The gut microbiota as a contributing factor to antipsychotic-induced weight gain and metabolic dysfunction

Schizophrenia represents one of the world’s most devastating illnesses due to its often lifelong course and debilitating nature. The treatment of schizophrenia has vastly improved over recent decades with the discovery of several antipsychotic compounds; however these drugs are not without adverse effects that must be addressed to maximize their therapeutic value. Newer, atypical, antipsychotics are associated with a compilation of serious metabolic side effects including weight gain, insulin resistance, fat deposition, glucose dysregulation and ensuing co-morbidities such as type II diabetes mellitus. The mechanisms underlying these side effects remain to be fully elucidated and adequate interventions are lacking. Further understanding of the factors that contribute these side effects is therefore required in order to develop effective adjunctive therapies and to potentially design antipsychotic drugs in the future with reduced impact on the metabolic health of patients. We investigated if the gut microbiota represented a novel mechanism contributing to the metabolic dysfunction associated with atypical antipsychotics. The gut microbiota comprises the bacteria that exist symbiotically within the gastrointestinal tract, and has been shown in recent years to be involved in several aspects of energy balance and metabolism. We have demonstrated that administration of certain antipsychotics in the rat results in an altered microbiota profile and, moreover, that the microbiota is required for the full scale of metabolic dysfunction to occur. We have further shown that specific antibiotics can attenuate certain aspects of olanzapine and risperidone–induced metabolic dysfunction, in particular fat deposition and adipose tissue inflammation. Mechanisms underlying this novel link appear to involve energy utilization via expression of lipogenic genes as well as reduced inflammatory tone. Taken together, these data indicate that the gut microbiota is an important factor involved in the myriad of metabolic complications associated with antipsychotic therapy. Furthermore, these data support the future investigation of microbial-based therapeutics for not only antipsychotic-induced weight gain but also for tackling the global obesity epidemic.

Investigations into selective metabolic aspects of bifidobacteria: carbohydrate metabolism, fatty acid biosynthesis and plasmid biology

The gastrointestinal tract (GIT) is a diverse ecosystem, and is colonised by a diverse array of bacteria, of which bifidobacteria are a significant component. Bifidobacteria are Gram-positive, saccharolytic, non-motile, non-sporulating, anaerobic, Y-shaped bacteria, which possess a high GC genome content. Certain bifidobacteria possess the ability to produce conjugated linoleic acid (CLA) from linoleic acid (LA) by a biochemical pathway that is hypothesised to be achieved via a linoleic isomerase. In Chapter two of this thesis it was found that the MCRA-specifying gene is not involved in CLA production in B. breve NCFB 2258, and that this gene specifies an oleate hydratase involved in the conversion of oleic acid into 10-hydroxystearic acid. Prebiotics are defined as non-digestible food ingredients that beneficially affect the host by selectively stimulating growth and/or activity of one or a limited number of bacteria in the colon. Key to the development of such novel prebiotics is to understand which carbohydrates support growth of bifidobacteria and how such carbohydrates are metabolised. In Chapter 3 of this thesis we describe the identification and characterisation of two neighbouring gene clusters involved in the metabolism of raffinose-containing carbohydrates (plus related carbohydrate melibiose) and melezitose by Bifidobacterium breve UCC2003. The fourth chapter of this thesis describes the analysis of transcriptional regulation of the raf and mel clusters. In the final experimental chapter two putative rep genes, designated repA7017 and repB7017, are identified on the megaplasmid pBb7017 of B. breve JCM 7017, the first bifidobacterial megaplasmid to be reported. One of these, repA7017, was subjected to an in-depth characterisation. The work described in this thesis has resulted in an improved understanding of bifidobacterial fatty acid and carbohydrate metabolism, Furthermore, attempts were made to develop novel genetic tools.

