bims-mascan 2023-09-03 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2023–09–03
twenty-two papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz

Deep and fast label-free Dynamic Organellar Mapping.
Mass Spectrometry-based Lipidomics, Lipid Bioenergetics, and Web Tool for Lipid Profiling and Quantification in Human Cells.
SCALiR: a web application for automating absolute quantification of mass spectrometry-based metabolomics data.
Adipocytes reprogram cancer cell metabolism by diverting glucose towards glycerol-3-phosphate thereby promoting metastasis.
Assessing the Role of Trypsin in Quantitative Plasma and Single-Cell Proteomics toward Clinical Application.
Spotlight on GOT2 in Cancer Metabolism.
Mass spectrometry-based proteomics as an emerging tool in clinical laboratories.
Clinical Proteomics: Liquid Chromatography-Mass Spectrometry (LC-MS) Purification Systems.
Investigating the Potential of Drift Tube Ion Mobility for the Analysis of Oxidized Lipids.
Proteomics analysis of circulating small extracellular vesicles: Focus on the contribution of EVs to tumor metabolism.
Deep Learning Based MS2 Feature Detection for Data-Independent Shotgun Proteomics.
Dual strategy for 13C-Metabolic flux analysis of central carbon and energy metabolism in Mammalian cells based on LC-isoMRM-MS.
A multipathway phosphopeptide standard for rapid phosphoproteomics assay development.
Permethylation and Metal Adduction: A Toolbox for the Improved Characterization of Glycolipids with Cyclic Ion Mobility Separations Coupled to Mass Spectrometry.
Design of experiments approach for systematic optimization of a single-shot diaPASEF plasma proteomics workflow applicable for high-throughput.
Lipid metabolic vulnerabilities of multiple myeloma.
Foresight in clinical proteomics: current status, ethical considerations, and future perspectives.
Automated Sample Preparation Workflow for Tandem Mass Tag-Based Proteomics.
Multitargeted Internal Calibration for the Quantification of Chronic Kidney Disease-Related Endogenous Metabolites Using Liquid Chromatography-Mass Spectrometry.
Scout triggered multiple reaction monitoring mass spectrometry for the rapid transfer of large multiplexed targeted methods in metabolomics.
Formate promotes invasion and metastasis in reliance on lipid metabolism.
Serum methylmalonic acid concentrations at breast cancer diagnosis significantly correlate with clinical frailty.

Nat Commun. 2023 Aug 29. 14(1): 5252

Deep and fast label-free Dynamic Organellar Mapping.

Julia P Schessner, Vincent Albrecht, Alexandra K Davies, Pavel Sinitcyn, Georg H H Borner.

The Dynamic Organellar Maps (DOMs) approach combines cell fractionation and shotgun-proteomics for global profiling analysis of protein subcellular localization. Here, we enhance the performance of DOMs through data-independent acquisition (DIA) mass spectrometry. DIA-DOMs achieve twice the depth of our previous workflow in the same mass spectrometry runtime, and substantially improve profiling precision and reproducibility. We leverage this gain to establish flexible map formats scaling from high-throughput analyses to extra-deep coverage. Furthermore, we introduce DOM-ABC, a powerful and user-friendly open-source software tool for analyzing profiling data. We apply DIA-DOMs to capture subcellular localization changes in response to starvation and disruption of lysosomal pH in HeLa cells, which identifies a subset of Golgi proteins that cycle through endosomes. An imaging time-course reveals different cycling patterns and confirms the quantitative predictive power of our translocation analysis. DIA-DOMs offer a superior workflow for label-free spatial proteomics as a systematic phenotype discovery tool.

DOI: https://doi.org/10.1038/s41467-023-41000-7
Bio Protoc. 2023 Aug 20. 13(16): e4742

Mass Spectrometry-based Lipidomics, Lipid Bioenergetics, and Web Tool for Lipid Profiling and Quantification in Human Cells.

Liang Cui, Meisam Yousefi, Xin Yap, Clara W T Koh, Kwan Sing Leona Tay, Yaw Shin Ooi, Kuan Rong Chan.

  Lipids can play diverse roles in metabolism, signaling, transport across membranes, regulating body temperature, and inflammation. Some viruses have evolved to exploit lipids in human cells to promote viral entry, fusion, replication, assembly, and energy production through fatty acid beta-oxidation. Hence, studying the virus-lipid interactions provides an opportunity to understand the biological processes involved in the viral life cycle, which can facilitate the development of antivirals. Due to the diversity and complexity of lipids, the assessment of lipid utilization in infected host cells can be challenging. However, the development of mass spectrometry, bioenergetics profiling, and bioinformatics has significantly advanced our knowledge on the study of lipidomics. Herein, we describe the detailed methods for lipid extraction, mass spectrometry, and assessment of fatty acid oxidation on cellular bioenergetics, as well as the bioinformatics approaches for detailed lipid analysis and utilization in host cells. These methods were employed for the investigation of lipid alterations in TMEM41B- and VMP1-deficient cells, where we previously found global dysregulations of the lipidome in these cells. Furthermore, we developed a web app to plot clustermaps or heatmaps for mass spectrometry data that is open source and can be hosted locally or at https://kuanrongchan-lipid-metabolite-analysis-app-k4im47.streamlit.app/. This protocol provides an efficient step-by-step methodology to assess lipid composition and usage in host cells.

