ltda, Santiago, Chile) was added, stirring vigorously at room temperature for 1 h and left at -80°C overnight. To continue, DNA was removed with 1 µg/mL DNase (Roche Diagnostic, Mannheim, Germany) and 1 µg/mL MgSO4 (Roche Diagnostic, Mannheim, Germany) at 37°C for 1 h at 250 rpm. Nanoparticles were then collected by centrifugation (15,000 x g, 15 min, 4°C) and the supernatant was used as a soluble fraction control. Nanoparticles were then resuspended in lysis buffer and Triton X-100 (0.2% (v/v)) for 1 h. X-100 (0.2% (v/v)) (Winkler Ltda, Santiago, Chile). Subsequently, a sterility control was performed for each recombinant protein without antibiotics: 100 µL of suspension were cultured on LB agar plates at 37°C for 3 days. Finally, the samples were centrifuged at 4°C for 15 min at 15,000 xg. The quantification of each nanoparticle was evaluated by Western Blot (López-Cano et al., 2022 ), using the primary antibody anti-His (Thermo Fisher Scientific, Waltham, USA) and the secondary antibody Goat anti-mouse IgG (Thermo Fisher Scientific, Waltham, USA). The WBs were revealed in the ChemiDoc Imaging Systems Bio-Rad system (Bio-Rad Laboratories, Hercules, USA) and quantified with ImageJ software against a standard line of the soluble protein. Due to the null quantification of the Hoptech nanoprotein, it was discarded from future analysis. 2.3 Uptake of NPs by RTS-11 cells The monocyte/macrophage cell line from the spleen of rainbow trout RTS11 (Oncorhynchus mykiss) was used to analyze endocytosis by salmonid cells. Nanoparticles (NPs) labeled with the fluorophore atto-488 (Sigma-Aldrich, St. Louis, USA) were used in a 1:3 ratio to RTS-11 cell cultures that were 70–80% confluent. A total of 500,000 cells were stimulated at 20 µg/mL for 3 hours of incubation in minimal medium (2% Fetal Bovine Serum (FBS)). All experiments were performed in duplicate. After treatment, RTS11 cells were washed with PBS and incubated at 16°C with 1 mg/ml trypsin (Gibco) for 15 min. Cells were then pelleted by centrifugation at 200×g for 5 min at room temperature. Pellets were resuspended in PBS for flow cytometry using Gallios Flow Cytometer (Beckman Coulter, Brea, USA), and 10,000 events were analyzed. 2.4 Dose response evaluation by in vitro assay The expression of genes involved in antigen presentation was evaluated in the RTS11 cell line by RT-qPCR. For this, the nanoparticles were incubated in RTS11 at 18°C in Leibovitz L-15 medium (Thermo Fisher Scientific, Waltham, USA) supplemented with 10% FBS (Thermo Fisher Scientific, Waltham, USA). The cell cultures were stimulated for 12 hours with SkipZ, PulseJ, HopQ nanoparticles at 5, 10 and 20 µg/mL. As a positive control, 10 µg/mL LPS (lipopolysaccharides from Escherichia coli O111:B4; Sigma-Aldrich, St. Louis, USA) was used, iRFP (10 µg/mL) was used as a nanoparticle control, and 1X PBS was used as a negative control. Each treatment was performed in triplicate. Total RNA from the culture was extracted with TRIzol® (Thermo Fisher Scientific, Waltham, USA) following the manufacturer's instructions and quantified using the NanoDropTM device (Thermo Fisher Scientific, Waltham, USA). Residual DNA was removed, and 1 µg of RNA was used to synthesize cDNA using the RevertAid kit (Thermo Fisher Scientific, Waltham, USA) according to the manufacturer's instructions. Real-time quantitative PCR (qPCR) assays were performed on the AriaMX real-time PCR thermocycler (Agilent, Santa Clara, USA), using SYBR Green (KAPA SYBR® FAST, Merck, Darmstadt, Germany). Genes associated with antigen presentation were analyzed: cluster of differentiation 80/86 (cd80/86), cluster of differentiation 83 (cd83) and major histocompatibility complex class II (mhc-ii); as well as pro-inflammatory cytokines (interleukin one-beta (il1β) and tumor necrosis factor-alpha (tnfα)). Elongation factor 1 alpha (ef1α) was used as a normalizing agent (Table S1). Gene expression (fold change) was calculated using the Livak method (Livak & Schmittgen, 2001 ). 2.5 Immunofluorescence RTS11 cells were incubated with the nanoparticles for 12 hours at concentrations that showed a response in the relative gene expression analysis: SkipZ at 5 µg/mL, 10 µg/mL for PulseJ, and HopQ at 20 µg/mL. Adherent cells were then washed with 1X PBS and fixed with 4% paraformaldehyde (PFA) in 1X PBS for 10 min at RT, and permeabilized and blocked with 3% BSA with 0.3% Triton in 1X TBS for 30 min at RT; then, to prevent auto-fluorescence, quenching solution (50 mM ammonium chloride) was used for 10 min. Next, the cells were incubated overnight at 4°C with anti-CD80/86, CD83 and MHC-II monoclonal antibodies (1:200) synthesized against antigenic peptides of Atlantic salmon in CF-1 mice, according to Morales-Lange et al 2021 (Morales-Lange et al., 2021 ). The samples were washed with 1X TBS with 0.02% Tween-20 and incubated with the commercial secondary antibody Alexa fluortm 488 goat anti-mouse IgG, (Invitrogen, Thermo Scientific, Waltham, USA) diluted 1:700 for 90 min in the dark at room temperature. Nuclear staining was performed with DAPI (Vector Laboratories, Burlingame, USA) for conventional fluorescence microscopy, following the manufacturer's instructions. Images were captured using a Leica CTR5000 fluorescence microscope (Leica Microsystems, Wetzlar, Germany). 2.6 Statistical analysis Gene expression results by RT-qPCR were presented as means ± standard error of the mean (SEM) from triplicates obtained from three independent experiments (n = 3). All data were previously evaluated to verify compliance with the assumptions of the parametric tests, including normality, homogeneity of variances and independence. In case these assumptions were not met, non-parametric tests were applied. Gene expression data were normalized using the reference gene elf-1, and the changes in gene expression between the control and the different treatments were subsequently calculated, transformed to the log₂ Fold Change. Statistical analysis of the differences in expression levels was performed using the Wilcoxon test, with significance levels set at p < 0.05 (*). All statistical analyses and graphics were generated using R core Team software, 2021. 3. Results 3.1 First generation of multi-epitope nanoparticles Four nanoparticles with different peptide sequences and antigenic potential were designed and synthesized, derived from structural proteins of the LF-89 and EM-90 genogroups of P. salmonis. The four constructs were named: Hoptech, SkipZ, PulseJ and HopQ, for the continuation of the article (Fig. 1 ). The Hoptech nanoparticle was composed of 182 amino acid residues and included a His6 tag at the C-terminal end to facilitate its subsequent purification, resulting in a mature protein of 18.47 kDa. This nanoparticle presented an antigenic potential of 2, according to the VaxiJen server (Doytchinova & Flower, 2007 ) and a GRAVY hydropathicity index (Chang & Yang, 2013 ) of -0.606, suggesting high hydrophilicity and potential solubility. Similarly, SkipZ was designed with 194 residues, yielding a mature protein of 19.53 kDa and an antigenic potential of 2. GRAVY analysis yielded a value of -0.374, also indicating a trend towards hydrophilicity. PulseJ has 176 amino acid residues, yielding a mature protein of 18.12 kDa, with an antigenic potential according to Vaxijen of 2 and a GRAVY index of -0.374. Finally, HopQ has 178 residues, yielding a mature protein of 17.5 kDa, with an antigenic potential of 2.2 and a GRAVY index of 0.05 suggesting lower hydrophilicity compared to the other nanoparticles. These features suggest that the designed nanoparticles could have a favorable behavior in terms of solubility and immunological efficacy. Each nanoparticle (NPs) was formed from the N- to the C-terminus from a combination of peptide sequences with antigenic potential originating from: outer membrane, secretion system, kinases, chaperones, flagellars, lysosomal glycoprotein, cytoskeletal, transferases and ribosomal of the LF-89 and EM-90 genogroups of P. salmonis (Supplementary Fig. 2). 3.2 Characterization of Nanoparticles Three of the four nanoparticles were successfully produced in E. coli as bacterial inclusion bodies (NPs) with low to very good yield. In the case of SkipZ, a production yield of 286 mg/mL was obtained, PulseJ a yield of 143 mg/mL, and HopQ a yield of 78 mg/mL was obtained (Supplementary Fig. 4). Although Hoptech NPs were produced, their production yield was low (results not shown), which is why it was discarded for future trials. The positive control iRFP was successfully produced with efficiencies of 186 mg/mL. 3.3 Endocytosis of NPs in the RST-11 cell line The chimeric nanoparticles were endocytosed by the Rainbow Trout monocyte/macrophage line RTS11. Using fluorescence emission flow cytometry, HopQ uptake was observed to be more efficient than that observed for PulseJ and SkipZ, reaching approximately 54% fluorescent cells at 20 µg/mL compared to 26% fluorescent cells induced by PulseJ and 5% by SkipZ at the same concentration, for 4 hours (Fig. 4 ). 3.4 Gene expression analysis in RST-11 stimulated with NPs Gene expression analysis of immune response genes was evaluated in the RTS-11 cell line after stimulation with multi-epitope nanoparticles (NPs). RTS-11 cells were incubated with SkipZ, PulseJ, HopQ at concentrations of 5, 10 and 20 µg/mL for 12 hours. As controls, cells without stimulation (negative control), LPS (10 µg/mL) as a positive control of innate immune response activation, and iRFP nanoproteins (10 µg/mL) as a control of nanoproteins without immunological relevance were used. The results demonstrated that SkipZNP stimulation induced a significant increase in the expression of genes related to antigen presentation, such as co-stimulatory molecules major histocompatibility complex class II (MHC-II), cluster of differentiation 86 (CD86), cluster of differentiation 83 (CD83), and proinflammatory cytokines such as interleukin 1-beta, IL1b, and tumor necrosis factor alpha (TNF-α) (p < 0.005) at all doses tested. These findings suggest that SkipZcan enhance the activation of the immune system in the RTS-11 cell line (Fig. 5 ). Figure 6 presents the gene expression results of PulseJ-stimulated cells. When analyzing the expression of the mhc-ii and cd86 genes, the results show that stimulation with PulseJ at 5 and 10 µg/mL induced a significant increase in the expression of these markers compared to the controls (p < 0.05). While, for the gene expression of cd83 a significant increase was only observed at 5 µg/mL, moreover, as the concentration of PulseJ increases, the expression of cd83 tends to decrease significantly, up to 20 µg/mL (p < 0.005). The same behavior is observed in the proinflammatory cytokines il1b and tnfα, the data show that as the concentration increases (from 5 µg/mL to 20 µg/mL), a progressive underexpression of these proinflammatory genes occurs. In contrast to LPS which shows an increase in the gene expression of these cytokines, in the same way as the positive control without immunological relevance iRFP which increases its expression significantly (p < 0.005) for both cytokines. A similar behavior to SkipZ was observed with the induction of HopQ at the three doses evaluated (Fig. 7 ). The gene expression of mhc-ii, cd86 and cd83 showed a significant increase at all concentrations tested. However, the greatest increase in expression was observed at the concentration of 20 µg/mL, where the expression of these genes was significantly higher compared to the concentrations of 5 and 10 µg/mL (p < 0.005). When observing the expression of il1b and tnfα, although all doses exerted a significant increase in expression (p < 0.005), at 5 and 20 µg/mL it generated a greater increase in the expression of proinflammatory cytokines. 3.5 NP-induced antigen presentation in cell culture Induction with 5 µg/mL SkipZ, 10 µg/mL PulseJ, and 20 µg/mL HopQ in the RTS11 cell line resulted in increased fluorescence activity of surface markers involved in antigen presentation, such as MHC-II, CD83, and CD86. In particular, HopQNP at 20 µg/mL showed a significant fluorescence signal associated with MHC-II, CD83, and CD86 (green) compared to negative controls and to the iRFP nanoprotein positive control, which has no immunological relevance. 4. Discussion Recent studies have shown that the reverse vaccinology approach allows the identification of vaccine candidates and drug targets (Alsowayeh & Albutti, 2022 ; Moxon et al., 2019 ; Solanki et al., 2019 ). In this context, this project proposes the use of this strategy for the preselection of immunogenic epitopes of Piscirickettsia salmonis belonging to the LF-89 and EM-90 genogroups, which could serve as potential targets for vaccine development. These peptide sequences with chimeric characteristics have the function of activating the immune system of fish by enhancing a cellular response through the activation of antigen-presenting cells and Th1-type lymphocytes. Currently, there are few studies that address approaches similar to the present study, in which chimeric antigenic sequences of a specific pathogen are incorporated and produced in the form of inclusion bodies. A related study is the one carried out by Roca-Pinilla et al. ( 2022 ), in which multidomain recombinant proteins with antimicrobial activity were designed, using host defense peptides (HDPs) fused to GFP and more advanced configurations without carriers. These multidomain proteins were specifically designed to include multiple domains with conserved and functional epitopes, which can be recognized and processed by antigen-presenting cells (APCs) and subsequently presented to T lymphocytes. This approach significantly increased the probability of activating specific T lymphocytes, promoting the generation of a long-lasting immune memory. Inclusion bodies (IBs) present an amyloidogenic behavior, similar to that of natural functional amyloids (Céspedes et al., 2016 ). This amyloid network ensures a stable fibrous scaffold, which confers both mechanical stability and high porosity, allowing them to be used as functional biomaterials. In this context, previous studies have shown that the size and surface characteristics of IBs directly influence their cellular uptake. For example, particles larger than 4 µm have difficulties in reaching secondary lymphoid organs (Folgueira et al., 2015 ), while smaller nanoparticles have a greater internalization capacity (Rojas-Peña et al., 2022 ). The evidence of IB uptake by cells differs according to their size. In the case of the RTS-11 cell line, derived from the spleen of rainbow trout (Oncorhynchus mykiss), which exhibits monocyte/macrophage characteristics and is commonly used to study immune responses in fish; the uptake efficiency was lower than that observed in other cell lines, such as those derived from zebrafish (ZFL) (Rojas-Peña et a., 2022) or human Hela cells (Roca-Pinilla et al. 2020 ). In summary, in the study by Rojas-Peña and collaborators (Rojas-Peña et al., 2022 ), the internalization of recombinant Spring viremia of carp (SVCV) antigen G nanoparticles was evaluated with the gamma interferon module (SVCV-IFN) that showed efficiencies of 100 and 90% in ZFL cells. On the other hand, (Vázquez et al., 2012), managed to internalize 100% of the GFP-IBs into Hela cells, compared to the 5, 26 and 56% uptake observed in this article, using RTS-11. The difference in uptake can be attributed to the membrane receptor profile of each cell line, as well as the size of the cells used and hydrophobic characteristics of each nanoprotein. Once taken up by RTS-11 cells, it is suggested that nanoproteins, like HDPs, interact with pattern recognition receptors (PRRs), such as Toll-like receptors (TLRs), present on the surface of antigen-presenting cells (APCs). This interaction triggers intracellular signaling pathways that favor the uptake, processing, and presentation of antigens by the major histocompatibility complex (MHC). This process is crucial for the activation of T lymphocytes, triggering an adaptive immune response. To evaluate this mechanism, genes involved in antigen presentation were analyzed, such as MHC-II, CD80/86, and CD83, whose expression in fish can vary significantly depending on immunological stimuli. It has been shown that MHC-II, mainly expressed in B cells and dendritic cells, plays an essential role in antigen