Studies on factors relating to the development of defects in commercial cheese

Defects in commercial cheese result in a downgrading of the final cheese and a consequential economic loss to the cheese producer. Developments of defects in cheese are often not fully understood and therefore not controllable by the producer. This research investigated the underlying factors in the development of split and secondary fermentation defect and of pinking defects in commercial Irish cheeses. Split defect in Swiss-type cheese is a common defect associated with eye formation and manifests as slits and cracks visible in the cut cheese loaf (Reinbold, 1972; Daly et al., 2010). No consensus exists as to the definitive causes of the defect and possible factors which may contribute to the defect were reviewed. Models were derived to describe the relationship between moisture, pH, and salt levels and the distance from sample location to the closest external block surface during cheese ripening. Significant gradients within the cheese blocks were observed for all measured parameters in cheeses at 7 day post/after manufacture. No significant pH gradient was found within the blocks on exit from hot-room ripening and at three months post exit from the hot-room. Moisture content reached equilibrium within the blocks between exit from hot-room and 3 months after exit from hot-room while salt and salt-to-moisture levels had not reached equilibrium within the cheese blocks even at three months after exit from hot-room ripening. A characterisation of Swiss-type cheeses produced from a seasonal milk supply was undertaken. Cheeses were sampled on two days per month of the production year, at three different times during the manufacturing day, at internal and external regions of the cheese block and at four ripening time points (7 days post manufacture, post hot-room, 14 days post hot-room and 3 months in a cold room after exit from hot-room). Compositional, biochemical and microbial indices were determined, and the results were analysed as a splitplot with a factorial arrangement of treatments (season, time of day, area) on the main plot and ripening time on the sub-plot. Season (and interactions) had a significant effect on pH and salt-in-moisture levels (SM), mean viable counts of L. helveticus, propionic acid and non-starter lactic acid bacteria, levels of primary and secondary proteolysis and cheese firmness. Levels of proteolysis increased significantly during hot-room ripening but also during cold room storage, signifying continued development of cheese ripening during cold storage (> 8°C). Rheological parameters (e.g. springiness and cohesiveness) were significantly affected by interactions between ripening and location within cheese blocks. Time of day of manufacture significantly affected mean cheese calcium levels at 7 days post manufacture and mean levels of arginine and mean viable counts of NSLAB. Cheeses produced during the middle of the production day had the best grading scores and were more consistent compared to cheeses produced early or late during day of manufacture. Cheeses with low levels of S/M and low values of resilience were associated with poor grades at 7 days post manufacture. Chesses which had high elastic index values and low values of springiness in the external areas after exit from hot-room ripening also obtained good commercial grades. Development of a pink colour defect is an intermittent defect in ripened cheese which may or may not contain an added colourant, e.g., annatto. Factors associated with the defect were reviewed. Attempts at extraction and identification of the pink discolouration were unsuccessful. The pink colour partitioned with the water insoluble protein fraction. No significant difference was observed between ripened control and defect cheese for oxygen levels and redox potential or for the results of elemental analysis. A possible relationship between starter activity and defect development was established in cheeses with added coulourant, as lower levels of residual galactose and lactose were observed in defective cheese compared to control cheese free of the defect. Swiss-type cheese without added colourant had significantly higher levels of arginine and significantly lower lactate levels. Flow cell cytometry indicated that levels of bacterial cell viability and metabolic state differed between control and defect cheeses (without added colourant). Pyrosequencing analysis of cheese samples with and without the defect detected the previously unreported bacteria in cheese, Deinococcus thermus (a potential carotenoid producer). Defective Swiss-type cheeses had elevated levels of Deinococcus thermus compared to control cheeses, however the direct cause of pink was not linked to this bacterium alone. Overall, research was undertaken on underlying factors associated with the development of specific defects in commercial cheese, but also characterised the dynamic changes in key microbial and physicochemical parameters during cheese ripening and storage. This will enable the development of processing technologies to enable seasonal manipulation of manufacture protocols to minimise compositional and biochemical variability and to reduce and inhibit the occurrence of specific quality defects.

Power system parameters forecasting using Hilbert-Huang transform and machine learning

A novel hybrid data-driven approach is developed for forecasting power system parameters with the goal of increasing the efficiency of short-term forecasting studies for non-stationary time-series. The proposed approach is based on mode decomposition and a feature analysis of initial retrospective data using the Hilbert-Huang transform and machine learning algorithms. The random forests and gradient boosting trees learning techniques were examined. The decision tree techniques were used to rank the importance of variables employed in the forecasting models. The Mean Decrease Gini index is employed as an impurity function. The resulting hybrid forecasting models employ the radial basis function neural network and support vector regression. A part from introduction and references the paper is organized as follows. The second section presents the background and the review of several approaches for short-term forecasting of power system parameters. In the third section a hybrid machine learningbased algorithm using Hilbert-Huang transform is developed for short-term forecasting of power system parameters. Fourth section describes the decision tree learning algorithms used for the issue of variables importance. Finally in section six the experimental results in the following electric power problems are presented: active power flow forecasting, electricity price forecasting and for the wind speed and direction forecasting.

Multi-parametric metabolic assessment of cells under stress conditions

Glycolysis, glutaminolysis, the Krebs cycle and oxidative phosphorylation are the main metabolic pathways. Exposing cells to key metabolic substrates (glucose, glutamine and pyruvate); investigation of the contribution of substrates in stress conditions such as uncoupling and hypoxia was conducted. Glycolysis, O2 consumption, O2 and ATP levels and hypoxia inducible factor (HIF) signalling in PC12 cells were investigated. Upon uncoupling with FCCP mitochondria were depolarised similarly in all cases, but a strong increase in respiration was only seen in the cells fed on glutamine with either glucose or pyruvate. Inhibition of glutaminolysis reversed the glutamine dependant effect. Differential regulation of the respiratory response to FCCP by metabolic environment suggests mitochondrial uncoupling has a potential for substrate-specific inhibition of cell function. At reduced O2 availability (4 % and 0 % O2), cell bioenergetics and local oxygenation varied depending on the substrate composition. Results indicate that both supply and utilisation of key metabolic substrates can affect the pattern of HIF-1/2α accumulation by differentially regulating iO2¬, ATP levels and Akt/Erk/AMPK pathways. Inhibition of key metabolic pathways can modulate HIF regulatory pathways, metabolic responses and survival of cancer cells in hypoxia. Hypoxia leads to transcriptional activation, by HIF, of pyruvate dehydrogenase (PDH) kinase which phosphorylates and inhibits PDH, a mitochondrial enzyme that converts pyruvate into acetyl-CoA. The levels of PDH (total and phosphorylated), PDH kinase and HIF-1α were analysed in HCT116 and HCT116 SCO2-/- (deficient in complex IV of the respiratory chain) grown under 20.9 % and 3 % O2. Data indicate that regulation of PDH can occur in a manner independent of the HIF-1/PDH kinase 1 axis, mitochondrial respiration and the demand for acetyl-CoA. Collectively these results can be applied to many diseases; reduced nutrient supply and O2 during ischemia/stroke, hypoglycaemia in diabetes mellitus and cancer associated changes in uncoupling protein expression levels.