bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2022‒11‒06
twenty-one papers selected by
Giovanny Rodriguez Blanco
University of Edinburgh
  1. Tumor glycolysis, an essential sweet tooth of tumor cells.
  2. Analytical and computational workflow for in-depth analysis of oxidized complex lipids in blood plasma.
  3. Reversal of mitochondrial malate dehydrogenase 2 enables anaplerosis via redox rescue in respiration-deficient cells.
  4. Untargeted stable isotope-resolved metabolomics to assess the effect of PI3Kβ inhibition on metabolic pathway activities in a PTEN null breast cancer cell line.
  5. Comprehensive lipidomic profiling by plasma separation cards.
  6. Hypoxia-driven metabolic reprogramming of adipocytes fuels cancer cell proliferation.
  7. Metabolite annotation from knowns to unknowns through knowledge-guided multi-layer metabolic networking.
  8. A functional analysis of 180 cancer cell lines reveals conserved intrinsic metabolic programs.
  9. Heterogeneity of the cancer cell line metabolic landscape.
  10. Transient Systemic Autophagy Ablation Irreversibly Inhibits Lung Tumor Cell Metabolism and Promotes T-Cell Mediated Tumor Killing.
  11. Metabolic fingerprinting of chemotherapy-resistant prostate cancer stem cells. An untargeted metabolomic approach by liquid chromatography-mass spectrometry.
  12. A software-assisted untargeted liquid chromatography-mass spectrometry method for lipidomic profiling of human plasma samples.
  13. Leveraging a Fluorescent Fatty Acid Probe to Discover Cell-Permeable Inhibitors of Plasmodium falciparum Glycerolipid Biosynthesis.
  14. Targeting UGCG overcomes resistance to lysosomal autophagy inhibition.
  15. Comparative Evaluation of Proteome Discoverer and FragPipe for the TMT-Based Proteome Quantification.
  16. Advancing Orbitrap Measurements of Collision Cross Sections to Multiple Species for Broad Applications.
  17. GPX4-independent ferroptosis-a new strategy in disease's therapy.
  18. Introducing new group leaders: Devin Schweppe.
  19. More than Meets the Eye: Untargeted Metabolomics and Lipidomics Reveal Complex Pathways Spurred by Activation of Acid Resistance Mechanisms in Escherichia coli.
  20. Ganglioside lipidomics of CNS myelination using direct infusion shotgun mass spectrometry.
  21. Circulating fatty acids from high-throughput metabolomics platforms as potential biomarkers of dietary fatty acids.
  1. Semin Cancer Biol. 2022 Oct 28. pii: S1044-579X(22)00204-8. [Epub ahead of print]86(Pt 3): 1216-1230
    Tumor glycolysis, an essential sweet tooth of tumor cells.
    Sumana Paul, Saikat Ghosh, Sushil Kumar.
      Cancer cells undergo metabolic alterations to meet the immense demand for energy, building blocks, and redox potential. Tumors show glucose-avid and lactate-secreting behavior even in the presence of oxygen, a process known as aerobic glycolysis. Glycolysis is the backbone of cancer cell metabolism, and cancer cells have evolved various mechanisms to enhance it. Glucose metabolism is intertwined with other metabolic pathways, making cancer metabolism diverse and heterogeneous, where glycolysis plays a central role. Oncogenic signaling accelerates the metabolic activities of glycolytic enzymes, mainly by enhancing their expression or by post-translational modifications. Aerobic glycolysis ferments glucose into lactate which supports tumor growth and metastasis by various mechanisms. Herein, we focused on tumor glycolysis, especially its interactions with the pentose phosphate pathway, glutamine metabolism, one-carbon metabolism, and mitochondrial oxidation. Further, we describe the role and regulation of key glycolytic enzymes in cancer. We summarize the role of lactate, an end product of glycolysis, in tumor growth, and the metabolic adaptations during metastasis. Lastly, we briefly discuss limitations and future directions to improve our understanding of glucose metabolism in cancer.
    Keywords:  Cancer metabolism; Lactate; Metastasis; Tumor glycolysis; metabolic adaptations
    DOI:  https://doi.org/10.1016/j.semcancer.2022.09.007
  2. Nat Commun. 2022 Nov 01. 13(1): 6547
    Analytical and computational workflow for in-depth analysis of oxidized complex lipids in blood plasma.
    Angela Criscuolo, Palina Nepachalovich, Diego Fernando Garcia-Del Rio, Mike Lange, Zhixu Ni, Massimo Baroni, Gabriele Cruciani, Laura Goracci, Matthias Blüher, Maria Fedorova.
