Gigapixel Next-Generation-Sequencing: An Ultra-Sensitive Diagnostic for Infections of the CNS

NIH RePORTER · AI · R01 · $610,736 · view on reporter.nih.gov ↗

Abstract

ABSTRACT Infectious diseases remain a significant cause of morbidity worldwide, highlighting the critical need for accurate diagnosis. However, shared symptoms among different infections and the emergence of drug resistance make diagnosis and treatment selection challenging. In this competing renewal, we propose to develop Gigapixel NGS (gNGS) to enable rapid, sensitive, and information-rich infectious disease diagnosis. gNGS builds upon our Gigapixel PCR (gPCR) technology by incorporating powerful next-generation sequencing capabilities. By utilizing double emulsion vesicles for single cell assays, gNGS eliminates the need for specialized droplet analyzers and allows common flow cytometers to be used for genome isolation. Our goal in this renewal is to leverage the capabilities of Gigapixel NGS to detect, isolate, and sequence infectious pathogen genomes from patient samples, which will improve the efficiency and sensitivity of pathogen sequencing. We will collaborate with Dr. Charles Chiu, a renowned expert in infectious disease diagnostics who leads the CLIA-certified pathogen lab at UCSF, to develop clinical workflows and bioinformatic tools for interrogating the recovered genomes for relevant biomarker sequences, including virulence factors and drug resistance genes. Dr. Chiu's expertise in infectious disease diagnostics and practical experience in clinical sample sequencing for pathogen detection will ensure that the new diagnostic is effective and practical in a clinical setting.

Key facts

NIH application ID
11228402
Project number
5R01AI178795-11
Recipient
UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
Principal Investigator
Adam R. Abate
Activity code
R01
Funding institute
AI
Fiscal year
2026
Award amount
$610,736
Award type
5
Project period
2023-11-01T00:00:00 → 2027-10-31T00:00:00