bims-metlip 2021-08-15 papers

bims-metlip

Biomed News

on Methods and protocols in metabolomics and lipidomics

Issue of 2021‒08‒15
eighteen papers selected by
Sofia Costa
Cold Spring Harbor Laboratory

Sensitive and quantitative determination of short-chain fatty acids in human serum using liquid chromatography mass spectrometry.
Cross platform solutions to improve the zebrafish polar metabolome coverage using LC-QTOF MS: Optimization of separation mechanisms, solvent additives, and resuspension solvents.
A Preprocessing Tool for Enhanced Ion Mobility-Mass Spectrometry-Based Omics Workflows.
Integration of Chemical Derivatization and in-Source Fragmentation Mass Spectrometry for High-Coverage Profiling of Submetabolomes.
Preparation of racemic α-amino acid standards for accurate mass spectrometric analysis via racemization catalyzed by a hydrophobic pyridoxal derivative.
Per-pixel absolute quantitation for mass spectrometry imaging of endogenous lipidomes by model prediction of mass transfer kinetics in single-probe-based ambient liquid extraction.
Development of a novel analytical method for inflammation and immunity-related metabolites in serum based on liquid chromatography tandem mass spectrometry.
Ambient Single-Cell Analysis and Native Tissue Imaging Using Laser-Ablation Electrospray Ionization Mass Spectrometry with Increased Spatial Resolution.
Lipidomics dataset of Danio rerio optic nerve regeneration model.
The determination of the Paraxanthine/Caffeine ratio as a metabolic biomarker for CYP1A2 activity in various human matrices by UHPLC-ESIMS/MS.
Developing a SWATH capillary LC-MS/MS method for simultaneous therapeutic drug monitoring and untargeted metabolomics analysis of neonatal plasma.
A Mathematical Comparison of Non-negative Matrix Factorization-Related Methods with Practical Implications for the Analysis of Mass Spectrometry Imaging Data.
Metabolic profiles of human brain parenchyma and glioma for rapid tissue diagnosis by targeted desorption electrospray ionization mass spectrometry.
An integrative approach based on GC-qMS and NMR metabolomics data as a comprehensive strategy to search potential breast cancer biomarkers.
Analyzing Assay Specificity in Metabolomics Using Unique Ion Signature Simulations.
High-throughput quantitation method for amodiaquine and desethylamodiaquine in plasma using supported liquid extraction technology.
Metabolomic Profiling of Biological Reference Materials using a Multiplatform High-Resolution Mass Spectrometric Approach.
MoS2-Assisted LDI Mass Spectrometry for the Detection of Small Molecules and Quantitative Analysis of Sulfonamides in Serum.

Anal Bioanal Chem. 2021 Aug 11.

Sensitive and quantitative determination of short-chain fatty acids in human serum using liquid chromatography mass spectrometry.

Armaghan Shafaei, Veronica Vamathevan, Jessica Pandohee, Nathan G Lawler, David Broadhurst, Mary C Boyce.

  Short-chain fatty acids (SCFAs) are increasingly being monitored to elucidate the link between gut health and disease. These metabolites are routinely measured in faeces, but their determination in serum is more challenging due to their low concentrations. A method for the determination of eight SCFAs in serum is described here. High-resolution mass spectrometry and gas chromatography were used to identify the presence of isomeric interferences, which were then overcome through a combination of chromatographic separation and judicious choice of MS fragment ion. The SCFAs were derivatised to form 3-nitrophenylhydrazones before being separated on a reversed-phase column and then detected using liquid chromatography tandem mass spectrometry (LC-QQQ-MS). The LODs and LOQs of SCFAs using this method were in the range 1 to 7 ng mL-1 and 3 to 19 ng mL-1, respectively. The recovery of the SCFAs in serum ranged from 94 to 114% over the three concentration ranges tested.

Keywords:  High-resolution mass spectrometry; LC-MS/MS; SCFA; Serum

DOI:  https://doi.org/10.1007/s00216-021-03589-w
Talanta. 2021 Nov 01. pii: S0039-9140(21)00609-3. [Epub ahead of print]234 122688

Cross platform solutions to improve the zebrafish polar metabolome coverage using LC-QTOF MS: Optimization of separation mechanisms, solvent additives, and resuspension solvents.

Mengmeng Xu, Jessica Legradi, Pim Leonards.

