True Slime Mold Physarum Polycephalum Research Articles

Analysis of the trehalose synthesis pathway of Physarum polycehalum

Desiccation is a severe survival problem for organisms. We have been studying the desiccation tolerance mechanisms in the true slime mold Physarum polycephalum. We measured the trehalose content of P. polycephalum vegetative cells (plasmodia) and drought cells (sclerotia). Surprisingly, we found that the content in sclerotia was about 473-fold greater than in the plasmodia. We then examined trehalose metabolism-related genes via RNAseq, and consequently found that trehalose 6-phosphate phosphorylase (T6pp) expression levels increased following desiccation. Next, we cloned and expressed the genes for T6pp, trehalose 6-phosphate synthase/phosphatase (Tps/Tpp), maltooligosyltrehalose trehalohydrolase (TreZ), and maltooligosyltrehalose synthase (TreY) in E. coli. Incidentally, TreY and TreZ clones have been reported in several prokaryotes, but not in eukaryotes. This report in P. polycephalum is the first evidence of their presence in a eukaryote species. Recombinant T6pp, TreY, and TreZ were purified and confirmed to be active. Our results showed that these enzymes catalyze reactions related to trehalose production, and their reaction kinetics follow the Michaelis-Menten equation.The t6pp mRNA levels of the sclerotia were about 15-fold higher than in the plasmodia. In contrast, the expression levels of TreZ and TreY showed no significant change between the sclerotia and plasmodia. Thus, T6pp is probably related to desiccation tolerance, whereas the contribution of TreY and TreZ is insufficient to account for the considerable accumulation of trehalose in sclerotia.

Two-carba cyclic phosphatidic acid treatment promotes phenotypic switch from M1 to M2 microglia and prevents behavioral abnormalities in a mouse model of neuropsychiatric systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is an autoimmune disease associated with the production of double-stranded DNA (dsDNA) antibodies and other antibodies that predominantly affects women with a wide range of lesions. Although neuropsychiatric lupus erythematosus (NPSLE), characterized by neuropsychiatric symptoms related to cerebrovascular diseases or depression, ranks high in severity, no specific treatment has been defined. Two-carba cyclic phosphatidic acid (2ccPA), a derivative of cyclic phosphatidic acid, was isolated from the true slime mold Physarum polycephalum in 1992. 2ccPA treatment suppresses neuroinflammation and promotes tissue repair in mouse multiple sclerosis and traumatic brain injury models. In this study, we performed behavioral tests on MRL/lpr mice as an NPSLE model. MRL/lpr mice showed increased depression-like behaviors compared with control mice, which were significantly suppressed by 2ccPA treatment. The expression of CD68, an M1 phenotypic marker of microglia, was significantly elevated in the prefrontal cortex and hippocampus of MRL/lpr mice, which was significantly suppressed by 2ccPA treatment. In contrast, the expression of Arginase1, an M2 phenotypic marker of microglia, was significantly increased by 2ccPA treatment. Compared to control mice, MRL/lpr mice showed higher plasma levels of anti-dsDNA antibodies, which are mainly involved in SLE pathogenesis. 2ccPA treatment decreased these levels in the MRL/lpr mice. These results suggest that 2ccPA treatment suppresses behavioral abnormalities by promoting a microglial phenotypic switch from M1 to M2 in MRL/lpr mice.

Emergence of dynamic contractile patterns in slime mold confined in a ring geometry

Coordination of cytoplasmic flows on large scales in space and time are at the root of many cellular processes, including growth, migration or division. These flows are driven by organized contractions of the actomyosin cortex. In order to elucidate the basic mechanisms at work in the self-organization of contractile activity, we investigate the dynamic patterns of cortex contraction in true slime mold Physarum polycephalum confined in ring-shaped chambers of controlled geometrical dimensions. We make an exhaustive inventory of the different stable contractile patterns in the absence of migration and growth. We show that the primary frequency of the oscillations is independent of the ring perimeter, while the wavelength scales linearly with it. We discuss the consistence of these results with the existing models, shedding light on the possible feedback mechanisms leading to coordinated contractile activity.

