bims-metlip 2020-11-22 papers

bims-metlip

Biomed News

on Methods and protocols in metabolomics and lipidomics

Issue of 2020‒11‒22
seventeen papers selected by
Sofia Costa
Cold Spring Harbor Laboratory

Evaluation of Different Tandem MS Acquisition Modes to Support Metabolite Annotation in Human Plasma Using Ultra High-Performance Liquid Chromatography High-Resolution Mass Spectrometry for Untargeted Metabolomics.
Derivatization-based sample-multiplexing for enhancing throughput in liquid chromatography/tandem mass spectrometry quantification of metabolites: an overview.
Chemically informed analyses of metabolomics mass spectrometry data with Qemistree.
Rapid orthogonal screening of forensic drugs using a compact UHPLC-PDA/SQD; a complement to GC-MS.
A graph density-based strategy for features fusion from different peak extract software to achieve more metabolites in metabolic profiling from high-resolution mass spectrometry.
Development and Application of High-Throughput Single Cell Lipid Profiling: A Study of SNCA-A53T Human Dopamine Neurons.
High Throughput Targeted Metabolomics Panels to Support Large Studies.
Selective and reliable determination of obacunone in rat plasma using solid phase extraction by liquid chromatography tandem mass spectrometry: application to a pharmacokinetic study.
Towards a More Reliable Identification of Isomeric Metabolites Using Pattern Guided Retention Validation.
Targeted and untargeted quantification of quorum sensing signalling molecules in bacterial cultures and biological samples via HPLC-TQ MS techniques.
Uncovering the complexity of the yeast lipidome by means of nLC/NSI-MS/MS.
Rapid simultaneous determination of gut microbial phenylalanine, tyrosine, and tryptophan metabolites in rat serum, urine, and faeces using LC-MS/MS and its application to a type 2 diabetes mellitus study.
Delineation of Isomers by the 13C Shifts in Ion Mobility Spectra.
Standardizing and increasing the utility of lipidomics: a look to the next decade.
High Precision Sulfur Metabolomics Innovated by a New Specific Probe for Trapping Reactive Sulfur Species.
Metabolite-Investigator: An integrated userfriendly workflow for metabolomics multi-study analysis.
An improved method for the separation of carotenoids and carotenoid isomers by LC-MS.

Metabolites. 2020 Nov 15. pii: E464. [Epub ahead of print]10(11):

Evaluation of Different Tandem MS Acquisition Modes to Support Metabolite Annotation in Human Plasma Using Ultra High-Performance Liquid Chromatography High-Resolution Mass Spectrometry for Untargeted Metabolomics.

Julian Pezzatti, Víctor González-Ruiz, Julien Boccard, Davy Guillarme, Serge Rudaz.

  Ultra-high performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC-HRMS) is a powerful and essential technique for metabolite annotation in untargeted metabolomic applications. The aim of this study was to evaluate the performance of diverse tandem MS (MS/MS) acquisition modes, i.e., all ion fragmentation (AIF) and data-dependent analysis (DDA), with and without ion mobility spectrometry (IM), to annotate metabolites in human plasma. The influence of the LC separation was also evaluated by comparing the performance of MS/MS acquisition in combination with three complementary chromatographic separation modes: reversed-phase chromatography (RPLC) and hydrophilic interaction chromatography (HILIC) with either an amide (aHILIC) or a zwitterionic (zHILIC) stationary phase. RPLC conditions were first chosen to investigate all the tandem MS modes, and we found out that DDA did not provide a significant additional amount of chemical coverage and that cleaner MS/MS spectra can be obtained by performing AIF acquisitions in combination with IM. Finally, we were able to annotate 338 unique metabolites and demonstrated that zHILIC was a powerful complementary approach to both the RPLC and aHILIC chromatographic modes. Moreover, a better analytical throughput was reached for an almost negligible loss of metabolite coverage when IM-AIF and AIF using ramped instead of fixed collision energies were used.

