Imperial College London

DrThomasOuldridge

Faculty of EngineeringDepartment of Bioengineering

Senior Lecturer
 
 
 
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4.04Royal School of MinesSouth Kensington Campus

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Summary

 

Publications

Publication Type
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67 results found

Poulton JM, Ouldridge TE, 2021, Edge-effects dominate copying thermodynamics for finite-length molecular oligomers, New Journal of Physics, Vol: 23, Pages: 1-14, ISSN: 1367-2630

A signature feature of living systems is their ability to produce copies ofinformation-carrying molecular templates such as DNA. These copies are madeby assembling a set of monomer molecules into a linear macromolecule with a sequence determined by the template. The copies produced have a finite length –they are often “oligomers”, or short polymers – and must eventually detach fromtheir template. We explore the role of the resultant initiation and termination ofthe copy process in the thermodynamics of copying. By splitting the free-energychange of copy formation into informational and chemical terms, we show that,surprisingly, copy accuracy plays no direct role in the overall thermodynamics. Instead, finite-length templates function as highly-selective engines that interconvertchemical and information-based free energy stored in the environment; it is thermodynamically costly to produce outputs that are more similar to the oligomersin the environment than sequences obtained by randomly sampling monomers. Incontrast to previous work that neglects separation, any excess free energy stored incorrelations between copy and template sequences is lost when the copy fully detaches and mixes with the environment; these correlations therefore do not featurein the overall thermodynamics. Previously-derived constraints on copy accuracytherefore only manifest as kinetic barriers experienced while the copy is templateattached; these barriers are easily surmounted by shorter oligomers.

Journal article

Sengar A, Ouldridge TE, Henrich O, Rovigatti L, Sulc Pet al., 2021, A primer on the oxDNA model of DNA: When to use it, how to simulate it and how to interpret the results, Frontiers in Molecular Biosciences, Vol: 8, Pages: 1-22, ISSN: 2296-889X

The oxDNA model of DNA has been applied widely to systems in biology,biophysics and nanotechnology. It is currently available via two independentopen source packages. Here we present a set of clearly-documented exemplarsimulations that simultaneously provide both an introduction to simulating themodel, and a review of the model's fundamental properties. We outline howsimulation results can be interpreted in terms of -- and feed into ourunderstanding of -- less detailed models that operate at larger length scales,and provide guidance on whether simulating a system with oxDNA is worthwhile.

Journal article

Plesa T, Stan G-B, Ouldridge TE, Bae Wet al., 2021, Quasi-robust control of biochemical reaction networks via stochastic morphing., Journal of the Royal Society Interface, Vol: 18, Pages: 1-14, ISSN: 1742-5662

One of the main objectives of synthetic biology is the development of molecular controllers that can manipulate the dynamics of a given biochemical network that is at most partially known. When integrated into smaller compartments, such as living or synthetic cells, controllers have to be calibrated to factor in the intrinsic noise. In this context, biochemical controllers put forward in the literature have focused on manipulating the mean (first moment) and reducing the variance (second moment) of the target molecular species. However, many critical biochemical processes are realized via higher-order moments, particularly the number and configuration of the probability distribution modes (maxima). To bridge the gap, we put forward the stochastic morpher controller that can, under suitable timescale separations, morph the probability distribution of the target molecular species into a predefined form. The morphing can be performed at a lower-resolution, allowing one to achieve desired multi-modality/multi-stability, and at a higher-resolution, allowing one to achieve arbitrary probability distributions. Properties of the controller, such as robustness and convergence, are rigorously established, and demonstrated on various examples. Also proposed is a blueprint for an experimental implementation of stochastic morpher.

Journal article

Cabello-Garcia J, Bae W, Stan G-BV, Ouldridge TEet al., 2021, Handhold-mediated strand displacement: a nucleic acid based mechanism for generating far-from-equilibrium assemblies through templated reactions., ACS Nano, Vol: 15, Pages: 3272-3283, ISSN: 1936-0851

