Please read the abstract in the section 00front of this document / Thesis (PhD (Pharmacology))--University of Pretoria, 2005. / Pharmacology / unrestricted

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Ample studies have shown that perturbation of metabolic phenotype is correlated with gene mutation and pathogenesis of colorectal cancer (CRC) and rheumatoid arthritis (RA). Mass spectrometry (MS)-based metabolomics as a powerful and stable approach is widely applied to bridge the gap from genotype/metabolites to phenotype. In CRC suffers, KRAS mutation accounts for 35%-45%. In previous study, SLC25A22 that encodes the mitochondrial glutamate transporter was found to be overexpressed in CRC tumor and thus to be essential for the proliferation of CRC cells harboring KRAS mutations. However, the role of SLC25A22 on metabolic regulation in KRAS-mutant CRC cells has not been comprehensively characterized. We performed non-targeted metabolomics, targeted metabolomics and isotope kinetic analysis of KRAS-mutant DLD1 cells with or without SLC25A22 knockdown using ultra-high performance liquid chromatography (UHPLC) coupled to Orbitrap MS and tandem MS (MS/MS). In global metabolomics analysis, 35 differentially regulated metabolites were identified, which were primarily involved in alanine, aspartate and glutamate metabolism, urea cycle and polyamine metabolism. Then targeted metabolomics analysis on intracellular metabolites, including tricarboxylic acid (TCA) cycle intermediates, amino acids and polyamines, was established by using LC-MS/MS coupled with an Amide BEH column. Targeted metabolomics analysis revealed that most TCA cycle intermediates, aspartate (Asp)-derived asparagine, alanine and ornithine (Orn)-derived polyamines were strongly down-regulated in SLC25A22 knockdown cells. Moreover, the targeted kinetic isotope analysis using [U-13C5]-glutamine as isotope tracer showed that most of the 13C-labeled TCA cycle intermediates were down-regulated in SLC25A22-silencing cells. Orn-derived polyamines were significantly decreased in SLC25A22 knockdown cells and culture medium. Meanwhile, accumulation of Asp in knockdown of GOT1 cells indicated that oxaloacetate (OAA) was majorly converted from Asp through GOT1. Exogenous addition of polyamines could significantly promote cell proliferation in DLD1 cells, highlighting their potential role as oncogenic metabolites that function downstream of SLC25A22-mediated glutamine metabolism. SLC25A22 acts as an essential metabolic regulator during CRC progression as promotes the synthesis of TCA cycle intermediates, Asp-derived amino acids and polyamines in KRAS-mutant CRC cells. Moreover, OAA and polyamine could promote KRAS-mutant CRC cell growth and survival. Rheumatoid arthritis (RA) is a chronic, inflammatory and symmetric autoimmune disease and a major cause of disability. However, there is insufficient pathological evidence in term of metabolic signatures of rheumatoid arthritis, especially the metabolic perturbation associated with gut microbiota (GM). Based on consistent criteria without special diet and therapeutic intervention to GM, we enrolled 50 RA patients and 50 healthy controls. On basis of the platform of UHPLC-MS and GC-MS, were performed for the non-targeted metabolomics to investigate alterations of endogenous metabolites in response to RA inflammation and interaction with GM. 32 and 34 significantly changed metabolites were identified in urine and serum of patients with RA, respectively. The altered metabolites were identified by HMDB, METLIN database or authentic standards, and mostly metabolites were attributed into tryptophan and phenylalanine metabolism, valine, leucine and isoleucine biosynthesis, aminoacyl-tRNA biosynthesis and citrate cycle. To obtain alterations of more components in tryptophan and phenylalanine metabolism, we developed and validated a targeted metabolomics method of 19 metabolites by using LC-QqQ MS. Combining the results of targeted metabolomics with global metabolomics, significantly up-regulated kynurenine (KYN), anthranilic acid (AA) and 5-hydroxylindoleacetic acid (HIAA) simultaneously in urine and serum was found to implicate the activation of tryptophan metabolism under the condition of RA, which acted pro-inflammatory roles in inflammation and was closely correlated with GM. IDO/TDO functioned as a pro-inflammation mediator was overexpressed in RA patients. Urinary kynurenic acid and serum serotonin that have impacts on anti-inflammation in immune system were down-regulated in RA patients. The levels of phenylacetic acid and phenyllactic acid serving as a pro-inflammatory and an anti-inflammatory agent, respectively, increased in serum of patients with RA. Moreover, certain essential amino acids (EAAs), and mostly conditional EAAs were decreased in RA patients, which have been reported to inhibit cell proliferation of immune cells. In particular, deficiency of branched chain amino acids (BCAAs, valine and isoleucine) was observed in serum of patients with RA, which may lead to muscle loss and cartilage damage. The specificity of all altered metabolites resulted from RA was considerably contributed through the GM-derived metabolites. The findings revealed that GM-modulated RA inflammation was mainly resulted from tryptophan and phenylalanine metabolism, and amino acid biosynthesis, which may provide more information for better understanding the RA mechanism.

