Finding and defining the natural automata acting in living plants: Toward the synthetic biology for robotics and informatics in vivo

Plants have two minds as we do

This discussion paper carefully analyzes the cognition-related theories proposed for behavioral economics, to expand the concepts from human behaviors to those of plants. Behavioral economists analyze the roles of the intuitive sense and the rational thoughts affecting the human behavior, by employing the psychology-based models such as Two Minds theory (TMT) highlighting intuitive rapid thoughts (System 1) and rational slower thoughts (System 2) and Prospect theory (PT) with probability (p)-weighting functions explaining the human tendencies to overrate the low p events and to underrate the high p events. There are similarities between non-consciously processed System 1 (of TMT) and overweighing of low-p events (as in PT) and also, between the consciously processed System 2 (of TMT) and underrating of high-p events (as in PT). While most known p-weighting mathematical models employed single functions, we propose a pair of Hill-type functions reflecting the collective behaviors of two types of automata corresponding to intuition (System 1) and rationality (System 2), as a metaphor to the natural light processing in layered plant leaves. Then, the model was applied to two different TMT/PT-related behaviors, namely, preference reversal and habituation. Furthermore, we highlight the behaviors of plants through the above conceptual frameworks implying that plants behave as if they have Two Minds. Lastly, the possible evolutionary origins of the nature of Two Minds are discussed.

How (not) to Talk to a Plant: An Application of Automata Theory to Plant Communication

Plants are capable of a range of complex interactions with the environment. Over the last decade, some authors have used this as evidence to argue that plants are cognitive agents. While there is no consensus on this view, it is certainly interesting to approach the debate from a comparative perspective, trying to understand whether different lineages of plants show different degrees of responsiveness to environmental cues, and how their responses compare with those of animals or humans. In this paper, I suggest that a potentially fruitful approach to these comparative studies is provided by automata theory. Accordingly, I shall present a possible application of this theory to plant communication. Two tentative results will emerge. First, that different lineages may exhibit different levels of complexity in response to similar stimuli. Second, that current evidence does not allow to infer great cognitive sophistication in plants.

Bio-mimic energy storage system with solar light conversion to hydrogen by combination of photovoltaic devices and electrochemical cells inspired by the antenna-associated photosystem II

Global warming caused by anthropogenic activity is one of the serious problems today. In order to suppress the global warming, the shift from fossil fuel-based energy source to the nature-oriented sustainable energy is encouraged. In this concept paper, possible biomimetic engineering approach inspired by the efficient and sustainable natural energy utilization in living plants is demonstrated. The focal features in plants include (1) the light-harvesting and energy condensing apparatus, (2) water splitting O₂ evolving apparatus, (3) storage of energy-related chemicals, and (4) reversal conversion of storage into the "energy in use" by meeting the demands. Demonstration of solar-driven chemical energy conversion was performed using a system consisted of (i) photovoltaic power-generating device, (ii) an electrochemical unit converting electric power into chemical energy, (iii) storage of H₂, and (iv) polymer electrolyte cells converting H₂ back to electricity by meeting the demands on site. The present concept paper presenting a technical perspective based on the plant-inspired knowledge (conceptual similarity between natural photosynthesis and solar-to-H₂ conversion) is a fruit of interdisciplinary collaboration between the team of chemical energy conversion renown for the world highest record of solar-to-hydrogen conversion efficiency (24.4%, as of 2015) and a group of plant biologists.

How Organisms Gained Causal Independence and How It Might Be Quantified

Two broad features are jointly necessary for autonomous agency: organisational closure and the embodiment of an objective-function providing a ‘goal’: so far only organisms demonstrate both. Organisational closure has been studied (mostly in abstract), especially as cell autopoiesis and the cybernetic principles of autonomy, but the role of an internalised ‘goal’ and how it is instantiated by cell signalling and the functioning of nervous systems has received less attention. Here I add some biological ‘flesh’ to the cybernetic theory and trace the evolutionary development of step-changes in autonomy: (1) homeostasis of organisationally closed systems; (2) perception-action systems; (3) action selection systems; (4) cognitive systems; (5) memory supporting a self-model able to anticipate and evaluate actions and consequences. Each stage is characterised by the number of nested goal-directed control-loops embodied by the organism, summarised as will-nestedness N. Organism tegument, receptor/transducer system, mechanisms of cellular and whole-organism re-programming and organisational integration, all contribute to causal independence.

CONCLUSION

organisms are cybernetic phenomena whose identity is created by the information structure of the highest level of causal closure (maximum N), which has increased through evolution, leading to increased causal independence, which might be quantifiable by ‘Integrated Information Theory’ measures.

Plant Science View on Biohybrid Development

Biohybrid consists of a living organism or cell and at least one engineered component. Designing robot-plant biohybrids is a great challenge: it requires interdisciplinary reconsideration of capabilities intimate specific to the biology of plants. Envisioned advances should improve agricultural/horticultural/social practice and could open new directions in utilization of plants by humans. Proper biohybrid cooperation depends upon effective communication. During evolution, plants developed many ways to communicate with each other, with animals, and with microorganisms. The most notable examples are: the use of phytohormones, rapid long-distance signaling, gravity, and light perception. These processes can now be intentionally re-shaped to establish plant-robot communication. In this article, we focus on plants physiological and molecular processes that could be used in bio-hybrids. We show phototropism and biomechanics as promising ways of effective communication, resulting in an alteration in plant architecture, and discuss the specifics of plants anatomy, physiology and development with regards to the bio-hybrids. Moreover, we discuss ways how robots could influence plants growth and development and present aims, ideas, and realized projects of plant-robot biohybrids.

