bims-mascan 2022-05-22 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2022–05–22
25 papers selected by
Giovanny Rodriguez Blanco, University of Edinburgh

Trapped ion mobility spectrometry-mass spectrometry improves the coverage and accuracy of four-dimensional untargeted lipidomics.
The structural context of posttranslational modifications at a proteome-wide scale.
A Mass Spectrometry-Based Proteomics Approach for Global and High-Confidence Protein R-Methylation Analysis.
Proteomic Analysis of Human Neural Stem Cell Differentiation by SWATH-MS.
PHGDH heterogeneity potentiates cancer cell dissemination and metastasis.
IDSL.IPA Characterizes the Organic Chemical Space in Untargeted LC/HRMS Data Sets.
Dynamic human liver proteome atlas reveals functional insights into disease pathways.
Low and high resolution gas chromatography-mass spectrometry for untargeted metabolomics: A tutorial.
Direct anabolic metabolism of three carbon propionate to a six carbon metabolite occurs in vivo across tissues and species.
Aspartate metabolism in endothelial cells activates the mTORC1 pathway to initiate translation during angiogenesis.
Advanced nanomedicines for the regulation of cancer metabolism.
Gas chromatography-mass spectrometry-based untargeted metabolomics reveals metabolic perturbations in medullary thyroid carcinoma.
Mitochondria preserve an autarkic one-carbon cycle to confer growth-independent cancer cell migration and metastasis.
Evaluation of Fatty Acid Oxidation in Cultured Bone Cells.
Metabolic Reprogramming in Cholangiocarcinoma.
Prolonged deprivation of arginine or leucine induces PI3K/Akt-dependent reactivation of mTORC1.
Metabolic reprogramming as an emerging mechanism of resistance to endocrine therapies in prostate cancer.
Pyruvate kinase M1 suppresses development and progression of prostate adenocarcinoma.
Deep Visual Proteomics defines single-cell identity and heterogeneity.
Application of Immunoaffinity Mass Spectrometry (IA-MS) for Protein Biomarker Quantification.
Role of fatty acid transport protein 4 in metabolic tissues: insights into obesity and fatty liver disease.
Profiling Sequence Specificity of Proteolytic Activities Using Proteome-Derived Peptide Libraries.
Development and application of a fast ultra-high performance liquid chromatography-trapped ion mobility mass spectrometry method for untargeted lipidomics.
Purine nucleotide depletion prompts cell migration by stimulating the serine synthesis pathway.
Optimized sample preparation and data analysis for TMT proteomic analysis of cerebrospinal fluid applied to the identification of Alzheimer's disease biomarkers.

Anal Chim Acta. 2022 Jun 01. pii: S0003-2670(22)00457-3. [Epub ahead of print]1210 339886

Trapped ion mobility spectrometry-mass spectrometry improves the coverage and accuracy of four-dimensional untargeted lipidomics.

Xi Chen, Yandong Yin, Mingdu Luo, Zhiwei Zhou, Yuping Cai, Zheng-Jiang Zhu.

  Lipids play vital roles in many physiological and pathological processes in living organisms. Due to the high structural diversity and the numerous isomers and isobars of lipids, high-coverage and high-accuracy lipidomic analysis of complex biological samples remain the bottleneck to investigate lipid metabolism. Here, we developed the trapped ion mobility spectrometry-mass spectrometry (TIMS-MS) based four-dimensional untargeted lipidomics to support accurate lipid identification and quantification in biological samples. We first demonstrated that the TIMS based multi-dimensional separation improved the differentiations of isomeric and isobaric lipids, and increased the purity of precursor ion isolation and the quality of MS/MS spectra. Hyphenation of TIMS and PASEF technologies significantly improved the coverages of MS/MS spectra. These technological advantages jointly improved the coverage and accuracy of lipid identification in untargeted lipidomics. We further demonstrated that the CCS values of lipids acquired using TIMS were highly consistent with those from drift tube ion mobility spectrometry (DTIMS). Lipid identification and quantification results of NIST human plasma samples were also verified with inter-laboratory reports. Finally, we applied the TIMS-MS based untargeted lipidomics to characterize the spatial distributions of 1393 distinctive lipids in the mouse brain, and demonstrated that diverse lipid distributions and compositions among brain regions contributed to different functions of brain regions. Altogether, TIMS-MS based four-dimensional untargeted lipidomics significantly improved the coverage and accuracy of untargeted metabolomics, thereby facilitating a system-level understanding of lipid metabolism in biological organisms.

Keywords:  Isobaric and isomeric lipids; Lipid identification; Trapped ion mobility spectrometry; Untargeted lipidomics

DOI:  https://doi.org/10.1016/j.aca.2022.339886
PLoS Biol. 2022 May 16. 20(5): e3001636

The structural context of posttranslational modifications at a proteome-wide scale.

Isabell Bludau, Sander Willems, Wen-Feng Zeng, Maximilian T Strauss, Fynn M Hansen, Maria C Tanzer, Ozge Karayel, Brenda A Schulman, Matthias Mann.

The recent revolution in computational protein structure prediction provides folding models for entire proteomes, which can now be integrated with large-scale experimental data. Mass spectrometry (MS)-based proteomics has identified and quantified tens of thousands of posttranslational modifications (PTMs), most of them of uncertain functional relevance. In this study, we determine the structural context of these PTMs and investigate how this information can be leveraged to pinpoint potential regulatory sites. Our analysis uncovers global patterns of PTM occurrence across folded and intrinsically disordered regions. We found that this information can help to distinguish regulatory PTMs from those marking improperly folded proteins. Interestingly, the human proteome contains thousands of proteins that have large folded domains linked by short, disordered regions that are strongly enriched in regulatory phosphosites. These include well-known kinase activation loops that induce protein conformational changes upon phosphorylation. This regulatory mechanism appears to be widespread in kinases but also occurs in other protein families such as solute carriers. It is not limited to phosphorylation but includes ubiquitination and acetylation sites as well. Furthermore, we performed three-dimensional proximity analysis, which revealed examples of spatial coregulation of different PTM types and potential PTM crosstalk. To enable the community to build upon these first analyses, we provide tools for 3D visualization of proteomics data and PTMs as well as python libraries for data accession and processing.