Cannabis use may occur during pregnancy to alleviate symptoms of nausea, anxiety, and stress. However, fetal exposure to cannabinoids, such as THC and CBD, poses potential risks to neurodevelopment and long-term health outcomes. The endocannabinoid system (ECS) is involved in neurodevelopment and gastrointestinal (GI) homeostasis and responds to exogenous cannabinoids. This study aimed to investigate both the baseline development of the ECS in the GI tract and the effects of prenatal cannabis exposure on the development of gut-brain axis components and the ECS. Samples from outbred mice were collected at a set of developmentally important time points, ranging from embryonic day 14 to postnatal day 21. The localization of cannabinoid receptor 1 (CB1) expression was examined in the fetal and postnatal small intestine, and mRNA analysis was performed to evaluate changes in gene expression. Under normal conditions, components of the ECS display developmental regulation in the GI tract. A subset of pregnant mice was exposed to cannabis smoke daily, using a strain of cannabis containing high concentrations of THC, simulating ‘real world’ cannabis use. Exposure to cannabis prenatally revealed significant changes in biometric outcomes, and in the transcription of genes associated with the ECS, ENS development, barrier function, and serotonin signaling pathways. In addition, the onset of ambulation was delayed. These findings provide valuable insights into the developmental regulation of ECS during the prenatal period and highlight the potential risks associated with prenatal cannabis exposure, particularly in terms of gut-brain axis development. Further research is required to better understand the underlying mechanisms. / Thesis / Master of Science (MSc) / There have been growing reports of cannabis consumption during pregnancy, to relieve nausea, anxiety, and stress. However, compounds in cannabis, like THC and CBD, can pose risks to the baby's development and long-term health. This project studied how cannabis use during pregnancy affects gastrointestinal (GI) development, and communication between the GI system and the brain. The endocannabinoid system (ECS) plays a role in regulating the normal functioning of the GI tract and is influenced by cannabis compounds. By exposing pregnant mice to cannabis smoke, we observed significant changes in gene expression in the fetal intestine relating to the GI nervous system, the strength of the gut barrier, and various molecular signalling pathways. In addition, prenatally exposed mice had delayed walking ability. These findings highlight the potential risks of cannabis use during pregnancy on gut-brain axis development. Further research is needed to understand the mechanisms causing these disruptions.

