bims-metlip Biomed News
on Methods and protocols in metabolomics and lipidomics
Issue of 2022‒08‒14
twenty papers selected by
Sofia Costa
Matterworks
  1. Targeted analysis of sugar phosphates from glycolysis pathway by phosphate methylation with liquid chromatography coupled to tandem mass spectrometry.
  2. High-throughput single cell metabolomics and cellular heterogeneity exploration by inertial microfluidics coupled with pulsed electric field-induced electrospray ionization-high resolution mass spectrometry.
  3. Assessing the Energy Status of Low Numbers of Mammalian Cells by Capillary Electrophoresis-Mass Spectrometry.
  4. massDatabase: utilities for the operation of the public compound and pathway database.
  5. Deep learning-based pseudo-mass spectrometry imaging analysis for precision medicine.
  6. Advanced unified monophasic lipid extraction protocol with wide coverage on the polarity scale optimized for large-scale untargeted clinical lipidomics analysis of platelets.
  7. Quality-by-design approach for development of aqueous headspace microextraction GC-MS method for targeted metabolomics of small aldehydes in plasma of cardiovascular patients.
  8. Comparison of Cosine, Modified Cosine, and Neutral Loss Based Spectrum Alignment For Discovery of Structurally Related Molecules.
  9. AI/ML-driven advances in untargeted metabolomics and exposomics for biomedical applications.
  10. Graph Properties of Mass-Difference Networks for Profiling and Discrimination in Untargeted Metabolomics.
  11. Development and validation of a novel LC-MS/MS method for simultaneous quantitative determination of tyrosine kinase inhibitors in human plasma.
  12. Criteria of slope and endogenous level for selection of matrix in the quantitation of endogenous compounds by LC-MS/MS.
  13. Simultaneous determination of oxalate and citrate in urine and serum of calcium oxalate kidney stone rats by IP-RP LC-MS/MS.
  14. High sensitivity and high-confidence compound identification with a flexible BoxCar acquisition method.
  15. Introducing the Lipidomics Minimal Reporting Checklist.
  16. Critical evaluation of the role of external calibration strategies for IM-MS.
  17. Green bioanalysis: an innovative and eco-friendly approach for analyzing drugs in biological matrices.
  18. Fully Automated Unconstrained Analysis of High-Resolution Mass Spectrometry Data with Machine Learning.
  19. q value and parent energy optimization using a low-voltage ionization approach increases resolution in linear ion trap mass spectrometry.
  20. Effects of Molecular Size on Resolution in Charge Detection Mass Spectrometry.
  1. Anal Chim Acta. 2022 Aug 15. pii: S0003-2670(22)00670-5. [Epub ahead of print]1221 340099
    Targeted analysis of sugar phosphates from glycolysis pathway by phosphate methylation with liquid chromatography coupled to tandem mass spectrometry.
    Peng Li, Min Su, Madhumita Chatterjee, Michael Lämmerhofer.
      Monitoring the glycolysis pathway remains an analytical challenge as most metabolites involved are sugar phosphates. Structural similarity, instability, high polarity, and rich negative charges of sugar phosphates make LC-MS based analysis challenging. Here, we developed an improved workflow integrating uniformly 13C-labeled yeast metabolite extract, TiO2-based enrichment, differential stable isotope labeling phosphate methylation, porous graphic carbon column, and selected reaction monitoring acquisition. Uniformly 13C labeled yeast metabolite extract was used as internal standards while differential stable isotope labeled sugar phosphates worked as calibrants. The established method was validated in human plasma, platelet and cultured HeLa cells. The limits of quantification ranged between 0.25 and 0.54 pmol on column. The method was adapted and its applicability tested for human platelets in which activation with collagen-related peptide (CRP) clearly showed the upregulation of some SPx metabolites. The results document that this newly established method can be successfully used to monitor glycolysis in different biological samples. As an extension, more phosphorylated and carboxylated metabolites from the central carbon metabolism (pentose phosphate cycle, TCA cycle) were tested as well. This method showed superior performance, especially for multiple phosphorylated and carboxylated metabolites. For quantitative purpose, the concept of SPx in three sets (12C-analytes, U-13C-IS, deuterated calibrants) has the potential to be adapted for more anionic metabolites.
    Keywords:  Derivatization; Isotope labeling; Porous graphitic carbon column; Solid-phase extraction; Sugar phosphate; Targeted metabolomics
    DOI:  https://doi.org/10.1016/j.aca.2022.340099
  2. Anal Chim Acta. 2022 Aug 15. pii: S0003-2670(22)00687-0. [Epub ahead of print]1221 340116
    High-throughput single cell metabolomics and cellular heterogeneity exploration by inertial microfluidics coupled with pulsed electric field-induced electrospray ionization-high resolution mass spectrometry.
