bims-mascan 2023-07-23 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2023–07–23
twenty-one papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz

Deep-profiling of phospholipidome via rapid orthogonal separations and isomer-resolved mass spectrometry.
Recent advances towards mass spectrometry-based clinical lipidomics.
Evaluating cPILOT Data toward Quality Control Implementation.
Amino acid analysis for peptide quantitation using reversed-phase liquid chromatography combined with multiple reaction monitoring mass spectrometry.
Lipidomics Workflow for Analyzing Lipid Profiles Using Multiple Reaction Monitoring (MRM) in Liver Homogenate of Mice with Non-alcoholic Steatohepatitis (NASH).
Oxonium ion scanning mass spectrometry for large-scale plasma glycoproteomics.
Untargeted hair lipidomics: comprehensive evaluation of the hair-specific lipid signature and considerations for retrospective analysis.
Non-targeted multimodal metabolomics data from ovine rumen fluid fractions.
Enhancing Classification of liquid chromatography mass spectrometry data with Batch Effect Removal Neural Networks (BERNN).
UHPLC-HRMS-based serum untargeted lipidomics: Phosphatidylcholines and sphingomyelins are the main disturbed lipid markers to distinguish colorectal advanced adenoma from cancer.
The BinDiscover database: a biology-focused meta-analysis tool for 156,000 GC-TOF MS metabolome samples.
Statistical Detection of Differentially Abundant Proteins in Experiments with Repeated Measures Designs and Isobaric Labeling.
A chemical derivatization-based pseudotargeted LC-MS/MS method for high coverage determination of dipeptides.
Mass spectrometry-based techniques for single-cell analysis.
Metabolic profiling of Alzheimer's disease: Untargeted metabolomics analysis of plasma samples.
Chemical tagging mass spectrometry: an approach for single-cell omics.
Chemical QuantArray: A Quantitative Tool for Mass Spectrometry Imaging.
Monitoring both extended and tryptic forms of stable isotope-labeled standard peptides provides an internal quality control of proteolytic digestion in targeted mass spectrometry-based assays.
Comprehensive review of MS-based studies on N-glycoproteome and N-glycome of extracellular vesicles.
Identification of Peptides of Small Extracellular Vesicles from Bone Marrow-Derived Macrophages.
Comprehensive analysis of oxylipins using reverse phase liquid chromatography and data dependent acquisition workflow on LTQ-Orbitrap® Velos Pro.

Nat Commun. 2023 07 17. 14(1): 4263

Deep-profiling of phospholipidome via rapid orthogonal separations and isomer-resolved mass spectrometry.

Tian Xia, Feng Zhou, Donghui Zhang, Xue Jin, Hengxue Shi, Hang Yin, Yanqing Gong, Yu Xia.

A lipidome comprises thousands of lipid species, many of which are isomers and isobars. Liquid chromatography-tandem mass spectrometry (LC-MS/MS), although widely used for lipidomic profiling, faces challenges in differentiating lipid isomers. Herein, we address this issue by leveraging the orthogonal separation capabilities of hydrophilic interaction liquid chromatography (HILIC) and trapped ion mobility spectrometry (TIMS). We further integrate isomer-resolved MS/MS methods onto HILIC-TIMS, which enable pinpointing double bond locations in phospholipids and sn-positions in phosphatidylcholine. This system profiles phospholipids at multiple structural levels with short analysis time (<10 min per LC run), high sensitivity (nM detection limit), and wide coverage, while data analysis is streamlined using a home-developed software, LipidNovelist. Notably, compared to our previous report, the system doubles the coverage of phospholipids in bovine liver and reveals uncanonical desaturation pathways in RAW 264.7 macrophages. Relative quantitation of the double bond location isomers of phospholipids and the sn-position isomers of phosphatidylcholine enables the phenotyping of human bladder cancer tissue relative to normal control, which would be otherwise indistinguishable by traditional profiling methods. Our research offers a comprehensive solution for lipidomic profiling and highlights the critical role of isomer analysis in studying lipid metabolism in both healthy and diseased states.

DOI: https://doi.org/10.1038/s41467-023-40046-x
Curr Opin Chem Biol. 2023 Jul 18. pii: S1367-5931(23)00108-4. [Epub ahead of print]76 102370

Recent advances towards mass spectrometry-based clinical lipidomics.

Samira Salihovic, Santosh Lamichane, Tuulia Hyötyläinen, Matej Orešič.

