Environmental air sampling for detection and quantification of Mycobacterium tuberculosis in clinical settings: Proof of concept

Abstract

Abstract Objective: Novel approaches are needed to understand and disrupt Mycobacterium tuberculosis transmission. In this proof-of-concept study, we investigated the use of environmental air samplings to detect and quantify M. tuberculosis in different clinic settings in a high-burden area. Design: Cross-sectional, environmental sampling. Setting: Primary-care clinic. Methods: A portable, high-flow dry filter unit (DFU) was used to draw air through polyester felt filters for 2 hours. Samples were collected in the waiting area and TB room of a primary care clinic. Controls included sterile filters placed directly into collection tubes at the DFU sampling site, and filter samplings performed outdoors. DNA was extracted from the filters, and droplet digital polymerase chain reaction (ddPCR) was used to quantify M. tuberculosis DNA copies. Carbon dioxide (CO2) data loggers captured CO2 concentrations in the sampled areas. Results: The median sampling time was 123 minutes (interquartile range [IQR], 121–126). A median of 121 (IQR, 35–243) M. tuberculosis DNA copies were obtained from 74 clinic samplings, compared to a median of 3 (IQR, 1–33; P < .001) obtained from 47 controls. At a threshold of 320 DNA copies, specificity was 100%, and 18% of clinic samples would be classified as positive. Conclusions: This proof-of-concept study suggests that the potential for airborne M. tuberculosis detection based on M. tuberculosis DNA copy yield to enable the identification of high-risk transmission locations. Further optimization of the M. tuberculosis extraction technique and ddPCR data analysis would improve detection and enable robust interpretation of these data.