Shingo Suzuki

RIKEN, Вако, Saitama, Japan

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Publications (19)71.01 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: Laboratory evolution provides phenotype-genotype mappings and quantitative analysis of selective pressures, giving important insights about evolutionary dynamics. Moreover, parallel laboratory evolution clarifies which phenotypic and genotypic changes are inevitable for adaptive evolution. Such parallel experiments, however, remain labor-intensive. In this study, to facilitate massive parallel laboratory evolution, we developed an automated culture system that can maintain hundreds of independent culture series in exponential growth phase under various culture conditions. We demonstrate the performance of this automated culture system using the laboratory evolution of Escherichia coli under various stressors.
    Journal of the Association for Laboratory Automation 02/2014; · 1.46 Impact Factor
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    ABSTRACT: Chloroplasts originated from cyanobacteria through endosymbiosis. The original cyanobacterial endosymbiont evolved to adapt to the biochemically rich intracellular environment of the host cell while maintaining its photosynthetic function; however, no such process has been experimentally demonstrated. Here, we show the adaptation of a model cyanobacterium, Synechocystis sp. PCC 6803, to a biochemically rich environment by experimental evolution. Synechocystis sp. PCC 6803 does not grow in a biochemically rich, chemically defined medium because several amino acids are toxic to the cells at approximately 1 mM. We cultured the cyanobacteria in media with the toxic amino acids at 0.1 mM, then serially transferred the culture, gradually increasing the concentration of the toxic amino acids. The cells evolved to show approximately the same specific growth rate in media with 0 and 1 mM of the toxic amino acid in approximately 84 generations and evolved to grow faster in the media with 1 mM than in the media with 0 mM in approximately 181 generations. We did not detect a statistically significant decrease in the autotrophic growth of the evolved strain in an inorganic medium, indicating the maintenance of the photosynthetic function. Whole-genome resequencing revealed changes in the genes related to the cell membrane and the carboxysome. Moreover, we quantitatively analyzed the evolutionary changes by using simple mathematical models, which evaluated the evolution as an increase in the half-maximal inhibitory concentration (IC50) and estimated quantitative characteristics of the evolutionary process. Our results clearly demonstrate not only the potential of a model cyanobacterium to adapt to a biochemically rich environment without a significant decrease in photosynthetic function but also the properties of its evolutionary process, which sheds light of the evolution of chloroplasts at the initial stage.
    PLoS ONE 01/2014; 9(5):e98337. · 3.53 Impact Factor
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    ABSTRACT: Although many mutations contributing to antibiotic resistance have been identified, the relationship between the mutations and the related phenotypic changes responsible for the resistance has yet to be fully elucidated. To better characterize phenotype-genotype mapping for drug resistance, here we analyse phenotypic and genotypic changes of antibiotic-resistant Escherichia coli strains obtained by laboratory evolution. We demonstrate that the resistances can be quantitatively predicted by the expression changes of a small number of genes. Several candidate mutations contributing to the resistances are identified, while phenotype-genotype mapping is suggested to be complex and includes various mutations that cause similar phenotypic changes. The integration of transcriptome and genome data enables us to extract essential phenotypic changes for drug resistances.
    Nature Communications 01/2014; 5:5792. · 10.74 Impact Factor
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    ABSTRACT: The microbial coculture of multiple cell populations is used to study community evolution and for bioengineering applications. The cells in coculture undergo dynamic changes because of cell-cell and cell-environment interactions. Transcriptome analysis allows us to study the molecular basis of these changes in cell physiology. For transcriptome analysis, it is essential that the cell populations in the coculture are harvested separately. Here, we describe a method for transcriptome analysis of a microbial coculture in which two different cell populations are separated by a porous membrane.
