bims-mascan 2024-03-31 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2024–03–31
nineteen papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz

Label-Free Quantitation of Endogenous Peptides.
Data-Independent Acquisition Peptidomics.
Matrix- and Surface-Assisted Laser Desorption/Ionization Mass Spectrometry Methods for Urological Cancer Biomarker Discovery-Metabolomics and Lipidomics Approaches.
Systematic optimization of automated phosphopeptide enrichment for high-sensitivity phosphoproteomics.
Correction: Proteomic signature associated with chronic kidney disease (CKD) progression identified by data-independent acquisition mass spectrometry.
Lipid Wizard: Analysis Software for Comprehensive Two-Dimensional Liquid Chromatography-Mass Spectrometry-Based Lipid Profiling.
DIP-MS: ultra-deep interaction proteomics for the deconvolution of protein complexes.
Simultaneous Determination of One-Carbon Folate Metabolites and One-Carbon-Related Amino Acids in Biological Samples Using a UHPLC-MS/MS Method.
Rapid quantification of 50 fatty acids in small amounts of biological samples for population molecular phenotyping.
SpectiCal: m/z Calibration of MS2 Peptide Spectra Using Known Low Mass Ions.
Use of Nonhuman Sera as a Highly Cost-Effective Internal Standard for Quantitation of Multiple Human Proteins Using Species-Specific Tryptic Peptides: Applicability in Clinical LC-MS Analyses.
BCAA metabolism in pancreatic cancer affects lipid balance by regulating fatty acid import into mitochondria.
Identification and Targeted Quantification of Endogenous Neuropeptides in the Nematode Caenorhabditis elegans Using Mass Spectrometry.
A Chiral-LC-MS Method for the Simultaneous Quantification of Short-Chain Fatty Acids and D/L-Lactate in the Ruminal Fluid of Dairy Cows.
Association of Altered Plasma Lipidome with Disease Severity in COVID-19 Patients.
Tandem Mass Spectrometry across Platforms.
Isomers-oriented separation of forty-five plasma bile acids with liquid chromatography-tandem mass spectrometry.
Diagnostic and Prognostic Performance of Metabolic Signatures in Pancreatic Ductal Adenocarcinoma: The Clinical Application of Quantitative NextGen Mass Spectrometry.
Derivatization of carboxylic groups prior to their LC analysis - A review.

Methods Mol Biol. 2024 ;2758 125-150

Label-Free Quantitation of Endogenous Peptides.

Md Shadman Ridwan Abid, Haowen Qiu, James W Checco.

  Liquid chromatography-mass spectrometry (LC-MS)-based peptidomics methods allow for the detection and identification of many peptides in a complex biological mixture in an untargeted manner. Quantitative peptidomics approaches allow for comparisons of peptide abundance between different samples, allowing one to draw conclusions about peptide differences as a function of experimental treatment or physiology. While stable isotope labeling is a powerful approach for quantitative proteomics and peptidomics, advances in mass spectrometry instrumentation and analysis tools have allowed label-free methods to gain popularity in recent years. In a general label-free quantitative peptidomics experiment, peak intensity information for each peptide is compared across multiple LC-MS runs. Here, we outline a general approach for label-free quantitative peptidomics experiments, including steps for sample preparation, LC-MS data acquisition, data processing, and statistical analysis. Special attention is paid to address run-to-run variability, which can lead to several major problems in label-free experiments. Overall, our method provides researchers with a framework for the development of their own quantitative peptidomics workflows applicable to quantitation of peptides from a wide variety of different biological sources.

Keywords:  LC-MS; Label-free; Mass spectrometry; Missing values; Peptides; Peptidomics; Pooled QC samples; Run-to-run variability

DOI:  https://doi.org/10.1007/978-1-0716-3646-6_7
Methods Mol Biol. 2024 ;2758 77-88

Data-Independent Acquisition Peptidomics.

Leon Bichmann, Shubham Gupta, Hannes Röst.

