bims-metlip 2021-12-05 papers

bims-metlip

Biomed News

on Methods and protocols in metabolomics and lipidomics

Issue of 2021–12–05
29 papers selected by
Sofia Costa, Icahn School of Medicine at Mount Sinai

Experimental design of a stable isotope labeling derivatized UHPLC-MS/MS method for the detection/quantification of primary/secondary bile acids in biofluids.
Neutron encoded derivatization of endothelial cell lysates for quantitation of aldehyde metabolites using nESI-LC-HRMS.
Comparison of Microflow and Analytical Flow Liquid Chromatography Coupled to Mass Spectrometry Global Metabolomics Methods Using a Urea Cycle Disorder Mouse Model.
An optimized LC-HRMS untargeted metabolomics workflow for multi-matrices investigations in the three-spined stickleback.
Cross-Laboratory Standardization of Preclinical Lipidomics Using Differential Mobility Spectrometry and Multiple Reaction Monitoring.
Kendrick Mass Defect Variation to Decipher Isotopic Labeling in Brain Metastases Studied by Mass Spectrometry Imaging.
Development of Liquid-Chromatography Tandem-Mass-Spectrometry Method for Determining Environmental Contamination by Powdered Medicinal Drugs in Pharmacies.
Dispersive liquid-liquid microextraction of 11-nor-Δ9-tetrahydrocannabinol-carboxylic acid applied to urine testing.
Boronic derivatization-based strategy for monoacylglycerol identification, isomer annotation and quantification.
Spectral entropy outperforms MS/MS dot product similarity for small-molecule compound identification.
MetEx, a Metabolomics Explorer Application for Natural Product Discovery.
Development of an analytical method to detect simultaneously 219 new psychoactive substances and 65 other substances in urine specimens using LC-QqQ MS/MS with CriticalPairFinder and TransitionFinder.
Tandem mass spectrometry approaches for recognition of isomeric compounds mixtures.
Validation of a robust and rapid liquid chromatography tandem mass spectrometric method for the quantitative analysis of navitoclax.
Mass Spectrometry based Metabolomics for Small Molecule Metabolites Mining and Confirmation as Potential Biomarkers for Schistosomiasis - Case of the Okavango Delta Communities in Botswana.
Automated Solid Phase Extraction and Polarity-Switching Tandem Mass Spectrometry Technique for High Throughput Analysis of Urine Biomarkers for 14 Tobacco-related Compounds.
Single-cell metabolomics hits its stride.
Bladder cancer biomarker screening based on non-targeted urine metabolomics.
Accelerating strain phenotyping with desorption electrospray ionization-imaging mass spectrometry and untargeted analysis of intact microbial colonies.
Mass spectrometry-based lipid analysis and imaging.
Stable Isotopes for Tracing Cardiac Metabolism in Diseases.
Isocratic HPLC analysis for the simultaneous determination of dNTPs, rNTPs and ADP in biological samples.
Mass Spectrometry Adduct Calculator.
Liquid chromatography coupled to Venturi easy ambient sonic spray ionization mass spectrometry.
Data mining of natural hazard biomarkers and metabolites with integrated metabolomic tools.
Multimodal Mass Spectrometry Imaging of Rat Brain Using IR-MALDESI and NanoPOTS-LC-MS/MS.
A novel method development and validation for determination of 2,4,6-Trinitrotoluene and its metabolites on LC-MS/MS.
GNPS Dashboard: collaborative exploration of mass spectrometry data in the web browser.
Identification of glycerophospholipids using self-built recognition software based on positive and negative ion high-resolution mass spectrometric fragmentation experiments.

J Pharm Biomed Anal. 2021 Nov 25. pii: S0731-7085(21)00596-3. [Epub ahead of print]209 114485

Experimental design of a stable isotope labeling derivatized UHPLC-MS/MS method for the detection/quantification of primary/secondary bile acids in biofluids.

Yoshio Muguruma, Ryosuke Nagatomo, Shihori Kamatsuki, Katsuyuki Miyabe, Go Asano, Hiroyasu Akatsu, Koichi Inoue.

  An efficient analytical platform is required to characterize the human metabolome in pathology. For this purpose, ultra-high performance liquid chromatography with tandem mass spectrometry (UHPLC-MS/MS) combined with chemical derivatization stands out as one of the most powerful techniques. A targeted metabolomics platform for 11 bile acids (BAs) profiling in human serum and bile samples using a stable isotope labeling derivatization (SILD) was applied. For SILD, the design of experiments (DoE) was employed to optimize the reaction conditions such five factors in three levels. The sample preparation built upon a liquid-liquid extraction requiring small volumes (20 μL). In application, the relation between the BA and short-chain fatty acid levels in human serum and bile samples from patients with bile duct diseases were investigated. The proposed method offers significant utility in the large-scale biological analyses of hepato-biliary-pancreatic-related diseases.

Keywords:  Bile; Bile acids; Design of experiments; Serum; Short-chain fatty acids; Stable isotope labeling derivatization; Ultrahigh performance liquid chromatography–tandem mass spectrometry

DOI:  https://doi.org/10.1016/j.jpba.2021.114485
Anal Chim Acta. 2022 Jan 15. pii: S0003-2670(21)01086-2. [Epub ahead of print]1190 339260

Neutron encoded derivatization of endothelial cell lysates for quantitation of aldehyde metabolites using nESI-LC-HRMS.

Michael Armbruster, Scott Grady, Julius Agongo, Christopher K Arnatt, James L Edwards.

  Biological aldehydes are difficult to analyze by electrospray ionization mass spectrometry due to their poor proton affinity and low biological concentrations. Chemical derivatization with stable isotope tags is used here for sample multiplexing, increased throughput, improved signal intensity, and quantitation. Nine quaternary amine tags with mass differences as low as 0.0058 Da had no observable chromatographic shifts, small amounts of ion suppression, and minimal matrix effects. Low concentration perfluoropentanoic acid was used as an ion pairing reagent to improve the retention of derivatized aldehydes. Perfluoropentanoic acid addition showed an average of three-fold improvement in limits of detection, 50% reduction in peak width, and 2.5 fold increase in analyte retention. Analysis of fifteen tagged aldehydes yielded an average of 13 nM limit of detection, 9 %RSD, R2 of 0.995, and linear dynamic range of 40-1000 nM. In a single 20 min separation, absolute quantitative data was obtained for 11 reactive aldehydes across 8 aortic endothelial cell samples. High glucose treatment produced significant changes to malondialdehyde, decanal, and (2E)-hexadecenal. These changes are consistent with glucose-induced oxidative stress. This method demonstrates that neutron encoded tagging of aldehydes is suitable for the analysis of complex samples.