  The objective of this review is to provide a comprehensive summary of the latest methodological advancements and emerging patterns in utilizing lipidomics in clinical research.In this review, we assess the recent advancements in lipidomics methodologies that exhibit high levels of selectivity and sensitivity, capable of generating numerous molecular lipid species from limited quantities of biological matrices. The reviewed studies demonstrate that molecular lipid signatures offer new opportunities for precision medicine by providing sensitive diagnostic tools for disease prediction and monitoring. Moreover, the latest innovations in microsampling techniques have the potential to make a substantial contribution to clinical lipidomics. The review also shows that more work is needed to harmonize results across diverse lipidomics platforms and avoid significant errors in analysis and reporting. The increased implementation of internal standards and standard reference materials in analytical workflows will aid in this direction.

Keywords:  Biomarkers; Human health; Lipidomics; Mass spectrometry; Microsampling

DOI:  https://doi.org/10.1016/j.cbpa.2023.102370
J Am Soc Mass Spectrom. 2023 Jul 17.

Evaluating cPILOT Data toward Quality Control Implementation.

Bailey L Bowser, Khiry L Patterson, Renã As Robinson.

  Multiplexing enables the monitoring of hundreds to thousands of proteins in quantitative proteomics analyses and increases sample throughput. In most mass-spectrometry-based proteomics workflows, multiplexing is achieved by labeling biological samples with heavy isotopes via precursor isotopic labeling or isobaric tagging. Enhanced multiplexing strategies, such as combined precursor isotopic labeling and isobaric tagging (cPILOT), combine multiple technologies to afford an even higher sample throughput. Critical to enhanced multiplexing analyses is ensuring that analytical performance is optimal and that missingness of sample channels is minimized. Automation of sample preparation steps and use of quality control (QC) metrics can be incorporated into multiplexing analyses and reduce the likelihood of missing information, thus maximizing the amount of usable quantitative data. Here, we implemented QC metrics previously developed in our laboratory to evaluate a 36-plex cPILOT experiment that encompassed 144 mouse samples of various tissue types, time points, genotypes, and biological replicates. The evaluation focuses on the use of a sample pool generated from all samples in the experiment to monitor the daily instrument performance and to provide a means for data normalization across sample batches. Our results show that tracking QC metrics enabled the quantification of ∼7000 proteins in each sample batch, of which ∼70% had minimal missing values across up to 36 sample channels. Implementation of QC metrics for future cPILOT studies as well as other enhanced multiplexing strategies will help yield high-quality data sets.

Keywords:  TMT; cPILOT; multiplexing; quality control; quantitative proteomics

DOI:  https://doi.org/10.1021/jasms.3c00179
Anal Bioanal Chem. 2023 Jul 19.

Amino acid analysis for peptide quantitation using reversed-phase liquid chromatography combined with multiple reaction monitoring mass spectrometry.

Deema O Qasrawi, Evgeniy V Petrotchenko, Christoph H Borchers.

  Amino acid analysis (AAA) can be used for absolute quantitation of standard peptides after acid hydrolysis using 6 M HCl. Obtained individual amino acids can then be quantified by liquid chromatography-mass spectrometry (LC-MS). Achieving baseline separation of non-derivatized amino acids is challenging when reversed-phase (RP) chromatography is used. Several derivatization methods are commonly utilized to address this issue; however, derivatization has several drawbacks, such as derivative instability and lack of reproducibility. Currently, separation of non-derivatized amino acids is typically done using HILIC, but HILIC has problems of poor reproducibility and long column equilibration times. We developed a method to quantify non-derivatized amino acids, including methionine and cysteine, from peptide hydrolysates by RP-LC-MS without special pre-treatment of the samples. Samples were spiked with certified isotopically labeled (13C- and/or 15N-) amino acids as internal standards. The amino acids released from acid hydrolysis were then analyzed by RP-UPLC-MRM-MS and quantified using the analyte/internal standard chromatographic peak area ratios. Peptide quantitation was based on the sum of the individual amino acid concentrations from the known peptide sequences. The resulting method did not require derivatization, used standard C18-based reversed-phase liquid chromatography, did not require external calibration, was robust, and was able to quantify all 17 amino acids for which we had internal standards, including the sulfur-containing amino acids, cysteine and methionine, in their respective oxidized forms. This simple and robust method enabled the absolute quantitation of standard peptides using only acid hydrolysis and a standard RP-UPLC-MRM-MS setup.

Keywords:  Amino acid analysis (AAA); Hydrochloric acid hydrolysis; LC-MRM-MS; Peptide quantification; Stable isotope-labeled internal standards

DOI:  https://doi.org/10.1007/s00216-023-04840-2
Bio Protoc. 2023 Jul 05. 13(13): e4773

Lipidomics Workflow for Analyzing Lipid Profiles Using Multiple Reaction Monitoring (MRM) in Liver Homogenate of Mice with Non-alcoholic Steatohepatitis (NASH).

Hai Ning Wee, Lye Siang Lee, Sharon Hong Yu Han, Jin Zhou, Paul Michael Yen, Jianhong Ching.

