Research Theses Submission

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    Characterising the techno- and bio-functional properties of milk protein-polyphenol complexes for application in performance nutrition
    (University College Cork, 2023) van de Langerijt, Tessa M.; Crowley, Shane; O'Mahony, Seamus Anthony; Food Institutional Research Measure
    There is increased consumer interest in performance nutrition, focusing especially on enhancing muscle strength and recovery. Dairy-plant hybrid beverages, rich in milk proteins and polyphenols, have considerable potential in this area, because both proteins and polyphenols have been positively linked to muscle strength and recovery. However, there is limited knowledge of the effects of protein-polyphenol interactions on the techno- and bio-functional properties (e.g., physical stability of casein micelles, heat stability, bioaccessibility and bioavailability) of liquid dairy systems. In these studies, the addition of polyphenols to systems containing casein micelles increased the attractive forces within the casein micelles, due to complex formation, preventing casein micelle dissociation. When milk protein systems contained blackberry polyphenols, their heat stability increased in the pH range 6.2-6.4. In this pH range, blackberry polyphenols bound calcium, which prevented protein aggregation and increased heat stability. Co-concentration of milk proteins and polyphenols was achieved by ultrafiltration, enabled by milk protein-polyphenol complex formation, allowing the complexes to be retained. Milk fat in mixed milk protein-blackberry systems positively influenced the bioaccessibility of polyphenols but had a negative effect on their bioavailability after in vitro digestion. Increasing the leucine content in these systems did not impact the bioaccessibility or bioavailability of polyphenols. In contrast, proteins increased the bioaccessibility of polyphenols and reduced the hydrolysis of polyphenols during in vitro digestion, which resulted in an increased polyphenol bioavailability. In conclusion, protein-polyphenol complexes showed considerable promise for preventing casein micelle dissociation, improving heat stability, facilitating co-concentration by ultrafiltration and improving the bioaccessibility and bioavailability of blackberry polyphenols. This new knowledge may help support the successful development of protein-polyphenol rich beverages for performance nutrition.
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    Development and evaluation of tools and methodologies for estimating behaviour and predicting training outcome of working dogs
    (University College Cork, 2023) Marcato, Marinara; Galvin, Paul; O'Flynn, Brendan; O'Mahony, Conor; Tedesco, Salvatore; INTERREG Programme (CALIN project); Science Foundation Ireland; Department of Agriculture, Food and the Marine, Ireland; European Regional Development Fund
    Background: The average training success rate in different dog industries is as low as 50% and the cost of training a guide dog is as high as 53,00 in Ireland. The key to reducing costs is in the assessment of trainee dogs for identifying likely to fail at an early stage. Objectives: This thesis aims to improve behavioural assessment methods by including machine learning methods to (1) predict future outcomes in trainee assistance dogs based on ratings and test batteries, and (2) estimate canine posture based on a recognition system specifically designed for working dogs. Methods: (1) Two standardised ratings were used, in particular, the Canine Behavioral Assessment and Research Questionnaire (C-BARQ) was completed by puppy raisers and the Monash Canine Personality Questionnaire - Revised (MCPQ-R) was answered by dog trainers. Rating data were independently analysed to investigate their relationship with training outcomes. The novel Assistance Dog Test Battery (ADTB) was designed to assess the suitability of trainee assistance dogs for assistance work during training. The test was conducted at 3 weeks - Data Collection 1 (DC1) - and 10 weeks - Data Collection 2 (DC2) - after the start of formal training to investigate the optimal timing to predict working outcomes. (2) Three Inertial Measurement Units (IMUs) were placed on the dogs in different positions (neck, back and chest) and five postures (walking, standing, sitting, lying down and body shake) were annotated. Advanced machine learning techniques were applied for the first time in this field to improve state-of-the-art posture