The use of templates is a well-established method for the production of sequence-controlled assemblies, particularly long polymers. Templating is canonically envisioned as akin to a self-assembly process, wherein sequence-specific recognition interactions between a template and a pool of monomers favor the assembly of a particular polymer sequence at equilibrium. However, during the biogenesis of sequence-controlled polymers, template recognition interactions are transient; RNA and proteins detach spontaneously from their templates to perform their biological functions and allow template reuse. Breaking template recognition interactions puts the product sequence distribution far from equilibrium, since specific product formation can no longer rely on an equilibrium dominated by selective copy-template bonds. The rewards of engineering artificial polymer systems capable of spontaneously exhibiting nonequilibrium templating are large, but fields like DNA nanotechnology lack the requisite tools; the specificity and drive of conventional DNA reactions rely on product stability at equilibrium, sequestering any recognition interaction in products. The proposed alternative is handhold-mediated strand displacement (HMSD), a DNA-based reaction mechanism suited to producing out-of-equilibrium products. HMSD decouples the drive and specificity of the reaction by introducing a transient recognition interaction, the handhold. We measure the kinetics of 98 different HMSD systems to prove that handholds can accelerate displacement by 4 orders of magnitude without being sequestered in the final product. We then use HMSD to template the selective assembly of any one product DNA duplex from an ensemble of equally stable alternatives, generating a far-from-equilibrium output. HMSD thus brings DNA nanotechnology closer to the complexity of out-of-equilibrium biological systems.

Journal article

Berengut J, Kui Wong C, Berengut J, Doye J, Ouldridge T, Lee Let al., 2020, Self-limiting polymerization of DNA origami subunits with strain accumulation, ACS Nano, Vol: 14, Pages: 17428-17441, ISSN: 1936-0851

Biology demonstrates how a near infinite array of complex systems and structures at many scales can originate from the self-assembly of component parts on the nanoscale. But to fully exploit the benefits of self-assembly for nanotechnology, a crucial challenge remains: How do we rationally encode well-defined global architectures in subunits that are much smaller than their assemblies? Strain accumulation via geometric frustration is one mechanism that has been used to explain the self-assembly of global architectures in diverse and complex systems a posteriori. Here we take the next step and use strain accumulation as a rational design principle to control the length distributions of self-assembling polymers. We use the DNA origami method to design and synthesize a molecular subunit known as the PolyBrick, which perturbs its shape in response to local interactions via flexible allosteric blocking domains. These perturbations accumulate at the ends of polymers during growth, until the deformation becomes incompatible with further extension. We demonstrate that the key thermodynamic factors for controlling length distributions are the intersubunit binding free energy and the fundamental strain free energy, both which can be rationally encoded in a PolyBrick subunit. While passive polymerization yields geometrical distributions, which have the highest statistical length uncertainty for a given mean, the PolyBrick yields polymers that approach Gaussian length distributions whose variance is entirely determined by the strain free energy. We also show how strain accumulation can in principle yield length distributions that become tighter with increasing subunit affinity and approach distributions with uniform polymer lengths. Finally, coarse-grained molecular dynamics and Monte Carlo simulations delineate and quantify the dominant forces influencing strain accumulation in a molecular system. This study constitutes a fundamental investigation of the use of strain accumula

Journal article

Ouldridge T, Stan G-B, Bae W, 2020, In situ generation of RNA complexes for synthetic molecular strand displacement circuits in autonomous systems, Nano Letters: a journal dedicated to nanoscience and nanotechnology, Vol: 21, Pages: 265-271, ISSN: 1530-6984

Synthetic molecular circuits implementing DNA or RNA strand-displacement reactions can be used to build complex systems such as molecular computers and feedback control systems. Despite recent advances, application of nucleic acid-based circuits in vivo remains challenging due to a lack of efficient methods to produce their essential components, namely, multistranded complexes known as gates, in situ, i.e., in living cells or other autonomous systems. Here, we propose the use of naturally occurring self-cleaving ribozymes to cut a single-stranded RNA transcript into a gate complex of shorter strands, thereby opening new possibilities for the autonomous and continuous production of RNA strands in a stoichiometrically and structurally controlled way.

Journal article

Deshpande A, Ouldridge T, 2020, Optimizing enzymatic catalysts for rapid turnover of substrates with low enzyme sequestration, Biological Cybernetics: communication and control in organisms and automata, Vol: 114, Pages: 653-668, ISSN: 0340-1200

