bims-mascan 2024-02-11 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2024–02–11
23 papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz

Lipidome isotope labelling of gut microbes (LILGM): A method of discovering endogenous microbial lipids.
Integrative open workflow for confident annotation and molecular networking of metabolomics MSE/DIA data.
Stable-Isotope N-Me Aziridination Enables Accurate Quantitative C═C Isomeric Lipidomics.
O-Glycoproteomics Sample Preparation and Analysis Using NanoHPLC and Tandem MS.
Sample preparation for fatty acid analysis in biological samples with mass spectrometry-based strategies.
microbeMASST: a taxonomically informed mass spectrometry search tool for microbial metabolomics data.
Metabolic Signature of Warburg Effect in Cancer: An Effective and Obligatory Interplay between Nutrient Transporters and Catabolic/Anabolic Pathways to Promote Tumor Growth.
Targeted Glycoproteomics Analysis Using MRM/PRM Approaches.
Automated single-cell proteomics providing sufficient proteome depth to study complex biology beyond cell type classifications.
MRMPro: a web-based tool to improve the speed of manual calibration for multiple reaction monitoring data analysis by mass spectrometry.
Biomarker Identification in Liver Cancers Using Desorption Electrospray Ionization Mass Spectrometry (DESI-MS) Imaging: An Approach for Spatially Resolved Metabolomics.
Lipid droplets provide metabolic flexibility for cancer progression.
A quantitative and site-specific atlas of the citrullinome reveals widespread existence of citrullination and insights into PADI4 substrates.
Kinetic Modeling of Hepatic Metabolism and Simulation of Treatment Effects.
Targeted Analysis of Permethylated N-Glycans Using MRM/PRM Approaches.
Small-Scale Serial Size Exclusion Chromatography (s3SEC) for High Sensitivity Top-Down Proteomics of Large Proteoforms.
AutonoMS: Automated Ion Mobility Metabolomic Fingerprinting.
High-Throughput Extracellular Matrix Proteomics of Human Lungs Enabled by Photocleavable Surfactant and diaPASEF.
Single-Cell Unsaturated Lipid Profiling for Studying Chemoresistance Heterogeneity of Triple-Negative Breast Cancer Cells.
Analysis of Native and Permethylated N-Glycan Isomers Using MGC-LC-MS Techniques.
A Simplified Label-Free Method for Proteotyping Sets of Six Isolates in a Single Liquid Chromatography-High-Resolution Tandem Mass Spectrometry Analysis.
Mass spectrometry imaging methods for visualizing tumor heterogeneity.
Methionine Alkylation as an Approach to Quantify Methionine Oxidation Using Mass Spectrometry.

Talanta. 2024 Feb 01. pii: S0039-9140(24)00109-7. [Epub ahead of print]271 125730

Lipidome isotope labelling of gut microbes (LILGM): A method of discovering endogenous microbial lipids.

Li Chen, Rui Xu, Jiangjiang Zhu.

  Lipidomics analysis of gut microbiome has become critical in recent surge of extensive human disease studies that investigate microbiome contributions. However, challenges remain in comprehending the origins of thousands of lipid species produced by the diverse microbes. Here, we proposed the development and utilization of a liquid chromatography-mass spectrometry-based approach, named lipidome isotope labelling of gut microbes (LILGM), which enables confident detection and identification of endogenous gut microbial lipidome via 13C/15N labeling strategy and high-resolution mass spectrometry. Our method leveraged in vitro microbial cultures and stable isotope-labeled 13C and 15N, allowing a reasonable degree of isotope incorporation into microbial lipids over short-term of inoculation. We then systematically detected the mass spectral patterns of 182 labeled lipid species by our in-house data analysis pipeline. Further bioinformatics analyses confidently identified biologically relevant microbial lipids from lipid classes such as diacylglycerols (DGs), fatty acids (FAs), phosphatidylglycerols (PGs), and phosphatidylethanolamines (PEs) that may have profound impacts to human physiology. Our study also demonstrated the application of LILGM by showcasing the confident detection of dysregulated microbial lipids post antibiotic perturbation. The debiased sparse partial correlation analysis provides insights into lipid metabolism intricacies. Overall, our method can provide unambiguous analyses to the endogenous microbial lipids in given biological context, and can also instantly reflect the lipidomic changes of gut microbes in response to environmental factors. We believe our LILGM approach has the potential to provide new body of knowledge by combining promising analytical approaches for sensitive and specific lipid detection to support functional microbiome studies.

Keywords:  Anaerobic microbes; Endogenous metabolites; Isotope labeling; Lipidomics; Metabolism

DOI:  https://doi.org/10.1016/j.talanta.2024.125730
Brief Bioinform. 2024 Jan 22. pii: bbae013. [Epub ahead of print]25(2):

Integrative open workflow for confident annotation and molecular networking of metabolomics MSE/DIA data.

