bims-metlip Biomed News
on Methods and protocols in metabolomics and lipidomics
Issue of 2021‒10‒17
thirty papers selected by
Sofia Costa
Icahn School of Medicine at Mount Sinai

  1. Adv Exp Med Biol. 2021 ;1336 139-157
      This chapter discusses the fundamentals of gas chromatography (GC) to improve method development for metabolic profiling of complex biological samples. The selection of column geometry and phase ratio impacts analyte mass transfer, which must be carefully optimized for fast analysis. Stationary phase selection is critical to obtain baseline resolution of critical pairs, but such selection must consider important aspects of metabolomic protocols, such as derivatization and dependence of analyte identification on existing databases. Sample preparation methods are also addressed depending on the sample matrix, including liquid-liquid extraction and solid-phase microextraction.
    Keywords:  Comprehensive two-dimensional gas chromatography; Liquid-liquid extraction; Mass spectrometry; Metabolic profiling; Metabolomics; Sample preparation; Untargeted analysis
  2. Talanta. 2022 Jan 01. pii: S0039-9140(21)00749-9. [Epub ahead of print]236 122828
      Non-targeted metabolomics is increasingly applied in various applications for understanding biological processes and finding novel biomarkers in living organisms. However, high-confidence identity confirmation of metabolites in complex biological samples is still a significant bottleneck, especially when using single-stage mass analysers. In the current study, a complete workflow for alternating in-source fragmentation on a time-of-flight mass spectrometry (TOFMS) instrument for non-targeted metabolomics is presented. Hydrophilic interaction liquid chromatography (HILIC) was employed to assess polar metabolites in yeast following ESI parameter optimization using experimental design principles, which revealed the key influence of fragmentor voltage for this application. Datasets from alternating in-source fragmentation high resolution mass spectrometry (HRMS) were evaluated using open-source data processing tools combined with public reference mass spectral databases. The significant influence of the selected fragmentor voltages on the abundance of the primary analyte ion of interest and the extent of in-source fragmentation allowed an optimum selection of qualifier fragments for the different metabolites. The new acquisition and evaluation workflow was implemented for the non-targeted analysis of yeast extract samples whereby more than 130 metabolites were putatively annotated with more than 40% considered to be of high confidence. The presented workflow contains a fully elaborated acquisition and evaluation methodology using alternating in-source fragmentor voltages suitable for peak annotation and metabolite identity confirmation for non-targeted metabolomics applications performed on a single-stage HRMS platform.
    Keywords:  All-ions fragmentation; Deconvolution; Design of experiments; Metabolomics; Yeast
  3. Adv Exp Med Biol. 2021 ;1336 215-242
      Metabolomics studies rely on the availability of suitable analytical platforms to determine a vast collection of chemically diverse metabolites in complex biospecimens. Liquid chromatography-mass spectrometry operated under reversed-phase conditions is the most commonly used platform in metabolomics, which offers extensive coverage for nonpolar and moderately polar compounds. However, complementary techniques are required to obtain adequate separation of polar and ionic metabolites, which are involved in several fundamental metabolic pathways. This chapter focuses on the main mass-spectrometry-based analytical platforms used to determine polar and/or ionizable compounds in metabolomics (GC-MS, HILIC-MS, CE-MS, IPC-MS, and IC-MS). Rather than comprehensively describing recent applications related to GC-MS, HILIC-MS, and CE-MS, which have been covered in a regular basis in the literature, a brief discussion focused on basic principles, main strengths, limitations, as well as future trends is presented in this chapter, and only key applications with the purpose of illustrating important analytical aspects of each platform are highlighted. On the other hand, due to the relative novelty of IPC-MS and IC-MS in the metabolomics field, a thorough compilation of applications for these two techniques is presented here.
    Keywords:  Analytical platforms; CE-MS; GC-MS; HILIC; Ion chromatography; Ion pairing chromatography; Ionic compounds; Ionizable compounds; Metabolomics; Polar compounds
  4. Adv Exp Med Biol. 2021 ;1336 179-213
      Metabolomics is a discipline that offers a comprehensive analysis of metabolites in biological samples. In the last decades, the notable evolution in liquid chromatography and mass spectrometry technologies has driven an exponential progress in LC-MS-based metabolomics. Targeted and untargeted metabolomics strategies are important tools in health and medical science, especially in the study of disease-related biomarkers, drug discovery and development, toxicology, diet, physical exercise, and precision medicine. Clinical and biological problems can now be understood in terms of metabolic phenotyping. This overview highlights the current approaches to LC-MS-based metabolomics analysis and its applications in the clinical research.
    Keywords:  Biomarkers; Clinical research; LC-MS; Mass analyzers; Metabolomics; Sample preparation
  5. Adv Exp Med Biol. 2021 ;1336 159-178
      Capillary electrophoresis-mass spectrometry (CE-MS) is a very useful analytical technique for the selective and highly efficient profiling of polar and charged metabolites in a wide range of biological samples. Compared to other analytical techniques, the use of CE-MS in metabolomics is relatively low as the approach is still regarded as technically challenging and not reproducible. In this chapter, the possibilities of CE-MS for metabolomics are highlighted with special emphasis on the use of recently developed interfacing designs. The utility of CE-MS for targeted and untargeted metabolomics studies is demonstrated by discussing representative and recent examples in the biomedical and clinical fields. The potential of CE-MS for large-scale and quantitative metabolomics studies is also addressed. Finally, some general conclusions and perspectives are given on this strong analytical separation technique for probing the polar metabolome.