    Disheng Feng, Hang Li, Tianrun Xu, Fujian Zheng, Chunxiu Hu, Xianzhe Shi, Guowang Xu.
      Single cell metabolomics can obtain the metabolic profiles of individual cells and reveal cellular heterogeneity. However, high-throughput single-cell mass spectrometry (MS) analysis under physiological conditions remains a great challenge due to the presence of complex matrix and extremely small cell volumes. Herein, a serpentine channel microfluidic device which was designed to achieve continuous cell separation and inertial focusing, was coupled with a pulsed electric field-induced electrospray ionization-high resolution MS (PEF-ESI-HRMS) to achieve high-throughput single cell analysis. The pulsed square wave electric field was applied to realize on-line cell disruption and induce electrospray ionization. Single cells were analyzed under near-physiological conditions at a throughput of up to 80 cells min-1. More than 900 features were detected and approximately 120 metabolites were tentatively identified from a single cell. Further, by continually analyzing more than 3000 MCF7 and HepG2 cells, discrimination of different cancer cells based on their individual metabolic profiles was achieved by using the principal component analysis. The PEF-ESI-HRMS method was also applied for the analysis of single yeast cells, and more than 40 metabolites were annotated. This method is versatile and has good robustness, which is promising for high-throughput single cell metabolomics analysis.
    Keywords:  Cellular heterogeneity; High-throughput; Mass spectrometry; Microfluidic device; Single cell metabolomics
    DOI:  https://doi.org/10.1016/j.aca.2022.340116
  3. Methods Mol Biol. 2022 ;2531 203-209
    Assessing the Energy Status of Low Numbers of Mammalian Cells by Capillary Electrophoresis-Mass Spectrometry.
    Wei Zhang, Rawi Ramautar.
      Capillary electrophoresis-mass spectrometry (CE-MS) employing a sheathless porous tip interface has become a strong analytical tool for the efficient profiling of highly polar and charged metabolites in volume/material-restricted biological samples. As more and more metabolomics studies are (intrinsically) dealing with low numbers of mammalian cells, it would be important to use an additional performance metric to effectively evaluate the sampling and sample preparation procedure, in particular quenching. An established parameter to assess the sampling and sample preparation quality when working with cell cultures is the adenylate energy charge (AEC), which represents an index of the energy state of a cell. In this protocol, a CE-MS strategy is proposed for the reliable determination of the adenylate energy charge (AEC) in metabolomics studies dealing with low numbers of mammalian cells.
    Keywords:  Adenylate energy charge; Biomass-limited samples; Capillary electrophoresis; Mass spectrometry; Metabolic profiling
    DOI:  https://doi.org/10.1007/978-1-0716-2493-7_13
  4. Bioinformatics. 2022 Aug 09. pii: btac546. [Epub ahead of print]
    massDatabase: utilities for the operation of the public compound and pathway database.
    Xiaotao Shen, Chuchu Wang, Michael P Snyder.
      SUMMARY: One of the major challenges in LC-MS data is converting many metabolic feature entries to biological function information, such as metabolite annotation and pathway enrichment, which are based on the compound and pathway databases. Multiple online databases have been developed. However, no tool has been developed for operating all these databases for biological analysis. Therefore, we developed massDatabase, an R package that operates the online public databases and combines with other tools for streamlined compound annotation and pathway enrichment. massDatabase is a flexible, simple, and powerful tool that can be installed on all platforms, allowing the users to leverage all the online public databases for biological function mining. A detailed tutorial and a case study are provided in the Supplementary Materials.AVAILABILITY AND IMPLEMENTATION: https://massdatabase.tidymass.org/.
    SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
    DOI:  https://doi.org/10.1093/bioinformatics/btac546
  5. Brief Bioinform. 2022 Aug 10. pii: bbac331. [Epub ahead of print]
    Deep learning-based pseudo-mass spectrometry imaging analysis for precision medicine.
    Xiaotao Shen, Wei Shao, Chuchu Wang, Liang Liang, Songjie Chen, Sai Zhang, Mirabela Rusu, Michael P Snyder.
      Liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics provides systematic profiling of metabolic. Yet, its applications in precision medicine (disease diagnosis) have been limited by several challenges, including metabolite identification, information loss and low reproducibility. Here, we present the deep-learning-based Pseudo-Mass Spectrometry Imaging (deepPseudoMSI) project (https://www.deeppseudomsi.org/), which converts LC-MS raw data to pseudo-MS images and then processes them by deep learning for precision medicine, such as disease diagnosis. Extensive tests based on real data demonstrated the superiority of deepPseudoMSI over traditional approaches and the capacity of our method to achieve an accurate individualized diagnosis. Our framework lays the foundation for future metabolic-based precision medicine.
    Keywords:  deep-learning; diagnosis; pseudo-mass spectrometry imaging
    DOI:  https://doi.org/10.1093/bib/bbac331
  6. Anal Chim Acta. 2022 Aug 15. pii: S0003-2670(22)00726-7. [Epub ahead of print]1221 340155
    Advanced unified monophasic lipid extraction protocol with wide coverage on the polarity scale optimized for large-scale untargeted clinical lipidomics analysis of platelets.
    Xiaoqing Fu, Carlos Calderón, Tobias Harm, Meinrad Gawaz, Michael Lämmerhofer.
      Lipid extraction is a critical step in sample preparation of lipidomics studies. Biphasic liquid-liquid extraction protocol with methyl tert-butyl ether (MTBE)/methanol (MeOH) as organic solvents are widely adopted by researchers nowadays as an eco-friendly replacement of classic Folch, and Bligh&Dyer protocols. Yet, it has some limitations such as suboptimal performance for the most polar lipids (e.g. acylcarnitines), complicated handling as it requires phase separation, and is therefore non-ideal for large-scale clinical studies. To advance the extraction protocol for large-scale clinical lipidomics, in this study we explored i) 6 different extraction solvent systems, ii) distinct processing procedures (sonication, mechanical cell lysis and bead homogenizer), and iii) also 7 different reconstitution solvents. The extraction systems investigated included biphasic systems MTBE/MeOH/H2O and Hexane/2-propanol (IPA)/1 M acetic acid, and monophasic systems MTBE/MeOH/CHCl3, IPA/H2O (90% IPA), MeOH/MTBE/IPA, and IPA/H2O/MTBE as solvent system for lipid extraction of human platelets. Extraction recovery was investigated by repeated extraction cycles. Subcellular extraction efficiency was assessed by the mitochondria-specific cardiolipins. It turned out that monophasic extraction with MeOH/MTBE/IPA (1.3:1:1, v/v/v), bead homogenizer for cell disruption and MeOH/MTBE (1:1, v/v) as reconstitution solvent provide optimal cellular and subcellular extraction efficiencies for both polar (e.g. acylcarnitines) and apolar lipids (e.g. triglycerides). It is simplified (no phase separation), eco-friendly (reduced solvent consumption and no halogenated ones), fast (5 min for 24 samples in parallel), and can be easily adapted for cells, plasma, and tissue. Therefore, it has great potential for large-scale clinical lipidomics studies.
    Keywords:  Cell lysis; Cellular/subcellular lipid extraction; Clinical analysis; Green technology; Lipidomics; Monophasic lipid extraction
    DOI:  https://doi.org/10.1016/j.aca.2022.340155
  7. Anal Chim Acta. 2022 Aug 15. pii: S0003-2670(22)00747-4. [Epub ahead of print]1221 340176
    Quality-by-design approach for development of aqueous headspace microextraction GC-MS method for targeted metabolomics of small aldehydes in plasma of cardiovascular patients.
    Rasha S Hanafi, Michael Lämmerhofer.