Keywords:  Aldehyde; Derivatization; Multiplex; NeuCode

DOI:  https://doi.org/10.1016/j.aca.2021.339260
J Proteome Res. 2021 Nov 29.

Comparison of Microflow and Analytical Flow Liquid Chromatography Coupled to Mass Spectrometry Global Metabolomics Methods Using a Urea Cycle Disorder Mouse Model.

Sarah Geller, Harvey Lieberman, Adam J Belanger, Nelson S Yew, Alla Kloss, Alexander R Ivanov.

  Microscale-based separations are increasingly being applied in the field of metabolomics for the analysis of small-molecule metabolites. These methods have the potential to provide improved sensitivity, less solvent waste, and reduced sample-size requirements. Ion-pair free microflow-based global metabolomics methods, which we recently reported, were further compared to analytical flow ion-pairing reagent containing methods using a sample set from a urea cycle disorder (UCD) mouse model. Mouse urine and brain homogenate samples representing healthy, diseased, and disease-treated animals were analyzed by both methods. Data processing was performed using univariate and multivariate techniques followed by analyte trend analysis. The microflow methods performed comparably to the analytical flow ion-pairing methods with the ability to separate the three sample groups when analyzed by partial least-squares analysis. The number of detected metabolic features present after each data processing step was similar between the microflow-based methods and the ion-pairing methods in the negative ionization mode. The observed analyte trend and coverage of known UCD biomarkers were the same for both evaluated approaches. The 12.5-fold reduction in sample injection volume required for the microflow-based separations highlights the potential of this method to support studies with sample-size limitations.

Keywords:  LC-MS; metabolic profiling; metabolomics; microbore columns; microflow LC

DOI:  https://doi.org/10.1021/acs.jproteome.1c00628
PLoS One. 2021 ;16(11): e0260354

An optimized LC-HRMS untargeted metabolomics workflow for multi-matrices investigations in the three-spined stickleback.

Emmanuelle Lebeau-Roche, Gaëlle Daniele, Aurélie Fildier, Cyril Turies, Odile Dedourge-Geffard, Jean-Marc Porcher, Alain Geffard, Emmanuelle Vulliet.

Environmental metabolomics has become a growing research field to understand biological and biochemical perturbations of organisms in response to various abiotic or biotic stresses. It focuses on the comprehensive and systematic analysis of a biologic system's metabolome. This allows the recognition of biochemical pathways impacted by a stressor, and the identification of some metabolites as biomarkers of potential perturbations occurring in a body. In this work, we describe the development and optimization of a complete reliable methodology based on liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS) for untargeted metabolomics studies within a fish model species, the three-spined stickleback (Gasterosteus aculeatus). We evaluated the differences and also the complementarities between four different matrices (brain, gills, liver and whole fish) to obtain metabolome information. To this end, we optimized and compared sample preparation and the analytical method, since the type and number of metabolites detected in any matrix are closely related to these latter. For the sample preparation, a solid-liquid extraction was performed on a low quantity of whole fish, liver, brain, or gills tissues using combinations of methanol/water/heptane. Based on the numbers of features observed in LC-HRMS and on the responses of analytical standards representative of different metabolites groups (amino acids, sugars…), we discuss the influence of the nature, volume, and ratio of extraction solvents, the sample weight, and the reconstitution solvent. Moreover, the analytical conditions (LC columns, pH and additive of mobile phases and ionization modes) were also optimized so as to ensure the maximum metabolome coverages. Thus, two complementary chromatographic procedures were combined in order to cover a broader range of metabolites: a reversed phase separation (RPLC) on a C18 column followed by detection with positive ionization mode (ESI+) and a hydrophilic interaction chromatography (HILIC) on a zwitterionic column followed by detection with negative ionization mode (ESI-). This work provides information on brain, gills, liver, vs the whole body contribution to the stickleback metabolome. These information would help to guide ecotoxicological and biomonitoring studies.

DOI: https://doi.org/10.1371/journal.pone.0260354
Anal Chem. 2021 Dec 03.

Cross-Laboratory Standardization of Preclinical Lipidomics Using Differential Mobility Spectrometry and Multiple Reaction Monitoring.

Mohan Ghorasaini, Yassene Mohammed, Jerzy Adamski, Lisa Bettcher, John A Bowden, Matias Cabruja, Kévin Contrepois, Mathew Ellenberger, Bharat Gajera, Mark Haid, Daniel Hornburg, Christie Hunter, Christina M Jones, Theo Klein, Oleg Mayboroda, Mina Mirzaian, Ruin Moaddel, Luigi Ferrucci, Jacqueline Lovett, Kenneth Nazir, Mackenzie Pearson, Baljit K Ubhi, Daniel Raftery, Fabien Riols, Rebekah Sayers, Eric J G Sijbrands, Michael P Snyder, Baolong Su, Vidya Velagapudi, Kevin J Williams, Yolanda B de Rijke, Martin Giera.

Modern biomarker and translational research as well as personalized health care studies rely heavily on powerful omics' technologies, including metabolomics and lipidomics. However, to translate metabolomics and lipidomics discoveries into a high-throughput clinical setting, standardization is of utmost importance. Here, we compared and benchmarked a quantitative lipidomics platform. The employed Lipidyzer platform is based on lipid class separation by means of differential mobility spectrometry with subsequent multiple reaction monitoring. Quantitation is achieved by the use of 54 deuterated internal standards and an automated informatics approach. We investigated the platform performance across nine laboratories using NIST SRM 1950-Metabolites in Frozen Human Plasma, and three NIST Candidate Reference Materials 8231-Frozen Human Plasma Suite for Metabolomics (high triglyceride, diabetic, and African-American plasma). In addition, we comparatively analyzed 59 plasma samples from individuals with familial hypercholesterolemia from a clinical cohort study. We provide evidence that the more practical methyl-tert-butyl ether extraction outperforms the classic Bligh and Dyer approach and compare our results with two previously published ring trials. In summary, we present standardized lipidomics protocols, allowing for the highly reproducible analysis of several hundred human plasma lipids, and present detailed molecular information for potentially disease relevant and ethnicity-related materials.

