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Rotator cuff tear (RCT) is a common shoulder disorder related to pain and dysfunction. However, the pathological mechanism of RCT remains unclear. Thus, this study aims to investigate the molecular events in RCT synovium and identify possible target genes and pathways as determined by RNA sequencing (RNA-Seq). The synovial tissue was biopsied from 3 patients with RCT (RCT group) and 3 patients with shoulder instability (Control group) during arthroscopic surgery. Then, differentially expressed (DE) mRNAs, long non-coding RNAs (lncRNAs) and micro RNAs (miRNAs) were comprehensively profiled by RNA-Seq. Gene ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and competing endogenous RNA (ceRNA) network analysis were performed to identify the potential functions of these DE genes. 447 mRNAs, 103 lncRNAs and 15 miRNAs were identified differentially expressed. The DE mRNAs were highlighted in inflammatory pathway including up-regulated T cell costimulation, positive regulation of T cell activation, and T cell receptor signaling. Down-regulated fatty acid degradation pathway and 5′-AMP-activated protein kinase (AMPK) signaling in RCT group are also enriched. Validation assay showed that the expression of pro-inflammatory molecules including IL21R, CCR5, TNFSF11, and MMP11 was significantly increased in RCT group compared with Control group. CeRNA analysis further revealed lncRNA-miRNA-mRNA regulatory networks involving IL21R and TNFSF11 in RCT. Activated synovial inflammation is the remarkable event of RCT. Importantly, increased T cell activation and disordered fatty acid metabolism signaling might play a significant role. ceRNA networks involving IL21R and TNFSF11 identified could potentially control the progression of RCT. In conclusion, our findings could provide new evidence for the molecular mechanisms of RCT and might identify new therapeutic targets. [ABSTRACT FROM AUTHOR]

Glioma is an aggressive tumor, currently there is no satisfactory management available. Psoralen, as a natural product, has been found to have an effect of treating cancer in recent years, but its effect on glioma has not been explored. In this study, we investigated the in vitro inhibition effect and potential targets of psoralen on glioma through network pharmacology and in vitro glioma treatment experiments. First, we used network pharmacology to preliminarily predict the 21 core genes of psoralen in the treatment of glioma, including PIK3CA, PIK3CB, PIK3CG, and JAK2. The CCK-8 method was used to detect the effect of psoralen on the proliferation of glioma U87 and U251 cells, and the results showed that psoralen could significantly inhibit the proliferation of U87 and U251 cells. The flow cytometry was used to detect the apoptosis and cell cycle changes, and it was found that psoralen could significantly promote the early apoptosis of U87 and U251 cells and had a significant cycle arrest effect on the two cells. The cell scratch test showed that psoralen could significantly inhibit the migration of U87 and U251 cells. The relative expression levels of PIK3CA, PIK3CB, PIK3CG, and JAK2 were analyzed by Real-time Quantitative polymerase chain reaction (QT-PCR), and the results showed that psoralen could inhibit the gene expression of PIK3CA, PIK3CB, PIK3CG, and JAK2. Later, Western blotting (WB) experiments showed that psoralen could inhibit the protein expressions of PI3K and JAK2. This study has preliminarily explored and verified the antiglioma effect of psoralen in the form of inhibiting cell proliferation and migration, promoting cell apoptosis and organizing cell cycle in vitro. And may play a role by inhibiting the expression of PIK3CA, PIK3CB, PIK3CG, JAK2 gene and PI3K, JAK2 protein, psoralen has become a potential antiglioma drug. [ABSTRACT FROM AUTHOR]