presentation and responds significantly to exogenous antigens and T cell-dependent antigens (Xing et al., 2023 ). CD80/86 is mainly found on antigen-presenting cells and could help elicit humoral immune responses in teleosts through the CD80/86-CD28 signaling pathway involving CD4 + lymphocytes. For example, Morales-Lange and co-workers (Morales-Lange et al., 2021 ) demonstrated that interferon gamma (IFNγ) can induce overexpression of these markers in Atlantic salmon splenocytes, suggesting a role in modulating immune responses through antigen-presenting cells (APCs). Similarly, Nombela and co-workers (Nombela et al., 2019 ) reported that exposure to viral hemorrhagic septicemia virus leads to an increase in the expression of MHC I and II, as well as CD86 and CD83 in rainbow trout, indicating a robust activation of antigen-processing mechanisms. Furthermore, dendritic cell (DC) maturation is associated with increased expression of these markers, as shown in studies involving various stimuli, including lipopolysaccharides (Lakho et al., 2020 ; Sepulcre et al., 2009 ). The latter has been shown to be able to induce the overexpression of proinflammatory cytokines such as TNFα, IL-1β and IL-6. LPS activates the TLR4 signaling pathway, resulting in increased secretion of TNF-α and IL-6 by macrophages (Arranz et al., 2012 ; Li et al., 2018 ). This activation is mediated by various intracellular signaling cascades, including the PI3K/Akt pathway, which is essential for the production of proinflammatory mediators (Arranz et al., 2012 ). This is in agreement with the results obtained, where LPS acts as a positive control of the inflammatory response. Taken together, these findings underline the critical role of specific cytokines and pathogens in modulating the expression of key immune markers in fish, thus improving their immune response capacity. In our study, SkipZ and especially HopQ NPs were able to increase the expression of genes involved in antigen presentation and T cell activation (such as cd86, mhc-ii, and cd83) and proinflammatory cytokines (such as il-1β and tnf-α) in a dose-dependent manner at low (5 µg/mL) and high (20 µg/mL) concentrations. On the other hand, PulseJ showed a lower expression profile than the positive control (iRFP), suggesting that sequences with antigenic potential can, in some cases, generate a modulation of the immune response, significantly decreasing the production of proinflammatory cytokines. These results support the hypothesis that the designed chimeric antigenic sequences improve the intrinsic biological capacity of nanoparticles. The use of modular protein nanoparticles (NPs) derived from inclusion bodies (IBs) to improve the efficacy of antiviral vaccines in fish, specifically against spring viremia of carp virus (SVCV), has been investigated. The study concluded that IBs, when used as NPs, not only act as antigen delivery vehicles, but also function as immunostimulants. They promote the activation of genes related to the inflammatory and antiviral response, such as vig1, mx, lmp2, and ifngr1 (Rojas-Peña et al. 2022 ). Furthermore, Puente Marín (Puente-Marin et al., 2019 ) demonstrated that trout erythrocytes, despite not being phagocytic, can internalize IBs and modulate the expression of immune genes. For example, TNFα IBs reduce the expression of genes related to antigen presentation (such as cd83 and mhcI), while VHSV glycoprotein G IBs (IBfrg16G − VHSV) activate genes involved in the antiviral response, such as mx and mhcII, and in the production of cytokines such as il6 and il2. These antecedents support the hypothesis that the incorporation of sequences with antigenic potential of the pathogen can be captured by fish macrophage cells, which would trigger an immune response. This is achieved by activating antigen presentation and the costimulation necessary for a complete activation of T cells, particularly CD8 + cells and the Th1 response, which includes the production of cytokines such as interferon gamma (IFNγ), essential to control and eliminate P. salmonis (Rozas-Serri et al., 2024 ). 5. Conclusions In this study, a prototype of a nanostructured multi-epitope vaccine targeting Piscirickettsia salmonis, the pathogen responsible for Piscirickettsiosis in salmonids, was developed and evaluated. Using reverse vaccinology tools, four nanoparticles (SkipZ, PulseJ, HopQ and Hoptech) derived from the LF-89 and EM-90 genogroups, prevalent in Chilean aquaculture, were designed. The results showed that the nanoparticles, particularly SkipZ and HopQ, induce a significant immune response in the RTS-11 macrophage cell line, stimulating the expression of key markers in antigen presentation, as well as the production of proinflammatory cytokines. Furthermore, the study highlights the use of inclusion body (IB) nanoparticles as antigen vehicles, which not only serve as platforms for epitope presentation, but also act as immunomodulators, enhancing the immune response. This multi-epitope nanoparticle-based approach could represent a promising alternative for the control of Piscirickettsiosis, offering a potential solution to improve the efficacy of vaccines in the field. The incorporation of multiple epitopes derived from the predominant genogroups allows addressing the genetic diversity of the pathogen, which could result in a more durable and effective protection in aquaculture. This work addresses a proof of concept at laboratory scale, being the first step that will allow continuing with the challenge with the pathogen under controlled conditions. Declarations Supplementary Materials: The following supporting information can be downloaded at: Author Contributions: Conceptualization, P.V.-A and D.T.; methodology, P.V.-A, D.T., D.L., M.P., N.S.-P.; software, P.V.-A; validation, P.V.-A, D.L; formal analysis, P.V.-A and D.T; investigation, P.V.-A, D.T., D.L.; resources, D.T., L.M., C.F. and J.G.-M.; data curation, P.V.-A and D.T.; writing—original draft preparation, P.V.-A; writing—review and editing, P.V.-A., N.S.-P., E.G.-F., A.A., M.P., C.F., L.M., J.G.-M. and D.T.; visualization, P.V.-A, D.T., C.F, N.S.-P., E.G.-F. and A.A.; supervision, D.T., J.G.-M. and L.M.; project administration, P.V.-A.; funding acquisition, P.V.-A. D.T. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by ANID, Proyecto de Tesis de doctorado en el sector productive No. TDP220008 granted by P.V.-A. and was supported by ANID Doctoral Scholarship No. 21220464 D.L. was supported by ANID Doctoral Scholarship No. 21232344.N.S.-P. was supported by Pontificia Universidad Católica de Valparaíso as a postdoctoral fellowship (Proyecto VINCI-PUCV Postdoctorado. D.T. was supported by ANID, FONDECYT de Iniciación No. 11240684. Institutional Review Board Statement: The study was approved by the bioethics committee of Pontificia Universidad Católica de Valparaíso BIOEPUCV-B 395-2021. Informed Consent Statement: Not applicable. Data Availability Statement: The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation, to any qualified researcher. Acknowledgments: Conflicts of Interest: The authors declare no conflicts of interest. References Adams, A. (2019). Progress, challenges and opportunities in fish vaccine development. Fish & Shellfish Immunology , 90 , 210-214. https://doi.org/10.1016/j.fsi.2019.04.066 Alsowayeh, N., & Albutti, A. (2022). Designing a novel chimeric multi-epitope vaccine against Burkholderia pseudomallei, a causative agent of melioidosis. Frontiers in Medicine , 9 . https://doi.org/10.3389/fmed.2022.945938 Aravena, P., Pulgar, R., Ortiz-Severín, J., Maza, F., Gaete, A., Martínez, S., Serón, E., González, M., & Cambiazo, V. (2020). PCR-RFLP Detection and Genogroup Identification of Piscirickettsia salmonis in Field Samples. Pathogens , 9 (5), 358. https://doi.org/10.3390/pathogens9050358 Arranz, A., Doxaki, C., Vergadi, E., Martinez De La Torre, Y., Vaporidi, K., Lagoudaki, E. D., Ieronymaki, E., Androulidaki, A., Venihaki, M., Margioris, A. N., Stathopoulos, E. N., Tsichlis, P. N., & Tsatsanis, C. (2012). Akt1 and Akt2 protein kinases differentially contribute to macrophage polarization. Proceedings of the National Academy of Sciences , 109 (24), 9517-9522. https://doi.org/10.1073/pnas.1119038109 Aziz, R. K., Bartels, D., Best, A. A., DeJongh, M., Disz, T., Edwards, R. A., Formsma, K., Gerdes, S., Glass, E. M., Kubal, M., Meyer, F., Olsen, G. J., Olson, R., Osterman, A. L., Overbeek, R. A., McNeil, L. K., Paarmann, D., Paczian, T., Parrello, B.,…Zagnitko, O. (2008). The RAST server: Rapid annotations using subsystems technology. Bmc Genomics , 9 , Article 75. https://doi.org/10.1186/1471-2164-9-75 Cabello, F. C., Godfrey, H. P., Tomova, A., Ivanova, L., Dolz, H., Millanao, A., & Buschmann, A. H. (2013). Antimicrobial use in aquaculture re-examined: its relevance to antimicrobial resistance and to animal and human health. Environmental Microbiology , 15 (7), 1917-1942. https://doi.org/10.1111/1462-2920.12134 Calis, J.J.A., De Boer, R.J., Keşmir, C., 2012. Degenerate T-cell Recognition of Peptides on MHC Molecules Creates Large Holes in the T-cell Repertoire. PLOS Computational Biology 8, e1002412.. https://doi.org/10.1371/journal.pcbi.1002412 Calis, J.J.A., Maybeno, M., Greenbaum, J.A., Weiskopf, D., De Silva, A.D., Sette, A., Keşmir, C., Peters, B., 2013. Properties of MHC Class I Presented Peptides That Enhance Immunogenicity. PLOS Computational Biology 9, e1003266. https://doi.org/10.1371/journal.pcbi.1003266 Carril, G., Winther-Larsen, H.C., Løvoll, M., Sørum, H., 2023. Cohabitation of Piscirickettsia salmonis genogroups (LF-89 and EM-90): synergistic effect on growth dynamics. Frontiers in Cellular and Infection Microbiology 13. https://doi.org/10.3389/fcimb.2023.1253577 Caruffo, M., Vidal, S., Santis, L., Siel, D., Perez, O., Huenchullan, P. R., & Saenz, L. (2021). Effectiveness of a proteoliposome-based vaccine against salmonid rickettsial septicaemia in Oncorhynchus mykiss. Veterinary Research , 52 (1), Article 111. https://doi.org/10.1186/s13567-021-00982-2 Céspedes, M. V., Fernández, Y., Unzueta, U., Mendoza, R., Seras-Franzoso, J., Sánchez-Chardi, A., Álamo, P., Toledo-Rubio, V., Ferrer-Miralles, N., Vázquez, E., Schwartz, S., Abasolo, I., Corchero, J. L., Mangues, R., & Villaverde, A. (2016). Bacterial mimetics of endocrine secretory granules as immobilized in vivo depots for functional protein drugs. Scientific Reports , 6 (1), 35765. https://doi.org/10.1038/srep35765 Chang, K. Y., & Yang, J.-R. (2013). Analysis and Prediction of Highly Effective Antiviral Peptides Based on Random Forests. PLoS ONE , 8 (8), e70166. https://doi.org/10.1371/journal.pone.0070166 Consejo del Salmón, Chile. (2022). Informe de Exportaciones de Salmón y Trucha, cierre año 2022 [Informe]. de Marco, A. (2013). Recombinant polypeptide production in E. coli: towards a rational approach to improve the yields of functional proteins. Microbial Cell Factories , 12 , Article 101. https://doi.org/10.1186/1475-2859-12-101 de Marco, A., Ferrer-Miralles, N., Garcia-Fruitos, E., Mitraki, A., Peternel, S., Rinas, U., Trujillo-Roldan, M. A., Valdez-Cruz, N. A., Vazquez, E., & Villaverde, A. (2019). Bacterial inclusion bodies are industrially exploitable amyloids. Fems Microbiology Reviews , 43 (1), 53-72. https://doi.org/10.1093/femsre/fuy038 Doytchinova, I. A., & Flower, D. R. (2007). VaxiJen: a server for prediction of protective antigens, tumour antigens and subunit vaccines. Bmc Bioinformatics , 8 , Article 4. https://doi.org/10.1186/1471-2105-8-4 Figueroa, C., Bustos, P., Torrealba, D., Dixon, B., Soto, C., Conejeros, P., & Gallardo, J. A. (2017). Coinfection takes its toll: Sea lice override the protective effects of vaccination against a bacterial pathogen in Atlantic salmon. Scientific Reports , 7 , Article 17817. https://doi.org/10.1038/s41598-017-18180-6 Figueroa, C., Veloso, P., Espin, L., Dixon, B., Torrealba, D., Elalfy, I. S., Afonso, J. M., Soto, C., Conejeros, P., & Gallardo, J. A. (2020). Host genetic variation explains reduced protection of commercial vaccines against Piscirickettsia salmonis in Atlantic salmon. Scientific Reports , 10 (1), Article 18252. https://doi.org/10.1038/s41598-020-70847-9 Folgueira, I., Noia, M., Blanco-Abad, V., Mallo, N., Leiro, J.M., & Lamas, J. (2015). Particle size and traffic of phagocytes between the turbot peritoneal cavity and lymphoid organs. Fish & shellfish immunology, 44 2 , 652-61 Gasteiger, E., Gattiker, A., Hoogland, C., Ivanyi, I., Appel, R. D., & Bairoch, A. (2003). ExPASy: the proteomics server for in-depth protein knowledge and analysis. Nucleic Acids Research , 31 (13), 3784-3788. https://doi.org/10.1093/nar/gkg563 Gupta, S., Kapoor, P., Chaudhary, K., Gautam, A., Kumar, R., Raghava, G. P. S., & Open Source Drug, D. (2013). In Silico Approach for Predicting Toxicity of Peptides and Proteins. Plos One , 8 (9), Article e73957. https://doi.org/10.1371/journal.pone.0073957 Gupta, S. K., & Shukla, P. (2016). Advanced technologies for improved expression of recombinant proteins in bacteria: perspectives and applications. Critical reviews in biotechnology , 36 (6), 1089–1098. https://doi.org/10.3109/07388551.2015.1084264 Ji, J., Torrealba, D., Thwaite, R., Gomez, A. C., Parra, D., & Roher, N. (2019). Nanostructured TNF alpha protein targets the zebrafish (Danio rerio) immune system through mucosal surfaces and improves the survival after Mycobacterium marinum lethal infection. Aquaculture , 510 , 138-149. https://doi.org/10.1016/j.aquaculture.2019.05.050 Källberg, M., Wang, H., Wang, S., Peng, J., Wang, Z., Lu, H., & Xu, J. (2012). Template-based protein structure modeling using the RaptorX web server. Nature Protocols , 7 (8), 1511-1522. https://doi.org/10.1038/nprot.2012.085 Kelley, L. A., Mezulis, S., Yates, C. M., Wass, M. N., & Sternberg, M. J. E. (2015). The Phyre2 web portal for protein modeling, prediction and analysis. Nature Protocols , 10 (6), 845-858. https://doi.org/10.1038/nprot.2015.053 Kennedy, D. A., Kurath, G., Brito, I. L., Purcell, M. K., Read, A. F., Winton, J. R., & Wargo, A. R. (2016). Potential drivers of virulence evolution in aquaculture. Evolutionary Applications , 9 (2), 344-354. https://doi.org/10.1111/eva.12342 Kyte, J., & Doolittle, R. F. (1982). A SIMPLE METHOD FOR DISPLAYING THE HYDROPATHIC CHARACTER OF A PROTEIN. Journal of Molecular Biology , 157 (1), 105-132. https://doi.org/10.1016/0022-2836(82)90515-0 Lakho, S. A., Haseeb, M., Huang, J., Yang, Z., Hasan, M. W., Aleem, M. T., Naqvi, M. A.-U.