bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2021‒08‒08
thirty-nine papers selected by
Giovanny Rodriguez Blanco
University of Edinburgh

  1. Cell Metab. 2021 Aug 03. pii: S1550-4131(21)00327-2. [Epub ahead of print]33(8): 1507-1509
      Lipid metabolism is altered in the acidic tumor microenvironment. Here, the authors show that polyunsaturated fatty acid supplementation, together with concomitant inhibition of lipid droplet biogenesis, induces ferroptosis in acidic cancer cells. These findings highlight the potential to exploit cancer dependence on exogenous lipids as a therapeutic vulnerability.
  2. Anal Chem. 2021 Aug 06.
      The accurate processing of complex liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) data from biological samples is a major challenge for metabolomics, proteomics, and related approaches. Here, we present the pipelines and systems for threshold-avoiding quantification (PASTAQ) LC-MS/MS preprocessing toolset, which allows highly accurate quantification of data-dependent acquisition LC-MS/MS datasets. PASTAQ performs compound quantification using single-stage (MS1) data and implements novel algorithms for high-performance and accurate quantification, retention time alignment, feature detection, and linking annotations from multiple identification engines. PASTAQ offers straightforward parameterization and automatic generation of quality control plots for data and preprocessing assessment. This design results in smaller variance when analyzing replicates of proteomes mixed with known ratios and allows the detection of peptides over a larger dynamic concentration range compared to widely used proteomics preprocessing tools. The performance of the pipeline is also demonstrated in a biological human serum dataset for the identification of gender-related proteins.
  3. Cancer Res. 2021 Aug 06. pii: canres.3863.2020. [Epub ahead of print]
      Dysregulated lipid metabolism is a prominent feature of prostate cancer that is driven by androgen receptor (AR) signaling. Here we used quantitative mass spectrometry to define the "lipidome" in prostate tumors with matched benign tissues (n=21), independent unmatched tissues (n=47), and primary prostate explants cultured with the clinical AR antagonist enzalutamide (n=43). Significant differences in lipid composition were detected and spatially visualized in tumors compared to matched benign samples. Notably, tumors featured higher proportions of monounsaturated lipids overall and elongated fatty acid chains in phosphatidylinositol and phosphatidylserine lipids. Significant associations between lipid profile and malignancy were validated in unmatched samples, and phospholipid composition was characteristically altered in patient tissues that responded to AR inhibition. Importantly, targeting tumor-related lipid features via inhibition of acetyl-CoA carboxylase 1 significantly reduced cellular proliferation and induced apoptosis in tissue explants. This first characterization of the prostate cancer lipidome in clinical tissues reveals enhanced fatty acid synthesis, elongation, and desaturation as tumor-defining features, with potential for therapeutic targeting.
  4. Nat Protoc. 2021 Aug 04.
      T cells are integral players in the adaptive immune system that readily adapt their metabolism to meet their energetic and biosynthetic needs. A major hurdle to understand physiologic T-cell metabolism has been the differences between in vitro cell culture conditions and the complex in vivo milieu. To address this, we have developed a protocol that merges traditional immunology infection models with whole-body metabolite infusion and mass-spectrometry-based metabolomic profiling to assess T-cell metabolism in vivo. In this protocol, pathogen-infected mice are infused via the tail vein with an isotopically labeled metabolite (2-6 h), followed by rapid magnetic bead isolation to purify T-cell populations (<1 h) and then stable isotope labeling analysis conducted by mass spectrometry (~1-2 d). This procedure enables researchers to evaluate metabolic substrate utilization into central carbon metabolic pathways (i.e., glycolysis and the tricarboxylic acid cycle) by specific T-cell subpopulations in the context of physiological immune responses in vivo.
  5. J Proteome Res. 2021 Aug 03.
      Lung cancer (LC) is a widespread cancer that is the cause of the highest mortality rate accounting for 25% of all cancer deaths. To date, most LC patients are diagnosed at the advanced stage owing to the lack of obvious symptoms in the early stage and the limitations of current clinical diagnostic techniques. Therefore, developing a high throughput technique for early screening is of great importance. In this work, we established an effective and rapid salivary metabolic analysis platform for early LC diagnosis and combined metabolomics and transcriptomics to reveal the metabolic fluctuations correlated to LC. Saliva samples were collected from a total of 150 volunteers including 89 patients with early LC, 11 patients with advanced LC, and 50 healthy controls. The metabolic profiling of noninvasive samples was investigated on an ultralow noise TELDI-MS platform. In addition, data normalization methods were screened and assessed to overcome the MS signal variation caused by individual difference for biomarker mining. For untargeted metabolic profiling of saliva samples, around 264 peaks could be reliably detected in each sample. After multivariate analysis, 23 metabolites were sorted out and verified to be related to the dysfunction of the amino acid and nucleotide metabolism in early LC. Notably, transcriptomic data from online TCGA repository were utilized to support findings from the salivary metabolomics experiment, including the disorder of amino acid biosynthesis and amino acid metabolism. Based on the verified differential metabolites, early LC patients could be clearly distinguished from healthy controls with a sensitivity of 97.2% and a specificity of 92%. The ultralow noise TELDI-MS platform displayed satisfactory ability to explore salivary metabolite information and discover potential biomarkers that may help develop a noninvasive screening tool for early LC.
    Keywords:  high-throughput; lung cancer; noninvasive diagnosis; salivary metabolomics
  6. Metabolites. 2021 Jul 20. pii: 466. [Epub ahead of print]11(7):
      Major depressive disorder (MDD) is a neuropsychiatric illness with an increasing incidence and a shortfall of efficient diagnostic tools. Interview-based diagnostic tools and clinical examination often lead to misdiagnosis and inefficient systematic treatment selection. Diagnostic and treatment monitoring biomarkers are warranted for MDD. Thus, the emerging field of metabolomics is a promising tool capable of portraying the metabolic repertoire of biomolecules from biological samples in a minimally invasive fashion. Herein, we report an untargeted metabolomic profiling performed in plasma samples of 11 MDD patients, at baseline (MDD1) and at 12 weeks following antidepressant therapy with escitalopram (MDD2), and in 11 healthy controls (C), using ultra-high performance liquid chromatography coupled with electrospray ionization-quadrupole-time of flight-mass spectrometry (UHPLC-QTOF-(ESI+)-MS). We found two putative metabolites ((phosphatidylserine PS (16:0/16:1) and phosphatidic acid PA (18:1/18:0)) as having statistically significant increased levels in plasma samples of MDD1 patients compared to healthy subjects. ROC analysis revealed an AUC value of 0.876 for PS (16:0/16:1), suggesting a potential diagnostic biomarker role. In addition, PS (18:3/20:4) was significantly decreased in MDD2 group compared to MDD1, with AUC value of 0.785.