  Non-alcoholic steatohepatitis (NASH) is a condition characterized by inflammation and hepatic injury/fibrosis caused by the accumulation of ectopic fats in the liver. Recent advances in lipidomics have allowed the identification and characterization of lipid species and have revealed signature patterns of various diseases. Here, we describe a lipidomics workflow to assess the lipid profiles of liver homogenates taken from a NASH mouse model. The protocol described below was used to extract and analyze the metabolites from the livers of mice with NASH by liquid chromatography-mass spectrometry (LC-MS); however, it can be applied to other tissue homogenate samples. Using this method, over 1,000 species of lipids from five classes can be analyzed in a single run on the LC-MS. Also, partial elucidation of the identity of neutral lipid (triacylglycerides and diacylglycerides) aliphatic chains can be performed with this simple LC-MS setup. Key features Over 1,000 lipid species (sphingolipids, cholesteryl esters, neutral lipids, phospholipids, fatty acids) are analyzed in one run. Analysis of liver lipids in non-alcoholic steatohepatitis (NASH) mouse model. Normal-phase chromatography coupled to a triple quadrupole mass spectrometer.

Keywords:  Cholesteryl esters; Fatty acids; Glycerolipids; LC-MS; Lipidomics; Liver; Phospholipids; Sphingolipids

DOI:  https://doi.org/10.21769/BioProtoc.4773
Nat Biomed Eng. 2023 Jul 20.

Oxonium ion scanning mass spectrometry for large-scale plasma glycoproteomics.

Matthew E H White, Ludwig R Sinn, D Marc Jones, Joost de Folter, Simran Kaur Aulakh, Ziyue Wang, Helen R Flynn, Lynn Krüger, Pinkus Tober-Lau, Vadim Demichev, Florian Kurth, Michael Mülleder, Véronique Blanchard, Christoph B Messner, Markus Ralser.

Protein glycosylation, a complex and heterogeneous post-translational modification that is frequently dysregulated in disease, has been difficult to analyse at scale. Here we report a data-independent acquisition technique for the large-scale mass-spectrometric quantification of glycopeptides in plasma samples. The technique, which we named 'OxoScan-MS', identifies oxonium ions as glycopeptide fragments and exploits a sliding-quadrupole dimension to generate comprehensive and untargeted oxonium ion maps of precursor masses assigned to fragment ions from non-enriched plasma samples. By applying OxoScan-MS to quantify 1,002 glycopeptide features in the plasma glycoproteomes from patients with COVID-19 and healthy controls, we found that severe COVID-19 induces differential glycosylation in IgA, haptoglobin, transferrin and other disease-relevant plasma glycoproteins. OxoScan-MS may allow for the quantitative mapping of glycoproteomes at the scale of hundreds to thousands of samples.

DOI: https://doi.org/10.1038/s41551-023-01067-5
Anal Bioanal Chem. 2023 Jul 19.

Untargeted hair lipidomics: comprehensive evaluation of the hair-specific lipid signature and considerations for retrospective analysis.

Maria van de Lavoir, Katyeny Manuela da Silva, Elias Iturrospe, Rani Robeyns, Alexander L N van Nuijs, Adrian Covaci.

  Lipidomics investigates the composition and function of lipids, typically employing blood or tissue samples as the primary study matrices. Hair has recently emerged as a potential complementary sample type to identify biomarkers in early disease stages and retrospectively document an individual's metabolic status due to its long detection window of up to several months prior to the time of sampling. However, the limited coverage of lipid profiling presented in previous studies has hindered its exploitation. This study aimed to evaluate the lipid coverage of hair using an untargeted liquid chromatography-high-resolution mass spectrometry lipidomics platform. Two distinct three-step exhaustive extraction experiments were performed using a hair metabolomics one-phase extraction technique that has been recently optimized, and the two-phase Folch extraction method which is recognized as the gold standard for lipid extraction in biological matrices. The applied lipidomics workflow improved hair lipid coverage, as only 99 species could be annotated using the one-phase extraction method, while 297 lipid species across six categories were annotated with the Folch method. Several lipids in hair were reported for the first time, including N-acyl amino acids, diradylglycerols, and coenzyme Q10. The study suggests that hair lipids are not solely derived from de novo synthesis in hair, but are also incorporated from sebum and blood, making hair a valuable matrix for clinical, forensic, and dermatological research. The improved understanding of the lipid composition and analytical considerations for retrospective analysis offers valuable insights to contextualize untargeted hair lipidomic analysis and facilitate the use of hair in translational studies.

Keywords:  Data interpretation; Extraction methods; Hair; Metabolomics; Profiling; Sample preparation

DOI:  https://doi.org/10.1007/s00216-023-04851-z
Microbiol Resour Announc. 2023 Jul 19. e0039223

Non-targeted multimodal metabolomics data from ovine rumen fluid fractions.