prediction performance. Results: (1) The machine learning models achieved an area under the ROC of 0.84 and 0.85 when using the ratings C-BARQ and MCPQ-R to predict training outcome; and 0.74 and 0.84 when using the DC1 and DC2 of the ADTB to predict working outcomes, respectively. (2) The optimal canine posture classifier achieved an f1-weighted of 0.90. Conclusions: (1) These novel machine learning models provided the most effective early prediction of suitability for assistance work. The MCPQ-R and ADTB were demonstrated for the first time to be a reliable canine behavioural assessment method for estimating future outcomes in trainee dogs. (2) Comparison with previous work reveals a superior performance of the new canine posture estimation system for working
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    The emission and atmospheric oxidation of biogenic volatile organic compounds from Sitka spruce
    (University College Cork, 2023) Furnell, Hayley; Wenger, John; Hellebust, Stig; Irish Research Council; Environmental Protection Agency
    Biogenic volatile organic compounds (BVOCs) emitted by plants undergo chemical reactions in the atmosphere resulting in the formation of oxidised products and secondary organic aerosols (SOA), which have a large impact on climate. In this work an on-line time-of-flight chemical ionisation mass spectrometer (ToF-CIMS) was used in laboratory studies to identify the main BVOCs emitted from the main plantation tree species in Ireland, Picea Sitchensis (Sitka spruce). Experiments have also been conducted to assess the atmospheric oxidation pathways of the BVOCs emitted by Sitka spruce and their SOA formation potential. The ToF-CIMS was used in combination with off-line gas chromatography-mass spectrometry to identify the BVOC emissions from three Sitka spruce trees maintained in a plant growth chamber under conditions relevant to the Irish climate. Fifty-two of the seventy-four BVOCs emitted from Sitka spruce were oxygenated compounds, with piperitone (C10H16O), an oxygenated monoterpene, being the dominant emission. Other prevalent emissions included isoprene and five monoterpenes (myrcene, β-phellandrene, δ-limonene, α-pinene, and camphene). Temperature, light intensity and stress were all found to alter the emission profiles, with different BVOCs exhibiting different responses. At the current conditions of the Irish climate the annual BVOC flux for isoprene was found to exceed that for piperitone, although this is expected to change in a warming climate. A series of simulation chamber experiments was performed to determine, for the first time, the kinetics, products and mechanisms for the gas-phase reaction of piperitone with the main atmospheric oxidant the hydroxyl radical (OH•). The rate coefficient was determined by the relative rate method and used to calculate an atmospheric lifetime of under 2 hours. Calculations based on structure activity relationships identified the reaction with OH• as the dominant loss pathway for piperitone and was used to identify its most reactive sites. The ToF-CIMS detected thirty-three gas-phase oxidation products, and formation mechanisms for seventeen of the products have been proposed. The results from these experiments provide new and useful information on the atmospheric fate of piperitone. Oxidation experiments were also conducted with OH• on all the BVOCs emitted by a Sitka spruce tree, to identify oxidation products, reaction pathways and determine the SOA formation potential of whole Sitka spruce BVOC emissions. Eight gas-phase BVOCs were identified as key reactive emissions, and upon reaction with OH• led to the formation of twenty-five gas-phase products and ninety-nine particle-phase products. Eight of these products were identified as originating from the oxidation of piperitone, myrcene and isoprene across the gas-phase and particle-phase, with the majority of the remining products resulting from oligomerisation reactions. Rapid SOA formation was observed soon after the onset of oxidation, likely due to the formation of low volatility oxidation products which caused new particle formation. SOA yields were estimated to be around 15%. Overall, this work has produced a wealth of new information on the emission and atmospheric oxidation of BVOCs emitted from Sitka spruce, which will be valuable to decision makers in the forestry sector. Moreover, the research highlights the importance of assessing BVOC emissions and the associated SOA formation potential prior to establishing tree plantations.
