Metabolite Measurement: Pitfalls to Avoid and Practices to Follow.

Metabolites are the small biological molecules involved in energy conversion and biosynthesis. Studying metabolism is inherently challenging due to metabolites' reactivity, structural diversity, and broad concentration range. Herein, we review the common pitfalls encountered in metabolomics and provide concrete guidelines for obtaining accurate metabolite measurements, focusing on water-soluble primary metabolites. We show how seemingly straightforward sample preparation methods can introduce systematic errors (e.g., owing to interconversion among metabolites) and how proper selection of quenching solvent (e.g., acidic acetonitrile:methanol:water) can mitigate such problems. We discuss the specific strengths, pitfalls, and best practices for each common analytical platform: liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS), nuclear magnetic resonance (NMR), and enzyme assays. Together this information provides a pragmatic knowledge base for carrying out biologically informative metabolite measurements.

Development of metabolome extraction strategy for metabolite profiling of skin tissue.

INTRODUCTION: Changes in skin phenotypic characteristics are based on skin tissue. The study of the metabolic changes in skin tissue can help understand the causes of skin diseases and identify effective therapeutic interventions. OBJECTIVES: We aimed to establish and optimize a non-targeted skin metabolome extraction system for skin tissue metabolomics with high metabolite coverage, recovery, and reproducibility using gas chromatography/mass spectrometry. METHODS: The metabolites in skin tissues were extracted using eleven different extraction systems, which were designed using reagents with different polarities based on sequential solid-liquid extraction employing a two-step strategy and analyzed using gas chromatograph/mass spectrometry. The extraction efficiency of diverse solvents was evaluated by coefficient of variation (CV), multivariate analysis, metabolites coverage, and relative peak area analysis. RESULTS: We identified 119 metabolites and the metabolite profiles differed significantly between the eleven extraction systems. Metabolites with high abundances in the organic extraction systems, followed by aqueous extraction, were involved in the biosynthesis of unsaturated fatty acids, while metabolites with high abundances in the aqueous extraction systems, followed by organic extraction, were involved in amino sugar and nucleotide sugar metabolism, and glycerolipid metabolism. MeOH/chloroform-H2O and MeOH/H2O-chloroform were the extraction systems that yielded the highest number of metabolites, while MeOH/acetonitrile (ACN)-H2O and ACN/H2O-IPA exhibited superior metabolite recoveries. CONCLUSION: Our results demonstrated that our research facilitates the selection of an appropriate metabolite extraction approach based on the experimental purpose for the metabolomics study of skin tissue.

Sample Preparation in Microbial Metabolomics: Advances and Challenges.

Microbial metabolomics has gained significant interest as it reflects the physiological state of microorganisms. Due to the great variability of biological organisms, in terms of physicochemical characteristics and variable range of concentration of metabolites, the choice of sample preparation methods is a crucial step in the metabolomics workflow and will reflect on the quality and reliability of the results generated. The procedures applied to the preparation of microbial samples will vary according to the type of microorganism studied, the metabolomics approach (untargeted or targeted), and the analytical platform of choice. This chapter aims to provide an overview of the sample preparation workflow for microbial metabolomics, highlighting the pre-analytical factors associated with cultivation, harvesting, metabolic quenching, and extraction. Discussions focus on obtaining intracellular and extracellular metabolites. Finally, we introduced advanced sample preparation methods based on automated systems.

An improved extraction method enables the comprehensive analysis of lipids, proteins, metabolites and phytohormones from a single sample of leaf tissue under water-deficit stress.

Phytohormones play essential roles in the regulation of growth and development in plants. Plant hormone profiling is therefore essential to understand developmental processes and the adaptation of plants to biotic and/or abiotic stresses. Interestingly, commonly used hormone extraction and profiling methods do not adequately resolve other molecular entities, such as polar metabolites, lipids, starch and proteins, which would be required to comprehensively describe the continuing biological processes at a systematic level. In this article we introduce an updated version of a previously published liquid:liquid metabolite extraction protocol, which not only allows for the profiling of primary and secondary metabolites, lipids, starch and proteins, but also enables the quantitative analysis of the major plant hormone classes, including abscisic acid, auxins, cytokinins, jasmonates and salicylates, from a single sample aliquot. The optimization of the method, which uses the introduction of acidified water, enabling the complete purification of major plant hormones into the organic (methyl-tert-butyl-ether) phase, eliminated the need for solid-phase extraction for sample clean-up, and therefore reduces both sampling time and cost. As a proof-of-concept analysis, Arabidopsis thaliana plants were subjected to water-deficit stress, which were then profiled for hormonal, metabolic, lipidomic and proteomic changes. Surprisingly, we determined not only previously described molecular changes but also significant changes regarding the breakdown of specific galactolipids, followed by the substantial accumulation of unsaturated fatty-acid derivatives and diverse jasmonates in the course of adaptation to water-deficit stress.

