東京大学 竹内研究室 公式ウェブページ

Active diffusion, i.e., fluctuating dynamics driven by athermal noise is found in various out-of-equilibrium systems. Here we discuss the nature of the active diffusion of tagged monomers in a flexible polymer. A scaling argument based on the notion of tension propagation clarifies how the polymeric effect is reflected in the anomalous diffusion exponent, which may be of relevance to the dynamics of chromosomal loci in living cells. The idea could be applicable to the behavior of polymers in bacterial suspension as well.

Reference:
T. Sakaue and T. Saito, Soft Matter, 2016, DOI: 10.1039/C6SM00775A

Recent advances in single-cell time-lapse microscopy have revealed large phenotypic heterogeneity at the single-cell level in genetically homogeneous cellular populations. It has been often assumed that such phenotypic noise is evolutionary unimportant because phenotypic differences among cells are not encoded on the stable genetic materials, thus non-heritable. However, the evidences are accumulating that many cellular phenotypes have trans-generational "memories", which might drive clonal cellular populations to quickly and efficiently adapt to harsh environments if the heterogeneous phenotypes are correlated with cellular fitness. Using custom microfluidic single-cell measurement devices, we have recently uncovered several biological roles of phenotypic noise at the single-cell level: (1) Heterogeneity in division interval causes clonal proliferation to grow faster than the constituent single cells on average in constant environments, thus a cellular population can grow faster than cells [1]; and (2) noise in the expression level of a survival-correlated gene allows a fraction of cells in the population to survive and persist during antibiotic drug exposures [2]. Also, our ongoing study have revealed that clonal bacterial populations can acclimatize to drug exposures through multi-generational dynamics, which is enabled by some uncharacterized stable intracellular memory not encoded on genome. In this seminar, I will present the overviews of these studies, and discuss the implications of the results for evolution and genetics.

References:
[1] Hashimoto, M. et al. Noise-driven growth rate gain in clonal cellular populations. Proc. Natl. Acad. Sci. 113, 3251–3256 (2016).
[2] Wakamoto, Y. et al. Dynamic persistence of antibiotic-stressed mycobacteria. Science. 339, 91–5 (2013).

※本セミナーは、講演は日本語、スライドは英語でお願いしてあります。
This seminar will be given in Japanese, but slides are in English.

Fluctuation theorems have attracted considerable attention in the context of statistical mechanics and information thermodynamics. Although integral fluctuation theorems are valid in rather general nonequilibrium situations, they cannot apply to absolutely irreversible processes, where the forward-path probability vanishes and the entropy production diverges in terms of detailed fluctuation theorems. We identify the mathematical origin of this inapplicability as the singularity of probability measure. As a result, we generalize conventional integral fluctuation theorems to absolutely irreversible processes. The new equalities give a more stringent constraint to the average of the entropy production than the conventional second-law-like inequality does.

As a notable application of the new fluctuation theorems, we discuss the Gibbs paradox in small thermodynamic systems. The Gibbs paradox originated from gas mixing, and has raised fundamental problems in thermodynamics and statistical mechanics. Among them, we here consider the consistency between thermodynamic and statistical-mechanical entropies. In this context, the Gibbs paradox is resolved based on the requirement of extensivity in macroscopic thermodynamic systems. However, this resolution cannot apply to small thermodynamic systems because extensivity breaks down. We offer a resolution applicable to small thermodynamic systems based on our fluctuation theorems.

Recent in vivo experiments with optical tracking of particles in living biological cells indicate that active forces strongly dominate thermal Brownian forces in the cellular environment, impacting motion of objects from nanometers to microns in scale. As we show [PNAS 112, E3639 (2015)], such non-thermal fluctuating forces can arise from hydrodynamic stirring of the cytoplasm by various protein machines, enzymes and molecular motors that densely populate the cell. Independent of their specific functions, all such macromolecules are repeatedly changing their conformations and act as oscillating stochastic force dipoles. Numerical estimates reveal that hydrodynamic collective effects of active proteins may account for the experimentally observed dramatic diffusion enhancement in the cytoplasm under ATP supply.

In this talk, I will introduce the new, fast-growing, interdisciplinary field of active matter and present some recent important advances.

Active matter is the term now used by physicists to designate out-of-equilibrium systems in which energy is spent in the bulk, locally, to produce persistent motion/displacement. Examples abound, not just within living systems (bird flocks, fish schools, collective motion of cells, etc.) but also, increasingly, in man-made, well-controlled, non-living systems such as micro- and nano-swimmers, active colloids, in vitro mixtures of biofilaments and motor proteins, etc.

I will show some striking experimental/observational examples and then proceed to give an account of our current understanding of some of the simplest active matter models, which consist of self-propelled particles locally aligning their velocities. In this context, the fluid in which the particles move is neglected, and one speaks of "dry active matter". I will argue that these models do have experimental relevance, in addition to being important per se, much as the Ising model is important in statistical mechanics. I will show that a wealth of new physics arises, which calls for further theoretical studies.

In nature the time trace of a signal might be random however its long time average converges to the corresponding ensemble average (ergodicity). We discuss weak ergodicity breaking a framework introduced by Bouchaud, which describes statistical properties of dynamical systems with power law distributed sojourn times. Examples of blinking quantum dots and diffusion of mRNA in the cell are discussed. The basic question is what is the statistical mechanical framework replacing ordinary statistical mechanics, and the consequence in single particle dynamics.

References:
[1] F. D. Stefani, J. P. Hoogenboom, and E. Barkai, Beyond Quantum Jumps: Blinking Nano-scale Light Emitters, Physics Today, 62, nu. 2, p.34 (February 2009)
[2] E. Barkai, Y. Garini and R. Metzler, Strange Kinetics of Single Molecules in the Cell, Physics Today, 65(8), 29 (2012).

第2種超伝導体に垂直磁場を印加すると, 量子化された磁束が渦糸として試料に侵入する。渦糸系は互いに斥力作用を及ぼし合う多粒子系とみなすことができ, 液体, グラス, あるいは格子といった物質に大きく依存しない多彩な相や運動で誘起される相転移－動的相転移－を発現する。近年我々が進めている渦糸系のダイナミクスの研究は, 超伝導分野のみならず, 自然界に広く見られる固体のプラスチックフロー[1], あるいはランダムポテンシャル中を運動する多粒子系の非平衡現象, 新しい動的相転移の探求といった, より普遍的な物理現象の解明にもつながる。セミナーではまず, 超伝導渦糸系の基本的事項の説明からはじめ, 駆動した渦糸系で最近見出した新奇非平衡現象, 動的相転移[2]を紹介する。さらに, 他の物理系で報告されている類似の現象[3]や理論[4]との関連についても触れる。

[1] G.W. Crabtree, Nat. Mater. 2, 435 (2003): S. Okuma, Y. Yamazaki, N. Kokubo, PRB 80, 220501(R) (2009): Y. Kawamura et al., SUST 28, 045002 (2015).
[2] S. Okuma et al., PRB 83, 012503 (2011): New J. Phys. 14, 123021 (2012): PRB 85, 064508 (2012): JPSJ 81, 114718 (2012).
[3] D.J. Pine et al., Nature 438, 997 (2005): K.A. Takeuchi et al., PRL 99, 234503 (2007): PRE 80, 051116 (2009).　
[4] H. Hinrichsen, Adv. Phys. 49, 815 (2000): C. Reichhardt et al., PRL 103, 168301 (2009): PRL 100, 187002 (2008): H. Barghathi, T. Vojta, PRL 109, 170603 (2012).