Keywords:  high-resolution mass spectrometry; human plasma; ion mobility mass spectrometry; metabolite annotation; metabolomics; tandem mass spectrometry; ultra-high performance liquid chromatography

DOI:  https://doi.org/10.3390/metabo10110464
J Chromatogr A. 2020 Nov 05. pii: S0021-9673(20)30953-5. [Epub ahead of print]1634 461679

Derivatization-based sample-multiplexing for enhancing throughput in liquid chromatography/tandem mass spectrometry quantification of metabolites: an overview.

Tatsuya Higashi, Shoujiro Ogawa.

  The quantification of metabolites in various samples, including body fluids, tissues, cells, and foodstuffs, contributes to our understanding of their biological activities and roles in the body, diagnosis for many diseases, drug and biomarker discovery, and many aspects of human health. Liquid chromatography (LC)/tandem mass spectrometry (MS/MS) is the most powerful and reliable methodology for the quantification of metabolites due to its high specificity and sensitivity, and broad coverage of various compounds. Derivatization often makes the quantification power of LC/MS/MS stronger due to the desirable LC behavior and enhanced MS/MS detectability of the derivatized metabolites. On the other hand, LC/MS/MS-based quantification has room for improvement regarding its analysis throughput. Derivatization is also a promising approach to overcome this drawback; the multiplexing of samples in the same LC/MS/MS injection, which is achieved by derivatization of multiple samples with multiple well-designed reagents, can enhance the throughput. Based on this background, this article reviews the derivatization-based sample-multiplexing strategy, especially the characteristics and applications of the derivatization reagents, for the LC/MS/MS quantification of metabolites. This strategy has been used for the relative and absolute quantification of a variety of metabolites, and expansion of the coverage of metabolites.

Keywords:  Derivatization; LC/MS/MS; Metabolite; Quantification; Sample-multiplexing; Throughput

DOI:  https://doi.org/10.1016/j.chroma.2020.461679
Nat Chem Biol. 2020 Nov 16.

Chemically informed analyses of metabolomics mass spectrometry data with Qemistree.

Anupriya Tripathi, Yoshiki Vázquez-Baeza, Julia M Gauglitz, Mingxun Wang, Kai Dührkop, Mélissa Nothias-Esposito, Deepa D Acharya, Madeleine Ernst, Justin J J van der Hooft, Qiyun Zhu, Daniel McDonald, Asker D Brejnrod, Antonio Gonzalez, Jo Handelsman, Markus Fleischauer, Marcus Ludwig, Sebastian Böcker, Louis-Félix Nothias, Rob Knight, Pieter C Dorrestein.

Untargeted mass spectrometry is employed to detect small molecules in complex biospecimens, generating data that are difficult to interpret. We developed Qemistree, a data exploration strategy based on the hierarchical organization of molecular fingerprints predicted from fragmentation spectra. Qemistree allows mass spectrometry data to be represented in the context of sample metadata and chemical ontologies. By expressing molecular relationships as a tree, we can apply ecological tools that are designed to analyze and visualize the relatedness of DNA sequences to metabolomics data. Here we demonstrate the use of tree-guided data exploration tools to compare metabolomics samples across different experimental conditions such as chromatographic shifts. Additionally, we leverage a tree representation to visualize chemical diversity in a heterogeneous collection of samples. The Qemistree software pipeline is freely available to the microbiome and metabolomics communities in the form of a QIIME2 plugin, and a global natural products social molecular networking workflow.

DOI: https://doi.org/10.1038/s41589-020-00677-3
Forensic Sci Int. 2020 Nov 01. pii: S0379-0738(20)30427-8. [Epub ahead of print] 110565

Rapid orthogonal screening of forensic drugs using a compact UHPLC-PDA/SQD; a complement to GC-MS.

Li Li, Ximena Quintero.