      Lipid peroxidation products, such as short chain aldehydes, are powerful biomarkers of oxidative stress, due to the advantage of long lifetime compared to other metabolites of the lipidome. This work proposes an advanced combined derivatization/solvent-less extraction procedure from plasma followed by rapid Gas Chromatography with Mass Spectrometric detection (GC-MS). A new sample pretreatment protocol is presented which is based on a combination of aldehyde derivatization with methoxyamine under fully aqueous-based conditions of diluted plasma samples followed by headspace solid-phase microextraction (HS-SPME) which is faster compared to methods in the literature serving the same purpose. Being the smallest oximation reagent, methoxyamine derivatization does not require a silylation step of hydroxyl groups as customary and made it possible to have the shortest run times for this series of aldehydes by GC-MS. A Response Surface Methodology (RSM) is employed to optimize the HS-SPME of the aldehyde methoximes to provide insights into the Design Space (DS) of HS-SPME of aldehydes of variable chain lengths and unsaturation. The workflow includes a Quality by Design (QbD) approach for optimization of sample microextraction and derivatization methodology under fully aqueous conditions, in contrast to all reported non-aqueous tedious and long extraction methods in the literature followed by development of a rapid GC-MS assay. The optimal sample preparation obtained from the RSM, and multiple linear regression procedure involved addition of 15 mg methoxyamine (CH3ONH2) and 160 mg Na2SO4 to 0.5 mL plasma diluted to 1 mL with water in an extraction vial followed by HS-SPME using Polydimethylsiloxane/Divinylbenzene fiber at 750 rpm and 77 °C for 15 min. The developed HS-SPME-GC-MS method was validated according to FDA guidelines in SIM mode and applied for targeted determination of lipid peroxidation aldehyde metabolites in plasma of 24 cardiovascular patients vs 20 healthy controls. The run time of the GCMS method was less than 15 min and the LOQ of the 10 targeted aldehydes were 0.5 nM for decanal, 5 nM for hexanal, heptanal, octanal, citronellal and citral, 7 nM for malondialdehyde, 35 nM for 4- hydroxynonenal, 105 nM for 4- hydroxyhexenal and 500 nM for glyoxal. Hexanal, Malondialdehyde and Hydroxynonenal concentrations were significantly higher in patients (p-value<0.05) in the targeted study, while citral was significantly lower as obtained from the untargeted study. Reporting an aldehydic profile signature -whether predictive or diagnostic-for cardiovascular patients would support proper medical intervention at the initiation or progression phases of the disease when expanded on larger number of subjects.
    Keywords:  Aldehydes; Cardiovascular disease; Headspace solid phase microextraction (HS-SPME); Plasma; Quality by Design (QbD); Targeted metabolomics
    DOI:  https://doi.org/10.1016/j.aca.2022.340176
  8. J Am Soc Mass Spectrom. 2022 Aug 12.
    Comparison of Cosine, Modified Cosine, and Neutral Loss Based Spectrum Alignment For Discovery of Structurally Related Molecules.
    Wout Bittremieux, Robin Schmid, Florian Huber, Justin J J van der Hooft, Mingxun Wang, Pieter C Dorrestein.
      Spectrum alignment of tandem mass spectrometry (MS/MS) data using the modified cosine similarity and subsequent visualization as molecular networks have been demonstrated to be a useful strategy to discover analogs of molecules from untargeted MS/MS-based metabolomics experiments. Recently, a neutral loss matching approach has been introduced as an alternative to MS/MS-based molecular networking with an implied performance advantage in finding analogs that cannot be discovered using existing MS/MS spectrum alignment strategies. To comprehensively evaluate the scoring properties of neutral loss matching, the cosine similarity, and the modified cosine similarity, similarity measures of 955 228 peptide MS/MS spectrum pairs and 10 million small molecule MS/MS spectrum pairs were compared. This comparative analysis revealed that the modified cosine similarity outperformed neutral loss matching and the cosine similarity in all cases. The data further indicated that the performance of MS/MS spectrum alignment depends on the location and type of the modification, as well as the chemical compound class of fragmented molecules.
    Keywords:  cosine similarity; mass spectrometry; molecular modification; spectrum alignment
    DOI:  https://doi.org/10.1021/jasms.2c00153
  9. Cell Rep Phys Sci. 2022 Jul 20. pii: 100978. [Epub ahead of print]3(7):
    AI/ML-driven advances in untargeted metabolomics and exposomics for biomedical applications.
    Lauren M Petrick, Noam Shomron.
      Metabolomics describes a high-throughput approach for measuring a repertoire of metabolites and small molecules in biological samples. One utility of untargeted metabolomics, unbiased global analysis of the metabolome, is to detect key metabolites as contributors to, or readouts of, human health and disease. In this perspective, we discuss how artificial intelligence (AI) and machine learning (ML) have promoted major advances in untargeted metabolomics workflows and facilitated pivotal findings in the areas of disease screening and diagnosis. We contextualize applications of AI and ML to the emerging field of high-resolution mass spectrometry (HRMS) exposomics, which unbiasedly detects endogenous metabolites and exogenous chemicals in human tissue to characterize exposure linked with disease outcomes. We discuss the state of the science and suggest potential opportunities for using AI and ML to improve data quality, rigor, detection, and chemical identification in untargeted metabolomics and exposomics studies.
    DOI:  https://doi.org/10.1016/j.xcrp.2022.100978
  10. Front Mol Biosci. 2022 ;9 917911
    Graph Properties of Mass-Difference Networks for Profiling and Discrimination in Untargeted Metabolomics.
    Francisco Traquete, João Luz, Carlos Cordeiro, Marta Sousa Silva, António E N Ferreira.
