A Link between Atmospheric Pressure and Fertility of Drosophila Laboratory Strains

Standardization of conditions under which insects are kept is of great importance when studying their physiology and researchers do their best to maintain it. Nevertheless, sometimes an obvious side effect of some unaccounted factor affecting insects’ reproduction can be revealed even under thoroughly controlled laboratory conditions. We faced such a phenomenon when studying the fertility level in two wild type Drosophila melanogaster strains. For fertility analysis, 50 newly emerged females and 50 males of each strain under study were transferred to fresh medium daily within 10 days. We found out that fertility of both strains was stable on days 2–10 after the oviposition onset in one experiment, while in another one it was significantly decreased during days 5–10. When compared to publicly available meteorological data, these changes in the fertility level demonstrated a strong association with one weather factor: barometric pressure. Thus, we conclude that changes in atmospheric pressure can be considered a factor affecting insects reproduction and discuss a possible mechanism of their influence on fertility

Various Wolbachia genotypes differently influence host Drosophila dopamine metabolism and survival under heat stress conditions

Abstract Background One of the most widespread prokaryotic symbionts of invertebrates is the intracellular bacteria of Wolbachia genus which can be found in about 50% of insect species. Wolbachia causes both parasitic and mutualistic effects on its host that include manipulating the host reproductive systems in order to increase their transmission through the female germline, and increasing the host fitness. One of the mechanisms, promoting adaptation in biological organisms, is a non-specific neuroendocrine stress reaction. In insects, this reaction includes catecholamines, dopamine, serotonin and octopamine, which act as neurotransmitters, neuromodulators and neurohormones. The level of dopamine metabolism correlates with heat stress resistance in Drosophila adults. Results To examine Wolbachia effect on Drosophila survival under heat stress and dopamine metabolism we used five strains carrying the nuclear background of interbred Bi90 strain and cytoplasmic backgrounds with different genotype variants of Wolbachia (produced by 20 backcrosses of Bi90 males with appropriate source of Wolbachia). Non-infected Bi90 strain (treated with tetracycline for 3 generations) was used as a control group. We demonstrated that two of five investigated Wolbachia variants promote changes in Drosophila heat stress resistance and activity of enzymes that produce and degrade dopamine, alkaline phosphatase and dopamine-dependent arylalkylamine N-acetyltransferase. What is especially interesting, wMelCS genotype of Wolbachia increases stress resistance and the intensity of dopamine metabolism, whereas wMelPop strain decreases them. wMel, wMel2 and wMel4 genotypes of Wolbachia do not show any effect on the survival under heat stress or dopamine metabolism. L-DOPA treatment, known to increase the dopamine content in Drosophila, levels the difference in survival under heat stress between all studied groups. Conclusions The genotype of symbiont determines the effect that the symbiont has on the stress resistance of the host insect

The impact of FOXO on dopamine and octopamine metabolism in Drosophila under normal and heat stress conditions

The forkhead boxO transcription factor (FOXO) is a component of the insulin signalling pathway and plays a role in responding to adverse conditions, such as oxidative stress and starvation. In stressful conditions, FOXO moves from the cytosol to the nucleus where it activates gene expression programmes. Here, we show that FOXO in Drosophila melanogaster responds to heat stress as it does to other stressors. The catecholamine signalling pathway is another component of the stress response. In Drosophila, dopamine and octopamine levels rise steeply under heat, nutrition and mechanical stresses, which are followed by a decrease in the activity of synthesis enzymes. We demonstrate that the nearly twofold decline of FOXO expression in foxoBG01018 mutants results in dramatic changes in the metabolism of dopamine and octopamine and the overall response to stress. The absence of FOXO increases tyrosine decarboxylase activity, the first enzyme in octopamine synthesis, and decreases the enzymatic activity of enzymes in dopamine synthesis, alkaline phosphatase and tyrosine hydroxylase, in young Drosophila females. We identified the juvenile hormone as a mediator of FOXO regulation of catecholamine metabolism. Our findings suggest that FOXO is a possible trigger for endocrinological stress reactions

Classification of Fruit Flies by Gender in Images Using Smartphones and the YOLOv4-Tiny Neural Network

The fruit fly Drosophila melanogaster is a classic research object in genetics and systems biology. In the genetic analysis of flies, a routine task is to determine the offspring size and gender ratio in their populations. Currently, these estimates are made manually, which is a very time-consuming process. The counting and gender determination of flies can be automated by using image analysis with deep learning neural networks on mobile devices. We proposed an algorithm based on the YOLOv4-tiny network to identify Drosophila flies and determine their gender based on the protocol of taking pictures of insects on a white sheet of paper with a cell phone camera. Three strategies with different types of augmentation were used to train the network. The best performance (F1 = 0.838) was achieved using synthetic images with mosaic generation. Females gender determination is worse than that one of males. Among the factors that most strongly influencing the accuracy of fly gender recognition, the fly’s position on the paper was the most important. Increased light intensity and higher quality of the device cameras have a positive effect on the recognition accuracy. We implement our method in the FlyCounter Android app for mobile devices, which performs all the image processing steps using the device processors only. The time that the YOLOv4-tiny algorithm takes to process one image is less than 4 s

Classification of Fruit Flies by Gender in Images Using Smartphones and the YOLOv4-Tiny Neural Network

The fruit fly Drosophila melanogaster is a classic research object in genetics and systems biology. In the genetic analysis of flies, a routine task is to determine the offspring size and gender ratio in their populations. Currently, these estimates are made manually, which is a very time-consuming process. The counting and gender determination of flies can be automated by using image analysis with deep learning neural networks on mobile devices. We proposed an algorithm based on the YOLOv4-tiny network to identify Drosophila flies and determine their gender based on the protocol of taking pictures of insects on a white sheet of paper with a cell phone camera. Three strategies with different types of augmentation were used to train the network. The best performance (F1 = 0.838) was achieved using synthetic images with mosaic generation. Females gender determination is worse than that one of males. Among the factors that most strongly influencing the accuracy of fly gender recognition, the fly’s position on the paper was the most important. Increased light intensity and higher quality of the device cameras have a positive effect on the recognition accuracy. We implement our method in the FlyCounter Android app for mobile devices, which performs all the image processing steps using the device processors only. The time that the YOLOv4-tiny algorithm takes to process one image is less than 4 s