-H., Memon, M. A., Song, X., Yan, R., Xu, L., & Li, X. (2020). Glyceraldehyde-3-phosphate dehydrogenase from Eimeria acervulina modulates the functions of chicken dendritic cells to boost Th1 type immune response and stimulates autologous CD4+ T cells differentiation in-vitro. Veterinary Research , 51 (1). https://doi.org/10.1186/s13567-020-00864-z Li, Y., Lu, Z., Ru, J. H., Lopes-Virella, M. F., Lyons, T. J., & Huang, Y. (2018). Saturated fatty acid combined with lipopolysaccharide stimulates a strong inflammatory response in hepatocytes in vivo and in vitro. American Journal of Physiology-Endocrinology and Metabolism , 315 (5), E745-E757. https://doi.org/10.1152/ajpendo.00015.2018 Livak, K. J., & Schmittgen, T. D. (2001). Analysis of relative gene expression data using real-time quantitative PCR and the 2(T)(-Delta Delta C) method. Methods , 25 (4), 402-408. https://doi.org/10.1006/meth.2001.1262 López-Cano, A., Martínez-Miguel, M., Guasch, J., Ratera, I., Arís, A., & Garcia-Fruitós, E. (2022). Exploring the impact of the recombinant Escherichia coli strain on defensins antimicrobial activity: BL21 versus Origami strain. Microbial Cell Factories , 21 (1). https://doi.org/10.1186/s12934-022-01803-7 Magnan, C. N., Randall, A., & Baldi, P. (2009). SOLpro: accurate sequence-based prediction of protein solubility. Bioinformatics , 25 (17), 2200-2207. https://doi.org/10.1093/bioinformatics/btp386 Maisey, K., Montero, R., & Christodoulides, M. (2017). Vaccines for piscirickettsiosis (salmonid rickettsial septicaemia, SRS): the Chile perspective. Expert Review of Vaccines , 16 (3), 215-228. https://doi.org/10.1080/14760584.2017.1244483 Martinez, D., Diaz-Ibarrola, D., Vargas-Lagos, C., Oyarzun, R., Pontigo, J. P., Munoz, J. L. P., Yanez, A. J., & Vargas-Chacoff, L. (2018). Immunological response of the Sub-Antarctic Notothenioid fish Eleginops maclovinus injected with two strains of Piscirickettsia salmonis. Fish & Shellfish Immunology , 75 , 139-148. https://doi.org/10.1016/j.fsi.2018.01.012 Morales-Lange, B., Ramirez-Cepeda, F., Schmitt, P., Guzman, F., Lagos, L., Overland, M., Wong-Benito, V., Imarai, M., Fuentes, D., Boltana, S., Alcaino, J., Soto, C., & Mercado, L. (2021). Interferon Gamma Induces the Increase of Cell-Surface Markers (CD80/86, CD83 and MHC-II) in Splenocytes From Atlantic Salmon. Frontiers in Immunology , 12 , Article 666356. https://doi.org/10.3389/fimmu.2021.666356 Moxon, R., Reche, P. A., & Rappuoli, R. (2019). Editorial: Reverse Vaccinology. Frontiers in Immunology , 10 . https://doi.org/10.3389/fimmu.2019.02776 Nombela, I., Requena-Platek, R., Morales-Lange, B., Chico, V., Puente-Marin, S., Ciordia, S., Mena, M., Coll, J., Perez, L., Mercado, L., & Ortega-Villaizan, M. (2019). Rainbow Trout Red Blood Cells Exposed to Viral Hemorrhagic Septicemia Virus Up-Regulate Antigen-Processing Mechanisms and MHC I&II, CD86, and CD83 Antigen-presenting Cell Markers. Cells , 8 (5), 386. https://doi.org/10.3390/cells8050386 Nourdin-Galindo, G., Sanchez, P., Molina, C. F., Espinoza-Rojas, D. A., Oliver, C., Ruiz, P., Vargas-Chacoff, L., Carcamo, J. G., Figueroa, J. E., Mancilla, M., Maracaja-Coutinho, V., & Yanez, A. J. (2017). Comparative Pan-Genome Analysis of Piscirickettsia salmonis Reveals Genomic Divergences within Genogroups. Frontiers in Cellular and Infection Microbiology , 7 , Article 459. https://doi.org/10.3389/fcimb.2017.00459 Omasits, U., Ahrens, C. H., Muller, S., & Wollscheid, B. (2014). Protter: interactive protein feature visualization and integration with experimental proteomic data. Bioinformatics , 30 (6), 884-886. https://doi.org/10.1093/bioinformatics/btt607 Overbeek, R., Olson, R., Pusch, G. D., Olsen, G. J., Davis, J. J., Disz, T., Edwards, R. A., Gerdes, S., Parrello, B., Shukla, M., Vonstein, V., Wattam, A. R., Xia, F. F., & Stevens, R. (2014). The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST). Nucleic Acids Research , 42 (D1), D206-D214. https://doi.org/10.1093/nar/gkt1226 Pontigo, J. P., Espinoza, C., Hernandez, M., Nourdin, G., Oliver, C., Avendano-Herrera, R., Figueroa, J., Rauch, C., Troncoso, J. M., Vargas-Chacoff, L., & Yanez, A. J. (2021). Protein-Based Vaccine Protect Against Piscirickettsia salmonis in Atlantic Salmon (Salmo salar). Frontiers in Immunology , 12 , Article 602689. https://doi.org/10.3389/fimmu.2021.602689 Puente-Marin, S., Thwaite, R., Mercado, L., Coll, J., Roher, N., & Ortega-Villaizan, M. D. M. (2019). Fish Red Blood Cells Modulate Immune Genes in Response to Bacterial Inclusion Bodies Made of TNFα and a G-VHSV Fragment. Frontiers in Immunology , 10 . https://doi.org/10.3389/fimmu.2019.01055 Ramirez, R., Gomez, F. A., & Marshall, S. H. (2015). The infection process of Piscirickettsia salmonis in fish macrophages is dependent upon interaction with host-cell clathrin and actin. Fems Microbiology Letters , 362 (1). https://doi.org/10.1093/femsle/fnu012 Reche, P. A., Glutting, J. P., & Reinherz, E. L. (2002). Prediction of MHC class I binding peptides using profile motifs. Human Immunology , 63 (9), 701-709, Article Pii s0198-8859(02)00432-9. https://doi.org/10.1016/s0198-8859(02)00432-9 Roca-Pinilla, R., López-Cano, A., Saubi, C., Garcia-Fruitós, E., Arís, A., 2020. A new generation of recombinant polypeptides combines multiple protein domains for effective antimicrobial activity. Microbial Cell Factories 19.. https://doi.org/10.1186/s12934-020-01380-7 Roca-Pinilla, R., Lisowski, L., Arís, A., Garcia-Fruitós, E., 2022. The future of recombinant host defense peptides. Microbial Cell Factories 21.. https://doi.org/10.1186/s12934-022-01991-2 Rojas-Peña, M., Aceituno, P., Salvador, M. E., Garcia-Ordoñez, M., Teles, M., Ortega-Villaizan, M. D. M., Perez, L., & Roher, N. (2022). How modular protein nanoparticles may expand the ability of subunit anti-viral vaccines: The spring viremia carp virus (SVCV) case. Fish & shellfish immunology , 131 , 1051–1062. https://doi.org/10.1016/j.fsi.2022.10.067 Rozas-Serri, M. (2022). Why Does Piscirickettsia salmonis Break the Immunological Paradigm in Farmed Salmon? Biological Context to Understand the Relative Control of Piscirickettsiosis. Frontiers in Immunology , 13 , Article 856896. https://doi.org/10.3389/fimmu.2022.856896 Rozas-Serri, M., Pena, A., & Maldonado, L. (2019). Gene expression associated with immune response in Atlantic salmon head-kidney vaccinated with inactivated whole-cell bacterin of Piscirickettsia salmonis and pathogenic isolates. Fish & Shellfish Immunology , 93 , 789-795. https://doi.org/10.1016/j.fsi.2019.08.031 Rozas-Serri, M., Peña, A., Arriagada, G., Enríquez, R., & Maldonado, L. (2018). Comparison of gene expression in post-smolt Atlantic salmon challenged by LF-89-like and EM-90-likePiscirickettsia salmonisisolates reveals differences in the immune response associated with pathogenicity. Journal of Fish Diseases , 41 (3), 539-552. https://doi.org/10.1111/jfd.12756 Rozas-Serri, M., Peña, A., Gardner, I., Peñaloza, E., Maldonado, L., Muñoz, A., Mardones, F. O., Rodríguez, C., Ildefonso, R., Senn, C., & Aranis, F. (2023). Co-Infection by LF-89-Like and EM-90-Like Genogroups of Piscirickettsia Salmonis in Farmed Atlantic Salmon in Chile: Implications for Surveillance and Control of Piscirickettsiosis. Pathogens , 12 (3), 450. https://doi.org/10.3390/pathogens12030450 Rozas‐Serri, M., Kani, T., Jaramillo, V., Correa, R., Ildefonso, R., Rabascall, C., Barrientos, S., Coñuecar, D., & Peña, A. (2024). Current vaccination strategy against Piscirickettsia salmonis in Chile based only on the EM-90 genogroup shows incomplete cross-protection for the LF-89 genogroup. Fish & shellfish immunology , 109893 Saavedra, J., Hernandez, N., Osses, A., Castillo, A., Cancino, A., Grothusen, H., Navas, E., Henriquez, P., Bohle, H., Bustamante, F., Bustos, P., & Mancilla, M. (2017). Prevalence, geographic distribution and phenotypic differences of Piscirickettsia salmonis EM-90-like isolates. Journal of Fish Diseases , 40 (8), 1055-1063. https://doi.org/10.1111/jfd.12581 SAG. (2024). PRODUCTOS BIOLÓGICOS INMUNOLÓGICOS CON REGISTRO PROVISIONAL USO EN SALMÓNIDOS. Saha S., & Raghava, G. P. S. (2004). BcePred: Prediction of continuous B-cell epitopes in antigenic sequences using physico-chemical properties. Artificial Immune Systems, Proceedings , 3239 , 197-204 Schrodinger, LLC. (2015). The PyMOL Molecular Graphics System,Version 1.8 Sepulcre, M. P., Alcaraz-Perez, F., Lopez-Munoz, A., Roca, F. J., Meseguer, J., Cayuela, M. L., & Mulero, V. (2009). Evolution of Lipopolysaccharide (LPS) Recognition and Signaling: Fish TLR4 Does Not Recognize LPS and Negatively Regulates NF-kappa B Activation. Journal of Immunology , 182 (4), 1836-1845. https://doi.org/10.4049/jimmunol.0801755 Seras-Franzoso, J., Sanchez-Chardi, A., Garcia-Fruitos, E., Vazquez, E., & Villaverde, A. (2016). Cellular uptake and intracellular fate of protein releasing bacterial amyloids in mammalian cells. Soft Matter , 12 (14), 3451-3460. https://doi.org/10.1039/c5sm02930a SERNAPESCA. (2022). Informe sobre uso de antimicrobianos en la salmonicultura nacional. In. Subdirección de Acuicultura Departamento de Salud Animal Valparaíso. SERNAPESCA. (2023). Informe con antecedentes sanitarios de agua dulce y mar año 1° semestre 2023. Departamento de Salud Animal. SERNAPESCA b. (2023). Informe sobre uso de antimicrobianos y antiparasitarios en la salmonicultura nacional. Departamento de salud animal SERNAPESCA. (2024).Informe con antecedentes sanitarios de agua dulce y mar. Departamento Salud Animal. Solanki, V., Tiwari, M., & Tiwari, V. (2019). Prioritization of potential vaccine targets using comparative proteomics and designing of the chimeric multi-epitope vaccine against Pseudomonas aeruginosa. Scientific Reports , 9 (1). https://doi.org/10.1038/s41598-019-41496-4 Sommerset, I., Krossoy, B., Biering, E., & Frost, P. (2005). Vaccines for fish in aquaculture. Expert Review of Vaccines , 4 (1), 89-101. https://doi.org/10.1586/14760584.4.1.89 Thwaite, R., Ji, J., Torrealba, D., Coll, J., Sabés, M., Villaverde, A., & Roher, N. (2018). Protein Nanoparticles Made of Recombinant Viral Antigens: A Promising Biomaterial for Oral Delivery of Fish Prophylactics. Frontiers in immunology , 9 , 1652. https://doi.org/10.3389/fimmu.2018.01652 Thwaite, R., Berbel, C., Aparicio, M., Torrealba, D., Pesarrodona, M., Villaverde, A., Borrego, J.J., Manchado, M., Roher, N., 2020. Nanostructured recombinant protein particles raise specific antibodies against the nodavirus NNV coat protein in sole. Fish & Shellfish Immunology 99, 578–586.. https://doi.org/10.1016/j.fsi.2020.02.029 Tobar, I., Arancibia, S., Torres, C., Vera, V., Soto, P., Carrasco, C., Alvarado, M., Neira, E., Arcos, S., & Tobar, J. A. (2015). Successive oral immunizations against Piscirickettsia salmonis and infectious salmon anemia virus are required to maintain a long-term protection in farmed salmonids. Frontiers in Immunology , 6 , Article 244. https://doi.org/10.3389/fimmu.2015.00244 Torrealba, D., Seras-Franzoso, J., Mamat, U., Wilke, K., Villaverde, A., Roher, N., & Garcia-Fruitos, E. (2016). Complex Particulate Biomaterials as Immunostimulant-Delivery Platforms. Plos One , 11 (10), Article e0164073. https://doi.org/10.1371/journal.pone.0164073 Torrealba, D., López, D., Zelada, P., Salinas-Parra, N., Valenzuela-Avilés, P., Garcia-Fruitós, E., Arís, A., Mercado, L., Altamirano, C., & Gallardo-Matus, J. (2024). Immunomodulation Evidence of Nanostructured Recombinant Proteins in Salmonid Cells. Animals : an open access journal from MDPI, 14(6), 844. https://doi.org/10.3390/ani14060844 Valenzuela-Aviles, P., Torrealba, D., Figueroa, C., Mercado, L., Dixon, B., Conejeros, P., & Gallardo-Matus, J. (2022). Why vaccines fail against Piscirickettsiosis in farmed salmon and trout and how to avoid it: A review. Frontiers in Immunology , 13 . https://doi.org/10.3389/fimmu.2022.1019404 Vasquez, I., Retamales, J., Parra, B., Machimbirike, V., Robeson, J., & Santander, J. (2023). Comparative Genomics of a Polyvalent Escherichia-Salmonella Phage fp01 and In Silico Analysis of Its Receptor Binding Protein and Conserved Enterobacteriaceae Phage Receptor. Viruses , 15 (2), 379. https://doi.org/10.3390/v15020379 Wang, L., Maji, S. K., Sawaya, M. R., Eisenberg, D., & Riek, R. (2008). Bacterial Inclusion Bodies Contain Amyloid-Like Structure. PLoS Biology , 6 (8), e195. https://doi.org/10.1371/journal.pbio.0060195 Waterhouse, A., Bertoni, M., Bienert, S., Studer, G., Tauriello, G., Gumienny, R., Heer, F. T., de Beer, T. A. P., Rempfer, C., Bordoli, L., Lepore, R., & Schwede, T. (2018). SWISS-MODEL: homology modelling of protein structures and complexes. Nucleic Acids Research , 46 (W1), W296-W303. https://doi.org/10.1093/nar/gky427 Wiederstein, M., & Sippl, M. J. (2007). ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Research , 35 , W407-W410. https://doi.org/10.1093/nar/gkm290 Xing, J., An, Z., Tang, X., Sheng, X., Chi, H., & Zhan, W. (2023). Expression and Immune Characterization of Major Histocompatibility Complex in Paralichthys olivaceus after Antigen Stimulation. Biology , 12 (12), 1464. https://doi.org/10.3390/biology12121464 Yang, J. Y., & Zhang, Y. (2015). I-TASSER server: new development for protein structure and function predictions. Nucleic Acids Research , 43 (W1), W174-W181. https://doi.org/10.1093/nar/gkv342 Additional Declarations The authors declare potential competing interests as follows: The authors declare no conflicts of interest. Supplementary Files MaterialSuplementario.docx Material suplementario Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5941909","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":409898850,"identity":"ead62f78-c9de-465b-bca1-7eb47199febb","order_by":0,"name":"Paula","email":"data:image/png;base64,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","orcid":"","institution":"Valenzuela-Avilés","correspondingAuthor":true,"prefix":"","firstName":"","middleName":"","lastName":"Paula","suffix":""}],"badges":[],"createdAt":"2025-02-01 12:56:51","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":true,"conflictsOfInterestStatement":true,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":true},"doi":"10.21203/rs.3.rs-5941909/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5941909/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":75382307,"identity":"56799114-d88a-4dd6-bcbc-da45be0dd6c9","added_by":"auto","created_at":"2025-02-04 03:10:28","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":227557,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic representation of diagram of the multi-epitope subunit vaccine construct against \u003cem\u003eP. salmonis\u003c/em\u003e. A) Selection of genogroups. B) Indicates the selection of proteins with antigenic potential. C) Represents the prediction of peptides with antigenic potential. D) Encompasses the construction of the chimeric protein.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5941909/v1/b28775ae230dfdbf10d6953e.png"},{"id":75381444,"identity":"41f72975-9610-45c4-90c8-25e095c1764f","added_by":"auto","created_at":"2025-02-04 03:02:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":128665,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 4. Endocytosis of nanoparticles by RTS-11 cells. Cells were exposed to 20 ug/mL of each NP for 4 hours, with n = 3 biological replicates.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5941909/v1/9dfce92474340b86d9b069ef.png"},{"id":75381447,"identity":"7dcb349b-752c-4bee-9d60-ac0c275a8a37","added_by":"auto","created_at":"2025-02-04 03:02:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":101567,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 5. Gene expression analysis in RTS11 cells stimulated with SkipZ, LPS and iRFP. Cells were incubated with 10 μg/ml iRFP, 10 μg/ml LPS, and 5.10 and 20 μg/mL SkipZ for 12 hours. RT-qPCR analyzes were normalized with the ef-1 gene, and the results are presented as means ± SEMs of triplicates from three independent experiments (n = 3). Differences between the treatment means and controls were analyzed by Wilcox-test. Differences in transcription levels are indicated by asterisks (Doytchinova \u0026amp; Flower), p-value is considered * p \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5941909/v1/cd2a6d2219a26f6c99d7716c.png"},{"id":75381451,"identity":"1859ea64-8303-48ef-bde3-4913d8523cd9","added_by":"auto","created_at":"2025-02-04 03:02:28","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":92685,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 6. Gene expression analysis in RTS-11 cells stimulated with PulseJ, LPS and iRFP. Cells were incubated with 10 μg/ml iRFP, 10 μg/ml LPS, and 5.10 and 20 μg/mL PulseJ for 12 hours. RT-qPCR analyzes were normalized with the ef-1 gene, and the results are presented as means ± SEMs of triplicates from three independent experiments (n = 3). Differences between the treatment means and controls were analyzed by Wilcox-test. Differences in transcription levels are indicated by asterisks (Doytchinova \u0026amp; Flower), p-value is considered * p \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-5941909/v1/082ffd3f5039d1ec7f199f0b.png"},{"id":75381454,"identity":"174cfa2c-d592-4a89-a002-3cb6a35a6bf0","added_by":"auto","created_at":"2025-02-04 03:02:28","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":107501,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 7. Gene expression analysis in RTS11 cells stimulated with HopQ, LPS and iRFP. Cells were incubated with 10 μg/ml iRFP, 10 μg/ml LPS, and 5.10 and 20 μg/mL HopQ for 12 hours. RT-qPCR analyzes were normalized with the ef-1 gene, and the results are presented as means ± SEMs of triplicates from three independent experiments (n = 3). Differences between the treatment means and controls were analyzed by the Wilcox-test. Differences in transcription levels are indicated by asterisks (Doytchinova \u0026amp; Flower), p-value is considered * p \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-5941909/v1/16547b7e59da3717a9e3de9c.png"},{"id":75382660,"identity":"34a9dbf3-74cf-4e0c-9b49-c6d70f322d44","added_by":"auto","created_at":"2025-02-04 03:18:29","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":200388,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 8. Analysis of protein expression by immunofluorescence of the 3 proposed nanoparticles in the RST11 cell line stimulated with 5 µg/mL de SkipZ\u003csup\u003eNP\u003c/sup\u003e; 10 µg/mL de PulseJ\u003csup\u003eNP \u003c/sup\u003ey 20 µg/mL de HopQ\u003csup\u003eNP\u003c/sup\u003e for 12 hours. A) Expression of the anti-MHC-II antibody. B) Expression of the anti-CD83 antibody. C) Expression of the anti-CD86 antibody. As controls, the negative control (with water) and control without immunological relevance iRFP (10 ug/mL) were used.