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BACKGROUND: Rice dwarf virus (RDV)‐induced rice plant volatiles (E)‐β‐caryophyllene and 2‐heptanol modulate the olfactory behavior of RDV insect vectors that promote viral acquisition and transmission. However, it remains elusive whether these two volatiles could influence the behaviors of the natural enemies of RDV insect vectors. Herein, we determined the effects of these two volatiles on the olfactory and predatory behaviors of Cyrtorhinus lividipennis (Hemiptera: Miridae), an important predator of RDV insect vectors in rice paddies. RESULTS: The results showed that C. lividipennis preferred RDV‐infected rice plant odors over RDV‐free rice plant odors. C. lividipennis was attracted by (E)‐β‐caryophyllene, but showed no behavioral responses to 2‐heptanol. The attraction of (E)‐β‐caryophyllene towards C. lividipennis was further confirmed using oscas1 rice plants, which do not release (E)‐β‐caryophyllene in response to RDV infection, through a series of complementary assays. The oviposition preference of the RDV vector insect Nephotettix cincticeps (Hemiptera: Cicadellidae) showed no significant difference between RDV‐infected and RDV‐free wild‐type plants, nor between oscas1‐RDV and oscas1 plants. However, the predation rate of C. lividipennis for N. cincticeps eggs on RDV‐infected plants was higher than that on RDV‐free plants, whereas there was no significant difference between oscas1‐RDV and oscas1 plants. CONCLUSION: (E)‐β‐caryophyllene induced by RDV attracted more C. lividipennis to prey on N. cincticeps eggs and played a crucial role in plant–virus–vector–enemy interactions. These novel findings will promote the design of new strategies for disease control by controlling the populations of insect vectors, for example recruiting more natural enemies by virus‐induced plant volatiles. © 2023 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

The rapid rise of antibiotic resistance and slow discovery of new antibiotics have threatened global health. While novel phage lysins have emerged as potential antibacterial agents, experimental screening methods for novel lysins pose significant challenges due to the enormous workload. Here, the first unified software package, namely DeepLysin, is developed to employ artificial intelligence for mining the vast genome reservoirs ("dark matter") for novel antibacterial phage lysins. Putative lysins are computationally screened from uncharacterized Staphylococcus aureus phages and 17 novel lysins are randomly selected for experimental validation. Seven candidates exhibit excellent in vitro antibacterial activity, with LLysSA9 exceeding that of the best-in-class alternative. The efficacy of LLysSA9 is further demonstrated in mouse bloodstream and wound infection models. Therefore, this study demonstrates the potential of integrating computational and experimental approaches to expedite the discovery of new antibacterial proteins for combating increasing antimicrobial resistance., (© 2024 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)

Large-scale and cost-less production of double-stranded RNA (dsRNA) is the basis for the widespread application of dsRNA in agriculture. Bidirectional transcription of target sequence in RNase III-deficient Escherichia coli strain HT115 (DE3) is an efficient way to produce large amounts of dsRNA. Here, we present a detailed method for the production of dsRNA by bidirectional transcription in E. coli from vector construction, induction of expression by isopropylthio-β-galactoside (IPTG), and purification of dsRNA from E. coli., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)