bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2021–12–12
seventeen papers selected by
Giovanny Rodríguez Blanco, University of Edinburgh
  1. Plasma Metabolomics and Lipidomics Differentiate Obese Individuals by Peripheral Neuropathy Status.
  2. Current state-of-the-art of separation methods used in LC-MS based metabolomics and lipidomics.
  3. Microenvironmental Factors Modulating Tumor Lipid Metabolism: Paving the Way to Better Antitumoral Therapy.
  4. Targeting ferroptosis for cancer therapy: iron metabolism and anticancer immunity.
  5. Development and Application of Multidimensional Lipid Libraries to Investigate Lipidomic Dysregulation Related to Smoke Inhalation Injury Severity.
  6. Scratching the Surface (Modification): Developing a Quantitative Liquid Chromatography-Tandem Mass Spectrometry Method for the Investigation of PEGylated and Non-PEGylated Lipid Mixtures on Lipid-Coated Lanthanide Nanoparticles.
  7. Global metabolome profiling of COVID-19 respiratory specimen using High Resolution Mass Spectrometry (HRMS).
  8. Targeting Metabolism to Control Immune Responses in Cancer and Improve Checkpoint Blockade Immunotherapy.
  9. Trapped Ion Mobility Spectrometry Reduces Spectral Complexity in Mass Spectrometry-Based Proteomics.
  10. Metabolic disturbances in systemic lupus erythematosus evaluated with UPLC-MS/MS.
  11. The Importance of Cellular Metabolic Pathways in Pathogenesis and Selective Treatments of Hematological Malignancies.
  12. Lipidomics Reveals the Dysregulated Ceramide Metabolism in Oxidized Low-density Lipoprotein Induced Macrophage-Derived Foam Cell.
  13. Metabolic Interactions Between Tumor and Stromal Cells in the Tumor Microenvironment.
  14. Multiplexed Cross-Linking with Isobaric Quantitative Protein Interaction Reporter Technology.
  15. PhosPiR: an automated phosphoproteomic pipeline in R.
  16. Spatial-proteomics reveals phospho-signaling dynamics at subcellular resolution.
  17. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) based assay for the simultaneous quantification of 18-hydroxycorticosterone, 18-hydroxycortisol and 18-oxocortisol in human plasma.
  1. J Clin Endocrinol Metab. 2021 Nov 20. pii: dgab844. [Epub ahead of print]
    Plasma Metabolomics and Lipidomics Differentiate Obese Individuals by Peripheral Neuropathy Status.
    Kai Guo, Masha G Savelieff, Amy E Rumora, Fadhl M Alakwaa, Brian C Callaghan, Junguk Hur, Eva L Feldman.
       CONTEXT: Peripheral neuropathy (PN) is a frequent prediabetes and type 2 diabetes (T2D) complication. Multiple clinical studies reveal that obesity and dyslipidemia can also drive PN progression, independent of glycemia, suggesting a complex interplay of specific metabolite and/or lipid species may underlie PN.
    OBJECTIVE: This work aimed to identify the plasma metabolomics and lipidomics signature that underlies PN in an observational study of a sample of individuals with average class 3 obesity.
    METHODS: We performed plasma global metabolomics and targeted lipidomics on obese participants with (n = 44) and without PN (n = 44), matched for glycemic status, vs lean nonneuropathic controls (n = 43). We analyzed data by Wilcoxon, logistic regression, partial least squares-discriminant analysis, and group-lasso to identify differential metabolites and lipids by obesity and PN status. We also conducted subanalysis by prediabetes and T2D status.
    RESULTS: Lean vs obese comparisons, regardless of PN status, identified the most significant differences in gamma-glutamyl and branched-chain amino acid metabolism from metabolomics analysis and triacylglycerols from lipidomics. Stratification by PN status within obese individuals identified differences in polyamine, purine biosynthesis, and benzoate metabolism. Lipidomics found diacylglycerols as the most significant subpathway distinguishing obese individuals by PN status, with additional contributions from phosphatidylcholines, sphingomyelins, ceramides, and dihydroceramides. Stratifying the obese group by glycemic status did not affect discrimination by PN status.
