bims-metlip Biomed News
on Methods and protocols in metabolomics and lipidomics
Issue of 2021‒06‒13
eighteen papers selected by
Sofia Costa
Cold Spring Harbor Laboratory

  1. Anal Chim Acta. 2021 Jul 25. pii: S0003-2670(21)00432-3. [Epub ahead of print]1170 338606
      We have developed an analytical procedure to measure the carbon isotopic composition of multiple compounds even when there is a partial overlap in the chromatographic profiles and applied this procedure to measure the carbon isotopic composition of different metabolites in human urine and exhaled breath. Method development and validation was performed with CRM IAEA-600 caffeine after calibration of the reference CO2 gas using a mixture of certified undecane, pentadecane and eicosane δ(13C) standards. The alternative data treatment procedure included the correction of time-lag between Faraday cup amplifiers (44 ms at mass 45 and -160 ms at mass 46), the calculation and correction of chromatographic isotope effects on each peak (isotope shifts) and the calculation of the isotope ratio for each compound using the linear regression slope procedure with data only at the top of the chromatographic peak. In that way, partial chromatographic overlap between different metabolites can be tolerated (resolution equal or higher than 1). The reproducibility (SD) of the carbon isotope composition of 93 metabolites in human urine (n = 8) from one volunteer was typically better than 0.5 δ(13C) (range 0.1-2.0 δ(13C), median 0.4 δ(13C)). The method was applied to follow the carbon isotope composition of different metabolites in human urine and exhaled breath after the oral administration of 100 mg of universally labelled 13C-glucose to another human volunteer. It was demonstrated that isotopically labelled compounds could be detected in both samples even 2 h after administration. So, the developed methodology can be applied to multiple types of samples containing a large number of partially overlapping analytes including environmental applications, anti-doping control or metabolomics studies, including the use of enriched isotope tracers.
    Keywords:  Carbon isotope ratios; Exhaled breath; Metabolomics; Urine
  2. Anal Chem. 2021 Jun 07.
      Spatial metabolomics using mass spectrometry imaging (MSI) is a powerful tool to map hundreds to thousands of metabolites in biological systems. One major challenge in MSI is the annotation of m/z values, which is substantially complicated by background ions introduced throughout the chemicals and equipment used during experimental procedures. Among many factors, the formation of adducts with sodium or potassium ions, or in case of matrix-assisted laser desorption ionization (MALDI)-MSI, the presence of abundant matrix clusters strongly increases total m/z peak counts. Currently, there is a limitation to identify the chemistry of the many unknown peaks to interpret their biological function. We took advantage of the co-localization of adducts with their parent ions and the accuracy of high mass resolution to estimate adduct abundance in 20 datasets from different vendors of mass spectrometers. Metabolites ranging from lipids to amines and amino acids form matrix adducts with the commonly used 2,5-dihydroxybenzoic acid (DHB) matrix like [M + (DHB-H2O) + H]+ and [M + DHB + Na]+. Current data analyses neglect those matrix adducts and overestimate total metabolite numbers, thereby expanding the number of unidentified peaks. Our study demonstrates that MALDI-MSI data are strongly influenced by adduct formation across different sample types and vendor platforms and reveals a major influence of so far unrecognized metabolite-matrix adducts on total peak counts (up to one third). We developed a software package, mass2adduct, for the community for an automated putative assignment and quantification of metabolite-matrix adducts enabling users to ultimately focus on the biologically relevant portion of the MSI data.
  3. OMICS. 2021 Jun;25(6): 389-399
      Metabolomics is a leading frontier of systems science and biomedical innovation. However, metabolite identification in mass spectrometry (MS)-based global metabolomics investigations remains a formidable challenge. Moreover, lack of comprehensive spectral databases hinders accurate identification of compounds in global MS-based metabolomics. Creating experiment-derived metabolite spectral libraries tailored to each experiment is labor-intensive. Therefore, predicted spectral libraries could serve as a better alternative. User-friendly tools are much needed, as the currently available metabolomic analysis tools do not offer adequate provision for users to create or choose context-specific databases. Here, we introduce the MS2Compound, a metabolite identification tool, which can be used to generate a custom database of predicted spectra using the Competitive Fragmentation Modeling-ID (CFM-ID) algorithm, and identify metabolites or compounds from the generated database. The database generator can create databases of the model/context/species used in the metabolomics study. The MS2Compound is also powered with mS-score, a scoring function for matching raw fragment spectra to a predicted spectra database. We demonstrated that mS-score is robust in par with dot product and hypergeometric score in identifying metabolites using benchmarking datasets. We evaluated and highlight here the unique features of the MS2Compound by a re-analysis of a publicly available metabolomic dataset (MassIVE id: MSV000086784) for a complex traditional drug formulation called Triphala. In conclusion, we believe that the omics systems science and biomedical research and innovation community in the field of metabolomics will find the MS2Compound as a user-friendly analysis tool of choice to accelerate future metabolomic analyses.