DOI: https://doi.org/10.1371/journal.pbio.3001636
J Vis Exp. 2022 Apr 28.

A Mass Spectrometry-Based Proteomics Approach for Global and High-Confidence Protein R-Methylation Analysis.

Marianna Maniaci, Federica Marini, Enrico Massignani, Tiziana Bonaldi.

Protein Arginine (R)-methylation is a widespread protein post-translational modification (PTM) involved in the regulation of several cellular pathways, including RNA processing, signal transduction, DNA damage response, miRNA biogenesis, and translation. In recent years, thanks to biochemical and analytical developments, mass spectrometry (MS)-based proteomics has emerged as the most effective strategy to characterize the cellular methyl-proteome with single-site resolution. However, identifying and profiling in vivo protein R-methylation by MS remains challenging and error-prone, mainly due to the substoichiometric nature of this modification and the presence of various amino acid substitutions and chemical methyl-esterification of acidic residues that are isobaric to methylation. Thus, enrichment methods to enhance the identification of R-methyl-peptides and orthogonal validation strategies to reduce False Discovery Rates (FDR) in methyl-proteomics studies are required. Here, a protocol specifically designed for high-confidence R-methyl-peptides identification and quantitation from cellular samples is described, which couples metabolic labeling of cells with heavy isotope-encoded Methionine (hmSILAC) and dual protease in-solution digestion of whole cell extract, followed by off-line High-pH Reversed Phase (HpH-RP) chromatography fractionation and affinity enrichment of R-methyl-peptides using anti-pan-R-methyl antibodies. Upon high-resolution MS analysis, raw data are first processed with the MaxQuant software package and the results are then analyzed by hmSEEKER, a software designed for the in-depth search of MS peak pairs corresponding to light and heavy methyl-peptide within the MaxQuant output files.

DOI: https://doi.org/10.3791/62409
Methods Mol Biol. 2022 May 18.

Proteomic Analysis of Human Neural Stem Cell Differentiation by SWATH-MS.

Jirina Tyleckova, Jakub Cervenka, Ievgeniia Poliakh, Jaromir Novak, Katerina Vodickova Kepkova, Helena Kupcova Skalnikova, Petr Vodicka.

  The unique properties of stem cells to self-renew and differentiate hold great promise in disease modelling and regenerative medicine. However, more information about basic stem cell biology and thorough characterization of available stem cell lines is needed. This is especially essential to ensure safety before any possible clinical use of stem cells or partially committed cell lines. As proteins are the key effector molecules in the cell, the proteomic characterization of cell lines, cell compartments or cell secretome and microenvironment is highly beneficial to answer above mentioned questions. Nowadays, method of choice for large-scale discovery-based proteomic analysis is mass spectrometry (MS) with data-independent acquisition (DIA). DIA is a robust, highly reproducible, high-throughput quantitative MS approach that enables relative quantification of thousands of proteins in one sample. In the current protocol, we describe a specific variant of DIA known as SWATH-MS for characterization of neural stem cell differentiation. The protocol covers the whole process from cell culture, sample preparation for MS analysis, the SWATH-MS data acquisition on TTOF 5600, the complete SWATH-MS data processing and quality control using Skyline software and the basic statistical analysis in R and MSstats package. The protocol for SWATH-MS data acquisition and analysis can be easily adapted to other samples amenable to MS-based proteomics.

Keywords:  Data independent acquisition; Mass spectrometry; Neural differentiation; Neural stem cell; Proteomics; SWATH-MS; Skyline; Spectral library

DOI:  https://doi.org/10.1007/7651_2022_462
Nature. 2022 May 18.

PHGDH heterogeneity potentiates cancer cell dissemination and metastasis.

Matteo Rossi, Patricia Altea-Manzano, Margherita Demicco, Ginevra Doglioni, Laura Bornes, Marina Fukano, Anke Vandekeere, Alejandro M Cuadros, Juan Fernández-García, Carla Riera-Domingo, Cristina Jauset, Mélanie Planque, H Furkan Alkan, David Nittner, Dongmei Zuo, Lindsay A Broadfield, Sweta Parik, Antonino Alejandro Pane, Francesca Rizzollo, Gianmarco Rinaldi, Tao Zhang, Shao Thing Teoh, Arin B Aurora, Panagiotis Karras, Ines Vermeire, Dorien Broekaert, Joke Van Elsen, Maximilian M L Knott, Martin F Orth, Sofie Demeyer, Guy Eelen, Lacey E Dobrolecki, Ayse Bassez, Thomas Van Brussel, Karl Sotlar, Michael T Lewis, Harald Bartsch, Manfred Wuhrer, Peter van Veelen, Peter Carmeliet, Jan Cools, Sean J Morrison, Jean-Christophe Marine, Diether Lambrechts, Massimiliano Mazzone, Gregory J Hannon, Sophia Y Lunt, Thomas G P Grünewald, Morag Park, Jacco van Rheenen, Sarah-Maria Fendt.

Cancer metastasis requires the transient activation of cellular programs enabling dissemination and seeding in distant organs1. Genetic, transcriptional and translational heterogeneity contributes to this dynamic process2,3. Metabolic heterogeneity has also been observed4, yet its role in cancer progression is less explored. Here we find that the loss of phosphoglycerate dehydrogenase (PHGDH) potentiates metastatic dissemination. Specifically, we find that heterogeneous or low PHGDH expression in primary tumours of patients with breast cancer is associated with decreased metastasis-free survival time. In mice, circulating tumour cells and early metastatic lesions are enriched with Phgdhlow cancer cells, and silencing Phgdh in primary tumours increases metastasis formation. Mechanistically, Phgdh interacts with the glycolytic enzyme phosphofructokinase, and the loss of this interaction activates the hexosamine-sialic acid pathway, which provides precursors for protein glycosylation. As a consequence, aberrant protein glycosylation occurs, including increased sialylation of integrin αvβ3, which potentiates cell migration and invasion. Inhibition of sialylation counteracts the metastatic ability of Phgdhlow cancer cells. In conclusion, although the catalytic activity of PHGDH supports cancer cell proliferation, low PHGDH protein expression non-catalytically potentiates cancer dissemination and metastasis formation. Thus, the presence of PHDGH heterogeneity in primary tumours could be considered a sign of tumour aggressiveness.