      Lipids are a structurally diverse class of biomolecules which can undergo a variety of chemical modifications. Among them, lipid (per)oxidation attracts most of the attention due to its significance in the regulation of inflammation, cell proliferation and death programs. Despite their apparent regulatory significance, the molecular repertoire of oxidized lipids remains largely elusive as accurate annotation of lipid modifications is complicated by their low abundance and often unknown, biological context-dependent structural diversity. Here, we provide a workflow based on the combination of bioinformatics and LC-MS/MS technologies to support identification and relative quantification of oxidized complex lipids in a modification type- and position-specific manner. The developed methodology is used to identify epilipidomics signatures of lean and obese individuals with and without type 2 diabetes. The characteristic signature of lipid modifications in lean individuals, dominated by the presence of modified octadecanoid acyl chains in phospho- and neutral lipids, is drastically shifted towards lipid peroxidation-driven accumulation of oxidized eicosanoids, suggesting significant alteration of endocrine signalling by oxidized lipids in metabolic disorders.
    DOI:  https://doi.org/10.1038/s41467-022-33225-9
  3. Mol Cell. 2022 Oct 31. pii: S1097-2765(22)00962-5. [Epub ahead of print]
    Reversal of mitochondrial malate dehydrogenase 2 enables anaplerosis via redox rescue in respiration-deficient cells.
    Patricia Altea-Manzano, Anke Vandekeere, Joy Edwards-Hicks, Mar Roldan, Emily Abraham, Xhordi Lleshi, Ania Naila Guerrieri, Domenica Berardi, Jimi Wills, Jair Marques Junior, Asimina Pantazi, Juan Carlos Acosta, Rosario M Sanchez-Martin, Sarah-Maria Fendt, Miguel Martin-Hernandez, Andrew J Finch.
      Inhibition of the electron transport chain (ETC) prevents the regeneration of mitochondrial NAD+, resulting in cessation of the oxidative tricarboxylic acid (TCA) cycle and a consequent dependence upon reductive carboxylation for aspartate synthesis. NAD+ regeneration alone in the cytosol can rescue the viability of ETC-deficient cells. Yet, how this occurs and whether transfer of oxidative equivalents to the mitochondrion is required remain unknown. Here, we show that inhibition of the ETC drives reversal of the mitochondrial aspartate transaminase (GOT2) as well as malate and succinate dehydrogenases (MDH2 and SDH) to transfer oxidative NAD+ equivalents into the mitochondrion. This supports the NAD+-dependent activity of the mitochondrial glutamate dehydrogenase (GDH) and thereby enables anaplerosis-the entry of glutamine-derived carbon into the TCA cycle and connected biosynthetic pathways. Thus, under impaired ETC function, the cytosolic redox state is communicated into the mitochondrion and acts as a rheostat to support GDH activity and cell viability.
    Keywords:  anaplerosis; cancer; cancer metabolism; metabolism; mitochondrion; redox; redox transfer; respiration
    DOI:  https://doi.org/10.1016/j.molcel.2022.10.005
  4. Front Mol Biosci. 2022 ;9 1004602
    Untargeted stable isotope-resolved metabolomics to assess the effect of PI3Kβ inhibition on metabolic pathway activities in a PTEN null breast cancer cell line.
    Marcel Lackner, Sylvia K Neef, Stefan Winter, Sandra Beer-Hammer, Bernd Nürnberg, Matthias Schwab, Ute Hofmann, Mathias Haag.
      The combination of high-resolution LC-MS untargeted metabolomics with stable isotope-resolved tracing is a promising approach for the global exploration of metabolic pathway activities. In our established workflow we combine targeted isotopologue feature extraction with the non-targeted X13CMS routine. Metabolites, detected by X13CMS as differentially labeled between two biological conditions are subsequently integrated into the original targeted library. This strategy enables monitoring of changes in known pathways as well as the discovery of hitherto unknown metabolic alterations. Here, we demonstrate this workflow in a PTEN (phosphatase and tensin homolog) null breast cancer cell line (MDA-MB-468) exploring metabolic pathway activities in the absence and presence of the selective PI3Kβ inhibitor AZD8186. Cells were fed with [U-13C] glucose and treated for 1, 3, 6, and 24 h with 0.5 µM AZD8186 or vehicle, extracted by an optimized sample preparation protocol and analyzed by LC-QTOF-MS. Untargeted differential tracing of labels revealed 286 isotope-enriched features that were significantly altered between control and treatment conditions, of which 19 features could be attributed to known compounds from targeted pathways. Other 11 features were unambiguously identified based on data-dependent MS/MS spectra and reference substances. Notably, only a minority of the significantly altered features (11 and 16, respectively) were identified when preprocessing of the same data set (treatment vs. control in 24 h unlabeled samples) was performed with tools commonly used for label-free (i.e. w/o isotopic tracer) non-targeted metabolomics experiments (Profinder´s batch recursive feature extraction and XCMS). The structurally identified metabolites were integrated into the existing targeted isotopologue feature extraction workflow to enable natural abundance correction, evaluation of assay performance and assessment of drug-induced changes in pathway activities. Label incorporation was highly reproducible for the majority of isotopologues in technical replicates with a RSD below 10%. Furthermore, inter-day repeatability of a second label experiment showed strong correlation (Pearson R 2 > 0.99) between tracer incorporation on different days. Finally, we could identify prominent pathway activity alterations upon PI3Kβ inhibition. Besides pathways in central metabolism, known to be changed our workflow revealed additional pathways, like pyrimidine metabolism or hexosamine pathway. All pathways identified represent key metabolic processes associated with cancer metabolism and therapy.
