dc.contributor.author
Pietzke, Matthias
dc.date.accessioned
2018-06-07T15:06:29Z
dc.date.available
2015-02-18T13:59:38.055Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/584
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-4786
dc.description
1\. INTRODUCTION 1.1. Metabolomics and the central carbon metabolism 1.2. The
use of stable isotopes for flux measurements 1.3. The role of the cell cycle
1.4. The metabolic difference of cancer cells 1.5. Glycolytic inhibition as a
potential therapeutic target against cancer cells 1.5.1. Inhibition by
2-deoxyglucose 1.5.2. Inhibition by glyceraldehyde 1.5.3. Inhibition by
3-bromopyruvate 1.6. Aim of this study 2\. CHEMICALS AND MATERIAL 2.1. Lab
Equipment 2.2. Materials 2.2.1. Cell lines: 2.2.2. Chemicals for cell culture
2.2.3. Chemicals for metabolite harvest and measurement 3\. METHODS 3.1.
Growth media composition for cell culture 3.2. Standard cell culture 3.3.
Sample preparation for metabolomics 3.3.1. Standard metabolomic harvest for
adherent cells 3.3.2. Standard metabolomic harvest for weakly adherent cells
3.3.3. Performing labeling experiments 3.3.4. Preparation of the Ident-mix
3.3.5. Preparation of the Quant-mix 3.3.6. Derivatization 3.3.7. GC-MS
measurement 3.3.8. GC-MS data analysis 3.4. Flow cytometry for detecting cell
cycle phases 3.5. Proteomics Preparation 3.5.1. Solutions 3.5.2. Harvest and
extraction 3.6. Additional Data analysis 3.7. Experimental description 3.7.1.
Experimental verification of correcting strategies by mixing 13C with 12C-
glucose 3.7.2. Reproducibility of harvest procedure and label incorporation
3.7.3. Cell Cycle experiment 3.7.4. Growth inhibition under influence of
glycolytic inhibitors 3.7.5. Incorporation of 13C-Glyceraldehyde 3.7.6. Effect
of glycolytic inhibition to metabolism 3.7.7. In vivo study in mice to monitor
gluconeogenesis from pyruvate 3.7.8. In vivo study to elucidate differential
use of substrates in HCC tumor models 4\. RESULTS 4.1. Section 1 - Method
development of pulsed stable isotope resolved metabolomics (pSIRM) of cell
culture samples 4.1.1. A high percentage of the central carbon metabolism can
be measured by GC-MS 4.1.2. The Ident-mixture enables a more reliable and
semiautomated identification in complex biological samples 4.1.3. Multiple
metabolites can be simultaneously quantified with external calibration curves
4.1.4. The sample preparation and the quantification of compounds in cell
culture samples is reproducible 4.1.5. The natural 13C abundance must be
subtracted 4.1.6. Correction of natural abundance and calculation of label
incorporation can be done in a single step in an untargeted way 4.1.7. Mass
isotopomer distributions are concentration dependent 4.1.8. Many metabolites
of the CCM in mammalian cell lines can be found labeled and have a turnover on
the minute time scale 4.1.9. Label incorporation and quantification of
metabolites can be obtained from a single sample with high precision 4.2.
Section 2 – Cell cycle Experiment 4.2.1. After release from mimosine block
cells immediately start entering S-phase 4.2.2. Proteins showed a continuous
increase in their heavy to light ratios 4.2.3. Glycolysis and glutaminolysis
are differentially regulated 4.3. Section 3 – Measuring the effect of
glycolytic inhibitors on the central carbon metabolism and growth 4.3.1. All
compounds inhibit cell growth and induced a stress phenotype in a dose
dependent manner 4.3.2. Further estimation of effective concentrations 4.3.3.
L-Glyceraldehyde inhibits glycolysis downstream of the hexokinase reaction
4.3.4. Bromopyruvate inhibits glycolysis primarily at GAPDH-reaction 4.3.5.
2-Deoxyglucose is rapidly phosphorylated but only acts indirectly on
glycolysis 4.3.6. The fate of glyceraldehyde can be monitored 4.3.7. Sorbose
itself has no effect to growth or viability 4.3.8. Glyceraldehyde further
induces a growth crises which depends on the availability of glucose 4.4.