Keywords:  Bioenergetics; Clustergram; Lipid profiling; Lipidomics; Mass spectrometry; Seahorse assay; Virus–lipid interactions; Web tool

DOI:  https://doi.org/10.21769/BioProtoc.4742
bioRxiv. 2023 Aug 16. pii: 2023.08.16.551807. [Epub ahead of print]

SCALiR: a web application for automating absolute quantification of mass spectrometry-based metabolomics data.

Stephanie L Bishop, Luis F Ponce-Alvarez, Soren Wacker, Ryan A Groves, Ian A Lewis.

Metabolomics is an important approach for studying complex biological systems. Quantitative liquid chromatography-mass spectrometry (LC-MS)-based metabolomics is becoming a mainstream strategy but presents several technical challenges that limit its widespread use. Computing metabolite concentrations using standard curves generated from standard mixtures of known concentrations is a labor-intensive process which is often performed manually. Currently, there are few options for open-source software tools that can automatically calculate metabolite concentrations. Herein, we introduce SCALiR (Standard Curve Application for determining Linear Ranges), a new web-based software tool specifically built for this task, which allows users to automatically transform LC-MS signal data into absolute quantitative data ( https://www.lewisresearchgroup.org/software ). The algorithm used in SCALiR automatically finds the equation of the line of best fit for each standard curve and uses this equation to calculate compound concentrations from their LC-MS signal. Using a standard mix containing 77 metabolites, we found excellent correlation between the concentrations calculated by SCALiR and the expected concentrations of each compound (R 2 = 0.99) and that SCALiR reproducibly calculated concentrations of mid-range standards across ten analytical batches (average coefficient of variation 0.091). SCALiR offers users several advantages, including that it (1) is open-source and vendor agnostic; (2) requires only 10 seconds of analysis time to compute concentrations of >75 compounds; (3) facilitates automation of quantitative workflows; and (4) performs deterministic evaluation of compound quantification limits. SCALiR provides the metabolomics community with a simple and rapid tool that enables rigorous and reproducible quantitative metabolomics studies.

DOI: https://doi.org/10.1101/2023.08.16.551807
Nat Metab. 2023 Aug 31.

Adipocytes reprogram cancer cell metabolism by diverting glucose towards glycerol-3-phosphate thereby promoting metastasis.

Abir Mukherjee, Divya Bezwada, Francesco Greco, Malu Zandbergen, Tong Shen, Chun-Yi Chiang, Medine Tasdemir, Johannes Fahrmann, Dmitry Grapov, Michael R La Frano, Hieu S Vu, Brandon Faubert, John W Newman, Liam A McDonnell, Luigi Nezi, Oliver Fiehn, Ralph J DeBerardinis, Ernst Lengyel.

In the tumor microenvironment, adipocytes function as an alternate fuel source for cancer cells. However, whether adipocytes influence macromolecular biosynthesis in cancer cells is unknown. Here we systematically characterized the bidirectional interaction between primary human adipocytes and ovarian cancer (OvCa) cells using multi-platform metabolomics, imaging mass spectrometry, isotope tracing and gene expression analysis. We report that, in OvCa cells co-cultured with adipocytes and in metastatic tumors, a part of the glucose from glycolysis is utilized for the biosynthesis of glycerol-3-phosphate (G3P). Normoxic HIF1α protein regulates the altered flow of glucose-derived carbons in cancer cells, resulting in increased glycerophospholipids and triacylglycerol synthesis. The knockdown of HIF1α or G3P acyltransferase 3 (a regulatory enzyme of glycerophospholipid synthesis) reduced metastasis in xenograft models of OvCa. In summary, we show that, in an adipose-rich tumor microenvironment, cancer cells generate G3P as a precursor for critical membrane and signaling components, thereby promoting metastasis. Targeting biosynthetic processes specific to adipose-rich tumor microenvironments might be an effective strategy against metastasis.

DOI: https://doi.org/10.1038/s42255-023-00879-8
Anal Chem. 2023 Aug 28.

Assessing the Role of Trypsin in Quantitative Plasma and Single-Cell Proteomics toward Clinical Application.

Jakob Woessmann, Valdemaras Petrosius, Nil Üresin, David Kotol, Pedro Aragon-Fernandez, Andreas Hober, Ulrich Auf dem Keller, Fredrik Edfors, Erwin M Schoof.

Mass spectrometry-based bottom-up proteomics is rapidly evolving and routinely applied in large-scale biomedical studies. Proteases are a central component of every bottom-up proteomics experiment, digesting proteins into peptides. Trypsin has been the most widely applied protease in proteomics due to its characteristics. With ever-larger cohort sizes and possible future clinical application of mass spectrometry-based proteomics, the technical impact of trypsin becomes increasingly relevant. To assess possible biases introduced by trypsin digestion, we evaluated the impact of eight commercially available trypsins in a variety of bottom-up proteomics experiments and across a range of protease concentrations and storage times. To investigate the universal impact of these technical attributes, we included bulk HeLa cell lysate, human plasma, and single HEK293 cells, which were analyzed over a range of selected reaction monitoring (SRM), data-independent acquisition (DIA), and data-dependent acquisition (DDA) instrument methods on three LC-MS instruments. The quantification methods employed encompassed both label-free approaches and absolute quantification utilizing spike-in heavy-labeled recombinant protein fragment standards. Based on this extensive data set, we report variations between commercial trypsins, their source, and their concentration. Furthermore, we provide suggestions on the handling of trypsin in large-scale studies.