      Untargeted metabolomics seeks to identify and quantify most metabolites in a biological system. In general, metabolomics results are represented by numerical matrices containing data that represent the intensities of the detected variables. These matrices are subsequently analyzed by methods that seek to extract significant biological information from the data. In mass spectrometry-based metabolomics, if mass is detected with sufficient accuracy, below 1 ppm, it is possible to derive mass-difference networks, which have spectral features as nodes and chemical changes as edges. These networks have previously been used as means to assist formula annotation and to rank the importance of chemical transformations. In this work, we propose a novel role for such networks in untargeted metabolomics data analysis: we demonstrate that their properties as graphs can also be used as signatures for metabolic profiling and class discrimination. For several benchmark examples, we computed six graph properties and we found that the degree profile was consistently the property that allowed for the best performance of several clustering and classification methods, reaching levels that are competitive with the performance using intensity data matrices and traditional pretreatment procedures. Furthermore, we propose two new metrics for the ranking of chemical transformations derived from network properties, which can be applied to sample comparison or clustering. These metrics illustrate how the graph properties of mass-difference networks can highlight the aspects of the information contained in data that are complementary to the information extracted from intensity-based data analysis.
    Keywords:  Fourier transform mass spectrometry; graph properties; mass-difference networks; metabolomics data analysis; untargeted metabolomics
    DOI:  https://doi.org/10.3389/fmolb.2022.917911
  11. J Chromatogr B Analyt Technol Biomed Life Sci. 2022 Jul 28. pii: S1570-0232(22)00298-7. [Epub ahead of print]1208 123394
    Development and validation of a novel LC-MS/MS method for simultaneous quantitative determination of tyrosine kinase inhibitors in human plasma.
    Yutao Lou, Hui Qin, Qing Hu, Yitao Chai, Hongying Zhou, Mengting Chen, Qiyue Wang, Ping Huang, Jinping Gu, Yiwen Zhang.
      The objective of this study was to develop and validate a simple, rapid, and sensitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the simultaneous determination of three tyrosine kinase inhibitors (ceritinib, osimertinib, and crizotinib) in human plasma using a single-step protein precipitation extraction. Chromatographic separation was achieved using a Waters X Bridge C18 (2.1 mm × 100 mm, 3.5 µm) and gradient elution with 0.2 % formic acid in water and acetonitrile. The total run time was 4.0 min, and the injection volume was 5 μL. The analytes were detected in the multiple reaction monitoring mode using electrospray ionization with positive ion mode. The m/z transitions of ceritinib, osimertinib, crizotinib and nilotinib were 558.0 → 433.2, 500.0 → 72.1, 450.0 → 259.3, and 530.0 → 289.1, respectively. The method was linear in the range of 2-500 ng/mL with lower limit of quantification of 2 ng/mL. Based on the guidelines on bioanalytical methods by the FDA, the validation studies demonstrated that the three analytes were both precise and accurate at four concentration levels, and the coefficient of variation was < 10.59 % and accuracy was > 88.26 %. We present a simple, rapid, and sensitive method for the simultaneous quantification of ceritinib, osimertinib, and crizotinib in human plasma by LC-MS/MS, which could be used in routine therapeutic drug monitoring.
    Keywords:  Human plasma; Liquid chromatography-tandem mass spectrometry; Non-small cell lung cancer; Single-step protein precipitation; Tyrosine kinase inhibitors
    DOI:  https://doi.org/10.1016/j.jchromb.2022.123394
  12. Bioanalysis. 2022 Jun;14(11): 807-816
    Criteria of slope and endogenous level for selection of matrix in the quantitation of endogenous compounds by LC-MS/MS.
    Allena Ji Ji, Guangxin Xu, Lin Tao, Hongqin Jenny Jiao, Rachel Elisabeth Palmer.
      Selection of the appropriate matrix for standard curve is critical for an accurate and sensitive biomarker method. Slope of a standard curve is the key factor for parallelism assessment between tested matrix and authentic matrix for LC-MS/MS assays. Here the authors have established slope criteria using a generic equation and endogenous level criteria for achieving assay sensitivity. The slope difference criterion is from -13.0 to +17.6% for LC-MS assays with ± 15% bias criteria. When the ratio of endogenous concentration in the tested matrix to the lower limit of quantitation is <4.0, the lower limit of quantitation is achievable. If these criteria are met, the tested matrix can be used for assays. The utility of the two criteria has been illustrated with case studies.