Trillions of microbes line the gastrointestinal tract to form the gut microbiome, a symbiotic organ whose supportive functions include energy production, immune homeostasis, and defense against pathogens. Disturbances to gut microbial composition, in turn, drive the pathogenesis of various metabolic, inflammatory, and carcinogenic diseases. Much effort has been dedicated to elucidating environmental triggers of gut dysbiosis, not the least of which is the consumption of medications. Antibiotics eradicate keystone commensals and enhance pathogenic behaviors of persisting pathobionts, whose resistance mechanisms can have off-target effects on human physiology and treatment response. Recent evidence indicates that the spectrum of antimicrobial compounds that disturb the gut microbiome extends far beyond traditional antibiotics, and includes commonly prescribed cardiovascular, neuropsychiatric, metabolic, and cancer medications. Although the capacity of non-antibiotic pharmaceuticals to induce gut dysbiosis is well appreciated, their impact on gut microbial function has not been studied systematically. Bacterial multi-omic profiling offers a cost-effective, high-throughput approach to understanding bacterial genetic responses to chemical perturbations, and how these functional changes might reciprocally impact relevant human phenotypes. Our laboratory, which houses a personal strain biobank of over 30,000 gut bacterial isolates spanning over 400 taxa, has established scalable pipelines for bacterial genomic and transcriptomic profiling that are readily applicable to diverse non-model gut microbes. We applied these methodologies to healthy fecal samples and bacterial isolates to elucidate strain-level responses to common pharmaceuticals with known gut microbiome associations. We first performed a gut microbiota transcriptomic screen of 19 representative fecal isolates against 20 top-prescribed orally delivered medications. Computational analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG) revealed induction of pathways associated with metabolism and multidrug resistance, including upregulation of efflux machinery by lipid-lowering drugs, antidepressants and cardiovascular medications. We discovered many bacterial responses with clinical significance, which we computationally validated using clinical metagenomic datasets. Most importantly, we showed that statin-mediated overexpression of the AcrAB-TolC efflux pump generates collateral toxicity in dietary retinol and secondary bile acids, resulting in depletion of pump-containing Bacteroidales species from patient microbiomes. We next performed the first comprehensive screen for antimicrobial activity in cancer drugs by exposing three healthy fecal samples to a panel of 41 first-line cancer therapeutics. Using 16S-genomic profiling, we identified several members of the targeted kinase inhibitor (TKI) class that induced gut dysbiosis, including first-line hepatocellular carcinoma (HCC) treatment sorafenib. We profiled natural bacterial isolates exposed to different TKI HCC treatments, and again observed transcriptional induction of conserved multidrug efflux pumps. Adaptive evolution assays identified Resistance-Nodulation-Division (RND) efflux pumps as effectors of TKI resistance. Remarkably, we demonstrated that acquired TKI resistance in evolved Bacteroidales lineages generated strain-specific cross-resistances and collateral sensitivities to several unrelated antibiotics. Collectively, our work demonstrates the importance of profiling xenobiotic impacts on the gut microbial resistome, as bacterial adaptations to pharmaceutical toxicities can feed back onto microbiome communities and the human host to affect health outcomes.

The Attwater’s prairie-chicken (Tympanuchus cupido attwateri; APC) is a species of grouse native to Texas coastal prairies and is on the critically endangered species list as a result of habitat destruction and overhunting. All of the current populations were captively bred and released into the wild. Survivorship for released APCs is very low, and individuals seldom survive to reproduce in the wild. One factor contributing to this may be an alteration in the gut microbiota as a result of captivity. Factors potentially influencing the gut microbial composition in captivity include antibiotic therapy, stress, and a predominantly commercially formulated diet. Recent studies have begun to shed light on the importance of the host microbial endosymbionts. Antibiotic administration, stress, diet, age, genotype and other factors have been shown to influence microbial populations in the gastrointestinal tracts of many different vertebrates. Sequencing of 16S rRNA gene amplicons on the Ion Torrent™ platform was used in this study to identify groups of bacteria in the cloacas as a surrogate for the gut microbiota in the APC. Antibiotic-treated and untreated birds, wild-hatched and captive-bred birds, and individuals sampled before and after release to the wild were examined. Significant differences were found between wild-hatched and captive raised birds both pre- and post release. In addition, there was extensive variation among the populations at the lower taxonomic ranks between individuals for each group of APCs. Principal coordinate analysis based on the weighted UniFrac distance metric further exhibited some clustering of individuals by treatment. These data suggest that captive breeding may have long-term effects on the cloacal microbiota of APCs with unknown consequences to their long-term health and survivorship.

