bims-metlip 2023-01-29 papers

bims-metlip

Biomed News

on Methods and protocols in metabolomics and lipidomics

Issue of 2023‒01‒29
eighteen papers selected by
Sofia Costa
Matterworks

An isotope dilution-liquid chromatography-tandem mass spectrometry (ID-LC-MS/MS)-based candidate reference measurement procedure (RMP) for the quantification of gabapentin in human serum and plasma.
CCWeights: an R package and web application for automated evaluation and selection of weighting factors for accurate quantification using linear calibration curve.
Expanding our coverage: Strategies to detect a greater range of metabolites.
Liquid chromatography-mass spectrometry metabolite library for metabolomics: Evaluating column suitability using a scoring approach.
Unified and Standardized Mass Spectrometry Data Processing in Python Using spectrum_utils.
Lipid Spectrum Generator: A Simple Script for the Generation of Accurate In Silico Lipid Fragmentation Spectra.
A highly sensitive LC-MS/MS method for quantitative determination of 7 vitamin D metabolites in mouse brain tissue.
Quasi-continuous infrared matrix-assisted laser desorption electrospray ionization source coupled to a quadrupole time-of-flight mass spectrometer for direct analysis from well plates.
Enhanced correlation-based linking of biosynthetic gene clusters to their metabolic products through chemical class matching.
Data-Driven and Machine Learning-Based Framework for Image-Guided Single-Cell Mass Spectrometry.
Rapid Approximate Subset-Based Spectra Prediction for Electron Ionization-Mass Spectrometry.
Determination of endogenous sphingolipid content in stroke rats and HT22 cells subjected to oxygen-glucose deprivation by LC‒MS/MS.
Low-volume plasma sampling for determination of Dextromethorphan and Dextrorphan in Rat plasma: LC-MS/MS method and its application in pharmacokinetic study.
Development of a Gaussian-Based Alignment Algorithm for the Ultrahigh-Resolution Mass Spectra of Dissolved Organic Matter.
Development of a dispersive liquid-liquid microextraction for synthetic cathinones in biological fluids based on principles of Green Analytical Toxicology.
Serum metabolic profiling of rats infected with Clonorchis sinensis using LC-MS/MS method.
Identification of a frit-related sample carryover in newborn screening by tandem mass spectrometry.
Chiral Separation and Quantitation of Methylphenidate, Ethylphenidate and Ritalinic Acid in Blood using Supercritical Fluid Chromatography.

Clin Chem Lab Med. 2023 Jan 23.

An isotope dilution-liquid chromatography-tandem mass spectrometry (ID-LC-MS/MS)-based candidate reference measurement procedure (RMP) for the quantification of gabapentin in human serum and plasma.

Linda Salzmann, Janik Wild, Neeraj Singh, Tobias Schierscher, Franziska Liesch, Friederike Bauland, Andrea Geistanger, Lorenz Risch, Christian Geletneky, Christoph Seger, Judith Taibon.

  OBJECTIVES: To describe and validate a reference measurement procedure (RMP) for gabapentin, employing quantitative nuclear magnetic resonance (qNMR) spectroscopy to determine the absolute content of the standard materials in combination with isotope dilution-liquid chromatograph-tandem mass spectrometry (ID-LC-MS/MS) to accurately measure serum and plasma concentrations.METHODS: A sample preparation protocol based on protein precipitation in combination with LC-MS/MS analysis using a C8 column for chromatographic separation was established for the quantification of gabapentin. Assay validation and determination of measurement uncertainty were performed according to guidance from the Clinical and Laboratory Standards Institute, the International Conference on Harmonization, and the Guide to the expression of uncertainty in measurement. ID-LC-MS/MS parameters evaluated included selectivity, specificity, matrix effects, precision and accuracy, inter-laboratory equivalence, and uncertainty of measurement.
RESULTS: The use of qNMR provided traceability to International System (SI) units. The chromatographic assay was highly selective, allowing baseline separation of gabapentin and the gabapentin-lactam impurity, without observable matrix effects. Variability between injections, preparations, calibrations, and days (intermediate precision) was <2.3%, independent of the matrix, while the coefficient of variation for repeatability was 0.9-2.0% across all concentration levels. The relative mean bias ranged from -0.8-1.0% for serum and plasma samples. Passing-Bablok regression analysis indicated very good inter-laboratory agreement; the slope was 1.00 (95% confidence interval [CI] 0.98 to 1.03) and the intercept was -0.05 (95% CI -0.14 to 0.03). Pearson's correlation coefficient was ≥0.996. Expanded measurement uncertainties for single measurements were found to be ≤5.0% (k=2).
CONCLUSIONS: This analytical protocol for gabapentin, utilizing traceable and selective qNMR and ID-LC-MS/MS techniques, allows for the standardization of routine tests and the reliable evaluation of clinical samples.

