Improved stability of TMS derivatives for the robust quantification of plant polar metabolites by gas chromatography-mass spectrometry

Evaluation of normalization strategies for GC-based metabolomics

INTRODUCTION

For many samples studied by GC-based metabolomics applications, extensive sample preparation involving extraction followed by a two-step derivatization procedure of methoximation and trimethylsilylation (TMS) is typically required to expand the metabolome coverage. Performing normalization is critical to correct for variations present in samples and any biases added during the sample preparation steps and analytical runs. Addressing the totality of variations with an adequate normalization method increases the reliability of the downstream data analysis and interpretation of the results.

OBJECTIVES

Normalizing to sample mass is one of the most commonly employed strategies, while the total peak area (TPA) as a normalization factor is also frequently used as a post-acquisition technique. Here, we present a new normalization approach, total derivatized peak area (TDPA), where data are normalized to the intensity of all derivatized compounds. TDPA relies on the benefits of silylation as a universal derivatization method for GC-based metabolomics studies.

METHODS

Two sample classes consisting of systematically incremented sample mass were simulated, with the only difference between the groups being the added amino acid concentrations. The samples were TMS derivatized and analyzed using comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC × GC-TOFMS). The performance of five normalization strategies (no normalization, normalized to sample mass, TPA, total useful peak area (TUPA), and TDPA) were evaluated on the acquired data.

RESULTS

Of the five normalization techniques compared, TUPA and TDPA were the most effective. On PCA score space, they offered a clear separation between the two classes.

CONCLUSION

TUPA and TDPA carry different strengths: TUPA requires peak alignment across all samples, which depends upon the completion of the study, while TDPA is free from the requirement of alignment. The findings of the study would enhance the convenient and effective use of data normalization strategies and contribute to overcoming the data normalization challenges that currently exist in the metabolomics community.

Seasonal Variation in Cell Wall Composition and Carbohydrate Metabolism in the Seagrass Posidonia oceanica Growing at Different Depths

Posidonia oceanica is a common seagrass in the Mediterranean Sea that is able to sequester large amounts of carbon. The carbon assimilated during photosynthesis can be partitioned into non-structural sugars and cell-wall polymers. In this study, we investigated the distribution of carbon in starch, soluble carbohydrates and cell-wall polymers in leaves and rhizomes of P. oceanica. Analyses were performed during summer and winter in meadows located south of the Frioul archipelago near Marseille, France. The leaves and rhizomes were isolated from plants collected in shallow (2 m) and deep water (26 m). Our results showed that P. oceanica stores more carbon as starch, sucrose and cellulose in summer and that this is more pronounced in rhizomes from deep-water plants. In winter, the reduction in photoassimilates was correlated with a lower cellulose content, compensated with a greater lignin content, except in rhizomes from deep-water plants. The syringyl-to-guaiacyl (S/G) ratio in the lignin was higher in leaves than in rhizomes and decreased in rhizomes in winter, indicating a change in the distribution or structure of the lignin. These combined data show that deep-water plants store more carbon during summer, while in winter the shallow- and deep-water plants displayed a different cell wall composition reflecting their environment.

Matrix Effects in GC–MS Profiling of Common Metabolites after Trimethylsilyl Derivatization

Metabolite profiling using gas chromatography coupled to mass spectrometry (GC–MS) is one of the most frequently applied and standardized methods in research projects using metabolomics to analyze complex samples. However, more than 20 years after the introduction of non-targeted approaches using GC–MS, there are still unsolved challenges to accurate quantification in such investigations. One particularly difficult aspect in this respect is the occurrence of sample-dependent matrix effects. In this project, we used model compound mixtures of different compositions to simplify the study of the complex interactions between common constituents of biological samples in more detail and subjected those to a frequently applied derivatization protocol for GC–MS analysis, namely trimethylsilylation. We found matrix effects as signal suppression and enhancement of carbohydrates and organic acids not to exceed a factor of ~2, while amino acids can be more affected. Our results suggest that the main reason for our observations may be an incomplete transfer of carbohydrate and organic acid derivatives during the injection process and compound interaction at the start of the separation process. The observed effects were reduced at higher target compound concentrations and by using a more suitable injection-liner geometry.

