The Overexpression of Zea mays Strigolactone Receptor Gene D14 Enhances Drought Resistance in Arabidopsis thaliana L.

Strigolactones (SLs) represent a recently identified class of plant hormones that are crucial for plant tillering and mycorrhizal symbiosis. The D14 gene, an essential receptor within the SLs signaling pathway, has been well-examined in crops, like rice (Oryza sativa L.) and Arabidopsis (Arabidopsis thaliana L.), yet the research on its influence in maize (Zea mays L.) remains scarce. This study successfully clones and establishes Arabidopsis D14 gene overexpression lines (OE lines). When compared with the wild type (WT), the OE lines exhibited significantly longer primary roots during germination. By seven weeks of age, these lines showed reductions in plant height and tillering, alongside slight decreases in rosette and leaf sizes, coupled with early aging symptoms. Fluorescence-based quantitative assays indicated notable hormonal fluctuations in OE lines versus the WT, implying that D14 overexpression disrupts plant hormonal homeostasis. The OE lines, exposed to cold, drought, and sodium chloride stressors during germination, displayed an especially pronounced resistance to drought. The drought resistance of OE lines, as evident from dehydration-rehydration assays, outmatched that of the WT lines. Additionally, under drought conditions, the OE lines accumulated less reactive oxygen species (ROS) as revealed by the assessment of the related physiological and biochemical parameters. Upon confronting the pathogens Pseudomonas syringae pv. tomato DC3000 (Pst DC3000), post-infection, fluorescence quantitative investigations showed a significant boost in the salicylic acid (SA)-related gene expression in OE lines compared to their WT counterparts. Overall, our findings designate the SL receptor D14 as a key upregulator of drought tolerance and a regulator in the biotic stress response, thereby advancing our understanding of the maize SL signaling pathway by elucidating the function of the pivotal D14 gene.

Functional analysis of transgenic cry1Ah-1 maize.

Maize is an important food crop in the world, but the yield and quality of maize have been significantly reduced due to the impact of insect pests. In order to address this issue, the cry1Ah gene was subjected to error-prone PCR for mutagenesis, and subsequently, the mutant cry1Ah-1 gene was introduced into maize inbred line GSH9901 callus using the Agrobacterium-mediated method. The T2 generation transformed plants were obtained by subculture, and 9 transgenic positive plants were obtained by molecular detection which was carried out by PCR, qRT-PCR, Bt gold-labeled immunoassay test strips, Western blot and ELISA. It was found that the Cry1Ah-1 gene could be transcribed normally in maize leaves, of which OE1 and OE3 had higher relative expression levels and could successfully express proteins of 71.94 KD size. They were expressed in different tissues at the 6-leaf stage, heading stage and grain-filling stage, and could ensure the protection of maize from corn borer throughout the growth period. The biological activities of OE1 and OE3 were tested indoors and in the field, and the results showed that in indoors, the corn borer that fed on OE1 and OE3 corn leaves had a mortality rate of 100 % after 3 days; in the field, OE1 and OE3 had strong insecticidal activity against corn borer, reaching a high resistance level. In conclusion, the transgenic cry1Ah-1 maize has a strong insecticidal effect on corn borer, and has a good prospect of commercialization.

Advances and Challenges in De Novo Drug Design Using Three-Dimensional Deep Generative Models.

A persistent goal for de novo drug design is to generate novel chemical compounds with desirable properties in a labor-, time-, and cost-efficient manner. Deep generative models provide alternative routes to this goal. Numerous model architectures and optimization strategies have been explored in recent years, most of which have been developed to generate two-dimensional molecular structures. Some generative models aiming at three-dimensional (3D) molecule generation have also been proposed, gaining attention for their unique advantages and potential to directly design drug-like molecules in a target-conditioning manner. This review highlights current developments in 3D molecular generative models combined with deep learning and discusses future directions for de novo drug design.

SIDERITE: Unveiling hidden siderophore diversity in the chemical space through digital exploration.

In this work, we introduced a siderophore information database (SIDERTE), a digitized siderophore information database containing 649 unique structures. Leveraging this digitalized data set, we gained a systematic overview of siderophores by their clustering patterns in the chemical space. Building upon this, we developed a functional group-based method for predicting new iron-binding molecules with experimental validation. Expanding our approach to the collection of open natural products (COCONUT) database, we predicted a staggering 3199 siderophore candidates, showcasing remarkable structure diversity that is largely unexplored. Our study provides a valuable resource for accelerating the discovery of novel iron-binding molecules and advancing our understanding of siderophores.