bims-metlip Biomed News
on Methods and protocols in metabolomics and lipidomics
Issue of 2022–06–26
twenty-one papers selected by
Sofia Costa, Matterworks



  1. Metabolites. 2022 Jun 07. pii: 525. [Epub ahead of print]12(6):
      Gut microbial metabolites, short-chain fatty acids (SCFAs), are found at multiple locations in the host body and are identified as important metabolites in gut microbiome-associated diseases. Quantifying SCFAs in diverse biological samples is important to understand their roles in host health. This study developed an accurate SCFA quantification method by performing gas chromatography-mass spectrometry (GC/MS) in human plasma, serum, feces, and mouse cecum tissue. The samples were acidified with hydrochloric acid, and the SCFAs were extracted using methyl tert-butyl ether. In this method, distilled water was selected as a surrogate matrix for the quantification of SCFAs in target biological samples. The method was validated in terms of linearity, parallelism, precision, recovery, and matrix effect. The developed method was further applied in target biological samples. In conclusion, this optimized method can be used as a simultaneous SCFA quantification method in diverse biological samples.
    Keywords:  GC/MS; cecum tissue; feces; plasma; serum; short-chain fatty acids; surrogate matrix
    DOI:  https://doi.org/10.3390/metabo12060525
  2. Methods Mol Biol. 2022 ;2505 59-68
      Recent approaches developed in metabolomics using liquid chromatography-tandem mass spectrometry (LC-MS/MS) enabled us to assign a part of specialized metabolites in plants. However, the approaches are not good enough for the rest of the metabolites, which are still unknown. To characterize the unknown metabolites, more appropriate and precise approaches need to be developed. Here, a procedure to analyze 15N-labeled and nonlabeled LC-MS/MS data for identification of monoterpene indole alkaloids was developed.
    Keywords:  15N labeling; MS/MS similarity network analysis; Metabolomics; Monoterpene indole alkaloids; N-containing metabolites
    DOI:  https://doi.org/10.1007/978-1-0716-2349-7_4
  3. Methods Mol Biol. 2022 ;2505 33-43
      To understand how the plant regulates metabolism, it is important to determine where metabolites localize in the tissues and cells. Single-cell level omics approaches in plants have shown remarkable development over the last several years, and this data has been instrumental in gene discovery efforts for enzymes and transporters involved in metabolism. For metabolomics, Imaging Mass Spectrometry (IMS) is a powerful tool to map the spatial distribution of molecules in the tissue. Here, we describe the methods which we used to reveal where secondary metabolites, primarily alkaloids, localize in Catharanthus roseus stem and leaf tissues.
    Keywords:  Alkaloid; Apocynaceae; Catharanthus roseus; Idioblast cell; Imaging MS; Laticifer cell; Single-cell metabolomics; Specialized metabolism
    DOI:  https://doi.org/10.1007/978-1-0716-2349-7_2
  4. Bioinformatics. 2022 Jun 24. pii: btac407. [Epub ahead of print]
       MOTIVATION: Meticulous selection of chromatographic peak detection parameters and algorithms is a crucial step in preprocessing LC-MS data. However, as mass-to-charge ratio (m/z) and retention time shifts are larger between batches than within batches, finding apt parameters for all samples of a large-scale multi-batch experiment with the aim of minimizing information loss becomes a challenging task. Preprocessing independent batches individually can curtail said problems but requires a method for aligning and combining them for further downstream analysis.
    RESULTS: We present two methods for aligning and combining individually preprocessed batches in multi-batch LC-MS experiments. Our developed methods were tested on six sets of simulated and six sets of real datasets. Furthermore, by estimating the probabilities of peak insertion, deletion, and swap between batches in authentic datasets we demonstrate that retention order swaps are not rare in untargeted LC-MS data.
    AVAILABILITY: kmersAlignment and rtcorrectedAlignment algorithms are made available as an R package with raw data at https://metabocombiner.img.cas.cz.
    SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
    DOI:  https://doi.org/10.1093/bioinformatics/btac407
  5. Metabolites. 2022 Jun 04. pii: 519. [Epub ahead of print]12(6):
      Emerging technologies now allow for mass spectrometry-based profiling of thousands of small molecule metabolites ('metabolomics') in an increasing number of biosamples. While offering great promise for insight into the pathogenesis of human disease, standard approaches have not yet been established for statistically analyzing increasingly complex, high-dimensional human metabolomics data in relation to clinical phenotypes, including disease outcomes. To determine optimal approaches for analysis, we formally compare traditional and newer statistical learning methods across a range of metabolomics dataset types. In simulated and experimental metabolomics data derived from large population-based human cohorts, we observe that with an increasing number of study subjects, univariate compared to multivariate methods result in an apparently higher false discovery rate as represented by substantial correlation between metabolites directly associated with the outcome and metabolites not associated with the outcome. Although the higher frequency of such associations would not be considered false in the strict statistical sense, it may be considered biologically less informative. In scenarios wherein the number of assayed metabolites increases, as in measures of nontargeted versus targeted metabolomics, multivariate methods performed especially favorably across a range of statistical operating characteristics. In nontargeted metabolomics datasets that included thousands of metabolite measures, sparse multivariate models demonstrated greater selectivity and lower potential for spurious relationships. When the number of metabolites was similar to or exceeded the number of study subjects, as is common with nontargeted metabolomics analysis of relatively small cohorts, sparse multivariate models exhibited the most-robust statistical power with more consistent results. These findings have important implications for metabolomics analysis in human disease.
    Keywords:  metabolomics; multivariate; statistical methods; univariate
    DOI:  https://doi.org/10.3390/metabo12060519
  6. J Mass Spectrom. 2022 Jul;57(7): e4872
      Untargeted analyses in mass spectrometry imaging produce hundreds of ion images representing spatial distributions of biomolecules in biological tissues. Due to the large diversity of ions detected in untargeted analyses, normalization standards are often difficult to implement to account for pixel-to-pixel variability in imaging studies. Many normalization strategies exist to account for this variability, but they largely do not improve image quality. In this study, we present a new approach for improving image quality and visualization of tissue features by application of sequential paired covariance (SPC). This approach was demonstrated using previously published tissue datasets such as rat brain and human prostate with different biomolecules like metabolites and N-linked glycans. Data transformation by SPC improved ion images resulting in increased smoothing of biological features compared with commonly used normalization approaches.
    Keywords:  MSiReader; data visualization; heatmaps; mass spectrometry imaging; sequential paired covariance
    DOI:  https://doi.org/10.1002/jms.4872
  7. Toxins (Basel). 2022 Jun 02. pii: 387. [Epub ahead of print]14(6):
      Neurotoxin β-N-methylamino-L-alanine (BMAA) is hypothesized as an important pathogenic factor for neurodegenerative diseases such as amyotrophic lateral sclerosis/parkinsonism-dementia complex (ALS-PDC). Comparative study on the accuracy of BMAA analyzed by the regular LC-MS/MS methods is still limited for different biological matrices. In this study, a free-BMAA sample of cyanobacterium and BMAA-containing positive samples of diatom, mussel, scallop, and oyster were extracted with varied extraction ratios (ER) ranging from 1:20 to 1:2000. These extracts were then purified by MCX cartridges. After SPE purification, these different biological samples were analyzed by two common LC-MS/MS analysis methods, a direct analysis without derivatization by a hydrophilic interaction liquid chromatography (HILIC)-MS/MS and pre-column 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate (AQC) derivatization combined with a C18 column. The results suggested that the recoveries of BMAA spiked in the cyanobacterial sample were close to 100% in the total soluble form extracts with the ER of 1:100 (g/mL) and the precipitated bound form extracts with the ER of 1:500. The recommended ER for the precipitated bound form of BMAA in diatoms and the total soluble form of BMAA in mollusks are 1:500 and 1:50, respectively. The quantitative results determined by the AQC derivatization method were lower than those determined by the direct analysis of the HILIC method in diatom and mollusk samples. The results of the HILIC method without the derivatization process were closer to the true value of BMAA in cyanobacteria. This work contributes to the performance of the solid-phase extraction (SPE) purification protocol and the accuracy of BMAA analysis by LC-MS/MS in diverse biological samples.