  In recent years, data-independent acquisition (DIA) has emerged as a powerful analysis method in biological mass spectrometry (MS). Compared to the previously predominant data-dependent acquisition (DDA), it offers a way to achieve greater reproducibility, sensitivity, and dynamic range in MS measurements. To make DIA accessible to non-expert users, a multifunctional, automated high-throughput pipeline DIAproteomics was implemented in the computational workflow framework "Nextflow" ( https://nextflow.io ). This allows high-throughput processing of proteomics and peptidomics DIA datasets on diverse computing infrastructures. This chapter provides a short summary and usage protocol guide for the most important modes of operation of this pipeline regarding the analysis of peptidomics datasets using the command line. In brief, DIAproteomics is a wrapper around the OpenSwathWorkflow and relies on either existing or ad-hoc generated spectral libraries from matching DDA runs. The OpenSwathWorkflow extracts chromatograms from the DIA runs and performs chromatographic peak-picking. Further downstream of the pipeline, these peaks are scored, aligned, and statistically evaluated for qualitative and quantitative differences across conditions depending on the user's interest. DIAproteomics is open-source and available under a permissive license. We encourage the scientific community to use or modify the pipeline to meet their specific requirements.

Keywords:  Automated data analysis; Biological mass spectrometry; DIA; Nextflow; Peptidomics; Proteomics; SWATH

DOI:  https://doi.org/10.1007/978-1-0716-3646-6_4
Metabolites. 2024 Mar 20. pii: 173. [Epub ahead of print]14(3):

Matrix- and Surface-Assisted Laser Desorption/Ionization Mass Spectrometry Methods for Urological Cancer Biomarker Discovery-Metabolomics and Lipidomics Approaches.

Adrian Arendowski.

  Urinary tract cancers, including those of the bladder, the kidneys, and the prostate, represent over 12% of all cancers, with significant global incidence and mortality rates. The continuous challenge that these cancers present necessitates the development of innovative diagnostic and prognostic methods, such as identifying specific biomarkers indicative of cancer. Biomarkers, which can be genes, proteins, metabolites, or lipids, are vital for various clinical purposes including early detection and prognosis. Mass spectrometry (MS), particularly soft ionization techniques such as electrospray ionization (ESI) and laser desorption/ionization (LDI), has emerged as a key tool in metabolic profiling for biomarker discovery, due to its high resolution, sensitivity, and ability to analyze complex biological samples. Among the LDI techniques, matrix-assisted laser desorption/ionization (MALDI) and surface-assisted laser desorption/ionization (SALDI) should be mentioned. While MALDI methodology, which uses organic compounds as matrices, is effective for larger molecules, SALDI, based on the various types of nanoparticles and nanostructures, is preferred for smaller metabolites and lipids due to its reduced spectral interference. This study highlights the application of LDI techniques, along with mass spectrometry imaging (MSI), in identifying potential metabolic and lipid biomarkers for urological cancers, focusing on the most common bladder, kidney, and prostate cancers.

Keywords:  biomarkers; bladder cancer; kidney cancer; lipids; mass spectrometry; matrix-assisted laser desorption/ionization; metabolites; prostate cancer; surface-assisted laser desorption/ionization

DOI:  https://doi.org/10.3390/metabo14030173
Mol Cell Proteomics. 2024 Mar 26. pii: S1535-9476(24)00044-6. [Epub ahead of print] 100754

Systematic optimization of automated phosphopeptide enrichment for high-sensitivity phosphoproteomics.

Patricia Bortel, Ilaria Piga, Claire Koenig, Christopher Gerner, Ana Martinez-Val, Jesper V Olsen.

Improving coverage, robustness and sensitivity is crucial for routine phosphoproteomics analysis by single-shot liquid chromatography tandem mass spectrometry (LC-MS/MS) from minimal peptide inputs. Here, we systematically optimized key experimental parameters for automated on-beads phosphoproteomics sample preparation with focus on low input samples. Assessing the number of identified phosphopeptides, enrichment efficiency, site localization scores and relative enrichment of multiply-phosphorylated peptides pinpointed critical variables influencing the resulting phosphoproteome. Optimizing glycolic acid concentration in the loading buffer, percentage of ammonium hydroxide in the elution buffer, peptide-to-beads ratio, binding time, sample and loading buffer volumes, allowed us to confidently identify >16,000 phosphopeptides in half-an-hour LC-MS/MS on an Orbitrap Exploris 480 using 30 μg of peptides as starting material. Furthermore, we evaluated how sequential enrichment can boost phosphoproteome coverage and showed that pooling fractions into a single LC-MS/MS analysis increased the depth. We also present an alternative phosphopeptide enrichment strategy based on stepwise addition of beads thereby boosting phosphoproteome coverage by 20%. Finally, we applied our optimized strategy to evaluate phosphoproteome depth with the Orbitrap Astral MS using a cell dilution series and were able to identify >32,000 phosphopeptides from 0.5 million HeLa cells in half-an-hour LC-MS/MS using narrow-window data-independent acquisition (nDIA).