Albert Katchborian-Neto, Matheus F Alves, Paula C P Bueno, Karen de Jesus Nicácio, Miller S Ferreira, Tiago B Oliveira, Henrique Barbosa, Michael Murgu, Ana C C de Paula Ladvocat, Danielle F Dias, Marisi G Soares, João H G Lago, Daniela A Chagas-Paula.

  Liquid chromatography coupled with high-resolution mass spectrometry data-independent acquisition (LC-HRMS/DIA), including MSE, enable comprehensive metabolomics analyses though they pose challenges for data processing with automatic annotation and molecular networking (MN) implementation. This motivated the present proposal, in which we introduce DIA-IntOpenStream, a new integrated workflow combining open-source software to streamline MSE data handling. It provides 'in-house' custom database construction, allows the conversion of raw MSE data to a universal format (.mzML) and leverages open software (MZmine 3 and MS-DIAL) all advantages for confident annotation and effective MN data interpretation. This pipeline significantly enhances the accessibility, reliability and reproducibility of complex MSE/DIA studies, overcoming previous limitations of proprietary software and non-universal MS data formats that restricted integrative analysis. We demonstrate the utility of DIA-IntOpenStream with two independent datasets: dataset 1 consists of new data from 60 plant extracts from the Ocotea genus; dataset 2 is a publicly available actinobacterial extract spiked with authentic standard for detailed comparative analysis with existing methods. This user-friendly pipeline enables broader adoption of cutting-edge MS tools and provides value to the scientific community. Overall, it holds promise for speeding up metabolite discoveries toward a more collaborative and open environment for research.

Keywords:  Ocotea; chemical annotation; data-independent acquisition; mass spectrometry; open software

DOI:  https://doi.org/10.1093/bib/bbae013
Anal Chem. 2024 Feb 03.

Stable-Isotope N-Me Aziridination Enables Accurate Quantitative C═C Isomeric Lipidomics.

Guifang Feng, Ming Gao, Hongyu Chen, Zhourui Zhang, Jiayi Chen, Yongjia Tong, Pengfei Wu, Rongrong Fu, Yun Lin, Suming Chen.

Accurate lipid quantification is essential to revealing their roles in physiological and pathological processes. However, difficulties in the structural resolution of lipid isomers hinder their further accurate quantification. To address this challenge, we developed a novel stable-isotope N-Me aziridination strategy that enables simultaneous qualification and quantification of unsaturated lipid isomers. The one-step introduction of the 1-methylaziridine structure not only serves as an activating group for the C═C bond to facilitate positional identification but also as an isotopic inserter to achieve accurate relative quantification. The high performance of this reaction for the identification of unsaturated lipids was verified by large-scale resolution of the C═C positions of 468 lipids in serum. More importantly, by using this bifunctional duplex labeling method, various unsaturated lipids such as fatty acids, phospholipids, glycerides, and cholesterol ester were accurately and individually quantified at the C═C bond isomeric level during the mouse brain ischemia. This study provides a new approach to quantitative structural lipidomics.

DOI: https://doi.org/10.1021/acs.analchem.3c04824
Methods Mol Biol. 2024 ;2762 281-290

O-Glycoproteomics Sample Preparation and Analysis Using NanoHPLC and Tandem MS.

Junyao Wang, Sherifdeen Onigbinde, Waziha Purba, Judith Nwaiwu, Yehia Mechref.

  Glycosylation refers to the biological processes that covalently attach carbohydrates to the peptide backbone after the synthesis of proteins. As one of the most common post-translational modifications (PTMs), glycosylation can greatly affect proteins' features and functions. Moreover, aberrant glycosylation has been linked to various diseases. There are two major types of glycosylation, known as N-linked and O-linked glycosylation. Here, we focus on O-linked glycosylation and thoroughly describe a bottom-up strategy to perform O-linked glycoproteomics studies. The experimental section involves enzymatic digestions using trypsin and O-glycoprotease at 37 °C. The prepared samples containing O-glycopeptides are analyzed using nanoHPLC coupled with tandem mass spectrometry (MS) for accurate identification and quantification.

Keywords:  Glycosylation; O-Glycoprotease; O-Linked Glycopeptide; RPLC; Tandem MS

DOI:  https://doi.org/10.1007/978-1-0716-3666-4_17
Anal Bioanal Chem. 2024 Feb 06.

Sample preparation for fatty acid analysis in biological samples with mass spectrometry-based strategies.

Li Yang, Jie Yuan, Bolin Yu, Shuang Hu, Yu Bai.

  Fatty acids (FAs) have attracted many interests for their pivotal roles in many biological processes. Imbalance of FAs is related to a variety of diseases, which makes the measurement of them important in biological samples. Over the past two decades, mass spectrometry (MS) has become an indispensable technique for the analysis of FAs owing to its high sensitivity and precision. Due to complex matrix effect of biological samples and inherent poor ionization efficiency of FAs in MS, sample preparation including extraction and chemical derivatization prior to analysis are often employed. Here, we describe an updated overview of FA extraction techniques, as well as representative derivatization methods utilized in different MS platforms including gas chromatography-MS, liquid chromatography-MS, and mass spectrometry imaging based on different chain lengths of FAs. Derivatization strategies for the identification of double bond location in unsaturated FAs are also summarized and highlighted. The advantages, disadvantages, and prospects of these methods are compared and discussed. This review provides the development and valuable information for sample pretreatment approaches and qualitative and quantitative analysis of interested FAs using different MS-based platforms in complex biological matrices. Finally, the challenges of FA analysis are summarized and the future perspectives are prospected.

