Accommodating curvature in a highly ordered functionalized metal oxide nanofiber: synthesis, characterization and multi-scale modeling of layered nanosheets

A key element in the rational design of hybrid organic-inorganic nanostructures, is control of surfactant packing and adsorption onto the inorganic phase in crystal growth and assembly. In layered single crystal nanofibers and bilayered 2D nanosheets of vanadium oxide, we show how the chemisorption of preferred densities of surfactant molecules can direct formation of ordered, curved layers. The atom-scale features of the structures are described using molecular dynamics simulations that quantify surfactant packing effects and confirm the preference for a density of 5 dodecanethiol molecules per 8 vanadium attachment sites in the synthesised structures. This assembly maintains a remarkably well ordered interlayer spacing, even when curved. The assemblies of interdigitated organic bilayers on V2O5 are shown to be sufficiently flexible to tolerate curvature while maintaining a constant interlayer distance without rupture, delamination or cleavage. The accommodation of curvature and invariant structural integrity points to a beneficial role for oxide-directed organic film packing effects in layered architectures such as stacked nanofibers and hybrid 2D nanosheet systems.

Development of germanium/silicon integration for near infrared detection

Silicon (Si) is the base material for electronic technologies and is emerging as a very attractive platform for photonic integrated circuits (PICs). PICs allow optical systems to be made more compact with higher performance than discrete optical components. Applications for PICs are in the area of fibre-optic communication, biomedical devices, photovoltaics and imaging. Germanium (Ge), due to its suitable bandgap for telecommunications and its compatibility with Si technology is preferred over III-V compounds as an integrated on-chip detector at near infrared wavelengths. There are two main approaches for Ge/Si integration: through epitaxial growth and through direct wafer bonding. The lattice mismatch of ~4.2% between Ge and Si is the main problem of the former technique which leads to a high density of dislocations while the bond strength and conductivity of the interface are the main challenges of the latter. Both result in trap states which are expected to play a critical role. Understanding the physics of the interface is a key contribution of this thesis. This thesis investigates Ge/Si diodes using these two methods. The effects of interface traps on the static and dynamic performance of Ge/Si avalanche photodetectors have been modelled for the first time. The thesis outlines the original process development and characterization of mesa diodes which were fabricated by transferring a ~700 nm thick layer of p-type Ge onto n-type Si using direct wafer bonding and layer exfoliation. The effects of low temperature annealing on the device performance and on the conductivity of the interface have been investigated. It is shown that the diode ideality factor and the series resistance of the device are reduced after annealing. The carrier transport mechanism is shown to be dominated by generation–recombination before annealing and by direct tunnelling in forward bias and band-to-band tunnelling in reverse bias after annealing. The thesis presents a novel technique to realise photodetectors where one of the substrates is thinned by chemical mechanical polishing (CMP) after bonding the Si-Ge wafers. Based on this technique, Ge/Si detectors with remarkably high responsivities, in excess of 3.5 A/W at 1.55 μm at −2 V, under surface normal illumination have been measured. By performing electrical and optical measurements at various temperatures, the carrier transport through the hetero-interface is analysed by monitoring the Ge band bending from which a detailed band structure of the Ge/Si interface is proposed for the first time. The above unity responsivity of the detectors was explained by light induced potential barrier lowering at the interface. To our knowledge this is the first report of light-gated responsivity for vertically illuminated Ge/Si photodiodes. The wafer bonding approach followed by layer exfoliation or by CMP is a low temperature wafer scale process. In principle, the technique could be extended to other materials such as Ge on GaAs, or Ge on SOI. The unique results reported here are compatible with surface normal illumination and are capable of being integrated with CMOS electronics and readout units in the form of 2D arrays of detectors. One potential future application is a low-cost Si process-compatible near infrared camera.

