Isotopologue analysis of sugar phosphates in yeast cell extracts by gas chromatography chemical ionization time-of-flight mass spectrometry

Advances in Chromatographic and Mass Spectrometric Techniques for Analyzing Reducing Monosaccharides and Their Phosphates in Biological Samples

Reducing monosaccharides and their phosphates are critical metabolites in the central carbon metabolism pathway of living organisms. Variations in their content can indicate abnormalities in metabolic pathways and the onset of certain diseases, necessitating their analysis and detection. Reducing monosaccharides and their phosphates exhibit significant variations in content within biological samples and are present in many isomers, which makes the accurate quantification of reducing monosaccharides and their phosphates in biological samples a challenging task. Various analytical methods such as spectroscopy, fluorescence detection, colorimetry, nuclear magnetic resonance spectroscopy, sensor-based techniques, chromatography, and mass spectrometry are employed to detect monosaccharides and phosphates. In comparison, chromatography and mass spectrometry are highly favored for their ability to simultaneously analyze multiple components and their high sensitivity and selectivity. This review thoroughly evaluates the current chromatographic and mass spectrometric methods used for detecting reducing monosaccharides and their phosphates from 2013 to 2023, highlighting their efficacy and the advancements in these analytical technologies.

First proof-of-concept of UC/HILIC for extending the versatility of the current art of supercritical fluid separation

Supercritical Fluid Chromatography (SFC), a high-throughput separation technique, has been widely applied as a promising routine method in pharmaceutical, pesticides, and metabolome analysis in the same way as conventional liquid chromatography and gas chromatography. Unified chromatography (UC), an advanced version of SFC, which applied gradient elution with mobile phase changing continuously from supercritical to subcritical and to liquid states, can further extend the SFC applications. UC mostly applying the popular mobile phase of 95%:5%/Methanol:Water with additives allows to analyze many hydrophilic compounds. However, many of phosphorylated metabolites or multi carboxylic acids show very poor peak shapes or even can't be eluted under UC conditions, thus hampering the UC's metabolome coverage. In this study, we proposed the first proof-of-concept of UC/HILIC, a novel strategy to extend the current UC metabolome coverage by employing an aqueous gradient right after the UC gradient on a single packed column in a single measurement. The proposed method showed significant improvement regarding the chromatographic performance and metabolome coverage, while still maintaining the precision and high throughput in comparison with conventional UC methods.

Isomer selectivity of one- and two-dimensional approaches of mixed-mode and hydrophilic interaction liquid chromatography coupled to tandem mass spectrometry for sugar phosphates of glycolysis and pentose phosphate pathways

In this study, the chromatographic behavior of mixed-mode and hydrophilic interaction liquid chromatography (HILIC) with the mixed-mode HILIC/strong anion-exchange (SAX) column HILICpak VT-50 2D and the two HILIC columns Atlantis Premier BEH Z-HILIC and Acquity Premier BEH Amide was assessed with regard to their separation capability of the metabolites from the glycolysis and pentose phosphate pathways. Chromatographic conditions were evaluated with the aim of achieving separation of the isomeric glycolytic phosphorylated carbohydrate metabolites free from isomeric interferences and thus allowing for selective targeted analysis by liquid chromatography with tandem mass spectrometry (MS/MS) using multiple reaction monitoring acquisition. The effects of pH values (8.0/9.0/10.0) of the ammonium bicarbonate buffer and gradient time were investigated during HILIC-MS/MS analysis, with the optimal conditions found at pH = 10.0. Separation of the pentose phosphate isomers (ribose 5- and 1-phosphate, xylulose 5-phosphate and ribulose 5-phosphate) was achieved on the mixed-mode HILIC/SAX (HILICpak VT-50 2D) column and HILIC BEH Amide column. Column performance was evaluated based on the direct comparison of chromatographic parameters, i.e. peak width at 50% and peak tailing factors of the individual metabolites. Parity plots were generated allowing a direct comparison between the normalized retention times and assessment of orthogonality of all 3 stationary phases evaluated. Separation of 7 biologically relevant hexose monophosphates metabolites turned out to be challenging by HILIC-MS/MS, with the BEH Amide providing the best individual results for such a separation. However, fructose 6-phosphate and glucose 1-phosphate co-eluted. Therefore, an on-line heart-cutting HILIC-Mixed Mode 2D-LC-QToF experiment was conducted, allowing the separation of this critical isomer pair. In this setup, the BEH Amide column in the ¹D separated the majority of target metabolites, while a heart-cut of the peak from totally coeluted fructose 6-phosphate and glucose 1-phosphate was separated in the ²D with HILICpak VT50-2D column, thus allowing undisturbed determination of the glycolytic phosphorylated carbohydrate metabolites due to their chromatographic separation from hexose monophosphate metabolites. The assay specificity towards 7 common hexose monophosphates was characterized (glucose 1- and 6-phosphate, galactose 1- and 6-phosphate, fructose 6-phosphate, mannose 1- and 6-phosphate). The selectivity of some rare hexose monophosphates (allose 6-phosphate, tagatose 6-phosphate, sorbose 1-phosphate) was also tested.