DOI: https://doi.org/10.1038/s41586-022-04758-2
J Proteome Res. 2022 May 17.

IDSL.IPA Characterizes the Organic Chemical Space in Untargeted LC/HRMS Data Sets.

Sadjad Fakouri Baygi, Yashwant Kumar, Dinesh Kumar Barupal.

  Generating comprehensive and high-fidelity metabolomics data matrices from LC/HRMS data remains to be extremely challenging for population-scale large studies (n > 200). Here, we present a new data processing pipeline, the Intrinsic Peak Analysis (IDSL.IPA) R package (https://ipa.idsl.me), to generate such data matrices specifically for organic compounds. The IDSL.IPA pipeline incorporates (1) identifying potential 12C and 13C ion pairs in individual mass spectra; (2) detecting and characterizing chromatographic peaks using a new sensitive and versatile approach to perform mass correction, peak smoothing, baseline development for local noise measurement, and peak quality determination; (3) correcting retention time and cross-referencing peaks from multiple samples by a dynamic retention index marker approach; (4) annotating peaks using a reference database of m/z and retention time; and (5) accelerating data processing using a parallel computation of the peak detection and alignment steps for larger studies. This pipeline has been successfully evaluated for studies ranging from 200 to 1600 samples. By specifically isolating high quality and reliable signals pertaining to carbon-containing compounds in untargeted LC/HRMS data sets from larger studies, IDSL.IPA opens new opportunities for discovering new biological insights in the population-scale metabolomics and exposomics projects. The package is available in the R CRAN repository at https://cran.r-project.org/package=IDSL.IPA.

Keywords:  12C/13C isotope pairs; chromatography analysis; mass spectrometry; metabolomics; peak-picking; retention time correction; untargeted analysis

DOI:  https://doi.org/10.1021/acs.jproteome.2c00120
Mol Syst Biol. 2022 May;18(5): e10947

Dynamic human liver proteome atlas reveals functional insights into disease pathways.

Lili Niu, Philipp E Geyer, Rajat Gupta, Alberto Santos, Florian Meier, Sophia Doll, Nicolai J Wewer Albrechtsen, Sabine Klein, Cristina Ortiz, Frank E Uschner, Robert Schierwagen, Jonel Trebicka, Matthias Mann.

  Deeper understanding of liver pathophysiology would benefit from a comprehensive quantitative proteome resource at cell type resolution to predict outcome and design therapy. Here, we quantify more than 150,000 sequence-unique peptides aggregated into 10,000 proteins across total liver, the major liver cell types, time course of primary cell cultures, and liver disease states. Bioinformatic analysis reveals that half of hepatocyte protein mass is comprised of enzymes and 23% of mitochondrial proteins, twice the proportion of other liver cell types. Using primary cell cultures, we capture dynamic proteome remodeling from tissue states to cell line states, providing useful information for biological or pharmaceutical research. Our extensive data serve as spectral library to characterize a human cohort of non-alcoholic steatohepatitis and cirrhosis. Dramatic proteome changes in liver tissue include signatures of hepatic stellate cell activation resembling liver cirrhosis and providing functional insights. We built a web-based dashboard application for the interactive exploration of our resource (www.liverproteome.org).

Keywords:  MS-based proteomics; clinical proteomics; liver disease; liver fibrosis; tissue proteome atlas

DOI:  https://doi.org/10.15252/msb.202210947
Anal Chim Acta. 2022 Jun 01. pii: S0003-2670(21)00869-2. [Epub ahead of print]1210 339043

Low and high resolution gas chromatography-mass spectrometry for untargeted metabolomics: A tutorial.

Fernanda Rey-Stolle, Danuta Dudzik, Carolina Gonzalez-Riano, Miguel Fernández-García, Vanesa Alonso-Herranz, David Rojo, Coral Barbas, Antonia García.

  GC-MS for untargeted metabolomics is a well-established technique. Small molecules and molecules made volatile by derivatization can be measured and those compounds are key players in main biological pathways. This tutorial provides ready-to-use protocols for GC-MS-based metabolomics, using either the well-known low-resolution approach (GC-Q-MS) with nominal mass or the more recent high-resolution approach (GC-QTOF-MS) with accurate mass, discussing their corresponding strengths and limitations. Analytical procedures are covered for different types of biofluids (plasma/serum, bronchoalveolar lavage, urine, amniotic fluid) tissue samples (brain/hippocampus, optic nerve, lung, kidney, liver, pancreas) and samples obtained from cell cultures (adipocytes, macrophages, Leishmania promastigotes, mitochondria, culture media). Together with the sample preparation and data acquisition, data processing strategies are described specially focused on Agilent equipments, including deconvolution software and database annotation using spectral libraries. Manual curation strategies and quality control are also deemed. Finally, considerations to obtain a semiquantitative value for the metabolites are also described. As a case study, an illustrative example from one of our experiments at CEMBIO Research Centre, is described and findings discussed.

Keywords:  Compound identification; GC-MS protocols; High-resolution mass spectrometry; Metabolic fingerprinting; Metabolomics or metabonomics; Spectral library

DOI:  https://doi.org/10.1016/j.aca.2021.339043
J Lipid Res. 2022 May 11. pii: S0022-2275(22)00057-8. [Epub ahead of print] 100224

Direct anabolic metabolism of three carbon propionate to a six carbon metabolite occurs in vivo across tissues and species.

Mary T Doan, Michael D Neinast, Erika L Varner, Kenneth Bedi, David Bartee, Helen Jiang, Sophie Trefely, Peining Xu, Jay P Singh, Cholsoon Jang, Eduardo Rame, Donita Brady, Jordan L Meier, Kenneth Marguiles, Zoltan Arany, Nathaniel W Snyder.

