Deciphering the role of RNA structure in translation efficiency.

BACKGROUND: RNA secondary structure has broad impact on the fate of RNA metabolism. The reduced stability of secondary structures near the translation initiation site/start codon of the coding region promotes the efficiency of translation in both prokaryotic and eukaryotic species. However, the inaccuracy of in silico folding and the focus on the coding region limit our understanding of the global relationship between the whole mRNA structure and translation efficiency. Leveraging high-throughput RNA structure probing data in the transcriptome, we aim to systematically investigate the role of RNA structure in regulating translation efficiency. RESULTS: Here, we analyze the influences of hundreds of sequence and structural features on translation efficiency in the mouse embryonic stem cells (mESCs) and zebrafish developmental stages. Our findings reveal that overall in vivo RNA structure has a higher relative importance in predicting translation efficiency than in vitro RNA structure in both mESCs and zebrafish. Also, RNA structures in 3\u27 untranslated region (UTR) have much stronger influence on translation efficiency compared to those in coding regions or 5\u27 UTR. Furthermore, strong alternation between in vitro and in vivo structures in 3\u27 UTR are detected in highly translated mRNAs in mESCs but not zebrafish. Instead, moderate alteration between in vitro and in vivo RNA structures in the 5\u27 UTR and proximal coding regions are detected in highly translated mRNAs in zebrafish. CONCLUSIONS: Our results suggest the openness of the 3\u27 UTR promotes the translation efficiency in both mice and zebrafish, with the in vivo structure in 3\u27 UTR more important in mice than in zebrafish. This reveals a novel role of RNA secondary structure on translational regulation

PRAS: Predicting functional targets of RNA binding proteins based on CLIP-seq peaks.

RNA-protein interaction plays important roles in post-transcriptional regulation. Recent advancements in cross-linking and immunoprecipitation followed by sequencing (CLIP-seq) technologies make it possible to detect the binding peaks of a given RNA binding protein (RBP) at transcriptome scale. However, it is still challenging to predict the functional consequences of RBP binding peaks. In this study, we propose the Protein-RNA Association Strength (PRAS), which integrates the intensities and positions of the binding peaks of RBPs for functional mRNA targets prediction. We illustrate the superiority of PRAS over existing approaches on predicting the functional targets of two related but divergent CELF (CUGBP, ELAV-like factor) RBPs in mouse brain and muscle. We also demonstrate the potential of PRAS for wide adoption by applying it to the enhanced CLIP-seq (eCLIP) datasets of 37 RNA decay related RBPs in two human cell lines. PRAS can be utilized to investigate any RBPs with available CLIP-seq peaks. PRAS is freely available at http://ouyanglab.jax.org/pras/

Inhibition of SPRY2 expression protects sevoflurane-induced nerve injury via ERK signaling pathway

Purpose: To investigate the effect of Sprouty2 (SPRY2) on sevoflurane (SEV) induced nerve injury in rats and its potential signaling pathway. Methods: Male Sprague-Dawley rats were divided into sham and SEV groups containing six rats per group. Neurological injury assessment and H & E staining were performed to evaluate the degree of nerve injury in the rats, while quantitative polymerase chain reaction (qPCR) and immunoblot assays were performed to confirm the expression levels of SPRY2 in hippocampus tissues. Morris water maze tests were performed to determine the degree of cognitive deficit in rats. TUNEL and immunoblot assays were performed to evaluate the effects of SPRY2 on the apoptosis of hippocampus tissues. Results: The SPRY2 expression was elevated in sevoflurane-induced hippocampus injury (p < 0.001). Ablation of SPRY2 inhibited sevoflurane-induced hippocampal neuron apoptosis (p < 0.001). In addition, depletion of SPRY2 promoted hippocampal neuron activity and decreased apoptosis (p < 0.001). Knockdown of SPRY2 promoted ERK signaling pathway, thereby protecting against sevoflurane-induced nerve injury and cognitive deficit in the rats (p < 0.001). Conclusion: Sevoflurane induces cognitive dysfunction and upregulates SPRY2 expression in brain tissues in rats. The SPRY2 knockdown improves SEV-induced neural injuries and cognitive deficits, inhibits hippocampal neuron apoptosis, and enhances its activity. Meanwhile, SPRY2 depletion protects SEV-induced nerve injury via the ERK pathway. Thus, Sprouty2 could serve as a promising drug target for the treatment of SEV-induced cognitive dysfunctions

Multiplex immunofluorescence-guided laser capture microdissection for spatial transcriptomics of metastatic melanoma tissues.

We describe a pipeline for optimized and streamlined multiplexed immunofluorescence-guided laser capture microdissection allowing the harvest of individual cells based on their phenotype and tissue localization for transcriptomic analysis with next-generation RNA sequencing. Here, we analyze transcriptomes of CD3+ T cells, CD14+ monocytes/macrophages, and melanoma cells in non-dissociated metastatic melanoma tissue. While this protocol is described for melanoma tissues, we successfully applied it to human tonsil, skin, and breast cancer tissues as well as mouse lung tissues. For complete details on the use and execution of this protocol, please refer to Martinek et al. (2022)

Reactive oxygen species formation and its effect on CD4+ T cell-mediated inflammation

Reactive oxygen species (ROS) are produced both enzymatically and non-enzymatically in vivo. Physiological concentrations of ROS act as signaling molecules that participate in various physiological and pathophysiological activities and play an important role in basic metabolic functions. Diseases related to metabolic disorders may be affected by changes in redox balance. This review details the common generation pathways of intracellular ROS and discusses the damage to physiological functions when the ROS concentration is too high to reach an oxidative stress state. We also summarize the main features and energy metabolism of CD4+ T-cell activation and differentiation and the effects of ROS produced during the oxidative metabolism of CD4+ T cells. Because the current treatment for autoimmune diseases damages other immune responses and functional cells in the body, inhibiting the activation and differentiation of autoreactive T cells by targeting oxidative metabolism or ROS production without damaging systemic immune function is a promising treatment option. Therefore, exploring the relationship between T-cell energy metabolism and ROS and the T-cell differentiation process provides theoretical support for discovering effective treatments for T cell-mediated autoimmune diseases

Small Object Detection Based on Two-Stage Calculation Transformer

Despite the current small object detection task has achieved significant improvements, it still suffers from some problems. For example, it is a challenge to extract small object features because of little information in the scene of small objects, which may lose the original feature information of small object, resulting in poor detection results. To address this problem, this paper proposes a two-stage calculation Transformer (TCT) based small object detection network. Firstly, a two-stage calculation Transformer is embedded in the backbone feature extraction network for feature enhancement. Based on the traditional Transformer values computation, multiple 1D dilated convolutional layer branches with different feature fusions are utilized to implement global self-attention for the purpose of improving the feature representation and information interaction. Secondly, this paper proposes an effective residual connection module to improve the low-efficiency convolution and activation of the current CSPLayer, which helps to advance the information flow and learn more rich contextual details. Finally, this paper proposes a feature fusion and refinement module for fusing multi-scale features and improving the target feature representation capability. Quantitative and qualitative experiments on PASCAL VOC2007+2012 dataset, COCO2017 dataset and TinyPerson dataset show that the proposed algorithm has better ability of target feature extraction and higher detection accuracy for small target detection, compared with YOLOX