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theses

One of the most fascinating aspects of biomedical sciences is searching for the links between the observed phenotypic changes with the underlying causes linked to known biological functions at the molecular level. These functions, however, are observed at different physiologic levels interacting physically, spatially, and/or temporally. Systems biology fundamentally studies the interactions taking place at genomic, proteomic and metabolomic levels under homeostatic conditions or in response to pathologic or pharmacologic stimuli. Each of these data-rich “-omics” fields have instrumental contributions to describe biological phenomena at their complementary levels. Integration of the knowledge from one or more such levels gives us opportunity to determine causal links more thoroughly and rationalize the focused question from initiating source to the observed end point. This dissertation is centered on extracting information from the data provided by the -omics analyses, as well as interconnecting the information gained at different levels through bioinformatics and modeling approaches. We applied these approaches to understand the impact of systemic inflammation and anti-inflammatory therapy on the metabolism in two distinct studies. Our first focus was on the major changes arising in plasma metabolome during the response to systemic inflammation, and how these changes affect the transcriptome of immune cells, in turn. We defined the dominant metabolic dynamics in the plasma of humans administered with bacterial endotoxin, as a surrogate for reproducing the pathophysiology of systemic inflammation. Subsequently, we integrated this analysis with transcriptional response of leukocytes to understand how their gene expression might have been affected from the metabolic landscape of the fluid environment in which they circulate. We hypothesized that the drastic changes in the immediate environment of the leukocytes might have an adaptive effect on shaping their transcriptional response in conjunction with the initial inflammatory stimuli. Secondly, we explored the interplay between transcriptional and translational dynamics in liver in response to an anti-inflammatory drug administration. This involved the integration of temporal gene and protein expression patterns extracted from the livers of rats injected with a synthetic corticosteroid (methylprednisolone, MPL); long term use of which is associated with many metabolism related side effects. Our approach involved both combining and contrasting the same gene products in two different expression levels, in essence, pursuing the best integration approach yielding most useful mechanistic information. The significant disparity between the proteome and corresponding transcriptome in this study suggested that additional translational or post-translational implications of CSs are very plausible in addition to their direct effects on transcription; while also cautioning against the use of transcriptional data for deciphering the regulation of the functional pathways which they represent.

ETD_6629

Ph.D.

Includes bibliographical references

by Kubra Kamisoglu

doi:10.7282/T3C82C9M

ETD doctoral

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