Systematic and integrated analysis of tRNA-derived small RNAs reveals novel potential pathogenesis targets of sarcoidosis

The pathogenesis of sarcoidosis, which involves several systems, is unclear, and its pathological type is non-caseating epithelioid granulomas. tRNA-derived small RNA (tsRNA) is a novel class of short non-coding RNAs with potential regulatory functions. However, whether tsRNA contributes to sarcoidosis pathogenesis remains unclear. Deep sequencing technology was used to identify alterations in tsRNA expression profiles between patients with sarcoidosis and healthy controls. A total of 360 tsRNAs were identified for exact matches. Among them, the expression of three tRNAs (tiRNA-Glu-TTC-001, tiRNA-Lys-CTT-003, and tRF-Ser-TGA-007) was markedly regulated in sarcoidosis and validated by quantitative real-time polymerase chain reaction. The expression of various tsRNAs was significantly correlated with age, the number of affected systems, and calcium levels in the blood. Additionally, target prediction and bioinformatics analyses revealed that these tsRNAs may play roles in chemokine, cAMP, cGMP-PKG, retrograde endorphin, and FoxO signalling pathways. The Cytoscape software was used for visual analysis to obtain 10 hub genes of each target tsRNA. Among the hub genes, APP, PRKACB, ARRB2, and NR5A1 finding may participate in the occurrence and development of sarcoidosis through immune inflammation. This study provides novel insights to explore tsRNA as a novel and efficacious pathogenic target of sarcoidosis.

Exploring the Mechanism of Quercetin for the Treatment of Atrial Fibrillation by GEO Gene Chip Combined with Network Pharmacology and Molecular Docking

Atrial fibrillation (AF) is a common atrial arrhythmia for which there is no specific therapeutic drug. Quercetin (Que) has been used to treat cardiovascular diseases such as arrhythmias. In this study, we explored the mechanism of action of Que in AF using network pharmacology and molecular docking. The chemical structure of Que was obtained from Pubchem. TCMSP, Swiss Target Prediction, Drugbank, STITCH, Binding DB, Pharmmapper, CTD, GeneCards, DISGENET and TTD were used to obtain drug component targets and AF-related genes, and extract AF and normal tissue by GEO database differentially expressed genes by GEO database. The top targets were IL6, VEGFA, JUN, MMP9 and EGFR, and Que for AF treatment might involve the lipid and atherosclerosis pathway, the role of AGE-RAGE signaling pathway in diabetic complications, MAPK signaling pathway and IL-17 signaling pathway. In addition, molecular docking showed that Que binds strongly to key targets and is differentially expressed in AF. This study systematically elucidated the key targets of Que treatment for AF and the specific mechanisms, providing a new direction for further basic experimental exploration and clinical treatment.

The ectomycorrhizal fungus Pisolithus microcarpus encodes a microRNA involved in cross-kingdom gene silencing during symbiosis

Small RNAs (sRNAs) are known to regulate pathogenic plant–microbe interactions. Emerging evidence from the study of these model systems suggests that microRNAs (miRNAs) can be translocated between microbes and plants to facilitate symbiosis. The roles of sRNAs in mutualistic mycorrhizal fungal interactions, however, are largely unknown. In this study, we characterized miRNAs encoded by the ectomycorrhizal fungus Pisolithus microcarpus and investigated their expression during mutualistic interaction with Eucalyptus grandis. Using sRNA sequencing data and in situ miRNA detection, a novel fungal miRNA, Pmic_miR-8, was found to be transported into E. grandis roots after interaction with P. microcarpus. Further characterization experiments demonstrate that inhibition of Pmic_miR-8 negatively impacts the maintenance of mycorrhizal roots in E. grandis, while supplementation of Pmic_miR-8 led to deeper integration of the fungus into plant tissues. Target prediction and experimental testing suggest that Pmic_miR-8 may target the host NB-ARC domain containing transcripts, suggesting a potential role for this miRNA in subverting host signaling to stabilize the symbiotic interaction. Altogether, we provide evidence of previously undescribed cross-kingdom sRNA transfer from ectomycorrhizal fungi to plant roots, shedding light onto the involvement of miRNAs during the developmental process of mutualistic symbioses.

