Quantification of Total Ketone Bodies in Biological Matrices Using Stable Isotope-Labeled Internal Standards and RP-UHPLC-MS/MS.

Acetoacetate (AcAc) and D-beta-hydroxybutyrate (D-ßOHB), the two major ketone bodies found in circulation, are linked to multiple physiological and pathophysiological states. Therefore, analytical methodologies surrounding the quantification of total ketone body (TKB) concentrations in biological matrices are paramount. Traditional methods to quantify TKBs relied on indirect spectrophotometric assays with narrow dynamic ranges, which have been significantly improved upon by modern mass spectrometry (MS)-based approaches. However, the lack of stable isotope-labeled internal standards (ISs) for AcAc and the need to distinguish D-ßOHB from its closely related structural and enantiomeric isomers pose significant obstacles. Here, we provide a protocol to synthesize and quantify a [13C] stable isotope-labeled IS for AcAc, which, in conjunction with a commercially available [2H] stable isotope-labeled IS for ßOHB, allows TKBs to be measured across multiple biological matrices. This rapid (7 min) analysis employs reverse phase ultra-high performance liquid chromatography (RP-UHPLC) coupled to tandem MS (MS/MS) to distinguish ßOHB from three structural isomers using parallel reaction monitoring (PRM), providing excellent specificity and selectivity. Finally, a method is provided that distinguishes D-ßOHB from L-ßOHB using a simple one-step derivatization to produce the corresponding diastereomers, which can be chromatographically resolved using the same rapid RP-UHPLC separation with new PRM transitions. In summary, this method provides a rigorous analytical pipeline for the analysis of TKBs in biological matrices via leveraging two authentic stable isotope-labeled ISs and RP-UHPLC-MS/MS.

Impact of internal standard selection on measurement results for long chain fatty acids in blood.

Introduction: Internal standards correct for measurement variation due to sample loss. Isotope labeled analytes are ideal internal standards for the measurement of fatty acids in human plasma but are not always readily available. For this reason, quantification of multiple analytes at once is most often done using only a single or few internal standards. The magnitude of the impact this has on method accuracy and precision is not well studied for gas chromatography-mass spectrometry systems. Objective: This study aims to estimate bias and changes in uncertainty associated with using alternative fatty acid isotopologue internal standards for the estimation of similar or dissimilar long chain fatty acids. Method: Using a previously reported method for the quantification of 27 fatty acids in human plasma using 18 internal standards we obtained estimates of bias and uncertainty at up to three levels of fatty acid concentration. Results: With some notable exceptions, method accuracy remained relatively stable when using an alternative internal standard (Median Relative Absolute Percent Bias: 1.76%, Median Spike-Recovery Absolute Percent Bias: 8.82%), with larger changes in method precision (Median Increase in Variance: 141%). Additionally, the degree of difference between analyte and internal standard structure was related to the magnitude of bias and uncertainty of the measurement. Conclusion: The data presented here show that the choice of internal standard used to estimate fatty acid concentration can affect the accuracy and reliability of measurement results and, therefore, needs to be assessed carefully when developing analytical methods for the measurement of fatty acid profiles.Disclaimer: The findings and conclusions in this report are those of the author(s) and do not necessarily represent the official position of the Centers for Disease Control and Prevention/the Agency for Toxic Substances and Disease Registry. Use of trade names is for identification only and does not imply endorsement by the Centers for Disease Control and Prevention, the Public Health Service, and the US Department of Health and Human Services.

Challenges and recent advances in quantitative mass spectrometry-based metabolomics.

The field of metabolomics has gained tremendous interest in recent years. Whether the goal is to discover biomarkers related to certain pathologies or to better understand the impact of a drug or contaminant, numerous studies have demonstrated how crucial it is to understand variations in metabolism. Detailed knowledge of metabolic variabilities can lead to more effective treatments, as well as faster or less invasive diagnostics. Exploratory approaches are often employed in metabolomics, using relative quantitation to look at perturbations between groups of samples. Most metabolomics studies have been based on metabolite profiling using relative quantitation, with very few studies using an approach for absolute quantitation. Using accurate quantitation facilitates the comparison between different studies, as well as enabling longitudinal studies. In this review, we discuss the most widely used techniques for quantitative metabolomics using mass spectrometry (MS). Various aspects will be addressed, such as the use of external and/or internal standards, derivatization techniques, in vivo isotopic labelling, or quantitative MS imaging. The principles, as well as the associated limitations and challenges, will be described for each approach.