    CONCLUSION: Obesity may be as strong a PN driver as prediabetes or T2D in a sample of individuals with average class 3 obesity, at least by plasma metabolomics and lipidomics profile. Metabolic and complex lipid pathways can differentiate obese individuals with and without PN, independent of glycemic status.
    Keywords:  complex lipid; diacylglycerol; lipidomics; metabolomics; obesity; polyneuropathy
    DOI:  https://doi.org/10.1210/clinem/dgab844
  2. J Chromatogr B Analyt Technol Biomed Life Sci. 2021 Nov 27. pii: S1570-0232(21)00550-X. [Epub ahead of print]1188 123069
    Current state-of-the-art of separation methods used in LC-MS based metabolomics and lipidomics.
    Eva-Maria Harrieder, Fleming Kretschmer, Sebastian Böcker, Michael Witting.
      Metabolomics deals with the large-scale analysis of metabolites, belonging to numerous compound classes and showing an extremely high chemical diversity and complexity. Lipidomics, being a subcategory of metabolomics, analyzes the cellular lipid species. Both require state-of-the-art analytical methods capable of accessing the underlying chemical complexity. One of the major techniques used for the analysis of metabolites and lipids is Liquid Chromatography-Mass Spectrometry (LC-MS), offering both different selectivities in LC separation and high sensitivity in MS detection. Chromatography can be divided into different modes, based on the properties of the employed separation system. The most popular ones are Reversed-Phase (RP) separation for non- to mid-polar molecules and Hydrophilic Interaction Liquid Chromatography (HILIC) for polar molecules. So far, no single analysis method exists that can cover the entire range of metabolites or lipids, due to the huge chemical diversity. Consequently, different separation methods have been used for different applications and research questions. In this review, we explore the current use of LC-MS in metabolomics and lipidomics. As a proxy, we examined the use of chromatographic methods in the public repositories EBI MetaboLights and NIH Metabolomics Workbench. We extracted 1484 method descriptions, collected separation metadata and generated an overview on the current use of columns, eluents, etc. Based on this overview, we reviewed current practices and identified potential future trends as well as required improvements that may allow us to increase metabolite coverage, throughput or both simultaneously.
    Keywords:  Lipidomics; Liquid Chromatography-Mass Spectrometry; Metabolomics
    DOI:  https://doi.org/10.1016/j.jchromb.2021.123069
  3. Front Oncol. 2021 ;11 777273
    Microenvironmental Factors Modulating Tumor Lipid Metabolism: Paving the Way to Better Antitumoral Therapy.
    Limeng Cai, Minfeng Ying, Hao Wu.
      Metabolic reprogramming is one of the emerging hallmarks of cancer and is driven by both the oncogenic mutations and challenging microenvironment. To satisfy the demands of energy and biomass for rapid proliferation, the metabolism of various nutrients in tumor cells undergoes important changes, among which the aberrant lipid metabolism has gained increasing attention in facilitating tumor development and metastasis in the past few years. Obstacles emerged in the aspect of application of targeting lipid metabolism for tumor therapy, due to lacking of comprehensive understanding on its regulating mechanism. Tumor cells closely interact with stromal niche, which highly contributes to metabolic rewiring of critical nutrients in cancer cells. This fact makes the impact of microenvironment on tumor lipid metabolism a topic of renewed interest. Abundant evidence has shown that many factors existing in the tumor microenvironment can rewire multiple signaling pathways and proteins involved in lipid metabolic pathways of cancer cells. Hence in this review, we summarized the recent progress on the understanding of microenvironmental factors regulating tumor lipid metabolism, and discuss the potential of modulating lipid metabolism as an anticancer approach.
