Fusarium graminearum is responsible for causing Fusarium head blight in cereals and maize imposing a significant impact in Canadian agriculture. While a handful of secondary metabolites produced by F. graminearum are recognized as contributors to disease virulence, the functions of numerous molecular products arising from biosynthetic gene clusters expressed during infection remain undiscovered. Presented here are the results of CRISPR-Cas9 mediated gene-deletion experiments disrupting core biosynthetic genes from four biosynthetic gene clusters with reported in-planta transcription: C08, C16, C13 and C70. Both wheat head infection assays and coleoptile infection assays were used to evaluate the pathology phenotypes of transformant strains illustrating potential links between C16 and pathogenicity. Culture medium screening experiments using transformant strains were profiled by UHPLC-HRMS and targeted MS2 experiments to confirm the associated secondary metabolite products and attempt to identify unknown secondary metabolites of the biosynthetic gene clusters. While C08 secondary metabolite remained elusive, confirmation of C16 secondary metabolites led to hypotheses regarding their potential connections to the inhibition of plant immune response and untargeted secondary metabolite profiling of the C13/C70 transformant strains suggests that this BGC may have significant implications for global secondary metabolite production.

Obesity is a major risk factor for multiple common chronic diseases. The prevalence in European countries is high and a significant public health concern. This thesis aims to explore the obesity landscape in the Cooperative Health Research in South Tyrol (CHRIS) study. The first step was to characterise the obese CHRIS population, taking into account the established body mass index (BMI) classification from the World Health Organization (WHO) and looking at metabolically healthy and unhealthy obesity. We investigated the familial aggregation of these traits. We identified several families with significant familial aggregation and observed varying degrees of overlap for these traits in different families. The focus was then on implementing and applying a Genome-Wide Polygenic Score for obese participants. These scores were computed for individuals based on the presence of different genetic variants weighted according to their measured effects in genome-wide association studies (GWAS). We then paid attention to the targeted metabolomics data of the CHRIS study, to identify different serum metabolites associated with metabolically healthy/unhealthy obesity, using logistic regression and random forest methods to explore metabolic signatures to distinguish obesity into metabolically healthy and metabolically unhealthy obesity. Several biomarkers were shown to be related to obesity, many of which confirmed by existing evidence (such as BCAAs, tyrosine, and lysophosphatidylcholines).

<p>The work in this thesis encompasses (a) the development of a robust analytical method suitable for the comprehensive analysis of polar and non-polar metabolites in a single analysis and (b) the application of this method to the study of the metabolites involved in peanut allergy. During the course of this work the methods for the analysis of large metabolite data sets evolved significantly and the approaches used in this work evolved in parallel to the literature. This work constitutes the first comprehensive metabolomic investigation of an allergy response.</p> <p>Hypersensitivity or allergy to peanuts is an increasingly problematic health concern around the world involving approximately 1-2% of children in North America. There are no useful clinical biomarkers for this allergy. Comprehensive metabolomics holds vast potential for the discovery of metabolites and metabolite pathways that may be involved during the development of peanut allergy and during peanut-induced anaphylaxis. The comprehensive study of metabolites involved in peanut allergy presented a significant challenge since no single analytical technique is capable of analysis of all metabolites within a single analytical run.</p> <p>The thesis begins with development of a tandem column liquid chromatography-electrospray ionization-mass spectrometry method which allowed the separation and analysis of both polar and non-polar metabolites in a single analysis. This tandem column technique was also shown to significantly reduce the amount of ion suppression observed compared to the ion suppression observed when using either column independently.</p> <p>This methodology was applied to the comprehensive metabolomics analysis of blood serum samples obtained from mice which were (a) being sensitized to peanuts and (b) undergoing anaphylaxis. This analysis discovered a profound impact on metabolites involved with purine metabolism, resulting in an elevation of uric acid levels. This discovery led to further investigations which confirmed that uric acid is essential for peanut sensitization in mice. This discovery was only possible due to the use of a comprehensive metabolomics approach.