DOI: https://doi.org/10.1016/j.mcpro.2024.100754
Clin Proteomics. 2024 Mar 28. 21(1): 25

Correction: Proteomic signature associated with chronic kidney disease (CKD) progression identified by data-independent acquisition mass spectrometry.

Carlos R Ramírez Medina, Ibrahim Ali, Ivona Baricevic-Jones, Aghogho Odudu, Moin A Saleem, Anthony D Whetton, Philip A Kalra, Nophar Geifman.

DOI: https://doi.org/10.1186/s12014-024-09471-y
Anal Chem. 2024 Mar 24.

Lipid Wizard: Analysis Software for Comprehensive Two-Dimensional Liquid Chromatography-Mass Spectrometry-Based Lipid Profiling.

Raobo Xu, Huan Liu, Fang Yuan, Seongho Kim, Irina Kirpich, Craig J McClain, Xiang Zhang.

Lipids play a significant role in life activities and participate in the biological system through different pathways. Although comprehensive two-dimensional liquid chromatography-mass spectrometry (2DLC-MS) has been developed to profile lipid abundance changes, lipid identification and quantification from 2DLC-MS data remain a challenge. We created Lipid Wizard, open-source software for lipid assignment and isotopic peak stripping of the 2DLC-MS data. Lipid Wizard takes the peak list deconvoluted from the 2DLC-MS data as input and assigns each isotopic peak to the lipids recorded in the LIPID MAPS database by precursor ion m/z matching. The matched lipids are then filtered by the first-dimension retention time (1D RT), followed by the second-dimension retention time (2D RT), where the 2D RT of each lipid is predicted using an equivalent carbon number (ECN) model. The remaining assigned lipids are used for isotopic peak stripping via an iterative linear regression. The performance of Lipid Wizard was tested using a set of lipid standards and then applied to study the lipid changes in the livers of mice (fat-1) fed with alcohol.

DOI: https://doi.org/10.1021/acs.analchem.3c04419
Nat Methods. 2024 Mar 26.

DIP-MS: ultra-deep interaction proteomics for the deconvolution of protein complexes.

Fabian Frommelt, Andrea Fossati, Federico Uliana, Fabian Wendt, Peng Xue, Moritz Heusel, Bernd Wollscheid, Ruedi Aebersold, Rodolfo Ciuffa, Matthias Gstaiger.

Most proteins are organized in macromolecular assemblies, which represent key functional units regulating and catalyzing most cellular processes. Affinity purification of the protein of interest combined with liquid chromatography coupled to tandem mass spectrometry (AP-MS) represents the method of choice to identify interacting proteins. The composition of complex isoforms concurrently present in the AP sample can, however, not be resolved from a single AP-MS experiment but requires computational inference from multiple time- and resource-intensive reciprocal AP-MS experiments. Here we introduce deep interactome profiling by mass spectrometry (DIP-MS), which combines AP with blue-native-PAGE separation, data-independent acquisition with mass spectrometry and deep-learning-based signal processing to resolve complex isoforms sharing the same bait protein in a single experiment. We applied DIP-MS to probe the organization of the human prefoldin family of complexes, resolving distinct prefoldin holo- and subcomplex variants, complex-complex interactions and complex isoforms with new subunits that were experimentally validated. Our results demonstrate that DIP-MS can reveal proteome modularity at unprecedented depth and resolution.

DOI: https://doi.org/10.1038/s41592-024-02211-y
Int J Mol Sci. 2024 Mar 19. pii: 3458. [Epub ahead of print]25(6):

Simultaneous Determination of One-Carbon Folate Metabolites and One-Carbon-Related Amino Acids in Biological Samples Using a UHPLC-MS/MS Method.

Yi Ling, Mei Tan, Xiaoyun Wang, Ziyi Meng, Xiaodong Quan, Hosahalli Ramaswamy, Chao Wang.