    Keywords:  Applications; Capillary electrophoresis; Interfacing designs; Mass spectrometry; Metabolomics
  6. Adv Exp Med Biol. 2021 ;1336 243-264
      The present chapter describes basic aspects of the main steps for data processing on mass spectrometry-based metabolomics platforms, focusing on the main objectives and important considerations of each step. Initially, an overview of metabolomics and the pivotal techniques applied in the field are presented. Important features of data acquisition and preprocessing such as data compression, noise filtering, and baseline correction are revised focusing on practical aspects. Peak detection, deconvolution, and alignment as well as missing values are also discussed. Special attention is given to chemical and mathematical normalization approaches and the role of the quality control (QC) samples. Methods for uni- and multivariate statistical analysis and data pretreatment that could impact them are reviewed, emphasizing the most widely used multivariate methods, i.e., principal components analysis (PCA), partial least squares-discriminant analysis (PLS-DA), orthogonal partial least square-discriminant analysis (OPLS-DA), and hierarchical cluster analysis (HCA). Criteria for model validation and softwares used in data processing were also approached. The chapter ends with some concerns about the minimal requirements to report metadata in metabolomics.
    Keywords:  Chromatography; Data analysis; Data processing; Data treatment; Mass spectrometry; Software tools; Statistical analysis; Untargeted metabolomics
  7. Anal Biochem. 2021 Oct 11. pii: S0003-2697(21)00310-9. [Epub ahead of print] 114409
      Nicotinamide adenine dinucleotide (NAD) is a key metabolic intermediate found in all cells and involved in numerous cellular functions. Perturbances in the NAD metabolome are linked to various diseases such as diabetes and schizophrenia, and to congenital malformations and recurrent miscarriage. Mouse models are central to the investigation of these and other NAD-related conditions because mice can be readily genetically modified and treated with diets with altered concentrations of NAD precursors. Simultaneous quantification of as many metabolites of the NAD metabolome as possible is required to understand which pathways are affected in these disease conditions and what are the functional consequences. Here, we report the development of a fit-for-purpose method to simultaneously quantify 26 NAD-related metabolites and creatinine in mouse plasma, whole blood, and liver tissue using ultra-high performance liquid chromatography - tandem mass spectrometry (UHPLC-MS/MS). The included metabolites represent dietary precursors, intermediates, enzymatic cofactors, and excretion products. Sample preparation was optimized for each matrix and included 21 isotope-labeled internal standards. The method reached adequate precision and accuracy for the intended context of use of exploratory pathway-related biomarker discovery in mouse models. The method was tested by determining metabolite levels in mice fed a special diet with defined precursor content.
    Keywords:  LC-MS/MS; Liver; Method development; NAD metabolism; Plasma; Vitamin B3
  8. Molecules. 2021 Sep 24. pii: 5787. [Epub ahead of print]26(19):
      In mass spectrometry (MS)-based metabolomics, missing values (NAs) may be due to different causes, including sample heterogeneity, ion suppression, spectral overlap, inappropriate data processing, and instrumental errors. Although a number of methodologies have been applied to handle NAs, NA imputation remains a challenging problem. Here, we propose a non-negative matrix factorization (NMF)-based method for NA imputation in MS-based metabolomics data, which makes use of both global and local information of the data. The proposed method was compared with three commonly used methods: k-nearest neighbors (kNN), random forest (RF), and outlier-robust (ORI) missing values imputation. These methods were evaluated from the perspectives of accuracy of imputation, retrieval of data structures, and rank of imputation superiority. The experimental results showed that the NMF-based method is well-adapted to various cases of data missingness and the presence of outliers in MS-based metabolic profiles. It outperformed kNN and ORI and showed results comparable with the RF method. Furthermore, the NMF method is more robust and less susceptible to outliers as compared with the RF method. The proposed NMF-based scheme may serve as an alternative NA imputation method which may facilitate biological interpretations of metabolomics data.
    Keywords:  mass spectrometry; metabolomics data; missing pattern; missing values imputation; non-negative matrix factorization; outliers
  9. Cell Rep. 2021 Oct 12. pii: S2211-1247(21)01297-3. [Epub ahead of print]37(2): 109833
      Glucose tolerance represents a complex phenotype in which many tissues play important roles and interact to regulate metabolic homeostasis. Here, we perform an analysis of 13C6-glucose tissue distribution, which maps the metabolome and lipidome across 12 metabolically relevant mouse organs and plasma, with integrated 13C6-glucose-derived carbon tracing during oral glucose tolerance test (OGTT). We measure time profiles of water-soluble metabolites and lipids and integrate the global metabolite response into metabolic pathways. During the OGTT, glucose use is turned on with specific kinetics at the organ level, but fasting substrates like β-hydroxybutyrate are switched off in all organs simultaneously. Timeline profiling of 13C-labeled fatty acids and triacylglycerols across tissues suggests that brown adipose tissue may contribute to the circulating fatty acid pool at maximal plasma glucose levels. The GTTAtlas interactive web application serves as a unique resource for the exploration of whole-body glucose metabolism and time profiles of tissue and plasma metabolites during the OGTT.
