Predicting Functional Interactions Among Genes in Prokaryotes by Genomic Context.

Genomic context methods for finding functions of unannotated genes were implemented very early after the publication of the first few prokaryotic genomes. The ideas behind these methods include gene fusions, conservation of gene adjacency, and the patters of co-occurrence of genes across available genomes. A later addition was the prediction of features related to functional organization, such as operons, stretches of genes co-transcribed into a single messenger RNA. The ideas behind these methods tend to be easy to understand, while the strategies for transforming those basic ideas into predictions can vary in complexity, mostly because genes whose products are known to functionally interact vary in the way they relate to those basic ideas. We present here a view of genomic context methods for predicting functional interactions, with simple examples of their implementation as compared and evaluated using genes whose products are known to functionally interact.

Isolation and characterization of genetic variability in bacteria with ß-hemolytic and antifungal activity isolated from the rhizosphere of Medicago truncatula plants.

In the present study, we analyzed the frequency of hemolytic and antifungal activities in bacterial isolates from the rhizosphere of Medicago truncatula plants. Of the 2000 bacterial colonies, 96 showed ß-hemolytic activities (frequency, 4.8 x 10(-2)). Hemolytic isolates were analyzed for their genetic diversity by using random amplification of polymorphic DNA, yielding 88 haplotypes. The similarity coefficient of Nei and Li showed a polymorphic diversity ranging from 0.3 to 1. Additionally, 8 of the hemolytic isolates showed antifungal activity toward plant pathogens, Diaporthe phaseolorum, Colletotrichum acutatum, Rhizoctonia solani, and Fusarium oxysporum. The 16S ribosomal sequencing analysis showed that antagonistic bacterial isolates corresponded to Bacillus subtilis (UM15, UM33, UM42, UM49, UM52, and UM91), Bacillus pumilus (UM24), and Bacillus licheniformis (UM88). The present results revealed a higher genetic diversity among hemolytic isolates compared to that of isolates with antifungal action.

Open resource metagenomics: a model for sharing metagenomic libraries.

Both sequence-based and activity-based exploitation of environmental DNA have provided unprecedented access to the genomic content of cultivated and uncultivated microorganisms. Although researchers deposit microbial strains in culture collections and DNA sequences in databases, activity-based metagenomic studies typically only publish sequences from the hits retrieved from specific screens. Physical metagenomic libraries, conceptually similar to entire sequence datasets, are usually not straightforward to obtain by interested parties subsequent to publication. In order to facilitate unrestricted distribution of metagenomic libraries, we propose the adoption of open resource metagenomics, in line with the trend towards open access publishing, and similar to culture- and mutant-strain collections that have been the backbone of traditional microbiology and microbial genetics. The concept of open resource metagenomics includes preparation of physical DNA libraries, preferably in versatile vectors that facilitate screening in a diversity of host organisms, and pooling of clones so that single aliquots containing complete libraries can be easily distributed upon request. Database deposition of associated metadata and sequence data for each library provides researchers with information to select the most appropriate libraries for further research projects. As a starting point, we have established the Canadian MetaMicroBiome Library (CM(2)BL [1]). The CM(2)BL is a publicly accessible collection of cosmid libraries containing environmental DNA from soils collected from across Canada, spanning multiple biomes. The libraries were constructed such that the cloned DNA can be easily transferred to Gateway® compliant vectors, facilitating functional screening in virtually any surrogate microbial host for which there are available plasmid vectors. The libraries, which we are placing in the public domain, will be distributed upon request without restriction to members of both the academic research community and industry. This article invites the scientific community to adopt this philosophy of open resource metagenomics to extend the utility of functional metagenomics beyond initial publication, circumventing the need to start from scratch with each new research project.

Network-based function prediction and interactomics: the case for metabolic enzymes.

