Biomedical subjects

Masaru Tomita

Publications and source records attributed to Masaru Tomita.

At least 19 recordsLinked to original sources

PubMed2007

A mathematical model for the Kai-protein-based chemical oscillator and clock gene expression rhythms in cyanobacteria.

In the cyanobacterium, Synechococcus elongatus, most promoters are regulated by a circadian clock under continuous light (LL) conditions. Nevertheless, the basic circadian oscillation is primarily generated by alternating KaiC phosphorylation/dephosphorylation reactions at the posttranslational level. Indeed, the KaiC phosphorylation cycle was recently reconstituted in vitro by incubating KaiA, KaiB, and KaiC proteins with ATP. However, the molecular dynamics of this chemical oscillation and the mechanism that drives the circadian transcription/translation rhythms remain unknown. In this report, the KaiC phosphorylation cycle and the gene regulatory network in the cyanobacterial circadian system have been modeled. The model reproduces the robust KaiC phosphorylation cycle in the absence of de novo gene expression as is observed in vitro, as well as its coupling to transcriptional/translational feedback in LL conditions in vivo. Moreover, the model is consistent with most previous experiments, including various combinations of genetic knockout or overexpression of kai genes. It also predicts that multiple KaiC phosphorylation states and dynamic Kai protein interactions may be required for the cyanobacterial circadian system.

Bacterial Proteins↗

PubMed2006

Noise-reduction filtering for accurate detection of replication termini in bacterial genomes.

Bacterial chromosomes are highly polarized in their nucleotide composition through mutational selection related to replication. Using compositional skews such as the GC skew, replication origin and terminus can be predicted in silico by observing the shift points. However, the genome sequence is affected by myriad functional requirements and selection on numerous subgenomic features, and elimination of this "noise" should lead to better predictions. Here, we present a noise-reduction approach that uses low-pass filtering through Fast Fourier transform coupled with cumulative skew graphs. It increases the prediction accuracy of the replication termini compared with previously documented methods based on genomic base composition.

Bacteria↗

PubMed2006

MathDAMP: a package for differential analysis of metabolite profiles.

BACKGROUND: With the advent of metabolomics as a powerful tool for both functional and biomarker discovery, the identification of specific differences between complex metabolite profiles is becoming a major challenge in the data analysis pipeline. The task remains difficult, given the datasets' size, complexity, and common shifts in migration (elution/retention) times between samples analyzed by hyphenated mass spectrometry methods. RESULTS: We present a Mathematica (Wolfram Research, Inc.) package MathDAMP (Mathematica package for Differential Analysis of Metabolite Profiles), which highlights differences between raw datasets acquired by hyphenated mass spectrometry methods by applying arithmetic operations to all corresponding signal intensities on a datapoint-by-datapoint basis. Peak identification and integration is thus bypassed and the results are displayed graphically. To facilitate direct comparisons, the raw datasets are automatically preprocessed and normalized in terms of both migration times and signal intensities. A combination of dynamic programming and global optimization is used for the alignment of the datasets along the migration time dimension. The processed datasets and the results of direct comparisons between them are visualized using density plots (axes represent migration time and m/z values while peaks appear as color-coded spots) providing an intuitive overall view. Various forms of comparisons and statistical tests can be applied to highlight subtle differences. Overlaid electropherograms (chromatograms) corresponding to the vicinities of the candidate differences from any result may be generated in a descending order of significance for visual confirmation. Additionally, a standard library table (a list of m/z values and migration times for known compounds) may be aligned and overlaid on the plots to allow easier identification of metabolites. CONCLUSION: Our tool facilitates the visualization and identification of differences between complex metabolite profiles according to various criteria in an automated fashion and is useful for data-driven discovery of biomarkers and functional genomics.

Biomarkers↗

PubMed2006

Role of phosphoenolpyruvate in the NADP-isocitrate dehydrogenase and isocitrate lyase reaction in Escherichia coli.

Phosphoenolpyruvate inhibited Escherichia coli NADP-isocitrate dehydrogenase allosterically (Ki of 0.31 mM) and isocitrate lyase uncompetitively (Ki' of 0.893 mM). Phosphoenolpyruvate enhances the uncompetitive inhibition of isocitrate lyase by increasing isocitrate, which protects isocitrate dehydrogenase from the inhibition, and contributes to the control through the tricarboxylic acid cycle and glyoxylate shunt.

