Dataset Information

Exploring Host-Microbiome Interactions using an in Silico Model of Biomimetic Robots and Engineered Living Cells.

ABSTRACT: The microbiome's underlying dynamics play an important role in regulating the behavior and health of its host. In order to explore the details of these interactions, we created an in silico model of a living microbiome, engineered with synthetic biology, that interfaces with a biomimetic, robotic host. By analytically modeling and computationally simulating engineered gene networks in these commensal communities, we reproduced complex behaviors in the host. We observed that robot movements depended upon programmed biochemical network dynamics within the microbiome. These results illustrate the model's potential utility as a tool for exploring inter-kingdom ecological relationships. These systems could impact fields ranging from synthetic biology and ecology to biophysics and medicine.

SUBMITTER: Heyde KC

PROVIDER: S-EPMC4648426 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Exploring Host-Microbiome Interactions using an in Silico Model of Biomimetic Robots and Engineered Living Cells.

Heyde Keith C KC Ruder Warren C WC

Scientific reports 20150716

The microbiome's underlying dynamics play an important role in regulating the behavior and health of its host. In order to explore the details of these interactions, we created an in silico model of a living microbiome, engineered with synthetic biology, that interfaces with a biomimetic, robotic host. By analytically modeling and computationally simulating engineered gene networks in these commensal communities, we reproduced complex behaviors in the host. We observed that robot movements depen ...[more]

PMID: 26178309

Similar Datasets

Project description:BackgroundHost-microbiome interactions (HMIs) are critical for the modulation of biological processes and are associated with several diseases. Extensive HMI studies have generated large amounts of data. We propose that the logical representation of the knowledge derived from these data and the standardized representation of experimental variables and processes can foster integration of data and reproducibility of experiments and thereby further HMI knowledge discovery.MethodsThrough a multi-institutional collaboration, a community-based Ontology of Host-Microbiome Interactions (OHMI) was developed following the Open Biological/Biomedical Ontologies (OBO) Foundry principles. As an OBO library ontology, OHMI leverages established ontologies to create logically structured representations of (1) microbiomes, microbial taxonomy, host species, host anatomical entities, and HMIs under different conditions and (2) associated study protocols and types of data analysis and experimental results.ResultsAligned with the Basic Formal Ontology, OHMI comprises over 1000 terms, including terms imported from more than 10 existing ontologies together with some 500 OHMI-specific terms. A specific OHMI design pattern was generated to represent typical host-microbiome interaction studies. As one major OHMI use case, drawing on data from over 50 peer-reviewed publications, we identified over 100 bacteria and fungi from the gut, oral cavity, skin, and airway that are associated with six rheumatic diseases including rheumatoid arthritis. Our ontological study identified new high-level microbiota taxonomical structures. Two microbiome-related competency questions were also designed and addressed. We were also able to use OHMI to represent statistically significant results identified from a large existing microbiome database data analysis.ConclusionOHMI represents entities and relations in the domain of HMIs. It supports shared knowledge representation, data and metadata standardization and integration, and can be used in formulation of advanced queries for purposes of data analysis.

Dataset Information

Exploring Host-Microbiome Interactions using an in Silico Model of Biomimetic Robots and Engineered Living Cells.

Publications

Exploring Host-Microbiome Interactions using an in Silico Model of Biomimetic Robots and Engineered Living Cells.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets