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Journal articleOuldridge T, 2024,
Is stochastic thermodynamics the key to understanding the energy costs of computation
, Proceedings of the National Academy of Sciences of USA, ISSN: 0027-8424The relationship between the thermodynamic and computational characteristics of dynamical physical systems has been a major theoreticalinterest since at least the 19th century, and has been of increasing practical importance as the energetic cost of digital devices has explodedover the last half century. One of the most important thermodynamic features of real-world computers is that they operate very far fromthermal equilibrium, in finite time, with many quickly (co-)evolving degrees of freedom. Such computers also must almost always obey multiplephysical constraints on how they work. For example, all modern digital computers are periodic processes, governed by a global clock. Anotherexample is that many computers are modular, hierarchical systems, with strong restrictions on the connectivity of their subsystems. Thisproperties hold both for naturally occurring computers, like brains or Eukaryotic cells, as well as digital systems. These features of real-worldcomputers are absent in 20th century analyses of the thermodynamics of computational processes, which focused on quasi-statically slowprocesses. However, the field of stochastic thermodynamics has been developed in the last few decades — and it provides the formal tools foranalyzing systems that have exactly these features of real-world computers. We argue here that these tools, together with other tools currentlybeing developed in stochastic thermodynamics, may help us understand at a far deeper level just how the fundamental physical properties ofdynamic systems are related to the computation that they perform.
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Journal articlePoole W, Ouldridge T, Gopalkrishnan M,
Autonomous learning of generative models with chemical reaction network ensembles
, Journal of the Royal Society Interface, ISSN: 1742-5662Can a micron sized sack of interacting molecules autonomously learn an internalmodel of a complex and fluctuating environment? We draw insights from controltheory, machine learning theory, chemical reaction network theory, and statisticalphysics to develop a general architecture whereby a broad class of chemical systemscan autonomously learn complex distributions. Our construction takes the form ofa chemical implementation of machine learning’s optimization workhorse: gradientdescent on the relative entropy cost function which we demonstrate can be viewedas a form of integral feedback control. We show how this method can be applied tooptimize any detailed balanced chemical reaction network and that the constructionis capable of using hidden units to learn complex distributions.
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Journal articleSmith F, Goetz J, Jurinovic K, et al., 2024,
Strong sequence-dependence in RNA/DNA hybrid strand displacement kinetics
, Nanoscale, Vol: 16, Pages: 17624-17637, ISSN: 2040-3364Strand displacement reactions underlie dynamic nucleic acid nanotechnology. The kinetic and thermodynamic features of DNA-based displacement reactions are well understood and well predicted by current computational models. By contrast, understanding of RNA/DNA hybrid strand displacement kinetics is limited, restricting the design of increasingly complex RNA/DNA hybrid reaction networks with more tightly regulated dynamics. Given the importance of RNA as a diagnostic biomarker, and its critical role in intracellular processes,this shortfall is particularly limiting for the development of strand displacement-based therapeutics and diagnostics. Herein, we characterise 22 RNA/DNA hybrid strand displacement systems, alongside 11 DNA/DNA systems, varying a range of common design parameters including toehold length and branch migration domain length. We observe the differences in stability between RNA-DNA hybrids and DNA-DNA duplexes have large effects on strand displacement rates, with rates for equivalent sequences differing by up to 3 orders of magnitude. Crucially, however, this effect is strongly sequence-dependent, with RNA invaders strongly favoured in a system with RNA strands of high purine content, and disfavoured in a system when the RNA strands have low purine content. These results lay the groundwork for more general design principles, allowing for creation of de novo reaction networks with novel complexity while maintaining predictable reaction kinetics.
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Journal articleLee CF, 2024,
It takes more than forceful leaders
, Nature Physics, Vol: 20, Pages: 1532-1533, ISSN: 1745-2473Migrating cell clusters exhibit finger-like protrusions at the front, attributed to leader cells physically dragging follower cells along. Now, an optogenetics experiment has shown that follower cells must also play a role in protrusion formation.
