Bloodstream infection diagnosis using long-read metagenomics (Blood-Gen Dx)
In plain English
AI plain-English summaryA single blood sample contains too few microbial cells for standard DNA sequencing to reliably detect an infection. Current tests for bloodstream infections are slow and often miss the culprit entirely. Doctors typically rely on blood cultures that take days to grow and fail in up to half of all cases. This delay forces clinicians to prescribe broad-spectrum antibiotics while they wait, contributing to antimicrobial resistance and poor patient outcomes. The problem is that infecting microbes in the blood are present at extremely low abundance—far below what conventional sequencing can pick up. This project aims to solve that bottleneck. The researchers are optimising the earliest steps: how to collect, concentrate, and retain enough microbial DNA from a blood sample to produce a definitive result. If they succeed, a single blood draw could reveal the exact pathogen and its antibiotic resistance profile within hours, not days. The impact would be immediate in hospital settings. Clinicians could switch from guesswork to targeted therapy, reducing unnecessary antibiotic use and improving survival rates for sepsis patients. The work is applied and diagnostic—not fundamental science—and its success depends on solving a practical engineering problem in sample preparation.
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