Enhancing the utility of Proteomics Signature Profiling (PSP) with Pathway Derived Subnets (PDSs), performance analysis and specialised ontologies

BACKGROUND

Proteomics Signature Profiling (PSP) is a novel hit-rate based method that proved useful in resolving consistency and coverage issues in proteomics. As a follow-up study, several points need to be addressed: 1/ PSP's generalisability to pathways, 2/ understanding the biological interplay between significant complexes and pathway subnets co-located on the same pathways on our liver cancer dataset, 3/ understanding PSP's false positive rate and 4/ demonstrating that PSP works on other suitable proteomics datasets as well as expanding PSP's analytical resolution via the use of specialised ontologies.

RESULTS

1/ PSP performs well with Pathway-Derived Subnets (PDSs). Comparing the performance of PDSs derived from various pathway databases, we find that an integrative approach is best for optimising analytical resolution. Feature selection also confirms that significant PDSs are closely connected to the cancer phenotype.2/ In liver cancer, correlation studies of significant PSP complexes and PDSs co-localised on the same pathways revealed an interesting relationship between the purine metabolism pathway and two other complexes involved in DNA repair. Our work suggests progression to poor stage requires additional mutations that disrupt DNA repair enzymes.3/ False positive analysis reveals that PSP, applied on both complexes and PDSs, is powerful and precise.4/ Via an expert-curated lipid ontology, we uncovered several interesting lipid-associated complexes that could be associated with cancer progression. Of particular interest is the HMGB1-HMGB2-HSC70-ERP60-GAPDH complex which is also involved in DNA repair. We also demonstrated generalisability of PSP using a non-small-cell lung carcinoma data set.

CONCLUSIONS

PSP is a powerful and precise technique, capable of identifying biologically coherent features. It works with biological complexes, network-predicted clusters as well as PDSs. Here, an instance of the interplay between significant PDSs and complexes, possibly significantly involved in liver cancer progression but not well understood as yet, is demonstrated. Also demonstrated is the enhancement of PSP's analytical resolution using specialised ontologies.

The role of miRNAs in complex formation and control

microRibonucleic acid (miRNAs) are small regulatory molecules that act by mRNA degradation or via translational repression. Although many miRNAs are ubiquitously expressed, a small subset have differential expression patterns that may give rise to tissue-specific complexes.

MOTIVATION

This work studies gene targeting patterns amongst miRNAs with differential expression profiles, and links this to control and regulation of protein complexes.

RESULTS

We find that, when a pair of miRNAs are not expressed in the same tissues, there is a higher tendency for them to target the direct partners of the same hub proteins. At the same time, they also avoid targeting the same set of hub-spokes. Moreover, the complexes corresponding to these hub-spokes tend to be specific and nonoverlapping. This suggests that the effect of miRNAs on the formation of complexes is specific.

SEAN: SNP prediction and display program utilizing EST sequence clusters

SEAN is an application that predicts single nucleotide polymorphisms (SNPs) using multiple sequence alignments produced from expressed sequence tag (EST) clusters. The algorithm uses rules of sequence identity and SNP abundance to determine the quality of the prediction. A Java viewer is provided to display the EST alignments and predicted SNPs.

Visualization of microarray results to assist interpretation

Whole genome microarrays allow assessment of the profile of genes expressed under particular experimental conditions, including external stimuli such as pH or temperature, and internal changes brought about by deleting or over-expressing a gene. Such experiments produce large data sets, for which sophisticated analysis software is available. What is lacking are tools for analysing data sets from different experiments, in order to test and generate hypotheses about the links between regulatory networks. We describe here a method for presenting results from different experiments as a directed graph constructed using an automated graph drawing program xneato, enhanced by a logic program designed to cluster data and aid in the generation of hypotheses about possible gene interactions. A web-based front-end to the system has been constructed to explore and manipulate the graphical displays produced. Results of microarray experiments on Mycobacterium tuberculosis were used to develop and evaluate the visualization tool and initiate the development of an inference system for gene interactions based on such data. The GeneGraph project can be accessed at: zebrafish.doc.ic.ac.uk

GANESH: software for customized annotation of genome regions

GANESH is a software package designed to support the genetic analysis of regions of human and other genomes. It provides a set of components that may be assembled to construct a self-updating database of DNA sequence, mapping data, and annotations of possible genome features. Once one or more remote sources of data for the target region have been identified, all sequences for that region are downloaded, assimilated, and subjected to a (configurable) set of standard database-searching and genome-analysis packages. The results are stored in compressed form in a relational database, and are updated automatically on a regular schedule so that they are always immediately available in their most up-to-date versions. A Java front-end, executed as a stand alone application or web applet, provides a graphical interface for navigating the database and for viewing the annotations. There are facilities for importing and exporting data in the format of the Distributed Annotation System (DAS), enabling a GANESH database to be used as a component of a DAS configuration. The system has been used to construct databases for about a dozen regions of human chromosomes and for three regions of mouse chromosomes.

An integrated genetic, radiation hybrid, physical and transcription map of a region of distal mouse chromosome 12, including an imprinted locus and the 'Legs at odd angles' (Loa) mutation

A variety of loci with interesting patterns of regulation such as imprinted expression, and critical functions such as involvement in tumour necrosis factor pathways, map to a distal portion of mouse chromosome 12. This region also contains disease related loci including the 'Legs at odd angles' mutation (Loa) that we are pursuing in a positional cloning project. To further define the region and prepare for comparative sequencing projects, we have produced genetic, radiation hybrid, physical and transcript maps of the region, with probes providing anchors between the maps. We show a summary of 95 markers and 91 genomic clones that has enabled us to identify 18 transcripts including new genes and candidates for Loa which will help in future studies of gene context and regulation.