Sensor array detection of malaria volatile signature in a murine model

Abstract The relationship between malaria infection and volatile compounds has been claimed mainly on the basis that they are believed to be an attractant for mosquitoes. However, since the association of emitted molecules with diseases has been observed for many pathologies, malaria-related volatile compounds are a potential diagnostic tool. The recent confirms of this hypothesis prompts the development of sensors for an effective exploitation of these potentialities. 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.