bims-metlip 2023-05-14 papers

bims-metlip

Biomed News

on Methods and protocols in metabolomics and lipidomics

Issue of 2023–05–14
fiveteen papers selected by
Sofia Costa, Matterworks

Identification of Metabolite Interference Is Necessary for Accurate LC-MS Targeted Metabolomics Analysis.
Validation of LC-MS/MS methods for quantitative analysis of kynurenine pathway metabolites in human plasma and cerebrospinal fluid.
Simultaneous determination of UDCA and its major metabolites in human plasma with surrogate matrix by a rapid and specific LC-MS/MS method.
Contrastive Learning-Based Embedder for the Representation of Tandem Mass Spectra.
General Method to Obtain Collision Cross-Section Values in Multipass High-Resolution Cyclic Ion Mobility Separations.
Localization analysis of metabolites from complex biological samples-recent analytical technique of mass spectrometry imaging.
Improved Structural Characterization of Glycerophospholipids and Sphingomyelins with Real-Time Library Searching.
Diazo probe-based chemical isotope labeling assisted liquid chromatography-tandem mass spectrometry analysis for sensitive determination of amino acids in biofluids.
Lipidomics in food quality and authentication: A comprehensive review of novel trends and applications using chromatographic and spectroscopic techniques.
High-throughput quantitation of serological dimethylarginines by LC/MS/MS: Potential cardiovascular biomarkers for rheumatoid arthritis.
Effect of Sample Plates and Sample Matrix on the Quantification Capabilities of Surface-Assisted Flowing Atmospheric-Pressure Afterglow Mass Spectrometry (SA-FAPA-MS).
Sensitive Instrumental Method for Quantitative Determination of High-Brominated Flame Retardants in Human Serum Samples.
Annotation of Dipeptides and Tripeptides Derivatized via Dansylation Based on Liquid Chromatography-Mass Spectrometry and Iterative Quantitative Structure Retention Relationship.
Global xenobiotic profiling of rat plasma using untargeted metabolomics and background subtraction-based approaches: Method evaluation and comparison.
Spatially resolved multi-omics highlights cell-specific metabolic remodeling and interactions in gastric cancer.

Anal Chem. 2023 May 08.

Identification of Metabolite Interference Is Necessary for Accurate LC-MS Targeted Metabolomics Analysis.

Zhikun Jia, Qiongju Qiu, Ruiping He, Tianyu Zhou, Li Chen.

Targeted metabolomics has been broadly used for metabolite measurement due to its good quantitative linearity and simple metabolite annotation workflow. However, metabolite interference, the phenomenon where one metabolite generates a peak in another metabolite's MRM setting (Q1/Q3) with a close retention time (RT), may lead to inaccurate metabolite annotation and quantification. Besides isomeric metabolites having the same precursor and product ions that may interfere with each other, we found other metabolite interferences as the result of inadequate mass resolution of triple-quadruple mass spectrometry and in-source fragmentation of metabolite ions. Characterizing the targeted metabolomics data using 334 metabolite standards revealed that about 75% of the metabolites generated measurable signals in at least one other metabolite's MRM setting. Different chromatography techniques can resolve 65-85% of these interfering signals among standards. Metabolite interference analysis combined with the manual inspection of cell lysate and serum data suggested that about 10% out of ∼180 annotated metabolites were mis-annotated or mis-quantified. These results highlight that a thorough investigation of metabolite interference is necessary for accurate metabolite measurement in targeted metabolomics.

DOI: https://doi.org/10.1021/acs.analchem.3c00804
Bioanalysis. 2023 May 12.

Validation of LC-MS/MS methods for quantitative analysis of kynurenine pathway metabolites in human plasma and cerebrospinal fluid.

Vinod Khetarpal, Todd Herbst, Shahzad Akhtar, Amber LaFayette, Dennis Miller, James Farnham, Troy Steege, Zhixin Miao, Bryan Marks, Aaron Ledvina, Celia Dominguez.