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-5941909/v1/50830a4b39845b8cd9134aeb.png"},{"id":75383406,"identity":"b447cb99-3489-4c71-8d7a-67894fad85d1","added_by":"auto","created_at":"2025-02-04 03:26:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1547623,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5941909/v1/dbeaf931-f018-4117-b9b3-72b859c5f126.pdf"},{"id":75381448,"identity":"077d5cce-534c-47eb-b89c-295bcc5406cb","added_by":"auto","created_at":"2025-02-04 03:02:28","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1683686,"visible":true,"origin":"","legend":"\u003cp\u003eMaterial suplementario\u003c/p\u003e","description":"","filename":"MaterialSuplementario.docx","url":"https://assets-eu.researchsquare.com/files/rs-5941909/v1/aa84186b26a4f64c1ed92ba0.docx"}],"financialInterests":"The authors declare potential competing interests as follows: The authors declare no conflicts of interest.","formattedTitle":"\u003cp\u003e\u003cstrong\u003ePrototype of a nanostructured multi-epitope vaccine for the control of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ePiscirickettsiosis\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e: Proof-of concept in salmonid cells\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eIn recent years, Chile has established itself as a world leader in salmonid exports. In 2022, exports totaled 751,259 tons, generating a commercial value of US\u003cspan\u003e$\u003c/span\u003e 6,606\u0026nbsp;million (Chile, 2022). However, salmon farming faces significant challenges, especially in relation to infectious diseases in farms. In particular, mortality caused by infectious factors is a critical problem, representing 26.9% of deaths in Atlantic salmon (SERNAPESCA, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The main health challenge of the salmon farming industry in Chile is Salmon Rickettsial Syndrome (SRS) (Maisey et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e); (SERNAPESCA, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) caused by the intracellular pathogen Piscirickettsia salmonis. This pathogen is responsible for 44.7% of deaths due to infectious causes, significantly affecting salmon in the fattening phase (SERNAPESCA, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). As the fish are close to the harvest period, the economic impact caused by P. salmonis is significant, resulting in estimated losses for the industry of around US\u003cspan\u003e$\u003c/span\u003e 700\u0026nbsp;million annually. These economic losses related to mortality added to the cost of prophylactic treatments decrease the competitiveness of Chilean salmon compared to its main competitor, Norway (Maisey et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e); (Caruffo et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In 2023, more than 93.21% of the 338.9 tons of antimicrobial compounds used in marine waters were used to treat Piscirickettsiosis (SERNAPESCAb, 2023). Although the use of antibiotics mitigates the effects of this disease, its extensive use carries environmental, regulatory and public health risks (Cabello et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Despite the decrease in the antibiotic consumption index in aquaculture (ICA) from 0.063% in 2015 to 0.031% in 2023, equivalent to 338.9 tons of antibiotics compared to 1,107,109 tons of harvested biomass, these figures are still alarmingly high (SERNAPESCA b, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough vaccines have been considered essential for the development of salmon farming worldwide (Sommerset et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), their effectiveness against P. salmonis has been limited (Caruffo et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In Chile, there are approximately 17 provisionally registered vaccines authorized for commercialization against Piscirickettsiosis (SAG, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, recent evidence suggests persistent susceptibility to the disease, possibly due to decreased vaccine-induced immunity and/or immunological compromise associated with co-infections and stress (Figueroa et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) (Figueroa et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e); (Valenzuela-Aviles et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Despite the sustained use of P. salmonis vaccines, the consensus within the industry is that the long-term protection provided by them remains low (Rozas-Serri et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2023\u003c/span\u003e); (Tobar et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). In the last nine years, an average of 1.1\u0026nbsp;billion doses of vaccines have been administered in Chilean aquaculture, of which approximately 50% were used to prevent Piscirickettsiosis (Valenzuela-Aviles et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Currently marketed SRS vaccines include bacterins with inactivated or attenuated live pathogens, as well as subunit vaccines, which manage to delay the onset of infection but do not effectively prevent the continuous outbreaks affecting fish farms (Martinez et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The high mortality rates observed in the field can be explained by a combination of intrinsic and extrinsic factors. Intrinsic factors include inherent biological characteristics such as family group, sex, and population variations, which directly affect the efficacy of vaccines due to the wide heritable genetic diversity in fish (Figueroa et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Figueroa et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). On the other hand, extrinsic factors include environmental and ecological conditions such as temperature, salinity, sea lion attacks, algal blooms, co-infections with ectoparasites, and the variable virulence of the different genogroups of Piscirickettsia salmonis. These external factors are often not adequately considered in the design and development of current vaccines, which negatively impacts their effectiveness under real-life culture conditions (Figueroa et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Valenzuela-Avil\u0026eacute;s et al., 2022).\u003c/p\u003e \u003cp\u003ePangenomic analyses have revealed the existence of two predominant genogroups of P. salmonis, LF-89-like and EM-90-like (Ramirez et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2015\u003c/span\u003e); (Nourdin-Galindo et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2017\u003c/span\u003e); (Saavedra et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2017\u003c/span\u003e); (Aravena et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), which have shown a variable spatiotemporal distribution in farms in southern Chile during the last years. These two genogroups, in addition to a variable distribution, present different surface antigenic structures and virulence; therefore, genetic surveillance has been defined as crucial to define effective vaccination strategies against Salmon Rickettsiosis Syndrome (Rozas-Serri et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2023\u003c/span\u003e); (Rozas-Serri et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2024\u003c/span\u003e); (Carril et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Current vaccination in the salmon industry relies on formulations based mainly on isolates of the EM-90-like genogroup, such as the live attenuated vaccine introduced in 2016 and the pentavalent bacterin adopted since 2017 (Rozas-Serri et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, the combination of both vaccines has shown significant deficiencies in protection against infections by the LF-89-like genogroup, which has increased its prevalence to become the dominant genogroup in 2023, with an estimated rate of 94% (Rozas-Serri et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These vaccine formulations, although they manage to stimulate a temporary and limited humoral response, do not generate a sufficiently strong or long-lasting cellular immune response (CMI) to effectively control SRS (Rozas-Serri et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2019\u003c/span\u003e); (Figueroa et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e); (Vargas et al., 2021). The absence of complete cross-protection between the LF-89-like and EM-90-like genogroups highlights the need to develop new vaccines that incorporate representative antigenic sequences from both genogroups. In this sense, reverse vaccinology is positioned as a key tool to identify conserved and specific antigens from each genogroup, allowing the design of multivalent vaccines with greater protection potential. This strategy would not only address the genetic diversity of P. salmonis, but would also mitigate the limitations of current vaccines, improving their efficacy against co-infections and the increasing infection pressure from the LF-89-like genogroup.\u003c/p\u003e \u003cp\u003eBased on this challenge, the present work includes the development of a multi-epitope nanostructured vaccine prototype, using antigens from the most relevant P. salmonis genogroups for salmonids on the Chilean coasts. This strategy is based on reverse vaccinology, which allows the identification of specific antigenic sequences from the pathogen genome and their subsequent use as vaccine candidates.\u003c/p\u003e \u003cp\u003eMulti-epitope vaccines will be designed as structured nanoparticles, composed of high concentrations of antigenic proteins and presenting various degrees of packaging (de Marco et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). These nanoparticles assemble in the form of interdigitated amyloid and non-amyloid fibers (de Marco et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), and can incorporate variable amounts of the protein of interest in their secondary structure, depending on the production conditions (Gupta et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2013\u003c/span\u003e); (de Marco, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2013\u003c/span\u003e); (Seras-Franzoso et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). These nanoparticles could play a key role as natural vehicles for the delivery of therapeutic proteins in vaccine development, due to their highly desirable characteristics, such as mechanical and biological stability (Torrealba et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), low production cost (Thwaite et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2018\u003c/span\u003e); (Lopez-Cano et al., 2023); scalability (Torrealba et al.,2024); cell penetration capacity through endocytosis (Vazquez et al. 2012); (Seras-Franzoso et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), immunostimulatory trace drag (Thwaite et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and sustained release over time (Lopez-cano et al., 2023)\u003c/p\u003e \u003cp\u003eRecent advances have highlighted the transformative potential of reverse vaccinology in vaccine development and the identification of therapeutic targets (Alsowayeh \u0026amp; Albutti, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Moxon et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Solanki et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This approach, based on the exploitation of genomic data through bioinformatics tools, has demonstrated its efficacy against various pathogens, such as Acinetobacter baumannii, where in silico analysis has allowed the identification of promising vaccine candidates from the bacterial proteome. For example, Alsowayeh et al. (2022) applied this strategy to design a multi-epitopic vaccine against Burkholderia cepacia, selecting highly conserved surface proteins and assembling immunogenic epitopes into an optimized construct, thus validating the ability of reverse vaccinology to generate specific and effective immunogens.\u003c/p\u003e \u003cp\u003eIn this context, we propose to use reverse vaccinology to preselect immunogenic epitopes of Piscirickettsia salmonis belonging to the LF-89-like and EM-90-like genogroups, with the aim of developing nanostructured vaccine prototypes based on multiple epitopes. This design would integrate key antigens from both genogroups, providing a more precise and effective approach for the control of Salmon Rickettsial Septicemia (SRS) in salmon. The present study seeks to establish new prophylactic strategies that respond to the growing need for innovative tools to confront this endemic disease in the aquaculture industry.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Design of multi-epitope amino acid sequences\u003c/h2\u003e\n \u003cp\u003eThrough the application of the reverse vaccinology technique, key antigenic epitopes of Piscirickettsia salmonis, EM.90 and LF89, were identified. Based on these sequences, the amino acid sequence of four selected multi-epitope nanoparticle prototypes was designed. Using the subtractive proteomics approach, proteins that declared a predicted antigenic potential for vaccine development were selected. For this purpose, the BLAST tool of the SEED Viewer version 2.0 platform (Overbeek et al., \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e) was first used on the RAST server (Aziz et al., \u003cspan class=\"CitationRef\"\u003e2008\u003c/span\u003e), which allowed a search for sequences corresponding to these proteins to perform an alignment with the P. salmonis genogroups: strain LF-89 and strain EM-90. The antigenic property of all selected proteins was determined using the VaxiJen v2.0 web server (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.ddg-pharmfac.net/vaxijen/VaxiJen/VaxiJen.html\u003c/span\u003e\u003c/span\u003e) (Doytchinova \u0026amp; Flower, \u003cspan class=\"CitationRef\"\u003e2007\u003c/span\u003e). To determine the physicochemical characteristics of the selected proteins, the ProtParam tool (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://web.expasy.org/protparam/\u003c/span\u003e\u003c/span\u003e) (Gasteiger et al., \u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e) and the Protter tool (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://wlab.ethz.ch/protter/start/\u003c/span\u003e\u003c/span\u003e) (Omasits et al., \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e) were used to predict the subcellular localization. Subsequently, the predicted proteins were modeled in their 3D structure by homology using the Phyre2 platforms (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.sbg.bio.ic.ac.uk/phyre2/html/page.cgi?id=index\u003c/span\u003e\u003c/span\u003e) (Kelley et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e); SwissModel (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://swissmodel.expasy.org/\u003c/span\u003e\u003c/span\u003e) (Waterhouse et al., \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e); ITASSER (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://zhanggroup.org/I-TASSER/\u003c/span\u003e\u003c/span\u003e) (Yang \u0026amp; Zhang, \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e) and RaptorX (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://raptorx.uchicago.edu/\u003c/span\u003e\u003c/span\u003e) (K\u0026auml;llberg et al., \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e). The degree of homology between the models was determined with the QMEAN tool (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://swissmodel.expasy.org/qmean/\u003c/span\u003e\u003c/span\u003e) of the SwissModel platform, which allows the quality of protein models to be assessed by considering the Z-score, a value that indicates the overall quality of the model and measures the deviation of the total energy of the structure with respect to an