Metabolomics and modelling approaches for systems metabolic engineering

Metabolic engineering involves the manipulation of microbes to produce desirable compounds through genetic engineering or synthetic biology approaches. Metabolomics involves the quantitation of intracellular and extracellular metabolites, where mass spectrometry and nuclear magnetic resonance based analytical instrumentation are often used. Here, the experimental designs, sample preparations, metabolite quenching and extraction are essential to the quantitative metabolomics workflow. The resultant metabolomics data can then be used with computational modelling approaches, such as kinetic and constraint-based modelling, to better understand underlying mechanisms and bottlenecks in the synthesis of desired compounds, thereby accelerating research through systems metabolic engineering. Constraint-based models, such as genome scale models, have been used successfully to enhance the yield of desired compounds from engineered microbes, however, unlike kinetic or dynamic models, constraint-based models do not incorporate regulatory effects. Nevertheless, the lack of time-series metabolomic data generation has hindered the usefulness of dynamic models till today. In this review, we show that improvements in automation, dynamic real-time analysis and high throughput workflows can drive the generation of more quality data for dynamic models through time-series metabolomics data generation. Spatial metabolomics also has the potential to be used as a complementary approach to conventional metabolomics, as it provides information on the localization of metabolites. However, more effort must be undertaken to identify metabolites from spatial metabolomics data derived through imaging mass spectrometry, where machine learning approaches could prove useful. On the other hand, single-cell metabolomics has also seen rapid growth, where understanding cell-cell heterogeneity can provide more insights into efficient metabolic engineering of microbes. Moving forward, with potential improvements in automation, dynamic real-time analysis, high throughput workflows, and spatial metabolomics, more data can be produced and studied using machine learning algorithms, in conjunction with dynamic models, to generate qualitative and quantitative predictions to advance metabolic engineering efforts.

An Arabidopsis GCMS chemical ionization technique to quantify adaptive responses in central metabolism

We present a methodology to survey central metabolism in 13CO2-labeled Arabidopsis (Arabidopsis thaliana) rosettes by ammonia positive chemical ionization-gas chromatography-mass spectrometry. This technique preserves the molecular ion cluster of methyloxime/trimethylsilyl-derivatized analytes up to 1 kDa, providing unambiguous nominal mass assignment of >200 central metabolites and 13C incorporation rates into a subset of 111 from the tricarboxylic acid (TCA) cycle, photorespiratory pathway, amino acid metabolism, shikimate pathway, and lipid and sugar metabolism. In short-term labeling assays, we observed plateau labeling of ∼35% for intermediates of the photorespiratory cycle except for glyoxylate, which reached only ∼4% labeling and was also present at molar concentrations several fold lower than other photorespiratory intermediates. This suggests photorespiratory flux may involve alternate intermediate pools besides the generally accepted route through glyoxylate. Untargeted scans showed that in illuminated leaves, noncyclic TCA cycle flux and citrate export to the cytosol revert to a cyclic flux mode following methyl jasmonate (MJ) treatment. MJ also caused a block in the photorespiratory transamination of glyoxylate to glycine. Salicylic acid treatment induced the opposite effects in both cases, indicating the antagonistic relationship of these defense signaling hormones is preserved at the metabolome level. We provide complete chemical ionization spectra for 203 Arabidopsis metabolites from central metabolism, which uniformly feature the unfragmented pseudomolecular ion as the base peak. This unbiased, soft ionization technique is a powerful screening tool to identify adaptive metabolic trends in photosynthetic tissue and represents an important advance in methodology to measure plant metabolic flux.

Genotypic and phenotypic diversity among Komagataella species reveals a hidden pathway for xylose utilization

BACKGROUND

The yeast genus Komagataella currently consists of seven methylotrophic species isolated from tree environments. Well-characterized strains of K. phaffii and K. pastoris are important hosts for biotechnological applications, but the potential of other species from the genus remains largely unexplored. In this study, we characterized 25 natural isolates from all seven described Komagataella species to identify interesting traits and provide a comprehensive overview of the genotypic and phenotypic diversity available within this genus.

