Zeins are the most abundant storage proteins in maize (Zea mays) kernels, thereby affecting the nutritional quality and texture of this crop. 27-kD γ-zein is highly expressed and plays a crucial role in protein body formation. Several transcription factors (TFs) (O2, PBF1, OHP1, and OHP2) regulate the expression of the 27-kD γ-zein gene, but the complexity of its transcriptional regulation is not fully understood. Here, using probe affinity purification and mass spectrometry analysis, we identified ZmbZIP22, a TF that binds to the 27-kD γ-zein promoter. ZmbZIP22 is a bZIP-type TF that is specifically expressed in endosperm. ZmbZIP22 bound directly to the ACAGCTCA box in the 27-kD γ-zein promoter and activated its expression in wild tobacco (Nicotiana benthamiana) cells. 27-kD γ-zein gene expression was significantly reduced in CRISPR/Cas9-generated zmbzip22 mutants. ChIP-seq (chromatin immunoprecipitation coupled to high-throughput sequencing) confirmed that ZmbZIP22 binds to the 27-kD γ-zein promoter in vivo and identified additional direct targets of ZmbZIP22. ZmbZIP22 can interact with PBF1, OHP1, and OHP2, but not O2. Transactivation assays using various combinations of these TFs revealed multiple interaction modes for the transcriptional activity of the 27-kD γ-zein promoter. Therefore, ZmbZIP22 regulates 27-kD γ-zein gene expression together with other known TFs.

The alpha-zein super gene family encodes the most predominant storage protein in maize (Zea mays) endosperm. In maize inbred line B73, it consists of four gene families with 41 member genes. In this study, we combined quantitative real-time PCR and random clone sequencing to successfully profile the expression of alpha-zein super gene family during endosperm development. We found that only 18 of the 41 member genes were expressed, and their expression levels diverge greatly. At the gene family level, all families had characteristic "up-and-down" oscillating expressional patterns that diverged into two major groups. At the individual gene level, member genes showed dramatic divergence of expression patterns, indicating fast differentiation of their expression regulation. A comparison study among different inbred lines revealed significantly different expressed gene sets, indicating the existence of highly diverged haplotypes. Large gene families containing long gene clusters, e.g. z1A or z1C, mainly contributed the highly divergent haplotypes. In addition, allelic genes also showed significant divergence in their expressional levels. These results indicated a highly dynamic and fast evolving nature to the maize alpha-zein super gene family, which might be a common feature for other large gene families.

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Chemodynamic therapy (CDT) has been emerging as a promising strategy for cancer treatment. But the CDT efficiency is restricted by the insufficient intracellular hydrogen peroxide (H2O2) level. Herein, we present a method for H2O2 accumulation in tumor cells by silencing the catalase (CAT) gene with siRNA to achieve enhanced CDT. Cu-siRNA nanocomposites are fabricated by self-assembly of Cu2+ and CAT siRNA and then modified with hyaluronic acid (HA) for active tumor targeting. After tumor cell uptake, the released Cu2+ is reduced by highly expressed glutathione (GSH) to Cu+, which then catalyzes H2O2 to produce toxic hydroxyl radicals (•OH) to kill tumor cells. CAT siRNA can efficiently silence the CAT mRNA to inhibit the consumption of H2O2, resulting in H2O2 accumulation. The Cu2+-mediated GSH elimination and siRNA-induced endogenous H2O2 enrichment both potentiate CDT. Cu-siRNA@HA exhibits good biocompatibility and therapeutic efficiency. This work thus paves a new way to supply H2O2 in CDT and may hold potential for clinical application.

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Introduction Breast cancer is the main reason for cancer-related deaths in women and the most common malignant cancer among women. In recent years, immunosuppressive factors have become a new type of treatment for cancer. However, there are no effective biomarkers for breast cancer immunotherapy. Therefore, exploring immune-related biomarkers is presently an important topic in breast cancer. Methods Gene expression profile data of breast cancer from The Cancer Genome Atlas (TCGA) was downloaded. Scale-free gene co-expression networks were built with weighted gene co-expression network analysis. The correlation of genes was performed with Pearson’s correlation values. The potential associations between clinical features and gene sets were studied, and the hub genes were screened out. Gene Ontology and gene set enrichment analysis were used to reveal the function of hub gene in breast cancer. The gene expression profiles of GSE15852, downloaded from the Gene Expression Omnibus database, were used for hub gene verification. In addition, candidate biomarkers expression in breast cancer was studied. Survival analysis was performed using Log rank test and Kaplan–Meier. Immunohistochemistry was used to analyze the expression of CCNA2 . Results A total of 6 modules related to immune cell infiltration were identified via the average linkage hierarchical clustering. According to the threshold criteria (module membership >0.9 and gene significance >0.35), a significant module consisting of 13 genes associated with immune cells infiltration were identified as candidate hub genes after performed with the human protein interaction network. And 3 genes with high correlation to clinical traits were identified as hub genes, which were negatively associated with the overall survival. Among them, the expression of CCNA2 was increased in metastatic breast cancer compare with non-metastatic breast cancer, who underwent immunotherapy. Immunohistochemistry results showed that CCNA2 expression in carcinoma tissues was elevated compared with normal control. Discussion CCNA2 identified as a potential immune therapy marker in breast cancer, which were first reported here and deserved further research.

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