    Methods in molecular biology (Clifton, N.J.) 01/2014; 1151:151-64. · 1.29 Impact Factor
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    ABSTRACT: Mutualism is ubiquitous in nature but is known to be intrinsically vulnerable with regard to both population dynamics and evolution. Synthetic ecology has indicated that it is feasible for organisms to establish novel mutualism merely through encountering each other by showing that it is feasible to construct synthetic mutualism between organisms. However, bacteria-eukaryote mutualism, which is ecologically important, has not yet been constructed. In this study, we synthetically constructed mutualism between a bacterium and a eukaryote by using two model organisms. We mixed a bacterium, Escherichia coli (a genetically engineered glutamine auxotroph), and an amoeba, Dictyostelium discoideum, in 14 sets of conditions in which each species could not grow in monoculture but potentially could grow in coculture. Under a single condition in which the bacterium and amoeba mutually compensated for the lack of required nutrients (lipoic acid and glutamine, respectively), both species grew continuously through several subcultures, essentially establishing mutualism. Our results shed light on the establishment of bacteria-eukaryote mutualism and indicate that a bacterium and eukaryote pair in nature also has a non-negligible possibility of establishing novel mutualism if the organisms are potentially mutualistic.
    Bio Systems 05/2013; · 1.27 Impact Factor
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    ABSTRACT: High-density DNA microarrays are useful tools for analyzing sequence changes in DNA samples. Although microarray analysis provides informative signals from a large number of probes, the analysis and interpretation of these signals have certain inherent limitations, namely, complex dependency of signals on the probe sequences and the existence of false signals arising from non-specific binding between probe and target. In this study, we have developed a novel algorithm to detect the single-base substitutions by using microarray data based on a thermodynamic model of hybridization. We modified the thermodynamic model by introducing a penalty for mismatches that represent the effects of substitutions on hybridization affinity. This penalty results in significantly higher detection accuracy than other methods, indicating that the incorporation of hybridization free energy can improve the analysis of sequence variants by using microarray data.
    PLoS ONE 01/2013; 8(1):e54571. · 3.53 Impact Factor
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    ABSTRACT: Stochastic switching is considered as a cost-saving strategy for adaptation to environmental challenges. We show here that stochastic switching of a monostable circuit can mediate the adaptation of the engineered OSU12-hisC Escherichia coli strain to histidine starvation. In this strain, the hisC gene was deleted from the His operon and placed under the control of a monostable foreign promoter. In response to histidine depletion, the OSU12-hisC population shifted to a higher HisC expression level, which is beneficial under starving conditions but is not favoured by the monostable circuit. The population shift was accompanied by growth recovery and was reversible upon histidine addition. A weak directionality in stochastic switching of hisC was observed in growing microcolonies under histidine-free conditions. Directionality and fate decision were in part dependent on the initial cellular status. Finally, microarray analysis indicated that OSU12-hisC reorganized its transcriptome to reach the appropriate physiological state upon starvation. These findings suggest that bacteria do not necessarily need to evolve signalling mechanisms to control gene expression appropriately, even for essential genes.
    Molecular Systems Biology 05/2011; 7:493. · 11.34 Impact Factor
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    ABSTRACT: To understand how two organisms that have not previously been in contact can establish mutualism, it is first necessary to examine temporal changes in their phenotypes during the establishment of mutualism. Instead of tracing back the history of known, well-established, natural mutualisms, we experimentally simulated the development of mutualism using two genetically-engineered auxotrophic strains of Escherichia coli, which mimic two organisms that have never met before but later establish mutualism. In the development of this synthetic mutualism, one strain, approximately 10 hours after meeting the partner strain, started oversupplying a metabolite essential for the partner's growth, eventually leading to the successive growth of both strains. This cooperative phenotype adaptively appeared only after encountering the partner strain but before the growth of the strain itself. By transcriptome analysis, we found that the cooperative phenotype of the strain was not accompanied by the local activation of the biosynthesis and transport of the oversupplied metabolite but rather by the global activation of anabolic metabolism. This study demonstrates that an organism has the potential to adapt its phenotype after the first encounter with another organism to establish mutualism before its extinction. As diverse organisms inevitably encounter each other in nature, this potential would play an important role in the establishment of a nascent mutualism in nature.