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Journal articleJentsch P, Lee CF, 2024,
A new universality class describes Vicsek’s flocking phase in physical dimensions
, Physical Review Letters, Vol: 133, ISSN: 0031-9007The Vicsek simulation model of flocking together with its theoretical treatment by Toner and Tuin 1995 were two foundational cornerstones of active matter physics. However, despite the field’stremendous progress, the actual universality class (UC) governing the scaling behavior of Viscek’s“flocking” phase remains elusive. Here, we use nonperturbative, functional renormalization groupmethods to analyze, numerically and analytically, a simplified version of the Toner-Tu model, anduncover a novel UC with scaling exponents that agree remarkably well with the values obtained ina recent simulation study by Mahault et al. [Phys. Rev. Lett. 123, 218001 (2019)], in both two andthree spatial dimensions. We therefore believe that there is strong evidence that the UC uncoveredhere describes Vicsek’s flocking phase.
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Journal articleFallesen T, Amerteifio S, Pruessner G, et al., 2024,
Intermittent cell division dynamics in regenerating Arabidopsis roots reveals complex long-range interactions
, Quantitative Plant Biology, Vol: 5, ISSN: 2632-8828In this work, we present a quantitative comparison of the cell division dynamics between populations of intact and regenerating root tips in the plant model system Arabidopsis thaliana. To achieve the required temporal resolution and to sustain it for the duration of the regeneration process, we adopted a live imaging system based on light-sheet fluorescence microscopy, previously developed in the laboratory. We offer a straightforward quantitative analysis of the temporal and spatial patterns of cell division events showing a statistically significant difference in the frequency of mitotic events and spatial separation of mitotic event clusters between intact and regenerating roots.
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Journal articleMoratto E, Tang Z, Bozkurt T, et al., 2024,
Reduction of Phytophthora palmivora plant root infection in weak electric fields
, Scientific Reports, Vol: 14, ISSN: 2045-2322The global food security crisis is partly caused by significant crop losses due to pests and pathogens, leading to economic burdens. Phytophthora palmivora, an oomycete pathogen, affects many plantation crops and costs over USD 1 billion each year. Unfortunately, there is currently no prevention plan in place, highlighting the urgent need for an effective solution. P. palmivora produces motile zoospores that respond to weak electric fields. Here, we show that external electric fields can be used to reduce root infection in two plant species. We developed two original essays to study the effects of weak electric fields on the interaction between P. palmivora’s zoospores and roots of Arabidopsis thaliana and Medicago truncatula. In the first configuration, a global artificial electric field is set up to induce ionic currents engulfing the plant roots while, in the second configuration, ionic currents are induced only locally and at a distance from the roots. In both cases, we found that weak ionic currents (250–550 μA) are sufficient to reduce zoospore attachment to Arabidopsis and Medicago roots, without affecting plant health. Moreover, we show that the same configurations decrease P. palmivora mycelial growth in Medicago roots after 24 h. We conclude that ionic currents can reduce more than one stage of P. palmivora root infection in hydroponics. Overall, our findings suggest that weak external electric fields can be used as a sustainable strategy for preventing P. palmivora infection, providing innovative prospects for agricultural crop protection.
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Journal articleMukherjee R, Sengar A, Cabello Garcia J, et al., 2024,
Kinetic proofreading can enhance specificity in a non-enzymatic DNA strand displacement network
, Journal of the American Chemical Society, Vol: 146, Pages: 18916-18926, ISSN: 0002-7863Kinetic proofreading is used throughout natural systems to enhance the specificity of molecular recognition. At its most basic level, kinetic proofreading uses a supply of chemical fuel to drive a recognition interaction out of equilibrium, allowing a single free-energy difference between correct and incorrect targets to be exploited two or more times. Despite its importance in biology, there has been little effort to incorporate kinetic proofreading into synthetic systems in which molecular recognition is important, such as nucleic acid nanotechnology. In this article, we introduce a DNA strand displacement-based kinetic proofreading motif, showing that the consumption of a DNA-based fuel can be used to enhance molecular recognition during a templated dimeri zation reaction. We then show that kinetic proofreading can enhance the specificity with which a probe discriminates single nucleo tide mutations, both in terms of the initial rate with which the probe reacts and the long-time behaviour.