    Keywords:  cancer therapy; lipid metabolism; metabolic reprogramming; microenvironment factor; tumor micoenvironment
    DOI:  https://doi.org/10.3389/fonc.2021.777273
  4. Am J Cancer Res. 2021 ;11(11): 5508-5525
    Targeting ferroptosis for cancer therapy: iron metabolism and anticancer immunity.
    Lianxiang Luo, Han Wang, Wen Tian, Jiayan Zeng, Yuru Huang, Hui Luo.
      Ferroptosis is a new form of programmed cell death characterized by iron-dependent accumulation of lipid peroxidation, which plays an important role in cancer biology. Ferroptosis is involved in many biological processes, such as amino acid metabolism, glutathione metabolism, iron metabolism, and lipid metabolism. Iron is an essential trace element in a variety of normal cell processes, such as DNA synthesis and repair, cell respiration, metabolism and signal transduction, etc., and iron metabolism disorder has been considered as one of the metabolic markers of malignant cancer cells. In addition, iron is involved in the regulation of innate and adaptive immune responses, suggesting that targeted regulation of iron metabolism may contribute to anti-tumor immunity and cancer therapy. In this review, the regulatory mechanism of ferroptosis, the interaction between ferroptosis on tumor cell metabolism, and anti-tumor immunity were systematically reviewed. Immunotherapy combined with targeted regulation of iron and iron-dependent regulation of ferroptosis should be the focus of future ferroptosis research.
    Keywords:  Ferroptosis; anti-tumor immunity; cancer; lipid peroxidation; metabolism
  5. J Proteome Res. 2021 Dec 07.
    Development and Application of Multidimensional Lipid Libraries to Investigate Lipidomic Dysregulation Related to Smoke Inhalation Injury Severity.
    Kaylie I Kirkwood, Michael W Christopher, Jefferey L Burgess, Sally R Littau, Kevin Foster, Karen Richey, Brian S Pratt, Nicholas Shulman, Kaipo Tamura, Michael J MacCoss, Brendan X MacLean, Erin S Baker.
      The implication of lipid dysregulation in diseases, toxic exposure outcomes, and inflammation has brought great interest to lipidomic studies. However, lipids have proven to be analytically challenging due to their highly isomeric nature and vast concentration ranges in biological matrices. Therefore, multidimensional techniques such as those integrating liquid chromatography, ion mobility spectrometry, collision-induced dissociation, and mass spectrometry (LC-IMS-CID-MS) have been implemented to separate lipid isomers as well as provide structural information and increased identification confidence. These data sets are however extremely large and complex, resulting in challenges for data processing and annotation. Here, we have overcome these challenges by developing sample-specific multidimensional lipid libraries using the freely available software Skyline. Specifically, the human plasma library developed for this work contains over 500 unique lipids and is combined with adapted Skyline functions such as indexed retention time (iRT) for retention time prediction and IMS drift time filtering for enhanced selectivity. For comparison with other studies, this database was used to annotate LC-IMS-CID-MS data from a NIST SRM 1950 extract. The same workflow was then utilized to assess plasma and bronchoalveolar lavage fluid (BALF) samples from patients with varying degrees of smoke inhalation injury to identify lipid-based patient prognostic and diagnostic markers.
    Keywords:  data annotation; ion mobility spectrometry; lipidomics; smoke inhalation; spectral libraries
    DOI:  https://doi.org/10.1021/acs.jproteome.1c00820
  6. Langmuir. 2021 Dec 08.
    Scratching the Surface (Modification): Developing a Quantitative Liquid Chromatography-Tandem Mass Spectrometry Method for the Investigation of PEGylated and Non-PEGylated Lipid Mixtures on Lipid-Coated Lanthanide Nanoparticles.
    Loryn P Arnett, Matthew W Forbes, Rachel Keunen, Mitchell A Winnik.
