bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2021‒12‒05
28 papers selected by
Giovanny Rodriguez Blanco
University of Edinburgh
  1. Cross-Laboratory Standardization of Preclinical Lipidomics Using Differential Mobility Spectrometry and Multiple Reaction Monitoring.
  2. Quantitative subcellular acyl-CoA analysis reveals distinct nuclear metabolism and isoleucine-dependent histone propionylation.
  3. Comprehensive Workflow of Mass Spectrometry-based Shotgun Proteomics of Tissue Samples.
  4. p53: A Double-Edged Sword in Tumor Ferroptosis.
  5. Too complex to fail? Targeting fatty acid metabolism for cancer therapy.
  6. Experimental design of a stable isotope labeling derivatized UHPLC-MS/MS method for the detection/quantification of primary/secondary bile acids in biofluids.
  7. Targeting cancer metabolism in the era of precision oncology.
  8. Phosphatidylinositol metabolism, phospholipases, lipidomics, and cancer: In Memoriam: Michael J. O. Wakelam (1955-2020).
  9. Spectral entropy outperforms MS/MS dot product similarity for small-molecule compound identification.
  10. Kendrick Mass Defect Variation to Decipher Isotopic Labeling in Brain Metastases Studied by Mass Spectrometry Imaging.
  11. Metabolic Reprogramming in the Tumor Microenvironment With Immunocytes and Immune Checkpoints.
  12. Serum Untargeted UHPLC-HRMS-Based Lipidomics to Discover the Potential Biomarker of Colorectal Advanced Adenoma.
  13. Serine catabolism generates liver NADPH and supports hepatic lipogenesis.
  14. Mass Spectrometry based Metabolomics for Small Molecule Metabolites Mining and Confirmation as Potential Biomarkers for Schistosomiasis - Case of the Okavango Delta Communities in Botswana.
  15. Elucidating tumor-stromal metabolic crosstalk in colorectal cancer through integration of constraint-based models and LC-MS metabolomics.
  16. Accelerating strain phenotyping with desorption electrospray ionization-imaging mass spectrometry and untargeted analysis of intact microbial colonies.
  17. Pharmacological reduction of mitochondrial iron triggers a non-canonical BAX/BAK dependent cell death.
  18. Collision energies: Optimization strategies for bottom-up proteomics.
  19. 1-deoxysphinganine initiates adaptive responses to serine and glycine starvation in cancer cells via proteolysis of sphingosine kinase.
  20. Tandem mass spectrometry approaches for recognition of isomeric compounds mixtures.
  21. Neutron encoded derivatization of endothelial cell lysates for quantitation of aldehyde metabolites using nESI-LC-HRMS.
  22. ASS1 and ASL suppress growth in clear cell renal cell carcinoma via altered nitrogen metabolism.
  23. Comparison of Microflow and Analytical Flow Liquid Chromatography Coupled to Mass Spectrometry Global Metabolomics Methods Using a Urea Cycle Disorder Mouse Model.
  24. GNPS Dashboard: collaborative exploration of mass spectrometry data in the web browser.
  25. Personalized phosphoproteomics identifies functional signaling.
  26. 15-Lipoxygenase and its metabolites in the pathogenesis of breast cancer: A double-edged sword.
  27. Fumarate is a terminal electron acceptor in the mammalian electron transport chain.
  28. Targeted Metabolomics Reveals Birth Screening Biomarkers for Biliary Atresia in Dried Blood Spots.
  1. Anal Chem. 2021 Dec 03.
    Cross-Laboratory Standardization of Preclinical Lipidomics Using Differential Mobility Spectrometry and Multiple Reaction Monitoring.
    Mohan Ghorasaini, Yassene Mohammed, Jerzy Adamski, Lisa Bettcher, John A Bowden, Matias Cabruja, Kévin Contrepois, Mathew Ellenberger, Bharat Gajera, Mark Haid, Daniel Hornburg, Christie Hunter, Christina M Jones, Theo Klein, Oleg Mayboroda, Mina Mirzaian, Ruin Moaddel, Luigi Ferrucci, Jacqueline Lovett, Kenneth Nazir, Mackenzie Pearson, Baljit K Ubhi, Daniel Raftery, Fabien Riols, Rebekah Sayers, Eric J G Sijbrands, Michael P Snyder, Baolong Su, Vidya Velagapudi, Kevin J Williams, Yolanda B de Rijke, Martin Giera.
      Modern biomarker and translational research as well as personalized health care studies rely heavily on powerful omics' technologies, including metabolomics and lipidomics. However, to translate metabolomics and lipidomics discoveries into a high-throughput clinical setting, standardization is of utmost importance. Here, we compared and benchmarked a quantitative lipidomics platform. The employed Lipidyzer platform is based on lipid class separation by means of differential mobility spectrometry with subsequent multiple reaction monitoring. Quantitation is achieved by the use of 54 deuterated internal standards and an automated informatics approach. We investigated the platform performance across nine laboratories using NIST SRM 1950-Metabolites in Frozen Human Plasma, and three NIST Candidate Reference Materials 8231-Frozen Human Plasma Suite for Metabolomics (high triglyceride, diabetic, and African-American plasma). In addition, we comparatively analyzed 59 plasma samples from individuals with familial hypercholesterolemia from a clinical cohort study. We provide evidence that the more practical methyl-tert-butyl ether extraction outperforms the classic Bligh and Dyer approach and compare our results with two previously published ring trials. In summary, we present standardized lipidomics protocols, allowing for the highly reproducible analysis of several hundred human plasma lipids, and present detailed molecular information for potentially disease relevant and ethnicity-related materials.
    DOI:  https://doi.org/10.1021/acs.analchem.1c02826
  2. Mol Cell. 2021 Nov 22. pii: S1097-2765(21)00956-4. [Epub ahead of print]
    Quantitative subcellular acyl-CoA analysis reveals distinct nuclear metabolism and isoleucine-dependent histone propionylation.