Keywords:  ID-LC-MS/MS; gabapentin; qNMR; reference measurement procedure; standardization; traceability

DOI:  https://doi.org/10.1515/cclm-2022-0998
Bioinform Adv. 2021 ;1(1): vbab029

CCWeights: an R package and web application for automated evaluation and selection of weighting factors for accurate quantification using linear calibration curve.

Yonghui Dong, Tal Wachsman, Liat Morgan, Ehud Gazit, Rune Isak Dupont Birkler.

Summary: The accuracy of any analytical method is highly dependent on the selection of an appropriate calibration model. Here, we present CCWeights, an R package for automated assessment and selection of weighting factors for accurate quantification using linear calibration curve. Additionally, CCWeights includes a web application that allows users to analyze their data using an interactive graphical user interface, without any programming requirements. The workflow and features of CCWeights are illustrated by the analyses of two datasets acquired by liquid chromatography-mass spectrometry (LC-MS). The resulting quantification table can be directly utilized for further model assessment and subsequent data analysis.Availability and implementation: CCWeights is publicly available on CRAN repository (https://cran.r-project.org/web/packages/CCWeights), with source code available on GitHub (https://github.com/YonghuiDong/CCWeights) under a GPL-3 license. The web application can be run locally from R console using a simple command "runGui()". Alternatively, the web application can be freely accessed for direct online use at https://bcdd.shinyapps.io/CCWeights/.
Supplementary information: Supplementary data are available at Bioinformatics Advances online.

DOI: https://doi.org/10.1093/bioadv/vbab029
Curr Opin Plant Biol. 2023 Jan 21. pii: S1369-5266(22)00164-9. [Epub ahead of print]73 102335

Expanding our coverage: Strategies to detect a greater range of metabolites.

Saleh Alseekh, Alisdair R Fernie.

  Whilst the study of metabolites can arguably be traced back several hundred years it began in earnest in the 20th century with studies based on single metabolites or simple metabolic pathways. The advent of metabolomics and in particular the adoption of high-resolution mass spectrometry now means we can faithfully annotate and quantify in excess of 1000 plant metabolites. Whilst this is an impressive leap it falls well short of the estimated number of metabolites in the plant kingdom. This, whilst considerable and important insights have been achieved using commonly utilized approaches, there is a need to improve the coverage of the metabolome. Here, we review three largely complementary strategies (i) methods based on using chemical libraries (ii) methods based on molecular networking and (iii) approaches that link metabolomics and genetic variance. It is our contention that using all three approaches in tandem represents the best approach to tackle this challenge.

Keywords:  Mass spectrometry; Metabolite identification; Metabolome

DOI:  https://doi.org/10.1016/j.pbi.2022.102335
J Chromatogr A. 2023 Jan 11. pii: S0021-9673(23)00007-9. [Epub ahead of print]1690 463779

Liquid chromatography-mass spectrometry metabolite library for metabolomics: Evaluating column suitability using a scoring approach.

Dimitra Diamantidou, Ioannis Sampsonidis, Theodoros Liapikos, Helen Gika, Georgios Theodoridis.

  Untargeted metabolomic studies require an extensive set of analyte (metabolic) information to be obtained from each analyzed sample. Thus, highly selective, and efficient analytical methodologies together with reversed-phase (RP) or hydrophilic interaction liquid chromatography (HILIC) are usually applied in these approaches. Here, we present a performance comparison of five different chromatographic columns (C18, C8, RP Amide, zicHILIC, OH5 HILIC phases) to evaluate their sufficiency of analysis for a large analyte library, consisting of 817 authentic standards. By taking into account experimental chromatographic parameters (i.e. retention time, peak tailing and asymmetry, FWHM, signal-to-noise ratio and peak area and intensity), the proposed column scoring approach provides a simple criterion that may assist analysis in the select of a stationary phase for those metabolites of interest. RPLC methods offered better results regarding metabolic library coverage, while the zicHILIC stationary phase delivered a bigger number of properly eluted compounds. This study demonstrates the importance of choosing the most suitable configuration for the analysis of different metabolic classes.

