Active Infection & Immunity Genetics & Molecular Biology

Predicting Tuberculosis Transmission, Drug Resistance and Disease from Pathogen and Host Sequence Data

In plain English

AI plain-English summary

In 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.

View original technical description
This proposal will build upon the principal applicant’s experience of 15-years’ research work in Lima, Peru. The province of Callao, Lima, has a tuberculosis incidence above 150 per 100,000 population whilst Peru has the highest burden of multidrug-resistant tuberculosis in the Americas. Mycobacterium tuberculosis is the focus of this work, although the concepts are equally applicable to many pathogens. This proposal has three key aims: - To apply hybrid genome sequencing to understand tuberculosis transmission. - To quantify the clinical impact of tuberculosis pre-resistance. - To define the association between pathogen genotype and the host transcriptomic response to tuberculosis infection and disease. Comprehensive population level surveys of Mycobacterium tuberculosis combined with prospective household cohort studies and the latest in genome sequencing technology will address these aims. The potential for hybrid deep sequencing to unravel tuberculosis who- infected-whom transmission chains has never been evaluated. Similarly, pathogen pre-resistance – first described by the principal applicant - has never been evaluated in a clinical setting. The association between the pathogen genome and gene expression following tuberculosis infection has never been adequately addressed. Understanding the importance of pathogen lineage and the trajectory of the host transcriptome following infection could improve prediction of tuberculosis progression from latency to disease.

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Researchers

Louis Grandjean (EPMC Awardee)

Related Research

Grants with similar aims, by meaning.

Applying Personalised Pathogen Genomic Medicine to Mycobacterium tuberculosis
Resolving Tuberculosis Transmission Using Long Read And Deep Sequencing Data To Inform Targeted Interventions
Using whole genome sequencing to characterise drug resistant Mycobacterium tuberculosis in Thailand
Investigating the genomic basis of antimicrobial resistance in Mycobacterium tuberculosis (Mtb) using genome-wide methodologies
Understanding the transmission of tuberculosis using Mycobacterium tuberculosis sequence data

Original classification

Career Development Award

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