Die Qualität von Nutzpflanzen ist von zahlreichen Einflussfaktoren wie beispielsweise Lagerbedingungen und Sorteneigenschaften abhängig. Um Qualitätsmängel zu minimieren und Absatzchancen von Nutzpflanzen zu steigern sind umfangreiche Analysen hinsichtlich ihrer stofflichen Zusammensetzung notwendig. Chromatographische Techniken gekoppelt an ein Massenspektrometer und die Kernspinresonanzspektroskopie wurden dafür bislang verwendet. In der vorliegenden Arbeit wurde ein Gaschromatograph an ein Flugzeitmassenspektrometer (GC-TOF-MS) gekoppelt, um physiologische Prozesse bzw. Eigenschaften (die Schwarzfleckigkeit, die Chipsbräunung, das Physiologische Alter und die Keimhemmung) von Nutzpflanzen aufzuklären. Als Pflanzenmodell wurde dafür die Kartoffelknolle verwendet. Dazu wurden neue analytische Lösungsansätze entwickelt, die eine zielgerichtete Auswertung einer Vielzahl von Proben, die Etablierung einer umfangreichen Referenzspektrenbibliothek und die sichere Archivierung aller experimentellen Daten umfassen. Das Verfahren der Probenvorbereitung wurde soweit modifiziert, dass gering konzentrierte Substanzen mittels GC-TOF-MS analysiert werden können. Dadurch wurde das durch die Probenvorbereitung limitierte Substanzspektrum erweitert. Anhand dieser Lösungsansätze wurden physiologisch relevante Stoffwechselprodukte identifiziert, welche indikativ (klassifizierend) bzw. prädiktiv (vorhersagend) für die physiologischen Prozesse sind. Für die Schwarzfleckigkeitsneigung und die Chipseignung wurde jeweils ein biochemisches Modell zur Vorhersage dieser Prozesse aufgestellt und auf eine Züchtungspopulation übertragen. Ferner wurden für die Schwarzfleckigkeit Stoffwechselprodukte des Respirationsstoffwechsels identifiziert sowie Aminosäuren, Glycerollipide und Phenylpropanoide für das Physiologische Alter als relevant erachtet. Das physiologische Altern konnte durch die Anwendung höherer Temperaturen beschleunigt werden. Durch Anwendung von Keimhemmern (Kümmelöl, Chlorpropham) wurde eine Verzögerung des physiologischen Alterns beobachtet. Die Applikation von Kümmelöl erwies sich dabei als besonders vorteilhaft. Kümmelöl behandelte Knollen wiesen im Vergleich zu unbehandelten Knollen nur Veränderungen im Aminosäure-, Zucker- und Sekundärstoffwechsel auf. Chlorpropham behandelte Knollen wiesen einen ähnlichen Stoffwechsel wie die unbehandelten Knollen auf. Für die bislang noch nicht identifizierten Stoffwechselprodukte wurden im Rahmen dieser Arbeit das Verfahren der „gezielten An-/Abreicherung“, der „gepaarten NMR/GC-TOF-MS Analyse“ und das „Entscheidungsbaumverfahren“ entwickelt. Diese ermöglichen eine Klassifizierung von GC-MS Signalen im Hinblick auf ihre chemische Funktionalität. Das Verfahren der gekoppelten NMR/GC-TOF-MS Analyse erwies sich dabei als besonders erfolgversprechend, da es eine Aufklärung bislang unbekannter gaschromatographischer Signale ermöglicht. In der vorliegenden Arbeit wurden neue Stoffwechselprodukte in der Kartoffelknolle identifiziert, wodurch ein wertvoller Beitrag zur Analytik der Metabolomik geleistet wurde. / Several factors influence the quality of crops. These include particular storage conditions and cultivar properties. Minimization of quality defects requires the employment of comprehensive metabolic analysis to enhance the marketing potential of crops. From this point of view chromatographic techniques coupled either with a mass spectrometer or the combination with nuclear magnetic resonance spectroscopy have been successfully applied to solve the main tasks. In the present work, a gas chromatograph was coupled to a time of flight mass spectrometer (GC-TOF-MS) to analyze physiological processes and attitudes of crops like black spot bruising, chips tanning, physiological aging, and sprouting inhibition. For this purpose the potato tuber was employed as a model plant. Therefore, new analytical approaches were developed comprising the targeted analysis of a multitude of samples, the establishment of a comprehensive mass spectral reference library and the built up of a secure archival storage system. Furthermore, the sample preparation protocol was modified to analyze trace components with the help of GC-TOF-MS as well. This helped to extend the discovery of more endogenous metabolites. These analytical approaches were required to identify physiological relevant indicative and predictive metabolites. Consequently, a biochemical model was build up for the process of black spot bruising and chips tanning respectively. These models could be applied to an unknown breeding progeny. Metabolites of the respiratory chain were identified as relevant for the process of black spot bruising whereas amino acids, lipids and phenylpropanoids were of high importance for the process of physiological aging.  The process of physiological aging could be accelerated while applying higher temperatures and could be delayed while applying sprouting inhibitors, like caraway oil and chlorpropham. Compared to chlorpropham, caraway oil exhibited more advantages with respect to storage attitudes although it caused significant changes in the amino acid, sugar and secondary metabolism during a common storage period. However, the chlorpropham treated tubers showed a similar phenotype in comparison to the control tubers. In addition, several methods were developed with respect to the classification of yet unidentified signals. These cover the decision tree process, the targeted enrichment and depletion of specific metabolites with the help of solid phase extraction and the paired NMR and GC-MS analyses. The paired NMR and GC-MS analysis appears very promising because it allows for the identification of unknown GC-MS signals. Thus, this work makes a valuable contribution to the analytics of the metabolome, as new metabolites could be identified which are of physiological relevance for the potato tuber.

