Prediction of protein-protein interactions using protein signature profiling

Protein domains are conserved and functionally independent structures that play an important role in interactions among related proteins. Domain-domain interactions have been recently used to predict protein-protein interactions (PPI). In general, the interaction probability of a pair of domains is scored using a trained scoring function. Satisfying a threshold, the protein pairs carrying those domains are regarded as "interacting". In this study, the signature contents of proteins were utilized to predict PPI pairs in Saccharomyces cerevisiae, Caenorhabditis elegans, and Homo sapiens. Similarity between protein signature patterns was scored and PPI predictions were drawn based on the binary similarity scoring function. Results show that the true positive rate of prediction by the proposed approach is approximately 32% higher than that using the maximum likelihood estimation method when compared with a test set, resulting in 22% increase in the area under the receiver operating characteristic (ROC) curve. When proteins containing one or two signatures were removed, the sensitivity of the predicted PPI pairs increased significantly. The predicted PPI pairs are on average 11 times more likely to interact than the random selection at a confidence level of 0.95, and on average 4 times better than those predicted by either phylogenetic profiling or gene expression profiling.     

Characterizing gene sets with FuncAssociate

SUMMARY: FuncAssociate is a web-based tool to help researchers use Gene Ontology attributes to characterize large sets of genes derived from experiment. Distinguishing features of FuncAssociate include the ability to handle ranked input lists, and a Monte Carlo simulation approach that is more appropriate to determine significance than other methods, such as Bonferroni or idák p-value correction. FuncAssociate currently supports 10 organisms (Vibrio cholerae, Shewanella oneidensis, Saccharomyces cerevisiae, Schizosaccharomyces pombe, Arabidopsis thaliana, Caenorhaebditis elegans, Drosophila melanogaster, Mus musculus, Rattus norvegicus and Homo sapiens). AVAILABILITY: FuncAssociate is freely accessible at http://llama.med.harvard.edu/Software.html. Source code (in Perl and C) is freely available to academic users 'as is'.     

Expression signature of the mouse prostate

Genetically engineered mice are being used increasingly for delineating the molecular mechanisms of prostate cancer development. Epithelium-stroma interactions play a critical role in prostate development and tumorigenesis. To better understand gene expression patterns in the normal sexually mature mouse prostate, epithelium and stroma were laser-capture microdissected from ventral, dorsolateral, and anterior prostate lobes. Genome-wide expression was measured by DNA microarrays. Our analysis indicated that the gene expression pattern in the mouse dorsolateral lobe was closest to that of the human prostate peripheral zone, supporting the hypothesis that these prostate compartments are functionally equivalent. Stroma from a given lobe had closer gene expression patterns with stroma from other lobes than epithelium from the same lobe. Stroma appeared to have higher expression complexity than epithelium. Specifically, stromal cells had higher expression levels of genes implicated in cell adhesion, muscle development, and contraction, in structural constituents of cytoskeleton and actin binding, and in components such as sarcomere and extracellular matrix collagen. Among the genes that were enriched in the epithelium were secretory proteins, including seminal vesicle protein secretion 2 and 5. Surprisingly, prostate stroma expressed many osteogenic molecules, as confirmed by immunohistochemistry. A "bone-like" environment in the prostate may predispose prostate cells for survival in the bone. Chemokine Cxcl12 but not its receptor, Cxcr4, was expressed in normal prostate. In prostate tumors, interestingly, Cxcl12 was up-regulated in epithelial cells with a concomitant expression of Cxcr4. Expression of both the receptor and ligand may provide an autocrine mechanism for tumor cell migration and invasion.     

Gene Expression Commons: an open platform for absolute gene expression profiling

Gene expression profiling using microarrays has been limited to comparisons of gene expression between small numbers of samples within individual experiments. However, the unknown and variable sensitivities of each probeset have rendered the absolute expression of any given gene nearly impossible to estimate. We have overcome this limitation by using a very large number (>10,000) of varied microarray data as a common reference, so that statistical attributes of each probeset, such as the dynamic range and threshold between low and high expression, can be reliably discovered through meta-analysis. This strategy is implemented in a web-based platform named "Gene Expression Commons" (https://gexc.stanford.edu/) which contains data of 39 distinct highly purified mouse hematopoietic stem/progenitor/differentiated cell populations covering almost the entire hematopoietic system. Since the Gene Expression Commons is designed as an open platform, investigators can explore the expression level of any gene, search by expression patterns of interest, submit their own microarray data, and design their own working models representing biological relationship among samples.     