RESULTS

Growth tests on different carbon sources and in the presence of stressors at two different temperatures allowed us to identify strains with differences in tolerance to high pH, high temperature, and growth on xylose. As Komagataella species are generally not considered xylose-utilizing yeasts, xylose assimilation was characterized in detail. Growth assays, enzyme activity measurements and 13C labeling confirmed the ability of K. phaffii to utilize D-xylose via the oxidoreductase pathway. In addition, we performed long-read whole-genome sequencing to generate genome assemblies of all Komagataella species type strains and additional K. phaffii and K. pastoris isolates for comparative analysis. All sequenced genomes have a similar size and share 83-99% average sequence identity. Genome structure analysis showed that K. pastoris and K. ulmi share the same rearrangements in difference to K. phaffii, while the genome structure of K. kurtzmanii is similar to K. phaffii. The genomes of the other, more distant species showed a larger number of structural differences. Moreover, we used the newly assembled genomes to identify putative orthologs of important xylose-related genes in the different Komagataella species.

CONCLUSIONS

By characterizing the phenotypes of 25 natural Komagataella isolates, we could identify strains with improved growth on different relevant carbon sources and stress conditions. Our data on the phenotypic and genotypic diversity will provide the basis for the use of so-far neglected Komagataella strains with interesting characteristics and the elucidation of the genetic determinants of improved growth and stress tolerance for targeted strain improvement.

Ultrasensitive Determination of Sugar Phosphates in Trace Samples by Stable Isotope Chemical Labeling Combined with RPLC-MS

Sugar phosphates are important metabolic intermediates in organisms and play a vital role in energy and central carbon metabolism. Profiling of sugar phosphates is of great significance but full of challenges due to their high structural similarity and low sensitivities in liquid chromatography (LC)-mass spectrometry (MS). In this study, we developed a novel stable isotope chemical labeling combined with the reversed-phase (RP)LC-MS method for ultrasensitive determination of sugar phosphates at the single-cell level. By chemical derivatization with 2-(diazo-methyl)-N-methyl-N-phenyl-benzamide (2-DMBA) and d₅-2-DMBA, sugar phosphate isomers can obtain better separation and identification, and the detection sensitivities of sugar phosphates increased by 3.5-147 folds. The obtained limits of detection of sugar phosphates ranged from 5 to 16 pg/mL. Using this method, we achieved ultrasensitive and accurate quantification of 12 sugar phosphates in different trace biological samples. Benefiting from the improved separation and detection sensitivity, we successfully quantified five sugar phosphates (d-glucose 1-phosphate, d-mannose 6-phosphate, d-fructose 6-phosphate, d-glucose 6-phosphate, and seduheptulose 7-phosphate) in a single protoplast of Arabidopsis thaliana.

Yeast-based reference materials for quantitative metabolomics

We introduce a new concept of yeast-derived biological matrix reference material for metabolomics research relying on in vivo synthesis of a defined biomass, standardized extraction followed by absolute quantification with isotope dilution. The yeast Pichia pastoris was grown using full control- and online monitoring fed-batch fermentations followed by fast cold methanol quenching and boiling ethanol extraction. Dried extracts served for the quantification campaign. A metabolite panel of the evolutionarily conserved primary metabolome (amino acids, nucleotides, organic acids, and metabolites of the central carbon metabolism) was absolutely quantified by isotope dilution utilizing uniformly labeled ¹³C-yeast-based internal standards. The study involved two independent laboratories employing complementary mass spectrometry platforms, namely hydrophilic interaction liquid chromatography-high resolution mass spectrometry (HILIC-HRMS) and gas chromatography-tandem mass spectrometry (GC–MS/MS). Homogeneity, stability tests (on a panel of >70 metabolites over a period of 6 months), and excellent biological repeatability of independent fermentations over a period of 2 years showed the feasibility of producing biological reference materials on demand. The obtained control ranges proved to be fit for purpose as they were either superior or comparable to the established reference materials in the field.

Benchmarking Non-Targeted Metabolomics Using Yeast-Derived Libraries

Non-targeted analysis by high-resolution mass spectrometry (HRMS) is an essential discovery tool in metabolomics. To date, standardization and validation remain a challenge. Community-wide accepted cost-effective benchmark materials are lacking. In this work, we propose yeast (Pichia pastoris) extracts derived from fully controlled fermentations for this purpose. We established an open-source metabolite library of >200 identified metabolites based on compound identification by accurate mass, matching retention times, and MS/MS, as well as a comprehensive literature search. The library includes metabolites from the classes of (1) organic acids and derivatives (2) nucleosides, nucleotides, and analogs, (3) lipids and lipid-like molecules, (4) organic oxygen compounds, (5) organoheterocyclic compounds, (6) organic nitrogen compounds, and (7) benzoids at expected concentrations ranges of sub-nM to µM. As yeast is a eukaryotic organism, key regulatory elements are highly conserved between yeast and all annotated metabolites were also reported in the human metabolome database (HMDB). Orthogonal state-of-the-art reversed-phase (RP-) and hydrophilic interaction chromatography mass spectrometry (HILIC-MS) non-targeted analysis and authentic standards revealed that 104 out of the 206 confirmed metabolites were reproducibly recovered and stable over the course of three years when stored at −80 °C. Overall, 67 out of these 104 metabolites were identified with comparably stable areas over all three yeast fermentation and are the ideal starting point for benchmarking experiments. The provided yeast benchmark material enabled not only to test for the chemical space and coverage upon method implementation and developments but also allowed in-house routines for instrumental performance tests. Transferring the quality control strategy of proteomics workflows based on the number of protein identification in HeLa extracts, metabolite IDs in the yeast benchmarking material can be used as metabolomics quality control. Finally, the benchmark material opens new avenues for batch-to-batch corrections in large-scale non-targeted metabolomics studies.