No description available.

Rhizophytic algae are large, abundant primary producers throughout tropical and subtropical areas worldwide where they grow as an understory in seagrass beds, as well as form mixed or monospecific beds of exclusively rhizophytic algal species. In this dissertation, "rhizophytic algae" refers to coenocytic green algae (Chlorophyta) in the order Bryopsidales that use a net of rhizoids to anchor in unconsolidated sediments. In the development of seagrass beds, rhizophytic algae colonize bare patches and are thought to facilitate seagrass colonization by stabilizing sediments and providing organic matter. However, despite their prominence little is known about many aspects of the ecology of rhizophytic algae. Detailed information on the abundance and biomass of rhizophytic algae at the species level is scarce and the belowground components are seldom quantified. Moreover, rhizophytic algal communities located along the central west coast of Florida have received very little study. At three shallow coastal sites in the Lower Florida Keys and one on the central west coast of Florida, I measured the abundance, biomass, organic content, and morphometric features of the above- and belowground portions of all rhizophytic algal species present along transects in seagrass-algal bed habitat. Relatively diverse assemblages of these algae were present both in areas with and without a seagrass canopy, though dense (greater than or equal to 50%) seagrass cover correlated with decreased algal richness. Rhizophytic algal densities at Keys sites ranged from 68 - 143 thalli m-2 with total dry weights of 76.4 - 226.7 g m-2 with only calcified species present. The west coast of Florida site had the highest aboveground organic biomass (180 g m-2), the highest abundance of rhizophytic algae (365 thalli m-2), and abundant uncalcifed algae of the genus Caulerpa. Morphometric characteristics varied within a species among sites and may reflect differences in abiotic variables such as sediment grain size. The anchoring structures of these algae, made up of fine rhizoids and attached sediment, occupied up to 5.3% of the total volume of the top 5 cm of substrate. My results indicate that across rhizophytic algal species, even within a genus, the production of belowground structure and potential influence on ecosystem function is highly variable and not necessarily related to the aboveground biomass. These results provide new information on belowground structure provided by rhizophytic algal species and characterize the rhizophytic algal community on the central west coast of Florida. The role of rhizophytic algae in seagrass bed succession has been recognized, but little is known about the rate and species composition of colonization of recently created bare patches. In a series of field experiments at three sites on the central west coast of Florida, recruitment by rhizophytic algae into created cleared areas was rapid and dominated by two species of Penicillus and Udotea flabellum. In three weeks, rhizophytic algae were able to recruit, grow to their full height, and bind sufficient sediment to create full-sized holdfasts. Additional field experiments described here show thalli of all of the rhizophytic algal species tested (three species in three genera) were able to regenerate from holdfasts (with small stubs of stipe attached) in a matter of weeks. Overall, my results suggest that belowground structures play a key role in recolonization by, and recovery of, rhizophytic algae after disturbance and are likely important to the long-term persistence of these algal populations. Bryopsidalean algae often have high concentrations of defensive compounds inside their thalli and these terpenoid secondary metabolites possess anti-fouling capability in laboratory tests. Because fouling is ubiquitous in marine environments and epibonts have harmful effects on their hosts, researchers have proposed that rhizophytic algae use these compounds to prevent fouling. For this to be an effective strategy, the compounds must be presented to potential colonizers on the external aboveground surfaces. Thus, I examined the chemistry of rhizophytic algal surfaces using extractions that avoid mechanical damage. Secondary metabolites were not detected in the surface extracts of four species while these compounds were detected in the whole plant extracts. My results, coupled with previous studies on the degradation of these metabolites in seawater and the presence of fouled plants in the field, and suggest non-polar secondary metabolites are not deployed onto the surfaces of rhizophytic algae as a defense against fouling.