    Keywords:  LC-MS; biomarkers; depression; lipids; metabolomics
  7. EXCLI J. 2021 ;20 1170-1183
      Thyroid cancers (TCs) are the most prevalent malignancy of the endocrine system and the seventh most common cancer in women. According to estimates from the Global Cancer Observatory (GCO) in 2020, the incidence of thyroid cancer globally was 586,000 cases. As thyroid cancer incidences have dramatically increased, identifying the most important metabolic pathways and biochemical markers involved in thyroid tumorigenesis can be critical strategies for controlling the prevalence and ultimately treatment of this disease. Cancer cells undergo cellular metabolism and energy alteration in order to promote cell proliferation and invasion. Glutamine is one of the most abundant free amino acids in the human body that contributes to cancer metabolic remodeling as a carbon and nitrogen source to sustain cell growth and proliferation. In the present review, glutamine metabolism and its regulation in cancer cells are highlighted. Thereafter, emphasis is given to the perturbation of glutamine metabolism in thyroid cancer, focusing on metabolomics studies.
    Keywords:  amino acids; glutamine; metabolism; metabolomics; thyroid cancers
  8. Cell Metab. 2021 Aug 03. pii: S1550-4131(21)00320-X. [Epub ahead of print]33(8): 1509-1511
      The tumor microenvironment is immunosuppressive. Here we preview two recent studies from Ma et al. (2021) in Cell Metabolism and Xu et al. (2021) in Immunity that describe a key role of T cell-expressed CD36 in enhancing lipid uptake and mediating lipid peroxidation that ultimately leads to CD8+ T cell dysfunction, ferroptosis, and reduced anti-tumor function.
  9. Mol Omics. 2021 Aug 06.
      Metabolomics, especially the large-scale untargeted metabolomics, generates massive amounts of data on a regular basis, which often needs to be filtered, screened, analyzed and annotated via a variety of approaches. Data-dependent-acquisition (DDA) mode including inclusion and exclusion rules for tandem mass spectrometry (MS) is routinely used to perform such analyses. While the parameters of data acquisition are important in these processes, there is a lack of systematic studies on these parameters that can be used in data collection to generate metabolic features for molecular-network (MN) analysis on the Global Natural Products Social Molecular Networking (GNPS) platform. To explore the key parameters that impact the formation and quality of MNs, several data-acquisition parameters for metabolomic studies were proposed in this study. The influences of MS1 resolution, normalized collision energy (NCE), intensity threshold, and exclusion time on GNPS analyses were demonstrated. Moreover, an optimization workflow dedicated to Thermo Scientific QE Hybrid Orbitrap instruments is described, and a comparison of phytochemical contents from two forms of black raspberry extract was performed based on the GNPS MN results. Overall, we expect this study to provide additional thoughts on developing a natural-product-analysis workflow using the GNPS network, and to shed some light on future analyses that utilize similar instrumental setups.
  10. Lipids Health Dis. 2021 Aug 04. 20(1): 85
      BACKGROUND: Accumulating evidence indicates alterations in lipid metabolism and lipid composition in neoplastic tissue. Earlier nuclear magnetic resonance studies showed that the contents of major lipid groups, such as triacylglycerols, phospholipids and cholesterol, are changed in colon cancer tissue.METHODS: In this study, a more detailed analysis of lipids in cancer and tumor adjacent tissues from colorectal cancer patients, using liquid chromatography-mass spectrometry, allowed for comparison of 199 different lipids between cancer tissue and tumor adjacent tissue using principal component analysis.
    RESULTS: Significant differences were found in 67 lipid compounds between the two types of tissue; many of these lipid compounds are bioactive lipids such as ceramides, lysophospholipids or sterols and can influence the development of cancer. Additionally, increased levels of phospholipids and sphingolipids were present, which are major components of the cell membrane, and increases in these lipids can lead to changes in cell membrane properties.
    CONCLUSIONS: This study showed that many complex lipids are significantly increased or decreased in colon cancer tissue, reflecting significant alterations in lipid metabolism. This knowledge can be used for the selection of potential molecular targets of novel anticancer strategies based on the modulation of lipid metabolism and the composition of the cell membrane in colorectal cancer cells.
    Keywords:  Colorectal cancer; Liquid chromatography–mass spectrometry; Phospholipids; Sphingolipids; Triacylglycerols
  11. J Proteome Res. 2021 Aug 02.
      While identification-centric (qualitative) top-down proteomics (TDP) has seen rapid progress in the recent past, the quantification of intact proteoforms within complex proteomes is still challenging. The by far mostly applied approach is label-free quantification, which, however, provides limited multiplexing capacity, and its use in combination with multidimensional separation is encountered with a number of problems. Isobaric labeling, which is a standard quantification approach in bottom-up proteomics, circumvents these limitations. Here, we introduce the application of thiol-directed isobaric labeling for quantitative TDP. For this purpose, we analyzed the labeling efficiency and optimized tandem mass spectrometry parameters for optimal backbone fragmentation for identification and reporter ion formation for quantification. Two different separation schemes, gel-eluted liquid fraction entrapment electrophoresis × liquid chromatography-mass spectrometry (LC-MS) and high/low-pH LC-MS, were employed for the analyses of either Escherichia coli (E. coli) proteomes or combined E. coli/yeast samples (two-proteome interference model) to study potential ratio compression. While the thiol-directed labeling introduces a bias in the quantifiable proteoforms, being restricted to Cys-containing proteoforms, our approach showed excellent accuracy in quantification, which is similar to that achievable in bottom-up proteomics. For example, 876 proteoforms could be quantified with high accuracy in an E. coli lysate. The LC-MS data were deposited to the ProteomeXchange with the dataset identifier PXD026310.