  Untargeted metabolomics has been widely used for studies with zebrafish embryos. Until now, the number of analytical approaches to determine metabolites in zebrafish is limited, and there is a lack of consensus on the best platforms for comprehensive metabolomics analysis of zebrafish embryos. In addition, the capacity of these methods to detect metabolites is unsatisfactory and the confidence level for identifying compounds is relatively low. To improve the metabolome coverage, we mainly focused on the optimization of separation mechanisms, mobile phase additives, and resuspension solvents based on liquid chromatography (LC) coupling to high-resolution mass spectrometry (HRMS) techniques. Moreover, the procedures for optimizing methods were assessed when taking metabolite profiles in both positive and negative ionization modes into account. Four LC columns were studied: C18, T3, PFP, and HILIC. In positive ionization mode, it was strongly recommended to employ the HILIC approach operated at the neutral condition, which led to the presence of more than 4700 features and the annotation of 151 metabolites, mainly zwitterionic and basic compounds, in comparison to reverse phase (RP)-based methods with less than 1000 features. In negative ionization mode, the PFP column operated at 0.02% acetic acid showed the best performance in terms of metabolite coverage: 3100 metabolic features were detected and 218 metabolites were annotated in zebrafish embryos. Metabolite profiles mainly contained acidic and zwitterionic compounds. HILIC-based platforms were complementary to RP columns when analyzing highly polar metabolites. Additionally, it was preferable to reconstitute zebrafish extracts in 100% water for analysis of metabolites on RP columns, with a 20-30% increase in the number of identified metabolites compared to a 50% water in methanol solution. However, water/methanol (1:9, v/v), as resuspension solution, was advantageous over water/methanol (1:1, v/v) for HILIC analysis showing an 8-15% increase in detected metabolites. In total 336 polar metabolites were annotated by the combination of the optimized HILIC (positive) and PFP (negative) approaches. The largest metabolome coverage of polar metabolites in zebrafish embryos was obtained when three approaches were combined (negative PFP and HILIC, and HILIC positive) resulting in more than 420 annotated compounds.

Keywords:  Cross platforms; LC-QTOF; Metabolomics; Resuspension solvents; Zebrafish embryos

DOI:  https://doi.org/10.1016/j.talanta.2021.122688
J Proteome Res. 2021 Aug 12.

A Preprocessing Tool for Enhanced Ion Mobility-Mass Spectrometry-Based Omics Workflows.

Aivett Bilbao, Bryson C Gibbons, Sarah M Stow, Jennifer E Kyle, Kent J Bloodsworth, Samuel H Payne, Richard D Smith, Yehia M Ibrahim, Erin S Baker, John C Fjeldsted.

  The ability to improve the data quality of ion mobility-mass spectrometry (IM-MS) measurements is of great importance for enabling modular and efficient computational workflows and gaining better qualitative and quantitative insights from complex biological and environmental samples. We developed the PNNL PreProcessor, a standalone and user-friendly software housing various algorithmic implementations to generate new MS-files with enhanced signal quality and in the same instrument format. Different experimental approaches are supported for IM-MS based on Drift-Tube (DT) and Structures for Lossless Ion Manipulations (SLIM), including liquid chromatography (LC) and infusion analyses. The algorithms extend the dynamic range of the detection system, while reducing file sizes for faster and memory-efficient downstream processing. Specifically, multidimensional smoothing improves peak shapes of poorly defined low-abundance signals, and saturation repair reconstructs the intensity profile of high-abundance peaks from various analyte types. Other functionalities are data compression and interpolation, IM demultiplexing, noise filtering by low intensity threshold and spike removal, and exporting of acquisition metadata. Several advantages of the tool are illustrated, including an increase of 19.4% in lipid annotations and a two-times faster processing of LC-DT IM-MS data-independent acquisition spectra from a complex lipid extract of a standard human plasma sample. The software is freely available at https://omics.pnl.gov/software/pnnl-preprocessor.

Keywords:  data-independent acquisition; ion mobility spectrometry; lipid annotation; mass spectrometry; preprocessing software; time-of-flight detector saturation

DOI:  https://doi.org/10.1021/acs.jproteome.1c00425
Anal Chem. 2021 Aug 09.

Integration of Chemical Derivatization and in-Source Fragmentation Mass Spectrometry for High-Coverage Profiling of Submetabolomes.

Na An, Quan-Fei Zhu, Yan-Zhen Wang, Cai-Feng Xiong, Yu-Ning Hu, Yu-Qi Feng.

