@article{1170, abstract = {The increasing complexity of dynamic models in systems and synthetic biology poses computational challenges especially for the identification of model parameters. While modularization of the corresponding optimization problems could help reduce the “curse of dimensionality,” abundant feedback and crosstalk mechanisms prohibit a simple decomposition of most biomolecular networks into subnetworks, or modules. Drawing on ideas from network modularization and multiple-shooting optimization, we present here a modular parameter identification approach that explicitly allows for such interdependencies. Interfaces between our modules are given by the experimentally measured molecular species. This definition allows deriving good (initial) estimates for the inter-module communication directly from the experimental data. Given these estimates, the states and parameter sensitivities of different modules can be integrated independently. To achieve consistency between modules, we iteratively adjust the estimates for inter-module communication while optimizing the parameters. After convergence to an optimal parameter set---but not during earlier iterations---the intermodule communication as well as the individual modules\' state dynamics agree with the dynamics of the nonmodularized network. Our modular parameter identification approach allows for easy parallelization; it can reduce the computational complexity for larger networks and decrease the probability to converge to suboptimal local minima. We demonstrate the algorithm\'s performance in parameter estimation for two biomolecular networks, a synthetic genetic oscillator and a mammalian signaling pathway.}, author = {Lang, Moritz and Stelling, Jörg}, journal = {SIAM Journal on Scientific Computing}, number = {6}, pages = {B988 -- B1008}, publisher = {Society for Industrial and Applied Mathematics }, title = {{Modular parameter identification of biomolecular networks}}, doi = {10.1137/15M103306X}, volume = {38}, year = {2016}, } @article{1171, author = {Tkacik, Gasper}, journal = {Physics of Life Reviews}, pages = {166 -- 167}, publisher = {Elsevier}, title = {{Understanding regulatory networks requires more than computing a multitude of graph statistics: Comment on "Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function" by O. C. Martin et al.}}, doi = {10.1016/j.plrev.2016.06.005}, volume = {17}, year = {2016}, } @article{1188, abstract = {We consider a population dynamics model coupling cell growth to a diffusion in the space of metabolic phenotypes as it can be obtained from realistic constraints-based modelling. In the asymptotic regime of slow diffusion, that coincides with the relevant experimental range, the resulting non-linear Fokker–Planck equation is solved for the steady state in the WKB approximation that maps it into the ground state of a quantum particle in an Airy potential plus a centrifugal term. We retrieve scaling laws for growth rate fluctuations and time response with respect to the distance from the maximum growth rate suggesting that suboptimal populations can have a faster response to perturbations.}, author = {De Martino, Daniele and Masoero, Davide}, journal = { Journal of Statistical Mechanics: Theory and Experiment}, number = {12}, publisher = {IOPscience}, title = {{Asymptotic analysis of noisy fitness maximization, applied to metabolism & growth}}, doi = {10.1088/1742-5468/aa4e8f}, volume = {2016}, year = {2016}, } @article{1203, abstract = {Haemophilus haemolyticus has been recently discovered to have the potential to cause invasive disease. It is closely related to nontypeable Haemophilus influenzae (NT H. influenzae). NT H. influenzae and H. haemolyticus are often misidentified because none of the existing tests targeting the known phenotypes of H. haemolyticus are able to specifically identify H. haemolyticus. Through comparative genomic analysis of H. haemolyticus and NT H. influenzae, we identified genes unique to H. haemolyticus that can be used as targets for the identification of H. haemolyticus. A real-time PCR targeting purT (encoding phosphoribosylglycinamide formyltransferase 2 in the purine synthesis pathway) was developed and evaluated. The lower limit of detection was 40 genomes/PCR; the sensitivity and specificity in detecting H. haemolyticus were 98.9% and 97%, respectively. To improve the discrimination of H. haemolyticus and NT H. influenzae, a testing scheme combining two targets (H. haemolyticus purT and H. influenzae hpd, encoding protein D lipoprotein) was also evaluated and showed 96.7% sensitivity and 98.2% specificity for the identification of H. haemolyticus and 92.8% sensitivity and 100% specificity for the identification of H. influenzae, respectively. The dual-target testing scheme can be used for the diagnosis and surveillance of infection and disease caused by H. haemolyticus and NT H. influenzae.