Keywords:  Column comparison; Hydrophilic interaction liquid chromatography; MSMLS; Mass spectrometry; Reversed-phase chromatography

DOI:  https://doi.org/10.1016/j.chroma.2023.463779
J Proteome Res. 2023 Jan 23.

Unified and Standardized Mass Spectrometry Data Processing in Python Using spectrum_utils.

Wout Bittremieux, Lev Levitsky, Matteo Pilz, Timo Sachsenberg, Florian Huber, Mingxun Wang, Pieter C Dorrestein.

  spectrum_utils is a Python package for mass spectrometry data processing and visualization. Since its introduction, spectrum_utils has grown into a fundamental software solution that powers various applications in proteomics and metabolomics, ranging from spectrum preprocessing prior to spectrum identification and machine learning applications to spectrum plotting from online data repositories and assisting data analysis tasks for dozens of other projects. Here, we present updates to spectrum_utils, which include new functionality to integrate mass spectrometry community data standards, enhanced mass spectral data processing, and unified mass spectral data visualization in Python. spectrum_utils is freely available as open source at https://github.com/bittremieux/spectrum_utils.

Keywords:  Python; mass spectrometry; metabolomics; open source; proteomics

DOI:  https://doi.org/10.1021/acs.jproteome.2c00632
Anal Chem. 2023 Jan 24.

Lipid Spectrum Generator: A Simple Script for the Generation of Accurate In Silico Lipid Fragmentation Spectra.

David S Gertner, Jake P Violi, David P Bishop, Matthew P Padula.

Due to the complexity of lipids in nature, the use of in silico generated spectral libraries to identify lipid species from mass spectral data has become an integral part of many lipidomic workflows. However, many in silico libraries are either limited in usability or their capacity to represent lipid species. Here, we introduce Lipid Spectrum Generator, an open-source in silico spectral library generator specifically designed to aid in the identification of lipids in liquid chromatography-tandem mass spectrometry analysis.

DOI: https://doi.org/10.1021/acs.analchem.2c04518
Anal Bioanal Chem. 2023 Jan 27.

A highly sensitive LC-MS/MS method for quantitative determination of 7 vitamin D metabolites in mouse brain tissue.

Andrea Joy Stephenson, Benjamin Hunter, Paul Nicholas Shaw, Nur Sofiah Abu Kassim, Robert Trengove, Ryu Takechi, Virginie Lam, John Mamo.

  Despite its critical role in neurodevelopment and brain function, vitamin D (vit-D) homeostasis, metabolism, and kinetics within the central nervous system remain largely undetermined. Thus, it is of critical importance to establish an accurate, highly sensitive, and reproducible method to quantitate vit-D in brain tissue. Here, we present a novel liquid chromatography tandem mass spectrometry (LC-MS/MS) method and for the first time, demonstrate detection of seven major vit-D metabolites in brain tissues of C57BL/6J wild-type mice, namely 1,25(OH)2D3, 3-epi-1,25(OH)2D3, 1,25(OH)2D2, 25(OH)D3, 25(OH)D2, 24,25(OH)2D3, and 24,25(OH)2D2. Chromatographic separation was achieved on a pentaflurophenyl column with 3 mM ammonium formate water/methanol [A] and 3 mM ammonium formate methanol/isopropanol [B] mobile phase components. Detection was by positive ion electrospray tandem mass spectrometry with the EVOQ elite triple quadrupole mass spectrometer with an Advance ultra-high-performance liquid chromatograph and online extraction system. Calibration standards of each metabolite prepared in brain matrices were used to validate the detection range, precision, accuracy, and recovery. Isotopically labelled analogues, 1,25(OH)2D3-d3, 25(OH)D3-c5, and 24,25(OH)2D3-d6, served as the internal standards for the closest molecular-related metabolite in all measurements. Standards between 1 fg/mL and 10 ng/mL were injected with a resulting linear range between 0.001 and 1 ng, with an LLOD and LLOQ of 1 pg/mL and 12.5 pg/mL, respectively. The intra-/inter-day precision and accuracy for measuring brain vit-D metabolites ranged between 0.12-11.53% and 0.28-9.11%, respectively. Recovery in acetonitrile ranged between 99.09 and 106.92% for all metabolites. Collectively, the sensitivity and efficiency of our method supersedes previously reported protocols used to measure vit-D and to our knowledge, the first protocol to reveal the abundance of 25(OH)D2, 1,25(OH)D2, and 24,25(OH)2D2, in brain tissue of any species. This technique may be important in supporting the future advancement of pre-clinical research into the function of vit-D in neurophysiological and neuropsychiatric disorders, and neurodegeneration.

