Comparison of quenching and extraction methodologies for metabolome analysis of Lactobacillus plantarum

Screening of leaf extraction and storage conditions for eco-metabolomics studies

Mass spectrometry-based plant metabolomics is frequently used to identify novel natural products or study the effect of specific treatments on a plant's metabolism. Reliable sample handling is required to avoid artifacts, which is why most protocols mandate shock freezing of plant tissue in liquid nitrogen and an uninterrupted cooling chain. However, the logistical challenges of this approach make it infeasible for many ecological studies. Especially for research in the tropics, permanent cooling poses a challenge, which is why many of those studies use dried leaf tissue instead. We screened a total of 10 extraction and storage approaches for plant metabolites extracted from maize leaf tissue across two cropping seasons to develop a methodology for agroecological studies in logistically challenging tropical locations. All methods were evaluated based on changes in the metabolite profile across a 2-month storage period at different temperatures with the goal of reproducing the metabolite profile of the living plant as closely as possible. We show that our newly developed on-site liquid-liquid extraction protocol provides a good compromise between sample replicability, extraction efficiency, material logistics, and metabolite profile stability. We further discuss alternative methods which showed promising results and feasibility of on-site sample handling for field studies.

A Simple, Fast, Sensitive LC-MS/MS Method to Quantify NAD(H) in Biological Samples: Plasma NAD(H) Measurement to Monitor Brain Pathophysiology

Nicotinamide adenine dinucleotide (NAD) is a cofactor in redox reactions and an essential mediator of energy metabolism. The redox balance between NAD+ and NADH affects various diseases, cell differentiation, and aging, and in recent years there has been a growing need for measurement techniques with improved accuracy. However, NAD(H) measurements, representing both NAD+ and NADH, have been limited by the compound's properties. We achieved highly sensitive simultaneous measurement of NAD+ and NADH under non-ion pairing, mobile phase conditions of water, or methanol containing 5 mM ammonium acetate. These were achieved using a simple pre-treatment and 7-min analysis time. Use of the stable isotope 13C5-NAD+ as an internal standard enabled validation close to BMV criteria and demonstrated the robustness of NAD(H) determination. Measurements using this method showed that brain NAD(H) levels correlate strongly with plasma NAD(H) levels in the same mouse, indicating that NAD(H) concentrations in brain tissue are reflected in plasma. As NAD(H) is involved in various neurodegenerative diseases and cerebral ischemia, as well as brain diseases such as mitochondrial myopathies, monitoring changes in NADH levels in plasma after drug administration will be useful for development of future diagnostics and therapeutics.

Differences in the management of intracellular redox state between wine yeast species dictate their fermentation performances and metabolite production

The maintenance of the balance between oxidised and reduced redox cofactors is essential for the functioning of many cellular processes in all living organisms. While the electron transport chain plays a key role in maintaining this balance under respiratory conditions, its inactivity in the absence of oxygen poses a challenge that yeasts such as Saccharomyces cerevisiae overcome through the production of various metabolic end-products during alcoholic fermentation. In this study, we investigated the diversity occurring between wine yeast species in their management of redox balance and its consequences on the fermentation performances and the formation of metabolites. To this aim, we quantified the changes in NAD(H) and NADP(H) concentrations and redox status throughout the fermentation of 6 wine yeast species. While the availability of NADP and NADPH remained balanced and stable throughout the process for all the strains, important differences between species were observed in the dynamics of NAD and NADH intracellular pools. A comparative analysis of these data with the fermentation capacity and metabolic profiles of the strains revealed that Saccharomyces cerevisiae, Torulaspora delbrueckii and Lachancea thermotolerans strains were able to reoxidise NADH to NAD throughout the fermentation, mainly by the formation of glycerol. These species exhibited good fermentation capacities. Conversely, Starmerella bacillaris and Metschnikowia pulcherrima species were unable to regenerate NAD as early as one third of sugars were consumed, explaining at least in part their poor growth and fermentation performances. The Kluyveromyces marxianus strain exhibited a specific behaviour, by maintaining similar levels of NAD and NADH throughout the process. This balance between oxidised and reduced redox cofactors ensured the consumption of a large part of sugars by this species, despite a low fermentation rate. In addition, the dynamics of redox cofactors affected the production of by-products by the various strains either directly or indirectly, through the formation of precursors. Major examples are the increased formation of glycerol by S. bacillaris and M. pulcherrima strains, as a way of trying to reoxidise NADH, and the greater capacity to produce acetate and derived metabolites of yeasts capable of maintaining their redox balance. Overall, this study provided new insight into the contribution of the management of redox status to the orientation of yeast metabolism during fermentation. This information should be taken into account when developing strategies for more efficient and effective fermentation.

Multiplatform untargeted metabolomics

Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics.

Multiplatform untargeted metabolomics

Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics.

The Commensal Anaerobe Veillonella dispar Reprograms Its Lactate Metabolism and Short-Chain Fatty Acid Production during the Stationary Phase

Veillonella spp. are obligate, anaerobic, Gram-negative bacteria found in the human oral cavity and gut. Recent studies have indicated that gut Veillonella promote human homeostasis by producing beneficial metabolites, specifically short-chain fatty acids (SCFAs), by lactate fermentation. The gut lumen is a dynamic environment with fluctuating nutrient levels, so the microbes present shifting growth rates and significant variations of gene expression. The current knowledge of lactate metabolism by Veillonella has focused on log phase growth. However, the gut microbes are mainly in the stationary phase. In this study, we investigated the transcriptomes and major metabolites of Veillonella dispar ATCC 17748T during growth from log to stationary phases with lactate as the main carbon source. Our results revealed that V. dispar reprogrammed its lactate metabolism during the stationary phase. Lactate catabolic activity and propionate production were significantly decreased during the early stationary phase but were partially restored during the stationary phase. The propionate/acetate production ratio was lowered from 1.5 during the log phase to 0.9 during the stationary phase. Pyruvate secretion was also greatly decreased during the stationary phase. Furthermore, we have demonstrated that the gene expression of V. dispar is reprogrammed during growth, as evidenced by the distinct transcriptomes present during the log, early stationary, and stationary phases. In particular, propionate metabolism (the propanediol pathway) was downregulated during the early stationary phase, which explains the decrease in propionate production during the stationary phase. The fluctuations in lactate fermentation during the stationary phase and the associated gene regulation expand our understanding of the metabolism of commensal anaerobes in changing environments. IMPORTANCE Short-chain fatty acids produced by gut commensal bacteria play an important role in human physiology. Gut Veillonella and the metabolites acetate and propionate, produced by lactate fermentation, are associated with human health. Most gut bacteria in humans are in the stationary phase. Lactate metabolism by Veillonella spp. during the stationary phase is poorly understood and was therefore the focus of the study. To this end, we used a commensal anaerobic bacterium and explored its short-chain fatty acid production and gene regulation in order to provide a better understanding of lactate metabolism dynamics during nutrient limitation.