Enantioselective Surface-Enhanced Raman Scattering by Chiral Au Nanocrystals with Finely Modulated Chiral Fields and Internal Standards.

The chiral discrimination of enantiomers is crucial for drug screening and agricultural production. Surface-enhanced Raman scattering (SERS) is proposed for discriminating enantiomers benefiting from chiral plasmonic materials. However, the mechanism of enantioselective SERS is unclear, and fluctuating SERS intensities may result in errors. Herein, this work demonstrates a reliable SERS substrate using chiral Au nanocrystals with finely modulated chiral fields and internal standards. Chiral electromagnetic fields are enhanced after modulation, which is conducive to increasing the difference in the enantiomeric SERS intensity, as evidenced by the experimental and simulation results. Furthermore, the SERS stability is improved by the corrective effect of the internal standards, and the relative standard deviation is significantly reduced. Using finely modulated chiral fields and internal standards, L- and D-phenylalanine exhibit a stable six times difference in SERS ratio. Theoretical simulations reveal that linearly polarized light can also excite the chiral fields of chiral Au nanocrystals, indicating non-chiral far-field light is converted into chiral near-field sources by chiral Au nanocrystals. Thus, the mechanism of enantioselective SERS can be elucidated by the scattering difference of chiral molecules in chiral near fields. This study will pave the way for the development of enantioselective SERS and related chiroptical technologies.

Simultaneous quantification of 11 antiepileptic drugs using limited isotope-labeled internal standards in LC-MS/MS: An accuracy assessment.

This study aims to establish an LC-MS/MS method to simultaneously analyze 11 antiepileptic drugs with a particular focus on maintaining accuracy while reducing the number of isotope-labeled internal standards employed for cost-effectiveness. By applying a water/acetonitrile gradient elution containing 0.1 % formic acid and 2 mM ammonium formate as the mobile phase, optimal sensitivity for the target drugs could be obtained in positive ESI mode in LC-MS/MS. After optimizing various extraction techniques, extraction with 70 % acetonitrile was selected as it provided good recoveries (>93 %) for all targets without matrix effects. Accuracies within 3 % were achieved from the combination of six internal standards, while accuracies of 5 % and 10 % were obtained by reducing the number of internal standards to four and two, respectively, for more economical analysis. The accuracy of the established method was maintained in hyperglycemia, hyperlipidemia, and hyperalbuminemia sera, suggesting that it can be successfully applied to individual serum samples with various properties.

Self-assembled core-shell nanoparticles with embedded internal standards for SERS quantitative detection and identification of nicotine released from snus products.

Surface enhanced Raman spectroscopy (SERS) is a unique analytical technique with excellent performance in terms of sensitivity, non-destructive detection and resolution. However, due to the randomness and poor repeatability of hot spot distribution, SERS quantitative analysis is still challenging. Meanwhile, snus is a type of tobacco product that can release nicotine and other components in the mouth without burning, and the rapid detection technique based on SERS can reliably evaluate the amount of nicotine released from snus, which is of great significance for understanding its characteristics and regulating its components. Herein, the strategy was proposed to solve the feasibility of SERS quantitative detection based on self-assembled core-shell nanoparticles with embedded internal standards (EIS) due to EIS signal can effectively correct SERS signal fluctuations caused by different aggregation states and measurement conditions, thus allowing reliable quantitative SERS analysis of targets with different surface affinity. By means of process control, after the Au nanoparticles (Au NPs) were modified with 4-Mercaptobenzonitrile (4-MBN) as internal standard molecules, Ag shell with a certain thickness was grown on the surface of the AuNP@4-MBN, and then the Au@4-MBN@Ag NPs were used to regulate and control the assembly of liquid-liquid interface. The high-density nano-arrays assembled at the liquid-liquid interface ensure high reproducibility as SERS substrates, and which could be used for SERS detection of nicotine released from snus products. In addition, time-mapping research shows that this method can also be used to dynamically monitor the release of nicotine. Moreover, such destruction-free evaluation of the release of nicotine from snus products opens up new perspectives for further research about the impact of nicotinoids-related health programs.