    PLoS ONE 01/2011; 6(2):e17105. · 3.53 Impact Factor
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    ABSTRACT: Next-generation sequencing technologies enable the rapid cost-effective production of sequence data. To evaluate the performance of these sequencing technologies, investigation of the quality of sequence reads obtained from these methods is important. In this study, we analyzed the quality of sequence reads and SNP detection performance using three commercially available next-generation sequencers, i.e., Roche Genome Sequencer FLX System (FLX), Illumina Genome Analyzer (GA), and Applied Biosystems SOLiD system (SOLiD). A common genomic DNA sample obtained from Escherichia coli strain DH1 was applied to these sequencers. The obtained sequence reads were aligned to the complete genome sequence of E. coli DH1, to evaluate the accuracy and sequence bias of these sequence methods. We found that the fraction of "junk" data, which could not be aligned to the reference genome, was largest in the data set of SOLiD, in which about half of reads could not be aligned. Among data sets after alignment to the reference, sequence accuracy was poorest in GA data sets, suggesting relatively low fidelity of the elongation reaction in the GA method. Furthermore, by aligning the sequence reads to the E. coli strain W3110, we screened sequence differences between two E. coli strains using data sets of three different next-generation platforms. The results revealed that the detected sequence differences were similar among these three methods, while the sequence coverage required for the detection was significantly small in the FLX data set. These results provided valuable information on the quality of short sequence reads and the performance of SNP detection in three next-generation sequencing platforms.
    PLoS ONE 01/2011; 6(5):e19534. · 3.53 Impact Factor
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    ABSTRACT: Predator-prey interactions have been found at all levels within ecosystems. Despite their ecological ubiquity and importance, the process of transition to a stable coexistent state has been poorly verified experimentally. To investigate the stabilization process of predator-prey interactions, we previously constructed a reproducible experimental predator-prey system between Dictyostelium discoideum and Escherichia coli, and showed that the phenotypically changed E. coli contributed to stabilization of the system. In the present study, we focused on the transition to stable coexistence of both species after the phenotypic change in E. coli. Analysis of E. coli cells isolated from co-culture plates as single colony enabled us to readily identify the appearance of phenotypically changed E. coli that differed in colony morphology and growth rate. It was also demonstrated that two types of viscous colony, i.e., the dense-type and sparse-type, differing in spatial distribution of both species emerged probabilistically and all of the viscous colonies maintained stably were of the sparse-type. These results suggest that the phenotypically changed E. coli may produce two types of viscous colonies probabilistically. The difference in spatial distribution would affect localized interactions between both species and then cause probabilistic stabilization of predator-prey interactions.
    Bio Systems 11/2010; 103(3):342-7. · 1.27 Impact Factor
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    ABSTRACT: Understanding ethanol tolerance in microorganisms is important for the improvement of bioethanol production. Hence, we performed parallel-evolution experiments using Escherichia coli cells under ethanol stress to determine the phenotypic changes necessary for ethanol tolerance. After cultivation of 1,000 generations under 5% ethanol stress, we obtained 6 ethanol-tolerant strains that showed an approximately 2-fold increase in their specific growth rate in comparison with their ancestor. Expression analysis using microarrays revealed that common expression changes occurred during the adaptive evolution to the ethanol stress environment. Biosynthetic pathways of amino acids, including tryptophan, histidine, and branched-chain amino acids, were commonly up-regulated in the tolerant strains, suggesting that activating these pathways is involved in the development of ethanol tolerance. In support of this hypothesis, supplementation of isoleucine, tryptophan, and histidine to the culture medium increased the specific growth rate under ethanol stress. Furthermore, genes related to iron ion metabolism were commonly up-regulated in the tolerant strains, which suggests the change in intracellular redox state during adaptive evolution. The common phenotypic changes in the ethanol-tolerant strains we identified could provide a fundamental basis for designing ethanol-tolerant strains for industrial purposes.