Identification of novel miRNA targets in CHO cell lines and characterization of their impact on protein N-glycosylation

CHO cell lines are a workhorse for the production of pharmaceutical proteins, but show some limitations in the variability and stability of N-glycosylation profiles. One promising approach to addressing this at the required systems-level is miRNA, which can regulate a large number of genes and have predictable targets. Herein, we first identified de novo 656 potential miRNAs in the CHO genome based on a combination of literature, database searching, and miRNA sequencing. We further sequenced mRNA from the same cultures, and used a combination of mRNA-miRNA correlation analysis, target prediction and literature searches to find miRNAs potentially targeting N-glycosylation. Our ten best miRNA candidates were subjected to miRNA overexpression, knockdown, or knock-out in CHO cell lines. Out of the ten candidates, four (miR-128, miR-34c, miR-30b, and miR-449a) showed positive effects on N-glycosylation and could be applied directly for CHO cell engineering. The fact that 40% of the screened targets had a desired effect, and the prediction of 656 miRNAs illustrates the massive potential of miRNA engineering in CHO.

Predicting the targets of IRF8 and NFATc1 during osteoclast differentiation using the machine learning method framework cTAP

Background Interferon regulatory factor-8 (IRF8) and nuclear factor-activated T cells c1 (NFATc1) are two transcription factors that have an important role in osteoclast differentiation. Thanks to ChIP-seq technology, scientists can now estimate potential genome-wide target genes of IRF8 and NFATc1. However, finding target genes that are consistently up-regulated or down-regulated across different studies is hard because it requires analysis of a large number of high-throughput expression studies from a comparable context. Method We have developed a machine learning based method, called, Cohort-based TF target prediction system (cTAP) to overcome this problem. This method assumes that the pathway involving the transcription factors of interest is featured with multiple “functional groups” of marker genes pertaining to the concerned biological process. It uses two notions, Gene-Present Sufficiently (GP) and Gene-Absent Insufficiently (GA), in addition to log2 fold changes of differentially expressed genes for the prediction. Target prediction is made by applying multiple machine-learning models, which learn the patterns of GP and GA from log2 fold changes and four types of Z scores from the normalized cohort’s gene expression data. The learned patterns are then associated with the putative transcription factor targets to identify genes that consistently exhibit Up/Down gene regulation patterns within the cohort. We applied this method to 11 publicly available GEO data sets related to osteoclastgenesis. Result Our experiment identified a small number of Up/Down IRF8 and NFATc1 target genes as relevant to osteoclast differentiation. The machine learning models using GP and GA produced NFATc1 and IRF8 target genes different than simply using a log2 fold change alone. Our literature survey revealed that all predicted target genes have known roles in bone remodeling, specifically related to the immune system and osteoclast formation and functions, suggesting confidence and validity in our method. Conclusion cTAP was motivated by recognizing that biologists tend to use Z score values present in data sets for the analysis. However, using cTAP effectively presupposes assembling a sizable cohort of gene expression data sets within a comparable context. As public gene expression data repositories grow, the need to use cohort-based analysis method like cTAP will become increasingly important.

Molecular Characterization and Target Prediction of Candidate miRNAs Related to Abiotic Stress Responses and/or Storage Root Development in Sweet Potato

Sweet potato is a tuberous root crop with strong environmental stress resistance. It is beneficial to study its storage root formation and stress responses to identify sweet potato stress- and storage-root-thickening-related regulators. Here, six conserved miRNAs (miR156g, miR157d, miR158a-3p, miR161.1, miR167d and miR397a) and six novel miRNAs (novel 104, novel 120, novel 140, novel 214, novel 359 and novel 522) were isolated and characterized in sweet potato. Tissue-specific expression patterns suggested that miR156g, miR157d, miR158a-3p, miR167d, novel 359 and novel 522 exhibited high expression in fibrous roots or storage roots and were all upregulated in response to storage-root-related hormones (indole acetic acid, IAA; zeaxanthin, ZT; abscisic acid, ABA; and gibberellin, GAs). The expression of miR156g, miR158a-3p, miR167d, novel 120 and novel 214 was induced or reduced dramatically by salt, dehydration and cold or heat stresses. Moreover, these miRNAs were all upregulated by ABA, a crucial hormone modulator in regulating abiotic stresses. Additionally, the potential targets of the twelve miRNAs were predicted and analyzed. Above all, these results indicated that these miRNAs might play roles in storage root development and/or stress responses in sweet potato as well as provided valuable information for the further investigation of the roles of miRNA in storage root development and stress responses.