In-source fragmentation-based high-resolution mass spectrometry (ISF-HRMS) is a potential analytical technique, which is usually used to profile some specific compounds that can generate diagnostic neutral loss (NL) or fragment ion (FI) in ion source inherently. However, the ISF-HRMS method does not work for those compounds that cannot inherently produce diagnostic NL or FI in ion source. In this study, a derivatization-based in-source fragmentation-information-dependent acquisition (DISF-IDA) strategy was proposed for profiling the metabolites with easily labeled functional groups (submetabolomes) by liquid chromatography-electrospray ionization-quadrupole time-of-flight mass spectrometry (LC-ESI-Q-TOF MS). As a proof-of-concept study, 36 carboxylated compounds labeled with N,N-dimethylethylenediamine (DMED) were selected as model compounds to examine performance of DISF-IDA strategy in screening the carboxylated metabolites and acquiring their MSn spectra. In ESI source, the DEMD-derived carboxylated compounds were fragmented to produce characteristic neutral losses of 45.0578, 63.0684, and/or 88.1000 Da that were further used as diagnostic features for screening the carboxylated metabolites by DISF-IDA-based LC-Q-TOF MS. Furthermore, high-resolution MSn spectra of the model compounds were also obtained within a single run of DISF-IDA-based LC-Q-TOF MS analysis, which contributed to the improvement of the annotation confidence. To further verify its applicability, DISF-IDA strategy was used for profiling carboxylated submetabolome in mice feces. Using this strategy, a total of 351 carboxylated metabolites were detected from mice feces, of which 178 metabolites (51% of the total) were positively or putatively identified. Moreover, DISF-IDA strategy was also demonstrated to be applicable for profiling other submetabolomes with easily labeled functional groups such as amino, carbonyl, and cis-diol groups. Overall, our proposed DISF-IDA strategy is a promising technique for high-coverage profiling of submetabolomes with easily labeled functional groups in biological samples.

DOI: https://doi.org/10.1021/acs.analchem.1c02673
Talanta. 2021 Nov 01. pii: S0039-9140(21)00582-8. [Epub ahead of print]234 122661

Preparation of racemic α-amino acid standards for accurate mass spectrometric analysis via racemization catalyzed by a hydrophobic pyridoxal derivative.

Masashi Harada, Kazutaka Shimbo, Sachise Karakawa.

  Racemic α-amino acid standards for chiral metabolomics were prepared from l-α-amino acids using a hydrophobic pyridoxal derivative, namely 3-hydroxy-2-methyl-5-((octyloxy)methyl)isonicotinaldehyde (OPy), as the racemization catalyst. Among the 19 tested proteinogenic amino acids, 13 (including the generally unstable asparagine, glutamine, and tryptophan) underwent efficient racemization/epimerization under mildly basic conditions at room temperature, while solid-phase extraction allowed for effective and simple catalyst removal and amino acid recovery, obviating the need for chromatographic separation and recrystallization. Isotopically labeled racemic amino acids are commonly employed as internal standards for highly accurate mass spectrometric analysis. However, as isotopically labeled d-amino acids are often unavailable or highly expensive, the developed method was used to prepare racemic labeled amino acids, which were shown to enhance the repeatability and accuracy of d,l-amino acid quantitation in human urine by liquid chromatography-mass spectrometry (LC-MS). Given that our method should also be applicable to non-proteinogenic α-amino acids and the N-termini of peptides, the present study is expected to accelerate the development of LC-MS-based chiral metabolomics.

Keywords:  Amino acid; Biomimetic catalysis; Internal standard; Isotopic labeling; LC-MS/MS; Racemization

DOI:  https://doi.org/10.1016/j.talanta.2021.122661
Talanta. 2021 Nov 01. pii: S0039-9140(21)00575-0. [Epub ahead of print]234 122654

Per-pixel absolute quantitation for mass spectrometry imaging of endogenous lipidomes by model prediction of mass transfer kinetics in single-probe-based ambient liquid extraction.

Shifen Luo, Qian Wu, Youmei Li, Hongmei Lu.

  With the development of mass spectrometry imaging (MSI), techniques providing quantitative information on the spatial distribution have attracted more attentions recent years. However, for MSI of endogenous compounds in bio-samples, the uncertainty of locally varied sampling efficiencies always hinders accurate absolute quantitation. Here single-probe was used for ambient liquid extraction MSI in rat cerebellum, and standards of phosphatidylcholines (PCs) and cerebrosides (CBs) were doped in extraction solvent. The extraction kinetic curves of endogenous lipids in the ambient liquid extraction during probe parking in single pixel of tissue were investigated. From the results, the extraction kinetic curves were varied between different lipid species in different brain regions, resulting in variations of extraction efficiencies between imaging pixels, and calibration with standards deposited in tissue could not compensate for the variations. In our approach, the theoretical kinetic model of ambient liquid extraction was established, and original concentrations of endogenous lipids in each pixel of tissue were predicted by fitting the experimental extraction kinetic curve in each imaging pixel to the model. The experimental data was demonstrated to be well fitted to the kinetic model with R2 > 0.86, and only with 18-s extraction in each pixel, the original lipid concentrations were predicted accurately with relative errors <23%. With the new method, totally 157 lipids and small metabolites were imaged, and per-pixel quantitation was achieved for 19 PCs and 4 CBs. Compared with conventional quantitative MSI (q-MSI) method, the new q-MSI method had better reproducibility and wider linear range, and produced better contrast in the quantitative images of lipids in brain tissue with less hot spots and noises. The absolute quantitation results by the new method were verified by quantitative LC-MS method with Pearson'r > 0.9 and the slope of the linear fitting line of the correlation plot near 1.

