Phytophthora, a genus of oomycetes, contains many devastating plant pathogens, which cause substantial economic losses worldwide. Recently, CRISPR/Cas9-based genome editing tool was introduced into Phytophthora to delineate the functionality of individual genes. The available selection markers for Phytophthora transformation, however, are limited, which can restrain transgenic manipulation in some cases. We hypothesized that PcMuORP1, an endogenous fungicide resistance gene from P. capsici that confers resistance to the fungicide oxathiapiprolin via an altered target site in the ORP1 protein, could be used as an alternative marker. To test this hypothesis, the gene PcMuORP1 was introduced into the CRISPR/Cas9 system and complementation of a deleted gene in P. capsici was achieved using it as a selection marker. All of the oxathiapiprolin-resistant transformants were confirmed to contain the marker gene, indicating that the positive screening rate was 100%. The novel selection marker could also be used in other representative Phytophthora species including P. sojae and P. litchii, also with 100% positive screening rate. Furthermore, comparative studies indicated that use of PcMuORP1 resulted in a much higher efficiency of screening compared to the conventional selection marker NPT II, especially in P. capsici. Successive subculture and asexual reproduction in the absence of selective pressure were found to result in the loss of the selection marker from the transformants, which indicates that the PcMuORP1 gene would have little long term influence on the fitness of transformants and could be reused as the selection marker in subsequent projects. Thus, we have created an alternative selection marker for Phytophthora transformation by using a fungicide resistance gene, which would accelerate functional studies of genes in these species.
Rice false smut, caused by Ustilaginoidea virens, produces significant losses in rice yield and grain quality and has recently emerged as one of the most important rice diseases worldwide. Despite its importance in rice production, relatively few studies have been conducted to illustrate the complex interactome and the pathogenicity gene interactions. Here a protein-protein interaction network of U. virens was built through two well-recognized approaches, interolog- and domain-domain interaction-based methods. A total of 20 217 interactions associated with 3305 proteins were predicted after strict filtering. The reliability of the network was assessed computationally and experimentally. The topology of the interactome network revealed highly connected proteins. A pathogenicity-related subnetwork involving up-regulated genes during early U. virens infection was also constructed, and many novel pathogenicity proteins were predicted in the subnetwork. In addition, we built an interspecies PPI network between U. virens and Oryza sativa, providing new insights for molecular interactions of this host-pathogen pathosystem. A web-based publicly available interactive database based on these interaction networks has also been released. In summary, a proteome-scale map of the PPI network was described for U. virens, which will provide new perspectives for finely dissecting interactions of genes related to its pathogenicity.
Fungal pathogen Botrytis cinerea, the casual agent of gray mold of vegetables and fruits, has a high risk of developing resistance to fungicide. Tebuconazole, one kind of demethylation inhibitor (DMI) fungicides, has been increasingly applied for the control of tomato gray mold in China. However, very limited information is available on the resistance profile of B. cinerea to tebuconazole. In this study, the baseline sensitivity of B. cinerea to tebuconazole was determined based on 138 isolates from field sites having no history of DMI usage, with a mean EC50 value of 0.29 μg/mL. Another 159 B. cinerea isolates collected in the greenhouse and field from 2011 to 2016 were demonstrated to have a shifted sensitivity to tebuconazole, with a mean EC50 value of 0.66 μg/mL. EC50 values of 10 B. cinerea isolates with reduced sensitivity to tebuconazole were greater than 1.56 μg/mL, and these reduced-sensitive isolates had a fitness penalty in sporulation and conidial germination, but showed similar mycelial growth rate and pathogenicity with those of the sensitive isolates. Positive cross-resistance was observed only between tebuconazole and the other two DMIs difenoconazole and prochloraz, but not between tebuconazole and the non-DMIs iprodione, procymidone, or fludioxonil. In reduced-sensitive isolates, no amino acid variation was found in the BcCYP51 protein. When exposed to tebuconazole, the expression level of BcCYP51 increased in these reduced-sensitive B. cinerea isolates as compared to sensitive ones, thus contributing to the reduced sensitivity of the pathogen to tebuconazole. Additionally, the nucleotide mutation observed in the 1200 bp upstream region of BcCYP51 had no correlation with the development of fungicide resistance in B. cinerea isolates. These findings will be helpful for the understanding of DMI resistance mechnism in B. cinerea.
The collaborative development of complex products has gradually developed into a “main manufacturer-suppliers” mode, under which the manufacturing enterprises form a complex product collaborative manufacturing supply chain network. Quality risks which bring enormous hidden danger to the product quality can be propagated and accumulate along the supply chain. It is of great significance to quantify the propagation mechanism of quality risk between supply chain network nodes and identify the key quality risk factor that causes fluctuation of product quality. This study for the first time applies the SoV into the research on quality risk propagation of complex product collaborative manufacturing supply chain network. Firstly, this paper uses the CN to construct a complex product collaborative manufacturing supply chain network according to its characteristics. Secondly, on the basis of SoV, the quality risk propagation model is established. Thirdly, we put forward a method to identify the key quality risk factors of supply chain network based on the risk propagation effect. Lastly, a numerical simulation is given to verify the effectiveness of the model and its identification method. The results reveal that the quality risk propagation includes the vertical propagation within enterprises and the horizontal propagation from the lower-level enterprises to the upper-level enterprises of the supply chain. The quality risks of an enterprise are determined by its own quality risk factors and the quality risk passed by the lower-level enterprises.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.