Keywords:  1,25(OH)D; 24,25(OH)D; 25(OH)D; 3-Epi-1,25(OH)D; Brain; Liquid chromatography tandem mass spectrometry; Vitamin D

DOI:  https://doi.org/10.1007/s00216-023-04527-8
J Mass Spectrom. 2023 Jan;58(1): e4902

Quasi-continuous infrared matrix-assisted laser desorption electrospray ionization source coupled to a quadrupole time-of-flight mass spectrometer for direct analysis from well plates.

Cristina Arciniega, Kenneth P Garrard, Jacob P Guymon, Jeffrey G Manni, Alex Apffel, John C Fjeldsted, David C Muddiman.

  High-throughput screening (HTS) is a technique mostly used by pharmaceutical companies to rapidly screen multiple libraries of compounds to find drug hits with biological or pharmaceutical activity. Mass spectrometry (MS) has become a popular option for HTS given that it can simultaneously resolve hundreds to thousands of compounds without additional chemical derivatization. For this application, it is convenient to do direct analysis from well plates. Herein, we present the development of an infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) source coupled directly to an Agilent 6545 for direct analysis from well plates. The source is coupled to a quadrupole time-of-flight (Q-TOF) mass spectrometer to take advantage of the high acquisition rates without sacrificing resolving power as required with Orbitrap or Fourier-transform ion cyclotron resonance (FTICR) instruments. The laser used for this source operates at 100 Hz, firing 1 pulse-per-burst, and delivers around 0.7 mJ per pulse. Continuously firing this laser for an extended duration makes it a quasi-continuous ionization source. Additionally, a metal capillary was constructed to extend the inlet of the mass spectrometer, increase desolvation of electrospray charged droplets, improve ion transmission, and increase sensitivity. Its efficiency was compared with the conventional dielectric glass capillary by measured signal and demonstrated that the metal capillary increased ionization efficiency due to its more uniformly distributed temperature gradient. Finally, we present the functionality of the source by analyzing tune mix directly from well plates. This source is a proof of concept for HTS applications using IR-MALDESI coupled to a different MS platform.

Keywords:  IR-MALDESI; Q-TOF mass spectrometer; ambient ionization; direct analysis

DOI:  https://doi.org/10.1002/jms.4902
Microbiome. 2023 Jan 23. 11(1): 13

Enhanced correlation-based linking of biosynthetic gene clusters to their metabolic products through chemical class matching.

Joris J R Louwen, Marnix H Medema, Justin J J van der Hooft.

  BACKGROUND: It is well-known that the microbiome produces a myriad of specialised metabolites with diverse functions. To better characterise their structures and identify their producers in complex samples, integrative genome and metabolome mining is becoming increasingly popular. Metabologenomic co-occurrence-based correlation scoring methods facilitate the linking of metabolite mass fragmentation spectra (MS/MS) to their cognate biosynthetic gene clusters (BGCs) based on shared absence/presence patterns of metabolites and BGCs in paired omics datasets of multiple strains. Recently, these methods have been made more readily accessible through the NPLinker platform. However, co-occurrence-based approaches usually result in too many candidate links to manually validate. To address this issue, we introduce a generic feature-based correlation method that matches chemical compound classes between BGCs and MS/MS spectra.RESULTS: To automatically reduce the long lists of potential BGC-MS/MS spectrum links, we match natural product (NP) ontologies previously independently developed for genomics and metabolomics and developed NPClassScore: an empirical class matching score that we also implemented in the NPLinker platform. By applying NPClassScore on three paired omics datasets totalling 189 bacterial strains, we show that the number of links is reduced by on average 63% as compared to using a co-occurrence-based strategy alone. We further demonstrate that 96% of experimentally validated links in these datasets are retained and prioritised when using NPClassScore.
CONCLUSION: The matching genome-metabolome class ontologies provide a starting point for selecting plausible candidates for BGCs and MS/MS spectra based on matching chemical compound class ontologies. NPClassScore expedites genome/metabolome data integration, as relevant BGC-metabolite links are prioritised, and researchers are faced with substantially fewer proposed BGC-MS/MS links to manually inspect. We anticipate that our addition to the NPLinker platform will aid integrative omics mining workflows in discovering novel NPs and understanding complex metabolic interactions in the microbiome. Video Abstract.