    Keywords:  GElFrEE; LC−MS; isobaric labeling; post-translational modification; proteoform; proteolytic processing; quantitative proteomics; tandem mass tag; terminomics
  12. Adv Cancer Res. 2021 ;pii: S0065-230X(21)00049-X. [Epub ahead of print]152 103-177
      Metabolism is an important part of tumorigenesis as well as progression. The various cancer metabolism pathways, such as glucose metabolism and glutamine metabolism, directly regulate the development and progression of cancer. The pathways by which the cancer cells rewire their metabolism according to their needs, surrounding environment and host tissue conditions are an important area of study. The regulation of these metabolic pathways is determined by various oncogenes, tumor suppressor genes, as well as various constituent cells of the tumor microenvironment. Expanded studies on metabolism will help identify efficient biomarkers for diagnosis and strategies for therapeutic interventions and countering ways by which cancers may acquire resistance to therapy.
    Keywords:  Cancer; Hypoxia; Metabolism; Therapy; Warburg effect
  13. Biomed Chromatogr. 2021 Aug 07. e5224
      A liquid chromatography-tandem mass spectrometry method was developed and validated to quantify alectinib, crizotinib, erlotinib and gefitinib. This assay can be combined with our method for osimertinib, allowing quantification of the most used ALK- and EGFR- tyrosine kinase inhibitors (TKIs) in non-small cell lung cancer with a single-assay setup. Chromatographic separation was performed on a HyPURITY® C18 analytical column using an elution gradient of ammonium acetate in water and in methanol, both acidified with formic acid 0,1%. Detection and quantification were performed by a triple quad mass spectrometer with an electrospray ionization interface. This method led to robust results, as the selectivity, carry-over, precision and accuracy met all pre-specified requirements. The assay was validated over a linear range of 100 - 2000 ng/mL for alectinib and erlotinib and 50 - 1000 ng/mL for crizotinib and gefitinib. Alectinib, crizotinib, erlotinib and gefitinib were all stable for at least 4 hours in whole blood (at room temperature (RT) and at 4°C) and for at least one month in EDTA-plasma when stored at -80°C, while osimertinib proved to be unstable at RT. Although high-performance liquid chromatography was used, the run time was short and comparable with other methods using ultra-high performance liquid chromatography.
    Keywords:  LC-MS/MS analysis; non-small cell lung cancer; tyrosine kinase inhibitors; validation
  14. Metabolites. 2021 Jul 04. pii: 440. [Epub ahead of print]11(7):
      A 4-week dietary intervention with a starch- and sucrose-restricted diet (SSRD) was conducted in patients with irritable bowel syndrome (IBS) to examine the metabolic profile in relation to nutrient intake and gastrointestinal symptoms. IBS patients were randomized to SSRD intervention (n = 69) or control continuing with their ordinary food habits (n = 22). Food intake was registered and the questionnaires IBS-symptoms severity scale (IBS-SSS) and visual analog scale for IBS (VAS-IBS) were completed. Metabolomics untargeted analysis was performed by gas chromatography mass spectrometry (GC-MS) and liquid chromatography mass spectrometry (LC-MS) in positive and negative ionization modes. SSRD led to marked changes in circulating metabolite concentrations at the group level, most prominent for reduced starch intake and increased polyunsaturated fat, with small changes in the control group. On an individual level, the correlations were weak. The marked reduction in gastrointestinal symptoms did not correlate with the metabolic changes. SSRD was observed by clear metabolic effects mainly related to linoleic acid metabolism, fatty acid biosynthesis, and beta-oxidation.
    Keywords:  IBS; dietary advice; metabolic profiling; metabolomics; starch; sucrose
  15. Mol Cell Proteomics. 2021 Jul 28. pii: S1535-9476(21)00098-0. [Epub ahead of print] 100126
      Oral microbiome influences human health, specifically pre- and type 2 diabetes (Pre-DM/DM) and periodontal diseases (PD), through complex microbial interactions. To explore these relations, we performed 16S rDNA sequencing, metabolomics, lipidomics, and proteomics analyses on supragingival dental plaque collected from individuals with Pre-DM/DM (n=39), Pre-DM/DM and PD (n=37), PD alone (n=11), or neither (n=10). We identified on average 2,790 operational taxonomic units and 2,025 microbial and host proteins per sample and quantified 110 metabolites and 415 lipids. Plaque samples from Pre-DM/DM patients contained higher abundance of Fusobacterium and Tannerella vs. plaques from metabolically healthy. Phosphatidylcholines, plasmenyl-phosphatidylcholines, ceramides containing non-OH fatty acids, and host proteins related to actin filament rearrangement were elevated in plaques from PD vs. non-PD. Cross-omic correlation analysis enabled the detection of a strong association between Lautropia and mono-methyl phosphatidylethanolamine (PE-NMe), striking because synthesis of PE-NMe is uncommon in oral bacteria. Lipidomics analysis of in vitro cultures of Lautropia mirabilis confirmed the bacteria's synthesis of PE-NMe. This comprehensive analysis revealed a novel microbial metabolic pathway and significant associations of host-derived proteins with PD.