    Keywords:  LC-MS; background subtraction method; biomarker; endogenous level criterion; parallelism; pharmacokinetic assay; relative matrix effect; slope acceptance criterion; surrogate matrix
    DOI:  https://doi.org/10.4155/bio-2022-0066
  13. J Chromatogr B Analyt Technol Biomed Life Sci. 2022 Jul 26. pii: S1570-0232(22)00299-9. [Epub ahead of print]1208 123395
    Simultaneous determination of oxalate and citrate in urine and serum of calcium oxalate kidney stone rats by IP-RP LC-MS/MS.
    Wenjing Li, Jianan Zheng, Minqi Chen, Binjie Liu, Zhongqiu Liu, Lingzhi Gong.
      Oxalate and citrate in 24 h urine and serum are considered to be associated with the incidence and recurrence risk of calcium oxalate kidney stones. The quantification of oxalate and citrate contributes to understand the pathological metabolism of kidney stones and guide the early diagnosis and recurrence monitoring. Although simultaneous quantification of oxalate and citrate in urine using liquid chromatography tandem mass spectrometry (LC-MS/MS) have been reported, the optimization of chromatographic column, mobile phase and mass spectrometry (MS) parameters has not been performed. In addition, these is a lack of suitable method for simultaneous detection of oxalate and citrate both in serum and urine. Therefore, we developed a method for the simultaneous determination of oxalate and citrate in urine and serum based on ion-pairing reversed-phase (IP-RP) LC-MS/MS. Herein, five ion-pair reagents, namely, triethanolamine, dimethylbutyl amine, diisopropenyl amine, N,N-dimethylcyclohexylamine and tripropylamine, and three ion-pairing reagent (IPR) buffers, namely, acetic acid, hexafluoro-2-isopropanol, and hexafluoro-2-methyl-2-propanol, were compared in regard to their chromatographic peak abundance and separation of oxalate and citrate. Moreover, MS parameters and the multiple reaction monitoring (MRM) conditions were also evaluated and optimized to obtain the maximum peak abundance. After that, the method was validated in the linear range of 0.25-1000 µM, and the correlation coefficient was ≥ 0.99. The precision and accuracy were < 14.70% and < 19.73%, respectively. The extraction recovery was 80.53-108.79%, and the matrix effect was < 8.79%. The quality control samples were stable at room temperature for 4 h, 4 °C for 24 h, and for 3 freeze-thaw cycles. Finally, this method was applied to the determination of oxalate and citrate in the serum and urine of rats with calcium oxalate kidney stones. The establishment of a stable and effective oxalate and citrate detection method is conducive to the diagnosis and monitoring of kidney stones.
    Keywords:  Citrate; Kidney stone; Liquid chromatography tandem mass spectrometry; Oxalate
    DOI:  https://doi.org/10.1016/j.jchromb.2022.123395
  14. J Pharm Biomed Anal. 2022 Jul 29. pii: S0731-7085(22)00394-6. [Epub ahead of print]219 114973
    High sensitivity and high-confidence compound identification with a flexible BoxCar acquisition method.
    Jikang Wu, Hongxia Wang, Xueqing Zhao, Haibo Qiu, Ning Li.
      Liquid chromatography-mass spectrometry (LC-MS) is in wide use for compound identification and quantification in complex matrices. While advances in mass spectrometry and the incorporation of new acquisition methods have resulted in greatly improved detection, there is an ongoing need to expand the limits of highly sensitive and confident identification of low abundance species in complex samples. The data acquisition method known as "BoxCar" was originally designed to achieve in-depth proteome profiling on an Orbitrap mass analyzer by decomposing ions into segments with narrow m/z windows. Using this method, selected segments are packaged in C-trap and all ions are then sent to Orbitrap for detection. In this study, we developed a flexible BoxCar acquisition method by placing more segments in the low m/z range for small molecule profiling. This new MS1 acquisition method was successfully integrated with iterative data dependent MS/MS acquisition by generating an inclusion list of ions detected in the flexible BoxCar to trigger the fragmentation of parent ions. The developed acquisition method was applied to the analysis of cell culture media, which plays a key role in antibody production. This challenging goal is of critical importance, as none of the currently available methods provide a comprehensive understanding of how individual components, metabolites, and impurities associated with the cell culture process might influence recombinant antibody production. Even when present at relatively low abundance, some components or impurities in the cell culture medium could have a profound impact on the quality and titer of the antibodies produced. The complex soy hydrolysate cell culture medium used in antibody generation has not been fully characterized. Using the developed flexible BoxCar acquisition method, we achieved 90 % higher sensitivity in experiments designed to detect spiked chemical substances at low abundance at the MS1 level compared to the full scan method. Iterative data-dependent acquisition (DDA) based on the targeted inclusion list generated much higher quality MS2 spectra and facilitated confident identification of low-abundance compounds. Our method achieved a 50 % increase in MS2 coverage of compounds present at low concentrations compared to conventional DDA methods. The results of our study demonstrate that this data acquisition workflow can be easily operated on Orbitrap mass spectrometers and used as a highly effective approach to improve sensitivity and high-confidence small molecule profiling in soy hydrolysate-based cell culture medium and thus provides significant support for therapeutic monoclonal antibody production.