Escherichia coli↗

PubMed2006

On the interplay of gene positioning and the role of rho-independent terminators in Escherichia coli.

The majority of intrinsic rho-independent terminator signals, reported to consist of stable hairpin structures followed by T-rich regions, possess the potential to operate bi-directionally and to induce transcription terminations on both strands of the DNA duplex in Escherichia coli. By using RNAMotif software, we investigated the distributions of termination motifs around the 3'-ends of overlapping and non-overlapping genes at the genomic level. We suggest that the positions of compactly encoded E. coli genes and rho-independent terminators are optimized to terminate the adjoining genes on their antisense strands efficiently, and not to mis-terminate overlapping transcripts, due to their bi-directional properties.

Escherichia coli↗

PubMed2006

HybGFS: a hybrid method for genome-fingerprint scanning.

BACKGROUND: Protein identification based on mass spectrometry (MS) has previously been performed using peptide mass fingerprinting (PMF) or tandem MS (MS/MS) database searching. However, these methods cannot identify proteins that are not already listed in existing databases. Moreover, the alternative approach of de novo sequencing requires costly equipment and the interpretation of complex MS/MS spectra. Thus, there is a need for novel high-throughput protein-identification methods that are independent of existing predefined protein databases. RESULTS: Here, we present a hybrid method for genome-fingerprint scanning, known as HybGFS. This technique combines genome sequence-based peptide MS/MS ion searching with liquid-chromatography elution-time (LC-ET) prediction, to improve the reliability of identification. The hybrid method allows the simultaneous identification and mapping of proteins without a priori information about their coding sequences. The current study used standard LC-MS/MS data to query an in silico-generated six-reading-frame translation and the enzymatic digest of an entire genome. Used in conjunction with precursor/product ion-mass searching, the LC-ETs increased confidence in the peptide-identification process and reduced the number of false-positive matches. The power of this method was demonstrated using recombinant proteins from the Escherichia coli K12 strain. CONCLUSION: The novel hybrid method described in this study will be useful for the large-scale experimental confirmation of genome coding sequences, without the need for transcriptome-level expression analysis or costly MS database searching.

Algorithms↗

PubMed2006

Inferring rules of Escherichia coli translational efficiency using an artificial neural network.

Although the machinery for translation initiation in Escherichia coli is very complicated, the translational efficiency has been reported to be predictable from upstream oligonucleotide sequences. Conventional models have difficulties in their generalization ability and prediction nonlinearity and in their ability to deal with a variety of input attributions. To address these issues, we employed structural learning by artificial neural networks to infer general rules for translational efficiency. The correlation between translational activities measured by biological experiments and those predicted by our method in the test data was significant (r=0.78), and our method uncovered underlying rules of translational activities and sequence patterns from the obtained skeleton structure. The significant rules for predicting translational efficiency were (1) G- and A-rich oligonucleotide sequences, resembling the Shine-Dalgarno sequence, at positions -10 to -7; (2) first base A in the initiation codon; (3) transport/binding or amino acid metabolism gene function; (4) high binding energy between mRNA and 16S rRNA at positions -15 to -5. An additional inferred novel rule was that C at position -1 increases translational efficiency. When our model was applied to the entire genomic sequence of E. coli, translational activities of genes for metabolism and translational were significantly high.

Base Sequence↗

PubMed2006

Evaluation of metabolic alteration in transgenic rice overexpressing dihydroflavonol-4-reductase.