The role of glucocorticoid-induced tumour necrosis factor receptor in developing mouse sympathetic neurons

Hereditary sensory autonomic neuropathy IV (HSAN IV) is an autosomal recessive disorder characterised by inability to feel pain and anhidrosis and is a consequence of defective NGF/TrkA signalling and growth of sensory and sympathetic neurons. Glucocortiocoid-induced tumour necrosis factors receptor (GITR), a transmembrane protein, activated by its specific ligand, GITRL, is well known for its role in the regulation of innate and acquired immune system responses. Recently, GITR was found to be required for NGF-dependant and extracellular signal-related kinase 1/2 (ERK1/2)-induced neurite growth and target innervation in the developing sympathetic nervous system (SNS). Given this novel role of GITR, it is possible that strategies targeting GITR have potential therapeutic benefit in promoting neurite growth in autonomic neuropathies such as HSAN IV. Using P1 mouse SCG neurons as a model, in addition to various SCG cell treatments, knock down models and transfection methods, we investigated whether GITR increases the sensitivity of sympathetic neurons to NGF; the region of GITR required for the enhancement of NGF-promoted growth, the signalling pathways downstream of GITR and how extensively GITR is involved in regulating peripheral innervation of the SNS. Results indicate that the region responsible for the growth promoting effects of GITR lies in its juxtamembrane intracellular region (here termed the growth promoting domain (GPD)) of GITR. The GPD of GITR activates ERK1/2 and inhibits nuclear factor kappa B (NF-κB) in an inverse fashion to provide an optimal cellular growth environment for P1 SCG neurons. While deleting the GPD of GITR had no effect on TrkA expression, constitutive phosphorylation of specific sites in the GPD reduced TrkA expression indicating a possible role for GITR in increasing the sensitivity of SCG neurons to NGF by the regulation of these sites, TrkA expression and subsequent NGF/TrkA binding. GITR appears to be heterogeneously required for NGF-promoted target innervation of SCG neurons in some organs, implying additional factors are involved in extensive NGF-target innervation of the SNS. In conclusion, this study answers basic biological questions regarding the molecular mechanism behind the role of GITR in the development of the SNS, and provides a basis for future research if GITR modulation is to be developed as a strategy for promoting axonal growth.

The role of the IL-1 type 1 receptor in the life, death and differentiation of adult hippocampal neural precursor cells

Neurogenesis occurs in two distinct regions of the adult brain; the subgranular zone (SGZ) of the dentate gyrus (DG) in the hippocampus, and the subventricular zone (SVZ) lining the lateral ventricles. It is now well-known that adult hippocampal neurogenesis can be modulated by a number of intrinsic and extrinsic factors e.g. local signalling molecules, exercise, environmental enrichment and learning. Moreover, levels of adult hippocampal neurogenesis decrease with age, at least in rodents, and alterations in hippocampal neurogenesis have been reported in animal models and human studies of neuropsychiatric and neurodegenerative conditions. Neuroinflammation is a common pathological feature of these conditions and is also a potent modulator of adult hippocampal neurogenesis. Recently, the orphan nuclear receptor TLX has been identified as an important regulator of adult hippocampal neurogenesis as its expression is necessary to maintain the neural precursor cell (NPC) pool in the adult DG. Likewise, exposure of animals to voluntary exercise has been consistently demonstrated to promote adult hippocampal neurogenesis. Lentivirus (LV)- mediated gene transfer is a useful tool to elucidate gene function and to explore potential therapeutic candidates across an array of conditions as it facilitates sustained gene expression in both dividing and post-mitotic cell populations. Both intrinsic and extrinsic factors are important regulators of adult hippocampal neurogenesis. Examining how these factors are affected by an inflammatory stimulus, and the subsequent effects on adult hippocampal neurogenesis provides important information for the development of novel treatment strategies for neuropsychiatric and neurodegenerative conditions in which adult hippocampal neurogenesis is impaired. The aims of the series of experiments presented in this thesis were to examine the effect of the pro-inflammatory cytokine interleukin-1β (IL-1β) on adult hippocampal NPCs both in vitro and in vivo. In vitro, we have shown that IL-1β reduces proliferation of adult hippocampal NPCs in a dose and time-dependent manner. In addition, we have demonstrated that TLX expression is reduced by IL-1β. Blockade of IL-1β signalling prevented both the IL-1β-induced reduction in cell proliferation and TLX expression. In vivo, we examined the effect of short term and long term exposure to LV-IL-1β in sedentary mice and in mice exposed to voluntary running. We demonstrated that impaired hippocampal neurogenesis is only evident after long term exposure to IL-1β. In mice exposed to voluntary running, hippocampal neurogenesis is significantly increased following short-term but not long-term exposure to running. Moreover, short-term running effectively prevents any IL-1β-induced effects on hippocampal neurogenesis; however, no such effects are seen following long-term exposure to running.

