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  • 1
    Abstract: Gas chromatography using atmospheric pressure chemical ionization coupled to mass spectrometry (GC/APCI-MS) is an emerging metabolomics platform, providing much-enhanced capabilities for structural mass spectrometry as compared to traditional electron ionization (EI)-based techniques. To exploit the potential of GC/APCI-MS for more comprehensive metabolite annotation, a major bottleneck in metabolomics, we here present the novel R-based tool InterpretMSSpectrum assisting in the common task of annotating and evaluating in-source mass spectra as obtained from typical full-scan experiments. After passing a list of mass-intensity pairs, InterpretMSSpectrum locates the molecular ion (M0), fragment, and adduct peaks, calculates their most likely sum formula combination, and graphically summarizes results as an annotated mass spectrum. Using (modifiable) filter rules for the commonly used methoximated-trimethylsilylated (MeOx-TMS) derivatives, covering elemental composition, typical substructures, neutral losses, and adducts, InterpretMSSpectrum significantly reduces the number of sum formula candidates, minimizing manual effort for postprocessing candidate lists. We demonstrate the utility of InterpretMSSpectrum for 86 in-source spectra of derivatized standard compounds, in which rank-1 sum formula assignments were achieved in 84% of the cases, compared to only 63% when using mass and isotope information on the M0 alone. We further use, for the first time, automated annotation to evaluate the purity of pseudospectra generated by different metabolomics preprocessing tools, showing that automated annotation can serve as an integrative quality measure for peak picking/deconvolution methods. As an R package, InterpretMSSpectrum integrates flexibly into existing metabolomics pipelines and is freely available from CRAN ( https://cran.r-project.org/ ).
    Type of Publication: Journal article published
    PubMed ID: 27584561
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  • 2
    Abstract: Metabolomics, the analysis of potentially all small molecules within a biological system, has become a valuable tool for biomarker identification and the elucidation of biological processes. While metabolites are often present in complex mixtures at extremely different concentrations, the dynamic range of available analytical methods to capture this variance is generally limited. Here, we show that gas chromatography coupled to atmospheric pressure chemical ionization mass spectrometry (GC-APCI-MS), a state of the art analytical technology applied in metabolomics analyses, shows an average linear range (LR) of 2.39 orders of magnitude for a set of 62 metabolites from a representative compound mixture. We further developed a computational tool to extend this dynamic range on average by more than 1 order of magnitude, demonstrated with a dilution series of the compound mixture, using robust and automatic reconstruction of intensity values exceeding the detection limit. The tool is freely available as an R package (CorrectOverloadedPeaks) from CRAN ( https://cran.r-project.org/ ) and can be incorporated in a metabolomics data processing pipeline facilitating large screening assays.
    Type of Publication: Journal article published
    PubMed ID: 27377477
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  • 3
    Abstract: RATIONALE: A bottleneck in metabolic profiling of complex biological extracts is confident, non-supervised annotation of ideally all contained, chemically highly diverse small molecules. Recent computational strategies combining sum formula prediction with in silico fragmentation achieve confident de novo annotation, once the correct neutral mass of a compound is known. Current software solutions for automated adduct ion assignment, however, are either publicly unavailable or have been validated against only few experimental electrospray ionization (ESI) mass spectra. METHODS: We here present findMAIN (find Main Adduct IoN), a new heuristic approach for interpreting ESI mass spectra. findMAIN scores MS1 spectra based on explained intensity, mass accuracy and isotope charge agreement of adducts and related ionization products and annotates peaks of the (de)protonated molecule and adduct ions. The approach was validated against 1141 ESI positive mode spectra of chemically diverse standard compounds acquired on different high-resolution mass spectrometric instruments (Orbitrap and time-of-flight). Robustness against impure spectra was evaluated. RESULTS: Correct adduct ion assignment was achieved for up to 83% of the spectra. Performance was independent of compound class and mass spectrometric platform. The algorithm proved highly tolerant against spectral contamination as demonstrated exemplarily for co-eluting compounds as well as systematically by pairwise mixing of spectra. When used in conjunction with MS-FINDER, a state-of-the-art sum formula tool, correct sum formulas were obtained for 77% of spectra. It outperformed both 'brute force' approaches and current state-of-the-art annotation packages tested as potential alternatives. Limitations of the heuristic pertained to poorly ionizing compounds and cationic compounds forming [M]+ ions. CONCLUSIONS: A new, validated approach for interpreting ESI mass spectra is presented, filling a gap in the nontargeted metabolomics workflow. It is freely available in the latest version of R package InterpretMSSpectrum.
    Type of Publication: Journal article published
    PubMed ID: 28499062
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  • 4
    Abstract: Cancer metabolism is wired to sustain uncontrollable cell proliferation and ensure cell survival. Given the multitude of available approaches to study metabolic alterations it remains a challenging task to select the most appropriate method. In this mini-review we describe how cancer metabolism can be studied in vitro and in vivo providing an overview of available approaches and techniques, discussing their advantages and drawbacks and guiding through selection of an appropriate method to address particular research needs. This work is particularly intended to those cancer researchers who are new in the field but want to investigate metabolic alterations in their cancer model systems.