    Keywords:  13C; brown adipose tissue; de novo lipogenesis; glucose tolerance; lipidomics; metabolite cycling; metabolomics; metabolomics atlas; pathway analysis; tracer analysis
  10. J Am Soc Mass Spectrom. 2021 Oct 12.
      Differential mobility spectrometry (DMS) is highly useful for shotgun lipidomic analysis because it overcomes difficulties in measuring isobaric species within a complex lipid sample and allows for acyl tail characterization of phospholipid species. Despite these advantages, the resulting workflow presents technical challenges, including the need to tune the DMS before every batch to update compensative voltages settings within the method. The Sciex Lipidyzer platform uses a Sciex 5500 QTRAP with a DMS (SelexION), an LC system configured for direction infusion experiments, an extensive set of standards designed for quantitative lipidomics, and a software package (Lipidyzer Workflow Manager) that facilitates the workflow and rapidly analyzes the data. Although the Lipidyzer platform remains very useful for DMS-based shotgun lipidomics, the software is no longer updated for current versions of Analyst and Windows. Furthermore, the software is fixed to a single workflow and cannot take advantage of new lipidomics standards or analyze additional lipid species. To address this multitude of issues, we developed Shotgun Lipidomics Assistant (SLA), a Python-based application that facilitates DMS-based lipidomics workflows. SLA provides the user with flexibility in adding and subtracting lipid and standard MRMs. It can report quantitative lipidomics results from raw data in minutes, comparable to the Lipidyzer software. We show that SLA facilitates an expanded lipidomics analysis that measures over 1450 lipid species across 17 (sub)classes. Lastly, we demonstrate that the SLA performs isotope correction, a feature that was absent from the original software.
    Keywords:  DMS; flow injection; lipids; lipidyzer; shotgun lipidomics
  11. Int J Mol Sci. 2021 Sep 30. pii: 10598. [Epub ahead of print]22(19):
      Nicotinamide adenine dinucleotide (NAD+) and its reduced form (NADH) are coenzymes employed in hundreds of metabolic reactions. NAD+ also serves as a substrate for enzymes such as sirtuins, poly(ADP-ribose) polymerases (PARPs) and ADP-ribosyl cyclases. Given the pivotal role of NAD(H) in health and disease, studying NAD+ metabolism has become essential to monitor genetic- and/or drug-induced perturbations related to metabolic status and diseases (such as ageing, cancer or obesity), and its possible therapies. Here, we present a strategy based on liquid chromatography-tandem mass spectrometry (LC-MS/MS), for the analysis of the NAD+ metabolome in biological samples. In this method, hydrophilic interaction chromatography (HILIC) was used to separate a total of 18 metabolites belonging to pathways leading to NAD+ biosynthesis, including precursors, intermediates and catabolites. As redox cofactors are known for their instability, a sample preparation procedure was developed to handle a variety of biological matrices: cell models, rodent tissues and biofluids, as well as human biofluids (urine, plasma, serum, whole blood). For clinical applications, quantitative LC-MS/MS for a subset of metabolites was demonstrated for the analysis of the human whole blood of nine volunteers. Using this developed workflow, our methodology allows studying NAD+ biology from mechanistic to clinical applications.
    Keywords:  NAD+; mass spectrometry; metabolomics
  12. Talanta. 2022 Jan 01. pii: S0039-9140(21)00770-0. [Epub ahead of print]236 122849
      Lipidomics has great potential for the discovery of biomarkers, elucidation of metabolic processes and identifying dysregulations in complex biological systems. Concerning biofluids like plasma or cerebrospinal fluid, several studies for the comparison of lipid extraction solvents have already been conducted. With respect to tissues, which can differ significantly in terms of dry matter content and composition, only few studies are available. The proper selection of an extraction method that covers the complexity and individuality of different tissues is challenging. The goal of this work was to provide a systematic overview on the potential of different extraction methods for a broad applicability. This study covers six different extraction procedures and four different reconstitution solvents applied to ten different porcine tissues. To get an overview of the individual lipid profiles, a workflow was developed for a fast and reliable tentative lipid annotation. Therefore, several machine learning tools were utilized, like the prediction of collision cross sections to support the tentative lipid identification in case of untargeted lipidomics. In terms of data evaluation, unsupervised (e.g. principal component analysis) and supervised (e.g. partial least square - discriminant analysis) methods were applied to visualize and subsequently interpret all generated information. Furthermore, the influence of the tissue composition on the extraction performance was investigated. It could be shown that the ten porcine tissues can be distinguished based on their lipid profile with the applied workflow and that the methyl-tert-butyl ether (MTBE) based extraction method (two-phase) showed the best overall performance for the 16 examined lipid species. With this method the highest number of features (428 in lung tissue) could be annotated. Upcoming one-phase extractions also showed a high potential concerning total number of extracted lipids. Methanol/MTBE/chloroform (MMC) extracted slightly less lipids (393 in lung and liver) than MTBE but turned out to be the best one-phase extraction method. Additionally, the numbers of extracted lipids obtained by isopropanol/water 90:10 (IPA90) (399 in stomach) and by isopropanol/methanol/chloroform (IMC) (395 in stomach) were similar to those of the modified Folch method (402 in stomach). One-phase extractions can therefore clearly be seen as preferable when a high throughput is needed.