Secure architectures for pairing based public key cryptography

Along with the growing demand for cryptosystems in systems ranging from large servers to mobile devices, suitable cryptogrophic protocols for use under certain constraints are becoming more and more important. Constraints such as calculation time, area, efficiency and security, must be considered by the designer. Elliptic curves, since their introduction to public key cryptography in 1985 have challenged established public key and signature generation schemes such as RSA, offering more security per bit. Amongst Elliptic curve based systems, pairing based cryptographies are thoroughly researched and can be used in many public key protocols such as identity based schemes. For hardware implementions of pairing based protocols, all components which calculate operations over Elliptic curves can be considered. Designers of the pairing algorithms must choose calculation blocks and arrange the basic operations carefully so that the implementation can meet the constraints of time and hardware resource area. This thesis deals with different hardware architectures to accelerate the pairing based cryptosystems in the field of characteristic two. Using different top-level architectures the hardware efficiency of operations that run at different times is first considered in this thesis. Security is another important aspect of pairing based cryptography to be considered in practically Side Channel Analysis (SCA) attacks. The naively implemented hardware accelerators for pairing based cryptographies can be vulnerable when taking the physical analysis attacks into consideration. This thesis considered the weaknesses in pairing based public key cryptography and addresses the particular calculations in the systems that are insecure. In this case, countermeasures should be applied to protect the weak link of the implementation to improve and perfect the pairing based algorithms. Some important rules that the designers must obey to improve the security of the cryptosystems are proposed. According to these rules, three countermeasures that protect the pairing based cryptosystems against SCA attacks are applied. The implementations of the countermeasures are presented and their performances are investigated.

Digital signal processing and artificial intelligence for the automated classification of food allergy

As a by-product of the ‘information revolution’ which is currently unfolding, lifetimes of man (and indeed computer) hours are being allocated for the automated and intelligent interpretation of data. This is particularly true in medical and clinical settings, where research into machine-assisted diagnosis of physiological conditions gains momentum daily. Of the conditions which have been addressed, however, automated classification of allergy has not been investigated, even though the numbers of allergic persons are rising, and undiagnosed allergies are most likely to elicit fatal consequences. On the basis of the observations of allergists who conduct oral food challenges (OFCs), activity-based analyses of allergy tests were performed. Algorithms were investigated and validated by a pilot study which verified that accelerometer-based inquiry of human movements is particularly well-suited for objective appraisal of activity. However, when these analyses were applied to OFCs, accelerometer-based investigations were found to provide very poor separation between allergic and non-allergic persons, and it was concluded that the avenues explored in this thesis are inadequate for the classification of allergy. Heart rate variability (HRV) analysis is known to provide very significant diagnostic information for many conditions. Owing to this, electrocardiograms (ECGs) were recorded during OFCs for the purpose of assessing the effect that allergy induces on HRV features. It was found that with appropriate analysis, excellent separation between allergic and nonallergic subjects can be obtained. These results were, however, obtained with manual QRS annotations, and these are not a viable methodology for real-time diagnostic applications. Even so, this was the first work which has categorically correlated changes in HRV features to the onset of allergic events, and manual annotations yield undeniable affirmation of this. Fostered by the successful results which were obtained with manual classifications, automatic QRS detection algorithms were investigated to facilitate the fully automated classification of allergy. The results which were obtained by this process are very promising. Most importantly, the work that is presented in this thesis did not obtain any false positive classifications. This is a most desirable result for OFC classification, as it allows complete confidence to be attributed to classifications of allergy. Furthermore, these results could be particularly advantageous in clinical settings, as machine-based classification can detect the onset of allergy which can allow for early termination of OFCs. Consequently, machine-based monitoring of OFCs has in this work been shown to possess the capacity to significantly and safely advance the current state of clinical art of allergy diagnosis

Reactivity of sub 1 nm supported clusters: (TiO2)(n) clusters supported on rutile TiO2 (110)