Discovery of protein-metabolite and protein-substrate interactions that can specifically regulate genes involved in human biology is an important pursuit, as the study of such interactions can expand our understanding of human physiology and reveal novel therapeutic targets. The identification and characterization of these interactions can be approached from different perspectives. Chemists often use bioactive small molecules, such as natural products or synthetic compounds, as probes to identify therapeutically relevant protein targets. Biochemists and biologists often begin with a specific protein and seek to identify the endogenous ligands that bind to it. These interests have led to the development of methodology that relies heavily on synthetic and analytical chemistry to identify interactions, an approach that is complemented by in vivo strategies for validating the biological consequences of specific interactions.

This study investigates the etiology, diagnosis, and treatment of follicular stasis in female veiled chameleons (Chamaeleo calyptratus). Reproductive status was assessed by enzyme immunoassay of fecal metabolites of estrogen, progesterone, testosterone, and corticosterone; ultrasonography; and male introduction trials. Ultrasonography and hormone pattern analysis confirmed follicular stasis, while female response to male presence was inconclusive. Hormone patterns of corticosterone metabolites indicated a cyclical pattern consistent with reproductive events, but there was insufficient data to compare peak levels between ovulatory and non-ovulatory cycles. Ovulation induction was unsuccessful using either chicken GnRH-II, or a combination of progesterone and prostaglandin F2α. Feed restriction induced weight loss, but this was not directly related to changes in follicle size. Prevention of follicular development (i.e. contraception) was attempted using Depo-Provera and Lupron Depot, but neither treatment was effective. The outcomes of this study supplement the information on follicular stasis in reptiles, but further research is still needed. / NSERC, Toronto Zoo

No description available.

No description available.