</p> <p>The analytical methodology was then applied to the study of metabolomic changes in sensitized mice as they experienced peanut-induced anaphylaxis. A number of metabolomic changes including taurine level elevation were correlated with peanut-induced anaphylaxis. Finally, a serendipitous opportunity arose to analyze blood serum samples from peanut allergic children that had undergone an oral peanut challenge. The comprehensive metabolomic study of these samples revealed massive changes in their serum metabolomes as a result of peanut exposure. A number of lipids and lysophospho-lipids were shown to have increased dramatically and may represent novel biomarker candidates for peanut-induced anaphylaxis in humans.</p> <p>In summary, this thesis had demonstrated that comprehensive metabolomic analyses can be successfully applied to complex syndromes such as peanut allergy and yield useful mechanistic and clinical insights to this disorder.</p> / Doctor of Philosophy (PhD)

Dihydrochalcones (DHCs) are specialised metabolites with a limited natural distribution, found in significant amounts in Malus x domestica Borkh. (cultivated apple) and wild Malus species. Among them, M. x domestica accumulates significant amounts of phloridzin, whilst trilobatin and sieboldin are abundant in some wild relatives. DHCs have demonstrated a wide range of bioactive properties in biomedical models. Some DHCs have also been reported to act as flavour enhancers. Phloridzin may act as an anti-diabetic compound by blocking sodium-linked glucose transport and renal reabsorption of glucose in kidneys. Despite the protective effects reported in mammal models, little is known about how these metabolites are biosynthesised and what is their function in planta, where it has been hypothesised a role for phloridzin in plant growth. The biosynthetic pathway leading to DHC formation has been proposed in apple, and some steps have been characterised recently. DHC pathway diverts from the main phenylpropanoid pathway most probably from 4-coumaroyl-CoA by the action of a yet unknown reductase that would produce 4-dihydrocoumaroyl-CoA. Then, chalcone synthase (CHS) catalyses its condensation to form phloretin. Phloretin can be directly glycosylated at position 2′- or 4′ by the previously characterised 2′- and 4′-O-UDP-glycosyltransferases PGT1 and PGT2, to produce phloridzin or trilobatin, respectively. However, sieboldin has been postulated to derive from hydroxylation in position 3 of phloretin before been glycosylated, and the key responsible enzyme producing 3-hydroxyphloretin has not been yet discovered. The main aim of this PhD proposal was to provide a better understanding of the physiological functions of DHCs in apple, as well as to contribute to the elucidation of the biosynthetic pathway as the molecular basis for future genetic engineering in apple. Towards this aim, functional characterisation was conducted in MdPGT1 knockdown apple lines by RNAi silencing and CRISPR/Cas9 genome editing to assess the physiological effect of targeting a key biosynthetic gene involved in phloridzin biosynthesis. In addition, molecular, transcriptomic and metabolomic analyses were integrated to evaluate candidate genes accounting for 3-hydroxylase activity involved in DHC biosynthesis in wild Malus species accumulating sieboldin. Moreover, a de novo transcriptome assembly was carried out in an intergeneric hybrid between M. x domestica and Pyrus communis L. known to accumulate intermediate levels of DHCs compared to apple, in order to identify additional genes potentially involved in DHC pathway. We compared the physiological effect of reducing phloridzin through PGT1 knockdown by RNAi silencing and CRISPR/Cas9 genome editing. Knockdown lines exhibited characteristic impairment of plant growth and leaf morphology as reported in literature, whereas genome edited lines exhibited normal growth despite reduced foliar phloridzin. Bioactive brassinosteroids and gibberellins were found to be key players involved in the contrasting effects on growth observed following phloridzin reduction. Moreover, a cytochrome P450 from wild M. toringo (K. Koch) Carriere syn. sieboldii Rehder, and M. micromalus Makino was identified as dihydrochalcone 3-hydroxylase (DHCH), proving to produce 3-hydroxyphloretin and sieboldin in yeast. Different DHCH allele isoforms found in domesticated apple and M. toringo and M. micromalus correlated with sieboldin accumulation in a Malus germplasm collection. Finally, the assembled de novo transcriptome of the intergeneric apple/pear hybrid integrated to functional annotation and metabolomic analysis resulted in the identification of genes potentially involved in DHC biosynthesis, providing the basis for future biochemical characterisation. Altogether these results contribute to get insight into the roles of DHCs in apple and to illustrate how CRISPR/Cas9 genome editing can be applied to dissect the contribution of genes involved in phloridzin biosynthesis in apple. Furthermore, the present PhD thesis contributes to the state-of-the-art by elucidating key missing steps in the biosynthesis of DHCs, which could be relevant for future establishment of genetic engineered lines that contribute to assess physiological effects of altering DHCs content, as well as to establish heterologous expression systems to produce de novo DHCs.