BACKGROUND AND AIMS: Previous studies have shown that transgenic rice plants overexpressing YK1, which possesses dihydroflavonol-4-reductase (DFR) activity, showed biotic and abiotic stress tolerance. High throughput profiles of metabolites have also been shown in such transgenic plants by Fourier transform ion cyclotron mass spectrometry. In this study, capillary electrophoresis mass spectrometry analysis (CE/MS) was employed to identify precise metabolites such as organic acids, amino acids and sugars. METHODS: Using CE/MS, we analysed several metabolites of glycolysis, the tricarboxylic acid (TCA) cycle and the pentose phosphate pathway. In addition, the concentrations of sugars and ion were quantified. KEY RESULTS: In YK1 (DFR)-overexpressing plants, the concentrations of cis-aconitate, isocitrate and 2-oxoglutarate were higher in leaves, whereas those of fructose-1,6-bisphosphate and glyceraldehyde-3-phosphate were lower in roots. In seeds, the amounts of free amino acids and metals were altered, whereas sugars in seeds were kept constant. In YK1 calli, an approx. 3-fold increase in glutathione was observed, whereas the activities of glutathione peroxidase and glutathione reductase were concomitantly increased. CONCLUSIONS: The overexpression of YK1 (DFR) was associated with slight changes in the amounts of several metabolites analysed in whole plants, whilst glutathione derivatives were substantially increased in suspension-cultured cells.

Alcohol Oxidoreductases↗

PubMed2006

A simplified method for power-law modelling of metabolic pathways from time-course data and steady-state flux profiles.

BACKGROUND: In order to improve understanding of metabolic systems there have been attempts to construct S-system models from time courses. Conventionally, non-linear curve-fitting algorithms have been used for modelling, because of the non-linear properties of parameter estimation from time series. However, the huge iterative calculations required have hindered the development of large-scale metabolic pathway models. To solve this problem we propose a novel method involving power-law modelling of metabolic pathways from the Jacobian of the targeted system and the steady-state flux profiles by linearization of S-systems. RESULTS: The results of two case studies modelling a straight and a branched pathway, respectively, showed that our method reduced the number of unknown parameters needing to be estimated. The time-courses simulated by conventional kinetic models and those described by our method behaved similarly under a wide range of perturbations of metabolite concentrations. CONCLUSION: The proposed method reduces calculation complexity and facilitates the construction of large-scale S-system models of metabolic pathways, realizing a practical application of reverse engineering of dynamic simulation models from the Jacobian of the targeted system and steady-state flux profiles.

Kinetics↗

PubMed2006

Over-representation of Chi sequences caused by di-codon increase in Escherichia coli K-12.

Chi sequences (5'-GCTGGTGG-3') are cis-acting 8 bp sequence elements that enhance homologous recombination promoted by the RecBCD pathway in Escherichia coli. The genome of E. coli K-12 MG1655 contains 1009 Chi sequences and this frequency far exceeds the expected value for occurrence of an 8 bp sequence in a genome of this size. It is generally thought that the over-representation of Chi sequences indicates that they have been selected for during evolution because of their function in recombination. The genes from three E. coli strains (K-12, O157 and CFT) were classified into three categories (island, match to other E. coli, and backbone). Island genes have a different base composition and codon usage in comparison with those in the backbone genes, therefore they were relatively new and not yet adapted to the base composition patterns and codon usage typical of the recipient genome. The over-representation of Chi sequences was examined by comparing Chi frequencies and codon frequencies between island and backbone genes. The difference in the CTGGTG di-codon frequency between the backbone and island genes was correlated with the frequency of Chi sequences which were translated in the Leu-Val (-G/CTG/GTG/G-) reading frame in the K-12 strain. These results suggest that the main reading frame of Chi sequences increased as a result of the di-codon CTG-GTG increasing under a genome-wide pressure for adapting to the codon usage and base composition of the E. coli K-12 strain, and that the RecBCD recombinase might adjust its recognition sequence to a frequently occurring oligomer such as G-CTG-GTG-G.

Base Composition↗

PubMed2006

Modeling Hsp70-mediated protein folding.

The Hsp70 chaperone system is the major molecular chaperone system that assists protein-folding processes in all cells. To understand these processes, we analyzed the kinetic characteristics of the Escherichia coli homologs of this chaperone system during folding of a denatured protein using computer simulations and compared the results with in vitro refolding experiments. Rate constants used for the model were derived from recent literature or were determined and scrutinized for their applicability to the refolding reaction. Our simulation results are consistent with reported laboratory experiments, not only simulating the refolding reaction of wild-type proteins but also the behavior of mutant variants. Variation of kinetic parameters and concentrations of components of the Hsp70 system demonstrate the robustness of the chaperone system in assisting protein folding. Furthermore, the importance of the synergistic stimulation of the ATPase activity of Hsp70 is demonstrated. The limitations of our kinetic model indicate sore spots in our understanding of this chaperone system. Our model provides a platform for further research on chaperone action and the mechanism of chaperone-assisted refolding of denatured proteins.