  Anabolic metabolism of carbon in mammals is mediated via the one and two carbon carriers S-adenosyl methionine and acetyl-coenzyme A (acetyl-CoA). In contrast, anabolic metabolism of three-carbon units via propionate has not been shown to extensively occur. Mammals are primarily thought to oxidize the three-carbon short chain fatty acid propionate by shunting propionyl-CoA to succinyl-CoA for entry into the TCA cycle. Here, we found that this may not be absolute as, in mammals, one non-oxidative fate of propionyl-CoA is to condense to two three-carbon units into a six-carbon trans-2-methyl-2-pentenoyl-CoA (2M2PE-CoA). We confirmed this reaction pathway using purified protein extracts provided limited substrates and verified the product via LC-MS using a synthetic standard. In whole-body in vivo stable isotope tracing following infusion of 13C-labeled valine at steady state, 2M2PE-CoA was found to form via propionyl-CoA in multiple murine tissues, including heart, kidney, and to a lesser degree, in brown adipose tissue, liver, and tibialis anterior muscle. Using ex vivo isotope tracing, we found that 2M2PE-CoA also formed in human myocardial tissue incubated with propionate to a limited extent. While the complete enzymology of this pathway remains to be elucidated, these results confirm the in vivo existence of at least one anabolic three to six carbon reaction conserved in humans and mice that utilizes propionate.

Keywords:  2M2PE-CoA; LC-MS/HRMS; Metabolism; TCA cycle; acetyl-CoA; anabolism; condensation reaction; propionate; stable isotope tracing; valine

DOI:  https://doi.org/10.1016/j.jlr.2022.100224
Dev Cell. 2022 May 11. pii: S1534-5807(22)00286-6. [Epub ahead of print]

Aspartate metabolism in endothelial cells activates the mTORC1 pathway to initiate translation during angiogenesis.

Roxana E Oberkersch, Giovanna Pontarin, Matteo Astone, Marianna Spizzotin, Liaisan Arslanbaeva, Giovanni Tosi, Emiliano Panieri, Sara Ricciardi, Maria Francesca Allega, Alessia Brossa, Paolo Grumati, Benedetta Bussolati, Stefano Biffo, Saverio Tardito, Massimo M Santoro.

  Angiogenesis, the active formation of new blood vessels from pre-existing ones, is a complex and demanding biological process that plays an important role in physiological as well as pathological settings. Recent evidence supports cell metabolism as a critical regulator of angiogenesis. However, whether and how cell metabolism regulates endothelial growth factor receptor levels and nucleotide synthesis remains elusive. We here shown in both human cell lines and mouse models that during developmental and pathological angiogenesis, endothelial cells (ECs) use glutaminolysis-derived glutamate to produce aspartate (Asp) via aspartate aminotransferase (AST/GOT). Asp leads to mTORC1 activation which, in turn, regulates endothelial translation machinery for VEGFR2 and FGFR1 synthesis. Asp-dependent mTORC1 pathway activation also regulates de novo pyrimidine synthesis in angiogenic ECs. These findings identify glutaminolysis-derived Asp as a regulator of mTORC1-dependent endothelial translation and pyrimidine synthesis. Our studies may help overcome anti-VEGF therapy resistance by targeting endothelial growth factor receptor translation.

Keywords:  angiogenesis; aspartate metabolism; endothelial metabolism; mTOR signalling; tumor angiogenesis

DOI:  https://doi.org/10.1016/j.devcel.2022.04.018
Biomaterials. 2022 May 07. pii: S0142-9612(22)00205-8. [Epub ahead of print]286 121565

Advanced nanomedicines for the regulation of cancer metabolism.

Jiaying Yang, Yu Zhao, Yanyan Zhou, Xiaolu Wei, Hongjie Wang, Nan Si, Jian Yang, Qinghe Zhao, Baolin Bian, Haiyu Zhao.

  Cancer cells can reprogram metabolic pathways to facilitate proliferation, metastasis, biosynthesis, and chemoresistance. Metabolic reprogramming is currently considered as a hallmark of tumors and is recognized as a promising therapeutic strategy. The recent progress in nanomedicine has greatly improved the therapeutic effect of conventional therapeutic modalities such as surgical treatment, radiotherapy, chemical drug therapy. However, nanomedicine engineering still fails to achieve satisfactory therapeutic effects due to the metabolic reprogramming of tumor cells. The targeted delivery and development of precise therapeutic strategies are the latest focus in tumor metabolism to design nanomedicines according to the characteristics of cancer metabolic reprogramming. Therefore, this review focuses mainly on metabolic pathways of tumors. Pathways such as glycolysis, aerobic respiration, lipid metabolism, nucleotide metabolism, and glutathione metabolism are reviewed in detail. The latest advances are summarized in the design and combined treatment of smart nanomedicines that can regulate cancer metabolism to provide an emerging cancer therapeutic model. The challenges and future developments of this cancer therapeutic model are discussed in detail to understand as much as possible the prospects of this field. Designing nanomedicine therapy strategies by targeting tumor metabolic characteristics will provide a novel approach for the application of personalized biomedicine of tumors.

Keywords:  Metabolic reprogramming; Metabolism regulation; Nanomedicine; Synergistic therapy; Tumors metabolism

DOI:  https://doi.org/10.1016/j.biomaterials.2022.121565
Sci Rep. 2022 May 19. 12(1): 8397

Gas chromatography-mass spectrometry-based untargeted metabolomics reveals metabolic perturbations in medullary thyroid carcinoma.

Morteza Ghazanfari Jajin, Raziyeh Abooshahab, Kourosh Hooshmand, Ali Moradi, Seyed Davar Siadat, Roghieh Mirzazadeh, Koorosh Goodarzvand Chegini, Mehdi Hedayati.

