Consistency of cybernetic variables with gene expression profiles: A more rigorous test. (1st July 2018)

• Record Type: Journal Article
• Authors: DeVilbiss, Frank; Mandli, Aravinda; Ramkrishna, Doraiswami
• Is Part Of: Biotechnology progress. Volume 34:Number 4(2018)
• Page Start: 858
• Page End: 867
• Publication Date: 2018-07-01
• Subjects: metabolic engineering -- metabolic control -- cybernetics -- mathematical modeling; Biotechnology -- Periodicals; Food industry and trade -- Periodicals; Bioengineering -- Periodicals; 660.6
• DOI: 10.1002/btpr.2654
• Languages: English
• ISSNs: 8756-7938

Abstract

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