Recent studies have shown that in-depth studies on epi-transcriptomic patterns of N6-methyladenosine (m6A) may help understand its complex functions and co-regulatory mechanisms. Since most biclustering algorithms are developed in scenarios of gene expression analysis, which does not share the same characteristics with m6A methylation profile, we propose a weighted Plaid biclustering model (FBCwPlaid) based on the Lagrange multiplier method to discover the potential functional patterns. Each pattern is achieved by minimizing approximation error between FBCwPlaid predicted value and real data. To address the issue that site expression level determines methylation level confidence, it uses RNA expression levels of each site as weights to make lower expressed sites less confident. FBCwPlaid also allows overlapping biclusters, indicating some sites may participate in multiple biological functions. FBCwPlaid was then applied on MeRIP-Seq data of 69,446 methylation sites under 32 experimental conditions, each of which represented a stimulus to a particular cell line or environment. Finally, three patterns were discovered, and further pathway analysis and enzyme specificity test showed that sites involved in each pattern are highly relevant to m6A methyltransferases. Further detailed analyses showed that some patterns are condition-specific, indicating that some specific sites’ methylation profiles may occur in specific cell lines or conditions. [ABSTRACT FROM AUTHOR]

To study the molecular mechanism of the hyperaccumulator plant Phytolacca americana against cadmium (Cd) stress, the leaves of P. americana treated with 400 μM Cd for 0, 2, 12, and 24 h were harvested for comparative transcriptome analysis. In total, 110.07 Gb of clean data were obtained, and 63,957 unigenes were acquired after being assembled. Due to the lack of P. americana genome information, only 24,517 unigenes were annotated by public databases. After Cd treatment, 5054 differentially expressed genes (DEGs) were identified. KEGG pathway enrichment analysis of DEGs showed that genes involved in the flavonoid biosynthesis and antenna proteins of photosynthesis were significantly down-regulated, while genes related to the lignin biosynthesis pathway were remarkably up-regulated, indicating that P. americana could synthesize more lignin to cope with Cd stress. Moreover, genes related to heavy metal accumulation, sulfur metabolism and glutathione metabolism were also significantly up-regulated. The gene expression pattern of several key genes related to distinct metabolic pathways was verified by qRT-PCR. The results indicated that the immobilization of lignin in cell wall, chelation, vacuolar compartmentalization, as well as the increase of thiol compounds content may be the important mechanisms of Cd detoxification in hyperaccumulator plant P. americana. Accession numbers: the raw data of P. americana transcriptome presented in this study are openly available in NCBI SRA database, under the BioProject of PRJNA649785. [ABSTRACT FROM AUTHOR]

RNA N 6-methyladenosine (m6A) has emerged as an important epigenetic modification for its role in regulating the stability, structure, processing, and translation of RNA. Instability of m6A homeostasis may result in flaws in stem cell regulation, decrease in fertility, and risk of cancer. To this day, experimental detection and quantification of RNA m6A modification are still time-consuming and labor-intensive. There is only a limited number of epitranscriptome samples in existing databases, and a matched RNA methylation profile is not often available for a biological problem of interests. As gene expression data are usually readily available for most biological problems, it could be appealing if we can estimate the RNA methylation status from gene expression data using in silico methods. In this study, we explored the possibility of computational prediction of RNA methylation status from gene expression data using classification and regression methods based on mouse RNA methylation data collected from 73 experimental conditions. Elastic Net-regularized Logistic Regression (ENLR), Support Vector Machine (SVM), and Random Forests (RF) were constructed for classification. Both SVM and RF achieved the best performance with the mean area under the curve (AUC) = 0.84 across samples; SVM had a narrower AUC spread. Gene Site Enrichment Analysis was conducted on those sites selected by ENLR as predictors to access the biological significance of the model. Three functional annotation terms were found statistically significant: phosphoprotein, SRC Homology 3 (SH3) domain, and endoplasmic reticulum. All 3 terms were found to be closely related to m6A pathway. For regression analysis, Elastic Net was implemented, which yielded a mean Pearson correlation coefficient = 0.68 and a mean Spearman correlation coefficient = 0.64. Our exploratory study suggested that gene expression data could be used to construct predictors for m6A methylation status with adequate accuracy. Our work showed for the first time that RNA methylation status may be predicted from the matched gene expression data. This finding may facilitate RNA modification research in various biological contexts when a matched RNA methylation profile is not available, especially in the very early stage of the study. [ABSTRACT FROM AUTHOR]

