Katsutoshi Takahashi

Dynamic modeling of genetic networks using genetic algorithm and S-system

MOTIVATIONnThe modeling of system dynamics of genetic networks, metabolic networks or signal transduction cascades from time-course data is formulated as a reverse-problem. Previous studies focused on the estimation of only network structures, and they were ineffective in inferring a network structure with feedback loops. We previously proposed a method to predict not only the network structure but also its dynamics using a Genetic Algorithm (GA) and an S-system formalism. However, it could predict only a small number of parameters and could rarely obtain essential structures. In this work, we propose a unified extension of the basic method. Notable improvements are as follows: (1) an additional term in its evaluation function that aims at eliminating futile parameters; (2) a crossover method called Simplex Crossover (SPX) to improve its optimization ability; and (3) a gradual optimization strategy to increase the number of predictable parameters.nnnRESULTSnThe proposed method is implemented as a C program called PEACE1 (Predictor by Evolutionary Algorithms and Canonical Equations 1). Its performance was compared with the basic method. The comparison showed that: (1) the convergence rate increased about 5-fold; (2) the optimization speed was raised about 1.5-fold; and (3) the number of predictable parameters was increased about 5-fold. Moreover, we successfully inferred the dynamics of a small genetic network constructed with 60 parameters for 5 network variables and feedback loops using only time-course data of gene expression.

A strategy for the determination of the elemental composition by fourier transform ion cyclotron resonance mass spectrometry based on isotopic peak ratios

We propose a novel strategy for determining the elemental composition of organic compounds using the peak ratio of isotopic fine structure observed by high-magnetic field Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS). Using 3-phosphoadenosine 5-phosphosulfate and CTU guanamine as standard organic compounds, isotopic peaks derived from (15)N-, (34)S-, and (18)O-substituted forms were separated from (13)C-substituted species. Furthermore, these isotopic peaks were quantitatively detected and closely matched the natural abundance of each element. These data successfully led us to determine the one elemental composition in a standard independent manner. The approach should be particularly amenable to the metabolomics research field.

Bleomycin-resistant cells contain increased bleomycin-hydrolase activities

Summary We have previously isolated mutants relatively resistant to bleomycin, a potent anticancer agent, from mutagenized Chinese hamster ovary (CHO) cells that are more sensitive to the antibiotic (BLMS). Three bleomycin-resistant mutants (BLMR-1, -3, -4) showed higher bleomycin-inactivating activity than the parental CHO cell (BLMS), using an assay for DNA degradation to measure active drug. A hybrid clone, CBH-1, derived from a BLMR × BLMS cell fusion, was as resistant to bleomycin-A2 as was BLMR-1; it also contained increased bleomycin-inactivating activity comparable to that in BLMR-1 cells. Bleomycin-hydrolase activity of these cell lines was compared in cell-free extracts by assaying the conversion of bleomycin into its deamidated form. The specific activities of bleomycin hydrolase in the BLMR clones were shown to be 2–3 fold higher than that in CHO cells.

MALDI−MS-Based High-Throughput Metabolite Analysis for Intracellular Metabolic Dynamics

In the present study, a high-throughput analytical method for intracellular metabolites using MALDI-MS has been developed. As an analytical tool, the quantitative performance and dynamic range of MALDI-TOF-MS was confirmed to be suitable for characterizing the trends of intracellular metabolism. The technique was tested by investigating the intracellular metabolism of Escherichia coli by analyzing whole cell samples taken consecutively before and after a perturbation of the environmental carbon source. As the result, dramatic changes of metabolite concentrations responding to the perturbation were observed. The whole analysis process (i.e., sample preparation and MALDI-MS analysis for 24 time points in triplicate) was completed within 4 hours. MALDI-FTICR-MS was used to identify the elemental compositions of detected metabolites to support the reliability of the MALDI-MS-based analysis. The MALDI-MS-based analytical method developed herein should be suitable for high-throughput analysis of dynamic intracellular metabolism events.