Quantifying payloads of antibody‒drug conjugates using a postcolumn infused-internal standard strategy with LC‒MS.

BACKGROUND: Antibody‒drug conjugates (ADCs) are innovative biopharmaceutics consisting of a monoclonal antibody, linkers, and cytotoxic payloads. Monitoring circulating payload concentrations has the potential to identify ADC toxicity; however, accurate quantification faces challenges, including low plasma concentrations, severe matrix effects, and the absence of stable isotope-labeled internal standards (SIL-IS) for payloads and their derivatives. Previous studies used structural analogs as internal standards, but different retention times between structural analogs and target analytes may hinder effective matrix correction. Therefore, a more flexible approach is required for precise payload quantification. RESULTS: We developed an LC‒MS/MS method incorporating a postcolumn-infused internal standard (PCI-IS) strategy for quantifying payloads and their derivatives of trastuzumab emtansine, trastuzumab deruxtecan, and sacituzumab govitecan, including DM1, MCC-DM1, DXd, SN-38, and SN-38G. Structural analogs (maytansine, Lys-MCC-DM1, and exatecan) were selected as PCI-IS candidates, and their accuracy performance was evaluated based on the percentage of samples within 80%-120% quantification accuracy. Compared to the approach without PCI-IS correction, exatecan enhanced the accuracy performance from 30-40%-100% for SN-38 and DXd, while maytansine and Lys-MCC-DM1 showed comparable accuracy for DM1 and MCC-DM1. This validated PCI-IS analytical method showed superior normalization of matrix effect in all analytes compared to the conventional internal standard approach. The clinical application of this approach showed pronounced differences in DXd and SN-38 concentrations before and after PCI-IS correction. Moreover, only DXd concentrations after PCI-IS correction were significantly higher in patients with thrombocytopenia (p = 0.037). SIGNIFICANCE: This approach effectively addressed the issue of unavailability of SIL-IS for novel ADC payloads and provided more accurate quantification, potentially yielding more robust statistical outcomes for understanding the exposure-toxicity relationship in ADCs. It is anticipated that this PCI-IS strategy may be extrapolated to quantify payloads and derivatives in diverse ADCs, thereby providing invaluable insights into drug toxicity and fortifying patient safety in ADC usage.

Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) methods for the therapeutic drug monitoring of cytotoxic anticancer drugs: An update.

In the era of precision medicine, there is increasing evidence that conventional cytotoxic agents may be suitable candidates for therapeutic drug monitoring (TDM)- guided drug dosage adjustments and patient's tailored personalization of non-selective chemotherapies. To that end, many liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) assays have been developed for the quantification of conventional cytotoxic anticancer chemotherapies, that have been comprehensively and critically reviewed. The use of stable isotopically labelled internal standards (IS) of cytotoxic drugs was strikingly uncommon, accounting for only 48 % of the methods found, although their use could possible to suitably circumvent patients' samples matrix effects variability. Furthermore, this approach would increase the reliability of cytotoxic drug quantification in highly multi-mediated cancer patients with complex fluctuating pathophysiological and clinical conditions. LC-MS/MS assays can accommodate multiplexed analyses of cytotoxic drugs with optimal selectivity and specificity as well as short analytical times and, when using stable-isotopically labelled IS for quantification, provide concentrations measurements with a high degree of certainty. However, there are still organisational, pharmacological, and medical constraints to tackle before TDM of cytotoxic drugs can be more largely adopted in the clinics for contributing to our ever-lasting quest to improve cancer treatment outcomes.

A novel synthetic nucleic acid mixture for quantification of microbes by mNGS.

