BACKGROUND: Proteomics of bacterial pathogens is a developing field exploring microbial physiology, gene expression and the complex interactions between bacteria and their hosts. One of the complications in proteomic approach is micro- and macro-heterogeneity of bacterial species, which makes it impossible to build a comprehensive database of bacterial genomes for identification, while most of the existing algorithms rely largely on genomic data. RESULTS: Here we present a large scale study of identification of single amino acid polymorphisms between bacterial strains. An ad hoc method was developed based on MS/MS spectra comparison without the support of a genomic database. Whole-genome sequencing was used to validate the accuracy of polymorphism detection. Several approaches presented earlier to the proteomics community as useful for polymorphism detection were tested on isolates of Helicobacter pylori, Neisseria gonorrhoeae and Escherichia coli. CONCLUSION: The developed method represents a perspective approach in the field of bacterial proteomics allowing to identify hundreds of peptides with novel SAPs from a single proteome.

The recognition of transcription factor binding sites (TFBSs) is the first step on the way to deciphering the DNA regulatory code. There is a large variety of experimental approaches providing information on TFBS location in genomic sequences. Many computational approaches to TFBS recognition based on the experimental data obtained are available, each having its own advantages and shortcomings. This article provides short review of approaches to computational recognition of TFBS in genomic sequences and methods of experimental verification of predicted sites. We also present a case study of the interplay between experimental and theoretical approaches to the successful prediction of Steroidogenic Factor 1 (SF1).

BACKGROUND: Computational analysis of gene regulatory regions is important for prediction of functions of many uncharacterized genes. With this in mind, search of the target genes for interferon (IFN) induction appears of interest. IFNs are multi-functional cytokines. Their effects are immunomodulatory, antiviral, antibacterial, and antitumor. The interaction of the IFNs with their cell surface receptors produces an activation of several transcription factors. Four regulatory factors, ISGF3, STAT1, IRF1, and NF-kappaB, are essential for the function of the IFN system. The aim of this work is the development of computational approaches for the recognition of DNA binding sites for these factors and computer programs for the prediction of the IFN-inducible regions. RESULTS: We developed computational approaches to the recognition of the binding sites for ISGF3, STAT1, IRF1, and NF-kappaB. Analysis of the distribution of these binding sites demonstrated that the regions -500 upstream of the transcription start site in IFN-inducible genes are enriched in putative binding sites for these transcription factors. Based on selected combinations of the sites whose frequencies were significantly higher than in the other functional gene groups, we developed methods for the prediction of the IFN-inducible promoters and enhancers. We analyzed 1004 sequences of the IFN-inducible genes compiled using microarray data analyses and also about 10,000 human gene sequences from the EPD and RefSeq databases; 74 of 1,664 human genes annotated in EPD were significantly IFN-inducible. CONCLUSION: Analyses of several control datasets demonstrated that the developed methods have a high accuracy of prediction of the IFN-inducible genes. Application of these methods to several datasets suggested that the number of the IFN-inducible genes is approximately 1500-2000 in the human genome.

BACKGROUND: The translation start site plays an important role in the control of translation efficiency of eukaryotic mRNAs. The recognition of the start AUG codon by eukaryotic ribosomes is considered to depend on its nucleotide context. However, the fraction of eukaryotic mRNAs with the start codon in a suboptimal context is relatively large. It may be expected that mRNA should possess some features providing efficient translation, including the proper recognition of a translation start site. It has been experimentally shown that a downstream hairpin located in certain positions with respect to start codon can compensate in part for the suboptimal AUG context and also increases translation from non-AUG initiation codons. Prediction of such a compensatory hairpin may be useful in the evaluation of eukaryotic mRNA translation properties. RESULTS: We evaluated interdependency between the start codon context and mRNA secondary structure at the CDS beginning: it was found that a suboptimal start codon context significantly correlated with higher base pairing probabilities at positions 13 - 17 of CDS of human and mouse mRNAs. It is likely that the downstream hairpins are used to enhance translation of some mammalian mRNAs in vivo. Thus, we have developed a tool, AUG_hairpin, to predict local stem-loop structures located within the defined region at the beginning of mRNA coding part. The implemented algorithm is based on the available published experimental data on the CDS-located stem-loop structures influencing the recognition of upstream start codons. CONCLUSION: An occurrence of a potential secondary structure downstream of start AUG codon in a suboptimal context (or downstream of a potential non-AUG start codon) may provide researchers with a testable assumption on the presence of additional regulatory signal influencing mRNA translation initiation rate and the start codon choice. AUG_hairpin, which has a convenient Web-interface with adjustable parameters, will make such an evaluation easy and efficient.

