bims-mascan 2023-02-05 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2023–02–05
25 papers selected by
Giovanny Rodriguez Blanco, University of Edinburgh

A palmitate-rich metastatic niche enables metastasis growth via p65 acetylation resulting in pro-metastatic NF-κB signaling.
Strategies for Increasing the Depth and Throughput of Protein Analysis by plexDIA.
Quantification of Dolichyl Phosphates Using Phosphate Methylation and Reverse-Phase Liquid Chromatography-High Resolution Mass Spectrometry.
Generalized tree structure to annotate untargeted metabolomics and stable isotope tracing data.
Reconstruction of Glutathione Metabolism in the Neuronal Model of Rotenone-Induced Neurodegeneration Using Mass Isotopologue Analysis with Hydrophilic Interaction Liquid Chromatography-Zeno High-Resolution Multiple Reaction Monitoring.
Omic-Scale High-Throughput Quantitative LC-MS/MS Approach for Circulatory Lipid Phenotyping in Clinical Research.
Automated Enrichment of Phosphotyrosine Peptides for High-Throughput Proteomics.
Quantification of short-chain fatty acids in human stool samples by LC-MS/MS following derivatization with aniline analogues.
Metabolite fingerprinting: A powerful metabolomics approach for marker identification and functional gene annotation.
Data-dependent and -independent acquisition lipidomics analysis reveals the tissue-dependent effect of metformin on lipid metabolism.
Targeted Small-Molecule Identification Using Heartcutting Liquid Chromatography-Infrared Ion Spectroscopy.
Data Processing of Product Ion Spectra: Quality Improvement by Averaging Multiple Similar Spectra of Small Molecules.
Fatty liver-mediated glycine restriction impairs glutathione synthesis and causes hypersensitization to acetaminophen.
Lysophospholipids and branched chain amino acids are associated with aging: a metabolomics-based study of Chinese adults.
Immunometabolic factors contributing to obesity-linked hepatocellular carcinoma.
Attempts to Detect Lipid Metabolites from a Single Cell Using Proton-Transfer-Reaction Mass Spectrometry Coupled with Micro-Scale Supercritical Fluid Extraction: A Preliminary Study.
NPOmix: A machine learning classifier to connect mass spectrometry fragmentation data to biosynthetic gene clusters.
Analysis of RNA Sequences and Modifications Using NASE.
PI5P4Kα supports prostate cancer metabolism and exposes a survival vulnerability during androgen receptor inhibition.
ASAP─Automated Sonication-Free Acid-Assisted Proteomes─from Cells and FFPE Tissues.
Host-microbe co-metabolism via MCAD generates circulating metabolites including hippuric acid.
Slow TCA flux and ATP production in primary solid tumours but not metastases.
MYC disrupts transcriptional and metabolic circadian oscillations in cancer and promotes enhanced biosynthesis.
Trace analysis of dimethoxytrityl alcohol (DMT-OH) in oligonucleotide matrices using liquid chromatography coupled with tandem mass spectrometry.
Integrated multi-omics reveals anaplerotic rewiring in methylmalonyl-CoA mutase deficiency.

Nat Cancer. 2023 Feb 02.

A palmitate-rich metastatic niche enables metastasis growth via p65 acetylation resulting in pro-metastatic NF-κB signaling.

Patricia Altea-Manzano, Ginevra Doglioni, Yawen Liu, Alejandro M Cuadros, Emma Nolan, Juan Fernández-García, Qi Wu, Mélanie Planque, Kathrin Julia Laue, Florencia Cidre-Aranaz, Xiao-Zheng Liu, Oskar Marin-Bejar, Joke Van Elsen, Ines Vermeire, Dorien Broekaert, Sofie Demeyer, Xander Spotbeen, Jakub Idkowiak, Aurélie Montagne, Margherita Demicco, H Furkan Alkan, Nick Rabas, Carla Riera-Domingo, François Richard, Tatjana Geukens, Maxim De Schepper, Sophia Leduc, Sigrid Hatse, Yentl Lambrechts, Emily Jane Kay, Sergio Lilla, Alisa Alekseenko, Vincent Geldhof, Bram Boeckx, Celia de la Calle Arregui, Giuseppe Floris, Johannes V Swinnen, Jean-Christophe Marine, Diether Lambrechts, Vicent Pelechano, Massimiliano Mazzone, Sara Zanivan, Jan Cools, Hans Wildiers, Véronique Baud, Thomas G P Grünewald, Uri Ben-David, Christine Desmedt, Ilaria Malanchi, Sarah-Maria Fendt.

Metabolic rewiring is often considered an adaptive pressure limiting metastasis formation; however, some nutrients available at distant organs may inherently promote metastatic growth. We find that the lung and liver are lipid-rich environments. Moreover, we observe that pre-metastatic niche formation increases palmitate availability only in the lung, whereas a high-fat diet increases it in both organs. In line with this, targeting palmitate processing inhibits breast cancer-derived lung metastasis formation. Mechanistically, breast cancer cells use palmitate to synthesize acetyl-CoA in a carnitine palmitoyltransferase 1a-dependent manner. Concomitantly, lysine acetyltransferase 2a expression is promoted by palmitate, linking the available acetyl-CoA to the acetylation of the nuclear factor-kappaB subunit p65. Deletion of lysine acetyltransferase 2a or carnitine palmitoyltransferase 1a reduces metastasis formation in lean and high-fat diet mice, and lung and liver metastases from patients with breast cancer show coexpression of both proteins. In conclusion, palmitate-rich environments foster metastases growth by increasing p65 acetylation, resulting in a pro-metastatic nuclear factor-kappaB signaling.

DOI: https://doi.org/10.1038/s43018-023-00513-2
J Proteome Res. 2023 Feb 03.

Strategies for Increasing the Depth and Throughput of Protein Analysis by plexDIA.

Jason Derks, Nikolai Slavov.