  16. Metabolites. 2021 Jul 20. pii: 467. [Epub ahead of print]11(7):
      Improved methods are required for investigating the systemic metabolic effects of SARS-CoV-2 infection and patient stratification for precision treatment. We aimed to develop an effective method using lipid profiles for discriminating between SARS-CoV-2 infection, healthy controls, and non-SARS-CoV-2 respiratory infections. Targeted liquid chromatography-mass spectrometry lipid profiling was performed on discovery (20 SARS-CoV-2-positive; 37 healthy controls; 22 COVID-19 symptoms but SARS-CoV-2negative) and validation (312 SARS-CoV-2-positive; 100 healthy controls) cohorts. Orthogonal projection to latent structure-discriminant analysis (OPLS-DA) and Kruskal-Wallis tests were applied to establish discriminant lipids, significance, and effect size, followed by logistic regression to evaluate classification performance. OPLS-DA reported separation of SARS-CoV-2 infection from healthy controls in the discovery cohort, with an area under the curve (AUC) of 1.000. A refined panel of discriminant features consisted of six lipids from different subclasses (PE, PC, LPC, HCER, CER, and DCER). Logistic regression in the discovery cohort returned a training ROC AUC of 1.000 (sensitivity = 1.000, specificity = 1.000) and a test ROC AUC of 1.000. The validation cohort produced a training ROC AUC of 0.977 (sensitivity = 0.855, specificity = 0.948) and a test ROC AUC of 0.978 (sensitivity = 0.948, specificity = 0.922). The lipid panel was also able to differentiate SARS-CoV-2-positive individuals from SARS-CoV-2-negative individuals with COVID-19-like symptoms (specificity = 0.818). Lipid profiling and multivariate modelling revealed a signature offering mechanistic insights into SARS-CoV-2, with strong predictive power, and the potential to facilitate effective diagnosis and clinical management.
    Keywords:  COVID-19; SARS-CoV-2; infectious disease; lipidomics; lipids; liquid chromatography-mass spectrometry (LC-MS); metabolic phenotyping
  17. Molecules. 2021 Jul 29. pii: 4610. [Epub ahead of print]26(15):
      Cocaine toxicity has been a subject of study because cocaine is one of the most common and potent drugs of abuse. In the current study the effect of cocaine on human liver cancer cell line (HepG2) was assessed. Cocaine toxicity (IC50) on HepG2 cells was experimentally calculated using an XTT assay at 2.428 mM. The metabolic profile of HepG2 cells was further evaluated to investigate the cytotoxic activity of cocaine at 2 mM at three different time points. Cell medium and intracellular material samples were analyzed with a validated HILIC-MS/MS method for targeted metabolomics on an ACQUITY Amide column in gradient mode with detection on a triple quadrupole mass spectrometer in multiple reaction monitoring. About 106 hydrophilic metabolites from different metabolic pathways were monitored. Multivariate analysis clearly separated the studied groups (cocaine-treated and control samples) and revealed potential biomarkers in the extracellular and intracellular samples. A predominant effect of cocaine administration on alanine, aspartate, and glutamate metabolic pathway was observed. Moreover, taurine and hypotaurine metabolism were found to be affected in cocaine-treated cells. Targeted metabolomics managed to reveal metabolic changes upon cocaine administration, however deciphering the exact cocaine cytotoxic mechanism is still challenging.
    Keywords:  HepG2; cocaine toxicity; liquid chromatography; mass spectrometry; targeted metabolomics
  18. Int J Mol Sci. 2021 Jul 29. pii: 8149. [Epub ahead of print]22(15):
      Cellular senescence is a form of proliferative arrest triggered in response to a wide variety of stimuli and characterized by unique changes in cell morphology and function. Although unable to divide, senescent cells remain metabolically active and acquire the ability to produce and secrete bioactive molecules, some of which have recognized pro-inflammatory and/or pro-tumorigenic actions. As expected, this "senescence-associated secretory phenotype (SASP)" accounts for most of the non-cell-autonomous effects of senescent cells, which can be beneficial or detrimental for tissue homeostasis, depending on the context. It is now evident that many features linked to cellular senescence, including the SASP, reflect complex changes in the activities of mTOR and other metabolic pathways. Indeed, the available evidence indicates that mTOR-dependent signaling is required for the maintenance or implementation of different aspects of cellular senescence. Thus, depending on the cell type and biological context, inhibiting mTOR in cells undergoing senescence can reverse senescence, induce quiescence or cell death, or exacerbate some features of senescent cells while inhibiting others. Interestingly, autophagy-a highly regulated catabolic process-is also commonly upregulated in senescent cells. As mTOR activation leads to repression of autophagy in non-senescent cells (mTOR as an upstream regulator of autophagy), the upregulation of autophagy observed in senescent cells must take place in an mTOR-independent manner. Notably, there is evidence that autophagy provides free amino acids that feed the mTOR complex 1 (mTORC1), which in turn is required to initiate the synthesis of SASP components. Therefore, mTOR activation can follow the induction of autophagy in senescent cells (mTOR as a downstream effector of autophagy). These functional connections suggest the existence of autophagy regulatory pathways in senescent cells that differ from those activated in non-senescence contexts. We envision that untangling these functional connections will be key for the generation of combinatorial anti-cancer therapies involving pro-senescence drugs, mTOR inhibitors, and/or autophagy inhibitors.
    Keywords:  autophagy; mTOR; senescence
  19. Cancers (Basel). 2021 Jul 28. pii: 3804. [Epub ahead of print]13(15):
      Endometrial cancer is the most common gynaecological malignancy in high-income countries and its incidence is rising. Early detection, aided by highly sensitive and specific biomarkers, has the potential to improve outcomes as treatment can be provided when it is most likely to effect a cure. Sequential window acquisition of all theoretical mass spectra (SWATH-MS), an accurate and reproducible platform for analysing biological samples, offers a technological advance for biomarker discovery due to its reproducibility, sensitivity and potential for data re-interrogation. SWATH-MS requires a spectral library in order to identify and quantify peptides from multiplexed mass spectrometry data. Here we present a bespoke spectral library of 154,206 transitions identifying 19,394 peptides and 2425 proteins in the cervico-vaginal fluid of postmenopausal women with, or at risk of, endometrial cancer. We have combined these data with a library of over 6000 proteins generated based on mass spectrometric analysis of two endometrial cancer cell lines. This unique resource enables the study of protein biomarkers for endometrial cancer detection in cervico-vaginal fluid. Data are available via ProteomeXchange with unique identifier PXD025925.
