Structural Basis of Differential Neutralization of DENV-1 Genotypes by an Antibody that Recognizes a Cryptic Epitope

We previously developed a panel of neutralizing monoclonal antibodies against Dengue virus (DENV)-1, of which few exhibited inhibitory activity against all DENV-1 genotypes. This finding is consistent with reports observing variable neutralization of different DENV strains and genotypes using serum from individuals that experienced natural infection or immunization. Herein, we describe the crystal structures of DENV1-E111 bound to a novel CC′ loop epitope on domain III (DIII) of the E protein from two different DENV-1 genotypes. Docking of our structure onto the available cryo-electron microscopy models of DENV virions revealed that the DENV1-E111 epitope was inaccessible, suggesting that this antibody recognizes an uncharacterized virus conformation. While the affinity of binding between DENV1-E111 and DIII varied by genotype, we observed limited correlation with inhibitory activity. Instead, our results support the conclusion that potent neutralization depends on genotype-dependent exposure of the CC′ loop epitope. These findings establish new structural complexity of the DENV virion, which may be relevant for the choice of DENV strain for induction or analysis of neutralizing antibodies in the context of vaccine development.     

Bio-Logic Builder: A Non-Technical Tool for Building Dynamical,Qualitative Models

Computational modeling of biological processes is a promising tool in biomedical research. While a large part of its potential lies in the ability to integrate it with laboratory research, modeling currently generally requires a high degree of training in mathematics and/or computer science. To help address this issue, we have developed a web-based tool, Bio-Logic Builder, that enables laboratory scientists to define mathematical representations (based on a discrete formalism) of biological regulatory mechanisms in a modular and non-technical fashion. As part of the user interface, generalized “bio-logic” modules have been defined to provide users with the building blocks for many biological processes. To build/modify computational models, experimentalists provide purely qualitative information about a particular regulatory mechanisms as is generally found in the laboratory. The Bio-Logic Builder subsequently converts the provided information into a mathematical representation described with Boolean expressions/rules. We used this tool to build a number of dynamical models, including a 130-protein large-scale model of signal transduction with over 800 interactions, influenza A replication cycle with 127 species and 200+ interactions, and mammalian and budding yeast cell cycles. We also show that any and all qualitative regulatory mechanisms can be built using this tool.     

Chaotic synchronization using a network of neural oscillators

Synchronization of chaotic low-dimensional systems has been a topic of much recent research. Such systems have found applications for secure communications. In this work we show how synchronization can be achieved in a high-dimensional chaotic neural network. The network used in our studies is an extension of the Hopfield Network, known as the Complex Hopfield Network (CHN). The CHN, also an associative memory, has both fixed point and limit cycle or oscillatory behavior. In the oscillatory mode, the network wanders chaotically from one stored pattern to another. We show how a pair of identical high-dimensional CHNs can be synchronized by communicating only a subset of state vector components. The synchronizability of such a system is characterized through simulations.     

Low-coverage massively parallel pyrosequencing of cDNAs enables proteomics in non-model species: comparison of a species-specific database generated by pyrosequencing with databases from related species for proteome analysis of pea chloroplast envelopes

Proteomics is a valuable tool for establishing and comparing the protein content of defined tissues, cell types, or subcellular structures. Its use in non-model species is currently limited because the identification of peptides critically depends on sequence databases. In this study, we explored the potential of a preliminary cDNA database for the non-model species Pisum sativum created by a small number of massively parallel pyrosequencing (MPSS) runs for its use in proteomics and compared it to comprehensive cDNA databases from Medicago truncatula and Arabidopsis thaliana created by Sanger sequencing. Each database was used to identify proteins from a pea leaf chloroplast envelope preparation. It is shown that the pea database identified more proteins with higher accuracy, although the sequence quality was low and the sequence contigs were short compared to databases from model species. Although the number of identified proteins in non-species-specific databases could potentially be increased by lowering the threshold for successful protein identifications, this strategy markedly increases the number of wrongly identified proteins. The identification rate with non-species-specific databases correlated with spectral abundance but not with the predicted membrane helix content, and strong conservation is necessary but not sufficient for protein identification with a non-species-specific database. It is concluded that massively parallel sequencing of cDNAs substantially increases the power of proteomics in non-model species.     

Biological control of bacterial spot disease and plant growth-promoting effects of lactic acid bacteria on pepper

In our previous studies, we observed the biological control effect of lactic acid bacteria strains (LABs) KLF01, KLC02 and KPD03 against different plant pathogenic bacteria in vitro against Ralstonia solanacearum, and strains KLF01 and KLC02 against Pectobacterium carotovorum under greenhouse and field experiments, respectively. In this study, we observed the efficacy of these bacteria against bacterial spot pathogen (Xanthomonas campestris pv. vesicatoria) and their plant growth-promoting activities in pepper (Capsicum annuum L. var. annuum), under greenhouse and field conditions. LABs significantly (P < 0.05) reduced bacterial spot on pepper plants in comparison to untreated plants in both the greenhouse and the field experiments. The plant growth-promoting effect of LABs on pepper varied; some strains had a significant effect on growth promotion (P < 0.05) compared with untreated plants, while some showed no significant effect in the greenhouse and field experiments. Additionally, LABs were able to colonise roots, produce indole-3-acetic acid (IAA), siderophores and solubilise phosphate. These findings indicate that application of LABs could provide a promising alternative for the management of bacterial spot disease in pepper plants and could therefore be used as a healthy plant growth-promoting agent.