    Keywords:  extraction ratio; liquid chromatography-tandem mass spectrometry (LC-MS/MS); matrix effect; solid-phase extraction (SPE) purification; β-N-methylamino-L-alanine
    DOI:  https://doi.org/10.3390/toxins14060387
  8. ACS Meas Sci Au. 2022 Jun 15. 2(3): 287-295
      Isobaric labeling in mass spectrometry enables multiplexed absolute quantitation and high throughput, while minimizing full scan spectral complexity. Here, we use 4-plex isobaric labeling with a fixed positive charge tag to improve quantitation and throughput for polar carboxylic acid metabolites. The isobaric tag uses an isotope-encoded neutral loss to create mass-dependent reporters spaced 2 Da apart and was validated for both single- and double-tagged analytes. Tags were synthesized in-house using deuterated formaldehyde and methyl iodide in a total of four steps, producing cost-effective multiplexing. No chromatographic deuterium shifts were observed for single- or double-tagged analytes, producing consistent reporter ratios across each peak. Perfluoropentanoic acid was added to the sample to drastically increase retention of double-tagged analytes on a C18 column. Excess tag was scavenged and extracted using hexadecyl chloroformate after reaction completion. This allowed for removal of excess tag that typically causes ion suppression and column overloading. A total of 54 organic acids were investigated, producing an average linearity of 0.993, retention time relative standard deviation (RSD) of 0.58%, and intensity RSD of 12.1%. This method was used for absolute quantitation of acid metabolites comparing control and type 1 diabetic urine. Absolute quantitation of organic acids was achieved by using one isobaric lane for standards, thereby allowing for analysis of six urine samples in two injections. Quantified acids showed good agreement with previous work, and six significant changes were found. Overall, this method demonstrated 4-plex absolute quantitation of acids in a complex biological sample.
    DOI:  https://doi.org/10.1021/acsmeasuresciau.1c00061
  9. J Chromatogr B Analyt Technol Biomed Life Sci. 2022 Jun 09. pii: S1570-0232(22)00234-3. [Epub ahead of print]1205 123330
      The aim of this study was to develop a quantitative method for the analysis of methylphenidate, the analog ethylphenidate and their metabolite ritalinic acid in oral fluid, using micro-QuEChERS extraction and liquid chromatography-tandem mass spectrometry (LC-MS/MS). Oral fluid samples were collected with Quantisal™ device, extracted by micro-QuEChERS technique and analyzed by LC-MS/MS. The developed method met the validation criteria of Academy Standards Board (ASB) Standard Practices for Method Validation in Forensic Toxicology (Standard 036, 2019) with limits of detection and quantification of 0.5 ng/mL and calibration curve from 0.5 to 50 ng/mL. Within-run imprecision was greater than 18.7% while between-run imprecision was greater than 17.0 % for all analytes. Bias did not vary more than 7.7 %. No evidence of carryover was found. Stability studies presented satisfactory results for 24 h on autosampler (10 °C), after 3 cycles of freeze/thaw, 7 days on freezer (-20 °C) and until 7 days on refrigerator (4 °C) for methylphenidate. The validated method was further successfully applied to the analysis of 5 authentic oral fluid samples collected from volunteers at parties and music festivals from different cities in Brazil. Four samples had positive results for methylphenidate and ritalinic acid, and only one sample was positive for methylphenidate. Ethylphenidate was not detected in the samples. The method showed acceptable analytical performance and is environmentally friendly, requiring reduced use of solvents and reagents, with potential to be applied to clinical and forensic analyses.
    Keywords:  Ethylphenidate; LC−MS/MS; Methylphenidate; Oral fluid; Ritalinic acid; Toxicological analysis
    DOI:  https://doi.org/10.1016/j.jchromb.2022.123330
  10. Metabolites. 2022 May 29. pii: 491. [Epub ahead of print]12(6):
      The number of metabolomics studies and spectral libraries for compound annotation (i.e., assigning possible compound identities to a fragmentation spectrum) has been growing steadily in recent years. Accompanying this growth is the number of mass spectra available for searching through those libraries. As the size of spectral libraries grows, accurate and fast compound annotation becomes more challenging. We herein report a prescreening algorithm that was developed to address the speed of spectral search under the constraint of low memory requirements. This prescreening has been incorporated into the Automated Data Analysis Pipeline Spectral Knowledgebase (ADAP-KDB) and can be applied to compound annotation by searching other spectral libraries as well. Performance of the prescreening algorithm was evaluated for different sets of parameters and compared to the original ADAP-KDB spectral search and the MSSearch software. The comparison has demonstrated that the new algorithm is about four-times faster than the original when searching for low-resolution mass spectra, and about as fast as the original when searching for high-resolution mass spectra. However, the new algorithm is still slower than MSSearch due to the relational database design of the former. The new search workflow can be tried out at the ADAP-KDB web portal.