Symmetry breaking transition towards directional locomotion in Physarum microplasmodia

True slime mold Physarum polycephalum has been widely used as a model organism to study flow-driven amoeboid locomotion as well as the dynamics of its complex mechanochemical self-oscillations. The aim of this work is to quantify the mechanical aspects of symmetry breaking and its transition into directional flow-driven amoeboid locomotion in small (<m) fragments of Physarum polycephalum. To this end, we combined measurements of traction stresses, fragment morphology, and ectoplasmic microrheology with experimental manipulations of cell–substrate adhesion, cortical strength, and microplasmodium size. These measurements show that initiation of locomotion is accompanied by the symmetry breaking of traction stresses and the polarization of ectoplasmic mechanical properties, with the rear part of the microplasmodium becoming significantly stiffer after the onset of locomotion. Our experimental data suggest that the initiation of locomotion in Physarum could be analogous to an interfacial instability process and that microplasmodial size is a critical parameter governing the instability. Specifically, our results indicate that the instability driving the onset of locomotion is strengthened by substrate adhesiveness and weakened by cortical stiffness. Furthermore, the Fourier spectral analysis of morphology revealed lobe number n = 2 as the consistent dominant mode number across various experimental manipulations, suggesting that the instability mechanism driving the onset of Physarum locomotion is robust with respect to changes in environmental conditions and microplasmodial properties.

Lessons from a virtual slime: marginal mechanisms, minimal cognition and radical enactivism

Radical enactivism (REC) and similar embodied and enactive approaches to the mind deny that cognition is fundamentally representational, skull-bound and mechanistic in its organisation. In this article, I argue that modellers may still adopt a mechanistic strategy to produce explanations that are compatible with REC. This argument is scaffolded by a multi-agent model of the true slime mould Physarum polycephalum.

Spatial mapping reveals multi-step pattern of wound healing in Physarum polycephalum

Wounding is a severe impairment of function, especially for an exposed organism like the network-forming true slime mould Physarum polycephalum. The tubular network making up the organism’s body plan is entirely interconnected and shares a common cytoplasm. Oscillatory contractions of the enclosing tube walls drive the shuttle streaming of the cytoplasm. Cytoplasmic flows underlie the reorganization of the network for example by movement toward attractive stimuli or away from repellants. Here, we follow the reorganization of P. polycephalum networks after severe wounding. Spatial mapping of the contraction changes in response to wounding reveal a multi-step pattern. Phases of increased activity alternate with cessation of contractions and stalling of flows, giving rise to coordinated transport and growth at the severing site. Overall, severing surprisingly acts like an attractive stimulus enabling healing of severed tubes. The reproducible cessation of contractions arising during this wound-healing response may open up new venues to investigate the biochemical wiring underlying P. polycephalum’s complex behaviours.

Analysis of peristaltic waves and their role in migrating Physarum plasmodia

The true slime mold Physarum polycephalum exhibits a vast array of sophisticated manipulations of its intracellular cytoplasm. Growing microplasmodia of Physarum have been observed to adopt an elongated tadpole shape, then contract in a rhythmic, traveling wave pattern that resembles peristaltic pumping. This contraction drives a fast flow of non-gelated cytoplasm along the cell longitudinal axis. It has been hypothesized that this flow of cytoplasm is a driving factor in generating motility of the plasmodium. In this work, we use two different mathematical models to investigate how peristaltic pumping within Physarum may be used to drive cellular motility. We compare the relative phase of flow and deformation waves predicted by both models to similar phase data collected from in vivo experiments using Physarum plasmodia. The first is a PDE model based on a dimensional reduction of peristaltic pumping within a finite length chamber. The second is a more sophisticated computational model which accounts for more general shape changes, more complex cellular mechanics, and dynamically modulated adhesion to the underlying substrate. This model allows us to directly compute cell crawling speed. Both models suggest that a mechanical asymmetry in the cell is required to reproduce the experimental observations. Such a mechanical asymmetry is also shown to increase the potential for cellular migration, as measured by both stress generation and migration velocity.

Response to various periods of mechanical stimuli in Physarum plasmodium

Response to mechanical stimuli is a fundamental and critical ability for living cells to survive in hazardous conditions or to form adaptive and functional structures against force(s) from the environment. Although this ability has been extensively studied by molecular biology strategies, it is also important to investigate the ability from the viewpoint of biological rhythm phenomena so as to reveal the mechanisms that underlie these phenomena. Here, we use the plasmodium of the true slime mold Physarum polycephalum as the experimental system for investigating this ability. The plasmodium was repetitively stretched for various periods during which its locomotion speed was observed. Since the plasmodium has inherent oscillation cycles of protoplasmic streaming and thickness variation, how the plasmodium responds to various periods of external stretching stimuli can shed light on the other biological rhythm phenomena. The experimental results show that the plasmodium exhibits response to periodic mechanical stimulation and changes its locomotion speed depending on the period of the stretching stimuli.