Adenosine Triphosphate↗

PubMed2006

Parameter estimation for stiff equations of biosystems using radial basis function networks.

BACKGROUND: The modeling of dynamic systems requires estimating kinetic parameters from experimentally measured time-courses. Conventional global optimization methods used for parameter estimation, e.g. genetic algorithms (GA), consume enormous computational time because they require iterative numerical integrations for differential equations. When the target model is stiff, the computational time for reaching a solution increases further. RESULTS: In an attempt to solve this problem, we explored a learning technique that uses radial basis function networks (RBFN) to achieve a parameter estimation for biochemical models. RBFN reduce the number of numerical integrations by replacing derivatives with slopes derived from the distribution of searching points. To introduce a slight search bias, we implemented additional data selection using a GA that searches data-sparse areas at low computational cost. In addition, we adopted logarithmic transformation that smoothes the fitness surface to obtain a solution simply. We conducted numerical experiments to validate our methods and compared the results with those obtained by GA. We found that the calculation time decreased by more than 50% and the convergence rate increased from 60% to 90%. CONCLUSION: In this work, our RBFN technique was effective for parameter optimization of stiff biochemical models.

Algorithms↗

PubMed2006

Comparative analysis of base correlations in 5' untranslated regions of various species.

Translational initiation signals, such as Shine-Dalgarno (SD) sequences in bacteria and Kozak consensus sequences in vertebrates, direct ribosomes to initiate protein synthesis from mRNAs. Investigating sequence characteristics of these signals is important, particularly to infer translational initiation mechanisms. Although various statistical analyses of translational initiation signals have been done, few have focused on base correlations that assess base dependencies in the signal sequences. We used relative entropy and mutual information to analyze base conservation and correlation, respectively, in the 5' UTRs of various species. In eukaryotes, we found peaks of relative entropy at -3 from the translational start site but no peak of mutual information at that position, indicating that the base at that position (known as the core base of the Kozak sequence) is well conserved but not correlated with neighboring bases and thus functions as a single base. We observed unexpected peaks of mutual information between positions -2 and -1 in most eukaryotes. Surprisingly these base correlation also occurred in some bacteria and archaea, although there were no base preferences at neither position. Various dinucleotide patterns existed at these positions, and the correlation between bases at -2 and -1 may be relevant to the context of translational initiation. Because dinucleotide patterns of correlated pairs of nucleotides at -2 and -1 were not unique within respective organisms, the correlation could not be found when analyzing single-nucleotide conservation. Therefore, mutual information allowed us to discover signals that were not found by simply analyzing base conservation.

5' Untranslated Regions↗

PubMed2006

Differential metabolomics reveals ophthalmic acid as an oxidative stress biomarker indicating hepatic glutathione consumption.

Metabolomics is an emerging tool that can be used to gain insights into cellular and physiological responses. Here we present a metabolome differential display method based on capillary electrophoresis time-of-flight mass spectrometry to profile liver metabolites following acetaminophen-induced hepatotoxicity. We globally detected 1,859 peaks in mouse liver extracts and highlighted multiple changes in metabolite levels, including an activation of the ophthalmate biosynthesis pathway. We confirmed that ophthalmate was synthesized from 2-aminobutyrate through consecutive reactions with gamma-glutamylcysteine and glutathione synthetase. Changes in ophthalmate level in mouse serum and liver extracts were closely correlated and ophthalmate levels increased significantly in conjunction with glutathione consumption. Overall, our results provide a broad picture of hepatic metabolite changes following acetaminophen treatment. In addition, we specifically found that serum ophthalmate is a sensitive indicator of hepatic GSH depletion, and may be a new biomarker for oxidative stress. Our method can thus pinpoint specific metabolite changes and provide insights into the perturbation of metabolic pathways on a large scale and serve as a powerful new tool for discovering low molecular weight biomarkers.

Animals↗

PubMed2006

Large-scale identification of protein-protein interaction of Escherichia coli K-12.