  With the recent development of hand-held and miniature mass spectrometers, low cost and compact mass detectors have become more available and accessible for on-site and routine laboratory use. Here we present a rapid ultra-high performance liquid chromatography-photodiode array/mass spectrometry (UHPLC-PDA/MS) method for the routine screening of a wide variety of illicit drugs using a small and cost effective single quadrupole MS (SQD) with electron spray ionization (ESI). Two libraries for common drugs of forensic interest, a PDA library including retention time (RT) and PDA spectra and a MS library including RT and [M+H]+/[M-H]-, were developed. Using a BEH phenyl column and gradient elution of acetonitrile and 0.1% formic acid, drugs of forensic interest were detected within 8.5min and identified based on their RT/RRT to an internal standard (Codeine-d6), UV spectrum, and/or MS spectrum/(de)protonated molecular mass. The method proved to be efficient, reproducible, and sensitive with a limit of detection (LOD) ≤0.5μg/mL for untargeted screening using PDA and MS in full scan mode and ≤0.1μg/mL for targeted screening by MS in select ion recording (SIR) mode. Improved isomer discrimination was achieved, when a second injection and separation by a charged column (CSH C18) was incorporated into the same acquisition sequence. The method was applied to 20 seized drugs with similar detection limits and identifications by GC-MS. Using an orthogonal separation technique and dual detection systems, the UHPLC-PDA/SQD method serves as an attractive technique for a direct and fast screening of illicit drugs with excellent discrimination power and detection capacity. The developed method can be an alternative screening method to GC-FID and complementary technique to GC-MS for routine forensic drug screening.

Keywords:  Compact mass spectrometry; Forensic drug screening; Ultra-high performance liquid chromatography-photodiode array/mass spectrometry

DOI:  https://doi.org/10.1016/j.forsciint.2020.110565
Anal Chim Acta. 2020 Dec 01. pii: S0003-2670(20)30950-8. [Epub ahead of print]1139 8-14

A graph density-based strategy for features fusion from different peak extract software to achieve more metabolites in metabolic profiling from high-resolution mass spectrometry.

Ran Ju, Xinyu Liu, Fujian Zheng, Xinjie Zhao, Xin Lu, Xiaohui Lin, Zhongda Zeng, Guowang Xu.

  In metabolomics study, it is not easy to extract the metabolites from data of ultra high-performance liquid chromatography-high-resolution mass spectrometry, especially for those with low abundance. Different software for peak recognition and matching use different algorithms, leading to different extract results. Therefore, integration of results from different software can obtain richer metabolome information, but the redundant features should be removed. In this study, an integrated strategy of fusing features and removing redundancy based on graph density (FRRGD) was proposed. A graph is used to cover the ion features generated by two open access software (XCMS, MZmine 2) and a software (SIEVE) from an instrument vendor, and redundant features were removed by searching the maximal complete sub-graphs. A standard mixture containing 41 metabolites and a spontaneous urine were utilized to develop the method and demonstrate its usefulness. For the standard mixture, 19, 19 and 27 metabolites were extracted by XCMS, MZmine 2 and SIEVE, respectively. After fusion by FRRGD, 37 metabolites were obtained. For the diluted spontaneous urine sample, 1103, 1500 and 387 metabolites were extracted by XCMS, MZmine 2 and SIEVE, respectively, FRRGD produced 1619 metabolites which were much more than individual software, significantly increasing metabolome coverage. The proposed FRRGD shows a great prospect as a new data processing strategy for metabolomics study.

Keywords:  Graph density; Low abundant metabolites; Mass spectrometry; Metabolic profiling; Removal of redundancy; Untargeted metabolomics

DOI:  https://doi.org/10.1016/j.aca.2020.09.029
iScience. 2020 Nov 20. 23(11): 101703

Development and Application of High-Throughput Single Cell Lipid Profiling: A Study of SNCA-A53T Human Dopamine Neurons.

Stuart G Snowden, Hugo J R Fernandes, Josh Kent, Stefanie Foskolou, Peri Tate, Sarah F Field, Emmanouil Metzakopian, Albert Koulman.