MicroRNA expression signature and target prediction in familial and sporadic primary macronodular adrenal hyperplasia (PMAH)

Background Primary macronodular adrenal hyperplasia (PMAH), previously termed ACTH-independent macronodular adrenal hyperplasia (AIMAH), is a rare cause of Cushing’s syndrome usually characterized by functioning adrenal macronodules and increased cortisol production. Methods To screen and analyse the microRNA (miRNA) profile of PMAH in order to elucidate its possible pathogenesis, a miRNA microarray was used to test tissue samples from patients with familial PMAH, patients with sporadic PMAH and normal control samples of other nontumour adrenocortical tissues and identify characteristic microRNA expression signatures. Randomly selected miRNAs were validated by quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR). Furthermore, the key signalling pathways and miRNAs involved in PMAH pathogenesis were determined by gene ontology and pathway analysis. Results Characteristic microRNA expression signatures were identified for patients with familial PMAH (16 differentially expressed microRNAs) and patients with sporadic PMAH (8 differentially expressed microRNAs). The expression of the selected miRNAs was confirmed by qRT-PCR, suggesting the high reliability of the miRNA array analysis results. Pathway analysis showed that the most enriched pathway was the renal cell carcinoma pathway. Overexpression of miR-17, miR-20a and miR-130b may inhibit glucocorticoid-induced apoptosis in PMAH pathogenesis. Conclusion We identified the miRNA signatures in patients with familial and sporadic PMAH. The differentially expressed miRNAs may be involved in the mechanisms of PMAH pathogenesis. Specific miRNAs, such as miR-17, miR-20a and miR-130b, may be new targets for further functional studies of PMAH.

In silico ADME/Pharmacokinetic and Target Prediction Studies of Ethambutol as Drug Molecule

Background: The conventional approach for the development of any pharmaceutically active molecule is a time-consuming and costly process because the synthesis is followed by laboratory tests which are then followed by long clinical trials. Hence a faster approach is desired. This article discusses Ethambutol, a frontline anti-tubercular drug that has its properties predicted by the SwissADME tool and the results would be compared with the findings published in the literature. Objective: The main objective is to study the predicted and experimental ADME properties, compare them. As well as study the predicted targets and understand the use of SwissADME for designing other drug molecules. Method: SwissADME, an online tool for ADME prediction was used along with Swiss Target Prediction to understand the targets of the drug. Further, experimental data was obtained from the available scientific literature. Results: We found certain similarities between the predicted and experimental data. However, there were some variations, depending on the testing conditions. The results are interpreted ahead in the article. Conclusion: Ethambutol’s predicted ADME properties are discussed and as per findings from results, it can be concluded that other drug molecules can be similarly predicted using these tools. Also, based on predicted data we can reformulate and prepare some different preparations of the drug.

Anticancer Activities of 9-chloro-6-(piperazin-1-yl)-11H-indeno[1,2-c] quinolin-11-one (SJ10) in Glioblastoma Multiforme (GBM) Chemoradioresistant Cell Cycle-Related Oncogenic Signatures

Current anticancer treatments are inefficient against glioblastoma multiforme (GBM), which remains one of the most aggressive and lethal cancers. Evidence has shown the presence of glioblastoma stem cells (GSCs), which are chemoradioresistant and associated with high invasive capabilities in normal brain tissues. Moreover, accumulating studies have indicated that radiotherapy contributes to abnormalities in cell cycle checkpoints, including the G1/S and S phases, which may potentially lead to resistance to radiation. Through computational simulations using bioinformatics, we identified several GBM oncogenes that are involved in regulating the cell cycle. Cyclin B1 (CCNB1) is one of the cell cycle-related genes that was found to be upregulated in GBM. Overexpression of CCNB1 was demonstrated to be associated with higher grades, proliferation, and metastasis of GBM. Additionally, increased expression levels of CCNB1 were reported to regulate activation of mitogen-activated protein kinase 7 (MAPK7) in the G2/M phase, which consequently modulates mitosis; additionally, in clinical settings, MAPK7 was demonstrated to promote resistance to temozolomide (TMZ) and poor patient survival. Therefore, MAPK7 is a potential novel drug target due to its dysregulation and association with TMZ resistance in GBM. Herein, we identified MAPK7/extracellular regulated kinase 5 (ERK5) genes as being overexpressed in GBM tumors compared to normal tissues. Moreover, our analysis revealed increased levels of the cell division control protein homolog (CDC42), a protein which is also involved in regulating the cell cycle through the G1 phase in GBM tissues. This therefore suggests crosstalk among CCNB1/CDC42/MAPK7/cluster of differentiation 44 (CD44) oncogenic signatures in GBM through the cell cycle. We further evaluated a newly synthesized small molecule, SJ10, as a potential target agent of the CCNB1/CDC42/MAPK7/CD44 genes through target prediction tools and found that SJ10 was indeed a target compound for the above-mentioned genes; in addition, it displayed inhibitory activities against these oncogenes as observed from molecular docking analysis.