DOI: https://doi.org/10.1021/acs.analchem.3c02543
Onco Targets Ther. 2023 ;16 695-702

Spotlight on GOT2 in Cancer Metabolism.

Samuel A Kerk, Javier Garcia-Bermudez, Kivanc Birsoy, Mara H Sherman, Yatrik M Shah, Costas A Lyssiotis.

  GOT2 is at the nexus of several critical metabolic pathways in homeostatic cellular and dysregulated cancer metabolism. Despite this, recent work has emphasized the remarkable plasticity of cancer cells to employ compensatory pathways when GOT2 is inhibited. Here, we review the metabolic roles of GOT2, highlighting findings in both normal and cancer cells. We emphasize how cancer cells repurpose cell intrinsic metabolism and their flexibility when GOT2 is inhibited. We close by using this framework to discuss key considerations for future investigations into cancer metabolism.

Keywords:  mitochondria; nucleotides; pancreatic cancer; redox; transaminase; tumor microenvironment

DOI:  https://doi.org/10.2147/OTT.S382161
Clin Proteomics. 2023 Aug 26. 20(1): 32

Mass spectrometry-based proteomics as an emerging tool in clinical laboratories.

Alemayehu Godana Birhanu.

  Mass spectrometry (MS)-based proteomics have been increasingly implemented in various disciplines of laboratory medicine to identify and quantify biomolecules in a variety of biological specimens. MS-based proteomics is continuously expanding and widely applied in biomarker discovery for early detection, prognosis and markers for treatment response prediction and monitoring. Furthermore, making these advanced tests more accessible and affordable will have the greatest healthcare benefit.This review article highlights the new paradigms MS-based clinical proteomics has created in microbiology laboratories, cancer research and diagnosis of metabolic disorders. The technique is preferred over conventional methods in disease detection and therapy monitoring for its combined advantages in multiplexing capacity, remarkable analytical specificity and sensitivity and low turnaround time.Despite the achievements in the development and adoption of a number of MS-based clinical proteomics practices, more are expected to undergo transition from bench to bedside in the near future. The review provides insights from early trials and recent progresses (mainly covering literature from the NCBI database) in the application of proteomics in clinical laboratories.

Keywords:  Biomarker; Cancer; Clinical proteomics; Diagnosis; Mass spectrometry; Metabolic Disorders; Microbiology; Prognosis

DOI:  https://doi.org/10.1186/s12014-023-09424-x
Methods Mol Biol. 2023 ;2699 255-269

Clinical Proteomics: Liquid Chromatography-Mass Spectrometry (LC-MS) Purification Systems.

Michael Henry, Paula Meleady.

  Liquid chromatography/mass spectrometry (LC/MS) has become a routine powerful technology in clinical proteomic studies for protein identification, protein characterization, and the discovery of biomarkers. In this chapter, we describe two protocol methods to analyze clinical patient samples using a resin-based depletion column followed by either protein In-Gel enzymatic digestion or protein In-Solution enzymatic digestion using a simple kit-based approach (i.e., using the PreOmics iST sample preparation kit), followed by analysis using one-dimensional reverse-phase chromatography (RPC) or high pH reversed-phase peptide fractionation.

Keywords:  Clinical proteomics; High-resolution tandem mass spectrometry; Immunodepletion; Peptide separation; Protein digestion; Protein identification; Protein separation

DOI:  https://doi.org/10.1007/978-1-0716-3362-5_14
Anal Chem. 2023 Aug 30.

Investigating the Potential of Drift Tube Ion Mobility for the Analysis of Oxidized Lipids.

Katyeny Manuela da Silva, Michele Wölk, Palina Nepachalovich, Elias Iturrospe, Adrian Covaci, Alexander L N van Nuijs, Maria Fedorova.

Epilipids, a subset of the lipidome that comprises oxidized, nitrated, and halogenated lipid species, show important biochemical activity in the regulation of redox lipid metabolism by influencing cell fate decisions, including death, health, and aging. Due to the large chemical diversity, reversed-phase liquid chromatography-high-resolution mass spectrometry (RPLC-HRMS) methods have only a limited ability to separate numerous isobaric and isomeric epilipids. Ion mobility spectrometry (IMS) is a gas-phase separation technique that can be combined with LC-HRMS to improve the overall peak capacity of the analytical platform. Here, we illustrate the advantages and discuss the current limitations of implementing IMS in LC-HRMS workflows for the analysis of oxylipins and oxidized complex lipids. Using isomeric mixtures of oxylipins, we demonstrated that while deprotonated ions of eicosanoids were poorly resolved by IMS, sodium acetate and metal adducts (e.g., Li, Na, Ag, Ba, K) of structural isomers often showed ΔCCS% above 1.4% and base peak separation with high-resolution demultiplexing (HRDm). The knowledge of the IM migration order was also used as a proof of concept to help in the annotation of oxidized complex lipids using HRDm and all-ion fragmentation spectra. Additionally, we used a mixture of deuterium-labeled lipids for a routine system suitability test with the purpose of improving harmonization and interoperability of IMS data sets in (epi)lipidomics.