    Sophie Trefely, Katharina Huber, Joyce Liu, Michael Noji, Stephanie Stransky, Jay Singh, Mary T Doan, Claudia D Lovell, Eliana von Krusenstiern, Helen Jiang, Anna Bostwick, Hannah L Pepper, Luke Izzo, Steven Zhao, Jimmy P Xu, Kenneth C Bedi, J Eduardo Rame, Juliane G Bogner-Strauss, Clementina Mesaros, Simone Sidoli, Kathryn E Wellen, Nathaniel W Snyder.
      Quantitative subcellular metabolomic measurements can explain the roles of metabolites in cellular processes but are subject to multiple confounding factors. We developed stable isotope labeling of essential nutrients in cell culture-subcellular fractionation (SILEC-SF), which uses isotope-labeled internal standard controls that are present throughout fractionation and processing to quantify acyl-coenzyme A (acyl-CoA) thioesters in subcellular compartments by liquid chromatography-mass spectrometry. We tested SILEC-SF in a range of sample types and examined the compartmentalized responses to oxygen tension, cellular differentiation, and nutrient availability. Application of SILEC-SF to the challenging analysis of the nuclear compartment revealed a nuclear acyl-CoA profile distinct from that of the cytosol, with notable nuclear enrichment of propionyl-CoA. Using isotope tracing, we identified the branched chain amino acid isoleucine as a major metabolic source of nuclear propionyl-CoA and histone propionylation, thus revealing a new mechanism of crosstalk between metabolism and the epigenome.
    Keywords:  acyl-CoA; branched chain amino acids; histone; internal standard; isoleucine; matrix effects; metabolomics; mitochondria; nucleus; propionylation; subcellular
    DOI:  https://doi.org/10.1016/j.molcel.2021.11.006
  3. J Vis Exp. 2021 Nov 13.
    Comprehensive Workflow of Mass Spectrometry-based Shotgun Proteomics of Tissue Samples.
    Ayushi Verma, Vipin Kumar, Saicharan Ghantasala, Shuvolina Mukherjee, Sanjeeva Srivastava.
      Recent advances in mass spectrometry have resulted in deep proteomic analysis along with the generation of robust and reproducible datasets. However, despite the considerable technical advancements, sample preparation from biospecimens such as patient blood, CSF, and tissue still poses considerable challenges. For identifying biomarkers, tissue proteomics often provides an attractive sample source to translate the research findings from the bench to the clinic. It can reveal potential candidate biomarkers for early diagnosis of cancer and neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, etc. Tissue proteomics also yields a wealth of systemic information based on the abundance of proteins and helps to address interesting biological questions. Quantitative proteomics analysis can be grouped into two broad categories: a label-based and a label-free approach. In the label-based approach, proteins or peptides are labeled using stable isotopes such as SILAC (stable isotope labeling with amino acids in cell culture) or by chemical tags such as ICAT (isotope-coded affinity tags), TMT (tandem mass tag) or iTRAQ (isobaric tag for relative and absolute quantitation). Label-based approaches have the advantage of more accurate quantitation of proteins and using isobaric labels, multiple samples can be analyzed in a single experiment. The label-free approach provides a cost-effective alternative to label-based approaches. Hundreds of patient samples belonging to a particular cohort can be analyzed and compared with other cohorts based on clinical features. Here, we have described an optimized quantitative proteomics workflow for tissue samples using label-free and label-based proteome profiling methods, which is crucial for applications in life sciences, especially biomarker discovery-based projects.
    DOI:  https://doi.org/10.3791/61786
  4. Pharmacol Res. 2021 Nov 29. pii: S1043-6618(21)00597-1. [Epub ahead of print] 106013
    p53: A Double-Edged Sword in Tumor Ferroptosis.
    Haixia Ji, Wenzhe Wang, Xia Li, Xiaoying Han, Xinyu Zhang, Juan Wang, Changxiao Liu, Luqi Huang, Wenyuan Gao.
      Ferroptosis is a type of lipid peroxidation-induced cell death that can be regulated in various ways, from changing the activity of antioxidant enzymes to the levels of transcription factors. The p53 tumor suppressor gene is the "guardian of the genome" and is involved in controlling cell survival and division under various pressures. In addition to its effects on apoptosis, autophagy, and cell cycle, p53, through the way of transcription dependent or independent two-way, also regulates the biological processes of tumor cell sensitivity to ferroptosis, including the metabolism of amino acids, nicotinamide adenine dinucleotide phosphate, and lipid peroxidation, as well as the biosynthesis of glutathione, phospholipids, NADPH and coenzyme Q10.As reviewed here, we summarized the metabolic network of p53 and its signaling pathway in regulating ferroptosis and elucidated possible factors and potential clinical application of p53 regulating ferroptosis. This review will provide a basis for further understanding the role of p53 in tumor ferroptosis and new strategies for cancer therapeutic avenues.
    Keywords:  Ferroptosis; Metabolism; P53; Sensitivity; Tumor suppressor
    DOI:  https://doi.org/10.1016/j.phrs.2021.106013
  5. Prog Lipid Res. 2021 Nov 29. pii: S0163-7827(21)00059-X. [Epub ahead of print] 101143
    Too complex to fail? Targeting fatty acid metabolism for cancer therapy.
    Rimsha Munir, Jan Lisec, Johannes V Swinnen, Nousheen Zaidi.
      Given the central role of fatty acids in cancer pathophysiology, the exploitation of fatty acid metabolism as a potential antineoplastic therapy has gained much attention. Several natural and synthetic compounds targeting fatty acid metabolism were hitherto identified, and their effectiveness against cancer cell proliferation and survival was determined. This review will discuss the most clinically viable inhibitors or drugs targeting various proteins or enzymes mapped on nine interconnected fatty acid metabolism-related processes. We will discuss the general significance of each of these processes and the effects of their inhibition on cancer cell progression. Moreover, their mechanisms of action, limitations, and future perspectives will be assessed.
    Keywords:  Cancer therapy; Fatty acid desaturation; Fatty acid synthesis; Fatty acid uptake; Fatty acids
    DOI:  https://doi.org/10.1016/j.plipres.2021.101143
  6. J Pharm Biomed Anal. 2021 Nov 25. pii: S0731-7085(21)00596-3. [Epub ahead of print]209 114485
    Experimental design of a stable isotope labeling derivatized UHPLC-MS/MS method for the detection/quantification of primary/secondary bile acids in biofluids.