    Keywords:  Ion mobility; Mass spectrometry; One-phase extraction; Tissue extraction; Two-phase extraction; Untargeted lipidomics
  13. Anal Bioanal Chem. 2021 Oct 13.
      We introduce a new concept of yeast-derived biological matrix reference material for metabolomics research relying on in vivo synthesis of a defined biomass, standardized extraction followed by absolute quantification with isotope dilution. The yeast Pichia pastoris was grown using full control- and online monitoring fed-batch fermentations followed by fast cold methanol quenching and boiling ethanol extraction. Dried extracts served for the quantification campaign. A metabolite panel of the evolutionarily conserved primary metabolome (amino acids, nucleotides, organic acids, and metabolites of the central carbon metabolism) was absolutely quantified by isotope dilution utilizing uniformly labeled 13C-yeast-based internal standards. The study involved two independent laboratories employing complementary mass spectrometry platforms, namely hydrophilic interaction liquid chromatography-high resolution mass spectrometry (HILIC-HRMS) and gas chromatography-tandem mass spectrometry (GC-MS/MS). Homogeneity, stability tests (on a panel of >70 metabolites over a period of 6 months), and excellent biological repeatability of independent fermentations over a period of 2 years showed the feasibility of producing biological reference materials on demand. The obtained control ranges proved to be fit for purpose as they were either superior or comparable to the established reference materials in the field.
    Keywords:  Absolute quantification; Harmonization; Metabolomics; Pichia pastoris; Reference material; Targeted analysis
  14. Nat Biotechnol. 2021 Oct 14.
      Untargeted metabolomics experiments rely on spectral libraries for structure annotation, but, typically, only a small fraction of spectra can be matched. Previous in silico methods search in structure databases but cannot distinguish between correct and incorrect annotations. Here we introduce the COSMIC workflow that combines in silico structure database generation and annotation with a confidence score consisting of kernel density P value estimation and a support vector machine with enforced directionality of features. On diverse datasets, COSMIC annotates a substantial number of hits at low false discovery rates and outperforms spectral library search. To demonstrate that COSMIC can annotate structures never reported before, we annotated 12 natural bile acids. The annotation of nine structures was confirmed by manual evaluation and two structures using synthetic standards. In human samples, we annotated and manually validated 315 molecular structures currently absent from the Human Metabolome Database. Application of COSMIC to data from 17,400 metabolomics experiments led to 1,715 high-confidence structural annotations that were absent from spectral libraries.
  15. Biomed Chromatogr. 2021 Oct 14. e5262
      Furosemide is a diuretic drug used to increase urine flow in order to reduce the amount of salt and water in the body. It is commonly utilized to treat preterm infants with chronic lung disease of prematurity. There is a need for a simple and reliable quantitation of furosemide in human urine. We have developed and validated an ultra-high performance liquid chromatographic-tandem mass spectrometry method for furosemide quantitation in human urine with an assay range of 0.100 - 50.0 μg/mL. Sample preparation involved solid-phase extraction with 10 μL of urine. Intra-day accuracies and precisions for the quality control samples ranged from 94.5 - 106% and 1.86 - 10.2%, respectively, while inter-day accuracies and precision ranged from 99.2 - 102% and 3.38 - 7.41%, respectively. Recovery for furosemide had an average of 23.8%, with an average matrix effect of 101%. Furosemide was stable in human urine under the assay conditions. Stability for furosemide was shown at 1 week (room temperature, 4 °C, -20 °C, and -78 °C), 6 months (-78 °C), and through three freeze-thaw cycles. This robust assay demonstrates accurate and precise quantitation of furosemide in a small volume (10 μL) of human urine. It is currently implemented in an ongoing pediatric clinical study.
    Keywords:  LC-MS/MS; furosemide; pediatrics; solid phase extraction
  16. Anal Biochem. 2021 Oct 10. pii: S0003-2697(21)00314-6. [Epub ahead of print] 114413
      Measurement of Thrombin-activatable fibrinolysis inhibitor (TAFI) in human plasma is dependent on reproducible assays. To date, standards for measuring TAFI are frequently calibrated relative to pooled normal human plasma and arbitrarily assigned a potency of 100% TAFI, despite variation in TAFI concentrations between plasma pools. Alternatively, TAFI calibrators can be assigned a value in SI units but the approach used for value assignment is not consistent and furthermore, if purified TAFI is used to determine TAFI concentration in plasma, may be adversely affected by matrix effects. A TAFI plasma standard in mass units with traceability to the SI unit of mass is desirable. We report here the establishment of a quantitative mass spectrometry method for TAFI in plasma. Traceability is obtained by reference to calibrators that consist of blank plasma spiked with a defined amount of purified TAFI, value assigned by amino acid analysis. The calibrators are run alongside the samples, using the same preparation steps and conditions; an acetonitrile assisted tryptic digestion and multi-dimensional liquid chromatography (LC) separation followed by SRM-MS analysis. We measured the TAFI quantitatively in human plasma with reproducibility, reliability and precision, and demonstrated the applicability of this approach for value assigning a common reference standard.
    Keywords:  CBP2; Mass spectrometry; Pro-carboxypeptidase U; TAFI; Thrombin-activatable fibrinolysis inhibitor
  17. Ann Lab Med. 2022 Mar 01. 42(2): 121-140
      The process of method development for a diagnostic assay based on liquid chromatography-tandem mass spectrometry (LC-MS/MS) involves several disparate technologies and specialties. Additionally, method development details are typically not disclosed in journal publications. Method developers may need to search widely for pertinent information on their assay(s). This review summarizes the current practices and procedures in method development. Additionally, it probes aspects of method development that are generally not discussed, such as how exactly to calibrate an assay or where to place quality controls, using examples from the literature. This review intends to provide a comprehensive resource and induce critical thinking around the experiments for and execution of developing a clinically meaningful LC-MS/MS assay.
