Webinar VHIR - Dr. Joan Joseph Munné "Pre-clinical development of recombinant Mycobacterium bovis BCG-based vaccine for HIV-TB. Lessons learned"
Dr. Joan Joseph Munné, Investigador del Grup de Microbiologia del Vall d'Hebron Institut de Recerca (VHIR) i Metge Adjunt de Microbiologia en l'Hospital Universitari Vall d'Hebron Barcelona Hospital Campus
Human Immunodeficiency Virus/Acquired Immune Deficiency Syndrome, tuberculosis, and malaria are responsible for most human deaths produced by infectious diseases worldwide. Vaccination against HIV requires generation of memory T cells and neutralizing antibodies, mucosal immunity, and stimulation of an innate immune responses. In this context, the use of Mycobacterium bovis bacillus Calmette–Guérin (BCG) as a live vaccine vehicle is a promising approach for T-cell induction. We will provide expert commentary and 5-year view on how the development of potential recombinant BCG-based HIV vaccines involves careful selection of the HIV antigen, expression vectors, promoters, BCG strain, preclinical animal models, influence of preexisting immunity, and safety issues, for the rational design of recombinant BCG:HIV vaccines to prevent HIV transmission in the general population. The three critical issues to be considered when developing a rBCG:HIV vaccine are codon optimization, antigen localization, and plasmid stability in vivo. The use of integrative expression vectors are likely to improve the mycobacterial vaccine stability and immunogenicity to develop not only recombinant BCG-based vaccines expressing second generation of HIV-1 immunogens but also other major pediatric pathogens to prime protective responses shortly following birth.
Joan Joseph belongs to the Microbiology Research Group at Vall d'Hebron Research Institute and Microbiology Department at Vall d’Hebron Hospital. He made a postdoctoral training working on recombinant BCG based HIV vaccines in the laboratory led by Dr. Barry R Bloom at Albert Einstein College of Medicine, New York and later in the microbiology laboratory at Harvard School of Public Health, Boston. He is currently, leading the research line on Preventive HIV vaccine, where they are developing a pediatric bivalent vaccine against HIV and Tuberculosis based on recombinant BCG. They are also developing a bivalent vaccine against human papillomavirus and HIV based on Virus-like particles. He is member of the Spanish Network for Cooperative AIDS Research and member of the European consortium EAVI2020, European Initiative for the Development of a Preventive / Therapeutic Vaccine against HIV / AIDS (H2020 Research and Innovation Program/ grant # 681137). Within the framework of the European consortium, they have built the recombinant BCG strains expressing different T-cell immunogens. He is also leading the teaching program addressed to predoctoral, master's and postdoctoral students from all over Europe (23 research groups). He has also participated and coordinated several health care programs and humanitarian projects in the field of HIV, Malaria, Tuberculosis and Ebola in rural Africa. Recently, they have developed a new mycobacterial vaccine design using an antibiotic-free selection system (patent PCT / EP2013 / 063978). Part of this work has been done in collaboration with Dr. Tomas Hanke and Professor Adrian Hill from Jenner Institute at Oxford University. On the other hand, in collaboration with Professor Carlos Martín from University of Zaragoza, they have built the recombinant MTBVAC strain expressing the HIVA immunogen (PI14 / 00494) as a possible candidate for a bivalent TB / HIV vaccine. MTBVAC is a live attenuated strain of M. tuberculosis constructed as a tuberculosis vaccine and is currently assessed in clinical trials. They are currently evaluating the safety and immunogenicity of recombinant BCG expressing the SIV:consv immunogen in Cynomolgus macaques (PI20/00217). On the other hand, he participates in the coordination of a collaborative project between HUVH, UPC, Fundación Probitas and WHO, for the development of a mobile application for the automated diagnosis of malaria by Digital Microscopy Imaging and artificial intelligence algorithms.
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