CRIT:Identifying RNA-binding protein regulator in circRNA life cycle via non-negative matrix factorization

Circular RNAs (circRNAs) are endogenous non-coding RNAs that regulate gene expression and participate in carcinogenesis. However, the RNA-binding proteins (RBPs) involved in circRNAs biogenesis and modulation remain largely unclear. We developed the circRNA regulator identification tool (CRIT), a non-negative matrix-factorization-based pipeline to identify regulating RBPs in cancers. CRIT uncovered 73 novel regulators across thousands of samples by effectively leveraging genomics data and functional annotations. We demonstrated that known RBPs involved in circRNA control are significantly enriched in these predictions. Analysis of circRNA-RBP interactions using two large cross-linking immunoprecipitation (CLIP) databases, we validated the consistency between CRIT prediction and the CLIP experiments. Furthermore, newly discovered RBPs are functionally connected with authentic circRNA regulators by various biological associations, such as physical interaction, similar binding motifs, common transcription factor modulation, and co-expression. When analyzing RNA sequencing (RNA-seq) datasets after short hairpin RNA (shRNA)/small interfering RNA (siRNA) knockdown, we found several novel RBPs that can affect global circRNA expression, which strengthens their role in the circRNA life cycle. The above evidence provided independent confirmation that CRIT is a useful tool to capture RBPs in circRNA processing. Finally, we show that authentic regulators are more likely the core splicing proteins and peripheral factors and usually harbor more alterations in the vast majority of cancers

Splicing factor TRA2A contributes to esophageal cancer progression via a noncanonical role in lncRNA m⁶A methylation

Transformer 2 alpha homolog (TRA2A), a member of the serine/arginine-rich splicing factor family, has been shown to control mRNA splicing in development and cancers. However, it remains unclear whether TRA2A is involved in lncRNA regulation. In the present study, we found that TRA2A was upregulated and correlated with poor prognosis in esophageal cancer. Downregulation of TRA2A suppressed the tumor growth in xenograft nude mice. Epitranscriptomic microarray showed that depletion of TRA2A affected global lncRNA methylation similarly to the key m6A methyltransferase, METTL3, by silencing. MeRIP-qPCR, RNA pull-down, CLIP analyses, and stability assays indicated that ablation of TRA2A reduced m6A-modification of the oncogenic lncRNA MALAT1, thus inducing structural alterations and reduced stability. Furthermore, Co-IP experiments showed TRA2A directly interacted with METTL3 and RBMX, which also affected the writer KIAA1429 expression. Knockdown of TRA2A inhibited cell proliferation in a manner restored by RBMX/KIAA1429 overexpression. Clinically, MALAT1, RBMX, and KIAA1429 were prognostic factors of worse survival in ESCA patients. Structural similarity-based virtual screening in FDA-approved drugs repurposed nebivolol, a β1-adrenergic receptor antagonist, as a potent compound to suppress the proliferation of esophageal cancer cells. Cellular thermal shift and RIP assay indicated that nebivolol may compete with MALAT1 to bind TRA2A. In conclusion, our study revealed the noncanonical function of TRA2A, which coordinates with multiple methylation proteins to promote oncogenic MALAT1 during ESCA carcinogenesis.</p

Rapid detection of multiple resistance genes to last-resort antibiotics in Enterobacteriaceae pathogens by recombinase polymerase amplification combined with lateral flow dipstick

The worrying emergence of multiple resistance genes to last-resort antibiotics in food animals and human populations throughout the food chain and relevant environments has been increasingly reported worldwide. Enterobacteriaceae pathogens are considered the most common reservoirs of such antibiotic resistance genes (ARGs). Thus, a rapid, efficient and accurate detection method to simultaneously screen and monitor such ARGs in Enterobacteriaceae pathogens has become an urgent need. Our study developed a recombinase polymerase amplification (RPA) assay combined with a lateral flow dipstick (LFD) for simultaneously detecting predominant resistance genes to last-resort antibiotics of Enterobacteriaceae pathogens, including mcr-1, blaNDM-1 and tet(X4). It is allowed to complete the entire process, including crude DNA extraction, amplification as well as reading, within 40 min at 37°C, and the detection limit is 101 copies/μl for mcr-1, blaNDM-1 and tet(X4). Sensitivity analysis showed obvious association of color signals with the template concentrations of mcr-1, blaNDM-1 and tet(X4) genes in Enterobacteriaceae pathogens using a test strip reader (R2 = 0.9881, R2 = 0.9745, and R2 = 0.9807, respectively), allowing for quantitative detection using multiplex RPA-LFD assays. Therefore, the RPA-LFD assay can suitably help to detect multiple resistance genes to last-resort antibiotics in foodborne pathogens and has potential applications in the field