Human ovarian cancer cell lines resistant to cisplatin, doxorubicin, and l-phenylalanine mustard are sensitive to Δ7-prostaglandin Δ1 and Δ12-prostaglandin J2

Abstract The antitumor activity of Δ 7 -prostaglandin A 1 (Δ 7 -PGA 1 ) or Δ 12 -prostaglandin J 2 (Δ 7 -PGJ 2 ) on human ovarian cancer cell lines resistant to cisplatin (CDDP), doxorubicin (ADR), and l-phenylalanine mustard (1-PAM) was studied in vitro . A2780 AD , A2780 (parent cells of A2780 AD ), 2008DDP, and 2008 cells (parent cells of 2008DDP) were used. The antitumor activities of the drugs were defined with 50% inhibitory concentration (IC50) estimated from growth inhibition curves, which were obtained by an indirect colorimetric method. Drug-resistance ratios obtained from IC50 values, by comparing A2780 AD and A2780 cells, were 62.5 for ADR, 4.6 for CDDP, 4.9 for 1-PAM, 1.5 for Δ 7 -PGA 1 , and 1.8 for Δ 7 -PGJ 2 . Those obtained by comparing 2008DDP and 2008 cells were 1.1 for ADR, 16.0 for CDDP, 2.9 for 1-PAM, 2.3 for Δ 7 -PGA 1 , and 3.2 for Δ 7 -PGJ 2 . Thus some human ovarian cancer cells resistant to ADR, CDDP, and 1-PAM remain sensitive to antitumor PGs.

Cell-specific localization of alkaloids in Catharanthus roseus stem tissue measured with Imaging MS and Single-cell MS

Significance Terpenoid indole alkaloids are known to be valuable bioactive compounds. In situ RNA hybridization of gene expression of the terpenoid indole alkaloid (TIA) synthetic enzymes has suggested that the TIA metabolic pathway in Catharanthus roseus stem tissue involves the successive metabolic flow of four types of cells: internal phloem-associated parenchyma, epidermal, idioblast, and laticifer cells. It has never been directly determined in which of these cells these TIA intermediates are localized. The present study showed, using both Imaging mass spectrometry (MS) and Single-cell MS, that many kinds of TIA intermediates, including catharanthine and serpentine, were accumulated in idioblast and laticifer cells. The developed methods should prove useful for studying other aspects of secondary metabolism in plants. Catharanthus roseus (L.) G. Don is a medicinal plant well known for producing antitumor drugs such as vinblastine and vincristine, which are classified as terpenoid indole alkaloids (TIAs). The TIA metabolic pathway in C. roseus has been extensively studied. However, the localization of TIA intermediates at the cellular level has not been demonstrated directly. In the present study, the metabolic pathway of TIA in C. roseus was studied with two forefront metabolomic techniques, that is, Imaging mass spectrometry (MS) and live Single-cell MS, to elucidate cell-specific TIA localization in the stem tissue. Imaging MS indicated that most TIAs localize in the idioblast and laticifer cells, which emit blue fluorescence under UV excitation. Single-cell MS was applied to four different kinds of cells [idioblast (specialized parenchyma cell), laticifer, parenchyma, and epidermal cells] in the stem longitudinal section. Principal component analysis of Imaging MS and Single-cell MS spectra of these cells showed that similar alkaloids accumulate in both idioblast cell and laticifer cell. From MS/MS analysis of Single-cell MS spectra, catharanthine, ajmalicine, and strictosidine were found in both cell types in C. roseus stem tissue, where serpentine was also accumulated. Based on these data, we discuss the significance of TIA synthesis and accumulation in the idioblast and laticifer cells of C. roseus stem tissue.

In Vitro Selection of DNA Aptamers on Chips Using a Method for Generating Point Mutations

Abstract We successfully developed a novel selection method for the acquisition of DNA aptamers that selectively recognize resorufin using on‐chip selection in combination with method for point mutations. This method proved efficient for selection for DNA aptamers of single‐stranded oligo‐DNAs. A genetic algorithm was applied to produce oligonucleotides for the combinatorial library. A fluorescent molecule, resorufin, was applied for the ligand selection as a target. The binding affinity of the library was analyzed by the DNA chip. This selection method of DNA ligands includes on‐chip selection and point‐mutated sequence, which the highest affinity was selected. The fluorescence intensity of the library on the DNA chip increased after three repetitions of the selection round. The average of response for the affinity test increased with each generation.

