The emergence of azole-resistant fungal pathogens has posed a great threat to public health worldwide. Although the molecular mechanism of azole resistance has been extensively investigated, the potential regulators of azole resistance remain largely unexplored. Here we identified a new function of the fungal specific C₂H₂ zinc finger transcription factor SltA (involved in salt-tolerance pathway) in the regulation of azole resistance of the human fungal pathogen Aspergillus fumigatus. Lack of SltA results in an itraconazole hypersusceptibility phenotype. Transcriptional profiling combined with LacZ reporter analysis and electrophoretic mobility shift assays (EMSA) demonstrate that SltA is involved in its own transcriptional regulation and also regulates the expression of genes related to ergosterol biosynthesis (erg11A, erg13A and erg24A) and drug efflux pumps (mdr1, mfsC and abcE) by directly binding to the conserved 5’-AGGCA-3’ motif in their promoter regions, and this binding is dependent on the conserved cysteine and histidine within the C₂H₂ DNA binding domain of SltA. Moreover, overexpression of erg11A or mdr1 rescues sltA deletion defects under itraconazole conditions, suggesting that erg11A and mdr1 are related to sltA-mediated itraconazole resistance. Most importantly, deletion of SltA in laboratory-derived and clinical azole-resistant isolates significantly attenuates drug resistance. Collectively, we have identified a new function of the transcription factor SltA in regulating azole resistance by coordinately mediating the key azole target Erg11A and the drug efflux pump Mdr1, and targeting SltA may provide a potential strategy for intervention of clinical azole-resistant isolates to improve the efficiency of currently approved antifungal drugs.

Purpose: Herein, an emerging drug delivery system was constructed based on zeolite imidazole backbone (ZIF-8) to improve antibacterial defects of nanosilver (AgNPs), such as easily precipitated and highly cytotoxic. Methods: The homogeneous dispersion of AgNPs on ZIF-8 was confirmed by UV-Vis spectroscopy, FTIR spectroscopy, particle size analysis, zeta potential analysis, and SEM. The appropriate AgNPs loading ratio on ZIF-8 was screened through the cell and antibacterial experiments based on biosafety and antibacterial performance. The optimal environment for AgNPs@ZIF-8 to exert antibacterial performance was probed in the context of bacterial communities under different acid-base conditions. The potential mechanism of AgNPs@ZIF-8 to inhibit the common clinical strains was investigated by observing the biofilm metabolic activity and the level of reactive oxygen species (ROS) in bacteria. Results: The successful piggybacking of AgNPs by ZIF-8 was confirmed using UV-Vis spectroscopy, FTIR spectroscopy, particle size analysis, zeta potential analysis, and SEM characterization methods. Based on the bacterial growth curve (0– 24 hours), the antibacterial ability of AgNPs@ZIF-8 was found to be superior to AgNPs. When the mass ratio of ZIF-8 and AgNPs was 1:0.25, the selection of AgNPs@ZIF-8 was based on its superior antimicrobial efficacy and enhanced biocompatibility. Notably, under weakly acidic bacterial microenvironments (pH=6.4), AgNPs@ZIF-8 demonstrated a more satisfactory antibacterial effect. In addition, experiments on biofilms showed that concentrations of AgNPs@ZIF-8 exceeding 1×MIC resulted in more than 50% biofilm removal. The nanomedicine was found to increase ROS levels upon detecting the ROS concentration in bacteria. Conclusion: Novel nanocomposites consisting of low cytotoxicity drug carrier ZIF-8 loaded with AgNPs exhibited enhanced antimicrobial effects compared to AgNPs alone. The pH-responsive nano drug delivery system, AgNPs@ZIF-8, exhibited superior antimicrobial activity in a mildly acidic environment. Moreover, AgNPs@ZIF-8 effectively eradicated pathogenic bacterial biofilms and elevated the intracellular level of ROS. Graphical Abstract:

Cuproptosis, a new cell death pattern, is promising as an intervention target to treat tumors. Abnormal long non-coding RNA (lncRNA) expression is closely associated with the occurrence and development of papillary renal cell carcinoma (pRCC). However, cuproptosis-related lncRNAs (CRLs) remain largely unknown as prognostic markers for pRCC. We aimed to forecast the prognosis of pRCC patients by constructing models according to CRLs and to examine the correlation between the signatures and the inflammatory microenvironment. From the Cancer Genome Atlas (TCGA), RNA sequencing, genomic mutations and clinical data of TCGA-KIRP (Kidney renal papillary cell carcinoma) were analyzed. Randomly selected pRCC patients were allotted to the training and testing sets. To determine the independent prognostic impact of the training characteristic, the least absolute shrinkage and selection operator (LASSO) algorithm was utilized, together with univariate and multivariate Cox regression models. Further validation was performed in the testing and whole cohorts. External datasets were utilized to verify the prognostic value of CRLs as well. The CRLs prognostic features in pRCC were established based on the five CRLs (AC244033.2, LINC00886, AP000866.1, MRPS9-AS1 and CKMT2-AS1). The utility of CRLs was evaluated and validated in training, testing and all sets on the basis of the Kaplan–Meier (KM) survival analysis. The risk score could be a robust prognostic factor to forecast clinical outcomes for pRCC patients by the LASSO algorithm and univariate and multivariate Cox regression. Analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) data demonstrated that differentially expressed genes (DEGs) are primarily important for immune responses and the PI3K-Akt pathway. Arachidonic acid metabolism was enriched in the high-risk set by Gene Set Enrichment Analysis (GSEA). In addition, Tumor Immune Dysfunction and Exclusion (TIDE) analysis suggested that there was a high risk of immune escape in the high-risk cohort. The immune functions of the low- and high-risk sets differed significantly based on immune microenvironment analysis. Finally, four drugs were screened with a higher sensitivity to the high-risk set. Taken together, a novel model according to five CRLs was set up to forecast the prognosis of pRCC patients, which provides a potential strategy to treat pRCC by a combination of cuproptosis and immunotherapy.