Δfcpa/δfcpb modified-live vaccine for canine leptospira cross-protection
A second-generation modified-live vaccine using CRISPR-generated ΔfcpA/ΔfcpB mutations in L. interrogans sv. Canicola for cross-protection against canine Leptospira, providing sterilizing immunity and integrating a DIVA ELISA for effective surveillance.
Overview
This innovative solution offers a modified-live vaccine (MLV) designed for canine Leptospira cross-protection. Utilizing CRISPR technology, it introduces a dual mutation (ΔfcpA/ΔfcpB) in L. interrogans sv. Canicola, leading to a non-motile, rod-shaped bacterium that retains an immunogenic protein repertoire. This vaccine is administered intranasally, ensuring sterilizing immunity, preventing renal colonization and leptospiruria in dogs. Additionally, a DIVA ELISA (rFcpA) system is integrated to differentiate vaccinated from infected dogs, facilitating effective disease surveillance.
Technical specifications
- CRISPR-generated dual knockout (ΔfcpA/ΔfcpB): Ensures enhanced safety and stability by collapsing the periplasmic flagellum, validated through Cryo-EM.
- Non-motile bacterial structure: The mutations yield a stable, non-reverting strain, confirmed through 50 passages and whole-genome sequencing.
- Immunogenic repertoire: Contains 154 conserved proteins eliciting cross-protective antibodies.
- DIVA ELISA integration: Differentiates vaccinated (negative) from infected (positive) dogs, enabling improved surveillance.
Technology readiness level
The vaccine is currently at Technology Readiness Level 4, with ongoing validations in various phases, including double mutant generation, safety and stability assessments, and cross-protection efficacy tests in animal models. The project is moving towards patent application and pilot study design for further development and commercialization.
About Consulting-ai
Consulting-ai operates as a consultancy providing customized artificial intelligence solutions designed to transform enterprise operations. The company claims to develop proprietary technology integrated with scientific databases—including TOXNET, PubChem, DrugBank, and MatWeb—to deliver specialized results. Their approach utilizes adaptive deep learning models with specific fine-tuning and federated learning techniques that employ homomorphic encryption to maintain data privacy and regulatory compliance, such as GDPR, HIPAA, and REACH.
These services are aimed at helping organizations across various industries reduce operational costs, optimize processes, and improve the precision of their workflows. By emphasizing the use of proprietary data and tailored implementations, the firm positions its offerings as distinct from generic commercial AI models, intending to provide scalable, high-performance solutions for complex, heterogeneous data environments.
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