Keywords:  Derivatization; Extraction; Fatty acids; Mass spectrometry

DOI:  https://doi.org/10.1007/s00216-024-05185-0
Nat Microbiol. 2024 Feb;9(2): 336-345

microbeMASST: a taxonomically informed mass spectrometry search tool for microbial metabolomics data.

Simone Zuffa, Robin Schmid, Anelize Bauermeister, Paulo Wender P Gomes, Andres M Caraballo-Rodriguez, Yasin El Abiead, Allegra T Aron, Emily C Gentry, Jasmine Zemlin, Michael J Meehan, Nicole E Avalon, Robert H Cichewicz, Ekaterina Buzun, Marvic Carrillo Terrazas, Chia-Yun Hsu, Renee Oles, Adriana Vasquez Ayala, Jiaqi Zhao, Hiutung Chu, Mirte C M Kuijpers, Sara L Jackrel, Fidele Tugizimana, Lerato Pertunia Nephali, Ian A Dubery, Ntakadzeni Edwin Madala, Eduarda Antunes Moreira, Leticia Veras Costa-Lotufo, Norberto Peporine Lopes, Paula Rezende-Teixeira, Paula C Jimenez, Bipin Rimal, Andrew D Patterson, Matthew F Traxler, Rita de Cassia Pessotti, Daniel Alvarado-Villalobos, Giselle Tamayo-Castillo, Priscila Chaverri, Efrain Escudero-Leyva, Luis-Manuel Quiros-Guerrero, Alexandre Jean Bory, Juliette Joubert, Adriano Rutz, Jean-Luc Wolfender, Pierre-Marie Allard, Andreas Sichert, Sammy Pontrelli, Benjamin S Pullman, Nuno Bandeira, William H Gerwick, Katia Gindro, Josep Massana-Codina, Berenike C Wagner, Karl Forchhammer, Daniel Petras, Nicole Aiosa, Neha Garg, Manuel Liebeke, Patric Bourceau, Kyo Bin Kang, Henna Gadhavi, Luiz Pedro Sorio de Carvalho, Mariana Silva Dos Santos, Alicia Isabel Pérez-Lorente, Carlos Molina-Santiago, Diego Romero, Raimo Franke, Mark Brönstrup, Arturo Vera Ponce de León, Phillip Byron Pope, Sabina Leanti La Rosa, Giorgia La Barbera, Henrik M Roager, Martin Frederik Laursen, Fabian Hammerle, Bianka Siewert, Ursula Peintner, Cuauhtemoc Licona-Cassani, Lorena Rodriguez-Orduña, Evelyn Rampler, Felina Hildebrand, Gunda Koellensperger, Harald Schoeny, Katharina Hohenwallner, Lisa Panzenboeck, Rachel Gregor, Ellis Charles O'Neill, Eve Tallulah Roxborough, Jane Odoi, Nicole J Bale, Su Ding, Jaap S Sinninghe Damsté, Xue Li Guan, Jerry J Cui, Kou-San Ju, Denise Brentan Silva, Fernanda Motta Ribeiro Silva, Gilvan Ferreira da Silva, Hector H F Koolen, Carlismari Grundmann, Jason A Clement, Hosein Mohimani, Kirk Broders, Kerry L McPhail, Sidnee E Ober-Singleton, Christopher M Rath, Daniel McDonald, Rob Knight, Mingxun Wang, Pieter C Dorrestein.

microbeMASST, a taxonomically informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbe-derived metabolites and relative producers without a priori knowledge will vastly enhance the understanding of microorganisms' role in ecology and human health.

DOI: https://doi.org/10.1038/s41564-023-01575-9
Cancers (Basel). 2024 Jan 24. pii: 504. [Epub ahead of print]16(3):

Metabolic Signature of Warburg Effect in Cancer: An Effective and Obligatory Interplay between Nutrient Transporters and Catabolic/Anabolic Pathways to Promote Tumor Growth.

Marilyn Mathew, Nhi T Nguyen, Yangzom D Bhutia, Sathish Sivaprakasam, Vadivel Ganapathy.

