School of Mathematics and Statistics - Research Publications

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Type: Journal Article × Author: Le Cao, Kim-Anh × Author: Ellul, Susan ×

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    Statistical challenges in longitudinal microbiome data analysis
    Kodikara, S ; Ellul, S ; Le Cao, K-A (OXFORD UNIV PRESS, 2022-07-18)
    The microbiome is a complex and dynamic community of microorganisms that co-exist interdependently within an ecosystem, and interact with its host or environment. Longitudinal studies can capture temporal variation within the microbiome to gain mechanistic insights into microbial systems; however, current statistical methods are limited due to the complex and inherent features of the data. We have identified three analytical objectives in longitudinal microbial studies: (1) differential abundance over time and between sample groups, demographic factors or clinical variables of interest; (2) clustering of microorganisms evolving concomitantly across time and (3) network modelling to identify temporal relationships between microorganisms. This review explores the strengths and limitations of current methods to fulfill these objectives, compares different methods in simulation and case studies for objectives (1) and (2), and highlights opportunities for further methodological developments. R tutorials are provided to reproduce the analyses conducted in this review.
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    An integrated metagenomics and metabolomics approach implicates the microbiota-gut-brain axis in the pathogenesis of Huntington's disease
    Kong, G ; Ellul, S ; Narayana, VK ; Kanojia, K ; Ha, HTT ; Li, S ; Renoir, T ; Kim-Anh, LC ; Hannan, AJ (ACADEMIC PRESS INC ELSEVIER SCIENCE, 2021-01)
    BACKGROUND: Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder with onset and severity of symptoms influenced by various environmental factors. Recent discoveries have highlighted the importance of the gastrointestinal microbiome in mediating the gut-brain-axis bidirectional communication via circulating factors. Using shotgun sequencing, we investigated the gut microbiome composition in the R6/1 transgenic mouse model of HD from 4 to 12 weeks of age (early adolescent through to adult stages). Targeted metabolomics was also performed on the blood plasma of these mice (n = 9 per group) at 12 weeks of age to investigate potential effects of gut dysbiosis on the plasma metabolome profile. RESULTS: Modelled time profiles of each species, KEGG Orthologs and bacterial genes, revealed heightened volatility in the R6/1 mice, indicating potential early effects of the HD mutation in the gut. In addition to gut dysbiosis in R6/1 mice at 12 weeks of age, gut microbiome function was perturbed. In particular, the butanoate metabolism pathway was elevated, suggesting increased production of the protective SCFA, butyrate, in the gut. No significant alterations were found in the plasma butyrate and propionate levels in the R6/1 mice at 12 weeks of age. The statistical integration of the metagenomics and metabolomics unraveled several Bacteroides species that were negatively correlated with ATP and pipecolic acid in the plasma. CONCLUSIONS: The present study revealed the instability of the HD gut microbiome during the pre-motor symptomatic stage of the disease which may have dire consequences on the host's health. Perturbation of the HD gut microbiome function prior to significant cognitive and motor dysfunction suggest the potential role of the gut in modulating the pathogenesis of HD, potentially via specific altered plasma metabolites which mediate gut-brain signaling.