  Advances in single cell genomics and transcriptomics have shown that at tissue level there is complex cellular heterogeneity. To understand the effect of this inter-cell heterogeneity on metabolism it is essential to develop a single cell lipid profiling approach that allows the measurement of lipids in large numbers of single cells from a population. This will provide a functional readout of cell activity and membrane structure. Using liquid extraction surface analysis coupled with high-resolution mass spectrometry we have developed a high-throughput method for untargeted single cell lipid profiling. This technological advance highlighted the importance of cellular heterogeneity in the functional metabolism of individual human dopamine neurons, suggesting that A53T alpha-synuclein (SNCA) mutant neurons have impaired membrane function. These results demonstrate that this single cell lipid profiling platform can provide robust data that will expand the frontiers in biomedical research.

Keywords:  Cellular Neuroscience; Lipidomics; Metabolomics; Molecular Neuroscience

DOI:  https://doi.org/10.1016/j.isci.2020.101703
J Biomol Tech. 2020 Aug;31(Suppl): S20-S21

High Throughput Targeted Metabolomics Panels to Support Large Studies.

Suraj Dhungana, Billy Molloy, Rob Plumb, Jinxi Li.

There is increasing need for throughput as the metabolomics studies are getting larger. Throughput can be achieved on the analytical side by using rapid methods or speeding up the data analysis and metabolite identification steps. Series of rapid UPLC-MS/MS methods have been developed on a single platform with identical analysis workflow for high throughput measurement of derivatized amino acids, acylcarnitines, bile acids, free fatty acids, tryptophan metabolites in human serum to support metabolomics research. The separation of isomers (amino acids and bile acids) are achieved in analytical runtimes of <4mins making these methods powerful and are well suited for a Core laboratory. Here we discuss these methods and demonstrate their usability for the analysis of metabolites in patient derived serum samples during targeted multi-omics analysis. Sample preparation involved protein precipitation with methanol (1:4 serum:methanol) for the extraction of acylcarnitines, bile acids, and free fatty acids. For amino acid analysis, serum samples were prepared using the Waters™ AccQTag Kit following the Kit protocol. Tryptophan metabolites sample preparation was achieved using Oasis HLB PRiME µElution Plate. UPLC separation was performed on an ACQUITY UPLC I-Class System (fixed loop), equipped with a CORTECS T3 2.7 µm (2.1 x 30 mm) analytical column. A 2 µ Lextract was injected at a flow rate of 1.3 mL/min. Mobile phase A was 0.01% formic acid (aq) and Mobile phase B was 50% isopropanol in acetonitrile containing 0.01% formic acid. The LC gradient and column equilibration times were optimized for each class of metabolites. The analytical column temperature was maintained at 60°C. Multiple Reaction Monitoring (MRM) analyses were performed using a Xevo TQ-S micro mass spectrometer. All experiments were performed in electrospray ionization mode. Data processing was done using in TargetLynx and Skyline.
Biomed Chromatogr. 2020 Nov 20. e5031

Selective and reliable determination of obacunone in rat plasma using solid phase extraction by liquid chromatography tandem mass spectrometry: application to a pharmacokinetic study.

Qian Li, Yong Gao, Maoyu Wang.

  This study was concerned with the development of a highly selective, sensitive and fast liquid chromatography tandem mass spectrometric (LC-MS/MS) method for the determination of obacunone in rat plasma. Sample preparation was accomplished by a simple solid phase extraction (SPE) procedure. Chromatographic separation was carried out on an ACQUITY BEH C18 column using acetonitrile/methanol (1:1, v/v) and 0.1% formic acid in water as mobile phase delivered at a flow rate of 0.4 mL/min. Quantification was performed with multiple reactions monitoring in positive ion mode with the precursor-to-product ion transitions at m/z 455.2 > 161.1 for obacunone and m/z 515.2 > 161.1 for nomilin (internal standard). The assay was demonstrated to be linear over the concentration range of 0.1-1000 ng/mL with correlation coefficient > 0.999 (r > 0.999). The intra- and inter-day accuracy ranged from -8.33% to 10.40%, while the precision was no more than 10.41%. The mean extraction recovery was > 75.32% and the assay was free of matrix effect. The validated LC-MS/MS method was successfully applied to the pharmacokinetic study of obacunone in rats after oral and intravenous administrations. The oral bioavailability of obacunone was 13.59%.

