SELEX_DB: an activated database on selected randomized DNA/RNA sequences addressed to genomic sequence annotation

Improving synthesis and binding affinities of nucleic acid aptamers and their therapeutics and diagnostic applications

Nucleic acid aptamers have captivated the attention of analytical and medicinal scientists globally due to their several advantages as recognition molecules over conventional antibodies because of their small size, simple and inexpensive synthesis, broad target range, and high stability in varied environmental conditions. These recognition molecules can be chemically modified to make them resistant to nuclease action in blood serum, reduce rapid renel clearance, improve the target affinity and selectivity, and make them amenable to chemically conjugate with a support system that facilitates their selective applications. This review focuses on the development of efficient aptamer candidates and their application in clinical diagnosis and therapeutic applications. Significant advances have been made in aptamer-based diagnosis of infectious and non-infectious diseases. Collaterally, the progress made in therapeutic applications of aptamers is encouraging, as evident from their use in diagnosing cancer, neurodegenerative diseases, microbial infection, and in imaging. This review also updates the progress on clinical trials of many aptamer-based products of commercial interests. The key development and critical issues on the subject have been summarized in the concluding remarks.

Harnessing genetic engineering to drive economic bioproduct production in algae

Our reliance on agriculture for sustenance, healthcare, and resources has been essential since the dawn of civilization. However, traditional agricultural practices are no longer adequate to meet the demands of a burgeoning population amidst climate-driven agricultural challenges. Microalgae emerge as a beacon of hope, offering a sustainable and renewable source of food, animal feed, and energy. Their rapid growth rates, adaptability to non-arable land and non-potable water, and diverse bioproduct range, encompassing biofuels and nutraceuticals, position them as a cornerstone of future resource management. Furthermore, microalgae's ability to capture carbon aligns with environmental conservation goals. While microalgae offers significant benefits, obstacles in cost-effective biomass production persist, which curtails broader application. This review examines microalgae compared to other host platforms, highlighting current innovative approaches aimed at overcoming existing barriers. These approaches include a range of techniques, from gene editing, synthetic promoters, and mutagenesis to selective breeding and metabolic engineering through transcription factors.

Refactoring transcription factors for metabolic engineering

Due to the ability to regulate target metabolic pathways globally and dynamically, metabolic regulation systems composed of transcription factors have been widely used in metabolic engineering and synthetic biology. This review introduced the categories, action principles, prediction strategies, and related databases of transcription factors. Then, the application of global transcription machinery engineering technology and the transcription factor-based biosensors and quorum sensing systems are overviewed. In addition, strategies for optimizing the transcriptional regulatory tools' performance by refactoring transcription factors are summarized. Finally, the current limitations and prospects of constructing various regulatory tools based on transcription factors are discussed. This review will provide theoretical guidance for the rational design and construction of transcription factor-based metabolic regulation systems.

Current approaches in SELEX: An update to aptamer selection technology

Systematic evolution of ligands by exponential enrichment (SELEX) is a well-established and efficient technology for the generation of oligonucleotides with a high target affinity. These SELEX-derived single stranded DNA and RNA molecules, called aptamers, were selected against various targets, such as proteins, cells, microorganisms, chemical compounds etc. They have a great potential in the use as novel antibodies, in cancer theragnostics and in biomedical research. Vast interest in aptamers stimulated continuous development of SELEX, which underwent numerous modifications since its first application in 1990. Novel modifications made the selection process more efficient, cost-effective and significantly less time-consuming. This article brings a comprehensive and up-to-date review of recent advances in SELEX methods and pinpoints advantages, main obstacles and limitations. The post-SELEX strategies and examples of application are also briefly outlined in this review.