Keywords:  Ambient liquid extraction techniques; Mass transfer kinetic model; Quantitative mass spectrometry imaging; Single-probe

DOI:  https://doi.org/10.1016/j.talanta.2021.122654
Talanta. 2021 Nov 01. pii: S0039-9140(21)00552-X. [Epub ahead of print]234 122631

Development of a novel analytical method for inflammation and immunity-related metabolites in serum based on liquid chromatography tandem mass spectrometry.

Xin Lu, Peng Dou, Xiaoyu Xie, Xiaolin Wang, Xinyu Liu, Rui Hua, Guowang Xu.

  Some metabolites have been found to play key roles in inflammation and immunity events that are associated with diseases such as cancer, diabetes and cytokine release syndrome. Characterization upon the inflammation and immunity-related metabolites (IIMs) will be helpful to the assessment of related pathological states. Although these metabolites have been partially reported in previous studies, the methods for specific measurement of them remain lacking. In the present study, a liquid chromatography - mass spectrometry based method was developed for the targeted analyses of 45 IIMs including amino acids, organic acids, phosphatidylcholines (PCs), polyunsaturated fatty acids and hormones selected based on the literature knowledge. Direct extraction with dansyl-chloride in acetonitrile was proved to be the most efficient and time-saving strategy, in which precipitation, extraction and derivatization were integrated. IIMs derivatized for 4 min and quenched for 2 min revealed the most comprehensive abundance. Based on the defined conditions, all the IIMs had a low limit of detection smaller than 1 ng/mL with the linear range greater than three orders of magnitude. The relative standard derivations of intra-day and inter-day precisions were ranged from 2.2% to 13.4% and 1.7% to 19.5%, respectively. The recovery rates and accuracy in low concentration were 98.9% ± 5.6% and 106.7% ± 11.6%, in medium concentration were 97.1% ± 6.8% and 106.9% ± 9.5%, and in high concentration were 98.4% ± 8.9% and 98.1% ± 8.1%, respectively. Matrix effect and stability were ranged from -37.8% to 35.6% and 2.9% to 14.2%, respectively. To show the usefulness of the method, serum IIMs in hepatitis B virus (HBV) infected patients and healthy subjects were determined and compared. Bile acids, lipoxygenase-mediated lipid mediators and non-enzymatic products showed global increases, whereas most of LysoPCs and cyclooxygenase-mediated prostaglandin D2 decreased in HBV serum samples. This study provided a robust approach for the characterization of IIMs.

Keywords:  Immunity; Inflammation; Mass spectrometry; Metabolite markers; Metabolomics; Targeted analysis

DOI:  https://doi.org/10.1016/j.talanta.2021.122631
J Am Soc Mass Spectrom. 2021 Aug 10.

Ambient Single-Cell Analysis and Native Tissue Imaging Using Laser-Ablation Electrospray Ionization Mass Spectrometry with Increased Spatial Resolution.

Michael J Taylor, Andrey Liyu, Akos Vertes, Christopher R Anderton.

  Laser-ablation electrospray ionization mass spectrometry (LAESI-MS) is an emerging method that has the potential to transform the field of metabolomics. This is in part due to LAESI-MS being an ambient ionization method that requires minimal sample preparation and uses (endogenous) water for in situ analysis. This application note details the employment of the "LAESI microscope" source to perform spatially resolved MS analysis of cells and MS imaging (MSI) of tissues at high spatial resolution. This source configuration utilizes a long-working-distance reflective objective that permits both visualization of the sample and a smaller LAESI laser beam profile than conventional LAESI setups. Here, we analyzed 200 single cells of Allium cepa (red onion) and imaged Fittonia argyroneura (nerve plant) in high spatial resolution using this source coupled to a Fourier transform mass spectrometer for high-mass-resolution and high-mass-accuracy metabolomics.

Keywords:  LAESI; mass spectrometry imaging; metabolomics; native analysis; spatial metabolomics

DOI:  https://doi.org/10.1021/jasms.1c00149
Data Brief. 2021 Aug;37 107260

Lipidomics dataset of Danio rerio optic nerve regeneration model.

Jennifer Arcuri, Matthew B Veldman, Sanjoy K Bhattacharya.