    Yoshio Muguruma, Ryosuke Nagatomo, Shihori Kamatsuki, Katsuyuki Miyabe, Go Asano, Hiroyasu Akatsu, Koichi Inoue.
      An efficient analytical platform is required to characterize the human metabolome in pathology. For this purpose, ultra-high performance liquid chromatography with tandem mass spectrometry (UHPLC-MS/MS) combined with chemical derivatization stands out as one of the most powerful techniques. A targeted metabolomics platform for 11 bile acids (BAs) profiling in human serum and bile samples using a stable isotope labeling derivatization (SILD) was applied. For SILD, the design of experiments (DoE) was employed to optimize the reaction conditions such five factors in three levels. The sample preparation built upon a liquid-liquid extraction requiring small volumes (20 μL). In application, the relation between the BA and short-chain fatty acid levels in human serum and bile samples from patients with bile duct diseases were investigated. The proposed method offers significant utility in the large-scale biological analyses of hepato-biliary-pancreatic-related diseases.
    Keywords:  Bile; Bile acids; Design of experiments; Serum; Short-chain fatty acids; Stable isotope labeling derivatization; Ultrahigh performance liquid chromatography–tandem mass spectrometry
    DOI:  https://doi.org/10.1016/j.jpba.2021.114485
  7. Nat Rev Drug Discov. 2021 Dec 03.
    Targeting cancer metabolism in the era of precision oncology.
    Zachary E Stine, Zachary T Schug, Joseph M Salvino, Chi V Dang.
      One hundred years have passed since Warburg discovered alterations in cancer metabolism, more than 70 years since Sidney Farber introduced anti-folates that transformed the treatment of childhood leukaemia, and 20 years since metabolism was linked to oncogenes. However, progress in targeting cancer metabolism therapeutically in the past decade has been limited. Only a few metabolism-based drugs for cancer have been successfully developed, some of which are in - or en route to - clinical trials. Strategies for targeting the intrinsic metabolism of cancer cells often did not account for the metabolism of non-cancer stromal and immune cells, which have pivotal roles in tumour progression and maintenance. By considering immune cell metabolism and the clinical manifestations of inborn errors of metabolism, it may be possible to isolate undesirable off-tumour, on-target effects of metabolic drugs during their development. Hence, the conceptual framework for drug design must consider the metabolic vulnerabilities of non-cancer cells in the tumour immune microenvironment, as well as those of cancer cells. In this Review, we cover the recent developments, notable milestones and setbacks in targeting cancer metabolism, and discuss the way forward for the field.
    DOI:  https://doi.org/10.1038/s41573-021-00339-6
  8. J Lipid Res. 2020 Jun;pii: S0022-2275(20)43592-8. [Epub ahead of print]61(6): 809-814
    Phosphatidylinositol metabolism, phospholipases, lipidomics, and cancer: In Memoriam: Michael J. O. Wakelam (1955-2020).
    Edward A Dennis, Valerie B O'Donnell.
      
    DOI:  https://doi.org/10.1194/jlr.T120000868
  9. Nat Methods. 2021 Dec 02.
    Spectral entropy outperforms MS/MS dot product similarity for small-molecule compound identification.
    Yuanyue Li, Tobias Kind, Jacob Folz, Arpana Vaniya, Sajjan Singh Mehta, Oliver Fiehn.
      Compound identification in small-molecule research, such as untargeted metabolomics or exposome research, relies on matching tandem mass spectrometry (MS/MS) spectra against experimental or in silico mass spectral libraries. Most software programs use dot product similarity scores. Here we introduce the concept of MS/MS spectral entropy to improve scoring results in MS/MS similarity searches via library matching. Entropy similarity outperformed 42 alternative similarity algorithms, including dot product similarity, when searching 434,287 spectra against the high-quality NIST20 library. Entropy similarity scores proved to be highly robust even when we added different levels of noise ions. When we applied entropy levels to 37,299 experimental spectra of natural products, false discovery rates of less than 10% were observed at entropy similarity score 0.75. Experimental human gut metabolome data were used to confirm that entropy similarity largely improved the accuracy of MS-based annotations in small-molecule research to false discovery rates below 10%, annotated new compounds and provided the basis to automatically flag poor-quality, noisy spectra.
    DOI:  https://doi.org/10.1038/s41592-021-01331-z
  10. Anal Chem. 2021 Dec 03.
    Kendrick Mass Defect Variation to Decipher Isotopic Labeling in Brain Metastases Studied by Mass Spectrometry Imaging.
    Landry Blanc, Gino B Ferraro, Michael Tuck, Brendan Prideaux, Véronique Dartois, Rakesh K Jain, Nicolas Desbenoit.
      Besides many other applications, isotopic labeling is commonly used to decipher the metabolism of living biological systems. By giving a stable isotopically labeled compound as a substrate, the biological system will use this labeled nutrient as it would with a regular substrate and incorporate stable heavy atoms into new metabolites. Utilizing mass spectrometry, by comparing heavy atom enriched isotopic profiles and naturally occurring ones, it is possible to identify these metabolites and deduce valuable information about metabolism and biochemical pathways. The coupling of this approach with mass spectrometry imaging (MSI) allows one then to obtain 2D maps of metabolisms used by living specimens. As metabolic networks are convoluted, a global overview of the isotopically labeled data set to detect unexpected metabolites is crucial. Unfortunately, due to the complexity of MSI spectra, such untargeted processing approaches are difficult to decipher. In this technical note, we demonstrate the potential of a variation around the Kendrick analysis concept to detect the incorporation of stable heavy atoms into metabolites. The Kendrick analysis uses as a base unit the difference between the mass of the most abundant isotope and the mass of the corresponding stable isotopic tracer (namely, 12C and 13C). The resulting Kendrick plot offers an alternative method to process the MSI data set with a new perspective allowing for the rapid detection of the 13C-enriched metabolites and separating unrelated compounds. This processing method of MS data could therefore be a useful tool to decipher isotopic labeling and study metabolic networks, especially as it does not require advanced computational capabilities.
    DOI:  https://doi.org/10.1021/acs.analchem.1c03916
  11. Front Oncol. 2021 ;11 759015
    Metabolic Reprogramming in the Tumor Microenvironment With Immunocytes and Immune Checkpoints.