  Aerobic glycolysis in cancer cells, originally observed by Warburg 100 years ago, which involves the production of lactate as the end product of glucose breakdown even in the presence of adequate oxygen, is the foundation for the current interest in the cancer-cell-specific reprograming of metabolic pathways. The renewed interest in cancer cell metabolism has now gone well beyond the original Warburg effect related to glycolysis to other metabolic pathways that include amino acid metabolism, one-carbon metabolism, the pentose phosphate pathway, nucleotide synthesis, antioxidant machinery, etc. Since glucose and amino acids constitute the primary nutrients that fuel the altered metabolic pathways in cancer cells, the transporters that mediate the transfer of these nutrients and their metabolites not only across the plasma membrane but also across the mitochondrial and lysosomal membranes have become an integral component of the expansion of the Warburg effect. In this review, we focus on the interplay between these transporters and metabolic pathways that facilitates metabolic reprogramming, which has become a hallmark of cancer cells. The beneficial outcome of this recent understanding of the unique metabolic signature surrounding the Warburg effect is the identification of novel drug targets for the development of a new generation of therapeutics to treat cancer.

Keywords:  aerobic glycolysis; glutamine addiction; glutaminolysis; lactate receptors; nutrient transporters; oncogenes; oncometabolites; one-carbon metabolism; reductive carboxylation; tumor microenvironment

DOI:  https://doi.org/10.3390/cancers16030504
Methods Mol Biol. 2024 ;2762 231-250

Targeted Glycoproteomics Analysis Using MRM/PRM Approaches.

Cristian D Gutierrez Reyes, Akeem Sanni, Moyinoluwa Adeniyi, Damir Mogut, Hector R Najera Gonzalez, Parisa Ahmadi, Mojgan Atashi, Sherifdeen Onigbinde, Yehia Mechref.

  MS-target analyses are frequently utilized to analyze and validate structural changes of biomolecules across diverse fields of study such as proteomics, glycoproteomics, glycomics, lipidomics, and metabolomics. Targeted studies are commonly conducted using multiple reaction monitoring (MRM) and parallel reaction monitoring (PRM) techniques. A reliable glycoproteomics analysis in intricate biological matrices is possible with these techniques, which streamline the analytical workflow, lower background interference, and enhance selectivity and specificity.

Keywords:  Glycopeptides; MRM; PRM

DOI:  https://doi.org/10.1007/978-1-0716-3666-4_14
bioRxiv. 2024 Jan 22. pii: 2024.01.20.576369. [Epub ahead of print]

Automated single-cell proteomics providing sufficient proteome depth to study complex biology beyond cell type classifications.

Claudia Ctortecka, Natalie M Clark, Brian Boyle, Anjali Seth, D R Mani, Namrata D Udeshi, Steven A Carr.

Mass spectrometry (MS)-based single-cell proteomics (SCP) has gained massive attention as a viable complement to other single cell approaches. The rapid technological and computational advances in the field have pushed the boundaries of sensitivity and throughput. However, reproducible quantification of thousands of proteins within a single cell at reasonable proteome depth to characterize biological phenomena remains a challenge. To address some of those limitations we present a combination of fully automated single cell sample preparation utilizing a dedicated chip within the picolitre dispensing robot, the cellenONE. The proteoCHIP EVO 96 can be directly interfaced with the Evosep One chromatographic system for in-line desalting and highly reproducible separation with a throughput of 80 samples per day. This, in combination with the Bruker timsTOF MS instruments, demonstrates double the identifications without manual sample handling. Moreover, relative to standard high-performance liquid chromatography, the Evosep One separation provides further 2-fold improvement in protein identifications. The implementation of the newest generation timsTOF Ultra with our proteoCHIP EVO 96-based sample preparation workflow reproducibly identifies up to 4,000 proteins per single HEK-293T without a carrier or match-between runs. Our current SCP depth spans over 4 orders of magnitude and identifies over 50 biologically relevant ubiquitin ligases. We complement our highly reproducible single-cell proteomics workflow to profile hundreds of lipopolysaccharide (LPS)-perturbed THP-1 cells and identified key regulatory proteins involved in interleukin and interferon signaling. This study demonstrates that the proteoCHIP EVO 96-based SCP sample preparation with the timsTOF Ultra provides sufficient proteome depth to study complex biology beyond cell-type classifications.

DOI: https://doi.org/10.1101/2024.01.20.576369
BMC Bioinformatics. 2024 Feb 06. 25(1): 60

MRMPro: a web-based tool to improve the speed of manual calibration for multiple reaction monitoring data analysis by mass spectrometry.

Ruimin Wang, Hengxuan Jiang, Miaoshan Lu, Junjie Tong, Shaowei An, Jinyin Wang, Changbin Yu.