Metagenomic next-generation sequencing (mNGS) provides considerable advantages in identifying emerging and re-emerging, difficult-to-detect and co-infected pathogens; however, the clinical application of mNGS remains limited primarily due to the lack of quantitative capabilities. This study introduces a novel approach, KingCreate-Quantification (KCQ) system, for quantitative analysis of microbes in clinical specimens by mNGS, which co-sequence the target DNA extracted from the specimens along with a set of synthetic dsDNA molecules used as Internal-Standard (IS). The assay facilitates the conversion of microbial reads into their copy numbers based on IS reads utilizing a mathematical model proposed in this study. The performance of KCQ was systemically evaluated using commercial mock microbes with varying IS input amounts, different proportions of human genomic DNA, and at varying amounts of sequence analysis data. Subsequently, KCQ was applied in microbial quantitation in 36 clinical specimens including blood, bronchoalveolar lavage fluid, cerebrospinal fluid and oropharyngeal swabs. A total of 477 microbe genetic fragments were screened using the bioinformatic system. Of these 83 fragments were quantitatively compared with digital droplet PCR (ddPCR), revealing a correlation coefficient of 0.97 between the quantitative results of KCQ and ddPCR. Our study demonstrated that KCQ presents a practical approach for the quantitative analysis of microbes by mNGS in clinical samples.

Metabolomics 2022 workshop report: state of QA/QC best practices in LC-MS-based untargeted metabolomics, informed through mQACC community engagement initiatives.

INTRODUCTION: The Metabolomics Quality Assurance and Quality Control Consortium (mQACC) organized a workshop during the Metabolomics 2022 conference. OBJECTIVES: The goal of the workshop was to disseminate recent findings from mQACC community-engagement efforts and to solicit feedback about a living guidance document of QA/QC best practices for untargeted LC-MS metabolomics. METHODS: Four QC-related topics were presented. RESULTS: During the discussion, participants expressed the need for detailed guidance on a broad range of QA/QC-related topics accompanied by use-cases. CONCLUSIONS: Ongoing efforts will continue to identify, catalog, harmonize, and disseminate QA/QC best practices, including outreach activities, to establish and continually update QA/QC guidelines.

A new spike-in-based method for quantitative metabarcoding of soil fungi and bacteria.

Metabarcoding is a powerful tool to characterize biodiversity in biological samples. The interpretation of taxonomic profiles from metabarcoding data has been hindered by their compositional nature. Several strategies have been proposed to transform compositional data into quantitative data, but they have intrinsic limitations. Here, I propose a workflow based on bacterial and fungal cellular internal standards (spike-ins) for absolute quantification of the microbiota in soil samples. These standards were added to the samples before DNA extraction in amounts estimated after qPCRs, to target around 1-2% coverage in the sequencing run. In bacteria, proportions of spike-in reads in the sequencing run were very similar (< 2-fold change) to those predicted by the qPCR assessment, and for fungi they differed up to 40-fold. The low variation among replicates highlights the reproducibility of the method. Estimates based on multiple bacterial spike-ins were highly correlated (r = 0.99). Procrustes analysis evidenced significant biological effects on the community composition when normalizing compositional data. A protocol based on qPCR estimation of input amounts of cellular spikes is proposed as a cheap and reliable strategy for quantitative metabarcoding of biological samples.

Amino acid analysis for peptide quantitation using reversed-phase liquid chromatography combined with multiple reaction monitoring mass spectrometry.