    Yaolin Xu, Lijie He, Qiang Fu, Junzhe Hu.
      Immune checkpoint inhibitors (ICIs), Ipilimumab, Nivolumab, Pembrolizumab and Atezolizumab, have been applied in anti-tumor therapy and demonstrated exciting performance compared to conventional treatments. However, the unsatisfactory response rates, high recurrence and adaptive resistance limit their benefits. Metabolic reprogramming appears to be one of the crucial barriers to immunotherapy. The deprivation of required nutrients and altered metabolites not only promote tumor progression but also confer dysfunction on immune cells in the tumor microenvironment (TME). Glycolysis plays a central role in metabolic reprogramming and immunoregulation in the TME, and many therapies targeting glycolysis have been developed, and their combinations with ICIs are in preclinical and clinical trials. Additional attention has been paid to the role of amino acids, lipids, nucleotides and mitochondrial biogenesis in metabolic reprogramming and clinical anti-tumor therapy. This review attempts to describe reprogramming metabolisms within tumor cells and immune cells, from the aspects of glycolysis, amino acid metabolism, lipid metabolism, nucleotide metabolism and mitochondrial biogenesis and their impact on immunity in the TME, as well as the significance of targeting metabolism in anti-tumor therapy, especially in combination with ICIs. In particular, we highlight the expression mechanism of programmed cell death (ligand) 1 [PD-(L)1] in tumor cells and immune cells under reprogramming metabolism, and discuss in detail the potential of targeting key metabolic pathways to break resistance and improve the efficacy of ICIs based on results from current preclinical and clinical trials. Besides, we draw out biomarkers of potential predictive value in ICIs treatment from a metabolic perspective.
    Keywords:  PD-1; amino acid metabolism; glycolysis; immune checkpoints; lipid metabolism; mitochondrial biogenesis; nucleotide metabolism; the tumor microenvironment
    DOI:  https://doi.org/10.3389/fonc.2021.759015
  12. Cancer Manag Res. 2021 ;13 8865-8878
    Serum Untargeted UHPLC-HRMS-Based Lipidomics to Discover the Potential Biomarker of Colorectal Advanced Adenoma.
    Yifan Zhu, Lisheng Wang, Yanying Nong, Yunxiao Liang, Zongsheng Huang, Pingchuan Zhu, Qisong Zhang.
      Background: As a key precancerous lesion, colorectal advanced adenoma (CAA) is closely related to the occurrence and development of colorectal cancer (CRC). Effective identification of CAA-related biomarkers can prevent CRC morbidity and mortality. Lipids, as an important endogenous substance, have been proved to be involved in the occurrence and development of CRC. Lipidomics is an advanced technique that studies lipid metabolism and biomarkers of diseases. However, there are no lipidomics studies based on large serum samples to explore diagnostic biomarkers for CAA.Methods: An integrated serum lipid profile from 50 normal (NR) and 46 CAA subjects was performed using ultra-high performance liquid chromatography tandem high-resolution mass spectrometry (UHPLC-HRMS). Lipidomic data were acquired for negative and positive ionization modes, respectively. Differential lipids were selected by univariate and multivariate statistics analyses. A receiver operator characteristic curve (ROC) analysis was conducted to evaluate the diagnostic performance of differential lipids.
    Results: A total of 53 differential lipids were obtained by combining univariate and multivariate statistical analyses (P < 0.05 and VIP > 1). In addition, 12 differential lipids showed good diagnostic performance (AUC > 0.90) for the discrimination of NR and CAA by receiver operating characteristic curve (ROC) analysis. Of them, the performance of PC 44:5 and PC 35:6e presented the outstanding performance (AUC = 1.00, (95% CI, 1.00-1.00)). Moreover, triglyceride (TAG) had the highest proportion (37.74%) as the major dysregulated lipids in the CAA.
    Conclusion: This is the first study that profiled serum lipidomics and explored lipid biomarkers with good diagnostic ability of CAA to contribute to the early prevention of CRC. Twelve differential lipids that effectively discriminate between NR and CAA serve as the potential diagnostic markers of CAA. An obvious perturbation of TAG metabolism could be involved in the CAA formation.
    Keywords:  UHPLC-HRMS; biomarker; colorectal advanced adenoma; colorectal cancer; serum lipidomics
    DOI:  https://doi.org/10.2147/CMAR.S336322
  13. Nat Metab. 2021 Nov 29.
    Serine catabolism generates liver NADPH and supports hepatic lipogenesis.
    Zhaoyue Zhang, Tara TeSlaa, Xincheng Xu, Xianfeng Zeng, Lifeng Yang, Gang Xing, Gregory J Tesz, Michelle F Clasquin, Joshua D Rabinowitz.
      Carbohydrate can be converted into fat by de novo lipogenesis, a process upregulated in fatty liver disease. Chemically, de novo lipogenesis involves polymerization and reduction of acetyl-CoA, using NADPH as the electron donor. The feedstocks used to generate acetyl-CoA and NADPH in lipogenic tissues remain, however, unclear. Here we show using stable isotope tracing in mice that de novo lipogenesis in adipose is supported by glucose and its catabolism via the pentose phosphate pathway to make NADPH. The liver, in contrast, derives acetyl-CoA for lipogenesis from acetate and lactate, and NADPH from folate-mediated serine catabolism. Such NADPH generation involves the cytosolic serine pathway in liver running in the opposite direction to that observed in most tissues and tumours, with NADPH made by the SHMT1-MTHFD1-ALDH1L1 reaction sequence. SHMT inhibition decreases hepatic lipogenesis. Thus, liver folate metabolism is distinctively wired to support cytosolic NADPH production and lipogenesis. More generally, while the same enzymes are involved in fat synthesis in liver and adipose, different substrates are used, opening the door to tissue-specific pharmacological interventions.
    DOI:  https://doi.org/10.1038/s42255-021-00487-4
  14. Expert Rev Proteomics. 2021 Nov 30.
    Mass Spectrometry based Metabolomics for Small Molecule Metabolites Mining and Confirmation as Potential Biomarkers for Schistosomiasis - Case of the Okavango Delta Communities in Botswana.
