Pyramiding BPH genes in rice maintains resistance against the brown planthopper under climate change.

BACKGROUND: Nilaparvata lugens (brown planthopper; BPH) is a significant rice pest in Asia, causing substantial yield losses. Pyramiding BPH resistance genes with diverse resistance traits into rice cultivars is an effective strategy for pest management. However, the response of pyramiding combinations to environmental changes remains unclear. To address this knowledge gap, we investigated three pyramiding rice lines (BPH2 + 32, BPH9 + 32, and BPH18 + 32) in the context of varying climate change conditions, ensuring sufficient N. lugens-rice interactions. Thus, we set three environmental conditions [30/25 °C (day/night) with 500 ppm CO2 concentration, 32/27 °C (day/night) with 600 ppm CO2 concentration, and 35/30 °C (day/night) with 1000 ppm CO2 concentration]. RESULTS: All three pyramiding rice lines maintained the insect resistant ability under the three environmental settings. In particular, the BPH18 + 32 rice line exhibited stronger antibiotic and antixenosis effects against N. lugens. In addition, BPH18 + 32 rice line had better shoot resilience under N. lugens infestation, whereas the performance of the other two selected pyramiding rice lines varied. Thus, although BPH2, BPH9, and BPH18 represent three alleles at the same locus, their resistance levels against N. lugens may vary under distinct climate change scenarios, as evidenced by the performance of N. lugens on the three pyramiding rice lines. CONCLUSION: Our findings indicate that all three tested pyramiding rice lines maintained their insect resistance in the face of diverse climate change scenarios. However, these lines exhibited varied repellent responses and resilience capacities in response to climate change. Thus, the combination of pyramiding genes needs to be considered for future breeding programs. © 2023 Society of Chemical Industry.

[Bioinformatics Analysis of Hub Genes of Diabetic Foot Ulcer and Their Biofunctions].

Objective: To explore the hub genes associated with the pathogenesis and healing of diabetic foot ulcer (DFU) and their biological functions through bioinformatics analysis of transcriptome sequencing data. Methods: The transcriptome sequencing datasets of DFU were selected from Gene Expression Omnibus (GEO) database, and the data were regrouped and normalized for bioinformatics analysis. The skin transcriptome sequencing datasets of DFU patients were compared with those of normal controls and the transcriptome sequencing datasets of skin from ulcerous wound edge of DFU patients were compared with those of non-ulcerous skin of DFU patients so that differentially expressed genes were identified, pathway enrichment and protein-to-protein interaction (PPI) analyses were performed, hub genes were found through nodal analysis, and receiver operating characteristic (ROC) curve was applied to a testing dataset to validate the diagnostic efficiency of the hub genes related to DFU. The intersecting genes from the two sets of analyses were again subjected to pathway enrichment and PPI analyses to screen for hub genes associated with DFU wound healing. What's more, gene set enrichment analysis (GSEA) was carried out on relevant samples to probe for the possible functions and pathway of non-significant genes in DFU. Results: A total of 620 up-regulated differentially expressed genes and 196 down-regulated differentially expressed genes were identified in the training dataset which compared DFU patients with non-diabetic patients. The functions of these genes were enriched in the metabolism of terpenoids and polyketides, signaling molecules and interaction, phospholipase D signaling pathway, propanoate metabolism, PI3K-Akt signaling pathway, Toll-like receptor signaling pathway, pyrimidine metabolism, IL-17 signaling pathway, Rap1 signaling pathway, etc. A total of 10 hub genes were identified with the PPI network. Among them, BGN's value of the area under the curve of ROC analysis was 0.714 and CCND1's was 0.712. In the sequencing analysis of ulcerous wound edge of DFU patients and non-ulcerous skin of DFU patients, 4072 up-regulated genes and 911 down-regulated genes were identified, of which, 372 genes were also detected in the differentially expressed genes of DFU. The functions of these differentially expressed genes were enriched in phospholipase D signaling pathway, xenobiotics biodegradation and energy metabolism, glutathione metabolism, pyrimidine metabolism, ErbB signaling pathway, melanin production, etc. A total of 7 hub genes were identified from PPI network. In GSEA analysis, pathways including pentose and glucuronate interconversions and homologous recombination, nicotinate and nicotinamide metabolism, neuroactive ligand receptor interaction, maturity-onset diabetes of the young, butanoate metabolism, lysine degradation, pantothenate and coenzyme A biosynthesis, riboflavin metabolism, steroid hormone biosynthesis, and valine, leucine and isoleucine degradation showed significant expression differences between DFU patients and normal controls. Conclusion: Bioinformatics analysis results suggest that BGN and CCND1 are potential biomarkers for predicting DFU; CXCL12, TLR4, JAK2, PPARA, UBC, DCN, KDR, and ARNTL are the hub genes of DFU, while CXCL8, CXCL12, TXN, SLIT3, KRT14, KIT, and NEO1 are the hub genes related to wound healing of DFU.

Asprosin in the Paraventricular Nucleus Induces Sympathetic Activation and Pressor Responses via cAMP-Dependent ROS Production.

Asprosin is a newly discovered adipokine that is involved in regulating metabolism. Sympathetic overactivity contributes to the pathogenesis of several cardiovascular diseases. The paraventricular nucleus (PVN) of the hypothalamus plays a crucial role in the regulation of sympathetic outflow and blood pressure. This study was designed to determine the roles and underlying mechanisms of asprosin in the PVN in regulating sympathetic outflow and blood pressure. Experiments were carried out in male adult SD rats under anesthesia. Renal sympathetic nerve activity (RSNA), mean arterial pressure (MAP), and heart rate (HR) were recorded, and PVN microinjections were performed bilaterally. Asprosin mRNA and protein expressions were high in the PVN. The high asprosin expression in the PVN was involved in both the parvocellular and magnocellular regions according to immunohistochemical analysis. Microinjection of asprosin into the PVN produced dose-related increases in RSNA, MAP, and HR, which were abolished by superoxide scavenger tempol, antioxidant N-acetylcysteine (NAC), and NADPH oxidase inhibitor apocynin. The asprosin promoted superoxide production and increased NADPH oxidase activity in the PVN. Furthermore, it increased the cAMP level, adenylyl cyclase (AC) activity, and protein kinase A (PKA) activity in the PVN. The roles of asprosin in increasing RSNA, MAP, and HR were prevented by pretreatment with AC inhibitor SQ22536 or PKA inhibitor H89 in the PVN. Microinjection of cAMP analog db-cAMP into the PVN played similar roles with asprosin in increasing the RSNA, MAP, and HR, but failed to further augment the effects of asprosin. Pretreatment with PVN microinjection of SQ22536 or H89 abolished the roles of asprosin in increasing superoxide production and NADPH oxidase activity in the PVN. These results indicated that asprosin in the PVN increased the sympathetic outflow, blood pressure, and heart rate via cAMP-PKA signaling-mediated NADPH oxidase activation and the subsequent superoxide production.