Nikola Palevich, Paul H Maclean, Mingshu Cao.

  From an animal health perspective, our understanding of the metabolites in rumen fluid across different host species is poorly understood. Here, we present a metabolomic data set generated using hydrophilic interaction liquid chromatography and semi-polar (C18) chromatography methods coupled to high-resolution mass spectrometry of fractionated ovine rumen samples.

Keywords:  biofluid; metabolomics; ovine; rumen

DOI:  https://doi.org/10.1128/MRA.00392-23
Res Sq. 2023 Jul 06. pii: rs.3.rs-3112514. [Epub ahead of print]

Enhancing Classification of liquid chromatography mass spectrometry data with Batch Effect Removal Neural Networks (BERNN).

Arnaud Droit, Simon Pelletier, Mickaël Leclerq, Florence Roux-Dalvai, Matthijs de Geus, Shannon Leslie, Weiwei Wang, TuKiet Lam, Angus Nairn, Steven Arnold, Becky Carlyle, Frederic Precioso.

Liquid Chromatography Mass Spectrometry (LC-MS) is a powerful method for profiling complex biological samples. However, batch effects typically arise from differences in sample processing protocols, experimental conditions and data acquisition techniques, significantlyimpacting the interpretability of results. Correcting batch effects is crucial for the reproducibility of proteomics research, but current methods are not optimal for removal of batch effects without compressing the genuine biological variation under study. We propose a suite of Batch Effect Removal Neural Networks (BERNN) to remove batch effects in large LC-MS experiments, with the goal of maximizing sample classification performance between conditions. More importantly, these models must efficiently generalize in batches not seen during training. Comparison of batch effect correction methods across three diverse datasets demonstrated that BERNN models consistently showed the strongest sample classification performance. However, the model producing the greatest classification improvements did not always perform best in terms of batch effect removal. Finally, we show that overcorrection of batch effects resulted in the loss of some essential biological variability. These findings highlight the importance of balancing batch effect removal while preserving valuable biological diversity in large-scale LC-MS experiments.

DOI: https://doi.org/10.21203/rs.3.rs-3112514/v1
J Pharm Biomed Anal. 2023 Jul 16. pii: S0731-7085(23)00351-5. [Epub ahead of print]234 115582

UHPLC-HRMS-based serum untargeted lipidomics: Phosphatidylcholines and sphingomyelins are the main disturbed lipid markers to distinguish colorectal advanced adenoma from cancer.

Hongwei Chen, Hailin Zhou, Yunxiao Liang, Zongsheng Huang, Shanyi Yang, Xuancheng Wang, Zhiyong She, Zhijuan Wei, Qisong Zhang.

  Colorectal advanced adenoma (CAA) is a key precancerous lesion of colorectal cancer (CRC), and early diagnosis can lessen CRC morbidity and mortality. Although abnormal lipid metabolism is associated with the development of CRC, there are no studies on the biomarkers and mechanism of lipid metabolism linked to CAA carcinogenesis. Hence, we performed a lipidomics study of serum samples from 46 CAA, and 50 CRC patients by the ultra high-performance liquid chromatography tandem high resolution mass spectrometry (UHPLC-HRMS) in both electrospray ionization (ESI) modes. Differential lipids were selected by univariate and multivariate statistics analysis, and their diagnostic performance was evaluated using a receiver operating characteristic curve (ROC) analysis. Combining P < 0.05 and variable importance in projection (VIP) > 1, 59 differential lipids were obtained totally. Ten of them showed good discriminant ability for CAA and CRC (AUC > 0.900). Especially, the lipid panel consisting of PC 44:5, PC 35:6e, and SM d40:3 showed the highest selection frequency and outperformed (AUC = 0.952). Additionally, phosphatidylcholine (PC) and sphingomyelin (SM) were the main differential and high-performance lipids. In short, this is the first study to explore the biomarkers and mechanism for CAA-CRC sequence with large-scale serum lipidomics. The findings should provide valuable reference and new clues for the development of diagnostic and therapeutic strategies of CRC.

Keywords:  Biomarkers; Colorectal advanced adenoma; Colorectal cancer; Serum lipidomics; UHPLC-HRMS

DOI:  https://doi.org/10.1016/j.jpba.2023.115582
J Cheminform. 2023 Jul 20. 15(1): 66

The BinDiscover database: a biology-focused meta-analysis tool for 156,000 GC-TOF MS metabolome samples.

Parker Ladd Bremer, Gert Wohlgemuth, Oliver Fiehn.