  One-carbon folate metabolites and one-carbon-related amino acids play an important role in human physiology, and their detection in biological samples is essential. However, poor stability as well as low concentrations and occurrence in different species in various biological samples make their quantification very challenging. The aim of this study was to develop a simple, fast, and sensitive ultra-high-performance liquid chromatography MS/MS (UHPLC-MS/MS) method for the simultaneous quantification of various one-carbon folate metabolites (folic acid (FA), tetrahydrofolic acid (THF), p-aminobenzoyl-L-glutamic acid (pABG), 5-formyltetrahydrofolic acid (5-CHOTHF), 5-methyltetrahydrofolic acid (5-CH3THF), 10-formylfolic acid (10-CHOFA), 5,10-methenyl-5,6,7,8-tetrahydrofolic acid (5,10-CH+-THF), and 4-α-hydroxy-5-methyltetrahydrofolate (hmTHF)) and one-carbon-related amino acids (homocysteine (Hcy), methionine (Met), S-ade-L-homocysteine (SAH), and S-ade-L-methionine (SAM)). The method was standardized and validated by determining the selectivity, carryover, limits of detection, limits of quantitation, linearity, precision, accuracy, recovery, and matrix effects. The extraction methods were optimized with respect to several factors: protease-amylase treatment on embryos, deconjugation time, methanol precipitation, and proteins' isoelectric point precipitation on the folate recovery. Ten one-carbon folate metabolites and four one-carbon-related amino acids were detected using the UHPLC-MS/MS technique in various biological samples. The measured values of folate in human plasma, serum, and whole blood (WB) lay within the concentration range for normal donors. The contents of each analyte in mouse plasma were as follows: pABG (864.0 nmol/L), 5-CH3THF (202.2 nmol/L), hmTHF (122.2 nmol/L), Met (8.63 μmol/L), and SAH (0.06 μmol/L). The concentration of each analyte in mouse embryos were as follows: SAM (1.09 μg/g), SAH (0.13 μg/g), Met (16.5 μg/g), 5,10-CH+THF (74.3 ng/g), pABG (20.6 ng/g), and 5-CH3THF (185.4 ng/g). A simple and rapid sample preparation and UHPLC-MS/MS method was developed and validated for the simultaneous determination of the one-carbon-related folate metabolites and one-carbon-related amino acids in different biological samples.

Keywords:  UHPLC–MS/MS; amino acids; biological samples; folate

DOI:  https://doi.org/10.3390/ijms25063458
Biophys Rep. 2023 Dec 31. 9(6): 299-308

Rapid quantification of 50 fatty acids in small amounts of biological samples for population molecular phenotyping.

Pinghui Liu, Qinsheng Chen, Lianglong Zhang, Chengcheng Ren, Biru Shi, Jingxian Zhang, Shuaiyao Wang, Ziliang Chen, Qi Wang, Hui Xie, Qingxia Huang, Huiru Tang.

  Efficient quantification of fatty-acid (FA) composition (fatty-acidome) in biological samples is crucial for understanding physiology and pathophysiology in large population cohorts. Here, we report a rapid GC-FID/MS method for simultaneous quantification of all FAs in numerous biological matrices. Within eight minutes, this method enabled simultaneous quantification of 50 FAs as fatty-acid methyl esters (FAMEs) in femtomole levels following the efficient transformation of FAs in all lipids including FFAs, cholesterol-esters, glycerides, phospholipids and sphingolipids. The method showed satisfactory inter-day and intra-day precision, stability and linearity (R2 > 0.994) within a concentration range of 2-3 orders of magnitude. FAs were then quantified in typical multiple biological matrices including human biofluids (urine, plasma) and cells, animal intestinal content and tissue samples. We also established a quantitative structure-retention relationship (QSRR) for analytes to accurately predict their retention time and aid their reliable identification. We further developed a novel no-additive retention index (NARI) with endogenous FAMEs reducing inter-batch variations to 15 seconds; such NARI performed better than the alkanes-based classical RI, making meta-analysis possible for data obtained from different batches and platforms. Collectively, this provides an inexpensive high-throughput analytical system for quantitative phenotyping of all FAs in 8-minutes multiple biological matrices in large cohort studies of pathophysiological effects.

Keywords:  Fatty-acidomics; High-throughput quantification; No-additive retention index; Structure-retention relationship

DOI:  https://doi.org/10.52601/bpr.2023.230042
J Proteome Res. 2024 Mar 27.

SpectiCal: m/z Calibration of MS2 Peptide Spectra Using Known Low Mass Ions.

Nathan H Zhang, Eric W Deutsch.

  Most tandem mass spectrometry fragmentation spectra have small calibration errors that can lead to suboptimal interpretation and annotation. We developed SpectiCal, a software tool that can read mzML files from data-dependent acquisition proteomics experiments in parallel, compute m/z calibrations for each file prior to identification analysis based on known low-mass ions, and produce information about frequently observed peaks and their explanations. Using calibration coefficients, the data can be corrected to generate new calibrated mzML files. SpectiCal was tested using five public data sets, creating a table of commonly observed low-mass ions and their identifications. Information about the calibration and individual peaks is written in PDF and TSV files. This includes information for each peak, such as the number of runs in which it appears, the percentage of spectra in which it appears, and a plot of the aggregated region surrounding each peak. SpectiCal can be used to compute MS run calibrations, examine MS runs for artifacts that might hinder downstream analysis, and generate tables of detected low-mass ions for further analysis. SpectiCal is freely available at https://github.com/PlantProteomes/SpectiCal.