  Accurate protein quantification is key to identifying protein markers, regulatory relationships between proteins, and pathophysiological mechanisms. Realizing this potential requires sensitive and deep protein analysis of a large number of samples. Toward this goal, proteomics throughput can be increased by parallelizing the analysis of both precursors and samples using multiplexed data independent acquisition (DIA) implemented by the plexDIA framework: https://plexDIA.slavovlab.net. Here we demonstrate the improved precisions of retention time estimates within plexDIA and how this enables more accurate protein quantification. plexDIA has demonstrated multiplicative gains in throughput, and these gains may be substantially amplified by improving the multiplexing reagents, data acquisition, and interpretation. We discuss future directions for advancing plexDIA, which include engineering optimized mass-tags for high-plexDIA, introducing isotopologous carriers, and developing algorithms that utilize the regular structures of plexDIA data to improve sensitivity, proteome coverage, and quantitative accuracy. These advances in plexDIA will increase the throughput of functional proteomic assays, including quantifying protein conformations, turnover dynamics, modifications states and activities. The sensitivity of these assays will extend to single-cell analysis, thus enabling functional single-cell protein analysis.

Keywords:  high-throughput; isotopologous carriers; mass tags; multiplexed data independent acquisition; multiplexed proteomics; plexDIA; sensitive proteomics; single-cell proteomics

DOI:  https://doi.org/10.1021/acs.jproteome.2c00721
Anal Chem. 2023 Jan 30.

Quantification of Dolichyl Phosphates Using Phosphate Methylation and Reverse-Phase Liquid Chromatography-High Resolution Mass Spectrometry.

Dipali Kale, Frauke Kikul, Prasad Phapale, Lars Beedgen, Christian Thiel, Britta Brügger.

Dolichyl monophosphates (DolPs) are essential lipids in glycosylation pathways that are highly conserved across almost all domains of life. The availability of DolP is critical for all glycosylation processes, as these lipids serve as membrane-anchored building blocks used by various types of glycosyltransferases to generate complex post-translational modifications of proteins and lipids. The analysis of DolP species by reverse-phase liquid chromatography-mass spectrometry (RPLC-MS) remains a challenge due to their very low abundance and wide range of lipophilicities. Until now, a method for the simultaneous qualitative and quantitative assessment of DolP species from biological membranes has been lacking. Here, we describe a novel approach based on simple sample preparation, rapid and efficient trimethylsilyl diazomethane-dependent phosphate methylation, and RPLC-MS analysis for quantification of DolP species with different isoprene chain lengths. We used this workflow to selectively quantify DolP species from lipid extracts derived of Saccharomyces cerevisiae, HeLa, and human skin fibroblasts from steroid 5-α-reductase 3- congenital disorders of glycosylation (SRD5A3-CDG) patients and healthy controls. Integration of this workflow with global lipidomics analyses will be a powerful tool to expand our understanding of the role of DolPs in pathophysiological alterations of metabolic pathways downstream of HMG-CoA reductase, associated with CDGs, hypercholesterolemia, neurodegeneration, and cancer.

DOI: https://doi.org/10.1021/acs.analchem.2c03623
bioRxiv. 2023 Jan 04. pii: 2023.01.04.522722. [Epub ahead of print]

Generalized tree structure to annotate untargeted metabolomics and stable isotope tracing data.

Shuzhao Li, Shujian Zheng.

In untargeted metabolomics, multiple ions are often measured for each original metabolite, including isotopic forms and in-source modifications, such as adducts and fragments. Without prior knowledge of the chemical identity or formula, computational organization and interpretation of these ions is challenging, which is the deficit of previous software tools that perform the task using network algorithms. We propose here a generalized tree structure to annotate ions to relationships to the original compound and infer neutral mass. An algorithm is presented to convert mass distance networks to this tree structure with high fidelity. This method is useful for both regular untargeted metabolomics and stable isotope tracing experiments. It is implemented as a Python package (khipu), and provides a JSON format for easy data exchange and software interoperability. By generalized pre-annotation, khipu makes it feasible to connect metabolomics data with common data science tools, and supports flexible experimental designs.

DOI: https://doi.org/10.1101/2023.01.04.522722
Anal Chem. 2023 Feb 03.

Reconstruction of Glutathione Metabolism in the Neuronal Model of Rotenone-Induced Neurodegeneration Using Mass Isotopologue Analysis with Hydrophilic Interaction Liquid Chromatography-Zeno High-Resolution Multiple Reaction Monitoring.

Luojiao Huang, Nicolas Drouin, Jason Causon, Agnieszka Wegrzyn, Jose Castro-Perez, Ronan Fleming, Amy Harms, Thomas Hankemeier.

Accurate reconstruction of metabolic pathways is an important prerequisite for interpreting metabolomics changes and understanding the diverse biological processes in disease models. A tracer-based metabolomics strategy utilizes stable isotope-labeled precursors to resolve complex pathways by tracing the labeled atom(s) to downstream metabolites through enzymatic reactions. Isotope enrichment analysis is informative and achieved by counting total labeled atoms and acquiring the mass isotopologue distribution (MID) of the intact metabolite. However, quantitative analysis of labeled metabolite substructures/moieties (MS2 fragments) can offer more valuable insights into the reaction connections through measuring metabolite transformation. In order to acquire the isotopic labeling information at the intact metabolite and moiety level simultaneously, we developed a method that couples hydrophilic interaction liquid chromatography (HILIC) with Zeno trap-enabled high-resolution multiple reaction monitoring (MRMHR). The method enabled accurate and reproducible MID quantification for intact metabolites as well as their fragmented moieties, with notably high sensitivity in the MS2 fragmentation mode based on the measurement of 13C- or 15N-labeled cellular samples. The method was applied to human-induced pluripotent stem cell-derived neurons to trace the fate of 13C/15N atoms from D-13C6-glucose/L-15N2-glutamine added to the media. With the MID analysis of both intact metabolites and fragmented moieties, we validated the pathway reconstruction of de novo glutathione synthesis in mid-brain neurons. We discovered increased glutathione oxidization from both basal and newly synthesized glutathione pools under neuronal oxidative stress. Furthermore, the significantly decreased de novo glutathione synthesis was investigated and associated with altered activities of several key enzymes, as evidenced by suppressed glutamate supply via glucose metabolism and a diminished flux of glutathione synthetic reaction in the neuronal model of rotenone-induced neurodegeneration.

