Peculiar feed-forward loop network motifs in Escherichia coli / Kok Eng Piew
A feed-forward loop (FFL) is one type of transcription network motifs studied in systems biology. So far, eight types of FFL based on their regulatory patterns have been identified. The majority of FFL found in transcription networks of biological systems have been identified to belong to cohe...
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| Format: | Thesis |
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2012
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| Online Access: | http://studentsrepo.um.edu.my/3830/1/1_title%2C_abstract%2C_content.pdf http://studentsrepo.um.edu.my/3830/2/2_chap_1_intro%26lit_review.pdf http://studentsrepo.um.edu.my/3830/3/3_chap_2_methodology.pdf http://studentsrepo.um.edu.my/3830/4/4_chap_3_results.pdf http://studentsrepo.um.edu.my/3830/5/5_chap_4%265_discussion_%26_conclusion.pdf http://studentsrepo.um.edu.my/3830/6/6_ref_%26_appndx.pdf http://pendeta.um.edu.my/client/default/search/results?qu=Peculiar+feed-forward+loop+network+motifs+in+Escherichia+coli&te= http://studentsrepo.um.edu.my/3830/ |
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| Summary: | A feed-forward loop (FFL) is one type of transcription network motifs studied in
systems biology. So far, eight types of FFL based on their regulatory patterns have been
identified. The majority of FFL found in transcription networks of biological systems have
been identified to belong to coherent and incoherent type 1 FFL. Nevertheless, six FFL
types (coherent and incoherent type 2, 3 and 4 FFL) are present in low frequencies in
Escherichia coli. The persistence and not elimination of these “peculiar” FFL through
natural selection is perplexing. One way to understanding this conundrum is to study the
dynamics of these FFL and empirically study their relative abundance using public
databases. To this end, data mining from RegulonDB and simulation using CellDesigner
4.2 were carried out. Coherent FFL shows delay in target gene expression upon the
activation or repression by the activated forms of first and second transcription factors.
Incoherent FFL shows acceleration of target gene expression that results in over production
of target gene product. In particular, the acceleration of target gene expression in incoherent
type 3 and 4 FFL are highly dependent on the promoter binding activity of the second
transcription factor. We identified 84 of 1702 transcription factor-operon interactions in
RegulonDB to be involved in FFL transcription networks in E. coli. A total of 28 FFL were
identified, nine of them found to participate in biochemical processes such as maltose
utilization, arabinose utilization and anaerobic respiration. The efficacy of peculiar FFL
was discussed in the context of these processes. We find that in silico simulation of FFL
dynamics using CellDesigner 4.2 provide explicit results that are useful for guiding
biological interpretation of important biological processes in E. coli. It is also a practical means of generating useful hypotheses in gene regulatory networks for experimental validation in the laboratory |
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