Reiko Okura
University of Tokyo
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Publication
Featured researches published by Reiko Okura.
Proceedings of the National Academy of Sciences of the United States of America | 2016
Mikihiro Hashimoto; Takashi Nozoe; Hidenori Nakaoka; Reiko Okura; Sayo Akiyoshi; Kunihiko Kaneko; Edo Kussell; Yuichi Wakamoto
Significance Differences between individuals exist even in the absence of genetic differences, e.g., in identical twins. Over the last decade, experiments have shown that even genetically identical microbes exhibit large cell-to-cell differences. In particular, the timing of cell division events is highly variable between single bacterial cells. The effect of this variability on long-term growth and survival of bacteria, however, remains elusive. Here, we present a striking finding showing that a bacterial population grows faster on average than its constituent cells. To explain this counterintuitive result, we present a mathematical model that precisely predicts our measurements. Furthermore, we show an empirical growth law that constrains the maximal growth rate of Escherichia coli. Cellular populations in both nature and the laboratory are composed of phenotypically heterogeneous individuals that compete with each other resulting in complex population dynamics. Predicting population growth characteristics based on knowledge of heterogeneous single-cell dynamics remains challenging. By observing groups of cells for hundreds of generations at single-cell resolution, we reveal that growth noise causes clonal populations of Escherichia coli to double faster than the mean doubling time of their constituent single cells across a broad set of balanced-growth conditions. We show that the population-level growth rate gain as well as age structures of populations and of cell lineages in competition are predictable. Furthermore, we theoretically reveal that the growth rate gain can be linked with the relative entropy of lineage generation time distributions. Unexpectedly, we find an empirical linear relation between the means and the variances of generation times across conditions, which provides a general constraint on maximal growth rates. Together, these results demonstrate a fundamental benefit of noise for population growth, and identify a growth law that sets a “speed limit” for proliferation.
Current Biology | 2016
Maroš Pleška; Long Qian; Reiko Okura; Tobias Bergmiller; Yuichi Wakamoto; Edo Kussell; Călin C. Guet
Restriction-modification (RM) systems represent a minimal and ubiquitous biological system of self/non-self discrimination in prokaryotes [1], which protects hosts from exogenous DNA [2]. The mechanism is based on the balance between methyltransferase (M) and cognate restriction endonuclease (R). M tags endogenous DNA as self by methylating short specific DNA sequences called restriction sites, whereas R recognizes unmethylated restriction sites as non-self and introduces a double-stranded DNA break [3]. Restriction sites are significantly underrepresented in prokaryotic genomes [4-7], suggesting that the discrimination mechanism is imperfect and occasionally leads to autoimmunity due to self-DNA cleavage (self-restriction) [8]. Furthermore, RM systems can promote DNA recombination [9] and contribute to genetic variation in microbial populations, thus facilitating adaptive evolution [10]. However, cleavage of self-DNA by RM systems as elements shaping prokaryotic genomes has not been directly detected, and its cause, frequency, and outcome are unknown. We quantify self-restriction caused by two RM systems of Escherichia coli and find that, in agreement with levels of restriction site avoidance, EcoRI, but not EcoRV, cleaves self-DNA at a measurable rate. Self-restriction is a stochastic process, which temporarily induces the SOS response, and is followed by DNA repair, maintaining cell viability. We find that RM systems with higher restriction efficiency against bacteriophage infections exhibit a higher rate of self-restriction, and that this rate can be further increased by stochastic imbalance between R and M. Our results identify molecular noise in RM systems as a factor shaping prokaryotic genomes.
生物物理 | 2013
Sumire Ono; Reiko Okura; Yuichi Wakamoto
Seibutsu Butsuri | 2013
Sumire Ono; Reiko Okura; Yuichi Wakamoto
Seibutsu Butsuri | 2013
Takashi Nozoe; Reiko Okura; Yuichi Wakamoto
生物物理 | 2012
Sumire Ono; Reiko Okura; Yuichi Wakamoto
Seibutsu Butsuri | 2012
Takashi Nozoe; Reiko Okura; Yuichi Wakamoto
Seibutsu Butsuri | 2012
Sumire Ono; Reiko Okura; Yuichi Wakamoto
Biophysical Journal | 2012
Takashi Nozoe; Reiko Okura; Yuichi Wakamoto
生物物理 | 2011
Mikihiro Hashimoto; Reiko Okura; Yuichi Wakamoto