Diagnosing melioidosis and tracking treatment outcomes using breath

Melioidosis is a life-threatening infectious disease caused byBurkholderia pseudomallei(Bp). Rapid diagnosis and appropriate antimicrobial treatment are critical to reduce mortality, yet diagnosis is hindered by diverse clinical manifestations, mimicry with other diseases, and reliance on slow culture-based methods. Detecting volatile compounds offers a non-invasive approach for rapid infection detection. In this study, we aim to identify volatile compounds in patients' breath that can aid in diagnosing melioidosis and indicating response to treatment. Breath samples were collected from 17 patients with culture-confirmed melioidosis and eight patients with other febrile illnesses. Longitudinal samples were collected from five of the 17 melioidosis patients over approximately one month of antibiotic treatment. Breath samples were analyzed using comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry. Data analysis involved statistical comparison and machine learning-based feature selection. We identified three breath markers-camphene, 1-butanol, and 3-methylheptyl acetate-that discriminated melioidosis (n= 7) from febrile controls (n= 6) with an area under the receiver operating characteristic curve of 1.00. These three markers correctly classified 11 additional samples from 11 melioidosis patients, with one febrile control misclassified. Separately, we selected four breath markers, three of which were hydrocarbons, that differentiated samples associated with a positiveBpculture from those with a negativeBpculture, with a random forest model developed upon these four markers showing a sensitivity of 98% and specificity of 95%. Moreover, we identified a set of 16 volatile compounds that significantly correlated (correlation coefficient > 0.6) with blood C-reactive protein levels. Lastly, a panel of 144 volatile compounds was identified that corresponded to treatment time, indicating that the breath profile may reflect treatment response or shifts in disease severity. This pilot study reports candidate breath-based markers for diagnosing melioidosis and assessing treatment outcome, supporting further validation in larger studies.