As sequencing technologies increase in power, determining the functions of unknown proteins encoded by the DNA sequences so produced becomes a major challenge. Functional annotation is commonly done on the basis of amino-acid sequence similarity alone. Long after sequence similarity becomes undetectable by pair-wise comparison, profile-based identification of homologs can often succeed due to the conservation of position-specific patterns, important for a protein's three dimensional folding and function. Nevertheless, prediction of protein function from homology-driven approaches is not without problems. Homologous proteins might evolve different functions and the power of homology detection has already started to reach its maximum. Computational methods for inferring protein function, which exploit the context of a protein in cellular networks, have come to be built on top of homology-based approaches. These network-based functional inference techniques provide both a first hand hint into a proteins' functional role and offer complementary insights to traditional methods for understanding the function of uncharacterized proteins. Most recent network-based approaches aim to integrate diverse kinds of functional interactions to boost both coverage and confidence level. These techniques not only promise to solve the moonlighting aspect of proteins by annotating proteins with multiple functions, but also increase our understanding on the interplay between different functional classes in a cell. In this article we review the state of the art in network-based function prediction and describe some of the underlying difficulties and successes. Given the volume of high-throughput data that is being reported the time is ripe to employ these network-based approaches, which can be used to unravel the functions of the uncharacterized proteins accumulating in the genomic databases.

GeConT 2: gene context analysis for orthologous proteins, conserved domains and metabolic pathways.

The Gene Context Tool (GeConT) allows users to visualize the genomic context of a gene or a group of genes and their orthologous relationships within fully sequenced bacterial genomes. The new version of the server incorporates information from the COG, Pfam and KEGG databases, allowing users to have an integrated graphical representation of the function of genes at multiple levels, their phylogenetic distribution and their genomic context. The sequence of any of the genes can be easily retrieved, as well as the 5' or 3' regulatory regions, greatly facilitating further types of analysis. GeConT 2 is available at: http://bioinfo.ibt.unam.mx/gecont.

VIR.II: a new interface with the antibody sequences in the Kabat database.

The Kabat database is the source of information par excellence on antibody sequences. In 1995, we developed an interface with the Kabat database, called VIR. VIR has been very useful in conducting studies aiming to find structure-function relationships in antibodies. Here we report a new version adapted to the World Wide Web, called VIR.II. VIR.II allows searches by type of chain (V(H) or V(L)), by species, and by specificity. The species are selected using a pulldown menu, whereas the specificities can be selected from a list containing the unique specificities reported in the Kabat database. These facilities avoid mistakes and redundancies in the searches. Another feature, and probably the most important one, is that VIR.II introduces a classification of specificities in terms of the chemical and biochemical nature of the antigen, like anti-protein, anti-peptide, anti-hapten, etc. This classification has been useful in discovering patterns in the antigen-binding site of antibodies that correlate with the type of antigen the antibody interacts with. To illustrate this, while showing the capabilities of VIR.II, we analyze all the murine anti-peptide and anti-protein antibody sequences compiled as of July, 2000 in the Kabat database.

A comparative genomics approach to prediction of new members of regulons.

Identifying the complete transcriptional regulatory network for an organism is a major challenge. For each regulatory protein, we want to know all the genes it regulates, that is, its regulon. Examples of known binding sites can be used to estimate the binding specificity of the protein and to predict other binding sites. However, binding site predictions can be unreliable because determining the true specificity of the protein is difficult because of the considerable variability of binding sites. Because regulatory systems tend to be conserved through evolution, we can use comparisons between species to increase the reliability of binding site predictions. In this article, an approach is presented to evaluate the computational predictions of regulatory sites. We combine the prediction of transcription units having orthologous genes with the prediction of transcription factor binding sites based on probabilistic models. We augment the sets of genes in Escherichia coli that are expected to be regulated by two transcription factors, the cAMP receptor protein and the fumarate and nitrate reduction regulatory protein, through a comparison with the Haemophilus influenzae genome. At the same time, we learned more about the regulatory networks of H. influenzae, a species with much less experimental knowledge than E. coli. By studying orthologous genes subject to regulation by the same transcription factor, we also gained understanding of the evolution of the entire regulatory systems.

