SPIC: A novel similarity metric for comparing transcription factor binding site motifs based on information contents

BACKGROUND: Discovering transcription factor binding sites (TFBS) is one of primary challenges to decipher complex gene regulatory networks encrypted in a genome. A set of short DNA sequences identified by a transcription factor (TF) is known as a motif, which can be expressed accurately in matrix form such as a position-specific scoring matrix (PSSM) and a position frequency matrix. Very frequently, we need to query a motif in a database of motifs by seeking its similar motifs, merge similar TFBS motifs possibly identified by the same TF, separate irrelevant motifs, or filter out spurious motifs. Therefore, a novel metric is required to seize slight differences between irrelevant motifs and highlight the similarity between motifs of the same group in all these applications. While there are already several metrics for motif similarity proposed before, their performance is still far from satisfactory for these applications. METHODS: A novel metric has been proposed in this paper with name as SPIC (Similarity with Position Information Contents) for measuring the similarity between a column of a motif and a column of another motif. When defining this similarity score, we consider the likelihood that the column of the first motif's PFM can be produced by the column of the second motif's PSSM, and multiply the likelihood by the information content of the column of the second motif's PSSM, and vise versa. We evaluated the performance of SPIC combined with a local or a global alignment method having a function for affine gap penalty, for computing the similarity between two motifs. We also compared SPIC with seven existing state-of-the-arts metrics for their capability of clustering motifs from the same group and retrieving motifs from a database on three datasets. RESULTS: When used jointly with the Smith-Waterman local alignment method with an affine gap penalty function (gap open penalty is equal to1, gap extension penalty is equal to 0.5), SPIC outperforms the seven existing state-of-the-art motif similarity metrics combined with their best alignments for matching motifs in database searches, and clustering the same TF's sub-motifs or distinguishing relevant ones from a miscellaneous group of motifs. CONCLUSIONS: We have developed a novel motif similarity metric that can more accurately match motifs in database searches, and more effectively cluster similar motifs and differentiate irrelevant motifs than do the other seven metrics we are aware of

Antidiabetic Activity and Potential Mechanism of Amentoflavone in Diabetic Mice

Aim: To investigate the anti-diabetic activity of amentoflavone (AME) in diabetic mice, and to explore the potential mechanisms. Methods: Diabetic mice induced by high fat diet and streptozotocin were administered with amentoflavone for 8 weeks. Biochemical indexes were tested to evaluate its anti-diabetic effect. Hepatic steatosis, the histopathology change of the pancreas was evaluated. The activity of glucose metabolic enzymes, the expression of Akt and pAkt, and the glucose transporter type 4 (GLUT4) immunoreactivity were detected. Results: AME decreased the level of glucose, total cholesterol (TC), triglyceride (TG), low density lipoprotein cholesterol (LDL-C) and glucagon, and increased the levels of high density lipoprotein cholesterol (HDL-C) and insulin. Additionally, AME increased the activity of glucokinase (GCK), phosphofructokinase-1 (PFK-1), and pyruvate kinase (PK), and inhibited the activity of glycogen synthase kinase-3 (GSK-3), phosphoenolpyruvate carboxykinase (PEPCK), and glucose-6-phosphatase (G-6-Pase). Mechanistically, AME increased superoxide dismutase (SOD), decreased malondialdehyde (MDA), activation of several key signaling molecules including pAkt (Ser473), and increased the translocation to the sedimenting membranes of GLUT4 in skeletal muscle tissue. Conclusions: AME exerted anti-diabetic effects by regulating glucose and lipid metabolism, perhaps via anti-oxidant effects and activating the PI3K/Akt pathway. Our study provided novel insight into the role and underlying mechanisms of AME in diabetes

Synthesis of taurine–fluorescein conjugate and evaluation of its retina-targeted efficiency in vitro

In this work, retinal penetration of fluorescein was achieved in vitro by covalent attachment of taurine to fluorescein, yielding the F–Tau conjugate. Nuclear magnetic resonance (NMR) and high resolution mass spectrometry (HRMS) were used to confirm the successful synthesis of F–Tau. The cellular uptake of F–Tau in adult retinal pigment epithelial cells (ARPE-19) and human retinal microvascular endothelial cells (hRMECs) was visualized via confocal scanning microscopy. The results indicated an improvement of solubility and a reduction of logP of F–Tau compared with fluorescein. As compared with fluorescein, F–Tau showed little toxicity, and was retained longer by cells in uptake experiments. F–Tau also displayed higher transepithelial permeabilities than fluorescein in ARPE-19 and hRMECs monolayer cells (P<0.05). These results showed that taurine may be a useful ligand for targeting small-molecule hydrophobic pharmaceuticals into the retina

Intron Lariat RNA Inhibits MicroRNA Biogenesis by Sequestering the Dicing Complex in <i>Arabidopsis</i>