BACKGROUND: Reliable transcription factor binding site (TFBS) prediction methods are essential for computer annotation of large amount of genome sequence data. However, current methods to predict TFBSs are hampered by the high false-positive rates that occur when only sequence conservation at the core binding-sites is considered. RESULTS: To improve this situation, we have quantified the performance of several Position Weight Matrix (PWM) algorithms, using exhaustive approaches to find their optimal length and position. We applied these approaches to bio-medically important TFBSs involved in the regulation of cell growth and proliferation as well as in inflammatory, immune, and antiviral responses (NF-kappaB, ISGF3, IRF1, STAT1), obesity and lipid metabolism (PPAR, SREBP, HNF4), regulation of the steroidogenic (SF-1) and cell cycle (E2F) genes expression. We have also gained extra specificity using a method, entitled SiteGA, which takes into account structural interactions within TFBS core and flanking regions, using a genetic algorithm (GA) with a discriminant function of locally positioned dinucleotide (LPD) frequencies. To ensure a higher confidence in our approach, we applied resampling-jackknife and bootstrap tests for the comparison, it appears that, optimized PWM and SiteGA have shown similar recognition performances. Then we applied SiteGA and optimized PWMs (both separately and together) to sequences in the Eukaryotic Promoter Database (EPD). The resulting SiteGA recognition models can now be used to search sequences for BSs using the web tool, SiteGA. Analysis of dependencies between close and distant LPDs revealed by SiteGA models has shown that the most significant correlations are between close LPDs, and are generally located in the core (footprint) region. A greater number of less significant correlations are mainly between distant LPDs, which spanned both core and flanking regions. When SiteGA and optimized PWM models were applied together, this substantially reduced false positives at least at higher stringencies. CONCLUSION: Based on this analysis, SiteGA adds substantial specificity even to optimized PWMs and may be considered for large-scale genome analysis. It adds to the range of techniques available for TFBS prediction, and EPD analysis has led to a list of genes which appear to be regulated by the above TFs.

MOTIVATION: It is known that the physico-chemical characteristics of proteins underlying specific folding of the polypeptide chain and the protein function are evolutionary conserved. Detection of such characteristics while analyzing homologous sequences would expand essentially the knowledge on protein function, structure, and evolution. These characteristics are maintained constant, in particular, by co-ordinated substitutions. In this process, the destabilizing effect of a substitution may be compensated by another substitution at a different position within the same protein, making the overall change in this protein characteristic insignificant. Consequently, the patterns of co-ordinated substitutions contain important information on conserved physico-chemical properties of proteins, requiring their investigation and development of the corresponding methods and software for correlation analysis of protein sequences available to a wide range of users. RESULTS: A software package for analyzing correlated amino acid substitutions at different positions within aligned protein sequences was developed. The approach implies searching for evolutionary conserved physico-chemical characteristics of proteins based on the information on the pairwise correlations of amino acid substitutions at different protein positions. The software was applied to analyze DNA-binding domains of the homeodomain class. As a result, two conservative physico-chemical characteristics preserved due to the co-ordinated substitutions at certain groups of positions in the protein sequence. Possible functional roles of these characteristics are discussed. AVAILABILITY: The program package is available at http://wwwmgs.bionet.nsc.ru/programs/CRASP/.

Nikolay Kolchanov, Charlie Hodgman; The 2nd international conference on the Bioinformatics of Genome Regulation and Structure (BGRS-2000), Novosibirsk, Aug

MOTIVATION: A rapid growth in the number of genes with known sequences calls for developing automated tools for their classification and analysis. It became clear that nucleosome packaging of eukaryotic DNA is very important for gene functioning. Automated computer tools for characterization of nucleosome packaging density could be useful for studying of gene regulation and genome annotation. RESULTS: A program for constructing nucleosome formation potential profiles of eukaryotic DNA sequences was developed. Nucleosome packaging density was analyzed for different functional types of human promoters. It was found that in promoters of tissue-specific genes, the nucleosome formation potential was essentially higher than in genes expressed in many tissues, or housekeeping genes. Hence, capability of nucleosome positioning in the promoter region may serve as a factor regulating gene expression. AVAILABILITY: The program for nucleosome sites recognition is included into the GeneExpress system; section 'DNA Nucleosomal Organization', http://wwwmgs.bionet.nsc.ru/mgs/programs/recon/.