The tawny crazy ant (Nylanderia fulva) is a new invasive pest in the United States. At present, its management mainly relies on the use of synthetic insecticides, which are generally ineffective at producing lasting control of the pest, necessitating alternative environmentally friendly measures. In this study, we evaluated the feasibility of gene silencing to control this ant species. Six housekeeping genes encoding actin (NfActin), coatomer subunit β (NfCOPβ), arginine kinase (NfArgK), and V‐type proton ATPase subunits A (NfvATPaseA), B (NfvATPaseB) and E (NfvATPaseE) were cloned. Phylogenetic analysis revealed high sequence similarity to homologs from other ant species, particularly the Florida carpenter ant (Camponotus floridanus). To silence these genes, vector L4440 was used to generate six specific RNAi constructs for bacterial expression. Heat‐inactivated, dsRNA‐expressing Escherichia coli were incorporated into artificial diet. Worker ants exhibited reduced endogenous gene expression after feeding on such diet for 9 d. However, only ingestion of dsRNAs of NfCOPβ (a gene involved in protein trafficking) and NfArgK (a cellular energy reserve regulatory gene in invertebrates) caused modest but significantly higher ant mortality than the control. These results suggest that bacterially expressed dsRNA can be orally delivered to ant cells as a mean to target its vulnerabilities. Improved efficacy is necessary for the RNAi‐based approach to be useful in tawny crazy ant management. [ABSTRACT FROM AUTHOR]

Background and Purpose: Aseptic prosthesis loosening, caused by wear particles, is one of the most common causes of arthroplasty failure. Extensive and over-activated osteoclast formation and physiological functioning are regarded as the mechanism of prosthesis loosening. Therapeutic modalities based on inhibiting osteoclast formation and bone resorption have been confirmed to be an effective way of preventing aseptic prosthesis loosening. In this study, we have investigated the effects of sophocarpine (SPC, derived from Sophora flavescens) on preventing implant loosening and further explored the underlying mechanisms.Experimental Approach: The effects of SPC in inhibiting osteoclastogenesis and bone resorption were evaluated in osteoclast formation, induced in vitro by the receptor activator of NF-κB ligand (RANKL). A rat femoral particle-induced peri-implant osteolysis model was established. Subsequently, micro-CT, histology, mechanical testing and bone turnover were used to assess the effects of SPC in preventing implant loosening.Key Results: In vitro, we found that SPC suppressed osteoclast formation, bone resorption, F-actin ring formation and osteoclast-associated gene expression by inhibiting NF-κB signalling, specifically by targeting IκB kinases. Our in vivo study showed that SPC prevented particle-induced prosthesis loosening by inhibiting osteoclast formation, resulting in reduced periprosthetic bone loss, diminished pseudomembrane formation, improved bone-implant contact, reduced bone resorption-related turnover and enhanced stability of implants. Inhibition of NF-κB signalling by SPC was confirmed in vivo.Conclusion and Implications: SPC can prevent implant loosening through inhibiting osteoclast formation and bone resorption. Thus, SPC might be a novel therapeutic agent to prevent prosthesis loosening and for osteolytic diseases. [ABSTRACT FROM AUTHOR]