<div><p>Lariat RNAs formed as by-products of splicing are quickly degraded by the RNA debranching enzyme 1 (DBR1), leading to their turnover. Null <i>dbr1</i> mutants in both animals and plants are embryo lethal, but the mechanism underlying the lethality remains unclear. Here we characterized a weak mutant allele of <i>DBR1</i> in <i>Arabidopsis</i>, <i>dbr1-2</i>, and showed that a global increase in lariat RNAs was unexpectedly accompanied by a genome-wide reduction in miRNA accumulation. The <i>dbr1-2</i> mutation had no effects on expression of miRNA biogenesis genes or primary miRNAs (pri-miRNAs), but the association of pri-miRNAs with the DCL1/HYL1 dicing complex was impaired. Lariat RNAs were associated with the DCL1/HYL1 dicing complex <i>in vivo</i> and competitively inhibited the binding of HYL1 with pri-miRNA. Consistent with the impacts of lariat RNAs on miRNA biogenesis, over-expression of lariat RNAs reduced miRNA accumulation. Lariat RNAs localized in nuclear bodies, and partially co-localize with HYL1, and both DCL1 and HYL1 were mis-localized in <i>dbr1-2</i>. Together with our findings that nearly four hundred lariat RNAs exist in wild type plants and that these lariat RNAs also associate with the DCL1/HYL1 dicing complex <i>in vivo</i>, we thus propose that lariat RNAs, as decoys, inhibit miRNA processing, suggesting a hitherto unknown layer of regulation in miRNA biogenesis.</p></div

A Model for lariat RNA inhibits miRNA biogenesis in plants.

<p>Pri-miRNAs are specifically recruited to the DCL1/HYL1 complex (blue indicated) for processing. In wild type plants, most lariat RNAs (indicated in purple) are quickly debranched by DBR1, only a small portion of lariat RNAs (indicated in red) naturally escapes debranching, also associates with the DCL1/HYL1 complex. In contrast, in <i>dbr1-2</i>, over-accumulated lariat RNAs might be recognized by the DCL1/HYL1 complex, and thus attenuate the association between the DCL1/HYL1 complex and pri-miRNAs, producing less miRNA.</p

DBR1 is required for miRNA accumulation.

<p>(A) Morphological phenotypes of Col-0 and <i>dbr1-2</i> plants. DBR1-GFP <i>dbr1-2</i>, DBR1-RFP <i>dbr1-2</i>, and DBR1-Flag <i>dbr1-2</i> represent rescued lines of <i>dbr1-2</i> with different protein fusion constructs driven by the native <i>DBR1</i> promoter. (B) miRNA northern blot analysis in Col-0, <i>dbr1-2</i>, and a <i>dbr1-2</i> transgenic line containing the <i>pDBR1</i>::<i>DBR1-RFP</i> transgene (Compl). The numbers indicate the relative abundance of miRNAs among the three genotypes and represent the mean of three repeats (P < 0.05). U6 was used as a loading control. (C) Deep sequencing analysis of miRNAs in Col-0 and <i>dbr1-2</i>. Small RNA libraries were generated from inflorescences of two biological replicates. The normalized abundances of miRNAs were calculated as reads per ten million (RPTM), and log2-transformed ratios of <i>dbr1-2</i>/Col-0 were plotted. Each circle represents one miRNA. Thick lines indicate mean values. Rep1 and Rep2 denote replicate 1 and replicate 2, respectively.</p

DCL1 and HYL1 are mis-localized in <i>dbr1-2</i> mutants.

<p>(A-B) Subnuclear localization of DCL1 (A) and HYL1 (B) in Col-0 and <i>dbr1-2</i> root cells. Right panels show the percentage distribution of dicing bodies per cell. The X-axis represents the number of dicing bodies per cell, and the Y-axis represents the percentage of cells with the corresponding numbers. “n” represents the numbers of analyzed cells. (C) Morphological phenotypes of the <i>hyl1-2</i> and the <i>dbr1-2 hyl1-2</i> double mutant. Pictures were taken of 5-week-old plants. (D) Expression levels of indicated pri-miRNAs in Col-0, <i>dbr1-2</i>, <i>hyl1-2</i>, and <i>dbr1-2 hyl1-2</i> plants by qRT-PCR. <i>UBQ5</i> was used as an internal control and for normalization of the data. Standard deviations were calculated from three technical replicates. The results shown were reproduced with three biological replicates. Scale bars = 10 μm.</p

Subcellular localization of DBR1 and lariat RNA.

<p>(A) Subcellular localization of <i>Arabidopsis</i> DBR1. 35S::DBR1-RFP was transiently expression in tobacco leaves and RFP signal was observed after 48 hr. Roots from 35S::DBR1-GFP transgenic plants were observed under the GFP channel. (B) Strategy to visualize lariat RNAs in live cells. The MS2 sequence (indicated as stem-loops) was inserted into a lariat24a-located intron. A co-expressed GFP-tagged MS2-CP protein was used to visualize lariat RNAs. Grey boxes indicate exons, and lines indicate the intron. (C) Genomic DNA of lariat24a and lariat41 was fused to 6XMS2 repeats and co-infiltrated into tobacco leaves with MS2-CP-GFP and HYL1-RFP. The genomic DNA of pri-miR163 was used as the positive control. Scale bars = 10 μm.</p