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Journal articleEndres R, Matas-Gil A, 2024,
Unraveling biochemical spatial patterns: machine learning approaches to the inverse problem of stationary Turing patterns
, iScience, Vol: 27, ISSN: 2589-0042The diffusion-driven Turing instability is a potential mechanism for spatial pattern formation in numerous biological and chemical systems. However, engineering these patterns and demonstrating that they are produced by this mechanism is challenging. To address this, we aim to solve the inverse problem in artificial and experimental Turing patterns. This task is challenging since patterns are often corrupted by noise and slight changes in initial conditions can lead to different patterns. We used both least squares to explore the problem and physics-informed neural networks to build a noise-robust method. We elucidate the functionality of our network in scenarios mimicking biological noise levels and showcase its application using an experimentally obtained chemical pattern. The findings reveal the significant promise of machine learning in steering the creation of synthetic patterns in bioengineering, thereby advancing our grasp of morphological intricacies within biological systems while acknowledging existing limitations.
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Journal articlePazuki RH, Endres RG, 2024,
Robustness of Turing models and gene regulatory networks with a sweet spot
, Physical review E (statistical, nonlinear, biological, and soft matter physics), Vol: 109, ISSN: 2470-0045Traditional linear stability analysis based on matrix diagonalization is a computationally intensive process for high-dimensional systems of differential equations, posing substantial limitations for the exploration of Turing systems of pattern formation where an additional wave-number parameter needs to be investigated. In this paper, we introduce an efficient and intuitive technique that leverages Gershgorin's theorem to determine upper limits on regions of parameter space and the wave number beyond which Turing instabilities cannot occur. This method offers a streamlined avenue for exploring the phase diagrams of other complex multi-parametric models, such as those found in gene regulatory networks in systems biology. Due to its suitability for the asymptotic limit of infinitely large systems, it predicts the existence of a sweet spot in network size for maximal Jacobian stability.
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Journal articleAnand S, Lee CF, Bertrand T, 2024,
Active jamming at criticality
, Physical Review Research, Vol: 6, ISSN: 2643-1564Jamming is ubiquitous in disordered systems, but the critical behavior of jammed solids subjected to active forces or thermal fluctuations remains elusive. In particular, while passive athermal jamming remains mean-field-like in two and three dimensions, diverse active matter systems exhibit anomalous scaling behavior in all physical dimensions. It is therefore natural to ask whether activity leads to anomalous scaling in jammed systems. Here, we use numerical and analytical methods to study systems of active, soft, frictionless spheres in two dimensions, and elucidate the universal scaling behavior that relates the excess coordination, active forces or temperature, and pressure close to the athermal jammed point. We show that active forces and thermal effects around the critical jammed state can again be captured by a mean-field picture, thus highlighting the distinct and crucial role of amorphous structure in active matter systems.
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Journal articleSalvalaio M, Sena G, 2024,
Long-term root electrotropism reveals habituation and hysteresis
, Plant Physiology, Vol: 194, Pages: 2697-2708, ISSN: 0032-0889Plant roots sense many physical and chemical cues in soil, such as gravity, humidity, light, and chemical gradients, and respond by redirecting their growth toward or away from the source of the stimulus. This process is called tropism. While gravitropism is the tendency to follow the gravitational field downwards, electrotropism is the alignment of growth with external electric fields and the induced ionic currents. Although root tropisms are at the core of their ability to explore large volumes of soil in search of water and nutrients, the molecular and physical mechanisms underlying most of them remain poorly understood. We have previously provided a quantitative characterization of root electrotropism in Arabidopsis (Arabidopsis thaliana) primary roots exposed for 5 h to weak electric fields, showing that auxin asymmetric distribution is not necessary for root electrotropism but that cytokinin biosynthesis is. Here, we extend that study showing that long-term electrotropism is characterized by a complex behavior. We describe overshoot and habituation as key traits of long-term root electrotropism in Arabidopsis and provide quantitative data about the role of past exposures in the response to electric fields (hysteresis). On the molecular side, we show that cytokinin, although necessary for root electrotropism, is not asymmetrically distributed during the bending. Overall, the data presented here represent a step forward toward a better understanding of the complexity of root behavior and provide a quantitative platform for future studies on the molecular mechanisms of electrotropism.