N6-methyladenosine (m6A) is the most abundant methylation, existing in >25% of human mRNAs. Exciting recent discoveries indicate the close involvement of m6A in regulating many different aspects of mRNA metabolism and diseases like cancer. However, our current knowledge about how m6A levels are controlled and whether and how regulation of m6A levels of a specific gene can play a role in cancer and other diseases is mostly elusive. We propose in this paper a computational scheme for predicting m6A-regulated genes and m6A-associated disease, which includes Deep-m6A, the first model for detecting condition-specific m6A sites from MeRIP-Seq data with a single base resolution using deep learning and Hot-m6A, a new network-based pipeline that prioritizes functional significant m6A genes and its associated diseases using the Protein-Protein Interaction (PPI) and gene-disease heterogeneous networks. We applied Deep-m6A and this pipeline to 75 MeRIP-seq human samples, which produced a compact set of 709 functionally significant m6A-regulated genes and nine functionally enriched subnetworks. The functional enrichment analysis of these genes and networks reveal that m6A targets key genes of many critical biological processes including transcription, cell organization and transport, and cell proliferation and cancer-related pathways such as Wnt pathway. The m6A-associated disease analysis prioritized five significantly associated diseases including leukemia and renal cell carcinoma. These results demonstrate the power of our proposed computational scheme and provide new leads for understanding m6A regulatory functions and its roles in diseases. [ABSTRACT FROM AUTHOR]

The guilt by association (GBA) principle has been widely used to predict gene functions, and a network-based approach may enhance the confidence and stability of the analysis compared with focusing on individual genes. Fetal growth restriction (FGR), is the second primary cause of perinatal mortality. Therefore, the present study aimed to predict the optimal gene functions for FGR using a network-based GBA method. The method was comprised of four parts: Identification of differentially-expressed genes (DEGs) between patients with FGR and normal controls based on gene expression data; construction of a co-expression network (CEN) dependent on DEGs, using the Spearman correlation coefficient algorithm; collection of gene ontology (GO) data on the basis of a known confirmed database and DEGs; and prediction of optimal gene functions using the GBA algorithm, for which the area under the receiver operating characteristic curve (AUC) was obtained for each GO term. A total of 115 DEGs and 109 GO terms were obtained for subsequent analysis. All DEGs were mapped to the CEN and formed 6,555 edges. The results of GBA algorithm demonstrated that 78 GO terms had a good classification performance with AUC >0.5. In particular, the AUC for 5 of the GO terms was >0.7, and these were defined as optimal gene functions, including defense response, immune system process, response to stress, cellular response to chemical stimulus and positive regulation of biological process. In conclusion, the results of the present study provided insights into the pathological mechanism underlying FGR, and provided potential biomarkers for early detection and targeted treatment of this disease. However, the interactions between the 5 GO terms remain unclear, and further studies are required. [ABSTRACT FROM AUTHOR]

AccD6 is an important component of acetyl-CoA/propionyl-CoA carboxylase, which acts as a key role in mycolic acid synthesis and short chain fatty acyl-coenzyme A metabolism. In this study, we demonstrated that AccD6 of Mycobacterium smegmatis associates with AccA3 (α subunit of acetyl-CoA carboxylase, MSMEG 1807) and AccE (ε subunit, MSMEG 1812) to form the acetyl-CoA (propionyl-CoA) carboxylase. Results showed that the MSMEG 4331 subunit is a regulator that interacts with the promoter region of accD6 to inhibit its transcription. Transcription of accD6 was reduced by 50% in the mutant M. smegmatis strain overexpressing MSMEG 4331. Moreover, the activity of AccD6 was inhibited by acylation (such as acetylation and propionylation). These results demonstrate that AccD6 of M. smegmatis is regulated at both the transcriptional and post-translational levels. Our findings highlight the novel regulatory mechanism underlying mycolic acid biosynthesis in mycobacteria. [ABSTRACT FROM AUTHOR]