    Keywords:  Calibration; Internal Standards; Liquid Chromatography; Matrix Effects; Method Development; Quality Control; Sample Preparation; Tandem Mass Spectrometry
  18. Sci Rep. 2021 Oct 13. 11(1): 20322
      Early detection of cancer is one of the unmet needs in clinical medicine. Peripheral blood analysis is a preferred method for efficient population screening, because blood collection is well embedded in clinical practice and minimally invasive for patients. Lipids are important biomolecules, and variations in lipid concentrations can reflect pathological disorders. Lipidomic profiling of human plasma by the coupling of ultrahigh-performance supercritical fluid chromatography and mass spectrometry is investigated with the aim to distinguish patients with breast, kidney, and prostate cancers from healthy controls. The mean sensitivity, specificity, and accuracy of the lipid profiling approach were 85%, 95%, and 92% for kidney cancer; 91%, 97%, and 94% for breast cancer; and 87%, 95%, and 92% for prostate cancer. No association of statistical models with tumor stage is observed. The statistically most significant lipid species for the differentiation of cancer types studied are CE 16:0, Cer 42:1, LPC 18:2, PC 36:2, PC 36:3, SM 32:1, and SM 41:1 These seven lipids represent a potential biomarker panel for kidney, breast, and prostate cancer screening, but a further verification step in a prospective study has to be performed to verify clinical utility.
  19. J Pharm Biomed Anal. 2021 Sep 29. pii: S0731-7085(21)00513-6. [Epub ahead of print]207 114402
      Miltefosine is the only oral drug approved for the treatment of various clinical presentations of the neglected parasitic disease leishmaniasis. In cutaneous leishmaniasis and post-kala-azar dermal leishmaniasis, Leishmania parasites reside and multiply in the dermis of the skin. As miltefosine is orally administered and this drug is currently studied for the treatment of these skin-related types of leishmaniasis, there is an urgent need for an accurate assay to determine actual miltefosine levels in human skin tissue to further optimize treatment regimens through target-site pharmacokinetic studies. We describe here the development and validation of a sensitive method to quantify miltefosine in 4-mm human skin biopsies utilizing high-performance liquid chromatography coupled to tandem mass spectrometry. After the skin tissues were homogenized overnight by enzymatic digestion using collagenase A, the skin homogenates were further processed by protein precipitation and phenyl-bonded solid phase extraction. Final extracts were injected onto a Gemini C18 column using alkaline eluent for separation and elution. Detection was performed by positive ion electrospray ionization followed by a quadrupole - linear ion trap mass spectrometer, using deuterated miltefosine as an internal standard. The method was validated over a linear calibration range of 4-1000 ng/mL (r2 ≥ 0.9996) using miltefosine spiked digestion solution for calibration and quality control samples. Validation parameters were all within internationally accepted criteria, including intra- and inter-assay accuracies and precisions within± 15% and ≤ 15% (within± 20% and ≤ 20% at the lower limit of quantitation). There was no significant matrix effect of the human skin tissue matrix and the recovery for miltefosine, and internal standard were comparable. Miltefosine in human skin tissue homogenates was stable during the homogenization incubation (37 °C,± 16 h) and after a minimum of 10 days of storage at - 20 °C after the homogenization process. With our assay we could successfully detect miltefosine in skin biopsies from patients with post-kala azar dermal leishmaniasis who were treated with this drug in Bangladesh.
    Keywords:  Assay; Bioanalytical validation; Human skin tissue; Leishmaniasis; Miltefosine; Tandem mass spectrometry
  20. Anal Chim Acta. 2021 Oct 23. pii: S0003-2670(21)00795-9. [Epub ahead of print]1183 338969
      Ion mobility spectrometry is an important gas analysis method used in the rapid detection field. However, due to a lacking of explicit mathematical model of ion peak, it is difficult to extract characteristic analyte peaks from a spectrum containing overlapping peaks to achieve online qualitative analysis. Here, we present an asymmetric peak model for processing ion mobility peaks. For the asymmetric peak model, the key is to accurately estimate the standard deviation of the peak model and the fitting function of the tailing edge. We focused on the Coulombic effects on resolution of ion mobility spectrometry based on a new hypothesis of ion cloud shape and derived a formula for calculating the standard deviation taking the initial pulse width, diffusion and Coulomb repulsion factors into account. The proposed asymmetric peak model combines the advantages of optimal physical and chemical interpretation and explicit mathematical meaning. A fast decomposition method based on the peak model was developed to decompose overlapping peaks. Two overlapping simulated data sets and one real data set (a mixture of acetone and methyl salicylate) were used to test the method. The results indicated that our proposed method successfully decomposed the overlapping spectrum into individual peaks and performed markedly better than other three available methods in terms of the execution time. The proposed method meets the requirements for online qualitative analysis.
    Keywords:  Asymmetric peak model; Improved ion mobility resolution; Ion diffusion modeling; Peak deconvolution
  21. J Appl Lab Med. 2021 Oct 11. pii: jfab112. [Epub ahead of print]
      BACKGROUND: The circulating concentration of 1α,25-dihydroxyvitamin D [1α,25(OH)2D] is very low, and the presence of multiple isomers may lead to inaccurate quantitation if not separated prior to analysis. Antibody-based immunoextraction procedures are sometimes used to remove structurally related isomers of 1α,25(OH)2D prior to an LC-MS/MS analysis. However, immunoextraction increases sample preparation time and cost. In addition, some dihydroxyvitamin D metabolites are not completely removed by immunoextraction.METHOD: We developed an HPLC method using a phenyl-hexyl column to investigate interfering isomers of 1α,25(OH)2D.