Amino acid analysis (AAA) can be used for absolute quantitation of standard peptides after acid hydrolysis using 6 M HCl. Obtained individual amino acids can then be quantified by liquid chromatography-mass spectrometry (LC-MS). Achieving baseline separation of non-derivatized amino acids is challenging when reversed-phase (RP) chromatography is used. Several derivatization methods are commonly utilized to address this issue; however, derivatization has several drawbacks, such as derivative instability and lack of reproducibility. Currently, separation of non-derivatized amino acids is typically done using HILIC, but HILIC has problems of poor reproducibility and long column equilibration times. We developed a method to quantify non-derivatized amino acids, including methionine and cysteine, from peptide hydrolysates by RP-LC-MS without special pre-treatment of the samples. Samples were spiked with certified isotopically labeled (13C- and/or 15N-) amino acids as internal standards. The amino acids released from acid hydrolysis were then analyzed by RP-UPLC-MRM-MS and quantified using the analyte/internal standard chromatographic peak area ratios. Peptide quantitation was based on the sum of the individual amino acid concentrations from the known peptide sequences. The resulting method did not require derivatization, used standard C18-based reversed-phase liquid chromatography, did not require external calibration, was robust, and was able to quantify all 17 amino acids for which we had internal standards, including the sulfur-containing amino acids, cysteine and methionine, in their respective oxidized forms. This simple and robust method enabled the absolute quantitation of standard peptides using only acid hydrolysis and a standard RP-UPLC-MRM-MS setup.

Matrix Effects Free Imaging of Thin Tissue Sections Using Pneumatically Assisted Nano-DESI MSI.

Mass spectrometry imaging has the potential to reveal important molecular interaction in morphological regions in tissue. However, the simultaneous ionization of the continuously altered and complex chemistry in each pixel can introduce artifacts that result in skewed molecular distributions in the compiled ion images. These artifacts are known as matrix effects. Mass spectrometry imaging using nanospray desorption electrospray ionization (nano-DESI MSI) enables the elimination of matrix effects by doping the nano-DESI solvent with internal standards. Carefully selected internal standards ionize similarly and simultaneously with the extracted analytes from thin tissue sections, and the matrix effects are eliminated through a robust data normalization method. Herein we describe the setup and use of pneumatically assisted (PA) nano-DESI MSI with standards doped in the solvent for elimination of matrix effects in ion images.

A standardized quantitative analysis strategy for stable isotope probing metagenomics.

Stable isotope probing (SIP) facilitates culture-independent identification of active microbial populations within complex ecosystems through isotopic enrichment of nucleic acids. Many DNA-SIP studies rely on 16S rRNA gene sequences to identify active taxa, but connecting these sequences to specific bacterial genomes is often challenging. Here, we describe a standardized laboratory and analysis framework to quantify isotopic enrichment on a per-genome basis using shotgun metagenomics instead of 16S rRNA gene sequencing. To develop this framework, we explored various sample processing and analysis approaches using a designed microbiome where the identity of labeled genomes and their level of isotopic enrichment were experimentally controlled. With this ground truth dataset, we empirically assessed the accuracy of different analytical models for identifying active taxa and examined how sequencing depth impacts the detection of isotopically labeled genomes. We also demonstrate that using synthetic DNA internal standards to measure absolute genome abundances in SIP density fractions improves estimates of isotopic enrichment. In addition, our study illustrates the utility of internal standards to reveal anomalies in sample handling that could negatively impact SIP metagenomic analyses if left undetected. Finally, we present SIPmg, an R package to facilitate the estimation of absolute abundances and perform statistical analyses for identifying labeled genomes within SIP metagenomic data. This experimentally validated analysis framework strengthens the foundation of DNA-SIP metagenomics as a tool for accurately measuring the in situ activity of environmental microbial populations and assessing their genomic potential. IMPORTANCE Answering the questions, "who is eating what?" and "who is active?" within complex microbial communities is paramount for our ability to model, predict, and modulate microbiomes for improved human and planetary health. These questions can be pursued using stable isotope probing to track the incorporation of labeled compounds into cellular DNA during microbial growth. However, with traditional stable isotope methods, it is challenging to establish links between an active microorganism's taxonomic identity and genome composition while providing quantitative estimates of the microorganism's isotope incorporation rate. Here, we report an experimental and analytical workflow that lays the foundation for improved detection of metabolically active microorganisms and better quantitative estimates of genome-resolved isotope incorporation, which can be used to further refine ecosystem-scale models for carbon and nutrient fluxes within microbiomes.

Quantitative 1H Nuclear Magnetic Resonance (qNMR) of Aromatic Amino Acids for Protein Quantification.