    Sedireng M Ndolo, Matshediso Zachariah, Lebotse Molefi, Nthabiseng Phaladze, Kwenga F Sichilongo.
      INTRODUCTION: Metabolomics for identifying schistosomiasis biomarkers in non-invasive samples at various infection stages is being actively explored. The literature on the traditional detection of schistosomiasis in human specimens is well documented. However, state-of-the-art technologies based on mass spectrometry have simplified the use of biomarkers for diagnostics. This review examines methods currently in use for the metabolomics of small molecules using separation science and mass spectrometry.AREA COVERED: This article highlights the evolution of traditional diagnostic methods for schistosomiasis based on inter alia microscopy, immunology, and polymerase chain reaction. An exhaustive literature search of metabolite mining, focusing on separation science and mass spectrometry, is presented. A comparative analysis of mass spectrometry methods was undertaken, including a projection for the future.
    EXPERT COMMENTARY: Mass spectrometry metabolomics for schistosomiasis will lead to biomarker discovery for non-invasive human samples. These biomarkers, together with those from other neglected tropical diseases, such as malaria and sleeping sickness, could be incorporated as arrays on a single biosensor chip and inserted into smartphones, in order to improve surveillance, monitoring, and management.
    Keywords:  Biomarker; Botswana; GC-MS; LC-MS; Mass Spectrometry; Metabolomics; Okavango Delta; Schistosomiasis
    DOI:  https://doi.org/10.1080/14789450.2021.2012454
  15. Metab Eng. 2021 Nov 25. pii: S1096-7176(21)00177-4. [Epub ahead of print]
    Elucidating tumor-stromal metabolic crosstalk in colorectal cancer through integration of constraint-based models and LC-MS metabolomics.
    Junmin Wang, Alireza Delfarah, Patrick Gelbach, Emma Fong, Paul Macklin, Shannon M Mumenthaler, Nicholas A Graham, Stacey Finley.
      Colorectal cancer (CRC) is a major cause of morbidity and mortality in the United States. Tumor-stromal metabolic crosstalk in the tumor microenvironment promotes CRC development and progression, but exactly how stromal cells, in particular cancer-associated fibroblasts (CAFs), affect the metabolism of tumor cells remains unknown. Here we take a data-driven approach to investigate the metabolic interactions between CRC cells and CAFs, integrating constraint-based modeling and metabolomic profiling. Using metabolomics data, we perform unsteady-state parsimonious flux balance analysis to infer flux distributions for central carbon metabolism in CRC cells treated with or without CAF-conditioned media. We find that CAFs reprogram CRC metabolism through stimulation of glycolysis, the oxidative arm of the pentose phosphate pathway (PPP), and glutaminolysis as well as inhibition of the tricarboxylic acid cycle. To identify potential therapeutic targets, we simulate enzyme knockouts and find that CAF-treated CRC cells are especially sensitive to inhibitions of hexokinase and glucose-6-phosphate, the rate limiting steps of glycolysis and oxidative PPP. Our work gives mechanistic insights into the metabolic interactions between CRC cells and CAFs and provides a framework for testing hypotheses towards CRC-targeted therapies.
    Keywords:  Flux balance analysis; Mathematical biosciences; Metabolomics; Systems biology; Tumor microenvironment
    DOI:  https://doi.org/10.1016/j.ymben.2021.11.006
  16. Proc Natl Acad Sci U S A. 2021 Dec 07. pii: e2109633118. [Epub ahead of print]118(49):
    Accelerating strain phenotyping with desorption electrospray ionization-imaging mass spectrometry and untargeted analysis of intact microbial colonies.
    Berkley M Ellis, Piyoosh K Babele, Jody C May, Carl H Johnson, Brian F Pfleger, Jamey D Young, John A McLean.
      Reading and writing DNA were once the rate-limiting step in synthetic biology workflows. This has been replaced by the search for the optimal target sequences to produce systems with desired properties. Directed evolution and screening mutant libraries are proven technologies for isolating strains with enhanced performance whenever specialized assays are available for rapidly detecting a phenotype of interest. Armed with technologies such as CRISPR-Cas9, these experiments are capable of generating libraries of up to 1010 genetic variants. At a rate of 102 samples per day, standard analytical methods for assessing metabolic phenotypes represent a major bottleneck to modern synthetic biology workflows. To address this issue, we have developed a desorption electrospray ionization-imaging mass spectrometry screening assay that directly samples microorganisms. This technology increases the throughput of metabolic measurements by reducing sample preparation and analyzing organisms in a multiplexed fashion. To further accelerate synthetic biology workflows, we utilized untargeted acquisitions and unsupervised analytics to assess multiple targets for future engineering strategies within a single acquisition. We demonstrate the utility of the developed method using Escherichia coli strains engineered to overproduce free fatty acids. We determined discrete metabolic phenotypes associated with each strain, which include the primary fatty acid product, secondary products, and additional metabolites outside the engineered product pathway. Furthermore, we measured changes in amino acid levels and membrane lipid composition, which affect cell viability. In sum, we present an analytical method to accelerate synthetic biology workflows through rapid, untargeted, and multiplexed metabolomic analyses.
    Keywords:  DESI-IMS; free fatty acid profiling; imaging mass spectrometry; multiplexed metabolomics; synthetic biology
    DOI:  https://doi.org/10.1073/pnas.2109633118
  17. Cancer Discov. 2021 Dec 03. pii: candisc.0522.2021. [Epub ahead of print]
    Pharmacological reduction of mitochondrial iron triggers a non-canonical BAX/BAK dependent cell death.
    Sylvain Garciaz, Andrew A Guirguis, Sebastian Muller, Fiona C Brown, Yih-Chih Chan, Ali Motazedian, Caitlin L Rowe, James A Kuzich, Kah Lok Chan, Kevin Tran, Lorey Smith, Laura MacPherson, Brian Liddicoat, Enid Y N Lam, Tatiana Caneque, Marian L Burr, Veronique Litalien, Giovanna Pomilio, Mathilde Poplineau, Estelle Duprez, Sarah-Jane Dawson, Georg Ramm, Andrew G Cox, Kristin K Brown, David C S Huang, Andrew H Wei, Kate McArthur, Raphael Rodriguez, Mark A Dawson.