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Journal articleKilleen A, Bertrand T, Lee CF, 2024,
Machine learning topological defects in confluenttissues
, Biophysical Reports, Vol: 4, ISSN: 2667-0747Active nematics is an emerging paradigm for characterizing biological systems. One aspect of particularly intense focus is the role active nematic defects play in these systems, as they have been found to mediate a growing number of biological processes. Accurately detecting and classifying these defects in biological systems is, therefore, of vital importance to improving our understanding of such processes. While robust methods for defect detection exist for systems of elongated constituents, other systems, such as epithelial layers, are not well suited to such methods. Here, we address this problem by developing a convolutional neural network to detect and classify nematic defects in confluent cell layers. Crucially, our method is readily implementable on experimental images of cell layers and is specifically designed to be suitable for cells that are not rod shaped, which we demonstrate by detecting defects on experimental data using the trained model. We show that our machine learning model outperforms current defect detection techniques and that this manifests itself in our method as requiring less data to accurately capture defect properties. This could drastically improve the accuracy of experimental data interpretation while also reducing costs, advancing the study of nematic defects in biological systems.
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Journal articleChen L, Lee CF, Maitra A, et al., 2024,
Dynamics of packed swarms: time-displaced correlators of two dimensional incompressible flocks
, Physical Review E: Statistical, Nonlinear, and Soft Matter Physics, Vol: 109, ISSN: 1539-3755We analytically calculate the scaling exponents of a two-dimensional KPZ-like system: coherentlymoving incompressible polar active fluids. Using three different renormalization group approxima-tion schemes, we obtain values for the “roughness” exponent χ and anisotropy exponent ζ that areextremely near the known exact results. This implies our prediction for the previously completelyunknown dynamic exponent z is likely to be quantitatively accurate.
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Journal articleKilleen A, Bertrand T, Lee CF, 2023,
Modeling growing confluent tissues using a lattice Boltzmann method: interface stability and fluctuations
, Physical Review Research, Vol: 5, ISSN: 2643-1564Tissue growth underpins a wide array of biological and developmental processes, and numerical modeling of growing systems has been shown to be a useful tool for understanding these processes. However, the phenomena that can be captured are often limited by the size of systems that can be modeled. Here, we address this limitation by introducing a lattice Boltzmann method (LBM) for a growing system that is able to efficiently model hydrodynamic length scales. The model incorporates a bounce-back approach to describing the growing front of a tissue, which we use to investigate the dynamics of the interface of growing model tissues. We find that the interface grows with scaling in agreement with the Kardar-Parisi-Zhang (KPZ) universality class when growth in the system is bulk driven. Interestingly, we also find the emergence of a previously unreported hydrodynamic instability when proliferation is restricted to the tissue edge. We then develop an analytical theory to show that the instability arises due to a coupling between the number of cells actively proliferating and the position of the interface.
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Journal articlePlesa T, Dack A, Ouldridge T, 2023,
Integral feedback in synthetic biology: negative-equilibrium catastrophe
, Journal of Mathematical Chemistry, Vol: 61, Pages: 1980-2018, ISSN: 0259-9791A central goal of synthetic biology is the design of molecular controllers that can manipulate the dynamics of intracellular networks in a stable and accurate manner. To address the factthat detailed knowledge about intracellular networks is unavailable, integral-feedback controllers(IFCs) have been put forward for controlling molecular abundances. These controllers can maintainaccuracy in spite of the uncertainties in the controlled networks. However, this desirable feature isachieved only if stability is also maintained. In this paper, we show that molecular IFCs can sufferfrom a hazardous instability called negative-equilibrium catastrophe (NEC), whereby all nonnegative equilibria vanish under the action of the controllers, and some of the molecular abundancesblow up. We show that unimolecular IFCs do not exist due to a NEC. We then derive a familyof bimolecular IFCs that are safeguarded against NECs when uncertain unimolecular networks,with any number of molecular species, are controlled. However, when IFCs are applied on uncertain bimolecular (and hence most intracellular) networks, we show that preventing NECs generallybecomes an intractable problem as the number of interacting molecular species increases. NECstherefore place a fundamental limit to design and control of molecular networks.
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Journal articleMoratto E, Rothery S, Bozkurt TO, et al., 2023,
Enhanced germination and electrotactic behaviour of Phytophthora palmivora zoospores in weak electric fields
, Physical Biology, Vol: 20, Pages: 1-10, ISSN: 1478-3967Soil-dwelling microorganisms use a variety of chemical and physical signals to navigate their environment. Plant roots produce endogenous electric fields which result in characteristic current profiles. Such electrical signatures are hypothesised to be used by pathogens and symbionts to track and colonise plant roots.