Proanthocyanidins (PCs) have shown inhibition of oxidative damage by improving Nrf-2 expression in many tissues. However, the cytoprotective effects of PCs on H2O2-induced tendon damage have not been verified. The current study was aimed at assessing the cytoprotection of PCs on the oxidative cellular toxicity of tendon-derived stem cells (TDSCs) induced by H2O2. The TDSCs were isolated from patellar tendons of Sprague Dawley (SD) rats, and the cells after third passage were used for subsequent experiments. The isolated cells were identified by flow cytometry assay and multidifferentiation potential assay. Cell Counting Kit-8 assay was performed to examine cell viability. Real-Time PCR and Western Blot were employed to, respectively, assess the mRNA and protein expressions of Nrf-2, GCLM, NQO-1, and HO-1. PCs significantly improved the cell viability of TDSCs. Furthermore, H2O2 upregulated Nrf-2, GCLM, NQO-1, and HO-1 without significant difference, while the proteins expressions were increased with significant difference in PCs group and PCs + H2O2 cotreated group. All the findings indicated that PCs could protect against the oxidative damage induced by H2O2 in TDSCs, and the cytoprotective effects might be due to the ability of PCs to activate the expressions of GCLM, HO-1, and NQO-1 via upregulating Nrf-2 signaling pathway. [ABSTRACT FROM AUTHOR]

Different types of genomic aberration may simultaneously contribute to tumorigenesis. To obtain a more accurate prognostic assessment to guide therapeutic regimen choice for cancer patients, the heterogeneous multi-omics data should be integrated harmoniously, which can often be difficult. For this purpose, we propose a Gene Interaction Regularized Elastic Net (GIREN) model that predicts clinical outcome by integrating multiple data types. GIREN conveniently embraces both gene measurements and gene-gene interaction information under an elastic net formulation, enforcing structure sparsity, and the “grouping effect” in solution to select the discriminate features with prognostic value. An iterative gradient descent algorithm is also developed to solve the model with regularized optimization. GIREN was applied to human ovarian cancer and breast cancer datasets obtained from The Cancer Genome Atlas, respectively. Result shows that, the proposed GIREN algorithm obtained more accurate and robust performance over competing algorithms (LASSO, Elastic Net, and Semi-supervised PCA, with or without average pathway expression features) in predicting cancer progression on both two datasets in terms of median area under curve (AUC) and interquartile range (IQR), suggesting a promising direction for more effective integration of gene measurement and gene interaction information. [ABSTRACT FROM PUBLISHER]

As the most prevalent mammalian mRNA epigenetic modification, N6-methyladenosine (m6A) has been shown to possess important post-transcriptional regulatory functions. However, the regulatory mechanisms and functional circuits of m6A are still largely elusive. To help unveil the regulatory circuitry mediated by mRNA m6A methylation, we develop here m6A-Driver, an algorithm for predicting m6A-driven genes and associated networks, whose functional interactions are likely to be actively modulated by m6A methylation under a specific condition. Specifically, m6A-Driver integrates the PPI network and the predicted differential m6A methylation sites from methylated RNA immunoprecipitation sequencing (MeRIP-Seq) data using a Random Walk with Restart (RWR) algorithm and then builds a consensus m6A-driven network of m6A-driven genes. To evaluate the performance, we applied m6A-Driver to build the context-specific m6A-driven networks for 4 known m6A (de)methylases, i.e., FTO, METTL3, METTL14 and WTAP. Our results suggest that m6A-Driver can robustly and efficiently identify m6A-driven genes that are functionally more enriched and associated with higher degree of differential expression than differential m6A methylated genes. Pathway analysis of the constructed context-specific m6A-driven gene networks further revealed the regulatory circuitry underlying the dynamic interplays between the methyltransferases and demethylase at the epitranscriptomic layer of gene regulation. [ABSTRACT FROM AUTHOR]