      We are interested in developing lanthanide nanoparticles (LnNPs) of the general formula NaLnF4 as high-sensitivity reagents for mass cytometry. These LnNPs must be coated to provide colloidal stability in aqueous buffer and functionality for detecting cellular biomarkers. Lipid bilayer coatings are a promising approach, but one requires an analytical technique to enable characterization of the NP coating composition as opposed to the composition of the lipid formulation used in the coating process. However, quantification of the lipid composition of lipid coatings on polymer and inorganic NPs is not common practice in the field. Here we describe a method based on high-performance liquid chromatography (LC) for separations and triple quadrupole tandem mass spectrometry (MS/MS) instrumentation for detection and show that it can quantify complex lipid mixtures using small (<1 μg) amounts of sample. Our lipid formulation consisted of a mixture of egg sphingomyelin, 1,2-dioleoyl-sn-glycero-3-phosphocholine, 1,2-dioleoyl-3-trimethylammonium-propane, cholesterol-PEG600, and 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[biotinyl(polyethylene glycol)-2000]. We were able to extract the coating from lipid-coated 35 nm diameter LnNPs, quantify the lipid/NP ratio, and show that the coating composition differed from the composition of the lipid formulation for several of the species. Knowledge of the actual composition of the lipid coating for lipid-coated NPs is critical for designing and optimizing application of these materials. Our results establish the value of LC-MS/MS characterization of lipid-coated NPs, thus providing an important new addition to the toolbox available for characterizing these types of nanomaterials.
    DOI:  https://doi.org/10.1021/acs.langmuir.1c02260
  7. STAR Protoc. 2021 Dec 03. 101051
    Global metabolome profiling of COVID-19 respiratory specimen using High Resolution Mass Spectrometry (HRMS).
    Nupur Sharma, Sadam H Bhat, Gaurav Tripathi, Manisha Yadav, Babu Mathew, Vasundhra Bindal, Shvetank Sharma, Ekta Gupta, Jaswinder Singh, Shiv Kumar Sarin.
      Here we describe a protocol for identifying metabolites in respiratory specimens of patients that are SARS-CoV-2 positive, SARS-CoV-2 negative, or H1N1 positive. This protocol provides step-by-step instructions on sample collection from patients, followed by metabolite extraction. We use ultra high-pressure liquid chromatography (UHPLC) coupled High Resolution Mass Spectrometry (HRMS) for data acquisition and describe the steps for data analysis. The protocol was standardized with specific customization for SARS-CoV-2 containing respiratory specimens.
    DOI:  https://doi.org/10.1016/j.xpro.2021.101051
  8. Cancers (Basel). 2021 Nov 24. pii: 5912. [Epub ahead of print]13(23):
    Targeting Metabolism to Control Immune Responses in Cancer and Improve Checkpoint Blockade Immunotherapy.
    Angèle Luby, Marie-Clotilde Alves-Guerra.
      Over the past decade, advances in cancer immunotherapy through PD1-PDL1 and CTLA4 immune checkpoint blockade have revolutionized the management of cancer treatment. However, these treatments are inefficient for many cancers, and unfortunately, few patients respond to these treatments. Indeed, altered metabolic pathways in the tumor play a pivotal role in tumor growth and immune response. Thus, the immunosuppressive tumor microenvironment (TME) reprograms the behavior of immune cells by altering their cellular machinery and nutrient availability to limit antitumor functions. Today, thanks to a better understanding of cancer metabolism, immunometabolism and immune checkpoint evasion, the development of new therapeutic approaches targeting the energy metabolism of cancer or immune cells greatly improve the efficacy of immunotherapy in different cancer models. Herein, we highlight the changes in metabolic pathways that regulate the differentiation of pro- and antitumor immune cells and how TME-induced metabolic stress impedes their antitumor activity. Finally, we propose some drug strategies to target these pathways in the context of cancer immunotherapy.
    Keywords:  cancer; immune response; immunotherapy; metabolic drug; metabolism
    DOI:  https://doi.org/10.3390/cancers13235912
  9. Anal Chem. 2021 Dec 09.
    Trapped Ion Mobility Spectrometry Reduces Spectral Complexity in Mass Spectrometry-Based Proteomics.
    Joshua Charkow, Hannes L Röst.
