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Matthijs AMF, Auray G, Jakob V, García-Nicolás O, Braun RO, Keller I, Bruggman R, Devriendt B, Boyen F, Guzman CA, Michiels A, Haesebrouck F, Collin N, Barnier-Quer C, Maes D, Summerfield A. Systems Immunology Characterization of Novel Vaccine Formulations for Mycoplasma hyopneumoniae Bacterins. Front Immunol 2019; 10:1087. [PMID: 31178860 PMCID: PMC6543460 DOI: 10.3389/fimmu.2019.01087] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2019] [Accepted: 04/29/2019] [Indexed: 12/20/2022] Open
Abstract
We characterized five different vaccine candidates and a commercial vaccine in terms of safety, immunogenicity and using a systems vaccinology approach, with the aim to select novel vaccine candidates against Mycoplasma hyopneumoniae. Seven groups of six M. hyopneumoniae-free piglets were primo- and booster vaccinated with the different experimental bacterin formulations, the commercial vaccine Hyogen® as a positive control or PBS as a negative control. The experimental bacterin was formulated with cationic liposomes + c-di-AMP (Lipo_AMP), cationic liposomes + Toll-like receptor (TLR) 2/1, TLR7, and TLR9 ligands (TLR ligands; Lipo_TLR), micro-particles + TLR ligands (PLGA_TLR), squalene-in-water emulsion + TLR ligands (SWE_TLR), or DDA:TDB liposomes (Lipo_DDA:TDB). Lipo_DDA:TDB and Lipo_AMP were the most potent in terms of serum antibody induction, and Lipo_DDA:TDB, Lipo_AMP, and SWE_TLR significantly induced Th1 cytokine-secreting T-cells. Only PLGA_TLR appeared to induce Th17 cells, but was unable to induce serum antibodies. The transcriptomic analyses demonstrated that the induction of inflammatory and myeloid cell blood transcriptional modules (BTM) in the first 24 h after vaccination correlated well with serum antibodies, while negative correlations with the same modules were found 7 days post-vaccination. Furthermore, many cell cycle and T-cell BTM upregulated at day seven correlated positively with adaptive immune responses. When comparing the delivery of the identical TLR ligands with the three formulations, we found SWE_TLR to be more potent in the induction of an early innate immune response, while the liposomal formulation more strongly promoted late cell cycle and T-cell BTM. For the PLGA formulation we found signs of a delayed and weak perturbation of these BTM. Lipo_AMP was found to be the most potent vaccine at inducing a BTM profile similar to that correlating with adaptive immune response in this and other studies. Taken together, we identified four promising vaccine candidates able to induce M. hyopneumoniae-specific antibody and T-cell responses. In addition, we have adapted a systems vaccinology approach developed for human to pigs and demonstrated its capacity in identifying early immune signatures in the blood relating to adaptive immune responses. This approach represents an important step in a more rational design of efficacious vaccines for pigs.
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Affiliation(s)
- Anneleen M F Matthijs
- Department of Reproduction, Obstetrics and Herd Health, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | - Gaël Auray
- Institute of Virology and Immunology, Mittelhäusern, Switzerland.,Department of Infectious Diseases and Pathobiology, Vetsuisse Faculty, University of Bern, Bern, Switzerland
| | - Virginie Jakob
- Vaccine Formulation Laboratory, University of Lausanne, Epalinges, Switzerland
| | - Obdulio García-Nicolás
- Institute of Virology and Immunology, Mittelhäusern, Switzerland.,Department of Infectious Diseases and Pathobiology, Vetsuisse Faculty, University of Bern, Bern, Switzerland
| | - Roman O Braun
- Institute of Virology and Immunology, Mittelhäusern, Switzerland.,Department of Infectious Diseases and Pathobiology, Vetsuisse Faculty, University of Bern, Bern, Switzerland
| | - Irene Keller
- Interfaculty Bioinformatics Unit, Swiss Institute of Bioinformatics, University of Bern, Bern, Switzerland.,Department of Biomedical Research, University of Bern, Bern, Switzerland
| | - Rémy Bruggman
- Interfaculty Bioinformatics Unit, Swiss Institute of Bioinformatics, University of Bern, Bern, Switzerland
| | - Bert Devriendt
- Laboratory of Veterinary Immunology, Department of Virology, Parasitology and Immunology, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | - Filip Boyen
- Department of Pathology, Bacteriology and Avian Diseases, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | - Carlos A Guzman
- Department of Vaccinology and Applied Microbiology, Helmholtz Centre for Infection Research, Brunswick, Germany
| | - Annelies Michiels
- Department of Reproduction, Obstetrics and Herd Health, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | - Freddy Haesebrouck
- Department of Pathology, Bacteriology and Avian Diseases, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | - Nicolas Collin
- Vaccine Formulation Laboratory, University of Lausanne, Epalinges, Switzerland
| | | | - Dominiek Maes
- Department of Reproduction, Obstetrics and Herd Health, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | - Artur Summerfield
- Institute of Virology and Immunology, Mittelhäusern, Switzerland.,Department of Infectious Diseases and Pathobiology, Vetsuisse Faculty, University of Bern, Bern, Switzerland
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