MicroRNAs (miRNAs) are small non-coding RNA molecules capable of negatively regulating gene expression to control many cellular mechanisms. The miRTarBase database (http://mirtarbase.mbc.nctu.edu.tw/) provides the most current and comprehensive information of experimentally validated miRNA-target interactions. The database was launched in 2010 with data sources for >100 published studies in the identification of miRNA targets, molecular networks of miRNA targets and systems biology, and the current release (2013, version 4) includes significant expansions and enhancements over the initial release (2010, version 1). This article reports the current status of and recent improvements to the database, including (i) a 14-fold increase to miRNA-target interaction entries, (ii) a miRNA-target network, (iii) expression profile of miRNA and its target gene, (iv) miRNA target-associated diseases and (v) additional utilities including an upgrade reminder and an error reporting/user feedback system.

The objectives of this study were to determine if human ejaculated sperm exhibit active caspases and if caspase-dependent apoptosis markers are identifiable. Sperm from fertile donors and infertile patients were examined after gradient separation into leukocyte-free fractions of high and low motility. Sperm were evaluated for motion parameters, morphology, caspase activation, and apoptosis markers including phosphatidylserine (PS) translocation (annexin V binding) and DNA fragmentation (TUNEL). Active caspase-3 was detected by immunofluorescent microscopy in a small proportion of sperm in situ, in fractions of high and low motility sperm of patients and donors, but low motility fractions had significantly higher numbers of positive sperm. Immunoblot analysis detected inactive procaspase-3 (32 kDa) in all fractions of low sperm motility from patients and donors, while active caspase-3 (17 kDa) was only detected by immunoblotting in a limited number of low motility fractions from patients and in even fewer fractions from donors. Caspase enzymatic activity, as measured using the fluorogenic substrate DEVD-afc, was higher in patients than in donors in both low and high motility fractions. Annexin V staining and DNA fragmentation were detected in a proportion of sperm, with a higher frequency in the low motility fractions. A significant positive correlation between in-situ active caspase-3 in the sperm midpiece and DNA fragmentation was observed in the low motility fractions of patients, suggesting that caspase-dependent apoptotic mechanisms could originate in the cytoplasmic droplet or within mitochondria and function in the nucleus. These data suggest that in some ejaculated sperm populations, caspases are present and may function to increase PS translocation and DNA fragmentation.

In this study we extended earlier work to determine whether sperm respond to somatic cell apoptotic stimuli and whether apoptotic phenotypes are significant indicators of human sperm quality. We evaluated ejaculated sperm from fertile donors and subfertile patients following purification of fractions of high and low motility. In unstimulated conditions, caspase enzymatic activity was higher in motile fractions from subfertile patients than in donors, and was higher in low motility fractions from both groups. Staurosporine, but not a Fas ligand or H2O2, significantly increased caspase activity, but only in high motility fractions. Procaspase-3, -7 and -9 and low levels of active caspase-3, -7 and -9 were identified by immunoblot analysis. Apoptosis-inducing factor (AIF) was present in all samples but poly ADP-ribose polymerase-1 (PARP-1) was not detected. Phosphatidylserine translocation was significantly increased only with H2O2 treatment. In ejaculates of both subfertile and fertile men, we demonstrated the presence and activation of several proteins that are key constituents of apoptosis-related pathways in somatic cells, which may serve as markers for sperm quality.

Rationale: Triple-negative breast cancer (TNBC), which has the highest recurrence rate and shortest survival time of all breast cancers, is in urgent need of a risk assessment method to determine an accurate treatment course. Recently, miRNA expression patterns have been identified as potential biomarkers for diagnosis, prognosis, and personalized therapy. Here, we investigate a combination of candidate miRNAs as a clinically applicable signature that can precisely predict relapse in TNBC patients after surgery. Methods: Four total cohorts of training (TCGA_TNBC and GEOD-40525) and validation (GSE40049 and GSE19783) datasets were analyzed with logistic regression and Gaussian mixture analyses. We established a miRNA signature risk model and identified an 8-miRNA signature for the prediction of TNBC relapse. Results: The miRNA signature risk model identified ten candidate miRNAs in the training set. By combining 8 of the 10 miRNAs (miR-139-5p, miR-10b-5p, miR-486-5p, miR-455-3p, miR-107, miR-146b-5p, miR-324-5p and miR-20a-5p), an accurate predictive model of relapse in TNBC patients was established and was highly correlated with prognosis (AUC of 0.80). Subsequently, this 8-miRNA signature prognosticated relapse in the two validation sets with AUCs of 0.89 and 0.90. Conclusion: The 8-miRNA signature predictive model may help clinicians provide a prognosis for TNBC patients with a high risk of recurrence after surgery and provide further personalized treatment to decrease the chance of relapse.