    Keywords:  compound annotation; library search; metabolomics
    DOI:  https://doi.org/10.3390/metabo12060491
  11. Metabolites. 2022 Jun 09. pii: 532. [Epub ahead of print]12(6):
      The lack of effective screening strategies for high-grade serous carcinoma (HGSC), a subtype of ovarian cancer (OC) responsible for 70-80% of OC related deaths, emphasizes the need for new diagnostic markers and a better understanding of disease pathogenesis. Capillary electrophoresis (CE) coupled with high-resolution mass spectrometry (HRMS) offers high selectivity and sensitivity for ionic compounds, thereby enhancing biomarker discovery. Recent advances in CE-MS include small, chip-based CE systems coupled with nanoelectrospray ionization (nanoESI) to provide rapid, high-resolution analysis of biological specimens. Here, we describe the development of a targeted microchip (µ) CE-HRMS method, with an acquisition time of only 3 min and sample injection volume of 4nL, to analyze 40 target metabolites in serum samples from a triple-mutant (TKO) mouse model of HGSC. Extracted ion electropherograms showed sharp, baseline resolved peak shapes, even for structural isomers such as leucine and isoleucine. All calibration curves of the analytes maintained good linearity with an average R2 of 0.994, while detection limits were in the nM range. Thirty metabolites were detected in mouse serum with recoveries ranging from 78 to 120%, indicating minimal ionization suppression and good accuracy. We applied the µCE-HRMS method to biweekly-collected serum samples from TKO and TKO control mice. A time-resolved analysis revealed characteristic temporal trends for amino acids, nucleosides, and amino acid derivatives. These metabolic alterations are indicative of altered nucleotide biosynthesis and amino acid metabolism in HGSC development and progression. A comparison of the µCE-HRMS dataset with non-targeted ultra-high performance liquid chromatography (UHPLC)-MS results showed identical temporal trends for the five metabolites detected with both platforms, indicating the µCE-HRMS method performed satisfactorily in terms of capturing metabolic reprogramming due to HGSC progression while reducing the total data collection time three-fold.
    Keywords:  high-grade serous ovarian cancer; mass spectrometry; microchip capillary electrophoresis
    DOI:  https://doi.org/10.3390/metabo12060532
  12. Wei Sheng Yan Jiu. 2022 May;51(3): 476-482
       OBJECTIVE: To establish a rapid, accurate and sensitive method by liquid chromatography-tandem mass spectrometry with isotope internal standard dilution technique for the determination of chlorpromazine and promethazine and their metabolites in swine tissues.
    METHODS: The swine tissues sample was extracted with acetonitrile and purified on MCX cartridge. The liquid chromatography separation was performed on an ACQUITY UFLC® HSS T3(100 mm×2.1 mm, 1.8 μm) with a linear gradient elution program of 0.1%(V/V) fomic acid-acetonitrile and 0.1%(V/V) formic acid-water solution as the mobile phase. The analytes were analyzed using ESI operating in the positive multiple reaction monitoring(MRM) mode.
    RESULTS: The limits of quantitation(LOQs) and limits of detection(LODs) for the target objects were 0.12-0.51 μg/kg and 0.04-0.17 μg/kg, respectively. The calibration curves were linear in range of 0.1-20.0 μg/L for chlorpromazine and promethazine, and 0.5-100.0 μg/L for their metabolites(chlorpromazine sulfoxide and isopropyl sulfoxide). The recoveries were between 90.8%-106.0%, and the relative standard deviations(RSDs) were between 1.9%-6.2%(n=6).
    CONCLUSION: The method is highly sensitive and accurate, and is suitable for the analysis of chlorpromazine and promethazine and their metabolites(chlorpromazine sulfoxide and isopropyl sulfoxide) in swine tissues.
