Data Sheet 1_Metagenomic and metatranscriptomic profiling of bronchoalveolar lavage fluid identifies microbial and host biomarkers of drug-resistant tuberculosis.docx
收藏NIAID Data Ecosystem2026-05-10 收录
下载链接:
https://figshare.com/articles/dataset/Data_Sheet_1_Metagenomic_and_metatranscriptomic_profiling_of_bronchoalveolar_lavage_fluid_identifies_microbial_and_host_biomarkers_of_drug-resistant_tuberculosis_docx/31177834
下载链接
链接失效反馈官方服务:
资源简介:
BackgroundDrug-resistant tuberculosis (DR-TB) undermines global TB control, yet how resistant Mycobacterium tuberculosis strains interact with the lung microbiome, phage communities, and local host immunity remains poorly defined.
MethodsIn a prospective cohort of 130 pulmonary TB patients (49 DR-TB, 81 drug-susceptible TB [DS-TB] patients), bronchoalveolar lavage fluid (BALF) was subjected to paired metagenomic and transcriptomic profiling. Microbial and bacteriophage community structures were assessed by diversity metrics and differential abundance testing, whereas host responses were characterized by gene expression, pathway enrichment, and immune cell deconvolution. A Random Forest model was trained to evaluate the diagnostic potential of host transcriptional signatures.
ResultsDR-TB airways presented distinct microbial beta diversity, with enrichment of Streptococcus spp. and streptococcal-targeting phages (e.g., Javan variants, phi-Ssu5SJ28rum). Transcriptomic analysis revealed 494 differentially expressed genes, which were associated with increased oxidative phosphorylation, suppressed ion channel and transporter activity, and enrichment of extracellular matrix remodeling pathways. Immune profiling demonstrated a significant reduction in γδ T cells in DR-TB patients (P = 0.0059). An 8-gene host-derived signature (ARHGEF5, PTGES3L, GAL3ST1, RANBP17, ACTA2_AS1, CBY3, MAMSTR, and LOC102031319) discriminated DR-TB from DS-TB with high accuracy (AUC = 0.837).
ConclusionThis dual-omics study defines the airway niche of DR-TB as a convergence of microbial dysbiosis, phage imbalance, and host immune–metabolic dysfunction. By uncovering DR-TB–specific microbial and transcriptional signatures, and deriving a predictive host-based classifier, our findings provide mechanistic insights and highlight novel opportunities for microbiome- and host-directed interventions in drug-resistant tuberculosis.
创建时间:
2026-01-29