Beyond alcohol oxidase: the methylotrophic yeast Komagataella phaffii utilizes methanol also with its native alcohol dehydrogenase Adh2

Methylotrophic yeasts are considered to use alcohol oxidases to assimilate methanol, different to bacteria which employ alcohol dehydrogenases with better energy conservation. The yeast Komagataella phaffii carries two genes coding for alcohol oxidase, AOX1 and AOX2. The deletion of the AOX1 leads to the Mut^S phenotype and the deletion of AOX1 and AOX2 to the Mut^– phenotype. The Mut^– phenotype is commonly regarded as unable to utilize methanol. In contrast to the literature, we found that the Mut^– strain can consume methanol. This ability was based on the promiscuous activity of alcohol dehydrogenase Adh2, an enzyme ubiquitously found in yeast and normally responsible for ethanol consumption and production. Using ¹³C labeled methanol as substrate we could show that to the largest part methanol is dissimilated to CO₂ and a small part is incorporated into metabolites, the biomass, and the secreted recombinant protein. Overexpression of the ADH2 gene in K. phaffii Mut^– increased both the specific methanol uptake rate and recombinant protein production, even though the strain was still unable to grow. These findings imply that thermodynamic and kinetic constraints of the dehydrogenase reaction facilitated the evolution towards alcohol oxidase-based methanol metabolism in yeast.

Selective and Accurate Quantification of N-Acetylglucosamine in Biotechnological Cell Samples via GC-MS/MS and GC-TOFMS

N-Acetylglucosamine is a key component of bacterial and fungal cell walls and of the extracellular matrix of animal cells. It plays a variety of roles at the cell surface structure and is under discussion to be involved in signaling pathways. The presence of a number of N-acetylhexosamine stereoisomers in samples of biological or biotechnological origin demands for dedicated high efficiency separation methods, due to identical exact mass and similar fragmentation patterns of the stereoisomers. Gas chromatography offers high sample capacity, separation efficiency, and precision under repeatability conditions of measurement, which is a necessity for the analysis of low abundant stereoisomers in biological samples. Automated online derivatization facilitates to overcome the main obstacle for the use of gas chromatography in metabolomics, namely, the derivatization of polar metabolites prior to analysis. Using alkoximation and subsequent trimethylsilylation, carbohydrates and their derivatives are known to show several derivatives, since derivatization is incomplete as well as highly matrix dependent inherent to the high number of functional groups present in carbohydrates. A method based on efficient separation of ethoximated and trimethylsilylated N-acetylglucosamines was developed. Accurate absolute quantification is enabled using biologically derived ¹³C labeled internal standards eliminating systematic errors related to sample pretreatment and analysis. Due to the lack of certified reference materials, a methodological comparison between tandem and time-of-flight mass spectrometric instrumentation was performed for mass spectrometric assessment of trueness. Both methods showed limits of detection in the lower femtomol range. The methods were applied to biological samples of Penicillium chrysogenum cultivations with different matrices revealing excellent agreement of both mass spectrometric techniques.

Determination of Isotopologue and Tandem Mass Isotopologue Ratios Using Gas Chromatography Chemical Ionization Time of Flight Mass Spectrometry - Methodology and Uncertainty of Measurement

The accurate and precise analysis of isotopologue and tandem mass isotopologue ratios in heavy stable isotope labeling experiments is a critical part of assessing absolute intracellular metabolic fluxes. Resulting from feeding the organism of interest with a specifically isotope-labeled substrate, the principal characteristics of these labeling experiments are the metabolites' non-naturally distributed isotopologue patterns. For the purpose of inferring metabolic rates by maximizing the fit between a priori simulated and experimentally obtained labeling patterns, ¹³C is the preferred stable isotope of use.The analysis of the obtained labeling patterns can be approached by different mass spectrometric approaches. Gas chromatography (GC) features broad metabolite coverage and excellent separation efficiency of biologically relevant isomers. These advantages compensate for laborious derivatization steps and the resulting need for interference correction for natural abundant isotopes.Here, we describe a workflow based on GC-high resolution mass spectrometry with chemical ionization for the analysis of carbon-isotopologue distributions and some positional labeling information of primary metabolites. To study the associated measurement uncertainty of the resulting ¹³C labeling patterns, guidance to uncertainty estimation according to the EURACHEM guidelines with Monte-Carlo simulation is provided.

