MAPPINGS v1.0, a tool for network analysis of large phospho-signalling datasets: application to host erythrocyte response to Plasmodium infection

Phosphorylation-based signalling implicates a complex and intertwined series of pathways and is critical to all domains of life. The interconnectivity between pathways results in the emergence of complex networks whose elucidation present a serious challenge. Large datasets of phosphorylation interactions through the activity of kinases on their numerous substrates are constantly being generated, however deciphering the complex network structure hidden in these datasets remains challenging. Many phosphorylation interactions occurring in human cells have been identified and constitute the basis for the known phosphorylation interaction network. We overlayed onto this network phosphorylation datasets obtained from an antibody microarray approach aimed at determining changes in phospho-signalling of host erythrocytes to infection with the malaria parasite Plasmodium falciparum. To analyse the datasets now mapped into the interaction network, we designed a pathway analysis tool denoted MAPPINGS that uses random walks to identify chains of phosphorylation events occurring much more or much less frequently than expected. MAPPINGS highlights pathways of phosphorylation that work synergistically, providing a rapid interpretation of the most critical pathways in each dataset. MAPPINGS confirmed several signalling interactions previously shown to be modulated by infection, and revealed additional interactions which could form the basis of numerous future studies. The MAPPINGS analysis strategy described here is widely applicable to comparative phosphorylation datasets in any context (e.g. response of cells to infection, treatment, or comparison between differentiation stages of any cell populations) and provides a rapid and reliable analysis to guide validation studies.

An Integrative Multi-Omics Workflow to Address Multifactorial Toxicology Experiments

Toxicology studies can take advantage of omics approaches to better understand the phenomena underlying the phenotypic alterations induced by different types of exposure to certain toxicants. Nevertheless, in order to analyse the data generated from multifactorial omics studies, dedicated data analysis tools are needed. In this work, we propose a new workflow comprising both factor deconvolution and data integration from multiple analytical platforms. As a case study, 3D neural cell cultures were exposed to trimethyltin (TMT) and the relevance of the culture maturation state, the exposure duration, as well as the TMT concentration were simultaneously studied using a metabolomic approach combining four complementary analytical techniques (reversed-phase LC and hydrophilic interaction LC, hyphenated to mass spectrometry in positive and negative ionization modes). The ANOVA multiblock OPLS (AMOPLS) method allowed us to decompose and quantify the contribution of the different experimental factors on the outcome of the TMT exposure. Results showed that the most important contribution to the overall metabolic variability came from the maturation state and treatment duration. Even though the contribution of TMT effects represented the smallest observed modulation among the three factors, it was highly statistically significant. The MetaCore™ pathway analysis tool revealed TMT-induced alterations in biosynthetic pathways and in neuronal differentiation and signaling processes, with a predominant deleterious effect on GABAergic and glutamatergic neurons. This was confirmed by combining proteomic data, increasing the confidence on the mechanistic understanding of such a toxicant exposure.

TriPOINT: a software tool to prioritize important genes in pathways and their non-coding regulators

Summary Current approaches for pathway analyses focus on representing gene expression levels on graph representations of pathways and conducting pathway enrichment among differentially expressed genes. However, gene expression levels by themselves do not reflect the overall picture as non-coding factors play an important role to regulate gene expression. To incorporate these non-coding factors into pathway analyses and to systematically prioritize genes in a pathway we introduce a new software: Triangulation of Perturbation Origins and Identification of Non-Coding Targets. Triangulation of Perturbation Origins and Identification of Non-Coding Targets is a pathway analysis tool, implemented in Java that identifies the significance of a gene under a condition (e.g. a disease phenotype) by studying graph representations of pathways, analyzing upstream and downstream gene interactions and integrating non-coding regions that may be regulating gene expression levels. Availability and implementation The TriPOINT open source software is freely available at https://github.uconn.edu/ajt06004/TriPOINT under the GPL v3.0 license. Supplementary information Supplementary data are available at Bioinformatics online.

Decomposing the Mechanism of Qishen Granules in the Treatment of Heart Failure by a Quantitative Pathway Analysis Method

Qishen granules (QSG) have beneficial therapeutic effects for heart failure, but the effects of decomposed recipes, including Wenyang Yiqi Huoxue (WYH) and Qingre Jiedu (QJ), are not clear. In this study, the efficacy of WYH and QJ on heart failure is evaluated by using transverse aortic constriction (TAC) induced mice and the significantly changed genes in heart tissues were screened with a DNA array. Furthermore, a new quantitative pathway analysis tool is developed to evaluate the differences of pathways in different groups and to identify the pharmacological contributions of the decomposed recipes. Finally, the related genes in the significantly changed pathways are verified by a real-time polymerase chain reaction and a Western blot. Our data show that both QJ and WYH improve the left ventricular ejection fraction, which explain their contributions to protect against heart failure. In the energy metabolism, QJ achieves the therapeutic effects of QSG through nicotinamide nucleotide transhydrogenase (Nnt)-mediated mechanisms. In ventricular remodeling and inflammation reactions, QJ and WYH undertake the therapeutic effects through 5′-nucleotidase ecto (Nt5e)-mediated mechanisms. Together, QJ and WYH constitute the therapeutic effects of QSG and play important roles in myocardial energy metabolism and inflammation, which can exert therapeutic effects for heart failure.

A Pathway Analysis Tool for Analyzing Microarray Data of Species with Low Physiological Information

Pathway information provides insight into the biological processes underlying microarray data. Pathway information is widely available for humans and laboratory animals in databases through the internet, but less for other species, for example, livestock. Many software packages use species-specific gene IDs that cannot handle genomics data from other species. We developed a species-independent method to search pathways databases to analyse microarray data. Three PERL scripts were developed that use the names of the genes on the microarray. (1) Add synonyms of gene names by searching the Gene Ontology (GO) database. (2) Search the Kyoto Encyclopaedia of Genes and Genomes (KEGG) database for pathway information using this GO-enriched gene list. (3) Combine the pathway data with the microarray data and visualize the results using color codes indicating regulation. To demonstrate the power of the method, we used a previously reported chicken microarray experiment investigating line-specific reactions to Salmonella infection as an example.