    Keywords:  13C labeling; LC-QTOF-MS; PI3K; TCA cycle; cancer metabolism; glycolysis; non-targeted analysis; stable isotope-resolved metabolomics (SIRM)
    DOI:  https://doi.org/10.3389/fmolb.2022.1004602
  5. Anal Bioanal Chem. 2022 Nov 01.
    Comprehensive lipidomic profiling by plasma separation cards.
    Lauren M Bishop, Oliver Fiehn.
      Large-scale lipidomic analyses have been limited by the cost and accessibility of traditional venipuncture sampling. Microsampling techniques offer a less-invasive and more accessible alternative. From a single drop of blood, plasma separation cards (PSC) deliver two volumetric dried plasma samples which are studied here for profiling endogenous blood lipids. Six lots of EDTA-treated human whole blood were used to compare PSC, dried blood spot analyses (DBS), and classic wet plasma extractions. Six replicate extractions were performed for each lot. Nontargeted lipidomics was performed by liquid chromatography-high resolution tandem mass spectrometry. Lipids were annotated by accurate mass/retention time matching and MS/MS spectral library matching using peak intensities for quantitation. Four hundred ninety-eight compounds covering 24 lipid subclasses were annotated. Inter-lot repeatability was evaluated by the percent relative standard deviation (%RSD) for each lot, giving median %RSD values across the lots at 14.6% for PSC, 9.3% for DBS, and 8.6% for wet plasma. Strong correlations of lipid peak intensities between wet plasma and PSCs were observed, but less for DBS. Lipid recovery and stability were comparable between the PSC and DBS samples, with roughly 60% of annotated lipids stable at room temperature after 28 days. Overall, PSCs provide a better alternative for quantitative blood lipidomic analyses compared to dried blood spots. However, problems with lipid stability for samples handled and shipped at room temperature are currently unavoidable outside of a clinical setting. Data transferability and comparability to standard plasma is lipid and lipid class dependent.
    Keywords:  Lipidomics; Mass spectrometry; Method validation; Microsampling
    DOI:  https://doi.org/10.1007/s00216-022-04399-4
  6. Front Endocrinol (Lausanne). 2022 ;13 989523
    Hypoxia-driven metabolic reprogramming of adipocytes fuels cancer cell proliferation.
    R Aird, J Wills, K F Roby, C Bénézech, R H Stimson, M Wabitsch, J W Pollard, A Finch, Z Michailidou.
      Objective: Obesity increases the risk of certain cancers, especially tumours that reside close to adipose tissue (breast and ovarian metastasis in the omentum). The obesogenic and tumour micro-environment share a common pathogenic feature, oxygen deprivation (hypoxia). Here we test how hypoxia changes the metabolome of adipocytes to assist cancer cell growth.Methods: Human and mouse breast and ovarian cancer cell lines were co-cultured with human and mouse adipocytes respectively under normoxia or hypoxia. Proliferation and lipid uptake in cancer cells were measured by commercial assays. Metabolite changes under normoxia or hypoxia were measured in the media of human adipocytes by targeted LC/MS.
    Results: Hypoxic cancer-conditioned media increased lipolysis in both human and mouse adipocytes. This led to increased transfer of lipids to cancer cells and consequent increased proliferation under hypoxia. These effects were dependent on HIF1α expression in adipocytes, as mouse adipocytes lacking HIF1α showed blunted responses under hypoxic conditions. Targeted metabolomics of the human Simpson-Golabi-Behmel syndrome (SGBS) adipocytes media revealed that culture with hypoxic-conditioned media from non-malignant mammary epithelial cells (MCF10A) can alter the adipocyte metabolome and drive proliferation of the non-malignant cells.
    Conclusion: Here, we show that hypoxia in the adipose-tumour microenvironment is the driving force of the lipid uptake in both mammary and ovarian cancer cells. Hypoxia can modify the adipocyte metabolome towards accelerated lipolysis, glucose deprivation and reduced ketosis. These metabolic shifts in adipocytes could assist both mammary epithelial and cancer cells to bypass the inhibitory effects of hypoxia on proliferation and thrive.
    Keywords:  adipocytes; cancer cells; hypoxia; lipids; metabolites; obesity
    DOI:  https://doi.org/10.3389/fendo.2022.989523
  7. Nat Commun. 2022 Nov 04. 13(1): 6656
    Metabolite annotation from knowns to unknowns through knowledge-guided multi-layer metabolic networking.
    Zhiwei Zhou, Mingdu Luo, Haosong Zhang, Yandong Yin, Yuping Cai, Zheng-Jiang Zhu.
