Mining bacterial genomes for novel arylesterase activity

One hundred and seventy-one genes encoding potential esterases from 11 bacterial genomes were cloned and overexpressed in Escherichia coli; 74 of the clones produced soluble proteins. All 74 soluble proteins were purified and screened for esterase activity; 36 proteins showed carboxyl esterase activity on short-chain esters, 17 demonstrated arylesterase activity, while 38 proteins did not exhibit any activity towards the test substrates. Esterases from Rhodopseudomonas palustris (RpEST-1, RpEST-2 and RpEST-3), Pseudomonas putida (PpEST-1, PpEST-2 and PpEST-3), Pseudomonas aeruginosa (PaEST-1) and Streptomyces avermitilis (SavEST-1) were selected for detailed biochemical characterization. All of the enzymes showed optimal activity at neutral or alkaline pH, and the half-life of each enzyme at 50°C ranged from < 5 min to over 5 h. PpEST-3, RpEST-1 and RpEST-2 demonstrated the highest specific activity with pNP-esters; these enzymes were also among the most stable at 50°C and in the presence of detergents, polar and non-polar organic solvents, and imidazolium ionic liquids. Accordingly, these enzymes are particularly interesting targets for subsequent application trials. Finally, biochemical and bioinformatic analyses were compared to reveal sequence features that could be correlated to enzymes with arylesterase activity, facilitating subsequent searches for new esterases in microbial genome sequences.     

Mining bacterial genomes for antimicrobial targets

The elucidation of whole-genome sequences is expected to have a revolutionary impact on the discovery of novel medicines. With the availability of complete genome sequences of more than 30 different species, the field of antimicrobial drug discovery has the opportunity to access a remarkable diversity of genomic information. In this review, I summarize how microbial genomics has changed strategies of drug discovery by applying bioinformatics, novel genetic approaches and genomics-based technologies, including analysis of gene expression using DNA microarrays.     

Immuno-informatics: Mining genomes for vaccine components

The complete genome sequences of more than 60 microbes have been completed in the past decade. Concurrently, a series of new informatics tools, designed to harness this new wealth of information, have been developed. Some of these new tools allow researchers to select regions of microbial genomes that trigger immune responses. These regions, termed epitopes, are ideal components of vaccines. When the new tools are used to search for epitopes, this search is usually coupled with in vitro screening methods; an approach that has been termed computational immunology or immuno-informatics.Researchers are now implementing these combined methods to scan genomic sequences for vaccine components. They are thereby expanding the number of different proteins that can be screened for vaccine development, while narrowing this search to those regions of the proteins that are extremely likely to induce an immune response.As the tools improve, it may soon be feasible to skip over many of the in vitro screening steps, moving directly from genome sequence to vaccine design. The present article reviews the work of several groups engaged in the development of immuno-informatics tools and illustrates the application of these tools to the process of vaccine discovery.     

Mining microsatellites in eukaryotic genomes

During recent decades, microsatellites have become the most popular source of genetic markers. More recently, the availability of enormous sequence data for a large number of eukaryotic genomes has accelerated research aimed at understanding the origin and functions of microsatellites and searching for new applications. This review presents recent developments of in silico mining of microsatellites to reveal various facets of the distribution and dynamics of microsatellites in eukaryotic genomes. Two aspects of microsatellite search strategies--using a suitable search tool and accessing a relevant microsatellite database--have been explored. Judicious microsatellite mining not only helps in addressing biological questions but also facilitates better exploitation of microsatellites for diverse applications.     

Gene finding in novel genomes

Background  

Computational gene prediction continues to be an important problem, especially for genomes with little experimental data.     

Mining prokaryotic genomes for unknown amino acids: a stop-codon-based approach

Background  

Selenocysteine and pyrrolysine are the 21st and 22nd amino acids, which are genetically encoded by stop codons. Since a number of microbial genomes have been completely sequenced to date, it is tempting to ask whether the 23rd amino acid is left undiscovered in these genomes. Recently, a computational study addressed this question and reported that no tRNA gene for unknown amino acid was found in genome sequences available. However, performance of the tRNA prediction program on an unknown tRNA family, which may have atypical sequence and structure, is unclear, thereby rendering their result inconclusive. A protein-level study will provide independent insight into the novel amino acid.     

A novel common triplet profile for GC-rich prokaryotic genomes

It has been reported that there is a majority triplet profile among genomes, which was considered as a reflection of general mechanisms of genome evolution (Albrecht-Buehler, 2007). However, there are actually, according to our further analysis and at least among prokaryotic genomes, two common triplet profiles: one is from low-GC content genomes; the other is from high-GC content genomes. Both common profiles would be direct reflections of GC content variations and strand symmetry of genomic sequences.     

