Optimal regulatory strategies for metabolic pathways in Escherichia coli depending on protein costs

Abstract

Pathways in Escherichia coli show large differences in the extent to which enzymes from the same pathway are expressed in a coordinated manner.Using dynamic optimization, we show that regulation of the initial and terminal reactions of a pathway is the minimum requirement for a precise control of flux.We find that in E. coli a regulation of initial and terminal reactions is predominantly used to control pathways with low costs of enzymes while a regulation of all enzymes occurs if protein costs are high.A trade-off between minimization of protein investment and minimization of response time can explain the preference for transcriptional regulation at key positions (leading to high protein costs, but low response time) or coordinated transcriptional regulation of all enzymes (leading to low protein costs, but high response time).

Comprehensive Absolute Quantification of the Cytosolic Proteome of Bacillus subtilis by Data Independent, Parallel Fragmentation in Liquid Chromatography/Mass Spectrometry (LC/MSE)

“…Since the amounts of polyamines in biomass requirements are usually weak, the apparent cost for this pathway is surprisingly high in B. subtilis. In E. coli, the cost of methionine metabolism is also very high compared with other metabolic pathways (48). Altogether, the protein investment in metabolic pathways seems to be comparable in these two organisms.…”

“…This view allows better assessing of the "slight" effect of some gene expression regulations, which is hard to understand on basis of transcriptional and translational control alone. TCA cycle appears to be one of the most expensive pathways of the cell as in E. coli (48). Therefore modest changes therein are causing large consequences and fine tuning of the amount of these enzymes is essential for the cell.…”

Efficient Search, Mapping, and Optimization of Multi-protein Genetic Systems in Diverse Bacteria

“…These relationships, called sequence-expression-activity maps (SEAMAPs), can be formulated by combining sequencedependent models predicting changes in protein expression levels (Rhodius & Mutalik, 2010;Salis, 2011;Brewster et al, 2012;Johnson et al, 2012;Borujeni et al, 2013;Kilpinen et al, 2013) with systemlevel models describing genetic system function (Fendt et al, 2010;Sneppen et al, 2010;Hyeon & Thirumalai, 2011;Wessely et al, 2011;Smallbone et al, 2013). Several types of models can be combined, utilizing thermodynamics, kinetics, mass transfer, and dynamical systems theory, to describe the multi-scale physical interactions affecting system function (Hyeon & Thirumalai, 2011).…”

“…The genetic part sequences controlling protein expression levels directly affect an organism's behavior by modulating binding occupancies, rates of catalysis, and the competition for shared resources. Finding a quantitative relationship between DNA sequence and host behavior has been a central goal toward understanding evolution and adaptation, treating human disease, and the engineering of organisms for biotechnology applications (Strohman, 2002;Wessely et al, 2011;O'Brien et al, 2013;de Vos et al, 2013;Quandt et al, 2014).…”

Model-based identification of drug targets that revert disrupted metabolism and its application to ageing

“…4). GSMMs have been used for a variety of applications [5][6][7][8][9][10] including drug discovery 2 and metabolic engineering tasks 11 . Over the last 6 years, GSMM has been successfully used for modelling human metabolism as well, both in health and disease 3,[12][13][14][15][16] .…”