  The right optic nerve of adult, 6 month to 1 year old, female and male Danio rerio were crushed and collected three days after. Matching controls of uninjured left optic nerves were also collected. The tissue was dissected from euthanized fish and frozen on dry ice. Samples were pooled for each category (female crush, female control, male crush, male control) n = 24 to obtain sufficient tissue for analysis. The brain from one male fish was also collected for control/calibration. Lipid extraction was done with the Bligh and Dyer [1] method, followed by untargeted liquid chromatography-mass spectrometry (LC MS-MS) lipid profiling using a Q-Exactive Orbitrap instrument coupled with Vanquish Horizon Binary UHPLC LC-MS system. The lipids were identified and quantified with LipidSearch 4.2.21 and the statistical analysis was conducted through Metaboanalyst 5.0. This data is available at Metabolomics Workbench, Study ID ST001725.

Keywords:  CNS Injury; Lipids; Optic Nerve; Regeneration; Zebra-fish

DOI:  https://doi.org/10.1016/j.dib.2021.107260
Talanta. 2021 Nov 01. pii: S0039-9140(21)00579-8. [Epub ahead of print]234 122658

The determination of the Paraxanthine/Caffeine ratio as a metabolic biomarker for CYP1A2 activity in various human matrices by UHPLC-ESIMS/MS.

Bassam Lajin, Natascha Schweighofer, Walter Goessler, Barbara Obermayer-Pietsch.

  The Cytochrome P450 CYP1A2 is a central enzyme in the metabolism of drugs and xenobiotics. The overall activity of this enzyme is influenced by a complex array of biochemical, dietary, and genetic factors. One of the simplest ways to probe the overall output of CYP1A2 is to measure the ratio between the concentration of a precursor and a product of its activity. With the growing interest in the Paraxanthine/Caffeine ratio, the need arises to develop improved analytical methods specifically optimized for the rapid and sensitive determination of paraxanthine and caffeine in biological samples. We report a new optimized method for the determination of caffeine and paraxanthine in various human matrices. The method involved direct determination following protein precipitation based on ultra high performance liquid chromatographic separation with tandem mass spectrometric detection (UHPLC-ESIMS/MS). The method offers an improvement in the detection limit over previously published methods by at least 10-fold (0.1 pg), rapid chromatographic separation (ca. 5 min), the utilization of a green chromatographic solvent (5% v/v ethanol), direct determination with little sample preparation, and the employment of isotopically labeled internal standards and qualifier ions to ensure accuracy. Method validation in urine, saliva, and plasma was performed by spiking at various concentration levels where the recovery and repeatability were within ±15% and ±10%, respectively. The method was applied to investigate the levels of caffeine and paraxanthine in volunteers following controlled caffeine administration and to investigate the inter- and intra-individual variability in the paraxanthine/caffeine ratio in volunteers following an unrestricted caffeine diet. In conclusion, the developed UHPLC-ESIMS/MS method is optimized specifically for the simultaneous determination of the paraxanthine/caffeine ratio in multiple biological matrices, offers several advantages over the current methods, and is well suitable for application in large clinical studies.

Keywords:  (U)HPLC; Caffeine metabolism; Cytochrome P450; Mass spectrometry

DOI:  https://doi.org/10.1016/j.talanta.2021.122658
J Chromatogr B Analyt Technol Biomed Life Sci. 2021 Jul 27. pii: S1570-0232(21)00346-9. [Epub ahead of print]1179 122865

Developing a SWATH capillary LC-MS/MS method for simultaneous therapeutic drug monitoring and untargeted metabolomics analysis of neonatal plasma.

Jingcheng Xiao, Jian Shi, Ruiting Li, Lucy Her, Xinwen Wang, Jiapeng Li, Matthew J Sorensen, Varsha Bhatt-Mehta, Hao-Jie Zhu.

  Most medications prescribed to neonatal patients are off-label uses. The pharmacokinetics and pharmacodynamics of drugs differ significantly between neonates and adults. Therefore, personalized pharmacotherapy guided by therapeutic drug monitoring (TDM) and drug response biomarkers are particularly beneficial to neonatal patients. Herein, we developed a capillary LC-MS/MS metabolomics method using a SWATH-based data-independent acquisition strategy for simultaneous targeted and untargeted metabolomics analysis of neonatal plasma samples. We applied the method to determine the global plasma metabolomics profiles and quantify the plasma concentrations of five drugs commonly used in neonatal intensive care units, including ampicillin, caffeine, fluconazole, vancomycin, and midazolam and its active metabolite α-hydroxymidazolam, in neonatal patients. The method was successfully validated and found to be suitable for the TDM of the drugs of interest. Moreover, the global metabolomics analysis revealed plasma metabolite features that could differentiate preterm and full-term neonates. This study demonstrated that the SWATH-based capillary LC-MS/MS metabolomics approach could be a powerful tool for simultaneous TDM and the discovery of neonatal plasma metabolite biomarkers.