Establishing a Metabolite Extraction Method to Study the Metabolome of Blastocystis Using NMR.

Blastocystis is an opportunistic parasite commonly found in the intestines of humans and other animals. Despite its high prevalence, knowledge regarding Blastocystis biology within and outside the host is limited. Analysis of the metabolites produced by this anaerobe could provide insights that can help map its metabolism and determine its role in both health and disease. Due to its controversial pathogenicity, these metabolites could define its deterministic role in microbiome's "health" and/or subsequently resolve Blastocystis' potential impact in gastrointestinal health. A common method for elucidating the presence of these metabolites is through 1H nuclear magnetic resonance (NMR). However, there are currently no described benchmarked methods available to extract metabolites from Blastocystis for 1H NMR analysis. Herein, several extraction solvents, lysis methods and incubation temperatures were compared for their usefulness as an extraction protocol for this protozoan. Following extraction, the samples were freeze-dried, re-solubilized and analysed with 1H NMR. The results demonstrate that carrying out the procedure at room temperature using methanol as an extraction solvent and bead bashing as a lysis technique provides a consistent, reproducible and efficient method to extract metabolites from Blastocystis for NMR.

Balancing metabolome coverage and reproducibility for untargeted NMR-based metabolic profiling in tissue samples through mixture design methods.

Untargeted metabolomics attempts to acquire a comprehensive and reproducible set of small-molecule metabolites in biological systems. However, metabolite extraction method significantly affects the quality of metabolomics data. In the present study, we calculated the number of peaks (NP) and coefficient of variation (CV) to reflect metabolome coverage and reproducibility in untargeted NMR-based metabolic profiling of tissue samples in rats under different methanol/chloroform/water (MCW) extraction conditions. Different MCW extractions expectedly generated diverse characteristics of metabolome. Moreover, the classic MCW method revealed tissue-specific differences in the NP and CV values. To obtain high-quality metabolomics data, therefore, we used mixture design methods to optimize the MCW extraction strategy by maximizing the NP value and minimizing the CV value in each tissue sample. Results show that the optimal formulations of MCW extraction were 2:2:8 (ml/mg tissue) for brain sample, 2:4:6 (ml/mg tissue) for heart sample, 1.3:2:8.7 (ml/mg tissue) for liver sample, 4:2:6 (ml/mg tissue) for kidney sample, 2:3:7 (ml/mg tissue) for muscle sample, and 2:4:6 (ml/mg tissue) for pancreas sample. Therefore, these findings demonstrate that different tissue samples need a specific optimal extraction condition for balancing metabolome coverage and reproducibility in the untargeted metabolomics study. Mixture design method is an effective tool to optimize metabolite extraction strategy for tissue samples. Graphical abstract ᅟ.

The Role of Metabolomics in the Study of Cancer Biomarkers and in the Development of Diagnostic Tools.

This chapter introduces the emerging field of metabolomics and its application in the context of cancer biomarker research. Taking advantage of modern high-throughput technologies, and enhanced computational power, metabolomics has a high potential for cancer biomarker identification and the development of diagnostic tools. This chapter describes current metabolomics technologies used in cancer research, starting with metabolomics sample preparation, elaborating on current analytical methodologies for metabolomics measurement and introducing existing software for data analysis. The last part of this chapter deals with the statistical analysis of very large metabolomics datasets and their relevance for cancer biomarker identification.

Development of an NMR microprobe procedure for high-throughput environmental metabolomics of Daphnia magna.

Nuclear magnetic resonance (NMR) is the primary platform used in high-throughput environmental metabolomics studies because its non-selectivity is well suited for non-targeted approaches. However, standard NMR probes may limit the use of NMR-based metabolomics for tiny organisms because of the sample volumes required for routine metabolic profiling. Because of this, keystone ecological species, such as the water flea Daphnia magna, are not commonly studied because of the analytical challenges associated with NMR-based approaches. Here, the use of a 1.7-mm NMR microprobe in analyzing tissue extracts from D. magna is tested. Three different extraction procedures (D2O-based buffer, Bligh and Dyer, and acetonitrile : methanol : water) were compared in terms of the yields and breadth of polar metabolites. The D2O buffer extraction yielded the most metabolites and resulted in the best reproducibility. Varying amounts of D. magna dry mass were extracted to optimize metabolite isolation from D. magna tissues. A ratio of 1-1.5-mg dry mass to 40 µl of extraction solvent provided excellent signal-to-noise and spectral resolution using (1)H NMR. The metabolite profile of a single daphnid was also investigated (approximately 0.2 mg). However, the signal-to-noise of the (1)H NMR was considerably lower, and while feasible for select applications would likely not be appropriate for high-throughput NMR-based metabolomics. Two-dimensional NMR experiments on D. magna extracts were also performed using the 1.7-mm NMR probe to confirm (1)H NMR metabolite assignments. This study provides an NMR-based analytical framework for future metabolomics studies that use D. magna in ecological and ecotoxicity studies.