      Liquid chromatography - mass spectrometry (LC-MS) based untargeted metabolomics allows to measure both known and unknown metabolites in the metabolome. However, unknown metabolite annotation is a major challenge in untargeted metabolomics. Here, we develop an approach, namely, knowledge-guided multi-layer network (KGMN), to enable global metabolite annotation from knowns to unknowns in untargeted metabolomics. The KGMN approach integrates three-layer networks, including knowledge-based metabolic reaction network, knowledge-guided MS/MS similarity network, and global peak correlation network. To demonstrate the principle, we apply KGMN in an in vitro enzymatic reaction system and different biological samples, with ~100-300 putative unknowns annotated in each data set. Among them, >80% unknown metabolites are corroborated with in silico MS/MS tools. Finally, we validate 5 metabolites that are absent in common MS/MS libraries through repository mining and synthesis of chemical standards. Together, the KGMN approach enables efficient unknown annotations, and substantially advances the discovery of recurrent unknown metabolites for common biological samples from model organisms, towards deciphering dark matter in untargeted metabolomics.
    DOI:  https://doi.org/10.1038/s41467-022-34537-6
  8. Mol Syst Biol. 2022 11;18(11): e11033
    A functional analysis of 180 cancer cell lines reveals conserved intrinsic metabolic programs.
    Sarah Cherkaoui, Stephan Durot, Jenna Bradley, Susan Critchlow, Sebastien Dubuis, Mauro Miguel Masiero, Rebekka Wegmann, Berend Snijder, Alaa Othman, Claus Bendtsen, Nicola Zamboni.
      Cancer cells reprogram their metabolism to support growth and invasion. While previous work has highlighted how single altered reactions and pathways can drive tumorigenesis, it remains unclear how individual changes propagate at the network level and eventually determine global metabolic activity. To characterize the metabolic lifestyle of cancer cells across pathways and genotypes, we profiled the intracellular metabolome of 180 pan-cancer cell lines grown in identical conditions. For each cell line, we estimated activity for 49 pathways spanning the entirety of the metabolic network. Upon clustering, we discovered a convergence into only two major metabolic types. These were functionally confirmed by 13 C-flux analysis, lipidomics, and analysis of sensitivity to perturbations. They revealed that the major differences in cancers are associated with lipid, TCA cycle, and carbohydrate metabolism. Thorough integration of these types with multiomics highlighted little association with genetic alterations but a strong association with markers of epithelial-mesenchymal transition. Our analysis indicates that in absence of variations imposed by the microenvironment, cancer cells adopt distinct metabolic programs which serve as vulnerabilities for therapy.
    Keywords:  cancer metabolism; cell lines; metabolic flux; metabolomics; omics
    DOI:  https://doi.org/10.15252/msb.202211033
  9. Mol Syst Biol. 2022 11;18(11): e11006
    Heterogeneity of the cancer cell line metabolic landscape.
    David Shorthouse, Jenna Bradley, Susan E Critchlow, Claus Bendtsen, Benjamin A Hall.
      The unravelling of the complexity of cellular metabolism is in its infancy. Cancer-associated genetic alterations may result in changes to cellular metabolism that aid in understanding phenotypic changes, reveal detectable metabolic signatures, or elucidate vulnerabilities to particular drugs. To understand cancer-associated metabolic transformation, we performed untargeted metabolite analysis of 173 different cancer cell lines from 11 different tissues under constant conditions for 1,099 different species using mass spectrometry (MS). We correlate known cancer-associated mutations and gene expression programs with metabolic signatures, generating novel associations of known metabolic pathways with known cancer drivers. We show that metabolic activity correlates with drug sensitivity and use metabolic activity to predict drug response and synergy. Finally, we study the metabolic heterogeneity of cancer mutations across tissues, and find that genes exhibit a range of context specific, and more general metabolic control.
    Keywords:  cancer; heterogeneity; metabolomics; mutation
    DOI:  https://doi.org/10.15252/msb.202211006
  10. Autophagy. 2022 Oct 31.
    Transient Systemic Autophagy Ablation Irreversibly Inhibits Lung Tumor Cell Metabolism and Promotes T-Cell Mediated Tumor Killing.
    Kyle Nunn, Jessie Yanxiang Guo.
      Macroautophagy/autophagy is a highly conserved catabolic process pivotal to cellular homeostasis and support of tumorigenesis. Being a potential therapeutic target for cancer, we have worked to understand the implications of autophagy inhibition both systemically, and tumor-specifically. We utilized inducible expression of Atg5 shRNA to temporally control autophagy levels in a reversible manner to study the effects of tumor-intrinsic and systemic autophagic loss and restoration on established KrasG12D/+;trp53-/- (KP) lung tumor growth. We reported that transient systemic ATG5 loss significantly reduces KP lung tumor growth. Through in vivo isotope tracing and metabolic flux analyses, we noted that systemic ATG5 knockdown significantly reduces the uptake of glucose and lactate in lung tumors, leading to impaired TCA cycle metabolism and biosynthesis. Additionally, we observed an increased tumor T cell infiltration in the absence of systemic ATG5, which is essential for T cell-mediated tumor killing. Moreover, the impaired tumor metabolism and increased T cell infiltration are sustained when autophagy is restored in a short term. Finally, we found that intermittent systemic ATG5 knockdown, a mock therapy situation, significantly prolongs the lifespan of mice bearing KP lung tumors. Our findings lay the proof of concept for inhibition of autophagy as a valid approach to cancer therapy.