    Keywords:  SWATH-MS; cervico-vaginal fluid; endometrial cancer; mass spectrometry; non-invasive; peptide; protein; proteomics; spectral library
  20. Angew Chem Int Ed Engl. 2021 Aug 02.
      The microbiome has a fundamental impact on the human host's physiology through the production of highly reactive compounds that can lead to disease development. One class of such compounds are carbonyl-containing metabolites, which are involved in diverse biochemical processes. Mass spectrometry is the method of choice for analysis of metabolites but carbonyls are analytically challenging. Herein, we have developed a new chemical biology tool using chemoselective modification to overcome analytical limitations. Two isotopic probes allow for the simultaneous and semi-quantitative analysis at femto- and attomole quantities, and detection of more than 200 metabolites in human fecal, urine and plasma samples. This comprehensive mass spectrometric analysis enhances the scope of metabolomics-driven biomarker discovery. We anticipate that our Chemical Biology tool will be of general use in metabolomics analysis to obtain a better understanding of microbial interactions with the human host and disease development.
    Keywords:  Bioorganic Chemistry; Mass Spectrometry; chemoselectivity; metabolites; microbiome
  21. Angew Chem Int Ed Engl. 2021 Aug 02.
      In this report, we perform structure validation of recently reported RNA phosphorothioate (PT) modifications, a new set of epitranscriptome marks found in bacteria and eukaryotes including humans. By comparing synthetic PT-containing diribonucleotides with native species in RNA hydrolysates by high resolution mass spectrometry (MS), metabolic stable isotope labeling, and PT-specific iodine-desulfurization, we disprove the existence of PTs in RNA from E.   coli , S. cerevisiae , human cell lines, and mouse brain. Furthermore, we discuss how an MS artifact led to the initial misidentification of 2'-O-methylated diribonucleotides as RNA phosphorothioates. To aid structure validation, we present a detailed guideline for MS analysis of RNA hydrolysates, emphasizing how the chosen RNA hydrolysis protocol can be a decisive factor in discovering and quantifying RNA modifications in biological samples.
    Keywords:  RNA phosphorothioate RNA modification RNA mass spectrometry stucture validation epitranscriptome analysis
  22. Cancers (Basel). 2021 Jul 24. pii: 3727. [Epub ahead of print]13(15):
      BACKGROUND: Dysregulated lipid metabolism is emerging as a hallmark in several malignancies, including ovarian cancer (OC). Specifically, metastatic OC is highly dependent on lipid-rich omentum. We aimed to investigate the therapeutic value of targeting lipid metabolism in OC. For this purpose, we studied the role of PCSK9, a cholesterol-regulating enzyme, in OC cell survival and its downstream signaling. We also investigated the cytotoxic efficacy of a small library of metabolic (n = 11) and mTOR (n = 10) inhibitors using OC cell lines (n = 8) and ex vivo patient-derived cell cultures (PDCs, n = 5) to identify clinically suitable drug vulnerabilities. Targeting PCSK9 expression with siRNA or PCSK9 specific inhibitor (PF-06446846) impaired OC cell survival. In addition, overexpression of PCSK9 induced robust AKT phosphorylation along with increased expression of ERK1/2 and MEK1/2, suggesting a pro-survival role of PCSK9 in OC cells. Moreover, our drug testing revealed marked differences in cytotoxic responses to drugs targeting metabolic pathways of high-grade serous ovarian cancer (HGSOC) and low-grade serous ovarian cancer (LGSOC) PDCs. Our results show that targeting PCSK9 expression could impair OC cell survival, which warrants further investigation to address the dependency of this cancer on lipogenesis and omental metastasis. Moreover, the differences in metabolic gene expression and drug responses of OC PDCs indicate the existence of a metabolic heterogeneity within OC subtypes, which should be further explored for therapeutic improvements.
    Keywords:  PCSK9; drug testing; mTOR; metabolism; omentum; ovarian cancers; rapalogs
  23. Cell Rep. 2021 Aug 03. pii: S2211-1247(21)00914-1. [Epub ahead of print]36(5): 109487
      Ketone bodies are bioactive metabolites that function as energy substrates, signaling molecules, and regulators of histone modifications. β-hydroxybutyrate (β-OHB) is utilized in lysine β-hydroxybutyrylation (Kbhb) of histones, and associates with starvation-responsive genes, effectively coupling ketogenic metabolism with gene expression. The emerging diversity of the lysine acylation landscape prompted us to investigate the full proteomic impact of Kbhb. Global protein Kbhb is induced in a tissue-specific manner by a variety of interventions that evoke β-OHB. Mass spectrometry analysis of the β-hydroxybutyrylome in mouse liver revealed 891 sites of Kbhb within 267 proteins enriched for fatty acid, amino acid, detoxification, and one-carbon metabolic pathways. Kbhb inhibits S-adenosyl-L-homocysteine hydrolase (AHCY), a rate-limiting enzyme of the methionine cycle, in parallel with altered metabolite levels. Our results illuminate the role of Kbhb in hepatic metabolism under ketogenic conditions and demonstrate a functional consequence of this modification on a central metabolic enzyme.
    Keywords:  AHCY; S-adenosyl-L-homocysteine hydrolase; ketogenesis; ketogenic diet; liver metabolism; lysine acylation; methionine cycle; β-hydroxybutyrate; β-hydroxybutyrylation
  24. Oncogene. 2021 Jul 31.
      Cancer cells exhibit dysregulation of critical genes including those involved in lipid biosynthesis, with subsequent defects in metabolism. Here, we show that ELOngation of Very Long chain fatty acids protein 4 (ELOVL4), a rate-limiting enzyme in the biosynthesis of very-long polyunsaturated fatty acids (n-3, ≥28 C), is expressed and transcriptionally repressed by the oncogene MYCN in neuroblastoma cells. In keeping, ELOVL4 positively regulates neuronal differentiation and lipids droplets accumulation in neuroblastoma cells. At the molecular level we found that MYCN binds to the promoter of ELOVL4 in close proximity to the histone deacetylases HDAC1, HDAC2, and the transcription factor Sp1 that can cooperate in the repression of ELOVL4 expression. Accordingly, in vitro differentiation results in an increase of fatty acid with 34 carbons with 6 double bonds (FA34:6); and when MYCN is silenced, FA34:6 metabolite is increased compared with the scrambled. In addition, analysis of large neuroblastoma datasets revealed that ELOVL4 expression is highly expressed in localized clinical stages 1 and 2, and low in high-risk stages 3 and 4. More importantly, high expression of ELOVL4 stratifies a subsets of neuroblastoma patients with good prognosis. Indeed, ELOVL4 expression is a marker of better overall clinical survival also in MYCN not amplified patients and in those with neuroblastoma-associated mutations. In summary, our findings indicate that MYCN, by repressing the expression of ELOVL4 and lipid metabolism, contributes to the progression of neuroblastoma.