A structural-based strategy for recognition of transcription factor binding sites

Scanning through genomes for potential transcription factor binding sites (TFBSs) is becoming increasingly important in this post-genomic era. The position weight matrix (PWM) is the standard representation of TFBSs utilized when scanning through sequences for potential binding sites. However, many transcription factor (TF) motifs are short and highly degenerate, and methods utilizing PWMs to scan for sites are plagued by false positives. Furthermore, many important TFs do not have well-characterized PWMs, making identification of potential binding sites even more difficult. One approach to the identification of sites for these TFs has been to use the 3D structure of the TF to predict the DNA structure around the TF and then to generate a PWM from the predicted 3D complex structure. However, this approach is dependent on the similarity of the predicted structure to the native structure. We introduce here a novel approach to identify TFBSs utilizing structure information that can be applied to TFs without characterized PWMs, as long as a 3D complex structure (TF/DNA) exists. This approach utilizes an energy function that is uniquely trained on each structure. Our approach leads to increased prediction accuracy and robustness compared with those using a more general energy function. The software is freely available upon request.

MINING GENOME VARIATION TO ASSOCIATE GENETIC DISEASE WITH MUTATION ALTERATIONS AND ORTHO/PARALOGOUS POLIMORPHYSMS IN TRANSCRIPTION FACTOR BINDING SITE

We have developed a system rSNP_Guide, , predicting the transcription factor (TF) binding sites on DNA, which mutation-caused alterations may explain disease penetration. rSNP_Guide uses the detected alterations in the mutant DNA binding to unknown TF caused by diseases and, upon the DNA sequences, calculates the alterations in known TF sites so that to select only the known ones with calculated alterations in the best consistence with those detected. Our system has been control tested on the SNP's with known site-disease relationships. For practical aims, two TF sites associated with diseases were predicted and confirmed by the immune assay with anti-TF antibodies. In the case of tumor susceptibility, the GATA site in the second intron of mouse K-ras gene was truly predicted, whereas mutation damage of this site causes tumor resistance. In the case of alcohol dependencies and others behavioral diseases, the mutation-caused spurious YY1 site in the sixth intron of human tryptophan 2,3-dioxygenase (TDO2) gene was successfully predicted. Finally, sixteen non-documented TF sites localizable at both orthologous and paralogous genes were first characterized by three rates "present", "weakened" or "absent", with significance estimated by rSNP_Guide relatively to six TF sites with known mutation-caused alterations in DNA/TF-binding.

Inferring protein-DNA interaction parameters from SELEX experiments

Systematic Evolution of Ligands by EXponential enrichment (SELEX) is an experimental procedure that allows extraction, from an initially random pool of oligonucleotides, of the oligomers with a high binding affinity for a given molecular target. The highest affinity binding sequences isolated through SELEX can have numerous research, diagnostic, and therapeutic applications. Recently, important new modifications of the SELEX protocol have been proposed. In particular, a suitably modified SELEX experiment, together with an appropriate computational procedure, allows inference of protein-DNA interaction parameters with up to now unprecedented accuracy. Such inference is possible even when there is no a priori information on transcription factor binding specificity, which allows accurate predictions of binding sites for any transcription factor of interest. In this chapter we discuss how to accurately determine protein-DNA interaction parameters from SELEX experiments. The chapter addresses experimental and computational procedure needed to generate and analyze appropriate data.

SELEX experiments: new prospects, applications and data analysis in inferring regulatory pathways

Systematic Evolution of Ligands by EXponential enrichment (SELEX) is an experimental procedure that allows extraction, from an initially random pool of oligonucleotides, of the oligomers with a desired binding affinity for a given molecular target. The procedure can be used to infer the strongest binders for a given DNA or RNA binding protein, and the highest affinity binding sequences isolated through SELEX can have numerous research, diagnostic and therapeutic applications. Recently, important new modifications of the SELEX protocol have been proposed. In particular, a modification of the standard SELEX procedure allows generating a dataset from which protein-DNA interaction parameters can be determined with unprecedented accuracy. Another variant of SELEX allows investigating interactions of a protein with nucleic-acid fragments derived from the entire genome of an organism. We review here different SELEX-based methods, with particular emphasis on the experimental design and on the applications aimed at inferring protein-DNA interactions. In addition to the experimental issues, we also review relevant methods of data analysis, as well as theoretical modeling of SELEX.

Recognition of interferon-inducible sites, promoters, and enhancers

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.

