Improving upon nature: active site remodeling produces highly efficient aldolase activity toward hydrophobic electrophilic substrates

The substrate specificity of enzymes is frequently narrow and constrained by multiple interactions, limiting the use of natural enzymes in biocatalytic applications. Aldolases have important synthetic applications, but the usefulness of these enzymes is hampered by their narrow reactivity profile with unnatural substrates. To explore the determinants of substrate selectivity and alter the specificity of Escherichia coli 2-keto-3-deoxy-6-phosphogluconate (KDPG) aldolase, we employed structure-based mutagenesis coupled with library screening of mutant enzymes localized to the bacterial periplasm. We identified two active site mutations (T161S and S184L) that work additively to enhance the substrate specificity of this aldolase to include catalysis of retro-aldol cleavage of (4S)-2-keto-4-hydroxy-4-(2'-pyridyl)butyrate (S-KHPB). These mutations improve the value of k(cat)/K(M)(S-KHPB) by >450-fold, resulting in a catalytic efficiency that is comparable to that of the wild-type enzyme with the natural substrate while retaining high stereoselectivity. Moreover, the value of k(cat)(S-KHPB) for this mutant enzyme, a parameter critical for biocatalytic applications, is 3-fold higher than the maximal value achieved by the natural aldolase with any substrate. This mutant also possesses high catalytic efficiency for the retro-aldol cleavage of the natural substrate, KDPG, and a >50-fold improved activity for cleavage of 2-keto-4-hydroxy-octonoate, a nonfunctionalized hydrophobic analogue. These data suggest a substrate binding mode that illuminates the origin of facial selectivity in aldol addition reactions catalyzed by KDPG and 2-keto-3-deoxy-6-phosphogalactonate aldolases. Furthermore, targeting mutations to the active site provides a marked improvement in substrate selectivity, demonstrating that structure-guided active site mutagenesis combined with selection techniques can efficiently identify proteins with characteristics that compare favorably to those of naturally occurring enzymes.     

Diversity and antagonistic potential of Bacillus spp. associated to the rhizosphere of tomato for the management of Rhizoctonia solani

Bacillus spp. has emerged as the most effective alternative to synthetic chemical fungicides. To get a better insight in the antagonistic potential of Bacillus strains, rhizospheric soil samples of healthy tomato plants from Indo-gangetic plain regions of India were analysed. A total of 108 Bacillus strains were obtained from preliminary screening. Potent strains identified on the basis of in vitro antagonistic and biochemical assays were subjected to diversity analysis using 16S-rDNA, BOX and ERIC-PCR. Furthermore, the four best performing antagonistic Bacillus strains under in vitro plant growth promotion and antagonistic assay were selected for pot experiment. In field study, Bacillus amyloliquefaciens MB101 and Bacillus subtilis MB14 showed drastic reduction in disease index by 55.7 and 41.74% with significant elevation in fruit yield up to 220 and 184 qha^–1, respectively. The present study was successful in selecting effective Bacillus strains by performing phenotypic and genotypic characterisation of Bacillus strains that can be used as an integral component of integrated disease management of tomato root rot and damping-off.     

A genome-wide survey of switchgrass genome structure and organization

The perennial grass, switchgrass (Panicum virgatum L.), is a promising bioenergy crop and the target of whole genome sequencing. We constructed two bacterial artificial chromosome (BAC) libraries from the AP13 clone of switchgrass to gain insight into the genome structure and organization, initiate functional and comparative genomic studies, and assist with genome assembly. Together representing 16 haploid genome equivalents of switchgrass, each library comprises 101,376 clones with average insert sizes of 144 (HindIII-generated) and 110 kb (BstYI-generated). A total of 330,297 high quality BAC-end sequences (BES) were generated, accounting for 263.2 Mbp (16.4%) of the switchgrass genome. Analysis of the BES identified 279,099 known repetitive elements, >50,000 SSRs, and 2,528 novel repeat elements, named switchgrass repetitive elements (SREs). Comparative mapping of 47 full-length BAC sequences and 330K BES revealed high levels of synteny with the grass genomes sorghum, rice, maize, and Brachypodium. Our data indicate that the sorghum genome has retained larger microsyntenous regions with switchgrass besides high gene order conservation with rice. The resources generated in this effort will be useful for a broad range of applications.     

