Akiko Kashiwagi

Ubiquity of log-normal distributions in intra-cellular reaction dynamics

The discovery of two fundamental laws concerning cellular dynamics with recursive growth is reported. Firstly, the chemical abundances measured over many cells were found to obey a log-normal distribution and secondly, the relationship between the average and standard deviation of the abundances was found to be linear. The ubiquity of these laws was explored both theoretically and experimentally. By means of a model with a catalytic reaction network, the laws were shown to exist near a critical state with efficient self-reproduction. Additionally, by measuring distributions of fluorescent proteins in bacteria cells, the ubiquity of log-normal distribution of protein abundances was confirmed. Relevance of these findings to cellular function and biological plasticity is briefly discussed.

Experimental optimization of probe length to increase the sequence specificity of high-density oligonucleotide microarrays

BackgroundHigh-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.ResultsTo 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.ConclusionOur 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.

Cooperative adaptation to establishment of a synthetic bacterial mutualism.

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 partners 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.

An improved physico-chemical model of hybridization on high-density oligonucleotide microarrays

Motivation: 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. Results: 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. Availability: 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/). Contact: furusawa@ist.osaka-u.ac.jp Supplementary information: Supplementary data are available at Bioinformatics online.

Noisy cell growth rate leads to fluctuating protein concentration in bacteria

The present study discusses a prime cause of fluctuating protein concentrations, which play a significant role in generating phenotypic diversity in bacteria. A genetic circuit integrated in a bacterial genome was used to evaluate the cell-to-cell variation in protein concentration. A simple dynamic model, comprising terms for synthesis and dilution, was used to elucidate the contributions of distinct noises to the fluctuation in cell protein concentration. Experimental and theoretical results demonstrated that noise in the rate of increase in cell volume (cell growth rate) serves as a source of extrinsic noise that accounts for dozens of percent of the total noise, whereas intrinsic noise in protein synthesis makes only a moderate contribution to the fluctuation in protein concentration. This suggests that such external noise in the cell growth rate has a global effect on cellular components, resulting in a large fluctuation in protein concentration in bacterial cells.

Ongoing Phenotypic and Genomic Changes in Experimental Coevolution of RNA Bacteriophage Qβ and Escherichia coli

According to the Red Queen hypothesis or arms race dynamics, coevolution drives continuous adaptation and counter-adaptation. Experimental models under simplified environments consisting of bacteria and bacteriophages have been used to analyze the ongoing process of coevolution, but the analysis of both parasites and their hosts in ongoing adaptation and counter-adaptation remained to be performed at the levels of population dynamics and molecular evolution to understand how the phenotypes and genotypes of coevolving parasite–host pairs change through the arms race. Copropagation experiments with Escherichia coli and the lytic RNA bacteriophage Qβ in a spatially unstructured environment revealed coexistence for 54 days (equivalent to 163–165 replication generations of Qβ) and fitness analysis indicated that they were in an arms race. E. coli first adapted by developing partial resistance to infection and later increasing specific growth rate. The phage counter-adapted by improving release efficiency with a change in host specificity and decrease in virulence. Whole-genome analysis indicated that the phage accumulated 7.5 mutations, mainly in the A2 gene, 3.4-fold faster than in Qβ propagated alone. E. coli showed fixation of two mutations (in traQ and csdA) faster than in sole E. coli experimental evolution. These observations suggest that the virus and its host can coexist in an evolutionary arms race, despite a difference in genome mutability (i.e., mutations per genome per replication) of approximately one to three orders of magnitude.

Construction of Escherichia coli gene expression level perturbation collection.

We generated 61 strains of Escherichia coli in which the expression level of a specific single gene can be changed continuously over a physiologically significant range. In each strain, one auxotrophic gene was deleted from its original position and reinserted at a specific position on the chromosome under the control of the tetA promoter. Therefore, the level of expression of the target gene can be controlled easily by altering the concentrations of inducers, e.g., anhydrotetracycline and doxycycline, in the medium. Protein and mRNA levels and changes in proliferation rate were examined in some of the strains in our collection to determine the ability to control the level of target gene expression over a physiologically significant range. These strains will be useful for extracting omics data sets and for the construction of genome-scale mathematical models, because causality between perturbations in gene expression level and their consequences can be clearly determined.

Plasticity of Fitness and Diversification Process During an Experimental Molecular Evolution

Abstract. A simplified experimental evolution encompassing the essence of natural one was designed in an attempt to understand the involved mechanism. In our system, molecular evolution was observed through three serial cycles of consecutive random mutagenesis of the glutamine synthetase gene and chemostat culture of the transformed Escherichia coli cells containing the mutated genes. Selection pressure was imposed solely on the glutamine synthetase gene when varieties of mutant genes compete in an unstructured environment of the chemostat. The molecular phylogeny and population dynamics were deduced from the nucleotide sequences of the genes isolated from each of the chemostat runs. An initial mutant population in each cycle, comprised of diversified closely-related genes, ended up with several varieties of mutants in a state of coexistence. Competition between two mutant genes in the final population of the first cycle ascertained that the observed coexisting state is not an incidental event and that cellular interaction via environmental nutrients is a possible mechanism of coexistence. In addition, the mutant gene once extinct in the previous passage was found to have the capacity to reinvade and constitute the gene pool of the later cycle of molecular evolution. These results, including the kinetic characteristics of the purified wild-type and mutant glutamine synthetases in the phylogenetic tree, revealed that the enzyme activity had diverged, rather than optimized, to a fittest value during the course of evolution. Here, we proposed that the plasticity of gene fitness in consequence of cellular interaction via the environment is an essential mechanism governing molecular evolution.

Fate of a mutant emerging at the initial stage of evolution

A simple system was constructed and used in the experimental elucidation of the fate of a mutant emerging in a population. ThreeEscherichia coli strains having the same genetic background except for their glutamine synthetase gene were used as model competitors. The difference in the enzyme gene were introduced by random mutation. Competition between these bacterial strains was carried out and observed in a continuous liquid culture. In most cases, the competitors stably coexist either in a steady state or in an oscillating state. In addition, the competition between the strains was found to be a deterministic process and not a stochastic one. These results showed that an emerging mutant in a population, be it a closely related one to the original members, can attain a state of stable coexistence even in a homogeneous environment. The ability of each of the emerging mutants to maintain its stable coexistence with the original population gives rise to the accumulation of various mutants in a population. Therefore, evolution starts from gradual accumulation of various mutants in the population, which in turn leads to the diversification of the population. As our experimental system is a minimum model for the various competitions in the natural ecosystem, the observed competitive coexistence is proposed to be a general phenomenon in nature.

Adaptation by stochastic switching of a monostable genetic circuit in Escherichia coli

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.