DOI: https://doi.org/10.1021/acs.analchem.2c04231
Anal Chem. 2023 Jan 30.

Omic-Scale High-Throughput Quantitative LC-MS/MS Approach for Circulatory Lipid Phenotyping in Clinical Research.

Jessica Medina, Rebecca Borreggine, Tony Teav, Liang Gao, Shanshan Ji, Justin Carrard, Christina Jones, Niek Blomberg, Martin Jech, Alan Atkins, Claudia Martins, Arno Schmidt-Trucksass, Martin Giera, Amaury Cazenave-Gassiot, Hector Gallart-Ayala, Julijana Ivanisevic.

Lipid analysis at the molecular species level represents a valuable opportunity for clinical applications due to the essential roles that lipids play in metabolic health. However, a comprehensive and high-throughput lipid profiling remains challenging given the lipid structural complexity and exceptional diversity. Herein, we present an 'omic-scale targeted LC-MS/MS approach for the straightforward and high-throughput quantification of a broad panel of complex lipid species across 26 lipid (sub)classes. The workflow involves an automated single-step extraction with 2-propanol, followed by lipid analysis using hydrophilic interaction liquid chromatography in a dual-column setup coupled to tandem mass spectrometry with data acquisition in the timed-selective reaction monitoring mode (12 min total run time). The analysis pipeline consists of an initial screen of 1903 lipid species, followed by high-throughput quantification of robustly detected species. Lipid quantification is achieved by a single-point calibration with 75 isotopically labeled standards representative of different lipid classes, covering lipid species with diverse acyl/alkyl chain lengths and unsaturation degrees. When applied to human plasma, 795 lipid species were measured with median intra- and inter-day precisions of 8.5 and 10.9%, respectively, evaluated within a single and across multiple batches. The concentration ranges measured in NIST plasma were in accordance with the consensus intervals determined in previous ring-trials. Finally, to benchmark our workflow, we characterized NIST plasma materials with different clinical and ethnic backgrounds and analyzed a sub-set of sera (n = 81) from a clinically healthy elderly population. Our quantitative lipidomic platform allowed for a clear distinction between different NIST materials and revealed the sex-specificity of the serum lipidome, highlighting numerous statistically significant sex differences.

DOI: https://doi.org/10.1021/acs.analchem.2c02598
bioRxiv. 2023 Jan 06. pii: 2023.01.05.522335. [Epub ahead of print]

Automated Enrichment of Phosphotyrosine Peptides for High-Throughput Proteomics.

Alexis Chang, Mario Leutert, Ricard A Rodriguez-Mias, Judit Vill N.

Phosphotyrosine (pY) enrichment is critical for expanding fundamental and clinical understanding of cellular signaling by mass spectrometry-based proteomics. However, current pY enrichment methods exhibit a high cost per sample and limited reproducibility due to expensive affinity reagents and manual processing. We present rapid-robotic phosphotyrosine proteomics (R2-pY), which uses a magnetic particle processor and pY superbinders or antibodies. R2-pY handles 96 samples in parallel, requires 2 days to go from cell lysate to mass spectrometry injections, and results in global proteomic, phosphoproteomic and tyrosine specific phosphoproteomic samples. We benchmark the method on HeLa cells stimulated with pervanadate and serum and report over 4000 unique pY sites from 1 mg of peptide input, strong reproducibility between replicates, and phosphopeptide enrichment efficiencies above 99%. R2-pY extends our previously reported R2-P2 proteomic and global phosphoproteomic sample preparation framework, opening the door to large-scale studies of pY signaling in concert with global proteome and phosphoproteome profiling.

DOI: https://doi.org/10.1101/2023.01.05.522335
J Chromatogr B Analyt Technol Biomed Life Sci. 2023 Jan 27. pii: S1570-0232(23)00028-4. [Epub ahead of print]1217 123618

Quantification of short-chain fatty acids in human stool samples by LC-MS/MS following derivatization with aniline analogues.

Matthew J McKay, Miguel Castaneda, Sarah Catania, Kellie A Charles, Erin Shanahan, Stephen J Clarke, Alexander Engel, Peter Varelis, Mark P Molloy.

  The gut microbiome produces a range of short chain fatty acids (SCFA) crucially linked with diet and nutrition, metabolism, gastrointestinal health and homeostasis. SCFA are primarily measured using gas or liquid chromatography-mass spectrometry (LC/MS) after undergoing chemical derivatization. Here we assess the merits of a derivatization protocol using aniline and two aniline analogues (3-phenoxyaniline and 4-(benzyloxy)aniline) for the targeted LC-MS/MS quantification of nine SCFA (acetic, propionic, butyric, valeric, caproic acid, isobutyric, isovaleric, 2-methylbutyric, and 2-ethylbutyric acid). Evaluation of product ion spectra and optimization of MS detection conditions, provided superior detection sensitivity for 3-phenoxyaniline and 4-(benzyloxy)aniline compared to aniline. We developed a facile SCFA derivatization method using 3-phenoxyaniline under mild reaction conditions which allows for the simultaneous quantification of these SCFA in human stool samples in under eleven minutes using multiple reaction monitoring LC-MS/MS. The method was successfully validated and demonstrates intra- and inter-day accuracy (88.5-103% and 86.0-109%) and precision (CV of 0.55-7.00% and 0.33-9.55%) with recoveries (80.1-87.2% for LLOQ, 88.5-93.0% for ULOQ) and carry-over of (2.68-17.9%). Selectivity, stability and matrix effects were also assessed and satisfied validation criteria. Method applicability was demonstrated by analysing SCFA profiles in DNA-stabilized human stool samples from newly diagnosed colorectal cancer patients prior to surgery. The development of this improved method and its compatibility to measure SCFAs from DNA-stabilized stool will facilitate studies investigating the gut microbiome in health and disease.