Enzymes are central to both metabolism and information processing in cells. In both cases, an enzyme’s ability to accelerate a reaction without being consumed in the reaction is crucial. Nevertheless, enzymes are transiently sequestered when they bind to their substrates; this sequestration limits activity and potentially compromises information processing and signal transduction. In this article, we analyse the mechanism of enzyme–substrate catalysis from the perspective of minimizing the load on the enzymes through sequestration, while maintaining at least a minimum reaction flux. In particular, we ask: which binding free energies of the enzyme–substrate and enzyme–product reaction intermediates minimize the fraction of enzymes sequestered in complexes, while sustaining a certain minimal flux? Under reasonable biophysical assumptions, we find that the optimal design will saturate the bound on the minimal flux and reflects a basic trade-off in catalytic operation. If both binding free energies are too high, there is low sequestration, but the effective progress of the reaction is hampered. If both binding free energies are too low, there is high sequestration, and the reaction flux may also be suppressed in extreme cases. The optimal binding free energies are therefore neither too high nor too low, but in fact moderate. Moreover, the optimal difference in substrate and product binding free energies, which contributes to the thermodynamic driving force of the reaction, is in general strongly constrained by the intrinsic free-energy difference between products and reactants. Both the strategies of using a negative binding free-energy difference to drive the catalyst-bound reaction forward and of using a positive binding free-energy difference to enhance detachment of the product are limited in their efficacy.

Journal article

Lankinen A, Ruiz IM, Ouldridge TE, 2020, Implementing non-equilibrium networks with active circuits of duplex catalysts, 26th International Conference on DNA Computing and Molecular Programming (DNA 26), Publisher: Schloss Dagstuhl--Leibniz-Zentrum, Pages: 1-25

DNA strand displacement (DSD) reactions have been used to construct chemicalreaction networks in which species act catalytically at the level of theoverall stoichiometry of reactions. These effective catalytic reactions aretypically realised through one or more of the following: many-stranded gatecomplexes to coordinate the catalysis, indirect interaction between thecatalyst and its substrate, and the recovery of a distinct ``catalyst'' strandfrom the one that triggered the reaction. These facts make emulation of theout-of-equilibrium catalytic circuitry of living cells more difficult. Here, wepropose a new framework for constructing catalytic DSD networks: ActiveCircuits of Duplex Catalysts (ACDC). ACDC components are all double-strandedcomplexes, with reactions occurring through 4-way strand exchange. Catalystsdirectly bind to their substrates, and and the ``identity'' strand of thecatalyst recovered at the end of a reaction is the same molecule as the onethat initiated it. We analyse the capability of the framework to implementcatalytic circuits analogous to phosphorylation networks in living cells. Wealso propose two methods of systematically introducing mismatches within DNAstrands to avoid leak reactions and introduce driving through net base pairformation. We then combine these results into a compiler to automate theprocess of designing DNA strands that realise any catalytic network allowed byour framework.

Conference paper

Irmisch P, Ouldridge TE, Seidel R, 2020, Modelling DNA-strand displacement reactions in the presence of base-pair mismatches, Journal of the American Chemical Society, Vol: 142, Pages: 11451-11463, ISSN: 0002-7863

Toehold-mediated strand displacement is the most abundantly used method to achieve dynamic switching in DNA-based nanotechnology. An ‘invader’ strand binds to the ‘toehold’ overhang of a target strand and replaces a target-bound ’incumbent’ strand. Hereby, complementarity of the invader to the single-stranded toehold provides the energetic bias of the reaction. Despite the widespread use of strand displacement reactions for realizing dynamic DNA nanostructures, variants on the basic motif have not been completely characterized. Here we introduce a simple thermodynamic model, which is capable of quantitatively describing the kinetics of strand displacement reactions in the presence of mismatches, using a minimal set of parameters. Furthermore, our model highlights that base pair fraying and internal loop formation are important mechanisms when involving mismatches in the displacement process. Our model should provide a helpful tool for the rational design of strand-displacement reaction networks.

Journal article

Ouldridge T, Turberfield A, Mullor Ruiz I, Louis A, Bath J, Haley N, Geraldini Aet al., 2020, Design of hidden thermodynamic driving for non-equilibrium systems via mismatch elimination during DNA strand displacement, Nature Communications, Vol: 11, ISSN: 2041-1723

Recent years have seen great advances in the development of synthetic self-assembling molecular systems. Designing out-of-equilibrium architectures, however, requires a more subtle control over the thermodynamics and kinetics of reactions. We propose a mechanism for enhancing the thermodynamic drive of DNA strand-displacement reactions whilst barely perturbing forward reaction rates: the introduction of mismatches within the initial duplex. Through a combination of experiment and simulation, we demonstrate that displacement rates are strongly sensitive to mismatch location and can be tuned by rational design. By placing mismatches away from duplex ends, the thermodynamic drive for a strand-displacement reaction can be varied without significantly affecting the forward reaction rate. This hidden thermodynamic driving motif is ideal for the engineering of non-equilibrium systems that rely on catalytic control and must be robust to leak reactions.