Keywords:  Data-independent acquisition; SWATH; Therapeutic drug monitoring; Untargeted metabolomics

DOI:  https://doi.org/10.1016/j.jchromb.2021.122865
Rapid Commun Mass Spectrom. 2021 Aug 09. e9181

A Mathematical Comparison of Non-negative Matrix Factorization-Related Methods with Practical Implications for the Analysis of Mass Spectrometry Imaging Data.

Melanie Nijs, Tina Smets, Etienne Waelkens, Bart De Moor.

RATIONALE: Non-negative matrix factorization (NMF) has been used extensively for the analysis of mass spectrometry imaging (MSI) data, visualizing simultaneously the spatial and spectral distributions present in a slice of tissue. The statistical framework offers two related NMF methods: probabilistic latent semantic analysis (PLSA) and latent Dirichlet allocation (LDA), which is a generative model. This work offers a mathematical comparison between NMF, PLSA, and LDA, and includes a detailed evaluation of Kullback-Leibler NMF (KL-NMF) for MSI for the first time. We will inspect their results for MSI data analysis as these different mathematical approaches impose different characteristics on the data and the resulting decomposition.METHODS: The four methods (NMF, KL-NMF, PLSA, and LDA) are compared on seven different samples: three originated from mice pancreas and four from human-lymph-node tissues, all obtained using MALDI-TOF MS.
RESULTS: Where matrix factorization methods are often used for the analysis of MSI data, we find that each method has different implications on the exactness and interpretability of the results. We have discovered promising results using KL-NMF, which has only rarely been used for MSI so far, improving both NMF and PLSA, and have shown that the hitherto stated equivalent KL-NMF and PLSA algorithms do differ in case of MSI data analysis. LDA, assumed to be the better method in the field of text-mining, is shown to be outperformed by PLSA in the setting of MALDI-MSI. Additionally, the molecular results of the human-lymph-node data have been thoroughly analysed for better assessment of the methods under investigation.
CONCLUSIONS: This paper offers an in-depth comparison of multiple NMF related factorization methods for MSI. We aim to provide fellow researchers in the field of MSI a clear understanding of the mathematical implications using each of these analysis techniques, which might affect the exactness and interpretation of the results.

DOI: https://doi.org/10.1002/rcm.9181
Anal Bioanal Chem. 2021 Aug 09.

Metabolic profiles of human brain parenchyma and glioma for rapid tissue diagnosis by targeted desorption electrospray ionization mass spectrometry.

Rong Chen, Hannah Marie Brown, R Graham Cooks.

  Desorption electrospray ionization mass spectrometry (DESI-MS) is well suited for intraoperative tissue analysis since it requires little sample preparation and offers rapid and sensitive molecular diagnostics. Currently, intraoperative assessment of the tumor cell percentage of glioma biopsies can be made by measuring a single metabolite, N-acetylaspartate (NAA). The inclusion of additional biomarkers will likely improve the accuracy when distinguishing brain parenchyma from glioma by DESI-MS. To explore this possibility, mass spectra were recorded for extracts from 32 unmodified human brain samples with known pathology. Statistical analysis of data obtained from full-scan and multiple reaction monitoring (MRM) profiles identified discriminatory metabolites, namely gamma-aminobutyric acid (GABA), creatine, glutamic acid, carnitine, and hexane-1,2,3,4,5,6-hexol (abbreviated as hexol), as well as the established biomarker NAA. Brain parenchyma was readily differentiated from glioma based on these metabolites as measured both in full-scan mass spectra and by the intensities of their characteristic MRM transitions. New DESI-MS methods (5 min acquisition using full scans and MS/MS), developed to measure ion abundance ratios among these metabolites, were tested using smears of 29 brain samples. Ion abundance ratios based on signals for GABA, creatine, carnitine, and hexol all had sensitivities > 90%, specificities > 80%, and accuracies > 85%. Prospectively, the implementation of diagnostic ion abundance ratios should strengthen the discriminatory power of individual biomarkers and enhance method robustness against signal fluctuations, resulting in an improved DESI-MS method of glioma diagnosis.

Keywords:  Ambient ionization; Biomarker; Glioma; Metabolomics; Multiple reaction monitoring; Tandem mass spectrometry

DOI:  https://doi.org/10.1007/s00216-021-03593-0
Metabolomics. 2021 Aug 13. 17(8): 72

An integrative approach based on GC-qMS and NMR metabolomics data as a comprehensive strategy to search potential breast cancer biomarkers.

Catarina Luís Silva, Rosa Perestrelo, Filipa Capelinha, Helena Tomás, José S Câmara.

