Identification of miRNA signatures and their therapeutic potentials in prostate cancer

Molecular Biology Reports - Herein, we identified miRNA signatures that were able to differentiate malignant prostate cancer from benign prostate hyperplasia and revealed the therapeutic potential...     

Antifungal Effect of Long Noncoding RNA 9708-1 in the Vulvovaginal Candidiasis Murine Model

Mycopathologia - Vulvovaginal candidiasis (VVC) caused by Candida spp. affects 70–75% of women at least once during their lives. We aim to elucidate the potential mechanism of VVC and...     

RTKN-1/Rhotekin shields endosome-associated F-actin from disassembly to ensure endocytic recycling

Cargo sorting and the subsequent membrane carrier formation require a properly organized endosomal actin network. To better understand the actin dynamics during endocytic recycling, we performed a genetic screen in C. elegans and identified RTKN-1/Rhotekin as a requisite to sustain endosome-associated actin integrity. Loss of RTKN-1 led to a prominent decrease in actin structures and basolateral recycling defects. Furthermore, we showed that the presence of RTKN-1 thwarts the actin disassembly competence of UNC-60A/cofilin. Consistently, in RTKN-1–deficient cells, UNC-60A knockdown replenished actin structures and alleviated the recycling defects. Notably, an intramolecular interaction within RTKN-1 could mediate the formation of oligomers. Overexpression of an RTKN-1 mutant form that lacks self-binding capacity failed to restore actin structures and recycling flow in rtkn-1 mutants. Finally, we demonstrated that SDPN-1/Syndapin acts to direct the recycling endosomal dwelling of RTKN-1 and promotes actin integrity there. Taken together, these findings consolidated the role of SDPN-1 in organizing the endosomal actin network architecture and introduced RTKN-1 as a novel regulatory protein involved in this process.     

Visualization Analysis of CRISPR Gene-editing Knowledge Map based on Citespace

Biology Bulletin - CRISPR is an adaptive immune defense system found in bacteria and archaea that is resistant to heterologous invasive genetic material. Later studies showed that the CRISPR system...     

A Highlights from MBoC Selection: Serine 129 phosphorylation of membrane-associated α-synuclein modulates dopamine transporter function in a G protein–coupled receptor kinase–dependent manner

Most α-synuclein (α-syn) deposited in Lewy bodies, the pathological hallmark of Parkinson disease (PD), is phosphorylated at Ser-129. However, the physiological and pathological roles of this modification are unclear. Here we investigate the effects of Ser-129 phosphorylation on dopamine (DA) uptake in dopaminergic SH-SY5Y cells expressing α-syn. Subcellular fractionation of small interfering RNA (siRNA)–treated cells shows that G protein–coupled receptor kinase 3 (GRK3), GRK5, GRK6, and casein kinase 2 (CK2) contribute to Ser-129 phosphorylation of membrane-associated α-syn, whereas cytosolic α-syn is phosphorylated exclusively by CK2. Expression of wild-type α-syn increases DA uptake, and this effect is diminished by introducing the S129A mutation into α-syn. However, wild-type and S129A α-syn equally increase the cell surface expression of dopamine transporter (DAT) in SH-SY5Y cells and nonneuronal HEK293 cells. In addition, siRNA-mediated knockdown of GRK5 or GRK6 significantly attenuates DA uptake without altering DAT cell surface expression, whereas knockdown of CK2 has no effect on uptake. Taken together, our results demonstrate that membrane-associated α-syn enhances DA uptake capacity of DAT by GRKs-mediated Ser-129 phosphorylation, suggesting that α-syn modulates intracellular DA levels with no functional redundancy in Ser-129 phosphorylation between GRKs and CK2.     

