Abstract

BackgroundGrowth substrates, aerobic/anaerobic conditions, specific growth rate (μ) etc. strongly influence Escherichia coli cell physiology in terms of cell size, biomass composition, gene and protein expression. To understand the regulation behind these different phenotype properties, it is useful to know carbon flux patterns in the metabolic network which are generally calculated by metabolic flux analysis (MFA). However, rarely is biomass composition determined and carbon balance carefully measured in the same experiments which could possibly lead to distorted MFA results and questionable conclusions. Therefore, we carried out both detailed carbon balance and biomass composition analysis in the same experiments for more accurate quantitative analysis of metabolism and MFA.ResultsWe applied advanced continuous cultivation methods (A-stat and D-stat) to continuously monitor E. coli K-12 MG1655 flux and energy metabolism dynamic responses to change of μ and glucose-acetate co-utilisation. Surprisingly, a 36% reduction of ATP spilling was detected with increasing μ and carbon wasting to non-CO2 by-products under constant biomass yield. The apparent discrepancy between constant biomass yield and decline of ATP spilling could be explained by the rise of carbon wasting from 3 to 11% in the carbon balance which was revealed by the discovered novel excretion profile of E. coli pyrimidine pathway intermediates carbamoyl-phosphate, dihydroorotate and orotate. We found that carbon wasting patterns are dependent not only on μ, but also on glucose-acetate co-utilisation capability. Accumulation of these compounds was coupled to the two-phase acetate accumulation profile. Acetate overflow was observed in parallel with the reduction of TCA cycle and glycolysis fluxes, and induction of pentose phosphate pathway.ConclusionsIt can be concluded that acetate metabolism is one of the major regulating factors of central carbon metabolism. More importantly, our model calculations with actual biomass composition and detailed carbon balance analysis in steady state conditions with -omics data comparison demonstrate the importance of a comprehensive systems biology approach for more advanced understanding of metabolism and carbon re-routing mechanisms potentially leading to more successful metabolic engineering.

Highlights

  • Growth substrates, aerobic/anaerobic conditions, specific growth rate (μ) etc. strongly influence Escherichia coli cell physiology in terms of cell size, biomass composition, gene and protein expression

  • We carried out three replicate A-stat and four dilution rate stat (D-stat) continuous cultivation experiments at various dilution rates with E. coli K-12 MG1655 which growth characteristics are described in detail in Valgepea et al [11]

  • Carbon balance and biomass composition was carefully determined and the acquired data was used in metabolic flux analysis (MFA) to obtain better understanding about carbon flow in the metabolic network

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Summary

Introduction

Aerobic/anaerobic conditions, specific growth rate (μ) etc. strongly influence Escherichia coli cell physiology in terms of cell size, biomass composition, gene and protein expression. To understand the regulation behind these different phenotype properties, it is useful to know carbon flux patterns in the metabolic network which are generally calculated by metabolic flux analysis (MFA). Escherichia coli exerts a very different gene and protein expression profile under different growth substrates [1], aerobic/anaerobic conditions [2] etc. Specific growth rate (μ) has been shown to be one of the most definite parameters influencing E. coli cell physiology as shown by studies of cell size [3,4], biomass composition [5,6,7], To gain insights into the regulation and control mechanisms behind these different phenotype properties, it is useful to know carbon flow patterns in the metabolic network. MFA is generally carried out with steady state input data from chemostat cultures which provide reproducible and strictly defined physiological state of cells [7,9,12,13,14]

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