Implications of macromolecular crowding for signal transduction and metabolite channeling

Abstract

The effect of different total enzyme concentrations on the f lux through the bacterial phosphoenolpyruvate:carbohydrate phosphotransferase system (PTS) in vitro was determined by measuring PTS-mediated carbohydrate phosphorylation at different dilutions of cell-free extract of Escherichia coli. The dependence of the f lux on the protein concentration was more than linear but less than quadratic. The combined f lux-response coefficient of the four enzymes constituting the glucose PTS decreased slightly from values of Ϸ1.8 with increasing protein concentrations in the assay. Addition of the macromolecular crowding agents polyethylene glycol (PEG) 6000 and PEG 35000 led to a sharper decrease in the combined f lux-response coefficient, in one case to values of Ϸ1. PEG 6000 stimulated the PTS f lux at lower protein concentrations and inhibited the f lux at higher protein concentrations, with the transition depending on the PEG 6000 concentration. This suggests that macromolecular crowding decreases the dissociation rate constants of enzyme complexes. High concentrations of the microsolute glycerol did not affect the combined f lux-response coefficient. The data could be explained with a kinetic model of macromolecular crowding in a two-enzyme group-transfer pathway. Our results suggest that, because of the crowded environment in the cell, the different PTS enzymes form complexes that live long on the time-scale of their turnover. The implications for the metabolic behavior and control properties of the PTS, and for the effect of macromolecular crowding on nonequilibrium processes, are discussed.Understanding the functioning of the living cell on the basis of processes studied in vitro is a central aim of biochemistry; properties of biomolecules in vitro are extrapolated to the situation in vivo. The concentrations of macromolecules in a biochemical assay are much lower than inside the living cell; total intracellular macromolecule concentrations (RNA and protein) of 340 mg͞ml have been measured in exponentially growing Escherichia coli cells, with 70-73% thereof being protein (1). These high concentrations can lead to macromolecular crowding (reviewed in refs. 2 and 3). The ensuing nonideal equilibrium behavior of hemoglobin already was reported by Adair (4). To mimic cellular conditions in a test tube, inert macromolecular crowding agents such as polyethylene glycol (PEG) can be added (2, 3); this then promotes association between macromolecules. For example, addition of PEG can overcome the inhibition of E. coli DNA polymerase I activity by high salt concentrations (5), presumably by effecting the association of DNA and the enzyme, whose interaction was loosened by the high ionic strength.

Dynamic microcompartmentation in synthetic cells

“…The DNA partitioning within these vesicles (K ϭ 0.5 Ϯ 0.1) was improved over that for bulk solutions (K ϭ 0.86 Ϯ 0.01) by dehydrating in an external sucrose solution after vesicle formation. Other factors, such as the concentration of various ions or small molecules, are also capable of shifting the position of the binodal curve and altering partitioning and͞or phase behavior (29)(30)(31)(32). In living cells one might expect such transitions in response to import or efflux of specific ions or molecules, volume changes, or cytoskeletal protein polymerization.…”

“…Because macromolecular crowding is largely a physical phenomenon due to excluded volume, essentially any polymer can be used to mimic the crowding effects of cytoplasm. We have chosen the neutral polymers, PEG and dextran, which form well characterized ATPS at concentrations above a few wt % (27)(28)(29)(30). PEG and dextran are also commonly used crowding reagents for in vitro biochemical investigations (26)(27)(28), such as those demonstrating crowdinginduced changes in DNA hybridization (29), enzyme complex formation (30), and protein folding, association, and aggregation (31).…”

Understanding Glucose Transport by the Bacterial Phosphoenolpyruvate:Glycose Phosphotransferase System on the Basis of Kinetic Measurements in Vitro

“…These dependences were quantified with so-called flux response coefficients, defined as the percentage change in the uptake rate upon a 1% increase in the enzyme concentration (see "Appendix" for mathematical definitions). Furthermore, titrations with different amounts of E. coli cellfree extracts (11) have enabled the quantification of the extent to which the glucose PTS proteins together control PTS-mediated phosphorylation activity in vitro at different protein concentrations. There was a remarkable difference between the results obtained in vitro and in vivo; in vivo, the four flux response coefficients added up to 0.8 (9), whereas in vitro, this sum varied between 1.5 and 1.8 depending on the total protein concentration (11).…”

“…Furthermore, titrations with different amounts of E. coli cellfree extracts (11) have enabled the quantification of the extent to which the glucose PTS proteins together control PTS-mediated phosphorylation activity in vitro at different protein concentrations. There was a remarkable difference between the results obtained in vitro and in vivo; in vivo, the four flux response coefficients added up to 0.8 (9), whereas in vitro, this sum varied between 1.5 and 1.8 depending on the total protein concentration (11). A value of greater than unity for this sum is in itself remarkable, since it reflects a higher order than linear dependence of flux on total protein concentration and contrasts strongly with the linear relationship between reaction rate and enzyme concentration usually found in enzyme kinetics.…”

BDI-modelling of complex intracellular dynamics

“…(3) Biochemical pathways are integrated with other pathways, including ones of signal transduction and gene expression, for which reliable parameter estimates are even rarer [Kholodenko et al, 1999]. (4) It is still unclear whether parameter values determined in vitro are relevant in vivo [Visser et al, 2000;Rohwer et al 1998]. (5) Actual behavior of intracellular pathways may be much less complex than possible in principle on the basis of their complexity (e.g.…”