DOI: https://doi.org/10.1021/acs.analchem.3c02213
Cytokine Growth Factor Rev. 2023 Aug 19. pii: S1359-6101(23)00049-7. [Epub ahead of print]

Proteomics analysis of circulating small extracellular vesicles: Focus on the contribution of EVs to tumor metabolism.

Federica Anastasi, Asia Botto, Benoit Immordino, Elisa Giovannetti, Liam A McDonnell.

  The term small extracellular vesicle (sEV) is a comprehensive term that includes any type of cell-derived, membrane-delimited particle that has a diameter < 200 nm, and which includes exosomes and smaller microvesicles. sEVs transfer bioactive molecules between cells and are crucial for cellular homeostasis and particularly during tumor development, where sEVs provide important contributions to the formation of the premetastic niche and to their altered metabolism. sEVs are thus legitimate targets for intervention and have also gained increasing interest as an easily accessible source of biomarkers because they can be rapidly isolated from serum/plasma and their molecular cargo provides information on their cell-of origin. To target sEVs that are specific for a given cell/disease it is essential to identify EV surface proteins that are characteristic of that cell/disease. Mass-spectrometry based proteomics is widely used for the identification and quantification of sEV proteins. The methods used for isolating the sEVs, preparing the sEV sample for proteomics analysis, and mass spectrometry analysis, can have a strong influence on the results and requires careful consideration. This review provides an overview of the approaches used for sEV proteomics and discusses the inherent compromises regarding EV purity versus depth of coverage. Additionally, it discusses the practical applications of the methods to unravel the involvement of sEVs in regulating the metabolism of pancreatic ductal adenocarcinoma (PDAC). The metabolic reprogramming in PDAC includes enhanced glycolysis, elevated glutamine metabolism, alterations in lipid metabolism, mitochondrial dysfunction and hypoxia, all of which are crucial in promoting tumor cell growth. A thorough understanding of these metabolic adaptations is imperative for the development of targeted therapies to exploit PDAC's vulnerabilities.

Keywords:  Exosome; Extracellular vesicles; Metabolism; Pancreatic ductal adenocarcinoma; Proteomics

DOI:  https://doi.org/10.1016/j.cytogfr.2023.08.003
Proceedings (IEEE Int Conf Bioinformatics Biomed). 2022 Dec;2022 2342-2348

Deep Learning Based MS2 Feature Detection for Data-Independent Shotgun Proteomics.

Jonathan He, Olivia Liu, Xuan Guo.

  Accuracy of peptide identification in LC-MS analysis is crucial for information regarding the aspects of proteins that aid in biomarker discovery and the profiling of complex proteomes. The detection of peptide fragment ions in tandem mass spectrometry is still challenging given that current tools were not created or tested for the low-abundance, low-peak fragments of peptides found in MS2 data. Feature detection, a crucial pre-processing step in the LC-MS analysis pipeline that quantifies peptides by their mass-to-charge ratio, retention time, and intensity, is particularly challenging due to the overlapping nature of peptides and weak signals that are often indistinguishable from noises, thus creating a reliance on rigid mathematical structures and heuristics. In this study, we developed a deep-learning-based model with an innovative sliding window process that enables high-resolution processing of quantitative MS/MS data to conduct MS2 feature detection. Experimental results show that our model can produce more accurate values and identifications than existing feature detection tools, as well as a high rate of true positive features quantified. Therefore, we believe that our model illustrates the advantages of deep learning techniques applied towards computational proteomics.

Keywords:  MS2 feature detection; liquid chromatography mass spectrometry; machine learning; proteomics

DOI:  https://doi.org/10.1109/bibm55620.2022.9995258
Talanta. 2023 Aug 22. pii: S0039-9140(23)00825-1. [Epub ahead of print]266(Pt 2): 125074

Dual strategy for 13C-Metabolic flux analysis of central carbon and energy metabolism in Mammalian cells based on LC-isoMRM-MS.

Jie Zheng, Junjie Yang, Xu Liang, Mingliang Fang, Yulan Wang.