Keywords:  Chemical compound classification; Genome mining; Genomics; Metabolome mining; Metabolomics; Multi-omics; Natural products; Specialised metabolites

DOI:  https://doi.org/10.1186/s40168-022-01444-3
J Proteome Res. 2023 Jan 25.

Data-Driven and Machine Learning-Based Framework for Image-Guided Single-Cell Mass Spectrometry.

Yuxuan Richard Xie, Varsha K Chari, Daniel C Castro, Romans Grant, Stanislav S Rubakhin, Jonathan V Sweedler.

  Improved throughput of analysis and lowered limits of detection have allowed single-cell chemical analysis to go beyond the detection of a few molecules in such volume-limited samples, enabling researchers to characterize different functional states of individual cells. Image-guided single-cell mass spectrometry leverages optical and fluorescence microscopy in the high-throughput analysis of cellular and subcellular targets. In this work, we propose DATSIGMA (DAta-driven Tools for Single-cell analysis using Image-Guided MAss spectrometry), a workflow based on data-driven and machine learning approaches for feature extraction and enhanced interpretability of complex single-cell mass spectrometry data. Here, we implemented our toolset with user-friendly programs and tested it on multiple experimental data sets that cover a wide range of biological applications, including classifying various brain cell types. Because it is open-source, it offers a high level of customization and can be easily adapted to other types of single-cell mass spectrometry data.

Keywords:  data-driven analysis; machine learning; mass spectrometry; single-cell analysis

DOI:  https://doi.org/10.1021/acs.jproteome.2c00714
Anal Chem. 2023 Jan 25.

Rapid Approximate Subset-Based Spectra Prediction for Electron Ionization-Mass Spectrometry.

Richard Licheng Zhu, Eric Jonas.

Mass spectrometry is a vital tool in the analytical chemist's toolkit, commonly used to identify the presence of known compounds and elucidate unknown chemical structures. All of these applications rely on having previously measured spectra for known substances. Computational methods for predicting mass spectra from chemical structures can be used to augment existing spectral databases with predicted spectra from previously unmeasured molecules. In this paper, we present a method for prediction of electron ionization-mass spectra (EI-MS) of small molecules that combines physically plausible substructure enumeration and deep learning, which we term rapid approximate subset-based spectra prediction (RASSP). The first of our two models, FormulaNet, produces a probability distribution over chemical subformulae to achieve a state-of-the-art forward prediction accuracy of 92.9% weighted (Stein) dot product and database lookup recall (within top 10 ranked spectra) of 98.0% when evaluated against the NIST 2017 Mass Spectral Library. The second model, SubsetNet, produces a probability distribution over vertex subsets of the original molecule graph to achieve similar forward prediction accuracy and superior generalization in the high-resolution, low-data regime. Spectra predicted by our best model improve upon the previous state-of-the-art spectral database lookup error rate by a factor of 2.9×, reducing the lookup error (top 10) from 5.7 to 2.0%. Both models can train on and predict spectral data at arbitrary resolution. Source code and predicted EI-MS spectra for 73.2M small molecules from PubChem will be made freely accessible online.

DOI: https://doi.org/10.1021/acs.analchem.2c02093
Lipids Health Dis. 2023 Jan 25. 22(1): 13

Determination of endogenous sphingolipid content in stroke rats and HT22 cells subjected to oxygen-glucose deprivation by LC‒MS/MS.

Keqi Zeng, Xin Zhou, Wanyi Liu, Cong Nie, Yingfeng Zhang.