Sensitive quantitative analysis of phosphorylated primary metabolites using selective metal oxide enrichment and GC- and IC- MS/MS

In this study, we present a novel selective cleanup/enrichment method based on metal oxide solid phase extraction combined with quantitative gas chromatography-tandem mass spectrometry and ion exchange chromatography-tandem mass spectrometry for the analysis of phosphorylated metabolites in yeast cell extracts relevant to biotechnological processes. Following screening of several commercially available metal oxide-based enrichment materials, all steps of the enrichment process (loading, washing and elution) were optimized for both the selective enrichment of 12 phosphorylated compounds from the glycolysis and pentose phosphate pathways, and the simultaneous removal of highly abundant matrix components such as organic acids and sugars. The full analytical workflow was then validated to meet the demands of accurate quantification of phosphorylated metabolites in yeast (Pichia pastoris) cell extracts using the best performing material and cleanup/enrichment method combined with quantification strategies based on internal standardization with isotopically labeled internal standards and external calibration. A good recovery (>70%) for 5 of the 12 targeted phosphorylated compounds with RSDs of less than 6.0% was obtained while many sugars, organic acids and amino acids were removed (>99% of glucose, and >95% of aspartate, succinate, glutamate, alanine, glycine, serine, threonine, proline, and valine). The use of isotopically labeled internal standards added to the samples prior to SPE, enables accurate quantification of the metabolites as it compensates for errors introduced during sample pretreatment and GC-MS or LC-MS analysis. To the best of our knowledge, this is the first time an effective and selective metal oxide-based affinity chromatography cleanup/enrichment method was designed and applied successfully for intracellular phosphorylated metabolites.

The Design of FluxML: A Universal Modeling Language for 13C Metabolic Flux Analysis

¹³C metabolic flux analysis (MFA) is the method of choice when a detailed inference of intracellular metabolic fluxes in living organisms under metabolic quasi-steady state conditions is desired. Being continuously developed since two decades, the technology made major contributions to the quantitative characterization of organisms in all fields of biotechnology and health-related research. ¹³C MFA, however, stands out from other "-omics sciences," in that it requires not only experimental-analytical data, but also mathematical models and a computational toolset to infer the quantities of interest, i.e., the metabolic fluxes. At present, these models cannot be conveniently exchanged between different labs. Here, we present the implementation-independent model description language FluxML for specifying ¹³C MFA models. The core of FluxML captures the metabolic reaction network together with atom mappings, constraints on the model parameters, and the wealth of data configurations. In particular, we describe the governing design processes that shaped the FluxML language. We demonstrate the utility of FluxML to represent many contemporary experimental-analytical requirements in the field of ¹³C MFA. The major aim of FluxML is to offer a sound, open, and future-proof language to unambiguously express and conserve all the necessary information for model re-use, exchange, and comparison. Along with FluxML, several powerful computational tools are supplied for easy handling, but also to maintain a maximum of flexibility. Altogether, the FluxML collection is an "all-around carefree package" for ¹³C MFA modelers. We believe that FluxML improves scientific productivity as well as transparency and therewith contributes to the efficiency and reproducibility of computational modeling efforts in the field of ¹³C MFA.

GC-QTOFMS with a low-energy electron ionization source for advancing isotopologue analysis in 13C-based metabolic flux analysis

For the study of different levels of (intra)cellular regulation and condition-dependent insight into metabolic activities, fluxomics experiments based on stable isotope tracer experiments using ¹³C have become a well-established approach. The experimentally obtained non-naturally distributed ¹³C labeling patterns of metabolite pools can be measured by mass spectrometric detection with front-end separation and can be consequently incorporated into biochemical network models. Here, despite a tedious derivatization step, gas chromatographic separation of polar metabolites is favorable because of the wide coverage range and high isomer separation efficiency. However, the typically employed electron ionization energy of 70 eV leads to significant fragmentation and consequently only low-abundant ions with an intact carbon backbone. Since these ions are considered a prerequisite for the analysis of the non-naturally distributed labeling patterns and further integration into modeling strategies, a softer ionization technique is needed. In the present work, a novel low energy electron ionization source is optimized for the analysis of primary metabolites and compared with a chemical ionization approach in terms of trueness, precision, and sensitivity.