}, author = {Hu, Fang and Rishishwar, Lavanya and Sivadas, Ambily and Mitchell, Gabriel and King, Jordan and Murphy, Timothy and Gilsdorf, Janet and Mayer, Leonard and Wang, Xin}, journal = {Journal of Clinical Microbiology}, number = {12}, pages = {3010 -- 3017}, publisher = {American Society for Microbiology}, title = {{Comparative genomic analysis of Haemophilus haemolyticus and nontypeable Haemophilus influenzae and a new testing scheme for their discrimination}}, doi = {10.1128/JCM.01511-16}, volume = {54}, year = {2016}, } @inproceedings{1214, abstract = {With the accelerated development of robot technologies, optimal control becomes one of the central themes of research. In traditional approaches, the controller, by its internal functionality, finds appropriate actions on the basis of the history of sensor values, guided by the goals, intentions, objectives, learning schemes, and so forth. While very successful with classical robots, these methods run into severe difficulties when applied to soft robots, a new field of robotics with large interest for human-robot interaction. We claim that a novel controller paradigm opens new perspective for this field. This paper applies a recently developed neuro controller with differential extrinsic synaptic plasticity to a muscle-tendon driven arm-shoulder system from the Myorobotics toolkit. In the experiments, we observe a vast variety of self-organized behavior patterns: when left alone, the arm realizes pseudo-random sequences of different poses. By applying physical forces, the system can be entrained into definite motion patterns like wiping a table. Most interestingly, after attaching an object, the controller gets in a functional resonance with the object's internal dynamics, starting to shake spontaneously bottles half-filled with water or sensitively driving an attached pendulum into a circular mode. When attached to the crank of a wheel the neural system independently develops to rotate it. In this way, the robot discovers affordances of objects its body is interacting with.}, author = {Martius, Georg S and Hostettler, Raphael and Knoll, Alois and Der, Ralf}, location = {Daejeon, Korea}, publisher = {IEEE}, title = {{Compliant control for soft robots: Emergent behavior of a tendon driven anthropomorphic arm}}, doi = {10.1109/IROS.2016.7759138}, volume = {2016-November}, year = {2016}, } @inproceedings{1220, abstract = {Theoretical and numerical aspects of aerodynamic efficiency of propulsion systems coupled to the boundary layer of a fuselage are studied. We discuss the effects of local flow fields, which are affected both by conservative flow acceleration as well as total pressure losses, on the efficiency of boundary layer immersed propulsion devices. We introduce the concept of a boundary layer retardation turbine that helps reduce skin friction over the fuselage. We numerically investigate efficiency gains offered by boundary layer and wake interacting devices. We discuss the results in terms of a total energy consumption framework and show that efficiency gains of any device depend on all the other elements of the propulsion system.}, author = {Mikić, Gregor and Stoll, Alex and Bevirt, Joe and Grah, Rok and Moore, Mark}, location = {Washington, D.C., USA}, pages = {1 -- 19}, publisher = {AIAA}, title = {{Fuselage boundary layer ingestion propulsion applied to a thin haul commuter aircraft for optimal efficiency}}, doi = {10.2514/6.2016-3764}, year = {2016}, } @article{1242, abstract = {A crucial step in the regulation of gene expression is binding of transcription factor (TF) proteins to regulatory sites along the DNA. But transcription factors act at nanomolar concentrations, and noise due to random arrival of these molecules at their binding sites can severely limit the precision of regulation. Recent work on the optimization of information flow through regulatory networks indicates that the lower end of the dynamic range of concentrations is simply inaccessible, overwhelmed by the impact of this noise. Motivated by the behavior of homeodomain proteins, such as the maternal morphogen Bicoid in the fruit fly embryo, we suggest a scheme in which transcription factors also act as indirect translational regulators, binding to the mRNA of other regulatory proteins. Intuitively, each mRNA molecule acts as an independent sensor of the input concentration, and averaging over these multiple sensors reduces the noise. We analyze information flow through this scheme and identify conditions under which it outperforms direct transcriptional regulation. Our results suggest that the dual role of homeodomain proteins is not just a historical accident, but a solution to a crucial physics problem in the regulation of gene expression.