High-throughput Saccharomyces cerevisiae cultivation method for credentialing-based untargeted metabolomics.

Identifying metabolites in model organisms is critical for many areas of biology, including unravelling disease aetiology or elucidating functions of putative enzymes. Even now, hundreds of predicted metabolic genes in Saccharomyces cerevisiae remain uncharacterized, indicating that our understanding of metabolism is far from complete even in well-characterized organisms. While untargeted high-resolution mass spectrometry (HRMS) enables the detection of thousands of features per analysis, many of these have a non-biological origin. Stable isotope labelling (SIL) approaches can serve as credentialing strategies to distinguish biologically relevant features from background signals, but implementing these experiments at large scale remains challenging. Here, we developed a SIL-based approach for high-throughput untargeted metabolomics in S. cerevisiae, including deep-48 well format-based cultivation and metabolite extraction, building on the peak annotation and verification engine (PAVE) tool. Aqueous and nonpolar extracts were analysed using HILIC and RP liquid chromatography, respectively, coupled to Orbitrap Q Exactive HF mass spectrometry. Of the approximately 37,000 total detected features, only 3-7% of the features were credentialed and used for data analysis with open-source software such as MS-DIAL, MetFrag, Shinyscreen, SIRIUS CSI:FingerID, and MetaboAnalyst, leading to the successful annotation of 198 metabolites using MS2 database matching. Comparable metabolic profiles were observed for wild-type and sdh1Δ yeast strains grown in deep-48 well plates versus the classical shake flask format, including the expected increase in intracellular succinate concentration in the sdh1Δ strain. The described approach enables high-throughput yeast cultivation and credentialing-based untargeted metabolomics, providing a means to efficiently perform molecular phenotypic screens and help complete metabolic networks.

Micro-aerobic production of isobutanol with engineered Pseudomonas putida.

Pseudomonas putida KT2440 is emerging as a promising microbial host for biotechnological industry due to its broad range of substrate affinity and resilience to physicochemical stresses. Its natural tolerance towards aromatics and solvents qualifies this versatile microbe as promising candidate to produce next generation biofuels such as isobutanol. In this study, we scaled-up the production of isobutanol with P. putida from shake flask to fed-batch cultivation in a 30 L bioreactor. The design of a two-stage bioprocess with separated growth and production resulted in 3.35 gisobutanol L-1. Flux analysis revealed that the NADPH expensive formation of isobutanol exceeded the cellular catabolic supply of NADPH finally causing growth retardation. Concomitantly, the cell counteracted to the redox imbalance by increased formation of 2-ketogluconic thereby providing electrons for the respiratory ATP generation. Thus, P. putida partially uncoupled ATP formation from the availability of NADH. The quantitative analysis of intracellular pyridine nucleotides NAD(P)+ and NAD(P)H revealed elevated catabolic and anabolic reducing power during aerobic production of isobutanol. Additionally, the installation of micro-aerobic conditions during production doubled the integral glucose-to-isobutanol conversion yield to 60 mgisobutanol gglucose -1 while preventing undesired carbon loss as 2-ketogluconic acid.

Streamlining the Analysis of Dynamic 13C-Labeling Patterns for the Metabolic Engineering of Corynebacterium glutamicum as l-Histidine Production Host.

Today's possibilities of genome editing easily create plentitudes of strain mutants that need to be experimentally qualified for configuring the next steps of strain engineering. The application of design-build-test-learn cycles requires the identification of distinct metabolic engineering targets as design inputs for subsequent optimization rounds. Here, we present the pool influx kinetics (PIK) approach that identifies promising metabolic engineering targets by pairwise comparison of up- and downstream 13C labeling dynamics with respect to a metabolite of interest. Showcasing the complex l-histidine production with engineered Corynebacterium glutamicuml-histidine-on-glucose yields could be improved to 8.6 ± 0.1 mol% by PIK analysis, starting from a base strain. Amplification of purA, purB, purH, and formyl recycling was identified as key targets only analyzing the signal transduction kinetics mirrored in the PIK values.

Modular systems metabolic engineering enables balancing of relevant pathways for l-histidine production with Corynebacterium glutamicum.

BACKGROUND: l-Histidine biosynthesis is embedded in an intertwined metabolic network which renders microbial overproduction of this amino acid challenging. This is reflected in the few available examples of histidine producers in literature. Since knowledge about the metabolic interplay is limited, we systematically perturbed the metabolism of Corynebacterium glutamicum to gain a holistic understanding in the metabolic limitations for l-histidine production. We, therefore, constructed C. glutamicum strains in a modularized metabolic engineering approach and analyzed them with LC/MS-QToF-based systems metabolic profiling (SMP) supported by flux balance analysis (FBA). RESULTS: The engineered strains produced l-histidine, equimolar amounts of glycine, and possessed heavily decreased intracellular adenylate concentrations, despite a stable adenylate energy charge. FBA identified regeneration of ATP from 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR) as crucial step for l-histidine production and SMP identified strong intracellular accumulation of inosine monophosphate (IMP) in the engineered strains. Energy engineering readjusted the intracellular IMP and ATP levels to wild-type niveau and reinforced the intrinsic low ATP regeneration capacity to maintain a balanced energy state of the cell. SMP further indicated limitations in the C1 supply which was overcome by expression of the glycine cleavage system from C. jeikeium. Finally, we rerouted the carbon flux towards the oxidative pentose phosphate pathway thereby further increasing product yield to 0.093 ± 0.003 mol l-histidine per mol glucose. CONCLUSION: By applying the modularized metabolic engineering approach combined with SMP and FBA, we identified an intrinsically low ATP regeneration capacity, which prevents to maintain a balanced energy state of the cell in an l-histidine overproduction scenario and an insufficient supply of C1 units. To overcome these limitations, we provide a metabolic engineering strategy which constitutes a general approach to improve the production of ATP and/or C1 intensive products.

HILIC-Enabled 13C Metabolomics Strategies: Comparing Quantitative Precision and Spectral Accuracy of QTOF High- and QQQ Low-Resolution Mass Spectrometry.

Dynamic 13C-tracer-based flux analyses of in vivo reaction networks still require a continuous development of advanced quantification methods applying state-of-the-art mass spectrometry platforms. Utilizing alkaline HILIC chromatography, we adapt strategies for a systematic quantification study in non- and 13C-labeled multicomponent endogenous Corynebacterium glutamicum extracts by LC-QTOF high resolution (HRMS) and LC-QQQ tandem mass spectrometry (MS/MS). Without prior derivatization, a representative cross-section of 17 central carbon and anabolic key intermediates were analyzed with high selectivity and sensitivity under optimized ESI-MS settings. In column detection limits for the absolute quantification range were between 6.8-304.7 (QQQ) and 28.7-881.5 fmol (QTOF) with comparable linearities (3-5 orders of magnitude) and enhanced precision using QQQ-MRM detection. Tailor-made preparations of uniformly (U)13C-labeled cultivation extracts for isotope dilution mass spectrometry enabled the accurate quantification in complex sample matrices and extended linearities without effect on method parameters. Furthermore, evaluation of metabolite-specific m+1-to-m+0 ratios (ISR1:0) in non-labeled extracts exhibited sufficient methodical spectral accuracies with mean deviations of 3.89 ± 3.54% (QTOF) and 4.01 ± 3.01% (QQQ). Based on the excellent HILIC performance, conformity analysis of time-resolved isotopic enrichments in 13C-tracer experiments revealed sufficient spectral accuracy for QQQ-SIM detection. However, only QTOF-HRMS ensures determination of the full isotopologue space in complex matrices without mass interferences.