  Background: Dysregulation of the kynurenine metabolic pathway has been reported in several neurological conditions. Methods & results: Sensitive and selective LC-MS/MS methods have been validated for six kynurenine pathway metabolites in human cerebrospinal fluid and plasma. For each matrix, we validated three methods - one for the simultaneous determination of kynurenine, kynurenic acid, anthranilic acid and 3-hydroxy-kynurenine (four-analyte assay), one for quinolinic acid and one for tryptophan - using stable-isotopically labeled internal standards. The dynamic range and quantitation limits were based on endogenous concentrations for each analyte. Conclusion: The use of validated methods for kynurenine pathway metabolites in human cerebrospinal fluid and plasma will provide definitive information in neurological diseases.

Keywords:  3-hydroxy-kynurenine; CSF; Huntington’s disease; anthranilic acid; human plasma; kynurenic acid; kynurenine; kynurenine pathway metabolites; quinolinic acid; tryptophan; validation

DOI:  https://doi.org/10.4155/bio-2023-0016
J Chromatogr B Analyt Technol Biomed Life Sci. 2023 Apr 29. pii: S1570-0232(23)00136-8. [Epub ahead of print]1223 123726

Simultaneous determination of UDCA and its major metabolites in human plasma with surrogate matrix by a rapid and specific LC-MS/MS method.

Ning Li, Xue Zhang, Mengxin Li, Mengmeng Liu, Yi Jin, Haiyan Xu.

  A rapid, convenient, and specific liquid chromatography-tandem mass spectrometry method was developed and validated for the simultaneous quantification of ursodeoxycholic acid (UDCA), and its major metabolites, glycoursodeoxycholic acid (GUDCA) and tauroursodeoxycholic acid (TUDCA) in human plasma. Methanol was chosen as surrogate matrix for preparation the calibrators to establish calibration curves. Isotope internal standard was used for each analyte. After plasma samples were deproteinized with methanol, the post-treatment samples were analyzed on a ZORBAX SB-C18 column (2.1 × 50 mm, 1.8 μm) with 2 mM ammonium acetate and acetonitrile as mobile phase at a flow rate of 0.5 mL/min. Detection was performed on a triple quadrupole mass spectrometer operating in multiple reaction monitoring (MRM) employing negative ESI interface using API5500 triple quadrupole tandem mass spectrometer system, with the transitions set at m/z 391.4 → m/z 391.4, m/z 448.3 → m/z 73.9, m/z 498.4 → m/z 80.1, m/z 395.3 → m/z 395.3, m/z 453.3 → m/z 74.0, and m/z 503.2 → m/z 79.9 for UDCA, GUDCA, TUDCA, UDCA-d4, GUDCA-d5, and TUDCA-d5, respectively. The calibration curve ranges were 5.00-2500 ng/mL for UDCA and GUDCA and 0.500-250 ng/mL for TUDCA. The intra- and inter-day precision was within 7.00% in terms of relative standard deviation (RSD%) and the accuracy within 11.75% in terms of relative error. The selectivity, sensitivity, extraction recovery, matrix effect, dilution reliability, and stability were within the acceptable range. The method was successfully applied to a pharmacokinetic study in 12 healthy Chinese volunteers after oral administration of 250 mg UDCA.

Keywords:  GUDCA; LC-MS/MS; Pharmacokinetics; Surrogate matrix; TUDCA; UDCA

DOI:  https://doi.org/10.1016/j.jchromb.2023.123726
Anal Chem. 2023 May 12.

Contrastive Learning-Based Embedder for the Representation of Tandem Mass Spectra.

Hao Guo, Kebing Xue, Haiming Sun, Weihao Jiang, Shiliang Pu.

Tandem mass spectrometry (MS/MS) shows great promise in the research of metabolomics, providing an abundance of information on compounds. Due to the rapid development of mass spectrometric techniques, a large number of MS/MS spectral data sets have been produced from different experimental environments. The massive data brings great challenges into the spectral analysis including compound identification and spectra clustering. The core challenge in MS/MS spectral analysis is how to describe a spectrum more quantitatively and effectively. Recently, emerging deep-learning-based technologies have brought new opportunities to handle this challenge in which high-quality descriptions of MS/MS spectra can be obtained. In this study, we propose a novel contrastive learning-based method for the representation of MS/MS spectra, called CLERMS, which is based on transformer architecture. Specifically, an optimized model architecture equipped with a sinusoidal embedder and a novel loss function composed of InfoNCE loss and MSE loss has been proposed for the attainment of good embedding from the peak information and the metadata. We evaluate our method using a GNPS data set, and the results demonstrate that the learned embedding can not only distinguish spectra from different compounds but also reveal the structural similarity between them. Additionally, the comparison between our method and other methods on the performance of compound identification and spectra clustering shows that our method can achieve significantly better results.