Exploitation of marine bacteria for production of gold nanoparticles

Background

Gold nanoparticles (AuNPs) have found wide range of applications in electronics, biomedical engineering, and chemistry owing to their exceptional opto-electrical properties. Biological synthesis of gold nanoparticles by using plant extracts and microbes have received profound interest in recent times owing to their potential to produce nanoparticles with varied shape, size and morphology. Marine microorganisms are unique to tolerate high salt concentration and can evade toxicity of different metal ions. However, these marine microbes are not sufficiently explored for their capability of metal nanoparticle synthesis. Although, marine water is one of the richest sources of gold in the nature, however, there is no significant publication regarding utilization of marine micro-organisms to produce gold nanoparticles. Therefore, there might be a possibility of exploring marine bacteria as nanofactories for AuNP biosynthesis.

Results

In the present study, marine bacteria are exploited towards their capability of gold nanoparticles (AuNPs) production. Stable, monodisperse AuNP formation with around 10?nm dimension occur upon exposure of HAuCl₄ solution to whole cells of a novel strain of Marinobacter pelagius, as characterized by polyphasic taxonomy. Nanoparticles synthesized are characterized by Transmission electron microscopy, Dynamic light scattering and UV-visible spectroscopy.

Conclusion

The potential of marine organisms in biosynthesis of AuNPs are still relatively unexplored. Although, there are few reports of gold nanoparticles production using marine sponges and sea weeds however, there is no report on the production of gold nanoparticles using marine bacteria. The present work highlighted the possibility of using the marine bacterial strain of Marinobacter pelagius to achieve a fast rate of nanoparticles synthesis which may be of high interest for future process development of AuNPs. This is the first report of AuNP synthesis by marine bacteria.     

Homology inference of protein-protein interactions via conserved binding sites

The coverage and reliability of protein-protein interactions determined by high-throughput experiments still needs to be improved, especially for higher organisms, therefore the question persists, how interactions can be verified and predicted by computational approaches using available data on protein structural complexes. Recently we developed an approach called IBIS (Inferred Biomolecular Interaction Server) to predict and annotate protein-protein binding sites and interaction partners, which is based on the assumption that the structural location and sequence patterns of protein-protein binding sites are conserved between close homologs. In this study first we confirmed high accuracy of our method and found that its accuracy depends critically on the usage of all available data on structures of homologous complexes, compared to the approaches where only a non-redundant set of complexes is employed. Second we showed that there exists a trade-off between specificity and sensitivity if we employ in the prediction only evolutionarily conserved binding site clusters or clusters supported by only one observation (singletons). Finally we addressed the question of identifying the biologically relevant interactions using the homology inference approach and demonstrated that a large majority of crystal packing interactions can be correctly identified and filtered by our algorithm. At the same time, about half of biological interfaces that are not present in the protein crystallographic asymmetric unit can be reconstructed by IBIS from homologous complexes without the prior knowledge of crystal parameters of the query protein.     

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Finding the cost-efficient (i.e., lowest-cost) ways of targeting conservation practice investments for the achievement of specific water quality goals across the landscape is of primary importance in watershed management. Traditional economics methods of finding the lowest-cost solution in the watershed context (e.g.,^5,12,20) assume that off-site impacts can be accurately described as a proportion of on-site pollution generated. Such approaches are unlikely to be representative of the actual pollution process in a watershed, where the impacts of polluting sources are often determined by complex biophysical processes. The use of modern physically-based, spatially distributed hydrologic simulation models allows for a greater degree of realism in terms of process representation but requires a development of a simulation-optimization framework where the model becomes an integral part of optimization.Evolutionary algorithms appear to be a particularly useful optimization tool, able to deal with the combinatorial nature of a watershed simulation-optimization problem and allowing the use of the full water quality model. Evolutionary algorithms treat a particular spatial allocation of conservation practices in a watershed as a candidate solution and utilize sets (populations) of candidate solutions iteratively applying stochastic operators of selection, recombination, and mutation to find improvements with respect to the optimization objectives. The optimization objectives in this case are to minimize nonpoint-source pollution in the watershed, simultaneously minimizing the cost of conservation practices. A recent and expanding set of research is attempting to use similar methods and integrates water quality models with broadly defined evolutionary optimization methods^{3,4,9,10,13-15,17-19,22,23,25}. In this application, we demonstrate a program which follows Rabotyagov et al.''s approach and integrates a modern and commonly used SWAT water quality model⁷ with a multiobjective evolutionary algorithm SPEA2²⁶, and user-specified set of conservation practices and their costs to search for the complete tradeoff frontiers between costs of conservation practices and user-specified water quality objectives. The frontiers quantify the tradeoffs faced by the watershed managers by presenting the full range of costs associated with various water quality improvement goals. The program allows for a selection of watershed configurations achieving specified water quality improvement goals and a production of maps of optimized placement of conservation practices.