Journal article

Harrison RM, Romano F, Ouldridge TE, Louis AA, Doye JPKet al., 2019, Identifying physical causes of apparent enhanced cyclization of short DNA molecules with a coarse-grained model, Journal of Chemical Theory and Computation, Vol: 15, Pages: 4660-4672, ISSN: 1549-9618

DNA cyclization is a powerful technique to gain insight into the nature of DNA bending. While the worm-like chain model provides a good description of small to moderate bending fluctuations, it is expected to break down for large bending. Recent cyclization experiments on strongly-bent shorter molecules indeed suggest enhanced flexibility over and above that expected from the worm-like chain. Here, we use a coarse-grained model of DNA to investigate the subtle thermodynamics of DNA cyclization for molecules ranging from 30 to 210 base pairs. As the molecules get shorter we find increasing deviations between our computed equilibrium j-factor and the classic worm-like chain predictions of Shimada and Yamakawa for a torsionally aligned looped molecule. These deviations are due to sharp kinking, first at nicks, and only subsequently in the body of the duplex. At the shortest lengths, substantial fraying at the ends of duplex domains is the dominant method of relaxation. We also estimate the dynamic j-factor measured in recent FRET experiments. We find that the dynamic j-factor is systematically larger than its equilibrium counterpart - with the deviation larger for shorter molecules - because not all the stress present in the fully cyclized state is present in the transition state. These observations are important for the interpretation of recent cyclization experiments, suggesting that measured anomalously high j-factors may not necessarily indicate non-WLC behavior in the body of duplexes.

Journal article

Brittain R, Jones N, Ouldridge T, 2019, Biochemical Szilard engines for memory-limited inference, New Journal of Physics, Vol: 21, ISSN: 1367-2630

By designing and leveraging an explicit molecular realisation of a measurement-and-feedback-powered Szilard engine, we investigate the extraction of work from complex environments by minimal machines with finite capacity for memory and decision-making. Living systems perform inference to exploit complex structure, or correlations, in their environment, but the physical limits and underlying cost/benefit trade-offs involved in doing so remain unclear. To probe these questions, we consider a minimal model for a structured environment—a correlated sequence of molecules—and explore mechanisms based on extended Szilard engines for extracting the work stored in these non-equilibrium correlations. We consider systems limited to a single bit of memory making binary 'choices' at each step. We demonstrate that increasingly complex environments allow increasingly sophisticated inference strategies to extract more free energy than simpler alternatives, and argue that optimal design of such machines should also consider the free energy reserves required to ensure robustness against fluctuations due to mistakes.

Journal article

Quast N, Ouldridge T, 2019, Simulation of DNA tile self-assembly

Submitted in accompaniment with final year report of MEng Project. DNA tile self-assembly is the spontaneous assembly of nano-structures made from short single-stranded DNA sequences. Successful assembly occurs within a narrow parameter window. Thisproject presents a model with which DNA self-assembly is simulated. Simulations for different tem-perature, sequence binding specificity and DNA tile concentrations indicate that: the growth rateof assemblies from uniform strand solutions is linear and highly temperature dependent; the aver-age nucleation times of assembly increase exponentially with temperature; high binding strengthsof boundary strands improve the stability of the complete assembly; locally high concentrations ofstrands seed the growth of the assembly; and locally low strand concentrations spatially direct thegrowth of the assembly. The source code is written in C.

Software

Stopnitzky E, Still S, Ouldridge TE, Altenberg Let al., 2019, Physical limitations of work extraction from temporal correlations., Physical Review E, Vol: 99, ISSN: 1539-3755

Recently proposed information-exploiting systems extract work from a single heat bath by using temporal correlations on an input tape. We study how enforcing time-continuous dynamics, which is necessary to ensure that the device is physically realizable, constrains possible designs and drastically diminishes efficiency. We show that these problems can be circumvented by means of applying an external, time-varying protocol, which turns the device from a "passive," free-running machine into an "actively" driven one.

