Browsing by Author "Green, Brian D."
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ItemAssessment and Validation of Globodera pallida as a Novel In Vivo Model for Studying Alzheimer’s Disease(MDPI, 2021-09-19) Althobaiti, Norah A.; Menaa, Farid; Albalawi, Aishah E.; Dalzell, Johnathan; Warnock, Neil; McCammick, Erin M.; Alsolais, Abdulellah; Alkhaibari, Abeer M.; Green, Brian D.Background: Whole transgenic or non-transgenic organism model systems allow the screening of pharmacological compounds for protective actions in Alzheimer’s disease (AD). Aim: In this study, a plant parasitic nematode, Globodera pallida, which assimilates intact peptides from the external environment, was investigated as a new potential non-transgenic model system of AD. Methods: Fresh second-stage juveniles of G. pallida were used to measure their chemosensory, perform immunocytochemistry on their neurological structures, evaluate their survival rate, measure reactive oxygen species, and determine total oxidized glutathione to reduced glutathione ratio (GSSG/GSH) levels, before and after treatment with 100 µM of various amyloid beta (Aβ) peptides (1–40, 1–42, 17–42, 17–40, 1–28, or 1–16). Wild-type N2 C. elegans (strain N2) was cultured on Nematode Growth Medium and directly used, as control, for chemosensory assays. Results: We demonstrated that: (i) G. pallida (unlike Caenorhabditis elegans) assimilates amyloid-β (Aβ) peptides which co-localise with its neurological structures; (ii) pre-treatment with various Aβ isoforms (1–40, 1–42, 17–42, 17–40, 1–28, or 1–16) impairs G. pallida’s chemotaxis to differing extents; (iii) Aβ peptides reduced survival, increased the production of ROS, and increased GSSG/GSH levels in this model; (iv) this unique model can distinguish differences between different treatment concentrations, durations, and modalities, displaying good sensitivity; (v) clinically approved neuroprotective agents were effective in protecting G. pallida from Aβ (1–42) exposure. Taken together, the data indicate that G. pallida is an interesting in vivo model with strong potential for discovery of novel bioactive compounds with anti-AD activity. ItemImpact of industrial production system parameters on chicken microbiomes: mechanisms to improve performance and reduce Campylobacter(BMC, 2020-09-09) McKenna, Aaron; Ijaz, Umer Zeeshan; Kelly, Carmel A.; Linton, W. Mark R.; Sloan, William T.; Green, Brian D.; Lavery, Ursula; Dorrell, Nick; Wren, Brendan W.; Richmond, Anne; Corcionivoschi, Nicolae; Gundogdu, OzanBackground The factors affecting host-pathogen ecology in terms of the microbiome remain poorly studied. Chickens are a key source of protein with gut health heavily dependent on the complex microbiome which has key roles in nutrient assimilation and vitamin and amino acid biosynthesis. The chicken gut microbiome may be influenced by extrinsic production system parameters such as Placement Birds/m2 (stocking density), feed type and additives. Such parameters, in addition to on-farm biosecurity may influence performance and also pathogenic bacterial numbers such as Campylobacter. In this study, three different production systems ‘Normal’ (N), ‘Higher Welfare’ (HW) and ‘Omega-3 Higher Welfare’ (O) were investigated in an industrial farm environment at day 7 and day 30 with a range of extrinsic parameters correlating performance with microbial dynamics and Campylobacter presence. Results Our data identified production system N as significantly dissimilar from production systems HW and O when comparing the prevalence of genera. An increase in Placement Birds/m2 density led to a decrease in environmental pressure influencing the microbial community structure. Prevalence of genera, such as Eisenbergiella within HW and O, and likewise Alistipes within N were representative. These genera have roles directly relating to energy metabolism, amino acid, nucleotide and short chain fatty acid (SCFA) utilisation. Thus, an association exists between consistent and differentiating parameters of the production systems that affect feed utilisation, leading to competitive exclusion of genera based on competition for nutrients and other factors. Campylobacter was identified within specific production system and presence was linked with the increased diversity and increased environmental pressure on microbial community structure. Addition of Omega-3 though did alter prevalence of specific genera, in our analysis did not differentiate itself from HW production system. However, Omega-3 was linked with a positive impact on weight gain. Conclusions Overall, our results show that microbial communities in different industrial production systems are deterministic in elucidating the underlying biological confounders, and these recommendations are transferable to farm practices and diet manipulation leading to improved performance and better intervention strategies against Campylobacter within the food chain.