A novel approach to Lactiplantibacillus plantarum: From probiotic properties to the omics insights

Lactiplantibacillus plantarum (previously known as Lactobacillus plantarum) strains are one of the lactic acid bacteria (LAB) commonly used in fermentation and their probiotic and functional properties along with their health-promoting roles come to the fore. Food-derived L. plantarum strains have shown good resistance and adhesion in the gastrointestinal tract (GI) and excellent antioxidant and antimicrobial properties. Furthermore, many strains of L. plantarum can produce bacteriocins with interesting antimicrobial activity. This probiotic properties of L. plantarum and existing in different niches give a great potential to have beneficial effects on health. It is also has been shown that L. plantarum can regulate the intestinal microbiota composition in a good way. Recently, omics approaches such as metabolomics, secretomics, proteomics, transcriptomics and genomics try to understand the roles and mechanisms of L. plantarum that are related to its functional characteristics. This review provides an overview of the probiotic properties, including the specific interactions between microbiota and host, and omics insights of L. plantarum.

Cofactor Engineering for Efficient Production of α-Farnesene by Rational Modification of NADPH and ATP Regeneration Pathway in Pichia pastoris

α-Farnesene, an acyclic volatile sesquiterpene, plays important roles in aircraft fuel, food flavoring, agriculture, pharmaceutical and chemical industries. Here, by re-creating the NADPH and ATP biosynthetic pathways in Pichia pastoris, we increased the production of α-farnesene. First, the native oxiPPP was recreated by overexpressing its essential enzymes or by inactivating glucose-6-phosphate isomerase (PGI). This revealed that the combined over-expression of ZWF1 and SOL3 increases α-farnesene production by improving NADPH supply, whereas inactivating PGI did not do so because it caused a reduction in cell growth. The next step was to introduce heterologous cPOS5 at various expression levels into P. pastoris. It was discovered that a low intensity expression of cPOS5 aided in the production of α-farnesene. Finally, ATP was increased by the overexpression of APRT and inactivation of GPD1. The resultant strain P. pastoris X33-38 produced 3.09 ± 0.37 g/L of α-farnesene in shake flask fermentation, which was 41.7% higher than that of the parent strain. These findings open a new avenue for the development of an industrial-strength α-farnesene producer by rationally modifying the NADPH and ATP regeneration pathways in P. pastoris.

An NADPH-auxotrophic Corynebacterium glutamicum recombinant strain and used it to construct L-leucine high-yielding strain

The NADPH-regeneration enzymes in Corynebacterium glutamicum were inactivated to construct an NADPH-auxotrophic C. glutamicum strain by gene knockout and gene replacement. The resultant NADPH-auxotrophic C. glutamicum XL-1 ΔZMI_Cg::I_Sm (i.e., strain Leu-1) grew well in the basic medium only with gluconate as carbon source. Replacement of the native glyceraldehyde 3-phosphate dehydrogenase (NAD-GapDH_Cg) by NADP-GapDH_Ca from Clostridium acetobutylicum is an effective strategy for producing L-leucine in NADPH-prototrophic strain XL-1 and NADPH-auxotrophic strain Leu-1, whereas the L-leucine yield did not differ significantly between these strains (14.1 ± 1.8 g/L vs 16.2 ± 1.1 g/L). Enhancing the carbon flux in biosynthetic pathway by recombinant expression plasmid pEC-ABNCE promoted L-leucine production, but the shortage NADPH supply limited the L-leucine yield. The mutated promoters of zwf and icd_Cg were introduced into C. glutamicum with NADP-GapDH_Ca and pEC-ABNCE increased L-leucine yield (54.3 ± 2.9 g/L) and improved cell growth (OD₅₆₂ = 83.4 ± 7.5) in fed-batch fermentation because the resultant strain C. glutamicum XL-1 ΔMI_Cg::I_Sm G_Cg::G_Ca P_zwf-D1 P_icd-D2/pEC-ABNCE (i.e., strain Leu-9) exhibited the proper intracellular NADPH and NADH level. This is the first report of constructing an L-leucine high-yielding strain that reasonably supplies NADPH by optimizing the biosynthetic pathway of NADPH from an NADPH-auxotrophic strain.

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.

13C-Isotope-Assisted Assessment of Metabolic Quenching During Sample Collection from Suspension Cell Cultures

Metabolomics and fluxomics are core approaches to directly profile and interrogate cellular metabolism in response to various genetic or environmental perturbations. In order to accurately measure the abundance and isotope enrichment of intracellular metabolites, cell culture samples must be rapidly harvested and cold quenched to preserve the in vivo metabolic state of the cells at the time of sample collection. When dealing with suspension cultures, this process is complicated by the need to separate the liquid culture media from cellular biomass prior to metabolite extraction. Here, we examine the efficacy of several commonly used metabolic quenching methods, using the model cyanobacterium Synechocystis sp. PCC 6803 as an example. Multiple ¹³C-labeled compounds, including ¹³C-bicarbonate, ¹³C-glucose, and ¹³C-glutamine, were used as tracers during the sample collection and the cold-quenching process to assess the extent of metabolic turnover after cells were harvested from culture flasks. We show that the combination of rapid filtration followed by 100% cold (-80 °C) methanol quenching exhibits the highest quenching efficiency, while mixing cell samples with a partially frozen 30% methanol slurry (-24 °C) followed by centrifugation is slightly less effective at quenching metabolism but enables less laborious sample processing. By contrast, rapidly mixing the cells with a saline ice slurry (∼0 °C) is less effective, as indicated by high isotope-labeling rates after sample harvest, while mixing the cells with 60% cold methanol (-65 °C) prior to centrifugation causes significant metabolite loss. This study demonstrates a rigorous, quantitative, and broadly applicable method for assessing the metabolic quenching efficacy of protocols used for sample collection in metabolomics and fluxomics studies.

Hot isopropanol quenching procedure for automated microtiter plate scale 13C-labeling experiments

Background

Currently, the generation of genetic diversity for microbial cell factories outpaces the screening of strain variants with omics-based phenotyping methods. Especially isotopic labeling experiments, which constitute techniques aimed at elucidating cellular phenotypes and supporting rational strain design by growing microorganisms on substrates enriched with heavy isotopes, suffer from comparably low throughput and the high cost of labeled substrates.

