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The Practical Use of System Biology: K-12 E.coli Strain

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The Practical Use of System Biology: K-12 E.coli Strain

권희운(~~Heeun~~ [[HeeUn Kwon]]), 이강석([[Kangseok Lee]])  [UNIST 나노생명화학공학부]

After naming of something from cork as “cell” by Robert Hooke in 1665, biology, a subject researched from ancient, has been evolved in more radical way and reached gene level study though setting up modern research methodology in 17th and 18th century. And as more and more developing of biology and genomics, it needed to invest and understand about structure and dynamics of cell and organism than isolated parts of them. This necessity was known from long time ago because early development of genomics also had systemic way, there were lack of elements for understanding characteristics of system. By existence of better experimental tools and improved software and analytical way recently, progress of biology directs to not only collection of information but also knowing interactions of information and their roles: overall understanding of genes, understanding and research about complicated biosystem, and systemic way by using genetical information to this day[1-3], As differentiation of sequence genomics and functional genomics from genomics, this kind of research direction is related to system biology. Namely, we uses system biology to overcome post-genomic era hitherto[4]. System-level understanding is continuing issue in biological science, and technically making better system performance collecting understandable data and quality of important molecules of other biology, like genome sequencing and high-throughput measurement[5]. Future biology will be changed by spatiotemporal analytic techniques associated with mathematical, computational modeling. Different from usage of genomics and molecular biology, importance of system biology would be higher, with provision of “nothing more or less, obvious statistical way of thinking” by utilizing these statistics and information[6].

Functional Orphans Characteristics in E. coli

Figure 1. Annotated and Functional Orphan Genes of the E. coli K-12 Reference Strain

Translation seem to occur for the genes lacking annotation into bona fide proteins as their corresponding transcripts were not obviously (p ¼ 0.36) less stable than the products of annotated genes (Figure 1C). Nonetheless, some differences were clear with side of their biophysical attributes and evolutionary scope associated with annotated genes. Just 21 orphans about 1.5% are necessary for viability under regular laboratory conditions worthily. In contrast with the 280 annotated genes (10%) formerly considered must-have. The orphans were also obviously less sufficient at the protein and transcript levels, and that is major characteristic of the orphans. In addition, they prefer to encode 44% of smaller with fewer domain assignments than for 74% of annotated proteins according to the SUPERFAMILY database [34]. Using a maximum-score E-value cutoff of 1 3 106 for BLAST bidirectional best hits (BDBHs), orphans also overall find less orthologs in a nonredundant dataset, filtered at 90% similarity based on the frequency of shared orthologs (Figure 1G), with an average of 0.22 as compared with 0.48 for annotated genes. However, in metagenomes, more various sequence comparisons available against current one (Figure 1H) indicated that orphan homologs (one-way BLAST hits) are distributed in diverse conditions (PLS2, S2). With all of these things, that claims the functional importance of the orphans is more than the annotations as a result.

Overall analysis of K-12 system

Figure 2. Generation and Integration of Physical and Functional Networks and Orphan Function Prediction

Figure2 is outline of System biology studies based on PI, GC in this paper. Figure 2-a is scheme of construction of a physical network based on protein copurification and detection. Figure2-b is scheme of integration of four Genomic context methods.

First method is gene fusions which represent similarity of functionality [35,36], second method is similarity of Phylogenetic profiles [33,37-38], third method is evolutionary conservation of gene order which is direction that proteins are expressed [39-41], fourth method is measurement of intergenic distances which are close the more functionality is similar[42-44]. Figure2-c is scheme of integration of PI and GC probabilistic networks and function prediction based on Figure2-a or Figure2-b. So this group used “StepPLR” which is designed new integrated network topology-based method.

[44] Snel B, Bork P, Huynen MA (2002) The identification of functional modules from the genomic association of genes. Proc Natl Acad Sci USA 99: 5890–5895.

<div>[45] Hu, P., Janga, S. C., Babu, M., Díaz-Mejía, J. J., Butland, G., Yang, W., ... & Emili, A. (2009). Global functional atlas of Escherichia coli encompassing previously uncharacterized proteins. PLoS biology, 7(4), 929.</div>

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