   BACKGROUND: As a gold-standard quantitative technique based on mass spectrometry, multiple reaction monitoring (MRM) has been widely used in proteomics and metabolomics. In the analysis of MRM data, as no peak picking algorithm can achieve perfect accuracy, manual inspection is necessary to correct the errors. In large cohort analysis scenarios, the time required for manual inspection is often considerable. Apart from the commercial software that comes with mass spectrometers, the open-source and free software Skyline is the most popular software for quantitative omics. However, this software is not optimized for manual inspection of hundreds of samples, the interactive experience also needs to be improved.
RESULTS: Here we introduce MRMPro, a web-based MRM data analysis platform for efficient manual inspection. MRMPro supports data analysis of MRM and schedule MRM data acquired by mass spectrometers of mainstream vendors. With the goal of improving the speed of manual inspection, we implemented a collaborative review system based on cloud architecture, allowing multiple users to review through browsers. To reduce bandwidth usage and improve data retrieval speed, we proposed a MRM data compression algorithm, which reduced data volume by more than 60% and 80% respectively compared to vendor and mzML format. To improve the efficiency of manual inspection, we proposed a retention time drift estimation algorithm based on similarity of chromatograms. The estimated retention time drifts were then used for peak alignment and automatic EIC grouping. Compared with Skyline, MRMPro has higher quantification accuracy and better manual inspection support.
CONCLUSIONS: In this study, we proposed MRMPro to improve the usability of manual calibration for MRM data analysis. MRMPro is free for non-commercial use. Researchers can access MRMPro through http://mrmpro.csibio.com/ . All major mass spectrometry formats (wiff, raw, mzML, etc.) can be analyzed on the platform. The final identification results can be exported to a common.xlsx format for subsequent analysis.

Keywords:  Batch inspection; MRM; MRMPro; Mass spectrometry; Web service

DOI:  https://doi.org/10.1186/s12859-024-05685-x
Methods Mol Biol. 2024 ;2769 199-209

Biomarker Identification in Liver Cancers Using Desorption Electrospray Ionization Mass Spectrometry (DESI-MS) Imaging: An Approach for Spatially Resolved Metabolomics.

Hui Chen, Sylvère Durand, Olivia Bawa, Mélanie Bourgin, Léa Montégut, Flavia Lambertucci, Omar Motiño, Sijing Li, Uxía Nogueira-Recalde, Gerasimos Anagnostopoulos, Maria Chiara Maiuri, Guido Kroemer, Isabelle Martins.

  Liver cancers are characterized by interindividual and intratumoral heterogeneity, which makes early diagnosis and the development of therapies challenging. Desorption electrospray ionization mass spectrometry (DESI-MS) imaging is a potent and sensitive MS ionization technique for direct, unaltered 2D and 3D imaging of metabolites in complex biological samples. Indeed, DESI gently desorbs and ionizes analyte molecules from the sample surface using an electrospray source of highly charged aqueous spray droplets in ambient conditions. DESI-MS imaging of biological samples allows untargeted analysis and characterization of metabolites in liver cancers to identify new biomarkers of malignancy. In this chapter, we described a detailed protocol using liver cancer samples collected and stored for histopathology examination, either as frozen or as formalin-fixed, paraffin-embedded specimens. Such hepatocellular carcinoma samples can be subjected to DESI-MS analyses, illustrating the capacity of spatially resolved metabolomics to distinguish malignant lesions from adjacent normal liver tissue.

Keywords:  Cancer; DESI-MS; spatial metabolomics; Liver

DOI:  https://doi.org/10.1007/978-1-0716-3694-7_15
FEBS Lett. 2024 Feb 07.

Lipid droplets provide metabolic flexibility for cancer progression.

Rémi Safi, Pablo Menéndez, Albert Pol.

  A hallmark of cancer cells is their remarkable ability to efficiently adapt to favorable and hostile environments. Due to a unique metabolic flexibility, tumor cells can grow even in the absence of extracellular nutrients or in stressful scenarios. To achieve this, cancer cells need large amounts of lipids to build membranes, synthesize lipid-derived molecules, and generate metabolic energy in the absence of other nutrients. Tumor cells potentiate strategies to obtain lipids from other cells, metabolic pathways to synthesize new lipids, and mechanisms for efficient storage, mobilization, and utilization of these lipids. Lipid droplets (LDs) are the organelles that collect and supply lipids in eukaryotes and it is increasingly recognized that the accumulation of LDs is a new hallmark of cancer cells. Furthermore, an active role of LD proteins in processes underlying tumorigenesis has been proposed. Here, by focusing on three major classes of LD-resident proteins (perilipins, lipases, and acyl-CoA synthetases), we provide an overview of the contribution of LDs to cancer progression and discuss the role of LD proteins during the proliferation, invasion, metastasis, apoptosis, and stemness of cancer cells.

Keywords:  cancer; invasion; lipid droplets; lipids; metastasis; tumorigenesis

DOI:  https://doi.org/10.1002/1873-3468.14820
Nat Struct Mol Biol. 2024 Feb 06.

A quantitative and site-specific atlas of the citrullinome reveals widespread existence of citrullination and insights into PADI4 substrates.

Alexandra S Rebak, Ivo A Hendriks, Jonas D Elsborg, Sara C Buch-Larsen, Claus H Nielsen, Lene Terslev, Rebecca Kirsch, Dres Damgaard, Nadezhda T Doncheva, Caroline Lennartsson, Martin Rykær, Lars J Jensen, Maria A Christophorou, Michael L Nielsen.