Results

We present a miniaturized, parallelized, and automated approach to ¹³C-isotopic labeling experiments by establishing and validating a hot isopropanol quenching method on a robotic platform coupled with a microbioreactor cultivation system. This allows for the first time to conduct automated labeling experiments at a microtiter plate scale in up to 48 parallel batches. A further innovation enabled by the automated quenching method is the analysis of free amino acids instead of proteinogenic ones on said microliter scale. Capitalizing on the latter point and as a proof of concept, we present an isotopically instationary labeling experiment in Corynebacterium glutamicum ATCC 13032, generating dynamic labeling data of free amino acids in the process.

Conclusions

Our results show that a robotic liquid handler is sufficiently fast to generate informative isotopically transient labeling data. Furthermore, the amount of biomass obtained from a sub-milliliter cultivation in a microbioreactor is adequate for the detection of labeling patterns of free amino acids. Combining the innovations presented in this study, isotopically stationary and instationary automated labeling experiments can be conducted, thus fulfilling the prerequisites for ¹³C-metabolic flux analyses in high-throughput.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-022-01806-4.

Bacterial Metabolomics: Sample Preparation Methods

Metabolomics is a comprehensive analysis of metabolites existing in biological systems. As one of the important "omics" tools, the approach has been widely employed in various fields in helping to better understand the complex cellular metabolic states and changes. Bacterial metabolomics has gained a significant interest as bacteria serve to provide a better subject or model at systems level. The approach in metabolomics is categorized into untargeted and targeted which serves different paradigms of interest. Nevertheless, the bottleneck in metabolomics has been the sample or metabolite preparation method. A custom-made method and design for a particular species or strain of bacteria might be necessary as most studies generally refer to other bacteria or even yeast and fungi that may lead to unreliable analysis. The paramount aspect of metabolomics design comprises sample harvesting, quenching, and metabolite extraction procedures. Depending on the type of samples and research objective, each step must be at optimal conditions which are significantly important in determining the final output. To date, there are no standardized nor single designated protocols that have been established for a specific bacteria strain for untargeted and targeted approaches. In this paper, the existing and current developments of sample preparation methods of bacterial metabolomics used in both approaches are reviewed. The review also highlights previous literature of optimized conditions used to propose the most ideal methods for metabolite preparation, particularly for bacterial cells. Advantages and limitations of methods are discussed for future improvement of bacterial metabolomics.

Positive feedback exists and drives the glucose-mediated repression in Escherichia coli

The expression of the lac operon of E. coli is subject to positive feedback during growth in the presence of gratuitous inducers, but its existence in the presence of lactose remains controversial. The key question in this debate is: Do the lactose enzymes, Lac permease and β-galactosidase, promote accumulation of allolactose? If so, positive feedback exists since allolactose does stimulate synthesis of the lactose enzymes. Here, we addressed the above question by developing methods for determining the intracellular allolactose concentration as well as the kinetics of enzyme induction and dilution. We show that, during lac induction in the presence of lactose, the intracellular allolactose concentration increases with the lactose enzyme level, which implies that lactose enzymes promote allolactose accumulation, and positive feedback exists. We also show that, during lac repression in the presence of lactose + glucose, the intracellular allolactose concentration decreases with the lactose enzyme levels, which suggests that, under these conditions, the positive feedback loop turns in the reverse direction. The induction and dilution rates derived from the transient data show that the positive feedback loop is reversed due to a radical shift of the steady-state induction level. This is formally identical to the mechanism driving catabolite repression in the presence of TMG + glucose.

Improved Sample Preparation for Untargeted Metabolomics Profiling of Escherichia coli

Metabolomics is a powerful tool that can systematically describe global changes in the metabolome of microbes, thus improving our understanding of the mechanisms of action of antibiotics and facilitating the development of next-generation antibacterial therapies. However, current sample preparation methods are not efficient or reliable for studying the effects of antibiotics on microbes. In the present study, we reported a novel sample preparation approach using cold methanol/ethylene glycol for quenching Escherichia coli, thus overcoming the loss of intracellular metabolites caused by cell membrane damage. After evaluating the extraction efficiency of several extraction methods, we employed the optimized workflow to profile the metabolome of E. coli exposed to cephalexin. In doing so, we proved the utility of the proposed approach and provided insights into the comprehensive metabolic alterations associated with antibiotic treatment.

IMPORTANCE The emergence and global spread of multidrug-resistant bacteria and genes are a global problem. It is critical to understand the interactions between antibiotics and bacteria and find alternative treatments for infections when we are moving closer to a postantibiotic era. It has been demonstrated that the bacterial metabolic environment plays an important role in the modulation of antibiotic susceptibility and efficacy. In the present study, we proposed a novel metabolomic approach for intracellular metabolite profiling of E. coli, which can be used to investigate the metabolite alterations of bacteria caused by antibiotic treatment. Further understanding of antibiotic-induced perturbations of bacterial metabolism would facilitate the discovery of new therapeutic targets and pathways.

Comparative genomics and metabolomics analysis of Riemerella anatipestifer strain CH-1 and CH-2

Riemerella anatipestifer is a major pathogenic microorganism in poultry causing serositis with significant mortality. Serotype 1 and 2 were most pathogenic, prevalent, and liable over the world. In this study, the intracellular metabolites in R. anatipestifer strains RA-CH-1 (serotype 1) and RA-CH-2 (serotype 2) were identified by gas chromatography-mass spectrometer (GC–MS). The metabolic profiles were performed using hierarchical clustering and partial least squares discriminant analysis (PLS-DA). The results of hierarchical cluster analysis showed that the amounts of the detected metabolites were more abundant in RA-CH-2. RA-CH-1 and RA-CH-2 were separated by the PLS-DA model. 24 potential biomarkers participated in nine metabolisms were contributed predominantly to the separation. Based on the complete genome sequence database and metabolite data, the first large-scale metabolic models of iJL463 (RA-CH-1) and iDZ470 (RA-CH-2) were reconstructed. In addition, we explained the change of purine metabolism combined with the transcriptome and metabolomics data. The study showed that it is possible to detect and differentiate between these two organisms based on their intracellular metabolites using GC–MS. The present research fills a gap in the metabolomics characteristics of R. anatipestifer.