DOI: https://doi.org/10.1021/acs.analchem.1c02826
Anal Chem. 2021 Dec 03.

Kendrick Mass Defect Variation to Decipher Isotopic Labeling in Brain Metastases Studied by Mass Spectrometry Imaging.

Landry Blanc, Gino B Ferraro, Michael Tuck, Brendan Prideaux, Véronique Dartois, Rakesh K Jain, Nicolas Desbenoit.

Besides many other applications, isotopic labeling is commonly used to decipher the metabolism of living biological systems. By giving a stable isotopically labeled compound as a substrate, the biological system will use this labeled nutrient as it would with a regular substrate and incorporate stable heavy atoms into new metabolites. Utilizing mass spectrometry, by comparing heavy atom enriched isotopic profiles and naturally occurring ones, it is possible to identify these metabolites and deduce valuable information about metabolism and biochemical pathways. The coupling of this approach with mass spectrometry imaging (MSI) allows one then to obtain 2D maps of metabolisms used by living specimens. As metabolic networks are convoluted, a global overview of the isotopically labeled data set to detect unexpected metabolites is crucial. Unfortunately, due to the complexity of MSI spectra, such untargeted processing approaches are difficult to decipher. In this technical note, we demonstrate the potential of a variation around the Kendrick analysis concept to detect the incorporation of stable heavy atoms into metabolites. The Kendrick analysis uses as a base unit the difference between the mass of the most abundant isotope and the mass of the corresponding stable isotopic tracer (namely, 12C and 13C). The resulting Kendrick plot offers an alternative method to process the MSI data set with a new perspective allowing for the rapid detection of the 13C-enriched metabolites and separating unrelated compounds. This processing method of MS data could therefore be a useful tool to decipher isotopic labeling and study metabolic networks, especially as it does not require advanced computational capabilities.

DOI: https://doi.org/10.1021/acs.analchem.1c03916
Inquiry. 2021 Jan-Dec;58:58 469580211059281

Development of Liquid-Chromatography Tandem-Mass-Spectrometry Method for Determining Environmental Contamination by Powdered Medicinal Drugs in Pharmacies.

Shiori Hasegawa, Ryoichi Inaba, Hiroki Nakamura, Yamato Kato, Satoshi Nakao, Kouseki Hirade, Takaaki Suzuki, Mari Iwata, Takeshi Kato, Kazuhiro Iguchi, Masahide Yamada, Atsushi Hioki, Mitsuhiro Nakamura.

  The environment and personnel are both exposed to powdered pharmaceuticals inside pharmacies. This makes developing new methods for rapidly determining such contaminants an important objective. In this study, we developed a liquid-chromatography tandem-mass-spectrometry (LC-MS/MS) method for the simultaneous qualitative and quantitative determination of powdered medicinal drugs, such as famotidine, risperidone, lansoprazole, olanzapine, haloperidol, clarithromycin, promethazine, levomepromazine, and chlorpromazine. The method involves the use of acetaminophen as the internal standard, an LC-MS/MS method with a core-shell column, and a 10 mM ammonium formate/acetonitrile gradient mobile phase. The analytes were separated within 14 min, and MS with an electrospray ionization source in positive-ion mode was used. The limits of detection for the 9 drugs were .1-8.4 ng/mL. Linear calibration curves in the 10-50 000 ng/mL range were constructed, and inter-day accuracies of 92.6-113.8% were determined for the 9 drugs. The coefficients of variation were less than 14.6%. These data suggest that the proposed method is applicable for the routine assaying of powdered-medicine contamination in pharmacies.

Keywords:  core–shell column; environmental contamination; liquid-chromatography tandem-mass-spectrometry; pharmacy; powdered medicinal drugs

DOI:  https://doi.org/10.1177/00469580211059281
Bioanalysis. 2022 Jan;14(2): 87-100

Dispersive liquid-liquid microextraction of 11-nor-Δ9-tetrahydrocannabinol-carboxylic acid applied to urine testing.

Leonardo C Rodrigues, Júlia Mm Kahl, Kauê O de Chinaglia, Eduardo G de Campos, José Luiz Costa.

  Aim: THC-COOH is the major metabolite of Δ9-tetrahydrocannabinol commonly tested in urine to determine cannabis intake. In this study, a method based on dispersive liquid-liquid microextraction was developed for testing THC-COOH in urine. Materials & methods: Hydrolyzed urine specimens were extracted via dispersive liquid-liquid microextraction with acetonitrile (disperser solvent) and chloroform (extraction solvent). Derivatization was performed with N,O-Bis(trimethylsilyl)trifluoroacetamide with 1% trichloro(chloromethyl)silane. Analysis was performed by GC-MS/MS. Results: The method showed acceptable linearity (5-500 ng/ml), imprecision (<10.5%) and bias (<4.9%). Limits of detection and quantitation were 1 and 5 ng/ml, respectively. Twenty-four authentic samples were analyzed, with 22 samples being positive for THC-COOH. Conclusion: The proposed method is more environmentally friendly and provided good sensitivity, selectivity and reproducibility.

Keywords:  GC–MS/MS; THC-COOH; cannabinoids; cannabis; clinical toxicology; dispersive liquid–liquid microextraction; forensic toxicology; green analytical toxicology

DOI:  https://doi.org/10.4155/bio-2021-0237
Anal Chim Acta. 2022 Jan 15. pii: S0003-2670(21)01059-X. [Epub ahead of print]1190 339233

Boronic derivatization-based strategy for monoacylglycerol identification, isomer annotation and quantification.

Mengle Zhu, Kegui Lu, Yiting Jin, Xiaowei Xu, Chengyu Chu, Haiping Hao, Qiuling Zheng.

