Chloroplasts are semi-autonomous organelles, with more than 95% of their proteins encoded by the nuclear genome. The chloroplast-to-nucleus retrograde signals are critical for the nucleus to coordinate its gene expression for optimizing or repairing chloroplast functions in response to changing environments. In chloroplasts, the pentatricopeptide-repeat protein GENOMES UNCOUPLED 1 (GUN1) is a master switch that senses aberrant physiological states, such as the photooxidative stress induced by norflurazon (NF) treatment, and represses the expression of photosynthesis-associated nuclear genes (PhANGs). However, it is largely unknown how the retrograde signal is transmitted beyond GUN1. In this study, a protein GUN1-INTERACTING PROTEIN 1 (GIP1), encoded by At3g53630, was identified to interact with GUN1 by different approaches. We demonstrated that GIP1 has both cytosol and chloroplast localizations, and its abundance in chloroplasts is enhanced by NF treatment with the presence of GUN1. Our results suggest that GIP1 and GUN1 may function antagonistically in the retrograde signaling pathway.
Extracellular matrix changes are often crucial inciting events for fibroproliferative disease. Epigenetic changes, specifically DNA methylation, are critical factors underlying differentiated phenotypes. We examined the dependency of matrix-induced fibroproliferation and SMC phenotype on DNA methyltransferases. The cooperativity of matrix with growth factors, cell density and hypoxia was also examined. Primary rat visceral SMC of early passage (0–2) were plated on native collagen or damaged/heat-denatured collagen. Hypoxia was induced with 3% O2 (balanced 5% CO2 and 95% N2) over 48 hours. Inhibitors were applied 2–3 hours after cells were plated on matrix, or immediately before hypoxia. Cells were fixed and stained for DNMT3A and smooth muscle actin (SMA) or smooth muscle myosin heavy chain. Illumina 450 K array of CpG sites was performed on bisulfite-converted DNA from smooth muscle cells on damaged matrix vs native collagen. Matrix exquisitely regulates DNMT3A localization and expression, and influences differentiation in SMCs exposed to denatured matrix +/− hypoxia. Analysis of DNA methylation signatures showed that Matrix caused significant DNA methylation alterations in a discrete number of CpG sites proximal to genes related to SMC differentiation. Matrix has a profound effect on the regulation of SMC phenotype, which is associated with altered expression, localization of DNMTs and discrete changes DNA methylation. 相似文献
Autophagy is a highly conserved self-digestion pathway involved in various physiological and pathophysiological processes. Recent studies have implicated a pivotal role of autophagy in adipocyte differentiation, but the molecular mechanism for its role and how it is regulated during this process are not clear. Here, we show that CCAAT /enhancer-binding protein β (C/EBPβ), an important adipogenic factor, is required for the activation of autophagy during 3T3-L1 adipocyte differentiation. An autophagy-related gene, Atg4b, is identified as a de novo target gene of C/EBPβ and is shown to play an important role in 3T3-L1 adipocyte differentiation. Furthermore, autophagy is required for the degradation of Klf2 and Klf3, two negative regulators of adipocyte differentiation, which is mediated by the adaptor protein p62/SQSTM1. Importantly, the regulation of autophagy by C/EBPβ and the role of autophagy in Klf2/3 degradation and in adipogenesis are further confirmed in mouse models. Our data describe a novel function of C/EBPβ in regulating autophagy and reveal the mechanism of autophagy during adipocyte differentiation. These new insights into the molecular mechanism of adipose tissue development provide a functional pathway with therapeutic potential against obesity and its related metabolic disorders. 相似文献
There has been paid more and more attention to supervised classification models in the area of predicting drug-target interactions (DTIs). However, in terms of classification, unavoidable missing DTIs in data would cause three issues which have not yet been addressed appropriately by former approaches. Directly labeled as negatives (non-DTIs), missing DTIs increase the confusion of positives (DTIs) and negatives, aggravate the imbalance between few positives and many negatives, and are usually discriminated as highly-scored false positives, which influence the existing measures sharply.
Results
Under the framework of local classification model (LCM), this work focuses on the scenario of predicting how possibly a new drug interacts with known targets. To address the first two issues, two strategies, Spy and Super-target, are introduced accordingly and further integrated to form a two-layer LCM. In the bottom layer, Spy-based local classifiers for protein targets are built by positives, as well as reliable negatives identified among unlabeled drug-target pairs. In the top layer, regular local classifiers specific to super-targets are built with more positives generated by grouping similar targets and their interactions. Furthermore, to handle the third issue, an additional performance measure, Coverage, is presented for assessing DTI prediction. The experiments based on benchmark datasets are finally performed under five-fold cross validation of drugs to evaluate this approach. The main findings are concluded as follows. (1) Both two individual strategies and their combination are effective to missing DTIs, and the combination wins the best. (2) Having the advantages of less confusing decision boundary at the bottom layer and less biased decision boundary at the top layer, our two-layer LCM outperforms two former approaches. (3) Coverage is more robust to missing interactions than other measures and is able to evaluate how far one needs to go down the list of targets to cover all the proper targets of a drug.
Conclusions
Proposing two strategies and one performance measure, this work has addressed the issues derived from missing interactions, which cause confusing and biased decision boundaries in classifiers, as well as the inappropriate measure of predicting performance, in the scenario of predicting interactions between new drugs and known targets.
In this study, a novel Hsp90 inhibitor BJ-B11, was synthesized and evaluated for in vitro antiviral activity against several viruses. Possible anti-HSV-1 mechanisms were also investigated. BJ-B11 displayed no antiviral activity against coxsackievirus B3 (CVB3), human respiratory syncytial virus (RSV) and influenza virus (H1N1), but exhibited potent anti-HSV-1 and HSV-2 activity with EC50 values of 0.42 ± 0.18 μM and 0.60 ± 0.21 μM, respectively. Additionally, the inhibitory effects of BJ-B11 against HSV-1 were likely to be introduced at early stage of infection. Our results indicate that BJ-B11 with alternative mechanisms of action is potent as an anti-HSV clinical trial candidate. 相似文献