Shingo Suzuki

RIKEN, Вако, Saitama, Japan

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Publications (24)90.03 Total impact

  • Shingo Suzuki · Takaaki Horinouchi · Chikara Furusawa
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    ABSTRACT: Background: the acquisition of antibiotic resistance in bacterial cells is often accompanied with a reduction of fitness in the absence of antibiotics, known as the "fitness cost". The magnitude of this fitness cost is an important biological parameter that influences the degree to which antibiotic resistant strains become widespread. However, the relationship between the fitness cost and comprehensive phenotypic and genotypic changes remains unclear. Here, we quantified the fitness cost of resistant strains obtained by experimental evolution in the presence of various antibiotics, and analyzed how the cost correlated to phenotypic and genotypic changes in the resistant strains. Results: we measured the specific growth rate of the resistant strains in the presence of various concentrations of drugs or in their absence. In the absence of drugs, the resistant strains showed reductions of approximately 20% to 50% in growth rate compared with the parent strain, which corresponded to the fitness cost. We found that the decrease of the specific growth rate was correlated with overall expression changes between the parent and resistant strains, measured by the Euclid distance between expression profiles. We also found that there are a number of genes whose changes in expression levels were significantly correlated with the growth rate, which may account for the observed correlation between the fitness cost and overall expression changes. Conclusions: our analysis provides a basis for quantitative understanding of the mechanism of the fitness cost. This understanding may provide clues on how to influence the fitness cost that accompanies resistance acquisition and consequently how to limit the spread of antibiotic resistant strains.
    No preview · Article · Dec 2015 · Molecular BioSystems
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    ABSTRACT: Background: Evolution optimizes a living system at both the genome and transcriptome levels. Few studies have investigated transcriptome evolution, whereas many studies have explored genome evolution in experimentally evolved cells. However, a comprehensive understanding of evolutionary mechanisms requires knowledge of how evolution shapes gene expression. Here, we analyzed Escherichia coli strains acquired during long-term thermal adaptive evolution. Results: Evolved and ancestor Escherichia coli cells were exponentially grown under normal and high temperatures for subsequent transcriptome analysis. We found that both the ancestor and evolved cells had comparable magnitudes of transcriptional change in response to heat shock, although the evolutionary progression of their expression patterns during exponential growth was different at either normal or high temperatures. We also identified inverse transcriptional changes that were mediated by differences in growth temperatures and genotypes, as well as negative epistasis between genotype-and heat shock-induced transcriptional changes. Principal component analysis revealed that transcriptome evolution neither approached the responsive state at the high temperature nor returned to the steady state at the regular temperature. We propose that the molecular mechanisms of thermal adaptive evolution involve the optimization of steady-state transcriptomes at high temperatures without disturbing the heat shock response. Conclusions: Our results suggest that transcriptome evolution works to maintain steady-state gene expression during constrained differentiation at various evolutionary stages, while also maintaining responsiveness to environmental stimuli and transcriptome homeostasis.
    Full-text · Article · Oct 2015 · BMC Genomics
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    ABSTRACT: Bacterial cells have a remarkable ability to adapt to environmental changes, a phenomenon known as adaptive evolution. During adaptive evolution, phenotype and genotype dynamically changes; however, the relationship between these changes and associated constraints is yet to be fully elucidated. In this study, we analyzed phenotypic and genotypic changes in Escherichia coli cells during adaptive evolution to ethanol stress. Phenotypic changes were quantified by transcriptome and metabolome analyses and were similar among independently evolved ethanol tolerant populations, which indicate the existence of evolutionary constraints in the dynamics of adaptive evolution. Furthermore, the contribution of identified mutations in one of the tolerant strains was evaluated using site-directed mutagenesis. The result demonstrated that the introduction of all identified mutations cannot fully explain the observed tolerance in the tolerant strain. The results demonstrated that the convergence of adaptive phenotypic changes and diverse genotypic changes, which suggested that the phenotype-genotype mapping is complex. The integration of transcriptome and genome data provides a quantitative understanding of evolutionary constraints.
    Full-text · Article · Sep 2015 · BMC Evolutionary Biology