  Monoacylglycerols (MAGs) are important signaling molecules involved in various diseases. However, it is challenge for direct detection of MAGs and isomers. Additionally, difficulties in isomer annotation hinders the comprehensive profiling of MAGs and hampers revealing isomers' contributions to diseases. Herein, a boronic derivatization-based strategy was developed for unambiguous identification, isomer annotation and quantification of MAGs in biological samples. 3-Nitrophenylboronic acid was selected as the derivatization reagent owing to its rapid and selective reactivity toward cis-diol moiety. First, a prediction model was established for MAG identification by the integration of m/z, isotopic distribution of boron, and retention time attributed by the carbon chain length and number of double bonds, which solved the difficulty of obtaining MAG standards. In addition, the designed derivatization reaction enabled the capture of thermally unstable sn-2 MAG isomers to ensure the chromatographic separation and direct MS detection. What's more, distinguished fragmentation patterns were discovered for derivatized MAG isomers, which allowed a novel and unambiguous isomer annotation. Furthermore, by considering the availability of standards, the quantification of MAGs was based on the development of calibration curves or relative quantification by internal standard. On this basis, the developed strategy was utilized for MAG identification and quantification in breast cancer samples, which suggested that MAGs could be regarded as potential biomarkers in breast cancer diagnosis or as indicators to trace the process of chemotherapy. It also helped make the puzzle complete by revealing that only one single isomer associated with the onset of disease was possible, instead of regarding them as a whole. Therefore, the boronic derivatization-based strategy facilitated the unambiguous identification, annotation and quantification of MAGs and isomers in biofluids, and would be beneficial for the mechanism studies of related diseases.

Keywords:  Boronic derivatization; Isomer annotation; Mass spectrometry; Monoacylglycerol; Quantification

DOI:  https://doi.org/10.1016/j.aca.2021.339233
Nat Methods. 2021 Dec 02.

Spectral entropy outperforms MS/MS dot product similarity for small-molecule compound identification.

Yuanyue Li, Tobias Kind, Jacob Folz, Arpana Vaniya, Sajjan Singh Mehta, Oliver Fiehn.

Compound identification in small-molecule research, such as untargeted metabolomics or exposome research, relies on matching tandem mass spectrometry (MS/MS) spectra against experimental or in silico mass spectral libraries. Most software programs use dot product similarity scores. Here we introduce the concept of MS/MS spectral entropy to improve scoring results in MS/MS similarity searches via library matching. Entropy similarity outperformed 42 alternative similarity algorithms, including dot product similarity, when searching 434,287 spectra against the high-quality NIST20 library. Entropy similarity scores proved to be highly robust even when we added different levels of noise ions. When we applied entropy levels to 37,299 experimental spectra of natural products, false discovery rates of less than 10% were observed at entropy similarity score 0.75. Experimental human gut metabolome data were used to confirm that entropy similarity largely improved the accuracy of MS-based annotations in small-molecule research to false discovery rates below 10%, annotated new compounds and provided the basis to automatically flag poor-quality, noisy spectra.

DOI: https://doi.org/10.1038/s41592-021-01331-z
ACS Chem Biol. 2021 Dec 03.

MetEx, a Metabolomics Explorer Application for Natural Product Discovery.

Brett C Covington, Mohammad R Seyedsayamdost.

Advances in next-generation DNA sequencing technologies, bioinformatics, and mass spectrometry-based metabolite detection have ushered in a new era of natural product discovery. Microbial secondary metabolomes are complex, especially when otherwise silent biosynthetic genes are activated, and there is therefore a need for data analysis software to explore and map the resulting multidimensional datasets. To that end, we herein report the Metabolomics Explorer (MetEx), a publicly available web application for the analysis of parallel liquid chromatography-coupled mass spectrometry (LC-MS)-based metabolomics data. MetEx is a highly interactive application that facilitates visualization and analysis of complex metabolomics datasets, consisting of retention time, m/z, and MS intensity features, as a function of hundreds of conditions or elicitors. The software enables prioritization of leads from three-dimensional maps, extraction of two-dimensional slices from various higher order plots, organization of datasets by elicitor chemotypes, customizable library-based dereplication, and automatically scored lead selection. We describe the application of MetEx to the first UPLC-MS-guided high-throughput elicitor screen in which Burkholderia gladioli was challenged with 750 elicitors, and the resulting profiles were interrogated by UPLC-Qtof-MS and subsequently analyzed with the app. We demonstrate the utility of MetEx by reporting elicitors for several cryptic metabolite groups and by uncovering new natural products that remain to be characterized. MetEx is available at https://mo.princeton.edu/MetEx/.

DOI: https://doi.org/10.1021/acschembio.1c00737
Talanta. 2022 Feb 01. pii: S0039-9140(21)00901-2. [Epub ahead of print]238(Pt 1): 122979

Development of an analytical method to detect simultaneously 219 new psychoactive substances and 65 other substances in urine specimens using LC-QqQ MS/MS with CriticalPairFinder and TransitionFinder.

Ju-Yu Chen, Guan-Yuan Chen, San-Yuan Wang, Cheng-Chung Fang, Lian-Yu Chen, Te-I Weng.

  Emerging new psychoactive substances (NPS) poses a great risk to public health. Analyzing these large numbers of NPS and other associated substances often relies on liquid chromatography coupled to triple quadrupole mass spectrometry (LC-QqQ-MS) with multiple-reaction monitoring (MRM) mode. However, the differentiation of critical pairs, coeluted isobaric and/or isomeric species, is one of the challenges for this analytical platform. MRM transitions with poor selectivity can jeopardize accurate quantification and lead to biased interpretation. Herein, we refined a novel workflow for developing an MRM-based method with in-house CriticalPairFinder and TransitionFinder tools for the effective identification of unique and selective MRM transitions. Transitions selected by TransitionFinder showed much better accuracies than those selected only by fragment abundance in some mixtures of critical pairs. Using the proposed analytical strategy, a method that can simultaneously determine 219 NPS and 65 other substances across a variety of NPS classes in urine samples was developed, validated and applied to analyze clinical urine samples. This automated workflow is anticipated to facilitate method development for analyzing complex analytes while considering selectivity.

