Master Degree / Yüksek Lisans Tezleri
Permanent URI for this collectionhttps://hdl.handle.net/11147/3008
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Master Thesis Bioinformatic Analysis and Biostatistical Modelling of Genetic Interactions Between Microbiota and Host(01. Izmir Institute of Technology, 2020) Musa, Farid; Sezgin, EfeAdvances in genome sequencing technology have revolutionized the study of microorganisms. Recent genome-wide association studies (GWAS) on gut microbiota revealed fascinating discoveries about the effect of microbiota on our health. In this thesis, Drosophila Melanogaster samples were used to investigate the associations between the host's genotype and microbiota. The meta-analysis of microbiota data was performed using PhyloMAF, a novel, and comprehensive microbiome meta-analysis framework. The resulting microbial abundance tables were analyzed using alpha and phylogenetic beta bio-diversity metrics, which were used in the microbiome GWAS study. Significant variant associations were further analyzed in the post-GWAS analysis. The results of our study show that several genomic variants are significantly associated with bio-diversity estimates. Among identified variants, few were found to be associated with more specific phenotypes. Particularly, the gene involved in folate transport and linked to folate malabsorption was found to be associated with Proteobacteria. The latter for its part was found to be one of the primary phyla containing the highest number of genes responsible for de-novo folate synthesis. Similarly, the fly gene related to immune function with the human homologous gene linked to the inflammatory gut disease was found to be associated with the Acetobacter genus. This genus based on the literature survey was found to be associated with an immune deficiency in a fruit fly. In summary, this research revealed captivating findings of genetic factors associated with fruit fly microbiota. The limitations and future directions were stated in order to provide the basis for future prospective studies.Master Thesis Developing a Guide of Bioinformatic Database for Probiotic Products(Izmir Institute of Technology, 2019) Yılmaz, Melike; Harsa, Hayriye Şebnem; Sezgin, EfeRecently, probiotic use has rapidly expanded, as they have potential health effects for microbiota to protect homeostasis in the human body. Bioinformatics is generally defined as collecting and analysing biological data. Establishing a bioinformatic system for probiotics, would have a potential to emphasize the beneficial impacts for human health, while enabling cross examination on diseases and products. In this study, new information has been collected about probiotics based on in vitro, in vivo, clinical trials and meta-analysis to develop a comprehensive guide. Metaanalyses of sixteen and seventeen randomized, controlled trials of S. boulardii (Sb) against diarrhea reported pooled relative risks of 0.51 (95% CI [0.40-0.64]) in adults and 0.55 (95% CI [0.42-0.72]) in children, respectively. These results demonstrated that Sb was effective for preventing and treating different types of diarrhea in adult and children patients. An in silico gene expression study conducted in Tecnico Lisboa* comparing Sb probiotic and non-probiotic Saccharomyces cerevisiae (Sc) strains showed transcription regulation differences in 26 genes. An in silico pipeline that was used as the basis for a new query in the ProBioYeastract database was developed. A cross-strain promoter analysis, comparing Sb CNCM I-745 and Unique28 strains with Sc S288C strain showed that the expression of 26 probiotic-related genes was predicted to be controlled by different transcription factors in probiotic vs non-probiotic strains. Among the evaluated six selected genes, a gene involved in biofilm formation, aggregation, and adhesion, EFG1, was found to be up-regulated in Sb CNCM I-745 compared to Sc BY4741.