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    ABSTRACT: The molecular clock of neutral mutations, which represents linear mutation fixation over generations, is theoretically explained by genetic drift in fitness-steady evolution or hitchhiking in adaptive evolution. The present study is the first experimental demonstration for the molecular clock of neutral mutations in a fitness-increasing evolutionary process. The dynamics of genome mutation fixation in the thermal adaptive evolution of Escherichia coli were evaluated in a prolonged evolution experiment in duplicated lineages. The cells from the continuously fitness-increasing evolutionary process were subjected to genome sequencing and analyzed at both the population and single-colony levels. Although the dynamics of genome mutation fixation were complicated by the combination of the stochastic appearance of adaptive mutations and clonal interference, the mutation fixation in the population was simply linear over generations. Each genome in the population accumulated 1.6 synonymous and 3.1 non-synonymous neutral mutations, on average, by the spontaneous mutation accumulation rate, while only a single genome in the population occasionally acquired an adaptive mutation. The neutral mutations that preexisted on the single genome hitchhiked on the domination of the adaptive mutation. The successive fixation processes of the 128 mutations demonstrated that hitchhiking and not genetic drift were responsible for the coincidence of the spontaneous mutation accumulation rate in the genome with the fixation rate of neutral mutations in the population. The molecular clock of neutral mutations to the fitness-increasing evolution suggests that the numerous neutral mutations observed in molecular phylogenetic trees may not always have been fixed in fitness-steady evolution but in adaptive evolution.
    Full-text · Article · Jul 2015 · PLoS Genetics
  • Shingo Suzuki · Takaaki Horinouchi · Chikara Furusawa
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    ABSTRACT: We analyzed the effect of combinatorial use of antibiotics with a trade-off relationship of resistance, i.e., resistance acquisition to one drug causes susceptibility to the other drug, and vice versa, on the evolution of antibiotic resistance. We demonstrated that this combinatorial use of antibiotics significantly suppressed the acquisition of resistance. Copyright © 2015 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.
    No preview · Article · Mar 2015 · Journal of Bioscience and Bioengineering
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    Shingo Suzuki · Takaaki Horinouchi · Chikara Furusawa
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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.
    Preview · Article · Dec 2014 · Nature Communications
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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.
    Full-text · Article · May 2014 · PLoS ONE
  • Kazufumi Hosoda · Naoaki Ono · Shingo Suzuki · Tetsuya Yomo
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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.
    No preview · Article · May 2014 · Methods in molecular biology (Clifton, N.J.)
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    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.
    No preview · Article · Feb 2014 · Journal of the Association for Laboratory Automation
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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.
    Full-text · Article · May 2013 · Bio Systems
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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.
    Full-text · Article · Jan 2013 · PLoS ONE
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    ABSTRACT: The fundamental mechanisms underlying adaptations can be divided into responsive switching and stochastic switching (Kussell and Leibler, 2005). Responsive switching is generally considered as resulting from evolved regulatory units, such as operons and regulons, which enable immediate adaptation (Jacob and Monod, 1961). However, as cells are subject to a wide range of both genetic and environmental perturbations that damage the specificity or efficiency of regulatory systems (Carroll, 2005; Crombach and Hogeweg, 2008), the limited number of regulatory units that can evolve and remain functional may not be sufficient to completely protect cell populations from the danger of extinction. Whether and how cells are able to survive external perturbations, when the corresponding regulatory units are absent or have been genetically disrupted, is an open question of great importance. Recent studies showed the stochastic switching provided cells a huge potential for sustenance under severe conditions via a so-called ‘bet-hedging' strategy. The experimental evidence was generally based on a bistable genetic structure that fixed stochastically appearing fit state thus limiting further random switching (Kussell and Leibler, 2005; Acar et al, 2008). In contrast to bistable gene expression, monostable gene expression is much more common (Newman et al, 2006) and does not rely on a specific complex genetic architecture. Since a monostable structure has no fixation effect, the fit cells that would appear stochastically tend to return to the original steady state (i.e., unfit state). To achieve a population shift from a maladaptive state (but stable) to an adaptive state (but unstable), a significant increase in fitness (i.e., growth rate) of the fit cells is necessary. Otherwise, the random switching will mask