DOI: https://doi.org/10.1021/acs.analchem.3c00260
Anal Chem. 2023 May 10.

General Method to Obtain Collision Cross-Section Values in Multipass High-Resolution Cyclic Ion Mobility Separations.

Sanaz C Habibi, Gabe Nagy.

In recent years, ion mobility spectrometry-mass spectrometry (IMS-MS) has advanced the field of omics-based research, especially with the development of high-resolution platforms; however, these separations have generally been qualitative in nature. The rotationally averaged ion neutral collision cross section (CCS) is one of the only quantitative metrics available for aiding in characterizing biomolecules in IMS-MS. However, determining the CCS of an ion for multipass IMS systems, such as in cyclic ion mobility-mass spectrometry (cIMS-MS) and structures for lossless ion manipulations, has been challenging due to the lack of methods available for calculating CCS when more than a single pass is required for separation as well as the laborious nature of requiring calibrants and unknown compounds to be subjected to identical number of passes, which may not be possible in certain instances because of peak splitting, high levels of diffusion, etc. Herein, we present a general method that uses average ion velocities for calculating CCS values in cIMS-MS-based separations. Initially, we developed calibration curves using common CCS calibrants [i.e., tetra-alkylammonium salts, polyalanine, and hexakis(fluoroalkoxy)phosphazines] at different traveling wave (TW) conditions and the calculated cIMS CCS values were within ∼1% error or less compared to previously established drift tube IMS CCS measurements. Since it has been established that glycans can split into their α/β anomers, we utilized this method for two glycan species, 2α-mannobiose and melibiose. Both glycans were analyzed at the same TW conditions as the calibrants, and we observed anomer splitting at pathlengths of 20 m for 2α-mannobiose and 40 m for melibiose and thus assigned two unique CCS values for each glycan, which is the first time this has ever been done. We have demonstrated that the use of average ion velocities is a robust approach for obtaining CCS values with good agreement to CCS measurements from the previous literature and anticipate that this methodology can be applied to any IMS-MS platform that utilizes multipass separations. Our future work aims to incorporate this methodology for the development of a high-resolution CCS database to aid in the characterization of human milk oligosaccharides.

DOI: https://doi.org/10.1021/acs.analchem.3c00919
Front Mol Biosci. 2023 ;10 1169449

Localization analysis of metabolites from complex biological samples-recent analytical technique of mass spectrometry imaging.

Qiang Yang, Ying Cai, Sifan Guo, Zhibo Wang, Shi Qiu, Aihua Zhang.



Keywords:  diagnosis; mass spectrometry imaging; metabolite; metabolomics; target

DOI:  https://doi.org/10.3389/fmolb.2023.1169449
Anal Chem. 2023 May 12.

Improved Structural Characterization of Glycerophospholipids and Sphingomyelins with Real-Time Library Searching.

Dain R Brademan, Katherine A Overmyer, Yuchen He, William D Barshop, Jesse D Canterbury, Brandon J Bills, Benton J Anderson, Paul D Hutchins, Seema Sharma, Vlad Zabrouskov, Graeme C McAlister, Joshua J Coon.

In mass spectrometry-based lipidomics, complex lipid mixtures undergo chromatographic separation, are ionized, and are detected using tandem MS (MSn) to simultaneously quantify and structurally characterize eluting species. The reported structural granularity of these identified lipids is strongly reliant on the analytical techniques leveraged in a study. For example, lipid identifications from traditional collisionally activated data-dependent acquisition experiments are often reported at either species level or molecular species level. Structural resolution of reported lipid identifications is routinely enhanced by integrating both positive and negative mode analyses, requiring two separate runs or polarity switching during a single analysis. MS3+ can further elucidate lipid structure, but the lengthened MS duty cycle can negatively impact analysis depth. Recently, functionality has been introduced on several Orbitrap Tribrid mass spectrometry platforms to identify eluting molecular species on-the-fly. These real-time identifications can be leveraged to trigger downstream MSn to improve structural characterization with lessened impacts on analysis depth. Here, we describe a novel lipidomics real-time library search (RTLS) approach, which utilizes the lipid class of real-time identifications to trigger class-targeted MSn and to improve the structural characterization of phosphotidylcholines, phosphotidylethanolamines, phosphotidylinositols, phosphotidylglycerols, phosphotidylserine, and sphingomyelins in the positive ion mode. Our class-based RTLS method demonstrates improved selectivity compared to the current methodology of triggering MSn in the presence of characteristic ions or neutral losses.