Keywords:  Derivatization; Liquid chromatography-mass spectrometry (LC-MS); Microbiome; Quantitation; Short chain fatty acids; Stool

DOI:  https://doi.org/10.1016/j.jchromb.2023.123618
Methods Enzymol. 2023 ;pii: S0076-6879(22)00340-8. [Epub ahead of print]680 325-350

Metabolite fingerprinting: A powerful metabolomics approach for marker identification and functional gene annotation.

Kirstin Feussner, Ilka N Abreu, Moritz Klein, Ivo Feussner.

  Non-targeted metabolome approaches aim to detect metabolite markers related to stress, disease, developmental or genetic perturbation. In the later context, it is also a powerful means for functional gene annotation. A prerequisite for non-targeted metabolome analyses are methods for comprehensive metabolite extraction. We present three extraction protocols for a highly efficient extraction of metabolites from plant material with a very broad metabolite coverage. The presented metabolite fingerprinting workflow is based on liquid chromatography high resolution accurate mass spectrometry (LC-HRAM-MS), which provides suitable separation of the complex sample matrix for the analysis of compounds of different polarity by positive and negative electrospray ionization and mass spectrometry. The resulting data sets are then analyzed with the software suite MarVis and the web-based interface MetaboAnalyst. MarVis offers a straightforward workflow for statistical analysis, data merging as well as visualization of multivariate data, while MetaboAnalyst is used in our hands as complementary software for statistics, correlation networks and figure generation. Finally, MarVis provides access to species-specific metabolite and pathway data bases like KEGG and BioCyc and to custom data bases tailored by the user to connect the identified markers or features with metabolites. In addition, identified marker candidates can be interactively visualized and inspected in metabolic pathway maps by KEGG pathways for a more detailed functional annotation and confirmed by mass spectrometry fragmentation experiments or coelution with authentic standards. Together this workflow is a valuable toolbox to identify novel metabolites, metabolic steps or regulatory principles and pathways.

Keywords:  Custom databases; Data mining; Extraction; Metabolite fingerprinting; Metabolome; Non-targeted metabolomics

DOI:  https://doi.org/10.1016/bs.mie.2022.08.015
Res Sq. 2023 Jan 10. pii: rs.3.rs-2444456. [Epub ahead of print]

Data-dependent and -independent acquisition lipidomics analysis reveals the tissue-dependent effect of metformin on lipid metabolism.

Grace Scheidemantle, Likun Duan, Mareca Lodge, Magdalina J Cummings, Dalton Hilovsky, Eva Pham, Xiaoqiu Wang, Arion Kennedy, Xiaojing Liu.

Introduction Despite the well-recognized health benefits, the mechanisms and site of action of metformin remains elusive. Metformin-induced global lipidomic changes in plasma of animal models and human subjects have been reported. However, there is a lack of systemic evaluation of metformin-induced lipidomic changes in different tissues. Metformin uptake requires active transporters such as organic cation transporters (OCTs), and hence, it is anticipated that metformin actions are tissue-dependent. In this study, we aim to characterize metformin effects in non-diabetic male mice with a special focus on lipidomics analysis. The findings from this study will help us to better understand the cell-autonomous (direct actions in target cells) or non-cell-autonomous (indirect actions in target cells) mechanisms of metformin and provide insights into the development of more potent yet safe drugs targeting a particular organ instead of systemic metabolism for metabolic regulations without major side effects. Objectives To characterize metformin-induced lipidomic alterations in different tissues of non-diabetic male mice and further identify lipids affected by metformin through cell-autonomous or systemic mechanisms based on the correlation between lipid alterations in tissues and the corresponding in-tissue metformin concentrations. Methods Lipids were extracted from tissues and plasma of male mice treated with or without metformin in drinking water for 12 days and analyzed using MS/MS scan workflow (hybrid mode) on LC-Orbitrap Exploris 480 mass spectrometer using biologically relevant lipids-containing inclusion list for data-independent acquisition (DIA), named as BRI-DIA workflow followed by data-dependent acquisition (DDA), to maximum the coverage of lipids and minimize the negative effect of stochasticity of precursor selection on experimental consistency and reproducibility. Results Lipidomics analysis of 6 mouse tissues and plasma using MS/MS combining BRI-DIA and DDA allowed a systemic evaluation of lipidomic changes induced by metformin in different tissues. We observed that 1) the degrees of lipidomic changes induced by metformin treatment overly correlated with tissue concentrations of metformin; 2) the impact on lysophosphorylcholine and cardiolipins was positively correlated with tissue concentrations of metformin, while neutral lipids such as triglycerides did not correlate with the corresponding tissue metformin concentrations. Conclusion The data collected in this study from non-diabetic mice with 12-day metformin treatment suggest that the overall metabolic effect of metformin is positively correlated with tissue concentrations and the effect on individual lipid subclass is via both cell-autonomous mechanisms (cardiolipins and lysoPC) and non-cell-autonomous mechanisms (triglycerides).

DOI: https://doi.org/10.21203/rs.3.rs-2444456/v1
Anal Chem. 2023 Feb 03.

Targeted Small-Molecule Identification Using Heartcutting Liquid Chromatography-Infrared Ion Spectroscopy.

Rianne E van Outersterp, Jitse Oosterhout, Christoph R Gebhardt, Giel Berden, Udo F H Engelke, Ron A Wevers, Filip Cuyckens, Jos Oomens, Jonathan Martens.

Infrared ion spectroscopy (IRIS) can be used to identify molecular structures detected in mass spectrometry (MS) experiments and has potential applications in a wide range of analytical fields. However, MS-based approaches are often combined with orthogonal separation techniques, in many cases liquid chromatography (LC). The direct coupling of LC and IRIS is challenging due to the mismatching timescales of the two technologies: an IRIS experiment typically takes several minutes, whereas an LC fraction typically elutes in several seconds. To resolve this discrepancy, we present a heartcutting LC-IRIS approach using a setup consisting of two switching valves and two sample loops as an alternative to direct online LC-IRIS coupling. We show that this automated setup enables us to record multiple IR spectra for two LC-features from a single injection without degrading the LC-separation performance. We demonstrate the setup for application in drug metabolism research by recording six m/z-selective IR spectra for two drug metabolites from a single 2 μL sample of cell incubation extract. Additionally, we measure the IR spectra of two closely eluting diastereomeric biomarkers for the inborn error of metabolism pyridoxine-dependent epilepsy (PDE-ALDH7A1), which shows that the heartcutting LC-IRIS setup has good sensitivity (requiring ∼μL injections of ∼μM samples) and that the separation between closely eluting isomers is maintained. We envision applications in a range of research fields, where the identification of molecular structures detected by LC-MS is required.

