Predicting Tuberculosis Transmission, Drug Resistance and Disease from Pathogen and Host Sequence Data
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AI plain-English summaryIn Lima, Peru, a research team will sequence the full genomes of tuberculosis bacteria from thousands of patients to map exactly who infects whom and spot drug resistance before it becomes clinically detectable. Tuberculosis incidence in Callao province exceeds 150 cases per 100,000 people, and Peru has the highest rate of multidrug-resistant TB in the Americas. Standard tests detect resistance only after it has already emerged. The team previously identified a phenomenon called “pre-resistance”—genetic mutations that signal impending drug resistance—but it has never been tested in a clinical setting. They will also link the pathogen’s genetic lineage to the host’s immune response, measured through blood gene expression, to see whether certain bacterial strains drive progression from latent infection to active disease more aggressively. If successful, this work could transform TB control. Public health officials could trace transmission chains in real time, start patients on effective drugs before resistance solidifies, and identify who is most likely to develop active disease. The same sequencing approach could be adapted for other bacterial pathogens.
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