    RESULT: Using this method, 4-phenyl-1,2,4-triazoline-3,5-dione (PTAD) derivatization product of 1α,25(OH)2D was found to be present as 2 epimers, which were separated chromatographically with an area ratio of 2:1. PTAD derivatized metabolite of 25-hydroxyvitamin D3 [i.e., 4β,25-dihydroxyvitamin D3 (4β,25(OH)2D3)] eluted out between 6R and 6S epimers of derivatized 1α,25(OH)2D3. If not chromatographically resolved, 4β,25(OH)2D can affect 1α,25(OH)2D quantitation. In a method comparison study, it was found that the presence of 4β,25(OH)2D produced positive bias up to 127% on 1α,25(OH)2D3 quantitation.
    CONCLUSION: The LC-MS/MS method we developed without an immunoextraction procedure was able to resolve the major interference peak from 1α,25(OH)2D and achieved reliable quantitation of 1α,25(OH)2D.
    Keywords:  1,25-dihydroxyvitamin D; 4β,25-dihydroxyvitamin D; LC-MS/MS; epimer; isomer interference
  22. Anal Bioanal Chem. 2021 Oct 13.
      Accurate measurement of plasma metanephrines (MNs) including metanephrine (MN) and normetanephrine (NMN) is crucial for the screening and diagnosis in pheochromocytomas and paragangliomas (PPGLs). Although the number of laboratories using liquid chromatography tandem mass spectrometry (LC-MS/MS) method to measure MNs has been increasing rapidly, those laboratory-developed assays showed incomparable results. There are no reference measurement procedures (RMPs) or reference materials (RMs) for MNs in Joint Committee for Traceability in Laboratory Medicine (JCTLM), which hindered the standardization of MNs measurement. We established a candidate RMP (cRMP) based on isotope dilution liquid chromatography tandem mass spectrometry (ID-LC/MS/MS) method for plasma MNs measurement. Plasma samples were spiked with MN-D3 and NMN-D3 as internal standards; protein precipitation and ion-exchange solid phase extraction (SPE) were performed to extract samples, eventually analyzed by LC-MS/MS. The cRMP was applied to evaluate two routine ID-LC/MS/MS methods through split-sample comparisons. Fifty-three individual patient samples were determined by cRMP and two routine ID-LC/MS/MS methods; results were analyzed by ordinary linear regression and Bland-Altman plots. The cRMP exhibited desirable imprecision, with intra-run and total imprecision (coefficient variation, CV) for MN being 0.79-1.36% and 1.53-1.87% and for NMN being 1.10-1.34% and 1.15-1.64%. The analytical recoveries of MN and NMN ranged from 98.3 to 101.7% and from 98.5 to 101.9%, respectively. Significant calibrator biases and sample-specific deviations were observed in method comparison. An accurate, precise, and reliable cRMP for plasma MNs was developed, and RMs with value assigned following the cRMP would help minimize the calibration bias and improve the comparability of different measuring systems.
    Keywords:  Consistency; Liquid chromatography tandem mass spectrometry; Metanephrines; Pheochromocytomas and paragangliomas; Recalibration; Reference measurement procedure
  23. Comput Biol Med. 2021 Sep 29. pii: S0010-4825(21)00705-8. [Epub ahead of print]138 104911
      Transcriptomics and metabolomics data often contain missing values or outliers due to limitations of the data acquisition techniques. Most of the statistical methods require complete datasets for downstream analysis. A number of methods have been developed for missing value imputation using the classical mean and variance based on maximum likelihood estimators, which are not robust against outliers. Consequently, the performance of these methods deteriorates in the presence of outliers. Hence precise imputation of missing values and outliers handling are both concurrently important. Therefore, in this paper, we developed a robust iterative approach using robust estimators based on the minimum beta divergence method, which simultaneously impute missing values and outliers. We investigate the performance of the proposed method in a comparison with six frequently used missing value imputation methods such as Zero, KNN, robust SVD, EM, random forest (RF) and weighted least square approach (WLSA) through feature selection using both simulated and real datasets. Ten performance indices were used to explore the optimal method such as Frobenius norm (FOBN), accuracy (ACC), sensitivity (SN), specificity (SP), positive predictive value (PPV), negative predictive value (NPV), detection rate (DR), misclassification error rate (MER), the area under the ROC curve (AUC) and computational runtime. Evaluation based on both simulated and real data suggests the superiority of the proposed method over the other traditional methods in terms of various rates of outliers and missing values. The suggested approach also keeps almost equal performance in absence of outliers with the other methods. The proposed method is accurate, simple, and consumes lower computational time compared to the other methods. Therefore, our recommendation is to apply the proposed procedure for large-scale transcriptomics and metabolomics data analysis. The computational tool has been implemented in an R package, which is publicly available from
    Keywords:  And beta weight function; GC-MS metabolomics Data; Missing values; Outliers; Robustness; Transcriptomics data