DOI: https://doi.org/10.1021/acs.analchem.2c04904
Mass Spectrom (Tokyo). 2022 ;11(1): A0106

Data Processing of Product Ion Spectra: Quality Improvement by Averaging Multiple Similar Spectra of Small Molecules.

Fumio Matsuda, Shuka Komori, Yuki Yamada, Daiki Hara, Nobuyuki Okahashi.

  In metabolomics studies using high-resolution mass spectrometry (MS), a set of product ion spectra is comprehensively acquired from observed ions using the data-dependent acquisition (DDA) mode of various tandem MS. However, especially for low-intensity signals, it is sometimes difficult to distinguish artifact signals from true fragment ions derived from a precursor ion. Inadequate precision in the measured m/z value is also one of the bottlenecks to narrowing down the candidate compositional formula. In this study, we report that averaging multiple product ion spectra can improve m/z precision as well as the reliability of fragment ions that are observed in such spectra. A graph-based method was applied to cluster a set of similar spectra from multiple DDA data files resulting in creating an averaged product-ion spectrum. The error levels for the m/z values declined following the central limit theorem, which allowed us to reduce the number of candidate compositional formulas. The improved reliability and precision of the averaged spectra will contribute to a more efficient annotation of product ion spectral data.

Keywords:  data-dependent acquisition mode; elemental composition search; metabolomics; precision

DOI:  https://doi.org/10.5702/massspectrometry.A0106
bioRxiv. 2023 Jan 18. pii: 2023.01.16.524043. [Epub ahead of print]

Fatty liver-mediated glycine restriction impairs glutathione synthesis and causes hypersensitization to acetaminophen.

Alia Ghrayeb, Bella Agranovich, Daniel Peled, Alexandra C Finney, Ifat Abramovich, Jonatan Fernandez Garcia, James Traylor, Shani Drucker, Sara Isabelle Fernandes, Natan Weissman, Y Eugene Chen, Oren Rom, Inbal Mor, Eyal Gottlieb.

Non-alcoholic fatty liver disease (NAFLD) affects nearly one third of the population worldwide. Understanding metabolic pathways involved can provide insights into disease progression. Untargeted metabolomics of livers from mice with early-stage steatosis indicated a decrease in methylated metabolites suggesting altered one carbon metabolism. The levels of glycine, a central component of one carbon metabolism, were lower in steatotic mice, in line with clinical evidence. Isotope tracing studies demonstrated that increased synthesis of serine from glycine is the underlying cause for glycine limitation in fatty livers. Consequently, the low glycine availability in steatotic livers impaired glutathione (GSH) synthesis under oxidative stress induced by acetaminophen (APAP), enhancing hepatic toxicity. Glycine supplementation mitigated acute liver damage and overall toxicity caused by APAP in fatty livers by supporting de novo GSH synthesis. Thus, early metabolic changes in NAFLD that lead to glycine depletion sensitize mice to xenobiotic toxicity even at a reversible stage of NAFLD.

DOI: https://doi.org/10.1101/2023.01.16.524043
Eur J Med Res. 2023 Feb 02. 28(1): 58

Lysophospholipids and branched chain amino acids are associated with aging: a metabolomics-based study of Chinese adults.

Yiming Pan, Pan Liu, Shijie Li, Bowen Li, Yun Li, Lina Ma.

   BACKGROUND: Aging is an inevitable process associated with impairments in multiple organ systems, which increases the risk of comorbidity and disability, and reduces the health-span. Metabolomics is a powerful tool in aging research, which can reflect the characteristics of aging at the level of terminal metabolism, and may contribute to the exploration of aging mechanisms and the formulation of anti-aging strategies.
METHODS: To identify possible biomarkers and pathways associated with aging using untargeted metabolomics methods, we performed liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics profiling on serum samples from 32 older adults and 32 sex-matched young controls.
RESULTS: Metabolite profiling could distinguish the two groups. Among the 349 metabolites identified, 80-including lysophospholipids whose levels gradually decline-are possible candidate aging biomarkers. Valine, leucine and isoleucine degradation and biosynthesis were important pathways in aging, with reduced levels of L-isoleucine (r = - 0.30, p = 0.017) and L-leucine (r = - 0.32, p = 0.010) observed in older adults.
CONCLUSIONS: We preliminarily revealed the metabolite changes associated with aging in Chinese adults. Decreases in mitochondrial membrane-related lysophospholipids and dysfunction of branched-chain amino acid metabolism were determined to be the characteristics and promising research targets for aging.

Keywords:  Aging; Biomarker; Branched-chain amino acid; Lysophospholipid; Metabolomics

DOI:  https://doi.org/10.1186/s40001-023-01021-w
Front Cell Dev Biol. 2022 ;10 1089124

Immunometabolic factors contributing to obesity-linked hepatocellular carcinoma.

May G Akl, Scott B Widenmaier.