    Keywords:  KRAS; autophagy; cancer metabolism; cancer therapy; immune evasion; lung tumor
    DOI:  https://doi.org/10.1080/15548627.2022.2141534
  11. Front Cell Dev Biol. 2022 ;10 1005675
    Metabolic fingerprinting of chemotherapy-resistant prostate cancer stem cells. An untargeted metabolomic approach by liquid chromatography-mass spectrometry.
    Alicia Bort, Belén G Sánchez, Carlos León, Leonor Nozal, José M Mora-Rodríguez, Florentina Castro, Antonio L Crego, Inés Díaz-Laviada.
      Chemoresistance is one of the most important challenges in cancer therapy. The presence of cancer stem cells within the tumor may contribute to chemotherapy resistance since these cells express high levels of extrusion pumps and xenobiotic metabolizing enzymes that inactivate the therapeutic drug. Despite the recent advances in cancer cell metabolism adaptations, little is known about the metabolic adaptations of the cancer stem cells resistant to chemotherapy. In this study, we have undertaken an untargeted metabolomic analysis by liquid chromatography-high-resolution spectrometry combined with cytotoxicity assay, western blot, quantitative real-time polymerase chain reaction (qPCR), and fatty acid oxidation in a prostate cancer cell line resistant to the antiandrogen 2-hydroxiflutamide with features of cancer stem cells, compared to its parental androgen-sensitive cell line. Metabolic fingerprinting revealed 106 out of the 850 metabolites in ESI+ and 67 out of 446 in ESI- with significant differences between the sensitive and the resistant cell lines. Pathway analysis performed with the unequivocally identified metabolites, revealed changes in pathways involved in energy metabolism as well as posttranscriptional regulation. Validation by enzyme expression analysis indicated that the chemotherapy-resistant prostate cancer stem cells were metabolically dormant with decreased fatty acid oxidation, methionine metabolism and ADP-ribosylation. Our results shed light on the pathways underlying the entry of cancer cells into dormancy that might contribute to the mechanisms of drug resistance.
    Keywords:  cancer chemoresistance; cancer stem cells; fatty acid oxidation; liquid chromatography-mass spectrometry; prostate cancer; untargeted metabolomic
    DOI:  https://doi.org/10.3389/fcell.2022.1005675
  12. Int J Biol Markers. 2022 Oct 31. 3936155221132291
    A software-assisted untargeted liquid chromatography-mass spectrometry method for lipidomic profiling of human plasma samples.
    Francesco Segrado, Adalberto Cavalleri, Alice Cantalupi, Luigi Mariani, Sonia Dagnino, Vittorio Krogh, Elisabetta Venturelli, Claudia Agnoli.
      INTRODUCTION: In this paper, an analytical pipeline designed for untargeted lipidomic profiling in human plasma is proposed. The analytical pipeline was developed for case-control studies nested in prospective cohorts.METHODS: The procedure consisted of isopropanol protein precipitation followed by reverse phase liquid chromatography coupled to high resolution mass spectrometry and software-assisted data processing. The compounds are putatively annotated by matching experimental mass spectrometry data with spectral library data using LipidSearch software. The lipid profile of a pool of plasma samples from 10 healthy volunteers was detected in both positive and negative polarity modes. The impact of the chosen polarity on the number and quality of the lipid identification has been evaluated.
    RESULTS: More than 1000 lipids from 12 different classes were detected, 1150 in positive mode and 273 in negative mode. Nearly half of them were unambiguously identified by the software in positive mode, and about one-third in negative mode. The method repeatability was assessed on the plasma pool samples by means of variance components analysis. The intra- and inter-assay precision was measured for 10 lipids chosen among the most abundant found within the different lipid classes. The intra-assay coefficients of variation ranged from 2.56% to 4.56% while intra- and inter-day coefficients of variance never exceeded the 15% benchmark adopted. The lipidomic profiles of the 10 healthy volunteers were also investigated.
    DISCUSSION: This method detects a wide range of lipids and reports their degree of identification. It is particularly fit and well-designed for large case-control epidemiologic studies.
    Keywords:  Clinical and molecular epidemiology; epidemiology; mass spectrometry methods; metabolomics methods
    DOI:  https://doi.org/10.1177/03936155221132291
  13. Microbiol Spectr. 2022 Oct 31. e0245622
    Leveraging a Fluorescent Fatty Acid Probe to Discover Cell-Permeable Inhibitors of Plasmodium falciparum Glycerolipid Biosynthesis.
    Christie Dapper, Jiapeng Liu, Michael Klemba.
