For insects that aggregate on host plants, both attraction and antiaggregation among conspecifics can be important mechanisms for overcoming host resistance and avoiding overcrowding, respectively. These mechanisms can involve multiple sensory modalities, such as sound and pheromones. We explored how acoustic and chemical signals are integrated by the bark beetle Dendroctonus valens to limit aggregation in China. In its native North American range, this insect conducts nonlethal attacks on weakened trees at very low densities, but in its introduced zone in China, it uses mixtures of host tree compounds and the pheromone component frontalin to mass attack healthy trees. We found that exo-brevicomin was produced by both female and male D. valens, and that this pheromone functioned as an antiaggregating signal. Moreover, beetles feeding in pairs or in masses were more likely than were beetles feeding alone to produce exo-brevicomin, suggesting a potential role of sound by neighboring beetles in stimulating exo-brevicomin production. Sound playback showed that an agreement sound was produced by both sexes when exposed to the aggregation pheromone frontalin and attracts males, and an aggressive sound was produced only by males behaving territorially. These signals triggered the release of exo-brevicomin by both females and males, indicating an interplay of chemical and sonic communication. This study demonstrates that the bark beetle D. valens uses sounds to regulate the production of an antiaggregation pheromone, which may provide new approaches to pest management of this invasive species.

Summer diapause in Helicoverpa assulta (Hübner), which prolongs the pupal stage, particularly in males, is induced by high temperatures. In the laboratory, 3rd-, 4th-, 6th-instar and prepupal larvae were exposed to high temperatures – 33 and 35 °C with a photoperiod of LD16:8 – until pupation to induce summer diapause. The results showed that the incidence of summer diapause was influenced by temperature, stage exposed, and sex. The higher the temperature, the more often summer diapause was attained. Sixth-instar and prepupal larvae were the sensitive stages for summer diapause induction. H. assulta summer-diapausing pupae needed diapause development to resume development when temperatures became favorable. Furthermore, both body mass and energy storage capacity (lipid and glycogen) were significantly affected by diapause rather than sex, and were significantly higher in summer-diapausing pupae than in non-diapausing pupae. In addition, the body mass loss and respiration rate showed that the rate of metabolism in the summer-diapausing pupae was consistently lower than in non-diapausing pupae, which were significantly affected by diapause and pupal age. We conclude that summer diapause in H. assulta is a true diapause, and H. assulta has evolved mechanisms to accumulate energy storage and to lower its metabolism to adapt to hot summers.

Sugar transporters (STs), which mainly mediate cellular sugar exchanges, play critical physiological roles in living organisms, and they may be responsible for sugar exchanges among various insect tissues. However, the molecular and physiological functions of insect STs are largely unknown. Here, 16 STs of Helicoverpa armigera were identified. A phylogenetic analysis classified the putative HaSTs into 12 sub-families, and those identified in this study were distributed into 6 sub-families. Real-time polymerase chain reaction indicated that the 16 HaSTs had diverse tissue-specific expression levels. One transporter, HaST10, was highly expressed in thoracic muscles. A functional study using a Xenopus oocyte expression system revealed that HaST10 mediated both H + -driven trehalose and Na + -driven glucose antiport activities with high transport efficiency and low affinity levels. A HaST10 knockout clearly impaired the performance of H. armigera. Thus, HaST10 may participate in sugar-supply regulation and have essential physiological roles in H. armigera.

Tumor cells can result from gene mutations and over-expression. Synthetic lethality (SL) offers a desirable setting where cancer cells bearing one mutated gene of an SL gene pair can be specifically targeted by disrupting the function of the other genes, while leaving wide-type normal cells unharmed. Paralogs, a set of homologous genes that have diverged from each other as a consequence of gene duplication, make the concept of SL feasible as the loss of one gene does not affect the cell’s survival. Furthermore, homozygous loss of paralogs in tumor cells is more frequent than singletons, making them ideal SL targets. Although high-throughput CRISPR-Cas9 screenings have uncovered numerous paralog-based SL pairs, the unclear mechanisms of targeting these gene pairs and the difficulty in finding specific inhibitors that exclusively target a single but not both paralogs hinder further clinical development. Here, we review the potential mechanisms of paralog-based SL given their function and genetic combination, and discuss the challenge and application prospects of paralog-based SL in cancer therapeutic discovery.

Synthetic lethal (SL) pairs are pairs of genes whose simultaneous loss-of-function results in cell death, while a damaging mutation of either gene alone does not affect the cell’s survival. This makes SL pairs attractive targets for precision cancer therapies, as targeting the unimpaired gene of the SL pair can selectively kill cancer cells that already harbor the impaired gene. Limited by the difficulty of finding true SL pairs, especially on specific cell types, the identification of SL targets still relies on expensive, time-consuming experimental approaches. In this work, we utilized various cell-line specific omics data to design a deep learning model for predicting SL pairs on particular cell-lines. By incorporating multiple types of cell-specific omics data with a self-attention module, we represent gene relationships as graphs. Our approach demonstrates the potential to facilitate the discovery of cell-specific SL targets for cancer therapeutics, providing a tool to unearth mechanisms underlying the origin of SL in cancer biology. Our approach allows for prediction of SL pairs in a cell-specific manner and enhances cancer precision medicine. The code and data of our approach can be found athttps://github.com/promethiume/SLwiseHighlightsFew computational methods can systematically predict SL pairs at a cell-specific level, and their performance may not generalize well to clinical scenarios due to the heterogeneity of cancer types.The SLWise utilizes various cell-line specific omics data to design a deep learning model with a graph-based representation and self-attention mechanism.This approach allows for the prediction of SL pairs in a cell-specific manner, providing valuable insights on effectively identifying the cell-type specific SL targets for personalized treatment strategies.

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