}, author = {Sokolowski, Thomas R and Walczak, Aleksandra and Bialek, William and Tkacik, Gasper}, journal = {Physical Review E Statistical Nonlinear and Soft Matter Physics}, number = {2}, publisher = {American Institute of Physics}, title = {{Extending the dynamic range of transcription factor action by translational regulation}}, doi = {10.1103/PhysRevE.93.022404}, volume = {93}, year = {2016}, } @article{1244, abstract = {Cell polarity refers to a functional spatial organization of proteins that is crucial for the control of essential cellular processes such as growth and division. To establish polarity, cells rely on elaborate regulation networks that control the distribution of proteins at the cell membrane. In fission yeast cells, a microtubule-dependent network has been identified that polarizes the distribution of signaling proteins that restricts growth to cell ends and targets the cytokinetic machinery to the middle of the cell. Although many molecular components have been shown to play a role in this network, it remains unknown which molecular functionalities are minimally required to establish a polarized protein distribution in this system. Here we show that a membrane-binding protein fragment, which distributes homogeneously in wild-type fission yeast cells, can be made to concentrate at cell ends by attaching it to a cytoplasmic microtubule end-binding protein. This concentration results in a polarized pattern of chimera proteins with a spatial extension that is very reminiscent of natural polarity patterns in fission yeast. However, chimera levels fluctuate in response to microtubule dynamics, and disruption of microtubules leads to disappearance of the pattern. Numerical simulations confirm that the combined functionality of membrane anchoring and microtubule tip affinity is in principle sufficient to create polarized patterns. Our chimera protein may thus represent a simple molecular functionality that is able to polarize the membrane, onto which additional layers of molecular complexity may be built to provide the temporal robustness that is typical of natural polarity patterns.}, author = {Recouvreux, Pierre and Sokolowski, Thomas R and Grammoustianou, Aristea and Tenwolde, Pieter and Dogterom, Marileen}, journal = {PNAS}, number = {7}, pages = {1811 -- 1816}, publisher = {National Academy of Sciences}, title = {{Chimera proteins with affinity for membranes and microtubule tips polarize in the membrane of fission yeast cells}}, doi = {10.1073/pnas.1419248113}, volume = {113}, year = {2016}, } @article{1248, abstract = {Life depends as much on the flow of information as on the flow of energy. Here we review the many efforts to make this intuition precise. Starting with the building blocks of information theory, we explore examples where it has been possible to measure, directly, the flow of information in biological networks, or more generally where information-theoretic ideas have been used to guide the analysis of experiments. Systems of interest range from single molecules (the sequence diversity in families of proteins) to groups of organisms (the distribution of velocities in flocks of birds), and all scales in between. Many of these analyses are motivated by the idea that biological systems may have evolved to optimize the gathering and representation of information, and we review the experimental evidence for this optimization, again across a wide range of scales.}, author = {Tkacik, Gasper and Bialek, William}, journal = {Annual Review of Condensed Matter Physics}, pages = {89 -- 117}, publisher = {Annual Reviews}, title = {{Information processing in living systems}}, doi = {10.1146/annurev-conmatphys-031214-014803}, volume = {7}, year = {2016}, } @article{1260, abstract = {In this work, the Gardner problem of inferring interactions and fields for an Ising neural network from given patterns under a local stability hypothesis is addressed under a dual perspective. By means of duality arguments, an integer linear system is defined whose solution space is the dual of the Gardner space and whose solutions represent mutually unstable patterns. We propose and discuss Monte Carlo methods in order to find and remove unstable patterns and uniformly sample the space of interactions thereafter. We illustrate the problem on a set of real data and perform ensemble calculation that shows how the emergence of phase dominated by unstable patterns can be triggered in a nonlinear discontinuous way.