Precise and accurate quantification is a prerequisite for interpretation of targeted metabolomics data, but this task is challenged by the inherent instability of the analytes. The sampling, quenching, extraction, and sample purification conditions required to recover and stabilize metabolites in representative extracts have also been proven highly dependent on species-specific properties. For Escherichia coli, unspecific leakage has been demonstrated for conventional microbial metabolomics sampling protocols. We herein present a fast filtration-based sampling protocol for this widely applied model organism, focusing on pitfalls such as inefficient filtration, selective loss of biomass, matrix contamination, and membrane permeabilization and leakage. We evaluate the effect of and need for removal of extracellular components and demonstrate how residual salts can challenge analytical accuracy of hyphenated mass spectrometric analyses, even when sophisticated correction strategies are applied. Laborious extraction procedures are bypassed by direct extraction in cold acetonitrile:water:methanol (3:5:2, v/v%), ensuring compatibility with sample concentration and thus, any downstream analysis. By applying this protocol, we achieve and demonstrate high precision and low metabolite turnover, and, followingly, minimal perturbation of the inherent metabolic state. This allows us to herein report absolute intracellular concentrations in E. coli and explore its central carbon metabolome at several commonly applied cultivation conditions.

The Gram-negative bacterium Escherichia coli is the most widely used host for recombinant protein production, both as an industrial expression platform and as a model system at laboratory scale. The recombinant protein production industry generates proteins with direct applications as biopharmaceuticals and in technological processes central to a plethora of fields. Despite the increasing economic significance of recombinant protein production, and the importance of E. coli as an expression platform and model organism, only few studies have focused on the central carbon metabolic landscape of E. coli during high-level recombinant protein production. In the present work, we applied four targeted CapIC- and LC-MS/MS methods, covering over 60 metabolites, to perform an in-depth metabolite profiling of the effects of high-level recombinant protein production in strains derived from E. coli BL21, carrying XylS/Pm vectors with different characteristics. The mass-spectrometric central carbon metabolite profiling was complemented with the study of growth kinetics and protein production in batch bioreactors. Our work shows the robustness in E. coli central carbon metabolism when introducing increased plasmid copy number, as well as the greater importance of induction of recombinant protein production as a metabolic challenge, especially when strong promoters are used.

Background: Nicotinamide adenine dinucleotide (NAD⁺), its precursors, and its derivatives (collectively NADome) play a crucial role in cellular processes and maintain redox homeostasis. Understanding the dynamics of these metabolic pools and redox reactions can provide valuable insights into metabolic functions, especially cellular regulation and stress response mechanisms. The accurate quantification of these metabolites is challenging due to the interconversion between the redox forms. Methods: Our laboratory previously developed a zwitterionic hydrophilic interaction liquid chromatography (zic-HILIC)–tandem mass spectrometry method for the quantification of five essential pyridine nucleotides, including NAD⁺ derivatives and it’s reduced forms, with ¹³C isotope dilution and matrix-matched calibration. In this study, we have improved the performance of the chromatographic method and expanded its scope to twelve analytes for a comprehensive view of NAD⁺ biosynthesis and utilization. The analytical method was validated and applied to investigate Escherichia coli BL21 under varying oxygen supplies including aerobic, microaerobic, and anaerobic conditions. Conclusions: The intracellular absolute metabolite concentrations ranged over four orders of magnitude with NAD⁺ as the highest abundant, while its precursors were much less abundant. The composition of the NADome at oxygen-limited conditions aligned more with that in the anaerobic conditions rather than in the aerobic phase. Overall, the NADome was quite homeostatic and E. coli rapidly, but in a minor way, adapted the metabolic activity to the challenging shift in the growth conditions and achieved redox balance. Our findings demonstrate that the zic-HILIC-MS/MS method is sensitive, accurate, robust, and high-throughput, providing valuable insights into NAD⁺ metabolism and the potential significance of these metabolites in various biological contexts.

Genome-scale metabolic models (GEMs) are mathematical representations of metabolism that allow for in silico simulation of metabolic phenotypes and capabilities. A prerequisite for these predictions is an accurate representation of the biomolecular composition of the cell necessary for replication and growth, implemented in GEMs as the so-called biomass objective function (BOF). The BOF contains the metabolic precursors required for synthesis of the cellular macro- and micromolecular constituents (e.g. protein, RNA, DNA), and its composition is highly dependent on the particular organism, strain, and growth condition. Despite its critical role, the BOF is rarely constructed using specific measurements of the modeled organism, drawing the validity of this approach into question. Thus, there is a need to establish robust and reliable protocols for experimental condition-specific biomass determination. Here, we address this challenge by presenting a general pipeline for biomass quantification, evaluating its performance on Escherichia coli K-12 MG1655 sampled during balanced exponential growth under controlled conditions in a batch-fermentor set-up. We significantly improve both the coverage and molecular resolution compared to previously published workflows, quantifying 91.6% of the biomass. Our measurements display great correspondence with previously reported measurements, and we were also able to detect subtle characteristics specific to the particular E. coli strain. Using the modified E. coli GEM i ML1515a, we compare the feasible flux ranges of our experimentally determined BOF with the original BOF, finding that the changes in BOF coefficients considerably affect the attainable fluxes at the genome-scale.