Information-Theoretic Aspects of Control in a Bio-Hybrid Robot Device

Information processing in natural systems radically differs from current information technology. This difference is particularly apparent in the area of robotics, where both organisms and artificial devices face a similar challenge: the need to act in real time in a complex environment and to do so with computing resources severely limited by their size and power consumption. The formidable gap between artificial and natural systems in terms of information processing capability motivates research into the biological modes of information processing. Such undertakings, however, are hampered by the fact that nature directly exploits the manifold physical characteristics of its computing substrates, while available theoretical tools in general ignore the underlying implementation. Here we sketch the concept of bounded computability in an attempt towards reconciling the information-theoretic perspective with the need to take the material basis of information processing into account. We do so in the context of Physarum polycephalum as a naturally evolved information processor and the use of this organism as an integral component of a robot controller

Robot control with biological cells

At present there exists a large gap in size, performance, adaptability and robustness between natural and artificial information processors for performing coherent perception-action tasks under real-time constraints. Even the simplest organisms have an enviable capability of coping with an unknown dynamic environment. Robots, in contrast, are still clumsy if confronted with such complexity. This paper presents a bio-hybrid architecture developed for exploring an alternate approach to the control of autonomous robots. Circuits prepared from amoeboid plasmodia of the slime mold Physarum polycephalum are interfaced with an omnidirectional hexapod robot. Sensory signals from the macro-physical environment of the robot are transduced to cellular scale and processed using the unique micro-physical features of intracellular information processing. Conversely, the response form the cellular computation is amplified to yield a macroscopic output action in the environment mediated through the robot’s actuators

Population–reaction model and microbial experimental ecosystems for understanding hierarchical dynamics of ecosystems

Understanding ecosystem dynamics is crucial as contemporary human societies face ecosystem degradation. One of the challenges that needs to be recognized is the complex hierarchical dynamics. Conventional dynamic models in ecology often represent only the population level and have yet to include the dynamics of the sub-organism level, which makes an ecosystem a complex adaptive system that shows characteristic behaviors such as resilience and regime shifts. The neglect of the sub-organism level in the conventional dynamic models would be because integrating multiple hierarchical levels makes the models unnecessarily complex unless supporting experimental data are present. Now that large amounts of molecular and ecological data are increasingly accessible in microbial experimental ecosystems, it is worthwhile to tackle the questions of their complex hierarchical dynamics. Here, we propose an approach that combines microbial experimental ecosystems and a hierarchical dynamic model named population–reaction model. We present a simple microbial experimental ecosystem as an example and show how the system can be analyzed by a population–reaction model. We also show that population–reaction models can be applied to various ecological concepts, such as predator–prey interactions, climate change, evolution, and stability of diversity. Our approach will reveal a path to the general understanding of various ecosystems and organisms

Computing Substrates and Life

Alive matter distinguishes itself from inanimate matter by actively maintaining a high degree of inhomogenous organisation. Information processing is quintessential to this capability. The present paper inquires into the degree to which the information processing aspect of living systems can be abstracted from the physical medium of its implementation. Information processing serving to sustain the complex organisation of a living system faces both the harsh reality of real-time requirements and severe constraints on energy and material that can be expended on the task. This issue is of interest for the potential scope of Artificial Life and its interaction with Synthetic Biology. It is pertinent also for information technology. With regard to the latter aspect, the use of a living cell in a robot control architecture is considered

Shape transformations of lipid vesicles by insertion of bulky-head lipids

Lipid vesicles, in particular Giant Unilamellar Vesicles (GUVs), have been increasingly important as compartments of artificial cells to reconstruct living cell-like systems in a bottom-up fashion. Here, we report shape transformations of lipid vesicles induced by polyethylene glycol-lipid conjugate (PEG lipids). Statistical analysis of deformed vesicle shapes revealed that shapes vesicles tend to deform into depended on the concentration of the PEG lipids. When compared with theoretically simulated vesicle shapes, those shapes were found to be more energetically favorable, with lower membrane bending energies than other shapes. This result suggests that the vesicle shape transformations can be controlled by externally added membrane molecules, which can serve as a potential method to control the replications of artificial cells