Despite the importance of citrullination in physiology and disease, global identification of citrullinated proteins, and the precise targeted sites, has remained challenging. Here we employed quantitative-mass-spectrometry-based proteomics to generate a comprehensive atlas of citrullination sites within the HL60 leukemia cell line following differentiation into neutrophil-like cells. We identified 14,056 citrullination sites within 4,008 proteins and quantified their regulation upon inhibition of the citrullinating enzyme PADI4. With this resource, we provide quantitative and site-specific information on thousands of PADI4 substrates, including signature histone marks and transcriptional regulators. Additionally, using peptide microarrays, we demonstrate the potential clinical relevance of certain identified sites, through distinct reactivities of antibodies contained in synovial fluid from anti-CCP-positive and anti-CCP-negative people with rheumatoid arthritis. Collectively, we describe the human citrullinome at a systems-wide level, provide a resource for understanding citrullination at the mechanistic level and link the identified targeted sites to rheumatoid arthritis.

DOI: https://doi.org/10.1038/s41594-024-01214-9
Methods Mol Biol. 2024 ;2769 211-225

Kinetic Modeling of Hepatic Metabolism and Simulation of Treatment Effects.

Antje Egners, Thorsten Cramer, Iwona Wallach, Nikolaus Berndt.

  Mathematical modeling is a promising strategy to fill the experimentally unapproachable knowledge gaps about the relative contribution of various molecular processes to cellular metabolic function. To this end, we developed detailed kinetic models of the central metabolism of different cell types, comprising multiple metabolic functionalities. We used the model to simulate metabolic changes in several cell types under different experimental settings in health and disease. In this way, we show that it is possible to decipher and characterize the relative influence of various metabolic pathways and enzymes to overall metabolic performance and phenotype.Quantitative Systems Metabolism (QSM™) allows quantitative assessment of metabolic functionality and metabolic profiling based on proteomic data. Here, we describe the technique, namely, molecular resolved kinetic modeling, underlying QSM™. We explain the necessary steps for the generation of cell-specific models to functionally interpret proteomic data and point out some unresolved challenges and open questions.

Keywords:  Kinetic modeling; Liver; Metabolism; Quantitative proteomics

DOI:  https://doi.org/10.1007/978-1-0716-3694-7_16
Methods Mol Biol. 2024 ;2762 251-266

Targeted Analysis of Permethylated N-Glycans Using MRM/PRM Approaches.

Cristian D Gutierrez Reyes, Akeem Sanni, Damir Mogut, Moyinoluwa Adeniyi, Parisa Ahmadi, Mojgan Atashi, Sherifdeen Onigbinde, Yehia Mechref.

  Targeted mass spectrometric analysis is widely employed across various omics fields as a validation strategy due to its high sensitivity and accuracy. The approach has been successfully employed for the structural analysis of proteins, glycans, lipids, and metabolites. Multiple reaction monitoring (MRM) and parallel reaction monitoring (PRM) have been the methods of choice for targeted structural studies of biomolecules. These target analyses simplify the analytical workflow, reduce background interference, and increase selectivity/specificity, allowing for a reliable quantification of permethylated N-glycans in complex biological matrices.

Keywords:  MRM; PRM; Permethylated N-glycans

DOI:  https://doi.org/10.1007/978-1-0716-3666-4_15
Anal Chem. 2024 Feb 05.

Small-Scale Serial Size Exclusion Chromatography (s3SEC) for High Sensitivity Top-Down Proteomics of Large Proteoforms.

Holden T Rogers, Jake A Melby, Lauren E Ehlers, Matthew S Fischer, Eli J Larson, Zhan Gao, Kalina J Rossler, Daojing Wang, Andrew J Alpert, Ying Ge.

Top-down-mass spectrometry (MS)-based proteomics has emerged as a premier technology to examine proteins at the proteoform level, enabling characterization of genetic mutations, alternative splicing, and post-translational modifications. However, significant challenges that remain in top-down proteomics include the analysis of large proteoforms and the sensitivity required to examine proteoforms from minimal amounts of sample. To address these challenges, we have developed a new method termed "small-scale serial Size Exclusion Chromatography" (s3SEC), which incorporates a small-scale protein extraction (1 mg of tissue) and serial SEC without postfractionation sample handling, coupled with online high sensitivity capillary reversed-phase liquid chromatography tandem MS (RPLC-MS/MS) for analysis of large proteoforms. The s3SEC-RPLC-MS/MS method significantly enhanced the sensitivity and reduced the proteome complexity across the fractions, enabling the detection of high MW proteoforms previously undetected in one-dimensional (1D)-RPLC analysis. Importantly, we observed a drastic improvement in the signal intensity of high MW proteoforms in early fractions when using the s3SEC-RPLC method. Moreover, we demonstrate that this s3SEC-RPLC-MS/MS method also allows the analysis of lower MW proteoforms in subsequent fractions without significant alteration in proteoform abundance and equivalent or improved fragmentation efficiency to that of the 1D-RPLC approach. Although this study focuses on the use of cardiac tissue, the s3SEC-RPLC-MS/MS method could be broadly applicable to other systems with limited sample inputs.

