Infectious diseases are the top leading cause of death worldwide. Identifying essential genes, genes indispensable for survival, has been proven indispensable in defining new therapeutic targets against pathogens, major elements of the minimal set genome to be harnessed in synthetic biology, and determinants of evolutionary relationships of phylogenetically distant species. Thus, essentiality studies promise valuable revenues that can decipher much of biological complexities.
Taking advantage of the available microbial sequences and the essentiality studies conducted in various microbial models, we proposed a framework for the prediction of essential genes based on our experimentally verified knowledge of the pathways involved in three essential xiv functions: genetic information processing, cell wall biosynthesis, and energy metabolism. We investigated physiological pathways in Kyoto Encyclopedia of Genes and Genomes (KEGG) database and developed a bioinformatics approach to predict essential genes in 13 different microbial species. Our in silico findings matched to a high degree the experimental data derived from essentiality studies conducted on the same microbial models, providing insights about the microbial lifestyles, including energy resources, cell wall structure, and ecological preferences, but not virulence tools and mechanisms.
Furthermore, we believe that essential genes have survived the evolutionary purifying selection due to their evolved capacity to re-wire genetic and protein networks in response to any emerging stress. In this sense, an environmental specificity (stress) provides a dominant determinant of an essential gene set. The new challenge was understanding the contribution of the essential genome in S. sanguinis to the coping mechanisms to different clinically relevant stress factors, namely temperature elevation (43oC) and sub-inhibitory concentration of ampicillin, an abundantly prescribed antibiotic for prophylaxis and treatment against S. sanguinis. The current project investigated the transcriptomic and proteomic profiles of essential genes and proteins, using RNA-seq and mass spectrometry respectively, under the impact of the two stressors separately, to elucidate the essential genome and proteome dynamics on a temporal basis and define “pathogenesis signatures” as potential therapeutic targets. We believe that the current findings will help characterize a bacterial model for studying the dynamics of essential genes and assist in designing evidence-based guidelines for drug prescription in clinical practice.
Identifer | oai:union.ndltd.org:vcu.edu/oai:scholarscompass.vcu.edu:etd-6008 |
Date | 01 January 2017 |
Creators | El-rami, Fadi |
Publisher | VCU Scholars Compass |
Source Sets | Virginia Commonwealth University |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Theses and Dissertations |
Rights | © The Author |
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