  Metabolomics by gas chromatography/mass spectrometry (GC/MS) provides a standardized and reliable platform for understanding small molecule biology. Since 2005, the West Coast Metabolomics Center at the University of California at Davis has collated GC/MS metabolomics data from over 156,000 samples and 2000 studies into the standardized BinBase database. We believe that the observations from these samples will provide meaningful insight to biologists and that our data treatment and webtool will provide insight to others who seek to standardize disparate metabolomics studies. We here developed an easy-to-use query interface, BinDiscover, to enable intuitive, rapid hypothesis generation for biologists based on these metabolomic samples. BinDiscover creates observation summaries and graphics across a broad range of species, organs, diseases, and compounds. Throughout the components of BinDiscover, we emphasize the use of ontologies to aggregate large groups of samples based on the proximity of their metadata within these ontologies. This adjacency allows for the simultaneous exploration of entire categories such as "rodents", "digestive tract", or "amino acids". The ontologies are particularly relevant for BinDiscover's ontologically grouped differential analysis, which, like other components of BinDiscover, creates clear graphs and summary statistics across compounds and biological metadata. We exemplify BinDiscover's extensive applicability in three showcases across biological domains.

Keywords:  Gas chromatography; Mass spectrometry; Meta-analysis; Metabolomics; Ontologies

DOI:  https://doi.org/10.1186/s13321-023-00734-8
J Proteome Res. 2023 Jul 19.

Statistical Detection of Differentially Abundant Proteins in Experiments with Repeated Measures Designs and Isobaric Labeling.

Ting Huang, Mateusz Staniak, Felipe da Veiga Leprevost, Amanda M Figueroa-Navedo, Alexander R Ivanov, Alexey I Nesvizhskii, Meena Choi, Olga Vitek.

  Repeated measures experimental designs, which quantify proteins in biological subjects repeatedly over multiple experimental conditions or times, are commonly used in mass spectrometry-based proteomics. Such designs distinguish the biological variation within and between the subjects and increase the statistical power of detecting within-subject changes in protein abundance. Meanwhile, proteomics experiments increasingly incorporate tandem mass tag (TMT) labeling, a multiplexing strategy that gains both relative protein quantification accuracy and sample throughput. However, combining repeated measures and TMT multiplexing in a large-scale investigation presents statistical challenges due to unique interplays of between-mixture, within-mixture, between-subject, and within-subject variation. This manuscript proposes a family of linear mixed-effects models for differential analysis of proteomics experiments with repeated measures and TMT multiplexing. These models decompose the variation in the data into the contributions from its sources as appropriate for the specifics of each experiment, enable statistical inference of differential protein abundance, and recognize a difference in the uncertainty of between-subject versus within-subject comparisons. The proposed family of models is implemented in the R/Bioconductor package MSstatsTMT v2.2.0. Evaluations of four simulated datasets and four investigations answering diverse biological questions demonstrated the value of this approach as compared to the existing general-purpose approaches and implementations.

Keywords:  LC-MS/MS; TMT labeling; differential analysis; proteomics; repeated measures designs

DOI:  https://doi.org/10.1021/acs.jproteome.3c00155
Anal Chim Acta. 2023 Sep 15. pii: S0003-2670(23)00791-2. [Epub ahead of print]1274 341570

A chemical derivatization-based pseudotargeted LC-MS/MS method for high coverage determination of dipeptides.

Shaoran Tang, Pei Zhang, Meiyu Gao, Qinwen Xiao, Zhaoqian Li, Haijuan Dong, Yuan Tian, Fengguo Xu, Yuxin Zhang.

  Dipeptides (DPs) have attracted more and more attention in many research fields due to their important biological functions and promising roles as disease biomarkers. However, the determination of DPs in biological samples is very challenging owing to the limited availability of commercial standards, high structure diversity, distinct physical and chemical characteristics, wide concentration range, and the extensive existence of isomers. In this study, a pseudotargeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) method coupled with chemical derivatization for the simultaneous analysis of 400 DPs and their constructing amino acids (AAs) in biospecimens is established. Dansyl chloride (Dns-Cl) chemical derivatization was introduced to provide characteristic MS fragments for annotation and improve the chromatographic separation of DP isomers. A retention time (RT) prediction model was constructed using 83 standards (63 DPs and 20 AAs) based on their quantitative structural retention relationship (QSRR) after the Dns-Cl labeling, which largely facilitated the annotation of the DPs without standards. Finally, we applied this method to investigate the profile change of DPs in a cisplatin-induced acute kidney injury (AKI) rat model. The established workflow provides a platform to profile DPs and expand our understanding of these little-studied metabolites.

Keywords:  Acute kidney injury; Cisplatin; Dipeptide; LC-MS/MS; Pseudotargeted metabolomics; Quantitative structural retention relationship

DOI:  https://doi.org/10.1016/j.aca.2023.341570
Analyst. 2023 Jul 17.

Mass spectrometry-based techniques for single-cell analysis.