  BACKGROUND: Stroke is the leading cause of death in humans worldwide, and its incidence increases every year. It is well documented that lipids are closely related to stroke. Analyzing the changes in lipid content in the stroke model after absolute quantification and investigating whether changes in lipid content can predict stroke severity provides a basis for the combination of clinical stroke and quantitative lipid indicators.METHODS: This paper establishes a rapid, sensitive, and reliable LC‒MS/MS analytical method for the detection of endogenous sphingolipids in rat serum and brain tissue and HT22 cells and quantifies the changes in sphingolipid content in the serum and brain tissue of rats from the normal and pMCAO groups and in cells from the normal and OGD/R groups. Using sphingosine (d17:1) as the internal standard, a chloroform: methanol (9:1) mixed system was used for protein precipitation and lipid extraction, followed by analysis by reversed-phase liquid chromatography coupled to triple quadrupole mass spectrometry.
RESULTS: Based on absolute quantitative analysis of lipids in multiple biological samples, our results show that compared with those in the normal group, the contents of sphinganine (d16:0), sphinganine (d18:0), and phytosphingosine were significantly increased in the model group, except sphingosine-1-phosphate, which was decreased in various biological samples. The levels of each sphingolipid component in serum fluctuate with time.
CONCLUSION: This isotope-free and derivatization-free LC‒MS/MS method can achieve absolute quantification of sphingolipids in biological samples, which may also help identify lipid biomarkers of cerebral ischemia.

Keywords:  Content determination; Endogenous; Ischemic stroke; Liquid chromatography; Mass spectrometry; OGD/R-Induced; Sphingolipids

DOI:  https://doi.org/10.1186/s12944-022-01762-3
Biomed Chromatogr. 2023 Jan 25. e5588

Low-volume plasma sampling for determination of Dextromethorphan and Dextrorphan in Rat plasma: LC-MS/MS method and its application in pharmacokinetic study.

Praful Kumar Majhi, Samir Sayyad, Pratyush Mishra, Sainath Kamte, Rajanikant Sahu, Goutam Ghosh, Bharat Bhusan Subudhi.

  Dextromethorphan (DM) and its metabolite Dextrorphan (DX) continue to draw the attention of researchers to their diverse pharmacodynamics. Thus, there are possibilities for repurposing DM. Most of the pharmacodynamics of DM needs further validation in different preclinical models. Also, it is necessary to correlate pharmacodynamics with relevant pharmacokinetics data. Multiple bioanalytical techniques developed for this purpose primarily use a high sample processing volume. Since sample volume is a limiting factor for many preclinical models; an effort was taken to develop an alternative method suitable for handling low sample processing volume. Efficient solid phase extraction technique, robust liquid chromatographic (LC) separation and highly sensitive Tandem mass spectrometric detection (MS/MS) showed suitability for use of a 30μL sample processing volume. This led to the development of a highly specific, selective, accurate and precise-bio-analytical method for simultaneous quantification of DM and DX in rat plasma. The validated method was linear in the range of 0.196 ng/mL to 403.356 ng/mL for DM and 0.102 ng/mL to 209.017 ng/mL for DX. The application of the method was demonstrated through the estimation of pharmacokinetic parameters that showed good congruence with earlier studies.

Keywords:  Dextromethorphan; Dextrorphan; Tandem mass spectrometry; liquid chromatography; pharmacokinetic; preclinical

DOI:  https://doi.org/10.1002/bmc.5588
Anal Chem. 2023 Jan 23.

Development of a Gaussian-Based Alignment Algorithm for the Ultrahigh-Resolution Mass Spectra of Dissolved Organic Matter.

Qing-Long Fu, Manabu Fujii, Rui Ma.

The alignment of ultrahigh-resolution mass spectra (UHR-MS) is critical to inspect the presence of unique and common peaks across multiple UHR-MS spectra. However, few attempts have been conducted to develop an automated alignment method. In this study, a novel automated alignment algorithm, namely, FTMSCombine, that follows a Gaussian distribution of mass errors was developed and then integrated with existing FTMSCalibrate and TRFu algorithms to establish an open-source analysis platform, namely, FTMSAnalysis, for the UHR-MS analysis of the dissolved organic matter. The developed FTMSCombine was capable of automatically aligning peaks across different UHR-MS spectra by averaging the m/z values of each peak cluster, although the alignment should be restricted to Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) spectra collected by instruments under similar conditions. The FTMSCombine exhibited an insignificant difference in the reproducibility of chemical formulae but significantly higher mass accuracy than the ICBM-OCEAN. In addition to improving the overall mass accuracy of the whole UHR-MS dataset, the FTMSCombine could effectively exclude scatters or noise peaks using an optional rule that restricts peaks (continuously) detected in at least a certain number of spectra in the UHR-MS spectra dataset. The successfully established FTMSAnalysis (freely available in the Supporting Information of this study) is of great potential in automatically analyzing UHR-MS spectra for dissolved organic matter (DOM) and will largely facilitate the elucidation of DOM chemodivesity by UHR-MS techniques including FTICR-MS.