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.Peer reviewe

Simulation Study of FEUDT Structure Optimization and Sensitive Film Loading of SAW Devices

In order to further improve the degree of frequency response of the surface acoustic wave (SAW) sensor for gas detection, the structure of the forked-finger transducer was analyzed, and its optimal structural parameters were simulated and designed. The simulation model of the unidirectional fork-finger transducer is established by using COMSOL finite element software. The thickness of the piezoelectric substrate, the electrode structure and material, and the thickness of the coating film are optimized and simulated. The results show that: the optimal thickness of the piezoelectric substrate is 3λ. The optimal thickness ratio and the lay-up ratio of the forked-finger electrode are 0.02 and 0.5, respectively. The Al electrode is more suitable as the a forked-finger electrode material compared to Cu, Au and Pt materials. Under the same conditions, the metal oxide-sensitive film (ZnO and TiO2) has a higher frequency response than the polymer-sensitive film (polyisobutylene and polystyrene), and the best sensitive film thickness range is 0.5~1 μm

Computational Drug Repurposing Based on a Recommendation System and Drug&ndash;Drug Functional Pathway Similarity

Drug repurposing identifies new clinical indications for existing drugs. It can be used to overcome common problems associated with cancers, such as heterogeneity and resistance to established therapies, by rapidly adapting known drugs for new treatment. In this study, we utilized a recommendation system learning model to prioritize candidate cancer drugs. We designed a drug&ndash;drug pathway functional similarity by integrating multiple genetic and epigenetic alterations such as gene expression, copy number variation (CNV), and DNA methylation. When compared with other similarities, such as SMILES chemical structures and drug targets based on the protein&ndash;protein interaction network, our approach provided better interpretable models capturing drug response mechanisms. Furthermore, our approach can achieve comparable accuracy when evaluated with other learning models based on large public datasets (CCLE and GDSC). A case study about the Erlotinib and OSI-906 (Linsitinib) indicated that they have a synergistic effect to reduce the growth rate of tumors, which is an alternative targeted therapy option for patients. Taken together, our computational method characterized drug response from the viewpoint of a multi-omics pathway and systematically predicted candidate cancer drugs with similar therapeutic effects

Mechanism of Modified Danggui Sini Decoction for Knee Osteoarthritis Based on Network Pharmacology and Molecular Docking

Objective. This study aimed to explore the mechanism of Modified Danggui Sini Decoction in the treatment of knee osteoarthritis via a combination of network pharmacology and molecular docking. Methods. The main chemical components and corresponding targets of Modified Danggui Sini Decoction were searched and screened in TCMSP database. The disease targets of knee osteoarthritis were summarized in GeneCards, OMIM, PharmGkb, TTD, and DrugBank databases. The visual interactive network of “drugs-active components-disease targets” was drawn by Cytoscape 3.8.1 software. The protein-protein interaction network was constructed by STRING database. Then, GO function and KEGG pathway enrichment were analyzed by Bioconductor/R, and the pathway of the highest degree of correlation with knee osteoarthritis was selected for specific analysis. Finally, molecular docking was used to screen and verify core genes by AutoDockTools software. Results. Seventy-one main components of Modified Danggui Sini Decoction and 116 potential therapeutic targets of knee osteoarthritis were selected. The KEGG pathway and the GO function enrichment analysis showed that the targets of Modified Danggui Sini Decoction in the treatment of knee osteoarthritis were mainly concentrated on PI3K-Akt signaling pathway, TNF signaling pathway, IL-17 signaling pathway, apoptosis signaling pathway, Toll-like receptor signaling pathway, Th17 cell differentiation signaling pathway, HIF-1 signaling pathway, and NF-κB signaling pathway. It mainly involved inflammatory reaction, regulation of apoptotic signaling pathway, cellular response to regulation of inflammatory response, cellular response to oxidative stress, and other biological processes. The molecular docking results showed that ESR1-wogonin, MAPK1-quercetin, RELA-wogonin, RELA-baicalein, TP53-baicalein, TP53-quercetin, and RELA-quercetin have strong docking activities. Conclusion. Modified Danggui Sini Decoction has the hierarchical network characteristics of “multicomponent, multitarget, multifunction, and multipathway” in the treatment of knee osteoarthritis. It mainly regulates the proliferation and apoptosis of chondrocytes by regulating the PI3K-Akt signaling pathway and establishes cross-talk with many downstream inflammatory-related pathways to reduce the overall inflammatory response. Meanwhile, HIF-1 expression was used to ensure the normal function and metabolism of knee joint under hypoxia condition, and the above processes play a key role in the treatment of knee osteoarthritis