Plants are the primary producers of biomass and thereby the basis of all life. Many varieties are cultivated, mainly to produce food, but to an increasing amount as a source of renewable energy. Because of the limited acreage available, further improvements of cultivated species both with respect to yield and composition are inevitable. One approach to further progress in developing improved plant cultivars is a systems biology oriented approach. This work aimed to investigate the primary metabolism of the model plant A.thaliana and its relation to plant growth using quantitative genetics methods. A special focus was set on the characterization of heterosis, the deviation of hybrids from their parental means for certain traits, on a metabolic level. More than 2000 samples of recombinant inbred lines (RILs) and introgression lines (ILs) developed from the two accessions Col-0 and C24 were analyzed for 181 metabolic traces using gas-chromatography/ mass-spectrometry (GC-MS). The observed variance allowed the detection of 157 metabolic quantitative trait loci (mQTL), genetic regions carrying genes, which are relevant for metabolite abundance. By analyzing several hundred test crosses of RILs and ILs it was further possible to identify 385 heterotic metabolic QTL (hmQTL). Within the scope of this work a robust method for large scale GC-MS analyses was developed. A highly significant canonical correlation between biomass and metabolic profiles (r = 0.73) was found. A comparable analysis of the results of the two independent experiments using RILs and ILs showed a large agreement. The confirmation rate for RIL QTL in ILs was 56 % and 23 % for mQTL and hmQTL respectively. Candidate genes from available databases could be identified for 67 % of the mQTL. To validate some of these candidates, eight genes were re-sequenced and in total 23 polymorphisms could be found. In the hybrids, heterosis is small for most metabolites (< 20%). Heterotic QTL gave rise to less candidate genes and a lower overlap between both populations than was determined for mQTL. This hints that regulatory loci and epistatic effects contribute to metabolite heterosis. The data described in this thesis present a rich source for further investigation and annotation of relevant genes and may pave the way towards a better understanding of plant biology on a system level. / Pflanzen sind die Primärproduzenten von Biomasse und damit Grundlage allen Lebens. Sie werden nicht nur zur Gewinnung von Nahrungsmitteln, sondern zunehmend auch als Quelle erneuerbarer Energien kultiviert. Aufgrund der Begrenztheit der weltweit zu Verfügung stehenden Anbaufläche ist eine zielgerichtete Selektion und Verbesserung der verwendeten Sorten unabdingbar. Um solch eine kontinuierliche Verbesserung zu gewährleisten, ist ein grundlegendes Verständnis des biologischen Systems Pflanze nötig. Diese Arbeit hatte zum Ziel, den Primärmetabolismus der Modellpflanze A. thaliana mit Methoden der quantitativen Genetik zu untersuchen und in Beziehung zu Wachstum und Biomasse zu stellen. Insbesondere sollte Heterosis, die Abweichung von Hybriden in ihren Merkmalen vom Mittelwert der Eltern, auf Stoffwechselebene charakterisiert werden. Mit Hilfe der Gas Chromatographie/ Massen Spektrometrie (GC-MS) wurden über 2000 Proben von rekombinanten Inzucht Linien (RIL) und Introgressions Linien (IL) der Akzessionen Col 0 und C24 bezüglich des Vorkommens von 181 Metaboliten untersucht. Die beobachtete Varianz erlaubte die Bestimmung von 157 metabolischen QTL (mQTL), genetischen Regionen, die für die Metabolitkonzentrationen relevante Gene enthalten. Durch die Untersuchung von Testkreuzungen der RILs und ILs konnten weiterhin 385 heterotische metabolische QTL (hmQTL) identifiziert werden. Im Rahmen dieser Arbeit wurde eine robuste Methode zur Auswertung von GC-MS Analysen entwickelt. Es wurde eine hoch signifikante kanonische Korrelation (r=0.73) zwischen Biomasse und Metabolitprofilen gefunden. Die unterschiedlichen Ansätze zur QTL Analyse, RILs und ILs, wurden verglichen. Dabei konnte gezeigt werden, daß die Methoden komplementär sind, da mit RILs gefundene mQTL zu 56% und hmQTL zu 23% in ILs bestätigt wurden. Durch den Vergleich mit Datenbanken wurden für 67% der mQTL Kandidatengene identifiziert. Um diese zu überprüfen wurden acht dieser Gene resequenziert und insgesamt 23 Polymorphismen darin bestimmt. Die Heterosis in den Hybriden ist für die meisten Metabolite gering (<20%). Für hmQTL konnten weniger Kandidatengene als für mQTL bestimmt werden und sie zeigten eine geringere Übereinstimmung in den beiden Populationen. Dies deutet darauf hin, daß regulatorische Loci und epistatische Effekte einen wichtigen Beitrag zur Heterosis besteuern. Die gewonnenen Daten stellen eine reiche Quelle für die weitergehende Untersuchung und Annotation relevanter Gene dar und ebnen den Weg für ein besseres Verständnis des Systems Pflanze.