DOI: https://doi.org/10.1021/acs.analchem.2c04633
J Chromatogr B Analyt Technol Biomed Life Sci. 2023 Apr 26. pii: S1570-0232(23)00134-4. [Epub ahead of print]1223 123724

Diazo probe-based chemical isotope labeling assisted liquid chromatography-tandem mass spectrometry analysis for sensitive determination of amino acids in biofluids.

Chun-Yue Han, Li Ge, Chi Zhang, Li-Na Ding, Peng Wang, Fang Yu, Sheng Wang, Lili Zhu, Qunlin Zhang, Qi Liu, Fei-Long Liu.

  Amino acids are important biomolecules and contribute to essential biological processes. Liquid chromatography tandem mass spectrometry (LC-MS) now is a powerful tool for the analysis of amino acid metabolites; however, the structural similarity and polarity of amino acids can lead to the poor chromatographic retention and low detection sensitivities. In this study, we used a pair of light and heavy isotopomers of diazo probes, d0/d5-2-(diazomethyl)-N-methyl-N-phenyl-benzamide (2-DMBA/d5 -2-DMBA) to label amino acids. The paired MS probes of 2-DMBA and d5 -2-DMBA carry diazo groups that can efficiently and specifically react with the carboxyl group on free amino acid metabolites under mild conditions. Benefiting from the transfer of the 2-DMBA/d5 -2-DMBA to carboxyl group on amino acids, the ionization efficiencies of amino acids presented great enhancement during LC-MS analysis. The results suggested that the detection sensitivities of 17 amino acids increased by 9-133-fold upon 2-DMBA labeling, and the obtained limits of detection (LODs) of amino acids on-column ranged from 0.011 fmol-0.057 fmol. With the application of the developed method, we successfully achieved the sensitive and accurate detection of the 17 amino acids in microliter level of serum sample. Moreover, the contents of most amino acids were different in the serum from normal and B16F10-tumour mice, demonstrating that endogenous amino acids may play important roles in the regulation of tumors development. This developed method of chemical labeling of amino acids with diazo probes assisted LC-MS analysis provides a potentially valuable tool to investigate the relationships between amino acids metabolism and diseases.

Keywords:  Amino acids; Chemical isotope labeling; Diazo probe; Liquid chromatography-tandem mass spectrometry

DOI:  https://doi.org/10.1016/j.jchromb.2023.123724
Crit Rev Food Sci Nutr. 2023 May 10. 1-24

Lipidomics in food quality and authentication: A comprehensive review of novel trends and applications using chromatographic and spectroscopic techniques.

Engy Mahrous, Ruoxin Chen, Chao Zhao, Mohamed A Farag.

  Lipid analysis is an integral part of food authentication and quality control which provides consumers with the necessary information to make an informed decision about their lipid intake. Recent advancement in lipid analysis and lipidome scope represents great opportunities for food science. In this review we provide a comprehensive overview of available tools for extraction, analysis and interpretation of data related to dietary fats analyses. Different analytical platforms are discussed including GC, MS, NMR, IR and UV with emphasis on their merits and limitations alongside complementary tools such as chemometric models and lipid-targeted online databases. Applications presented here include quality control, authentication of organic and delicacy food, tracing dietary fat source and investigating the effect of heat/storage on lipids. A multitude of analytical methods with different sensitivity, affordability, reproducibility and ease of operation are now available to comprehensively analyze dietary fats. Application of these methods range from studies which favor the use of large data generating platforms such as MS-based methods, to routine quality control which demands easy to use affordable equipment as TLC and IR. Hence, this review provides a navigation tool for food scientists to help develop an optimal protocol for their future lipid analysis quest.

Keywords:  Dietary fats; NMR spectroscopy; lipid extraction; mass spectrometry; quality control; vibrational spectroscopy

DOI:  https://doi.org/10.1080/10408398.2023.2207659
J Pharm Biomed Anal. 2023 Mar 11. pii: S0731-7085(23)00105-X. [Epub ahead of print]232 115336

High-throughput quantitation of serological dimethylarginines by LC/MS/MS: Potential cardiovascular biomarkers for rheumatoid arthritis.