      In bottom-up mass spectrometry-based proteomics, deep proteome coverage is limited by high cofragmentation rates. Cofragmentation occurs when more than one analyte is isolated by the quadrupole and the subsequent fragmentation event produces fragment ions of heterogeneous origin. One strategy to reduce cofragmentation rates is through effective peptide separation techniques such as chromatographic separation and, the more recently popularized, ion mobility (IM) spectrometry, which separates peptides by their collisional cross section. Here, we use a computational model to investigate the capability of the trapped IM spectrometry (TIMS) device at effectively separating peptide ions and quantify the separation power of the TIMS device in the context of a parallel accumulation-serial fragmentation (PASEF) workflow. We found that TIMS separation increases the number of interference-free MS1 peptide features 9.2-fold, while decreasing the average peptide density in precursor spectra 6.5-fold. In a data-dependent acquisition PASEF workflow, IM separation increases the number of spectra without cofragmentation by a factor of 4.1 and the number of high-quality spectra 17-fold. Using a categorical model, we estimate that this observed decrease in spectral complexity results in an increased likelihood for peptide spectral matches, which may improve peptide identification rates. In the context of a data-independent acquisition workflow, the reduction in spectral complexity resulting from IM separation is estimated to be equivalent to a 4-fold decrease in the isolation window width (from 25 to 6.5 Da). Our study demonstrates that TIMS separation decreases spectral complexity by reducing cofragmentation rates, suggesting that TIMS separation may contribute toward the high identification rates observed in PASEF workflows.
    DOI:  https://doi.org/10.1021/acs.analchem.1c01399
  10. Clin Exp Rheumatol. 2021 Dec 07.
    Metabolic disturbances in systemic lupus erythematosus evaluated with UPLC-MS/MS.
    Kuo-Tung Tang, Han-Ju Chien, Ya-Han Chang, Tsai-Ling Liao, Der-Yuan Chen, Chien-Chen Lai.
       OBJECTIVES: Systemic lupus erythematosus (SLE) is an autoimmune disease. However, no surrogate biomarker is available for SLE diagnosis or predicting disease outcomes. Here, an ultra-performance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS)-based metabolomics strategy was executed to conduct biomarker discovery in SLE.
    METHODS: Metabolite profiles were analysed using UPLC-MS/MS analysis of serum samples obtained from the discovery cohort. Differentially expressed metabolites were identified using multivariate analyses. During the validation stage, the significant metabolites identified in the discovery cohort were quantified in a validation cohort using multiple reaction monitoring mass spectrometry (MRM-MS). Differences in serum metabolite levels and SLE disease activity markers were examined by using Spearman's correlation analysis.
    RESULTS: A total of 29 significant metabolites were identified by the UPLC-MS/MS analysis. These metabolites were primarily involved in fatty acid metabolism (20.69%) and phospholipid catabolism (17.24%). In the validation cohort, 11 of 29 metabolites were quantified, which demonstrated increased levels of pyroglutamic acid and L-phenylalanine in SLE patients compared with healthy controls. Patients with lupus nephritis (LN) presented with higher taurine levels, which could serve as a biomarker. The literature review indicated decreased levels of amino acids and adenosine among SLE patients and increased lipids, low-density lipoprotein, and very low-density lipoprotein among LN patients compared to healthy controls.
    CONCLUSIONS: Fatty acid metabolism and phospholipid catabolism were affected in SLE patients. Pyroglutamic acid and L-phenylalanine have the potential to act as SLE biomarkers, and taurine might be used to distinguish patients with and without LN.
  11. Front Oncol. 2021 ;11 767026
    The Importance of Cellular Metabolic Pathways in Pathogenesis and Selective Treatments of Hematological Malignancies.
    Mojdeh Soltani, Yue Zhao, Zhijia Xia, Mazdak Ganjalikhani Hakemi, Alexandr V Bazhin.