Metal oxide clusters of sub-nm dimensions dispersed on a metal oxide support are an important class of catalytic materials for a number of key chemical reactions, showing enhanced reactivity over the corresponding bulk oxide. In this paper we present the results of a density functional theory study of small sub-nm TiO2 clusters, Ti2O4, Ti3O6 and Ti4O8 supported on the rutile (110) surface. We find that all three clusters adsorb strongly with adsorption energies ranging from -3 eV to -4.5 eV. The more stable adsorption structures show a larger number of new Ti-O bonds formed between the cluster and the surface. These new bonds increase the coordination of cluster Ti and O as well as surface oxygen, so that each has more neighbours. The electronic structure shows that the top of the valence band is made up of cluster derived states, while the conduction band is made up of Ti 3d states from the surface, resulting in a reduction of the effective band gap and spatial separation of electrons and holes after photon absorption, which shows their potential utility in photocatalysis. To examine reactivity, we study the formation of oxygen vacancies in the cluster-support system. The most stable oxygen vacancy sites on the cluster show formation energies that are significantly lower than in bulk TiO2, demonstrating the usefulness of this composite system for redox catalysis.

Artefact detection and removal algorithms for EEG diagnostic systems

The electroencephalogram (EEG) is a medical technology that is used in the monitoring of the brain and in the diagnosis of many neurological illnesses. Although coarse in its precision, the EEG is a non-invasive tool that requires minimal set-up times, and is suitably unobtrusive and mobile to allow continuous monitoring of the patient, either in clinical or domestic environments. Consequently, the EEG is the current tool-of-choice with which to continuously monitor the brain where temporal resolution, ease-of- use and mobility are important. Traditionally, EEG data are examined by a trained clinician who identifies neurological events of interest. However, recent advances in signal processing and machine learning techniques have allowed the automated detection of neurological events for many medical applications. In doing so, the burden of work on the clinician has been significantly reduced, improving the response time to illness, and allowing the relevant medical treatment to be administered within minutes rather than hours. However, as typical EEG signals are of the order of microvolts (μV ), contamination by signals arising from sources other than the brain is frequent. These extra-cerebral sources, known as artefacts, can significantly distort the EEG signal, making its interpretation difficult, and can dramatically disimprove automatic neurological event detection classification performance. This thesis therefore, contributes to the further improvement of auto- mated neurological event detection systems, by identifying some of the major obstacles in deploying these EEG systems in ambulatory and clinical environments so that the EEG technologies can emerge from the laboratory towards real-world settings, where they can have a real-impact on the lives of patients. In this context, the thesis tackles three major problems in EEG monitoring, namely: (i) the problem of head-movement artefacts in ambulatory EEG, (ii) the high numbers of false detections in state-of-the-art, automated, epileptiform activity detection systems and (iii) false detections in state-of-the-art, automated neonatal seizure detection systems. To accomplish this, the thesis employs a wide range of statistical, signal processing and machine learning techniques drawn from mathematics, engineering and computer science. The first body of work outlined in this thesis proposes a system to automatically detect head-movement artefacts in ambulatory EEG and utilises supervised machine learning classifiers to do so. The resulting head-movement artefact detection system is the first of its kind and offers accurate detection of head-movement artefacts in ambulatory EEG. Subsequently, addtional physiological signals, in the form of gyroscopes, are used to detect head-movements and in doing so, bring additional information to the head- movement artefact detection task. A framework for combining EEG and gyroscope signals is then developed, offering improved head-movement arte- fact detection. The artefact detection methods developed for ambulatory EEG are subsequently adapted for use in an automated epileptiform activity detection system. Information from support vector machines classifiers used to detect epileptiform activity is fused with information from artefact-specific detection classifiers in order to significantly reduce the number of false detections in the epileptiform activity detection system. By this means, epileptiform activity detection which compares favourably with other state-of-the-art systems is achieved. Finally, the problem of false detections in automated neonatal seizure detection is approached in an alternative manner; blind source separation techniques, complimented with information from additional physiological signals are used to remove respiration artefact from the EEG. In utilising these methods, some encouraging advances have been made in detecting and removing respiration artefacts from the neonatal EEG, and in doing so, the performance of the underlying diagnostic technology is improved, bringing its deployment in the real-world, clinical domain one step closer.