Discrete Biochemistry of DNA: Arithmetic DNA Molecules for Binary Additions, Naturally Found Genetic Logic Circuits for Plant Sensing, and DNA-Based Animation

To date, a number of researchers are seeking for and/or designing novel molecules which function as arithmetic molecular engines. Biomolecules such as deoxyribonucleic acid (DNA) and proteins are examples of promising candidate molecules. In the present article, we showed our view that DNA-based molecules could be used as a novel class of platforms for discrete mathematical operations or tools for natural computation. Here, we report on a novel molecular logic circuit combining exclusive disjunction (XOR) gate and conjunction (AND) gate implemented on a single DNA molecule performing arithmetic operations with simple binary numbers through polymerase chain reactions (PCR); which was inspired by previously developed protein-based computing model allowing simple polynomial algebra over fields through algebraic representation of cyclic inter-conversions in the catalytic modes of a plant enzyme as a cyclic additive group. In addition, we showed that DNA can be used as the platform for image coding and processing leading to DNA-coded animation by using novel PCR-based protocols. Lastly, we discussed the significance of recent attempts in the stream of natural computing and synthetic biological research, by handling DNA and related biomolecules as the media for discrete mathematical operations.

Run-Length Encoding Graphic Rules Applied to DNA-Coded Images and Animation Editable by Polymerase Chain Reactions

We previously proposed novel designs for artificial genes as media for storing digitally compressed image data, specifically for biocomputing by analogy to natural genes mainly used to encode proteins. A run-length encoding (RLE) rule had been applied in DNA-based image data processing, to form coding regions, and noncoding regions were created as space for designing biochemical editing. In the present study, we apply the RLE-based image-coding rule to creation of DNAbased animation. This article consisted of three parts: (i) a theoretical review of RLE-based image coding by DNA, (ii) a technical proposal for biochemical editing of DNA-coded images using the polymerase chain reaction, and (iii) a minimal demonstration of DNAbased animation using simple model images encoded on short DNA molecules.

Platform for Two-Dimensional Cellular Automata Models Implemented by Living Cells of Electrically Controlled Green Paramecia Designed for Transport of Micro-Particles

Microscopic traffic flow models are a class of scientific models of vehicular traffic dynamics. Here, we attempted to establish an experimental platform for mimicking microscopic traffic flow models at microscopic dimensions. We achieved this, by monitoring the flow of micro-sized particles transported by the motile cells of living microorganisms. Some researchers have described the cells of protozoan species as “swimming neurons” or “swimming sensory cells” applicable to biological micro-electro-mechanical systems or micro-biorobotics. Therefore these cells, in a controlled environment, may form a good model system for bio-implementable cellular automata for traffic simulation. The living cells of theParameciumspecies including those of green paramecia (Paramecium bursaria), actively migrate towards a negatively charged electrode when exposed to an electric field. This type of cellular movement is known as galvanotaxis.P. bursariawas chosen as amodel organismsince the ideal micro-vehicles required for micro-particle transport must have a particular particle packing capacity within the cells. The present study establishes that the movement of cells with or without the loading of microspheres (Φ, 9.75 µm) can be controlled on a two-dimensional plane under strict electrical controls. Lastly, implementation of microchips equipped with optimally sized micro-flow channels that allow the single-cell traffic of swimmingP. bursariawas proposed for further studies and mathematical modeling.

The biological microprocessor, or how to build a computer with biological parts

Systemics, a revolutionary paradigm shift in scientific thinking, with applications in systems biology, and synthetic biology, have led to the idea of using silicon computers and their engineering principles as a blueprint for the engineering of a similar machine made from biological parts. Here we describe these building blocks and how they can be assembled to a general purpose computer system, a biological microprocessor. Such a system consists of biological parts building an input / output device, an arithmetic logic unit, a control unit, memory, and wires (busses) to interconnect these components. A biocomputer can be used to monitor and control a biological system.

Run-length encoding graphic rules, biochemically editable designs and steganographical numeric data embedment for DNA-based cryptographical coding system

There have been a wide variety of approaches for handling the pieces of DNA as the "unplugged" tools for digital information storage and processing, including a series of studies applied to the security-related area, such as DNA-based digital barcodes, water marks and cryptography. In the present article, novel designs of artificial genes as the media for storing the digitally compressed data for images are proposed for bio-computing purpose while natural genes principally encode for proteins. Furthermore, the proposed system allows cryptographical application of DNA through biochemically editable designs with capacity for steganographical numeric data embedment. As a model case of image-coding DNA technique application, numerically and biochemically combined protocols are employed for ciphering the given "passwords" and/or secret numbers using DNA sequences. The "passwords" of interest were decomposed into single letters and translated into the font image coded on the separate DNA chains with both the coding regions in which the images are encoded based on the novel run-length encoding rule, and the non-coding regions designed for biochemical editing and the remodeling processes revealing the hidden orientation of letters composing the original "passwords." The latter processes require the molecular biological tools for digestion and ligation of the fragmented DNA molecules targeting at the polymerase chain reaction-engineered termini of the chains. Lastly, additional protocols for steganographical overwriting of the numeric data of interests over the image-coding DNA are also discussed.