    BMC Genomics 10/2010; 11:579. · 4.40 Impact Factor
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    ABSTRACT: It remains to be determined experimentally whether increasing fitness is related to positive selection, while stationary fitness is related to neutral evolution. Long-term laboratory evolution in Escherichia coli was performed under conditions of thermal stress under defined laboratory conditions. The complete cell growth data showed common continuous fitness recovery to every 2°C or 4°C stepwise temperature upshift, finally resulting in an evolved E. coli strain with an improved upper temperature limit as high as 45.9°C after 523 days of serial transfer, equivalent to 7,560 generations, in minimal medium. Two-phase fitness dynamics, a rapid growth recovery phase followed by a gradual increasing growth phase, was clearly observed at diverse temperatures throughout the entire evolutionary process. Whole-genome sequence analysis revealed the transition from positive to neutral in mutation fixation, accompanied with a considerable escalation of spontaneous substitution rate in the late fitness recovery phase. It suggested that continually increasing fitness not always resulted in the reduction of genetic diversity due to the sequential takeovers by fit mutants, but caused the accumulation of a considerable number of mutations that facilitated the neutral evolution.
    PLoS Genetics 01/2010; 6(10):e1001164. · 8.52 Impact Factor
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    ABSTRACT: Escherichia coli and the cellular slime mold Dictyostelium discoideum form stable viscous symbiotic colonies in the laboratory. To examine changes in E. coli gene expression during establishment of this symbiotic relationship, cells of symbiotic co-cultures and monocultures at various time points were subjected to microarrays analysis. Genes changed significantly over time compared to the initial gene expression level were determined as characteristics of GO function categories. The categories that appeared significantly at the same sampling time points between the two cultures were also identified. Up-regulation of genes from several GO categories associated with polysaccharide synthesis, cell wall degradation, and iron acquisition as well as down-regulation of genes from GO categories associated with biosynthesis through starvation response were observed in co-cultures, indicating exchange of molecules between the two organisms. Up-regulation of genes from several GO categories associated with anaerobic respiration and flagella biosynthesis were also observed, indicating that the environment inside symbiotic colonies was similar to that in developed biofilms. Up-regulation of genes associated with energy-generating systems indicated that E. coli prolonged survival within the symbiotic colony. Thus, E. coli showed not only molecule exchange but also altered expression of various genes in symbiosis with D. discoideum.
    Bio Systems 06/2009; 96(2):141-64. · 1.27 Impact Factor
  • Journal of Bioscience and Bioengineering - J BIOSCI BIOENG. 01/2009; 108.
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    ABSTRACT: High-density DNA microarrays provide us with useful tools for analyzing DNA and RNA comprehensively. However, the background signal caused by the non-specific binding (NSB) between probe and target makes it difficult to obtain accurate measurements. To remove the background signal, there is a set of background probes on Affymetrix Exon arrays to represent the amount of non-specific signals, and an accurate estimation of non-specific signals using these background probes is desirable for improvement of microarray analyses. We developed a thermodynamic model of NSB on short nucleotide microarrays in which the NSBs are modeled by duplex formation of probes and multiple hypothetical targets. We fitted the observed signal intensities of the background probes with those expected by the model to obtain the model parameters. As a result, we found that the presented model can improve the accuracy of prediction of non-specific signals in comparison with previously proposed methods. This result will provide a useful method to correct for the background signal in oligonucleotide microarray analysis. The software is implemented in the R language and can be downloaded from our website (http://www-shimizu.ist.osaka-u.ac.jp/shimizu_lab/MSNS/).