A program for constructing nucleosome formation potential profile was applied for investigation of exons, introns, and repetitive sequences. The program is available at http://wwwmgs.bionet.nsc.ru/mgs/programs/recon/. We have demonstrated that introns and repetitive sequences exhibit higher nucleosome formation potentials than exons. This fact may be explained by functional saturation of exons with genetic code, hindering the localization of efficient nucleosome positioning sites.

MOTIVATION: It is well known that eukaryotic mRNAs are translated at different levels depending on their sequence characteristics. Evaluation of mRNA translatability is of importance in prediction of the gene expression pattern by computer methods and to improve the recognition of mRNAs within cloned nucleotide sequences. It may also be used in biotechnological experiments to optimize the expression of foreign genes in transgenic organisms. RESULTS: The sets of 5' untranslated region characteristics, significantly different between mRNAs encoding abundant and scarce polypeptides, were determined for mammals, dicot plants and monocot plants, and collected in the LEADER_RNA database. Computer tools for the prediction of mRNA translatability are presented. AVAILABILITY: Programs for mRNA translatability prediction are available at http://wwwmgs.bionet.nsc. ru/programs/acts2/mo_mRNA.htm (for monocots), http://wwwmgs.bionet. nsc.ru/programs/acts2/di_mRNA.htm (for dicots) and http://wwwmgs. bionet.nsc.ru/programs/acts2/ma_mRNA.htm (for mammals). The LEADER_RNA database may be accessed at: http://wwwmgs.bionet.nsc. ru/systems/LeaderRNA/.

MOTIVATION: The goal of the work was to develop a WWW-oriented computer system providing a maximal integration of informational and software resources on the regulation of gene expression and navigation through them. Rapid growth of the variety and volume of information accumulated in the databases on regulation of gene expression necessarily requires the development of computer systems for automated discovery of the knowledge that can be further used for analysis of regulatory genomic sequences. RESULTS: The GeneExpress system developed includes the following major informational and software modules: (1) Transcription Regulation (TRRD) module, which contains the databases on transcription regulatory regions of eukaryotic genes and TRRD Viewer for data visualization; (2) Site Activity Prediction (ACTIVITY), the module for analysis of functional site activity and its prediction; (3) Site Recognition module, which comprises (a) B-DNA-VIDEO system for detecting the conformational and physicochemical properties of DNA sites significant for their recognition, (b) Consensus and Weight Matrices (ConsFrec) and (c) Transcription Factor Binding Sites Recognition (TFBSR) systems for detecting conservative contextual regions of functional sites and their recognition; (4) Gene Networks (GeneNet), which contains an object-oriented database accumulating the data on gene networks and signal transduction pathways, and the Java-based Viewer for exploration and visualization of the GeneNet information; (5) mRNA Translation (Leader mRNA), designed to analyze structural and contextual properties of mRNA 5'-untranslated regions (5'-UTRs) and predict their translation efficiency; (6) other program modules designed to study the structure-function organization of regulatory genomic sequences and regulatory proteins. AVAILABILITY: GeneExpress is available at http://wwwmgs.bionet.nsc. ru/systems/GeneExpress/ and the links to the mirror site(s) can be found at http://wwwmgs.bionet.nsc.ru/mgs/links/mirrors.html+ ++.

MOTIVATION: Chromatin structure plays the crucial role in proper gene functioning. Therefore, it is very important to investigate nucleosomal DNA properties and recognize genome nucleosome positioning sequences. Nevertheless, applying different sequence analysis methods separately is insufficient for complete nucleosomal DNA description. One of the most probable reasons for that is the weakness of nucleosome positioning signals. The present paper offers a set of methods to reveal the most important nucleosomal DNA characteristics and to show a common pattern of nucleosome site properties. RESULTS: A complex approach was used to determine conformational and physicochemical properties that are most significant for nucleosome binding site description. The integrated database of nucleosomal DNA properties is compiled. This database comprises different sections for description of DNA characteristics. Revealing significant DNA characteristics allows the classification of various samples of site sequences and the generation of programs for site recognition. AVAILABILITY: The current version of the database is available at http://wwwmgs.bionet.nsc. ru/system/BDNAvideo/. C-code of the recognition program may be found in the section FEATURE. WWW-available programs for testing arbitrary sequences are accessible at http://wwwmgs.bionet.nsc. ru/Programs/bDNA/NA_bDNA.htm/. The links to the mirror site(s) can be found at http://wwwmgs.bionet.nsc.ru/mgs/links/mirrors.html+ ++.