    Keywords:  chlorpromazine; chlorpromazine sulfoxide; isopropyl sulfoxide; liquid chromatography-tandem mass spectrometry(LC-MS/MS); promethazine; swine tissues
    DOI:  https://doi.org/10.19813/j.cnki.weishengyanjiu.2022.03.022
  13. Pharmaceutics. 2022 May 27. pii: 1141. [Epub ahead of print]14(6):
      Warfarin is extensively used for venous thromboembolism and other coagulopathies. In clinical settings, warfarin is administered as a mixture of S- and R-warfarin, and both enantiomers are metabolized by multiple cytochrome P450 enzymes into many hydroxylation metabolites. Due to the high degree of structural similarity of hydroxylation metabolites, their profile possesses significant challenges. The previous methods generally suffer from lacking baseline resolution and/or involving complex analysis processes. To overcome this limitation, a sensitive and specific chiral liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed to simultaneously identify warfarin and hydroxywarfarins enantiomers. Chromatographic separation was achieved on a HYPERSIL CHIRAL-OT column. The mass spectrometric detection was carried out in negative ion MRM mode with electrospray ionization source. The optimized method exhibited satisfactory within-run and between-run accuracy and precision with lower limit of quantification (LLOQ) of 10.0 ng/mL and 1.0 ng/mL for warfarin and 7-, 10(R)-OH-warfarin enantiomers, respectively. Linear responses of warfarin enantiomers and 7-, and 10(R)-OH-warfarin enantiomers in rat plasma were observed over the range of 10.0-8000 ng/mL, and 1.00-800 ng/mL, respectively. The analytes were shown to be stable in various experimental conditions in rat plasma. Protein precipitation was used in sample preparation without a matrix effect. This method was successfully applied to pharmacokinetic study for quantitating the concentrations of S/R-warfarin, S/R-7-OH-warfarin, and S/R-10(R)-OH-warfarin and relatively quantitating 3'-, 4-, 6-, and 8-OH warfarin enantiomers in rat plasma.
    Keywords:  LC-MS/MS; enantiomers; hydroxywarfarin; metabolites; warfarin
    DOI:  https://doi.org/10.3390/pharmaceutics14061141
  14. J Mass Spectrom Adv Clin Lab. 2022 Jun 11.
       Introduction: Remdesivir (GS-5734) is a nucleoside analog prodrug with antiviral activity against several single-stranded RNA viruses, including the novel severe respiratory distress syndrome virus 2 (SARS-CoV-2). It is currently the only FDA-approved antiviral agent for the treatment of individuals with COVID-19 caused by SARS-CoV-2. However, remdesivir pharmacokinetics/pharmacodynamics (PK/PD) and toxicity data in humans are extremely limited. It is imperative that precise analytical methods for the quantification of remdesivir and its active metabolite, GS-441524, are developed for use in further studies. We report, herein, the first validated anti-viral paper spray-mass spectrometry (PS-MS/MS) assay for the quantification of remdesivir and GS-441524 in human plasma. We seek to highlight the utility of PS-MS/MS technology and automation advancements for its potential future use in clinical research and the clinical laboratory setting.
    Methods: Calibration curves for remdesivir and GS-441524 were created utilizing seven plasma-based calibrants of varying concentrations and two isotopic internal standards of set concentrations. Four plasma-based quality controls were prepared in a similar fashion to the calibrants and utilized for validation. No sample preparation was needed. Briefly, plasma samples were spotted on a paper substrate contained within pre-manufactured plastic cassette plates, and the spots were dried for 1 hour. The samples were then analyzed directly for 1.2 minutes utilizing PS-MS/MS. All experiments were performed on a Thermo Scientific Altis triple quadrupole mass spectrometer utilizing automated technology.
    Results: The calibration ranges were 20 - 5000 and 100 - 25000 ng/mL for remdesivir and GS-441524, respectively. The calibration curves for the two antiviral agents showed excellent linearity (average R2 = 0.99 - 1.00). The inter- and intra-day precision (%CV) across validation runs at 4 QC levels for both analytes was less than 11.2% and accuracy (%bias) was within ±15%. Plasma calibrant stability was assessed and degradation for the 4°C and room temperature samples were seen beginning at Day 7. The plasma calibrants were stable at -20°C. No interference, matrix effects, or carryover was discovered during the validation process.
    Conclusions: PS-MS/MS represents a useful methodology for rapidly quantifying remdesivir and GS-441524, which may be useful for clinical PK/PD, therapeutic drug monitoring (TDM), and toxicity assessment, particularly during the current COVID-19 pandemic and future viral outbreaks.
