Sensor array detection of malaria volatile signature in a murine model

On these bases, we investigated the alteration of volatile compounds in a malaria murine model. For the scope, the total “volatilome” of Plasmodium berghei-infected mice was compared with that of non-infected animals. Gas chromatographic analysis of the sampled air reveals the existence of a pattern of compounds that, collectively considered, detects malaria infection. Finally, an array of porphyrins functionalized quartz microbalance gas sensors was applied to sort non-infected from infected mice. The application of a classification model to the sensor data provided more than 80% of correct identification with errors confined to mice with a low parasitemia level. Noteworthy, the sensor array was trained on data collected months before to run the tests. These results provide, although limited to a murine model, a first evidence of the potentialities of gas sensor technology for malaria diagnosis.