Section 4 - in vivo applications of pSIRM 4.4.1. In vivo monitoring of
gluconeogenesis from 13C-pyruvate 4.4.2. In vivo usage of glucose and
glutamine in HCC model-mouse 5\. DISCUSSION 5.1. Labeling – a shorter
timescale reveals new insights 5.2. Calculation of label incorporation –
sometimes the wheel needs to be reinvented 5.3. Label incorporation can be
summarized into a single number 5.4. Interpretation of labeling data under
changing conditions improves with inclusion of quantities 5.5. Analysis of
metabolites and proteins during cell cycle progression 5.6. pSIRM as an
strategy to understand short termed processes like the inhibition of
glycolysis 5.7. The L-isomer of glyceraldehyde is an more effective inhibitor
of glycolysis than the D-isomer 5.8. BrPyr is very effective inhibitor of
glycolysis in the tested concentration 5.9. The failure of 2DG to inhibit
glycolysis 5.10. Comparison of the tested compounds and characterization as
possible therapeutics 5.11. GA and further effects to glucose sensing 5.12. In
vivo application of isotopic labeled compounds in mice 5.13. Conclusion and
outlook 6\. BIBLIOGRAPHY 7\. PUBLICATIONS 8\. APPENDIX
dc.description.abstract
Cancer cells typically collected a number of mutations resulting in modified
metabolism optimized to fulfill their needs to a maximize growth. In the
recent years -with development of reliable high-throughput techniques- there
was a shift from measuring single actors to an integrated view of the complex
regulatory network in a biological system. This thesis aimed at elucidation
and under-standing of the metabolic difference between cancer and healthy
cells in order to target these differences therapeutically. Firstly, cancer
and healthy cells differ metabolically in many aspects. It is generally
accepted that most cancer cells have a higher rate of glycolysis that results
in elevated level of lactate production, even in the presence of oxygen (known
as Warburg effect). Further the function and activity of the TCA cycle and the
glutaminolysis in cancer cells is heavily debated. Current, static
metabolomics protocols deliver only a limited amount of information and need
careful interpretation. With the help of heavy-labeled isotopes the metabolism
can be monitored in a more dynamic way. In frame of this thesis a method was
established that allows for monitoring changes in the carbon routing of the
highly connected central carbon metabolism in human tumor model cell lines.
The usage of substrates such as glucose can be compared under different
conditions. With this method the high activity of glycolysis and a tight
connection to lactate production as well as a truncated TCA cycle could be
shown. Secondly, cancer cells can be characterized by their permanent and
unlimited replication. During different phases of the cell cycle, cells are
expected to have different needs, with respect to precursors for synthesis or
energy production. The difference in metabolism during various phases of the
cell cycle was monitored with the established approach in synchronized cells.
Further the protein-turnover was measured in a pulsed-SILAC approach. Third,
both permanent growth and elevated glycolytic activity are potential targets
for therapy, aiming at cancer cells but leaving healthy cells unharmed. The
established method is perfectly suitable to detect rearrangements of
metabolism on the minute time scale, therefore differentiating between direct
inhibition of enzymes targeted by inhibitors and long-termed rearrangements of
metabolism. The strategy was tested with three different, putative inhibitors
of glycolysis: 3-bromopyruvate, glyceraldehyde and 2-deoxyglucose. The
monitored effects partially resembled effects previously described in the
literature and further evidenced criticism of 2-deoxyglucose as selective
inhibitor of glycolysis. Finally, the methods and strategies developed in
cancer-model cell lines were and will be further translated to in vivo mouse
models. Pulsed labeling with stable isotope enriched substrates such as
glucose or glutamine showed differences in the substrate utilization between
female and male HCC tumor model mice.
