Biophysical and transfection studies of an amine-modified poly(vinyl alcohol) for gene delivery

Novel, multifunctional polymers remain an attractive objective for drug delivery, especially for hydrophilic macromolecular drugs candidates such as peptides, proteins, RNA, and DNA. To facilitate intracellular delivery of DNA, new amine-modified poly(vinyl alcohol)s (PVAs) were synthesized by a two-step process using carbonyl diimidazole activated diamines to produce PVAs with different degrees of amine substitution. The resulting polymers were characterized using NMR, thermogravimetric analysis (TGA), and gelpermation chromatography (GPC). Atomic force microscopy (AFM), dynamic light scattering photon correlation spectroscopy (PCS), and zeta-potential were used to investigate polyplexes of DNA with PVA copolymers. These studies suggest an influence of the polycation structure on the morphology of condensed DNA in polyplexes. Significant differences were observed by changing both the degrees of amine substitution and the structure of the PVA backbone, demonstrating that both electrostatic and hydrophobic interactions affect DNA condensation. DNA condensation measured by an ethidium bromide intercalation assay showed a higher degree of condensation with pDNA with increasing degrees of amine substitution and more hydrophobic functional groups. These findings are in line with transfection experiments, in which a good uptake of these polymer DNA complexes was noted, unfortunately, with little endosomal escape. Co-administration of chloroquine resulted in increased endosomal escape and higher transfection efficiencies, due to disruption of the endosomal membrane. In this study, the structural requirements for DNA complexation and condensation were characterized to provide a basis for rational design of nonviral gene delivery systems.     

Distinct roles in folding, CD81 receptor binding and viral entry for conserved histidine residues of hepatitis C virus glycoprotein E1 and E2

The protonation of histidine in acidic environments underpins its role in regulating the function of pH-sensitive proteins. For pH-sensitive viral fusion proteins, histidine protonation in the endosome leads to the activation of their membrane fusion function. The HCV (hepatitis C virus) glycoprotein E1-E2 heterodimer mediates membrane fusion within the endosome, but the roles of conserved histidine residues in the formation of a functional heterodimer and in sensing pH changes is unknown. We examined the functional roles of conserved histidine residues located within E1 and E2. The E1 mutations, H222A/R, H298R and H352A, disrupted E1-E2 heterodimerization and reduced virus entry. A total of five out of six histidine residues located within the E2 RBD (receptor-binding domain) were important for the E2 fold, and their substitution with arginine or alanine caused aberrant heterodimerization and/or CD81 binding. Distinct roles in E1-E2 heterodimerization and in virus entry were identified for His691 and His693 respectively within the membrane-proximal stem region. Viral entry and cell-cell fusion at neutral and low pH values were enhanced with H445R, indicating that the protonation state of His445 is a key regulator of HCV fusion. However, H445R did not overcome the block to virus entry induced by bafilomycin A1, indicating a requirement for an endosomal activation trigger in addition to acidic pH.     

Gauging a hydrocarbon ruler by an intrinsic exciton probe

The structural basis of lipid acyl-chain selection by membrane-intrinsic enzymes is poorly understood because most integral membrane enzymes of lipid metabolism have proven refractory to structure determination; however, robust enzymes from the outer membranes of gram-negative bacteria are now providing a first glimpse at the underlying mechanisms. The methylene unit resolution of the phospholipid:lipid A palmitoyltransferase PagP is determined by the hydrocarbon ruler, a 16-carbon saturated acyl-chain-binding pocket buried within the transmembrane beta-barrel structure. Substitution of Gly88 lining the floor of the hydrocarbon ruler with Ala or Met makes the enzyme select specifically 15- or 12-carbon saturated acyl chains, respectively, indicating that hydrocarbon ruler depth determines acyl-chain selection. However, the Gly88Cys PagP resolution does not diminish linearly because it selects both 14- and 15-carbon saturated acyl chains. We discovered that an exciton, emanating from a buried Tyr26-Trp66 phenol-indole interaction, is extinguished by a local structural perturbation arising from the proximal Gly88Cys PagP sulfhydryl group. Site-specific S-methylation of the single Cys afforded Gly88Cys-S-methyl PagP, which reasserted both the exciton and methylene unit resolution by specifically selecting 13-carbon saturated acyl chains for transfer to lipid A. Unlike the other Gly88 substitutions, the Cys sulfhydryl group recedes from the hydrocarbon ruler floor and locally perturbs the subjacent Tyr26 and Trp66 aromatic rings. The resulting hydrocarbon ruler expansion thus occurs at the exciton's expense and accommodates an extra methylene unit in the selected acyl chain. The hydrocarbon ruler-exciton juxtaposition endows PagP with a molecular gauge for probing the structural basis of lipid acyl-chain selection in a membrane-intrinsic environment.     