  INTRODUCTION: Globally, breast cancer (BC) is leading at the top of women's diseases and, as a multifactorial disease, there is the need for the development of new approaches to aid clinicians on monitoring BC treatments. In this sense, metabolomic studies have become an essential tool allowing the establishment of interdependency among metabolites in biological samples.OBJECTIVE: The combination of nuclear magnetic resonance (NMR) and gas chromatography-quadrupole mass spectrometry (GC-qMS) based metabolomic analyses of urine and breast tissue samples from BC patients and cancer-free individuals was used.
METHODS: Multivariate statistical tools were used in order to obtain a panel of metabolites that could discriminate malignant from healthy status assisting in the diagnostic field. Urine samples (n = 30), cancer tissues (n = 30) were collected from BC patients, cancer-free tissues were resected outside the tumor margin from the same donors (n = 30) while cancer-free urine samples (n = 40) where obtained from healthy subjects and analysed by NMR and GC-qMS methodologies.
RESULTS: The orthogonal partial least square discriminant analysis model showed a clear separation between BC patients and cancer-free subjects for both classes of samples. Specifically, for urine samples, the goodness of fit (R2Y) and predictive ability (Q2) was 0.946 and 0.910, respectively, whereas for tissue was 0.888 and 0.813, revealing a good predictable accuracy. The discrimination efficiency and accuracy of tissue and urine metabolites was ascertained by receiver operating characteristic curve analysis that allowed the identification of metabolites with high sensitivity and specificity. The metabolomic pathway analysis identified several dysregulated pathways in BC, including those related with lactate, valine, aspartate and glutamine metabolism. Additionally, correlations between urine and tissue metabolites were investigated and five metabolites (e.g. acetone, 3-hexanone, 4-heptanone, 2-methyl-5-(methylthio)-furan and acetate) were found to be significant using a dual platform approach.
CONCLUSION: Overall, this study suggests that an improved metabolic profile combining NMR and GC-qMS may be useful to achieve more insights regarding the mechanisms underlying cancer.

Keywords:  Breast cancer; Chemometric tools; GC–qMS; Metabolomics; NMR; Tissue; Urine

DOI:  https://doi.org/10.1007/s11306-021-01823-1
Anal Chem. 2021 Aug 10.

Analyzing Assay Specificity in Metabolomics Using Unique Ion Signature Simulations.

Premy Shanthamoorthy, Adamo Young, Hannes Röst.

Targeted, untargeted, and data-independent acquisition (DIA) metabolomics workflows are often hampered by ambiguous identification based on either MS1 information alone or relatively few MS2 fragment ions. While DIA methods have been popularized in proteomics, it is less clear whether they are suitable for metabolomics workflows due to their large precursor isolation windows and complex coisolation patterns. Here, we quantitatively investigate the conditions necessary for unique metabolite detection in complex backgrounds using precursor and fragment ion mass-to-charge (m/z) separation, comparing three benchmarked mass spectrometry (MS) methods [MS1, MRM (multiple reaction monitoring), and DIA]. Our simulations show that DIA outperformed MS1-only and MRM-based methods with regards to specificity by factors of ∼2.8-fold and ∼1.8-fold, respectively. Additionally, we show that our results are not dependent on the number of transitions used or the complexity of the background matrix. Finally, we show that collision energy is an important factor in unambiguous detection and that a single collision energy setting per compound cannot achieve optimal pairwise differentiation of compounds. Our analysis demonstrates the power of using both high-resolution precursor and high-resolution fragment ion m/z for unambiguous compound detection. This work also establishes DIA as an emerging MS acquisition method with high selectivity for metabolomics, outperforming both data-dependent acquisition (DDA) and MRM with regards to unique compound identification potential.

DOI: https://doi.org/10.1021/acs.analchem.1c01204
J Chromatogr B Analyt Technol Biomed Life Sci. 2021 Jul 31. pii: S1570-0232(21)00368-8. [Epub ahead of print]1179 122887

High-throughput quantitation method for amodiaquine and desethylamodiaquine in plasma using supported liquid extraction technology.

Karnrawee Kaewkhao, Joel Tarning, Daniel Blessborn.

