A Cell paper describes the EGRIN model, which used Halobacterium salinarum NRC-1.

A multi-institute team of scientists say that they have developed a model which rapidly characterizes and accurately predicts the molecular-level, mechanistic response of a free-living cell to genetic and environmental changes. The study reportedly marks the first time researchers have accurately predicted a cell’s dynamics at the genome scale.

The knowledge gained through the Environmental and Gene Regulatory Influence (EGRIN) model demonstrates that it is possible to discover how complex biological systems work through a systems biology approach.

The research group used Halobacterium salinarum NRC-1, a member of the Archaea family of organisms, because it has been the subject of relatively little scientific study. Archaea have evolved to thrive in harsh environments that would be lethal to most other organisms. By focusing on such an organism, they were able to show definitively that they could understand and model the circuit controlling the cell directly from experiments designed to measure all genes in the genome simultaneously.

The investigators say that they accurately modeled how Halobacterium functioned over time and responded to changing environmental conditions. They were able to predict how over 80% of the total genome responded to stimuli over time, dynamically rearranging the cell’s makeup to meet environmental stresses.

The EGRIN model also linked biological processes with previously unknown molecular relationships and accurately predicted both new regulation of known biological processes and the transcriptional responses of more than 1,900 genes to completely novel genetic and environmental experiments.

“This is also a good model to explain how, in general, cells make stable decisions as they move through time scales,” says Richard Bonneau, New York University assistant biology professor. “If you want to understand how cells respond to their environments, the model offers a clearer window than previously existed for this domain of life.”

The process of discovery involved perturbing cells, characterizing growth and/or survival phenotype, quantitatively measuring steady state and dynamic changes in mRNA, assimilating the changes into a network model able to repeat the observations, and experimentally validating hypotheses formulated through the model. More than 230 out of 413 microarray experiments used were collected and/or conducted specifically for this study. In addition, the team used data from genome-wide binding location analysis for eight transcription factors, mass spectrometry-based proteomic analysis, protein structure predictions, computational analysis of genome structure and protein evolution, as well as data from public sources.

“It will take a lot more effort before the EGRIN model can be applied in a practical fashion,” points out Nitin Baliga of the Institute for Systems Biology. “At this point we’ve basically proven that we can develop a comprehensive understanding of how complex biological systems work, which has been an open question to this point.”

The study also included researchers at the University of Maryland, Vanderbilt University, and the University of Washington. The findings are described in the latest issue of the journal Cell.

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