Tuberculosis Research and Epidemiology

The paper uses machine learning to analyze M. tuberculosis RNA-seq data, identifying gene modules and their roles in metabolism, stress response, and infection.

The paper shows that redox state modulates mycobacterial pathogenicity through genetic mutations and gene expression changes in M. smegmatis.

This study identifies host-pathogen genetic interactions influencing tuberculosis susceptibility using a genetically diverse mouse panel and Mtb mutants.

The paper develops a whole-host model of Mtb infection to predict immune outcomes and shows blood biomarkers may only reflect early lung events.

This study shows that Mycobacterium tuberculosis alters its cell envelope gene expression in response to human alveolar lining fluid, with differences observed between young and elderly donors.

The paper identifies a new ancestral L2 sublineage of Mycobacterium tuberculosis in Japan, linking historical tuberculosis outbreaks through genetic analysis.

The paper uses whole genome sequences and movement data to infer M. bovis transmission routes between cattle and badgers, finding higher cattle-to-cattle and badger-to-badger transmission rates than between species.

This paper introduces XBS, a bioinformatics pipeline that improves variant detection in contaminated and low coverage Mycobacterium tuberculosis sequencing data, outperforming existing methods in complex genomic regions and low-depth samples.

This study uses human airway organoids to model tuberculosis infection, showing mycobacteria infect epithelial cells with low efficiency and the organoid microenvironment controls but does not eliminate the pathogen.

The paper investigates how HIV and antiretroviral therapy affect the transcriptional and epigenetic response of alveolar macrophages to Mycobacterium tuberculosis.

GenTB predicts tuberculosis drug resistance from genomic data using machine learning, achieving higher sensitivity than existing tools with slightly lower specificity.

The paper demonstrates epistatic interactions in Mycobacterium tuberculosis complex that can reverse antibiotic resistance, specifically showing that eis promoter mutations cannot confer resistance if paired with LoF mutations in the eis coding region.

The paper analyzes whole-genome sequencing data of Mycobacterium tuberculosis isolates to study lineage evolution and antigenic diversity in China and Zhejiang Province.

This paper introduces an interpretable classification method for predicting drug resistance in M. tuberculosis, achieving high accuracy and flexibility.

This study uses CRISPR interference to assess the vulnerability and lethality of 96 target genes in Mycobacterium tuberculosis, identifying bactericidal and bacteriostatic effects across different cellular pathways.

The paper identifies high within-lineage genomic diversity and gene content differences in Mycobacterium tuberculosis complex lineage 5 compared to H37Rv, affecting transmission analysis and suggesting the need for alternative reference genomes.

The paper integrates multi-omics data with genome-wide association results to identify infection response pathways and genomic variants associated with resistance to bovine tuberculosis.

This study uses whole genome sequencing to analyze the population structure and transmission patterns of Mycobacterium bovis in Ethiopia, identifying two distinct introductions of the Eu3 clonal complex from Europe.

This study uses whole genome sequencing to differentiate between TB relapse and re-infection in HIV-positive and negative patients, finding 95% relapse in HIV-negative and 75% re-infection in HIV-positive cases.

This paper links drug transcriptomics with pharmacokinetics to predict in vivo drug interactions for tuberculosis treatments.

The paper identifies reduced host transcriptomic signatures for tuberculosis using microarray data and validates them with digital PCR, showing high accuracy in distinguishing TB from other conditions and latent TB.

The paper analyzes genomes of Mycobacterium africanum strains to identify a new lineage and explore their evolutionary history and phylogeography.

The paper analyzes whole genome sequences of Mycobacterium tuberculosis lineages L1 and L3 to show South Asia's role in their dispersion and identify local adaptation at the esxH locus.

The paper shows that kinase inhibition in Mtb affects regulatory networks, altering cell wall integrity, stress response, and energy production through transcription factor activity changes.

The paper investigates the association between dysglycemia and Mycobacterium tuberculosis lineages in TB patients, finding specific lineages linked to diabetes and pre-diabetes comorbidities.

This study analyzes global M. tuberculosis whole genome sequences to trace the temporal and geographic patterns of drug resistance acquisition and its correlation with country wealth.

This study uses proteomics to identify differentially expressed proteins in peripheral blood mononuclear cells from tuberculosis and diabetes comorbid patients compared to other groups.

This study uses genomic data and mathematical modeling to reconstruct transmission events in a large TB outbreak, identifying key predictors of transmission.

The paper identifies a highly rifampicin-resistant Mycobacterium tuberculosis strain in Southern Brazil linked to a 12-nucleotide insertion in the rpoB gene and highlights its transmission among prison inmates.