Keywords:  Mass spectrometry; SpectiCal; immonium ions; low-mass ions; proteomics; spectral calibration

DOI:  https://doi.org/10.1021/acs.jproteome.3c00882
J Proteome Res. 2024 Mar 27.

Use of Nonhuman Sera as a Highly Cost-Effective Internal Standard for Quantitation of Multiple Human Proteins Using Species-Specific Tryptic Peptides: Applicability in Clinical LC-MS Analyses.

Geraldine Williams, Lewis Couchman, David R Taylor, Jatinderpal K Sandhu, Oliver C Slingsby, Leong L Ng, Cajetan F Moniz, Donald J L Jones, Colleen B Maxwell.

  Quantitation of proteins using liquid chromatography-tandem mass spectrometry (LC-MS/MS) is complex, with a multiplicity of options ranging from label-free techniques to chemically and metabolically labeling proteins. Increasingly, for clinically relevant analyses, stable isotope-labeled (SIL) internal standards (ISs) represent the "gold standard" for quantitation due to their similar physiochemical properties to the analyte, wide availability, and ability to multiplex to several peptides. However, the purchase of SIL-ISs is a resource-intensive step in terms of cost and time, particularly for screening putative biomarker panels of hundreds of proteins. We demonstrate an alternative strategy utilizing nonhuman sera as the IS for quantitation of multiple human proteins. We demonstrate the effectiveness of this strategy using two high abundance clinically relevant analytes, vitamin D binding protein [Gc globulin] (DBP) and albumin (ALB). We extend this to three putative risk markers for cardiovascular disease: plasma protease C1 inhibitor (SERPING1), annexin A1 (ANXA1), and protein kinase, DNA-activated catalytic subunit (PRKDC). The results show highly specific, reproducible, and linear measurement of the proteins of interest with comparable precision and accuracy to the gold standard SIL-IS technique. This approach may not be applicable to every protein, but for many proteins it can offer a cost-effective solution to LC-MS/MS protein quantitation.

Keywords:  bottom-up proteomics; cardiovascular risk markers; low cost; multiple reaction monitoring; quantitation; quantitative proteomics; selected reaction monitoring; surrogate standard; targeted proteomics

DOI:  https://doi.org/10.1021/acs.jproteome.3c00762
Cancer Metab. 2024 Mar 26. 12(1): 10

BCAA metabolism in pancreatic cancer affects lipid balance by regulating fatty acid import into mitochondria.

Klára Gotvaldová, Jitka Špačková, Jiří Novotný, Kamila Baslarová, Petr Ježek, Lenka Rossmeislová, Jan Gojda, Katarína Smolková.

   BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) has been associated with the host dysmetabolism of branched-chain amino acids (BCAAs), however, the implications for the role of BCAA metabolism in PDAC development or progression are not clear. The mitochondrial catabolism of valine, leucine, and isoleucine is a multistep process leading to the production of short-chain R-CoA species. They can be subsequently exported from mitochondria as short-chain carnitines (SC-CARs), utilized in anabolic pathways, or released from the cells.
METHODS: We examined the specificities of BCAA catabolism and cellular adaptation strategies to BCAA starvation in PDAC cells in vitro. We used metabolomics and lipidomics to quantify major metabolic changes in response to BCAA withdrawal. Using confocal microscopy and flow cytometry we quantified the fluorescence of BODIPY probe and the level of lipid droplets (LDs). We used BODIPY-conjugated palmitate to evaluate transport of fatty acids (FAs) into mitochondria. Also, we have developed a protocol for quantification of SC-CARs, BCAA-derived metabolites.
RESULTS: Using metabolic profiling, we found that BCAA starvation leads to massive triglyceride (TG) synthesis and LD accumulation. This was associated with the suppression of activated FA transport into the mitochondrial matrix. The suppression of FA import into mitochondria was rescued with the inhibitor of the acetyl-CoA carboxylase (ACC) and the activator of AMP kinase (AMPK), which both regulate carnitine palmitoyltransferase 1A (CPT1) activation status.
CONCLUSIONS: Our data suggest that BCAA catabolism is required for the import of long chain carnitines (LC-CARs) into mitochondria, whereas the disruption of this link results in the redirection of activated FAs into TG synthesis and its deposition into LDs. We propose that this mechanism protects cells against mitochondrial overload with LC-CARs and it might be part of the universal reaction to amino acid perturbations during cancer growth, regulating FA handling and storage.