Stable-Isotope Dilution GC-MS Measurement of Metformin in Human Serum and Urine after Derivatization with Pentafluoropropionic Anhydride and Its Application in Becker Muscular Dystrophy Patients Administered with Metformin, l-Citrulline, or Their Combination

Metformin (N,N-dimethylguanylguanidine) is one of the most prescribed drugs with pleiotropic, exerted in part by not fully elucidated mechanisms of action. We developed and validated a gas chromatography-mass spectrometry (GC-MS) method for the quantitative analysis of metformin (metformin-d₀) in 10-µL aliquots of human serum and urine using N,N-[dimethylo-²H₆]guanylguanidine (metformin-d₆) as the internal standard. The method involves evaporation of the samples to dryness, derivatization with pentafluoropropionic (PFP) anhydride in ethyl acetate (30 min, 65 °C), and extraction into toluene. The negative-ion chemical ionization GC-MS spectra of the PFP derivatives contain a single intense ion with mass-to-charge (m/z) ratios of m/z 383 for metformin-d₀ and m/z 389 for metformin-d₆. Our results suggest that all amine/imine groups of metformin-d₀ and metformin-d₆ are converted to their N,N,N-tripentafluoropropionyl derivatives, which cyclize to form a symmetric triazine derivative, of which the non-ring amine group is amidated. Quantification was performed by selected-ion monitoring (SIM) of m/z 383 and m/z 389. Upon validation, the method was applied to determine serum and urine metformin concentrations in 19 patients with Becker muscular dystrophy (BMD). Serum and urine samples were collected at baseline (Visit I), after six weeks of supplementation (Visit II) with metformin (3 × 500 mg/d; metformin group; n = 10) or l-citrulline (3 × 1500 mg/d; citrulline group; n = 9) followed by a six-week supplementation with 3 × 500 mg/d of metformin plus 3 × 1500 mg/d l-citrulline. At Visit I, the metformin concentration in the serum and urine was very low in both groups. The metformin concentrations in the serum and urine of the patients who first took metformin (MET group) were higher at Visit II and Visit III. The metformin concentration in the serum and urine samples of the patients who first took l-citrulline (CITR group) were higher at Visit III. The serum and urine concentrations of metformin were insignificantly lower in the CITR group at Visit III. The mean fractional excretion (FE) rate of metformin was 307% (Visit II) and 322% (Visit III) in the MET group, and 290% in the CITR group (Visit III). This observation suggests the accumulation of metformin in the kidney and its secretion in the urine. The GC-MS is suitable to measure reliably circulating and excretory metformin in clinical settings.

Calibration-Curve-Locking Database for Semi-Quantitative Metabolomics by Gas Chromatography/Mass Spectrometry

Calibration-Curve-Locking Databases (CCLDs) have been constructed for automatic compound search and semi-quantitative screening by gas chromatography/mass spectrometry (GC/MS) in several fields. CCLD felicitates the semi-quantification of target compounds without calibration curve preparation because it contains the retention time (RT), calibration curves, and electron ionization (EI) mass spectra, which are obtained under stable apparatus conditions. Despite its usefulness, there is no CCLD for metabolomics. Herein, we developed a novel CCLD and semi-quantification framework for GC/MS-based metabolomics. All analytes were subjected to GC/MS after derivatization under stable apparatus conditions using (1) target tuning, (2) RT locking technique, and (3) automatic derivatization and injection by a robotic platform. The RTs and EI mass spectra were obtained from an existing authorized database. A quantifier ion and one or two qualifier ions were selected for each target metabolite. The calibration curves were obtained as plots of the peak area ratio of the target compounds to an internal standard versus the target compound concentration. These data were registered in a database as a novel CCLD. We examined the applicability of CCLD for analyzing human plasma, resulting in time-saving and labor-saving semi-qualitative screening without the need for standard substances.

