Schilman, P. E. | Search bioRxiv

bioRxiv2026

Automated analysis of feeding dynamics from electromyographic recordings in a blood-sucking insect

Feeding behavior in blood-sucking insects relies on gustatory evaluation to decide on sustained ingestion, yet quantifying this process from electromyogram (EMG) recordings is labor-intensive. Here we developed MyoRec, an automated computational framework employing machine learning to analyse EMG signals from the triatomine bug Rhodnius prolixus. Using recordings under appetitive and aversive conditions, a convolutional neural network detected ingestion events with 97.7% accuracy. Automated analysis revealed distinct feeding dynamics, with prolonged ingestion and higher pumping frequency under appetitive stimuli, compared to rapid feeding cessation under aversive stimuli. MyoRec substantially reduces analysis time while maintaining accuracy, providing a scalable tool to investigate how gustatory cues modulate feeding decisions in hematophagous insects.

zoology↗

bioRxiv2023

Challenging popular belief, mosquito larvae breathe underwater

It is taken for granted that immature mosquito only breathe atmospheric air through their siphons. However, there is no quantitative study that demonstrated it. We analysed the survival of the last instar larvae of Aedes aegypti fully submerged at different temperatures, and measured oxygen consumption from air and dissolved in water, of larvae and pupae of this species under different conditions. Results revealed that under water, larvae survived much longer than expected, reaching 50% mortality only after 58, 10, and 5 days at 15{degrees}, 25{degrees} and 35{degrees}C, respectively. Interestingly, whereas we registered moults to pupae in larvae with access to air, individuals kept submerged never moulted. When remaining at the water surface, larvae obtained 12.72% of O2 from the water, while pupae only 5.32%. When completely submerged, larvae consumed less oxygen than in contact with the surface, but enough for surviving, while pupae did not. At both media, temperature affected larvae respiration rate, with relatively close Q10 values. In the related species, Ae. albopictus, a similar pattern of O2 consumption were observed. Larvae got 12.14% of their oxygen from the water. Interestingly, no significant differences in total O2 consumption were found between water O2 consumption, when Ae. albopictus larvae were submerged, or when they also have access to air (dual O2 consumption). Our findings not only challenge the classical idea that mosquito larvae only breathe atmospheric O2, but also force us to reconsider the potential effectiveness of control methods based on asphyxiating larvae by detaching from water surface. Summary statementWe present the first quantitative analysis of mosquito larvae respiration in air and water, unravelling the unknown capacity of larvae of the most cosmopolitan disease vector of breathing underwater.

zoology↗

bioRxiv2020

Machine-learning model led design to experimentally test species thermal limits: the case of kissing bugs (Triatominae)

Species Distribution Modelling (SDM) determines habitat suitability of a species across geographic areas using macro-climatic variables; however, micro-habitats can buffer or exacerbate the influence of macro-climatic variables, requiring links between physiology and species persistence. Experimental approaches linking species physiology to micro-climate are complex, time consuming and expensive. E.g., what combination of exposure time and temperature is important for a species thermal tolerance is difficult to judge a priori. We tackled this problem using an active learning approach that utilized machine learning methods to guide thermal tolerance experimental design for three kissing-bug species (Hemiptera: Reduviidae: Triatominae), vectors of the parasite causing Chagas disease. As with other pathogen vectors, triatomines are well known to utilize micro-habitats and the associated shift in microclimate to enhance survival. Using a limited literature-collected dataset, our approach showed that temperature followed by exposure time were the strongest predictors of mortality; species played a minor role, and life stage was the least important. Further, we identified complex but biologically plausible nonlinear interactions between temperature and exposure time in shaping mortality, together setting the potential thermal limits of triatomines. The results from this data led to the design of new experiments with laboratory results that produced novel insights of the effects of temperature and exposure for the triatomines. These results, in turn, can be used to better model micro-climatic envelope for the species. Here we demonstrate the power of an active learning approach to explore experimental space to design laboratory studies testing species thermal limits. Our analytical pipeline can be easily adapted to other systems and we provide code to allow practitioners to perform similar analyses. Not only does our approach have the potential to save time and money: it can also increase our understanding of the links between species physiology and climate, a topic of increasing ecological importance. Author summarySpecies Distribution Modelling determines habitat suitability of a species across geographic areas using macro-climatic variables; however, micro-habitats can buffer or exacerbate the influence of macro-climatic variables, requiring links between physiology and species persistence. We tackled the problem of the combination of exposure time and temperature (a combination difficult to judge a priori) in determining species thermal tolerance, using an active learning approach that utilized machine learning methods to guide thermal tolerance experimental design for three kissing-bug species, vectors of the parasite causing Chagas disease. These bugs are found in micro-habitats with associated shifts in microclimate to enhance survival. Using a limited literature-collected dataset, we showed that temperature followed by exposure time were the strongest predictors of mortality, that species played a minor role, that life stage was the least important, and a complex nonlinear interaction between temperature and exposure time in shaping mortality of kissing bugs. These results led to the design of new laboratory experiments to assess the effects of temperature and exposure for the triatomines. These results can be used to better model micro-climatic envelope for species. Our active learning approach to explore experimental space to design laboratory studies can also be applied to other environmental conditions or species.

physiology↗