MOTIVATION: The commonly accepted statistical mechanical theory is now multiply confirmed by using the weight matrix methods successfully recognizing DNA sites binding regulatory proteins in prokaryotes. Nevertheless, the recent evaluation of weight matrix methods application for transcription factor binding site recognition in eukaryotes has unexpectedly revealed that the matrix scores correlate better to each other than to the activity of DNA sites interacting with proteins. This observation points out that molecular mechanisms of DNA/protein recognition are more complicated in eukaryotes than in prokaryotes. As the extra events in eukaryotes, the following processes may be considered: (i) competition between the proteins and nucleosome core particle for DNA sites binding these proteins and (ii) interaction between two synergetic/antagonist proteins recognizing a composed element compiled from two DNA sites binding these proteins. That is why identification of the sequence-dependent DNA features correlating with affinity magnitudes of DNA sites interacting with a protein can pinpoint the molecular event limiting this protein/DNA recognition machinery. RESULTS: An approach for predicting site activity based on its primary nucleotide sequence has been developed. The approach is realized in the computer system ACTIVITY, containing the databases on site activity and on conformational and physicochemical DNA/RNA parameters. By using the system ACTIVITY, an analysis of some sites was provided and the methods for predicting site activity were constructed. The methods developed are in good agreement with the experimental data. AVAILABILITY: The database ACTIVITY is available at http://wwwmgs.bionet.nsc.ru/systems/Activity/ and the mirror site, http://www.cbil.upenn.edu/mgs/systems/acti vity/.

MOTIVATION: Recognition of functional sites remains a key event in the course of genomic DNA annotation. It is well known that a number of sites have their own specific oligonucleotide content. This pinpoints the fact that the preference of the site-specific nucleotide combinations at adjacent positions within an analyzed functional site could be informative for this site recognition. Hence, Web-available resources describing the site-specific oligonucleotide content of the functional DNA sites and applying the above approach for site recognition are needed. However, they have been poorly developed up to now. RESULTS: To describe the specific oligonucleotide content of the functional DNA sites, we introduce the oligonucleotide alphabets, out of which the frequency matrix for a given site could be constructed in addition to a traditional nucleotide frequency matrix. Thus, site recognition accuracy increases. This approach was implemented in the activated MATRIX database accumulating oligonucleotide frequency matrices of the functional DNA sites. We have demonstrated that the false-positive error of the functional site recognition decreases if the oligonucleotide frequency matrixes are added to the nucleotide frequency matrixes commonly used. AVAILABILITY: The MATRIX database is available on the Web, http://wwwmgs.bionet.nsc.ru/Dbases/MATRIX/ and the mirror site, http://www.cbil.upenn.edu/mgs/systems/c onsfreq/.

MOTIVATION: A reliable recognition of transcription factor binding sites is essential for analysis of regulatory genomic sequences. The experimental data make evident an important role of DNA conformational features for site functioning. However, Internet-available tools for revealing conformational and physicochemical DNA features significant for the site functioning and subsequent use of these features for site recognition have not been developed up to now. RESULTS: We suggest an approach for revealing significant conformational and physicochemical properties of functional sites implemented in the database B-DNA-VIDEO. This database is designed to study the sets of various transcription factor binding sites, providing evidence that transcription factor binding sites are characterized by specific sets of significant conformational and physicochemical DNA properties. For a fixed site, by using the B-DNA features selected for this site recognition, the C-program recognizing this site may be generated, control tested and stored in the database B-DNA-VIDEO. Each B-DNA-VIDEO entry links to the Web-applet recognizing the site, whose significant B-DNA features are stored in this entry as the 'site recognition programs'. The pairwise linked entry-applet pairs are compiled within the B-DNA-VIDEO system, which is simultaneously the database and the program tools package applicable immediately for recognizing the sites stored in the database. Indeed, this is the novelty. Hence, B-DNA-VIDEO is the Web resource of both 'searching for static data' and 'active computation' type, that is why it was called an 'activated database'. AVAILABILITY: B-DNA-VIDEO is available at http://wwwmgs.bionet.nsc.ru/systems/BDNAVideo/ and the mirror site at http://www.cbil.upenn.edu/mgs/systems/c onsfreq/.