    Keywords:  MS2Compound; bioinformatics; computational biology; data analysis; metabolite identification; metabolomics; systems science
  4. J Chromatogr A. 2021 May 28. pii: S0021-9673(21)00418-0. [Epub ahead of print]1651 462294
      Few articles are reported for the simultaneous separation and sensitive detection of the kynurenine pathway (KP) metabolites. This work describes a capillary electrochromatography-mass spectrometry (CEC-MS) method using acrylamido-2-methyl-1-propanesulfonic acid (AMPS) functionalized stationary phase. The AMPS column was prepared by first performing silanization of bare silica with gamma-maps, followed by polymerization with AMPS. The CEC-MS/MS methods were established for six upstream and three downstream KP metabolites. The simultaneous separation of all nine KP metabolites is achieved without derivatization for the first time in the open literature. Numerous parameters such as pH and the concentration of background electrolyte, the concentration of the polymerizable AMPS monomer, column length, field strength, and internal pressure were all tested to optimize the separation of multiple KP metabolites. A baseline separation of six upstream metabolites, namely tryptophan (TRP), kynurenine (KYN), 3-hydroxykynurenine (HKYN), kynurenic acid (KA), anthranilic acid (AA), and xanthurenic acid (XA), was possible at pH 9.25 within 26 min. Separation of six downstream and related metabolites, namely: tryptamine (TRPM), hydroxy‑tryptophan (HTRP), hydroxyindole-3 acetic acid (HIAA), 3-hydroxyanthranilic acid (3-HAA), picolinic acid (PA), and quinolinic acid (QA), was achieved at pH 9.75 in 30 min. However, the challenging simultaneous separation of all nine KP metabolites was only accomplished by increasing the column length and simultaneous application of internal pressure and voltage in 114 min. Quantitation of KP metabolites in commercial human plasma was carried out, and endogenous concentration of five KP metabolites was validated. The experimental limit of quantitation ranges from 100 to 10,000 nM (S/N = 8-832, respectively), whereas the experimental limit of detection ranges from 31 to 1000 nM (S/N = 2-16, respectively). Levels of five major KP metabolites, namely TRP, KYN, KA, AA, and QA, and their ratios in patient plasma samples previously screened for inflammatory biomarkers [C-reactive protein (CRP) and tumor necrosis factor-alpha (TNF-α)] was measured. Pairs of the level of metabolites with significant positive correlation were statistically evaluated.
    Keywords:  Capillary electrochromatography-mass spectrometry; Endogenous plasma quantitation; Low vs. high inflammation; Nine kynurenine pathway metabolites; Simultaneous separation; Standard addition-internal standard
  5. Anal Bioanal Chem. 2021 Jun;413(15): 3833-3845
      Long-chain fatty acids (LCFA) are commonly found in lipid-rich wastewaters and are a key factor to monitor the anaerobic digesters. A new simple, fast, precise, and suitable method for routine analysis of LCFA is proposed. The system involves in-syringe-magnetic stirring-assisted dispersive liquid-liquid microextraction (DLLME) prior to gas chromatography-mass spectrometry (GC-MS) without a derivatization process. Calibration curves were prepared in an ethanol solution (R2 ≥ 0.996), which was also useful as disperser solvent. Hexane was chosen as the extraction solvent. Several parameters (pH, ionic strength, extraction solvent volume, stirring time) were optimized in multivariate and univariate studies. Limits of detection (LODs) were found in the range 0.01-0.05 mg L-1 and good precision inter-day (RSDs≤7.9%) and intra-day (RSDs≤4.4%) were obtained. The method was applied to quantify LCFA in supernatants of anaerobic digesters and olive mill wastewaters (OMW). Palmitic, stearic, and oleic acids were the most abundant fatty acid in the analyzed samples and the relative recoveries for all of them were between 81 and 113%.