Hydrolysis of protein samples into amino acids facilitates the use of NMR spectroscopy for protein and peptide quantification. Different conditions have been tested for quantifying aromatic amino acids and proteins. The pH-dependent signal shifts in the aromatic region of amino acid samples were examined. A pH of 12 was found to minimize signal overlap of the four aromatic amino acids. Several aromatic compounds, such as terephthalic acid, sulfoisophthalic acid, and benzene tricarboxylic acid, were applied as internal standards. The quantification of amino acids from an amino acid standard was performed. Using the first two suggested internal standards, recovery was ~97% for histidine, phenylalanine, and tyrosine at a concentration of approximately 1 mM in solution. Acidic hydrolysis of a certified reference material (CRM) of bovine serum albumin (BSA) and subsequent quantification of Phe and Tyr yielded recoveries of 98% ± 2% and 88% ± 4%, respectively, at a protein concentration of 16 g/L or 250 µM.

Metabolic profiling workflow for cell extracts by targeted hydrophilic interaction liquid chromatography-tandem mass spectrometry.

In this study, a targeted approach with wide metabolite coverage was developed for cellular metabolomic analysis using a UHPLC-QTrap-MS system operated in the scheduled multiple reaction monitoring (sMRM) mode. MRM ion pairs were acquired from HeLa cell samples through untargeted analysis using UHPLC-QTOF-MS with SWATH acquisition complemented by missing metabolites from pathway databases. Four different cell extraction protocols were studied and compared based on an experiment series involving the calculation of individual metabolite recoveries (pre/post extraction spiking U-13C isotope-labeled standards), with a Methanol/Water extraction mixture (1:1; v/v) showing the best results. Two HILIC-MS methods employing a Waters Premier BEH Amide column were developed, utilizing two different chromatographic conditions (20 mM ammonium formate as buffer additive adjusted to a pH = 3.5 with formic acid in ESI+ mode and 20 mM ammonium acetate adjusted to a pH = 7.5 with acetic acid in ESI- mode. One hundred sixty-one (161) metabolites were successfully detected in ESI+ mode, whereas 92 were detected in negative ionization mode, totaling to a number of 253 compounds in three different biological matrices covered by the analytical system employed. Both established HILIC methods were calibrated and validated based on 105 authentic chemical standards and U-13C-labeled Pichia pastoris (Komagataella phaffii) yeast extract as internal standards for cellular matrix (HeLa cells). Within-day and between-day precision was determined on three different QC concentration levels and was below 15% for the entirety of the analytes. Inter- and intra-day accuracies showed values in the range between 85 and 115% (assessed as % recovery) in the entire range. Matrix effects, extraction recoveries and process efficiencies were evaluated following the Matuszewski protocol with U-13C-labeled Pichia pastoris metabolite extract as internal standards. Eventually, the method was utilized to quantify metabolites in HeLa cell extracts.

Metabolomics and flavoromics analysis of chemical constituent changes during roasting of germinated Sacha inchi (Plukenetia volubilis L.).

This study examined the changes in metabolites together with the flavor profiles of germinated Sacha inchi seeds during roasting by using gas chromatography. The results indicated that roasting partially increased the browning index, amino acid levels, total phenolic content, and antioxidant capacity, but slightly decreased the levels of reducing sugars. Oxidized and rancid compounds were significantly decreased at a 180 °C roasting temperature. Pyrazine, furan, and pyrrole were Maillard reaction products that were increased at 180 °C of roasting. Roasting at 145 °C for 45 min after germination for 4 days was determined to be the optimal conditions for roasting germinated Sacha inchi seeds, which reduced the off-flavor and burned taste. The roasted germinated Sacha inchi seed contains higher amino acids than raw seed, which could be used as an alternative source for food products and supplements. In addition, the roasted germinated seeds at 4 days were recommended for food applications.

Geochemical matrix differently affects the response of internal standards and target analytes for pesticide transformation products measured in groundwater samples.