BackgroundMesenchymal stem cell (MSC) found in bone marrow (BM-MSCs) and the Wharton's jelly matrix of human umbilical cord (WJ-MSCs) are able to transdifferentiate into neuronal lineage cells both in vitro and in vivo and therefore hold the potential to treat neural disorders such as stroke or Parkinson's disease. In bone marrow MSCs, miR-130a and miR-206 have been show to regulate the synthesis of neurotransmitter substance P in human mesenchymal stem cell-derived neuronal cells. However, how neuronal differentiation is controlled in WJ-MSC remains unclear.MethodsWJ-MSCs were isolated from human umbilical cords. We subjected WJ-MSCs into neurogenesis by a published protocol, and the miRNome patterns of WJ-MSCs and their neuronal progenitors (day 9 after differentiation) were analyzed by the Agilent microRNA microarray.ResultsFive miRNAs were enriched in WJ-MSCs, including miR-345, miR-106a, miR-17-5p, miR-20a and miR-20b. Another 11 miRNAs (miR-206, miR-34a, miR-374, miR-424, miR-100, miR-101, miR-323, miR-368, miR-137, miR-138 and miR-377) were abundantly expressed in transdifferentiated neuronal progenitors. Among these miRNAs, miR-34a and miR-206 were the only 2 miRNAs been linked to BM-MSC neurogenesis. Overexpressing miR-34a in cells suppressed the expression of 136 neuronal progenitor genes, which all possess putative miR-34a binding sites. Gene enrichment analysis according to the Gene Ontology database showed that those 136 genes were associated with cell motility, energy production (including those with oxidative phosphorylation, electron transport and ATP synthesis) and actin cytoskeleton organization, indicating that miR-34a plays a critical role in precursor cell migration. Knocking down endogenous miR-34a expression in WJ-MSCs resulted in the augment of WJ-MSC motility.ConclusionsOur data suggest a critical role of miRNAs in MSC neuronal differentiation, and miR-34a contributes in neuronal precursor motility, which may be crucial for stem cells to home to the target sites they should be.

BackgroundThe conjugation of ubiquitin to a substrate protein (protein ubiquitylation), which involves a sequential process – E1 activation, E2 conjugation and E3 ligation, is crucial to the regulation of protein function and activity in eukaryotes. This ubiquitin-conjugation process typically binds the last amino acid of ubiquitin (glycine 76) to a lysine residue of a target protein. The high-throughput of mass spectrometry-based proteomics has stimulated a large-scale identification of ubiquitin-conjugated peptides. Hence, a new web resource, UbiSite, was developed to identify ubiquitin-conjugation site on lysines based on large-scale proteome dataset.ResultsGiven a total of 37,647 ubiquitin-conjugated proteins, including 128026 ubiquitylated peptides, obtained from various resources, this study carries out a large-scale investigation on ubiquitin-conjugation sites based on sequenced and structural characteristics. A TwoSampleLogo reveals that a significant depletion of histidine (H), arginine (R) and cysteine (C) residues around ubiquitylation sites may impact the conjugation of ubiquitins in closed three-dimensional environments. Based on the large-scale ubiquitylation dataset, a motif discovery tool, MDDLogo, has been adopted to characterize the potential substrate motifs for ubiquitin conjugation. Not only are single features such as amino acid composition (AAC), positional weighted matrix (PWM), position-specific scoring matrix (PSSM) and solvent-accessible surface area (SASA) considered, but also the effectiveness of incorporating MDDLogo-identified substrate motifs into a two-layered prediction model is taken into account. Evaluation by five-fold cross-validation showed that PSSM is the best feature in discriminating between ubiquitylation and non-ubiquitylation sites, based on support vector machine (SVM). Additionally, the two-layered SVM model integrating MDDLogo-identified substrate motifs could obtain a promising accuracy and the Matthews Correlation Coefficient (MCC) at 81.06 % and 0.586, respectively. Furthermore, the independent testing showed that the two-layered SVM model could outperform other prediction tools, reaching at 85.10 % sensitivity, 69.69 % specificity, 73.69 % accuracy and the 0.483 of MCC value.ConclusionThe independent testing result indicated the effectiveness of incorporating MDDLogo-identified motifs into the prediction of ubiquitylation sites. In order to provide meaningful assistance to researchers interested in large-scale ubiquitinome data, the two-layered SVM model has been implemented onto a web-based system (UbiSite), which is freely available at http://csb.cse.yzu.edu.tw/UbiSite/. Two cases given in the UbiSite provide a demonstration of effective identification of ubiquitylation sites with reference to substrate motifs.Electronic supplementary materialThe online version of this article (doi:10.1186/s12918-015-0246-z) contains supplementary material, which is available to authorized users.