      Despite recent advancements in the treatment of hematologic malignancies and the emergence of newer and more sophisticated therapeutic approaches such as immunotherapy, long-term overall survival remains unsatisfactory. Metabolic alteration, as an important hallmark of cancer cells, not only contributes to the malignant transformation of cells, but also promotes tumor progression and metastasis. As an immune-escape mechanism, the metabolic adaptation of the bone marrow microenvironment and leukemic cells is a major player in the suppression of anti-leukemia immune responses. Therefore, metabolic rewiring in leukemia would provide promising opportunities for newer therapeutic interventions. Several therapeutic agents which affect essential bioenergetic pathways in cancer cells including glycolysis, β-oxidation of fatty acids and Krebs cycle, or anabolic pathways such as lipid biosynthesis and pentose phosphate pathway, are being tested in various types of cancers. So far, numerous preclinical or clinical trial studies using such metabolic agents alone or in combination with other remedies such as immunotherapy are in progress and have demonstrated promising outcomes. In this review, we aim to argue the importance of metabolic alterations and bioenergetic pathways in different types of leukemia and their vital roles in disease development. Designing treatments based on targeting leukemic cells vulnerabilities, particularly in nonresponsive leukemia patients, should be warranted.
    Keywords:  acute lymphocytic leukemia; acute myeloid leukemia; cellular metabolism; chronic lymphocytic leukemia; chronic myeloid leukemia; immunometabolism
    DOI:  https://doi.org/10.3389/fonc.2021.767026
  12. Biomed Chromatogr. 2021 Dec 10. e5297
    Lipidomics Reveals the Dysregulated Ceramide Metabolism in Oxidized Low-density Lipoprotein Induced Macrophage-Derived Foam Cell.
    Jie Liu, Tong Li, Wenxuan Pei, Ye Zhao, Xin Zhang, Xiujia Shi, Yanping Li, Wenjuan Xu.
      Atherosclerosis (AS) is associated with increasing lipid peroxidation, oxidative modification LDL (ox-LDL) is one most important factor contributing to the pathogenesis and clinical feature of AS. The lipid composition influenced by ox-LDL is not known clearly. In this work, UHPLC/Orbitrap MS-based lipidomics approach integrated pathway analysis was performed to advance the understanding of the lipid composition and feature pathway in ox-LDL induced foamy macrophage cell. In the lipid metabolic profiling, 196 lipid species from 15 (sub) classes were identified. Lipid profiling indicated overtaking ox-LDL caused lipid metabolic alternations, manifesting as phospholipids down-regulated and sphingolipids up-regulated. Pathway analysis explored glycerophospholipid and sphingolipid metabolism were mainly involved in atherogenic changes. Notably, dysregulated ceramide metabolism was the typical feature of foamy cell formation. qRT-PCR analysis was conducted to explore the differentially expressed gene. It indicated that ceramide metabolic balance might be a mainly disordered, performing higher synthesis and lower hydrolysis, with the ratio of SMPD1/SGMS2 up-regulated significantly (p<0.05) in ox-LDL induced group. Our work offers a comprehensive understanding of macrophage-derived foam cells and screen feature pathways associated with foamy cell formation, which provides a reference for the clinic diagnosis and drug intervention of AS.
    Keywords:  atherosclerosis; ceramide metabolism; drug discovery; foamy macrophages; lipidomics
    DOI:  https://doi.org/10.1002/bmc.5297
  13. Adv Exp Med Biol. 2021 ;1350 101-121
    Metabolic Interactions Between Tumor and Stromal Cells in the Tumor Microenvironment.
    Deepshikha Mishra, Debabrata Banerjee.
      In this chapter, we provide information about metabolic reprogramming in cancer cells, molecular interactions between tumor and stromal cells in the tumor microenvironment, focusing primarily on CAFs and tumor cell interaction. We have covered the role of cytokines, chemokines, and lactate in driving tumor-stroma interactions in the microenvironment. Here, we have discussed the pro-tumorigenic molecular interactions in between tumor cells and CAFs mediated via altered signaling pathways, cytokines, chemokines, and lactate in the tumor vicinity. A better understanding of the complex cancer cell-CAF interactions will help in designing successful therapeutic strategies targeting the stromal-rich tumors in the clinic.