Self-organized mechano-chemical dynamics in amoeboid locomotion of Physarum fragments

The aim of this work is to quantify the spatio-temporal dynamics of flow-driven amoeboid locomotion in small (∼100 μm) fragments of the true slime mold Physarum polycephalum. In this model organism, cellular contraction drives intracellular flows, and these flows transport the chemical signals that regulate contraction in the first place. As a consequence of these non-linear interactions, a diversity of migratory behaviors can be observed in migrating Physarum fragments. To study these dynamics, we measure the spatio-temporal distributions of the velocities of the endoplasm and ectoplasm of each migrating fragment, the traction stresses it generates on the substratum, and the concentration of free intracellular calcium. Using these unprecedented experimental data, we classify migrating Physarum fragments according to their dynamics, finding that they often exhibit spontaneously coordinated waves of flow, contractility and chemical signaling. We show that Physarum fragments exhibiting symmetric spatio-temporal patterns of endoplasmic flow migrate significantly slower than fragments with asymmetric patterns. In addition, our joint measurements of ectoplasm velocity and traction stress at the substratum suggest that forward motion of the ectoplasm is enabled by a succession of stick-slip transitions, which we conjecture are also organized in the form of waves. Combining our experiments with a simplified convection-diffusion model, we show that the convective transport of calcium ions may be key for establishing and maintaining the spatio-temporal patterns of calcium concentration that regulate the generation of contractile forces.

Structural machines and slime mould computation

A Physarum machine is a programmable amorphous biological computer experimentally implemented in the vegetative state of true slime mould Physarum polycephalum. It comprises an amorphous yellowish mass with networks of protoplasmic veins, programmed by spatial configurations of attracting and repelling gradients. The goal of this paper to advance formalism of Physarum machines providing theoretical tools for exploration of possibilities of these machines and extension of their applications. To achieve this goal, we introduce structural machines and study their properties.

The role of noise in self-organized decision making by the true slime mold Physarum polycephalum.

Self-organized mechanisms are frequently encountered in nature and known to achieve flexible, adaptive control and decision-making. Noise plays a crucial role in such systems: It can enable a self-organized system to reliably adapt to short-term changes in the environment while maintaining a generally stable behavior. This is fundamental in biological systems because they must strike a delicate balance between stable and flexible behavior. In the present paper we analyse the role of noise in the decision-making of the true slime mold Physarum polycephalum, an important model species for the investigation of computational abilities in simple organisms. We propose a simple biological experiment to investigate the reaction of P. polycephalum to time-variant risk factors and present a stochastic extension of an established mathematical model for P. polycephalum to analyze this experiment. It predicts that—due to the mechanism of stochastic resonance—noise can enable P. polycephalum to correctly assess time-variant risk factors, while the corresponding noise-free system fails to do so. Beyond the study of P. polycephalum we demonstrate that the influence of noise on self-organized decision-making is not tied to a specific organism. Rather it is a general property of the underlying process dynamics, which appears to be universal across a wide range of systems. Our study thus provides further evidence that stochastic resonance is a fundamental component of the decision-making in self-organized macroscopic and microscopic groups and organisms.

Decision-making ability of Physarum polycephalum enhanced by its coordinated spatiotemporal oscillatory dynamics

An amoeboid unicellular organism, a plasmodium of the true slime mold Physarum polycephalum, exhibits complex spatiotemporal oscillatory dynamics and sophisticated information processing capabilities while deforming its amorphous body. We previously devised an ‘amoeba-based computer (ABC),’ that implemented optical feedback control to lead this amoeboid organism to search for a solution to the traveling salesman problem (TSP). In the ABC, the shortest TSP route (the optimal solution) is represented by the shape of the organism in which the body area (nutrient absorption) is maximized while the risk of being exposed to aversive light stimuli is minimized. The shortness of the TSP route found by ABC, therefore, serves as a quantitative measure of the optimality of the decision made by the organism. However, it remains unclear how the decision-making ability of the organism originates from the oscillatory dynamics of the organism. We investigated the number of coexisting traveling waves in the spatiotemporal patterns of the oscillatory dynamics of the organism. We show that a shorter TSP route can be found when the organism exhibits a lower number of traveling waves. The results imply that the oscillatory dynamics are highly coordinated throughout the global body. Based on the results, we discuss the fact that the decision-making ability of the organism can be enhanced not by uncorrelated random fluctuations, but by its highly coordinated oscillatory dynamics.

