Clock controls timing of mouse pancreatic differentiation through regulation of Wnt- and Notch-based and cell division components

The oscillations of circadian genes control the daily circadian clock, regulating a diverse array of physiologies with the 24-hour light/dark cue across a wide variety of organisms. Here we first show that before embryonic circadian rhythms occur, the oscillation (nucleocytoplasmic shuttling) of core circadian gene Clock is tissue-specific and correlated with the state of differentiation during both early development and later pancreas organogenesis. Disruption of Clock as well as Timeless in the embryonic pancreas does not block pancreatic differentiation but alters the balance and maturity of endocrine and exocrine cells. Molecular analysis indicates that inhibition of Clock or Timeless expression disturbs not only cell cycle regulators, but also Wnt- and Notch-signaling components, whose oscillations establish the timing mechanism in somitogenesis. Thus, our results provide new insights about circadian genes' function in control of the timing of differentiation during embryonic development.     

Anti-atherosclerotic effects of sirolimus on human vascular smooth muscle cells

Sirolimus is a potent immunosuppressive agent and has an anti-atherosclerotic effect through its anti-proliferative property. The present study was undertaken to investigate the effect of sirolimus on intracellular cholesterol homeostasis in human vascular smooth muscle cells (VSMCs) in the presence of inflammatory cytokine IL-1 beta. We explored the effect of sirolimus on the lipid accumulation of VSMCs in the presence of IL-1 beta, using Oil Red O staining and quantitative measurement of intracellular cholesterol. The effect of sirolimus on the gene and protein expression of lipoprotein receptors and ATP binding cassettes (ABCA1 and ABCG1) was examined by real-time PCR and Western blotting, respectively. Furthermore, the effect of sirolimus on cholesterol efflux from VSMCs in the presence or absence of IL-1 beta was also investigated using [(3)H] cholesterol efflux. Finally, we examined the effect of sirolimus on the production of inflammatory cytokines in VSMCs using ELISA. Sirolimus reduced intracellular lipid accumulation in VSMCs mediated by IL-1 beta possibly due to the reduction of expression of low-density lipoprotein (LDL) and very low-density lipoprotein (VLDL) receptors. Sirolimus increased cholesterol efflux from VSMCs and overrode the suppression of cholesterol efflux induced by IL-1 beta. Sirolimus also increased ABCA1 and ABCG1 genes expression, even in the presence of IL-1 beta. We further confirmed that sirolimus inhibited mRNA and protein expression of inflammatory cytokines IL-6, tumor necrosis factor-alpha, IL-8, and monocyte chemoattractant protein-1. Inhibition of lipid uptake together with increasing cholesterol efflux and the inhibition of inflammatory cytokines are all important aspects of the anti-atherosclerotic effects of sirolimus on VSMCs.     

Functional expression and purification of bovine enterokinase light chain in recombinant Escherichia coli

Enterokinase (EC 3.4.21.9) is a serine proteinase of the intestinal brush border that exhibits specificity for the sequence (Asp)(4)-Lys and converts trypsinogen into its active form, trypsin. A codon optimized sequence coding light chain (catalytic subunit) of bovine enterokinase gene (sBEKLC) was synthesized, and it was fused with DsbA to construct the expression vector (pET39-sBEKLC). Then, the plasmid was transformed into E. coli BL21 (DE3) for expression. Under optimal conditions, the volumetric productivity of fusion protein reached 151.2 mg L(-1), i.e., 80.6 mg sBEKLC L(-1). The cold osmotic shock technique was successfully used to extract sBEKLC from periplasmic space, and nickel affinity chromatography was employed to obtain mature sBEKLC. Finally, about 6.8 mg of bioactive sBEKLC was purified from 1 liter fermentation broth and could be used to cleave one tested fusion protein with an inter-domain enteropeptidase recognition site. This work will be helpful for large-scale production of this increasingly demanded enterokinase.     

Prediction of protein secondary structure content for the twilight zone sequences

Secondary protein structure carries information about local structural arrangements, which include three major conformations: alpha-helices, beta-strands, and coils. Significant majority of successful methods for prediction of the secondary structure is based on multiple sequence alignment. However, multiple alignment fails to provide accurate results when a sequence comes from the twilight zone, that is, it is characterized by low (<30%) homology. To this end, we propose a novel method for prediction of secondary structure content through comprehensive sequence representation, called PSSC-core. The method uses a multiple linear regression model and introduces a comprehensive feature-based sequence representation to predict amount of helices and strands for sequences from the twilight zone. The PSSC-core method was tested and compared with two other state-of-the-art prediction methods on a set of 2187 twilight zone sequences. The results indicate that our method provides better predictions for both helix and strand content. The PSSC-core is shown to provide statistically significantly better results when compared with the competing methods, reducing the prediction error by 5-7% for helix and 7-9% for strand content predictions. The proposed feature-based sequence representation uses a comprehensive set of physicochemical properties that are custom-designed for each of the helix and strand content predictions. It includes composition and composition moment vectors, frequency of tetra-peptides associated with helical and strand conformations, various property-based groups like exchange groups, chemical groups of the side chains and hydrophobic group, auto-correlations based on hydrophobicity, side-chain masses, hydropathy, and conformational patterns for beta-sheets. The PSSC-core method provides an alternative for predicting the secondary structure content that can be used to validate and constrain results of other structure prediction methods. At the same time, it also provides useful insight into design of successful protein sequence representations that can be used in developing new methods related to prediction of different aspects of the secondary protein structure.     

