DMR040, a potential antifungal compound
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Soil bacterium manipulates antifungal weapons by sensing intracellular type IVA secretion system effectors of a competitor
Soil beneficial bacteria can effectively inhibit bacterial pathogens by assembling contact-dependent killing weapons, such as the type IVA secretion system (T4ASS). It’s not clear whether these antibacterial weapons are involved in biotrophic microbial interactions in soil. Here we showed that an antifungal antibiotic 2,4-DAPG production of the soil bacterium, Pseudomonas protegens can be triggered by another soil bacterium, Lysobacter enzymogenes, via T4ASS by co-culturing on agar plates to mimic cell-to-cell contact. We demonstrated that the induced 2,4-DAPG production of P. protegens is achieved by intracellular detection of the T4ASS effector protein Le1519 translocated from L. enzymogenes. We defined Le1519 as LtaE (Lysobacter T4E triggering antifungal effects), which specifically stimulates the expression of 2,4-DAPG biosynthesis genes in P. protegens, thereby protecting soybean seedlings from infection by the fungus Rhizoctonia solani. We further found that LtaE directly bound to PhlF, a pathway-specific transcriptional repressor of the 2,4-DAPG biosynthesis, then activated the 2,4-DAPG production. Our results highlight a novel pattern of microbial interspecies and interkingdom interactions, providing a unique case for expanding the diversity of soil microbial interactions.
Immunosurveillance of Candida albicans commensalism by the adaptive immune system
The fungal microbiota (mycobiota) is an integral part of the microbial community colonizing the body surfaces and is involved in many key aspects of human physiology, while an imbalance of the fungal communities, termed fungal dysbiosis, has been described in pathologies ranging from infections to inflammatory bowel disease. Commensal organisms, such as the fungus Candida albicans, induce antigen-specific immune responses that maintain immune homeostasis. Adaptive immune mechanisms are vital in this process, while deficiencies in adaptive immunity are linked to fungal infections. We start to understand the mechanisms by which a shift in mycobiota composition, in particular in C. albicans abundance, is linked to immunopathological conditions. This review discusses the mechanisms that ensure continuous immunosurveillance of C. albicans during mucosal colonization, how these protective adaptive immune responses can also promote immunopathology, and highlight therapeutic advances against C. albicans-associated disease.
Mechanisms of electrochemical hydrogenation of aromatic compound mixtures over a bimetallic PtRu catalyst
Efficient electrochemical hydrogenation (ECH) of organic compounds is essential for sustainability, promoting chemical feedstock circularity and synthetic fuel production. This study investigates the ECH of benzoic acid, phenol, guaiacol, and their mixtures, key components in upgradeable oils, using a carbon-supported PtRu catalyst under varying initial concentrations, temperatures, and current densities. Phenol achieved the highest conversion (83.17%) with a 60% Faradaic efficiency (FE). In mixtures, benzoic acid + phenol yielded the best performance (64.19% conversion, 74% FE), indicating a synergistic effect. Notably, BA consistently exhibited 100% selectivity for cyclohexane carboxylic acid (CCA) across all conditions. Density functional theory (DFT) calculations revealed that parallel adsorption of BA on the cathode (−1.12 eV) is more stable than perpendicular positioning (-0.58 eV), explaining the high selectivity for CCA. These findings provide a foundation for future developments in ECH of real pyrolysis oil.
Molecular optimization using a conditional transformer for reaction-aware compound exploration with reinforcement learning
Designing molecules with desirable properties is a critical endeavor in drug discovery. Because of recent advances in deep learning, molecular generative models have been developed. However, the existing compound exploration models often disregard the important issue of ensuring the feasibility of organic synthesis. To address this issue, we propose TRACER, which is a framework that integrates the optimization of molecular property optimization with synthetic pathway generation. The model can predict the product derived from a given reactant via a conditional transformer under the constraints of a reaction type. The molecular optimization results of an activity prediction model targeting DRD2, AKT1, and CXCR4 revealed that TRACER effectively generated compounds with high scores. The transformer model, which recognizes the entire structures, captures the complexity of the organic synthesis and enables its navigation in a vast chemical space while considering real-world reactivity constraints.
Chemogenomics for steroid hormone receptors (NR3)
The nine human NR3 nuclear receptors translate steroid hormone signals in transcriptomic responses and operate multiple highly important processes ranging from development over reproductive tissue function to inflammatory and metabolic homeostasis. Although several NR3 ligands such as glucocorticoids are invaluable drugs, this family is only partially explored, for example, in autoimmune diseases and neurodegeneration, but may hold therapeutic potential in new areas. Here we report a chemogenomics (CG) library to reveal elusive effects of NR3 receptor modulation in phenotypic settings. 34 highly annotated and chemically diverse ligands covering all NR3 receptors were selected considering complementary modes of action and activity, selectivity and lack of toxicity. Endoplasmic reticulum stress resolving effects of N3 CG subsets in proof-of-concept application validate suitability of the set to connect phenotypic outcomes with targets and to explore NR3 receptors from a translational perspective.
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