  Hepatocellular carcinoma (HCC) is a major public health concern that is promoted by obesity and associated liver complications. Onset and progression of HCC in obesity is a multifactorial process involving complex interactions between the metabolic and immune system, in which chronic liver damage resulting from metabolic and inflammatory insults trigger carcinogenesis-promoting gene mutations and tumor metabolism. Moreover, cell growth and proliferation of the cancerous cell, after initiation, requires interactions between various immunological and metabolic pathways that provide stress defense of the cancer cell as well as strategic cell death escape mechanisms. The heterogenic nature of HCC in addition to the various metabolic risk factors underlying HCC development have led researchers to focus on examining metabolic pathways that may contribute to HCC development. In obesity-linked HCC, oncogene-induced modifications and metabolic pathways have been identified to support anabolic demands of the growing HCC cells and combat the concomitant cell stress, coinciding with altered utilization of signaling pathways and metabolic fuels involved in glucose metabolism, macromolecule synthesis, stress defense, and redox homeostasis. In this review, we discuss metabolic insults that can underlie the transition from steatosis to steatohepatitis and from steatohepatitis to HCC as well as aberrantly regulated immunometabolic pathways that enable cancer cells to survive and proliferate in the tumor microenvironment. We also discuss therapeutic modalities targeted at HCC prevention and regression. A full understanding of HCC-associated immunometabolic changes in obesity may contribute to clinical treatments that effectively target cancer metabolism.

Keywords:  NAFLD; hepatocellular carcinoma (HCC); immunometabolism; obesity; stress pathways

DOI:  https://doi.org/10.3389/fcell.2022.1089124
Mass Spectrom (Tokyo). 2022 ;11(1): A0112

Attempts to Detect Lipid Metabolites from a Single Cell Using Proton-Transfer-Reaction Mass Spectrometry Coupled with Micro-Scale Supercritical Fluid Extraction: A Preliminary Study.

Toshinobu Hondo, Chihiro Ota, Kohta Nakatani, Yumi Miyake, Hiroshi Furutani, Takeshi Bamba, Michisato Toyoda.

  Proton-transfer-reaction (PTR) mass spectrometry (MS), a widely used method for detecting trace-levels of volatile organic compounds in gaseous samples, can also be used for the analysis of small non-volatile molecules by using supercritical fluid as a transporter for the molecules. Supercritical fluid extraction (SFE) is a method that permits lipophilic compounds to be rapidly and selectively extracted from complex matrices. The combination of the high sensitivity of PTR MS with the SFE is a potentially novel method for analyzing small molecules in a single cell, particularly for the analysis of lipophilic compounds. We preliminarily evaluated this method for analyzing the components of a single HeLa cell that is fixed on a stainless steel frit and is then directly introduces the SFE extracts into the PTR MS. A total of 200/91 ions were observed in positive/negative ion mode time-of-flight mass spectra, and the masses of 11/10 ions could be matched to chemical formulae obtained from the LipidMaps lipids structure database. Using various authentic lipophilic samples, the method could be used to detect free fatty acids in the sub-femtomole to femtomole order in the negative ion mode, the femtomole to sub-picomole order for fat-soluble vitamins, and the picomole order for poly aromatic hydrocarbons in both the positive and negative ion mode.

Keywords:  proton-transfer-reaction mass spectrometry; single-cell lipid metabolite analysis; supercritical fluid chromatography; supercritical fluid extraction; water ion chemical ionization

DOI:  https://doi.org/10.5702/massspectrometry.A0112
PNAS Nexus. 2022 Nov;1(5): pgac257

NPOmix: A machine learning classifier to connect mass spectrometry fragmentation data to biosynthetic gene clusters.

Tiago F Leão, Mingxun Wang, Ricardo da Silva, Alexey Gurevich, Anelize Bauermeister, Paulo Wender P Gomes, Asker Brejnrod, Evgenia Glukhov, Allegra T Aron, Joris J R Louwen, Hyun Woo Kim, Raphael Reher, Marli F Fiore, Justin J J van der Hooft, Lena Gerwick, William H Gerwick, Nuno Bandeira, Pieter C Dorrestein.

  Microbial specialized metabolites are an important source of and inspiration for many pharmaceuticals, biotechnological products and play key roles in ecological processes. Untargeted metabolomics using liquid chromatography coupled with tandem mass spectrometry is an efficient technique to access metabolites from fractions and even environmental crude extracts. Nevertheless, metabolomics is limited in predicting structures or bioactivities for cryptic metabolites. Efficiently linking the biosynthetic potential inferred from (meta)genomics to the specialized metabolome would accelerate drug discovery programs by allowing metabolomics to make use of genetic predictions. Here, we present a k-nearest neighbor classifier to systematically connect mass spectrometry fragmentation spectra to their corresponding biosynthetic gene clusters (independent of their chemical class). Our new pattern-based genome mining pipeline links biosynthetic genes to metabolites that they encode for, as detected via mass spectrometry from bacterial cultures or environmental microbiomes. Using paired datasets that include validated genes-mass spectral links from the Paired Omics Data Platform, we demonstrate this approach by automatically linking 18 previously known mass spectra (17 for which the biosynthesis gene clusters can be found at the MIBiG database plus palmyramide A) to their corresponding previously experimentally validated biosynthetic genes (e.g., via nuclear magnetic resonance or genetic engineering). We illustrated a computational example of how to use our Natural Products Mixed Omics (NPOmix) tool for siderophore mining that can be reproduced by the users. We conclude that NPOmix minimizes the need for culturing (it worked well on microbiomes) and facilitates specialized metabolite prioritization based on integrative omics mining.

Keywords:  biosynthetic gene clusters; genomics; machine learning; mass spectrometry; specialized metabolites

DOI:  https://doi.org/10.1093/pnasnexus/pgac257
Methods Mol Biol. 2023 ;2624 225-239

Analysis of RNA Sequences and Modifications Using NASE.

Samuel Wein.

  Mass spectrometry is an ideal method for the discovery and characterization of modified RNAs. Unlike other traditional sequencing methods, mass spectrometry can identify and localize multiple types of modifications in tandem. One of the traditional hurdles to using this powerful technique has been a paucity of software to interpret the complicated data produced by these experiments. Here I describe how to use the NucleicAcidSearchEngine (NASE), a component of OpenMS as well as best practices for acquiring RNA data, and potential pitfalls in the analysis process.

Keywords:  Mass spectrometry; OpenMS; RNA; Transcriptomics

DOI:  https://doi.org/10.1007/978-1-0716-2962-8_15
Sci Adv. 2023 Feb 03. 9(5): eade8641

PI5P4Kα supports prostate cancer metabolism and exposes a survival vulnerability during androgen receptor inhibition.