Two-Step Derivatization of Amino Acids for Stable-Isotope Dilution GC-MS Analysis: Long-Term Stability of Methyl Ester-Pentafluoropropionic Derivatives in Toluene Extracts

Analysis of amino acids by gas chromatography-mass spectrometry (GC–MS) requires at least one derivatization step to enable solubility in GC–MS-compatible water-immiscible organic solvents such as toluene, to make them volatile to introduce into the gas chromatograph and thermally stable enough for separation in the GC column and introduction into the ion-source, and finally to increase their ionization by increasing their electronegativity using F-rich reagents. In this work we investigated the long-term stability of the methyl esters pentafluoropropionic (Me-PFP) derivatives of 21 urinary amino acids prepared by a two-step derivatization procedure and extraction by toluene. In situ prepared trideuteromethyl ester pentafluoropropionic derivatives were used as internal standards. GC–MS analysis (injection of 1 µL aliquots and quantification by selected-ion monitoring of specific mass fragments) was performed on days 1, 2, 8, and 15. Measured peak areas and calculated peak area ratios were used to evaluate the stability of the derivatives of endogenous amino acids and their internal standards, as well as the precision and the accuracy of the method. All analyses were performed under routine conditions. Me-PFP derivatives of endogenous amino acids and their stable-isotope labelled analogs were stable in toluene for 14 days. The peak area values of the derivatives of most amino acids and their internal standards were slightly higher on days 8 and 15 compared to days 1 and 2, yet the peak area ratio values of endogenous amino acids to their internal standards did not change. Our study indicates that Me-PFP derivatives of amino acids from human urine samples can easily be prepared, are stable at least for 14 days in the extraction solvent toluene, and allow for precise and accurate quantitative measurements by GC–MS using in situ prepared deuterium-labelled methyl ester as internal standard.

Development and assessment of GC/MS and HPAEC/PAD methodologies for the quantification of α-galacto-oligosaccharides (GOS) in dry beans (Phaseolus vulgaris)

The quantification of α-Galacto-oligosaccharides (GOS) in beans has been increasingly approached through different methodologies. However, reported GOS contents revealed up to 8-times disparity, which cannot be only attributed to the bean cultivar and underlines the need of using validated analytical methodologies. This study aimed to optimize and validate the extraction of the most abundant GOS found in beans, namely raffinose, stachyose and verbascose, and comparatively assess their determination by High-Performance Anion Exchange Chromatography/Pulsed Amperometric Detector (HPAEC/PAD) and Gas Chromatography/Mass Spectrometry (GC/MS). Hot sonication followed by shaking with 70% ethanol resulted in excellent GOS extraction efficiencies (92.54-107.94%). GC/MS determination was more reliable than HPAEC/PAD, with limits of quantification of 4.48-224.31 mg/kg and intra/inter-day repeatabilities <10%. The analysis of six bean varieties proved the feasibility of the GC/MS methodology, displaying total GOS contents from 1453.07 ± 169.31 to 2814.34 ± 95.28 mg/100 g. Stachyose was significantly (p < 0.05) the main GOS in all samples.

Method development and validation for the quantification of organic acids in microbial samples using anionic exchange solid-phase extraction and gas chromatography-mass spectrometry

Organic acids play a key role in central metabolic functions of organisms, are crucial for understanding regulatory processes and are ubiquitous inside the cell. Therefore, quantification of these compounds provides a valuable approach for studying dynamics of metabolic processes, in particular when the organism faces changing environmental conditions. However, the extraction and analysis of organic acids can be challenging and validated methods available in this field are limited. In this study, we developed a method for the extraction and quantification of organic acids from microbial samples based on solid-phase extraction on a strong anionic exchange cartridge and gas chromatographic-mass spectrometric analysis. Full method validation was conducted to determine quality parameters of the new method. Recoveries for 12 of the 15 aromatic and aliphatic acids were between 100 and 111% and detection limits between 3 and 272 ng/mL. The ranges for the regression coefficients and process standard deviations for these compound classes were 0.9874–0.9994 and 0.04–0.69 μg/mL, respectively. Limitations were encountered when targeting aliphatic acids with hydroxy, oxo or enol ester functions. Finally, we demonstrated the applicability of the method on cell extracts of the bacterium Escherichia coli and the dinoflagellate Prorocentrum minimum.

