Mengcen Wang 교수

The findings indicate that a functional phyllosphere microbiota was assembled along with development-specific metabolites in tea plants, which continuously suppressed prevalent fungal pathogens. The insights gained into the temporally resolved metabolite response of the tea plant microbiota could provide novel solutions for disease management.

Recent studies have shown that various agrochemicals can substantially affect microbial communities; especially those that are associated with cultivated plants. Under certain circumstances, up to 50% of the naturally occurring microorganisms can be negatively affected by common agricultural practices such as seed coating with fungicide-based matrices. Nevertheless, the off-target effects of commonly applied agrochemicals are still understudied in terms of their interferences with microbial comm

Burkholderia heleia PAK1-2 is a potent biocontrol agent isolated from rice rhizosphere, as it prevents bacterial rice seedling blight disease caused by Burkholderia plantarii. Here, we isolated a non-antibacterial metabolite from the culture fluid of B. heleia PAK1-2 that was able to suppress B. plantarii virulence and subsequently identified as indole-3-acetic acid (IAA). IAA suppressed the production of tropolone in B. plantarii in a dose-dependent manner without any antibacterial and quorum q

Rice fungal pathogens, responsible for severe rice yield loss and biotoxin contamination, cause increasing concerns on environmental safety and public health. In the paddy environment, we observed that the asymptomatic rice phyllosphere microenvironment was dominated by an indigenous fungus, <i>Aspergillus cvjetkovicii</i>, which positively correlated with alleviated incidence of <i>Magnaporthe oryzae</i>, one of the most aggressive plant pathogens. Through the comparative metabolic profiling fo

Our study unveils the mechanism underpinning microbiome assembly in the tea plants, and a potential implication of the microbiome-mediated resilience framework on the phyllosphere homeostasis.

To screen biocontrol agents against Burkholderia plantarii, the causative agent of rice seedling blight, we employed catechol, an analog of the virulence factor tropolone, to obtain chemical stress-resistant microorganisms. The fungal isolate PS1-7, identified as a strain of Trichoderma virens, showed the highest resistance to catechol (20 mM) and exhibited efficacy as a biocontrol agent for rice seedling blight. During investigation of metabolic traits of T. virens PS1-7 exposed to catechol, we

Single pathogen-targeted disease management measure has shown drawbacks in field efficacy under the scenario of global change. An in-depth understanding of plant pathogenesis will provide a promising solution but faces the challenges of the emerging paradigm involving the plant microbiome. While the beneficial impact of the plant microbiome is well characterized, their potential role in facilitating pathological processes has so far remained largely overlooked. To address these unsolved controve

Our findings demonstrate that carot-4-en-9,10-diol released by T. virens PS1-7 acts as an interkingdom cell-to-cell signaling molecule against B. plantarii to repress tropolone production and induces pseudo-biofilm to the cells. This observation also led to another discovery that tropolone is an autoregulatory cell-to-cell signaling molecule of B. plantarii that induces a functional biofilm other than a simple B. plantarii virulence factor.

Abstract. Elevated nitrogen (N) deposition affects soil N transformations in the N-rich soil of tropical forests. However, the change in soil functional microorganisms responsible for soil N cycling remains largely unknown. Here, we investigated the variation in soil inorganic N content, net N mineralization (Rm), net nitrification (Rn), inorganic N leaching (Rl), N2O efflux and N-related functional gene abundance in a tropical forest soil over a 2-year period with four levels of N addition. The

The past few years have witnessed significant progress in emerging disease detection techniques for accurately and rapidly tracking rice diseases and predicting potential solutions. In this review we focus on image processing techniques using machine learning (ML) and deep learning (DL) models related to multi-scale rice diseases. Furthermore, we summarize applications of different detection techniques, including genomic, physiological, and biochemical approaches. In addition, we also present th

Bacteria equipped with virulence systems based on highly bioactive small molecules can circumvent their host's defense mechanisms. Pathogens employing this strategy are currently threatening global rice production. In the present study, variations in the virulence of the highly destructive <i>Burkholderia plantarii</i> were observed in different rice-producing regions. The environment-linked variation was not attributable to any known host-related or external factors. Co-occurrence analyses indi