The uptake of nutrients and their subsequent chemical conversion by reactions which provide energy and building blocks for growth and propagation is a fundamental property of life. This property is termed metabolism. In the course of evolution life has been dependent on chemical reactions which generate molecules that are common and indispensable to all life forms. These molecules are the so-called primary metabolites. In addition, life has evolved highly diverse biochemical reactions. These reactions allow organisms to produce unique molecules, the so-called secondary metabolites, which provide a competitive advantage for survival. The sum of all metabolites produced by the complex network of reactions within an organism has since 1998 been called the metabolome. The size of the metabolome can only be estimated and may range from less than 1,000 metabolites in unicellular organisms to approximately 200,000 in the whole plant kingdom. In current biology, three additional types of molecules are thought to be important to the understanding of the phenomena of life: (1) the proteins, in other words the proteome, including enzymes which perform the metabolic reactions, (2) the ribonucleic acids (RNAs) which constitute the so-called transcriptome, and (3) all genes of the genome which are encoded within the double strands of desoxyribonucleic acid (DNA). Investigations of each of these molecular levels of life require analytical technologies which should best enable the comprehensive analysis of all proteins, RNAs, et cetera. At the beginning of this thesis such analytical technologies were available for DNA, RNA and proteins, but not for metabolites. Therefore, this thesis was dedicated to the implementation of the gas chromatography – mass spectrometry technology, in short GC-MS, for the in-parallel analysis of as many metabolites as possible. Today GC-MS is one of the most widely applied technologies and indispensable for the efficient profiling of primary metabolites. The main achievements and research topics of this work can be divided into technological advances and novel insights into the metabolic mechanisms which allow plants to cope with environmental stresses. Firstly, the GC-MS profiling technology has been highly automated and standardized. The major technological achievements were (1) substantial contributions to the development of automated and, within the limits of GC-MS, comprehensive chemical analysis, (2) contributions to the implementation of time of flight mass spectrometry for GC-MS based metabolite profiling, (3) the creation of a software platform for reproducible GC-MS data processing, named TagFinder, and (4) the establishment of an internationally coordinated library of mass spectra which allows the identification of metabolites in diverse and complex biological samples. In addition, the Golm Metabolome Database (GMD) has been initiated to harbor this library and to cope with the increasing amount of generated profiling data. This database makes publicly available all chemical information essential for GC-MS profiling and has been extended to a global resource of GC-MS based metabolite profiles. Querying the concentration changes of hundreds of known and yet non-identified metabolites has recently been enabled by uploading standardized, TagFinder-processed data. Long-term technological aims have been pursued with the central aims (1) to enhance the precision of absolute and relative quantification and (2) to enable the combined analysis of metabolite concentrations and metabolic flux. In contrast to concentrations which provide information on metabolite amounts, flux analysis provides information on the speed of biochemical reactions or reaction sequences, for example on the rate of CO2 conversion into metabolites. This conversion is an essential function of plants which is the basis of life on earth. Secondly, GC-MS based metabolite profiling technology has been continuously applied to advance plant stress physiology. These efforts have yielded a detailed description of and new functional insights into metabolic changes in response to high and low temperatures as well as common and divergent responses to salt stress among higher plants, such as Arabidopsis thaliana, Lotus japonicus and rice (Oryza sativa). Time course analysis after temperature stress and investigations into salt dosage responses indicated that metabolism changed in a gradual manner rather than by stepwise transitions between fixed states. In agreement with these observations, metabolite profiles of the model plant Lotus japonicus, when exposed to increased soil salinity, were demonstrated to have a highly predictive power for both NaCl accumulation