}, author = {De Martino, Daniele}, journal = {International Journal of Modern Physics C}, number = {6}, publisher = {World Scientific Publishing}, title = {{The dual of the space of interactions in neural network models}}, doi = {10.1142/S0129183116500674}, volume = {27}, year = {2016}, } @article{1266, abstract = {Cortical networks exhibit ‘global oscillations’, in which neural spike times are entrained to an underlying oscillatory rhythm, but where individual neurons fire irregularly, on only a fraction of cycles. While the network dynamics underlying global oscillations have been well characterised, their function is debated. Here, we show that such global oscillations are a direct consequence of optimal efficient coding in spiking networks with synaptic delays and noise. To avoid firing unnecessary spikes, neurons need to share information about the network state. Ideally, membrane potentials should be strongly correlated and reflect a ‘prediction error’ while the spikes themselves are uncorrelated and occur rarely. We show that the most efficient representation is when: (i) spike times are entrained to a global Gamma rhythm (implying a consistent representation of the error); but (ii) few neurons fire on each cycle (implying high efficiency), while (iii) excitation and inhibition are tightly balanced. This suggests that cortical networks exhibiting such dynamics are tuned to achieve a maximally efficient population code.}, author = {Chalk, Matthew J and Gutkin, Boris and Denève, Sophie}, journal = {eLife}, number = {2016JULY}, publisher = {eLife Sciences Publications}, title = {{Neural oscillations as a signature of efficient coding in the presence of synaptic delays}}, doi = {10.7554/eLife.13824}, volume = {5}, year = {2016}, } @article{1290, abstract = {We developed a competition-based screening strategy to identify compounds that invert the selective advantage of antibiotic resistance. Using our assay, we screened over 19,000 compounds for the ability to select against the TetA tetracycline-resistance efflux pump in Escherichia coli and identified two hits, β-thujaplicin and disulfiram. Treating a tetracycline-resistant population with β-thujaplicin selects for loss of the resistance gene, enabling an effective second-phase treatment with doxycycline.}, author = {Stone, Laura and Baym, Michael and Lieberman, Tami and Chait, Remy P and Clardy, Jon and Kishony, Roy}, journal = {Nature Chemical Biology}, number = {11}, pages = {902 -- 904}, publisher = {Nature Publishing Group}, title = {{Compounds that select against the tetracycline-resistance efflux pump}}, doi = {10.1038/nchembio.2176}, volume = {12}, year = {2016}, } @inproceedings{1320, abstract = {In recent years, several biomolecular systems have been shown to be scale-invariant (SI), i.e. to show the same output dynamics when exposed to geometrically scaled input signals (u → pu, p > 0) after pre-adaptation to accordingly scaled constant inputs. In this article, we show that SI systems-as well as systems invariant with respect to other input transformations-can realize nonlinear differential operators: when excited by inputs obeying functional forms characteristic for a given class of invariant systems, the systems' outputs converge to constant values directly quantifying the speed of the input.}, author = {Lang, Moritz and Sontag, Eduardo}, location = {Boston, MA, USA}, publisher = {IEEE}, title = {{Scale-invariant systems realize nonlinear differential operators}}, doi = {10.1109/ACC.2016.7526722}, volume = {2016-July}, year = {2016}, } @article{1332, abstract = {Antibiotic-sensitive and -resistant bacteria coexist in natural environments with low, if detectable, antibiotic concentrations. Except possibly around localized antibiotic sources, where resistance can provide a strong advantage, bacterial fitness is dominated by stresses unaffected by resistance to the antibiotic. How do such mixed and heterogeneous conditions influence the selective advantage or disadvantage of antibiotic resistance? Here we find that sub-inhibitory levels of tetracyclines potentiate selection for or against tetracycline resistance around localized sources of almost any toxin or stress. Furthermore, certain stresses generate alternating rings of selection for and against resistance around a localized source of the antibiotic. In these conditions, localized antibiotic sources, even at high strengths, can actually produce a net selection against resistance to the antibiotic. Our results show that interactions between the effects of an antibiotic and other stresses in inhomogeneous environments can generate pervasive, complex patterns of selection both for and against antibiotic resistance.