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    PiRAMiD: predicting early onset autism through maternal immune activation and proteomic discovery
    (University College Cork, 2023) Carter, Michael; Murray, Deirdre M.; Gibson, Louise; O'Keeffe, Gerard W.; English, Jane; National Children's Research Centre
    Autism spectrum disorder (ASD) is a heterogeneous developmental disorder arising early in life. ASD is composed of a wide variety of clinical characteristics, neuropsychological impairments and complex phenotypes. The classical triad of ASD symptoms includes disrupted social function, atypical verbal and non-verbal communication skills, and restricted interests with repetitive behaviours. These core symptoms often coexist with other psychiatric and neurological comorbidities. Attention Deficit Hyperactivity Disorder (ADHD), epilepsy, migraine, and anxiety are much commoner in children with ASD. Children and adults with ASD often encounter difficulties with emotional and behavioural problems (EBPs) such as emotional reactivity, aggression, and depression. Up to 50% of those affected can have intellectual disability (ID) and limited verbal communication. Social, emotional and behavioural deficits in children with ASD are also important modifiers of outcome and are linked to elevated stress, mental and physical health problems, and lower overall family and caregiver well-being. We know that early intervention can be effective, and may be parent or therapist delivered. Pharmacological treatment of ASD can be successful insofar as it is useful for symptomatic management of some ASD comorbidities such as ADHD, and depression. Although genetic susceptibilities are increasingly recognised, the mechanism of disease development in ASD remains unknown. We are aware of both common and rare genetic risk factors with more than four hundred diverse high confidence genes now linked to ASD ( Singly, these genetic factors each convey only a modest increase in ASD risk (~1%), however collectively they can contribute to a far greater risk. Both de novo and inherited genetic defects are recognised but ASD risk in progeny does not follow a clear pattern of inheritance. Estimates of heritability of ASD in twin pairs vary widely between 50 – 90%. The apparent male preponderance in ASD persists with a clear bias towards males. Rates of ASD among males exceed those of females by three or fourfold hinting at a possible sex differential genetic foundation. Up to 20% of individuals with ASD may possess copy number variants (CNV) and de novo loss of function single nucleotide variants (SNV) that are individually rare but in combination, increase an individual’s overall ASD risk. While newer methods of genetic analysis (such as whole genome sequencing) are uncovering new candidate genes with regularity, the heterogeneity of the clinical and phenotypic groups within ASD strongly suggest that in those with a genetic predisposition, environmental factors may act in concert to bring about a multisystem dysfunction leading to ASD. Despite recent advances in gene analysis, we are yet to discover a single gene determinant that can account for more than a small percent of ASD cases. The current ASD literature suggests that mutations occurring in genes involved in synapse formation, cell adhesion molecule production (Cadherin), scaffolding proteins (SHANK proteins), ion channels (sodium, calcium, and potassium channels), and signaling molecules can disrupt regulatory or coding regions and affect synapse formation, plasticity and synaptic transmission. All this suggests that we cannot explain many cases of ASD by genetic factors alone, or at least we cannot explain them using our current understanding of ASD genetics or our current techniques of genetic analysis. The flawed picture of ASD genetics has led some to investigate the role of environmental exposures in the aetiology of ASD. Researchers have identified many environmental risks in ASD. Advanced parental age, foetal environmental exposures, perinatal and obstetric events, maternal medication use, smoking and alcohol use, psychosocial hardship, nutrition and toxic exposures have all been implicated as risks in the pathogenesis of ASD. While authors attribute between 17 - 41% of ASD risk to non-genetic or environmental exposures, the exact balance between genetic and environmental determinants and their roles in aetiology remains disputed. Multiple mechanisms have been proposed through which each of these exposures may exert an influence on genetic and epigenetic risk in ASD , but there are only a handful that are likely to effect abnormal neurodevelopment. Animal models of inflammation and maternal immune activation are particularly well characterised, and have successfully modelled ASD type behaviours and social difficulties in mice, rats and non-human primates. Maternal immune activation (MIA) is defined as an increase in measured levels of inflammatory markers in mothers during pregnancy. Through this process, a cytokine cascade transmits to the foetus, resulting in adverse neurodevelopmental phenotypes and even remodelling of the immature foetal brain. Many studies have profiled cytokine, chemokine, immune cell and inflammatory signatures in ASD affected individuals. Only a much smaller number have characterised cytokine profiles in expectant mothers who progressed to birth children who develop ASD. The few previous studies, which have examined gestational serum, have indicated mid-gestational upregulation in specific pro-inflammatory cytokines or indeed down-regulation in anti-inflammatory