Keywords:  LC-MS/MS; Obacunone; pharmacokinetics; solid phase extraction

DOI:  https://doi.org/10.1002/bmc.5031
Metabolites. 2020 Nov 12. pii: E457. [Epub ahead of print]10(11):

Towards a More Reliable Identification of Isomeric Metabolites Using Pattern Guided Retention Validation.

Tobias Opialla, Stefan Kempa, Matthias Pietzke.

  Reliable analyte identification is critical in metabolomics experiments to ensure proper interpretation of data. Due to chemical similarity of metabolites (as isobars and isomers) identification by mass spectrometry or chromatography alone can be difficult. Here we show that isomeric compounds are quite common in the metabolic space as given in common metabolite databases. Further, we show that retention information can shift dramatically between different experiments decreasing the value of external or even in-house compound databases. As a consequence the retention information in compound databases should be updated regularly, to allow a reliable identification. To do so we present a feasible and budget conscious method to guarantee updates of retention information on a regular basis using well designed compound mixtures. For this we combine compounds in "Ident-Mixes", showing a way to distinctly identify chemically similar compounds through combinatorics and principle of exclusion. We illustrate the feasibility of this approach by comparing Gas chromatography (GC)-columns with identical properties from three different vendors and by creating a compound database from measuring these mixtures by Liquid chromatography-mass spectrometry (LC-MS). The results show the high influence of used materials on retention behavior and the ability of our approach to generate high quality identifications in a short time.

Keywords:  GC–MS; LC–MS; chromatography; identification; metabolomics; retention index; standardization

DOI:  https://doi.org/10.3390/metabo10110457
Anal Bioanal Chem. 2020 Nov 18.

Targeted and untargeted quantification of quorum sensing signalling molecules in bacterial cultures and biological samples via HPLC-TQ MS techniques.

Federica Dal Bello, Michael Zorzi, Riccardo Aigotti, Davide Medica, Vito Fanelli, Vincenzo Cantaluppi, Eleonora Amante, Viviana Teresa Orlandi, Claudio Medana.

  Quorum sensing (QS) is the ability of some bacteria to detect and to respond to population density through signalling molecules. QS molecules are involved in motility and cell aggregation mechanisms in diseases such as sepsis. Few biomarkers are currently available to diagnose sepsis, especially in high-risk conditions. The aim of this study was the development of new analytical methods based on liquid chromatography-mass spectrometry for the detection and quantification of QS signalling molecules, including N-acyl homoserine lactones (AHL) and hydroxyquinolones (HQ), in biofluids. Biological samples used in the study were Pseudomonas aeruginosa bacterial cultures and plasma from patients with sepsis. We developed two MS analytical methods, based on neutral loss (NL) and product ion (PI) experiments, to identify and characterize unknown AHL and HQ molecules. We then established a multiple-reaction-monitoring (MRM) method to quantify specific QS compounds. We validated the HPLC-MS-based approaches (MRM-NL-PI), and data were in accord with the validation guidelines. With the NL and PI MS-based methods, we identified and characterized 3 and 13 unknown AHL and HQ compounds, respectively, in biological samples. One of the newly found AHL molecules was C12-AHL, first quantified in Pseudomonas aeruginosa bacterial cultures. The MRM quantitation of analytes in plasma from patients with sepsis confirmed the analytical ability of MRM for the quantification of virulence factors during sepsis. Graphical abstract.