de
dc.description.abstract
Krebszellen sammeln in ihrer Entwicklung zahlreiche verschiedene Mutationen,
die sich häufig in einem veränderten Stoffwechsel manifestieren, einem
Stoffwechsel optimiert auf maximales Wachstum. Die Entwicklung von
zuverlässigen Hochdurchsatz-Methoden ermöglichte einen Wechsel von der
Betrachtung einzelner Aspekte zu einer integrierten Betrachtung des gesamten,
komplexen Systems. Diese Arbeit zielt auf ein tieferes Verständnis der
Unterschiede zwischen Krebs und gesunden Zellen mit dem Ziel diese
Unterschiede therapeutisch auszunutzen. Krebs- und gesunde Zellen
unterscheiden sich in ihrem Metabolismus. Die meisten Krebszellen zeigen eine
höhere Glykolyse, die sich in einer starken Laktatausscheidung auch in
Gegenwart von Sauerstoff zeigt, der wohlbekannte „Warburg-Effekt“. Darüber
hinaus werden die Rolle des Citratzyklus und die Rolle des
Glutaminstoffwechsels intensiv diskutiert. Klassische Metabolitmessungen
liefern nur eingeschränkte Ergebnisse, die vorsichtig interpretiert werden
müssen. Das ändert sich durch die Verwendung stabiler, schwerer Isotope. In
dieser Arbeit wurde eine Methode etabliert um Veränderungen im Kohlenstoff-
Stoffwechsel in menschlichen Tumormodell-Zelllinien mit Hilfe von stabilen
Isotopen zu messen. Die Verwendung verschiedener Susbtrate, wie Glukose oder
Glutamin, kann somit unter verschiedenen Konditionen verglichen werden. Mit
dieser Methode konnte eine starke glykolytische Aktivität, eine enge Kopplung
von Pyruvat und Laktat und ein unvollständiger Citratzyklus gezeigt werden.
Krebszellen sind weiterhin charakterisiert durch ein unbegrenztes Wachstum.
Während verschiedener Phasen des Zell-Zyklus können unterschiedliche
metabolische Profile erwartet werden. Das wurde überprüft durch Anwendung der
etablierten Methode in verschiedenen Phasen des Zellzyklus von
synchronisierten Zellen. Zusätzlich wurde die Protein-Neusynthese mit Hilfe
eines „pulsed SILAC“ Ansatzes bestimmt. Beide Faktoren, erhöhte Glykolyse und
permanentes Wachstum sind potentielle Ziele für Krebstherapien. Die etablierte
Methode ist perfekt geeignet um kurzfristige Veränderungen des Stoffwechsels
zu beobachten. Damit können direkte Wirkungen auf die Enzyme von langfristigen
metabolischen Umstrukturierungen unterschieden werden. Mit diesem Ansatz
wurden drei verschiedene mögliche Inhibitoren der Glykolyse getestet und
verglichen, 3-Brompyruvate, Glyceraldehyd und 2-Deoxyglukose. Die beobachteten
Effekte spiegeln zum Teil bekannte Effekte wider, liefern aber auch neue
Hinweise und stärken die Kritik an 2-Deoxyglukose als selektiven Inhibitor der
Glykolyse. Die gleichen Methoden und Strategien die in Zellkulturproben
entwickelt wurden können schließlich auch in in vivo Mäuse Modellen benutzt
werden. Der kurzzeitige Einbau von stabilen Isotopen in Intermediate des
Stoffwechsels lieferte Hinweise über die notwendigen Zeiträume und über die
verschiedenartige Nutzung von Glukose und Glutamin in Mäusen die als Modelle
für menschlichen HCC-Tumor dienen.
de
dc.format.extent
XII, 141 S.
dc.rights.uri
http://www.fu-berlin.de/sites/refubium/rechtliches/Nutzungsbedingungen
dc.subject
glycolytic inhibition
dc.subject.ddc
500 Naturwissenschaften und Mathematik::570 Biowissenschaften; Biologie::572 Biochemie
dc.subject.ddc
500 Naturwissenschaften und Mathematik::570 Biowissenschaften; Biologie::570 Biowissenschaften; Biologie
dc.title
Analysis of the metabolic control of cell growth using stable isotope resolved
metabolomics
dc.contributor.contact
m.pietzke@web.de
dc.contributor.firstReferee
Dr. Stefan Kempa
dc.contributor.furtherReferee
Prof. Dr. Udo Heinemann
dc.date.accepted
2014-09-12
dc.identifier.urn
urn:nbn:de:kobv:188-fudissthesis000000098335-2
dc.title.translated
Analyse der metabolischen Kontrolle des Zellwachstums mit Hilfe von
Metabolitmessungen und stabiler Isotopenmarkierung
de
refubium.affiliation
Biologie, Chemie, Pharmazie
de
refubium.mycore.fudocsId
FUDISS_thesis_000000098335
refubium.mycore.derivateId
FUDISS_derivate_000000016541
dcterms.accessRights.dnb
free
dcterms.accessRights.openaire
open access