Mechanisms underlying variability in transmission of Mycobacterium tuberculosis strains remain undefined. By characterizing high and low transmission strains of M.tuberculosis in mice, we show here that high transmission M.tuberculosis strain induce rapid IL-1R-dependent alveolar macrophage migration from the alveolar space into the interstitium and that this action is key to subsequent temporal events of early dissemination of bacteria to the lymph nodes, Th1 priming, granulomatous response and bacterial control. In contrast, IL-1R-dependent alveolar macrophage migration and early dissemination of bacteria to lymph nodes is significantly impeded in infection with low transmission M.tuberculosis strain; these events promote the development of Th17 immunity, fostering neutrophilic inflammation and increased bacterial replication. Our results suggest that by inducing granulomas with the potential to develop into cavitary lesions that aids bacterial escape into the airways, high transmission M.tuberculosis strain is poised for greater transmissibility. These findings implicate bacterial heterogeneity as an important modifier of TB disease manifestations and transmission.

“Infection resisters” are broadly defined as individuals who despite significant exposure to Mycobacterium tuberculosis remain persistently unreactive to conventional detection assays, suggesting that they remain uninfected or rapidly clear their infection early on following exposure. In this review, we highlight recent studies that point to underlying host immune mechanisms that could mediate this natural resistance. We also illustrate some additional avenues that are likely to be differently modulated in resisters and possess the potential to be targeted, ranging from early mycobacterial sensing leading up to subsequent killing. Emerging research in this area can be harnessed to provide valuable insights into the development of novel therapeutic and vaccine strategies against M. tuberculosis.

BackgroundMost individuals exposed to Mycobacterium tuberculosis (Mtb) develop latent tuberculosis infection (LTBI) and remain at risk for progressing to active tuberculosis disease (TB). Malnutrition is an important risk factor driving progression from LTBI to TB. However, the performance of blood-based TB risk signatures in malnourished individuals with LTBI remains unexplored. The aim of this study was to determine if malnourished and control individuals had differences in gene expression, immune pathways and TB risk signatures.MethodsWe utilized data from 50 tuberculin skin test positive household contacts of persons with TB - 18 malnourished participants (body mass index [BMI] < 18.5 kg/m2) and 32 controls (individuals with BMI ≥ 18.5 kg/m2). Whole blood RNA-sequencing was conducted to identify differentially expressed genes (DEGs). Ingenuity Pathway Analysis was applied to the DEGs to identify top canonical pathways and gene regulators. Gene enrichment methods were then employed to score the performance of published gene signatures associated with progression from LTBI to TB.ResultsMalnourished individuals had increased activation of inflammatory pathways, including pathways involved in neutrophil activation, T-cell activation and proinflammatory IL-1 and IL-6 cytokine signaling. Consistent with known association of inflammatory pathway activation with progression to TB disease, we found significantly increased expression of the RISK4 (area under the curve [AUC] = 0.734) and PREDICT29 (AUC = 0.736) progression signatures in malnourished individuals.ConclusionMalnourished individuals display a peripheral immune response profile reflective of increased inflammation and a concomitant increased expression of risk signatures predicting progression to TB. With validation in prospective clinical cohorts, TB risk biomarkers have the potential to identify malnourished LTBI for targeted therapy.

Rationale Blood-based biomarkers for diagnosis of active tuberculosis (TB), monitoring treatment response and predicting risk of progression to TB disease have been reported. However, validation of the biomarkers across multiple independent cohorts is scarce. A robust platform to validate TB biomarkers in different populations with clinical endpoints is essential to the development of a point-of-care clinical test. Objectives NanoString nCounter technology is an amplification-free digital detection platform that directly measures mRNA transcripts with high specificity. Here, we investigated whether NanoString could serve as a platform for extensive validation of candidate TB biomarkers. Methods The NanoString platform was employed for performance evaluation of existing TB gene signatures in a cohort in which signatures were previously evaluated on RNA-seq dataset. A NanoString Codeset that probes 107 genes comprising twelve TB signatures and six house-keeping genes (NS-TB107) was developed and applied to total RNA derived from whole blood samples of TB patients and individuals with latent TB infection (LTBI) from South India. The TBSignatureProfiler tool was used to score samples for each signature. An ensemble of machine learning algorithms was used to derive a parsimonious biomarker. Measurements and Main Results Gene signatures present in NS-TB107 had statistically significant discriminative power for segregating TB from LTBI. Further analysis of the data yielded a six-gene set (NANO6) that when tested on ten published datasets was highly diagnostic for active TB. Conclusions The NanoString nCounter system provides a robust platform to validate existing TB biomarkers and to derive a parsimonious gene signature with enhanced diagnostic performance.

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