Keywords:  Homoserine lactones; Hydroxyquinolones; Mass spectrometry; Pseudomonas aeruginosa; Quorum sensing molecules; Triple quadrupole

DOI:  https://doi.org/10.1007/s00216-020-03040-6
Anal Chim Acta. 2020 Dec 15. pii: S0003-2670(20)31024-2. [Epub ahead of print]1140 199-209

Uncovering the complexity of the yeast lipidome by means of nLC/NSI-MS/MS.

Niklas Danne-Rasche, Stefanie Rubenzucker, Robert Ahrends.

  Saccharomyces cerevisiae is a eukaryotic model organism widely used for the investigation of fundamental cellular processes and disease mechanisms. Consequently, the lipid landscape of yeast has been extensively investigated and up to this day the lipidome is considered as rather basic. Here, we used a nLC/NSI-MS/MS method combined with a semi-autonomous data analysis workflow for an in-depth evaluation of the steady state yeast lipidome. We identified close to 900 lipid species across 26 lipid classes, including glycerophospholipids, sphingolipids, glycerolipids and sterol lipids. Most lipid classes are dominated by few high abundant species, with a multitude of lower abundant lipids contributing to the overall complexity of the yeast lipidome. Contrary to previously published datasets, odd-chain and diunsaturated fatty acyl moieties were found to be commonly incorporated in multiple lipid classes. Careful data evaluation furthermore revealed the presence of putative new lipid species such as MMPSs (mono-methylated phosphatidylserine), not yet described in yeast. Overall, our analysis achieved a more than 4-fold increase in lipid identifications compared to previous approaches, underscoring the use of nLC/NSI-MS/MS methods for the in-depth investigation of lipidomes.

Keywords:  Lipidomics; Nano-liquid chromatography; Saccharomyces cerevisiae; Untargeted lipidomics; Yeast lipidome; nLC/NSI-MS/MS

DOI:  https://doi.org/10.1016/j.aca.2020.10.012
Biomed Chromatogr. 2020 Nov 17. e4985

Rapid simultaneous determination of gut microbial phenylalanine, tyrosine, and tryptophan metabolites in rat serum, urine, and faeces using LC-MS/MS and its application to a type 2 diabetes mellitus study.

Baorong Zou, Yangwen Sun, Zengmei Xu, Yongda Chen, Lin Li, Lei Lin, Shaobao Zhang, Qiongfeng Liao, Zhiyong Xie.

  Gut microbial phenylalanine, tyrosine, and tryptophan metabolites are closely linked to various diseases. Monitoring the alterations of the related metabolites is vital to facilitate the understanding of pathophysiology of diseases. Herein, a rapid and sensitive assay based on LC-tandem mass spectrometry has been developed to analyze 20 gut microbial metabolites derived from phenylalanine, tyrosine, and tryptophan in rat serum, urine, and faeces. These microbial-derived metabolites were separated on a phenyl-hexyl column and simultaneously determined in a single run of 8 min. The detection limit for analytes ranged between 1.08 and 32.4 ng/mL. All calibration curves exhibited good linear relationships (R2 ≥ 0.9982). Intra- and inter-assay precision values were below 15% and accuracies ranged from 85% to 115% for all analytes. The selectivity, matrix effect, and recovery of this method were all satisfactory. The validated method was successfully applied to characterize the alterations of these metabolites in type 2 diabetes mellitus rat. In general, the developed assay is suitable for high-throughput monitoring of gut microbial phenylalanine, tyrosine, and tryptophan metabolites and provides a useful approach for exploring the mechanisms of microbial-derived metabolites in diseases.

Keywords:  gut microbial metabolites; liquid chromatography-tandem mass spectrometry; quantitative assay; type 2 diabetes mellitus

DOI:  https://doi.org/10.1002/bmc.4985
J Am Soc Mass Spectrom. 2020 Nov 17.

Delineation of Isomers by the 13C Shifts in Ion Mobility Spectra.