Sugar phosphate analysis with baseline separation and soft ionization by gas chromatography-negative chemical ionization-mass spectrometry improves flux estimation of bidirectional reactions in cancer cells

Precise measurement of sugar phosphates in glycolysis and the pentose phosphate (PP) pathway for ¹³C-metabolic flux analysis (¹³C-MFA) is needed to understand cancer-specific metabolism. Although various analytical methods have been proposed, analysis of sugar phosphates is challenging because of the structural similarity of various isomers and low intracellular abundance. In this study, gas chromatography-negative chemical ionization-mass spectrometry (GC-NCI-MS) is applied to sugar phosphate analysis with o-(2,3,4,5,6-pentafluorobenzyl) oxime (PFBO) and trimethylsilyl (TMS) derivatization. Optimization of the GC temperature gradient achieved baseline separation of sugar phosphates in 31 min. Mass spectra showed the predominant generation of fragment ions containing all carbon atoms in the sugar phosphate backbone. The limit of detection of pentose 5-phosphates and hexose 6-phosphates was 10 nM. The method was applied to ¹³C-labeling measurement of sugar phosphates for ¹³C-MFA of the MCF-7 human breast cancer cell line. ¹³C-labeling of sugar phosphates for ¹³C-MFA improved the estimation of the net flux and reversible flux of bidirectional reactions in glycolysis and the PP pathway.

Comprehensive assessment of measurement uncertainty in 13C-based metabolic flux experiments

In the field of metabolic engineering ¹³C-based metabolic flux analysis experiments have proven successful in indicating points of action. As every step of this approach is affected by an inherent error, the aim of the present work is the comprehensive evaluation of factors contributing to the uncertainty of nonnaturally distributed C-isotopologue abundances as well as to the absolute flux value calculation. For this purpose, a previously published data set, analyzed in the course of a ¹³C labeling experiment studying glycolysis and the pentose phosphate pathway in a yeast cell factory, was used. Here, for isotopologue pattern analysis of these highly polar metabolites that occur in multiple isomeric forms, a gas chromatographic separation approach with preceding derivatization was used. This rendered a natural isotope interference correction step essential. Uncertainty estimation of the resulting C-isotopologue distribution was performed according to the EURACHEM guidelines with Monte Carlo simulation. It revealed a significant increase for low-abundance isotopologue fractions after application of the necessary correction step. For absolute flux value estimation, isotopologue fractions of various sugar phosphates, together with the assessed uncertainties, were used in a metabolic model describing the upper part of the central carbon metabolism. The findings pinpointed the influence of small isotopologue fractions as sources of error and highlight the need for improved model curation.

Graphical abstract

In situ observation of localized, sub-mm scale changes of phosphorus biogeochemistry in the rhizosphere

AIMS

We imaged the sub-mm distribution of labile P and pH in the rhizosphere of three plant species to localize zones and hot spots of P depletion and accumulation along individual root axes and to relate our findings to nutrient acquisition / root exudation strategies in P-limited conditions at different soil pH, and to mobilization pattern of other elements (Al, Fe, Ca, Mg, Mn) in the rhizosphere.

METHODS

Sub-mm distributions of labile elemental patterns were sampled using diffusive gradients in thin films and analysed using laser ablation inductively coupled plasma mass spectrometry. pH images were taken using planar optodes.

RESULTS

We found distinct patterns of highly localized labile P depletion and accumulation reflecting the complex interaction of plant P acquisition strategies with soil pH, fertilizer treatment, root age, and elements (Al, Fe, Ca) that are involved in P biogeochemistry in soil. We show that the plants respond to P deficiency either by acidification or alkalization, depending on initial bulk soil pH and other factors of P solubility.

CONCLUSIONS

P solubilization activities of roots are highly localized, typically around root apices, but may also extend towards the extension / root hair zone.

Characterization of three pyranose dehydrogenase isoforms from the litter-decomposing basidiomycete Leucoagaricus meleagris (syn. Agaricus meleagris)

Multigenicity is commonly found in fungal enzyme systems, with the purpose of functional compensation upon deficiency of one of its members or leading to enzyme isoforms with new functionalities through gene diversification. Three genes of the flavin-dependent glucose-methanol-choline (GMC) oxidoreductase pyranose dehydrogenase (AmPDH) were previously identified in the litter-degrading fungus Agaricus (Leucoagaricus) meleagris, of which only AmPDH1 was successfully expressed and characterized. The aim of this work was to study the biophysical and biochemical properties of AmPDH2 and AmPDH3 and compare them with those of AmPDH1. AmPDH1, AmPDH2 and AmPDH3 showed negligible oxygen reactivity and possess a covalently tethered FAD cofactor. All three isoforms can oxidise a range of different monosaccarides and oligosaccharides including glucose, mannose, galactose and xylose, which are the main constituent sugars of cellulose and hemicelluloses, and judging from the apparent steady-state kinetics determined for these sugars, the three isoforms do not show significant differences pertaining to their reaction with sugar substrates. They oxidize glucose both at C2 and C3 and upon prolonged reaction C2 and C3 double-oxidized glucose is obtained, confirming that the A. meleagris genes pdh2 (AY753308.1) and pdh3 (DQ117577.1) indeed encode CAZy class AA3_2 pyranose dehydrogenases. While reactivity with electron donor substrates was comparable for the three AmPDH isoforms, their kinetic properties differed significantly for the model electron acceptor substrates tested, a radical (the 2,2'-azino-bis[3-ethylbenzothiazoline-6-sulphonic acid] cation radical), a quinone (benzoquinone) and a complexed iron ion (the ferricenium ion). Thus, a possible explanation for this PDH multiplicity in A. meleagris could be that different isoforms react preferentially with structurally different electron acceptors in vivo.