Qianyang Huang, Ying Liu, Yuna Cheng, Fujian Jia, Chunchao Pu, Qinghua Yan, Zhaoyu Chang, Ping Liao, Dandan Ma, Lei Xu, Hua Zhang, Yuanzhi Lu, Xin Liu, Kang Liu.

  Rheumatoid arthritis (RA) is a chronic autoimmune disorder characterized by systemic inflammation of the joints and extra-articular tissues. The incidence of cardiovascular disease (CVD) remains the main cause of morbidity and mortality in patients with RA. Despite the development of new therapeutics targeting the articular manifestations, the relief of the cardiovascular burden is still an unmet medical need during the management of RA. So, the early prognosis of RA-associated CVD plays a crucial role in improving the clinical outcomes of RA patients. Recently, circulating dimethylarginines have gained attention as potential biomarkers for CVDs. Here, we present the development and validation of a high-throughput liquid chromatography-tandem mass spectrometric (LC/MS/MS) method for simultaneous quantification of creatinine, arginine, and dimethylarginines in human serum within 2 mins by isotope dilution mass spectrometry. This method employed a protein precipitation method for rapid sample preparation, trichloroacetic acid (TCA)-based ion pairing chromatography for fast analyte separation, and multiple reaction monitoring (MRM) with stable isotope-labeled internal standards (ISs) for simultaneous quantitation. To assure the quality, our method was validated against the FDA guidelines for lower limit of quantitation (0.2 µM), linearity (square of coefficient correlation>0.99), precision (intra-&inter-assay imprecision < 10 %), accuracy (intra-&inter-assay inaccuracy < 10 %), sample preparation recovery (recovery ≥ 90 %), stability (instability < 10 %), matrix effect (signal suppression < 55 %), and carryover ( < 0.01 %). Afterward, we applied the validated method to a retrospective cross-sectional study. We aimed to evaluate the utility of serological dimethylarginines as potential cardiovascular biomarkers in the development of RA-associated CVD. Our results revealed that the serological ratio of asymmetric dimethylarginine (ADMA) and symmetric dimethylarginine (SDMA), an indicator of physiological arginine methylation status, was significantly elevated in patients with RA. This finding might provide value in detecting CVD to improve clinical outcomes in RA management.

Keywords:  ADMA; Arginine; Rheumatoid Arthritis; SDMA

DOI:  https://doi.org/10.1016/j.jpba.2023.115336
Appl Spectrosc. 2023 May 07. 37028231168617

Effect of Sample Plates and Sample Matrix on the Quantification Capabilities of Surface-Assisted Flowing Atmospheric-Pressure Afterglow Mass Spectrometry (SA-FAPA-MS).

Maximilian Heide, Carsten Engelhard.

  Ambient desorption/ionization mass spectrometry (ADI-MS) has been broadly applied to accomplish direct analysis without sample preparation or separation. However, quantification capabilities and analytical performance are sometimes limited. Here, we report signal enhancement effects and improved quantification capabilities in plasma-based ADI-MS, when a flowing atmospheric-pressure afterglow (FAPA) source is used to probe analytes on tailored thin-layer chromatography (TLC) plates. It was found that quantitative results could be achieved when the TLC plate merely served as a sampling plate without a preceding separation step. Specifically, the dynamic response of caffeine, nicotine, acetaminophen, and progesterone was investigated with FAPA-MS on a variety of different TLC surfaces (normal-phase silica, reversed-phase-modified silica, cyano [CN]-modified silica, and dimethyl [RP2]-modified silica). All analytes were studied as single-analyte standards and in a multianalyte mixture to evaluate the effect of sample plates and sample matrix on analytical performance and competitive ionization processes. Overall, dimethyl (RP2)- and CN-modified silica resulted in superior performance compared to other TLC materials. After careful optimization and without the use of internal standards, linear ranges of five orders of magnitude were accessible for caffeine and nicotine. Limits of detection down to femtomole amounts of analyte were achieved. Quantitation limits using RP2-TLC and FAPA-MS were 0.062, 0.062l, 0.31, and 14 pmol for caffeine, nicotine, progesterone, and acetaminophen, respectively. Interestingly, the presence of nicotine at relatively high amounts reduced the signal of the other analytes, an observation that was found to correlate with the differences in the enthalpy of vaporization (ΔHvap) and proton affinity. To prove the quantitative capabilities, nicotine quantification in a real matrix-heavy e-liquid sample was demonstrated using an isotopically labeled standard. The use of TLC-based surfaces with FAPA-MS can aid in the direct and quantitative mass spectrometric investigation of complex mixtures.