    Keywords:  ANOVA, A one-way analysis of variance; AUC, area under the curve; CE, collision energy; CES1, carboxylesterase-1; CES2, carboxylesterase-2; CV, coefficient of variation; DMSO, dimethyl sulfoxide; EC50, half maximum effective concentration; ECMO, extracorporal membranous oxygenation; H-ESI, heated electrospray ionization; IRB, institutional review board; IS, internal standard; Inc, Incorporated; LC-MS/MS, liquid chromatography–mass spectrometry; LLC, Limited Liability Company; LLOQ, lower limit of quantitation; LOD, limit of detection; MP, monophosphate; PD, pharmacodynamics; PK, pharmacokinetics; PS-MS/MS, paper spray–mass spectrometry; QC, quality control; QC-LLOQ, quality control-lower limit of quantification; R2, coefficient of determination; RF, radio frequency; S/B, Signal-to-Blank; SARS-CoV-2; SIL, stable isotopically-labeled; SS, spiking solution; V., volts; antiviral; kV, kilovolts; m/z, mass-to-charge; mL, milliliter; mass spectrometry; ng, nanogram; paper spray; remdesivir; therapeutic drug monitoring, TDM; µL, microliter; µg, microgram
    DOI:  https://doi.org/10.1016/j.jmsacl.2022.06.001
  15. Food Addit Contam Part A Chem Anal Control Expo Risk Assess. 2022 Jun 21. 1-16
      Food additives are used in numerous food products and are characterised by various physicochemical properties. In European member states, their use in food is regulated by the European Union. This work aimed to develop an accurate and high-throughput analytical method enabling the simultaneous determination of additives from different functional classes to facilitate controls and generate occurrence data for exposure assessments. The QuEChERS principle was applied due to its ease of implementation and flexibility to adjust to various food matrices. However, very polar substances could not be extracted with sufficient recoveries. Consequently, an alternative basic methanol sample-preparation methodology was developed. After sample preparation, the obtained extracts were analysed using ultra-high-performance liquid chromatography coupled to tandem mass spectrometry (UHPLC-MS/MS). Overall, the developed methodology allowed the quantification of 27 additives from the functional classes of colours, sweeteners, preservatives, and antioxidants in various foods (e.g. beverages, dairies, processed meals). The methods were also validated in terms of selectivity, linearity, matrix effect, limit of quantification, accuracy, repeatability, and intra-laboratory reproducibility. Finally, the methods were successfully applied to eighty-four actual samples. All additives were found below authorised levels. However, irregularities were spotted in labelling.
    Keywords:  Food additives; QuEChERS; beverages; colours; dairies; preservatives; processed foods; sweeteners; tandem mass spectrometry; ultra-high performance liquid chromatography
    DOI:  https://doi.org/10.1080/19440049.2022.2085887
  16. J Anal Toxicol. 2022 Jun 24. pii: bkac044. [Epub ahead of print]
      In recent years, identification and analysis of designer benzodiazepines have become a challenge in forensic toxicology. These substances are analogues of the classic benzodiazepines, but their pharmacology is not well known, and many of them have been associated with overdoses and deaths. As a result, there has been a surge in efforts to develop analytical methods to determine these compounds in different biological samples. Our aim was to develop and validate a fast, sensitive, and specific method for determining 17 designer benzodiazepines (adinazolam, clobazam, clonazolam, delorazepam, deschloroetizolam, diclazepam, etizolam, flualprazolam, flubromazepam, flubromazolam, flunitrazolam, N-desmethylclobazam, nifoxipam, nitrazolam, meclonazepam, pyrazolam and zolazepam) in hair by liquid chromatography-tandem mass spectrometry (LC-MS-MS). Hair samples were decontaminated, pulverized, and a 20-mg aliquot was incubated in methanol in an ultrasound bath (1h, 25ºC). The supernatant was evaporated and reconstituted in 200 µL of mobile phase, and the extracts were filtered (nano-filter vials) before injection into LC-MS-MS. All analytes eluted from the chromatographic column in 8 min, and two multiple-reaction monitoring (MRM) transitions were used to identify each compound. The limits of quantification were 5 or 25 pg/mg, depending on the analyte, and calibration functions were linear to 200 pg/mg. Imprecision was <19.2% (n = 15) and bias was from -13.7 up to 18.3% (n = 15). All the analytes yielded high extraction efficiencies >70%, and displayed ion suppression between -62.8% and -23.9% (n = 10). The method was applied to 19 authentic cases. Five samples were positive for flualprazolam (<LOQ - >200 pg/mg) and/or etizolam (47.4-88.5 pg/mg). In conclusion, the present validated method has proven to be fast, sensitive, specific, and capable of determining 17 designer benzodiazepines in hair using LC-MS-MS.