energy distribution derived from random conformations (Wiederstein \u0026amp; Sippl, \u003cspan class=\"CitationRef\"\u003e2007\u003c/span\u003e). Next, multi-epitope prediction was performed. For this, the predictions of the major histocompatibility complex class I and class II epitopes (MHC-I and MHC-II) were made by the RANKPEP server (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://imed.med.ucm.es/Tools/rankpep.html\u003c/span\u003e\u003c/span\u003e) (Reche et al., \u003cspan class=\"CitationRef\"\u003e2002\u003c/span\u003e). From the Rankpep server, those possible epitopes that presented an optimal score of \u0026gt;\u0026thinsp;20% were selected. The B cell epitope predictions were made with the BCPREDS online server (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://webs.iiitd.edu.in/raghava/bcepred/index.html\u003c/span\u003e\u003c/span\u003e) (Saha \u0026amp; Raghava, \u003cspan class=\"CitationRef\"\u003e2004\u003c/span\u003e). The prediction accuracy for models based on the combination of four amino acid properties (hydrophilicity, flexibility, polarity and exposed surface) reached 58.70%. Once the list of possible epitopes from both platforms (Rankpep and BCPREDS) was obtained, a comparative visual analysis was performed to identify matching amino acid sequences in both lists. Subsequently, using the VaxiJen 2.0 server (Doytchinova \u0026amp; Flower, \u003cspan class=\"CitationRef\"\u003e2007\u003c/span\u003e), the predicted antigenic level of the previously selected matching sequences was determined. Then, using the MHC I immunogenicity prediction tool, the IEDB server (Calis et al., \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e), the following were predicted: 1) the P4-6 positions of a presented peptide, which are more important for immunogenicity than other amino acids; 2) prediction of large and aromatic side chains of amino acids that are associated with immunogenicity. Therefore, according to these parameters, the epitopes that, according to the immunogenicity prediction, gave positive values were selected (Calis et al., \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e). Finally, the level of toxicity was analyzed using the ToxinPred server (Gupta et al., \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e). To continue, the visualization and structural characterization of the epitopes was carried out using the PyMOL server (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pymol.org/2/\u003c/span\u003e\u003c/span\u003e) (Schrodinger, \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e), and the peptide sequences were located in an alpha helix, a beta fold or a loop on the surface of the predicted proteins. Once the peptide sequences with chimeric characteristics were created, they were entered into the QUARK server (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://zhanggroup.org/QUARK/\u003c/span\u003e\u003c/span\u003e) (from the Zhang Lab at the University of Michigan) for analysis and modeling (Xu and Zhang, 2012). The same chimeric sequences were entered into the ToxinPred platform to analyze the level of toxicity (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://webs.iiitd.edu.in/raghava/toxinpred/protein.php\u003c/span\u003e\u003c/span\u003e) (Gupta et al., \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e). Additionally, the level of antigenicity was evaluated using the VaxiJen v2.0 server (Gasteiger et al., \u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e), ensuring that the selected chimeric proteins had an antigenic potential with a threshold\u0026thinsp;\u0026ge;\u0026thinsp;0.5. Subsequently, the SOLpro program (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://scratch.proteomics.ics.uci.edu/\u003c/span\u003e\u003c/span\u003e) (Magnan et al., \u003cspan class=\"CitationRef\"\u003e2009\u003c/span\u003e), to predict the propensity of the primary structure of multi-epitope sequences to be soluble or insoluble after overexpression in Escherichia coli (E. coli). Additionally, the functional characterization of the chimeras was performed using the Expasy ProtParam server (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://expasy.org/cgi-bin/protpraram\u003c/span\u003e\u003c/span\u003e) (Gasteiger et al., \u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e), determining the number of amino acids, the molecular weight, the isoelectric point (pI), the estimated half-life, the aliphatic index and the hydropathicity values (GRAVY). The latter was calculated using the hydropathy values of Kyte and Doolittle (Kyte \u0026amp; Doolittle, \u003cspan class=\"CitationRef\"\u003e1982\u003c/span\u003e) and adjusted to guarantee positive values that ensure an adequate hydrophobicity, contributing to the stability and functionality of the proteins. Based on these characteristics, four chimeric constructs were selected for production: Hoptech, SkipZ, PulseJ and HopQ.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2 Production and purification of nanostructured chimeric sequences.\u003c/h2\u003e\n \u003cp\u003eAll designed constructs were fused at the C-terminus to a six-histidine (H6)-tag for subsequent protein purification. The codons of the sequences were optimized for overexpression in E. coli by GenScript (Hong Kong, China) and cloned into pET22b (ampR). Competent E. coli BL21 (DE3) bacteria were transformed by heat shock with pET22b (ampR) with the chimeric nucleotide sequences of each construct. Once transformed, E. coli BL21 was cultured in 500 mL with Luria Bertani (LB) medium supplemented with 50 \u0026micro;g/mL ampicillin (Winkler Ltda., Santiago, Chile), aerobically at 37\u0026deg;C with constant shaking (250 rpm) in the Labtech LSI-3016R0 incubator (Labtech, Namyangju, Korea). When reaching OD600nm between 0.6 and 0.9, it was induced with 1 mM IPTG (Merck, Darmstadt, Germany), for 3 hours. The culture was then centrifuged at 6,000 x g at 4\u0026deg;C for 15 min, the supernatant was decanted, and the pellet was resuspended in 10% of the final volume of lysis buffer (50 mM TrisHCl (pH 8.1), 100 mM NaCl and 1 mM EDTA) and stored at -80\u0026deg;C overnight. After thawing the cells at room temperature, 0.1 mg/mL lysozyme (Winkler Ltda, Santiago, Chile) and 0.5 mM phenylmethanesulfonylfluoride (PMSF, Roche Diagnostic, Mannheim, Germany) were added for 2 h at 37\u0026deg;C at 250 rpm. The mixture was then placed on ice and sonicated for 3 min (10 sec on, 10 sec off at 30% amplitude; Ultrasonic processor GE505) and then Triton X-100 (0.2% (v/v) (Winkler Ltda, Santiago, Chile) was added, stirring vigorously at room temperature for 1 h and left at -80\u0026deg;C overnight. To continue, DNA was removed with 1 \u0026micro;g/mL DNase (Roche Diagnostic, Mannheim, Germany) and 1 \u0026micro;g/mL MgSO4 (Roche Diagnostic, Mannheim, Germany) at 37\u0026deg;C for 1 h at 250 rpm. Nanoparticles were then collected by centrifugation (15,000 x g, 15 min, 4\u0026deg;C) and the supernatant was used as a soluble fraction control. Nanoparticles were then resuspended in lysis buffer and Triton X-100 (0.2% (v/v)) for 1 h. X-100 (0.2% (v/v)) (Winkler Ltda, Santiago, Chile). Subsequently, a sterility control was performed for each recombinant protein without antibiotics: 100 \u0026micro;L of suspension were cultured on LB agar plates at 37\u0026deg;C for 3 days. Finally, the samples were centrifuged at 4\u0026deg;C for 15 min at 15,000 xg. The quantification of each nanoparticle was evaluated by Western Blot (L\u0026oacute;pez-Cano et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e), using the primary antibody anti-His (Thermo Fisher Scientific, Waltham, USA) and the secondary antibody Goat anti-mouse IgG (Thermo Fisher Scientific, Waltham, USA). The WBs were revealed in the ChemiDoc Imaging Systems Bio-Rad system (Bio-Rad Laboratories, Hercules, USA) and quantified with ImageJ software against a standard line of the soluble protein. Due to the null quantification of the Hoptech nanoprotein, it was discarded from future analysis.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3 Uptake of NPs by RTS-11 cells\u003c/h2\u003e\n \u003cp\u003eThe monocyte/macrophage cell line from the spleen of rainbow trout RTS11 (Oncorhynchus mykiss) was used to analyze endocytosis by salmonid cells. Nanoparticles (NPs) labeled with the fluorophore atto-488 (Sigma-Aldrich, St. Louis, USA) were used in a 1:3 ratio to RTS-11 cell cultures that were 70\u0026ndash;80% confluent. A total of 500,000 cells were stimulated at 20 \u0026micro;g/mL for 3 hours of incubation in minimal medium (2% Fetal Bovine Serum (FBS)). All experiments were performed in duplicate. After treatment, RTS11 cells were washed with PBS and incubated at 16\u0026deg;C with 1 mg/ml trypsin (Gibco) for 15 min. Cells were then pelleted by centrifugation at 200\u0026times;g for 5 min at room temperature. Pellets were resuspended in PBS for flow cytometry using Gallios Flow Cytometer (Beckman Coulter, Brea, USA), and 10,000 events were analyzed.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e2.4 Dose response evaluation by in vitro assay\u003c/h2\u003e\n \u003cp\u003eThe expression of genes involved in antigen presentation was evaluated in the RTS11 cell line by RT-qPCR. For this, the nanoparticles were incubated in RTS11 at 18\u0026deg;C in Leibovitz L-15 medium (Thermo Fisher Scientific, Waltham, USA) supplemented with 10% FBS (Thermo Fisher Scientific, Waltham, USA). The cell cultures were stimulated for 12 hours with SkipZ, PulseJ, HopQ nanoparticles at 5, 10 and 20 \u0026micro;g/mL. As a positive control, 10 \u0026micro;g/mL LPS (lipopolysaccharides from Escherichia coli O111:B4; Sigma-Aldrich, St. Louis, USA) was used, iRFP (10 \u0026micro;g/mL) was used as a nanoparticle control, and 1X PBS was used as a negative control. Each treatment was performed in triplicate. Total RNA from the culture was extracted with TRIzol\u0026reg; (Thermo Fisher Scientific, Waltham, USA) following the manufacturer\u0026apos;s instructions and quantified using the NanoDropTM device (Thermo Fisher Scientific, Waltham, USA). Residual DNA was removed, and 1 \u0026micro;g of RNA was used to synthesize cDNA using the RevertAid kit (Thermo Fisher Scientific, Waltham, USA) according to the manufacturer\u0026apos;s instructions. Real-time quantitative PCR (qPCR) assays were performed on the AriaMX real-time PCR thermocycler (Agilent, Santa Clara, USA), using SYBR Green (KAPA SYBR\u0026reg; FAST, Merck, Darmstadt, Germany). Genes associated with antigen presentation were analyzed: cluster of differentiation 80/86 (cd80/86), cluster of differentiation 83 (cd83) and major histocompatibility complex class II (mhc-ii); as well as pro-inflammatory cytokines (interleukin one-beta (il1\u0026beta;) and tumor necrosis factor-alpha (tnf\u0026alpha;)). Elongation factor 1 alpha (ef1\u0026alpha;) was used as a normalizing agent (Table S1). Gene expression (fold change) was calculated using the Livak method (Livak \u0026amp; Schmittgen, \u003cspan class=\"CitationRef\"\u003e2001\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003e2.5 Immunofluorescence\u003c/h2\u003e\n \u003cp\u003eRTS11 cells were incubated with the nanoparticles for 12 hours at concentrations that showed a response in the relative gene expression analysis: SkipZ at 5 \u0026micro;g/mL, 10 \u0026micro;g/mL for PulseJ, and HopQ at 20 \u0026micro;g/mL. Adherent cells were then washed with 1X PBS and fixed with 4% paraformaldehyde (PFA) in 1X PBS for 10 min at RT, and permeabilized and blocked with 3% BSA with 0.3% Triton in 1X TBS for 30 min at RT; then, to prevent auto-fluorescence, quenching solution (50 mM ammonium chloride) was used for 10 min. Next, the cells were incubated overnight at 4\u0026deg;C with anti-CD80/86, CD83 and MHC-II monoclonal antibodies (1:200) synthesized against antigenic peptides of Atlantic salmon in CF-1 mice, according to Morales-Lange et al \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e (Morales-Lange et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). The samples were washed with 1X TBS with 0.02% Tween-20 and incubated with the commercial secondary antibody Alexa fluortm 488 goat anti-mouse IgG, (Invitrogen, Thermo Scientific, Waltham, USA) diluted 1:700 for 90 min in the dark at room temperature. Nuclear staining was performed with DAPI (Vector Laboratories, Burlingame, USA) for conventional fluorescence microscopy, following the manufacturer\u0026apos;s instructions. Images were captured using a Leica CTR5000 fluorescence microscope (Leica Microsystems, Wetzlar, Germany).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003e2.6 Statistical analysis\u003c/h2\u003e\n \u003cp\u003eGene expression results by RT-qPCR were presented as means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error of the mean (SEM) from triplicates obtained from three independent experiments (n\u0026thinsp;=\u0026thinsp;3). All data were previously evaluated to verify compliance with the assumptions of the parametric tests, including normality, homogeneity of variances and independence. In case these assumptions were not met, non-parametric tests were applied. Gene expression data were normalized using the reference gene elf-1, and the changes in gene expression between the control and the different treatments were subsequently calculated, transformed to the log₂ Fold Change. Statistical analysis of the differences in expression levels was performed using the Wilcoxon test, with significance levels set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (*). All statistical analyses and graphics were generated using R core Team software, 2021.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1 First generation of multi-epitope nanoparticles\u003c/h2\u003e\n \u003cp\u003eFour nanoparticles with different peptide sequences and antigenic potential were designed and synthesized, derived from structural proteins of the LF-89 and EM-90 genogroups of P. salmonis. The four constructs were named: Hoptech, SkipZ, PulseJ and HopQ, for the continuation of the article (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). The Hoptech nanoparticle was composed of 182 amino acid residues and included a His6 tag at the C-terminal end to facilitate its subsequent purification, resulting in a mature protein of 18.47 kDa. This nanoparticle presented an antigenic potential of 2, according to the VaxiJen server (Doytchinova \u0026amp; Flower, \u003cspan class=\"CitationRef\"\u003e2007\u003c/span\u003e) and a GRAVY hydropathicity index (Chang \u0026amp; Yang, \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e) of -0.606, suggesting high hydrophilicity and potential solubility. Similarly, SkipZ was designed with 194 residues, yielding a mature protein of 19.53 kDa and an antigenic potential of 2. GRAVY analysis yielded a value of -0.374, also indicating a trend towards hydrophilicity. PulseJ has 176 amino acid residues, yielding a mature protein of 18.12 kDa, with an antigenic potential according to Vaxijen of 2 and a GRAVY index of -0.374. Finally, HopQ has 178 residues, yielding a mature protein of 17.5 kDa, with an antigenic potential of 2.2 and a GRAVY index of 0.05 suggesting lower hydrophilicity compared to the other nanoparticles. These features suggest that the designed nanoparticles could have a favorable behavior in terms of solubility and immunological efficacy. Each nanoparticle (NPs) was formed from the N- to the C-terminus from a combination of peptide sequences with antigenic potential originating from: outer membrane, secretion system, kinases, chaperones, flagellars, lysosomal glycoprotein, cytoskeletal, transferases and ribosomal of the LF-89 and EM-90 genogroups of P. salmonis (Supplementary Fig. 2).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2 Characterization of Nanoparticles\u003c/h2\u003e\n \u003cp\u003eThree of the four nanoparticles were successfully produced in E. coli as bacterial inclusion bodies (NPs) with low to very good yield. In the case of SkipZ, a production yield of 286 mg/mL was obtained, PulseJ a yield of 143 mg/mL, and HopQ a yield of 78 mg/mL was obtained (Supplementary Fig.\u0026nbsp;4). Although Hoptech NPs were produced, their production yield was low (results not shown), which is why it was discarded for future trials. The positive control iRFP was successfully produced with efficiencies of 186 mg/mL.