Summary:
UCLA researchers in the Departments of Computer Science and Anatomic Pathology have developed an untargeted NGS diagnostic tool capable of detecting all known and emerging respiratory RNA viruses in a single test, enhancing our capacity to rapidly address public health crises through improved diagnostics.
Background:
Most clinical diagnostic tools today are designed for specific known pathogens, which are crucial, but typically only available after an outbreak begins. Developing and validating such tests is time-consuming. In the face of a pandemic or public health emergency, time is of the essence, and agnostic diagnostic tests capable of identifying any known or novel pathogen become crucial for swift responses. Next-generation sequencing (NGS) technology offers promise in this regard, as it can sequence DNA or RNA of various types, enabling the identification of any present pathogen, including viruses like SARS-CoV-2. While NGS is already employed for surveillance and COVID-19 variant detection, it has not yet been fully integrated into the standard of care for medical diagnostics. There is a growing imperative within the standard of care to adopt commercial untargeted NGS diagnostic platforms, which could enable early pathogen detection and tracking of emerging variants.
Innovation:
Professor Eskin and Professor Arboleda led a team of researchers to invent SwabSeq, an untargeted next-generation sequencing (NGS) diagnostic tool tailored for the detection of nucleic acid from pathogens in upper respiratory specimens of potentially infected individuals. This scalable sequencing approach encompasses all known and emerging respiratory RNA viruses in a single test, enhancing our ability to swiftly respond to public health crises with an innovative diagnostic capability. The process involves nucleic acid extraction, NGS library preparation, and sequencing, with subsequent data analysis using a bioinformatics pipeline. Notably, this platform does not rely on targeted PCR amplification for pathogen sequences; instead, it generates a substantial number of sequencing reads, predominantly sourced from the patient's own nucleic acid. The bioinformatics pipeline then identifies and categorizes the minority of reads corresponding to pathogen sequences, utilizing the Reference Sequence database. Rigorous verification demonstrates that less than 1% of reads are misclassified for each organism, establishing the platform's accuracy in pathogen identification. In a proof-of-concept clinical validation, UCLA's diagnostic platform exhibits strong sensitivity (94.34%), specificity (98.91%), and overall accuracy (98.34%) in detecting an RNA virus (SARS-CoV-2). This pioneering advancement extends current technology to create an "agnostic" test capable of detecting any respiratory RNA virus, including novel and emerging ones, with rapid implementation and without requiring additional regulatory approvals in future pandemic scenarios.
Demonstration Video:
UCLA SwabSeq
Potential Applications:
• Identification of novel pathogens
• Investigating of emerging diseases
• Genomic sequencing in medicine
• Environmental monitoring
Advantages:
• Versatility; capable of detecting known and emerging pathogens
• Compatible with different commercial detecting systems
• Sensitive, accurate and fast turnaround time
• Scalability
Development to Date:
First description of complete invention (oral or written): September 6th, 2022
Estimated date of Public Disclosure: June 22nd, 2023
Reference:
UCLA Case No. 2023-293
Lead Inventor:
Prof. Eleazar Eskin and Prof. Valerie Arboleda.