  Central carbon and energy metabolism are the most concerned metabolic pathways in 13C-Metabolic flux analysis (13C-MFA). However, some α-keto acids, ribonucleoside triphosphate (NTPs) and deoxyribonucleoside triphosphate (dNTPs) involved in central carbon and energy metabolism pathways were unstable or reactive, leading to inaccurate metabolic flux analysis. To achieve accurate 13C-MFA of central carbon and energy metabolism, we proposed a dual strategy for the detection of 101 metabolites in glucose metabolism pathways. N-Methylphenylethylamine (MPEA) was utilized for derivatization of 4 carboxyl (α-keto acids) and 8 phosphate metabolites (NTPs and dNTPs). After derivatization, the MPEA derivatives were investigated to be stable for 4 weeks under 4 °C and detected with high intensity in ∼104 cells. On the other hand, we analyzed an additional 89 metabolites in central carbon and energy metabolic pathways were directly analyzed by liquid chromatography tandem mass spectrometry (LC-MRM-MS). The limit of detection (LODs) of our method were as low as 0.05 ng/mL and the linear range was at least two orders of magnitude with determination coefficient (R2) > 0.9701. The relative standard divisions (RSDs) of intra- and inter-day of 95% metabolites were below 20%. In addition, the isotope list of 82 detected metabolites in central carbon and energy metabolism were generated according to isotopologues and isotopomers for each metabolite resulting from 13C incorporation. Accurate assessment of mass isotopomer distributions (MIDs) of intracellular 13C-labeled metabolites was achieved in [U-13C]-glucose cultured HepG2 cells by our dual strategy. Finally, we performed MID analysis of 101 metabolites in central carbon and energy metabolism. Overall, this dual method is reproducible and robust for application on 13C-MFA and has a great potential for studying clinical isotope labeled samples.

Keywords:  (13)C-metabolic flux analysis; Carboxyl and phosphate metabolites; Central carbon and energy metabolism; Derivatization; Liquid chromatography-mass spectrometry; Mass isotopomer distributions

DOI:  https://doi.org/10.1016/j.talanta.2023.125074
Mol Cell Proteomics. 2023 Aug 30. pii: S1535-9476(23)00150-0. [Epub ahead of print] 100639

A multipathway phosphopeptide standard for rapid phosphoproteomics assay development.

Brian C Searle, Allis Chien, Antonius Koller, David Hawke, Anthony W Herren, Jenny Kim, Kimberly A Lee, Ryan D Leib, Alissa J Nelson, Purvi Patel, Jian Min Ren, Paul M Stemmer, Yiying Zhu, Benjamin A Neely, Bhavin Patel.

  Recent advances in methodology have made phosphopeptide analysis a tractable problem for many proteomics researchers. There are now a wide variety of robust and accessible enrichment strategies to generate phosphoproteomes, while free or inexpensive software tools for quantitation and site localization have simplified phosphoproteome analysis workflow tremendously. As a research group under the Association for Biomolecular Resource Facilities (ABRF) umbrella, the Proteomics Standards Research Group (sPRG) has worked to develop a multipathway phosphopeptide standard based on a mixture of heavy-labeled phosphopeptides designed to enable researchers to rapidly develop assays. This mixture contains 131 mass spectrometry vetted phosphopeptides specifically chosen to cover as many known biologically interesting phosphosites as possible from seven different signaling networks: AMPK signaling, death and apoptosis signaling, ErbB signaling, insulin/IGF-1 signaling, mTOR signaling, PI3K/AKT signaling, and stress (p38/SAPK/JNK) signaling. Here we describe a characterization of this mixture spiked into a HeLa tryptic digest stimulated with both EGF and IGF-1 to activate the MAPK and PI3K/AKT/mTOR pathways. We further demonstrate a comparison of phosphoproteomic profiling of HeLa performed independently in five labs using this phosphopeptide mixture with data-independent acquisition. Despite different experimental and instrumentation processes, we found that labs could produce reproducible, harmonized datasets by reporting measurements as ratios to the standard, while intensity measurements showed lower consistency between labs even after normalization. Our results suggest that widely available, biologically-relevant phosphopeptide standards can act as a quantitative "yardstick" across laboratories and sample preparations, enabling experimental designs larger than a single laboratory can perform. Raw data files are publicly available in the MassIVE dataset MSV000090564.

Keywords:  data-independent acquisition; mass spectrometry; phosphopeptide; phosphorylation; proteomics; stable isotope label; targeted

DOI:  https://doi.org/10.1016/j.mcpro.2023.100639
Anal Chem. 2023 Aug 31.

Permethylation and Metal Adduction: A Toolbox for the Improved Characterization of Glycolipids with Cyclic Ion Mobility Separations Coupled to Mass Spectrometry.

Cameron N Naylor, Gabe Nagy.

Lipids are an important class of molecules involved in various biological functions but remain difficult to characterize through mass-spectrometry-based methods because of their many possible isomers. Glycolipids, specifically, play important roles in cell signaling but display an even greater level of isomeric heterogeneity as compared to other lipid classes stemming from the introduction of a carbohydrate and its corresponding linkage position and α/β anomericity at the headgroup. While liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) remains the gold standard technique in lipidomics, it is still unable to characterize all isomeric species, thus presenting the need for new, orthogonal, methodologies. Ion mobility spectrometry-mass spectrometry (IMS-MS) can provide an additional dimension of information that supplements LC-MS/MS workflows, but has seen little use for glycolipid analyses. Herein, we present an analytical toolbox that enables the characterization of various glycolipid isomer sets using high-resolution cyclic ion mobility separations coupled with mass spectrometry (cIMS-MS). Specifically, we utilized a combination of both permethylation and metal adduction to fully resolve isomeric sphingolipids and ceramides with our cIMS-MS platform. We also introduce a new metric that can enable comparing peak-to-peak resolution across varying cIMS-MS pathlengths. Overall, we envision that our presented methodologies are highly amenable to existing LC-MS/MS-based workflows and can also have broad utility toward other omics-based analyses.