Keywords:  BCAA metabolism; Fatty acid/Transport; Fluorescence microscopy; Lipid droplets; Lipidomics; Mitochondria; Pancreatic cancer; Triglycerides

DOI:  https://doi.org/10.1186/s40170-024-00335-5
Methods Mol Biol. 2024 ;2758 341-373

Identification and Targeted Quantification of Endogenous Neuropeptides in the Nematode Caenorhabditis elegans Using Mass Spectrometry.

Sven Van Bael, Christina Ludwig, Geert Baggerman, Liesbet Temmerman.

  The nematode Caenorhabditis elegans lends itself as an excellent model organism for peptidomics studies. Its ease of cultivation and quick generation time make it suitable for high-throughput studies. The nervous system, with its 302 neurons, is probably the best-known and studied endocrine tissue. Moreover, its neuropeptidergic signaling pathways display numerous similarities with those observed in other metazoans. Here, we describe two label-free approaches for neuropeptidomics in C. elegans: one for discovery purposes, and another for targeted quantification and comparisons of neuropeptide levels between different samples. Starting from a detailed peptide extraction procedure, we here outline the liquid chromatography tandem mass spectrometry (LC-MS/MS) setup and describe subsequent data analysis approaches.

Keywords:  Caenorhabditis elegans; Data-dependent acquisition; FMRFamide-like peptide; LC-MS/MS; Label-free quantification; Mass spectrometry; Neuropeptide; Neuropeptide-like protein; Parallel reaction monitoring; Peptidomics; flp; nlp

DOI:  https://doi.org/10.1007/978-1-0716-3646-6_19
Molecules. 2024 Mar 21. pii: 1398. [Epub ahead of print]29(6):

A Chiral-LC-MS Method for the Simultaneous Quantification of Short-Chain Fatty Acids and D/L-Lactate in the Ruminal Fluid of Dairy Cows.

Zhiqian Liu, S Richard O Williams, Joe L Jacobs, Aodan S O Neachtain, Simone Rochfort.

  Short-chain fatty acids (SCFA) and lactate in ruminal fluid are products resulting from the microbial fermentation of substrates and can be used to reflect the composition and activity of the ruminal microbiome. Determination of SCFA and D-/L-lactate in ruminal fluid currently requires two separate protocols, which is time-consuming and costly. In this study, we have optimised and validated a simple and unified 3-nitrophenylhydrazine (3-NPH) derivatisation protocol and a 20 min chiral-LC-MS method for the simultaneous quantification of all SCFA and D- and L-lactate in ruminal fluid. This method, which requires no sample pretreatment or purification shows adequate sensitivity (limit of detection (LOD): 0.01 µg/mL), satisfactory accuracy (recovery: 88-103%), and excellent reproducibility (relative standard deviation (RSD) for repeated analyses < 3% for most analytes). The application of this method to a cohort of 24 animals allowed us to reveal a large inter-cow variation in ruminal SCFA and lactate level, the concentration range for each species, the widespread correlation between different SCFA, and the strong correlation between D- and L-lactate.

Keywords:  D-lactate; L-lactate; liquid chromatography–mass spectrometry; ruminal fluid; short-chain fatty acids

DOI:  https://doi.org/10.3390/molecules29061398
Biomolecules. 2024 Mar 01. pii: 296. [Epub ahead of print]14(3):

Association of Altered Plasma Lipidome with Disease Severity in COVID-19 Patients.

Zhengzheng Zhang, Naama Karu, Alida Kindt, Madhulika Singh, Lieke Lamont, Adriaan J van Gammeren, Anton A M Ermens, Amy C Harms, Lutzen Portengen, Roel C H Vermeulen, Willem A Dik, Anton W Langerak, Vincent H J van der Velden, Thomas Hankemeier.