DOI: https://doi.org/10.1021/acs.analchem.3c05733
J Am Soc Mass Spectrom. 2024 Feb 04.

AutonoMS: Automated Ion Mobility Metabolomic Fingerprinting.

Gabriel K Reder, Erik Y Bjurström, Daniel Brunnsåker, Filip Kronström, Praphapan Lasin, Ievgeniia Tiukova, Otto I Savolainen, James N Dodds, Jody C May, John P Wikswo, John A McLean, Ross D King.

Automation is dramatically changing the nature of laboratory life science. Robotic lab hardware that can perform manual operations with greater speed, endurance, and reproducibility opens an avenue for faster scientific discovery with less time spent on laborious repetitive tasks. A major bottleneck remains in integrating cutting-edge laboratory equipment into automated workflows, notably specialized analytical equipment, which is designed for human usage. Here we present AutonoMS, a platform for automatically running, processing, and analyzing high-throughput mass spectrometry experiments. AutonoMS is currently written around an ion mobility mass spectrometry (IM-MS) platform and can be adapted to additional analytical instruments and data processing flows. AutonoMS enables automated software agent-controlled end-to-end measurement and analysis runs from experimental specification files that can be produced by human users or upstream software processes. We demonstrate the use and abilities of AutonoMS in a high-throughput flow-injection ion mobility configuration with 5 s sample analysis time, processing robotically prepared chemical standards and cultured yeast samples in targeted and untargeted metabolomics applications. The platform exhibited consistency, reliability, and ease of use while eliminating the need for human intervention in the process of sample injection, data processing, and analysis. The platform paves the way toward a more fully automated mass spectrometry analysis and ultimately closed-loop laboratory workflows involving automated experimentation and analysis coupled to AI-driven experimentation utilizing cutting-edge analytical instrumentation. AutonoMS documentation is available at https://autonoms.readthedocs.io.

DOI: https://doi.org/10.1021/jasms.3c00396
J Proteome Res. 2024 Feb 05.

High-Throughput Extracellular Matrix Proteomics of Human Lungs Enabled by Photocleavable Surfactant and diaPASEF.

Elizabeth F Bayne, Kevin M Buck, Anna G Towler, Yanlong Zhu, Melissa R Pergande, Tianhua Zhou, Scott Price, Kalina J Rossler, Vanessa Morales-Tirado, Sarah Lloyd, Fei Wang, Yupeng He, Yu Tian, Ying Ge.

  The extracellular matrix (ECM) is a complex assembly of proteins that provide interstitial scaffolding and elastic recoil for human lungs. The pulmonary extracellular matrix is increasingly recognized as an independent bioactive entity, by creating biochemical and mechanical signals that influence disease pathogenesis, making it an attractive therapeutic target. However, the pulmonary ECM proteome ("matrisome") remains challenging to analyze by mass spectrometry due to its inherent biophysical properties and relatively low abundance. Here, we introduce a strategy designed for rapid and efficient characterization of the human pulmonary ECM using the photocleavable surfactant Azo. We coupled this approach with trapped ion mobility MS with diaPASEF to maximize the depth of matrisome coverage. Using this strategy, we identify nearly 400 unique matrisome proteins with excellent reproducibility that are known to be important in lung biology, including key core matrisome proteins.

Keywords:  Azo; Data Independent Acquisition; Diapasef; Extracellular Matrix; Matrisome

DOI:  https://doi.org/10.1021/acs.jproteome.3c00532
Anal Chem. 2024 Feb 09.

Single-Cell Unsaturated Lipid Profiling for Studying Chemoresistance Heterogeneity of Triple-Negative Breast Cancer Cells.

Jinlei Yang, Runsong Cheng, Xingyu Pan, Siyuan Pan, Murong Du, Huan Yao, Zhian Hu, Sichun Zhang, Xinrong Zhang.

Chemoresistance to triple-negative breast cancer (TNBC) is a critical issue in clinical practice. Lipid metabolism takes a unique role in breast cancer cells; especially, unsaturated lipids involving cell membrane fluidity and peroxidation are highly remarked. At present, for the lack of a high-resolution molecular recognition platform at the single-cell level, it is still hard to systematically study chemoresistance heterogeneity based on lipid unsaturation proportion. By designing a single-cell mass spectrometry workflow based on CyESI-MS, we profiled the unsaturated lipids of TNBC cells to evaluate lipidomic remodeling under platinum stress. Profiling revealed the heterogeneity of the polyunsaturated lipid proportion of TNBC cells under cisplatin treatment. A cluster of cells identified by polyunsaturated lipid accumulation was found to be involved in platinum sensitivity. Furthermore, we found that the chemoresistance of TNBC cells could be regulated by fatty acid supplementation, which determinates the composition of unsaturated lipids. These discoveries provide insights for monitoring and controlling cellular unsaturated lipid proportions to overcome chemoresistance in breast cancer.