  24. J Vis Exp. 2021 Sep 23.
      Engineering cellular metabolism for targeted biosynthesis can require extensive design-build-test-learn (DBTL) cycles as the engineer works around the cell's survival requirements. Alternatively, carrying out DBTL cycles in cell-free environments can accelerate this process and alleviate concerns with host compatibility. A promising approach to cell-free metabolic engineering (CFME) leverages metabolically active crude cell extracts as platforms for biomanufacturing and for rapidly discovering and prototyping modified proteins and pathways. Realizing these capabilities and optimizing CFME performance requires methods to characterize the metabolome of lysate-based cell-free platforms. That is, analytical tools are necessary for monitoring improvements in targeted metabolite conversions and in elucidating alterations to metabolite flux when manipulating lysate metabolism. Here, metabolite analyses using high-performance liquid chromatography (HPLC) coupled with either optical or mass spectrometric detection were applied to characterize metabolite production and flux in E. coli S30 lysates. Specifically, this report describes the preparation of samples from CFME lysates for HPLC analyses using refractive index detection (RID) to quantify the generation of central metabolic intermediates and by-products in the conversion of low-cost substrates (i.e., glucose) to various high-value products. The analysis of metabolite conversion in CFME reactions fed with 13C-labeled glucose through reversed-phase liquid chromatography coupled to tandem mass spectrometry (MS/MS), a powerful tool for characterizing specific metabolite yields and lysate metabolic flux from starting materials, is also presented. Altogether, applying these analytical methods to CFME lysate metabolism enables the advancement of these systems as alternative platforms for executing faster or novel metabolic engineering tasks.
  25. Molecules. 2021 Sep 24. pii: 5798. [Epub ahead of print]26(19):
      Methylphenidate is a powerful central nervous system stimulant with a high potential for abuse in horse racing. The detection of methylphenidate use is of interest to horse racing authorities for both prior to and during competition. The use of hair as an alternative sampling matrix for equine anti-doping has increased as the number of detectable compounds has expanded. Our laboratory developed a liquid chromatography-high-resolution mass spectrometry method to detect the presence of methylphenidate in submitted samples. Briefly, hair was decontaminated, cut, and pulverized prior to liquid-liquid extraction in basic conditions before introduction to the LC-MS system. Instrumental analysis was conducted using a Thermo Q Exactive mass spectrometer using parallel reaction monitoring using a stepped collision energy to obtain sufficient product ions for qualitative identification. The method was validated and limits of quantitation, linearity, matrix effects, recovery, accuracy, and precision were determined. The method has been applied to confirm the presence of methylphenidate in official samples submitted by racing authorities.
    Keywords:  anti-doping; hair; horse; liquid chromatography–mass spectrometry; methylphenidate
  26. Talanta. 2022 Jan 01. pii: S0039-9140(21)00765-7. [Epub ahead of print]236 122844
      Tile-based Fisher ratio (F-ratio) analysis is emerging as a versatile data analysis tool for supervised discovery-based experimentation using comprehensive two-dimensional (2D) gas chromatography coupled with time-of-flight mass spectrometry (GC × GC-TOFMS). None the less, analyte identification can often be marred by poor 2D resolution and low analyte abundance relative to overlapping compounds. Linear algebra-based chemometric methods, in particular multivariate curve resolution alternating least squares (MCR-ALS), parallel factor analysis (PARAFAC) and PARAFAC2, are often applied in an effort to address this situation. However, these chemometric methods can fail to produce an accurate spectrum when the analyte is at low 2D resolution and/or in low relative abundance. To address this challenge, we introduce class comparison enabled mass spectrum purification (CCE-MSP), a method that utilizes the underlying requirement for signal consistency of the background interference compounds between the two classes in the F-ratio analysis to purify the mass spectrum of the analyte hits. CCE-MSP is validated using a dataset obtained for a neat JP-8 jet fuel spiked with 14 sulfur containing compounds at two levels (15 ppm and 30 ppm), using the p-value and lack-of-fit (LOF) for each analyte hit as consistency metrics. A purified mass spectrum was produced for each spiked analyte hit and their mass spectrum match value (MV) was compared to the MV obtained by MCR-ALS, PARAFAC, and PARAFAC2. The resulting MV for CCE-MSP were found to be as good or better than these chemometric methods, eg., for 2-butyl-5-ethylthiophene with an analyte-to-interference relative signal abundance of 1:87 and a 2D resolution of 0.2, CCE-MSP produced a MV of 831, compared to 476 for MCR-ALS, 403 for PARAFAC, and 336 for PARAFAC2. CCE-MSP is also extended to obtain the purified spectrum for more than one analyte, eg., two analyte hits in overlapping hit locations. The spectra produced by CCE-MSP can also be utilized as estimates to facilitate quantitative signal decomposition using MCR-ALS.
