microRNAs in stroke pathogenesis

Stroke is one of the leading causes of death and disability worldwide. There are two major types of stroke: cerebral ischemia caused by obstruction of blood vessels in the brain and haemorrhagic stroke that is triggered by the disruption of blood vessels. Thrombolytic therapy involving recombinant tissue plasminogen activator (rtPA) has been shown to be beneficial only when used within 4.5 hours of onset of acute ischemic stroke. rtPA treatment beyond this time window has been found to be unsuitable and usually resulting in haemorrhagic transformation. Stroke is a multifactorial disease that forms a possible end state for majority of patients suffering from diabetes, atherosclerosis and hypertension which are known risk factors. Although the biochemistry of stroke and related diseases is quite well understood, the knowledge on the molecular mechanisms underlying these diseases is still at its infancy. microRNAs that form a unique class of endogenous riboregulators of gene function, offer tremendous potential in unraveling the mechanisms underlying stroke pathogenesis. microRNA expression also reflects the response of individuals to drugs and therapy. Several microRNAs and their target genes, known to be involved in endothelial dysfunction, dysregulation of neurovascular integrity, edema formation, pro-apoptosis, inflammation and extra-cellular matrix remodeling contribute to the critical processes in the pathogenesis of stroke. In this review, we will also be discussing the role of microRNAs as possible diagnostic and prognostic biomarkers as well as potential therapeutic targets in stroke pathogenesis.     

A method for handling metabonomics data from liquid chromatography/mass spectrometry: combinational use of support vector machine recursive feature elimination, genetic algorithm and random forest for feature selection

Metabolic markers are the core of metabonomic surveys. Hence selection of differential metabolites is of great importance for either biological or clinical purpose. Here, a feature selection method was developed for complex metabonomic data set. As an effective tool for metabonomics data analysis, support vector machine (SVM) was employed as the basic classifier. To find out meaningful features effectively, support vector machine recursive feature elimination (SVM-RFE) was firstly applied. Then, genetic algorithm (GA) and random forest (RF) which consider the interaction among the metabolites and independent performance of each metabolite in all samples, respectively, were used to obtain more informative metabolic difference and avoid the risk of false positive. A data set from plasma metabonomics study of rat liver diseases developed from hepatitis, cirrhosis to hepatocellular carcinoma was applied for the validation of the method. Besides the good classification results for 3 kinds of liver diseases, 31 important metabolites including lysophosphatidylethanolamine (LPE) C16:0, palmitoylcarnitine, lysophosphatidylethanolamine (LPC) C18:0 were also selected for further studies. A better complementary effect of the three feature selection methods could be seen from the current results. The combinational method also represented more differential metabolites and provided more metabolic information for a “global” understanding of diseases than any single method. Further more, this method is also suitable for other complex biological data sets.     

LC-MS/MS determination of helicid in human plasma and its application in pharmacokinetic studies

Helicid is a traditional Chinese medicine used to treat headache and insomnia with definite effects. To facilitate pharmacokinetic studies of helicid in man, a sensitive and specific LC-MS/MS method for the quantitative detection of helicid in human plasma was developed and validated. The method involved the addition of bergeninum as the internal standard (IS), protein precipitation, HPLC separation, and quantification by MS/MS system using negative electrospray ionization in the multiple reaction monitoring mode (MRM). The precursor→product ion transitions were monitored at m/z 282.8→120.9 for helicid and m/z 326.9→192.2 for the IS, respectively. The lower limit of quantification (LLOQ) was 0.2 μg/L. The calibration curves for helicid was linear over a concentration range of 0.2-20 μg/L. The intra- and inter-batch analyses of QC samples at 0.4, 2, 20 μg/L indicated good precision (%R.S.D. between 2.69 and 5.47%) and accuracy (between 96.15 and 105.05%). The helicid was stable in human plasma stored at room temperature for at least 24h, 4°C for at least 24h, -20°C for at least 1 month, and for routine three freeze-thaw cycles. This accurate and specific assay provides a useful method for evaluating the pharmacokinetic profile of helicid in humans.     

The role of CXCR7 on the adhesion, proliferation and angiogenesis of endothelial progenitor cells

Previous studies confirmed that stromal cell-derived factor 1 (SDF-1) was a principal regulator of retention, migration and mobilization of haematopoietic stem cells and endothelial progenitor cells (EPCs) during steady-state homeostasis and injury. CXC chemokine receptor 4 (CXCR4) has been considered as the unique receptor of SDF-1 and as the only mediator of SDF-1-induced biological effects for many years. However, recent studies found that SDF-1 could bind to not only CXCR4 but also CXC chemokine receptor 7 (CXCR7). The evidence that SDF-1 binds to the CXCR7 raises a concern how to distinguish the potential contribution of the SDF-1/CXCR7 pathway from SDF-1/CXCR4 pathway in all the processes that were previously attributed to SDF-1/CXCR4. In this study, the role of CXCR7 in EPCs was investigated in vitro. RT-PCR, Western blot and flow cytometry assay demonstrate that both CXCR4 and CXCR7 were expressed highly in EPCs. The adhesion of EPCs induced by SDF-1 was inhibited by blocking either CXCR4 or CXCR7 with their antibodies or antagonists. SDF-1 regulated the migration of EPCs via CXCR4 but not CXCR7. However, the transendothelial migration of EPCs was inhibited by either blocking of CXCR4 or CXCR7. Both CXCR7 and CXCR4 are essential for the tube formation of EPCs induced by SDF-1. These results suggested that both CXCR7 and CXCR4 are important for EPCs in response to SDF-1, indicating that CXCR7 may be another potential target molecule for angiogenesis-dependent diseases.     