Tuberculosis (TB) is one of the deadliest infectious diseases of our time, with 1.4 million deaths globally, recorded in 2010 (3800 deaths a day) by the World Health Organization (WHO). Currently, South Africa ranks third on the 2011 list of 22 high-burden TB countries in the world and it was estimated that each active-TB person could potentially infect 10–15 people annually. The WHO additionally reported that in the year 2009, 87% of all TB patients worldwide were successfully treated, with a treatment success rate of 74% reported for South Africa. Despite this however, non-adherence to anti-TB treatment is still a major issue, due to it resulting in a global increased prevalence of drug resistant TB and subsequently TB treatment failure. Treatment failure is thought to be caused by a number of factors, however, it still remains largely misunderstood. One aspect of this, that isn't clearly addressed in the literature, is the underlying variation in each patient, resulting in his/her varying reaction to the drug regimen, and hence it’s varying efficacy from one patient to the next. Furthermore, little is known about the underlying variation of the host to the primary TB infection or response to the TB disease state, and how some patients have more effective mechanisms for eliminating the infection, or recovering from the disease. Considering this, a metabolomics research study using GC×GC-TOFMS was conducted, in order to identify potential metabolite markers which may be used to better characterise the underlining mechanisms associated with poor treatment outcomes (treatment failure). The first aim was to evaluate the accuracy and efficiency of the methodology used, as well as to determine the capability and accuracy of the analyst to perform these methods. In order to evaluate the GCxGC-TOFMS analytical repeatability, one QC sample was extracted and injected repeatedly (6 times) onto the GC×GC-TOFMS. Similarly, the analyst's repeatability for performing the organic acid extraction and analyses was also determined, using 10 identical QC samples, which were extracted and injected separately. CV values were subsequently calculated from the collected and processed data as a measure of this. Of all the compounds detected from the 6 QC sample repeats used for GCxGC-TOFMS repeatability, 95.59% fell below a 50% CV value, and 93,7% of all the compounds analysed for analyst repeatability had a CV < 50. Subsequently, using the above metabolomics approach, in addition to a wide variety of univariate and multivariate statistical methods, two patient outcome groups were compared. A sample group cured from TB after 6 months of treatment was compared vs a sample group where treatment failed after the 6 month period. Using urine collected from these two patient groups at various time points, the following metabolomics comparisons where made: 1) at time of diagnosis, before any anti-TB treatment was administrated, 2) during the course of treatment, in order to determine any variance in these groups due to a varying response to the anti-TB drugs, 3) over the duration of the entire 6 months treatment regimen, in order to determine if differences exist between the two groups over time. A clear natural differentiation between the cured and failed outcome groups were obtained at time of diagnosis, and a total of 39 metabolites markers were subsequently identified. These metabolites were classified according to their various origins, and included (1) those associated with the presence of M. tuberculosis bacteria, (2) those resulting from an altered host metabolism due to the TB infection, and (3) metabolites of various exogenous origins. The detailed interpretation of these metabolites suggests that a possible underlying RCD or some sort of mitochondrial dysfunction may be present in the treatment failure group, which may also be induced through an external stimulus, such as alcohol consumption. We hypothesise that this may possibly result in a far greater severity to M. tuberculosis infection in this group, subsequently causing a reduced capacity for a successful treatment outcome, also considering the critical role of the mitochondria in the metabolism of anti-TB drugs. Furthermore, 20 metabolite markers were identified when comparing the two outcome groups during the treatment phase of this metabolomics investigation. A vast majority of these 20 metabolites were also identified as markers for time 0 (time of diagnosis). Additionally, metabolites associated with anti-TB drug induced side effects, were also found to be comparatively increased in the treatment failure group, indicative of more pronounced liver damage, accompanied by metabolites characteristic of a MADD metabolite profile, due to a deficient electron transport flavoprotein, confirming previous experiments done in rats. These side effects have also previously been implicated as a major contributor of poor treatment compliance, and ultimately treatment failure. Lastly, 35 metabolite markers were identified by time dependent statistical analysis and represented those metabolites best describing the variation between the treatment outcome groups over the entire study duration (from diagnosis, to week 26). This time dependent statistical analysis identified markers, using an alternative statistical approach, and confirmed previous findings and added in a better characterisation of treatment failure. Considering the above, we successfully applied a metabolomics approach for identifying metabolites which could ultimately aid in the prediction and monitoring of treatment outcomes. This additionally led to a better understanding and or characterisation of the phenomenon known as treatment failure, as well as the underlying mechanisms related to this occurrence. / MSc (Biochemistry), North-West University, Potchefstroom Campus, 2013