Medullary thyroid cancer (MTC) is a rare tumor that arises from parafollicular cells within the thyroid gland. The molecular mechanism underlying MTC has not yet been fully understood. Here, we aimed to perform plasma metabolomics profiling of MTC patients to explore the perturbation of metabolic pathways contributing to MTC tumorigenesis. Plasma samples from 20 MTC patients and 20 healthy subjects were obtained to carry out an untargeted metabolomics by gas chromatography-mass spectrometry. Multivariate and univariate analyses were employed as diagnostic tools via MetaboAnalyst and SIMCA software. A total of 76 features were structurally annotated; among them, 13 metabolites were selected to be differentially expressed in MTC patients compared to controls (P < 0.05). These metabolites were mainly associated with the biosynthesis of unsaturated fatty acids and amino acid metabolisms, mostly leucine, glutamine, and glutamate, tightly responsible for tumor cells' energy production. Moreover, according to the receiver operating characteristic curve analysis, metabolites with the area under the curve (AUC) value up to 0.90, including linoleic acid (AUC = 0.935), linolenic acid (AUC = 0.92), and leucine (AUC = 0.948) could discriminate MTC from healthy individuals. This preliminary work contributes to existing knowledge of MTC metabolism by providing evidence of a distinctive metabolic profile in MTC patients relying on the metabolomics approach.

DOI: https://doi.org/10.1038/s41598-022-12590-x
Nat Commun. 2022 May 16. 13(1): 2699

Mitochondria preserve an autarkic one-carbon cycle to confer growth-independent cancer cell migration and metastasis.

Nicole Kiweler, Catherine Delbrouck, Vitaly I Pozdeev, Laura Neises, Leticia Soriano-Baguet, Kim Eiden, Feng Xian, Mohaned Benzarti, Lara Haase, Eric Koncina, Maryse Schmoetten, Christian Jaeger, Muhammad Zaeem Noman, Alexei Vazquez, Bassam Janji, Gunnar Dittmar, Dirk Brenner, Elisabeth Letellier, Johannes Meiser.

Metastasis is the most common cause of death in cancer patients. Canonical drugs target mainly the proliferative capacity of cancer cells, which leaves slow-proliferating, persistent cancer cells unaffected. Metabolic determinants that contribute to growth-independent functions are still poorly understood. Here we show that antifolate treatment results in an uncoupled and autarkic mitochondrial one-carbon (1C) metabolism during cytosolic 1C metabolism impairment. Interestingly, antifolate dependent growth-arrest does not correlate with decreased migration capacity. Therefore, using methotrexate as a tool compound allows us to disentangle proliferation and migration to profile the metabolic phenotype of migrating cells. We observe that increased serine de novo synthesis (SSP) supports mitochondrial serine catabolism and inhibition of SSP using the competitive PHGDH-inhibitor BI-4916 reduces cancer cell migration. Furthermore, we show that sole inhibition of mitochondrial serine catabolism does not affect primary breast tumor growth but strongly inhibits pulmonary metastasis. We conclude that mitochondrial 1C metabolism, despite being dispensable for proliferative capacities, confers an advantage to cancer cells by supporting their motility potential.

DOI: https://doi.org/10.1038/s41467-022-30363-y
J Vis Exp. 2022 Apr 28.

Evaluation of Fatty Acid Oxidation in Cultured Bone Cells.

Soohyun P Kim, Zhu Li, Ryan C Riddle.

Bone formation by differentiating osteoblasts is expected to require significant energetic input as these specialized cells must synthesize large extracellular matrix proteins that compose bone tissue and then concentrate the ions necessary for its mineralization. Data on the metabolic requirements of bone formation are emerging rapidly. While much remains to be learned, it is expected that derangements in the intermediary metabolism contribute to skeletal disease. Here, a protocol is outlined to assess the capacity of osteoblastic cells to oxidize 14C-labeled fatty acids to 14CO2 and acid-soluble metabolites. Fatty acids represent a rich-energy reserve that can be taken up from the circulation after feeding or after their liberation from adipose tissue stores. The assay, performed in T-25 tissue culture flasks, is helpful for the study of gene gain or loss-of-function on fatty acid utilization and the effect of anabolic signals in the form of growth factors or morphogens necessary for the maintenance of bone mass. Details on the ability to adapt the protocol to assess the oxidation of glucose or amino acids like glutamine are also provided.

DOI: https://doi.org/10.3791/63638
J Hepatol. 2022 May 17. pii: S0168-8278(22)00314-2. [Epub ahead of print]

Metabolic Reprogramming in Cholangiocarcinoma.

Chiara Raggi, Maria Letizia Taddei, Colin Rae, Chiara Braconi, Fabio Marra.

  Metabolic reprogramming is a hallmark of cancer and allows tumor cells to meet the increased energy demands required for rapid proliferation, invasion, and metastasis. Indeed, many tumor cells acquire distinctive metabolic and bioenergetic features to survive under conditions of limited resources, mainly using alternative nutrients. Several recent studies have explored the metabolic plasticity of cancer cells with the aim to identify new druggable targets, and therapeutic strategies aimed to limit the access to nutrients have been successfully applied to the treatment of some tumors. Cholangiocarcinoma (CCA), a highly heterogeneous tumor, is the second most common form of primary liver cancer. It is characterized by resistance to chemotherapy and poor prognosis, with 5-year survival lower than 20%. Deregulation of metabolic pathways has been described during the onset and progression of CCA. Increased aerobic glycolysis and glutamine anaplerosis provide CCA cells with the ability to generate biosynthetic intermediates. Other metabolic alterations involving carbohydrates, amino acids and lipids have been shown to sustain cancer cell growth and dissemination. In this review, we discuss the complex metabolic rewiring taking place during CCA development, leading to unique nutrient addiction. The possible role of therapeutic interventions based on metabolic changes is also thoroughly discussed.

Keywords:  CD36; IDH1/2; PGC1α; cancer stem cells; fatty acids; fatty-acid synthase; glutamine; glycolysis; mTOR; methionine adenosyltransferases; mitochondria; oxidative metabolism

DOI:  https://doi.org/10.1016/j.jhep.2022.04.038
J Biol Chem. 2022 May 13. pii: S0021-9258(22)00470-7. [Epub ahead of print] 102030

Prolonged deprivation of arginine or leucine induces PI3K/Akt-dependent reactivation of mTORC1.