Keywords:  Ambient desorption/ionization; electronic cigarette e-liquid; flowing atmospheric-pressure afterglow; mass spectrometry; surface-assisted

DOI:  https://doi.org/10.1177/00037028231168617
J AOAC Int. 2023 May 12. pii: qsad057. [Epub ahead of print]

Sensitive Instrumental Method for Quantitative Determination of High-Brominated Flame Retardants in Human Serum Samples.

Cristina Grande, Argelia Castaño, Juan José Ramos.

BACKGROUND: High-brominated flame retardants can be released into the environment from consumer products, such as electric and electronic equipment, and enter the human body by different pathways. Due to their toxicity and the regulations, is very relevant to know their levels and trends in human samples. However, chromatographic serum analysis of some of these compounds represents nowadays a challenge in general population.
OBJECTIVE: To optimise and validate an instrumental method based on gas chromatography coupled to mass spectrometry, which, together with, a simple sample preparation procedure allows the analysis of decabromodiphenyl ether (BDE-209), decabromodiphenyl ethane (DBDPE) and tetrabromobisphenol A-bis(2,3-dibromopropyl ether) (TBBPA-DBPE) in human serum samples from the general population.
METHODS: In order to minimise the high degradation during instrumental analysis, GC parameters such as injection volumes, carrier flow rates and column lengths, were assessed and optimized. This instrumental approach in combination with solid-phase extraction (SPE) followed by multi-layer silica gel column purification allowed satisfactory analysis using only 1 mL of serum.
RESULTS: The performance of the complete method was evaluated at three spiking levels, 0.01, 0.05 and 0.2 ng/mL Recoveries in the range 87-108% were obtained whereas the relative standard deviation in interday measurements, were in general lower than 19%. Limits of detection were in the range of 0.0045-0.0070 ng/mL. The optimized procedure was successfully applied to the determination of the investigated pollutants in real human samples of general population.
CONCLUSION: The proposed method could contribute to the inclusion of these environmental pollutants in human biomonitoring studies, increasing the knowledge of levels and trends in the general population.
HIGHLIGHTS: GC-MS parameters optimization to minimise instrumental analytes degradation.Successful application to human serum samples from the general population.Tetrabromobisphenol A bis(2,3-dibromopropyl ether) human serum levels are reported first time.

DOI: https://doi.org/10.1093/jaoacint/qsad057
J Proteome Res. 2023 May 10.

Annotation of Dipeptides and Tripeptides Derivatized via Dansylation Based on Liquid Chromatography-Mass Spectrometry and Iterative Quantitative Structure Retention Relationship.

Xin Lu, Peng Dou, Chao Li, Fujian Zheng, Lina Zhou, Xiaoyu Xie, Zixuan Wang, Guowang Xu.

  Small peptides such as dipeptides and tripeptides show various biological activities in organisms. However, methods for identifying dipeptides/tripeptides from complex biological samples are lacking. Here, an annotation strategy involving the derivatization of dipeptides and tripeptides via dansylation was suggested based on liquid chromatography-mass spectrometry (LC-MS) and iterative quantitative structure retention relationship (QSRR) to choose dipeptides/tripeptides by using a small number of standards. First, the LC-autoMS/MS method and initial QSRR model were built based on 25 selected grid-dipeptides and 18 test-dipeptides. To achieve high-coverage detection, dipeptide/tripeptide pools containing abundant dipeptides/tripeptides were then obtained from four dansylated biological samples including serum, tissue, feces, and soybean paste by using the parameter-optimized LC-autoMS/MS method. The QSRR model was further optimized through an iterative train-by-pick strategy. Based on the specific fragments and tR tolerances, 198 dipeptides and 149 tripeptides were annotated. The dipeptides at lower annotation levels were verified by using authentic standards and grid-correlation analysis. Finally, variation in serum dipeptides/tripeptides of three different liver diseases including hepatitis B infection, liver cirrhosis, and hepatocellular carcinoma was characterized. Dipeptides with N-prolinyl, C-proline, N-glutamyl, and N-valinyl generally increased with disease severity. In conclusion, this study provides an efficient strategy for annotating dipeptides/tripeptides from complex samples.