DOI: https://doi.org/10.1021/acs.analchem.3c03448
Proteomics Clin Appl. 2023 Aug 31. e2300006

Design of experiments approach for systematic optimization of a single-shot diaPASEF plasma proteomics workflow applicable for high-throughput.

Shawn J Rice, Chandra P Belani.

   PURPOSE: Plasma is an abundant source of protein biomarkers. Mass spectrometry (MS) is an effective means to measure a large number of proteins in a single run. The recent development of data-independent acquisition with parallel accumulation and serial fragmentation (diaPASEF) on a trapped ion mobility spectrometer (TIMS) affords deep proteomic coverage with short liquid chromatography gradients. In this work, we utilized a process optimization approach, design of experiments (DoE), to maximize precursor identification for a plasma proteomic diaPASEF workflow.
EXPERIMENTAL DESIGN: A partial factorial design was used to screen 11 sample preparation factors and six diaPASEF MS acquisition factors. Selected factors were optimized using the response surface method.
RESULTS: Three important sample preparation factors and the two important MS acquisition factors were identified in the screening experiments and were selected for separate optimization experiments. The optimal parameters were compared to our standard plasma proteomics workflows using either a 1-h or overnight trypsin digestion. The optimized method outperformed the 1-h digestion, and it was similar in performance to the overnight digestion, however, the optimized method could be completed in a day.
CONCLUSION AND CLINICAL RELEVANCE: We have used DoE to report an optimized plasma proteomics workflow for diaPASEF, however, established methods are already highly optimized, and resources may be better spent on running samples than comprehensive optimization.

Keywords:  design of experiments; diaPASEF; ion mobility; plasma proteome

DOI:  https://doi.org/10.1002/prca.202300006
Clin Exp Med. 2023 Aug 28.

Lipid metabolic vulnerabilities of multiple myeloma.

Roberta Torcasio, Maria Eugenia Gallo Cantafio, Raissa Kaori Ikeda, Ludovica Ganino, Giuseppe Viglietto, Nicola Amodio.

  Multiple myeloma (MM) is the second most common hematological malignancy worldwide, characterized by abnormal proliferation of malignant plasma cells within a tumor-permissive bone marrow microenvironment. Metabolic dysfunctions are emerging as key determinants in the pathobiology of MM. In this review, we highlight the metabolic features of MM, showing how alterations in various lipid pathways, mainly involving fatty acids, cholesterol and sphingolipids, affect the growth, survival and drug responsiveness of MM cells, as well as their cross-talk with other cellular components of the tumor microenvironment. These findings will provide a new path to understanding the mechanisms underlying how lipid vulnerabilities may arise and affect the phenotype of malignant plasma cells, highlighting novel druggable pathways with a significant impact on the management of MM.

Keywords:  Cholesterol; Fatty acids; Lipid metabolism; Metabolic reprogramming; Multiple myeloma; Sphingolipids

DOI:  https://doi.org/10.1007/s10238-023-01174-2
Open Res Eur. 2023 ;3 59

Foresight in clinical proteomics: current status, ethical considerations, and future perspectives.

Filip Mundt, Nicolai J Wewer Albrechtsen, Sebastian Porsdam Mann, Peter Treit, Medini Ghodgaonkar-Steger, Martina O'Flaherty, Reinout Raijmakers, Juan Antonio Vizcaíno, Albert J R Heck, Matthias Mann.

  With the advent of robust and high-throughput mass spectrometric technologies and bioinformatics tools to analyze large data sets, proteomics has penetrated broadly into basic and translational life sciences research. More than 95% of FDA-approved drugs currently target proteins, and most diagnostic tests are protein-based. The introduction of proteomics to the clinic, for instance to guide patient stratification and treatment, is already ongoing. Importantly, ethical challenges come with this success, which must also be adequately addressed by the proteomics and medical communities. Consortium members of the H2020 European Union-funded proteomics initiative: European Proteomics Infrastructure Consortium-providing access (EPIC-XS) met at the Core Technologies for Life Sciences (CTLS) conference to discuss the emerging role and implementation of proteomics in the clinic. The discussion, involving leaders in the field, focused on the current status, related challenges, and future efforts required to make proteomics a more mainstream technology for translational and clinical research. Here we report on that discussion and provide an expert update concerning the feasibility of clinical proteomics, the ethical implications of generating and analyzing large-scale proteomics clinical data, and recommendations to ensure both ethical and effective implementation in real-world applications.

Keywords:  Clinical proteomics; clinical research; ethical challenges

DOI:  https://doi.org/10.12688/openreseurope.15810.1
J Am Soc Mass Spectrom. 2023 Sep 01.

Automated Sample Preparation Workflow for Tandem Mass Tag-Based Proteomics.

Dong-Gi Mun, Neha S Joshi, Rohit Budhraja, Gunveen S Sachdeva, Taewook Kang, Firdous A Bhat, Husheng Ding, Benjamin J Madden, Jun Zhong, Akhilesh Pandey.