The oomycete pathogen Phytophthora palmivora generates motile zoospores which swim towards the positive pole when exposed to an external electric field in vitro.
Here, we provide a quantitative characterization of their electrotactic behaviour in 3D. We found that a weak electric field (0.7 - 1.0 V/cm) is sufficient to induce an accumulation of zoospore at the positive pole, without affecting their encystment rate. We also show that the same external electric field increases the zoospore germination rate and orients the germ tube's growth. We conclude that several early stages of the P. palmivora infection cycle are affected by external electric fields.
Taken together, our results are compatible with the hypothesis that pathogens use plant endogenous electric fields for host targeting.
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Journal articleIllukkumbura R, Hirani N, Borrego-Pinto J, et al., 2023,
Design principles for selective polarization of PAR proteins by cortical flows
, JOURNAL OF CELL BIOLOGY, Vol: 222, ISSN: 0021-9525 -
Journal articleRudzite M, Subramoni S, Endres RG, et al., 2023,
Effectiveness of <i>Pseudomonas aeruginosa</i> type VI secretion system relies on toxin potency and type IV pili-dependent interaction
, PLOS PATHOGENS, Vol: 19, ISSN: 1553-7366 -
Journal articleJentsch P, Lee CF, 2023,
Critical phenomena in compressible polar active fluids: dynamical and functional renormalization group studies
, Physical Review Research, Vol: 5, Pages: 1-24, ISSN: 2643-1564Active matter is not only relevant to living matter and diverse nonequilibrium systems, but also constitutes a fertile ground for novel physics. Indeed, dynamic renormalization group (DRG) analyses have uncovered many new universality classes (UCs) in polar active fluids (PAFs)—an archetype of active matter systems. However, due to the inherent technical difficulties in the DRG methodology, almost all previous studies have been restricted to polar active fluids in the incompressible or infinitely compressible (i.e., Malthusian) limits, and, when the ε expansion was used in conjunction, to the one-loop level. Here, we use functional renormalization group (FRG) methods to overcome some of these difficulties and unveil critical behavior in compressible polar active fluids, and calculate the corresponding critical exponents beyond the one-loop level. Specifically, we investigate the multicritical point of compressible PAFs, where the critical order-disorder transition coincides with critical phase separation. We first study the critical phenomenon using a DRG analysis and find that it is insufficient since two-loop effects are important to obtain a nontrivial correction to the scaling exponents. We then remedy this defect by using a FRG analysis. We find three universality classes and obtain their critical exponents, which we then use to show that at least two of these universality classes are out of equilibrium because they violate the fluctuation-dissipation relation.
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Journal articleQureshi BJ, Juritz J, Poulton JM, et al., 2023,
A universal method for analyzing copolymer growth
, Journal of Chemical Physics, Vol: 158, Pages: 1-22, ISSN: 0021-9606Polymers consisting of more than one type of monomer, known as copolymers,are vital to both living and synthetic systems. Copolymerisation has beenstudied theoretically in a number of contexts, often by considering a Markovprocess in which monomers are added or removed from the growing tip of a longcopolymer. To date, the analysis of the most general models of this class hasnecessitated simulation. We present a general method for analysing suchprocesses without resorting to simulation. Our method can be applied to modelswith an arbitrary network of sub-steps prior to addition or removal of amonomer, including non-equilibrium kinetic proofreading cycles. Moreover, theapproach allows for a dependency of addition and removal reactions on theneighbouring site in the copolymer, and thermodynamically self-consistentmodels in which all steps are assumed to be microscopically reversible. Usingour approach, thermodynamic quantities such as chemical work; kineticquantities such as time taken to grow; and statistical quantities such as thedistribution of monomer types in the growing copolymer can be derived eitheranalytically or numerically directly from the model definition.