    Keywords:  LC–MS-MS; designer benzodiazepines; etizolam; flualprazolam; hair
    DOI:  https://doi.org/10.1093/jat/bkac044
  17. Metabolites. 2022 May 30. pii: 497. [Epub ahead of print]12(6):
      MALDI imaging is a novel technique with which to study the pathophysiologies of diseases. Advancements in the field of metabolomics and lipidomics have been instrumental in mapping the signaling pathways involved in various diseases, such as cancer and neurodegenerative diseases (Parkinson's). MALDI imaging is flexible and can handle many sample types. Researchers primarily use either formalin-fixed paraffin-embedded (FFPE) or fresh frozen tissue samples to answer their scientific questions. FFPE samples allow for easy long-term storage, but the requirement for extensive sample processing may limit the ability to provide a clear picture of metabolite distribution in biological tissue. Frozen samples require less handling, but present logistical challenges for collection and storage. A few studies, mostly focused on cancer cell lines, have directly compared the results of MALDI imaging using these two tissue fixation approaches. Herein, we directly compared FFPE and fresh frozen sample preparation for murine skin samples, and performed detailed pathway analysis to understand how differences in processing impact MALDI results from otherwise identical tissues. Our results indicate that FFPE and fresh frozen methods differ significantly in the putative identified metabolite content and distribution. The fixation methods shared only 2037 metabolites in positive mode and only 4079 metabolites in negative ion mode. However, both fixation approaches allowed for downstream fluorescent staining, which may save time and resources for samples that are clinically precious. This work represents a direct comparison of the impacts of the two main tissue processing methods on subsequent MALDI-MSI. While our results are similar to previous work in cancer tissue, they provide novel insights for those using MALDI-MSI in skin.
    Keywords:  FFPE; IHC; MALDI-MSI; metabolites
    DOI:  https://doi.org/10.3390/metabo12060497
  18. J Environ Sci (China). 2022 Jul;pii: S1001-0742(22)00197-8. [Epub ahead of print]117 190-196
      Amino acids (AAs) are prevalent in source water, particularly during spring run-off. Monitoring of amino acids in source water is desirable for water treatment plants (WTP) to indicate changes in source water quality. The objective of this study was to establish analytical procedures for reliable monitoring of amino acids in source water. Therefore, we examined two different methods, large volume inject (LVI) and solid phase extraction (SPE), for sample preparation prior to HILIC-MS/MS. The LVI-HILIC-MS/MS method can provide fast and sensitive detection for clean samples, but suffers from matrix effects, resulting in irreproducible separation and shortening column lifetime. We have demonstrated that SPE was necessary prior to HILIC-MS/MS to achieve reproducible and reliable quantification of AAs in source water. A natural heterocyclic amine 1-methyl-1,2,3,4-tetrahydro-β-carboline-3-carboxylic acid (MTCCA) was also included in the method to indicate changes in other natural nitrogenous compounds in source water. The SPE-HILIC-MS/MS method was able to achieve limits of detection from 2.6-3400 ng/L for the amino acids and MTCCA with RSDs (n=3) of 1.1%-4.8%. As well, retention times (RT) of the analytes were reproducible with variation less than 0.01 min (n=3) through the entire project. We further applied the SPE-HILIC-MS/MS method to determine AAs in authentic source water samples collected from two drinking water treatment plants (WTPs) during the 2021 spring run-off season. The results support that the SPE-HILIC-MS/MS method does not require derivatization and can provide reliable, accurate, and robust analysis of AAs and MTCCA in source water, supporting future monitoring of source water quality.
    Keywords:  Amino acids; Disinfection byproducts; HILIC; HPLC; MS; Water analysis
    DOI:  https://doi.org/10.1016/j.jes.2022.04.025
  19. J Expo Sci Environ Epidemiol. 2022 Jun 24.
       BACKGROUND: The nasal mucosa, as a primary site of entry for inhaled substances, contains both inhaled xenobiotic and endogenous biomarkers. Nasal mucosa can be non-invasively sampled (nasal epithelial lining fluid "NELF") and analyzed for biological mediators. However, methods for untargeted analysis of compounds inhaled and/or retained in the nasal mucosa are needed.
    OBJECTIVES: This study aimed to develop a high resolution LC-MS untargeted method to analyze collected NELF. Profiling of compounds in NELF samples will also provide baseline data for future comparative studies to reference.
    METHODS: Extracted NELF analytes were injected to LC-ESI-MS. After spectrum processing, an in-house library provided annotations with high confidence, while more tentative annotation proposals were obtained via ChemSpider database matching.
    RESULTS: The established method successfully detected unique molecular signatures within NELF. Baseline profiling of 27 samples detected 2002 unknown molecules, with 77 and 463 proposed structures by our in-house library and Chemspider matching. High confidence annotations revealed common metabolites and tentative annotations implied various environmental exposure biomarkers are also present in NELF.