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3 Endocytosis of NPs in the RST-11 cell line\u003c/h2\u003e\n \u003cp\u003eThe chimeric nanoparticles were endocytosed by the Rainbow Trout monocyte/macrophage line RTS11. Using fluorescence emission flow cytometry, HopQ uptake was observed to be more efficient than that observed for PulseJ and SkipZ, reaching approximately 54% fluorescent cells at 20 \u0026micro;g/mL compared to 26% fluorescent cells induced by PulseJ and 5% by SkipZ at the same concentration, for 4 hours (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003e3.4 Gene expression analysis in RST-11 stimulated with NPs\u003c/h2\u003e\n \u003cp\u003eGene expression analysis of immune response genes was evaluated in the RTS-11 cell line after stimulation with multi-epitope nanoparticles (NPs). RTS-11 cells were incubated with SkipZ, PulseJ, HopQ at concentrations of 5, 10 and 20 \u0026micro;g/mL for 12 hours. As controls, cells without stimulation (negative control), LPS (10 \u0026micro;g/mL) as a positive control of innate immune response activation, and iRFP nanoproteins (10 \u0026micro;g/mL) as a control of nanoproteins without immunological relevance were used. The results demonstrated that SkipZNP stimulation induced a significant increase in the expression of genes related to antigen presentation, such as co-stimulatory molecules major histocompatibility complex class II (MHC-II), cluster of differentiation 86 (CD86), cluster of differentiation 83 (CD83), and proinflammatory cytokines such as interleukin 1-beta, IL1b, and tumor necrosis factor alpha (TNF-\u0026alpha;) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.005) at all doses tested. These findings suggest that SkipZcan enhance the activation of the immune system in the RTS-11 cell line (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). Figure \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e presents the gene expression results of PulseJ-stimulated cells. When analyzing the expression of the mhc-ii and cd86 genes, the results show that stimulation with PulseJ at 5 and 10 \u0026micro;g/mL induced a significant increase in the expression of these markers compared to the controls (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). While, for the gene expression of cd83 a significant increase was only observed at 5 \u0026micro;g/mL, moreover, as the concentration of PulseJ increases, the expression of cd83 tends to decrease significantly, up to 20 \u0026micro;g/mL (p\u0026thinsp;\u0026lt;\u0026thinsp;0.005). The same behavior is observed in the proinflammatory cytokines il1b and tnf\u0026alpha;, the data show that as the concentration increases (from 5 \u0026micro;g/mL to 20 \u0026micro;g/mL), a progressive underexpression of these proinflammatory genes occurs. In contrast to LPS which shows an increase in the gene expression of these cytokines, in the same way as the positive control without immunological relevance iRFP which increases its expression significantly (p\u0026thinsp;\u0026lt;\u0026thinsp;0.005) for both cytokines. A similar behavior to SkipZ was observed with the induction of HopQ at the three doses evaluated (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e). The gene expression of mhc-ii, cd86 and cd83 showed a significant increase at all concentrations tested. However, the greatest increase in expression was observed at the concentration of 20 \u0026micro;g/mL, where the expression of these genes was significantly higher compared to the concentrations of 5 and 10 \u0026micro;g/mL (p\u0026thinsp;\u0026lt;\u0026thinsp;0.005). When observing the expression of il1b and tnf\u0026alpha;, although all doses exerted a significant increase in expression (p\u0026thinsp;\u0026lt;\u0026thinsp;0.005), at 5 and 20 \u0026micro;g/mL it generated a greater increase in the expression of proinflammatory cytokines.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003e3.5 NP-induced antigen presentation in cell culture\u003c/h2\u003e\n \u003cp\u003eInduction with 5 \u0026micro;g/mL SkipZ, 10 \u0026micro;g/mL PulseJ, and 20 \u0026micro;g/mL HopQ in the RTS11 cell line resulted in increased fluorescence activity of surface markers involved in antigen presentation, such as MHC-II, CD83, and CD86. In particular, HopQNP at 20 \u0026micro;g/mL showed a significant fluorescence signal associated with MHC-II, CD83, and CD86 (green) compared to negative controls and to the iRFP nanoprotein positive control, which has no immunological relevance.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eRecent studies have shown that the reverse vaccinology approach allows the identification of vaccine candidates and drug targets (Alsowayeh \u0026amp; Albutti, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Moxon et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Solanki et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In this context, this project proposes the use of this strategy for the preselection of immunogenic epitopes of Piscirickettsia salmonis belonging to the LF-89 and EM-90 genogroups, which could serve as potential targets for vaccine development. These peptide sequences with chimeric characteristics have the function of activating the immune system of fish by enhancing a cellular response through the activation of antigen-presenting cells and Th1-type lymphocytes. Currently, there are few studies that address approaches similar to the present study, in which chimeric antigenic sequences of a specific pathogen are incorporated and produced in the form of inclusion bodies. A related study is the one carried out by Roca-Pinilla et al. (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), in which multidomain recombinant proteins with antimicrobial activity were designed, using host defense peptides (HDPs) fused to GFP and more advanced configurations without carriers. These multidomain proteins were specifically designed to include multiple domains with conserved and functional epitopes, which can be recognized and processed by antigen-presenting cells (APCs) and subsequently presented to T lymphocytes. This approach significantly increased the probability of activating specific T lymphocytes, promoting the generation of a long-lasting immune memory.\u003c/p\u003e \u003cp\u003eInclusion bodies (IBs) present an amyloidogenic behavior, similar to that of natural functional amyloids (C\u0026eacute;spedes et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). This amyloid network ensures a stable fibrous scaffold, which confers both mechanical stability and high porosity, allowing them to be used as functional biomaterials. In this context, previous studies have shown that the size and surface characteristics of IBs directly influence their cellular uptake. For example, particles larger than 4 \u0026micro;m have difficulties in reaching secondary lymphoid organs (Folgueira et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), while smaller nanoparticles have a greater internalization capacity (Rojas-Pe\u0026ntilde;a et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The evidence of IB uptake by cells differs according to their size. In the case of the RTS-11 cell line, derived from the spleen of rainbow trout (Oncorhynchus mykiss), which exhibits monocyte/macrophage characteristics and is commonly used to study immune responses in fish; the uptake efficiency was lower than that observed in other cell lines, such as those derived from zebrafish (ZFL) (Rojas-Pe\u0026ntilde;a et a., 2022) or human Hela cells (Roca-Pinilla et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In summary, in the study by Rojas-Pe\u0026ntilde;a and collaborators (Rojas-Pe\u0026ntilde;a et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), the internalization of recombinant Spring viremia of carp (SVCV) antigen G nanoparticles was evaluated with the gamma interferon module (SVCV-IFN) that showed efficiencies of 100 and 90% in ZFL cells. On the other hand, (V\u0026aacute;zquez et al., 2012), managed to internalize 100% of the GFP-IBs into Hela cells, compared to the 5, 26 and 56% uptake observed in this article, using RTS-11. The difference in uptake can be attributed to the membrane receptor profile of each cell line, as well as the size of the cells used and hydrophobic characteristics of each nanoprotein.\u003c/p\u003e \u003cp\u003eOnce taken up by RTS-11 cells, it is suggested that nanoproteins, like HDPs, interact with pattern recognition receptors (PRRs), such as Toll-like receptors (TLRs), present on the surface of antigen-presenting cells (APCs). This interaction triggers intracellular signaling pathways that favor the uptake, processing, and presentation of antigens by the major histocompatibility complex (MHC). This process is crucial for the activation of T lymphocytes, triggering an adaptive immune response. To evaluate this mechanism, genes involved in antigen presentation were analyzed, such as MHC-II, CD80/86, and CD83, whose expression in fish can vary significantly depending on immunological stimuli.\u003c/p\u003e \u003cp\u003eIt has been shown that MHC-II, mainly expressed in B cells and dendritic cells, plays an essential role in antigen presentation and responds significantly to exogenous antigens and T cell-dependent antigens (Xing et al., \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). CD80/86 is mainly found on antigen-presenting cells and could help elicit humoral immune responses in teleosts through the CD80/86-CD28 signaling pathway involving CD4\u0026thinsp;+\u0026thinsp;lymphocytes. For example, Morales-Lange and co-workers (Morales-Lange et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) demonstrated that interferon gamma (IFNγ) can induce overexpression of these markers in Atlantic salmon splenocytes, suggesting a role in modulating immune responses through antigen-presenting cells (APCs). Similarly, Nombela and co-workers (Nombela et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) reported that exposure to viral hemorrhagic septicemia virus leads to an increase in the expression of MHC I and II, as well as CD86 and CD83 in rainbow trout, indicating a robust activation of antigen-processing mechanisms. Furthermore, dendritic cell (DC) maturation is associated with increased expression of these markers, as shown in studies involving various stimuli, including lipopolysaccharides (Lakho et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Sepulcre et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). The latter has been shown to be able to induce the overexpression of proinflammatory cytokines such as TNFα, IL-1β and IL-6. LPS activates the TLR4 signaling pathway, resulting in increased secretion of TNF-α and IL-6 by macrophages (Arranz et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This activation is mediated by various intracellular signaling cascades, including the PI3K/Akt pathway, which is essential for the production of proinflammatory mediators (Arranz et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). This is in agreement with the results obtained, where LPS acts as a positive control of the inflammatory response. Taken together, these findings underline the critical role of specific cytokines and pathogens in modulating the expression of key immune markers in fish, thus improving their immune response capacity.\u003c/p\u003e \u003cp\u003eIn our study, SkipZ and especially HopQ NPs were able to increase the expression of genes involved in antigen presentation and T cell activation (such as cd86, mhc-ii, and cd83) and proinflammatory cytokines (such as il-1β and tnf-α) in a dose-dependent manner at low (5 \u0026micro;g/mL) and high (20 \u0026micro;g/mL) concentrations. On the other hand, PulseJ showed a lower expression profile than the positive control (iRFP), suggesting that sequences with antigenic potential can, in some cases, generate a modulation of the immune response, significantly decreasing the production of proinflammatory cytokines. These results support the hypothesis that the designed chimeric antigenic sequences improve the intrinsic biological capacity of nanoparticles.\u003c/p\u003e \u003cp\u003eThe use of modular protein nanoparticles (NPs) derived from inclusion bodies (IBs) to improve the efficacy of antiviral vaccines in fish, specifically against spring viremia of carp virus (SVCV), has been investigated. The study concluded that IBs, when used as NPs, not only act as antigen delivery vehicles, but also function as immunostimulants. They promote the activation of genes related to the inflammatory and antiviral response, such as vig1, mx, lmp2, and ifngr1 (Rojas-Pe\u0026ntilde;a et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Furthermore, Puente Mar\u0026iacute;n (Puente-Marin et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) demonstrated that trout erythrocytes, despite not being phagocytic, can internalize IBs and modulate the expression of immune genes. For example, TNFα IBs reduce the expression of genes related to antigen presentation (such as cd83 and mhcI), while VHSV glycoprotein G IBs (IBfrg16G\u0026thinsp;\u0026minus;\u0026thinsp;VHSV) activate genes involved in the antiviral response, such as mx and mhcII, and in the production of cytokines such as il6 and il2. These antecedents support the hypothesis that the incorporation of sequences with antigenic potential of the pathogen can be captured by fish macrophage cells, which would trigger an immune response. This is achieved by activating antigen presentation and the costimulation necessary for a complete activation of T cells, particularly CD8\u0026thinsp;+\u0026thinsp;cells and the Th1 response, which includes the production of cytokines such as interferon gamma (IFNγ), essential to control and eliminate P. salmonis (Rozas-Serri et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eIn this study, a prototype of a nanostructured multi-epitope vaccine targeting Piscirickettsia salmonis, the pathogen responsible for Piscirickettsiosis in salmonids, was developed and evaluated. Using reverse vaccinology tools, four nanoparticles (SkipZ, PulseJ, HopQ and Hoptech) derived from the LF-89 and EM-90 genogroups, prevalent in Chilean aquaculture, were designed. The results showed that the nanoparticles, particularly SkipZ and HopQ, induce a significant immune response in the RTS-11 macrophage cell line, stimulating the expression of key markers in antigen presentation, as well as the production of proinflammatory cytokines. Furthermore, the study highlights the use of inclusion body (IB) nanoparticles as antigen vehicles, which not only serve as platforms for epitope presentation, but also act as immunomodulators, enhancing the immune response. This multi-epitope nanoparticle-based approach could represent a promising alternative for the control of Piscirickettsiosis, offering a potential solution to improve the efficacy of vaccines in the field. The incorporation of multiple epitopes derived from the predominant genogroups allows addressing the genetic diversity of the pathogen, which could result in a more durable and effective protection in aquaculture. This work addresses a proof of concept at laboratory scale, being the first step that will allow continuing with the challenge with the pathogen under controlled conditions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eSupplementary Materials:\u003c/strong\u003e The following supporting information can be downloaded at:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e Conceptualization, P.V.-A and D.T.; methodology, P.V.-A, D.T., D.L., M.P., N.S.-P.; software, P.V.-A; validation, P.V.-A, D.L; formal analysis, P.V.-A and D.T; investigation, P.V.-A, D.T., D.L.; resources, D.T., L.M., C.F. and J.G.-M.; data curation, P.V.-A and D.T.; writing—original draft preparation, P.V.-A; writing—review and editing, P.V.-A., N.S.-P., E.G.-F., A.A., M.P., C.F., L.M., J.G.-M. and D.T.; visualization, P.V.-A, D.T., C.F, N.S.-P., E.G.-F. and A.A.; supervision, D.T., J.G.-M. and L.M.; project administration, P.V.-A.; funding acquisition, P.V.-A. D.T. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis research was funded by ANID, Proyecto de Tesis de doctorado en el sector productive No. TDP220008 granted by P.V.-A. and was supported by ANID Doctoral Scholarship No. 21220464 D.L. was supported by ANID Doctoral Scholarship No. 21232344.N.S.