Joanna Triscott, Matthias Reist, Lukas Küng, Francielle C Moselle, Marika Lehner, John Gallon, Archna Ravi, Gurpreet K Arora, Simone de Brot, Mark Lundquist, Hector Gallart-Ayala, Julijana Ivanisevic, Salvatore Piscuoglio, Lewis C Cantley, Brooke M Emerling, Mark A Rubin.

Phosphatidylinositol (PI)regulating enzymes are frequently altered in cancer and have become a focus for drug development. Here, we explore the phosphatidylinositol-5-phosphate 4-kinases (PI5P4K), a family of lipid kinases that regulate pools of intracellular PI, and demonstrate that the PI5P4Kα isoform influences androgen receptor (AR) signaling, which supports prostate cancer (PCa) cell survival. The regulation of PI becomes increasingly important in the setting of metabolic stress adaptation of PCa during androgen deprivation (AD), as we show that AD influences PI abundance and enhances intracellular pools of PI-4,5-P2. We suggest that this PI5P4Kα-AR relationship is mitigated through mTORC1 dysregulation and show that PI5P4Kα colocalizes to the lysosome, the intracellular site of mTORC1 complex activation. Notably, this relationship becomes prominent in mouse prostate tissue following surgical castration. Finally, multiple PCa cell models demonstrate marked survival vulnerability following stable PI5P4Kα inhibition. These results nominate PI5P4Kα as a target to disrupt PCa metabolic adaptation to castrate resistance.

DOI: https://doi.org/10.1126/sciadv.ade8641
Anal Chem. 2023 Feb 01.

ASAP─Automated Sonication-Free Acid-Assisted Proteomes─from Cells and FFPE Tissues.

Georgina D Barnabas, Verena Goebeler, Janice Tsui, Jonathan W Bush, Philipp F Lange.

Formalin-fixed, paraffin-embedded (FFPE) tissues are an invaluable resource for retrospective studies, but protein extraction and subsequent sample processing steps have been shown to be challenging for mass spectrometry (MS) analysis. Streamlined high-throughput sample preparation workflows are essential for efficient peptide extraction from complex clinical specimens such as fresh frozen tissues or FFPE. Overall, proteome analysis has gained significant improvements in the instrumentation, acquisition methods, sample preparation workflows, and analysis pipelines, yet even the most recent FFPE workflows remain complex and are not readily scalable. Here, we present an optimized workflow for automated sonication-free acid-assisted proteome (ASAP) extraction from FFPE sections. ASAP enables efficient protein extraction from FFPE specimens, achieving similar proteome coverage as established methods using expensive sonicators, resulting in reduced sample processing time. The broad applicability of ASAP on archived pediatric tumor FFPE specimens resulted in high-quality data with increased proteome coverage and quantitative reproducibility. Our study demonstrates the practicality and superiority of the ASAP workflow as a streamlined, time- and cost-effective pipeline for high-throughput FFPE proteomics of clinical specimens.

DOI: https://doi.org/10.1021/acs.analchem.2c04264
Nat Commun. 2023 Jan 31. 14(1): 512

Host-microbe co-metabolism via MCAD generates circulating metabolites including hippuric acid.

Kali M Pruss, Haoqing Chen, Yuanyuan Liu, William Van Treuren, Steven K Higginbottom, John B Jarman, Curt R Fischer, Justin Mak, Beverly Wong, Tina M Cowan, Michael A Fischbach, Justin L Sonnenburg, Dylan Dodd.

The human gut microbiota produces dozens of small molecules that circulate in blood, accumulate to comparable levels as pharmaceutical drugs, and influence host physiology. Despite the importance of these metabolites to human health and disease, the origin of most microbially-produced molecules and their fate in the host remains largely unknown. Here, we uncover a host-microbe co-metabolic pathway for generation of hippuric acid, one of the most abundant organic acids in mammalian urine. Combining stable isotope tracing with bacterial and host genetics, we demonstrate reduction of phenylalanine to phenylpropionic acid by gut bacteria; the host re-oxidizes phenylpropionic acid involving medium-chain acyl-CoA dehydrogenase (MCAD). Generation of germ-free male and female MCAD-/- mice enabled gnotobiotic colonization combined with untargeted metabolomics to identify additional microbial metabolites processed by MCAD in host circulation. Our findings uncover a host-microbe pathway for the abundant, non-toxic phenylalanine metabolite hippurate and identify β-oxidation via MCAD as a novel mechanism by which mammals metabolize microbiota-derived metabolites.

DOI: https://doi.org/10.1038/s41467-023-36138-3
Nature. 2023 Feb 01.

Slow TCA flux and ATP production in primary solid tumours but not metastases.

Caroline R Bartman, Daniel R Weilandt, Yihui Shen, Won Dong Lee, Yujiao Han, Tara TeSlaa, Connor S R Jankowski, Laith Samarah, Noel R Park, Victoria da Silva-Diz, Maya Aleksandrova, Yetis Gultekin, Argit Marishta, Lin Wang, Lifeng Yang, Asael Roichman, Vrushank Bhatt, Taijin Lan, Zhixian Hu, Xi Xing, Wenyun Lu, Shawn Davidson, Martin Wühr, Matthew G Vander Heiden, Daniel Herranz, Jessie Yanxiang Guo, Yibin Kang, Joshua D Rabinowitz.

Tissues derive ATP from two pathways-glycolysis and the tricarboxylic acid (TCA) cycle coupled to the electron transport chain. Most energy in mammals is produced via TCA metabolism1. In tumours, however, the absolute rates of these pathways remain unclear. Here we optimize tracer infusion approaches to measure the rates of glycolysis and the TCA cycle in healthy mouse tissues, Kras-mutant solid tumours, metastases and leukaemia. Then, given the rates of these two pathways, we calculate total ATP synthesis rates. We find that TCA cycle flux is suppressed in all five primary solid tumour models examined and is increased in lung metastases of breast cancer relative to primary orthotopic tumours. As expected, glycolysis flux is increased in tumours compared with healthy tissues (the Warburg effect2,3), but this increase is insufficient to compensate for low TCA flux in terms of ATP production. Thus, instead of being hypermetabolic, as commonly assumed, solid tumours generally produce ATP at a slower than normal rate. In mouse pancreatic cancer, this is accommodated by the downregulation of protein synthesis, one of this tissue's major energy costs. We propose that, as solid tumours develop, cancer cells shed energetically expensive tissue-specific functions, enabling uncontrolled growth despite a limited ability to produce ATP.