Bifidobacterium infantis Metabolizes 2'Fucosyllactose-Derived and Free Fucose Through a Common Catabolic Pathway Resulting in 1,2-Propanediol Secretion

Human milk oligosaccharides (HMOs) enrich beneficial bifidobacteria in the infant gut microbiome which produce molecules that impact development and physiology. 2′fucosyllactose (2′FL) is a highly abundant fucosylated HMO which is utilized by Bifidobacterium longum subsp. infantis, despite limited scientific understanding of the underlying mechanism. Moreover, there is not a current consensus on whether free fucose could be metabolized when not incorporated in a larger oligosaccharide structure. Based on metabolic and genomic analyses, we hypothesize that B. infantis catabolizes both free fucose and fucosyl oligosaccharide residues to produce 1,2-propanediol (1,2-PD). Accordingly, systems-level approaches including transcriptomics and proteomics support this metabolic path. Co-fermentation of fucose and limiting lactose or glucose was found to promote significantly higher biomass and 1,2-PD concentrations than individual substrates, suggesting a synergistic effect. In addition, and during growth on 2′FL, B. infantis achieves significantly higher biomass corresponding to increased 1,2-PD. These findings support a singular fucose catabolic pathway in B. infantis that is active on both free and HMO-derived fucose and intimately linked with central metabolism. The impact of fucose and 2′FL metabolism on B. infantis physiology provides insight into the role of fucosylated HMOs in influencing host- and microbe-microbe interactions within the infant gut microbiome.

High-throughput screening for high-efficiency small-molecule biosynthesis

Systems metabolic engineering faces the formidable task of rewiring microbial metabolism to cost-effectively generate high-value molecules from a variety of inexpensive feedstocks for many different applications. Because these cellular systems are still too complex to model accurately, vast collections of engineered organism variants must be systematically created and evaluated through an enormous trial-and-error process in order to identify a manufacturing-ready strain. The high-throughput screening of strains to optimize their scalable manufacturing potential requires execution of many carefully controlled, parallel, miniature fermentations, followed by high-precision analysis of the resulting complex mixtures. This review discusses strategies for the design of high-throughput, small-scale fermentation models to predict improved strain performance at large commercial scale. Established and promising approaches from industrial and academic groups are presented for both cell culture and analysis, with primary focus on microplate- and microfluidics-based screening systems.

Evaluation of Sample Preparation Methods for Inter-Laboratory Metabolomics Investigation of Streptomyces lividans TK24

In the past two decades, metabolomics has proved to be a valuable tool with many potential applications in different areas of science. However, there are still some challenges that need to be addressed, particularly for multicenter studies. These challenges are mainly attributed to various sources of fluctuation and unwanted variations that can be introduced at pre-analytical, analytical, and/or post-analytical steps of any metabolomics experiment. Thus, this study aimed at using Streptomyces lividans TK24 as the model organism in a cross-laboratory experiment in Manchester and Leuven to evaluate the reproducibility of a standard sample preparation method, and determine the optimal sample format (cell extract or quenched biomass) required to preserve the metabolic profile of the cells during cross-lab sample transportation and storage. Principal component analysis (PCA) scores plot of the gas chromatography-mass spectrometry (GC-MS) data from both laboratories displayed clear growth-dependent clustering patterns which was in agreement with the Procrustes analysis findings. In addition, the data generated in Manchester displayed tight clustering of cell pellets (quenched biomass) and metabolite extracts, confirming the stability of both sample formats during the transportation and storage period.

Effects of Different Sample Pulverisation Methods on the Extraction of Metabolites from the Fermented Cottonseed Meal Based on UPLC-Q-TOF-MS

The precondition of studying biological sample is to extract sample metabolites by the best pretreatment methods. There is already limited information about pretreatments of fermented feed metabolites. The study compared the extraction effects of different pulverisation methods used in the sample pretreatment process for the extraction of metabolites from cottonseed meal fermented by Lactobacillus acidophilus based on UPLC-Q-TOF-MS. The extraction effects of three pretreatments (non-pulverisation (WF), pulverisation (F), and high-speed homogenisation methods (YJ)) were compared with the numbers of metabolites and the normalised peak areas of the metabolites. The results showed that the number of metabolites extracted with three pulverisation methods were 1745, 1896, 2132 (ESI+ mode) and 1447, 1675, 2073 (ESI- mode), respectively. The number of variable importance plot (VIP) metabolites and the relative peak areas of metabolites showed that the trend was YJ > F > WF. The extraction effect of high-speed homogenisation method was the best way to extract metabolites from the fermented cottonseed meal. This study built a foundation work for the further research of the fermented feed metabolomics.

Applications of MicroArrays for Mass Spectrometry (MAMS) in Single-Cell Metabolomics

The metabolic network is the endpoint in the flow of information that begins with the "gene" and ends with "phenotype" (observable function) of the cell. Previously, due to the variety of metabolites analyzed inside cells, the metabolomic measurements were performed with samples including multiple cells. Unfortunately, this sampling process may mask important metabolic phenomena, such as cell-to-cell heterogeneity. For these studies, we must use analytical techniques that can robustly deliver reproducible results with single-cell sensitivity. In this chapter, we summarize laser-based methods for single-cell analysis and a novel approach of MicroArrays for Mass Spectrometry (or MAMS) is described in full detail. This particular type of microarrays was tailored for the study of cells grown in liquid medium using multiple-analytical read-outs, such as optical and laser desorption/ionization (LDI) or MALDI mass spectrometry.

Determination of online quenching efficiency for an automated cellular microfluidic metabolomic platform using mass spectrometry based ATP degradation analysis

As microfluidic cell culture progresses, the need for robust and reproducible intracellular analyses grows. In particular, intracellular metabolites are subject to perturbation and degradation during the lysing process. The reliability of intracellular metabolomic analysis in microfluidic devices depends on the preservation of metabolite integrity during sample preparation and storage. Described here is a novel automated microfluidic system exhibiting the necessary rapid cellular lysis and quenching of enzymatic activity. Quenching efficiency was assessed using a novel ratiometric MALDI-MS-based assay of exogenous isotopic adenosine triphosphate (ATP) hydrolysis to isotopic adenosine diphosphate (ADP) as a marker of metabolite degradation. The lysis system of the microfluidic device was enhanced using a Peltier cooler to chill the lysate and quench aberrant enzymatic activity. Parameter optimization (flow rate, collection time, and temperature control) improved the endogenous and exogenous ADP/ATP ratios by 44.9% and 39.8% respectively consistent with traditional quenching techniques. The effects of chilling/quenching on metabolism were evaluated resulting in over 500 significant features compared to non-chilled from untargeted capillary LC-MS metabolomic analyses. These include increased levels of tryptophan, histidine, and pyruvate as well as decreased levels in UDP-N-acetylglucosamine. The results illustrate the need for both rapid lysis and quenching in microfluidic cell culture platforms. Graphical abstract.