Sample preparation workflow for the liquid chromatography tandem mass spectrometry based analysis of nicotinamide adenine dinucleotide phosphate cofactors in yeast.

The accurate quantification of the highly unstable intracellular cofactor nicotinamide adenine dinucleotide phosphate in its oxidized and reduced forms demands a thorough evaluation of the analytical workflow and dedicated methods reflecting their solution chemistry as well as the biological importance of their ratio. In this work, we present a workflow for the analysis of intracellular levels of oxidized and reduced nicotinamide adenine dinucleotide phosphate in the yeast Pichia pastoris, including hot aqueous extraction, chromatographic separation in reversed-phase conditions employing a 100% wettable stationary phase, and subsequent tandem mass spectrometric analysis. A thorough evaluation and optimization of the sample preparation procedure resulted in excellent biological repeatabilities (on average <10%, N = 3) without employing an internal standardization approach. As a consequence, the methodology proved to be appropriate for the relative assessment of intracellular levels of oxidized and reduced nicotinamide adenine dinucleotide phosphate in different P. pastoris strains. The ratio of reduced versus oxidized nicotinamide adenine dinucleotide phosphate was significantly higher in an engineered strain overexpressing glucose-6-phosphate dehydrogenase than in the corresponding wildtype strain. Interestingly, a difference was also observed in the nicotinamide adenine dinucleotide phosphate pool size, which was significantly higher in the wildtype than in the modified strain.

An easy, convenient cell and tissue extraction protocol for nuclear magnetic resonance metabolomics.

INTRODUCTION: As a complement to the classic metabolomics biofluid studies, the visualisation of the metabolites contained in cells or tissues could be a very powerful tool to understand how the local metabolism and biochemical pathways could be affected by external or internal stimuli or pathologies. Therefore, extraction and/or lysis is necessary to obtain samples adapted for use with the current analytical tools (liquid NMR and MS). These extraction or lysis work-ups are often the most labour-intensive and rate-limiting steps in metabolomics, as they require accuracy and repeatability as well as robustness. Many of the procedures described in the literature appear to be very time-consuming and not easily amenable to automation. OBJECTIVE: To find a fast, simplified procedure that allows release of the metabolites from cells and tissues in a way that is compatible with NMR analysis. METHODS: We assessed the use of sonication to disrupt cell membranes or tissue structures. Both a vibrating probe and an automated bath sonicator were explored. RESULTS: The application of sonication as the disruption procedure led to reproducible NMR spectral data compatible with metabolomics studies. This method requires only a small biological tissue or cell sample, and a rapid, reduced work-up was applied before analysis. The spectral patterns obtained are comparable with previous, well-described extraction protocols. CONCLUSION: The rapidity and the simplicity of this approach could represent a suitable alternative to the other protocols. Additionally, this approach could be favourable for high- throughput applications in intracellular and intratissular metabolite measurements.

Identification of Stress-Responsive Metabolites in Plants Using an Untargeted Metabolomics Approach.

Stress can affect different groups of plant metabolites and multiple signaling pathways. Untargeted metabolomics enables the collection of whole-spectrum data for the entire metabolite content present in plant tissues at that point in time. We present a thorough approach for large-scale, untargeted metabolomics of plant tissues using reverse-phase liquid chromatography connected to high-resolution mass spectrometry (LC-MS) of dilute methanolic extract. MZmine is a specialized computer software that automates the alignment and baseline modification of all derived mass peaks across all samples, resulting in precise information on the relative abundance of hundreds of metabolites reflected by thousands of mass signals. Further processing with statistic and bioinformatic techniques will provide a comprehensive perspective of the variations and connections among groups of samples.

Sustainable synergistic approach to chemolithotrophs-supported bioremediation of wastewater and flue gas.