    Keywords:  Cell culture medium; Flexible BoxCar; Iterative data-dependent acquisition; Mass spectrometry; Small-molecule profiling; Soy hydrolysate
    DOI:  https://doi.org/10.1016/j.jpba.2022.114973
  15. Nat Metab. 2022 Aug 08.
    Introducing the Lipidomics Minimal Reporting Checklist.
    Jeffrey G McDonald, Christer S Ejsing, Dominik Kopczynski, Michal Holčapek, Junken Aoki, Makoto Arita, Masanori Arita, Erin S Baker, Justine Bertrand-Michel, John A Bowden, Britta Brügger, Shane R Ellis, Maria Fedorova, William J Griffiths, Xianlin Han, Jürgen Hartler, Nils Hoffmann, Jeremy P Koelmel, Harald C Köfeler, Todd W Mitchell, Valerie B O'Donnell, Daisuke Saigusa, Dominik Schwudke, Andrej Shevchenko, Candice Z Ulmer, Markus R Wenk, Michael Witting, Denise Wolrab, Yu Xia, Robert Ahrends, Gerhard Liebisch, Kim Ekroos.
      
    DOI:  https://doi.org/10.1038/s42255-022-00628-3
  16. Anal Bioanal Chem. 2022 Aug 12.
    Critical evaluation of the role of external calibration strategies for IM-MS.
    Max L Feuerstein, Maykel Hernández-Mesa, Younes Valadbeigi, Bruno Le Bizec, Stephan Hann, Gaud Dervilly, Tim Causon.
      The major benefits of integrating ion mobility (IM) into LC-MS methods for small molecules are the additional separation dimension and especially the use of IM-derived collision cross sections (CCS) as an additional ion-specific identification parameter. Several large CCS databases are now available, but outliers in experimental interplatform IM-MS comparisons are identified as a critical issue for routine use of CCS databases for identity confirmation. We postulate that different routine external calibration strategies applied for traveling wave (TWIM-MS) in comparison to drift tube (DTIM-MS) and trapped ion mobility (TIM-MS) instruments is a critical factor affecting interplatform comparability. In this study, different external calibration approaches for IM-MS were experimentally evaluated for 87 steroids, for which TWCCSN2, DTCCSN2 and TIMCCSN2 are available. New reference CCSN2 values for commercially available and class-specific calibrant sets were established using DTIM-MS and the benefit of using consolidated reference values on comparability of CCSN2 values assessed. Furthermore, use of a new internal correction strategy based on stable isotope labelled (SIL) internal standards was shown to have potential for reducing systematic error in routine methods. After reducing bias for CCSN2 between different platforms using new reference values (95% of TWCCSN2 values fell within 1.29% of DTCCSN2 and 1.12% of TIMCCSN2 values, respectively), remaining outliers could be confidently classified and further studied using DFT calculations and CCSN2 predictions. Despite large uncertainties for in silico CCSN2 predictions, discrepancies in observed CCSN2 values across different IM-MS platforms as well as non-uniform arrival time distributions could be partly rationalized.
    Keywords:  CCS; DFT; Ion mobility-mass spectrometry; Stable isotope labelling; Steroids
    DOI:  https://doi.org/10.1007/s00216-022-04263-5
  17. Bioanalysis. 2022 Aug 10.
    Green bioanalysis: an innovative and eco-friendly approach for analyzing drugs in biological matrices.
    Siva Nageswara Rao Gajula, Nathani Tanaaz Navin, Sasikala Talari, Chinmayee Shende, Rajesh Sonti.
      Green bioanalytical techniques aim to reduce or eliminate the hazardous waste produced by bioanalytical technologies. A well-organized and practical approach towards bioanalytical method development has an enormous contribution to the green analysis. The selection of the appropriate sample extraction process, organic mobile phase components and separation technique makes the bioanalytical method green. UHPLC-MS is the best option, whereas supercritical fluid chromatography is one of the most effective green bioanalytical procedures. Nevertheless, there remains excellent scope for further research on green bioanalytical methods. This review details the various sample preparation techniques that follow green analytical chemistry principles. Furthermore, it presents green solvents as a replacement for conventional organic solvents and highlights the strategies to convert modern analytical techniques to green methods.
