RNA polymerase II (Pol II) generally pauses at certain positions along gene bodies, thereby interrupting the transcription elongation process, which is often coupled with various important biological functions, such as precursor mRNA splicing and gene expression regulation. Characterizing the transcriptional elongation dynamics can thus help us understand many essential biological processes in eukaryotic cells. However, experimentally measuring Pol II elongation rates is generally time and resource consuming. We developed PEPMAN (polymerase II elongation pausing modeling through attention-based deep neural network), a deep learning-based model that accurately predicts Pol II pausing sites based on the native elongating transcript sequencing (NET-seq) data. Through fully taking advantage of the attention mechanism, PEPMAN is able to decipher important sequence features underlying Pol II pausing. More importantly, we demonstrated that the analyses of the PEPMAN-predicted results around various types of alternative splicing sites can provide useful clues into understanding the cotranscriptional splicing events. In addition, associating the PEPMAN prediction results with different epigenetic features can help reveal important factors related to the transcription elongation process. All these results demonstrated that PEPMAN can provide a useful and effective tool for modeling transcription elongation and understanding the related biological factors from available high-throughput sequencing data.
This study aimed to identify potential anti-Alzheimer’s disease (AD) targets and action mechanisms of Ginkgo Folium (GF) through a network pharmacology approach. Eighty-four potential targets of 10 active anti-AD ingredients of GF were identified, among which genkwanin (GK) had the greatest number of AD-related targets. KEGG pathway enrichment analysis showed that the most significantly enriched signaling pathway of GF against AD was Alzheimer disease (hsa05010). More importantly, 29 of the 84 targets were significantly correlated with tau, Aβ or both Aβ and tau pathology. In addition, GO analysis suggested that the main biological processes of GF in AD treatment were the regulation of chemical synaptic transmission (GO:0007268), neuron death (GO:0070997), amyloid-beta metabolic process (GO:0050435), etc. We further investigated the anti-AD effects of GK using N2A-APP cells (a classical cellular model of AD). Treatment N2A-APP cells with 100 μM GK for 48 h affected core targets related to tau pathology (such as CDK5 and GSK3β). In conclusion, these findings indicate that GF exerts its therapeutic effects on AD by acting directly on multiple pathological processes of AD.
Protein-based condensates have been proposed to accelerate biochemical reactions by enriching reactants and enzymes simultaneously. Here, we engineered those condensates into a photo-activated switch in Escherichia coli (PhASE) to regulate enzymatic reactions via tuning the spatial correlation of enzymes and substrates. In this system, scaffold proteins undergo liquid-liquid phase separation (LLPS) to form light-responsive compartments. Tethered with a light-responsive protein, enzymes of interest (EOIs) can be recruited by those compartments from cytosol within only a few seconds after a pulse of light induction and fully released in 15 min. Furthermore, we managed to enrich small molecular substrates simultaneously with enzymes in the compartments and achieved the acceleration of luciferin and catechol oxidation by 2.3and 1.6-folds, respectively. We also developed a quantitative model to guide the further optimization of this demixed regulatory system. Our tool can thus be used to study the rapid redistribution of proteins, and reversibly regulate enzymatic reactions in E. coli.
Growing evidence supports the involvement of neuroinflammation in the pathophysiology of depression. Administrating curcumin could revert the depressive-like symptoms and weakened microglial activation and increased the level of pro-inflammatory cytokine. This study aimed to identify potential anti-depression targets and mechanisms of curcumin (CUR) by an approach of network pharmacology. GSEA and KEGG pathways showed the most significantly enriched pathway of CUR against depression was the PI3K-Akt pathway. Moreover, 52 targets were significantly correlated with PI3K-Akt signaling pathway and CUR-related targets. In addition, among these top 50 targets which were ranked by degree in the PPI network, there were 23 targets involved in the 52 intersection targets. Thus, our findings suggest that CUR exerts its anti-depression effects through PI3K-Akt signaling pathway. Furthermore, we investigated the anti-depression effects of CUR using a mouse model of depression induced by lipopolysaccharide (LPS). Administration of LPS alone (2 mg/kg/day, i.p.) extended the immobility time in the open filed test (OFT) and tail suspension test (TST), decreased sucrose consumption in the sucrose preference test (SPT). Pretreatment with CUR (50 mg/kg/day, i.p.) for 7 consecutive days relieved LPS-induced changes in the behavior tests, the activity of PI3K-Akt signaling pathway, neuronal damage in the PFC and inflammatory response. Moreover, inhibition of the PI3K-Akt signaling pathway by LY294002 (7.5 mg/kg/day, i.p.) blocks the therapeutic effects of CUR. In conclusion, our study indicate that CUR may be an effective antidepressant agent for LPS-induced mouse model, in part because of its anti-inflammatory actin through PI3K-Akt signaling pathway.
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