Liposome-based liquid handling platform featuring addition, mixing, and aliquoting of femtoliter volumes

This paper describes the utilization of giant unilamellar vesicles (GUVs) as a platform for handling chemical and biochemical reagents. GUVs with diameters of 5 to 10 µm and containing chemical/biochemical reagents together with inert polymers were fused with electric pulses (electrofusion). After reagent mixing, the fused GUVs spontaneously deformed to a budding shape, separating the mixed solution into sub-volumes. We utilized a microfluidic channel and optical tweezers to select GUVs of interest, bring them into contact, and fuse them together to mix and aliquot the reaction product. We also show that, by lowering the ambient temperature close to the phase transition temperature Tm of the lipid used, daughter GUVs completely detached (fission). This process performs all the liquid-handing features used in bench-top biochemistry using the GUV, which could be advantageous for the membrane-related biochemical assays

Towards heterotic computing with droplets in a fully automated droplet-maker platform

The control and prediction of complex chemical systems is a difficult problem due to the nature of the interactions, transformations and processes occurring. From self-assembly to catalysis and self-organization, complex chemical systems are often heterogeneous mixtures that at the most extreme exhibit system-level functions, such as those that could be observed in a living cell. In this paper, we outline an approach to understand and explore complex chemical systems using an automated droplet maker to control the composition, size and position of the droplets in a predefined chemical environment. By investigating the spatio-temporal dynamics of the droplets, the aim is to understand how to control system-level emergence of complex chemical behaviour and even view the system-level behaviour as a programmable entity capable of information processing. Herein, we explore how our automated droplet-maker platform could be viewed as a prototype chemical heterotic computer with some initial data and example problems that may be viewed as potential chemically embodied computations

Time-programmable drug dosing allows the manipulation, suppression and reversal of antibiotic drug resistance in vitro

Multi-drug strategies have been attempted to prolong the efficacy of existing antibiotics, but with limited success. Here we show that the evolution of multi-drug-resistant Escherichia coli can be manipulated in vitro by administering pairs of antibiotics and switching between them in ON/OFF manner. Using a multiplexed cell culture system, we find that switching between certain combinations of antibiotics completely suppresses the development of resistance to one of the antibiotics. Using this data, we develop a simple deterministic model, which allows us to predict the fate of multi-drug evolution in this system. Furthermore, we are able to reverse established drug resistance based on the model prediction by modulating antibiotic selection stresses. Our results support the idea that the development of antibiotic resistance may be potentially controlled via continuous switching of drugs

Efficient enzyme discovery from complex environmental microbiota using microbial single-cell sequencing

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Ionic Liquid Fluorohydrogenates and Their Applications

The recent results are described on the developments of ionic liquid (IL) fluorohydrogenates with high ionic conductivities and wide electrochemical windows. Several cyclic ammonium cations have been found to be combined with fluorohydrogenate anions giving a vacuum stable ionic liquid fluorohydrogenates, Cat+[(FH)2.3F]−. N-ethyl-N-methylpyrrolidinium fluorohydrogenate, EMPyrro(FH)2.3F, and N-allylpyrridinium fluorohydrogenate, APyrrid(FH)2.3F, exhibit wide electrochemical windows of around 5 V. A fluorohydrogenate fuel cell (FHFC) using HF-deficient IL, 1-ethyl-3-methyl- imidazolium fluorohydrogenate, EMIm(FH)1.3F, as the electrolyte operates at 120{degree sign}C without humidification. The maximum output power so far obtained in the preliminary cell test is 41 mWcm-2 (0.41 V and 100 mA cm-2) at 40{degree sign}C without humidification