Comprehensive and accurate tracking of carbon origin of LC-tandem mass spectrometry collisional fragments for 13C-MFA

In recent years the benefit of measuring positionally resolved 13C-labeling enrichment from tandem mass spectrometry (MS/MS) collisional fragments for improved precision of 13C-Metabolic Flux Analysis (13C-MFA) has become evident. However, the usage of positional labeling information for 13C-MFA faces two challenges: (1) The mass spectrometric acquisition of a large number of potentially interfering mass transitions may hamper accuracy and sensitivity. (2) The positional identity of carbon atoms of product ions needs to be known. The present contribution addresses the latter challenge by deducing the maximal positional labeling information contained in LC-ESI-MS/MS spectra of product anions of central metabolism as well as product cations of amino acids. For this purpose, we draw on accurate mass spectrometry, selectively labeled standards, and published fragmentation pathways to structurally annotate all dominant mass peaks of a large collection of metabolites, some of which with a complete fragmentation pathway. Compiling all available information, we arrive at the most detailed map of carbon atom fate of LC-ESI-MS/MS collisional fragments yet, comprising 170 intense and structurally annotated product ions with unique carbon origin from 76 precursor ions of 72 metabolites. Our 13C-data proof that heuristic fragmentation rules often fail to yield correct fragment structures and we expose common pitfalls in the structural annotation of product ions. We show that the positionally resolved 13C-label information contained in the product ions that we structurally annotated allows to infer the entire isotopomer distribution of several central metabolism intermediates, which is experimentally demonstrated for malate using quadrupole-time-of-flight MS technology. Finally, the inclusion of the label information from a subset of these fragments improves flux precision in a Corynebacterium glutamicum model of the central carbon metabolism.

Genome Analysis and Characterisation of the Exopolysaccharide Produced by Bifidobacterium longum subsp. longum 35624™

The Bifibobacterium longum subsp. longum35624^™ strain (formerly named Bifidobacterium longum subsp. infantis) is a well described probiotic with clinical efficacy in Irritable Bowel Syndrome clinical trials and induces immunoregulatory effects in mice and in humans. This paper presents (a) the genome sequence of the organism allowing the assignment to its correct subspeciation longum; (b) a comparative genome assessment with other B. longum strains and (c) the molecular structure of the 35624 exopolysaccharide (EPS₆₂₄). Comparative genome analysis of the 35624 strain with other B. longum strains determined that the sub-speciation of the strain is longum and revealed the presence of a 35624-specific gene cluster, predicted to encode the biosynthetic machinery for EPS₆₂₄. Following isolation and acid treatment of the EPS, its chemical structure was determined using gas and liquid chromatography for sugar constituent and linkage analysis, electrospray and matrix assisted laser desorption ionization mass spectrometry for sequencing and NMR. The EPS consists of a branched hexasaccharide repeating unit containing two galactose and two glucose moieties, galacturonic acid and the unusual sugar 6-deoxy-L-talose. These data demonstrate that the B. longum35624 strain has specific genetic features, one of which leads to the generation of a characteristic exopolysaccharide.

PCI-GC-MS-MS approach for identification of non-amino organic acid and amino acid profiles

Alkyl chloroformate have been wildly used for the fast derivatization of metabolites with amino and/or carboxyl groups, coupling of powerful separation and detection systems, such as GC-MS, which allows the comprehensive analysis of non-amino organic acids and amino acids. The reagents involving n-alkyl chloroformate and n-alcohol are generally employed for providing symmetric labeling terminal alkyl chain with the same length. Here, we developed an asymmetric labeling strategy and positive chemical ionization gas chromatography-tandem mass spectrometry (PCI-GC-MS-MS) approach for determination of non-amino organic acids and amino acids, as well as the short chain fatty acids. Carboxylic and amino groups could be selectively labelled by propyl and ethyl groups, respectively. The specific neutral loss of C₃H₈O (60Da), C₃H₅O₂ (74Da) and C₄H₈O₂ (88Da) were useful in the selective identification for qualitative analysis of organic acids and amino acid derivatives. PCI-GC-MS-MS using multiple reaction monitoring (MRM) was applied for semi-quantification of typical non-amino organic acids and amino acids. This method exhibited a wide range of linear range, good regression coefficient (R²) and repeatability. The relative standard deviation (RSD) of targeted metabolites showed excellent intra- and inter-day precision (<5%). Our method provided a qualitative and semi-quantitative PCI-GC-MS-MS, coupled with alkyl chloroformate derivatization.

