Dataset Information

Multi-Level Integration of Environmentally Perturbed Internal Phenotypes Reveals Key Points of Connectivity between Them.

ABSTRACT: 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.

SUBMITTER: Benis N

PROVIDER: S-EPMC5467433 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Multi-Level Integration of Environmentally Perturbed Internal Phenotypes Reveals Key Points of Connectivity between Them.

Benis Nirupama N Kar Soumya K SK Martins Dos Santos Vitor A P VAP Smits Mari A MA Schokker Dirkjan D Suarez-Diez Maria M

Frontiers in physiology 20170612

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-occ ...[more]

PMID: 28659815

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Project description:ObjectivesIntegrating multiple imaging modalities is crucial for MRI data interpretation. The purpose of this study is to determine whether a previously proposed multi-view approach can effectively integrate the histogram features from multi-parametric MRI and whether the selected features can offer incremental prognostic values over clinical variables.MethodsEighty newly-diagnosed glioblastoma patients underwent surgery and chemoradiotherapy. Histogram features of diffusion and perfusion imaging were extracted from contrast-enhancing (CE) and non-enhancing (NE) regions independently. An unsupervised patient clustering was performed by the multi-view approach. Kaplan-Meier and Cox proportional hazards regression analyses were performed to evaluate the relevance of patient clustering to survival. The metabolic signatures of patient clusters were compared using multi-voxel spectroscopy analysis. The prognostic values of histogram features were evaluated by survival and ROC curve analyses.ResultsTwo patient clusters were generated, consisting of 53 and 27 patients respectively. Cluster 2 demonstrated better overall survival (OS) (p = 0.007) and progression-free survival (PFS) (p < 0.001) than Cluster 1. Cluster 2 displayed lower N-acetylaspartate/creatine ratio in NE region (p = 0.040). A higher mean value of anisotropic diffusion in NE region was associated with worse OS (hazard ratio [HR] = 1.40, p = 0.020) and PFS (HR = 1.36, p = 0.031). The seven features selected by this approach showed significantly incremental value in predicting 12-month OS (p = 0.020) and PFS (p = 0.022).ConclusionsThe multi-view clustering method can provide an effective integration of multi-parametric MRI. The histogram features selected may be used as potential prognostic markers.Key points• Multi-parametric magnetic resonance imaging captures multi-faceted tumor physiology. • Contrast-enhancing and non-enhancing tumor regions represent different tumor components with distinct clinical relevance. • Multi-view data analysis offers a method which can effectively select and integrate multi-parametric and multi-regional imaging features.

Project description:While the effect of habitat connectivity on local and regional diversity has been analysed in a number of studies, time-dependent dynamics in metacommunities have received comparatively little consideration. When local patches of a metacommunity are identical in environmental conditions but differ in initial community composition, dispersal among patches may result in homogenization of local communities. In a microcosm experiment with benthic ciliates, we tested the hypothesis that the effect of connectivity on diversity is time-dependent and only transitory, with the degree of connectivity affecting the time to homogenization but not the final outcome. Six microcosms were connected to a metacommunity with one of three levels of connectivity. The six patches differed in initial community composition but were identical in environmental conditions. We found a time-dependent and transitory effect of connectivity on local and regional richness and on local Shannon diversity, while Bray-Curtis dissimilarity and regional Shannon diversity were persistently affected by connectivity. Local richness increased and regional richness decreased with connectivity during the initial phase of the experiment but soon converged to similar values in all three connectivity treatments. Local Shannon diversity was unimodally related to time, with maximum diversity reached sooner with high than with medium or low connectivity. Eventually, however, local diversity converged to similar values irrespective of connectivity. At the regional scale, Shannon diversity was persistently lower with high than with low connectivity. While initial differences in community composition vanished with medium and high connectivity, they were maintained with low connectivity resulting in persistently high beta and regional diversity. The effect of connectivity on ciliate community composition translated down to the algal resource, as stronger dominance of the superior competitor with high and medium connectivity resulted in stronger depletion of the resource.

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Multi-Level Integration of Environmentally Perturbed Internal Phenotypes Reveals Key Points of Connectivity between Them.

Publications

Multi-Level Integration of Environmentally Perturbed Internal Phenotypes Reveals Key Points of Connectivity between Them.

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