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本文データは平成22年度国立国会図書館の学位論文(博士)のデジタル化実施により作成された画像ファイルを基にpdf変換したものである京都大学0048新制・論文博士博士(工学)乙第8652号論工博第2893号新制||工||968(附属図書館)UT51-94-R411(主査)教授 長尾 真, 教授 堂下 修司, 教授 池田 克夫学位規則第4条第2項該当Doctor of EngineeringKyoto UniversityDFA

Modeling reaction-diffusion of molecules on surface and in volume spaces with the E-Cell System

The-Cell System is an advanced open-source simulation platform to model and analyze biochemical reaction networks. The present algorithm modules of the system assume that the reacting molecules are all homogeneously distributed in the reaction compartments, which is not the case in some cellular processes. The MinCDE system in Escherichia coli, for example, relies on intricately controlled reaction, diffusion and localization of Min proteins on the membrane and in the cytoplasm compartments to inhibit cell division at the poles of the rod-shaped cell. To model such processes, we have extended the E-Cell System to support reaction-diffusion and dynamic localization of molecules in volume and surface compartments. We evaluated our method by modeling the in vivo dynamics of MinD and MinE and comparing their simulated localization patterns to the observations in experiments and previous computational work. In both cases, our simulation results are in good agreement

The GC Skew Index: A Measure of Genomic Compositional Asymmetry and the Degree of Replicational Selection

Circular bacterial chromosomes have highly polarized nucleotide composition in the two replichores, and this genomic strand asymmetry can be visualized using GC skew graphs. Here we propose and discuss the GC skew index (GCSI) for the quantification of genomic compositional skew, which combines a normalized measure of fast Fourier transform to capture the shape of the skew graph and Euclidean distance between the two vertices in a cumulative skew graph to represent the degree of skew. We calculated GCSI for all available bacterial genomes, and GCSI correlated well with the visibility of GC skew. This novel index is useful for estimating confidence levels for the prediction of replication origin and terminus by methods based on GC skew and for measuring the strength of replicational selection in a genome

Selection Effects on the Positioning of Genes and Gene Structures from the Interplay of Replication and Transcription in Bacterial Genomes

Bacterial chromosomes are partly shaped by the functional requirements for efficient replication, which lead to strand bias as commonly characterized by the excess of guanines over cytosines in the leading strand. Gene structures are also highly organized within bacterial genomes as a result of such functional constraints, displaying characteristic positioning and structuring along the genome. Here we analyze the gene structures in completely sequenced bacterial chromosomes to observe the positional constraints on gene orientation, length, and codon usage with regard to the positions of replication origin and terminus. Selection on these gene features is different in regions surrounding the terminus of replication from the rest of the genome, but the selection could be either positive or negative depending on the species, and these positional effects are partly attributed to the A-T enrichment near the terminus. Characteristic gene structuring relative to the position of replication origin and terminus is commonly observed among most bacterial species with circular chromosomes, and therefore we argue that the highly organized gene positioning as well as the strand bias should be considered for genomics studies of bacteria

Emergence of macroscopic simplicity from the Tumor Necrosis Factor-alpha signaling dynamics

The Tumor Necrosis Factor-α (TNF-α), a cytokine produced during the innate immune response to invading pathogens, is involved in numerous fundamental cellular processes. Here, to understand the temporal activation profiles of the TNF-α regulated signaling network, we developed a dynamic computational model based on the perturbation-response approach and the law of information (signaling flux) conservation. Our simulations show that the temporal average population response of the TNF-α stimulated transcription factors NF-κB and AP-1, and 3 groups of 180 downstream gene expressions follow first-order equations. Using the model, in contrast to a well-known previous study, our model suggests that the continuous activation of the third group of genes is not mainly due to the poor rate of mRNA decay process, rather, the law of signaling flux conservation stipulates the presence of secondary signaling, such as feedback mechanism or autocrine signaling, is crucial. Although the living system is perceived as sophisticated and complex, notably, our work reveals the presence of simple governing principles in cell population dynamics

The Central Gas Systems of Early-Type Galaxies Traced by Dust Feature: Based on the HST WFPC2 Archival Images

We investigated the central gas systems of E/S0 galaxies by making use of the WFPC2 images of the Hubble Space Telescope archive. We searched the gas systems that were traced by the dust with a new method of making color excess images in F555W - F814W (V-I). Out of 25 sample galaxies, we detected gas system in 14 galaxies. The dust was newly detected in two galaxies that were thought to contain no dust based on single band, pre-refurbishment data. The full extents of the gas systems are 0.1 to 3.5 kpc, and the masses of the gas, log M(gas) [M(solar)], are 4.2 to 7.2. The AGN activity is well correlated with existence of the gas systems. None of galaxies without the gas systems show the AGN activity. On the other hand, some galaxies with the gas systems show the AGN activity; optical AGN activities are shown in 5 out of 11 galaxies of which AGNs are optically studied, and radio activities are shown in 6 out of 14 galaxies. This shows that the AGN activity is driven with the gas system.Comment: gzipped tarred file containing 7 files: Tomita.tex (main text, needs aaspp4.sty), Tomita.tab[1,2].tex (tables, need aj_pt4.sty), Tomita.fig [1a,1b,1c,2].ps (PS figures). To be appeared in AJ, Vol.120, No.1 (July 2000