  The severity of COVID-19 is linked to an imbalanced immune response. The dysregulated metabolism of small molecules and bioactive lipids has also been associated with disease severity. To promote understanding of the disease biochemistry and provide targets for intervention, we applied a range of LC-MS platforms to analyze over 100 plasma samples from patients with varying COVID-19 severity and with detailed clinical information on inflammatory responses (>30 immune markers). This is the third publication in a series, and it reports the results of comprehensive lipidome profiling using targeted LC-MS/MS. We identified 1076 lipid features across 25 subclasses, including glycerophospholipids, sterols, glycerolipids, and sphingolipids, among which 531 lipid features were dramatically changed in the plasma of intensive care unit (ICU) patients compared to patients in the ward. Patients in the ICU showed 1.3-57-fold increases in ceramides, (lyso-)glycerophospholipids, diglycerides, triglycerides, and plasmagen phosphoethanolamines, and 1.3-2-fold lower levels of a cyclic lysophosphatidic acid, sphingosine-1-phosphates, sphingomyelins, arachidonic acid-containing phospholipids, lactosylceramide, and cholesterol esters compared to patients in the ward. Specifically, phosphatidylinositols (PIs) showed strong fatty acid saturation-dependent behavior, with saturated fatty acid (SFA)- and monosaturated fatty acid (MUFA)-derived PI decreasing and polystaturated (PUFA)-derived PI increasing. We also found ~4000 significant Spearman correlations between lipids and multiple clinical markers of immune response with |R| ≥ 0.35 and FDR corrected Q < 0.05. Except for lysophosphatidic acid, lysophospholipids were positively associated with the CD4 fraction of T cells, and the cytokines IL-8 and IL-18. In contrast, sphingosine-1-phosphates were negatively correlated with innate immune markers such as CRP and IL-6. Further indications of metabolic changes in moderate COVID-19 disease were demonstrated in recovering ward patients compared to those at the start of hospitalization, where 99 lipid species were altered (6 increased by 30-62%; 93 decreased by 1.3-2.8-fold). Overall, these findings support and expand on early reports that dysregulated lipid metabolism is involved in COVID-19.

Keywords:  COVID-19; SARS-CoV-2; cytokine; inflammation; lipidomics; lipids

DOI:  https://doi.org/10.3390/biom14030296
Anal Chem. 2024 Mar 26.

Tandem Mass Spectrometry across Platforms.

Corey Hoang, Winnie Uritboonthai, Linh Hoang, Elizabeth M Billings, Aries Aisporna, Farshad A Nia, Rico J E Derks, James R Williamson, Martin Giera, Gary Siuzdak.

PubChem serves as a comprehensive repository, housing over 100 million unique chemical structures representing the breadth of our chemical knowledge across numerous fields including metabolism, pharmaceuticals, toxicology, cosmetics, agriculture, and many more. Rapid identification of these small molecules increasingly relies on electrospray ionization (ESI) paired with tandem mass spectrometry (MS/MS), particularly by comparison to genuine standard MS/MS data sets. Despite its widespread application, achieving consistency in MS/MS data across various analytical platforms remains an unaddressed concern. This study evaluated MS/MS data derived from one hundred molecular standards utilizing instruments from five manufacturers, inclusive of quadrupole time-of-flight (QTOF) and quadrupole orbitrap "exactive" (QE) mass spectrometers by Agilent (QTOF), Bruker (QTOF), SCIEX (QTOF), Waters (QTOF), and Thermo QE. We assessed fragment ion variations at multiple collisional energies (0, 10, 20, and 40 eV) using the cosine scoring algorithm for comparisons and the number of fragments observed. A parallel visual analysis of the MS/MS spectra across instruments was conducted, consistent with a standard procedure that is used to circumvent the still prevalent issue of mischaracterizations as shown for dimethyl sphingosine and C20 sphingosine. Our analysis revealed a notable consistency in MS/MS data and identifications, with fragment ions' m/z values exhibiting the highest concordance between instrument platforms at 20 eV, the other collisional energies (0, 10, and 40 eV) were significantly lower. While moving toward a standardized ESI MS/MS protocol is required for dependable molecular characterization, our results also underscore the continued importance of corroborating MS/MS data against standards to ensure accurate identifications. Our findings suggest that ESI MS/MS manufacturers, akin to the established norms for gas chromatography mass spectrometry instruments, should standardize the collision energy at 20 eV across different instrument platforms.

DOI: https://doi.org/10.1021/acs.analchem.3c05576
J Chromatogr A. 2024 Mar 20. pii: S0021-9673(24)00200-0. [Epub ahead of print]1721 464827

Isomers-oriented separation of forty-five plasma bile acids with liquid chromatography-tandem mass spectrometry.

Lei Zhang, Xu Liu, Tenghui Jin, Jing Dong, Xiaodong Li, Youyi Zhang, Dongyang Liu.

