TBK1-stabilized ZNF268a recruits SETD4 to methylate TBK1 for efficient interferon signaling.

Sufficient activation of interferon signaling is critical for the host to fight against invading viruses, in which post-translational modifications have been demonstrated to play a pivotal role. Here, we demonstrate that the human KRAB-zinc finger protein ZNF268a is essential for virus-induced interferon signaling. We find that cytoplasmic ZNF268a is constantly degraded by lysosome and thus remains low expressed in resting cell cytoplasm. Upon viral infection, TBK1 interacts with cytosolic ZNF268a to catalyze the phosphorylation of Serine 178 of ZNF268a, which prevents the degradation of ZNF268a, resulting in the stabilization and accumulation of ZNF268a in the cytoplasm. Furthermore, we provide evidence that stabilized ZNF268a recruits the lysine methyltransferase SETD4 to TBK1 to induce the mono-methylation of TBK1 on lysine 607, which is critical for the assembly of the TBK1 signaling complex. Notably, ZNF268 S178 is conserved among higher primates but absent in rodents. Meanwhile, rodent TBK1 607th aa happens to be replaced by arginine, possibly indicating a species-specific role of ZNF268a in regulating TBK1 during evolution. These findings reveal novel functions of ZNF268a and SETD4 in regulating antiviral interferon signaling.

Waste Detection System Based on Data Augmentation and YOLO_EC.

The problem of waste classification has been a major concern for both the government and society, and whether waste can be effectively classified will affect the sustainable development of human society. To perform fast and efficient detection of waste targets in the sorting process, this paper proposes a data augmentation + YOLO_EC waste detection system. First of all, because of the current shortage of multi-objective waste classification datasets, the heavy workload of human data collection, and the limited improvement of data features by traditional data augmentation methods, DCGAN (deep convolution generative adversarial networks) was optimized by improving the loss function, and an image-generation model was established to realize the generation of multi-objective waste images; secondly, with YOLOv4 (You Only Look Once version 4) as the basic model, EfficientNet is used as the backbone feature extraction network to realize the light weight of the algorithm, and at the same time, the CA (coordinate attention) attention mechanism is introduced to reconstruct the MBConv module to filter out high-quality information and enhance the feature extraction ability of the model. Experimental results show that on the HPU_WASTE dataset, the proposed model outperforms other models in both data augmentation and waste detection.

RNF138 Downregulates Antiviral Innate Immunity by Inhibiting IRF3 Activation.

A viral infection activates the transcription factors IRF3 and NF-κB, which synergistically induces type I interferons (IFNs). Here, we identify the E3 ubiquitin ligase RNF138 as an important negative regulator of virus-triggered IRF3 activation and IFN-ß induction. The overexpression of RNF138 inhibited the virus-induced activation of IRF3 and the transcription of the IFNB1 gene, whereas the knockout of RNF138 promoted the virus-induced activation of IRF3 and transcription of the IFNB1 gene. We further found that RNF138 promotes the ubiquitination of PTEN and subsequently inhibits PTEN interactions with IRF3, which is essential for the PTEN-mediated nuclear translocation of IRF3, thereby inhibiting IRF3 import into the nucleus. Our findings suggest that RNF138 negatively regulates virus-triggered signaling by inhibiting the interaction of PTEN with IRF3, and these data provide new insights into the molecular mechanisms of cellular antiviral responses.