      A sensitive and quantitative fluorescence-based approach is presented for characterizing fatty acid acquisition and lipid biosynthesis by asexually replicating, intraerythrocytic Plasmodium falciparum. We show that a BODIPY-containing, green-fluorescent fatty acid analog is efficiently and rapidly incorporated into parasite neutral lipids and phospholipids. Prelabeling with a red-fluorescent ceramide analog permits normalization and enables reliable quantitation of glycerolipid labeling. Inhibition of lipid labeling by competition with natural fatty acids and by acyl-coenzyme A synthetase and diacylglycerol acyltransferase inhibitors demonstrates that the fluorescent fatty acid probe is acquired, activated, and transferred to lipids through physiologically-relevant pathways. To assess its utility in discovering small molecules that block parasite lipid biosynthesis, the lipid labeling assay was used to screen a panel of mammalian lipase inhibitors and a selection of compounds from the "Malaria Box" anti-malarial collection. Several compounds were identified that inhibited the incorporation of the fluorescent fatty acid probe into lipids in cultured parasites at low micromolar concentrations. Two contrasting profiles of suppression of neutral lipid and phospholipid synthesis were observed, which implies the inhibition of distinct pathways. IMPORTANCE The human malaria parasite Plasmodium falciparum relies on fatty acid scavenging to supply this essential precursor of lipid synthesis during its asexual replication cycle in human erythrocytes. This dependence on host fatty acids represents a potential vulnerability that can be exploited to develop new anti-malarial therapies. The quantitative experimental approach described here provides a platform for simultaneously interrogating multiple facets of lipid metabolism- fatty acid uptake, fatty acyl-CoA synthesis, and neutral lipid and phospholipid biosynthesis- and of identifying cell-permeable inhibitors that are active in situ.
    Keywords:  Malaria Box; Plasmodium falciparum; fatty acid; fluorescent probe; malaria; neutral lipid; phospholipid
    DOI:  https://doi.org/10.1128/spectrum.02456-22
  14. Cancer Discov. 2022 Nov 04. pii: CD-22-0535. [Epub ahead of print]
    Targeting UGCG overcomes resistance to lysosomal autophagy inhibition.
    Vaibhav Jain, Sandra L Harper, Amanda M Versace, Dylan Fingerman, Gregory Schuyler Brown, Monika Bhardwaj, Mary Ann S Crissey, Aaron R Goldman, Gordon Ruthel, Qin Liu, Aleksandra Zivkovic, Holger Stark, Meenhard Herlyn, Phyllis A Gimotty, David W Speicher, Ravi K Amaravadi.
      Lysosomal autophagy inhibition (LAI) with hydroxychloroquine or DC661 can enhance cancer therapy, but tumor regrowth is common. To elucidate LAI resistance, proteomics and immunoblotting demonstrated that LAI induced lipid metabolism enzymes in multiple cancer cell lines. Lipidomics showed that LAI increased cholesterol, sphingolipids, and glycosphingolipids. These changes were associated with striking levels of GM1+ membrane microdomains (GMM) in plasma membranes and lysosomes. Inhibition of cholesterol/sphingolipid metabolism proteins enhanced LAI cytotoxicity. Targeting UDP-glucose ceramide glucosyltransferase (UGCG) synergistically augmented LAI cytotoxicity. While UGCG inhibition decreased LAI-induced GMM and augmented cell death, UGCG overexpression led to LAI resistance. Melanoma patients with high UGCG expression had significantly shorter disease-specific survival. The FDA-approved UGCG inhibitor eliglustat combined with LAI significantly inhibited tumor growth and improved survival in syngeneic tumors and a therapy-resistant patient-derived xenograft. These findings nominate UGCG as a new cancer target, and clinical trials testing UGCG inhibition in combination with LAI are warranted.
    DOI:  https://doi.org/10.1158/2159-8290.CD-22-0535
  15. J Proteome Res. 2022 Oct 31.
    Comparative Evaluation of Proteome Discoverer and FragPipe for the TMT-Based Proteome Quantification.
    Tianen He, Youqi Liu, Yan Zhou, Lu Li, He Wang, Shanjun Chen, Jinlong Gao, Wenhao Jiang, Yi Yu, Weigang Ge, Hui-Yin Chang, Ziquan Fan, Alexey I Nesvizhskii, Tiannan Guo, Yaoting Sun.