  25. Metab Eng Commun. 2021 Dec;13 e00177
      13C-based metabolic flux analysis (13C-MFA) is an essential tool for estimating intracellular metabolic flux levels in metabolic engineering and biology. In 13C-MFA, a metabolic flux distribution that explains the observed isotope labeling data was computationally estimated using a non-linear optimization method. Herein, we report the development of mfapy, an open-source Python package developed for more flexibility and extensibility for 13C-MFA. mfapy compels users to write a customized Python code by describing each step in the data analysis procedures of the isotope labeling experiments. The flexibility and extensibility provided by mfapy can support trial-and-error performance in the routine estimation of metabolic flux distributions, experimental design by computer simulations of 13C-MFA experiments, and development of new data analysis techniques for stable isotope labeling experiments. mfapy is available to the public from the Github repository (
    Keywords:  13C-based metabolic flux analysis; Experimental design; Non-linear optimization; Open-source software; Python package
  26. Cancer Metab. 2021 Aug 04. 9(1): 30
      BACKGROUND: Cholangiocarcioma (CCA) treatment is challenging because most of the patients are diagnosed when the disease is advanced, and cancer recurrence is the main problem after treatment, leading to low survival rates. Therefore, our understanding of the mechanism underlying CCA recurrence is essential in order to prevent CCA recurrence and improve patient outcomes.METHODS: We performed 1H-NMR and UPLC-MS-based metabolomics on the CCA serum. The differential metabolites were further analyzed using pathway analysis and potential biomarker identification.
    RESULTS: At an early stage, the metabolites involved in energy metabolisms, such as pyruvate metabolism, and the TCA cycle, are downregulated, while most lipids, including TGs, PCs, PEs, and PAs, are upregulated in recurrence patients. This metabolic feature has been described in cancer stem-like cell (CSC) metabolism. In addition, the CSC markers CD44v6 and CD44v8-10 are associated with CD36 (a protein involved in lipid uptake) as well as with recurrence-free survival. We also found that citrate, sarcosine, succinate, creatine, creatinine and pyruvate, and TGs have good predictive values for CCA recurrence.
    CONCLUSION: Our study demonstrates the possible molecular mechanisms underlying CCA recurrence, and these may associate with the existence of CSCs. The metabolic change involved in the recurrence pathway might be used to determine biomarkers for predicting CCA recurrence.
    Keywords:  Biomarker; Cancer recurrence; Cholangiocarcinoma; Lipidomics; Metabolomics
  27. Metabolites. 2021 Jul 01. pii: 434. [Epub ahead of print]11(7):
      Identifying the changes in endogenous metabolites in response to intrinsic and extrinsic factors has excellent potential to obtain an understanding of cells, biofluids, tissues, or organisms' functions and interactions with the environment. The advantages provided by the metabolomics strategy have promoted studies in bone research fields, including an understanding of bone cell behaviors, diagnosis and prognosis of diseases, and the development of treatment methods such as implanted biomaterials. This review article summarizes the metabolism changes during osteogenesis, osteoclastogenesis, and immunoregulation in hard tissue. The second section of this review is dedicated to describing and discussing metabolite changes in the most relevant bone diseases: osteoporosis, bone injuries, rheumatoid arthritis, and osteosarcoma. We consolidated the most recent finding of the metabolites and metabolite pathways affected by various bone disorders. This collection can serve as a basis for future metabolomics-driven bone research studies to select the most relevant metabolites and metabolic pathways. Additionally, we summarize recent metabolic studies on metabolomics for the development of bone disease treatment including biomaterials for bone engineering. With this article, we aim to provide a comprehensive summary of metabolomics in bone research, which can be helpful for interdisciplinary researchers, including material engineers, biologists, and clinicians.
    Keywords:  biomaterials; bone homeostasis; bone regeneration; metabolomics; osteoporosis; osteosarcoma
  28. Adv Protein Chem Struct Biol. 2021 ;pii: S1876-1623(21)00021-3. [Epub ahead of print]127 161-216
      With the tremendous developments in the fields of biological and medical technologies, huge amounts of data are generated in the form of genomic data, images in medical databases or as data on protein sequences, and so on. Analyzing this data through different tools sheds light on the particulars of the disease and our body's reactions to it, thus, aiding our understanding of the human health. Most useful of these tools is artificial intelligence and deep learning (DL). The artificially created neural networks in DL algorithms help extract viable data from the datasets, and further, to recognize patters in these complex datasets. Therefore, as a part of machine learning, DL helps us face all the various challenges that come forth during protein prediction, protein identification and their quantification. Proteomics is the study of such proteins, their structures, features, properties and so on. As a form of data science, Proteomics has helped us progress excellently in the field of genomics technologies. One of the major techniques used in proteomics studies is mass spectrometry (MS). However, MS is efficient with analysis of large datasets only with the added help of informatics approaches for data analysis and interpretation; these mainly include machine learning and deep learning algorithms. In this chapter, we will discuss in detail the applications of deep learning and various algorithms of machine learning in proteomics.