  Amodiaquine is a drug used for treatment of malaria and is often used in combination with artesunate in areas where malaria parasites are still susceptible to amodiaquine. Liquid chromatography tandem-mass spectrometry was used to quantify amodiaquine and its active metabolite, desethylamodiaquine, in plasma samples. A low sample volume of 100 µl, and high-throughput extraction technique using a supported liquid extraction (SLE+) technique on an automated liquid handler platform for faster sample processing are some of the advantages of this method. Separation of amodiaquine from desethylamodiaquine was achieved using a reversed phase Zorbax SB-CN 50 mm × 4.6 mm, I.D. 3.5 µm column with acetonitrile and 20 mM ammonium formate with 1% formic acid pH ~ 2.6 (15-85, v/v) as mobile phase. The absolute recoveries of amodiaquine and desethylamodiaquine were 66% to 76%, and their isotope label internal standard were in the range of 73% to 85%. Validation results of the developed method demonstrated intra-batch and inter-batch precisions within the acceptance criteria range of ± 15.0%. There were no matrix or carry-over effects observed. The lower limit of quantification was 1.08 ng/ml for amodiaquine and 1.41 ng/ml for desethylamodiaquine. The method showed robust and accurate performance with high sensitivity. Thus, the validated method was successfully implemented and applied in the evaluation of a clinical trial where participants received artemether-lumefantrine plus amodiaquine twice daily for three days (amodiaquine dose of 10 mg base/kg/day).

Keywords:  Amodiaquine; LC-MS/MS; Method validation; Plasma

DOI:  https://doi.org/10.1016/j.jchromb.2021.122887
J Am Soc Mass Spectrom. 2021 Aug 13.

Metabolomic Profiling of Biological Reference Materials using a Multiplatform High-Resolution Mass Spectrometric Approach.

Juan J Aristizabal-Henao, Dominick J Lemas, Emily K Griffin, Kaylie Anne Costa, Camden Camacho, John A Bowden.

  The number of metabolomics studies have increased dramatically in recent years, spanning from basic/mechanistic research to the identification and validation of clinical biomarkers. Developments in analyte separation techniques and the growth of databases are largely responsible for the rapid growth of metabolomics, although broad differences in analytical workflows can result in difficulty when comparing data across studies. The establishment of baseline metabolomics data for human reference materials using complementary/orthogonal data acquisition strategies can help to alleviate some of these challenges. To this end, we report nontargeted semiquantitative metabolomics data for 22 commercially available materials including plasma (healthy, diabetic, hypertriglyceridemic, African-American), serum (female, male, pregnant, among others), feces (meconium, vegan, omnivore), urine (smokers' and nonsmokers'), breast milk, saliva, and vaginal fluid, using ultrahigh-performance liquid chromatography-tandem mass spectrometry in positive and negative electrospray ionization, as well as gas chromatography-electron ionization-mass spectrometry. Significant differences were observed in the metabolomic fingerprints between all sample types. Post hoc comparisons between relevant sample types support the relevance of these materials and the validity of nontargeted strategies in global metabolomics. As the number and variety of reference materials continues to increase, it is imperative that their adoption is matched. The results of this study may inform future biomedical research by highlighting several metabolites across matrixes and treatments/states that could serve as clinical biomarkers or important biochemical pathway intermediates. Furthermore, our work can serve as a metric for systems suitability, quality assurance, and quality control across the community via the dissemination of high-quality and publicly available annotated metabolomics data.

Keywords:  gas chromatography; high-resolution mass spectrometry; liquid chromatography; metabolomics; reference materials

DOI:  https://doi.org/10.1021/jasms.1c00194
J Am Soc Mass Spectrom. 2021 Aug 09.

MoS2-Assisted LDI Mass Spectrometry for the Detection of Small Molecules and Quantitative Analysis of Sulfonamides in Serum.

Yaju Zhao, Qiaobo Liao, Kai Xi, Danke Xu.

  A two-dimensional MoS2 nanosheet was prepared by a chemical exfoliation method and served as an excellent matrix for the detection of small molecules by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). In comparison with organic matrices (CHCA, 3-AQ) and a graphene matrix, we found that a MoS2 matrix showed better performance in analysis of amino acids, peptides, fatty acids, and sulfonamides. A systematic comparison of the MoS2 matrix with both ion modes showed that mass spectra produced in negative ion mode featured a corresponding single deprotonated ion, which was rather different from the complex multiple alkali metal addition peaks present in positive ion mode. In addition, better sensitivity and reproducibility were obtained in negative ion mode. The ionization mechanism of MoS2 as a matrix in negative ion mode was further discussed. The deproton peak intensity of the analyte fatty acid decreased after the addition of the hole-scavenger KSCN, indicating that the ionization of the fatty acid was caused by the Auger complex effect of MoS2 and electron injection. Experiments have shown that the MoS2 matrix detects small molecules with good repeatability and can perform semiquantitative analysis of sulfonamides. Finally, the MoS2 matrix was employed for quantitative determination of sulfamethoxine in serum samples by an internal standard method. This MoS2-assisted laser desorption/ionization mass spectrometry (MoS2-assisted LDI MS) method provides a simple, rapid, high-throughput approach to evaluate the drug levels in the patient serum and can achieve convenient drug therapy monitoring.

Keywords:  MALDI-TOF MS; MoS2; ionization mechanism; matrix; sulfonamides

DOI:  https://doi.org/10.1021/jasms.1c00182