    Keywords:  Chemometrics; Comprehensive two-dimensional gas chromatography; MCR-ALS; Mass spectrum purification; Tile-based Fisher ratio analysis; Time-of-flight mass spectrometry
  27. Anal Bioanal Chem. 2021 Oct 14.
      With the increasing availability of high-resolution mass spectrometers, suspect screening and non-targeted analysis are becoming popular compound identification tools for environmental researchers. Samples of interest often contain a large (unknown) number of chemicals spanning the detectable mass range of the instrument. In an effort to separate these chemicals prior to injection into the mass spectrometer, a chromatography method is often utilized. There are numerous types of gas and liquid chromatographs that can be coupled to commercially available mass spectrometers. Depending on the type of instrument used for analysis, the researcher is likely to observe a different subset of compounds based on the amenability of those chemicals to the selected experimental techniques and equipment. It would be advantageous if this subset of chemicals could be predicted prior to conducting the experiment, in order to minimize potential false-positive and false-negative identifications. In this work, we utilize experimental datasets to predict the amenability of chemical compounds to detection with liquid chromatography-electrospray ionization-mass spectrometry (LC-ESI-MS). The assembled dataset totals 5517 unique chemicals either explicitly detected or not detected with LC-ESI-MS. The resulting detected/not-detected matrix has been modeled using specific molecular descriptors to predict which chemicals are amenable to LC-ESI-MS, and to which form(s) of ionization. Random forest models, including a measure of the applicability domain of the model for both positive and negative modes of the electrospray ionization source, were successfully developed. The outcome of this work will help to inform future suspect screening and non-targeted analyses of chemicals by better defining the potential LC-ESI-MS detectable chemical landscape of interest.
    Keywords:  Machine learning; Mass spectrometry; Non-targeted analysis; Predictive modeling; Random forest; Suspect screening analysis
  28. Talanta. 2022 Jan 01. pii: S0039-9140(21)00810-9. [Epub ahead of print]236 122889
      Phenolic compounds are an interesting class of natural products because of their proposed contribution to health benefits of foods and beverages and as a bio-source of organic (aromatic) building blocks. Phenolic extracts from natural products are often highly complex and contain compounds covering a broad range in molecular properties. While many 1D-LC and mass spectrometric approaches have been proposed for the analysis of phenolics, this complexity inevitably leads to challenging identification and purification. New insights into the composition of phenolic extracts can be obtained through online comprehensive two-dimensional liquid chromatography (LC × LC) coupled to photodiode array and mass spectrometric detection. However, several practical hurdles must be overcome to achieve high peak capacities and to obtain robust methods with this technique. In many LC × LC configurations, refocusing of analytes at the head of the 2D column is hindered by the high eluotropic strength of the solvent transferred from the 1D to the 2D, leading to peak breakthrough or broadening. LC × LC combinations whereby a purely aqueous mobile phase is used in the 1D and RPLC is used in the 2D are unaffected by these phenomena, leading to more robust methods. In this contribution, the combination of temperature-responsive liquid chromatography (TRLC) with RPLC is used for the first time for the analysis of phenolic extracts of natural origin to illustrate the potential of this alternative combination for natural product analyses. The possibilities of the combination are investigated through analysis of wine extracts by TRLC × RPLC-DAD and TRLC × RPLC-ESI-MS.
    Keywords:  Analyte refocusing; Comprehensive two-dimensional liquid chromatography (LC×LC); Flavonoids; Phenolics; Temperature-responsive liquid chromatography (TRLC); Wine
  29. Forensic Sci Int. 2021 Oct 06. pii: S0379-0738(21)00367-4. [Epub ahead of print]328 111047
      Hair drug testing can be used for the evaluation of cannabis use with a large detection window, and is required for professional driving license granting in Brazil. A positive hair result for cannabis use requires quantification of the metabolite THC-COOH above the cutoff value of 0.2 ng/g. The achievement of such lower limit of quantification is challenging, particularly with the use of liquid chromatography coupled to triple quadrupole mass spectrometers (LC-MS/MS). In this study, a very sensitive LCMS/ MS assay for the simultaneous quantification of THC-COOH along with THC, CBD, and CBN was developed and validated. Sample preparation was based on hair hydrolysis, followed by selective ion-exchange solid-phase extraction. The extraction yield was 101.5-101.6% for THC-COOH, 92.3-97.4% for THC, 89.7-95.2% for CBN, and 104.9-121.1% for CBD. Internal standard corrected matrix effects were - 2.7 to - 1,1 for THCCOOH and - 11.5 to - 0.1% for the other analytes. The lower limit of quantification was 01 ng/g for THC-COOH and 25 ng/g for THC, CBD, and CBN. The assay fulfilled validation guidelines acceptance criteria. The measurement uncertainties were determined and the assay was ISO17025 accredited, being currently used in routine testing.
    Keywords:  Cannabinoids; Hair analysis; LC-MS/MS; SPE; THC-COOH
  30. J Chromatogr B Analyt Technol Biomed Life Sci. 2021 Oct 04. pii: S1570-0232(21)00449-9. [Epub ahead of print]1183 122968
      Our previously reported, first validated, UPLC-MS/MS-based simultaneous analysis of five human milk B-vitamins revealed severe matrix effects. High levels of endogenous lactose fouled the electrospray ionization source affecting the analysis. We evaluated solid-phase extraction (SPE), liquid-solid extraction (LSE), protein precipitation (PPT), and liquid chromatography effluent diversion for lactose-removal. SPE failed to separate lactose from vitamins; LSE using 2-propanol reduced lactose and vitamin recoveries. PPT-solvent, milk volume, and reconstitution solvent influenced flavin adenine dinucleotide, pyridoxal and nicotinamide recoveries. Using an optimized LC-gradient enabled chromatographic separation of lactose from vitamins and its removal using a post-column switch-valve. Only 40 µL milk was subjected to methanol-PPT and non-polar matrix removal by methyl tert-butyl ether. B-vitamin recoveries were established (81.9-118.6%; CV ≤ 11.9%; precision: 4.9-13.7%) with greatly reduced matrix effects, and improved process efficiency, and recovery.
    Keywords:  B-vitamins; Human milk; Lactose; UPLC-MS/MS