}, author = {Chait, Remy P and Palmer, Adam and Yelin, Idan and Kishony, Roy}, journal = {Nature Communications}, publisher = {Nature Publishing Group}, title = {{Pervasive selection for and against antibiotic resistance in inhomogeneous multistress environments}}, doi = {10.1038/ncomms10333}, volume = {7}, year = {2016}, } @article{1342, abstract = {A key aspect of bacterial survival is the ability to evolve while migrating across spatially varying environmental challenges. Laboratory experiments, however, often study evolution in well-mixed systems. Here, we introduce an experimental device, the microbial evolution and growth arena (MEGA)-plate, in which bacteria spread and evolved on a large antibiotic landscape (120 × 60 centimeters) that allowed visual observation of mutation and selection in a migrating bacterial front.While resistance increased consistently, multiple coexisting lineages diversified both phenotypically and genotypically. Analyzing mutants at and behind the propagating front,we found that evolution is not always led by the most resistant mutants; highly resistant mutants may be trapped behindmore sensitive lineages.TheMEGA-plate provides a versatile platformfor studying microbial adaption and directly visualizing evolutionary dynamics.}, author = {Baym, Michael and Lieberman, Tami and Kelsic, Eric and Chait, Remy P and Gross, Rotem and Yelin, Idan and Kishony, Roy}, journal = {Science}, number = {6304}, pages = {1147 -- 1151}, publisher = {American Association for the Advancement of Science}, title = {{Spatiotemporal microbial evolution on antibiotic landscapes}}, doi = {10.1126/science.aag0822}, volume = {353}, year = {2016}, } @article{1394, abstract = {The solution space of genome-scale models of cellular metabolism provides a map between physically viable flux configurations and cellular metabolic phenotypes described, at the most basic level, by the corresponding growth rates. By sampling the solution space of E. coliʼs metabolic network, we show that empirical growth rate distributions recently obtained in experiments at single-cell resolution can be explained in terms of a trade-off between the higher fitness of fast-growing phenotypes and the higher entropy of slow-growing ones. Based on this, we propose a minimal model for the evolution of a large bacterial population that captures this trade-off. The scaling relationships observed in experiments encode, in such frameworks, for the same distance from the maximum achievable growth rate, the same degree of growth rate maximization, and/or the same rate of phenotypic change. Being grounded on genome-scale metabolic network reconstructions, these results allow for multiple implications and extensions in spite of the underlying conceptual simplicity.}, author = {De Martino, Daniele and Capuani, Fabrizio and De Martino, Andrea}, journal = {Physical Biology}, number = {3}, publisher = {IOP Publishing Ltd.}, title = {{Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli}}, doi = {10.1088/1478-3975/13/3/036005}, volume = {13}, year = {2016}, } @article{1420, abstract = {Selection, mutation, and random drift affect the dynamics of allele frequencies and consequently of quantitative traits. While the macroscopic dynamics of quantitative traits can be measured, the underlying allele frequencies are typically unobserved. Can we understand how the macroscopic observables evolve without following these microscopic processes? This problem has been studied previously by analogy with statistical mechanics: the allele frequency distribution at each time point is approximated by the stationary form, which maximizes entropy. We explore the limitations of this method when mutation is small (4Nμ < 1) so that populations are typically close to fixation, and we extend the theory in this regime to account for changes in mutation strength. We consider a single diallelic locus either under directional selection or with overdominance and then generalize to multiple unlinked biallelic loci with unequal effects. We find that the maximum-entropy approximation is remarkably accurate, even when mutation and selection change rapidly. }, author = {Bod'ová, Katarína and Tkacik, Gasper and Barton, Nicholas H}, journal = {Genetics}, number = {4}, pages = {1523 -- 1548}, publisher = {Genetics Society of America}, title = {{A general approximation for the dynamics of quantitative traits}}, doi = {10.1534/genetics.115.184127}, volume = {202}, year = {2016}, } @article{1485, abstract = {In this article the notion of metabolic turnover is revisited in the light of recent results of out-of-equilibrium thermodynamics. By means of Monte Carlo methods we perform an exact sampling of the enzymatic fluxes in a genome scale metabolic network of E. Coli in stationary growth conditions from which we infer the metabolites turnover times. However the latter are inferred from net fluxes, and we argue that this approximation is not valid for enzymes working nearby thermodynamic equilibrium. We recalculate turnover times from total fluxes by performing an energy balance analysis of the network and recurring to the fluctuation theorem. We find in many cases values one of order of magnitude lower, implying a faster picture of intermediate metabolism.