DOI: https://doi.org/10.1038/s41586-022-05661-6
bioRxiv. 2023 Jan 04. pii: 2023.01.03.522637. [Epub ahead of print]

MYC disrupts transcriptional and metabolic circadian oscillations in cancer and promotes enhanced biosynthesis.

Rachel E DeRollo, Juliana Cazarin, Siti Noor Ain Binti Ahmad Shahidan, Jamison B Burchett, Daniel Mwangi, Saikumari Krishnaiah, Annie L Hsieh, Zandra E Walton, Rebekah Brooks, Stephano S Mello, Aalim M Weljie, Chi V Dang, Brian J Altman.

The molecular circadian clock, which controls rhythmic 24-hour oscillation of genes, proteins, and metabolites, is disrupted across many human cancers. Deregulated expression of MYC oncoprotein has been shown to alter expression of molecular clock genes, leading to a disruption of molecular clock oscillation across cancer types. It remains unclear what benefit cancer cells gain from suppressing clock oscillation, and how this loss of molecular clock oscillation impacts global gene expression and metabolism in cancer. We hypothesized that MYC suppresses oscillation of gene expression and metabolism to instead upregulate pathways involved in biosynthesis in a static, non-oscillatory fashion. To test this, cells from distinct cancer types with inducible MYC or the closely related N-MYC were examined, using detailed time-series RNA-sequencing and metabolomics, to determine the extent to which MYC activation disrupts global oscillation of genes, gene expression, programs, and metabolites. We focused our analyses on genes, pathways, and metabolites that changed in common across multiple cancer cell line models. We report here that MYC disrupted over 85% of oscillating genes, while instead promoting enhanced ribosomal and mitochondrial biogenesis and suppressed cell attachment pathways. Notably, when MYC is activated, biosynthetic programs that were formerly circadian flipped to being upregulated in an oscillation-free manner. Further, activation of MYC ablates the oscillation of nutrient transporter glycosylation while greatly upregulating transporter expression, cell surface localization, and intracellular amino acid pools. Finally, we report that MYC disrupts metabolite oscillations and the temporal segregation of amino acid metabolism from nucleotide metabolism. Our results demonstrate that MYC disruption of the molecular circadian clock releases metabolic and biosynthetic processes from circadian control, which may provide a distinct advantage to cancer cells.

DOI: https://doi.org/10.1101/2023.01.03.522637
Anal Methods. 2023 Jan 27.

Trace analysis of dimethoxytrityl alcohol (DMT-OH) in oligonucleotide matrices using liquid chromatography coupled with tandem mass spectrometry.

Bing Guan, Wuming Yan, Jessica A Stolee.

A liquid chromatography (LC) method with ultraviolet (UV) and tandem mass spectrometry (MS/MS) detection was developed to quantify dimethoxytrityl alcohol (DMT-OH), a small molecule byproduct generated during the detritylation reaction in oligonucleotide synthesis. The pros and cons of quantification via multiple analytical methods including LC coupled with UV, selected ion monitoring (SIM), and multiple reaction monitoring (MRM) were evaluated. The MRM method was ultimately selected for further qualification and exhibited good linearity (R2 = 0.997 from 0.5 to 64 ng mL-1), accuracy (recoveries ranging 75-90% with ≤ 2% RSD), repeatability (<5% RSD), and sensitivity (LOQ of 1.6 ng mL-1). The MRM method was further applied to analyze DMT-OH in various oligonucleotide intermediates and drug substances. Similar MRM methods for six other small molecule impurities (aniline, benzamide, isobutyramide, 2-phenylacetamide, succinamide, and uny-CTP) as well as their application are also presented.

DOI: https://doi.org/10.1039/d2ay02020c
Nat Metab. 2023 Jan;5(1): 80-95

Integrated multi-omics reveals anaplerotic rewiring in methylmalonyl-CoA mutase deficiency.

Patrick Forny, Ximena Bonilla, David Lamparter, Wenguang Shao, Tanja Plessl, Caroline Frei, Anna Bingisser, Sandra Goetze, Audrey van Drogen, Keith Harshman, Patrick G A Pedrioli, Cedric Howald, Martin Poms, Florian Traversi, Céline Bürer, Sarah Cherkaoui, Raphael J Morscher, Luke Simmons, Merima Forny, Ioannis Xenarios, Ruedi Aebersold, Nicola Zamboni, Gunnar Rätsch, Emmanouil T Dermitzakis, Bernd Wollscheid, Matthias R Baumgartner, D Sean Froese.

Methylmalonic aciduria (MMA) is an inborn error of metabolism with multiple monogenic causes and a poorly understood pathogenesis, leading to the absence of effective causal treatments. Here we employ multi-layered omics profiling combined with biochemical and clinical features of individuals with MMA to reveal a molecular diagnosis for 177 out of 210 (84%) cases, the majority (148) of whom display pathogenic variants in methylmalonyl-CoA mutase (MMUT). Stratification of these data layers by disease severity shows dysregulation of the tricarboxylic acid cycle and its replenishment (anaplerosis) by glutamine. The relevance of these disturbances is evidenced by multi-organ metabolomics of a hemizygous Mmut mouse model as well as through identification of physical interactions between MMUT and glutamine anaplerotic enzymes. Using stable-isotope tracing, we find that treatment with dimethyl-oxoglutarate restores deficient tricarboxylic acid cycling. Our work highlights glutamine anaplerosis as a potential therapeutic intervention point in MMA.

DOI: https://doi.org/10.1038/s42255-022-00720-8