    Bioinformatics 11/2008; 25(1):36-41. · 5.47 Impact Factor
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    ABSTRACT: High-density DNA microarrays provide useful tools to analyze gene expression comprehensively. However, it is still difficult to obtain accurate expression levels from the observed microarray data because the signal intensity is affected by complicated factors involving probe-target hybridization, such as non-linear behavior of hybridization, non-specific hybridization, and folding of probe and target oligonucleotides. Various methods for microarray data analysis have been proposed to address this problem. In our previous report, we presented a benchmark analysis of probe-target hybridization using artificially synthesized oligonucleotides as targets, in which the effect of non-specific hybridization was negligible. The results showed that the preceding models explained the behavior of probe-target hybridization only within a narrow range of target concentrations. More accurate models are required for quantitative expression analysis. The experiments showed that finiteness of both probe and target molecules should be considered to explain the hybridization behavior. In this article, we present an extension of the Langmuir model that reproduces the experimental results consistently. In this model, we introduced the effects of secondary structure formation, and dissociation of the probe-target duplex during washing after hybridization. The results will provide useful methods for the understanding and analysis of microarray experiments. The method was implemented for the R software and can be downloaded from our website (http://www-shimizu.ist.osaka-u.ac.jp/shimizu_lab/FHarray/).
    Bioinformatics 06/2008; 24(10):1278-85. · 5.47 Impact Factor
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    ABSTRACT: High-density DNA microarrays provide useful tools to analyze gene expression comprehensively. However, it is still difficult to obtain accurate expression levels from the observed microarray data because the signal intensity is affected by complicated factors involving probe---target hybridization, such as nonlinear behavior of hybridization, nonspecific hybridization, and folding of probe and target oligonucleotides. Various methods for microarray data analysis have been proposed to address this problem. In our previous report [7], we presented a benchmark analysis of probe---target hybridization using artificially synthesized oligonucleotides as targets, in which effect of nonspecific hybridization was negligible. The results showed that the preceding models explained the behavior of probe---target hybridization only within a narrow range of target concentrations. The experiments showed that finiteness of both probe and target molecules should be considered to understand detail behavior of hybridization. In this paper, we present an extension of the Langmuir-model that reproduces the experimental results consistently and the 3-base nearest neighbor model to improve prediction accuracy. We also introduced effects of secondary structure formation, and dissociation of the probe---target duplex during washing after hybridization. The results will provide useful methods for the understanding and analysis of microarray experiments.
    3d International ICST Conference on Bio-Inspired Models of Network, Information, and Computing Systems; 01/2008
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    ABSTRACT: High-density oligonucleotide arrays are widely used for analysis of genome-wide expression and genetic variation. Affymetrix GeneChips - common high-density oligonucleotide arrays - contain perfect match (PM) and mismatch (MM) probes generated by changing a single nucleotide of the PMs, to estimate cross-hybridization. However, a fraction of MM probes exhibit larger signal intensities than PMs, when the difference in the amount of target specific hybridization between PM and MM probes is smaller than the variance in the amount of cross-hybridization. Thus, pairs of PM and MM probes with greater specificity for single nucleotide mismatches are desirable for accurate analysis. To investigate the specificity for single nucleotide mismatches, we designed a custom array with probes of different length (14- to 25-mer) tethered to the surface of the array and all possible single nucleotide mismatches, and hybridized artificially synthesized 25-mer oligodeoxyribonucleotides as targets in bulk solution to avoid the effects of cross-hybridization. The results indicated the finite availability of target molecules as the probe length increases. Due to this effect, the sequence specificity of the longer probes decreases, and this was also confirmed even under the usual background conditions for transcriptome analysis. Our study suggests that the optimal probe length for specificity is 19-21-mer. This conclusion will assist in improvement of microarray design for both transcriptome analysis and mutation screening.
    BMC Genomics 02/2007; 8:373. · 4.40 Impact Factor
  • Biophysics. 01/2007; 3:47-56.

Publication Stats

161 Citations
71.01 Total Impact Points

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Institutions

  • 2013–2014
    • RIKEN
      • Quantitative Biology Center (QBiC)
      Вако, Saitama, Japan
    • Nara Institute of Science and Technology
      • Graduate School of Information Science
      Ikoma, Nara, Japan
  • 2007–2013
    • Osaka University
      • • Department of Bioinformatic Engineering
      • • Graduate School of Information Science and Technology
      Suita, Osaka-fu, Japan
  • 2010
    • Toho University
      • Faculty of Science
      Tokyo, Tokyo-to, Japan