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Journal articleMoratto E, Sena G, 2023,
The bioelectricity of plant–biotic interactions
, Bioelectricity, Vol: 5, Pages: 47-54, ISSN: 2576-3105Plants form mutually beneficial or antagonistic interactions with organisms from various kingdoms of life. A clear understanding of the underlying mechanisms is fundamental for crop protection and environmental preservation. Although historically overlooked, the role of plant bioelectricity in initiating and maintaining biotic interactions is recently emerging as an exciting research topic. In this review, we summarize the state-of-the-art regarding the role of plant bioelectricity in biotic interactions focusing on both shoots and roots. We describe how root bioelectricity mediates interactions with pathogens and symbionts from different phyla, and the role played by flower electric fields in pollination.
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Journal articleCairoli A, Spenlehauer A, Overby D, et al., 2023,
Model of inverse bleb growth explains giant vacuole dynamics during cell mechanoadaptation
, PNAS Nexus, Vol: 2, Pages: 1-11, ISSN: 2752-6542Cells can withstand hostile environmental conditions manifest as large mechanical forces such as pressure gradients and/or shear stresses by dynamically changing their shape. Such conditions are realized in the Schlemm’s canal of the eye where endothelial cells that cover the inner vessel wall are subjected to the hydrodynamic pressure gradients exerted by the aqueous humor outflow. These cells form fluid-filled dynamic outpouchings of their basal membrane called giant vacuoles. The inverses of giant vacuoles are reminiscent of cellular blebs, extracellular cytoplasmic protrusions triggered by local temporary disruption of the contractile actomyosin cortex. Inverse blebbing has also been first observed experimentally during sprouting angiogenesis, but its underlying physical mechanisms are poorly understood. Here, we hypothesize that giant vacuole formation can be described as inverse blebbing and formulate a biophysical model of this process. Our model elucidates how cell membrane mechanical properties affect the morphology and dynamics of giant vacuoles and predicts coarsening akin to Ostwald ripening between multiple invaginating vacuoles. Our results are in qualitative agreement with observations from the formation of giant vacuoles during perfusion experiments. Our model not only elucidates the biophysical mechanisms driving inverse blebbing and giant vacuole dynamics, but also identifies universal features of the cellular response to pressure loads that are relevant to many experimental contexts.
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Journal articleChen L, Lee CF, Maitra A, et al., 2022,
Incompressible polar active fluids with quenched random field disorder in dimensions d>2
, Physical Review Letters, Vol: 129, ISSN: 0031-9007We present a hydrodynamic theory of incompressible polar active fluids with quenched random field disorder. This theory shows that such fluids can overcome the disruption caused by the quenched disorder and move coherently, in the sense of having a nonzero mean velocity in the hydrodynamic limit. However, the scaling behavior of this class of active systems cannot be described by linearized hydrodynamics in spatial dimensions between 2 and 5. Nonetheless, we obtain the exact dimension-dependent scaling exponents in these dimensions.
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Journal articleChen L, Lee CF, Maitra A, et al., 2022,
Packed swarms on dirt: two-dimensional incompressible flocks with quenched and annealed disorder
, Physical Review Letters, Vol: 129, ISSN: 0031-9007We show that incompressible polar active fluids can exhibit an ordered, coherently moving phase even in the presence of quenched disorder in two dimensions. Unlike such active fluids with annealed disorder (i.e., time-dependent random white noise) only, which behave like equilibrium ferromagnets with long-range interactions, this robustness against quenched disorder is a fundamentally non-equilibrium phenomenon. The ordered state belongs to a new universality class, whose scaling laws we calculate using three different renormalization group schemes, which all give scaling exponents within 0.02 of each other, indicating that our results are quite accurate. Our predictions can be quantitatively tested in readily available artificial active systems, and imply that biological systems such as cell layers can move coherently in vivo, where disorder is inevitable.
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Journal articleChen L, Lee CF, Maitra A, et al., 2022,
Hydrodynamic theory of two-dimensional incompressible polar active fluids with quenched and annealed disorder
, Physical Review E: Statistical, Nonlinear, and Soft Matter Physics, Vol: 106, Pages: 1-29, ISSN: 1539-3755We study the moving phase of two-dimensional (2D) incompressible polar active fluids in the presence of both quenched and annealed disorder. We show that long-range polar order persists even in this defect-ridden two-dimensional system. We obtain the large-distance, long-time scaling laws of the velocity fluctuations using three distinct dynamic renormalization group schemes. These are an uncontrolled one-loop calculation in exactly two dimensions, and two d=(dc−ε) expansions to O(ε), obtained by two different analytic continuations of our 2D model to higher spatial dimensions: a “hard” continuation which has dc=73, and a “soft” continuation with dc=52. Surprisingly, the quenched and annealed parts of the velocity correlation function have the same anisotropy exponent and the relaxational and propagating parts of the dispersion relation have the same dynamic exponent in the nonlinear theory even though they are distinct in the linearized theory. This is due to anomalous hydrodynamics. Furthermore, all three renormalization schemes yield very similar values for the universal exponents, and therefore we expect the numerical values that we predict for them to be highly accurate.
