Search

Objectives: We investigated whether quantifying the serial QuantiFERON-TB Gold (QFT) response improves tuberculosis (TB) risk stratification in pulmonary TB (PTB) contacts. Methods: A total of 297 untreated adult household PTB contacts, QFT tested at baseline and 3 months after index notification, were prospectively observed (median 1460 days). Normal variance of serial QFT responses was established in 46 extrapulmonary TB contacts. This informed categorisation of the response in QFT-positive PTB contacts as converters, persistently QFT-positive with significant increase (PPincrease), and without significant increase (PPno-increase). Results: In total, eight co-prevalent TB (disease ≤3 months after index notification) and 12 incident TB (>3 months after index notification) cases were diagnosed. Genetic linkage to the index strain was confirmed in all culture-positive progressors. The cumulative 2-year incident TB risk in QFT-positive contacts was 8.4% (95% confidence interval, 3.0-13.6%); stratifying by serial QFT response, significantly higher risk was observed in QFT converters (28%), compared with PPno-increase (4.8%) and PPincrease (3.7%). Converters were characterised by exposure to index cases with a shorter interval from symptom onset to diagnosis (median reduction 50.0 days, P = 0.013). Conclusions: QFT conversion, rather than quantitative changes of a persistently positive serial QFT response, is associated with greater TB risk and exposure to rapidly progressive TB.

Background CD4+ Th1 cells producing IFN-γ are required to eradicate intracellular pathogens, however if uncontrolled these cells can cause immunopathology. The cytokine IL-10 is produced by multiple immune cells including Th1 cells during infection and regulates the immune response to minimise collateral host damage. In this study we aimed to elucidate the transcriptional network of genes controlling the expression of Il10 and proinflammatory cytokines, including Ifng in Th1 cells differentiated from mouse naive CD4+ T cells. Methods We applied computational analysis of gene regulation derived from temporal profiling of gene expression clusters obtained from bulk RNA sequencing (RNA-seq) of flow cytometry sorted naïve CD4+ T cells from mouse spleens differentiated in vitro into Th1 effector cells with IL-12 and IL-27 to produce Ifng and Il10, compared to IL-27 alone which express Il10 only, or IL-12 alone which express Ifng and no Il10, or medium control driven-CD4+ T cells which do not express effector cytokines. Data were integrated with analysis of active genomic regions from these T cells using an assay for transposase-accessible chromatin with sequencing (ATAC)-seq, integrated with literature derived-Chromatin-immunoprecipitation (ChIP)-seq data and the RNA-seq data, to elucidate the transcriptional network of genes controlling expression of Il10 and pro-inflammatory effector genes in Th1 cells. The co-dominant role for the transcription factors, Prdm1 (encoding Blimp-1) and Maf (encoding c-Maf) , in cytokine gene regulation in Th1 cells, was confirmed using T cells obtained from mice with T-cell specific deletion of these transcription factors. Results We show that the transcription factors Blimp-1 and c-Maf each have unique and common effects on cytokine gene regulation and not only co-operate to induce Il10 gene expression in IL-12 plus IL-27 differentiated mouse Th1 cells, but additionally directly negatively regulate key proinflammatory cytokines including Ifng, thus providing mechanisms for reinforcement of regulated Th1 cell responses. Conclusions These data show that Blimp-1 and c-Maf positively and negatively regulate a network of both unique and common anti-inflammatory and pro-inflammatory genes to reinforce a Th1 response in mice that will eradicate pathogens with minimum immunopathology.

ABSTRACT The crucial transmission phase of tuberculosis (TB) relies on infectious sputum and yet cannot easily be modeled. We applied one-step RNA sequencing (RNA-Seq) to sputum from infectious TB patients to investigate the host and microbial environments underlying transmission of Mycobacterium tuberculosis. In such TB sputa, compared to non-TB controls, transcriptional upregulation of inflammatory responses, including an interferon-driven proinflammatory response and a metabolic shift toward glycolysis, was observed in the host. Among all bacterial sequences in the sputum, approximately 1.5% originated from M. tuberculosis, and its transcript abundance was lower in HIV-1-coinfected patients. Commensal bacterial abundance was reduced in the presence of M. tuberculosis infection. Direct alignment to the genomes of the predominant microbiota species also reveals differential adaptation, whereby firmicutes (e.g., streptococci) displayed a nonreplicating phenotype with reduced transcription of ribosomal proteins and reduced activities of ATP synthases, while Neisseria and Prevotella spp. were less affected. The transcriptome of sputum M. tuberculosis more closely resembled aerobic replication and shared similarity in carbon metabolism to in vitro and in vivo models with significant upregulation of genes associated with cholesterol metabolism and downstream propionate detoxification pathways. In addition, and counter to previous reports on intracellular M. tuberculosis infection in vitro, M. tuberculosis in sputum was zinc, but not iron, deprived, and the phoP loci were also significantly downregulated, suggesting that the pathogen is likely extracellular in location. IMPORTANCE Although a few studies have described the microbiome composition of TB sputa based on 16S ribosomal DNA, these studies did not compare to non-TB samples and the nature of the method does not allow any functional inference. This is the first study to apply such technology using clinical specimens and obtained functional transcriptional data on all three aspects simultaneously. We anticipate that an improved understanding on the biological interactions in the respiratory tract may also allow novel interventions, such as those involving microbiome manipulation or inhibitor targeting disease-specific metabolic pathways.