occasionally occurring adaptive transitions and lead to an unchanged population at the stable but maladaptive state. Whether adaptation can be achieved by stochastic switching based on a monostable structure is however an open issue. To address this question, we applied an engineered E. coli strain, OSU12-hisC, carrying a foreign gene circuit encompassing a physiologically functional gene, hisC, replaced from its native chromosomal locus (Figure 1A). Consequently, hisC in OSU12-hisC is no longer responsive to the native regulation (His operon) that senses histidine depletion. Instead, the foreign gene circuit provided a monostable structure for hisC's stochastic switching. The green fluorescent protein (gfpuv5) was co-expressed with hisC for the quantitative evaluation of HisC in single cells. The upstream regulation of TetR, whose expression level was reported by the red fluorescent protein (dsred.T4), was introduced to achieve the inducible GFP (HisC) level. The full induction of TetR by IPTG was applied to avoid any possible upstream noise that caused by the abundance of endogenous LacI. Microscopic observation revealed that the OSU12-hisC cells showed stronger green fluorescence after histidine depletion (Figure 1B), which suggested an increased expression level of hisC. Population analysis using flow cytometry showed that the distributions of both GFP concentration and GFP bias (GFP/RFP ratio) in OSU12-hisC shifted towards a higher level in histidine-free conditions (Figure 1C and D), whereas, the depletion caused only a slight change in distributions of OSU11, a control strain carrying both the same engineered genetic circuit and an intact His operon, including the hisC gene in its native context. Repeated experiments revealed that the increases in both GFP concentration (∼2.1 folds) and GFP bias (∼1.5 folds) due to histidine depletion were highly significant (P<0.005, N=6) in OSU12-hisC. In particular, the increased GFP bias strongly suggested that the change in gene expression occurred specifically in the rewired hisC (i.e., GFP) but not in all genes (e.g., RFP). Furthermore, both the growth recovery accompanied population shift and the stress relaxation triggered restoration were clearly observed. It strongly indicated that the adaptation was mediated by stochastic switching of hisC under the monostable control. Analysis on microcolonies' formation (Figure 4A) showed stochastic behaviour and directionality in individual cells. Variation in cellular GFP level was clearly observed in individual cells. Stochastic switching of hisC was verified according to the random changes in GFP bias along with the cell division under histidine-rich conditions (Figure 4B). On the other hand, the microcolonies formed under the histidine-free conditions tended to the higher level of GFP bias were observed (Figure 4B). The directional tendency favoured the high GFP (HisC) level was evidently detected in the first 2 h after histidine depletion, which resulted in a population shift (Figure 4C). In contrast, the distributions of microcolonies grown in histidine-rich conditions kept steady, due to the randomized directions of stochastic switching (Figure 4C). Further analysis showed that the stochastic fluctuations in the initial state had an important role not only in fate decision (i.e., whether to grow) but also in the directionality of the stochastic switch. Microarray analysis showed the adaptation of OSU12-hisC was resulted from the enhanced expression of the structural genes within the native His operon, along with the transcriptional reorganization of a large number of genes. In summary, in contrast to bistable structures, the monostable structure used here did not fix the phenotype but allowed the cells to decide where to go. Taken together, the findings suggest that bacteria do not necessarily need to evolve signalling mechanisms to control gene expression appropriately, even for essential genes.
    Full-text · Article · May 2011 · Molecular Systems Biology
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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.
    Full-text · Article · May 2011 · PLoS ONE
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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.
    Full-text · Article · Feb 2011 · PLoS ONE
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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.
    No preview · Article · Nov 2010 · Bio Systems
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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.
    Full-text · Article · Oct 2010 · PLoS Genetics
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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.
    Full-text · Article · Oct 2010 · BMC Genomics

  • No preview · Article · Nov 2009 · Journal of Bioscience and Bioengineering
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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.
    No preview · Article · Jun 2009 · Bio Systems
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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/).
    Full-text · Article · Nov 2008 · Bioinformatics

Publication Stats

279 Citations
90.03 Total Impact Points

Institutions

  • 2013-2015
    • RIKEN
      • Quantitative Biology Center (QBiC)
      Вако, Saitama, Japan
  • 2007-2013
    • Osaka University
      • Department of Bioinformatic Engineering
      Suika, Ōsaka, Japan