MOTIVATION: Gene networks that provide the regulation of physiological processes are the basic feature of organisms. Information regarding the regulation of gene expression and signal transduction pathways is increasing rapidly. However, the information is hard to formalize and systematize. Ways and means for automated visualization of the gene networks based on their formalized description are needed. RESULTS: The object-oriented database GeneNet and the software for its automated visualization have been developed. The main principles of a formalized description of the gene network have been worked out. Antiviral response and erythropoiesis are provided as examples to show how this is achieved. The GeneNet graphical user interface written in Java provides automated generation of the gene network diagrams and allows visualization and exploration of the GeneNet database through the Internet. A system of filters allows the selection of particular components of the network for visualization. AVAILABILITY: The GeneNet database and its graphical user interface are available at http://wwwmgs.bionet.nsc.ru/systems/MGL/GeneN et/ CONTACT: [email protected]

In this paper a new approach for the prediction of protein coding gene structures is described. The principal scheme of prediction is as follows: first, the exons with the best potential are predicted in a sequence with unknown functions and a list of potential amino acid fragments coded by these exons is formed. Second, testing the homology between each amino acid fragment from the list and proteins from the SWISS-PROT database of amino acid sequences. One protein with the best homology is chosen out of all the homologous sequences. Third, reconstruction of the exon-intron structure, basing it on its homology with the chosen protein sequences. The method was tested on an independent control set (20 genes). The results were as follows: 21% of real exons were lost and 3% of non-real exons were found. This system can be used to refine the results of gene prediction systems, especially if highly homologous proteins are found in the amino acid sequence database.

A method for identification of eukaryotic promoters by localization of binding sites for transcription factors has been suggested. The binding sites for a range of transcription factors have been found to be distributed unevenly. Based on these distributions, we have constructed a weight matrix of binding site localization. On the basis of the weight matrix we have, in turn, designed an algorithm for promoter recognition. To increase the accuracy of the method, we have developed a routine that breaks any promoter sample into subsamples. The method to be reported on allows much better recognition accuracy than does the approach based on detection of the TATA box. In particular, the overprediction error is three times lower following our method. The program FunSiteP recognizes promoters from newly uncovered sequences and tentatively identifies the functional class the promoters must belong to. We have introduced the notion of 'regulatory potential' for the degree to which any region of the sequences is similar to the real eukaryotic promoter. By making use of the potential, we have revealed putative transcription start sites and extended regions of transcription regulation.

Using a set of sequences of 63 cleavage/polyadenylation sites of vertebrate pre-mRNA, a generalized consensus matrix was constructed. The elements of the matrix were the absolute frequencies of oligonucleotides of length l at the ith position of sites. The cleavage point of each site was assigned the same position number. To recognize a polyadenylation site in a nucleotide sequence, a multiplicative measure was obtained using the elements of the generalized consensus matrix as weight factors. For any omega-long fragment of a nucleotide sequence, the estimated value of the functional mu was compared with the threshold value mu*. Based on the results obtained, we determined whether or not the given fragment is a processing site.

We developed the computer system SITEVIDEO for analysis and recognition of the functional sites in DNA and RNA molecules. It reveals contextual features essential for site function and thus enable the user to design efficient methods for recognition of the functional sites. We mainly considered only quantitative characteristics reflecting the uneven distribution of oligonucleotides in the sequences of functional sites of interest. The approach suggested makes use of available information about the hierarchical organization of the functional sites, and ensures highly precise prediction of the sites. The present analysis is concerned with the human donor and acceptor splice sites. A method for recognizing these sites in the sequences with an accuracy of approximately 90% was developed.

We present a new pairwise alignment algorithm that uses iterative statistical analysis of homologous subsequences. Apart from the classical conversion of the DOT-matrix characteristic of the Needleman-Wunsch algorithm (NW), we used only those matrix elements that corresponded to the most non-random subsequence homologies. The most reliable elements of the DOT-matrix are written to the compact competition matrices. The algorithm then searches for alignment on the base of only these matrix elements. Our algorithm has low storage and memory requirements, but provides a reliable alignment for the sequences of weak homology (or, at least for the homology regions). In such cases classical NW algorithms often produce unreliable results on the level of statistical noise due to accumulation of random matchings throughout the aligned sequences.