Enzymerhodopsins: novel photoregulated catalysts for optogenetics

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Mining metagenomes for novel cellulase genes

Cellulases hydrolyze the β-1,4 linkages of cellulose and are widely used in food, brewing and wine, animal feed, textiles and laundry, and pulp and paper industries, especially for hydrolyzing cellulosic materials into sugars, which can be fermented to produce useful products such as ethanol. Metagenomics has become an alternative approach to conventional culture-dependent methods as it allows exhaustive mining of microbial genomes in their natural environments. This review covers the current state of research and challenges in mining novel cellulase genes from the metagenomes of various environments, and discusses the potential biotechnological applications of metagenome-derived cellulases.     

Mining nematode genome data for novel drug targets

Expressed sequence tag projects have currently produced over 400 000 partial gene sequences from more than 30 nematode species and the full genomic sequences of selected nematodes are being determined. In addition, functional analyses in the model nematode Caenorhabditis elegans have addressed the role of almost all genes predicted by the genome sequence. This recent explosion in the amount of available nematode DNA sequences, coupled with new gene function data, provides an unprecedented opportunity to identify pre-validated drug targets through efficient mining of nematode genomic databases. This article describes the various information sources available and strategies that can expedite this process.     

Validation of reference-assisted assembly using existing and novel Heliothine genomes

Chloridea subflexa and Chloridea virescens are a pair of closely related noctuid species exhibiting pheromone-based sexual isolation and divergent host plant preferences. We produced a novel Illumina short read C. subflexa genome assembly and an improved C. virescens genome assembly, which offer opportunities to study the genomic basis for evolutionarily important traits in this lepidopteran family with few genomic resources. We then examined the feasibility of reference-assisted assembly, an approach that leverages existing high quality genomic resources for genome improvement in closely related taxa and applied it to our Heliothine genomes. Our work demonstrates that reference-assisted assembly has the potential to enhance contiguity and completeness of existing insect genomic resources with minimal additional laboratory costs. We conclude by discussing both the potential and pitfalls of reference-assisted assembly according to the intended downstream assembly application.     

Bacterial genomes pave the way to novel vaccines

The availability of complete genome sequences of pathogens has dramatically changed the scope for developing improved and novel vaccines by increasing the speed of target identification. Genomics-based technologies have many advantages, compared to conventional approaches, which are time-consuming and usually identify only abundant antigens that are expressible under in vitro culture conditions. This review focuses on recent reports of genomics-based strategies that can be applied to most pathogens and that exploit genome sequence information in alliance with adjunct technologies, including bioinformatics, expression analyses, random mutagenesis or protein/peptide-based selection methods. Despite the caveats that are associated with the individual approaches, these technologies have already made major contributions to the identification and selection of novel vaccine candidates to combat bacterial infections.     

A novel microarray strategy for detecting genes and pathways in microbes with unsequenced genomes

Expression profile analysis of genes provides valuable information concerning the genetic response of cells to stimuli. We describe an adaptation of this technology that can be used to probe for the expression of specific families of genes in microbial species. In our method a combination of sets of oligonucleotide probes representing fingerprint sequences specific to protein families is used to identify the presence and expression levels of family homologs in a microbial cell. We demonstrate computationally, using exemplars, that when the cDNA complement from an organism is sequentially screened against a set of specific motif oligonucleotides, statistically significant information can be obtained concerning the expression of the corresponding genes. This method can be used to identify specific genes and pathways simultaneously in several organisms of interest even in the absence of sequence information from the organisms.     

Mining the Leishmania genome for novel antigens and vaccine candidates

Leishmaniasis is a neglected disease with an estimated 12 million infected people. The recent completion of the sequencing of the Leishmania major genome has opened opportunities for the identification of targets for vaccine development. We present here the first attempt at identifying novel vaccine candidates by whole genome analysis. We predicted CD8⁺ T cell epitopes from the L. major proteome and validated in vivo in mice the immunogenicity of some of the best predicted epitopes. Consensus epitope predictions from 8272 annotated protein sequences with 5–8 different algorithms allowed the identification of 78 class I CD8⁺ epitopes. BALB/c mice were immunized with 26 synthetic peptides corresponding to the most likely epitopes. Fourteen (54%) resulted immunogenic, with eight being strong inducers of T cell IFNγ production. None of the proteins from which the epitopes are derived are differentially expressed, only two may be surface proteins, eight have putative enzymatic, and metabolic activities. These epitopes and proteins represent new antigen candidates for further studies. While pathogen genomes have not yet delivered their full promise in terms of human health applications, our study opens the way for extensive genome mining for antigen identification and vaccine development against Leishmania and other pathogens.     

PaaSiCats: novel polyamino acid catalysts

The abilities of five polyamino acids (Paa's) to catalyse the asymmetric epoxidation of enones 1-7 under three sets of reaction conditions were compared: polyneo-pentylglycine and polyleucine showed distinct advantages in most circumstances. All five polymers were adsorbed onto silica and from this further study, immobilised polyneo-pentylglycine (PLNSi) and polyleucine (PLLSi) were shown to be the catalysts of choice for the asymmetric epoxidation of less-reactive alpha,beta-unsaturated ketones.