Keywords:  CriticalPairFinder; Lc-ms; MRM; New psychoactive substances; TransitionFinder

DOI:  https://doi.org/10.1016/j.talanta.2021.122979
Mass Spectrom Rev. 2021 Nov 28. e21757

Tandem mass spectrometry approaches for recognition of isomeric compounds mixtures.

Sara Crotti, Marta Menicatti, Marco Pallecchi, Gianluca Bartolucci.

  The present review aims to collect the published literature pertaining the recognition of isobaric compounds (isomers or stereoisomers) using the features of tandem mass spectrometry (MS) experiments without any chromatographic separation or chemical modification (derivatization or isotopic enrichment) of the analytes. MS/MS methods possess high selectivity, wide dynamic range and high throughput capabilities. Generally, tandem MS has limited capability for distinguishing isomers that fragment similarly. However, some MS/MS methods have been developed and positively applied to isomers discrimination. Among the literature on this topic, the applications that fit on the review subject can be summarized as follow: (1) chiral discrimination by the kinetic method, (2) the use energy-resolved tandem mass spectra and the survival yield (SY) representation, (3) the kinetics evaluation of the ion-molecule interaction and (4) the postprocessing mathematical algorithm to resolve the isomers in MS/MS signal.

Keywords:  LEDA; MS/MS; ion-molecule interaction; isomers; kinetic method; survival yield

DOI:  https://doi.org/10.1002/mas.21757
Biomed Chromatogr. 2021 Nov 30. e5289

Validation of a robust and rapid liquid chromatography tandem mass spectrometric method for the quantitative analysis of navitoclax.

Susan C Scott, Nicole M Anders, Ping He, Avelina Hemingway, Steven D Gore, Christine L Hann, Michelle A Rudek.

  The Bcl-2 family small molecule inhibitor navitoclax is being clinically evaluated to treat multiple cancers including lymphoid malignancies and small cell lung cancer. A sensitive and reliable method was developed to quantitate navitoclax in human plasma using liquid chromatography with tandem mass spectrometry to perform detailed pharmacokinetic studies. Sample preparation involved protein precipitation using acetonitrile. Separation of navitoclax and the internal standard, navitoclax-d8, was achieved with a Waters Acquity UPLC BEH C18 column using isocratic flow over a 3 minute total analytical run time. A SCIEX 4500 triple quadrupole mass spectrometer operated in positive electrospray ionization mode was used for the detection of navitoclax. The assay range was 5-5000 ng/mL and proved to be accurate (89.5-104.9%) and precise (CV ≤11%). Long-term frozen plasma stability for navitoclax at -70°C has been determined for at least 34 months. The method was applied for the measurement of total plasma concentrations of navitoclax in a patient with receiving a 250 mg daily oral dose.

Keywords:  navitoclax; quantitative analysis; tandem mass spectrometry; validation

DOI:  https://doi.org/10.1002/bmc.5289
Expert Rev Proteomics. 2021 Nov 30.

Mass Spectrometry based Metabolomics for Small Molecule Metabolites Mining and Confirmation as Potential Biomarkers for Schistosomiasis - Case of the Okavango Delta Communities in Botswana.

Sedireng M Ndolo, Matshediso Zachariah, Lebotse Molefi, Nthabiseng Phaladze, Kwenga F Sichilongo.

   INTRODUCTION: Metabolomics for identifying schistosomiasis biomarkers in non-invasive samples at various infection stages is being actively explored. The literature on the traditional detection of schistosomiasis in human specimens is well documented. However, state-of-the-art technologies based on mass spectrometry have simplified the use of biomarkers for diagnostics. This review examines methods currently in use for the metabolomics of small molecules using separation science and mass spectrometry.
AREA COVERED: This article highlights the evolution of traditional diagnostic methods for schistosomiasis based on inter alia microscopy, immunology, and polymerase chain reaction. An exhaustive literature search of metabolite mining, focusing on separation science and mass spectrometry, is presented. A comparative analysis of mass spectrometry methods was undertaken, including a projection for the future.
EXPERT COMMENTARY: Mass spectrometry metabolomics for schistosomiasis will lead to biomarker discovery for non-invasive human samples. These biomarkers, together with those from other neglected tropical diseases, such as malaria and sleeping sickness, could be incorporated as arrays on a single biosensor chip and inserted into smartphones, in order to improve surveillance, monitoring, and management.

Keywords:  Biomarker; Botswana; GC-MS; LC-MS; Mass Spectrometry; Metabolomics; Okavango Delta; Schistosomiasis

DOI:  https://doi.org/10.1080/14789450.2021.2012454
ACS Omega. 2021 Nov 23. 6(46): 30901-30909

Automated Solid Phase Extraction and Polarity-Switching Tandem Mass Spectrometry Technique for High Throughput Analysis of Urine Biomarkers for 14 Tobacco-related Compounds.

Sujeewa C Piyankarage, Ernest McGahee, June Feng, Benjamin C Blount, Lanqing Wang.

Tobacco use is the leading preventable cause of premature disease and death in the United States. Approximately, 34 million U.S. adults currently smoke cigarettes. We developed a method for automated sample preparation and liquid chromatography-tandem mass spectrometry quantitation of 14 tobacco-related analytes: nicotine (NICF), cotinine (COTF), trans-3'-hydroxycotinine (HCTF), menthol glucuronide (MEG), anabasine (ANBF), anatabine (ANTF), isonicoteine (ISNT), myosmine (MYOS), beta-nicotyrine (BNTR), bupropion (BUPR), cytisine (CYTI), varenicline (VARE), arecaidine (ARD), and arecoline (ARL). The method includes automated solid-phase extraction using customized positive-pressure functions. The preparation scheme has the capacity to process a batch of 96 samples within 4 h with greater than 88% recovery for all analytes. The 14 analytes, separated within 4.15 min using reversed-phase liquid chromatography, were determined using a triple-quadrupole mass spectrometer with atmospheric-pressure chemical ionization and multiple reaction monitoring in negative and positive ionization modes. Wide quantitation ranges, within 1.2-72,000 ng/mL, were established especially for COTF, HCTF, MEG, and NICF to quantify the broad range of biomarker concentrations found in the U.S. population. The method accuracy is above 90% while the overall imprecision is below 7%. Finally, we tested urine samples from 90 smokers and observed detection rates of over 98% for six analytes with urinary HCTF and MEG concentrations ranging from 200-14,100 and 60-57,100 ng/mL, respectively. This high throughput analytical process can prepare and analyze a sample in 9 min and along with the 14-compound analyte panel can be useful for tobacco-exposure studies, in smoking-cessation programs, and for detecting changes in exposure related to tobacco products and their use.