Influence of Feature Encoding and Choice of Classifier on Disease Risk Prediction in Genome-Wide Association Studies

Various attempts have been made to predict the individual disease risk based on genotype data from genome-wide association studies (GWAS). However, most studies only investigated one or two classification algorithms and feature encoding schemes. In this study, we applied seven different classification algorithms on GWAS case-control data sets for seven different diseases to create models for disease risk prediction. Further, we used three different encoding schemes for the genotypes of single nucleotide polymorphisms (SNPs) and investigated their influence on the predictive performance of these models. Our study suggests that an additive encoding of the SNP data should be the preferred encoding scheme, as it proved to yield the best predictive performances for all algorithms and data sets. Furthermore, our results showed that the differences between most state-of-the-art classification algorithms are not statistically significant. Consequently, we recommend to prefer algorithms with simple models like the linear support vector machine (SVM) as they allow for better subsequent interpretation without significant loss of accuracy.     

Regional variation in pathogen prevalence predicts endorsement of group-focused moral concerns

According to Moral Foundations Theory, people endorse “individualizing” foundations (Harm/care, Fairness/reciprocity) or “binding” foundations (Ingroup/loyalty, Authority/respect, Purity/sanctity) to varying degrees. As societies with higher pathogen prevalence have been found to exhibit more pronounced antipathogen psychological tendencies and cultural practices (e.g., conformity, collectivism), we hypothesized that pathogen prevalence may predict endorsement of the binding moral foundations, which may also serve to minimize pathogen transmission. We examined associations between historical and contemporary pathogen prevalence and endorsement of the moral foundations via multilevel analyses. Country-level analyses showed that even when controlling for gross domestic product per capita, historical (but not contemporary) pathogen prevalence significantly predicted endorsement of the binding foundations, but not individualizing foundations. Multilevel analyses showed that this pattern held even when controlling for individual-level variation in political orientation, gender, education, and age. These results highlight the utility of a functional–evolutionary approach to understanding patterns of morals across societies and individuals.     

Physiology of phototrophic iron(II)-oxidizing bacteria: implications for modern and ancient environments

Phototrophic iron(II) [Fe(II)]-oxidizing bacteria are present in modern environments and evidence suggests that this metabolism was present already on early earth. We determined Fe(II) oxidation rates depending on pH, temperature, light intensity, and Fe(II) concentration for three phylogenetically different phototrophic Fe(II)-oxidizing strains (purple nonsulfur bacterium Rhodobacter ferrooxidans sp. strain SW2, purple sulfur bacterium Thiodictyon sp. strain F4, and green sulfur bacterium Chlorobium ferrooxidans strain KoFox). While we found the overall highest Fe(II) oxidation rates with strain F4 (4.5 mmol L(-1) day(-1), 800 lux, 20 degrees C), the lowest light saturation values [at which maximum Fe(II) oxidation occurred] were determined for strain KoFox with light saturation already below 50 lux. The oxidation rate per cell was determined for R. ferrooxidans strain SW2 to be 32 pmol Fe(II) h(-1) per cell. No significant toxic effect of Fe(II) was observed at Fe(II) concentrations of up to 30 mM. All three strains are mesophiles with upper temperature limits of c. 30 degrees C. The main pigments were identified to be spheroidene, spheroidenone, OH-spheroidenone (SW2), rhodopinal (F4), and chlorobactene (KoFox). This study will improve our ecophysiological understanding of iron cycling in modern environments and will help to evaluate whether phototrophic iron oxidizers may have contributed to the formation of Fe(III) on early earth.     

PARma: identification of microRNA target sites in AGO-PAR-CLIP data

PARma is a complete data analysis software for AGO-PAR-CLIP experiments to identify target sites of microRNAs as well as the microRNA binding to these sites. It integrates specific characteristics of the experiments into a generative model. The model and a novel pattern discovery tool are iteratively applied to data to estimate seed activity probabilities, cluster confidence scores and to assign the most probable microRNA. Based on differential PAR-CLIP analysis and comparison to RIP-Chip data, we show that PARma is more accurate than existing approaches. PARma is available from http://www.bio.ifi.lmu.de/PARma