Journal article

Poulton J, Wolde PRT, Ouldridge TE, 2019, Non-equilibrium correlations in minimal dynamical models of polymer copying, Proceedings of the National Academy of Sciences, Vol: 116, Pages: 1946-1951, ISSN: 0027-8424

Living systems produce "persistent" copies of information-carrying polymers, in which template and copy sequences remain correlated after physically decoupling. We identify a general measure of the thermodynamic efficiency with which these non-equilibrium states are created, and analyze the accuracy and efficiency of a family of dynamical models that produce persistent copies. For the weakest chemical driving, when polymer growth occurs in equilibrium, both the copy accuracy and, more surprisingly, the efficiency vanish. At higher driving strengths, accuracy and efficiency both increase, with efficiency showing one or more peaks at moderate driving. Correlations generated within the copy sequence, as well as between template and copy, store additional free energy in the copied polymer and limit the single-site accuracy for a given chemical work input. Our results provide insight in the design of natural self-replicating systems and can aid the design of synthetic replicators.

Journal article

Lawrence J, Chang S, Rodriguez LC, Ouldridge Tet al., 2019, Students go through the gears at the iGEM competition for engineering biology, Biochemist, Vol: 41, Pages: 58-61, ISSN: 0954-982X

The annual International Genetically Engineered Machine (iGEM) competition, represents an exciting opportunity for students to experience first-hand the potential of synthetic biology approaches to solve real-world problems. In this article, an iGEM team based at Imperial College London share some of the highlights from their participation in the 2018 iGEM event, including sharing their work at the annual Jamboree in Boston, Massachusetts.

Journal article

Ouldridge TE, Brittain R, ten Wolde PR, 2018, The power of being explicit: demystifying work, heat, and free energy in the physics of computation, The Interplay of Thermodynamics and Computation in Both Natural and Artificial Systems

Book chapter

Stopnitzky E, Still S, Ouldridge TE, Altenberg Let al., 2018, Physical Limitations of Work Extraction from Temporal Correlations, The Interplay of Thermodynamics and Computation in Both Natural and Artificial Systems, Publisher: SFI Press

Book chapter

Brittain R, Jones N, Ouldridge T, 2018, Biochemical Szilard engine for memory limited inference

Code and data for figures in 'Biochemical Szilard engine for memory limited inference'

Software

Henrich O, Gutiérrez Fosado YA, Curk T, Ouldridge TEet al., 2018, Coarse-grained simulation of DNA using LAMMPS : an implementation of the oxDNA model and its applications, European Physical Journal E. Soft Matter, Vol: 41, Pages: 57-57, ISSN: 1292-8941

During the last decade coarse-grained nucleotide models have emerged that allow us to study DNA and RNA on unprecedented time and length scales. Among them is oxDNA, a coarse-grained, sequence-specific model that captures the hybridisation transition of DNA and many structural properties of single- and double-stranded DNA. oxDNA was previously only available as standalone software, but has now been implemented into the popular LAMMPS molecular dynamics code. This article describes the new implementation and analyses its parallel performance. Practical applications are presented that focus on single-stranded DNA, an area of research which has been so far under-investigated. The LAMMPS implementation of oxDNA lowers the entry barrier for using the oxDNA model significantly, facilitates future code development and interfacing with existing LAMMPS functionality as well as other coarse-grained and atomistic DNA models.

Journal article

Fonseca P, Romano F, Schreck JS, Ouldridge TE, Doye JPK, Louis AAet al., 2018, Multi-scale coarse-graining for the study of assembly pathways in DNA-brick self assembly, Journal of Chemical Physics, Vol: 148, ISSN: 0021-9606

Inspired by recent successes using single-stranded DNA tiles to producecomplex structures, we develop a two-step coarse-graining approach that usesdetailed thermodynamic calculations with oxDNA, a nucleotide-based model ofDNA, to parametrize a coarser kinetic model that can reach the time and lengthscales needed to study the assembly mechanisms of these structures. We test themodel by performing a detailed study of the assembly pathways for atwo-dimensional target structure made up of 334 unique strands each of whichare 42 nucleotides long. Without adjustable parameters, the model reproduces acritical temperature for the formation of the assembly that is close to thetemperature at which assembly first occurs in experiments. Furthermore, themodel allows us to investigate in detail the nucleation barriers and thedistribution of critical nucleus shapes for the assembly of a single targetstructure. The assembly intermediates are compact and highly connected(although not maximally so) and classical nucleation theory provides a good fitto the height and shape of the nucleation barrier at temperatures close towhere assembly first occurs.

