An investigation of Dirofilaria immitis infection and its effects on mosquito wingbeat frequencies

Abstract

Each mosquito species has a different wingbeat frequency by which they attract mates. With just a brief recording (<1/10th of a second) these acoustic signatures can be analyzed to quickly determine if mosquitoes belong to a species that is known to transmit different pathogens. A recent study has shown that mobile phones are capable of capturing acoustic data from mosquito wingbeats. We examined wingbeat signatures and flight duration patterns of D. immitis infected and non-infected Aedes aegypti to determine if mobile phone recordings of wingbeat frequencies can be used to distinguish infected mosquitoes from non-infected ones. Female mosquitoes were recorded prior to and at various time points after feeding on infected or non-infected dog blood by placing individual mosquitoes into a collection vial and recording for 60 s using the Voice Memo app for iPhone 7 plus and 8. To uniformly analyze audio data, recordings were processed using a previously described automated algorithm in Python 3.0 to determine wingbeat frequency. A total of 1669 recordings were gathered, and mosquitoes were dissected to confirm the presence and number of D. immitis larvae. Our findings indicate that there was a significant effect on wingbeat frequency with an increasing number of L3 larvae. Specifically, as the number of L3, infective stage larvae increases, a decrease in wingbeat frequency is seen. However, there was no significant effect of increasing number of L1 or L2 larvae causing increasing wingbeat frequencies. The detection of a significant difference in wingbeat frequencies between mosquitoes harboring infective stage D. immitis larvae is unique and suggests the possibility of using wingbeat recordings as a tool for vector species and pathogen surveillance and monitoring.