Although tandem mass tag (TMT)-based isobaric labeling has become a powerful approach for multiplexed protein quantitation, automating the workflow for this technique has not been easy to achieve for widespread adoption. This is because preparation of TMT-labeled peptide samples involves multiple steps ranging from protein extraction, denaturation, reduction, and alkylation to tryptic digestion, desalting, labeling, and cleanup, all of which require a high level of proficiency. The variability resulting from multiple processing steps is inherently problematic, especially with large-scale clinical studies that involve hundreds of samples where reproducibility is critical for quantitation. Here, we sought to compare the performance of a recently introduced platform, AccelerOme, for an automated proteomic workflow employing TMT labeling with the manual processing of samples. Cell pellets were prepared and subjected to a 16-plex experiment using an automated platform and a conventional manual protocol. Single-shot liquid chromatography with tandem mass spectrometry analysis revealed a higher number of proteins and peptides identified using the automated platform. Efficiency of tryptic digestion, alkylation, and TMT labeling were similar in both manual and automated processes. In addition, comparison of quantitation accuracy and precision showed similar performance in an automated workflow compared to manual sample preparation by an expert. Overall, we demonstrated that the automated platform performs at a level similar to a manual process performed by an expert for TMT-based proteomics. We anticipate that this automated workflow will increasingly replace manual pipelines and has the potential to be applied to large-scale TMT-based studies, providing robust results and high sample throughput.

DOI: https://doi.org/10.1021/jasms.3c00095
Anal Chem. 2023 Sep 01.

Multitargeted Internal Calibration for the Quantification of Chronic Kidney Disease-Related Endogenous Metabolites Using Liquid Chromatography-Mass Spectrometry.

Gioele Visconti, Miguel de Figueiredo, Oriane Strassel, Julien Boccard, Nicolas Vuilleumier, David Jaques, Belén Ponte, Serge Rudaz.

Accurate quantitative analysis in liquid chromatography-mass spectrometry (LC-MS) benefits from calibration curves generated in the same matrix as the study sample. In the case of endogenous compound quantification, as no blank matrix exists, the multitargeted internal calibration (MTIC) is an attractive and straightforward approach to avoid the need for extensive matrix similarity evaluation. Its principle is to take advantage of stable isotope labeled (SIL) standards as internal calibrants to simultaneously quantify authentic analytes using a within sample calibration. An MTIC workflow was developed for the simultaneous quantification of metabolites related to chronic kidney disease (CKD) using a volumetric microsampling device to collect 20 μL of serum or plasma, followed by a single-step extraction with acetonitrile/water and liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. Since a single concentration of internal calibrant is necessary to calculate the study sample concentration, the instrument response function was investigated to determine the best SIL concentration. After validation, the trueness of 16 endogenous analytes in authentic human serum ranged from 72.2 to 116.0%, the repeatability from 1.9 to 11.3%, and the intermediate precision ranged overall from 2.1 to 15.4%. The proposed approach was applied to plasma samples collected from healthy control participants and two patient groups diagnosed with CKD. Results confirmed substantial concentration differences between groups for several analytes, including indoxyl sulfate and cortisone, as well as metabolite enrichment in the kynurenine and indole pathways. Multitargeted methodologies represent a major step toward rapid and straightforward LC-MS/MS absolute quantification of endogenous biomarkers, which could change the paradigm of MS use in clinical laboratories.

DOI: https://doi.org/10.1021/acs.analchem.3c02069
J Chromatogr B Analyt Technol Biomed Life Sci. 2023 Aug 12. pii: S1570-0232(23)00259-3. [Epub ahead of print]1228 123849

Scout triggered multiple reaction monitoring mass spectrometry for the rapid transfer of large multiplexed targeted methods in metabolomics.

Thomas Alexandre Brunet, Sophie Ayciriex, Delphine Arquier, Jérôme Lemoine, Jérôme Randon, Arnaud Salvador.

  The field of metabolomics based on mass spectrometry has grown considerably in recent years due to the need to detect and, above all, quantify a very large number of metabolites, simultaneously. Up to now, targeted multiplexed analysis on complex samples by Liquid Chromatography coupled with tandem Mass Spectrometry (LC-MS/MS) has relied almost exclusively on compound detection based on absolute retention times, as in the Scheduled-MRM (sMRM) approach. Those methods turn out to be poorly transferable from one instrument to another and result in a time-consuming and tedious method development involving a significant number of critical parameters that need specific re-optimisation. To address this challenge, we introduce a novel acquisition mode called scout-triggered MRM (stMRM). In stMRM, a marker transition is used to trigger MS analysis for a group of dependent target analytes. These marker transitions are strategically distributed throughout the chromatographic run, and the dependent analytes are associated based on their retention times. The result is a targeted assay that remains robust even in the presence of retention time shifts. A 3 to 5-fold increase in the number of detected transitions associated to plasma metabolites was obtained when transferring from a direct application of a published sMRM to a stMRM method. This significant improvement highlights the universal applicability of the stMRM method, as it can be implemented on any LC system without the need for extensive method development. We subsequently illustrate the robustness of stMRM in modified chromatographic elution conditions. Despite a large change in metabolite's selectivity, the multiplexed assay successfully recovered 70% of the monitored transitions when consequently modifying the gradient method. These findings demonstrate the versatility and adaptability of stMRM, opening new avenues for the development of highly multiplexed LC-MS/MS methods in metabolomics. These methods are characterized by their analytical transparency and straightforward implementation using existing literature data.

