Adaptations of Malus domestica Borkh. (Rosaceae) Fruits Grown at Different Altitudes

Russian Journal of Plant Physiology - Cytophysiological adaptive features of apple fruits (Malus domestica Borkh.) were examined as a function of growth altitude—300, 500, 700, and 1200 m...     

Eukaryotic class 1 translation termination factor eRF1--the NMR structure and dynamics of the middle domain involved in triggering ribosome-dependent peptidyl-tRNA hydrolysis

The eukaryotic class 1 polypeptide chain release factor is a three-domain protein involved in the termination of translation, the final stage of polypeptide biosynthesis. In attempts to understand the roles of the middle domain of the eukaryotic class 1 polypeptide chain release factor in the transduction of the termination signal from the small to the large ribosomal subunit and in peptidyl-tRNA hydrolysis, its high-resolution NMR structure has been obtained. The overall fold and the structure of the beta-strand core of the protein in solution are similar to those found in the crystal. However, the orientation of the functionally critical GGQ loop and neighboring alpha-helices has genuine and noticeable differences in solution and in the crystal. Backbone amide protons of most of the residues in the GGQ loop undergo fast exchange with water. However, in the AGQ mutant, where functional activity is abolished, a significant reduction in the exchange rate of the amide protons has been observed without a noticeable change in the loop conformation, providing evidence for the GGQ loop interaction with water molecule(s) that may serve as a substrate for the hydrolytic cleavage of the peptidyl-tRNA in the ribosome. The protein backbone dynamics, studied using 15N relaxation experiments, showed that the GGQ loop is the most flexible part of the middle domain. The conformational flexibility of the GGQ and 215-223 loops, which are situated at opposite ends of the longest alpha-helix, could be a determinant of the functional activity of the eukaryotic class 1 polypeptide chain release factor, with that helix acting as the trigger to transmit the signals from one loop to the other.     

Cellular laminin-binding protein and Venezuelan equine encephalomyelitis virus replication in Vero, 293 and 9S2 cells

The expression of the laminin-binding protein (LBP) on cellular membranes in different cell lines has been studied. A high level of replication of Venezuelan equine encephalomyelitis (VEE) virus was registered in Vero cells with high levels of LBP on the cell surface. The treatment of Vero cells with monoclonal antibodies to human LBP reduced VEE virus replication by a factor of more than 200. A low level of LBP expression on the surface of 293 cells was increased via transfection by plasmid with gene for human LBP. The VEE virus replication in transfected cells (9S2) was increased by more that 2000 times compared to the 293 cells. The results demonstrated the principal role of cellular LBP in the entry of VEE virus into mammalian cells. It is proposed that LBP is a key cellular protein for the early stage of the VEE virus replication in cells. LBP may be a target protein for the development of a new generation of antiviral drugs capable of inhibiting (enhancing) the alphavirus replication in human cells.     

shRNA knockdown of Bmi-1 reveals a critical role for p21-Rb pathway in NSC self-renewal during development

Knockout studies have shown that the polycomb gene Bmi-1 is important for postnatal, but not embryonic, neural stem cell (NSC) self-renewal and have identified the cell-cycle inhibitors p16/p19 as molecular targets. Here, using lentiviral-delivered shRNAs in vitro and in vivo, we determined that Bmi-1 is also important for NSC self-renewal in the embryo. We found that neural progenitors depend increasingly on Bmi-1 for proliferation as development proceeds from embryonic through adult stages. Acute shRNA-mediated Bmi-1 reduction causes defects in embryonic and adult NSC proliferation and self-renewal that, unexpectedly, are mediated by a different cell-cycle inhibitor, p21. Gene array analyses revealed developmental differences in Bmi-1-controlled expression of genes in the p21-Rb cell cycle regulatory pathway. Our data therefore implicate p21 as an important Bmi-1 target in NSCs, potentially with stage-related differences. Understanding stage-related mechanisms underlying NSC self-renewal has important implications for development of stem cell-based therapies.     

The Electromotive Protein Prestin as a Sensitive Core of the Fluorescent Voltage Indicator

Russian Journal of Bioorganic Chemistry - In this study, we first used prestin, an electromotive protein of the mammalian auditory analyzer, as a voltage-sensitive core of a genetically encoded...     

An Adiabatic Calorimetry Method to Determine the Thermodynamic Characteristics of Cryoprotectants

Biophysics - Abstract—The efficiency of cryoprotectants used to protect cells from damage is usually evaluated by the changes in vital cell parameters after a freezing–thawing cycle....     

The Generation of Superoxide Radicals by Cardiac Mitochondria and the Antioxidant Effect of the Water-Soluble Form of Ubiquinol-10

Biophysics - We have studied the effect of the water-soluble form of ubiquinol-10 (CoQ10-H2) on the processes of electron transport, oxidative phosphorylation, and the formation of reactive oxygen...     

Deeplasmid: deep learning accurately separates plasmids from bacterial chromosomes

Plasmids are mobile genetic elements that play a key role in microbial ecology and evolution by mediating horizontal transfer of important genes, such as antimicrobial resistance genes. Many microbial genomes have been sequenced by short read sequencers and have resulted in a mix of contigs that derive from plasmids or chromosomes. New tools that accurately identify plasmids are needed to elucidate new plasmid-borne genes of high biological importance. We have developed Deeplasmid, a deep learning tool for distinguishing plasmids from bacterial chromosomes based on the DNA sequence and its encoded biological data. It requires as input only assembled sequences generated by any sequencing platform and assembly algorithm and its runtime scales linearly with the number of assembled sequences. Deeplasmid achieves an AUC–ROC of over 89%, and it was more accurate than five other plasmid classification methods. Finally, as a proof of concept, we used Deeplasmid to predict new plasmids in the fish pathogen Yersinia ruckeri ATCC 29473 that has no annotated plasmids. Deeplasmid predicted with high reliability that a long assembled contig is part of a plasmid. Using long read sequencing we indeed validated the existence of a 102 kb long plasmid, demonstrating Deeplasmid''s ability to detect novel plasmids.     

Maximum antigen diversification in a lyme bacterial population and evolutionary strategies to overcome pathogen diversity

Natural populations of pathogens and their hosts are engaged in an arms race in which the pathogens diversify to escape host immunity while the hosts evolve novel immunity. This co-evolutionary process poses a fundamental challenge to the development of broadly effective vaccines and diagnostics against a diversifying pathogen. Based on surveys of natural allele frequencies and experimental immunization of mice, we show high antigenic specificities of natural variants of the outer surface protein C (OspC), a dominant antigen of a Lyme Disease-causing bacterium (Borrelia burgdorferi). To overcome the challenge of OspC antigenic diversity to clinical development of preventive measures, we implemented a number of evolution-informed strategies to broaden OspC antigenic reactivity. In particular, the centroid algorithm—a genetic algorithm to generate sequences that minimize amino-acid differences with natural variants—generated synthetic OspC analogs with the greatest promise as diagnostic and vaccine candidates against diverse Lyme pathogen strains co-existing in the Northeast United States. Mechanistically, we propose a model of maximum antigen diversification (MAD) mediated by amino-acid variations distributed across the hypervariable regions on the OspC molecule. Under the MAD hypothesis, evolutionary centroids display broad cross-reactivity by occupying the central void in the antigenic space excavated by diversifying natural variants. In contrast to vaccine designs based on concatenated epitopes, the evolutionary algorithms generate analogs of natural antigens and are automated. The novel centroid algorithm and the evolutionary antigen designs based on consensus and ancestral sequences have broad implications for combating diversifying pathogens driven by pathogen–host co-evolution.Subject terms: Population genetics, Bacterial genetics