Gwen R Buel, Huy Dang, John M Asara, John Blenis, Anders P Mutvei.

The mechanistic target of rapamycin complex 1 (mTORC1) is a serine/threonine kinase complex that promotes anabolic processes including protein, lipid, and nucleotide synthesis, while suppressing catabolic processes such as macroautophagy. mTORC1 activity is regulated by growth factors and amino acids which signal through distinct but integrated molecular pathways: growth factors largely signal through the PI3K/Akt-dependent pathway, whereas the availabilities of amino acids leucine and arginine are communicated to mTORC1 by the Rag-GTPase pathway. While it is relatively well described how acute changes in leucine and arginine levels affect mTORC1 signaling, the effects of prolonged amino acid deprivation remain less well understood. Here, we demonstrate that prolonged deprivation of arginine and/or leucine leads to reactivation of mTORC1 activity, which reaches activation levels similar to those observed in nutrient-rich conditions. Surprisingly, we find that this reactivation is independent of the regeneration of amino acids by canonical autophagy or proteasomal degradation, but is dependent on PI3K/Akt signaling. Together, our data identify a novel crosstalk between the amino acid and PI3K/Akt signaling pathways upstream of mTORC1. These observations extend our understanding of the role of mTORC1 in growth-related diseases and indicate that dietary intervention by removal of leucine and/or arginine may be an ineffective therapeutic approach.

DOI: https://doi.org/10.1016/j.jbc.2022.102030
Cancer Drug Resist. 2021 ;4(1): 143-162

Metabolic reprogramming as an emerging mechanism of resistance to endocrine therapies in prostate cancer.

Paolo Chetta, Giorgia Zadra.

  Prostate cancer (PCa) is the second leading cause of cancer-related death in the US. Androgen receptor (AR) signaling is the driver of both PCa development and progression and, thus, the major target of current in-use therapies. However, despite the survival benefit of second-generation inhibitors of AR signaling in the metastatic setting, resistance mechanisms inevitably occur. Thus, novel strategies are required to circumvent resistance occurrence and thereby to improve PCa survival. Among the key cellular processes that are regulated by androgens, metabolic reprogramming stands out because of its intricate links with cancer cell biology. In this review, we discuss how cancer metabolism and lipid metabolism in particular are regulated by androgens and contribute to the acquisition of resistance to endocrine therapy. We describe the interplay between genetic alterations, metabolic vulnerabilities and castration resistance. Since PCa cells adapt their metabolism to excess nutrient supply to promote cancer progression, we review our current knowledge on the association between diet/obesity and resistance to anti-androgen therapies. We briefly describe the metabolic symbiosis between PCa cells and tumor microenvironment and how this crosstalk might contribute to PCa progression. We discuss how tackling PCa metabolic vulnerabilities represents a potential approach of synthetic lethality to endocrine therapies. Finally, we describe how the continuous advances in analytical technologies and metabolic imaging have led to the identification of potential new prognostic and predictive biomarkers, and non-invasive approaches to monitor therapy response.

Keywords:  Metabolic reprogramming; castration resistance; endocrine therapies; metabolic imaging; metabolomics; prostate cancer; therapy respo nse

DOI:  https://doi.org/10.20517/cdr.2020.54
Cancer Res. 2022 May 18. pii: canres.CAN-21-2352-E.2021. [Epub ahead of print]

Pyruvate kinase M1 suppresses development and progression of prostate adenocarcinoma.

Shawn M Davdison, Daniel R Schmidt, Julia E Heyman, James P O'Brien, Amy C Liu, William J Israelsen, Talya L Dayton, Raghav Sehgal, Roderick T Bronson, Elizaveta Freinkman, Howard H Mak, Giuseppe Nicolo Fanelli, Scott Malstrom, Gary Bellinger, Arkaitz Carracedo, Pier Paolo Pandolfi, Kevin D Courtney, Abhishek Jha, Ronald A DePinho, James W Horner, Craig J Thomas, Lewis C Cantley, Massimo Loda, Matthew G Vander Heiden.

Altered metabolisms helps sustain cancer cell proliferation and survival. Most cancers, including prostate cancers, express the M2 splice isoform of pyruvate kinase (Pkm2), which can support anabolic metabolism to support cell proliferation. However, Pkm2 expression is dispensable for the formation and growth of many cancers in vivo. Expression of pyruvate kinase isoform M1 (Pkm1) is restricted to relatively few tissues and has been reported to promote growth of select tumors, but the role of Pkm1 in cancer has been less studied than Pkm2. To test how differential expression of pyruvate kinase isoforms affects cancer initiation and progression, we generated mice harboring a conditional allele of Pkm1, and crossed these mice or those with a Pkm2 conditional allele with a Pten loss-driven prostate cancer model. Pkm1 loss led to increased Pkm2 expression and accelerated prostate cancer development, while Pkm2 deletion of led to increased Pkm1 expression and suppressed tumor progression. Metabolic profiling revealed altered nucleotide levels in tumors with high Pkm1 expression, and failure of these tumors to progress was associated with DNA replication stress and senescence. Consistent with these data, a small molecule pyruvate kinase activator that mimics a high activity Pkm1-like state suppressed progression of established prostate tumors. Analysis of human specimens showed PKM2 expression is retained in most human prostate cancers. Overall, this study uncovers a role for pyruvate kinase isoforms in prostate cancer initiation and progression, and argues that pharmacological pyruvate kinase activation may be beneficial for treating prostate cancer.

DOI: https://doi.org/10.1158/0008-5472.CAN-21-2352
Nat Biotechnol. 2022 May 19.

Deep Visual Proteomics defines single-cell identity and heterogeneity.

Andreas Mund, Fabian Coscia, András Kriston, Réka Hollandi, Ferenc Kovács, Andreas-David Brunner, Ede Migh, Lisa Schweizer, Alberto Santos, Michael Bzorek, Soraya Naimy, Lise Mette Rahbek-Gjerdrum, Beatrice Dyring-Andersen, Jutta Bulkescher, Claudia Lukas, Mark Adam Eckert, Ernst Lengyel, Christian Gnann, Emma Lundberg, Peter Horvath, Matthias Mann.