      Cancer cell metabolism is increasingly recognised as providing an exciting therapeutic opportunity. However, a drug that directly couples targeting of a metabolic dependency with the induction of cell death in cancer cells has largely remained elusive. Here we report that the drug-like small molecule ironomycin (AM5) reduces the mitochondrial iron load, resulting in the potent disruption of mitochondrial metabolism. Ironomycin promotes the recruitment and activation of BAX/BAK but the resulting mitochondrial outer membrane permeabilization (MOMP) does not lead to potent activation of the apoptotic caspases, nor is the ensuing cell death prevented by inhibiting the previously established pathways of programmed cell death. Consistent with the fact that ironomycin and BH3 mimetics induce MOMP through independent non-redundant pathways, we find that ironomycin exhibits marked in vitro and in vivo synergy with venetoclax and overcomes venetoclax resistance in primary patient samples.
    DOI:  https://doi.org/10.1158/2159-8290.CD-21-0522
  18. Mass Spectrom Rev. 2021 Dec 02. e21763
    Collision energies: Optimization strategies for bottom-up proteomics.
    Ágnes Révész, Helga Hevér, Arnold Steckel, Gitta Schlosser, Dániel Szabó, Károly Vékey, László Drahos.
      Mass-spectrometry coupled to liquid chromatography is an indispensable tool in the field of proteomics. In the last decades, more and more complex and diverse biochemical and biomedical questions have arisen. Problems to be solved involve protein identification, quantitative analysis, screening of low abundance modifications, handling matrix effect, and concentrations differing by orders of magnitude. This led the development of more tailored protocols and problem centered proteomics workflows, including advanced choice of experimental parameters. In the most widespread bottom-up approach, the choice of collision energy in tandem mass spectrometric experiments has outstanding role. This review presents the collision energy optimization strategies in the field of proteomics which can help fully exploit the potential of MS based proteomics techniques. A systematic collection of use case studies is then presented to serve as a starting point for related further scientific work. Finally, this article discusses the issue of comparing results from different studies or obtained on different instruments, and it gives some hints on methodology transfer between laboratories based on measurement of reference species.
    Keywords:  bottom-up proteomics; collision energy optimization; instrument transferability; peptide fragmentation
    DOI:  https://doi.org/10.1002/mas.21763
  19. J Lipid Res. 2021 Nov 24. pii: S0022-2275(21)00137-1. [Epub ahead of print] 100154
    1-deoxysphinganine initiates adaptive responses to serine and glycine starvation in cancer cells via proteolysis of sphingosine kinase.
    Jean-Philip Truman, Christian F Ruiz, Emily Montal, Monica Garcia-Barros, Izolda Mileva, Ashley J Snider, Yusuf A Hannun, Lina M Obeid, Cungui Mao.
      Cancer cells can become dependent on exogenous serine, depletion of which results in slower growth and activation of a number of adaptive metabolic changes. We previously demonstrated that serine and glycine (SG) deprivation causes loss of sphingosine kinase 1 (SK1) in cancer cells, thereby increasing levels of its lipid substrate, sphingosine (Sph), which mediates several adaptive biological responses. However, the signaling molecules that regulate levels of SK1 and Sph in response to SG deprivation have yet to be defined. Here, we identify 1-deoxysphinganine (dSA), a non-canonical sphingoid base generated in the absence of serine from the alternative condensation of alanine and palmitoyl CoA by serine palmitoyl transferase (SPT), as a proximal mediator of SG deprivation in SK1 loss and Sph level elevation in SG deprivation in cancer cells. SG starvation markedly increased dSA levels in vitro and in vivo, and in turn induced SK1 degradation through a SPT-dependent mechanism, resulting in an increase in SPH levels. Addition of exogenous dSA caused a moderate increase in intracellular reactive oxygen species (ROS), which in turn decreased pyruvate kinase PKM2 activity while increasing phosphoglycerate dehydrogenase (PHGDH) levels, and thereby promoted serine synthesis. We further showed that increased dSA induces the adaptive cellular and metabolic functions in the response of cells to decreased availability of serine likely by increasing Sph levels. Thus, we conclude that dSA functions as an initial sensor of serine loss, SK1 functions as its direct target, and Sph functions as a downstream effector of cellular and metabolic adaptations. These studies define a previously unrecognized 'physiological' non-toxic function for dSA.
    Keywords:  Sphingosine kinase; hereditary sensory and autonomic neuropathy (HSAN); mass spectrometry; phosphoglycerate dehydrogenase (PHGDH); pyruvate kinase (PKM2); reactive oxygen species (ROS); serine biosynthesis; serine palmitoyl transferase (SPT); sphingosine; ubiquitination
    DOI:  https://doi.org/10.1016/j.jlr.2021.100154
  20. Mass Spectrom Rev. 2021 Nov 28. e21757
    Tandem mass spectrometry approaches for recognition of isomeric compounds mixtures.
    Sara Crotti, Marta Menicatti, Marco Pallecchi, Gianluca Bartolucci.
      The present review aims to collect the published literature pertaining the recognition of isobaric compounds (isomers or stereoisomers) using the features of tandem mass spectrometry (MS) experiments without any chromatographic separation or chemical modification (derivatization or isotopic enrichment) of the analytes. MS/MS methods possess high selectivity, wide dynamic range and high throughput capabilities. Generally, tandem MS has limited capability for distinguishing isomers that fragment similarly. However, some MS/MS methods have been developed and positively applied to isomers discrimination. Among the literature on this topic, the applications that fit on the review subject can be summarized as follow: (1) chiral discrimination by the kinetic method, (2) the use energy-resolved tandem mass spectra and the survival yield (SY) representation, (3) the kinetics evaluation of the ion-molecule interaction and (4) the postprocessing mathematical algorithm to resolve the isomers in MS/MS signal.
    Keywords:  LEDA; MS/MS; ion-molecule interaction; isomers; kinetic method; survival yield
    DOI:  https://doi.org/10.1002/mas.21757
  21. Anal Chim Acta. 2022 Jan 15. pii: S0003-2670(21)01086-2. [Epub ahead of print]1190 339260
    Neutron encoded derivatization of endothelial cell lysates for quantitation of aldehyde metabolites using nESI-LC-HRMS.
