Assessment of heterologous butyrate and butanol pathway activity by measurement of intracellular pathway intermediates in recombinant Escherichia coli

In clostridia, n-butanol production from carbohydrates at yields of up to 76% of the theoretical maximum and at titers of up to 13 g/L has been reported. However, in Escherichia coli, several groups have reported butyric acid or butanol production from recombinant expression of clostridial genes, at much lower titers and yields. To pinpoint deficient steps in the recombinant pathway, we developed an analytical procedure for the determination of intracellular pools of key pathway intermediates and applied the technique to the analysis of three sets of E. coli strains expressing various combinations of butyrate biosynthesis genes. Low expression levels of the hbd-encoded S-3-hydroxybutyryl-CoA dehydrogenase were insufficient to convert acetyl-CoA to 3-hydroxybutyryl-CoA, indicating that hbd was a rate-limiting step in the production of butyryl-CoA. Increasing hbd expression alleviated this bottleneck, but in resulting strains, our pool size measurements and thermodynamic analysis showed that the reaction step catalyzed by the bcd-encoded butyryl-CoA dehydrogenase was rate-limiting. E. coli strains expressing both hbd and ptb-buk produced crotonic acid as a byproduct, but this byproduct was not observed with expression of related genes from non-clostridial organisms. Our thermodynamic interpretation of pool size measurements is applicable to the analysis of other metabolic pathways

Microbial Maintenance: A Critical Review on Its Quantification

Microbial maintenance is an important concept in microbiology. Its quantification, however, is a subject of continuous debate, which seems to be caused by (1) its definition, which includes nongrowth components other than maintenance; (2) the existence of partly overlapping concepts; (3) the evolution of variables as constants; and (4) the neglect of cell death in microbial dynamics. The two historically most important parameters describing maintenance, the specific maintenance rate and the maintenance coefficient, are based on partly different nongrowth components. There is thus no constant relation between these parameters and previous equations on this subject are wrong. In addition, the partial overlap between these parameters does not allow the use of a simple combination of these parameters. This also applies for combinations of a threshold concentration with one of the other estimates of maintenance. Maintenance estimates should ideally explicitly describe each nongrowth component. A conceptual model is introduced that describes their relative importance and reconciles the various concepts and definitions. The sensitivity of maintenance on underlying components was analyzed and indicated that overall maintenance depends nonlinearly on relative death rates, relative growth rates, growth yield, and endogenous metabolism. This quantitative sensitivity analysis explains the felt need to develop growth-dependent adaptations of existing maintenance parameters, and indicates the importance of distinguishing the various nongrowth components. Future experiments should verify the sensitivity of maintenance components under cellular and environmental conditions

Genome-Scale Reconstruction and Analysis of the Pseudomonas putida KT2440 Metabolic Network Facilitates Applications in Biotechnology

A cornerstone of biotechnology is the use of microorganisms for the efficient production of chemicals and the elimination of harmful waste. Pseudomonas putida is an archetype of such microbes due to its metabolic versatility, stress resistance, amenability to genetic modifications, and vast potential for environmental and industrial applications. To address both the elucidation of the metabolic wiring in P. putida and its uses in biocatalysis, in particular for the production of non-growth-related biochemicals, we developed and present here a genome-scale constraint-based model of the metabolism of P. putida KT2440. Network reconstruction and flux balance analysis (FBA) enabled definition of the structure of the metabolic network, identification of knowledge gaps, and pin-pointing of essential metabolic functions, facilitating thereby the refinement of gene annotations. FBA and flux variability analysis were used to analyze the properties, potential, and limits of the model. These analyses allowed identification, under various conditions, of key features of metabolism such as growth yield, resource distribution, network robustness, and gene essentiality. The model was validated with data from continuous cell cultures, high-throughput phenotyping data, 13C-measurement of internal flux distributions, and specifically generated knock-out mutants. Auxotrophy was correctly predicted in 75% of the cases. These systematic analyses revealed that the metabolic network structure is the main factor determining the accuracy of predictions, whereas biomass composition has negligible influence. Finally, we drew on the model to devise metabolic engineering strategies to improve production of polyhydroxyalkanoates, a class of biotechnologically useful compounds whose synthesis is not coupled to cell survival. The solidly validated model yields valuable insights into genotype–phenotype relationships and provides a sound framework to explore this versatile bacterium and to capitalize on its vast biotechnological potential