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Exploring pathway interactions in insulin resistant mouse liver.

ABSTRACT: BACKGROUND: Complex phenotypes such as insulin resistance involve different biological pathways that may interact and influence each other. Interpretation of related experimental data would be facilitated by identifying relevant pathway interactions in the context of the dataset. RESULTS: We developed an analysis approach to study interactions between pathways by integrating gene and protein interaction networks, biological pathway information and high-throughput data. This approach was applied to a transcriptomics dataset to investigate pathway interactions in insulin resistant mouse liver in response to a glucose challenge. We identified regulated pathway interactions at different time points following the glucose challenge and also studied the underlying protein interactions to find possible mechanisms and key proteins involved in pathway cross-talk. A large number of pathway interactions were found for the comparison between the two diet groups at t = 0. The initial response to the glucose challenge (t = 0.6) was typed by an acute stress response and pathway interactions showed large overlap between the two diet groups, while the pathway interaction networks for the late response were more dissimilar. CONCLUSIONS: Studying pathway interactions provides a new perspective on the data that complements established pathway analysis methods such as enrichment analysis. This study provided new insights in how interactions between pathways may be affected by insulin resistance. In addition, the analysis approach described here can be generally applied to different types of high-throughput data and will therefore be useful for analysis of other complex datasets as well.

SUBMITTER: Kelder T

PROVIDER: S-EPMC3169508 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

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Exploring pathway interactions in insulin resistant mouse liver.

Kelder Thomas T Eijssen Lars L Kleemann Robert R van Erk Marjan M Kooistra Teake T Evelo Chris C

BMC systems biology 20110815

<h4>Background</h4>Complex phenotypes such as insulin resistance involve different biological pathways that may interact and influence each other. Interpretation of related experimental data would be facilitated by identifying relevant pathway interactions in the context of the dataset.<h4>Results</h4>We developed an analysis approach to study interactions between pathways by integrating gene and protein interaction networks, biological pathway information and high-throughput data. This approach ...[more]

PMID: 21843341

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Project description:Multiple millennia of human evolution have shaped the chemical composition of breast milk toward an optimal human body fluid for nutrition and protection and for shaping the early gut microbiota of newborns. This biological fluid is composed of water, lipids, simple and complex carbohydrates, proteins, immunoglobulins, and hormones. Potential interactions between hormones present in mother's milk and the microbial community of the newborn are a very fascinating yet unexplored topic. In this context, insulin, in addition to being one of the most prevalent hormones in breast milk, is also involved in a metabolic disease that affects many pregnant women, i.e., gestational diabetes mellitus (GDM). Analysis of 3,620 publicly available metagenomic data sets revealed that the bifidobacterial community varies in relation to the different concentrations of this hormone in breast milk of healthy and diabetic mothers. Starting from this assumption, in this study, we explored possible molecular interactions between this hormone and bifidobacterial strains that represent bifidobacterial species commonly occurring in the infant gut using 'omics' approaches. Our findings revealed that insulin modulates the bifidobacterial community by apparently improving the persistence of the Bifidobacterium bifidum taxon in the infant gut environment compared to other typical infant-associated bifidobacterial species. IMPORTANCE Breast milk is a key factor in modulating the infant's intestinal microbiota composition. Even though the interaction between human milk sugars and bifidobacteria has been extensively studied, there are other bioactive compounds in human milk that may influence the gut microbiota, such as hormones. In this article, the molecular interaction of the human milk hormone insulin and the bifidobacterial communities colonizing the human gut in the early stages of life has been explored. This molecular cross talk was assessed using an in vitro gut microbiota model and then analyzed by various omics approaches, allowing the identification of genes associated with bacterial cell adaptation/colonization in the human intestine. Our findings provide insights into the manner by which assembly of the early gut microbiota may be regulated by host factors such as hormones carried by human milk.

Dataset Information

Exploring pathway interactions in insulin resistant mouse liver.

Publications

Exploring pathway interactions in insulin resistant mouse liver.

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