Transcription unit conservation in the three domains of life: a perspective from Escherichia coli.

Here we address the question of the degree to which genes within experimentally characterized operons in one organism (Escherichia coli) are conserved in other genomes. We found that two genes adjacent within an operon are more likely both to have an ortholog in other organisms, regardless of relative position, than genes adjacent on the same strand but in two different transcription units. They are also more likely to occur next to, or fused to, one another in other genomes. Genes frequently conserved adjacent to each other, especially among evolutionarily distant species, must be part of the same transcription unit in most of them.

Operons in Escherichia coli: genomic analyses and predictions.

The rich knowledge of operon organization in Escherichia coli, together with the completed chromosomal sequence of this bacterium, enabled us to perform an analysis of distances between genes and of functional relationships of adjacent genes in the same operon, as opposed to adjacent genes in different transcription units. We measured and demonstrated the expected tendencies of genes within operons to have much shorter intergenic distances than genes at the borders of transcription units. A clear peak at short distances between genes in the same operon contrasts with a flat frequency distribution of genes at the borders of transcription units. Also, genes in the same operon tend to have the same physiological functional class. The results of these analyses were used to implement a method to predict the genomic organization of genes into transcription units. The method has a maximum accuracy of 88% correct identification of pairs of adjacent genes to be in an operon, or at the borders of transcription units, and correctly identifies around 75% of the known transcription units when used to predict the transcription unit organization of the E. coli genome. Based on the frequency distance distributions, we estimated a total of 630 to 700 operons in E. coli. This step opens the possibility of predicting operon organization in other bacteria whose genome sequences have been finished.

Escherichia coli TEM1 beta-lactamase in CTAB reverse micelles: exchange/diffusion-limited catalysis.

We report kinetic data of penicillin hydrolysis catalyzed by beta-lactamase entrapped in reverse micelles formed with cetyl trimethylammonium bromide (CTAB), n-octane, hexanol and aqueous buffer. The K(cat) of this diffusion-limited reaction can be improved in aqueous buffer by a factor of 1.1-1.2 just by increasing the phosphate buffer concentration from 50 to 100 mM. In reverse micelles, increasing the buffer concentration has little effect on K(cat) when the size of the empty micelle is below the size of the protein. However, in larger micelles, the effect is enhanced and the K(cat) improves several fold, changing the form of the curve of K(cat) versus Wo from bell-shaped to almost hyperbolic. The results indicate that micellar exchange and internal diffusion may limit the reaction in reverse micelles and provide further evidence that the form of the curve depends on other factors besides the relationship between the size of the enzyme and that of the empty reverse micelle.

Protein engineering as a powerful tool for the chemical modification of enzymes.

This article discusses the techniques of site-specific mutagenesis and protein engineering and their application in the study of enzyme active sites and the mechanism of enzyme action. Particular emphasis is given to beta-lactamase.

Protein engineering as a powerful tool for the chemical modification of enzymes

This article discusses the techniques of site-specific mutagenesis and protein engineering and their application in the study of enzyme active sites and the mechanism of enzyme action. Particular emphasis is given to beta-lactamase

The disulfide bridges of toxin 2 from the scorpion Centruroides noxius Hoffmann and its three-dimensional structure calculated using the coordinates of variant 3 from Centruroides sculpturatus.

The disulfide bridges of toxin 2 from the venom of the scorpion Centruroides noxius Hoffmann were found by amino acid sequence determination of fragments of native toxin, produced by enzymatic cleavage and separated by high-performance liquid chromatography (HPLC). They are: Cys12-Cys65, Cys16-Cys41, Cys25-Cys46 and Cys29-Cys48. The coordinates of the X-ray diffraction structure of toxin variant 3 of C. sculpturatus [(1980) Proc. Natl. Acad. Sci. USA 77, 6496-6500] were used to construct a three-dimensional model of toxin 2. All the amino acid replacements were easily accommodated, and the modeled structure reveals a clustered pattern of sequence variation, which may help to identify residues responsible for functional differences among toxins of mammals and insects.