Pratima Pathak, Anastasia Sarycheva, Matthew A Baird, Alexandre A Shvartsburg.

Mass spectrometry (MS) and isotopes were intertwined for a century, with stable isotopes central to many MS identification and quantification protocols. In contrast, the analytical separations including ion mobility spectrometry (IMS) largely ignored isotopes, partly because of insufficient resolution. We recently delineated various halogenated aniline isomers by structurally specific splitting in FAIMS spectra. While this capability hinges on the 13C shifts, all preceding studies leveraged 37Cl or 81Br to enhance the differentiation. However, such abundant heavy isotopes are absent from typical organic compounds. With single I isotope, iodinated organics generate similar isotopic envelopes dominated by the 13C atoms. Here, we distinguish the three monoiodoaniline isomers based on the shifts solely for one or two 13C atoms. The differentiation may be somewhat improved using multipoint peak position descriptions for more reproducible shifts. The interisomer order of shifts differs from those for chlorinated or brominated analogues, showcasing the specificity of approach. We also investigated the mass scaling of isotopic shifts, encountering divergent trends for different structural families.

DOI: https://doi.org/10.1021/jasms.0c00350
Expert Rev Proteomics. 2020 Nov 16.

Standardizing and increasing the utility of lipidomics: a look to the next decade.

Yuqin Wang, Eylan Yutuc, William J Griffiths.

  Introduction: We present our views on the current application of mass spectrometry (MS) based lipidomics and how lipidomics can develop in the next decade to be most practical use to society. That is not to say that lipidomics has not already been of value. In-fact, in its earlier guise as metabolite profiling most of the pathways of steroid biosynthesis were uncovered and via focused lipidomics many inborn errors of metabolism are routinely clinically identified. However, can lipidomics be extended to improve biochemical understanding of, and to diagnose, the most prevalent diseases of the 21st century? Areas covered: We will highlight the concept of "level of identification" and the equally crucial topic of "quantification". Only by using a standardised language for these terms can lipidomics be translated to fields beyond academia. We will remind the lipid scientist of the value of chemical derivatisation, a concept exploited since the dawn of lipid biochemistry. Expert opinion: Only by agreement of the concepts of identification and quantification and their incorporation in lipidomics reporting can lipidomics maximise its value.

Keywords:  Clinical chemistry; identification; imaging; in-born errors of metabolism; lipids; mass spectrometry; medicine; quantification

DOI:  https://doi.org/10.1080/14789450.2020.1847086
Antioxid Redox Signal. 2020 Nov 16.

High Precision Sulfur Metabolomics Innovated by a New Specific Probe for Trapping Reactive Sulfur Species.

Shingo Kasamatsu, Tomoaki Ida, Taisei Koga, Kosho Asada, Hozumi Motohashi, Hideshi Ihara, Takaaki Akaike.

AIMS: Persulfides and other reactive sulfur species are endogenously produced in large amounts in vivo and participate in multiple cellular functions underlying physiological and pathological conditions. In the current study, we aimed to develop an ideal alkylating agent for use in sulfur metabolomics, particularly targeting persulfides and other reactive sulfur species, with minimal artifactual decomposition.RESULTS: We synthesized a tyrosine-based iodoacetamide derivative, N-iodoacetyl L-tyrosine methyl ester (TME-IAM), which reacts with the thiol residue of cysteine identically to that of β-(4-hydroxyphenyl)ethyl iodoacetamide (HPE-IAM), a commercially available reagent. Our previous study revealed that although various electrophilic alkylating agents readily decomposed polysulfides, HPE-IAM exceptionally stabilized the polysulfides by inhibiting their alkaline hydrolysis. The newly synthesized TME-IAM stabilizes oxidized glutathione tetrasulfide more efficiently than other alkylating agents, including HPE-IAM, iodoacetamide, and monobromobimane. In fact, our quantitative sulfur-related metabolome analysis showed that TME-IAM is a more efficient trapping agent for endogenous persulfides/polysulfides containing a larger number of sulfur atoms in mouse liver and brain tissues compared to HPE-IAM. Innovation and Conclusion: We developed a novel iodoacetamide derivative which is the most ideal reagent developed to date for detecting endogenous persulfides/polysulfides formed in biological samples, such as cultured cells, tissues, and plasma. This new probe may be useful for investigating the unique chemical properties of reactive persulfides, thereby enabling identification of novel reactive sulfur metabolites that remain unidentified because of their instability, and thus can be applied in high-precision sulfur metabolomics in redox biology and medicine.