      Isobaric labeling-based proteomics is widely applied in deep proteome quantification. Among the platforms for isobaric labeled proteomic data analysis, the commercial software Proteome Discoverer (PD) is widely used, incorporating the search engine CHIMERYS, while FragPipe (FP) is relatively new, free for noncommercial purposes, and integrates the engine MSFragger. Here, we compared PD and FP over three public proteomic data sets labeled using 6plex, 10plex, and 16plex tandem mass tags. Our results showed the protein abundances generated by the two software are highly correlated. PD quantified more proteins (10.02%, 15.44%, 8.19%) than FP with comparable NA ratios (0.00% vs. 0.00%, 0.85% vs. 0.38%, and 11.74% vs. 10.52%) in the three data sets. Using the 16plex data set, PD and FP outputs showed high consistency in quantifying technical replicates, batch effects, and functional enrichment in differentially expressed proteins. However, FP saved 93.93%, 96.65%, and 96.41% of processing time compared to PD for analyzing the three data sets, respectively. In conclusion, while PD is a well-maintained commercial software integrating various additional functions and can quantify more proteins, FP is freely available and achieves similar output with a shorter computational time. Our results will guide users in choosing the most suitable quantification software for their needs.
    Keywords:  FragPipe; Proteome Discoverer; labeled quantitative proteomics; mass spectrometry; tandem mass tag
    DOI:  https://doi.org/10.1021/acs.jproteome.2c00390
  16. Anal Chem. 2022 Nov 03.
    Advancing Orbitrap Measurements of Collision Cross Sections to Multiple Species for Broad Applications.
    Virginia K James, James D Sanders, Konstantin Aizikov, Kyle L Fort, Dmitry Grinfeld, Alexander Makarov, Jennifer S Brodbelt.
      Measurement of collision cross section (CCS), a parameter reflecting an ion's size and shape, alongside high-resolution mass analysis extends the depth of molecular analysis by providing structural information beyond molecular mass alone. Although these measurements are most commonly undertaken using a dedicated ion mobility cell coupled to a mass spectrometer, alternative methods have emerged to extract CCSs directly by analysis of the decay rates of either time-domain transient signals or the FWHM of frequency domain peaks in FT mass analyzers. This information is also accessible from FTMS mass spectra obtained in commonly used workflows directly without the explicit access to transient or complex Fourier spectra. Previously, these experiments required isolation of individual charge states of ions prior to CCS analysis, limiting throughput. Here we advance Orbitrap CCS measurements to more users and applications by determining CCSs from commonly available mass spectra files as well as estimating CCS for multiple charge states simultaneously and showcase these methods by the measurement of CCSs of fragment ions produced from collisional activation of proteins.
    DOI:  https://doi.org/10.1021/acs.analchem.2c02146
  17. Cell Death Discov. 2022 Oct 30. 8(1): 434
    GPX4-independent ferroptosis-a new strategy in disease's therapy.
    Tianyu Ma, Jingtong Du, Yufeng Zhang, Yuyao Wang, Bingxuan Wang, Tianhong Zhang.
      Ferroptosis is a form of programmed cell death characterized by intracellular iron accumulation and lipid peroxidation, and earlier studies identified glutathione peroxidase 4 (GPX4) as an essential regulator of this process. Ferroptosis plays an essential role in tumors, degenerative diseases, and ischemia-reperfusion injury. However, researchers have found that inhibition of GPX4 does not entirely suppress ferroptosis in certain diseases, or cells express resistance to ferroptosis agonists that inhibit GPX4. As research progresses, it has been discovered that there are multiple regulatory pathways for ferroptosis that are independent of GPX4. The study of GPX4-independent ferroptosis pathways can better target ferroptosis to prevent and treat various diseases. Here, the currently inhibited pulmonary GPX4-dependent ferroptosis pathways will be reviewed.
    DOI:  https://doi.org/10.1038/s41420-022-01212-0
  18. Mol Cell. 2022 Nov 03. pii: S1097-2765(22)00903-0. [Epub ahead of print]82(21): 3961-3962
    Introducing new group leaders: Devin Schweppe.
      We talk to Devin Schweppe about setting up his group at the University of Washington, studying quantitative-mass-spectrometry-based proteomics (a field that is constantly evolving), overcoming self-doubt, going with your gut when hiring, and how he hopes to build an environment of excellence, inclusion, and trust and always encourage his lab members to keep asking "why?"
    DOI:  https://doi.org/10.1016/j.molcel.2022.09.014
  19. J Proteome Res. 2022 Nov 02.
    More than Meets the Eye: Untargeted Metabolomics and Lipidomics Reveal Complex Pathways Spurred by Activation of Acid Resistance Mechanisms in Escherichia coli.
    Andrew Gold, Li Chen, Jiangjiang Zhu.
      Escherichia coli is a ubiquitous group of bacteria that can be either commensal gut microbes or enterohemorrhagic food-borne pathogens. Regardless, both forms must survive acidic environments in the stomach and intestines to reach and colonize the gut, a process that partially relies on amino acid-dependent acid resistance (AR) mechanisms and modifications to membrane phospholipids. However, only the basic tenets of these mechanisms have been elucidated. In this paper, we aim to conduct a full-scale metabolic and lipidomic characterization of E. coli's adaptations to acid stress. We hypothesized that the use of untargeted metabolomics and lipidomics would reveal mechanisms downstream of AR processes that provide novel contributions to acid stress survival. We detected significant differences in the extracellular metabolome and the lipidome induced by amino acid supplementation (glutamine, arginine, or lysine) and contextualized these results using real-time quantitative polymerase chain reaction (RT-qPCR). We additionally identified several metabolic pathways as well as a significant alteration in phospholipid synthetic pathways induced by differential amino acid supplementation. These results demonstrate that AR may extend beyond canonical mechanisms to a coordinated metabolic phenotype. Future studies may benefit from our analysis to further elucidate distinct targets for prebiotic supplements to cultivate commensal strains or therapies to combat pathogenic ones.
