Evaluation the Therapeutic Index of Recombinant Antimicrobial S3 Tetramer-Peptides Expressed in E. coli

International Journal of Peptide Research and Therapeutics - There is still a long way to go to commercialize antimicrobial peptides (AMPs) due to critical issues like efficiency, safety, and...     

Identification of Tmem10 as a Novel Late-stage Oligodendrocytes Marker for Detecting Hypomyelination

Oligodendrocytes ensheath axons to form compact insulating multilamellar structures known as myelin. Tmem10 is a novel type I transmembrane glycoprotein that is highly expressed in oligodendrocytes and whose biological function remains largely unknown. Furthermore, the expression pattern of Tmem10 remains a matter of some controversy. Given the inconsistency of its expression pattern and the lack of validated specific antibodies, Tmem10 is not widely accepted as a marker for mature oligodendrocytes. As a means to solve these problems and to aid future studies of oligodendrocyte-associated diseases, we have generated a highly specific Tmem10 antibody. Using this Tmem10 antibody, we clarify that Tmem10 protein is firstly expressed at 2 weeks in the postnatal mouse brain with age-related increase, only in the central nervous system (CNS). We also reveal that Tmem10 is expressed specifically in late stage oligodendrocytes and later than MAG, a late-stage myelin marker. Finally, we show that Tmem10 co-expresses with MOG- and MBP-positive myelin fibers and is dramatically reduced in a hypomyelination mouse model. In conclusion, our study demonstrates that Tmem10 can be used as a specific marker for myelinating oligodendrocytes and perhaps for the evaluation of myelination diseases, such as multiple sclerosis.     

Genetic structure of Pyrenophora teres net and spot populations as revealed by microsatellite analysis

The population structure of the fungal pathogen Pyrenophora teres, collected mainly from different regions of the Czech and Slovak Republics, was examined using a microsatellite analyses (SSR). Among 305 P. teres f. teres (PTT) and 82 P. teres f. maculata (PTM) isolates that were collected, the overall gene diversity was similar (? = 0.12 and ? = 0.13, respectively). A high level of genetic differentiation (F_ST = 0.46; P < 0.001) indicated the existence of population structure. Nine clusters that were found using a Bayesian approach represent the genetic structure of the studied P. teres populations. Two clusters consisted of PTM populations; PTT populations formed another seven clusters. An exact test of population differentiation confirmed the results that were generated by Structure. There was no difference between naturally infected populations over time, and genetic distance did not correlate with geographical distance. The facts that all individuals had unique multilocus genotypes and that the hypothesis of random mating could not be rejected in several populations or subpopulations serve as evidence that a mixed mating system plays a role in the P. teres life cycle. Despite the fact that the genetic differentiation value between PTT and PTM (F_ST = 0.30; P < 0.001) is lower than it is between the populations within each form (F_ST = 0.40 (PTT); F_ST = 0.35 (PTM); P < 0.001) and that individuals with mixed PTT and PTM genomes were found, the two forms of P. teres form genetically separate populations. Therefore, it can be assumed that these populations have most likely undergone speciation.     

Boosting Antimicrobial Peptides by Hydrophobic Oligopeptide End Tags

A novel approach for boosting antimicrobial peptides through end tagging with hydrophobic oligopeptide stretches is demonstrated. Focusing on two peptides derived from kininogen, GKHKNKGKKNGKHNGWK (GKH17) and HKHGHGHGKHKNKGKKN (HKH17), tagging resulted in enhanced killing of Gram-positive Staphylococcus aureus, Gram-negative Escherichia coli, and fungal Candida albicans. Microbicidal potency increased with tag length, also in plasma, and was larger for Trp and Phe stretches than for aliphatic ones. The enhanced microbicidal effects correlated to a higher degree of bacterial wall rupture. Analogously, tagging promoted peptide binding to model phospholipid membranes and liposome rupture, particularly for anionic and cholesterol-void membranes. Tagged peptides displayed low toxicity, particularly in the presence of serum, and resisted degradation by human leukocyte elastase and by staphylococcal aureolysin and V8 proteinase. The biological relevance of these findings was demonstrated ex vivo and in vivo in porcine S. aureus skin infection models. The generality of end tagging for facile boosting of antimicrobial peptides without the need for post-synthesis modification was also demonstrated.     

A hybrid genetic-neural model for predicting protein structural classes

A genetic algorithm (GA) for feature selection in conjunction with neural network was applied to predict protein structural classes based on single amino acid and all dipeptide composition frequencies. These sequence parameters were encoded as input features for a GA in feature selection procedure and classified with a three-layered neural network to predict protein structural classes. The system was established through optimization of the classification performance of neural network which was used as evaluation function. In this study, self-consistency and jackknife tests on a database containing 498 proteins were used to verify the performance of this hybrid method, and were compared with some of prior works. The adoption of a hybrid model, which encompasses genetic and neural technologies, demonstrated to be a promising approach in the task of protein structural class prediction.