    Keywords:  Anaerobic supernatant; Automation; GC-MS; In-syringe-magnetic stirring-assisted dispersive liquid-liquid microextraction; Long-chain fatty acids; Olive mill wastewater
  6. Metabolomics. 2021 Jun 06. 17(6): 55
      BACKGROUND: Improvements in mass spectrometry (MS) technologies coupled with bioinformatics developments have allowed considerable advancement in the measurement and interpretation of lipidomics data in recent years. Since research areas employing lipidomics are rapidly increasing, there is a great need for bioinformatic tools that capture and utilize the complexity of the data. Currently, the diversity and complexity within the lipidome is often concealed by summing over or averaging individual lipids up to (sub)class-based descriptors, losing valuable information about biological function and interactions with other distinct lipids molecules, proteins and/or metabolites.AIM OF REVIEW: To address this gap in knowledge, novel bioinformatics methods are needed to improve identification, quantification, integration and interpretation of lipidomics data. The purpose of this mini-review is to summarize exemplary methods to explore the complexity of the lipidome.
    KEY SCIENTIFIC CONCEPTS OF REVIEW: Here we describe six approaches that capture three core focus areas for lipidomics: (1) lipidome annotation including a resolvable database identifier, (2) interpretation via pathway- and enrichment-based methods, and (3) understanding complex interactions to emphasize specific steps in the analytical process and highlight challenges in analyses associated with the complexity of lipidome data.
    Keywords:  Bioinformatics; Data integration; Lipid Identification; Lipidomics; Ontologies; Pathway enrichment
  7. Methods Mol Biol. 2021 ;2275 329-339
      Coenzyme Q10 (CoQ10) is an essential part of the mitochondrial respiratory chain . Here, we describe an accurate and sensitive liquid chromatography tandem mass spectrometry (LC-MS/MS) method for determination of mitochondrial CoQ10 in isolated mitochondria . In the assay, mitochondrial suspensions are spiked with CoQ10-[2H9] internal standard (IS), extracted with organic solvents and CoQ10 quantified by LC-MS/MS using multiple reaction monitoring (MRM).
    Keywords:  Coenzyme Q10; Isotope dilution; LC-MS/MS; Mitochondrial disease; Ubiquinone
  8. J Chromatogr Sci. 2021 Jun 09. pii: bmab069. [Epub ahead of print]
      A simple, fast and extremely sensitive for estimating Pimavanserin in human (K2EDTA) plasma using ultra high-performance liquid chromatography combined with tandem mass spectrometry (UHPLC-MS/MS) was newly developed and validated. Sample extraction was accomplished using a partition liquid extraction (LLE-liquid-liquid extraction) procedure utilizing extraction solvent, methyl tertiary butyl ether. Separation of the components, chromatography, was done using a C18 chromatographic analytical column employing acetonitrile:methanol: 0.1% formic acid solution (40:40:20 volume by volume) pumped with 0.800 mL/min as the flow rate. For Pimavanserin, the established methodology was linear throughout the calibration curve range from 0.25ng/mL till 50.0 ng/mL. Results of intraday and interday accuracy and precision of Pimavanserin met recent regulatory requirements. This methodology was effectively used to estimate Pimavanserin in vivo human (K2EDTA) plasma concentration for a clinical pharmacokinetic study.
  9. J Sep Sci. 2021 Jun 08.
      Chlorella vulgaris is a popular microalga used for biofuel production; nevertheless, it possesses a strong cell wall that hinders the extraction of molecules, especially lipids within the cell wall. For tackling this issue, we developed an efficient and cost-effective method for optimal lipid extraction. Microlaga cell disruption by acid hydrolysis was investigated comparing different temperatures and reaction times; after hydrolysis, lipids were extracted with n-hexane. The best recoveries were obtained at 140 °C for 90 min. The microalgae were then analyzed by an untargeted approach based on LC- high-resolution MS, providing the tentative identification of 28 fatty acids. First, a relative quantification on the untargeted data was performed using peak area as a surrogate of analyte abundance. Then, a targeted quantitative method was validated for the tentatively identified fatty acids, in terms of recovery (78-100%), intra- and inter-day relative standard deviations (<10% and <9%, respectively) and linearity (R2 >0.98). The most abundant fatty acids were palmitic, palmitoleic, oleic, linoleic, linolenic, and stearic acids. This article is protected by copyright. All rights reserved.
