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Updated: Feb 11, 2026

Using an Automated Cell Counter to Simplify Gene Expression Studies: siRNA Knockdown of IL-4 Dependent Gene Expression in Namalwa Cells
Published on: April 14, 2010
Consistency of cybernetic variables with gene expression profiles: A more rigorous test
Frank DeVilbiss1, Aravinda Mandli1, Doraiswami Ramkrishna1
1School of Chemical Engineering, Purdue University, West Lafayette, IN, 47907.
Abstract:
Diauxic growth of Escherichia coli is driven by a host of internal, complex regulatory actions. In this classic scenario of cellular control, the cell employs a rational algorithm to modulate its metabolism in a competitive fashion. Cybernetic models of metabolism, whose development now spans three decades, were first formulated to describe regulation of cells in complex, multi-substrate environments. They modeled this scenario using the hypothesis that the formation of the enzymatic machinery is regulated to maximize a return on investment. While this assumption is made on the basis of logical arguments rooted in evolutionary principles, little effort has been taken to validate if enzymes are truly synthesized in the same fashion that is predicted by cybernetic variables. This work revisits the original cybernetic models describing diauxic growth and compares their predictions of enzyme synthesis control with time series gene expression data in microarray and qRT-PCR formats. Three separate studies are made for two different strains of E. coli. The first is for the growth of E. coli BW25113 on a mixture of glucose and acetate, whose gene expression changes are metered by microarray. Another is also for the sequential consumption of glucose and acetate but involves strain MG1655 and employs qRT-PCR. The final is for E. coli MG1655 on glucose and lactose. By demonstrating how cybernetic variables for induced enzyme synthesis mimic the behavior of transcriptional data, a strong argument for using cybernetic models is made. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 34:858-867, 2018.
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