Single Step Multiplexed Metagenome Sequencing based Bacterial/Viral Pathogen Detection for Bovine Respiratory Disease

Case ID:
2021-036

BACKGROUND

Traditional pathogen identification is a cornerstone of both veterinary and medical diagnostics. For decades, methods such as Polymerase Chain Reaction (PCR) and bacterial or culturing have been widely used. However, these techniques are often time-consuming and resource intensive. Typically, only a limited number of pathogens can be detected at once, and results may require significant time for analysis. In today’s rapidly evolving infectious disease landscape, there is a pressing need for faster and more efficient pathogen identification to keep pace with the swift spread of infections.

SUMMARY OF TECHNOLOGY

OSU researchers have developed innovative in-silico technology for rapid and reliable identification of pathogens in metagenomic samples. MiFi (Microbial Finder), is a cutting-edge approach to pathogen detection, leveraging target-specific electronic probes (e-probes) for the rapid identification of pathogens in clinical samples. This two-step approach significantly improves the efficiency and accuracy of pathogen detection by minimizing the computational load and database requirements typically associated with metagenomic analysis.  Call us to meet the team today.

POTENTIAL AREAS OF APPLICATION

  • Veterinary & Human Pathogen Detection
  • Next-Generation Sequencing (NGS)
  • Water Quality & Monitoring Services
  • Biodefense and Biosurveillance
  • Microbiome Research

MAIN ADVANTAGES

  • Fast, Multiplexed and Reliable Pathogen Detection
  • Reduced Computation Load
  • Antibiotic Resistant Pathogen Identification
  • Specific Pathogen Detection
  • Increased Scalability

STAGE OF DEVELOPMENT

  • Working Model
Patent Information:
For Information, Contact:
Jai Hariprasad Rajendran
Commercialization Officer
Oklahoma State University
jair@okstate.edu
Inventors:
Jerry Malayer
Sai Narayanan
Kitty Cardwell
Andres Espindola Camacho
Akhilesh Ramachandran
Keywords:
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