    Keywords:  Compound Discoverer; biofuel; fatty acids; lipidomics; untargeted analysis
  10. ACS Nano. 2021 Jun 07.
      For organ transplantation patients, the therapeutic drug monitoring (TDM) of immunosuppressive drugs is essential to prevent the toxicity or rejection of the organ. Currently, TDM is done by immunoassays or liquid chromatography-tandem mass spectrometry (LC-MS/MS) methods; however, these methods lack specificity or are expensive, require high levels of skill, and offer limited sample throughput. Although matrix-assisted (MA) laser desorption ionization (LDI) mass spectrometry (MS) can provide enhanced throughput and cost-effectiveness, its application in TDM is limited due to the limitations of the matrixes such as a lack of sensitivity and reproducibility. Here, we present an alternative quantification method for the TDM of the immunosuppressive drugs in the blood of organ transplant patients by utilizing laser desorption ionization mass spectrometry (LDI-MS) based on a tungsten disulfide nanosheet, which is well-known for its excellent physicochemical properties such as a strong UV absorbance and high electron mobility. By adopting a microliquid inkjet printing system, a high-throughput analysis of the blood samples with enhanced sensitivity and reproducibility was achieved. Furthermore, up to 80 cases of patient samples were analyzed and the results were compared with those of LC-MS/MS by using Passing-Bablok regression and Bland-Altman analysis to demonstrate that our LDI-MS platform is suitable to replace current TDM techniques. Our approach will facilitate the rapid and accurate analysis of blood samples from a large number of patients for immunosuppressive drug prescriptions.
    Keywords:  chemical exfoliations; immunosuppressive drugs; laser desorption ionizations; nasnosheets; organ transplant; therapeutic drug monitorings; tungsten disulfides
  11. J Chromatogr A. 2021 May 24. pii: S0021-9673(21)00395-2. [Epub ahead of print]1651 462271
      Successful applications of lipidomics in clinic need study large-scale samples, and the bottlenecks are in throughput and robustness of the lipid analytical method. Here, we report an untargeted lipidomics method by combining high throughput pretreatment in the 96-well plate with ultra-high performance liquid chromatography coupled to quadrupole time-of-flight tandem mass spectrometry. The developed method was validated to have satisfactory analytical characteristics in terms of linearity, repeatability and extraction recovery. It can be used to handle 96 samples simultaneously in 25 min and detect 441 lipids in plasma sample. Storage stability investigation on lipid extracts provided an operable procedure for large-scale sample analysis and demonstrated most lipids were stable in autosampler at 10 °C within 36 h and at -80 °C within 72 h after the pretreatment. To prove the usefulness, the method was employed to investigate abnormal plasma lipidome related to atrial fibrillation. A biomarker panel with the area under the curve (AUC) values of 0.831 and 0.745 was achieved in the discovery and external validation sets, respectively. These results showed that the developed method is applicable for large-scale biological sample handling and lipid analysis of plasma.
    Keywords:  96-well plate; Atrial fibrillation; High throughput; Large-scale; Lipidomics
  12. J Sci Food Agric. 2021 Jun 07.
      BACKGROUND: Helminth infections in animals to be consumed by humans are an important medical and public health problem. Pharmaceutical research has focused on developing new anthelmintic drugs for parasite control in these animals. However, the incorrect use of anthelmintics can leave residues in animal products intended for human consumption. Therefore, their determination is crucial in terms of food safety.RESULTS: In this work, a simple and sensitive method has been developed for the analysis of anthelmintic drugs in milk. The method involves extraction of the analytes using the QuEChERS (Quick, Easy, Cheap, Effective, Rugged, and Safe) method, and separation and determination by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The use of a core-shell column significantly reduced the analysis time compared to conventional columns. The method was validated and applied to the analysis of different commercial milk samples: whole, semi-skimmed and skimmed cow's milk, and goat's milk. None of the benzimidazoles studied was found in the samples analyzed, so these were spiked with the analytes at three concentration levels (10, 50 and 100 μg kg-1 ).
    CONCLUSIONS: The proposed method provided high sensitivity compared with other methods for the determination of anthelmintics in milk samples, at concentration levels well below the established maximum residue limits (MRLs) values. The proposed method is simple, easy, precise, accurate, and leads to good recovery levels. It can be used successfully for the routine analysis. This article is protected by copyright. All rights reserved.