    Michael Armbruster, Scott Grady, Julius Agongo, Christopher K Arnatt, James L Edwards.
      Biological aldehydes are difficult to analyze by electrospray ionization mass spectrometry due to their poor proton affinity and low biological concentrations. Chemical derivatization with stable isotope tags is used here for sample multiplexing, increased throughput, improved signal intensity, and quantitation. Nine quaternary amine tags with mass differences as low as 0.0058 Da had no observable chromatographic shifts, small amounts of ion suppression, and minimal matrix effects. Low concentration perfluoropentanoic acid was used as an ion pairing reagent to improve the retention of derivatized aldehydes. Perfluoropentanoic acid addition showed an average of three-fold improvement in limits of detection, 50% reduction in peak width, and 2.5 fold increase in analyte retention. Analysis of fifteen tagged aldehydes yielded an average of 13 nM limit of detection, 9 %RSD, R2 of 0.995, and linear dynamic range of 40-1000 nM. In a single 20 min separation, absolute quantitative data was obtained for 11 reactive aldehydes across 8 aortic endothelial cell samples. High glucose treatment produced significant changes to malondialdehyde, decanal, and (2E)-hexadecenal. These changes are consistent with glucose-induced oxidative stress. This method demonstrates that neutron encoded tagging of aldehydes is suitable for the analysis of complex samples.
    Keywords:  Aldehyde; Derivatization; Multiplex; NeuCode
    DOI:  https://doi.org/10.1016/j.aca.2021.339260
  22. Cancer Metab. 2021 Dec 03. 9(1): 40
    ASS1 and ASL suppress growth in clear cell renal cell carcinoma via altered nitrogen metabolism.
    Sanika Khare, Laura C Kim, Graham Lobel, Paschalis-Thomas Doulias, Harry Ischiropoulos, Itzhak Nissim, Brian Keith, M Celeste Simon.
      BACKGROUND: Kidney cancer is a common adult malignancy in the USA. Clear cell renal cell carcinoma (ccRCC), the predominant subtype of kidney cancer, is characterized by widespread metabolic changes. Urea metabolism is one such altered pathway in ccRCC. The aim of this study was to elucidate the contributions of urea cycle enzymes, argininosuccinate synthase 1 (ASS1), and argininosuccinate lyase (ASL) towards ccRCC progression.METHODS: We employed a combination of computational, genetic, and metabolomic tools along with in vivo animal models to establish a tumor-suppressive role for ASS1 and ASL in ccRCC.
    RESULTS: We show that the mRNA and protein expression of urea cycle enzymes ASS1 and ASL are reduced in ccRCC tumors when compared to the normal kidney. Furthermore, the loss of ASL in HK-2 cells (immortalized renal epithelial cells) promotes growth in 2D and 3D growth assays, while combined re-expression of ASS1 and ASL in ccRCC cell lines suppresses growth in 2D, 3D, and in vivo xenograft models. We establish that this suppression is dependent on their enzymatic activity. Finally, we demonstrate that conservation of cellular aspartate, regulation of nitric oxide synthesis, and pyrimidine production play pivotal roles in ASS1+ASL-mediated growth suppression in ccRCC.
    CONCLUSIONS: ccRCC tumors downregulate the components of the urea cycle including the enzymes argininosuccinate synthase 1 (ASS1) and argininosuccinate lyase (ASL). These cytosolic enzymes lie at a critical metabolic hub in the cell and are involved in aspartate catabolism and arginine and nitric oxide biosynthesis. Loss of ASS1 and ASL helps cells redirect aspartate towards pyrimidine synthesis and support enhanced proliferation. Additionally, reduced levels of ASS1 and ASL might help regulate nitric oxide (NO) generation and mitigate its cytotoxic effects. Overall, our work adds to the understanding of urea cycle enzymes in a context-independent of ureagenesis, their role in ccRCC progression, and uncovers novel potential metabolic vulnerabilities in ccRCC.
    Keywords:  Argininosuccinate lyase; Argininosuccinate synthase 1; Aspartate; DNA synthesis; Nitric oxide metabolism; Urea cycle; ccRCC
    DOI:  https://doi.org/10.1186/s40170-021-00271-8
  23. J Proteome Res. 2021 Nov 29.
    Comparison of Microflow and Analytical Flow Liquid Chromatography Coupled to Mass Spectrometry Global Metabolomics Methods Using a Urea Cycle Disorder Mouse Model.
    Sarah Geller, Harvey Lieberman, Adam J Belanger, Nelson S Yew, Alla Kloss, Alexander R Ivanov.
      Microscale-based separations are increasingly being applied in the field of metabolomics for the analysis of small-molecule metabolites. These methods have the potential to provide improved sensitivity, less solvent waste, and reduced sample-size requirements. Ion-pair free microflow-based global metabolomics methods, which we recently reported, were further compared to analytical flow ion-pairing reagent containing methods using a sample set from a urea cycle disorder (UCD) mouse model. Mouse urine and brain homogenate samples representing healthy, diseased, and disease-treated animals were analyzed by both methods. Data processing was performed using univariate and multivariate techniques followed by analyte trend analysis. The microflow methods performed comparably to the analytical flow ion-pairing methods with the ability to separate the three sample groups when analyzed by partial least-squares analysis. The number of detected metabolic features present after each data processing step was similar between the microflow-based methods and the ion-pairing methods in the negative ionization mode. The observed analyte trend and coverage of known UCD biomarkers were the same for both evaluated approaches. The 12.5-fold reduction in sample injection volume required for the microflow-based separations highlights the potential of this method to support studies with sample-size limitations.
    Keywords:  LC-MS; metabolic profiling; metabolomics; microbore columns; microflow LC
    DOI:  https://doi.org/10.1021/acs.jproteome.1c00628
  24. Nat Methods. 2021 Dec 03.
    GNPS Dashboard: collaborative exploration of mass spectrometry data in the web browser.