Protein O-GlcNAcylation, involving the β-attachment of single N-acetylglucosamine (GlcNAc) to the hydroxyl group of serine or threonine residues, is an O-linked glycosylation catalyzed by O-GlcNAc transferase (OGT). Molecular level investigation of the basis for OGT's substrate specificity should aid understanding how O-GlcNAc contributes to diverse cellular processes. Due to an increasing number of O-GlcNAcylated peptides with site-specific information identified by mass spectrometry (MS)-based proteomics, we were motivated to characterize substrate site motifs of O-GlcNAc transferases. In this investigation, a non-redundant dataset of 410 experimentally verified O-GlcNAcylation sites were manually extracted from dbOGAP, OGlycBase and UniProtKB. After detection of conserved motifs by using maximal dependence decomposition, profile hidden Markov model (profile HMM) was adopted to learn a first-layered model for each identified OGT substrate motif. Support Vector Machine (SVM) was then used to generate a second-layered model learned from the output values of profile HMMs in first layer. The two-layered predictive model was evaluated using a five-fold cross validation which yielded a sensitivity of 85.4%, a specificity of 84.1%, and an accuracy of 84.7%. Additionally, an independent testing set from PhosphoSitePlus, which was really non-homologous to the training data of predictive model, was used to demonstrate that the proposed method could provide a promising accuracy (84.05%) and outperform other O-GlcNAcylation site prediction tools. A case study indicated that the proposed method could be a feasible means of conducting preliminary analyses of protein O-GlcNAcylation and has been implemented as a web-based system, OGTSite, which is now freely available at http://csb.cse.yzu.edu.tw/OGTSite/.

Coronavirus disease 2019 (COVID-19) is highly contagious, and thus has become an emerging health crisis worldwide. The optimal strategies to prevent the spread of this disease are inconclusive, and therefore, the adopted measurements to combat COVID-19 varies in different countries. In mid-March and late-August 2020, we performed internet searches to collect relevant information, from sources such as the website of the World Health Organization. The epidemiological data of COVID-19 from several countries were collected and we found that Taiwan had a comparably successful story for combating the pandemic. As of mid-March, Taiwan had high rates of diagnostic testing (688.5 tests per million citizens) with a lower infection rate (49 cases, 2.1 cases per million people). As of late-August, there were 488 cases (20 cases per million people). Furthermore, Taiwanese government-guided strategies and hospital data were also reviewed. We summarized some important strategies to combat COVID-19, which include: (1) border control; (2) official media channel and press conferences; (3) name-based rationing system for medical masks; (4) TOCC-based rapid triage, outdoor clinics, and protective sampling devices; and (5) social distancing, delaying the start of new semesters, and religious assembly restriction. In conclusion, Taiwan had lower rates of COVID-19 compared with other countries, and Taiwan government-guided strategies contributed to the control of the disease's spread.