Characterisation of the microbiota of traditional fermented beverages and screening these and other populations for novel antimicrobial producers and gene clusters

To screen for novel ribosomally synthesised antimicrobials, in-silico genome mining was performed on all publically available fully sequenced bacterial genomes. 49 novel type 1 lantibiotic clusters were identified from a number of species, genera and phyla not usually associated with lantibiotic production, and indicates high prevalence. A crucial step towards the commercialisation of fermented beverages is the characterisation of the microbial content. To achieve this goal, we applied next-generation sequencing techniques to analyse the bacterial and yeast populations of the organic, symbiotically-fermented beverages kefir, water kefir and kombucha. A number of minor components were revealed, many of which had not previously been associated with these beverages. The dominant microorganism in each of the water kefir grains and fermentates was Zymomonas, an ethanol-producing bacterium that had not previously been detected on such a scale. These studies represent the most accurate description of these populations to date, and should aid in future starter design and in determining which species are responsible for specific attributes of the beverages. Finally, high-throughput robotics was applied to screen for the presence of antimicrobial producers associated with these beverages. This revealed a low frequency of bacteriocin production amongst the bacterial isolates, with only lactococcins A, B and LcnN of lactococcin M being identified. However, a proteinaceous antimicrobial produced by the yeast Dekkera bruxellensis, isolated from kombucha, was found to be active against Lactobacillus bulgaricus. This peptide was patially purified.

A study of diet and health in the elderly; the gut microbiota as a source of bioactive agents

The global proportion of older persons is increasing rapidly. Diet and the intestinal microbiota independently and jointly contribute to health in the elderly. The habitual dietary patterns and functional microbiota components of elderly subjects were investigated in order to identify specific effector mechanisms. A study of the dietary intake of Irish community-dwelling elderly subjects showed that the consumption of foods high in fat and/or sugar was excessive, while consumption of dairy foods was inadequate. Elderly females typically had a more nutrient- dense diet than males and a considerable proportion of subjects, particularly males, had inadequate intakes of calcium, magnesium, vitamin D, folate, zinc and vitamin C. The association between dietary patterns, glycaemic index and cognitive function was also investigated. Elderly subjects consuming ‘prudent’ dietary patterns had better cognitive function compared to those consuming ‘Western’ dietary patterns. Furthermore, fully-adjusted regression models revealed that a high glycaemic diet was associated with poor cognitive function, demonstrating a new link between nutrition and cognition. An extensive screening study of the elderly faecal-derived microbiota was also undertaken to examine the prevalence of antimicrobial production by intestinal bacteria. A number of previously characterised bacteriocins were isolated (gassericin T, ABP-118, mutacin II, enterocin L-50 and enterocin P) in this study. Interestingly, a Lactobacillus crispatus strain was found to produce a potentially novel antimicrobial compound. Full genome sequencing of this strain revealed the presence of three loci which exhibited varying degrees of homology with the genes responsible for helveticin J production in Lb. helveticus. An additional study comparing the immunomodulatory capacity of ‘viable’ and ‘non-viable’ Bifidobacterium strains found that Bifidobacterium-fermented milks (BFMs) containing ‘non-viable’ cells could stimulate levels of IL-10 and TNF-α in a manner similar to those stimulated by BFMs containing ‘viable’ cells in vitro.