-P. was supported by Pontificia Universidad Católica de Valparaíso as a postdoctoral fellowship (Proyecto VINCI-PUCV Postdoctorado. D.T. was supported by ANID, FONDECYT de Iniciación No. 11240684.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitutional Review Board Statement:\u0026nbsp;\u003c/strong\u003eThe study was approved by the bioethics committee of Pontificia Universidad Católica de Valparaíso BIOEPUCV-B 395-2021.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent Statement:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u0026nbsp;\u003c/strong\u003eThe raw data supporting the conclusions of this article will be made available by the authors, without undue reservation, to any qualified researcher.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u0026nbsp;\u003c/strong\u003eThe authors declare no conflicts of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAdams, A. (2019). Progress, challenges and opportunities in fish vaccine development. \u003cem\u003eFish \u0026amp; Shellfish Immunology\u003c/em\u003e,\u003cem\u003e\u0026nbsp;90\u003c/em\u003e, 210-214. https://doi.org/10.1016/j.fsi.2019.04.066\u003c/li\u003e\n \u003cli\u003eAlsowayeh, N., \u0026amp; Albutti, A. (2022). Designing a novel chimeric multi-epitope vaccine against Burkholderia pseudomallei, a causative agent of melioidosis. \u003cem\u003eFrontiers in Medicine\u003c/em\u003e,\u003cem\u003e\u0026nbsp;9\u003c/em\u003e. https://doi.org/10.3389/fmed.2022.945938\u003c/li\u003e\n \u003cli\u003eAravena, P., Pulgar, R., Ortiz-Sever\u0026iacute;n, J., Maza, F., Gaete, A., Mart\u0026iacute;nez, S., Ser\u0026oacute;n, E., Gonz\u0026aacute;lez, M., \u0026amp; Cambiazo, V. (2020). PCR-RFLP Detection and Genogroup Identification of Piscirickettsia salmonis in Field Samples. \u003cem\u003ePathogens\u003c/em\u003e,\u003cem\u003e\u0026nbsp;9\u003c/em\u003e(5), 358. https://doi.org/10.3390/pathogens9050358\u003c/li\u003e\n \u003cli\u003eArranz, A., Doxaki, C., Vergadi, E., Martinez De La Torre, Y., Vaporidi, K., Lagoudaki, E. D., Ieronymaki, E., Androulidaki, A., Venihaki, M., Margioris, A. N., Stathopoulos, E. N., Tsichlis, P. N., \u0026amp; Tsatsanis, C. (2012). Akt1 and Akt2 protein kinases differentially contribute to macrophage polarization. \u003cem\u003eProceedings of the National Academy of Sciences\u003c/em\u003e,\u003cem\u003e\u0026nbsp;109\u003c/em\u003e(24), 9517-9522. https://doi.org/10.1073/pnas.1119038109\u003c/li\u003e\n \u003cli\u003eAziz, R. K., Bartels, D., Best, A. A., DeJongh, M., Disz, T., Edwards, R. A., Formsma, K., Gerdes, S., Glass, E. M., Kubal, M., Meyer, F., Olsen, G. J., Olson, R., Osterman, A. L., Overbeek, R. A., McNeil, L. K., Paarmann, D., Paczian, T., Parrello, B.,\u0026hellip;Zagnitko, O. (2008). The RAST server: Rapid annotations using subsystems technology. \u003cem\u003eBmc Genomics\u003c/em\u003e,\u003cem\u003e\u0026nbsp;9\u003c/em\u003e, Article 75. https://doi.org/10.1186/1471-2164-9-75\u003c/li\u003e\n \u003cli\u003eCabello, F. C., Godfrey, H. P., Tomova, A., Ivanova, L., Dolz, H., Millanao, A., \u0026amp; Buschmann, A. H. (2013). Antimicrobial use in aquaculture re-examined: its relevance to antimicrobial resistance and to animal and human health. \u003cem\u003eEnvironmental Microbiology\u003c/em\u003e,\u003cem\u003e\u0026nbsp;15\u003c/em\u003e(7), 1917-1942. https://doi.org/10.1111/1462-2920.12134\u003c/li\u003e\n \u003cli\u003eCalis, J.J.A., De Boer, R.J., Keşmir, C., 2012. Degenerate T-cell Recognition of Peptides on MHC Molecules Creates Large Holes in the T-cell Repertoire. PLOS Computational Biology 8, e1002412.. https://doi.org/10.1371/journal.pcbi.1002412\u003c/li\u003e\n \u003cli\u003eCalis, J.J.A., Maybeno, M., Greenbaum, J.A., Weiskopf, D., De Silva, A.D., Sette, A., Keşmir, C., Peters, B., 2013. Properties of MHC Class I Presented Peptides That Enhance Immunogenicity. PLOS Computational Biology 9, e1003266. https://doi.org/10.1371/journal.pcbi.1003266\u003c/li\u003e\n \u003cli\u003eCarril, G., Winther-Larsen, H.C., L\u0026oslash;voll, M., S\u0026oslash;rum, H., 2023. Cohabitation of Piscirickettsia salmonis genogroups (LF-89 and EM-90): synergistic effect on growth dynamics. Frontiers in Cellular and Infection Microbiology 13. https://doi.org/10.3389/fcimb.2023.1253577\u003c/li\u003e\n \u003cli\u003eCaruffo, M., Vidal, S., Santis, L., Siel, D., Perez, O., Huenchullan, P. R., \u0026amp; Saenz, L. (2021). Effectiveness of a proteoliposome-based vaccine against salmonid rickettsial septicaemia in Oncorhynchus mykiss. \u003cem\u003eVeterinary Research\u003c/em\u003e,\u003cem\u003e\u0026nbsp;52\u003c/em\u003e(1), Article 111. https://doi.org/10.1186/s13567-021-00982-2\u003c/li\u003e\n \u003cli\u003eC\u0026eacute;spedes, M. V., Fern\u0026aacute;ndez, Y., Unzueta, U., Mendoza, R., Seras-Franzoso, J., S\u0026aacute;nchez-Chardi, A., \u0026Aacute;lamo, P., Toledo-Rubio, V., Ferrer-Miralles, N., V\u0026aacute;zquez, E., Schwartz, S., Abasolo, I., Corchero, J. L., Mangues, R., \u0026amp; Villaverde, A. (2016). Bacterial mimetics of endocrine secretory granules as immobilized in vivo depots for functional protein drugs. \u003cem\u003eScientific Reports\u003c/em\u003e,\u003cem\u003e\u0026nbsp;6\u003c/em\u003e(1), 35765. https://doi.org/10.1038/srep35765\u003c/li\u003e\n \u003cli\u003eChang, K. Y., \u0026amp; Yang, J.-R. (2013). Analysis and Prediction of Highly Effective Antiviral Peptides Based on Random Forests. \u003cem\u003ePLoS ONE\u003c/em\u003e,\u003cem\u003e\u0026nbsp;8\u003c/em\u003e(8), e70166. https://doi.org/10.1371/journal.pone.0070166\u003c/li\u003e\n \u003cli\u003eConsejo del Salm\u0026oacute;n, Chile. (2022). \u003cem\u003eInforme de Exportaciones de Salm\u0026oacute;n y Trucha, cierre a\u0026ntilde;o 2022\u003c/em\u003e [Informe].\u003c/li\u003e\n \u003cli\u003ede Marco, A. (2013). Recombinant polypeptide production in E. coli: towards a rational approach to improve the yields of functional proteins. \u003cem\u003eMicrobial Cell Factories\u003c/em\u003e,\u003cem\u003e\u0026nbsp;12\u003c/em\u003e, Article 101. https://doi.org/10.1186/1475-2859-12-101\u003c/li\u003e\n \u003cli\u003ede Marco, A., Ferrer-Miralles, N., Garcia-Fruitos, E., Mitraki, A., Peternel, S., Rinas, U., Trujillo-Roldan, M. A., Valdez-Cruz, N. A., Vazquez, E., \u0026amp; Villaverde, A. (2019). Bacterial inclusion bodies are industrially exploitable amyloids. \u003cem\u003eFems Microbiology Reviews\u003c/em\u003e,\u003cem\u003e\u0026nbsp;43\u003c/em\u003e(1), 53-72. https://doi.org/10.1093/femsre/fuy038\u003c/li\u003e\n \u003cli\u003eDoytchinova, I. A., \u0026amp; Flower, D. R. (2007). VaxiJen: a server for prediction of protective antigens, tumour antigens and subunit vaccines. \u003cem\u003eBmc Bioinformatics\u003c/em\u003e,\u003cem\u003e\u0026nbsp;8\u003c/em\u003e, Article 4. https://doi.org/10.1186/1471-2105-8-4\u003c/li\u003e\n \u003cli\u003eFigueroa, C., Bustos, P., Torrealba, D., Dixon, B., Soto, C., Conejeros, P., \u0026amp; Gallardo, J. A. (2017). Coinfection takes its toll: Sea lice override the protective effects of vaccination against a bacterial pathogen in Atlantic salmon. \u003cem\u003eScientific Reports\u003c/em\u003e,\u003cem\u003e\u0026nbsp;7\u003c/em\u003e, Article 17817. https://doi.org/10.1038/s41598-017-18180-6\u003c/li\u003e\n \u003cli\u003eFigueroa, C., Veloso, P., Espin, L., Dixon, B., Torrealba, D., Elalfy, I. S., Afonso, J. M., Soto, C., Conejeros, P., \u0026amp; Gallardo, J. A. (2020). Host genetic variation explains reduced protection of commercial vaccines against Piscirickettsia salmonis in Atlantic salmon. \u003cem\u003eScientific Reports\u003c/em\u003e,\u003cem\u003e\u0026nbsp;10\u003c/em\u003e(1), Article 18252. https://doi.org/10.1038/s41598-020-70847-9\u003c/li\u003e\n \u003cli\u003eFolgueira, I., Noia, M., Blanco-Abad, V., Mallo, N., Leiro, J.M., \u0026amp; Lamas, J. (2015). Particle size and traffic of phagocytes between the turbot peritoneal cavity and lymphoid organs. \u003cem\u003eFish \u0026amp; shellfish immunology, 44 2\u003c/em\u003e, 652-61\u003c/li\u003e\n \u003cli\u003eGasteiger, E., Gattiker, A., Hoogland, C., Ivanyi, I., Appel, R. D., \u0026amp; Bairoch, A. (2003). ExPASy: the proteomics server for in-depth protein knowledge and analysis. \u003cem\u003eNucleic Acids Research\u003c/em\u003e,\u003cem\u003e\u0026nbsp;31\u003c/em\u003e(13), 3784-3788. https://doi.org/10.1093/nar/gkg563\u003c/li\u003e\n \u003cli\u003eGupta, S., Kapoor, P., Chaudhary, K., Gautam, A., Kumar, R., Raghava, G. P. S., \u0026amp; Open Source Drug, D. (2013). In Silico Approach for Predicting Toxicity of Peptides and Proteins. \u003cem\u003ePlos One\u003c/em\u003e,\u003cem\u003e\u0026nbsp;8\u003c/em\u003e(9), Article e73957. https://doi.org/10.1371/journal.pone.0073957\u003c/li\u003e\n \u003cli\u003eGupta, S. K., \u0026amp; Shukla, P. (2016). Advanced technologies for improved expression of recombinant proteins in bacteria: perspectives and applications. \u003cem\u003eCritical reviews in biotechnology\u003c/em\u003e, \u003cem\u003e36\u003c/em\u003e(6), 1089\u0026ndash;1098. https://doi.org/10.3109/07388551.2015.1084264\u003c/li\u003e\n \u003cli\u003eJi, J., Torrealba, D., Thwaite, R., Gomez, A. C., Parra, D., \u0026amp; Roher, N. (2019). Nanostructured TNF alpha protein targets the zebrafish (Danio rerio) immune system through mucosal surfaces and improves the survival after Mycobacterium marinum lethal infection. \u003cem\u003eAquaculture\u003c/em\u003e,\u003cem\u003e\u0026nbsp;510\u003c/em\u003e, 138-149. https://doi.org/10.1016/j.aquaculture.2019.05.050\u003c/li\u003e\n \u003cli\u003eK\u0026auml;llberg, M., Wang, H., Wang, S., Peng, J., Wang, Z., Lu, H., \u0026amp; Xu, J. (2012). Template-based protein structure modeling using the RaptorX web server. \u003cem\u003eNature Protocols\u003c/em\u003e,\u003cem\u003e\u0026nbsp;7\u003c/em\u003e(8), 1511-1522. https://doi.org/10.1038/nprot.2012.085\u003c/li\u003e\n \u003cli\u003eKelley, L. A., Mezulis, S., Yates, C. M., Wass, M. N., \u0026amp; Sternberg, M. J. E. (2015). The Phyre2 web portal for protein modeling, prediction and analysis. \u003cem\u003eNature Protocols\u003c/em\u003e,\u003cem\u003e\u0026nbsp;10\u003c/em\u003e(6), 845-858. https://doi.org/10.1038/nprot.2015.053\u003c/li\u003e\n \u003cli\u003eKennedy, D. A., Kurath, G., Brito, I. L., Purcell, M. K., Read, A. F., Winton, J. R., \u0026amp; Wargo, A. R. (2016). Potential drivers of virulence evolution in aquaculture. \u003cem\u003eEvolutionary Applications\u003c/em\u003e,\u003cem\u003e\u0026nbsp;9\u003c/em\u003e(2), 344-354. https://doi.org/10.1111/eva.12342\u003c/li\u003e\n \u003cli\u003eKyte, J., \u0026amp; Doolittle, R. F. (1982). A SIMPLE METHOD FOR DISPLAYING THE HYDROPATHIC CHARACTER OF A PROTEIN. \u003cem\u003eJournal of Molecular Biology\u003c/em\u003e,\u003cem\u003e\u0026nbsp;157\u003c/em\u003e(1), 105-132. https://doi.org/10.1016/0022-2836(82)90515-0\u003c/li\u003e\n \u003cli\u003eLakho, S. A., Haseeb, M., Huang, J., Yang, Z., Hasan, M. W., Aleem, M. T., Naqvi, M. A.-U.-H., Memon, M. A., Song, X., Yan, R., Xu, L., \u0026amp; Li, X. (2020). Glyceraldehyde-3-phosphate dehydrogenase from Eimeria acervulina modulates the functions of chicken dendritic cells to boost Th1 type immune response and stimulates autologous CD4+ T cells differentiation in-vitro. \u003cem\u003eVeterinary Research\u003c/em\u003e,\u003cem\u003e\u0026nbsp;51\u003c/em\u003e(1). https://doi.org/10.1186/s13567-020-00864-z\u003c/li\u003e\n \u003cli\u003eLi, Y., Lu, Z., Ru, J. H., Lopes-Virella, M. F., Lyons, T. J., \u0026amp; Huang, Y. (2018). Saturated fatty acid combined with lipopolysaccharide stimulates a strong inflammatory response in hepatocytes in vivo and in vitro. \u003cem\u003eAmerican Journal of Physiology-Endocrinology and Metabolism\u003c/em\u003e,\u003cem\u003e\u0026nbsp;315\u003c/em\u003e(5), E745-E757. https://doi.org/10.1152/ajpendo.00015.2018\u003c/li\u003e\n \u003cli\u003eLivak, K. J., \u0026amp; Schmittgen, T. D. (2001). Analysis of relative gene expression data using real-time quantitative PCR and the 2(T)(-Delta Delta C) method. \u003cem\u003eMethods\u003c/em\u003e,\u003cem\u003e\u0026nbsp;25\u003c/em\u003e(4), 402-408. https://doi.org/10.1006/meth.2001.1262\u003c/li\u003e\n \u003cli\u003eL\u0026oacute;pez-Cano, A., Mart\u0026iacute;nez-Miguel, M., Guasch, J., Ratera, I., Ar\u0026iacute;s, A., \u0026amp; Garcia-Fruit\u0026oacute;s, E. (2022). Exploring the impact of the recombinant Escherichia coli strain on defensins antimicrobial activity: BL21 versus Origami strain. \u003cem\u003eMicrobial Cell Factories\u003c/em\u003e,\u003cem\u003e\u0026nbsp;21\u003c/em\u003e(1). https://doi.org/10.1186/s12934-022-01803-7\u003c/li\u003e\n \u003cli\u003eMagnan, C. N., Randall, A., \u0026amp; Baldi, P. (2009). SOLpro: accurate sequence-based prediction of protein solubility. \u003cem\u003eBioinformatics\u003c/em\u003e,\u003cem\u003e\u0026nbsp;25\u003c/em\u003e(17), 2200-2207. https://doi.org/10.1093/bioinformatics/btp386\u003c/li\u003e\n \u003cli\u003eMaisey, K., Montero, R., \u0026amp; Christodoulides, M. (2017). Vaccines for piscirickettsiosis (salmonid rickettsial septicaemia, SRS): the Chile perspective. \u003cem\u003eExpert Review of Vaccines\u003c/em\u003e,\u003cem\u003e\u0026nbsp;16\u003c/em\u003e(3), 215-228. https://doi.org/10.1080/14760584.2017.1244483\u003c/li\u003e\n \u003cli\u003eMartinez, D., Diaz-Ibarrola, D., Vargas-Lagos, C., Oyarzun, R., Pontigo, J. P., Munoz, J. L. P., Yanez, A. J., \u0026amp; Vargas-Chacoff, L. (2018). Immunological response of the Sub-Antarctic Notothenioid fish Eleginops maclovinus injected with two strains of Piscirickettsia salmonis. \u003cem\u003eFish \u0026amp; Shellfish Immunology\u003c/em\u003e,\u003cem\u003e\u0026nbsp;75\u003c/em\u003e, 139-148. https://doi.org/10.1016/j.fsi.2018.01.012\u003c/li\u003e\n \u003cli\u003eMorales-Lange, B., Ramirez-Cepeda, F., Schmitt, P., Guzman, F., Lagos, L., Overland, M., Wong-Benito, V., Imarai, M., Fuentes, D., Boltana, S., Alcaino, J., Soto, C., \u0026amp; Mercado, L. (2021). Interferon Gamma Induces the Increase of Cell-Surface Markers (CD80/86, CD83 and MHC-II) in Splenocytes From Atlantic Salmon. \u003cem\u003eFrontiers in Immunology\u003c/em\u003e,\u003cem\u003e\u0026nbsp;12\u003c/em\u003e, Article 666356. https://doi.org/10.3389/fimmu.2021.666356\u003c/li\u003e\n \u003cli\u003eMoxon, R., Reche, P. A., \u0026amp; Rappuoli, R. (2019). Editorial: Reverse Vaccinology. \u003cem\u003eFrontiers in Immunology\u003c/em\u003e,\u003cem\u003e\u0026nbsp;10\u003c/em\u003e. https://doi.org/10.3389/fimmu.2019.02776\u003c/li\u003e\n \u003cli\u003eNombela, I., Requena-Platek, R., Morales-Lange, B., Chico, V., Puente-Marin, S., Ciordia, S., Mena, M., Coll, J., Perez, L., Mercado, L., \u0026amp; Ortega-Villaizan, M. (2019). Rainbow Trout Red Blood Cells Exposed to Viral Hemorrhagic Septicemia Virus Up-Regulate Antigen-Processing Mechanisms and MHC I\u0026amp;II, CD86, and CD83 Antigen-presenting Cell Markers. \u003cem\u003eCells\u003c/em\u003e,\u003cem\u003e\u0026nbsp;8\u003c/em\u003e(5), 386. https://doi.org/10.3390/cells8050386\u003c/li\u003e\n \u003cli\u003eNourdin-Galindo, G., Sanchez, P., Molina, C. F., Espinoza-Rojas, D. A., Oliver, C., Ruiz, P., Vargas-Chacoff, L., Carcamo, J. G., Figueroa, J. E., Mancilla, M., Maracaja-Coutinho, V., \u0026amp; Yanez, A. J. (2017). Comparative Pan-Genome Analysis of Piscirickettsia salmonis Reveals Genomic Divergences within Genogroups. \u003cem\u003eFrontiers in Cellular and Infection Microbiology\u003c/em\u003e,\u003cem\u003e\u0026nbsp;7\u003c/em\u003e, Article 459. https://doi.org/10.3389/fcimb.2017.00459\u003c/li\u003e\n \u003cli\u003eOmasits, U., Ahrens, C. H., Muller, S., \u0026amp; Wollscheid, B. (2014). Protter: interactive protein feature visualization and integration with experimental proteomic data. \u003cem\u003eBioinformatics\u003c/em\u003e,\u003cem\u003e\u0026nbsp;30\u003c/em\u003e(6), 884-886. https://doi.org/10.1093/bioinformatics/btt607\u003c/li\u003e\n \u003cli\u003eOverbeek, R., Olson, R., Pusch, G. D., Olsen, G. J., Davis, J. J., Disz, T., Edwards, R. A., Gerdes, S., Parrello, B., Shukla, M., Vonstein, V., Wattam, A. R., Xia, F. F., \u0026amp; Stevens, R. (2014). The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST). \u003cem\u003eNucleic Acids Research\u003c/em\u003e,\u003cem\u003e\u0026nbsp;42\u003c/em\u003e(D1), D206-D214. https://doi.org/10.1093/nar/gkt1226\u003c/li\u003e\n \u003cli\u003ePontigo, J. P., Espinoza, C., Hernandez, M., Nourdin, G., Oliver, C., Avendano-Herrera, R., Figueroa, J., Rauch, C., Troncoso, J. M., Vargas-Chacoff, L., \u0026amp; Yanez, A. J. (2021). Protein-Based Vaccine Protect Against Piscirickettsia salmonis in Atlantic Salmon (Salmo salar). \u003cem\u003eFrontiers in Immunology\u003c/em\u003e,\u003cem\u003e\u0026nbsp;12\u003c/em\u003e, Article 602689. https://doi.org/10.3389/fimmu.2021.602689\u003c/li\u003e\n \u003cli\u003ePuente-Marin, S., Thwaite, R., Mercado, L., Coll, J., Roher, N., \u0026amp; Ortega-Villaizan, M. D. M. (2019). Fish Red Blood Cells Modulate Immune Genes in Response to Bacterial Inclusion Bodies Made of TNF\u0026alpha; and a G-VHSV Fragment. \u003cem\u003eFrontiers in Immunology\u003c/em\u003e,\u003cem\u003e\u0026nbsp;10\u003c/em\u003e. https://doi.org/10.3389/fimmu.2019.01055\u003c/li\u003e\n \u003cli\u003eRamirez, R., Gomez, F. A., \u0026amp; Marshall, S. H. (2015). The infection process of Piscirickettsia salmonis in fish macrophages is dependent upon interaction with host-cell clathrin and actin. \u003cem\u003eFems Microbiology Letters\u003c/em\u003e,\u003cem\u003e\u0026nbsp;362\u003c/em\u003e(1). https://doi.org/10.1093/femsle/fnu012\u003c/li\u003e\n \u003cli\u003eReche, P. A., Glutting, J. P., \u0026amp; Reinherz, E. L. (2002). Prediction of MHC class I binding peptides using profile motifs. \u003cem\u003eHuman Immunology\u003c/em\u003e,\u003cem\u003e\u0026nbsp;63\u003c/em\u003e(9), 701-709, Article Pii s0198-8859(02)00432-9. https://doi.org/10.1016/s0198-8859(02)00432-9\u003c/li\u003e\n \u003cli\u003eRoca-Pinilla, R., L\u0026oacute;pez-Cano, A., Saubi, C., Garcia-Fruit\u0026oacute;s, E., Ar\u0026iacute;s, A., 2020. A new generation of recombinant polypeptides combines multiple protein domains for effective antimicrobial activity. Microbial Cell Factories 19.. https://doi.org/10.1186/s12934-020-01380-7\u003c/li\u003e\n \u003cli\u003eRoca-Pinilla, R., Lisowski, L., Ar\u0026iacute;s, A., Garcia-Fruit\u0026oacute;s, E., 2022. The future of recombinant host defense peptides. Microbial Cell Factories 21.. https://doi.org/10.1186/s12934-022-01991-2\u003c/li\u003e\n \u003cli\u003eRojas-Pe\u0026ntilde;a, M., Aceituno, P., Salvador, M. E., Garcia-Ordo\u0026ntilde;ez, M., Teles, M., Ortega-Villaizan, M. D. M., Perez, L., \u0026amp; Roher, N. (2022). How modular protein nanoparticles may expand the ability of subunit anti-viral vaccines: The spring viremia carp virus (SVCV) case. \u003cem\u003eFish \u0026amp; shellfish immunology\u003c/em\u003e, \u003cem\u003e131\u003c/em\u003e, 1051\u0026ndash;1062. https://doi.org/10.1016/j.fsi.2022.10.067\u003c/li\u003e\n \u003cli\u003eRozas-Serri, M. (2022). Why Does Piscirickettsia salmonis Break the Immunological Paradigm in Farmed Salmon? Biological Context to Understand the Relative Control of Piscirickettsiosis. \u003cem\u003eFrontiers in Immunology\u003c/em\u003e,\u003cem\u003e\u0026nbsp;13\u003c/em\u003e, Article 856896. https://doi.org/10.3389/fimmu.2022.856896\u003c/li\u003e\n \u003cli\u003eRozas-Serri, M., Pena, A., \u0026amp; Maldonado, L. (2019). Gene expression associated with immune response in Atlantic salmon head-kidney vaccinated with inactivated whole-cell bacterin of Piscirickettsia salmonis and pathogenic isolates. \u003cem\u003eFish \u0026amp; Shellfish Immunology\u003c/em\u003e,\u003cem\u003e\u0026nbsp;93\u003c/em\u003e, 789-795. https://doi.org/10.1016/j.fsi.2019.08.031\u003c/li\u003e\n \u003cli\u003eRozas-Serri, M., Pe\u0026ntilde;a, A., Arriagada, G., Enr\u0026iacute;quez, R., \u0026amp; Maldonado, L. (2018). Comparison of gene expression in post-smolt Atlantic salmon challenged by LF-89-like and EM-90-like\u0026lt;i\u0026gt;Piscirickettsia salmonis\u0026lt;/i\u0026gt;isolates reveals differences in the immune response associated with pathogenicity. \u003cem\u003eJournal of Fish Diseases\u003c/em\u003e,\u003cem\u003e\u0026nbsp;41\u003c/em\u003e(3), 539-552. https://doi.org/10.1111/jfd.12756\u003c/li\u003e\n \u003cli\u003eRozas-Serri, M., Pe\u0026ntilde;a, A., Gardner, I., Pe\u0026ntilde;aloza, E., Maldonado, L., Mu\u0026ntilde;oz, A., Mardones, F. O., Rodr\u0026iacute;guez, C., Ildefonso, R., Senn, C., \u0026amp; Aranis, F. (2023). Co-Infection by LF-89-Like and EM-90-Like Genogroups of Piscirickettsia Salmonis in Farmed Atlantic Salmon in Chile: Implications for Surveillance and Control of Piscirickettsiosis. \u003cem\u003ePathogens\u003c/em\u003e,\u003cem\u003e\u0026nbsp;12\u003c/em\u003e(3), 450. https://doi.org/10.3390/pathogens12030450\u003c/li\u003e\n \u003cli\u003eRozas‐Serri, M., Kani, T., Jaramillo, V., Correa, R., Ildefonso, R., Rabascall, C., Barrientos, S., Co\u0026ntilde;uecar, D., \u0026amp; Pe\u0026ntilde;a, A. (2024). Current vaccination strategy against Piscirickettsia salmonis in Chile based only on the EM-90 genogroup shows incomplete cross-protection for the LF-89 genogroup. \u003cem\u003eFish \u0026amp; shellfish immunology\u003c/em\u003e, 109893\u003c/li\u003e\n \u003cli\u003eSaavedra, J., Hernandez, N., Osses, A., Castillo, A., Cancino, A., Grothusen, H., Navas, E., Henriquez, P., Bohle, H., Bustamante, F., Bustos, P., \u0026amp; Mancilla, M. (2017). Prevalence, geographic distribution and phenotypic differences of Piscirickettsia salmonis EM-90-like isolates. \u003cem\u003eJournal of Fish Diseases\u003c/em\u003e,\u003cem\u003e\u0026nbsp;40\u003c/em\u003e(8), 1055-1063. https://doi.org/10.1111/jfd.12581\u003c/li\u003e\n \u003cli\u003eSAG. (2024). PRODUCTOS BIOL\u0026Oacute;GICOS INMUNOL\u0026Oacute;GICOS CON REGISTRO PROVISIONAL USO EN SALM\u0026Oacute;NIDOS.\u003c/li\u003e\n \u003cli\u003eSaha S., \u0026amp; Raghava, G. P. S. (2004). BcePred: Prediction of continuous B-cell epitopes in antigenic sequences using physico-chemical properties. \u003cem\u003eArtificial Immune Systems, Proceedings\u003c/em\u003e,\u003cem\u003e\u0026nbsp;3239\u003c/em\u003e, 197-204\u003c/li\u003e\n \u003cli\u003eSchrodinger, LLC. (2015). The PyMOL Molecular Graphics System,Version 1.8\u003c/li\u003e\n \u003cli\u003eSepulcre, M. P., Alcaraz-Perez, F., Lopez-Munoz, A., Roca, F. J., Meseguer, J., Cayuela, M. L., \u0026amp; Mulero, V. (2009). Evolution of Lipopolysaccharide (LPS) Recognition and Signaling: Fish TLR4 Does Not Recognize LPS and Negatively Regulates NF-kappa B Activation. \u003cem\u003eJournal of Immunology\u003c/em\u003e,\u003cem\u003e\u0026nbsp;182\u003c/em\u003e(4), 1836-1845. https://doi.org/10.4049/jimmunol.0801755\u003c/li\u003e\n \u003cli\u003eSeras-Franzoso, J., Sanchez-Chardi, A., Garcia-Fruitos, E., Vazquez, E., \u0026amp; Villaverde, A. (2016). Cellular uptake and intracellular fate of protein releasing bacterial amyloids in mammalian cells. \u003cem\u003eSoft Matter\u003c/em\u003e,\u003cem\u003e\u0026nbsp;12\u003c/em\u003e(14), 3451-3460. https://doi.org/10.1039/c5sm02930a\u003c/li\u003e\n \u003cli\u003eSERNAPESCA. (2022). Informe sobre uso de antimicrobianos en la salmonicultura nacional. In. Subdirecci\u0026oacute;n de Acuicultura Departamento de Salud Animal Valpara\u0026iacute;so.\u003c/li\u003e\n \u003cli\u003eSERNAPESCA. (2023). Informe con antecedentes sanitarios de agua dulce y mar a\u0026ntilde;o 1\u0026deg; semestre 2023. Departamento de Salud Animal.\u003c/li\u003e\n \u003cli\u003eSERNAPESCA b. (2023). Informe sobre uso de antimicrobianos y antiparasitarios en la salmonicultura nacional. Departamento de salud animal\u003c/li\u003e\n \u003cli\u003eSERNAPESCA. (2024).Informe con antecedentes sanitarios de agua dulce y mar. Departamento Salud Animal.\u003c/li\u003e\n \u003cli\u003eSolanki, V., Tiwari, M., \u0026amp; Tiwari, V. (2019). Prioritization of potential vaccine targets using comparative proteomics and designing of the chimeric multi-epitope vaccine against Pseudomonas aeruginosa. \u003cem\u003eScientific Reports\u003c/em\u003e,\u003cem\u003e\u0026nbsp;9\u003c/em\u003e(1). https://doi.org/10.1038/s41598-019-41496-4\u003c/li\u003e\n \u003cli\u003eSommerset, I., Krossoy, B., Biering, E., \u0026amp; Frost, P. (2005). Vaccines for fish in aquaculture. \u003cem\u003eExpert Review of Vaccines\u003c/em\u003e,\u003cem\u003e\u0026nbsp;4\u003c/em\u003e(1), 89-101. https://doi.org/10.1586/14760584.4.1.89\u003c/li\u003e\n \u003cli\u003eThwaite, R., Ji, J., Torrealba, D., Coll, J., Sab\u0026eacute;s, M., Villaverde, A., \u0026amp; Roher, N. (2018). Protein Nanoparticles Made of Recombinant Viral Antigens: A Promising Biomaterial for Oral Delivery of Fish Prophylactics. \u003cem\u003eFrontiers in immunology\u003c/em\u003e, \u003cem\u003e9\u003c/em\u003e, 1652. https://doi.org/10.3389/fimmu.2018.01652\u003c/li\u003e\n \u003cli\u003eThwaite, R., Berbel, C., Aparicio, M., Torrealba, D., Pesarrodona, M., Villaverde, A., Borrego, J.J., Manchado, M., Roher, N., 2020. Nanostructured recombinant protein particles raise specific antibodies against the nodavirus NNV coat protein in sole. Fish \u0026amp; Shellfish Immunology 99, 578\u0026ndash;586.. https://doi.org/10.1016/j.fsi.2020.02.029\u003c/li\u003e\n \u003cli\u003eTobar, I., Arancibia, S., Torres, C., Vera, V., Soto, P., Carrasco, C., Alvarado, M., Neira, E., Arcos, S., \u0026amp; Tobar, J. A. (2015). Successive oral immunizations against Piscirickettsia salmonis and infectious salmon anemia virus are required to maintain a long-term protection in farmed salmonids. \u003cem\u003eFrontiers in Immunology\u003c/em\u003e,\u003cem\u003e\u0026nbsp;6\u003c/em\u003e, Article 244. https://doi.org/10.3389/fimmu.2015.00244\u003c/li\u003e\n \u003cli\u003eTorrealba, D., Seras-Franzoso, J., Mamat, U., Wilke, K., Villaverde, A., Roher, N., \u0026amp; Garcia-Fruitos, E. (2016). Complex Particulate Biomaterials as Immunostimulant-Delivery Platforms. \u003cem\u003ePlos One\u003c/em\u003e,\u003cem\u003e\u0026nbsp;11\u003c/em\u003e(10), Article e0164073. https://doi.org/10.1371/journal.pone.0164073\u003c/li\u003e\n \u003cli\u003eTorrealba, D., L\u0026oacute;pez, D., Zelada, P., Salinas-Parra, N., Valenzuela-Avil\u0026eacute;s, P., Garcia-Fruit\u0026oacute;s, E., Ar\u0026iacute;s, A., Mercado, L., Altamirano, C., \u0026amp; Gallardo-Matus, J. (2024). Immunomodulation Evidence of Nanostructured Recombinant Proteins in Salmonid Cells. Animals : an open access journal from MDPI, 14(6), 844. https://doi.org/10.3390/ani14060844\u003c/li\u003e\n \u003cli\u003eValenzuela-Aviles, P., Torrealba, D., Figueroa, C., Mercado, L., Dixon, B., Conejeros, P., \u0026amp; Gallardo-Matus, J. (2022). Why vaccines fail against Piscirickettsiosis in farmed salmon and trout and how to avoid it: A review. \u003cem\u003eFrontiers in Immunology\u003c/em\u003e,\u003cem\u003e\u0026nbsp;13\u003c/em\u003e. https://doi.org/10.3389/fimmu.2022.1019404\u003c/li\u003e\n \u003cli\u003eVasquez, I., Retamales, J., Parra, B., Machimbirike, V., Robeson, J., \u0026amp; Santander, J. (2023). Comparative Genomics of a Polyvalent Escherichia-Salmonella Phage fp01 and In Silico Analysis of Its Receptor Binding Protein and Conserved Enterobacteriaceae Phage Receptor. \u003cem\u003eViruses\u003c/em\u003e,\u003cem\u003e\u0026nbsp;15\u003c/em\u003e(2), 379. https://doi.org/10.3390/v15020379\u003c/li\u003e\n \u003cli\u003eWang, L., Maji, S. K., Sawaya, M. R., Eisenberg, D., \u0026amp; Riek, R. (2008). Bacterial Inclusion Bodies Contain Amyloid-Like Structure. \u003cem\u003ePLoS Biology\u003c/em\u003e,\u003cem\u003e\u0026nbsp;6\u003c/em\u003e(8), e195. https://doi.org/10.1371/journal.pbio.0060195\u003c/li\u003e\n \u003cli\u003eWaterhouse, A., Bertoni, M., Bienert, S., Studer, G., Tauriello, G., Gumienny, R., Heer, F. T., de Beer, T. A. P., Rempfer, C., Bordoli, L., Lepore, R., \u0026amp; Schwede, T. (2018). SWISS-MODEL: homology modelling of protein structures and complexes. \u003cem\u003eNucleic Acids Research\u003c/em\u003e,\u003cem\u003e\u0026nbsp;46\u003c/em\u003e(W1), W296-W303. https://doi.org/10.1093/nar/gky427\u003c/li\u003e\n \u003cli\u003eWiederstein, M., \u0026amp; Sippl, M. J. (2007). ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. \u003cem\u003eNucleic Acids Research\u003c/em\u003e,\u003cem\u003e\u0026nbsp;35\u003c/em\u003e, W407-W410. https://doi.org/10.1093/nar/gkm290\u003c/li\u003e\n \u003cli\u003eXing, J., An, Z., Tang, X., Sheng, X., Chi, H., \u0026amp; Zhan, W. (2023). Expression and Immune Characterization of Major Histocompatibility Complex in Paralichthys olivaceus after Antigen Stimulation. \u003cem\u003eBiology\u003c/em\u003e,\u003cem\u003e\u0026nbsp;12\u003c/em\u003e(12), 1464. https://doi.org/10.3390/biology12121464\u003c/li\u003e\n \u003cli\u003eYang, J. Y., \u0026amp; Zhang, Y. (2015). I-TASSER server: new development for protein structure and function predictions. \u003cem\u003eNucleic Acids Research\u003c/em\u003e,\u003cem\u003e\u0026nbsp;43\u003c/em\u003e(W1), W174-W181. https://doi.org/10.1093/nar/gkv342\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[{"identity":"06461b60-3964-47f5-a893-15eb3f1be343","identifier":"10.13039/501100007434","name":"Agência Nacional de Inovação","awardNumber":"36000","order_by":0}],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Pontificial Catholic University of Valparaiso","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":"recombinant protein, cell line, SRS","lastPublishedDoi":"10.21203/rs.3.rs-5941909/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5941909/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe article focuses on the development of a nanostructured multi-epitope vaccine prototype to control Piscirickettsiosis, a serious bacterial infection caused by Piscirickettsia salmonis in salmonids.\u003c/p\u003e\n\u003cp\u003ePiscirickettsiosis, one of the main causes of mortality in Chilean aquaculture, generates significant economic losses and extensive use of antibiotics, which represents risks to environmental and public health. Despite the existence of vaccines, their efficacy remains limited, especially under field conditions, where the genetic variability of the pathogen and other external factors compromise immunological protection. This research applies reverse vaccinology to identify specific antigenic epitopes of P. salmonis, particularly of the LF-89 and EM-90 genogroups, which are predominant in Chilean aquaculture. The study includes the design and production of four nanoparticles (NPs) with chimeric characteristics, called SkipZ, PulseJ, HopQ and Hoptech, derived from P. salmonis epitopes. These nanoparticles were expressed in Escherichia coli and purified for further immunogenic evaluation. The research analyses the uptake of these nanostructures by salmonid RTS-11 macrophage cells and their ability to induce antigen presentation and pro-inflammatory responses. The results show that the nanoparticles, especially SkipZ and HopQ, effectively stimulate the expression of key markers involved in antigen presentation, such as MHC-II, CD83 and CD86, as well as pro-inflammatory cytokines such as IL-1β and TNF-α, in a dose-dependent manner. These findings suggest that the selected epitopes are capable of enhancing immune responses in salmonid cells. This multi-epitope vaccine approach seeks to offer a more specific and effective strategy to control Piscirickettsiosis, potentially reducing the dependence on antibiotics and improving the long-term protection of salmonid populations. The work highlights the potential of using nanoparticle-based vaccines to induce robust cellular immunity, critical to combat intracellular pathogens such as P. salmonis. This proof-of-concept study paves the way for the development and optimization of vaccines tailored to the pathogen-specific genetic diversity in aquaculture environments.\u003c/p\u003e","manuscriptTitle":"Prototype of a nanostructured multi-epitope vaccine for the control of Piscirickettsiosis: Proof-of concept in salmonid cells","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-04 03:02:23","doi":"10.21203/rs.3.rs-5941909/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":"59659dff-af73-4115-be19-3d9a1f81922c","owner":[],"postedDate":"February 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":43709300,"name":"Animal Science"}],"tags":[],"updatedAt":"2025-02-04T03:02:24+00:00","versionOfRecord":[],"versionCreatedAt":"2025-02-04 03:02:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5941909","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5941909","identity":"rs-5941909","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}