Download Elucidating the essentiality of essential genes in E. coli K-12

Elucidating the essentiality of essential genes in E. coli K-12
Yue-Yang Bow1,#, Jen-Yun Chang1,#, Hsueh-Fen Juan2, Hirotada Mori3,
Hsuan-Cheng Huang1
1
Institute of Bioinformatics, National Yang-Ming University, Taipei 112, Taiwan,
Department of Life Science, National Taiwan University, Taipei 106, Taiwan,
3
Graduate School of Biological Sciences, Nara Institute of Science and Technology,
Takayama, Ikoma, Nara 630-0101, Japan,
#
These authors contributed equally to this work.
2
We recently established single-gene deletion library for all of the predicted genes of E.
coli K-12 by Wanner’s method [1] and simultaneously 303 genes have been predicted as
essential genes in LB medium [2]. Elucidating the essentiality of these essential genes is
a key to understand the system level organization of living cells. Here we present our
analysis to address this issue from the perspectives of protein-protein interaction and
metabolic networks.
We have performed a comparison between essential and non-essential genes within an
interaction network of E. coli and found that essential genes have significantly more links
than the non-essential genes, validating earlier findings in budding yeast [3].
Furthermore, other topological features are investigated to find their correlation with
essential genes.
Based on the known metabolic reactions of E. coli collected from the KEGG (Kyoto
Encyclopedia of Genes and Genomes) [4] and EcoCyc [5] databases, a simple metabolic
simulator is developed to reconstruct and navigate all the possible pathways and
participated metabolites. In-silico gene deletion is performed to obtain the variation of
metabolite distributions and examine the effect of missing links. Our results indicate that
the average number of affected metabolites and reactions by deletion of essential genes
are significantly higher than non-essential genes. The predicted results are validated by
DNA microarray experiments with deletion mutatant and phenotype microarray data [6].
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