DOI: https://doi.org/10.1021/acs.analchem.3c04887
Methods Mol Biol. 2024 ;2762 219-230

Analysis of Native and Permethylated N-Glycan Isomers Using MGC-LC-MS Techniques.

Andrew I Bennett, Oluwatosin Daramola, Md Mostofa Al Amin Bhuiyan, Vishal Sandilya, Yehia Mechref.

  Glycosylation is an important post-translational modification that affects many critical cellular functions such as adhesion, signaling, protein stability, and function, among others. Abnormal glycosylation has been linked to many diseases. As such, the investigation of glycans and their roles in disease pathway and progression is important. Glycan analysis can be challenging, however, due to such factors as the heterogeneity of glycans and isomers as well as the poor ionization efficiency provided by mass spectrometry analyses. This chapter presents efficient methods that overcome these and other challenges for the analysis of native and permethylated N-glycan isomers in biological samples. Instructions regarding the packing of the MGC column, the N-glycan sample prep, and the LC-MS conditions are also provided.

Keywords:  Glycomics; Isomers; Liquid chromatography-mass spectrometry; Mesoporous graphitized carbon (MGC)

DOI:  https://doi.org/10.1007/978-1-0716-3666-4_13
J Proteome Res. 2024 Feb 07.

A Simplified Label-Free Method for Proteotyping Sets of Six Isolates in a Single Liquid Chromatography-High-Resolution Tandem Mass Spectrometry Analysis.

Madisson Chabas, Jean Armengaud, Béatrice Alpha-Bazin.

  Clinical diagnostics and microbiology require high-throughput identification of microorganisms. Sample multiplexing prior to detection is an attractive means to reduce analysis costs and time-to-result. Recent studies have demonstrated the discriminative power of tandem mass spectrometry-based proteotyping. This technology can rapidly identify the most likely taxonomical position of any microorganism, even uncharacterized organisms. Here, we present a simplified label-free multiplexing method to proteotype isolates by tandem mass spectrometry that can identify six microorganisms in a single 20 min analytical run. The strategy involves the production of peptide fractions with distinct hydrophobicity profiles using spin column fractionation. Assemblages of different fractions can then be analyzed using mass spectrometry. Results are subsequently interpreted based on the hydrophobic characteristics of the peptides detected, which make it possible to link each taxon identified to the initial sample. The methodology was tested on 32 distinct sets of six organisms including several worst-scenario assemblages-with differences in sample quantities or the presence of the same organisms in multiple fractions-and proved to be robust. These results pave the way for the deployment of tandem mass spectrometry-based proteotyping in microbiology laboratories.

Keywords:  bacterial isolates; concatenation; multiplex; proteomics; proteotyping; tandem mass spectrometry; taxonomy

DOI:  https://doi.org/10.1021/acs.jproteome.3c00535
Curr Opin Biotechnol. 2024 Feb 03. pii: S0958-1669(24)00004-1. [Epub ahead of print]86 103068

Mass spectrometry imaging methods for visualizing tumor heterogeneity.

Kyle D Duncan, Helena Pětrošová, Julian J Lum, David R Goodlett.

Profiling spatial distributions of lipids, metabolites, and proteins in tumors can reveal unique cellular microenvironments and provide molecular evidence for cancer cell dysfunction and proliferation. Mass spectrometry imaging (MSI) is a label-free technique that can be used to map biomolecules in tumors in situ. Here, we discuss current progress in applying MSI to uncover molecular heterogeneity in tumors. First, the analytical strategies to profile small molecules and proteins are outlined, and current methods for multimodal imaging to maximize biological information are highlighted. Second, we present and summarize biological insights obtained by MSI of tumor tissue. Finally, we discuss important considerations for designing MSI experiments and several current analytical challenges.

DOI: https://doi.org/10.1016/j.copbio.2024.103068
J Am Soc Mass Spectrom. 2024 Feb 07.

Methionine Alkylation as an Approach to Quantify Methionine Oxidation Using Mass Spectrometry.

Margaret Hoare, Ruiyue Tan, Kevin A Welle, Kyle Swovick, Jennifer R Hryhorenko, Sina Ghaemmaghami.

  Post-translational oxidation of methionine residues can destabilize proteins or modify their functions. Although levels of methionine oxidation can provide important information regarding the structural integrity and regulation of proteins, their quantitation is often challenging as analytical procedures in and of themselves can artifactually oxidize methionines. Here, we develop a mass-spectrometry-based method called Methionine Oxidation by Blocking with Alkylation (MObBa) that quantifies methionine oxidation by selectively alkylating and blocking unoxidized methionines. Thus, alkylated methionines can be used as a stable proxy for unoxidized methionines. Using proof of concept experiments, we demonstrate that MObBa can be used to measure methionine oxidation levels within individual synthetic peptides and on proteome-wide scales. MObBa may provide a straightforward experimental strategy for mass spectrometric quantitation of methionine oxidation.

Keywords:  mass spectrometry (MS); methionine alkylation; methionine oxidation; proteomics

DOI:  https://doi.org/10.1021/jasms.3c00337