  Some bile acids (BAs) were considered as biomarkers or have therapeutical effect on metabolic diseases. However, due to the existence of isomers and limitations in sensitivity, simultaneous quantification of multiple BAs remains a challenge. The aim of this study is to establish an accurate and sensitive method for the determination of multiple BAs with similar polarity. A LC-MS/MS analytical method capable of quantifying forty-five BAs simultaneously using nine stable isotope internal standards was developed and fully validated based on key isomers-oriented separation strategy. The method was further applied to analyze plasma samples to describe the dynamic profile of BAs after high glucose intake. The chromatography and mass spectrum conditions were optimized to enable the accurate quantification of forty-five BAs, while ensuring the lower limit of quantification between 0.05-10 ng/mL. The results of system suitability, linearity, dilution integrity, accuracy and precision demonstrated the good quantitative capacity and robustness of the method. A total of thirty-five BAs were quantified in plasma samples from twelve healthy Chinese individuals. The established method featured superior sensitivity and better separation efficiency compared to previous studies. Meanwhile, BAs exhibited correlations with glucose and insulin, suggesting their potential as biomarkers for metabolic disorders.

Keywords:  Bile acids; Isomers-oriented separation; LC-MS/MS; Metabolic diseases; Method validation

DOI:  https://doi.org/10.1016/j.chroma.2024.464827
Metabolites. 2024 Feb 29. pii: 148. [Epub ahead of print]14(3):

Diagnostic and Prognostic Performance of Metabolic Signatures in Pancreatic Ductal Adenocarcinoma: The Clinical Application of Quantitative NextGen Mass Spectrometry.

Paulo D'Amora, Ismael D C G Silva, Steven S Evans, Adam J Nagourney, Katharine A Kirby, Brett Herrmann, Daniela Cavalheiro, Federico R Francisco, Paula J Bernard, Robert A Nagourney.

  With 64,050 new diagnoses and 50,550 deaths in the US in 2023, pancreatic ductal adenocarcinoma (PDAC) is among the most lethal of all human malignancies. Early detection and improved prognostication remain critical unmet needs. We applied next-generation metabolomics, using quantitative tandem mass spectrometry on plasma, to develop biochemical signatures that identify PDAC. We first compared plasma from 10 PDAC patients to 169 samples from healthy controls. Using metabolomic algorithms and machine learning, we identified ratios that incorporate amino acids, biogenic amines, lysophosphatidylcholines, phosphatidylcholines and acylcarnitines that distinguished PDAC from normal controls. A confirmatory analysis then applied the algorithms to 30 PDACs compared with 60 age- and sex-matched controls. Metabolic signatures were then analyzed to compare survival, measured in months, from date of diagnosis to date of death that identified metabolite ratios that stratified PDACs into distinct survival groups. The results suggest that metabolic signatures could provide PDAC diagnoses earlier than tumor markers or radiographic measures and offer insights into disease severity that could allow more judicious use of therapy by stratifying patients into metabolic-risk subgroups.

Keywords:  NextGen metabolomics; biomarker; early detection; metabolic profiling; pancreatic cancer; prognostication; survival analysis

DOI:  https://doi.org/10.3390/metabo14030148
Anal Chim Acta. 2024 Apr 29. pii: S0003-2670(24)00236-8. [Epub ahead of print]1300 342435

Derivatization of carboxylic groups prior to their LC analysis - A review.

Timotej Jankech, Ivana Gerhardtova, Petra Majerova, Juraj Piestansky, Josef Jampilek, Andrej Kovac.

  Carboxylic acids (CAs) represent a large group of important molecules participating in various biologically significant processes. Analytical study of these compounds is typically performed by liquid chromatography (LC) combined with various types of detection. However, their analysis is often accompanied by a wide variety of problems depending on used separation system or detection method. The dominant ones are: i) poor chromatographic behavior of the CAs in reversed-phase LC; ii) absence of a chromophore (or fluorophore); iii) weak ionization in mass spectrometry (MS). To overcome these problems, targeted chemical modification, and derivatization, come into play. Therefore, derivatization still plays an important and, in many cases, irreplaceable role in sample preparation, and new derivatization methods of CAs are constantly being developed. The most commonly used type of reaction for CAs derivatization is amidation. In recent years, an increased interest in the isotopic labeling derivatization method has been observed. In this review, we comprehensively summarize the possibilities and actual trends in the derivatization of CAs that have been published over the past decade.

Keywords:  Carboxylic acid; Chemical modification; Derivatization; Liquid chromatography

DOI:  https://doi.org/10.1016/j.aca.2024.342435