DOI: https://doi.org/10.1021/acs.analchem.2c04113
J Anal Toxicol. 2023 Jan 24. pii: bkad003. [Epub ahead of print]

Development of a dispersive liquid-liquid microextraction for synthetic cathinones in biological fluids based on principles of Green Analytical Toxicology.

André Luis Fabris, Rafael Lanaro, Jose Luiz Costa, Mauricio Yonamine.

  The present work describes a practical application of Green Analytical Toxicology (GAT) during the development of an eco-friendly dispersive liquid-liquid microextraction (DLLME) avoiding the use of highly toxic chlorinated solvents that are commonly used in this type of technique. The purpose was to further consolidate GAT guidelines during method development. Thus, a full method optimization using a multivariate statistical approach and validation were performed. To that end, synthetic cathinones (SC), one of the major classes of new psychoactive substances, were the target analytes due to their relevance and chemical diversity. Furthermore, whole blood and urine samples were the matrices of choice due to their clinical relevance. The sample preparation step prior to DLLME consisted of protein precipitation of whole blood samples, while urine specimens were centrifuged and diluted with ultrapure water. Then, borate buffer, NaCl, and ethyl acetate:acetonitrile were added and vortexed. Finally, vials were centrifuged and the organic layer was transferred to autosampler vials, evaporated to dryness and resuspended with mobile phase prior to injection into the ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) system. Once optimized, the proposed DLLME was fully validated: 0.2 and 1 ng/mL as LOD; and 1 and 10 ng/mL as LOQ for urine and blood samples, respectively. Linear range was established as 1-100 and 10-1000 ng/mL for urine and blood samples, respectively (r2 > 0.99), while bias and precision were within acceptable limits (≥ 80%). The matrix effect was of 1.9-260.2% and -12.3-139.6%; while recovery was of 27.4-60.0% and 13.0-55.2%; and process efficiency ranged from 45.0% to 192.0% and 17.9% to 58.4% for whole blood and urine, respectively. Finally, the method was applied to real case samples as proof of applicability. Thus, a simple, cheap, and fast eco-friendly technique to analyze SC in two biological specimens was described.

Keywords:  DLLME; GAT; Green Analytical Toxicology; LC-MS/MS; Mass spectrometry; NPS; New psychoactive substances; forensic toxicology; synthetic cathinones

DOI:  https://doi.org/10.1093/jat/bkad003
Front Cell Infect Microbiol. 2022 ;12 1040330

Serum metabolic profiling of rats infected with Clonorchis sinensis using LC-MS/MS method.

Su Han, Xiaoli Zhang, Jian Ding, Xiang Li, Xueli Zhang, Xu Jiang, Shanshan Duan, Beibei Sun, Xinyi Hu, Yannan Gao.

  Background: Clonorchiasis is an important foodborne parasitic disease. The omics-based-techniques could illuminate parasite biology and further make innovations in the research for parasitic diseases. However, knowledge about the serum metabolic profiles and related metabolic pathways in clonorchiasis is very limited.Methods: A untargeted ultra-high performance liquid tandem chromatography quadrupole time of flight mass spectrometry (UHPLC-QTOF-MS) was used to profile the serum metabolites of rats at both 4 and 8 weeks post infection (wpi) with Clonorchis sinensis (C. sinensis). Additionally, multivariate statistical analysis methods were employed to identify differential metabolites. Next, serum amino acids and phosphatidylcholines (PCs) levels were determined by targeted metabolomics analysis.
Result: A total of 10530 and 6560 ions were identified in ESI+ and ESI- modes. The levels of phosphatidylcholines, glycerophosphocholine and choline were significantly changed, with the shift in lipid metabolism. Significant changes were also observed in amino acids (isoleucine, valine, leucine, threonine, glutamate and glutamine). Targeted analysis showed that BCAAs (isoleucine, valine, leucine) levels significantly increased at 4 wpi and decreased at 8 wpi; threonine was increased at 8 wpi, whereas glutamate and glutamine showed a decreasing trend at 8 wpi. Additionally, the level of 17 PCs were significantly changed in infected rats. Marked metabolic pathways were involved in clonorchiasis, including glycerophospholipid metabolism, alanine, aspartate and glutamate metabolism, histidine metabolism and pyrimidine metabolism.
Conclusion: These results show that C. sinensis infection can cause significant changes in the rat serum metabolism, especially in amino acids and lipids. The metabolic signature together with perturbations in metabolic pathways could provide more in depth understanding of clonorchiasis and further make potential therapeutic interventions.