    Keywords:  LC-MS/MS; QuEChERS; anthelmintic drugs, benzimidazoles; milk
  13. J Am Soc Mass Spectrom. 2021 Jun 09.
      The identification of metabolites in biological samples is challenging due to their chemical and structural diversity. Ion mobility spectrometry (IMS) separates ionized molecules based on their mobility in a carrier buffer gas giving information about the ionic shape by measuring the rotationally averaged collision cross-section (CCS) value. This orthogonal descriptor, in combination with the m/z, isotopic pattern distribution, and MS/MS spectrum, has the potential to improve the identification of molecular molecules in complex mixtures. Urine metabolomics can reveal metabolic differences, which arise as a result of a specific disease or in response to therapeutic intervention. It is, however, complicated by the presence of metabolic breakdown products derived from a wide range of lifestyle and diet-related byproducts, many of which are poorly characterized. In this study, we explore the use of trapped ion mobility spectrometry (TIMS) via LC parallel accumulation with serial fragmentation (PASEF) for urine metabolomics. A total of 362 urine metabolites were characterized from 80 urine samples collected from healthy volunteers using untargeted metabolomics employing HILIC and RP chromatography. Additionally, three analytes (Trp, Phe, and Tyr) were selected for targeted quantification. Both the untargeted and targeted data was highly reproducible and reported CCS measurements for identified metabolites were robust in the presence of the urine matrix. A comparison of CCS values among different laboratories was also conducted, showing less than 1.3% ΔCCS values across different platforms. This is the first report of a human urine metabolite database compiled with CCS values experimentally acquired using an LC-PASEF TIMS-qTOF platform.
  14. Anal Bioanal Chem. 2021 Jun;413(15): 3975-3986
      Pseudotargeted analysis combines the advantages of untargeted and targeted lipidomics methods based on chromatography-mass spectrometry (MS). This study proposed a comprehensive pseudotargeted lipidomics method based on three-phase liquid extraction (3PLE) and segment data-dependent acquisition (SDDA). We used a 3PLE method to extract the lipids with extensive coverage from biological matrixes. 3PLE was composed of one aqueous and two organic phases. The upper and middle organic phases enriched neutral lipids and glycerophospholipids, respectively, combined and detected together. Besides, the SDDA strategy improved the detection of co-elution ions in the lipidomics analysis. A total of 554 potential lipids were detected by the developed approach in both positive and negative modes using ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Compared with the conventional liquid-liquid extraction (LLE) approaches, including methyl tert-butyl ether (MTBE) and Bligh-Dyer (BD) methods, 3PLE combined with SDDA significantly increased the lipid coverage 87.2% and 89.7%, respectively. Also, the proposed pseudotargeted lipidomics approach exhibited higher sensitivity and better repeatability than the untargeted approach. Finally, we applied the established pseudotargeted method to the plasma lipid profiling from the depressed rats and screened 61 differential variables. The results demonstrated that the pseudotargeted method based on 3PLE and SDDA broadened lipid coverage and improved the detection of co-elution ions with excellent sensitivity and precision, indicating significant potential for the lipidomics analysis.
    Keywords:  Depression; Liquiritin; Pseudotargeted lipidomics; Segment data-dependent acquisition; Three-phase liquid extraction
  15. J Chromatogr B Analyt Technol Biomed Life Sci. 2021 May 25. pii: S1570-0232(21)00275-0. [Epub ahead of print]1177 122794
      Nonylphenol (NP) is an endocrine disrupting and ecotoxic substance that has been detected in a variety of environmental matrices. It is utilized for the production of non-ionic nonylphenol ethoxylate (NPEO) detergents and other high production volume chemicals. Human biomonitoring data are scarce and mostly limited to the non-oxidized NP, which is ubiquitous in the (laboratory) environment and susceptible to external contamination. Here, we describe a sensitive, precise, accurate and rugged analytical method for the determination of OH-NP and oxo-NP, two potential alkyl-chain-oxidized metabolites of NP in human urine. We used single isomer standards, obtained by custom synthesis, for the quantification of the sum of the respective isomers. After enzymatic hydrolysis of potential urinary phase II conjugates, urine samples were analyzed by online turbulent flow chromatography for analyte enrichment and matrix depletion coupled to reversed phase liquid chromatography with negative electrospray-ionization triple quadrupole tandem mass spectrometry detection (online-SPE-LC-MS/MS). Quantification was performed by stable isotope dilution analysis. Limits of quantification in urinary matrix were 0.5 µg/L for OH-NP and 0.25 µg/L for oxo-NP. Mean relative recoveries were 101-105% (OH-NP) and 112-117% (oxo-NP) and the method imprecision (CV) in matrix was below 5%. In spite of extensive use restrictions in the EU since 2003, we could quantify OH-NP and oxo-NP in 94% and 47% of spot urine samples from the general German population (n = 32) collected in 2014. Thus, both metabolites seem suitable as sensitive and specific urinary biomarkers of NP exposure for future human biomonitoring population studies. Currently this method is used to quantitatively investigate human NP metabolism and to derive urinary metabolite excretion fractions that can be used to calculate external doses based on urinary biomarker concentrations.