Ribosome profiling reveals sequence-independent post-initiation pausing as a signature of translation

The journey of a newly synthesized polypeptide starts in the peptidyltransferase center of the ribosome, from where it traverses the exit tunnel. The interior of the ribosome exit tunnel is neither straight nor smooth. How the ribosome dynamics in vivo is influenced by the exit tunnel is poorly understood. Genome-wide ribosome profiling in mammalian cells reveals elevated ribosome density at the start codon and surprisingly the downstream 5th codon position as well. We found that the highly focused ribosomal pausing shortly after initiation is attributed to the geometry of the exit tunnel, as deletion of the loop region from ribosome protein L4 diminishes translational pausing at the 5th codon position. Unexpectedly, the ribosome variant undergoes translational abandonment shortly after initiation, suggesting that there exists an obligatory step between initiation and elongation commitment. We propose that the post-initiation pausing of ribosomes represents an inherent signature of the translation machinery to ensure productive translation.     

TXTGate: profiling gene groups with text-based information

We implemented a framework called TXTGate that combines literature indices of selected public biological resources in a flexible text-mining system designed towards the analysis of groups of genes. By means of tailored vocabularies, term- as well as gene-centric views are offered on selected textual fields and MEDLINE abstracts used in LocusLink and the Saccharomyces Genome Database. Subclustering and links to external resources allow for in-depth analysis of the resulting term profiles.     

Expression profiling of human glial precursors

Background  

We have generated gene expression databases for human glial precursors, neuronal precursors, astrocyte precursors and neural stem cells and focused on comparing the profile of glial precursors with that of other populations.     

Expression profiling and functional characterization of a CBL-interacting protein kinase gene from Populus euphratica

Key message

This is the first report on the function of a member of the CIPK family in Populus euphratica.

Abstract

The Ca²⁺-dependent salt overly sensitive (SOS) pathway has been shown to play an essential role in maintaining ion homeostasis and conferring salt tolerance. One component of the SOS pathway, SOS1, was identified in the salt-resistant tree P. euphratica. In this study, we identified and functionally characterized another component of the SOS pathway in this tree called PeSOS2 or PeCIPK26. On the basis of protein sequence similarity and complementation studies in Arabidopsis, PeCIPK26 was concluded to be the functional homolog of Arabidopsis AtSOS2. Yeast two-hybrid assays revealed that PeCIPK26 can interact with four calcineurin B-like (CBL) genes, i.e., PeCBL1, PeCBL4/PeSOS3, PeCBL9 and PeCBL10. Autophosphorylation assays showed that PeCIPK26 is an active protein kinase. Expression profile analysis demonstrated that PeCIPK26 is expressed in root, stem and leaf, and throughout the cell including cell membrane, cytoplasm and nucleus; in addition, it can be induced under salt-stress treatment. Functions of PeCIPK26 in salt tolerance were evaluated by gene overexpression in Arabidopsis cipk24 mutants. The better salt tolerance of transgenic plants relative to mutants was shown by their higher germination rate, lower Na⁺ accumulation and higher capacity to discharge Na⁺ when grown with NaCl. These results suggest the involvement of PeCIPK26 in the salt-stress response of P. euphratica.     

Expression profiling of human renal carcinomas with functional taxonomic analysis

Background  

Molecular characterization has contributed to the understanding of the inception, progression, treatment and prognosis of cancer. Nucleic acid array-based technologies extend molecular characterization of tumors to thousands of gene products. To effectively discriminate between tumor sub-types, reliable laboratory techniques and analytic methods are required.     

Massively parallel signature sequencing (MPSS) as a tool for in-depth quantitative gene expression profiling in all organisms.

Massively parallel signature sequencing (MPSS) is one of the newest tools available for conducting in-depth expression profiling. MPSS is an open-ended platform that analyses the level of expression of virtually all genes in a sample by counting the number of individual mRNA molecules produced from each gene. There is no requirement that genes be identified and characterised prior to conducting an experiment. MPSS has a routine sensitivity at a level of a few molecules of mRNA per cell, and the datasets are in a digital format that simplifies the management and analysis of the data. Therefore, of the various microarray and non-microarray technologies currently available, MPSS provides many advantages for generating the type of complete datasets that will help to facilitate hypothesis-driven experiments in the era of digital biology.