Flue gas emissions are the waste gases produced during the combustion of fuel in industrial processes, which are released into the atmosphere. These identical processes also produce a significant amount of wastewater that is released into the environment. The current investigation aims to assess the viability of simultaneously mitigating flue gas emissions and remediating wastewater in a bubble column bioreactor utilizing bacterial consortia. A comparative study was done on different growth media prepared using wastewater. The highest biomass yield of 3.66 g L-1 was achieved with the highest removal efficiencies of 89.80, 77.30, and 80.77% for CO2, SO2, and NO, respectively. The study investigated pH, salinity, dissolved oxygen, and biochemical and chemical oxygen demand to assess their influence on the process. The nutrient balance validated the ability of bacteria to utilize compounds in flue gas and wastewater for biomass production. The Fourier Transform-Infrared Spectrometry (FT-IR) and Gas Chromatography-Mass Spectrometry (GC-MS) analyses detected commercial-use long-chain hydrocarbons, fatty alcohols, carboxylic acids, and esters in the biomass samples. The nuclear magnetic resonance (NMR) metabolomics detected the potential mechanism pathways followed by the bacteria for mitigation. The techno-economic assessment determined a feasible total capital investment of 245.74$ to operate the reactor for 288 h. The bioreactor's practicability was determined by mass transfer and thermodynamics assessment. Therefore, this study introduces a novel approach that utilizes bacteria and a bioreactor to mitigate flue gas and remediate wastewater.

Optimising Extracellular Vesicle Metabolomic Methodology for Prostate Cancer Biomarker Discovery.

Conventional diagnostic tools for prostate cancer (PCa), such as prostate-specific antigen (PSA), transrectal ultrasound (TRUS), digital rectal examination (DRE), and tissue biopsy face, limitations in individual risk stratification due to invasiveness or reliability issues. Liquid biopsy is a less invasive and more accurate alternative. Metabolomic analysis of extracellular vesicles (EVs) holds a promise for detecting non-genetic alterations and biomarkers in PCa diagnosis and risk assessment. The current research gap in PCa lies in the lack of accurate biomarkers for early diagnosis and real-time monitoring of cancer progression or metastasis. Establishing a suitable approach for observing dynamic EV metabolic alterations that often occur earlier than being detectable by other omics technologies makes metabolomics valuable for early diagnosis and monitoring of PCa. Using four distinct metabolite extraction approaches, the metabolite cargo of PC3-derived large extracellular vesicles (lEVs) was evaluated using a combination of methanol, cell shearing using microbeads, and size exclusion filtration, as well as two fractionation chemistries (pHILIC and C18 chromatography) that are also examined. The unfiltered methanol-microbeads approach (MB-UF), followed by pHILIC LC-MS/MS for EV metabolite extraction and analysis, is effective. Identified metabolites such as L-glutamic acid, pyruvic acid, lactic acid, and methylmalonic acid have important links to PCa and are discussed. Our study, for the first time, has comprehensively evaluated the extraction and separation methods with a view to downstream sample integrity across omics platforms, and it presents an optimised protocol for EV metabolomics in PCa biomarker discovery.

Metabolomic Fingerprint Assay in Zebrafish Embryos.

In order for new drugs to enter the market, extensive studies are needed to examine toxic effects. Among others, teratogenicity studies are of paramount importance. Of even higher importance is to gain knowledge on the biological responses that take place upon drug exposure, so as to have a better understanding of the molecular mechanisms that govern developmental changes. Metabolomics is the research field that studies the changes in the chemical composition of metabolites contained within cells. Conducting metabolomics studies results in valuable information. Zebrafish is a vertebrate model organism that bridges in vivo assays and in vivo studies. In this chapter, we propose a metabolomic fingerprint assay for the study of metabolic changes in zebrafish embryos upon exposure to various drugs. The metabolome of zebrafish is extracted, and the 1H-NMR spectrum is recorded. Using open-access metabolomic databases, a list of tentative metabolites is retrieved. The presence of the tentative metabolites is further confirmed by UHPLC-HRMS. Ultimately, after a metabolic pathway analysis, the metabolic network is revealed and useful conclusions can be drawn.

Critical Factors in Sample Collection and Preparation for Clinical Metabolomics of Underexplored Biological Specimens.

This review article compiles critical pre-analytical factors for sample collection and extraction of eight uncommon or underexplored biological specimens (human breast milk, ocular fluids, sebum, seminal plasma, sweat, hair, saliva, and cerebrospinal fluid) under the perspective of clinical metabolomics. These samples are interesting for metabolomics studies as they reflect the status of living organisms and can be applied for diagnostic purposes and biomarker discovery. Pre-collection and collection procedures are critical, requiring protocols to be standardized to avoid contamination and bias. Such procedures must consider cleaning the collection area, sample stimulation, diet, and food and drug intake, among other factors that impact the lack of homogeneity of the sample group. Precipitation of proteins and removal of salts and cell debris are the most used sample preparation procedures. This review intends to provide a global view of the practical aspects that most impact results, serving as a starting point for the designing of metabolomic experiments.