Xiangyi Xu, Xuanxi Jiang, Meiyun Shi, Lei Yin.

The cell is the most basic structural unit and plays a vital role in the function of an organism. Studying the heterogeneity of cells, especially the qualitative and quantitative analyses of proteins and lipids at the cellular level and even at the subcellular level, is of great significance for the study of some important pathological or physiological processes. Due to the small size of a single cell, low content of analytes and large interference from the biological matrix within the single cell, analytical methods at the single cell level must be highly sensitive and selective. Mass spectrometry is a powerful technology for single-cell analysis, because it has high sensitivity, high selectivity and the ability to monitor multiple chemicals at the same time. In this review, four mass spectrometry-based methods applied to single-cell analysis are introduced and discussed in detail; these are electrospray ionization mass spectrometry (ESI-MS), laser desorption ionization mass spectrometry (LDI-MS), secondary ion mass spectrometry (SIMS) and inductively coupled plasma mass spectrometry (ICP-MS). The recent advances in single-cell analysis with these mass spectrometry-based techniques are summarized. We believe that this review can provide some help and reference for single-cell analysis by mass spectrometry.

DOI: https://doi.org/10.1039/d3an00370a
Prog Neuropsychopharmacol Biol Psychiatry. 2023 Jul 16. pii: S0278-5846(23)00116-1. [Epub ahead of print]127 110830

Metabolic profiling of Alzheimer's disease: Untargeted metabolomics analysis of plasma samples.

Tina Milos, David Rojo, Gordana Nedic Erjavec, Marcela Konjevod, Lucija Tudor, Barbara Vuic, Dubravka Svob Strac, Suzana Uzun, Ninoslav Mimica, Oliver Kozumplik, Coral Barbas, Neven Zarkovic, Nela Pivac, Matea Nikolac Perkovic.

  Alzheimer's disease (AD) is often not recognized or is diagnosed very late, which significantly reduces the effectiveness of available pharmacological treatments. Metabolomic analyzes have great potential for improving existing knowledge about the pathogenesis and etiology of AD and represent a novel approach towards discovering biomarkers that could be used for diagnosis, prognosis, and therapy monitoring. In this study, we applied the untargeted metabolomic approach to investigate the changes in biochemical pathways related to AD pathology. We used gas chromatography and liquid chromatography coupled to mass spectrometry (GC-MS and LC-MS, respectively) to identify metabolites whose levels have changed in subjects with AD diagnosis (N = 40) compared to healthy controls (N = 40) and individuals with mild cognitive impairment (MCI, N = 40). The GC-MS identified significant differences between groups in levels of metabolites belonging to the classes of benzene and substituted derivatives, carboxylic acids and derivatives, fatty acyls, hydroxy acids and derivatives, keto acids and derivatives, and organooxygen compounds. Most of the compounds identified by the LC-MS were various fatty acyls, glycerolipids and glycerophospholipids. All of these compounds were decreased in AD patients and in subjects with MCI compared to healthy controls. The results of the study indicate disturbed metabolism of lipids and amino acids and an imbalance of metabolites involved in energy metabolism in individuals diagnosed with AD, compared to healthy controls and MCI subjects.

Keywords:  Alzheimer's disease; Metabolomics; Mild cognitive impairment; Plasma; Untargeted

DOI:  https://doi.org/10.1016/j.pnpbp.2023.110830
Anal Bioanal Chem. 2023 Jul 19.

Chemical tagging mass spectrometry: an approach for single-cell omics.

Haiyan Lu, Hua Zhang, Lingjun Li.

  Single-cell (SC) analysis offers new insights into the study of fundamental biological phenomena and cellular heterogeneity. The superior sensitivity, high throughput, and rich chemical information provided by mass spectrometry (MS) allow MS to emerge as a leading technology for molecular profiling of SC omics, including the SC metabolome, lipidome, and proteome. However, issues such as ionization suppression, low concentration, and huge span of dynamic concentrations of SC components lead to poor MS response for certain types of molecules. It is noted that chemical tagging/derivatization has been adopted in SCMS analysis, and this strategy has been proven an effective solution to circumvent these issues in SCMS analysis. Herein, we review the basic principle and general strategies of chemical tagging/derivatization in SCMS analysis, along with recent applications of chemical derivatization to single-cell metabolomics and multiplexed proteomics, as well as SCMS imaging. Furthermore, the challenges and opportunities for the improvement of chemical derivatization strategies in SCMS analysis are discussed.

Keywords:  Chemical derivatization; Lipidomics; Mass spectrometry imaging; Metabolomics; Proteomics; Single-cell analysis

DOI:  https://doi.org/10.1007/s00216-023-04850-0
Anal Chem. 2023 Jul 19.

Chemical QuantArray: A Quantitative Tool for Mass Spectrometry Imaging.