Electrospray ionization (ESI) is the most common technique in liquid chromatography coupled to tandem mass spectrometry (LC-MS-MS) allowing for sensitive detection of polar compounds with online water concentration. The technique is popular in groundwater monitoring programs and has permitted great progress in the detection and quantification of polar pesticide transformation products (TP) in recent years. However, ESI is also known to be prone to matrix effects. The common solution to this potential bias is the use of labelled internal standards. Unfortunately, these are not available for all target compounds, which leads to the linkage of target compounds to non-homologue internal standards with unknown consequences for quantification in variable geochemical settings. We investigated these matrix effects for polar TP with a molecular mass range of 225-350 Da and logDpH7 between -0.27 and -1.7 as well as for parent compounds with logDpH3 between 0.84 and 3.22. The acquired internal standards were tested on a gradient of DOC, anions, conductivity and inorganic carbon with a set of ten carefully chosen groundwater samples. Internal standards that were measured in positive ionization mode proved to be insensitive to geochemical variations while those that were measured in negative ionization mode showed reduced response with increasing anion concentration. All pairs of internal standards and target analytes were investigated for deviating matrix effects using standard addition experiments. Positive ionization compounds and target compounds with deuterated homologues showed little deviation while non-homologue pairs in negative mode proved to be strongly biased. Although bias was up to factor five for some compounds it was remarkably stable over the entire gradient studied, suggesting an identical suppression mode at varying matrix levels for different compounds. We advocate the conduct of standard addition experiments if homologue internal standards are not available.

Preparation of Deuterium-Labeled Armodafinil by Hydrogen-Deuterium Exchange and Its Application in Quantitative Analysis by LC-MS.

Armodafinil, the R enantiomer of modafinil, was approved in 2007 by the US Food and Drug Administration as a wake-promoting agent for excessive sleepiness treatment. Due to its abuse by students and athletes, there is a need of its quantification. Quantitative analysis by liquid chromatography-mass spectrometry, however, though very common and sensitive, frequently cannot be performed without isotopically labeled standards which usually have to be specially synthesized. Here we reported our investigation on the preparation of deuterated standard of armodafinil based on the simple and inexpensive hydrogen-deuterium exchange reaction at the carbon centers. The obtained results clearly indicate the possibility of introduction of three deuterons into the armodafinil molecule. The introduced deuterons do not undergo back exchange under neutral and acidic conditions. Moreover, the deuterated and non-deuterated armodafinil isotopologues revealed co-elution during the chromatographic analysis. The ability to control the degree of deuteration using different reaction conditions was determined. The proposed method of deuterated armodafinil standard preparation is rapid, cost-efficient and may be successfully used in its quantitative analysis by LC-MS.

Reference materials for MS-based untargeted metabolomics and lipidomics: a review by the metabolomics quality assurance and quality control consortium (mQACC).

INTRODUCTION: The metabolomics quality assurance and quality control consortium (mQACC) is enabling the identification, development, prioritization, and promotion of suitable reference materials (RMs) to be used in quality assurance (QA) and quality control (QC) for untargeted metabolomics research. OBJECTIVES: This review aims to highlight current RMs, and methodologies used within untargeted metabolomics and lipidomics communities to ensure standardization of results obtained from data analysis, interpretation and cross-study, and cross-laboratory comparisons. The essence of the aims is also applicable to other 'omics areas that generate high dimensional data. RESULTS: The potential for game-changing biochemical discoveries through mass spectrometry-based (MS) untargeted metabolomics and lipidomics are predicated on the evolution of more confident qualitative (and eventually quantitative) results from research laboratories. RMs are thus critical QC tools to be able to assure standardization, comparability, repeatability and reproducibility for untargeted data analysis, interpretation, to compare data within and across studies and across multiple laboratories. Standard operating procedures (SOPs) that promote, describe and exemplify the use of RMs will also improve QC for the metabolomics and lipidomics communities. CONCLUSIONS: The application of RMs described in this review may significantly improve data quality to support metabolomics and lipidomics research. The continued development and deployment of new RMs, together with interlaboratory studies and educational outreach and training, will further promote sound QA practices in the community.