6533b822fe1ef96bd127cdcb
RESEARCH PRODUCT
Multi-level integration of environmentally perturbed internal phenotypes reveals key points of connectivity between them
Nirupama BenisSoumya K. KarVitor A. P. Martins Dos SantosVitor A. P. Martins Dos SantosMari A. SmitsMari A. SmitsDirkjan SchokkerMaria Suarez-diezsubject
0301 basic medicineProteomicsPhysiologySystems biologyComputational biologyBiologyProteomicslcsh:PhysiologyCorrelation03 medical and health sciences0302 clinical medicineGenotype-phenotype distinctionGastrointestinal tractPhysiology (medical)GenotypeMetabolomicsSystems and Synthetic BiologyHost-Microbe InteractomicsFokkerij & GenomicaTranscriptomicsOriginal ResearchVLAGHost Pathogen Interaction & DiagnosticsGeneticsSysteem en Synthetische BiologieInternal phenotypelcsh:QP1-981Null modelMicrobiotaBacteriologieBacteriologyBacteriology Host Pathogen Interaction & DiagnosticsPhenotypeHost Pathogen Interactie & Diagnostiek030104 developmental biologyBacteriologie Host Pathogen Interactie & DiagnostiekKey (cryptography)Data integrationSystems biology030217 neurology & neurosurgeryAnimal Breeding & Genomicsdescription
The genotype and external phenotype of organisms are linked by so-called internal phenotypes which are influenced by environmental conditions. In this study, we used five existing -omics datasets representing five different layers of internal phenotypes, which were simultaneously measured in dietarily perturbed mice. We performed 10 pair-wise correlation analyses verified with a null model built from randomized data. Subsequently, the inferred networks were merged and literature mined for co-occurrences of identified linked nodes. Densely connected internal phenotypes emerged. Forty-five nodes have links with all other data-types and we denote them "connectivity hubs." In literature, we found proof of 6% of the 577 connections, suggesting a biological meaning for the observed correlations. The observed connectivities between metabolite and cytokines hubs showed higher numbers of literature hits as compared to the number of literature hits on the connectivities between the microbiota and gene expression internal phenotypes. We conclude that multi-level integrated networks may help to generate hypotheses and to design experiments aiming to further close the gap between genotype and phenotype. We describe and/or hypothesize on the biological relevance of four identified multi-level connectivity hubs.
year | journal | country | edition | language |
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2017-06-12 |