    Type of Publication: Journal article published
    PubMed ID: 28887205
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  • 5
    Keywords: IN-VIVO ; NF-KAPPA-B ; MASS-SPECTROMETRY ; ENDOPLASMIC-RETICULUM ; HETEROCHROMATIN ; HUMAN-CELLS ; AUTOPHAGY ; ONCOGENE-INDUCED SENESCENCE ; LYMPHOMAGENESIS ; P53 TUMOR-SUPPRESSOR
    Abstract: Activated oncogenes and anticancer chemotherapy induce cellular senescence, a terminal growth arrest of viable cells characterized by S-phase entry-blocking histone 3 lysine 9 trimethylation (H3K9me3). Although therapy-induced senescence (TIS) improves long-term outcomes, potentially harmful properties of senescent tumour cells make their quantitative elimination a therapeutic priority. Here we use the Emicro-myc transgenic mouse lymphoma model in which TIS depends on the H3K9 histone methyltransferase Suv39h1 to show the mechanism and therapeutic exploitation of senescence-related metabolic reprogramming in vitro and in vivo. After senescence-inducing chemotherapy, TIS-competent lymphomas but not TIS-incompetent Suv39h1(-) lymphomas show increased glucose utilization and much higher ATP production. We demonstrate that this is linked to massive proteotoxic stress, which is a consequence of the senescence-associated secretory phenotype (SASP) described previously. SASP-producing TIS cells exhibited endoplasmic reticulum stress, an unfolded protein response (UPR), and increased ubiquitination, thereby targeting toxic proteins for autophagy in an acutely energy-consuming fashion. Accordingly, TIS lymphomas, unlike senescence models that lack a strong SASP response, were more sensitive to blocking glucose utilization or autophagy, which led to their selective elimination through caspase-12- and caspase-3-mediated endoplasmic-reticulum-related apoptosis. Consequently, pharmacological targeting of these metabolic demands on TIS induction in vivo prompted tumour regression and improved treatment outcomes further. These findings unveil the hypercatabolic nature of TIS that is therapeutically exploitable by synthetic lethal metabolic targeting.
    Type of Publication: Journal article published
    PubMed ID: 23945590
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  • 6
    Publication Date: 2013-08-16
    Description: Activated oncogenes and anticancer chemotherapy induce cellular senescence, a terminal growth arrest of viable cells characterized by S-phase entry-blocking histone 3 lysine 9 trimethylation (H3K9me3). Although therapy-induced senescence (TIS) improves long-term outcomes, potentially harmful properties of senescent tumour cells make their quantitative elimination a therapeutic priority. Here we use the Emicro-myc transgenic mouse lymphoma model in which TIS depends on the H3K9 histone methyltransferase Suv39h1 to show the mechanism and therapeutic exploitation of senescence-related metabolic reprogramming in vitro and in vivo. After senescence-inducing chemotherapy, TIS-competent lymphomas but not TIS-incompetent Suv39h1(-) lymphomas show increased glucose utilization and much higher ATP production. We demonstrate that this is linked to massive proteotoxic stress, which is a consequence of the senescence-associated secretory phenotype (SASP) described previously. SASP-producing TIS cells exhibited endoplasmic reticulum stress, an unfolded protein response (UPR), and increased ubiquitination, thereby targeting toxic proteins for autophagy in an acutely energy-consuming fashion. Accordingly, TIS lymphomas, unlike senescence models that lack a strong SASP response, were more sensitive to blocking glucose utilization or autophagy, which led to their selective elimination through caspase-12- and caspase-3-mediated endoplasmic-reticulum-related apoptosis. Consequently, pharmacological targeting of these metabolic demands on TIS induction in vivo prompted tumour regression and improved treatment outcomes further. These findings unveil the hypercatabolic nature of TIS that is therapeutically exploitable by synthetic lethal metabolic targeting.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Dorr, Jan R -- Yu, Yong -- Milanovic, Maja -- Beuster, Gregor -- Zasada, Christin -- Dabritz, J Henry M -- Lisec, Jan -- Lenze, Dido -- Gerhardt, Anne -- Schleicher, Katharina -- Kratzat, Susanne -- Purfurst, Bettina -- Walenta, Stefan -- Mueller-Klieser, Wolfgang -- Graler, Markus -- Hummel, Michael -- Keller, Ulrich -- Buck, Andreas K -- Dorken, Bernd -- Willmitzer, Lothar -- Reimann, Maurice -- Kempa, Stefan -- Lee, Soyoung -- Schmitt, Clemens A -- England -- Nature. 2013 Sep 19;501(7467):421-5. doi: 10.1038/nature12437. Epub 2013 Aug 14.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Charite-Universitatsmedizin Berlin, Molekulares Krebsforschungszentrum, Augustenburger Platz 1, 13353 Berlin, Germany.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/23945590" target="_blank"〉PubMed〈/a〉
    Keywords: Animals ; Apoptosis/drug effects ; *Autophagy/drug effects ; Caspase 12/metabolism ; Caspase 3/metabolism ; *Cell Aging/drug effects ; Disease Models, Animal ; Endoplasmic Reticulum Stress ; Female ; Glucose/*metabolism ; Lymphoma, B-Cell/*drug therapy/genetics/*metabolism/pathology ; Male ; Mice ; Mice, Transgenic ; Proteolysis ; Stress, Physiological ; Survival Rate
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
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