    Keywords:  E. coli; acid stress; amino acids; bacteria; lipidomics; metabolomics; phospholipids
    DOI:  https://doi.org/10.1021/acs.jproteome.2c00459
  20. iScience. 2022 Nov 18. 25(11): 105323
    Ganglioside lipidomics of CNS myelination using direct infusion shotgun mass spectrometry.
    Martina Arends, Melanie Weber, Cyrus Papan, Markus Damm, Michal A Surma, Christopher Spiegel, Minou Djannatian, Shengrong Li, Lisa Connell, Ludger Johannes, Martina Schifferer, Christian Klose, Mikael Simons.
      Gangliosides are present and concentrated in axons and implicated in axon-myelin interactions, but how ganglioside composition changes during myelin formation is not known. Here, we present a direct infusion (shotgun) lipidomics method to analyze gangliosides in small amounts of tissue reproducibly and with high sensitivity. We resolve the mouse ganglioside lipidome during development and adulthood and determine the ganglioside content of mice lacking the St3gal5 and B4galnt1 genes that synthesize most ganglioside species. Our results reveal substantial changes in the ganglioside lipidome during the formation of myelinated nerve fibers. In sum, we provide insights into the CNS ganglioside lipidome with a quantitative and sensitive mass spectrometry method. Since this method is compatible with global lipidomic profiling, it will provide insights into ganglioside function in physiology and pathology.
    Keywords:  Cell biology; Neuroscience; Omics
    DOI:  https://doi.org/10.1016/j.isci.2022.105323
  21. Clin Nutr. 2022 Oct 13. pii: S0261-5614(22)00357-0. [Epub ahead of print]41(12): 2637-2643
    Circulating fatty acids from high-throughput metabolomics platforms as potential biomarkers of dietary fatty acids.
    Fredrik Rosqvist, Michael Fridén, Johan Vessby, Fredrik Rorsman, Lars Lind, Ulf Risérus.
      BACKGROUND: Some fatty acids, i.e. n-3 and n-6 polyunsaturated fatty acids (PUFA), from metabolomics platforms based on nuclear magnetic resonance imaging (NMR) or liquid chromatography mass-spectrometry (LC-MS) are suggested to reflect dietary exposure. NMR and LC-MS are both relatively fast and cheap, however few studies have investigated their validity. Linoleic acid (LA) and docosahexaenoic acid (DHA), measured using gas chromatography (GC), are established biomarkers of dietary n-6 and n-3 PUFA intake, respectively.OBJECTIVE: To examine if circulating fatty acids derived from two commonly applied metabolomics platforms (using NMR and LC-MS) provide similar information compared to GC in two pooled population-based cohorts, one patient cohort, and in a randomized controlled trial (RCT).
    METHODS: Spearman rank correlations were conducted between LA and DHA in cholesteryl esters (CE) from GC and whole serum/plasma LA and DHA from the metabolomics platforms in a pooled population-based cohort of men and women (n ˜ 1100) (primary analysis). Secondary correlation analyses included fatty acid classes such as n-3 PUFA, n-6 PUFA, saturated fatty acids (SFA), monounsaturated fatty acids (MUFA) and total PUFA. Additionally, correlations were investigated for LA, DHA and the five fatty acid classes in phospholipids (PL), triacylglycerols (TAG) and non-esterified fatty acids (NEFA) in a RCT of n = 60 as well as in a population with biopsy-verified non-alcoholic fatty liver disease (NAFLD) (n = 59). Misclassification was examined using cross-tabulation and visualized using alluvial plots.
    RESULTS: Moderate to strong correlations (r = 0.51-0.81) were observed for LA and DHA in multiple lipid fractions in all cohorts using the NMR platform. For the pooled cohort, LA (r = 0.67, P < 0.0001) and DHA (r = 0.68, P < 0.0001) assessed in CE were strongly correlated with LA and DHA derived using NMR. Nearly half (49%) were correctly classified into their respective quartiles. Using LC-MS, only DHA (r = 0.44, P < 0.0001) demonstrated moderate correlations with DHA from GC.
    CONCLUSIONS: Unless fatty acid data from GC analysis is available or feasible, NMR-based technology might be a better option than a LC-MS-based platform, at least for certain PUFA. This should be taken into account in future studies aiming to use circulating fatty acids as dietary biomarkers for the investigation of diet-disease relationships.
    Keywords:  Epidemiology; Fatty acids; Metabolomics; Nutrition; Validation
    DOI:  https://doi.org/10.1016/j.clnu.2022.10.005
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