DOI: https://doi.org/10.1021/acsomega.1c02543
Nat Methods. 2021 Dec 03.

Single-cell metabolomics hits its stride.

Caroline Seydel.

DOI: https://doi.org/10.1038/s41592-021-01333-x
Int Urol Nephrol. 2021 Nov 30.

Bladder cancer biomarker screening based on non-targeted urine metabolomics.

Jinkun Li, Bisheng Cheng, Hongbing Xie, Chuanchuan Zhan, Shipeng Li, Peiming Bai.

   PURPOSE: Bladder cancer is one of the most common malignancies of the urinary system, and its screening relies heavily on invasive cystoscopy, which increases the risk of urethral injury and infection. This study aims to use non-targeted metabolomics methods to screen for metabolites that are significantly different between the urine of bladder cancer patients and cancer-free controls.
METHODS: In this study, liquid chromatography-mass spectrometry was used to analyze the urine of bladder cancer patients (n = 57) and the cancer-free controls (n = 38) by non-targeted metabolomic analysis and metabolite identification.
RESULTS: The results showed that there were significant differences in the expression of 27 metabolites between bladder cancer patients and the cancer-free controls.
CONCLUSION: In the multivariate statistical analysis of this study, the urinary metabolic profile data of bladder cancer patients were analyzed, and the receiver operating characteristic curve analysis showed that it is possible to perform non-invasive clinical diagnoses of bladder cancer through these candidate biomarkers.

Keywords:  Biomarker; Bladder cancer; Liquid chromatography; Metabolomics

DOI:  https://doi.org/10.1007/s11255-021-03080-6
Proc Natl Acad Sci U S A. 2021 Dec 07. pii: e2109633118. [Epub ahead of print]118(49):

Accelerating strain phenotyping with desorption electrospray ionization-imaging mass spectrometry and untargeted analysis of intact microbial colonies.

Berkley M Ellis, Piyoosh K Babele, Jody C May, Carl H Johnson, Brian F Pfleger, Jamey D Young, John A McLean.

  Reading and writing DNA were once the rate-limiting step in synthetic biology workflows. This has been replaced by the search for the optimal target sequences to produce systems with desired properties. Directed evolution and screening mutant libraries are proven technologies for isolating strains with enhanced performance whenever specialized assays are available for rapidly detecting a phenotype of interest. Armed with technologies such as CRISPR-Cas9, these experiments are capable of generating libraries of up to 1010 genetic variants. At a rate of 102 samples per day, standard analytical methods for assessing metabolic phenotypes represent a major bottleneck to modern synthetic biology workflows. To address this issue, we have developed a desorption electrospray ionization-imaging mass spectrometry screening assay that directly samples microorganisms. This technology increases the throughput of metabolic measurements by reducing sample preparation and analyzing organisms in a multiplexed fashion. To further accelerate synthetic biology workflows, we utilized untargeted acquisitions and unsupervised analytics to assess multiple targets for future engineering strategies within a single acquisition. We demonstrate the utility of the developed method using Escherichia coli strains engineered to overproduce free fatty acids. We determined discrete metabolic phenotypes associated with each strain, which include the primary fatty acid product, secondary products, and additional metabolites outside the engineered product pathway. Furthermore, we measured changes in amino acid levels and membrane lipid composition, which affect cell viability. In sum, we present an analytical method to accelerate synthetic biology workflows through rapid, untargeted, and multiplexed metabolomic analyses.

Keywords:  DESI-IMS; free fatty acid profiling; imaging mass spectrometry; multiplexed metabolomics; synthetic biology

DOI:  https://doi.org/10.1073/pnas.2109633118
Curr Top Membr. 2021 ;pii: S1063-5823(21)00020-X. [Epub ahead of print]88 315-357

Mass spectrometry-based lipid analysis and imaging.

Koralege C Pathmasiri, Thu T A Nguyen, Nigina Khamidova, Stephanie M Cologna.

  Mass spectrometry imaging (MSI) is a powerful tool for in situ mapping of analytes across a sample. With growing interest in lipid biochemistry, the ability to perform such mapping without antibodies has opened many opportunities for MSI and lipid analysis. Herein, we discuss the basics of MSI with particular emphasis on MALDI mass spectrometry and lipid analysis. A discussion of critical advancements as well as protocol details are provided to the reader. In addition, strategies for improving the detection of lipids, as well as applications in biomedical research, are presented.

Keywords:  Lipid imaging; MALDI MSI; Mass spectrometry imaging

DOI:  https://doi.org/10.1016/bs.ctm.2021.10.005
Front Cardiovasc Med. 2021 ;8 734364

Stable Isotopes for Tracing Cardiac Metabolism in Diseases.

Anja Karlstaedt.

  Although metabolic remodeling during cardiovascular diseases has been well-recognized for decades, the recent development of analytical platforms and mathematical tools has driven the emergence of assessing cardiac metabolism using tracers. Metabolism is a critical component of cellular functions and adaptation to stress. The pathogenesis of cardiovascular disease involves metabolic adaptation to maintain cardiac contractile function even in advanced disease stages. Stable-isotope tracer measurements are a powerful tool for measuring flux distributions at the whole organism level and assessing metabolic changes at a systems level in vivo. The goal of this review is to summarize techniques and concepts for in vivo or ex vivo stable isotope labeling in cardiovascular research, to highlight mathematical concepts and their limitations, to describe analytical methods at the tissue and single-cell level, and to discuss opportunities to leverage metabolic models to address important mechanistic questions relevant to all patients with cardiovascular disease.

Keywords:  cardiovascular disease; metabolic flux analysis; metabolism; stable-isotope tracer; systems biology

DOI:  https://doi.org/10.3389/fcvm.2021.734364
Nucleic Acids Res. 2021 Nov 25. pii: gkab1117. [Epub ahead of print]

Isocratic HPLC analysis for the simultaneous determination of dNTPs, rNTPs and ADP in biological samples.