HTPSELEX--a database of high-throughput SELEX libraries for transcription factor binding sites

HTPSELEX is a public database providing access to primary and derived data from high-throughput SELEX experiments aimed at characterizing the binding specificity of transcription factors. The resource is primarily intended to serve computational biologists interested in building models of transcription factor binding sites from large sets of binding sequences. The guiding principle is to make available all information that is relevant for this purpose. For each experiment, we try to provide accurate information about the protein material used, details of the wet lab protocol, an archive of sequencing trace files, assembled clone sequences (concatemers) and complete sets of in vitro selected protein-binding tags. In addition, we offer in-house derived binding sites models. HTPSELEX also offers reasonably large SELEX libraries obtained with conventional low-throughput protocols. The FTP site contains the trace archives and database flatfiles. The web server offers user-friendly interfaces for viewing individual entries and quality-controlled download of SELEX sequence libraries according to a user-defined sequencing quality threshold. HTPSELEX is available from ftp://ftp.isrec.isb-sib.ch/pub/databases/htpselex/ and http://www.isrec.isb-sib.ch/htpselex.

Aptamer database

The aptamer database is designed to contain comprehensive sequence information on aptamers and unnatural ribozymes that have been generated by in vitro selection methods. Such data are not normally collected in 'natural' sequence databases, such as GenBank. Besides serving as a storehouse of sequences that may have diagnostic or therapeutic utility, the database serves as a valuable resource for theoretical biologists who describe and explore fitness landscapes. The database is updated monthly and is publicly available at http://aptamer. icmb.utexas.edu/.

A non-parametric model for transcription factor binding sites

We introduce a non-parametric representation of transcription factor binding sites which can model arbitrary dependencies between positions. As two parameters are varied, this representation smoothly interpolates between the empirical distribution of binding sites and the standard position-specific scoring matrix (PSSM). In a test of generalization to unseen binding sites using 10-fold cross-validation on known binding sites for 95 TRANSFAC transcription factors, this representation outperforms PSSMs on between 65 and 89 of the 95 transcription factors, depending on the choice of the two adjustable parameters. We also discuss how the non- parametric representation may be incorporated into frameworks for finding binding sites given only a collection of unaligned promoter regions.

SELEX_DB: a database on in vitro selected oligomers adapted for recognizing natural sites and for analyzing both SNPs and site-directed mutagenesis data

SELEX_DB is an online resource containing both the experimental data on in vitro selected DNA/RNA oligomers (aptamers) and the applets for recognition of these oligomers. Since in vitro experimental data are evidently system-dependent, the new release of the SELEX_DB has been supplemented by the database SYSTEM storing the experimental design. In addition, the recognition applet package, SELEX_TOOLS, applying in vitro selected data to annotation of the genome DNA, is accompanied by the cross-validation test database CROSS_TEST discriminating the sites (natural or other) related to in vitro selected sites out of random DNA. By cross-validation testing, we have unexpectedly observed that the recognition accuracy increases with the growth of homology between the training and test sets of protein binding sequences. For natural sites, the recognition accuracy was lower than that for the nearest protein homologs and higher than that for distant homologs and non-homologous proteins binding the common site. The current SELEX_DB release is available at http://wwwmgs.bionet.nsc.ru/mgs/systems/selex/.

ACTIVITY: a database on DNA/RNA sites activity adapted to apply sequence-activity relationships from one system to another

ACTIVITY is a database on DNA/RNA site sequences with known activity magnitudes, measurement systems, sequence-activity relationships under fixed experimental conditions and procedures to adapt these relationships from one measurement system to another. This database deposits information on DNA/RNA affinities to proteins and cell nuclear extracts, cutting efficiencies, gene transcription activity, mRNA translation efficiencies, mutability and other biological activities of natural sites occurring within promoters, mRNA leaders, and other regulatory regions in pro- and eukaryotic genomes, their mutant forms and synthetic analogues. Since activity magnitudes are heavily system-dependent, the current version of ACTIVITY is supplemented by three novel sub-databases: (i) SYSTEM, measurement systems; (ii) KNOWLEDGE, sequence-activity relationships under fixed experimental conditions; and (iii) CROSS_TEST, procedures adapting a relationship from one measurement system to another. These databases are useful in molecular biology, pharmacogenetics, metabolic engineering, drug design and biotechnology. The databases can be queried using SRS and are available through the Web, http://wwwmgs. bionet.nsc.ru/systems/Activity/.