    Keywords:  Algorithms; Artificial intelligence; Biomarkers; Deep learning; Machine learning; Mass spectrometry; Proteomics
  29. Anal Bioanal Chem. 2021 Aug 04.
      Glycosylation is a ubiquitous co- and post-translational modification involved in the sorting, folding, and trafficking of proteins in biological systems; in humans, >50% of gene products are glycosylated with the cellular machinery of glycosylation compromising ~2% of the genome. Perturbations in glycosylation have been implicated in a variety of diseases including neurodegenerative diseases and certain types of cancer. However, understanding the relationship between a glycan and its biological role is often difficult due to the numerous glycan isomers that exist. To address this challenge, nanoflow liquid chromatography, ion mobility spectrometry, and mass spectrometry (nLC-IMS-MS) were combined with the Individuality Normalization when Labeling with the Isotopic Glycan Hydrazide Tags (INLIGHT™) strategy to study a series of glycan standards and those enzymatically released from the glycoproteins horseradish peroxidase, fetuin, and pooled human plasma. The combination of IMS and the natural (NAT) and stable-isotope label (SIL) in the INLIGHT™ strategy provided additional confidence for each glycan identification due to the mobility aligned NAT- and SIL-labeled glycans and further capabilities for isomer examinations. Additionally, molecular trend lines based on the IMS and MS dimensions were investigated for the INLIGHT™ derivatized glycans, facilitating rapid identification of putative glycans in complex biological samples.
    Keywords:  Glycomics; INLIGHT™; Ion mobility spectrometry; LC-IMS-MS; N-Linked glycans
  30. J Lipid Res. 2021 Jul 28. pii: S0022-2275(21)00082-1. [Epub ahead of print] 100100
      Choline phospholipids (PLs) such as phosphatidylcholine (PC) and 1-alkyl-2-acyl-sn-glycerophosphocholine (plasmanyl-PC) are important components for cell membranes, and also serve as a source of several lipid mediators. These lipids are biosynthesized in mammals in the final step of the CDP-choline pathway by the choline phosphotransferases CPT1 and CEPT1. However, the contributions of these enzymes to the de novo biosynthesis of lipids remain unknown. Here, we established and characterized CPT1- and CEPT1-deficient HEK293 cells. Immunohistochemical analyses revealed that CPT1 localizes to the trans-Golgi network and CEPT1 to the ER. Enzyme assays and metabolic labeling with radiolabeled choline demonstrated that loss of CEPT1 dramatically decreases choline PL biosynthesis. Quantitative PCR and reintroduction of CPT1 and CEPT1 revealed that the specific activity of CEPT1 was much higher than that of CPT1. LC-MS/MS analysis of newly synthesized lipid molecular species from deuterium-labeled choline also showed that these enzymes have similar preference for the synthesis of PC molecular species, but that CPT1 had higher preference for plasmanyl-PC with PUFA than did CEPT1. The endogenous levels of various PC molecular species were significantly reduced in CEPT1-deficient cells grown in 0.1% FBS medium. These results suggest that CEPT1 accounts for most choline PL biosynthesis activity, and that both enzymes are responsible for the production of different lipid molecular species in distinct organelles.
    Keywords:  Kennedy pathway; PUFA; choline phosphotransferase 1 (CPT1); choline/ethanolamine phosphotransferase 1 (CEPT1); phosphatidylcholine; phospholipid biosynthesis; phospholipid metabolism; phospholipids; radiolabeling; trans-Golgi network
  31. Clin Chem Lab Med. 2021 Jul 30.
      Human Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) infection activates a complex interaction host/virus, leading to the reprogramming of the host metabolism aimed at the energy supply for viral replication. Alterations of the host metabolic homeostasis strongly influence the immune response to SARS-CoV-2, forming the basis of a wide range of outcomes, from the asymptomatic infection to the onset of COVID-19 and up to life-threatening acute respiratory distress syndrome, vascular dysfunction, multiple organ failure, and death. Deciphering the molecular mechanisms associated with the individual susceptibility to SARS-CoV-2 infection calls for a system biology approach; this strategy can address multiple goals, including which patients will respond effectively to the therapeutic treatment. The power of metabolomics lies in the ability to recognize endogenous and exogenous metabolites within a biological sample, measuring their concentration, and identifying perturbations of biochemical pathways associated with qualitative and quantitative metabolic changes. Over the last year, a limited number of metabolomics- and lipidomics-based clinical studies in COVID-19 patients have been published and are discussed in this review. Remarkable alterations in the lipid and amino acid metabolism depict the molecular phenotype of subjects infected by SARS-CoV-2; notably, structural and functional data on the lipids-virus interaction may open new perspectives on targeted therapeutic interventions. Several limitations affect most metabolomics-based studies, slowing the routine application of metabolomics. However, moving metabolomics from bench to bedside cannot imply the mere determination of a given metabolite panel; rather, slotting metabolomics into clinical practice requires the conversion of metabolic patient-specific data into actionable clinical applications.
    Keywords:  COVID-19; amino acids; lipidomics; metabolomics; system biology
  32. Front Physiol. 2021 ;12 702826
      Branched-chain amino acids (BCAAs) are critical for skeletal muscle and whole-body anabolism and energy homeostasis. They also serve as signaling molecules, for example, being able to activate mammalian/mechanistic target of rapamycin complex 1 (mTORC1). This has implication for macronutrient metabolism. However, elevated circulating levels of BCAAs and of their ketoacids as well as impaired catabolism of these amino acids (AAs) are implicated in the development of insulin resistance and its sequelae, including type 2 diabetes, cardiovascular disease, and of some cancers, although other studies indicate supplements of these AAs may help in the management of some chronic diseases. Here, we first reviewed the catabolism of these AAs especially in skeletal muscle as this tissue contributes the most to whole body disposal of the BCAA. We then reviewed emerging mechanisms of control of enzymes involved in regulating BCAA catabolism. Such mechanisms include regulation of their abundance by microRNA and by post translational modifications such as phosphorylation, acetylation, and ubiquitination. We also reviewed implications of impaired metabolism of BCAA for muscle and whole-body metabolism. We comment on outstanding questions in the regulation of catabolism of these AAs, including regulation of the abundance and post-transcriptional/post-translational modification of enzymes that regulate BCAA catabolism, as well the impact of circadian rhythm, age and mTORC1 on these enzymes. Answers to such questions may facilitate emergence of treatment/management options that can help patients suffering from chronic diseases linked to impaired metabolism of the BCAAs.