Farahnaz Ranjbarian, Sushma Sharma, Giulia Falappa, Walter Taruschio, Andrei Chabes, Anders Hofer.

Information about the cellular concentrations of deoxyribonucleoside triphosphates (dNTPs) is instrumental for mechanistic studies of DNA replication and for understanding diseases caused by defects in dNTP metabolism. The dNTPs are measured by methods based on either HPLC or DNA polymerization. An advantage with the HPLC-based techniques is that the parallel analysis of ribonucleoside triphosphates (rNTPs) can serve as an internal quality control of nucleotide integrity and extraction efficiency. We have developed a Freon-free trichloroacetic acid-based method to extract cellular nucleotides and an isocratic reverse phase HPLC-based technique that is able to separate dNTPs, rNTPs and ADP in a single run. The ability to measure the ADP levels improves the control of nucleotide integrity, and the use of an isocratic elution overcomes the shifting baseline problems in previously developed gradient-based reversed phase protocols for simultaneously measuring dNTPs and rNTPs. An optional DNA-polymerase-dependent step is used for confirmation that the dNTP peaks do not overlap with other components of the extracts, further increasing the reliability of the analysis. The method is compatible with a wide range of biological samples and has a sensitivity better than other UV-based HPLC protocols, closely matching that of mass spectrometry-based detection.

DOI: https://doi.org/10.1093/nar/gkab1117
J Chem Inf Model. 2021 Nov 29.

Mass Spectrometry Adduct Calculator.

Madison R Blumer, Christine H Chang, Evangelina Brayfindley, Jamie R Nunez, Sean M Colby, Ryan S Renslow, Thomas O Metz.

We describe the Mass Spectrometry Adduct Calculator (MSAC), an automated Python tool to calculate the adduct ion masses of a parent molecule. Here, adduct refers to a version of a parent molecule [M] that is charged due to addition or loss of atoms and electrons resulting in a charged ion, for example, [M + H]+. MSAC includes a database of 147 potential adducts and adduct/neutral loss combinations and their mass-to-charge ratios (m/z) as extracted from the NIST/EPA/NIH Mass Spectral Library (NIST17), Global Natural Products Social Molecular Networking Public Spectral Libraries (GNPS), and MassBank of North America (MoNA). The calculator relies on user-selected subsets of the combined database to calculate expected m/z for adducts of molecules supplied as formulas. This tool is intended to help researchers create identification libraries to collect evidence for the presence of molecules in mass spectrometry data. While the included adduct database focuses on adducts typically detected during liquid chromatography-mass spectrometry analyses, users may supply their own lists of adducts and charge states for calculating expected m/z. We also analyzed statistics on adducts from spectra contained in the three selected mass spectral libraries. MSAC is freely available at https://github.com/pnnl/MSAC.

DOI: https://doi.org/10.1021/acs.jcim.1c00579
Talanta. 2022 Feb 01. pii: S0039-9140(21)00926-7. [Epub ahead of print]238(Pt 1): 123004

Liquid chromatography coupled to Venturi easy ambient sonic spray ionization mass spectrometry.

Luan Felipe Campos Oliveira, David Ulisses Tega, Marcos Nogueira Eberlin, Alessandra Sussulini.

  Venturi easy ambient sonic spray ionization (V-EASI) is a soft ambient ionization (AI) source that has the advantages of being suitable to the analysis of samples in solution (differently from the majority of AI sources), performing self-pumping, voltage- and heat-free ionization, and requiring minimum or no sample preparation. Since this ionization technique has not been fully explored, the present study provides a proof of principle of the coupling of liquid chromatography to mass spectrometry (LC-MS) using V-EASI as the interface. In order to test the performance of the developed LC-V-EASI-MS system, a quantification method for bixin, a natural dye from annatto (Bixa Orellana L.), which is known to be sensitive to the high voltage applied for electrospray ionization mass spectrometry (ESI-MS) analysis, was validated according to FDA criteria and tested in real samples. The analytical method was successfully applied and met the validation criteria, providing a detectability 10 times better than methods already reported to the quantification of bixin and no matrix effect was observed. Therefore, this proof of principle contributes to the continuous development of AI sources that represents the last great technological advance in MS towards becoming a miniaturized technique able to analyze samples closer to their actual state.

Keywords:  Ambient ionization; Analytical methods; Annatto analysis; Liquid chromatography; Mass spectrometry; Venturi easy ambient sonic-spray ionization mass spectrometry

DOI:  https://doi.org/10.1016/j.talanta.2021.123004
J Hazard Mater. 2021 Nov 26. pii: S0304-3894(21)02881-8. [Epub ahead of print] 127912

Data mining of natural hazard biomarkers and metabolites with integrated metabolomic tools.

Xin Mao, Lining Xia, Li Yang, Yanli You, Pengjie Luo, Yanshen Li, Yongning Wu, Guibin Jiang.

  Data mining was one of the most important challenges in natural product analysis and biomarker discovery. In this work, we proposed an integrated data analysis protocol for natural products annotation and identification in data-dependent acquisition. Firstly, natural products and structure-related compounds could be identified by comparing mass spectrum behavior with commercial standard. Secondly, diagnostic fragmentation filtering (DFF) function in MZmine (http://mzmine.github.io/) was investigated for screening specific conjugation compounds with the same neutral loss. Thirdly, we present feature-based molecular networking (FBMN) in GNPS (https://gnps.ucsd.edu/) as a chromatographic feature detection and alignment tool. In addition, FBMN could enable natural products analysis based on molecular networks. This proposed integrated protocol should facilitate metabolomic data mining and biomarker discovery.

Keywords:  Data mining; High–resolution mass spectrum; Metabolites; Metabolomic; Natural hazard biomarkers

DOI:  https://doi.org/10.1016/j.jhazmat.2021.127912
J Proteome Res. 2021 Dec 03.

Multimodal Mass Spectrometry Imaging of Rat Brain Using IR-MALDESI and NanoPOTS-LC-MS/MS.

Crystal L Pace, Jared Simmons, Ryan T Kelly, David C Muddiman.