    Keywords:  CAFs; Cytokines; Lactate; Metabolic cooperation; Pyruvate; Tumor microenvironment
    DOI:  https://doi.org/10.1007/978-3-030-83282-7_5
  14. Anal Chem. 2021 Dec 09.
    Multiplexed Cross-Linking with Isobaric Quantitative Protein Interaction Reporter Technology.
    Juan D Chavez, Andrew Keller, Helisa H Wippel, Jared P Mohr, James E Bruce.
      Chemical cross-linking with mass spectrometry (XL-MS) has emerged as a useful technique for interrogating protein structures and interactions. When combined with quantitative proteomics strategies, protein conformational and interaction dynamics can be probed. Quantitative XL-MS has been demonstrated with the use of stable isotopes incorporated metabolically or into the cross-linker molecules. Isotope-labeled cross-linkers have primarily utilized deuterium and rely on MS1-based quantitation of precursor ion extracted ion chromatograms. Recently the development and application of isobaric quantitative protein interaction reporter (iqPIR) cross-linkers were reported, which utilize 13C and 15N isotope labels. Quantitation is accomplished using relative fragment ion isotope abundances in tandem mass spectra. Here we describe the synthesis and initial evaluation of a multiplexed set of iqPIR molecules, allowing for up to six cross-linked samples to be quantified simultaneously. To analyze data for such cross-linkers, the two-channel mode of iqPIR quantitative analysis was adapted to accommodate any number of channels with defined ion isotope peak mass offsets. The summed ion peak intensities in the overlapping channel isotope envelopes are apportioned among the channels to minimize the difference with respect to the predicted ion isotope envelopes. The result is accurate and reproducible relative quantitation enabling direct comparison among six differentially labeled cross-linked samples. The approach described here is generally extensible for the iqPIR strategy, accommodating future iqPIR reagent design, and enables large-scale in vivo quantitative XL-MS investigation of the interactome.
    DOI:  https://doi.org/10.1021/acs.analchem.1c02209
  15. Brief Bioinform. 2021 Dec 08. pii: bbab510. [Epub ahead of print]
    PhosPiR: an automated phosphoproteomic pipeline in R.
    Ye Hong, Dani Flinkman, Tomi Suomi, Sami Pietilä, Peter James, Eleanor Coffey, Laura L Elo.
      Large-scale phosphoproteome profiling using mass spectrometry (MS) provides functional insight that is crucial for disease biology and drug discovery. However, extracting biological understanding from these data is an arduous task requiring multiple analysis platforms that are not adapted for automated high-dimensional data analysis. Here, we introduce an integrated pipeline that combines several R packages to extract high-level biological understanding from large-scale phosphoproteomic data by seamless integration with existing databases and knowledge resources. In a single run, PhosPiR provides data clean-up, fast data overview, multiple statistical testing, differential expression analysis, phosphosite annotation and translation across species, multilevel enrichment analyses, proteome-wide kinase activity and substrate mapping and network hub analysis. Data output includes graphical formats such as heatmap, box-, volcano- and circos-plots. This resource is designed to assist proteome-wide data mining of pathophysiological mechanism without a need for programming knowledge.
    Keywords:  bioinformatics; data visualization; phosphoproteomics; pipeline; proteomics; statistics
    DOI:  https://doi.org/10.1093/bib/bbab510
  16. Nat Commun. 2021 Dec 07. 12(1): 7113
    Spatial-proteomics reveals phospho-signaling dynamics at subcellular resolution.
    Ana Martinez-Val, Dorte B Bekker-Jensen, Sophia Steigerwald, Claire Koenig, Ole Østergaard, Adi Mehta, Trung Tran, Krzysztof Sikorski, Estefanía Torres-Vega, Ewa Kwasniewicz, Sólveig Hlín Brynjólfsdóttir, Lisa B Frankel, Rasmus Kjøbsted, Nicolai Krogh, Alicia Lundby, Simon Bekker-Jensen, Fridtjof Lund-Johansen, Jesper V Olsen.
