mtTB: A Web-Based R/Shiny App for Pulmonary Tuberculosis Screening

Pulmonary tuberculosis caused by Mycobacterium tuberculosis remains a global issue. However, the diagnosis of active pulmonary tuberculosis (TB) remains a challenge in the clinic. Small non-coding RNAs are potential diagnostic biomarkers for pulmonary tuberculosis. However, the current normalization methods are not stable and usually fail to reliably detect differentially expressed sncRNAs. To identify reliable biomarkers for pulmonary tuberculosis screening, we utilized the ratio-based method on the newly discovered mitochondria-derived small RNAs in human peripheral blood mononuclear cells. The prediction model of seven mtRNA biomarkers noteworthily enables the discrimination between pulmonary tuberculosis patients and controls in discovery (AUC = 0.906, 23 patients) and independent validation cohort (AUC = 0.968, 20 patients). Moreover, we present mtTB (https://tuberculosis.shinyapps.io/mtTB/), a novel R Graphical User Interface (GUI) that provides reliable biomarkers for the feasibility of blood-based screening, and produce a more accurate tool for pulmonary tuberculosis diagnosis in real clinical practice.

Automated summary

Pulmonary tuberculosis caused by Mycobacterium tuberculosis remains a global issue, and the diagnosis of active pulmonary tuberculosis is challenging. However, by studying mitochondria-derived small RNAs, we have identified reliable biomarkers that can provide a more accurate diagnosis of pulmonary tuberculosis. We have also developed a user interface that offers reliable biomarkers for blood-based screening and improves the accuracy of pulmonary tuberculosis diagnosis in real clinical practice.