    Keywords:  branched-chain amino acids; catabolism; mTORC1; protein synthesis; skeletal muscle
  33. J Chromatogr A. 2021 Jul 24. pii: S0021-9673(21)00504-5. [Epub ahead of print]1653 462380
      Lipidomic samples are complex mixtures of structurally different species of a wide range of concentrations providing challenges in their characterization. In this work, we present a proof of concept for the application of a simple microgradient liquid chromatography device on the detailed analysis of lipid classes. Our lipidomic analysis is based on a lipid class microgradient fractionation of a total lipid extract using an in-house-prepared hydrophilic interaction liquid chromatography microcolumn followed by RP-LC/MS of the collected lipid class fractions. The final fractionation method uses a 40-mm-long microcolumn of 500 μm ID with silica stationary phase obtained from a commercially available chromatographic column and the microgradient of the mobile phase prepared in a microsyringe using methyl tert-butyl ether (MTBE) - methanol - water - ammonium acetate mixtures of various elution strengths. MTBE total lipid extract is directly separated by microgradient elution into lipid classes according to their polarity, which enables the collection of isolated fractions of most lipid classes. The method has been applied to the fractionation of porcine brain extract into nonpolar lipids, hexosylceramides, phosphoethanolamines, phosphocholines, sphingomyelins, and lysophosphocholines classes. Achieved repeatability, recovery, and advanced lipid coverage prove the applicability of the microgradient fractionation of total lipid extract for the comprehensive lipidomic analysis.
    Keywords:  Lipid class fractionation; Lipidomic analysis; Lipidomics; Microgradient separation; Sample preparation
  34. Cell Metab. 2021 Jul 30. pii: S1550-4131(21)00331-4. [Epub ahead of print]
      Exercise is a powerful driver of physiological angiogenesis during adulthood, but the mechanisms of exercise-induced vascular expansion are poorly understood. We explored endothelial heterogeneity in skeletal muscle and identified two capillary muscle endothelial cell (mEC) populations that are characterized by differential expression of ATF3/4. Spatial mapping showed that ATF3/4+ mECs are enriched in red oxidative muscle areas while ATF3/4low ECs lie adjacent to white glycolytic fibers. In vitro and in vivo experiments revealed that red ATF3/4+ mECs are more angiogenic when compared with white ATF3/4low mECs. Mechanistically, ATF3/4 in mECs control genes involved in amino acid uptake and metabolism and metabolically prime red (ATF3/4+) mECs for angiogenesis. As a consequence, supplementation of non-essential amino acids and overexpression of ATF4 increased proliferation of white mECs. Finally, deleting Atf4 in ECs impaired exercise-induced angiogenesis. Our findings illustrate that spatial metabolic angiodiversity determines the angiogenic potential of muscle ECs.
    Keywords:  amino acid metabolism; endothelial heterogeneity; endothelial metabolism; exercise; muscle angiogenesis; single-cell RNA-seq
  35. Cancers (Basel). 2021 Jul 28. pii: 3793. [Epub ahead of print]13(15):
      A high expression of the phosphoprotein osteopontin (OPN) has been associated with cancer progression in several tumor types, including breast cancer, hepatocarcinoma, ovarian cancer, and colorectal cancer (CRC). Interestingly, OPN is overexpressed in CRC and is associated with a poor prognosis linked to invasion and metastasis. Here, we review the regulation and functions of OPN with an emphasis on CRC. We examine how epigenetic and genetic regulators interact with the key signaling pathways involved in this disease. Then, we describe the role of OPN in cancer progression, including proliferation, survival, migration, invasion, and angiogenesis. Furthermore, we outline the interest of using OPN as a clinical biomarker, and discuss if and how osteopontin can be implemented as a routine assay in clinical laboratories for monitoring CRC patients. Finally, we discuss the use of OPN an attractive, but challenging, therapeutic target.
    Keywords:  biomarker; colorectal cancer (CRC); metastasis; osteopontin; therapeutic target
  36. Bioinformatics. 2021 Aug 06. pii: btab559. [Epub ahead of print]
      MOTIVATION: Lipids exhibit an essential role in cellular assembly and signaling. Dysregulation of these functions has been linked with many complications including obesity, diabetes, metabolic disorders, cancer, and more. Investigating lipid profiles in such conditions can provide insights into cellular functions and possible interventions. Hence the field of lipidomics is expanding in recent years. Even though the role of individual lipids in diseases has been investigated, there is no resource to perform disease enrichment analysis considering the cumulative association of a lipid set. To address this, we have implemented the LipiDisease web server. The tool analyzes millions of records from the PubMed biomedical literature database discussing lipids and diseases, predicts their association, and ranks them according to false discovery rates generated by random simulations. The tool takes into account 4270 diseases and 4798 lipids. Since the tool extracts the information from PubMed records, the number of diseases and lipids will be expanded over time as the biomedical literature grows.AVAILABILITY AND IMPLEMENTATION: The LipiDisease webserver can be freely accessed at
    SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
  37. J Proteome Res. 2021 Aug 03.
      The volume of proteomics and mass spectrometry data available in public repositories continues to grow at a rapid pace as more researchers embrace open science practices. Open access to the data behind scientific discoveries has become critical to validate published findings and develop new computational tools. Here, we present ppx, a Python package that provides easy, programmatic access to the data stored in ProteomeXchange repositories, such as PRIDE and MassIVE. The ppx package can be used as either a command line tool or a Python package to retrieve the files and metadata associated with a project when provided its identifier. To demonstrate how ppx enhances reproducible research, we used ppx within a Snakemake workflow to reanalyze a published data set with the open modification search tool ANN-SoLo and compared our reanalysis to the original results. We show that ppx readily integrates into workflows, and our reanalysis produced results consistent with the original analysis. We envision that ppx will be a valuable tool for creating reproducible analyses, providing tool developers easy access to data for development, testing, and benchmarking, and enabling the use of mass spectrometry data in data-intensive analyses. The ppx package is freely available and open source under the MIT license at
    Keywords:  FAIR; Python; bioinformatics; data access; data dissemination; data sharing; mass spectrometry; proteomics; repository; reproducibility