      Dynamic change in subcellular localization of signaling proteins is a general concept that eukaryotic cells evolved for eliciting a coordinated response to stimuli. Mass spectrometry-based proteomics in combination with subcellular fractionation can provide comprehensive maps of spatio-temporal regulation of protein networks in cells, but involves laborious workflows that does not cover the phospho-proteome level. Here we present a high-throughput workflow based on sequential cell fractionation to profile the global proteome and phospho-proteome dynamics across six distinct subcellular fractions. We benchmark the workflow by studying spatio-temporal EGFR phospho-signaling dynamics in vitro in HeLa cells and in vivo in mouse tissues. Finally, we investigate the spatio-temporal stress signaling, revealing cellular relocation of ribosomal proteins in response to hypertonicity and muscle contraction. Proteomics data generated in this study can be explored through https://SpatialProteoDynamics.github.io .
    DOI:  https://doi.org/10.1038/s41467-021-27398-y
  17. J Chromatogr B Analyt Technol Biomed Life Sci. 2021 Nov 23. pii: S1570-0232(21)00511-0. [Epub ahead of print]1188 123030
    Liquid chromatography-tandem mass spectrometry (LC-MS/MS) based assay for the simultaneous quantification of 18-hydroxycorticosterone, 18-hydroxycortisol and 18-oxocortisol in human plasma.
    Fangjun Chen, Ziyun Cheng, Zhenxin Wang, Yingfei Peng, Beili Wang, Wei Guo, Baishen Pan.
      18-hydroxycorticosterone (18-OHB), 18-hydroxycortisol (18-OHF) and 18-oxocortisol (18-OXOF) are important biomarkers for the diagnosis of subtypes of primary aldosteronism. The detection of these three analytes by liquid chromatography-tandem mass spectrometry (LC-MS/MS) is free from structurally similar compounds. The aim of this study was to develop and validate a new LC-MS/MS assay for the simultaneous quantification of 18-OHB, 18-OHF and 18-OXOF in plasma and to establish a reference intervals for apparently healthy population. Plasma samples were prepared by solid phase extraction and separated in an ultra-high performance reversed phase column. MS detection was achieved using a triple quadrupole mass spectrometer in both positive and negative ionization modes. The developed assay was then validated against standard guidelines. We collected 691 plasma samples from apparently healthy individuals (M:398, F:293) to establish the reference intervals. The analytes were separated and quantified within 5 min. The newly developed method demonstrated linearity for the detected steroid concentration in range of 5 to 3000 pg/ml for 18-OXOF (r2 = 0.999) and 20 to 3000 pg/ml for 18-OHB (r2 = 0.997) and 18-OHF (r2 = 0.997). The lower limit of quantification (LLOQ) was 2.5 pg/ml, 20 pg/ml and 20 pg/m for 18-OXOF, 18-OHB and 18-OHF respectively. Specificity, precision, accuracy and stability were tested, and met the requirements of the guidelines. 18-OHB was higher in females than in males, but 18-OHF were higher in males than females. The reference intervals of 18-OHB, 18-OHF and 18-OXOF for both genders together were 90.5-1040.6 pg/ml, 224.4-1685.2 pg/ml, 4.0-70.5 pg/ml, respectively. Age was also an important factor influencing the levels of these three hormones. We have developed a sensitive and reliable method for the simultaneous quantification of 18-OHB, 18-OHF, and 18-OXOF. Our work provides a reference interval for the clinical application of these three steroid hormones.
    Keywords:  18-hydroxycorticosterone; 18-hydroxycortisol; 18-oxocortisol; Liquid chromatography-tandem mass spectrometry
    DOI:  https://doi.org/10.1016/j.jchromb.2021.123030
This page is being maintained by Thomas Krichel. It was last updated on 2024‒12‒09 at 5:53.