The different roles of cyclinD1-CDK4 in STP and mGluR-LTD during the postnatal development in mice hippocampus area CA1

Background

The extraembryonic tissues, visceral endoderm (VE) and extraembryonic ectoderm (ExE) are known to be important for the induction of primordial germ cells (PGCs) in mice via activation of the bone morphogenetic protein (BMP) signalling pathway. We investigated whether the VE and ExE have a direct role in the specification of PGCs, or in an earlier event, namely the induction of the PGC precursors in the proximal posterior epiblast cells.

Results

We cultured embryonic day (E) 5.75 to E7.0 mouse embryos in an explant-assay with or without extraembryonic tissues. The reconstituted pieces of embryonic and extraembryonic tissues were assessed for the formation of both PGC precursors and specified PGCs. For this, Blimp1:gfp and Stella:gfp transgenic mouse lines were used to distinguish between PGC precursors and specified PGC, respectively. We observed that the VE regulates formation of an appropriate number of PGC precursors between E6.25–E7.25, but it is not essential for the subsequent specification of PGCs from the precursor cells. Furthermore, we show that the ExE has a different role from that of the VE, which is to restrict localization of PGC precursors to the posterior part of the embryo.

Conclusion

We show that the VE and ExE have distinct roles in the induction of PGC precursors, namely the formation of a normal number of PGC precursors, and their appropriate localization during early development. However, these tissues do not have a direct role during the final stages of specification of the founder population of PGCs.     

Prediction of flexible/rigid regions from protein sequences using k-spaced amino acid pairs

Background

Traditionally, it is believed that the native structure of a protein corresponds to a global minimum of its free energy. However, with the growing number of known tertiary (3D) protein structures, researchers have discovered that some proteins can alter their structures in response to a change in their surroundings or with the help of other proteins or ligands. Such structural shifts play a crucial role with respect to the protein function. To this end, we propose a machine learning method for the prediction of the flexible/rigid regions of proteins (referred to as FlexRP); the method is based on a novel sequence representation and feature selection. Knowledge of the flexible/rigid regions may provide insights into the protein folding process and the 3D structure prediction.

Results

The flexible/rigid regions were defined based on a dataset, which includes protein sequences that have multiple experimental structures, and which was previously used to study the structural conservation of proteins. Sequences drawn from this dataset were represented based on feature sets that were proposed in prior research, such as PSI-BLAST profiles, composition vector and binary sequence encoding, and a newly proposed representation based on frequencies of k-spaced amino acid pairs. These representations were processed by feature selection to reduce the dimensionality. Several machine learning methods for the prediction of flexible/rigid regions and two recently proposed methods for the prediction of conformational changes and unstructured regions were compared with the proposed method. The FlexRP method, which applies Logistic Regression and collocation-based representation with 95 features, obtained 79.5% accuracy. The two runner-up methods, which apply the same sequence representation and Support Vector Machines (SVM) and Naïve Bayes classifiers, obtained 79.2% and 78.4% accuracy, respectively. The remaining considered methods are characterized by accuracies below 70%. Finally, the Naïve Bayes method is shown to provide the highest sensitivity for the prediction of flexible regions, while FlexRP and SVM give the highest sensitivity for rigid regions.

Conclusion

A new sequence representation that uses k-spaced amino acid pairs is shown to be the most efficient in the prediction of the flexible/rigid regions of protein sequences. The proposed FlexRP method provides the highest prediction accuracy of about 80%. The experimental tests show that the FlexRP and SVM methods achieved high overall accuracy and the highest sensitivity for rigid regions, while the best quality of the predictions for flexible regions is achieved by the Naïve Bayes method.     

Electroacupuncture Ameliorates Cognitive Impairment Through the Inhibition of NLRP3 Inflammasome Activation by Regulating Melatonin-Mediated Mitophagy in Stroke Rats

Neurochemical Research - Previous studies found that electroacupuncture (EA) at the Shenting (DU24) and Baihui (DU20) acupoints alleviates cognitive impairment in cerebral...