DOI: https://doi.org/10.1089/ars.2020.8073
Bioinformatics. 2020 Nov 16. pii: btaa967. [Epub ahead of print]

Metabolite-Investigator: An integrated userfriendly workflow for metabolomics multi-study analysis.

Carl Beuchel, Holger Kirsten, Uta Ceglarek, Markus Scholz.

MOTIVATION: Many diseases have a metabolic background, which is increasingly investigated due to improved measurement techniques allowing high-throughput assessment of metabolic features in several body fluids. Integrating data from multiple cohorts is of high importance to obtain robust and reproducible results. However, considerable variability across studies due to differences in sampling, measurement techniques and study populations needs to be accounted for.RESULTS: We present Metabolite-Investigator, a scalable analysis workflow for quantitative metabolomics data from multiple studies. Our tool supports all aspects of data pre-processing including data integration, cleaning, transformation, batch analysis as well as multiple analysis methods including uni- and multivariable factor-metabolite associations, network analysis and factor prioritization in one or more cohorts. Moreover, it allows identifying critical interactions between cohorts and factors affecting metabolite levels and inferring a common covariate model, all via a graphical user interface.
AVAILABILITY: We constructed Metabolite-Investigator as a free and open web-tool and stand-alone Shiny-app. It is hosted at https://apps.health-atlas.de/metabolite-investigator/, the source code is freely available at https://github.com/cfbeuchel/Metabolite-Investigator.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

DOI: https://doi.org/10.1093/bioinformatics/btaa967
J Sep Sci. 2020 Nov 17.

An improved method for the separation of carotenoids and carotenoid isomers by LC-MS.

Shuang Li, Xinyi Tang, Yingying Lu, Jilin Xu, Juanjuan Chen, Haimin Chen.

  Carotenoids consists of a series of conjugated isoprene units that are characteristically highly conjugated through double bonds, leading to the formation of many isomers that are susceptible to oxidation and other chemical modifications. Extreme hydrophobicity and high complexity make carotenoids difficult to identify and quantify. We implemented the use of a common Syncronis C18 column with strong eluting solvent, here isopropanol, to successfully separate a mixture of 23 carotenoids standards with different structural properties. In addition, the method differentiated between three groups of isomeric carotenoids (lycopene/δ-carotene/γ-carotene/ε-carotene/α-carotene/β-carotene, α-cryptoxanthin/β-cryptoxanthin, and zeaxanthin/lutein) by optimizing the gradient profile and using LC-MS. The LOD ranged from 0.05 to 5.51 ng/mL, and the recovery of carotenoids in Mytilus coruscus was from 63.54 to 93.25%, with SDs less than 10%. Twenty-five carotenoids were detected with a total content of 857 ± 55.1 mg/kg, and three isomeric carotenoids were identified: ε-carotene, α-carotene, and β-carotene. Our results show that this methodology is a significant improvement over other alternatives for analyzing carotenoids because of its compatibility with carotenoids of different categories, and most importantly, its ability to resolve isomeric carotenes, which is significant not only for assessing carotenoid species, but also for the tracing of metabolic pathways of carotenoids. This article is protected by copyright. All rights reserved.

Keywords:  Mytilus coruscus; carotenoids; high-resolution mass spectrometry; high performance liquid chromatography; isomeric carotenoids

DOI:  https://doi.org/10.1002/jssc.202000902