Journal article

Khara DC, Schreck JS, Tomov TE, Berger Y, Ouldridge TE, Doye JPK, Nir Eet al., 2017, DNA bipedal motor walking dynamics: an experimental and theoretical study of the dependency on step size, Nucleic Acids Research, Vol: 46, Pages: 1553-1561, ISSN: 0305-1048

We present a detailed coarse-grained computer simulation and single molecule fluorescence study of the walking dynamics and mechanism of a DNA bipedal motor striding on a DNA origami. In particular, we study the dependency of the walking efficiency and stepping kinetics on step size. The simulations accurately capture and explain three different experimental observations. These include a description of the maximum possible step size, a decrease in the walking efficiency over short distances and a dependency of the efficiency on the walking direction with respect to the origami track. The former two observations were not expected and are non-trivial. Based on this study, we suggest three design modifications to improve future DNA walkers. Our study demonstrates the ability of the oxDNA model to resolve the dynamics of complex DNA machines, and its usefulness as an engineering tool for the design of DNA machines that operate in the three spatial dimensions.

Journal article

Davidchack RL, Ouldridge TE, Tretyakov MV, 2017, Geometric integrator for Langevin systems with quaternion-based rotational degrees of freedom and hydrodynamic interactions, Journal of Chemical Physics, Vol: 147, ISSN: 0021-9606

We introduce new Langevin-type equations describing the rotational andtranslational motion of rigid bodies interacting through conservative andnon-conservative forces, and hydrodynamic coupling. In the absence ofnon-conservative forces the Langevin-type equations sample from the canonicalensemble. The rotational degrees of freedom are described using quaternions,the lengths of which are exactly preserved by the stochastic dynamics. For theproposed Langevin-type equations, we construct a weak 2nd order geometricintegrator which preserves the main geometric features of the continuousdynamics. A number of numerical experiments are presented to illustrate boththe new Langevin model and the numerical method for it.

Journal article

Ouldridge TE, 2017, The importance of thermodynamics for molecular systems, and the importance of molecular systems for thermodynamics, Natural Computing, Vol: 17, Pages: 3-29, ISSN: 1567-7818

Improved understanding of molecular systems has only emphasised thesophistication of networks within the cell. Simultaneously, the advance ofnucleic acid nanotechnology, a platform within which reactions can beexquisitely controlled, has made the development of artificial architecturesand devices possible. Vital to this progress has been a solid foundation in thethermodynamics of molecular systems. In this pedagogical review andperspective, I will discuss how thermodynamics determines both the overallpotential of molecular networks, and the minute details of design. I will thenargue that, in turn, the need to understand molecular systems is helping todrive the development of theories of thermodynamics at the microscopic scale.

Journal article

Deshpande A, Ouldridge TE, 2017, High rates of fuel consumption are not required by insulating motifs to suppress retroactivity in biochemical circuits, Engineering Biology, Vol: 1, Pages: 86-99, ISSN: 2398-6182

Retroactivity arises when the coupling of a molecular network $\mathcal{U}$to a downstream network $\mathcal{D}$ results in signal propagation back from$\mathcal{D}$ to $\mathcal{U}$. The phenomenon represents a breakdown inmodularity of biochemical circuits and hampers the rational design of complexfunctional networks. Considering simple models of signal-transductionarchitectures, we demonstrate the strong dependence of retroactivity on theproperties of the upstream system, and explore the cost and efficacy offuel-consuming insulating motifs that can mitigate retroactive effects. We findthat simple insulating motifs can suppress retroactivity at a low fuel cost bycoupling only weakly to the upstream system $\mathcal{U}$. However, this designapproach reduces the signalling network's robustness to perturbations from leakreactions, and potentially compromises its ability to respond torapidly-varying signals.

Journal article

Poole W, Ortiz-Muñoz A, Behera A, Jones NS, Ouldridge TE, Winfree E, Gopalkrishnan Met al., 2017, Chemical Boltzmann Machines, Lecture Notes in Computer Science, Vol: 10467, Pages: 210-231, ISSN: 0302-9743

How smart can a micron-sized bag of chemicals be? How can an artificial orreal cell make inferences about its environment? From which kinds ofprobability distributions can chemical reaction networks sample? We begintackling these questions by showing four ways in which a stochastic chemicalreaction network can implement a Boltzmann machine, a stochastic neural networkmodel that can generate a wide range of probability distributions and computeconditional probabilities. The resulting models, and the associated theorems,provide a road map for constructing chemical reaction networks that exploittheir native stochasticity as a computational resource. Finally, to show thepotential of our models, we simulate a chemical Boltzmann machine to classifyand generate MNIST digits in-silico.