Sylwia A Stopka, Daniela Ruiz, Gerard Baquer, Clément Bodineau, Md Amin Hossain, Valentina T Pellens, Michael S Regan, Olivier Pourquié, Marcia C Haigis, Wenya L Bi, Shannon M Coy, Sandro Santagata, Nathalie Y R Agar, Sankha S Basu.

Matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) is a powerful analytical technique that provides spatially preserved detection and quantification of analytes in tissue specimens. However, clinical translation still requires improved throughput, precision, and accuracy. To accomplish this, we created "Chemical QuantArray", a gelatin tissue microarray (TMA) mold filled with serial dilutions of isotopically labeled endogenous metabolite standards. The mold is then cryo-sectioned onto a tissue homogenate to produce calibration curves. To improve precision and accuracy, we automatically remove pixels outside of each TMA well and investigated several intensity normalizations, including the utilization of a second stable isotope internal standard (IS). Chemical QuantArray enables the quantification of several endogenous metabolites over a wide dynamic range and significantly improve over current approaches. The technique reduces the space needed on the MALDI slides for calibration standards by approximately 80%. Furthermore, removal of empty pixels and normalization to an internal standard or matrix peak provided precision (<20% RSD) and accuracy (<20% DEV). Finally, we demonstrate the applicability of Chemical QuantArray by quantifying multiple purine metabolites in 14 clinical tumor specimens using a single MALDI slide. Chemical QuantArray improves the analytical characteristics and practical feasibility of MALDI-MSI metabolite quantification in clinical and translational applications.

DOI: https://doi.org/10.1021/acs.analchem.3c00803
Mol Cell Proteomics. 2023 Jul 19. pii: S1535-9476(23)00132-9. [Epub ahead of print] 100621

Monitoring both extended and tryptic forms of stable isotope-labeled standard peptides provides an internal quality control of proteolytic digestion in targeted mass spectrometry-based assays.

Rachel A Lundeen, Jacob J Kennedy, Oscar D Murillo, Richard G Ivey, Lei Zhao, Regine M Schoenherr, Andrew N Hoofnagle, Pei Wang, Jeffrey R Whiteaker, Amanda G Paulovich.

Targeted mass spectrometry (MS)-based proteomic assays, such as multiplexed multiple reaction monitoring (MRM)-MS assays, enable sensitive and specific quantification of proteotypic peptides as stoichiometric surrogates for proteins. Efforts are underway to expand the use of MRM-MS assays in clinical environments, which requires a reliable strategy to monitor proteolytic digestion efficiency within individual samples. Towards this goal, extended stable isotope-labeled standard (SIS) peptides (hE), which incorporate native proteolytic cleavage sites, can be spiked into protein lysates prior to proteolytic (trypsin) digestion, and release of the tryptic SIS peptide (hT) can be monitored. However, hT measurements alone cannot monitor the extent of digestion and may be confounded by matrix effects specific to individual patient samples; therefore they are not sufficient to monitor sample-to-sample digestion variability. We hypothesized that measuring undigested hE, along with its paired hT, would improve detection of digestion issues compared to only measuring hT. We tested the ratio of the SIS pair measurements, or hE/hT, as a quality control (QC) metric of trypsin digestion for two MRM assays: a direct-MRM (398 targets) and an immuno-MRM assay (126 targets requiring immunoaffinity peptide enrichment), with extended SIS peptides observable for 54% (216) and 62% (78) of the targets, respectively. We evaluated the quantitative bias for each target in a series of experiments that adversely affected proteolytic digestion (e.g., variable digestion times, pH, temperature). We identified a subset of SIS pairs (36 for the direct-MRM, 7 for the immuno-MRM assay) for which the hE/hT ratio reliably detected inefficient digestion that resulted in decreased assay sensitivity and unreliable endogenous quantification. The hE/hT ratio was more responsive to a decrease in digestion efficiency than a metric based on hT measurements alone. For clinical-grade MRM-MS assays, this study describes a ready-to-use QC panel and also provides a road map for designing custom QC panels.

DOI: https://doi.org/10.1016/j.mcpro.2023.100621
Proteomics. 2023 Jul 20. e2300065

Comprehensive review of MS-based studies on N-glycoproteome and N-glycome of extracellular vesicles.

Yang Li, Jun Wang, Weiyu Chen, Haojie Lu, Ying Zhang.