    Keywords:  Alkylphenols; Exposure assessment; Human biomonitoring; Human urinary metabolite; Nonylphenol; Online-SPE-LC-MS/MS
  16. Methods Mol Biol. 2021 ;2275 379-391
      Untargeted lipidomics profiling by liquid chromatography -mass spectrometry (LC-MS) allows researchers to observe the occurrences of lipids in a biological sample without showing intentional bias to any specific class of lipids and allows retrospective reanalysis of data collected. Typically, and in the specific method described, a general extraction method followed by LC separation is used to achieve nonspecific class coverage of the lipidome prior to high resolution accurate mass (HRAM) MS detection . Here we describe a workflow including the isolation of mitochondria from liver tissue, followed by mitochondrial lipid extraction and the LC-MS conditions used for data acquisition. We also highlight how, in this method, all ion fragmentation can be used to identify species of lower abundances, often missed by data dependent fragmentation techniques. Here we describe the isolation of mitochondria from liver tissue, followed by mitochondrial lipid extraction and the LC-MS conditions used for data acquisition.
    Keywords:  Cardiolipins; HCD; LC-MS; Lipidomics; Lysophospholipids; Mitochondria
  17. J Chromatogr A. 2021 May 24. pii: S0021-9673(21)00401-5. [Epub ahead of print]1651 462277
      Cannabis is by far the most widely abused illicit drug globe wide. The analysis of its main psychoactive components in conventional and non-conventional biological matrices has recently gained a great attention in forensic toxicology. Literature states that its abuse causes neurocognitive impairment in the domains of attention and memory, possible macrostructural brain alterations and abnormalities of neural functioning. This suggests the necessity for the development of a sensitive and a reliable analytical method for the detection and quantification of cannabinoids in human biological specimens. In this review, we focus on a number of analytical methods that have, so far, been developed and validated, with particular attention to the new "golden standard" method of forensic analysis, liquid chromatography mass spectrometry or tandem mass spectrometry. In addition, this review provides an overview of the effective and selective methods used for the extraction and isolation of cannabinoids from (i) conventional matrices, such as blood, urine and oral fluid and (ii) alternative biological matrices, such as hair, cerumen and meconium.
    Keywords:  Cannabinoids; LC-MS/MS; Review; Tandem MS Spectroscopy; biological samples
  18. Rapid Commun Mass Spectrom. 2021 Jun 09. e9141
      RATIONALE: The World Antidoping Agency (WADA) Monitoring program concentrates analytical data from the WADA Accredited Laboratories for substances, which are not prohibited, but their potential misuse has to become known. The WADA List of Monitoring substances is updated annually, where substances may be removed, introduced or transferred to the Prohibited List, depending on prevalence of their use. Retroactive processing of old samples datafiles has the potential to create information for the prevalence of use of candidate substances for the Monitoring List in years before. MetAlign is a freeware software with functionality to reduce the size of Liquid Chromatography (LC) high resolution (HR) full scan (FS) mass spectrometry (MS) datafiles and to perform fast search for presence of substances in thousands of reduced datafiles.METHODS: Validation was performed to the search procedure of MetAlign applied to ADLQ screening LC-HR-FS-MS reduced datafiles originated from antidoping samples for tramadol (TRA), ecdysterone (ECDY) and ECDY metabolite 14-desoxyecdysterone (DESECDY) of the WADA Monitoring List. Searching parameters were related to combinations of accurate masses and retention times (RT).
    RESULTS: MetAlign search validation criteria were based on the creation of correct identifications, false positives (FP) and false negatives (FN). The search for TRA in 7,410 ADLQ routine LC-HR-FS-MS datafiles of the years 2017 to 2020 revealed no false identification (FP and FN) compared to the ADLQ WADA reports. ECDY and DESECDY detected by MetAlign search in approximately 5% of the same cohort of antidoping samples.
    CONCLUSIONS: MetAlign is a powerful tool for the fast-retroactive processing of old reduced datafiles collected in screening LC-HR-FS-MS to reveal prevalence of use of antidoping substances. The current study proposed the validation scheme of MetAlign search procedure, to be implemented per individual substance of the WADA Monitoring program, for the elimination of FNs and FPs.