Increasing pentose phosphate pathway flux enhances recombinant protein production in Pichia pastoris

Production of heterologous proteins in Pichia pastoris (syn. Komagataella sp.) has been shown to exert a metabolic burden on the host metabolism. This burden is associated with metabolite drain, which redirects nucleotides and amino acids from primary metabolism. On the other hand, recombinant protein production affects energy and redox homeostasis of the host cell. In a previous study, we have demonstrated that overexpression of single genes of the oxidative pentose phosphate pathway (PPP) had a positive influence on recombinant production of cytosolic human superoxide dismutase (hSOD). In this study, different combinations of these genes belonging to the oxidative PPP were generated and analyzed. Thereby, a 3.8-fold increase of hSOD production was detected when glucose-6-phosphate dehydrogenase (ZWF1) and 6-gluconolactonase (SOL3) were simultaneously overexpressed, while the combinations of other genes from PPP had no positive effect on protein production. By measuring isotopologue patterns of ¹³C-labelled metabolites, we could detect an upshift in the flux ratio of PPP to glycolysis upon ZWF1 and SOL3 co-overexpression, as well as increased levels of 6-phosphogluconate. The substantial improvement of hSOD production by ZWF1 and SOL3 co-overexpression appeared to be connected to an increase in PPP flux. In conclusion, we show that overexpression of SOL3 together with ZWF1 enhanced both the PPP flux ratio and hSOD accumulation, providing evidence that in P. pastoris Sol3 limits the flux through PPP and recombinant protein production.

Gas Chromatography-Quadrupole Time-of-Flight Mass Spectrometry-Based Determination of Isotopologue and Tandem Mass Isotopomer Fractions of Primary Metabolites for (13)C-Metabolic Flux Analysis

For the first time an analytical work flow based on accurate mass gas chromatography-quadrupole time-of-flight mass spectrometry (GC-QTOFMS) with chemical ionization for analysis providing a comprehensive picture of (13)C distribution along the primary metabolism is elaborated. The method provides a powerful new toolbox for (13)C-based metabolic flux analysis, which is an emerging strategy in metabolic engineering. In this field, stable isotope tracer experiments based on, for example, (13)C are central for providing characteristic patterns of labeled metabolites, which in turn give insights into the regulation of metabolic pathway kinetics. The new method enables the analysis of isotopologue fractions of 42 free intracellular metabolites within biotechnological samples, while tandem mass isotopomer information is also accessible for a large number of analytes. Hence, the method outperforms previous approaches in terms of metabolite coverage, while also providing rich isotopomer information for a significant number of key metabolites. Moreover, the established work flow includes novel evaluation routines correcting for isotope interference of naturally distributed elements, which is crucial following derivatization of metabolites. Method validation in terms of trueness, precision, and limits of detection was performed, showing excellent analytical figures of merit with an overall maximum bias of 5.8%, very high precision for isotopologue and tandem mass isotopomer fractions representing >10% of total abundance, and absolute limits of detection in the femtomole range. The suitability of the developed method is demonstrated on a flux experiment of Pichia pastoris employing two different tracers, i.e., 1,6(13)C2-glucose and uniformly labeled (13)C-glucose.

Reaction of pyranose dehydrogenase from Agaricus meleagris with its carbohydrate substrates

Monomeric Agaricus meleagris pyranose dehydrogenase (AmPDH) belongs to the glucose-methanol-choline family of oxidoreductases. An FAD cofactor is covalently tethered to His103 of the enzyme. AmPDH can double oxidize various mono- and oligosaccharides at different positions (C1 to C4). To study the structure/function relationship of selected active-site residues of AmPDH pertaining to substrate (carbohydrate) turnover in more detail, several active-site variants were generated, heterologously expressed in Pichia pastoris, and characterized by biochemical, biophysical and computational means. The crystal structure of AmPDH shows two active-site histidines, both of which could take on the role as the catalytic base in the reductive half-reaction. Steady-state kinetics revealed that His512 is the only catalytic base because H512A showed a reduction in (kcat /KM )glucose by a factor of 10(5) , whereas this catalytic efficiency was reduced by two or three orders of magnitude for His556 variants (H556A, H556N). This was further corroborated by transient-state kinetics, where a comparable decrease in the reductive rate constant was observed for H556A, whereas the rate constant for the oxidative half-reaction (using benzoquinone as substrate) was increased for H556A compared to recombinant wild-type AmPDH. Steady-state kinetics furthermore indicated that Gln392, Tyr510, Val511 and His556 are important for the catalytic efficiency of PDH. Molecular dynamics (MD) simulations and free energy calculations were used to predict d-glucose oxidation sites, which were validated by GC-MS measurements. These simulations also suggest that van der Waals interactions are the main driving force for substrate recognition and binding.