    Daniel Petras, Vanessa V Phelan, Deepa Acharya, Andrew E Allen, Allegra T Aron, Nuno Bandeira, Benjamin P Bowen, Deirdre Belle-Oudry, Simon Boecker, Dale A Cummings, Jessica M Deutsch, Eoin Fahy, Neha Garg, Rachel Gregor, Jo Handelsman, Mirtha Navarro-Hoyos, Alan K Jarmusch, Scott A Jarmusch, Katherine Louie, Katherine N Maloney, Michael T Marty, Michael M Meijler, Itzhak Mizrahi, Rachel L Neve, Trent R Northen, Carlos Molina-Santiago, Morgan Panitchpakdi, Benjamin Pullman, Aaron W Puri, Robin Schmid, Shankar Subramaniam, Monica Thukral, Felipe Vasquez-Castro, Pieter C Dorrestein, Mingxun Wang.
      
    DOI:  https://doi.org/10.1038/s41592-021-01339-5
  25. Nat Biotechnol. 2021 Dec 02.
    Personalized phosphoproteomics identifies functional signaling.
    Elise J Needham, Janne R Hingst, Benjamin L Parker, Kaitlin R Morrison, Guang Yang, Johan Onslev, Jonas M Kristensen, Kurt Højlund, Naomi X Y Ling, Jonathan S Oakhill, Erik A Richter, Bente Kiens, Janni Petersen, Christian Pehmøller, David E James, Jørgen F P Wojtaszewski, Sean J Humphrey.
      Protein phosphorylation dynamically integrates environmental and cellular information to control biological processes. Identifying functional phosphorylation amongst the thousands of phosphosites regulated by a perturbation at a global scale is a major challenge. Here we introduce 'personalized phosphoproteomics', a combination of experimental and computational analyses to link signaling with biological function by utilizing human phenotypic variance. We measure individual subject phosphoproteome responses to interventions with corresponding phenotypes measured in parallel. Applying this approach to investigate how exercise potentiates insulin signaling in human skeletal muscle, we identify both known and previously unidentified phosphosites on proteins involved in glucose metabolism. This includes a cooperative relationship between mTOR and AMPK whereby the former directly phosphorylates the latter on S377, for which we find a role in metabolic regulation. These results establish personalized phosphoproteomics as a general approach for investigating the signal transduction underlying complex biology.
    DOI:  https://doi.org/10.1038/s41587-021-01099-9
  26. Lipids Health Dis. 2021 Nov 27. 20(1): 169
    15-Lipoxygenase and its metabolites in the pathogenesis of breast cancer: A double-edged sword.
    Mohammad Amin Vaezi, Banafsheh Safizadeh, Amir Reza Eghtedari, Seyedeh Sara Ghorbanhosseini, Mostafa Rastegar, Vahid Salimi, Masoumeh Tavakoli-Yaraki.
      15-lipoxygenase is one of the key enzymes for the metabolism of unsaturated fatty acids that its manipulation has been proposed recently as a new molecular target for regulating cancer cell growth. Aberrant expression of 15-lipoxygenase enzyme seems to play an indicative role in the pathology of different cancer types, tumor progression, metastasis, or apoptosis. Based on the fact that breast cancer is one of the most common cancers that imposes a burden of mortality in women also, on the other hand, evidence in experimental models and human studies indicate the emerging role of the 15-lipoxygenase pathway in breast cancer pathogenesis, we present a review of recent findings related to the role of 15- lipoxygenase enzyme and metabolites in breast cancer growth, apoptosis, metastasis, and invasion as well as their local and circulating expression pattern in patients with breast cancer. Our review supports the emerging role of 15- lipoxygenase in molecular and cellular processes regulating breast tumor cell fate with both positive and negative effects.
    Keywords:  15-lipoxygenase-1; 15-lipoxygenase-2; Apoptosis; Breast cancer; Cell growth; Metastasis
    DOI:  https://doi.org/10.1186/s12944-021-01599-2
  27. Science. 2021 Dec 03. 374(6572): 1227-1237
    Fumarate is a terminal electron acceptor in the mammalian electron transport chain.
    Jessica B Spinelli, Paul C Rosen, Hans-Georg Sprenger, Anna M Puszynska, Jessica L Mann, Julian M Roessler, Andrew L Cangelosi, Antonia Henne, Kendall J Condon, Tong Zhang, Tenzin Kunchok, Caroline A Lewis, Navdeep S Chandel, David M Sabatini.
      [Figure: see text].
    DOI:  https://doi.org/10.1126/science.abi7495
  28. J Proteome Res. 2021 Dec 01.
    Targeted Metabolomics Reveals Birth Screening Biomarkers for Biliary Atresia in Dried Blood Spots.
    Yongtao Xiao, Ying Zhou, Kejun Zhou, Wei Cai.
      Early diagnosis and timely surgical Kasai portoenterostomy greatly improve the survival of patients with biliary atresia (BA), a neonatal cholestatic disease, which has encouraged investigators to develop newborn screening for BA. In this study, we used ultraperformance liquid chromatography-triple quadrupole mass spectrometry-based targeted metabolomics profiling to identify potential BA biomarkers in dried blood spots (DBS) collected from BA patients (n = 21) and healthy controls (n = 100). A distinctive metabolic profile comprising eight significantly differentially expressed metabolites, taurohyocholic acid (THCA), glutamic acid, 2-hydroxyglutaric acid, ketoleucine, indoleacetic acid, alpha-ketoisovaleric acid, glycocholic acid, and taurocholic acid (TCA), clearly distinguished BA infants from control neonates. Three metabolites, THCA, 2-hydroxyglutaric acid, and indoleacetic acid, were selected using linear regression and receiver operating characteristic (ROC) curve analysis and model construction. The area under the ROC curve for this model to discriminate between BA and comparison infants was 0.938 (95% confidence interval, CI: 0.874-1.000). A cutoff value of -0.336 produced a sensitivity of 90.48% (95% CI: 69.62% - 98.83%) and specificity of 92% (95% CI: 84.84% - 96.48%). In conclusion, the results suggest that metabolic markers in DBS obtained from newborns have a great potential for BA screening.
    Keywords:  biliary atresia; biomarkers; dried blood spots; metabolomics
    DOI:  https://doi.org/10.1021/acs.jproteome.1c00775
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