Multi-scale modelling of atomic layer deposition

High-permittivity ("high-k") dielectric materials are used in the transistor gate stack in integrated circuits. As the thickness of silicon oxide dielectric reduces below 2 nm with continued downscaling, the leakage current because of tunnelling increases, leading to high power consumption and reduced device reliability. Hence, research concentrates on finding materials with high dielectric constant that can be easily integrated into a manufacturing process and show the desired properties as a thin film. Atomic layer deposition (ALD) is used practically to deposit high-k materials like HfO2, ZrO2, and Al2O3 as gate oxides. ALD is a technique for producing conformal layers of material with nanometer-scale thickness, used commercially in non-planar electronics and increasingly in other areas of science and technology. ALD is a type of chemical vapor deposition that depends on self-limiting surface chemistry. In ALD, gaseous precursors are allowed individually into the reactor chamber in alternating pulses. Between each pulse, inert gas is admitted to prevent gas phase reactions. This thesis provides a profound understanding of the ALD of oxides such as HfO2, showing how the chemistry affects the properties of the deposited film. Using multi-scale modelling of ALD, the kinetics of reactions at the growing surface is connected to experimental data. In this thesis, we use density functional theory (DFT) method to simulate more realistic models for the growth of HfO2 from Hf(N(CH3)2)4/H2O and HfCl4/H2O and for Al2O3 from Al(CH3)3/H2O.Three major breakthroughs are discovered. First, a new reaction pathway, ’multiple proton diffusion’, is proposed for the growth of HfO2 from Hf(N(CH3)2)4/H2O.1 As a second major breakthrough, a ’cooperative’ action between adsorbed precursors is shown to play an important role in ALD. By this we mean that previously-inert fragments can become reactive once sufficient molecules adsorb in their neighbourhood during either precursor pulse. As a third breakthrough, the ALD of HfO2 from Hf(N(CH3)2)4 and H2O is implemented for the first time into 3D on-lattice kinetic Monte-Carlo (KMC).2 In this integrated approach (DFT+KMC), retaining the accuracy of the atomistic model in the higher-scale model leads to remarkable breakthroughs in our understanding. The resulting atomistic model allows direct comparison with experimental techniques such as X-ray photoelectron spectroscopy and quartz crystal microbalance.

Identification and characterization of innate immune receptor substrates of γ-secretase enzyme complex

The γ-secretase protease complexes and associated regulated intramembrane proteolysis play an important role in controlling receptor-mediated intracellular signalling events, which have a central role in Alzheimer’s disease, cancer progression and immune surveillance. It has previously been reported that the Interleukin-1 receptor, type 1, (IL-1R1) is a substrate for regulated intramembrane proteolysis, mediated by presenilin (PS)-dependent γ-secretase activity. The aims of this project were twofold. Firstly, to determine the conservation of regulated intramembrane proteolysis as a physiological occurrence amongst other cytokine receptors. In this regard, similar to IL-1R1, we identified the Tumour necrosis factor receptor type 1 (TNFR1) and the Toll like receptor 4 (TLR4) as novel γ-secretase substrates. Secondly, given that the diversity of signalling events mediated by the IL-1R1, TLR4 and TNFR1 are spatially segregated, we investigated the spatial distribution, subcellular trafficking and subcellular occurrence of regulated intramembrane proteolysis of IL-1R1, TLR4 and TNFR1. Using dynasore an inhibitor of clathrin-dependent receptor endocytosis, both ectodomain shedding and γ-secretase-mediated cleavage of IL-1R1 were observed post-internalization. In contrast, TNFR-1 underwent ectodomain shedding at the cell surface followed by endosomal γ-secretase-mediated cleavage. Furthermore, immortalised fibroblasts from PS1-deficient mice showed impaired γ-secretasemediated cleavage of IL-1R1 and TNFR1, indicating that both are cleaved by PS1-and not PS2-containing γ-secretase complexes. Subcellular fractionation and immunofluorescence studies revealed that the γ-secretase generated IL-1R1 ICD translocates to the nucleus on IL-1β stimulation. These observations further demonstrate the novel PS-dependent means of modulating IL-1β, LPS and TNFα- mediated immune responses by regulating IL-1R1/TLR4/TNFR1 protein levels within the cells.

Cryptographic coprocessors for embedded systems

In the field of embedded systems design, coprocessors play an important role as a component to increase performance. Many embedded systems are built around a small General Purpose Processor (GPP). If the GPP cannot meet the performance requirements for a certain operation, a coprocessor can be included in the design. The GPP can then offload the computationally intensive operation to the coprocessor; thus increasing the performance of the overall system. A common application of coprocessors is the acceleration of cryptographic algorithms. The work presented in this thesis discusses coprocessor architectures for various cryptographic algorithms that are found in many cryptographic protocols. Their performance is then analysed on a Field Programmable Gate Array (FPGA) platform. Firstly, the acceleration of Elliptic Curve Cryptography (ECC) algorithms is investigated through the use of instruction set extension of a GPP. The performance of these algorithms in a full hardware implementation is then investigated, and an architecture for the acceleration the ECC based digital signature algorithm is developed. Hash functions are also an important component of a cryptographic system. The FPGA implementation of recent hash function designs from the SHA-3 competition are discussed and a fair comparison methodology for hash functions presented. Many cryptographic protocols involve the generation of random data, for keys or nonces. This requires a True Random Number Generator (TRNG) to be present in the system. Various TRNG designs are discussed and a secure implementation, including post-processing and failure detection, is introduced. Finally, a coprocessor for the acceleration of operations at the protocol level will be discussed, where, a novel aspect of the design is the secure method in which private-key data is handled