Cardiotoxicity is an aggravating side effect of many clinical antineoplastic agents such as arsenic trioxide (As2O3), which is the first-line treatment for acute promyelocytic leukemia (APL). Clinically, drug combination strategies are widely applied for complex disease management. Here, an optimized, cardiac-friendly therapeutic strategy for APL was investigated using a combination of As2O3 and genistein or resveratrol. Potential combinations were explored with respect to their effects on mitochondrial membrane potential, reactive oxygen species, superoxide dismutase activity, autophagy, and apoptosis in both NB4 cells and neonatal rat left ventricular myocytes. All experiments consistently suggested that 5 µM resveratrol remarkably alleviates As2O3-induced cardiotoxicity. To achieve an equivalent effect, a 10-fold dosage of genistein was required, thus highlighting the dose advantage of resveratrol, as poor bioavailability is a common concern for its clinical application. Co-administration of resveratrol substantially amplified the anticancer effect of As2O3 in NB4 cells. Furthermore, resveratrol exacerbated oxidative stress, mitochondrial damage, and apoptosis, thereby reflecting its full range of synergism with As2O3. Addition of 5 µM resveratrol to the single drug formula of As2O3 also further increased the expression of LC3, a marker of cellular autophagy activity, indicating an involvement of autophagy-mediated tumor cell death in the synergistic action. Our results suggest a possible application of an As2O3 and resveratrol combination to treat APL in order to achieve superior therapeutics effects and prevent cardiotoxicity. [ABSTRACT FROM AUTHOR]

In multicellular organisms, transcription factors (TFs) and microRNAs (miRNA) embody two largest families of molecules that modulate messenger RNA (mRNA) expressions through transcriptional and post-transcriptional regulations. While mRNA and microRNA expressions can be measured by microarray technique, the activities of transcription factors manifested by their protein expression are still difficult to observe, making it usually a complex problem to reconstruct a collaborative gene regulatory network (GRN) by TFs and miRNAs from expression data. In this paper, a novel Bayesian sparse non-negative factor regression (BSNFR) model is proposed for modeling the joint regulations of mRNAs by TFs and miRNAs and integration of multiple data types including gene expressions, microRNA expressions, TF targeted genes, and microRNA targets. Powered by a Gibbs sampling solution, BSNFR can infer both the TF/microRNA-mediated mRNA regulations and the unknown TF activities. Additionally, since BSNFR directly models the non-negative activities of TFs, it avoids the common problem of sign ambiguity with factor models and is capable of accurate prediction of the types (up or down) of regulations as well. BSNFR also includes a nonparametric Bayesian model for the latent factor activities, which enables the discovery of the clustering effects among samples due to (disease) subtypes. The proposed BSNFR model and the developed Gibbs sampling solution were validated on simulated systems and applied to real data of glioblastoma multiforme (GBM) patients from The Cancer Genome Atlas (TCGA). A GBM specific gene regulatory network by TFs and miRNAs was reconstructed. This GBM network includes 107 regulations recorded in the existing databases and 16 new regulations. Functional analysis suggests that the regulated genes are enriched in cell cycle and P53 pathways. In addition, BSNFR also identified 3 clusters among GBM patient samples, two of which demonstrates significant survival differences (p=0.004). Finally, the estimated TF activities imply that EGR-1 is significantly correlated with patient survivals (p=0.004) and may be used as a prognostic biomarker. The data and matlab code are available at: . [ABSTRACT FROM AUTHOR]

Summary: The ten-eleven translocation (Tet) family of methylcytosine dioxygenases catalyze oxidation of 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC) and promote DNA demethylation. Despite the abundance of 5hmC and Tet proteins in the brain, little is known about the functions of the neuronal Tet enzymes. Here, we analyzed Tet1 knockout mice (Tet1KO) and found downregulation of multiple neuronal activity-regulated genes, including Npas4, c-Fos, and Arc. Furthermore, Tet1KO animals exhibited abnormal hippocampal long-term depression and impaired memory extinction. Analysis of the key regulatory gene, Npas4, indicated that its promoter region, containing multiple CpG dinucleotides, is hypermethylated in both naive Tet1KO mice and after extinction training. Such hypermethylation may account for the diminished expression of Npas4 itself and its downstream targets, impairing transcriptional programs underlying cognitive processes. In summary, we show that neuronal Tet1 regulates normal DNA methylation levels, expression of activity-regulated genes, synaptic plasticity, and memory extinction. [ABSTRACT FROM AUTHOR]