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ABSTRACT The detection of soil-borne pathogens by quantitative PCR (qPCR) has been challenging due to the pronounced influence of soil type on DNA extraction and PCR reactions. In the present study, we developed a novel qPCR system and an internal sample process control (ISPC) strain, RsPC, for the detection of Ralstonia solanacearum species complex (RSSC), the pathogens causing bacterial wilt. Specific primers and TaqMan probe were designed based on analyses of 16S rRNA gene sequences from 581 Ralstonia genomes, and the RsPC was constructed by insertion of an artificial fragment, which consisted of two fragments from the kanamycin-resistant gene and the gfp gene, into the chromosome of a phylogenetically closely related strain, Ralstonia pickettii JCM 5969. The qPCR target sequences of RSSC and RsPC shared primers; however, different TaqMan probes were used to distinguish them from each other. The interaction assay between ISPC and target DNA showed no influence on sensitivity when their difference in concentration was

The abradable coating is one of the most important coatings for improving the efficiency of aeroengine. To improve the durability of Sc2O3-Y2O3-ZrO2-CaF2-PHB abradable coating under the conditions of high temperature thermal shock, the femtosecond laser processing technology is proposed to fabricate the texture on the surface of SiCf/SiC composites to improve the coating/matrix contact area. The environmental barrier coating (EBC) was prepared by vacuum plasma spraying (VPS) equipment on SiCf/SiC ceramic matrix composites to avoid water-oxygen corrosion. And the abradable coating was prepared by air plasma spraying (APS) equipment on the EBC. The thermal shock test of the abradable coating at (1,250 ± 50)°C was established in the simulated gas environment of the oxygen-propane flame, and the variation of interface stress between the layers during the thermal shock test was analyzed by ANSYS software. The hidden crack between the layers was detected by an infrared thermal imager. The results show that the surface textures have significant influences on the anti-thermal-shock properties of Sc2O3-Y2O3-ZrO2-CaF2-PHB abradable coating by improving the contact area and optimizing the interface stress distribution. The bonding strengths of the coating are increased by 14.6% and 42.2% when the surface textures increase the contact area of the substrate and the coating by 41.3% and 104%, respectively. Compared with the coatings without texture treatments, the coatings with texture treatments can reduce coating thickness by 30% and the coatings do not peel off after the thermal shock tests. Influenced by the cyclic thermal stress, the cracks of abradable coating are initiated at the defect position and gradually propagated a shell-like shape. The textures on the surface of SiCf/SiC composites have deep influences on improving the high-temperature thermal shock life of Sc2O3-Y2O3-ZrO2-CaF2-PHB abradable coating.

Motivation Identifying cancer genes remains a significant challenge in cancer genomics research. Annotated gene sets encode functional associations among multiple genes, and cancer genes have been shown to cluster in hallmark signaling pathways and biological processes. The knowledge of annotated gene sets is critical for discovering cancer genes but remains to be fully exploited. Results Here, we present the DIsease-Specific Hypergraph neural network (DISHyper), a hypergraph-based computational method that integrates the knowledge from multiple types of annotated gene sets to predict cancer genes. First, our benchmark results demonstrate that DISHyper outperforms the existing state-of-the-art methods and highlight the advantages of employing hypergraphs for representing annotated gene sets. Second, we validate the accuracy of DISHyper-predicted cancer genes using functional validation results and multiple independent functional genomics data. Third, our model predicts 44 novel cancer genes, and subsequent analysis shows their significant associations with multiple types of cancers. Overall, our study provides a new perspective for discovering cancer genes and reveals previously undiscovered cancer genes. Availability and implementation DISHyper is freely available for download at https://github.com/genemine/DISHyper. [ABSTRACT FROM AUTHOR]

Bacillus subtilis strain NCD-2 is an excellent biocontrol agent for plant soil-borne diseases, and the lipopeptide fengycin is one of the active antifungal compounds in strain NCD-2. The regulator PhoP and its sensor kinase PhoR compose a two-component system in B. subtilis. In this study, the phoR- and phoP-knockout mutants were constructed by in-frame deletion and the role of PhoR/PhoP on the production of fengycin was determined. Inactivation of phoR or phoP in B. subtilis decreased its inhibition ability against Botrytis cinerea growth in vitro compared to the strain NCD-2 wild type. The lipopeptides were extracted from strain NCD-2 wild type and its mutant strains by hydrochloric acid precipitate, and the lipopeptides from phoR-null mutant or phoP-null mutant almost lost the inhibition ability against B. cinerea growth compared to the lipopeptides from strain NCD-2 wild type. Fast protein liquid chromatography (FPLC) analysis of the lipopeptides showed that inactivation of phoR or phoP genes reduced the production of fengycin by strain NCD-2. The fengycin production abilities were compared for bacteria under low-phosphate medium (LPM) and high-phosphate medium (HPM), respectively. Results indicated that the regulation of fengycin production by the PhoR/PhoP two-component system occurred in LPM but not in HPM. Reverse transcriptional-PCR confirmed that the fengycin synthetase gene fenC was positively regulated by phoP when cultured in LPM. All of these characteristics could be partially restored by complementation of intact phoR or phoP gene in the mutant. These data indicated that the PhoR/PhoP two-component system greatly regulated fengycin production and antifungal ability in B. subtilis NCD-2 mainly under low-phosphate conditions.

Alternative splicing (AS) is a key transcriptional regulation pathway. Recent studies have shown that AS events are associated with the occurrence of complex diseases. Various computational approaches have been developed for the detection of disease-associated AS events. In this review, we first describe the metrics used for quantitative characterization of AS events. Second, we review and discuss the three types of methods for detecting disease-associated splicing events, which are differential splicing analysis, aberrant splicing detection and splicing-related network analysis. Third, to further exploit the genetic mechanism of disease-associated AS events, we describe the methods for detecting genetic variants that potentially regulate splicing. For each type of methods, we conducted experimental comparison to illustrate their performance. Finally, we discuss the limitations of these methods and point out potential ways to address them. We anticipate that this review provides a systematic understanding of computational approaches for the analysis of disease-associated splicing. [ABSTRACT FROM AUTHOR]