Towards a cognitive neurobiology of brain-gut axis disorders

The past two decades have seen substantial gains in our understanding of the complex processes underlying disturbed brain-gut communication in disorders such as irritable bowel syndrome (IBS) and inflammatory bowel disease (IBD). Despite a growing understanding of the neurobiology of brain-gut axis dysfunction, there is a relative paucity of investigations into how the various factors involved in dysregulating the brain-gut axis, including stress, immune activation and pain, could impact on fundamental brain processes such as cognitive performance. To this end, we proposed a cognitive neurobiology of brain-gut axis dysfunction and took a novel approach to examine how disturbed brain-gut interactions may manifest as altered cognitive performance in IBS and IBD, both cross-sectionally and prospectively. We have demonstrated that, disorders of the brain-gut axis are characterised by stable deficits in specific cognitive domains. Specifically, patients with IBS exhibit a consistent hippocampal mediated visuospatial memory impairment. In addition we have found evidence to suggest a similar visuospatial impairment in IBD. However, our most consistent finding within this population was that patients with Crohn’s disease exhibit impaired selective attention/ response inhibition on the classic Stroop interference test. These cognitive deficits may serve to perpetuate and sustain brain-gut axis dysfunction. Furthermore, this research has shed light on some of the underlying neurobiological mechanisms that may be mediating cognitive dysfunction in IBS. Our findings may have significant implications for the individual who suffers from a brain-gut axis disorder and may also inform future treatment strategies. Taken together, these findings can be incorporated into existing neurobiological models of brain-gut axis dysfunction, to develop a more comprehensive model accounting for the cognitive-neurobiology of brain-gut axis disorders. This has furthered our understanding of disease pathophysiology and may ultimately aid in both the diagnosis and treatment of these highly prevalent, but poorly understood disorders.

Functional metagenomic analysis of the human gut microbiome to identify novel salt tolerance genes

The ability to adapt to and respond to increases in external osmolarity is an important characteristic that enables bacteria to survive and proliferate in different environmental niches. When challenged with increased osmolarity, due to sodium chloride (NaCl) for example, bacteria elicit a phased response; firstly via uptake of potassium (K+), which is known as the primary response. This primary response is followed by the secondary response which is characterised by the synthesis or uptake of compatible solutes (osmoprotectants). The overall osmotic stress response is much broader however, involving many diverse cellular systems and processes. These ancillary mechanisms are arguably more interesting and give a more complete view of the osmotic stress response. The aim of this thesis was to identify novel genetic loci from the human gut microbiota that confer increased tolerance to osmotic stress using a functional metagenomic approach. Functional metagenomics is a powerful tool that enables the identification of novel genes from as yet uncultured bacteria from diverse environments through cloning, heterologous expression and phenotypic identification of a desired trait. Functional metagenomics does not rely on any previous sequence information to known genes and can therefore enable the discovery of completely novel genes and assign functions to new or known genes. Using a functional metagenomic approach, we have assigned a novel function to previously annotated genes; murB, mazG and galE, as well as a putative brp/blh family beta-carotene 15,15’-monooxygenase. Finally, we report the identification of a completely novel salt tolerance determinant with no current known homologues in the databases. Overall the genes identified originate from diverse taxonomic and phylogenetic groups commonly found in the human gastrointestinal (GI) tract, such as Collinsella and Eggerthella, Akkermansia and Bacteroides from the phyla Actinobacteria, Verrucomicrobia and Bacteroidetes, respectively. In addition, a number of the genes appear to have been acquired via lateral gene transfer and/or encoded on a prophage. To our knowledge, this thesis represents the first investigation to identify novel genes from the human gut microbiota involved in the bacterial osmotic stress response.