    Keywords:  advanced modern analytical techniques; green analytical chemistry principles; green bioanalysis; green solvents; sample preparation techniques
    DOI:  https://doi.org/10.4155/bio-2022-0095
  18. J Am Chem Soc. 2022 Aug 08.
    Fully Automated Unconstrained Analysis of High-Resolution Mass Spectrometry Data with Machine Learning.
    Daniil A Boiko, Konstantin S Kozlov, Julia V Burykina, Valentina V Ilyushenkova, Valentine P Ananikov.
      Mass spectrometry (MS) is a convenient, highly sensitive, and reliable method for the analysis of complex mixtures, which is vital for materials science, life sciences fields such as metabolomics and proteomics, and mechanistic research in chemistry. Although it is one of the most powerful methods for individual compound detection, complete signal assignment in complex mixtures is still a great challenge. The unconstrained formula-generating algorithm, covering the entire spectra and revealing components, is a "dream tool" for researchers. We present the framework for efficient MS data interpretation, describing a novel approach for detailed analysis based on deisotoping performed by gradient-boosted decision trees and a neural network that generates molecular formulas from the fine isotopic structure, approaching the long-standing inverse spectral problem. The methods were successfully tested on three examples: fragment ion analysis in protein sequencing for proteomics, analysis of the natural samples for life sciences, and study of the cross-coupling catalytic system for chemistry.
    DOI:  https://doi.org/10.1021/jacs.2c03631
  19. J Mass Spectrom. 2022 Aug;57(8): e4876
    q value and parent energy optimization using a low-voltage ionization approach increases resolution in linear ion trap mass spectrometry.
    Simone Madama, Ermelinda Falletta, Amir Mohammad Malvandi, Kevin Arzoni, Carlo Brogna, Marco Varelli, Matteo Bertelli, Matteo Conti, Martina Larini, Federico Guidugli, Pietro Traldi, Simone Cristoni.
      In this work, the isolation step in the linear ion trap was performed using different "q values" conditions at a low collision-induced dissociation (CID) energy leading to the parent ion resolution improvements, reasonably due to better ion energy distribution. According to the results, we obtained a greater resolution and mass accuracy operating in both traditional electrospray and low voltage ionization near the q value = 0.778 and with a CID energy of 10%. This effect was evaluated with low-molecular-mass compounds (skatole and arginine). The proposed optimization yielded a superior instrument performance without adding technological complexity to mass spectrometry analyses.
    Keywords:  MS accuracy; MS resolution; ion trap; low voltage ionization; metabolites; q value
    DOI:  https://doi.org/10.1002/jms.4876
  20. Anal Chem. 2022 Aug 12.
    Effects of Molecular Size on Resolution in Charge Detection Mass Spectrometry.
    Conner C Harper, Zachary M Miller, Hyuncheol Lee, Amanda J Bischoff, Matthew B Francis, David V Schaffer, Evan R Williams.
      Instrumental resolution of Fourier transform-charge detection mass spectrometry instruments with electrostatic ion trap detection of individual ions depends on the precision with which ion energy is determined. Energy can be selected using ion optic filters or from harmonic amplitude ratios (HARs) that provide Fellgett's advantage and eliminate the necessity of ion transmission loss to improve resolution. Unlike the ion energy-filtering method, the resolution of the HAR method increases with charge (improved S/N) and thus with mass. An analysis of the HAR method with current instrumentation indicates that higher resolution can be obtained with the HAR method than the best resolution demonstrated for instruments with energy-selective optics for ions in the low MDa range and above. However, this gain is typically unrealized because the resolution obtainable with molecular systems in this mass range is limited by sample heterogeneity. This phenomenon is illustrated with both tobacco mosaic virus (0.6-2.7 MDa) and AAV9 (3.7-4.7 MDa) samples where mass spectral resolution is limited by the sample, including salt adducts, and not by instrument resolution. Nevertheless, the ratio of full to empty AAV9 capsids and the included genome mass can be accurately obtained in a few minutes from 1× PBS buffer solution and an elution buffer containing 300+ mM nonvolatile content despite extensive adduction and lower resolution. Empty and full capsids adduct similarly indicating that salts encrust the complexes during late stages of droplet evaporation and that mass shifts can be calibrated in order to obtain accurate analyte masses even from highly salty solutions.
    DOI:  https://doi.org/10.1021/acs.analchem.2c02572
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