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Journal articlePartridge B, Gonzalez Anton S, Khorshed R, et al., 2022,
Heterogeneous run-and-tumble motion accounts for transient non-Gaussian super-diffusion in haematopoietic multi-potent progenitor cells
, PLoS One, Vol: 17, Pages: 1-26, ISSN: 1932-6203Multi-potent progenitor (MPP) cells act as a key intermediary step between haematopoietic stem cells and the entirety of the mature blood cell system. Their eventual fate determination is thought to be achieved through migration in and out of spatially distinct niches. Here we first analyze statistically MPP cell trajectory data obtained from a series of long time-course 3D in vivo imaging experiments on irradiated mouse calvaria, and report that MPPs display transient super-diffusion with apparent non-Gaussian displacement distributions. Second, we explain these experimental findings using a run-and-tumble model of cell motion which incorporates the observed dynamical heterogeneity of the MPPs. Third, we use our model to extrapolate the dynamics to time-periods currently inaccessible experimentally, which enables us to quantitatively estimate the time and length scales at which super-diffusion transitions to Fickian diffusion. Our work sheds light on the potential importance of motility in early haematopoietic progenitor function.
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Journal articleOuldridge T, Hertel S, Spinney R, et al., 2022,
The stability and number of nucleating interactions determine DNA hybridisation rates in the absence of secondary structure
, Nucleic Acids Research, Vol: 50, Pages: 7829-7841, ISSN: 0305-1048The kinetics of DNA hybridisation are fundamental to biological processes and DNA-based technologies.However, the precise physical mechanisms that determine why different DNA sequences hybridise at differentrates are not well understood. Secondary structure is one predictable factor that influences hybridisation ratesbut is not sufficient on its own to fully explain the observed sequence-dependent variance. In this context, wemeasured hybridisation rates of 43 different DNA sequences that are not predicted to form secondarystructure and present a parsimonious physically justified model to quantify our observations. Accounting onlyfor the combinatorics of complementary nucleating interactions and their sequence-dependent stability, themodel achieves good correlation with experiment with only two free parameters. Our results indicate thatgreater repetition of Watson-Crick pairs increases the number of initial states able to proceed to fullhybridisation, with the stability of those pairings dictating the likelihood of such progression, thus providingnew insight into the physical factors underpinning DNA hybridisation rates.
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Book chapterOuldridge T, Doye J, Louis A, et al., 2022,
Free energy landscapes of DNA and its assemblies: perspectives from coarse-grained modelling
, Energy Landscapes of Nanoscale Systems, Publisher: Elsevier, Pages: 195-210, ISBN: 9780128244067This chapter will provide an overview of how characterising free energy landscapes can provide insights into the biophysical properties of DNA, as well as into the behaviour of the DNA assemblies used in the field of DNA nanotechnology. The landscapes for these complex systems are accessible through the use of accurate coarse-grained descriptions of DNA. Particular foci will be the landscapes associated with DNA self-assembly and mechanical deformation, where the latter can arise from either externally imposed forces or internal stresses.
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Journal articleBertrand T, Lee CF, 2022,
Diversity of phase transitions and phase separations in active fluids
, Physical Review Research, Vol: 4, ISSN: 2643-1564Active matter is not only indispensable to our understanding of diverse biological processes, but also provides a fertile ground for discovering novel physics. Many emergent properties impossible for equilibrium systems have been demonstrated in active systems. These emergent features include motility-induced phase separation, a long-ranged ordered (collective motion) phase in two dimensions, and order-disorder phase coexistences (banding and reverse-banding regimes). Here, we unify these diverse phase transitions and phase coexistences into a single formulation based on generic hydrodynamic equations for active fluids. We also reveal a novel comoving coexistence phase and a multicritical point.
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