Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.525021
Title: SubtilNet2, a functional interaction model for the validation of potential therapeutic targets
Author: Hawes, Christopher Stephen
Awarding Body: Newcastle University
Current Institution: University of Newcastle upon Tyne
Date of Award: 2010
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Abstract:
Systems Biology- the study of interactions between components of biological systems, and how these can produce new functions and behaviours, is beginning to produce a more comprehensive understanding of biology. Its development is enabling many new opportunities, including the discovery and development of more effective and targeted therapeutics for a range of different conditions. It was in this context that this investigation began, with focus placed upon identifying therapeutic targets in Bacillus subtilis that could be used to limit the development and spread of infection, so called anti-infective targets. Using an in silico data driven Systems Biology approach, our industrial collaborators, e- Therapeutics predicted pairs of genes from B. subtilis that could act as anti-infective targets when targeted together. This investigation was tasked with the development and testing of experimental models and approaches that could be used to validate these potential targets. In a separate collaboration with the Integrative Bioinformatics Group at Newcastle University, a functional interaction network model for B. subtilis- SubtilNet2, was generated and tested. Compiled from a range of experimental, bioinformatical and literature based sources, it represented all known functional interactions known to occur within B. subtilis. This network was applied to investigate the selection of the predicted targets, and determine any biological basis for the experimental results seen. A single predicted target acting by itself was confirmed to be successful. As a second component to this investigation, Systems Biology was used to complement traditional hypothesis driven research, specifically the possibility of directed targeting and channelling of substrates between two biosynthetic pathways. This was explored by studying the synthesis of carbamoyl phosphate (CP), an intermediate in both the arginine and uracil biosynthetic pathways. Typically, prokaryotes encode a single heterodimeric carbamoyl phosphate synthetase (CPS) that is used by both the arginine and pyrimidine biosynthetic pathways. B. subtilis and its close relatives are unique in encoding arginine- and uracil-specific copies of this enzyme. Moreover, the genes encoding the respective arginine (carA and carB) and uracil (pyrAA and pyrAB) specific CPSs are clustered with the other genes in their respective pathways (e.g. argC,J,B,D-carA,B-argF and pyrB,C,AA,AB,K,D,F,E) This degree of clustering is not found in bacteria with single CPSs. Experimental and SubtilNet2 analysis approaches were developed to express and individually test for the presence of any interaction between the subunits of each systems CPS’s, as well as to other components within associated gene clusters. The presence or absence of interaction would be used to determine if CP produced by one system could be shared with the opposite system. If it couldn’t, could the unusual cluster of genes seen to surround each CPS be used to encode a macromolecular complex structure with a single point of entry and exit to channel CP and other substrates within a biosynthetic system? A failure despite repeated attempts and strategies to produce soluble CPS subunits and other biosynthesis proteins, when expressed independently of one another, suggested a need for the presence of other members of each pathway. SubtilNet2 testing of these components and their functional associations didn’t identify any distinct groups or systems being supplied with system specific CP, however this is more likely to result from limitations of the associated approaches, rather than genuine a biological property.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.525021  DOI: Not available
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