Suppression of lactate production by using sucrose as a carbon source in lactic acid bacteria

Lactic acid bacteria (LAB) grow by producing lactate from sugar. However, the accumulation of lactate inhibits their growth. Here, the lactate productivity per cell in a semi-solid medium prepared with a chlorella powder in several LAB strains was much lower than that in the conventional MRS medium. Furthermore, the lactate production was suppressed not only in semi-solid medium, but also in chlorella liquid medium. The lactate productivity by Lactococcus lactis subsp. lactis NBRC 12007 in the chlorella liquid medium and MRS medium was 3.0 and 6.9 g-lactate·g-cell^-1, respectively. The productivity of lactate in the chlorella liquid medium decreased to 44% of that in MRS medium. Gas chromatography/mass spectrometry (GC/MS) analysis of the culture supernatants revealed that the utilization of sucrose in the chlorella powder led to the suppression of lactate production. Comparison of the metabolites extracted from the cells indicated that the two ATP generating pathways, the arginine deiminase pathway and the decarboxylation reaction of glutamate and GABA, which are usually repressed by glucose, are activated in chlorella medium. It was considered that these pathways which do not require NAD⁺ for generation of ATP are not repressed when sucrose is used as a carbon source. Thus, the utilization of these pathways results in the suppression of the lactate production.

Dynamic 13C Labeling of Fast Turnover Metabolites for Analysis of Metabolic Fluxes and Metabolite Channeling

Dynamic or isotopically nonstationary ¹³C labeling experiments are a powerful tool not only for precise carbon flux quantification (e.g., metabolic flux analysis of photoautotrophic organisms) but also for the investigation of pathway bottlenecks, a cell's phenotype, and metabolite channeling. In general, isotopically nonstationary metabolic flux analysis requires three main components: (1) transient isotopic labeling experiments; (2) metabolite quenching and isotopomer analysis using LC-MS; (3) metabolic network construction and flux quantification. Labeling dynamics of key metabolites from ¹³C-pulse experiments allow flux estimation of key central pathways by solving ordinary differential equations to fit time-dependent isotopomer distribution data. Additionally, it is important to provide biomass requirements, carbon uptake rates, specific growth rates, and carbon excretion rates to properly and precisely balance the metabolic network. Labeling dynamics through cascade metabolites may also identify channeling phenomena in which metabolites are passed between enzymes without mixing with the bulk phase. In this chapter, we outline experimental protocols to probe metabolic pathways through dynamic labeling. We describe protocols for labeling experiments, metabolite quenching and extraction, LC-MS analysis, computational flux quantification, and metabolite channeling observations.

Equilibrium of the intracellular redox state for improving cell growth and L-lysine yield of Corynebacterium glutamicum by optimal cofactor swapping

Background

NAD(H/⁺) and NADP(H/⁺) are the most important redox cofactors in bacteria. However, the intracellular redox balance is in advantage of the cell growth and production of NAD(P)H-dependent products.

Results

In this paper, we rationally engineered glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and isocitrate dehydrogenase (IDH) to switch the nucleotide-cofactor specificity resulting in an increase in final titer [from 85.6 to 121.4 g L⁻¹] and carbon yield [from 0.33 to 0.46 g (g glucose)⁻¹] of l-lysine in strain RGI in fed-batch fermentation. To do this, we firstly analyzed the production performance of original strain JL-6, indicating that the imbalance of intracellular redox was the limiting factor for l-lysine production. Subsequently, we modified the native GAPDH and indicated that recombinant strain RG with nonnative NADP-GAPDH dramatically changed the intracellular levels of NADH and NADPH. However, l-lysine production did not significantly increase because cell growth was harmed at low NADH level. Lastly, the nonnative NAD-IDH was introduced in strain RG to increase the NADH availability and to equilibrate the intracellular redox. The resulted strain RGI showed the stable ratio of NADPH/NADH at about 1.00, which in turn improved cell growth (μ_max. = 0.31 h⁻¹) and l-lysine productivity (q_{Lys, max.} = 0.53 g g⁻¹ h⁻¹) as compared with strain RG (μ_max. = 0.14 h⁻¹ and q_{Lys, max.} = 0.42 g g⁻¹ h⁻¹).

Conclusions

This is the first report of balancing the intracellular redox state by switching the nucleotide-cofactor specificity of GAPDH and IDH, thereby improving cell growth and l-lysine production.

Electronic supplementary material

The online version of this article (10.1186/s12934-019-1114-0) contains supplementary material, which is available to authorized users.

Review of recent developments in GC-MS approaches to metabolomics-based research

BACKGROUND

Metabolomics aims to identify the changes in endogenous metabolites of biological systems in response to intrinsic and extrinsic factors. This is accomplished through untargeted, semi-targeted and targeted based approaches. Untargeted and semi-targeted methods are typically applied in hypothesis-generating investigations (aimed at measuring as many metabolites as possible), while targeted approaches analyze a relatively smaller subset of biochemically important and relevant metabolites. Regardless of approach, it is well recognized amongst the metabolomics community that gas chromatography-mass spectrometry (GC-MS) is one of the most efficient, reproducible and well used analytical platforms for metabolomics research. This is due to the robust, reproducible and selective nature of the technique, as well as the large number of well-established libraries of both commercial and 'in house' metabolite databases available.

AIM OF REVIEW

This review provides an overview of developments in GC-MS based metabolomics applications, with a focus on sample preparation and preservation techniques. A number of chemical derivatization (in-time, in-liner, offline and microwave assisted) techniques are also discussed. Electron impact ionization and a summary of alternate mass analyzers are highlighted, along with a number of recently reported new GC columns suited for metabolomics. Lastly, multidimensional GC-MS and its application in environmental and biomedical research is presented, along with the importance of bioinformatics.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The purpose of this review is to both highlight and provide an update on GC-MS analytical techniques that are common in metabolomics studies. Specific emphasis is given to the key steps within the GC-MS workflow that those new to this field need to be aware of and the common pitfalls that should be looked out for when starting in this area.