Keywords:  LC-MS/MS; Liquid chromatography; Method transfer; Multiple Reaction Monitoring; Targeted metabolomics; scout-triggered MRM

DOI:  https://doi.org/10.1016/j.jchromb.2023.123849
Cell Rep. 2023 Aug 30. pii: S2211-1247(23)01045-8. [Epub ahead of print]42(9): 113034

Formate promotes invasion and metastasis in reliance on lipid metabolism.

Catherine Delbrouck, Nicole Kiweler, Oleg Chen, Vitaly I Pozdeev, Lara Haase, Laura Neises, Anaïs Oudin, Aymeric Fouquier d'Hérouël, Ruolin Shen, Lisa Schlicker, Rashi Halder, Antoine Lesur, Anne Schuster, Nadja I Lorenz, Christian Jaeger, Maureen Feucherolles, Gilles Frache, Martyna Szpakowska, Andy Chevigne, Michael W Ronellenfitsch, Etienne Moussay, Marie Piraud, Alexander Skupin, Almut Schulze, Simone P Niclou, Elisabeth Letellier, Johannes Meiser.

  Metabolic rewiring is essential for cancer onset and progression. We previously showed that one-carbon metabolism-dependent formate production often exceeds the anabolic demand of cancer cells, resulting in formate overflow. Furthermore, we showed that increased extracellular formate concentrations promote the in vitro invasiveness of glioblastoma cells. Here, we substantiate these initial observations with ex vivo and in vivo experiments. We also show that exposure to exogeneous formate can prime cancer cells toward a pro-invasive phenotype leading to increased metastasis formation in vivo. Our results suggest that the increased local formate concentration within the tumor microenvironment can be one factor to promote metastases. Additionally, we describe a mechanistic interplay between formate-dependent increased invasiveness and adaptations of lipid metabolism and matrix metalloproteinase activity. Our findings consolidate the role of formate as pro-invasive metabolite and warrant further research to better understand the interplay between formate and lipid metabolism.

Keywords:  CP: Cancer; CP: Metabolism; cancer metastasis; formate overflow; invasion; one-carbon metabolism

DOI:  https://doi.org/10.1016/j.celrep.2023.113034
Geroscience. 2023 Aug 26.

Serum methylmalonic acid concentrations at breast cancer diagnosis significantly correlate with clinical frailty.

Qi Wu, Sigrid Hatse, Cindy Kenis, Juan Fernández-García, Patricia Altea-Manzano, Jaak Billen, Mélanie Planque, Anke Vandekeere, Yentl Lambrechts, François Richard, Kevin Punie, Patrick Neven, Ann Smeets, Ines Nevelsteen, Giuseppe Floris, Christine Desmedt, Ana P Gomes, Sarah-Maria Fendt, Hans Wildiers.

  Methylmalonic acid (MMA), a by-product of propionate metabolism, is known to increase with age. This study investigates the potential of serum MMA concentrations as a biomarker for age-related clinical frailty in older patients with breast cancer. One hundred nineteen patients ≥ 70 years old with early-stage breast cancer were included (median age 76 years). G8 screening, full geriatric assessment, clinical parameters (i.e., estimated glomerular filtration rate (eGFR) and body mass index (BMI)), and serum sample collection were collected at breast cancer diagnosis before any therapy was administered. MMA concentrations were measured via liquid chromatography with tandem mass spectrometry. MMA concentrations significantly increased with age and eGFR (all P < 0.001) in this older population. The group with an abnormal G8 (≤ 14, 51% of patients) had significantly higher MMA levels than the group with normal G8 (> 14, 49%): 260 nmol/L vs. 188 nmol/L, respectively (P = 0.0004), even after correcting for age and eGFR (P = 0.001). Furthermore, in the detailed assessment, MMA concentrations correlated most with mobility (Eastern Cooperative Oncology Group (ECOG) Performance Status and Activities of Daily Living (ADL) tools, all P ≤ 0.02), comorbidity (Charlson Comorbidity Index (CCI) tool, P = 0.005), and polypharmacy (P < 0.001), whereas no significant associations were noted for instrumental ADL (IADL), Mini-Mental State Examination (MMSE), Geriatric Depression Scale-15 (GDS15), Mini Nutritional Assessment-Short Form (MNA-SF), and pain (all P > 0.1). In addition, our results showed that higher MMA levels correlate with poor overall survival in breast cancer patients (P = 0.003). Elevated serum MMA concentrations at initial diagnosis are significantly associated, not only with age but also independently with clinical frailty, suggesting a possible influence of MMA on clinical frailty in older patients with early-stage breast cancer.

Keywords:  Breast cancer; Clinical frailty; Methylmalonic acid; Mobility

DOI:  https://doi.org/10.1007/s11357-023-00908-0