Development and Application of a High-Resolution Imaging Mass Spectrometer for the Study of Plant Tissues

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) or imaging mass spectrometry (imaging MS) has been a powerful tool to map the spatial distribution of molecules on the surface of biological materials. This technique has frequently been applied to animal tissue slices for the purpose of mapping proteins, peptides, lipids, sugars or small metabolites to find disease-specific biomarkers or to study drug metabolism. Recently, it has also been applied to intact plant tissues or thin slices thereof using commercial mass spectrometers. The present work is concerned with the refinement of MALDI/laser desorption/ionization (LDI)-Fourier transform ion cyclotron resonance (FTICR)-MS incorporating certain specific features namely, ultra-high mass resolution (>100,000), ultra-high molecular mass accuracy (<1 p.p.m.) and high spatial resolution (<10 µm) for imaging MS of plant tissues. Employing an in-house built mass spectrometer, the imaging MS analysis of intact Arabidopsis thaliana tissues, namely etiolated seedlings and roots of seedlings, glued to a small transparent ITO (indium tin oxide)-coated conductive glass was performed. A matrix substance was applied to the vacuum-dried intact tissues by sublimation prior to the imaging MS analysis. The images of various small metabolites representing their two-dimensional distribution on the dried intact tissues were obtained with or without different matrix substances. The effects of MALDI matrices on the ionization of small metabolites during imaging MS acquisition are discussed.

Power of isotopic fine structure for unambiguous determination of metabolite elemental compositions: In silico evaluation and metabolomic application

In mass spectrometry (MS)-based metabolomics studies, reference-free identification of metabolites is still a challenging issue. Previously, we demonstrated that the elemental composition (EC) of metabolites could be unambiguously determined using isotopic fine structure, observed by ultrahigh resolution MS, which provided the relative isotopic abundance (RIA) of (13)C, (15)N, (18)O, and (34)S. Herein, we evaluated the efficacy of the RIA for determining ECs based on the MS peaks of 20,258 known metabolites. The metabolites were simulated with a ≤25% error in the isotopic peak area to investigate how the error size effect affected the rate of unambiguous determination of the ECs. The simulation indicated that, in combination with reported constraint rules, the RIA led to unambiguous determination of the ECs for more than 90% of the tested metabolites. It was noteworthy that, in positive ion mode, the process could distinguish alkali metal-adduct ions ([M+Na](+) and [M+K](+)). However, a significant degradation of the EC determination performance was observed when the method was applied to real metabolomic data (mouse liver extracts analyzed by infusion ESI), because of the influence of noise and bias on the RIA. To achieve ideal performance, as indicated in the simulation, we developed an additional method to compensate for bias on the measured ion intensities. The method improved the performance of the calculation, permitting determination of ECs for 72% of the observed peaks. The proposed method is considered a useful starting point for high-throughput identification of metabolites in metabolomic research.

Automated detection and matching of spots in autoradiogram images of two-dimensional electrophoresis for high-speed genome scanning

Presents a pattern analysis scheme of autoradiogram images obtained with 2-D (two-dimensional) gel electrophoresis based on the RLGS (restriction landmark genome scanning) method for the purpose of high-speed genome scanning. By this means several thousands of spots are observed as signals; each spot corresponds to a genetic locus and its intensity reflects the copy number of the restriction landmark. The essential problems of image processing for automated analysis are to detect the location of each spot and to measure its intensity. Some kinds of operator including the gradient and ring operators are used for solving the problem. Then the matching and comparison of the RLGS patterns are also important to analyze the differential state. This is solved by using the Delaunay net and relative neighbourhood graphs. Some experimental results indicate that the authors method is effective enough to construct an automated analysis system of RLGS patterns and genetic mapping.