and plant biomass. Thus, it may be possible to use GC-MS based metabolite profiling as a breeding tool to support the selection of individual plants that cope best with salt stress or other environmental challenges. / Die Aufnahme von Nährstoffen und ihre chemische Umwandlung mittels Reaktionen, die Energie und Baustoffe für Wachstum und Vermehrung bereitstellen, ist eine grundlegende Eigenschaft des Lebens. Diese Eigenschaft wird Stoffwechsel oder, wie im Folgenden, Metabolismus genannt. Im Verlauf der Evolution war alles Leben abhängig von solchen Reaktionen, die essentielle und allen Lebensformen gemeinsame Moleküle erzeugen. Über diese sogenannten Primärmetabolite hinaus sind hochdiverse Reaktionen entstanden. Diese erlauben Organismen, einzigartige sogenannte Sekundärmetabolite zu produzieren, die in der Regel einen zusätzlichen Überlebensvorteil vermitteln. Die Gesamtheit aller Metabolite, die von dem komplexen Reaktionsnetzwerk in Organismen erzeugt werden, nennt man seit 1998 das Metabolom. Die Größe des Metaboloms kann nur geschätzt werden. Neben der Gesamtheit aller Metabolite werden heute drei weitere Arten an Molekülen als wesentlich betrachtet, um die Phänomene des Lebens zu verstehen: erstens die Proteine, deren Summe, das Proteom, auch die Enzyme einschließt, die die obigen metabolischen Reaktionen durchführen, zweitens die Ribonukleinsäuren (RNS), deren Gesamtheit als Transkriptom bezeichnet wird, und drittens die doppelsträngige Desoxyribonukleinsäure (DNS), die das Genom, die Summe aller Gene eines Organismus, ausmacht. Die Untersuchung aller dieser vier molekularen Ebenen des Lebens erfordert Technologien, die idealerweise die vollständige Analyse der Gesamtheit aller DNS-, RNS-, Protein-Moleküle, bzw. Metabolite erlauben. Zu Beginn meiner Arbeiten waren solche Technologien für DNS, RNS, und Proteine verfügbar, aber nicht für Metabolite. Aus diesem Grund habe ich meine Forschungstätigkeit auf das Ziel ausgerichtet, so viele Metabolite wie irgend möglich in einer gemeinsamen Analyse zu erfassen. Zu diesem Zweck habe ich mich auf eine einzelne Technik, nämlich die gekoppelte Gaschromatographie und Massenspektrometrie, kurz GC-MS, konzentriert. Nicht zuletzt durch meine Arbeiten ist GC-MS heute eine der am häufigsten angewandten Technologien und unverzichtbar für das breite Durchmustern der Metabolite. Neben der Etablierung der grundlegenden GC-MS-Profilanalyse-Technologie liegen die Haupterrungenschaften meiner Arbeiten sowohl in den technischen Neuerungen als auch in den Einsichten in metabolische Mechanismen, die es Pflanzen erlauben, erfolgreich auf Umwelteinflüsse zu reagieren. Die technologischen Errungenschaften waren erstens wesentliche Beiträge zur Labor-Automatisierung und zur Auswertung von modernen, auf Flugzeitmassenspektrometrie beruhenden, GC-MS-Profilanalysen, zweitens die Entwicklung einer entsprechenden Prozessierungs-Software, genannt TagFinder, und drittens die Etablierung einer internationalen Datensammlung zur Metabolitidentifizierung aus komplexen Mischungen. Diese massenspektralen und gaschromatographischen Daten haben seit 2005 Eingang in die von mir initiierte Entwicklung der Golm Metabolom Datenbank (GMD) gefunden, die die zunehmend wachsenden GC-MS-Referenzdaten wie auch die Metabolitprofildaten verwaltet und öffentlich zugänglich macht. Darüber hinaus wurden die langfristigen Ziele einer verbesserten Präzision für relative und absolute Quantifizierung wie auch einer Kopplung von Konzentrationsbestimmung und metabolischen Flussanalysen mittels GC-MS verfolgt. Sowohl die Stoffmengen als auch die Geschwindigkeit der Stoffaufnahme und der chemischen Umsetzung, d.h. der metabolische Fluss, sind wesentlich für neue biologische Einsichten. In diesem Zusammenhang wurde von mir die Aufnahme von CO2 durch Pflanzen, der Basis allen Lebens auf der Erde, untersucht. Angewandt auf das Temperaturstress- und Salzstressverhalten von Modell- und Kulturpflanzen, nämlich des Ackerschmalwands (Arabidopsis thaliana), des Hornklees (Lotus japonicus) und der global bedeutendsten Nutzpflanze Reis (Oryza sativa), wurden detaillierte und vergleichende neue metabolische Einsichten in den Zeitverlauf der Temperaturanpassung und die Anpassung an zunehmend salzhaltige Böden erzielt. Metabolismus verändert sich unter diesen Bedingungen allmählich fortschreitend und nicht in plötzlichen Übergängen. Am Beispiel des Hornklees konnte gezeigt werden, dass Metabolitprofilanalysen eine hohe Vorhersagekraft für die Biomasseerzeugung unter Salzeinfluss wie auch für die Aufnahme von Salz durch die Pflanze haben. So mag es in Zukunft möglich werden, GC-MS-Profilanaysen anzuwenden, um den Züchtungsprozess von Kulturpflanzen zu beschleunigen.