Despite the availabilty of imaging-based and mass-spectrometry-based methods for spatial proteomics, a key challenge remains connecting images with single-cell-resolution protein abundance measurements. Here, we introduce Deep Visual Proteomics (DVP), which combines artificial-intelligence-driven image analysis of cellular phenotypes with automated single-cell or single-nucleus laser microdissection and ultra-high-sensitivity mass spectrometry. DVP links protein abundance to complex cellular or subcellular phenotypes while preserving spatial context. By individually excising nuclei from cell culture, we classified distinct cell states with proteomic profiles defined by known and uncharacterized proteins. In an archived primary melanoma tissue, DVP identified spatially resolved proteome changes as normal melanocytes transition to fully invasive melanoma, revealing pathways that change in a spatial manner as cancer progresses, such as mRNA splicing dysregulation in metastatic vertical growth that coincides with reduced interferon signaling and antigen presentation. The ability of DVP to retain precise spatial proteomic information in the tissue context has implications for the molecular profiling of clinical samples.

DOI: https://doi.org/10.1038/s41587-022-01302-5
Methods Mol Biol. 2022 ;2466 111-119

Application of Immunoaffinity Mass Spectrometry (IA-MS) for Protein Biomarker Quantification.

Joe Palandra, Nikolaos Psychogios, Hendrik Neubert.

  Immunoaffinity mass spectrometry (IA-MS) is a powerful analytical technique for the determination of protein biomarkers with high sensitivity and unparalleled specificity. Typically, the protein antigen of interest is captured from biofluids and tissue lysates using an antibody prior to mass spectrometric analysis. Here we describe the specific steps of the protein immunoaffinity component of the IA-MS workflow that is applicable to most protein antigens.

Keywords:  Biomarker quantification; Immunoaffinity mass spectrometry (IA-MS )

DOI:  https://doi.org/10.1007/978-1-0716-2176-9_8
Biosci Rep. 2022 May 18. pii: BSR20211854. [Epub ahead of print]

Role of fatty acid transport protein 4 in metabolic tissues: insights into obesity and fatty liver disease.

Huili Li, Thomas Herrmann, Jessica Seeßle, Gerhard Liebisch, Uta Merle, Wolfgang Stremmel, Walee Chamulitrat.

  Fatty acid (FA) metabolism is a series of processes that provide structural substances, signalling molecules and energy. Ample evidence has shown that FA uptake is mediated by plasma membrane transporters including FA transport proteins (FATPs), caveolin-1, fatty-acid translocase (FAT)/CD36, and fatty-acid binding proteins. Unlike other FA transporters, the functions of FATPs have been controversial because they contain both motifs of FA transport and fatty acyl-CoA synthetase (ACS). The widely distributed FATP4 is not a direct FA transporter but plays a predominant function as an ACS. FATP4 deficiency causes ichthyosis premature syndrome in mice and humans associated with suppression of polar lipids but an increase in neutral lipids including triglycerides (TGs). Such a shift has been extensively characterized in enterocyte-, hepatocyte-, and adipocyte-specific Fatp4-deficient mice. The mutants under obese and non-obese fatty livers induced by different diets persistently show an increase in blood non-esterified free fatty acids and glycerol indicating the lipolysis of TGs. This review also focuses on FATP4 role on regulatory networks and factors that modulate FATP4 expression in metabolic tissues including intestine, liver, muscle, and adipose tissues. Metabolic disorders especially regarding blood lipids by FATP4 deficiency in different cell types are herein discussed. Our results may be applicable to not only patients with FATP4 mutations but also represent a model of dysregulated lipid homeostasis, thus providing mechanistic insights into obesity and development of fatty liver disease.

Keywords:  acyl CoA synthetase; fatty acid transport protein 4; fatty acids; lipidomics; phospholipids; triglycerides

DOI:  https://doi.org/10.1042/BSR20211854
Methods Mol Biol. 2022 ;2447 159-174

Profiling Sequence Specificity of Proteolytic Activities Using Proteome-Derived Peptide Libraries.

Fatih Demir, Maithreyan Kuppusamy, Andreas Perrar, Pitter F Huesgen.

  Substrate sequence specificity is a fundamental characteristic of proteolytic enzymes. Hundreds of proteases are encoded in plant genomes, but the vast majority of them have not been characterized and their distinct specificity remains largely unknown. Here we present our current protocol for profiling sequence specificity of plant proteases using Proteomic Identification of Cleavage Sites (PICS). This simple, cost-effective protocol is suited for detailed, time-resolved specificity profiling of purified or enriched proteases. The isolated active protease or fraction with enriched protease activity together with a suitable control are incubated with split aliquots of proteome-derived peptide libraries, followed by identification of specifically cleaved peptides using quantitative mass spectrometry. Detailed specificity profiles are obtained by alignment of many individual cleavage sites. The chapter covers preparation of complementary peptide libraries from heterologous sources, the cleavage assay itself, as well as mass spectrometry data analysis.

Keywords:  Protease specificity; Proteolysis; Proteome-derived peptide library; Proteomic identification of protease cleavage sites; Proteomics

DOI:  https://doi.org/10.1007/978-1-0716-2079-3_13
J Chromatogr A. 2022 May 06. pii: S0021-9673(22)00317-X. [Epub ahead of print]1673 463124

Development and application of a fast ultra-high performance liquid chromatography-trapped ion mobility mass spectrometry method for untargeted lipidomics.

Fabrizio Merciai, Simona Musella, Eduardo Sommella, Alessia Bertamino, Anna Maria D'Ursi, Pietro Campiglia.

