Post-SELEX chemical optimization of a trypanosome-specific RNA aptamer.

African trypanosomes are the causative agent of sleeping sickness. The therapeutics used to control and treat the disease are very ineffective and thus, the development of improved drugs is urgently needed. Recently, new strategies for the design of novel trypanocidals have been put forward. Among them are techniques that rely on parasite-specific RNA aptamers. One approach involves the aptamer-directed transport of lytic compounds to the lysosome of the parasite. The aptamer has been termed 2-16 RNA and here we report the optimization of the RNA for its applications in vivo. To convert aptamer 2-16 into a serum-stable reagent 2'-deoxy-2'-F- and/or 2'-deoxy-2'-NH(2)-uridine- and cytidine-substituted RNAs were generated. While 2'-NH(2)-dC/dU-modified RNAs were RNase-resistant, they were functionally inactive. By contrast, 2'-F-dC/dU-substituted 2-16 RNA retained its ability to bind to live trypanosomes (K(d)=45 nM) and was routed to the lysosome identically to unmodified RNA. 2'-F-dC/dU-substituted 2-16 RNA is thermostable (T(m)=75 degrees C) and has a serum half-life of 3.4 days. Furthermore, aptamer 2-16 was site-specifically PEGylated to increase its serum retention time. Conjugation with PEG polymers < or = 10 kDa only marginally impacted the binding characteristics of the RNA, while the addition of higher molecular mass PEG molecules resulted in non-functional aptamers. Together, the data provide optimized conjugation chemistries for the large-scale production of substituted aptamer 2-16 preparations with improved in vivo functionality.

Integration of biological networks and gene expression data using Cytoscape.

Cytoscape is a free software package for visualizing, modeling and analyzing molecular and genetic interaction networks. This protocol explains how to use Cytoscape to analyze the results of mRNA expression profiling, and other functional genomics and proteomics experiments, in the context of an interaction network obtained for genes of interest. Five major steps are described: (i) obtaining a gene or protein network, (ii) displaying the network using layout algorithms, (iii) integrating with gene expression and other functional attributes, (iv) identifying putative complexes and functional modules and (v) identifying enriched Gene Ontology annotations in the network. These steps provide a broad sample of the types of analyses performed by Cytoscape.

Pathway analysis of coronary atherosclerosis.

Large-scale gene expression studies provide significant insight into genes differentially regulated in disease processes such as cancer. However, these investigations offer limited understanding of multisystem, multicellular diseases such as atherosclerosis. A systems biology approach that accounts for gene interactions, incorporates nontranscriptionally regulated genes, and integrates prior knowledge offers many advantages. We performed a comprehensive gene level assessment of coronary atherosclerosis using 51 coronary artery segments isolated from the explanted hearts of 22 cardiac transplant patients. After histological grading of vascular segments according to American Heart Association guidelines, isolated RNA was hybridized onto a customized 22-K oligonucleotide microarray, and significance analysis of microarrays and gene ontology analyses were performed to identify significant gene expression profiles. Our studies revealed that loss of differentiated smooth muscle cell gene expression is the primary expression signature of disease progression in atherosclerosis. Furthermore, we provide insight into the severe form of coronary artery disease associated with diabetes, reporting an overabundance of immune and inflammatory signals in diabetics. We present a novel approach to pathway development based on connectivity, determined by language parsing of the published literature, and ranking, determined by the significance of differentially regulated genes in the network. In doing this, we identify highly connected "nexus" genes that are attractive candidates for therapeutic targeting and followup studies. Our use of pathway techniques to study atherosclerosis as an integrated network of gene interactions expands on traditional microarray analysis methods and emphasizes the significant advantages of a systems-based approach to analyzing complex disease.

An architecture for biological information extraction and representation.

MOTIVATIONS: Technological advances in biomedical research are generating a plethora of heterogeneous data at a high rate. There is a critical need for extraction, integration and management tools for information discovery and synthesis from these heterogeneous data. RESULTS: In this paper, we present a general architecture, called ALFA, for information extraction and representation from diverse biological data. The ALFA architecture consists of: (i) a networked, hierarchical, hyper-graph object model for representing information from heterogeneous data sources in a standardized, structured format; and (ii) a suite of integrated, interactive software tools for information extraction and representation from diverse biological data sources. As part of our research efforts to explore this space, we have currently prototyped the ALFA object model and a set of interactive software tools for searching, filtering, and extracting information from scientific text. In particular, we describe BioFerret, a meta-search tool for searching and filtering relevant information from the web, and ALFA Text Viewer, an interactive tool for user-guided extraction, disambiguation, and representation of information from scientific text. We further demonstrate the potential of our tools in integrating the extracted information with experimental data and diagrammatic biological models via the common underlying ALFA representation. CONTACT: aditya_vailaya@agilent.com.