Keywords:  clonorchiasis; metabolic pathway; serum; targeted metabolomics; untargeted metabolomics

DOI:  https://doi.org/10.3389/fcimb.2022.1040330
J Mass Spectrom Adv Clin Lab. 2023 Jan;27 56-60

Identification of a frit-related sample carryover in newborn screening by tandem mass spectrometry.

Kyunghun Kim, Howon Lee, Jeong Joong Lee, Kyoungho Cha, Nam Hyun Park, Young Keun Shin, Hyojin Chae, Eun-Jee Oh.

  The need for high-throughput analysis of multiple analytes for inborn errors of metabolism in newborn screening (NBS) has led to the introduction of tandem mass spectrometry (MS/MS) into the NBS laboratory. In a flow-injection analysis (FIA), the predominant MS/MS method utilized for NBS, samples are introduced directly into the mass spectrometer without chromatographic separation. When a high-throughput FIA-based MS/MS method is implemented on newer generations of mass spectrometers with increased sensitivity, the risk of carryover and contamination increases. In the present study, we report the carryover of ornithine identified during the implementation of the NeoBase™ 2 (PerkinElmer) non-derivatized kits on the Xevo-TQD platform (Waters Corporation) and describe the source of the carryover, which was traced to the stainless-steel frit-type inline filter. Furthermore, a possible compound-dependent interaction with the stainless-steel frit is suggested based on the structure of ornithine and its effect on separation techniques. Investigation and mitigation of carryover can be a time and resource consuming process, and to this end, our report on identification of a stainless-steel frit as the source of delayed elution and carryover of ornithine should be recognized as a rare, albeit possible source of carryover in FIA-MS/MS methods adopted for NST.

Keywords:  Carryover; DBS, Dried blood spot; ESI, Electrospray ionization; FIA, Flow-injection analysis; FTN, Flow through needle; Flow injection analysis; H, high; HPLC, High performance liquid chromatography; IEM, Inborn errors of metabolism; IPA, Isopropanol; L, low; LC, Liquid chromatography; LLOQ, Lower limit of quantitation; MS, Mass spectrometer; MS/MS, Tandem mass spectrometry; NBS, Newborn screening; Newborn screening; Ornithine; PEEK, Polyetheretherketone; QC, Quality control; SM, Sample manager; TIC, Total ion chromatogram; Tandem mass spectrometry; UPLC, Ultra performance liquid chromatography; pI, Isoelectric point

DOI:  https://doi.org/10.1016/j.jmsacl.2023.01.001
Drug Test Anal. 2023 Jan 24.

Chiral Separation and Quantitation of Methylphenidate, Ethylphenidate and Ritalinic Acid in Blood using Supercritical Fluid Chromatography.

Christina Smith, Svante Vikingsson, Robert Kronstrand, Madeleine J Swortwood.

  Supercritical fluid chromatography is a technique that analyzes compounds that are temperature-labile, have moderately low weight, or chiral compounds. Methylphenidate (MPH) is a chiral compound with two chiral centers. MPH has two chiral metabolites, ethylphenidate (EPH) and ritalinic acid (RA). MPH is sold as a racemic mixture. The d- enantiomer of threo-MPH is responsible for medicinal effects. Due to the differing effects of the enantiomers, it is important to analyze the enantiomers individually to better understand their effects. This method utilizes SFC and solid-phase extraction (SPE) to separate and analyze the enantiomers of MPH, EPH and RA in postmortem blood. The objective of this method was to assess a unique approach with SFC for enantiomeric separation of MPH, EPH, and RA. A SPE method was developed and optimized to isolate the analytes in blood and validated as fit-for-purpose following international guidelines. The linear range for MPH and EPH was 0.25-25ng/mL and 10-1000ng/mL for RA in blood. Bias was -8.6 to 0.8% and precision was within 15.4% for all analytes. Following method validation, this technique was applied to the analysis of 49 authentic samples previously analyzed with an achiral method. Quantitative results for RA were comparable to achiral technique while there was loss of MPH and EPH over time. The l:d enantiomer ratio was calculated and MPH demonstrated greater abundance of the d enantiomer. This is the first known method to separate and quantify the enantiomers of all three analytes utilizing SFC and SPE.

Keywords:  chiral separation; methylphenidate; supercritical fluid chromatography

DOI:  https://doi.org/10.1002/dta.3446