Journal article

Deshpande A, Gopalkrishnan M, Ouldridge TE, Jones Net al., 2017, Designing the Optimal Bit: Balancing Energetic Cost, Speed and Reliability, Proceedings of the Royal Society A: Mathematical, Physical & Engineering Sciences, Vol: 473, ISSN: 1364-5021

We consider the technologically relevant costs of operating a reliable bitthat can be erased rapidly. We find that both erasing and reliability times arenon-monotonic in the underlying friction, leading to a trade-off betweenerasing speed and bit reliability. Fast erasure is possible at the expense oflow reliability at moderate friction, and high reliability comes at the expenseof slow erasure in the underdamped and overdamped limits. Within a given classof bit parameters and control strategies, we define "optimal" designs of bitsthat meet the desired reliability and erasing time requirements with the lowestoperational work cost. We find that optimal designs always saturate the boundon the erasing time requirement, but can exceed the required reliability timeif critically damped. The non-trivial geometry of the reliability and erasingtime-scales allows us to exclude large regions of parameter space assub-optimal. We find that optimal designs are either critically damped or closeto critical damping under the erasing procedure.

Journal article

Brittain RA, Jones NS, Ouldridge TE, 2017, What we learn from the learning rate, Journal of Statistical Mechanics-Theory and Experiment, Vol: 2017, ISSN: 1742-5468

The learning rate is an information-theoretical quantity for bipartite Markovchains describing two coupled subsystems. It is defined as the rate at whichtransitions in the downstream subsystem tend to increase the mutual informationbetween the two subsystems, and is bounded by the dissipation arising fromthese transitions. Its physical interpretation, however, is unclear, althoughit has been used as a metric for the sensing performance of the downstreamsubsystem. In this paper we explore the behaviour of the learning rate for anumber of simple model systems, establishing when and how its behaviour isdistinct from the instantaneous mutual information between subsystems. In thesimplest case, the two are almost equivalent. In more complex steady-statesystems, the mutual information and the learning rate behave qualitativelydistinctly, with the learning rate clearly now reflecting the rate at which thedownstream system must update its information in response to changes in theupstream system. It is not clear whether this quantity is the most naturalmeasure for sensor performance, and, indeed, we provide an example in whichoptimising the learning rate over a region of parameter space of the downstreamsystem yields an apparently sub-optimal sensor.

Journal article

Ouldridge TE, ten Wolde PR, 2017, Fundamental Costs in the production and destruction of persistent polymer copies, Physical Review Letters, Vol: 118, ISSN: 0031-9007

Producing a polymer copy of a polymer template is central to biology, and effective copies must persist after template separation. We show that this separation has three fundamental thermodynamic effects. First, polymer-template interactions do not contribute to overall reaction thermodynamics and hence cannot drive the process. Second, the equilibrium state of the copied polymer is template independent and so additional work is required to provide specificity. Finally, the mixing of copies from distinct templates makes correlations between template and copy sequences unexploitable, combining with copying inaccuracy to reduce the free energy stored in a polymer ensemble. These basic principles set limits on the underlying costs and resource requirements, and suggest design principles, for autonomous copying and replication in biological and synthetic systems.

Journal article

Ouldridge TE, Govern CC, Wolde PRT, 2017, Thermodynamics of computational copying in biochemical systems, Physical Review X, Vol: 7, ISSN: 2160-3308

Living cells use readout molecules to record the state of receptor proteins, similar to measurements or copies in typical computational devices. But is this analogy rigorous? Can cells be optimally efficient, and if not, why? We show that, as in computation, a canonical biochemical readout network generates correlations; extracting no work from these correlations sets a lower bound on dissipation. For general input, the biochemical network cannot reach this bound, even with arbitrarily slow reactions or weak thermodynamic driving. It faces an accuracy-dissipation trade-off that is qualitatively distinct from and worse than implied by the bound, and more complex steady-state copy processes cannot perform better. Nonetheless, the cost remains close to the thermodynamic bound unless accuracy is extremely high. Additionally, we show that biomolecular reactions could be used in thermodynamically optimal devices under exogenous manipulation of chemical fuels, suggesting an experimental system for testing computational thermodynamics.

Journal article

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