}, author = {De Martino, Daniele}, journal = {Physical Biology}, number = {1}, publisher = {IOP Publishing Ltd.}, title = {{Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis}}, doi = {10.1088/1478-3975/13/1/016003}, volume = {13}, year = {2016}, } @article{1148, abstract = {Continuous-time Markov chain (CTMC) models have become a central tool for understanding the dynamics of complex reaction networks and the importance of stochasticity in the underlying biochemical processes. When such models are employed to answer questions in applications, in order to ensure that the model provides a sufficiently accurate representation of the real system, it is of vital importance that the model parameters are inferred from real measured data. This, however, is often a formidable task and all of the existing methods fail in one case or the other, usually because the underlying CTMC model is high-dimensional and computationally difficult to analyze. The parameter inference methods that tend to scale best in the dimension of the CTMC are based on so-called moment closure approximations. However, there exists a large number of different moment closure approximations and it is typically hard to say a priori which of the approximations is the most suitable for the inference procedure. Here, we propose a moment-based parameter inference method that automatically chooses the most appropriate moment closure method. Accordingly, contrary to existing methods, the user is not required to be experienced in moment closure techniques. In addition to that, our method adaptively changes the approximation during the parameter inference to ensure that always the best approximation is used, even in cases where different approximations are best in different regions of the parameter space. © 2016 Elsevier Ireland Ltd}, author = {Schilling, Christian and Bogomolov, Sergiy and Henzinger, Thomas A and Podelski, Andreas and Ruess, Jakob}, journal = {Biosystems}, pages = {15 -- 25}, publisher = {Elsevier}, title = {{Adaptive moment closure for parameter inference of biochemical reaction networks}}, doi = {10.1016/j.biosystems.2016.07.005}, volume = {149}, year = {2016}, } @inproceedings{8094, abstract = {With the accelerated development of robot technologies, optimal control becomes one of the central themes of research. In traditional approaches, the controller, by its internal functionality, finds appropriate actions on the basis of the history of sensor values, guided by the goals, intentions, objectives, learning schemes, and so forth. The idea is that the controller controls the world---the body plus its environment---as reliably as possible. This paper focuses on new lines of self-organization for developmental robotics. We apply the recently developed differential extrinsic synaptic plasticity to a muscle-tendon driven arm-shoulder system from the Myorobotics toolkit. In the experiments, we observe a vast variety of self-organized behavior patterns: when left alone, the arm realizes pseudo-random sequences of different poses. By applying physical forces, the system can be entrained into definite motion patterns like wiping a table. Most interestingly, after attaching an object, the controller gets in a functional resonance with the object's internal dynamics, starting to shake spontaneously bottles half-filled with water or sensitively driving an attached pendulum into a circular mode. When attached to the crank of a wheel the neural system independently discovers how to rotate it. In this way, the robot discovers affordances of objects its body is interacting with.}, author = {Martius, Georg S and Hostettler, Rafael and Knoll, Alois and Der, Ralf}, booktitle = {Proceedings of the Artificial Life Conference 2016}, isbn = {9780262339360}, location = {Cancun, Mexico}, pages = {142--143}, publisher = {MIT Press}, title = {{Self-organized control of an tendon driven arm by differential extrinsic plasticity}}, doi = {10.7551/978-0-262-33936-0-ch029}, volume = {28}, year = {2016}, }