  Extracellular vesicles (EVs) are lipid bilayer-enclosed particles that can be released by all type of cells. Whereas, as one of the most common post-translational modifications, glycosylation plays a vital role in various biological functions of EVs, such as EV biogenesis, sorting, and cellular recognition. Nevertheless, compared with studies on RNAs or proteins, those investigating the glycoconjugates of EVs are limited. An in-depth investigation of N-glycosylation of EVs can improve the understanding of the biological functions of EVs and help to exploit EVs from different perspectives. The general focus of studies on glycosylation of EVs primarily includes isolation and characterization of EVs, preparation of glycoproteome/glycome samples and MS analysis. However, the low content of EVs and non-standard separation methods for downstream analysis are the main limitations of these studies. In this review, we highlight the importance of glycopeptide/glycan enrichment and derivatization owing to the low abundance of glycoproteins and the low ionization efficiency of glycans. Diverse fragmentation patterns and professional analytical software are indispensable for analysing glycosylation via MS. Altogether, this review summarises recent studies on glycosylation of EVs, revealing the role of EVs in disease progression and their remarkable potential as biomarkers.

Keywords:  N-glycome; N-glycoproteome; extracellular vesicles; mass spectrometry

DOI:  https://doi.org/10.1002/pmic.202300065
J Vis Exp. 2023 06 30.

Identification of Peptides of Small Extracellular Vesicles from Bone Marrow-Derived Macrophages.

Jiale Cheng, Jiong Zhu, Yujiao Liu, Chen Yang, Yuehui Zhang, Yuchen Liu, Chaozhi Jin, Jian Wang.

Small extracellular vesicles (sEVs) are typically secreted by the exocytosis of multivesicular bodies (MVBs). These nanovesicles with a diameter of <200 nm are present in various body fluids. These sEVs regulate various biological processes such as gene transcription and translation, cell proliferation and survival, immunity and inflammation through their cargos, such as proteins, DNA, RNA, and metabolites. Currently, various techniques have been developed for sEVs isolation. Among them, the ultracentrifugation-based method is considered the gold standard and is widely used for sEVs isolation. The peptides are naturally biomacromolecules with less than 50 amino acids in length. These peptides participate in a variety of biological processes with biological activity, such as hormones, neurotransmitters, and cell growth factors. The peptidome is intended to systematically analyze endogenous peptides in specific biological samples by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Here, we introduced a protocol to isolate sEVs by differential ultracentrifugation and extracted peptidome for identification by LC-MS/MS. This method identified hundreds of sEVs-derived peptides from bone marrow-derived macrophages.

DOI: https://doi.org/10.3791/65521
Talanta. 2023 Jul 12. pii: S0039-9140(23)00672-0. [Epub ahead of print]266(Pt 1): 124921

Comprehensive analysis of oxylipins using reverse phase liquid chromatography and data dependent acquisition workflow on LTQ-Orbitrap® Velos Pro.

Kodjo Nouwade, Sana Tfaili, Bastien Prost, Hani Dakroub, Audrey Solgadi, Danielle Libong, Jean-Louis Paul, Natalie Fournier, Pierre Chaminade.

  Oxylipins - involved in inflammatory processes - are reported in several diseases, in biological, pharmacological, and physiological fields. To face the structural complexity of oxylipins, the study of isomers and isobars species relied on Selected Reaction Monitoring (SRM) and Multiple Reaction Monitoring (MRM) in tandem mass spectrometry such as triple quadrupole, quadrupole-Time of Flight (TOF). Unfortunately, false positive signals in cellular matrix could occur using MRM or SRM mode since the MS/MS spectrum of each molecule is not acquired with the previous mode to help molecule confirmation. Using the versatile ability of LTQ-Orbitrap® Velos Pro mass spectrometer, we developed a novel method based on data dependent acquisition (DDA) workflow for oxylipins analysis. To reach sufficient data points per peak and a better sensitivity to quantify oxylipins traces, an optimization of the acquisition frequency was carried out both on linear trap and Orbitrap analyzers. A segmentation of the chromatographic profile and an optimization of the collision energies by HCD (higher energy collision dissociation) for each eicosanoid increased the acquisition frequency significantly and the detection threshold: around 2 pg for some prostanoids and 0.02-2 pg for some leukotrienes and oxidized species. We validated our method in terms of specificity (RSD <10%), sensitivity, accuracy and precision. The intra and inter-day accuracy were between 86.56% and 114.93%. Besides, a relative standard deviation less than 15% as intra- and inter-day precision were obtained for almost all molecules. A linear range between 2.5 and 12,500 pg was reached. DDA approach on LTQ-Orbitrap® constitutes an alternative to MRM mode on triple quadrupole for eicosanoids quantification in complex matrices. Finally, this method helped us to compare for the first time the amount of prostanoids released by J774 and THP-1 macrophages under lipopolysaccharide (LPS) stimulation.

Keywords:  Data dependent acquisition (DDA); J774 and THP-1 macrophages; Mass spectrometry (LTQ-Orbitrap® Velos Pro); Oxylipins; Reverse phase liquid chromatography; Selected reaction monitoring (SRM)

DOI:  https://doi.org/10.1016/j.talanta.2023.124921