Protein-protein interactions play key roles in protein function and the structural organization of a cell. A thorough description of these interactions should facilitate elucidation of cellular activities, targeted-drug design, and whole cell engineering. A large-scale comprehensive pull-down assay was performed using a His-tagged Escherichia coli ORF clone library. Of 4339 bait proteins tested, partners were found for 2667, including 779 of unknown function. Proteins copurifying with hexahistidine-tagged baits on a Ni2+-NTA column were identified by MALDI-TOF MS (matrix-assisted laser desorption ionization time of flight mass spectrometry). An extended analysis of these interacting networks by bioinformatics and experimentation should provide new insights and novel strategies for E. coli systems biology.

Escherichia coli K12↗

PubMed2006

Prediction of non-coding and antisense RNA genes in Escherichia coli with Gapped Markov Model.

A new mathematical index was developed to identify and characterize non-coding RNA (ncRNA) genes encoded within the Escherichia coli (E. coli) genome. It was designated the GMMI (Gapped Markov Model Index) and used to evaluate sequence patterns located at the separate positions of consensus sequences, codon biases and/or possible RNA structures on the basis of the Markov model. The GMMI was able to separate a set of known mRNA sequences from a mixture of ncRNAs including tRNAs and rRNAs. Consequently, the GMMI was employed to predict novel ncRNA candidates. At the beginning, possible transcription units were extracted from the E. coli genome using consensus sequences for the sigma70 promoter and the rho-independent terminator. Then, these units were evaluated by using the GMMI. This identified 133 candidate ncRNAs, which contain 29 previously annotated small RNA genes and 46 possible antisense ncRNAs. Furthermore 12 transcripts (including five antisense RNAs) were confirmed according to the expression analysis. These data suggests that the expression of small antisense RNAs might be more common than previously thought in the E. coli genome.

Computational Biology↗

PubMed2006

GEM System: automatic prototyping of cell-wide metabolic pathway models from genomes.

BACKGROUND: Successful realization of a "systems biology" approach to analyzing cells is a grand challenge for our understanding of life. However, current modeling approaches to cell simulation are labor-intensive, manual affairs, and therefore constitute a major bottleneck in the evolution of computational cell biology. RESULTS: We developed the Genome-based Modeling (GEM) System for the purpose of automatically prototyping simulation models of cell-wide metabolic pathways from genome sequences and other public biological information. Models generated by the GEM System include an entire Escherichia coli metabolism model comprising 968 reactions of 1195 metabolites, achieving 100% coverage when compared with the KEGG database, 92.38% with the EcoCyc database, and 95.06% with iJR904 genome-scale model. CONCLUSION: The GEM System prototypes qualitative models to reduce the labor-intensive tasks required for systems biology research. Models of over 90 bacterial genomes are available at our web site.

Chromosome Mapping↗

PubMed2006

Characteristics and clustering of human ribosomal protein genes.

BACKGROUND: The ribosome is a central player in the translation system, which in mammals consists of four RNA species and 79 ribosomal proteins (RPs). The control mechanisms of gene expression and the functions of RPs are believed to be identical. Most RP genes have common promoters and were therefore assumed to have a unified gene expression control mechanism. RESULTS: We systematically analyzed the homogeneity and heterogeneity of RP genes on the basis of their expression profiles, promoter structures, encoded amino acid compositions, and codon compositions. The results revealed that (1) most RP genes are coordinately expressed at the mRNA level, with higher signals in the spleen, lymph node dissection (LND), and fetal brain. However, 17 genes, including the P protein genes (RPLP0, RPLP1, RPLP2), are expressed in a tissue-specific manner. (2) Most promoters have GC boxes and possible binding sites for nuclear respiratory factor 2, Yin and Yang 1, and/or activator protein 1. However, they do not have canonical TATA boxes. (3) Analysis of the amino acid composition of the encoded proteins indicated a high lysine and arginine content. (4) The major RP genes exhibit a characteristic synonymous codon composition with high rates of G or C in the third-codon position and a high content of AAG, CAG, ATC, GAG, CAC, and CTG. CONCLUSION: Eleven of the RP genes are still identified as being unique and did not exhibit at least some of the above characteristics, indicating that they may have unknown functions not present in other RP genes. Furthermore, we found sequences conserved between human and mouse genes around the transcription start sites and in the intronic regions. This study suggests certain overall trends and characteristic features of human RP genes.

Amino Acids↗