An orthotropic viscoelastic material model for passive myocardium: theory and algorithmic treatment

This contribution presents a novel constitutive model in order to simulate an orthotropic rate-dependent behaviour of the passive myocardium at finite strains. The motivation for the consideration of orthotropic viscous effects in a constitutive level lies in the disagreement between theoretical predictions and experimentally observed results. In view of experimental observations, the material is deemed as nearly incompressible, hyperelastic, orthotropic and viscous. The viscoelastic response is formulated by means of a rheological model consisting of a spring coupled with a Maxwell element in parallel. In this context, the isochoric free energy function is decomposed into elastic equilibrium and viscous non-equilibrium parts. The baseline elastic response is modelled by the orthotropic model of Holzapfel and Ogden [Holzapfel GA, Ogden RW. 2009. Constitutive modelling of passive myocardium: a structurally based framework for material characterization. Philos Trans Roy Soc A Math Phys Eng Sci. 367:3445–3475]. The essential aspect of the proposed model is the account of distinct relaxation mechanisms for each orientation direction. To this end, the non-equilibrium response of the free energy function is constructed in the logarithmic strain space and additively decomposed into three anisotropic parts, denoting fibre, sheet and normal directions each accompanied by a distinct dissipation potential governing the evolution of viscous strains associated with each orientation direction. The evolution equations governing the viscous flow have an energy-activated nonlinear form. The energy storage in the Maxwell branches has a quadratic form leading to a linear stress–strain response in the logarithmic strain space. On the numerical side, the algorithmic aspects suitable for the implicit finite element method are discussed in a Lagrangian setting. The model shows excellent agreement compared to experimental data obtained from the literature. Furthermore, the finite element simulations of a heart cycle carried out with the proposed model show significant deviations in the strain field relative to the elastic solution.     

Properties of MHC Class I Presented Peptides That Enhance Immunogenicity

T-cells have to recognize peptides presented on MHC molecules to be activated and elicit their effector functions. Several studies demonstrate that some peptides are more immunogenic than others and therefore more likely to be T-cell epitopes. We set out to determine which properties cause such differences in immunogenicity. To this end, we collected and analyzed a large set of data describing the immunogenicity of peptides presented on various MHC-I molecules. Two main conclusions could be drawn from this analysis: First, in line with previous observations, we showed that positions P4–6 of a presented peptide are more important for immunogenicity. Second, some amino acids, especially those with large and aromatic side chains, are associated with immunogenicity. This information was combined into a simple model that was used to demonstrate that immunogenicity is, to a certain extent, predictable. This model (made available at http://tools.iedb.org/immunogenicity/) was validated with data from two independent epitope discovery studies. Interestingly, with this model we could show that T-cells are equipped to better recognize viral than human (self) peptides. After the past successful elucidation of different steps in the MHC-I presentation pathway, the identification of variables that influence immunogenicity will be an important next step in the investigation of T-cell epitopes and our understanding of cellular immune responses.     

Prediction of Drug-Target Interactions for Drug Repositioning Only Based on Genomic Expression Similarity

Small drug molecules usually bind to multiple protein targets or even unintended off-targets. Such drug promiscuity has often led to unwanted or unexplained drug reactions, resulting in side effects or drug repositioning opportunities. So it is always an important issue in pharmacology to identify potential drug-target interactions (DTI). However, DTI discovery by experiment remains a challenging task, due to high expense of time and resources. Many computational methods are therefore developed to predict DTI with high throughput biological and clinical data. Here, we initiatively demonstrate that the on-target and off-target effects could be characterized by drug-induced in vitro genomic expression changes, e.g. the data in Connectivity Map (CMap). Thus, unknown ligands of a certain target can be found from the compounds showing high gene-expression similarity to the known ligands. Then to clarify the detailed practice of CMap based DTI prediction, we objectively evaluate how well each target is characterized by CMap. The results suggest that (1) some targets are better characterized than others, so the prediction models specific to these well characterized targets would be more accurate and reliable; (2) in some cases, a family of ligands for the same target tend to interact with common off-targets, which may help increase the efficiency of DTI discovery and explain the mechanisms of complicated drug actions. In the present study, CMap expression similarity is proposed as a novel indicator of drug-target interactions. The detailed strategies of improving data quality by decreasing the batch effect and building prediction models are also effectively established. We believe the success in CMap can be further translated into other public and commercial data of genomic expression, thus increasing research productivity towards valid drug repositioning and minimal side effects.