Combined transcriptomics-metabolomics profiling of the heat shock response in the hyperthermophilic archaeon Pyrococcus furiosus

Pyrococcus furiosus is a remarkable archaeon able to grow at temperatures around 100 °C. To gain insight into how this model hyperthermophile copes with heat stress, we compared transcriptomic and metabolomic data of cells subjected to a temperature shift from 90 °C to 97 °C. In this study, we used RNA-sequencing to characterize the global variation in gene expression levels, while nuclear magnetic resonance (NMR) and targeted ion exchange liquid chromatography-mass spectrometry (LC-MS) were used to determine changes in metabolite levels. Of the 552 differentially expressed genes in response to heat shock conditions, 257 were upregulated and 295 were downregulated. In particular, there was a significant downregulation of genes for synthesis and transport of amino acids. At the metabolite level, 37 compounds were quantified. The level of di-myo-inositol phosphate, a canonical heat stress solute among marine hyperthermophiles, increased considerably (5.4-fold) at elevated temperature. Also, the levels of mannosylglycerate, UDP-N-acetylglucosamine (UDPGlcNac) and UDP-N-acetylgalactosamine were enhanced. The increase in the pool of UDPGlcNac was concurrent with an increase in the transcript levels of the respective biosynthetic genes. This work provides the first metabolomic analysis of the heat shock response of a hyperthermophile.

Quenching for Microalgal Metabolomics: A Case Study on the Unicellular Eukaryotic Green Alga Chlamydomonas reinhardtii

Capturing a valid snapshot of the metabolome requires rapid quenching of enzyme activities. This is a crucial step in order to halt the constant flux of metabolism and high turnover rate of metabolites. Quenching with cold aqueous methanol is treated as a gold standard so far, however, reliability of metabolomics data obtained is in question due to potential problems connected to leakage of intracellular metabolites. Therefore, we investigated the influence of various parameters such as quenching solvents, methanol concentration, inclusion of buffer additives, quenching time and solvent to sample ratio on intracellular metabolite leakage from Chlamydomonas reinhardtii. We measured the recovery of twelve metabolite classes using gas chromatography mass spectrometry (GC-MS) in all possible fractions and established mass balance to trace the fate of metabolites during quenching treatments. Our data demonstrate significant loss of intracellular metabolites with the use of the conventional 60% methanol, and that an increase in methanol concentration or quenching time also resulted in higher leakage. Inclusion of various buffer additives showed 70 mM HEPES (4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid) to be suitable. In summary, we recommend quenching with 60% aqueous methanol supplemented with 70 mM HEPES (−40 °C) at 1:1 sample to quenching solvent ratio, as it resulted in higher recoveries for intracellular metabolites with subsequent reduction in the metabolite leakage for all metabolite classes.

An improved method for extraction of polar and charged metabolites from cyanobacteria

A key requirement for 13C Metabolic flux analysis (13C-MFA), a widely used technique to estimate intracellular metabolic fluxes, is an efficient method for the extraction of intermediate metabolites for analysis via liquid chromatography mass spectrometry (LC/MS). The 13C isotopic labeling results in further distribution of an already sparse pool of intermediate metabolites into isotopologues, each appearing as a separate chromatographic feature. We examined some of the reported solvent systems for the extraction of polar intracellular metabolites from three strains of cyanobacteria of the genus Synechococcus, viz., Synechococcus sp. PCC 7002, Synechococcus elongatus PCC 7942, and a newly isolated Synechococcus elongatus PCC 11801 (manuscript under review). High resolution-LC/MS was used to assess the relative abundance of the extracted metabolites. The different solvent systems used for extraction led to statistically significant changes in the extraction efficiency for a large number of metabolites. While a few hundred m/z features or potential metabolites were detected with different solvent systems, the abundance of over a quarter of all metabolites varied significantly from one solvent system to another. Further, the extraction methods were evaluated for a targeted set of metabolites that are important in 13C-MFA studies of photosynthetic organisms. While for the strain PCC 7002, the reported method using methanol-chloroform-water system gave satisfactory results, a mild base in the form of NH4OH had to be used in place of water to achieve adequate levels of extraction for PCC 7942 and PCC 11801. While minor changes in extraction solvent resulted in dramatic changes in the extraction efficiency of a number of compounds, certain metabolites such as amino acids and organic acids were adequately extracted in all the solvent systems tested. Overall, we present a new improved method for extraction using a methanol-chloroform-NH4OH system. Our method improves the extraction of polar compounds such as sugar phosphates, bisphosphates, that are central to 13C-MFA studies.

Metabolomics Analysis of the Toxic Effects of the Production of Lycopene and Its Precursors

Using cells as microbial factories enables highly specific production of chemicals with many advantages over chemical syntheses. A number of exciting new applications of this approach are in the area of precision metabolic engineering, which focuses on improving the specificity of target production. In recent work, we have used precision metabolic engineering to design lycopene-producing Escherichia coli for use as a low-cost diagnostic biosensor. To increase precursor availability and thus the rate of lycopene production, we heterologously expressed the mevalonate pathway. We found that simultaneous induction of these pathways increases lycopene production, but induction of the mevalonate pathway before induction of the lycopene pathway decreases both lycopene production and growth rate. Here, we aim to characterize the metabolic changes the cells may be undergoing during expression of either or both of these heterologous pathways. After establishing an improved method for quenching E. coli for metabolomics analysis, we used two-dimensional gas chromatography coupled to mass spectrometry (GCxGC-MS) to characterize the metabolomic profile of our lycopene-producing strains in growth conditions characteristic of our biosensor application. We found that the metabolic impacts of producing low, non-toxic levels of lycopene are of much smaller magnitude than the typical metabolic changes inherent to batch growth. We then used metabolomics to study differences in metabolism caused by the time of mevalonate pathway induction and the presence of the lycopene biosynthesis genes. We found that overnight induction of the mevalonate pathway was toxic to cells, but that the cells could recover if the lycopene pathway was not also heterologously expressed. The two pathways appeared to have an antagonistic metabolic effect that was clearly reflected in the cells’ metabolic profiles. The metabolites homocysteine and homoserine exhibited particularly interesting behaviors and may be linked to the growth inhibition seen when the mevalonate pathway is induced overnight, suggesting potential future work that may be useful in engineering increased lycopene biosynthesis.