Metabolomics Reveals Distinct Metabolites between Lonicera japonica and Lonicera macranthoides Based on GC-MS

Lonicera japonica Thunb. (LJ) and Lonicera macranthoides Hand. -Mazz. (LM) have been widely used in Chinese medicine for thousands of years. Although the morphological characteristics of LJ and LM are quite similar, there are significant distinctions of medicinal ingredients (mainly the secondary metabolites) and clinical indications between them. However, the in-depth differences of primary metabolites have not thoroughly been studied yet. Therefore, gas chromatography-mass spectrometry- (GC-MS-) based metabolomics method combined with chemometric methods were performed to analyze the distinction in this study. The results showed that LJ and LM were obviously classified into two groups. 10 metabolites were obtained as biomarkers on account of their p values, pcorr values, and differing variable importance in projection (VIP) values. Metabolic pathway analysis showed that the galactose metabolism and starch and sucrose metabolism gathered as potential pathways caused these extraordinary differences of primary metabolites between LJ and LM. Further, we found that the differences of main medicinal ingredients between LJ and LM could be interpreted from these metabolites according to the analysis of mainly related pathways. The metabolites involved in the starch and sucrose metabolism presented upregulated in LJ, while almost all metabolites in the galactose metabolism, the TCA cycle, and the phenolic acid part of phenylpropanoid metabolism were downregulated in LJ. Therefore, the energy stored in the starch and sucrose metabolism may be saved to produce flavonoid, which could be the reason that the level of flavonoid of phenylpropanoid metabolism is higher in LJ compared to LM. Consequently, this study presented an effective tool for quality evaluation of LJ and LM and laid a foundation for further studies of the metabolic mechanisms and high-quality manufacturing of them.

Accurate and sensitive quantitation of glucose and glucose phosphates derived from storage carbohydrates by mass spectrometry

The addition of phosphate groups into glycogen modulates its branching pattern and solubility which all impact its accessibility to glycogen interacting enzymes. As glycogen architecture modulates its metabolism, it is essential to accurately evaluate and quantify its phosphate content. Simultaneous direct quantitation of glucose and its phosphate esters requires an assay with high sensitivity and a robust dynamic range. Herein, we describe a highly-sensitive method for the accurate detection of both glycogen-derived glucose and glucose-phosphate esters utilizing gas-chromatography coupled mass spectrometry. Using this method, we observed higher glycogen levels in the liver compared to skeletal muscle, but skeletal muscle contained many more phosphate esters. Importantly, this method can detect femtomole levels of glucose and glucose phosphate esters within an extremely robust dynamic range with excellent accuracy and reproducibility. The method can also be easily adapted for the quantification of plant starch, amylopectin or other biopolymers.

Improved workflow for mass spectrometry-based metabolomics analysis of the heart

MS-based metabolomics methods are powerful techniques to map the complex and interconnected metabolic pathways of the heart; however, normalization of metabolite abundance to sample input in heart tissues remains a technical challenge. Herein, we describe an improved GC-MS-based metabolomics workflow that uses insoluble protein-derived glutamate for the normalization of metabolites within each sample and includes normalization to protein-derived amino acids to reduce biological variation and detect small metabolic changes. Moreover, glycogen is measured within the metabolomics workflow. We applied this workflow to study heart metabolism by first comparing two different methods of heart removal: the Langendorff heart method (reverse aortic perfusion) and in situ freezing of mouse heart with a modified tissue freeze-clamp approach. We then used the in situ freezing method to study the effects of acute β-adrenergic receptor stimulation (through isoproterenol (ISO) treatment) on heart metabolism. Using our workflow and within minutes, ISO reduced the levels of metabolites involved in glycogen metabolism, glycolysis, and the Krebs cycle, but the levels of pentose phosphate pathway metabolites and of many free amino acids remained unchanged. This observation was coupled to a 6-fold increase in phosphorylated adenosine nucleotide abundance. These results support the notion that ISO acutely accelerates oxidative metabolism of glucose to meet the ATP demand required to support increased heart rate and cardiac output. In summary, our MS-based metabolomics workflow enables improved quantification of cardiac metabolites and may also be compatible with other methods such as LC or capillary electrophoresis.