  Multimodal mass spectrometry imaging (MSI) is a critical technique used for deeply investigating biological systems by combining multiple MSI platforms in order to gain the maximum molecular information about a sample that would otherwise be limited by a single analytical technique. The aim of this work was to create a multimodal MSI approach that measures metabolomic and proteomic data from a single biological organ by combining infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) for metabolomic MSI and nanodroplet processing in one pot for trace samples (nanoPOTS) LC-MS/MS for spatially resolved proteome profiling. Adjacent tissue sections of rat brain were analyzed by each platform, and each data set was individually analyzed using previously optimized workflows. IR-MALDESI data sets were annotated by accurate mass and spectral accuracy using HMDB, METLIN, and LipidMaps databases, while nanoPOTS-LC-MS/MS data sets were searched against the rat proteome using the Sequest HT algorithm and filtered with a 1% FDR. The combined data revealed complementary molecular profiles distinguishing the corpus callosum against other sampled regions of the brain. A multiomic pathway integration showed a strong correlation between the two data sets when comparing average abundances of metabolites and corresponding enzymes in each brain region. This work demonstrates the first steps in the creation of a multimodal MSI technique that combines two highly sensitive and complementary imaging platforms. Raw data files are available in METASPACE (https://metaspace2020.eu/project/pace-2021) and MassIVE (identifier: MSV000088211).

Keywords:  IR-MALDESI; multimodal mass spectrometry imaging; multiomic analyses; nanoPOTS-LC-MS/MS

DOI:  https://doi.org/10.1021/acs.jproteome.1c00641
Anal Biochem. 2021 Nov 25. pii: S0003-2697(21)00397-3. [Epub ahead of print] 114496

A novel method development and validation for determination of 2,4,6-Trinitrotoluene and its metabolites on LC-MS/MS.

Muhammad Aamir, Sobia Irum, Amer Siddiq, Hafiza Monaza Batool, Nisar Ahmed, Muhammad Hamid Awais, Sadiq Ali.

  LC-MS/MS has recently emerged as the best practice for simultaneous analysis of 2, 4, 6 Trinitrotoluene (TNT) and its metabolites. We have developed and validated an LC-MS/MS method for simultaneous quantification of 2, 4, 6 Trinitrotoluene (TNT) and its metabolites 4-ADNT, 2-ADNT, 2,4-DNT, and 2,6-DNT in urine samples. These four metabolites were acid hydrolyzed using 1 mL of urine followed by extraction using n-Hexane and ethyl acetate as an extracting solvent. Separation was achieved by centrifugation, and the supernatant was dried under nitrogen, reconstituted with water and acetonitrile, and then filtered. Chromatographic separation was achieved on Agilent Poroshel 120 EC-C18 column (2.1 mm × 75 mm × 2.7 μm) utilizing two mobile phases 0.1% formic acid in water and 0.1% formic acid in acetonitrile in gradient flow. The validated AMR of TNT and its metabolites was 7.8-1000 ng/mL. The method showed an excellent correlation (>0.99) for TNT and its metabolites. Accuracy and within/between day precision of TNT and its metabolites were within ±15%. The integrity of diluted samples was maintained for each dilution factor. The method was found stable after storage and freeze-thaw cycle. The presented method can be used for TNT screening in occupationally exposed ordnance factory workers.

Keywords:  Liquid chromatography-mass spectrometry mass spectrometry (LC/MS/MS); Lower limit of quantitation (LLOQ); Method development; Trinitrotoluene (TNT); Validation

DOI:  https://doi.org/10.1016/j.ab.2021.114496
Nat Methods. 2021 Dec 03.

GNPS Dashboard: collaborative exploration of mass spectrometry data in the web browser.

Daniel Petras, Vanessa V Phelan, Deepa Acharya, Andrew E Allen, Allegra T Aron, Nuno Bandeira, Benjamin P Bowen, Deirdre Belle-Oudry, Simon Boecker, Dale A Cummings, Jessica M Deutsch, Eoin Fahy, Neha Garg, Rachel Gregor, Jo Handelsman, Mirtha Navarro-Hoyos, Alan K Jarmusch, Scott A Jarmusch, Katherine Louie, Katherine N Maloney, Michael T Marty, Michael M Meijler, Itzhak Mizrahi, Rachel L Neve, Trent R Northen, Carlos Molina-Santiago, Morgan Panitchpakdi, Benjamin Pullman, Aaron W Puri, Robin Schmid, Shankar Subramaniam, Monica Thukral, Felipe Vasquez-Castro, Pieter C Dorrestein, Mingxun Wang.

DOI: https://doi.org/10.1038/s41592-021-01339-5
Talanta. 2022 Feb 01. pii: S0039-9140(21)00928-0. [Epub ahead of print]238(Pt 1): 123006

Identification of glycerophospholipids using self-built recognition software based on positive and negative ion high-resolution mass spectrometric fragmentation experiments.

Ya Zhao, Xinnan Zhao, Tao Li, Xiao Wang, Cheng Zhong, Xiupin Wang, Peiwu Li.

  Glycerophospholipids (GPs) have a wide variety and complex structure, which makes their identification challenging. Our software affords a novel tool for the automated identification of non-target GPs in biological mixtures. Here, we explored the multi-stage fragmentation processes of GPs in positive and negative ion modes, and then constructed multi-stage fragment ion databases. This database includes 8214 simulated GP molecules from a random combination of fatty acids corresponding to 42,439 self-built predicted multi-stage fragment ions in positive ion mode and 31,487 self-built predicted multi-stage fragment ions in negative ion mode (MS ≤ 3). The automatic GP identification (AGPI) software can screen out GP candidates utilizing the MS1 accurate mass. The isomers of fatty acid chains and the phosphoryl head group can be distinguished using the MS2 and MS3 fragment spectra in positive-ion and negative-ion modes. All of the selected 45 GP standards were putatively identified using AGPI software; however, there were false positives because the software cannot distinguish positional isomers of fatty acids. Therefore, the AGPI software could be applied to identify GPs in samples, such as cancer cells; we successfully identified 41 GPs in cancer cells.

Keywords:  Cancer cells; Glycerophospholipids; Multi-stage mass spectrometry fragments; Recognition software

DOI:  https://doi.org/10.1016/j.talanta.2021.123006