Rational modification of Corynebacterium glutamicum dihydrodipicolinate reductase to switch the nucleotide-cofactor specificity for increasing l-lysine production

l-lysine is an important amino acid in animals and humans and NADPH is a vital cofactor for maximizing the efficiency of l-lysine fermentation. Dihydrodipicolinate reductase (DHDPR), an NAD(P)H-dependent enzyme, shows a variance in nucleotide-cofactor affinity in bacteria. In this study, we rationally engineered Corynebacterium glutamicum DHDPR (CgDHDPR) to switch its nucleotide-cofactor specificity resulting in an increase in final titer (from 82.6 to 117.3 g L^-1 ), carbon yield (from 0.35 to 0.44 g [g glucose]^-1 ) and productivity (from 2.07 to 2.93 g L^-1  hr^-1 ) of l-lysine in JL-6 ΔdapB::Ec-dapB^C115G,G116C in fed-batch fermentation. To do this, we comparatively analyzed the characteristics of CgDHDPR and Escherichia coli DHDPR (EcDHDPR), indicating that hetero-expression of NADH-dependent EcDHDPR increased l-lysine production. Subsequently, we rationally modified the conserved structure of cofactor-binding motif, and results indicated that introducing the mutation K11A or R13A in CgDHDPR and introducing the mutation R16A or R39A in EcDHDPR modifies the nucleotide-cofactor affinity of DHDPR. Lastly, the effects of these mutated DHDPRs on l-lysine production were investigated. The highest increase (26.2%) in l-lysine production was observed for JL-6 ΔdapB::Ec-dapB^C115G,G116C , followed by JL-6 Cg-dapB^C37G,G38C (21.4%) and JL-6 ΔdapB::Ec-dapB^C46G,G47C (15.2%). This is the first report of a rational modification of DHDPR that enhances the l-lysine production and yield through the modulation of nucleotide-cofactor specificity.

Quantifying the cellular NAD+ metabolome using a tandem liquid chromatography mass spectrometry approach

INTRODUCTION

Nicotinamide adenine dinucleotide (NAD⁺) is an essential pyridine nucleotide that serves as a key hydride transfer coenzyme for several oxidoreductases. It is also the substrate for intracellular secondary messenger signalling by CD38 glycohydrolases, DNA repair by poly(adenosine diphosphate ribose) polymerase, and epigenetic regulation of gene expression by a class of histone deacetylase enzymes known as sirtuins. The measurement of NAD⁺ and its related metabolites (hereafter, the NAD⁺ metabolome) represents an important indicator of cellular function.

OBJECTIVES

A study was performed to develop a sensitive, selective, robust, reproducible, and rapid method for the concurrent quantitative determination of intracellular levels of the NAD⁺ metabolome in glial and oocyte cell extracts using liquid chromatography coupled to mass spectrometry (LC/MS/MS).

METHODS

The metabolites were separated on a versatile amino column using a dual HILIC-RP gradient with heated electrospray (HESI) tandem mass spectrometry detection in mixed polarity multiple reaction monitoring mode.

RESULTS

Quantification of 17 metabolites in the NAD⁺ metabolome in U251 human astroglioma cells could be achieved. Changes in NAD⁺ metabolism in U251 cell line, and murine oocytes under different culture conditions were also investigated.

CONCLUSION

This method can be used as a sensitive profiling tool, tailoring chromatography for metabolites that express significant pathophysiological changes in several disease conditions and is indispensable for targeted analysis.

Evaluation of sample extracting methods of FCSM by Lactobacillus acidophilus based on a UPLC-Q-TOF-MS global metabolomics analysis

The study of metabolomics requires extracting as many metabolites as possible from a biological sample. This study aimed to determine the optimal method for the extraction of metabolites from solid-state fermented cottonseed meal (FCSM). The UPLC-Q-TOF-MS global metabolomics technology was used to detect the metabolites in FCSM, and the extraction quantity and extraction efficiency of seven different extraction methods, specifically the WA, 50MeOH, 50MeOHB, 50MeCNB, 80MeOHB, 80MeOH and AMF methods were evaluated. The results showed that the number of VIP metabolites extracted by AMF method are 196 and 184 in ESI+ and ESI− mode respectively, it is the largest number of all exacted methods; and the AMF methods also provided a higher extraction efficiency compared with the other methods, especially in indoleacrylic acid, dl-tryptophan and epicatechin (p < 0.01). As a result, AMF/−4 °C method was identified as the best method for the extraction of metabolites from FCSM by Lactobacillus acidophilus. Our study establishes a technical basis for future metabolomics research of fermented feed.

Analysis of Intracellular Metabolites from Microorganisms: Quenching and Extraction Protocols

Sample preparation is one of the most important steps in metabolome analysis. The challenges of determining microbial metabolome have been well discussed within the research community and many improvements have already been achieved in last decade. The analysis of intracellular metabolites is particularly challenging. Environmental perturbations may considerably affect microbial metabolism, which results in intracellular metabolites being rapidly degraded or metabolized by enzymatic reactions. Therefore, quenching or the complete stop of cell metabolism is a pre-requisite for accurate intracellular metabolite analysis. After quenching, metabolites need to be extracted from the intracellular compartment. The choice of the most suitable metabolite extraction method/s is another crucial step. The literature indicates that specific classes of metabolites are better extracted by different extraction protocols. In this review, we discuss the technical aspects and advancements of quenching and extraction of intracellular metabolite analysis from microbial cells.

Quantifying the Metabolome of Pseudomonas taiwanensis VLB120: Evaluation of Hot and Cold Combined Quenching/Extraction Approaches

Absolute quantification of free intracellular metabolites is a valuable tool in both pathway discovery and metabolic engineering. In this study, we conducted a comprehensive examination of different hot and cold combined quenching/extraction approaches to extract and quantify intracellular metabolites of Pseudomonas taiwanensis (P. taiwanensis) VLB120 to provide a useful reference data set of absolute intracellular metabolite concentrations. The suitability of commonly used metabolomics tools including a pressure driven fast filtration system followed by combined quenching/extraction techniques (such as cold methanol/acetonitrile/water, hot water, and boiling ethanol/water, as well as cold ethanol/water) were tested and evaluated for P. taiwanensis VLB120 metabolome analysis. In total 94 out of 107 detected intracellular metabolites were quantified using an isotope-ratio-based approach. The quantified metabolites include amino acids, nucleotides, central carbon metabolism intermediates, redox cofactors, and others. The acquired data demonstrate that the pressure driven fast filtration approach followed by boiling ethanol quenching/extraction is the most adequate technique for P. taiwanensis VLB120 metabolome analysis based on quenching efficiency, extraction yields of metabolites, and experimental reproducibility.