An optimized method for extraction and quantification of nucleotides and nucleotide sugars from mammalian cells.

Glycosylation is a critical attribute of therapeutic proteins given its impact on the clinical safety and efficacy of these molecules. The biochemical process of glycosylation is inextricably dependent on metabolism and ensuing availability of nucleotides and nucleotide sugars (NSs) during cell culture. Herein, we present a comprehensive methodology to extract and quantify these metabolites from cultured cells. To establish the full protocol, two methods for the extraction of these compounds were evaluated for efficiency, and the requirement for quenching and washing the sample was assessed. A chromatographic method based on anion exchange has been optimized to separate and quantify eight nucleotides and nine NSs in less than 30 min. Degradation of nucleotides and NSs under extraction conditions was evaluated to aid in selection of the most efficient extraction protocol. We conclude that the optimized chromatographic method is quick, robust, and sensitive for quantifying nucleotides and NSs. Furthermore, our results show that samples taken from cell culture should be treated with 50% v/v acetonitrile and do not require quenching or washing for reliable extraction of nucleotides and NSs. This comprehensive protocol should prove useful in determining the impact of nucleotide and NS metabolism on protein glycosylation.

Metabolomic Profiling to Understand Chondrocyte Metabolism.

Metabolism has long been recognized as a critical physiological process necessary to maintain homeostasis in all types of cells including the chondrocytes of articular cartilage. Alterations in metabolism in disease and metabolic adaptation to physiological stimuli such as mechanical loading are increasingly recognized as important for understanding musculoskeletal systems such as synovial joints. Metabolomics is an emerging technique that allows quantitative measurement of thousands of small molecule metabolites that serve as both products and reactants to myriad reactions of cellular biochemistry. This protocol describes procedures to perform metabolomic profiling on chondrocytes and other tissues and fluids within the synovial joint.

A liquid chromatography-mass spectrometry-based metabolomics strategy to explore plant metabolic diversity.

Plants are expert chemists producing millions of metabolites, only a fraction of which are known to date. Plant metabolomics explores the rationale for highly diverse metabolites evolved and synthesized by plants. Over two-thirds of modern medicines are somehow inspired and/or derived from plants, making the identification of phytochemicals a means of discovering new medicines to challenge existing and emerging diseases. This chapter introduces our established liquid chromatography-tandem mass spectrometry-based untargeted metabolomics approach centered around discovering specialized metabolites (so-called secondary metabolites) across broad lineages of nonmodel plant species. Detecting hundreds to thousands of metabolite peaks, including assigning chemical identity, makes metabolomics data generation and analysis a very complex process. Various mass spectrometry techniques are currently being developed to approach the comprehensive metabolome. Among them, untargeted metabolomics can provide new biological insights by simultaneously and unbiasedly measuring and analyzing all detected metabolites. We have provided a hands-on modular account for untargeted plant metabolomics, from preparing plant biological samples to data analysis and processing using ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry. The methods described here offer a foundation and expert opinion on plant metabolome analysis.

Ex vivo metabolomics-A hypothesis-free approach to identify native substrate(s) and product(s) of orphan enzymes.

Over the past decade, the number of fully sequenced genomes has increased at an awe-inspiring pace. Similarly, the quality and scope of tools for the prediction of both protein structure and function has seen vast improvements. However, to pinpoint the exact function of a protein, for instance the exact reaction catalyzed by an enzyme, experimental evidence is crucial. At the same time, this step is the main bottleneck when generating a conclusive model for the function of an enzyme and to interpret its function in a physiological context. Hence, a comprehensive experimental strategy for functional annotation of enzymes that is as efficient as possible is required. Ex vivo metabolomics is a powerful non-targeted approach that overcomes several of the challenges inherent to in vitro characterization of enzymes with unknown functions. By incubating the recombinant enzyme of interest in a quasi-native metabolite extract from its tissue of origin under specific environmental and developmental conditions, the complete native substrate range can be tested in a single assay. This unlocks compounds that are commercially unavailable or otherwise difficult to procure. Coupled with non-targeted metabolomics analysis, ex vivo has the capability to test for and identify even unexpected substrates and assign the respective products of the enzymatic reaction.

Optimized Fast Filtration-Based Sampling and Extraction Enables Precise and Absolute Quantification of the Escherichia coli Central Carbon Metabolome.

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