Obesity is a common disease among all ages that has threatened human health and has become a global concern. Gut microbiota can affect human metabolism and thus may modulate obesity. Certain mixes of gut microbiota can protect the host to be healthy or predispose the host to obesity. Modern next-generation sequencing technique allows accessing huge amount of genetic information underlying microbiota and thus provides new insights into the functionality of these micro-organisms and their interactions with the host. Multiple previous studies have demonstrated that the microbiome might contribute to obesity by increasing dietary energy harvest, promoting fat deposition and triggering systemic inflammation. However, these researches are either based on lab cultivation studies or basic statistical analysis. In order to further explore how gut microbiota affect obesity, this thesis utilize a series of machine learning methods to analyze large amount of metagenomics data from human gut microbiome. The publicly available HMP (Human Microbiome Project) metagenomic sequencing data, contain microbiome data for healthy adults, including overweight and obese individuals, were used for this study. HMP gut data were organized based on two different feature definitions: taxonomic information and metabolic reconstruction information. Several widely used classification algorithms: namely Naive Bayes, Random Forest, SVM and elastic net logistic regression were applied to predict healthy or obese status of the subjects based on the cross-validation accuracy. Furthermore, the corresponding feature selection algorithms were used to identify signature features in each dataset that lead to the differences between healthy and obese samples. The results showed that these algorithms perform poorly on taxonomic data than metabolic pathway data though lots of selected taxa are still supported by literature. Among all the combinations between different algorithms and data, elastic net logistic regression has the best cross-validation performance and thus becomes the best model. In this model, several important features are found and some of these are consistent with the previous studies. Rerunning classifiers by using features selected by elastic net logistic regression again further improved the performance of the classifiers. On the other hand, this study uncovered some new features that haven't been supported by previous studies. The new features could also be the potential target to distinguish obese and healthy subjects. The present thesis work compares the strengths and weaknesses of different machine learning techniques with different types of features originating from the same metagenomics data. The features selected by these models could provide a deep understanding of the metabolic mechanisms of micro-organisms. It is therefore worth to comprehensively understand the differences of gut microbiota between healthy and obese subjects, and particularly how gut microbiome affects obesity.

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Thesis (M.Tech.: Biotechnology)- Dept. of Biotechnology, Durban University of Technology, 2007 xv, 127 leaves / The human gut microbiota play a major role in host health, and attempts are being made to manipulate the composition of the gut microbiota-increase the composition of bacterial groups, such as lactobacilli and bifidobacteria that are perceived as exerting health promoting properties. These bacteria defined as food supplements (probiotics) beneficially affect the host by improving the intestinal microbial balance, and have been used to change the composition of the colonic microbiota. However, such changes may be transient, and the implantation of exogenous bacteria therefore becomes limited. In contrast, prebiotics are naturally occurring carbohydrates that are classified as non-digestible oligosaccharides present in edible plants. These carbohydrates enter the colon as intact compounds, elicit systemic physiological functions and act as fermentable substrates for colonic microflora-influencing the species composition and metabolic characteristics of intestinal microflora providing important health attributes. Currently, a widely marketed prebiotic, inulin is extracted from plants of the family Asteraceae. There are many unexploited plants that are regularly consumed and that may have a prebiotic effect or can have very high levels of inulin which could make them commercially viable. In this study, we investigated prebiotic compounds, especially inulin from locally growing, non-commercialised leafy plants. The aqueous extracts of 22 plants from the families Asparagaceae, Alliaceae, Asteraceae, Solanaceae, Cucurbitaceae, Amaranthaceae, Acanthaceae, Polygonaceae, Portulaceae, Fabaceae, Chenopodiaceae, Pedaliaceae and Apiaceae from Kwa-Zulu Natal were investigated for a prebiotic effect using a modified batch-culture technique with Lactobacillus bulgaricus, Lactobacillus lactis, Lactobacillus reuteri and Bifidobacterium longum, four common probiotics and the inulin content of the plants was determined using high performance liquid chromatography. Of the 22 plants studied, Solanum nigrum, Amaranthus spinosus, Amaranthus hybridus, Asystasia gangetica, Senna occidentalis, Cerathoteca triloba, Asparagus sprengeri, Tulbaghia violacea, Sonchus oleraceus and Taraxacum officinale exhibited a prebiotic effect. The prebiotic effect of the Taraxacum officinale, Sonchus oleraceus and Asparagus sprengeri extracts on L. lactis and L. reuteri was higher than or equivalent to inulin-a commercial prebiotic. In this study, Sonchus oleraceus exhibited the best prebiotic effect-was the only plant to stimulate all the probiotics including B. longum. Of all the plants analysed, Asparagus sprengeri tuber contained the highest amount of inulin (3.55%).