Quality assurance procedures for mass spectrometry untargeted metabolomics. a review

Untargeted metabolomics, as a global approach, has already proven its great potential and capabilities for the investigation of health and disease, as well as the wide applicability for other research areas. Although great progress has been made on the feasibility of metabolomics experiments, there are still some challenges that should be faced and that includes all sources of fluctuations and bias affecting every step involved in multiplatform untargeted metabolomics studies. The identification and reduction of the main sources of unwanted variation regarding the pre-analytical, analytical and post-analytical phase of metabolomics experiments is essential to ensure high data quality. Nowadays, there is still a lack of information regarding harmonized guidelines for quality assurance as those available for targeted analysis. In this review, sources of variations to be considered and minimized along with methodologies and strategies for monitoring and improvement the quality of the results are discussed. The given information is based on evidences from different groups among our own experiences and recommendations for each stage of the metabolomics workflow. The comprehensive overview with tools presented here might serve other researchers interested in monitoring, controlling and improving the reliability of their findings by implementation of good experimental quality practices in the untargeted metabolomics study.

Influence of washing and quenching in profiling the metabolome of adherent mammalian cells: a case study with the metastatic breast cancer cell line MDA-MB-231

Metabolome characterisation is a powerful tool in oncology. To obtain a valid description of the intracellular metabolome, two of the preparatory steps are crucial, namely washing and quenching. Washing must effectively remove the extracellular media components and quenching should stop the metabolic activities within the cell, without altering the membrane integrity of the cell. Therefore, it is important to evaluate the efficiency of the washing and quenching solvents. In this study, we employed two previously optimised protocols for simultaneous quenching and extraction, and investigated the effects of a number of washing steps/solvents and quenching solvent additives, on metabolite leakage from the adherent metastatic breast cancer cell line MDA-MB-231. We explored five washing protocols and five quenching protocols (including a control for each), and assessed for effectiveness by detecting ATP in the medium and cell morphology changes through scanning electron microscopy (SEM) analyses. Furthermore, we studied the overall recovery of eleven different metabolite classes using the GC-MS technique and compared the results with those obtained from the ATP assay and SEM analysis. Our data demonstrate that a single washing step with PBS and quenching with 60% methanol supplemented with 70 mM HEPES (-50 °C) results in minimum leakage of intracellular metabolites. Little or no interference of PBS (used in washing) and methanol/HEPES (used in quenching) on the subsequent GC-MS analysis step was noted. Together, these findings provide for the first time a systematic study into the washing and quenching steps of the metabolomics workflow for studying adherent mammalian cells, which we believe will improve reliability in the application of metabolomics technology to study adherent mammalian cell metabolism.

Metabolomic Analysis of Campylobacter jejuni by Direct-Injection Electrospray Ionization Mass Spectrometry

Direct-injection mass spectrometry (DIMS) is a means of rapidly obtaining metabolomic phenotype data in both prokaryotes and eukaryotes. Given our generally poor understanding of Campylobacter metabolism, the high-throughput and relatively simple sample preparation of DIMS has made this an attractive technique for metabolism-related studies and hypothesis generation, especially when attempting to analyze metabolic mutants with no clear phenotype. Here we describe a metabolomic fingerprinting approach with sampling and extraction methodologies optimized for direct-injection electrospray ionization mass spectrometry (ESI-MS), which we have used as a means of comparing wild-type and isogenic mutant strains of C. jejuni with various metabolic blocks.

The degradation of nucleotide triphosphates extracted under boiling ethanol conditions is prevented by the yeast cellular matrix

INTRODUCTION

Boiling ethanol extraction is a frequently used method for metabolomics studies of biological samples. However, the stability of several central carbon metabolites, including nucleotide triphosphates, and the influence of the cellular matrix on their degradation have not been addressed.

OBJECTIVES

To study how a complex cellular matrix extracted from yeast (Saccharomyces cerevisiae) may affect the degradation profiles of nucleotide triphosphates extracted under boiling ethanol conditions.

METHODS

We present a double-labelling LC-MS approach with a ¹³C-labeled yeast cellular extract as complex surrogate matrix, and ¹³C¹⁵N-labeled nucleotides as internal standards, to study the effect of the yeast matrix on the degradation of nucleotide triphosphates.

RESULTS

While nucleotide triphosphates were degraded to the corresponding diphosphates in pure solutions, degradation was prevented in the presence of the yeast matrix under typical boiling ethanol extraction conditions.

CONCLUSIONS

Extraction of biological samples under boiling ethanol extraction conditions that rapidly inactivate enzyme activity are suitable for labile central energy metabolites such as nucleotide triphosphates due to the stabilizing effect of the yeast matrix. The basis of this phenomenon requires further study.

Towards quantitative mass spectrometry-based metabolomics in microbial and mammalian systems

Metabolome analyses are a suite of analytical approaches that enable us to capture changes in the metabolome (small molecular weight components, typically less than 1500 Da) in biological systems. Mass spectrometry (MS) has been widely used for this purpose. The key challenge here is to be able to capture changes in a reproducible and reliant manner that is representative of the events that take place in vivo Typically, the analysis is carried out in vitro, by isolating the system and extracting the metabolome. MS-based approaches enable us to capture metabolomic changes with high sensitivity and resolution. When developing the technique for different biological systems, there are similarities in challenges and differences that are specific to the system under investigation. Here, we review some of the challenges in capturing quantitative changes in the metabolome with MS based approaches, primarily in microbial and mammalian systems.This article is part of the themed issue 'Quantitative mass spectrometry'.

Sample preparation procedures utilized in microbial metabolomics: An overview

Bacteria are remarkably diverse in terms of their size, structure and biochemical properties. Due to this fact, it is hard to develop a universal method for handling bacteria cultures during metabolomic analysis. The choice of suitable processing methods constitutes a key element in any analysis, because only appropriate selection of procedures may provide accurate results, leading to reliable conclusions. Because of that, every analytical experiment concerning bacteria requires individually and very carefully planned research methodology. Although every study varies in terms of sample preparation, there are few general steps to follow while planning experiment, like sampling, separation of cells from growth medium, stopping their metabolism and extraction. As a result of extraction, all intracellular metabolites should be washed out from cell environment. What is more, extraction method utilized cannot cause any chemical decomposition or degradation of the metabolome. Furthermore, chosen extraction method should correlate with analytical technique, so it will not disturb or prolong following sample preparation steps. For those reasons, we observe a need to summarize sample preparation procedures currently utilized in microbial metabolomic studies. In the presented overview, papers concerning analysis of extra- and intracellular metabolites, published over the last decade, have been discussed. Presented work gives some basic guidelines that might be useful while planning experiments in microbial metabolomics.