Tuberculosis (TB) is one of the deadliest infectious diseases of our time, with 1.4 million deaths globally, recorded in 2010 (3800 deaths a day) by the World Health Organization (WHO). Currently, South Africa ranks third on the 2011 list of 22 high-burden TB countries in the world and it was estimated that each active-TB person could potentially infect 10–15 people annually. The WHO additionally reported that in the year 2009, 87% of all TB patients worldwide were successfully treated, with a treatment success rate of 74% reported for South Africa. Despite this however, non-adherence to anti-TB treatment is still a major issue, due to it resulting in a global increased prevalence of drug resistant TB and subsequently TB treatment failure. Treatment failure is thought to be caused by a number of factors, however, it still remains largely misunderstood. One aspect of this, that isn't clearly addressed in the literature, is the underlying variation in each patient, resulting in his/her varying reaction to the drug regimen, and hence it’s varying efficacy from one patient to the next. Furthermore, little is known about the underlying variation of the host to the primary TB infection or response to the TB disease state, and how some patients have more effective mechanisms for eliminating the infection, or recovering from the disease. Considering this, a metabolomics research study using GC×GC-TOFMS was conducted, in order to identify potential metabolite markers which may be used to better characterise the underlining mechanisms associated with poor treatment outcomes (treatment failure). The first aim was to evaluate the accuracy and efficiency of the methodology used, as well as to determine the capability and accuracy of the analyst to perform these methods. In order to evaluate the GCxGC-TOFMS analytical repeatability, one QC sample was extracted and injected repeatedly (6 times) onto the GC×GC-TOFMS. Similarly, the analyst's repeatability for performing the organic acid extraction and analyses was also determined, using 10 identical QC samples, which were extracted and injected separately. CV values were subsequently calculated from the collected and processed data as a measure of this. Of all the compounds detected from the 6 QC sample repeats used for GCxGC-TOFMS repeatability, 95.59% fell below a 50% CV value, and 93,7% of all the compounds analysed for analyst repeatability had a CV < 50. Subsequently, using the above metabolomics approach, in addition to a wide variety of univariate and multivariate statistical methods, two patient outcome groups were compared. A sample group cured from TB after 6 months of treatment was compared vs a sample group where treatment failed after the 6 month period. Using urine collected from these two patient groups at various time points, the following metabolomics comparisons where made: 1) at time of diagnosis, before any anti-TB treatment was administrated, 2) during the course of treatment, in order to determine any variance in these groups due to a varying response to the anti-TB drugs, 3) over the duration of the entire 6 months treatment regimen, in order to determine if differences exist between the two groups over time. A clear natural differentiation between the cured and failed outcome groups were obtained at time of diagnosis, and a total of 39 metabolites markers were subsequently identified. These metabolites were classified according to their various origins, and included (1) those associated with the presence of M. tuberculosis bacteria, (2) those resulting from an altered host metabolism due to the TB infection, and (3) metabolites of various exogenous origins. The detailed interpretation of these metabolites suggests that a possible underlying RCD or some sort of mitochondrial dysfunction may be present in the treatment failure group, which may also be induced through an external stimulus, such as alcohol consumption. We hypothesise that this may possibly result in a far greater severity to M. tuberculosis infection in this group, subsequently causing a reduced capacity for a successful treatment outcome, also considering the critical role of the mitochondria in the metabolism of anti-TB drugs. Furthermore, 20 metabolite markers were identified when comparing the two outcome groups during the treatment phase of this metabolomics investigation. A vast majority of these 20 metabolites were also identified as markers for time 0 (time of diagnosis). Additionally, metabolites associated with anti-TB drug induced side effects, were also found to be comparatively increased in the treatment failure group, indicative of more pronounced liver damage, accompanied by metabolites characteristic of a MADD metabolite profile, due to a deficient electron transport flavoprotein, confirming previous experiments done in rats. These side effects have also previously been implicated as a major contributor of poor treatment compliance, and ultimately treatment failure. Lastly, 35 metabolite markers were identified by time dependent statistical analysis and represented those metabolites best describing the variation between the treatment outcome groups over the entire study duration (from diagnosis, to week 26). This time dependent statistical analysis identified markers, using an alternative statistical approach, and confirmed previous findings and added in a better characterisation of treatment failure. Considering the above, we successfully applied a metabolomics approach for identifying metabolites which could ultimately aid in the prediction and monitoring of treatment outcomes. This additionally led to a better understanding and or characterisation of the phenomenon known as treatment failure, as well as the underlying mechanisms related to this occurrence. / MSc (Biochemistry), North-West University, Potchefstroom Campus, 2013

Inflammatory bowel disease (IBD) is a chronic inflammatory disorder that occurs as a consequence of a genetic mutation that results in an overly aggressive immune response to normal bacteria. Metabolomics is a new born cousin to genomics and proteomics and involves a high throughput identification, characterization and quantification of small molecule metabolites generated by the organism. This study will show that metabolomics can be an effective tool in studying the differences between wild type and IL 10 KO mice as they age in axenic and conventional environments, and the onset of disease in a conventional environment. I show specific changes upon colonizing axenic mice with fecal bacteria that are similar to changes occurring over 16 weeks of conventional growth. Several bacterial metabolites have been identified that may play a role in the pathogenesis or provide clues to the interactions of the gut microbiota with the intestinal immune system. / Experimental Medicine