Myricetin Ameliorates Ethanol-Induced Lipid Accumulation in Liver Cells by Reducing Fatty Acid Biosynthesis

SCOPE

Alcoholic liver disease is a serious threat to human health. The development of drug candidates from complementary and alternative medicines is an attractive approach. Myricetin can be found in fruit, vegetables, and herbs. This study investigates the protective effect of myricetin on ethanol-induced injury in mouse liver cells.

METHODS AND RESULTS

Oil-red O staining, assays of oxidative stress and measurements of inflammatory markers in mouse AML12 liver cells collectively demonstrate that myricetin elicits a curative effect on ethanol-induced injury. Next, the role of myricetin in the metabolic regulation of ethanol pathology in liver cells is assessed by gas chromatography coupled with mass spectrometry. Myricetin inhibits ethanol-stimulated fatty acid biosynthesis. Additionally, dodecanoic acid may be proposed as a potential biomarker related to ethanol pathology or myricetin therapy. It is also observed that myricetin enhances ethanol-induced inhibition of the mitochondrial electron transport chain. Moreover, fumaric acid is found to be a candidate biomarker related to ethanol toxicity or myricetin therapy. Quantitative reverse-transcription-PCR shows that ethanol-induced fatty acid synthase and sterol regulatory element-binding protein-1c mRNA levels are alleviated by myricetin. Finally, myricetin increases ethanol-induced inhibition of phosphorylation of AMP-activated protein kinase.

CONCLUSION

These results elucidate the pharmacological mechanism of myricetin on ethanol-induced lipid accumulation.

Improved quantification of γ-aminobutyric acid in rice using stable isotope dilution gas chromatography-mass spectrometry

An accurate method for the analysis of γ-aminobutyric acid (GABA) in rice grain was developed using trimethylsilyl (TMS) derivatization and stable isotope dilution gas chromatography-mass spectrometry. When this method was used with GABA‑d₆ as an internal standard (IS), the observed GABA concentration was maintained at 100% of the initial concentration with increasing storage time of the vial in the autosampler. In contrast, when using ribitol as an IS and multiple injections from one vial or single injections from different vials, the observed GABA concentration was 85 and 113% of the initial concentration upon increased storage time, respectively. The improved method recoveries at two different spike levels were between 93.3 and 97.8%, with relative standard deviations of less than 3.3%. The GABA content of resveratrol-enriched transgenic rice was compared with that of its non-transgenic counterpart from two field sites, and statistically non-significant differences were observed between the two grains.

Comparison of sequential derivatization with concurrent methods for GC/MS-based metabolomics

The gas chromatography/mass spectrometry (GC/MS)-based metabolomics requires a two-step derivatization procedure consisting of oximation and silylation. However, due to the incomplete derivatization and degeneration of the metabolites, good repeatability is difficult to obtain during the batch derivatization, as the time between completing the derivatization process and GC analysis differs from sample to sample. In this research, we successfully obtained good repeatability for the peak areas of 52 selected metabolites by sequential derivatization and interval injection, in which the oximation and silylation times were maintained at constant values. In addition, the derivatization times and amount of reagents employed were varied to confirm that the optimal derivatization conditions differed for the various metabolites. In conventional batch derivatization, six metabolites, viz. glutamine, glutamic acid, histidine, alanine, asparagine, and tryptophan, exhibited fluctuations in their peak areas. Indeed, we found that for all six metabolites these differences originated from the silylation process, while the variations for glutamine and glutamic acid were related to the oximation process.