cytokines. Metabolomic analysis refers to the systematic identification and quantitation of all metabolites in a given biological sample. This collection of metabolites, known as the metabolome, is thought to directly reflect the biochemical activity of the studied system at a specific point in time. The metabolome has become an area of interest, as some inborn errors of metabolism (IEM) are clearly linked to ASD phenotypes. Phenylketonuria (PKU) and Smith-Lemli-Opitz syndrome (SLOS) are disorders of amino acid and cholesterol metabolism respectively. Untreated PKU is associated with strongly autistic phenotypes, while SLOS is phenotypically heterogeneous, but autism remains a common feature in these children. Similarly, proteomics is defined as the study of the complete protein profile in a given tissue, cell or biological sample. Proteomic studies of human sera have so far noted altered levels of proteins involved in inflammation or immune system regulation, including acute phase reactants and interleukins. Abnormalities of the complement system have also been found in ASD and other psychopathologies such as schizophrenia. Recent works demonstrate that the complement pathway can affect synaptic remodelling and has roles in neurodevelopmental processes. The initial focus of ASD research on genomics has largely failed to result in the much-hoped-for silver bullet of ASD aetiology, i.e. a common genetic cause. Instead, the genetic landscape has proven to be exceedingly complex and interdependent on a multitude of factors, including environmental exposures and other modifiers of genetic risk. Research examining the aetiology of ASD has shifted focus from genetics to a multimodal approach. In recent years, funding has become available for a far wider variety of ASD aligned research topics, beyond those with a focus on genetics. Opportunities now exist to adopt a multifaceted approach to ASD aetiology, shifting the focus from a narrow genetic base, to a broader multimodal approach to examine other potential mechanistic players. While this adds further complexity to what is already a complicated picture, the strived for parsimonious answer is simply never likely to materialise. Newer fields and modalities such as proteomics, metabolomics and machine learning will help to further refine and untangle the complicated web of ASD, and this variety of granular detail is what is likely to result in a practicable biomarker or effective therapy in the future. In this thesis using a multimodal approach (ELISA, metabolome and proteome analysis) we aim to explore further the role of MIA and alterations of the proteome and metabolome in the pathophysiology of ASD. We hope that our findings may ultimately help to identify a potential gestational biomarker of ASD, which will improve access to early diagnosis and treatment. We also aim to characterise co-morbid emotional and behavioural problems, which arise early in children with ASD and are pervasive throughout all spheres of life. Early recognition and intervention with these co-morbidities can improve treatment outcomes, patient, and family wellbeing.
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    The gut microbiome of the wild great tit (Parus major): drivers and fitness consequences
    (University College Cork, 2023) Somers, Shane Edmond; Quinn, John; Ross, R. Paul; Stanton, Catherine; Irish Research Council for Science, Engineering and Technology; European Research Council; Science Foundation Ireland
    The gut microbiome plays a vital role in its host’s ecology. Clinical studies have shown gut microbes increase host health and fitness by providing digestive and immune functions, as well as aiding development. Natural variation in the microbiome is widely believed to affect host fitness in the wild but we are lacking experimental studies to test this. The microbiome varies with both host and environmental factors but most studies to date have focussed on individual factors and not adequately addressed the multiple overlapping and hierarchical drivers of microbiome variation working at environmental, host and microbial scales. This thesis investigates the role of the gut microbiota in host fitness, and how this is affected by and varies across contexts. Additionally, we address sources of variation in the gut microbiota at a host and environmental level, accounting for host ecology and drivers at different scales. We find that the host’s weight is correlated with microbiome diversity during development but that the direction of this relationship is context dependent. This shows that the microbiome interacts with the environment to determine host fitness and is important because it helps explain the contradictory findings linking diversity to weight. We also show that the interaction between the host, its microbiome and environment change with developmental stage. Specifically, we found that the microbiome of developed individuals is remarkably resilient to environmental perturbation, while developing individuals are much more sensitive, with important implications for future experiments. We developed a novel method for experimentally perturbing the microbiome that will allow microbiome researchers to begin testing hypotheses linking the microbiome to host ecology and evolution in natural settings. Finally, we show that welfare measures, such as environmental enrichment may interact with the gut microbiota to impact on host health and behaviour. In summary, I show that variation in the microbiome is linked to host ecology and that this variation is linked to host fitness.