Keywords:  LC−MS; derivatization; dipeptides; quantitative structure retention relationship; tripeptides

DOI:  https://doi.org/10.1021/acs.jproteome.3c00002
Curr Drug Metab. 2023 May 08.

Global xenobiotic profiling of rat plasma using untargeted metabolomics and background subtraction-based approaches: Method evaluation and comparison.

Xiaojuan Jiang, Simian Chen, Mingshe Zhu, Caisheng Wu.

   BACKGROUND: Global xenobiotic profiling (GXP) is to detect and structurally characterize all xenobiotics in biological samples using mainly liquid chromatography-high resolution mass spectrometry (LC-HRMS) based methods. GXP is highly needed in drug metabolism study, food safety testing, forensic chemical analysis, and exposome research. For detecting known or predictable xenobiotics, targeted LC-HRMS data processing methods based on molecular weights, mass defects and fragmentations of analytes are routinely employed. For profiling unknown xenobiotics, untargeted and LC-HRMS based metabolomics and background subtraction-based approaches are required.
OBJECTIVE: This study aimed to evaluate the effectiveness of untargeted metabolomics and the precise and thorough background subtraction (PATBS) in GXP of rat plasma.
METHODS: Rat plasma samples collected from an oral administration of nefazodone (NEF) or Glycyrrhizae Radix et Rhizoma (Gancao, GC) were analyzed by LC-HRMS. NEF metabolites and GC components in rat plasma were thoroughly searched and characterized via processing LC-HRMS datasets using targeted and untargeted methods.
RESULTS: PATBS detected 68 NEF metabolites and 63 GC components, while the metabolomic approach (MS-DIAL) found 67 NEF metabolites and 60 GC components in rat plasma. The two methods found 79 NEF metabolites and 80 GC components with 96% and 91% successful rates, respectively.
CONCLUSION: Metabolomics methods are capable of GXP and measuring alternations of endogenous metabolites in a group of biological samples, while PATBS is more suited for sensitive GXP of a single biological sample. A combination of metabolomics and PATBS approaches can generate better results in the untargeted profiling of unknown xenobiotics.

Keywords:  drug metabolism; mass defect filtering; metabolomics; precise and thorough background subtraction; unpredicted metabolites

DOI:  https://doi.org/10.2174/1389200224666230508122240
Nat Commun. 2023 May 10. 14(1): 2692

Spatially resolved multi-omics highlights cell-specific metabolic remodeling and interactions in gastric cancer.

Chenglong Sun, Anqiang Wang, Yanhe Zhou, Panpan Chen, Xiangyi Wang, Jianpeng Huang, Jiamin Gao, Xiao Wang, Liebo Shu, Jiawei Lu, Wentao Dai, Zhaode Bu, Jiafu Ji, Jiuming He.

Mapping tumor metabolic remodeling and their spatial crosstalk with surrounding non-tumor cells can fundamentally improve our understanding of tumor biology, facilitates the designing of advanced therapeutic strategies. Here, we present an integration of mass spectrometry imaging-based spatial metabolomics and lipidomics with microarray-based spatial transcriptomics to hierarchically visualize the intratumor metabolic heterogeneity and cell metabolic interactions in same gastric cancer sample. Tumor-associated metabolic reprogramming is imaged at metabolic-transcriptional levels, and maker metabolites, lipids, genes are connected in metabolic pathways and colocalized in the heterogeneous cancer tissues. Integrated data from spatial multi-omics approaches coherently identify cell types and distributions within the complex tumor microenvironment, and an immune cell-dominated "tumor-normal interface" region where tumor cells contact adjacent tissues are characterized with distinct transcriptional signatures and significant immunometabolic alterations. Our approach for mapping tissue molecular architecture provides highly integrated picture of intratumor heterogeneity, and transform the understanding of cancer metabolism at systemic level.

DOI: https://doi.org/10.1038/s41467-023-38360-5