Precise, Accurate Bacterial Identification System

Technology #ua14-034

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Bonnie Hurwitz
Assistant Professor, Agricultural & Biosystems Engineering
George Watts
Research Associate Professor, Pharmacology
Managed By
Tod Mccauley

Title: BugSeq - Bacterial Identification in Clinical Infections


Invention: The technology is a rapid, whole genome sequence analysis tool to determine the type of bacteria, resistance, and virulence that lacks biases introduced by culture-based methods.


Background: The lack of accurate and precise methods to identify bacteria forces clinicians to use broad based antibiotic regimens. Unfortunately, only 20-40% of samples are diagnosed correctly with current methods. Use of these broad based antibiotic regimens can increase the rise of antibiotic resistance. For example, in diabetic foot ulcers, the microbial community is diverse and difficult for a clinician to predict which treatment would be effective. Lack of precise bacterial identification methods can lead to treatment failure, spread of infection, and ultimately, amputation of the affected limb. In addition, culture based methods generally only identify 1-4 species of bacteria within 24-72 hours.


  • Detection of pathogenic fungi, viruses, bacteria, and parasites



  • Utilizes next generation sequencing, fast k-mer based sequence analysis, and Bayesian network analysis for a full composition analysis
  • Able to stratify organism communities and detect drug resistance and virulence
  • Diagnoses within 6-8 hours
  • Lacks the bias in species detected compared to culture-based methods
  • Retains the potential to identify more species of bacteria in a sample


Licensing Manager: 

Rakhi Gibbons

(520) 626-6695