  The alteration of lipid profile in biological specimens, such as plasma, mirrors abnormalities in their homeostasis and offers pivotal information for disease comprehension. Fast analytical methods are needed to highlight changes in plasma lipid profile and deliver rapid results. In this study we developed a fast reversed phase ultra high performance liquid chromatography-trapped ion mobility mass spectrometry (RP-UHPLC-TIMS-MS) method for untargeted lipidomics. A short, narrow-bore fully porous particle CSH column (50 mm × 2.1 mm, 1.7 µm) was used, and by selecting appropriate flow rate, temperature and gradient conditions, the total analysis time was reduced from 20 to 4 min. TIMS was operated in parallel accumulation serial fragmentation mode (PASEF) which allowed to select multiple precursors for MS/MS and separate co-eluting lipids based on their different mobility. Lipid annotation was performed by rule-based approach, comparison with LipidBlast spectral library and manual data curation, by taking into account class-specific fragmentation pattern, accurate mass, adduct form, retention behavior in RP and comparison of their collision cross-section (CCS) values for increased confidence. 306 unique lipids from 21 subclasses were annotated from 20 µL of plasma, while their concentration was estimated by class-specific deuterated internal standards. The analytical method was validated and finally applied to elucidate the alteration of plasma lipid profiles in a small cohort of amyotrophic lateral sclerosis (ALS) patients. Univariate and multivariate statistics evidenced significant differences with respect to control patients, particularly in the levels of ether linked lipids (PC-O, PE-O, PE-P and LPC-O), sphingolipids (Ceramides), and triacylglycerols, showing the usefulness of this fast approach in providing accurate and rapid results with respect to longer (≥15 min) untargeted UHPLC-HRMS methods.

Keywords:  Amyotrophic lateral sclerosis; Plasma; Trapped ion mobility; UHPLC; Untargeted lipidomics

DOI:  https://doi.org/10.1016/j.chroma.2022.463124
Nat Commun. 2022 May 16. 13(1): 2698

Purine nucleotide depletion prompts cell migration by stimulating the serine synthesis pathway.

Mona Hoseini Soflaee, Rushendhiran Kesavan, Umakant Sahu, Alpaslan Tasdogan, Elodie Villa, Zied Djabari, Feng Cai, Diem H Tran, Hieu S Vu, Eunus S Ali, Halie Rion, Brendan P O'Hara, Sherwin Kelekar, James Hughes Hallett, Misty Martin, Thomas P Mathews, Peng Gao, John M Asara, Brendan D Manning, Issam Ben-Sahra, Gerta Hoxhaj.

Purine nucleotides are necessary for various biological processes related to cell proliferation. Despite their importance in DNA and RNA synthesis, cellular signaling, and energy-dependent reactions, the impact of changes in cellular purine levels on cell physiology remains poorly understood. Here, we find that purine depletion stimulates cell migration, despite effective reduction in cell proliferation. Blocking purine synthesis triggers a shunt of glycolytic carbon into the serine synthesis pathway, which is required for the induction of cell migration upon purine depletion. The stimulation of cell migration upon a reduction in intracellular purines required one-carbon metabolism downstream of de novo serine synthesis. Decreased purine abundance and the subsequent increase in serine synthesis triggers an epithelial-mesenchymal transition (EMT) and, in cancer models, promotes metastatic colonization. Thus, reducing the available pool of intracellular purines re-routes metabolic flux from glycolysis into de novo serine synthesis, a metabolic change that stimulates a program of cell migration.

DOI: https://doi.org/10.1038/s41467-022-30362-z
Clin Proteomics. 2022 May 14. 19(1): 13

Optimized sample preparation and data analysis for TMT proteomic analysis of cerebrospinal fluid applied to the identification of Alzheimer's disease biomarkers.

Sophia Weiner, Mathias Sauer, Pieter Jelle Visser, Betty M Tijms, Egor Vorontsov, Kaj Blennow, Henrik Zetterberg, Johan Gobom.

   BACKGROUND: Cerebrospinal fluid (CSF) is an important biofluid for biomarkers of neurodegenerative diseases such as Alzheimer's disease (AD). By employing tandem mass tag (TMT) proteomics, thousands of proteins can be quantified simultaneously in large cohorts, making it a powerful tool for biomarker discovery. However, TMT proteomics in CSF is associated with analytical challenges regarding sample preparation and data processing. In this study we address those challenges ranging from data normalization over sample preparation to sample analysis.
METHOD: Using liquid chromatography coupled to mass-spectrometry (LC-MS), we analyzed TMT multiplex samples consisting of either identical or individual CSF samples, evaluated quantification accuracy and tested the performance of different data normalization approaches. We examined MS2 and MS3 acquisition strategies regarding accuracy of quantification and performed a comparative evaluation of filter-assisted sample preparation (FASP) and an in-solution protocol. Finally, four normalization approaches (median, quantile, Total Peptide Amount, TAMPOR) were applied to the previously published European Medical Information Framework Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) dataset.
RESULTS: The correlation of measured TMT reporter ratios with spiked-in standard peptide amounts was significantly lower for TMT multiplexes composed of individual CSF samples compared with those composed of aliquots of a single CSF pool, demonstrating that the heterogeneous CSF sample composition influences TMT quantitation. Comparison of TMT reporter normalization methods showed that the correlation could be improved by applying median- and quantile-based normalization. The slope was improved by acquiring data in MS3 mode, albeit at the expense of a 29% decrease in the number of identified proteins. FASP and in-solution sample preparation of CSF samples showed a 73% overlap in identified proteins. Finally, using optimized data normalization, we present a list of 64 biomarker candidates (clinical AD vs. controls, p < 0.01) identified in the EMIF-AD cohort.
CONCLUSION: We have evaluated several analytical aspects of TMT proteomics in CSF. The results of our study provide practical guidelines to improve the accuracy of quantification and aid in the design of sample preparation and analytical protocol. The AD biomarker list extracted from the EMIF-AD cohort can provide a valuable basis for future biomarker studies and help elucidate pathogenic mechanisms in AD.

Keywords:  Alzheimer’s disease; Biomarkers; Cerebrospinal fluid; Labeling efficiency; Mass spectrometry; Normalization; Sample preparation; Tandem mass tag

DOI:  https://doi.org/10.1186/s12014-022-09354-0