Dataset Information

MathIOmica: An Integrative Platform for Dynamic Omics.

ABSTRACT: Multiple omics data are rapidly becoming available, necessitating the use of new methods to integrate different technologies and interpret the results arising from multimodal assaying. The MathIOmica package for Mathematica provides one of the first extensive introductions to the use of the Wolfram Language to tackle such problems in bioinformatics. The package particularly addresses the necessity to integrate multiple omics information arising from dynamic profiling in a personalized medicine approach. It provides multiple tools to facilitate bioinformatics analysis, including importing data, annotating datasets, tracking missing values, normalizing data, clustering and visualizing the classification of data, carrying out annotation and enumeration of ontology memberships and pathway analysis. We anticipate MathIOmica to not only help in the creation of new bioinformatics tools, but also in promoting interdisciplinary investigations, particularly from researchers in mathematical, physical science and engineering fields transitioning into genomics, bioinformatics and omics data integration.

SUBMITTER: Mias GI

PROVIDER: S-EPMC5121649 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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MathIOmica: An Integrative Platform for Dynamic Omics.

Mias George I GI Yusufaly Tahir T Roushangar Raeuf R Brooks Lavida R K LR Singh Vikas V VV Christou Christina C

Scientific reports 20161124

Multiple omics data are rapidly becoming available, necessitating the use of new methods to integrate different technologies and interpret the results arising from multimodal assaying. The MathIOmica package for Mathematica provides one of the first extensive introductions to the use of the Wolfram Language to tackle such problems in bioinformatics. The package particularly addresses the necessity to integrate multiple omics information arising from dynamic profiling in a personalized medicine a ...[more]

PMID: 27883025

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Project description:Bacteria constantly face stress conditions and therefore mount specific responses to ensure adaptation and survival. Stress responses were believed to be predominantly regulated at the transcriptional level. In the phototrophic bacterium Rhodobacter sphaeroides the response to singlet oxygen is initiated by alternative sigma factors. Further adaptive mechanisms include post-transcriptional and post-translational events, which have to be considered to gain a deeper understanding of how sophisticated regulation networks operate. To address this issue, we integrated three layers of regulation: (1) total mRNA levels at different time-points revealed dynamics of the transcriptome, (2) mRNAs in polysome fractions reported on translational regulation (translatome), and (3) SILAC-based mass spectrometry was used to quantify protein abundances (proteome). The singlet oxygen stress response exhibited highly dynamic features regarding short-term effects and late adaptation, which could in part be assigned to the sigma factors RpoE and RpoH2 generating distinct expression kinetics of corresponding regulons. The occurrence of polar expression patterns of genes within stress-inducible operons pointed to an alternative of dynamic fine-tuning upon stress. In addition to transcriptional activation, we observed significant induction of genes at the post-transcriptional level (translatome), which identified new putative regulators and assigned genes of quorum sensing to the singlet oxygen stress response. Intriguingly, the SILAC approach explored the stress-dependent decline of photosynthetic proteins, but also identified 19 new open reading frames, which were partly validated by RNA-seq. We propose that comparative approaches as presented here will help to create multi-layered expression maps on the system level ("expressome"). Finally, intense mass spectrometry combined with RNA-seq might be the future tool of choice to re-annotate genomes in various organisms and will help to understand how they adapt to alternating conditions.

Dataset Information

MathIOmica: An Integrative Platform for Dynamic Omics.

Publications

MathIOmica: An Integrative Platform for Dynamic Omics.

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