Aldose reductase inhibitor protects mice from alcoholic steatosis by repressing saturated fatty acid biosynthesis

Alcoholic liver injury results in morbidity and mortality worldwide, but there are currently no effective and safe therapeutics. Previously we demonstrated that aldose reductase (AR) inhibitor ameliorated alcoholic hepatic steatosis. To clarify the mechanism whereby AR inhibitor improves alcoholic hepatic steatosis, herein we investigated the effect of AR inhibitor on hepatic metabolism in mice fed a Lieber-DeCarli liquid diet with 5% ethanol. Nontargeted metabolomics showed carbohydrates and lipids were characteristic categories in ethanol diet-fed mice with or without AR inhibitor treatment, whereas AR inhibitor mainly affected carbohydrates and peptides. Ethanol-induced galactose metabolism and fatty acid biosynthesis are important for the induction of hepatic steatosis, while AR inhibitor impaired galactose metabolism without perturbing fatty acid biosynthesis. In parallel with successful treatment of steatosis, AR inhibitor suppressed ethanol-activated galactose metabolism and saturated fatty acid biosynthesis. Sorbitol in galactose metabolism and stearic acid in saturated fatty acid biosynthesis were potential biomarkers responsible for ethanol or ethanol plus AR inhibitor treatment. In vitro analysis confirmed that exogenous addition of sorbitol augmented ethanol-induced steatosis and stearic acid. These findings not only reveal metabolic patterns associated with disease and treatment, but also shed light on functional biomarkers contribute to AR inhibition therapy.

Investigations in the possibility of early detection of colorectal cancer by gas chromatography/triple-quadrupole mass spectrometry

In developed countries, the number of patients with colorectal cancer has been increasing, and colorectal cancer is one of the most common causes of cancer death. To improve the quality of life of colorectal cancer patients, it is necessary to establish novel screening methods that would allow early detection of colorectal cancer. We performed metabolome analysis of a plasma sample set from 282 stage 0/I/II colorectal cancer patients and 291 healthy volunteers using gas chromatography/triple-quadrupole mass spectrometry in an attempt to identify metabolite biomarkers of stage 0/I/II colorectal cancer. The colorectal cancer patients included patients with stage 0 (N=79), I (N=80), and II (N=123) in whom invasion and metastasis were absent. Our analytical system detected 64 metabolites in the plasma samples, and the levels of 29 metabolites differed significantly (Bonferroni-corrected p=0.000781) between the patients and healthy volunteers. Based on these results, a multiple logistic regression analysis of various metabolite biomarkers was carried out, and a stage 0/I/II colorectal cancer prediction model was established. The area under the curve, sensitivity, and specificity values of this model for detecting stage 0/I/II colorectal cancer were 0.996, 99.3%, and 93.8%, respectively. The model's sensitivity and specificity values for each disease stage were >90%, and surprisingly, its sensitivity for stage 0, specificity for stage 0, and sensitivity for stage II disease were all 100%. Our predictive model can aid early detection of colorectal cancer and has potential as a novel screening test for cases of colorectal cancer that do not involve lymph node or distant metastasis.

Investigation of the derivatization conditions for GC-MS metabolomics of biological samples

AIM

Metabolomics applications represent an emerging field where significant efforts are directed. Derivatization consists prerequisite for GC-MS metabolomics analysis.

METHODS

Common silylation agents were tested for the derivatization of blood plasma. Optimization of methoxyamination and silylation reactions was performed on a mixture of reference standards, consisting of 46 different metabolites. Stability of derivatized metabolites was tested at 4°C.

RESULTS

Optimum results were achieved using N-methyl-N-(trimethylsilyl)trifluoroacetamide. Methoxyamination at room temperature for 24 h followed by 2-h silylation at high temperature lead to efficient derivatization.

CONCLUSION

Formation and stability of derivatives among metabolites differ greatly, so derivatization should be studied before application in metabolomics studies.

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'.