No description available.

Metabolomics is a powerful science that can be applied for the discovery of disease biomarkers, and investigation of altered metabolomes due to abiotic and biotic perturbations. This dissertation is focused on untargeted metabolomic applications to investigate fungal metabolite alterations associated with pathogenicity, fungal disease propagations, and symbiosis. This dissertation employs qualitative analysis of metabolite mixtures using HS-SPME coupled GC-MS and TMS derivatization followed by GC-MS analytical platforms. In the first study, we discovered a biomarker combination to diagnose fungal soft tissue disease in sweet potato at an early stage of disease propagation. We used an HS-SPME GC-MS untargeted metabolomics workflow to analyze the VOC associated with Rhizopus stolonifer infected and healthy sweet potatoes in situ and simulated warehouse environments. A single combination of 4 biomarkers was able to diagnose R. stolonifer fungal soft tissue disease (AUC = 0.980, 95% C.I. 0.937-1) and the early stage of the fungal soft rot disease (AUC = 0.999, 95% C.I. 0.978-1). We were able to detect the biomarkers: 1- propanol, ethyl alcohol, ethyl propionate and 3-methyl-3- buten-1-ol during disease progression in a simulated warehouse environment. Therefore, this study shows the feasibility of early diagnosis of fungal soft tissue disease by a real-time screening of volatile profiles of sweet potato in post-harvest storage. When considering the study of a particular species metabolome, it is crucial to develop a metabolite extraction protocol. In the second study, the performance of the six different metabolite extraction solvents mixtures was tested with the preferred mix being: butanol:methanol:water (2:1:1, v/v at -20 °C) which was used as a single solvent mix to extract both polar and relatively non-polar metabolites simultaneously in a single extraction step. The Macrophomina phaseolina fungal metabolome was investigated using the solvent mix. Finally, fungal mutualism was studied using untargeted metabolomics. Most often mycorrhizal metabolomics workflows are based on analyzing the Arbuscular Mycorrhizae colonized root metabolome. But here, we used hyphal materials to examine the mutualistic symbiotic association of the AM fungi. All untargeted metabolomic studies included chemometric data analysis and specific biomarkers and or metabolites were determined using multivariate statistics or prediction model building and validating.

No description available.

The purpose of this thesis was to characterize cancer metabolism in vitro using epithelial ovarian cancer as a model on an untargeted, systems-level, basis with particular attention paid to the difference between cancer stem cell metabolism and cancer cell metabolism. Two-dimensional gas chromatography coupled to mass spectrometry was used to measure the metabolite profiles of the ovarian cancer and cancer stem cell lines under normal baseline conditions and also under chemotherapeutic and environmental perturbations. These two cell lines exhibited significant metabolic differences under normal baseline conditions and results demonstrated that metabolism in the ovarian cancer stem cell line was distinct from that of more differentiated isogenic cancer cells, showing similarities to stem cell metabolism that suggest the potential importance of metabolism for the cancer stem cell phenotype. Glucose deprivation, hypoxia, and ischemia all perturbed ovarian cancer and cancer stem cell metabolism, but not in the same ways between the cell types. Chemotherapeutic treatment with docetaxel caused metabolic changes mostly in amino acid and carbohydrate metabolism in ovarian cancer cells, while ovarian cancer stem cell metabolism was not affected by docetaxel. Overall, these metabolic differences between the two cell types will deepen our understanding of the metabolic changes occurring within the in vivo tumor and will help drive development of cancer stem cell targeted therapeutics.