    SIGNIFICANCE: The experimental pipeline for analyzing NELF samples serves as simple and robust method applicable for future studies to characterize identities/effects of inhaled substances and metabolites retained in the nasal mucosa.
    IMPACT STATEMENT: The nasal mucosa contains exogenous and endogenous compounds. The development of an untargeted analysis is necessary to characterize the nasal exposome by deciphering the identity and influence of inhaled compounds on nasal mucosal biology. This study established a high resolution LC-MS based untargeted analysis of non-invasively collected nasal epithelial lining fluid. Baseline profiling of the nasal mucosa (n = 27) suggests the presence of environmental pollutants, along with detection of endogenous metabolites. Our results show high potential for the analytical pipeline to facilitate future respiratory health studies involving inhaled pollutants or pharmaceutical compounds and their effects on respiratory biology.
    Keywords:  Exposomics; Exposure biomarker; LC-MS; Metabolomics; Nasal epithelial lining fluid; Untargeted analysis
    DOI:  https://doi.org/10.1038/s41370-022-00448-3
  20. J Am Soc Mass Spectrom. 2022 Jun 24.
      Unconjugated sex steroids in human serum play a crucial role in physiological and pathological studies and are frequently considered as biomarkers in clinical diagnosis. Because of their low polarity, poor volatility, and low concentration, the rapid and highly sensitive analysis of sex steroids in real serum matrix by ambient mass spectrometry is still challenging. Here, Leidenfrost effect-assisted thermal desorption atmospheric pressure photoionization orbitrap mass spectrometry (LETD-APPI-MS) was developed and applied to quantify free sex steroids in human serum without derivatization and chromatography separation within a few minutes. The concentration of target analyte could be increased by approximately two orders during the LETD process. The limit of quantifications and detections of endogenous sex steroids in human serum were measured at the ppt level. In contrast with commonly used immunoassays in clinical laboratories, LETD-APPI-MS enables the accurate measurements of multiple free sex steroids without the interference of cross-reactions. The endogenous sex steroids of 38 female serums at four physiological stages during pregnancy were rapidly tested by LETD-APPI-MS, whose results were highly consistent with that using liquid chromatography-atmospheric pressure chemical ionization mass spectrometry (LC-APCI-MS), indicating LETD-APPI-MS has a strong clinical application potential in steroid analysis.
    Keywords:  Leidenfrost effect-assisted thermal desorption; atmospheric pressure photoionization; human serum; sex steroid quantification
    DOI:  https://doi.org/10.1021/jasms.2c00077
  21. Food Chem. 2022 Nov 01. pii: S0308-8146(22)01364-4. [Epub ahead of print]393 133402
      Fish is an important nutrition source because its lipids, which are rich in ω-3 fatty acids, are beneficial for human health. However, studies focusing on their detection, composition, and nutritional value are limited. In this study, we applied a non-targeted lipidomic approach based on ultra-high performance liquid chromatography coupled with linear-ion trap-Orbitrap mass spectrometry (UHPLC/LTQ-Orbitrap-MS) to comprehensively profile, compare, and detect unknown lipids in eleven types of dietary fish. A total of 287 molecular species from five major lipid classes were characterized by MS/MS analysis. Multivariate principal component analysis revealed the distinct lipid composition in shishamo smelt and Japanese sardine compared to other fish types. The assessment of nutritional indices based on the levels of free fatty acid suggested that among the eleven fish types, shishamo smelt is highly beneficial for health. Further, lipids such as N-acyl lysophosphatidylethanolamine were detected and characterized for the first time in fish fillets. Hierarchical cluster correlations indicated the predominance of glycerophospholipids (GPs) and sphingolipids in sardine, whereas fatty acyls and triacylglycerols (TAGs) were predominant in shishamo smelt. The high levels of polyunsaturated fatty acid-enriched GPs and TAGs in dietary fish endow it with great potential as a health-promoting food for human consumption. This study offers a comprehensive analysis of lipids and their compositions in fish fillets, demonstrating their potential use in the nutritional assessment of functional foods.
    Keywords:  Correlation analysis; Fish fillet; Lipidomics; Liquid chromatography; Mass spectrometry; N-acyl lyso-phosphatidylethanolamine; Nutritional indices
    DOI:  https://doi.org/10.1016/j.foodchem.2022.133402