Micropilot: automation of fluorescence microscopy-based imaging for systems biology

Quantitative microscopy relies on imaging of large cell numbers but is often hampered by time-consuming manual selection of specific cells. The 'Micropilot' software automatically detects cells of interest and launches complex imaging experiments including three-dimensional multicolor time-lapse or fluorescence recovery after photobleaching in live cells. In three independent experimental setups this allowed us to statistically analyze biological processes in detail and is thus a powerful tool for systems biology.     

Computation of steady-state probability distributions in stochastic models of cellular networks

Cellular processes are "noisy". In each cell, concentrations of molecules are subject to random fluctuations due to the small numbers of these molecules and to environmental perturbations. While noise varies with time, it is often measured at steady state, for example by flow cytometry. When interrogating aspects of a cellular network by such steady-state measurements of network components, a key need is to develop efficient methods to simulate and compute these distributions. We describe innovations in stochastic modeling coupled with approaches to this computational challenge: first, an approach to modeling intrinsic noise via solution of the chemical master equation, and second, a convolution technique to account for contributions of extrinsic noise. We show how these techniques can be combined in a streamlined procedure for evaluation of different sources of variability in a biochemical network. Evaluation and illustrations are given in analysis of two well-characterized synthetic gene circuits, as well as a signaling network underlying the mammalian cell cycle entry.     

GC (Guanine‐Cytosine)‐Selective DNA‐Binding and Antitumor Activity of a Quercetin?Manganese(II) Complex

The DNA binding and cleavage properties of quercetin? manganese(II) complexes have been studied, but little attention has been devoted to the relationship between the antitumor activity of these complexes and the DNA‐binding properties. Here, the DNA binding properties of the quercetin? manganese(II) complex [Mn(Que)₂(H₂O)₂] were studied using UV/VIS and fluorescence spectroscopy and viscosity measurements. The results indicate that the complex was preferentially bound to DNA in the GC (guanine? cytosine)‐rich regions via an intercalative mode. Furthermore, the cytotoxicity experiments confirmed its apoptosis‐inducing activity. We also demonstrated that the levels of survivin protein expression in HepG2 cells decreased and that the relative activity of caspase‐3 significantly increased after treatment with the complex. Hence, our results suggest that the antitumor activity of the [Mn(Que)₂(H₂O)₂] complex might be related to its intercalation into DNA and its DNA‐binding selectivity.     

mTOR drives its own activation via SCF(βTrCP)-dependent degradation of the mTOR inhibitor DEPTOR

The activities of both mTORC1 and mTORC2 are negatively regulated by their endogenous inhibitor, DEPTOR. As such, the abundance of DEPTOR is a critical determinant in the activity status of the mTOR network. DEPTOR stability is governed by the 26S-proteasome through a largely unknown mechanism. Here we describe an mTOR-dependent phosphorylation-driven pathway for DEPTOR destruction via SCF(βTrCP). DEPTOR phosphorylation by mTOR in response to growth signals, and in collaboration with casein kinase I (CKI), generates a phosphodegron that binds βTrCP. Failure to degrade DEPTOR through either degron mutation or βTrCP depletion leads to reduced mTOR activity, reduced S6 kinase activity, and activation of autophagy to reduce cell growth. This work expands the current understanding of mTOR regulation by revealing a positive feedback loop involving mTOR and CKI-dependent turnover of its inhibitor, DEPTOR, suggesting that misregulation of the DEPTOR destruction pathway might contribute to aberrant activation of mTOR in disease.     

Genome-wide regulation of 5hmC, 5mC, and gene expression by Tet1 hydroxylase in mouse embryonic stem cells

DNA methylation at the 5 position of cytosine (5mC) in the mammalian genome is a key epigenetic event critical for various cellular processes. The ten-eleven translocation (Tet) family of 5mC-hydroxylases, which convert 5mC to 5-hydroxymethylcytosine (5hmC), offers a way for dynamic regulation of DNA methylation. Here we report that Tet1 binds to unmodified C or 5mC- or 5hmC-modified CpG-rich DNA through its CXXC domain. Genome-wide mapping of Tet1 and 5hmC reveals mechanisms by which Tet1 controls 5hmC and 5mC levels in mouse embryonic stem cells (mESCs). We also uncover a comprehensive gene network influenced by Tet1. Collectively, our data suggest that Tet1 controls DNA methylation both by binding to CpG-rich regions to prevent unwanted DNA methyltransferase activity, and by converting 5mC to 5hmC through hydroxylase activity. This Tet1-mediated antagonism of CpG methylation imparts differential maintenance of DNA methylation status at Tet1 targets, ultimately contributing to mESC differentiation and the onset of embryonic development.