Measure of synonymous codon usage diversity among genes in bacteria

<p>Abstract</p> <p>Background</p> <p>In many bacteria, intragenomic diversity in synonymous codon usage among genes has been reported. However, no quantitative attempt has been made to compare the diversity levels among different genomes. Here, we introduce a mean dissimilarity-based index (<it>D</it>mean) for quantifying the level of diversity in synonymous codon usage among all genes within a genome.</p> <p>Results</p> <p>The application of <it>D</it>mean to 268 bacterial genomes shows that in bacteria with extremely biased genomic G+C compositions there is little diversity in synonymous codon usage among genes. Furthermore, our findings contradict previous reports. For example, a low level of diversity in codon usage among genes has been reported for <it>Helicobacter pylori</it>, but based on <it>D</it>mean, the diversity level of this species is higher than those of more than half of bacteria tested here. The discrepancies between our findings and previous reports are probably due to differences in the methods used for measuring codon usage diversity.</p> <p>Conclusion</p> <p>We recommend that <it>D</it>mean be used to measure the diversity level of codon usage among genes. This measure can be applied to other compositional features such as amino acid usage and dinucleotide relative abundance as a genomic signature.</p

GeNESiS: gene network evolution simulation software

<p>Abstract</p> <p>Background</p> <p>There has been a lot of interest in recent years focusing on the modeling and simulation of Gene Regulatory Networks (GRNs). However, the evolutionary mechanisms that give rise to GRNs in the first place are still largely unknown. In an earlier work, we developed a framework to analyze the effect of objective functions, input types and starting populations on the evolution of GRNs with a specific emphasis on the robustness of evolved GRNs.</p> <p>Results</p> <p>In this work, we present a parallel software package, GeNESiS for the modeling and simulation of the evolution of gene regulatory networks (GRNs). The software models the process of gene regulation through a combination of finite-state and stochastic models. The evolution of GRNs is then simulated by means of a genetic algorithm with the network connections represented as binary strings. The software allows users to simulate the evolution under varying selective pressures and starting conditions. We believe that the software provides a way for researchers to understand the evolutionary behavior of populations of GRNs.</p> <p>Conclusion</p> <p>We believe that GeNESiS will serve as a useful tool for scientists interested in understanding the evolution of gene regulatory networks under a range of different conditions and selective pressures. Such modeling efforts can lead to a greater understanding of the network characteristics of GRNs.</p

Variation in the Correlation of G + C Composition with Synonymous Codon Usage Bias among Bacteria

G + C composition at the third codon position (GC3) is widely reported to be correlated with synonymous codon usage bias. However, no quantitative attempt has been made to compare the extent of this correlation among different genomes. Here, we applied Shannon entropy from information theory to measure the degree of GC3 bias and that of synonymous codon usage bias of each gene. The strength of the correlation of GC3 with synonymous codon usage bias, quantified by a correlation coefficient, varied widely among bacterial genomes, ranging from −0.07 to 0.95. Previous analyses suggesting that the relationship between GC3 and synonymous codon usage bias is independent of species are thus inconsistent with the more detailed analyses obtained here for individual species

OryzaPG-DB: Rice Proteome Database based on Shotgun Proteogenomics

<p>Abstract</p> <p>Background</p> <p>Proteogenomics aims to utilize experimental proteome information for refinement of genome annotation. Since mass spectrometry-based shotgun proteomics approaches provide large-scale peptide sequencing data with high throughput, a data repository for shotgun proteogenomics would represent a valuable source of gene expression evidence at the translational level for genome re-annotation.</p> <p>Description</p> <p>Here, we present OryzaPG-DB, a rice proteome database based on shotgun proteogenomics, which incorporates the genomic features of experimental shotgun proteomics data. This version of the database was created from the results of 27 nanoLC-MS/MS runs on a hybrid ion trap-orbitrap mass spectrometer, which offers high accuracy for analyzing tryptic digests from undifferentiated cultured rice cells. Peptides were identified by searching the product ion spectra against the protein, cDNA, transcript and genome databases from Michigan State University, and were mapped to the rice genome. Approximately 3200 genes were covered by these peptides and 40 of them contained novel genomic features. Users can search, download or navigate the database per chromosome, gene, protein, cDNA or transcript and download the updated annotations in standard GFF3 format, with visualization in PNG format. In addition, the database scheme of OryzaPG was designed to be generic and can be reused to host similar proteogenomic information for other species. OryzaPG is the first proteogenomics-based database of the rice proteome, providing peptide-based expression profiles, together with the corresponding genomic origin, including the annotation of novelty for each peptide.</p> <p>Conclusions</p> <p>The OryzaPG database was constructed and is freely available at <url>http://oryzapg.iab.keio.ac.jp/</url>.</p