Enhancing adaptability of amoeboid robot by synergetically coupling two decentralized controllers inspired by true slime mold

Autonomous decentralized control is a key concept for understanding the adaptive and versatile behaviors of living systems. To establish a design methodology for such a controller for robotic systems, we have proposed a fully decentralized control system, inspired by biochemical oscillators in true slime mold ( Physarum polycephalum), which allows a modular robot to exhibit adaptive and versatile behaviors. However, in real living systems, many adaptation mechanisms with different time constants co-exist without conflict in the body (e.g., reflex, learning, growth and evolution); this contributes to the amazingly resilient and intelligent behaviors of living systems. It is well known that in true slime mold, long time-scale morphological changes coexist with the oscillatory behavior stemming from biochemical oscillators. In the present study, we have designed a mathematical model and real physical robot in which two decentralized controllers are incorporated. Numerical and experimental results show that by combining the controllers with different time constants, a robot can use the proposed model to successfully negotiate a narrow aisle by deforming its body shape dynamically.

Mechanisms Inducing Parallel Computation in a Model of Physarum polycephalum Transport Networks

The giant amoeboid organism true slime mould Physarum polycephalum dynamically adapts its body plan in response to changing environmental conditions and its protoplasmic transport network is used to distribute nutrients within the organism. These networks are efficient in terms of network length and network resilience and are parallel approximations of a range of proximity graphs and plane division problems. The complex parallel distributed computation exhibited by this simple organism has since served as an inspiration for intensive research into distributed computing and robotics within the last decade. P. polycephalum may be considered as a spatially represented parallel unconventional computing substrate, but how can this ‘computer’ be programmed? In this paper we examine and catalogue individual low-level mechanisms which may be used to induce network formation and adaptation in a multi-agent model of P. polycephalum. These mechanisms include those intrinsic to the model (particle sensor angle, rotation angle, and scaling parameters) and those mediated by the environment (stimulus location, distance, angle, concentration, engulfment and consumption of nutrients, and the presence of simulated light irradiation, repellents and obstacles). The mechanisms induce a concurrent integration of chemoattractant and chemorepellent gradients diffusing within the 2D lattice upon which the agent population resides, stimulating growth, movement, morphological adaptation and network minimisation. Chemoattractant gradients, and their modulation by the engulfment and consumption of nutrients by the model population, represent an efficient outsourcing of spatial computation. The mechanisms may prove useful in understanding the search strategies and adaptation of distributed organisms within their environment, in understanding the minimal requirements for complex adaptive behaviours, and in developing methods of spatially programming parallel unconventional computers and robotic devices.

A morphological adaptation approach to path planning inspired by slime mould

Path planning is a classic problem in computer science and robotics which has recently been implemented in unconventional computing substrates such as chemical reaction–diffusion computers. These novel computing schemes utilise the parallel spatial propagation of information and often use a two-stage method involving diffusive propagation to discover all paths and a second stage to highlight or visualise the path between two particular points in the arena. The true slime mould Physarum polycephalum is known to construct efficient transport networks between nutrients in its environment. These networks are continuously remodelled as the organism adapts its body plan to changing spatial stimuli. It can be guided towards attractant stimuli (nutrients, warm regions) and it avoids locations containing hazardous stimuli (light irradiation, repellents, or regions occupied by predatory threats). Using a particle model of slime mould we demonstrate scoping experiments which explore how path planning may be performed by morphological adaptation. We initially demonstrate simple path planning by a shrinking blob of virtual plasmodium between two attractant sources within a polygonal arena. We examine the case where multiple paths are required and the subsequent selection of a single path from multiple options. Collision-free paths are implemented via repulsion from the borders of the arena. Finally, obstacle avoidance is implemented by repulsion from obstacles as they are uncovered by the shrinking blob. These examples show proof-of-concept results of path planning by morphological adaptation which complement existing research on path planning in novel computing substrates.

Soft-bodied amoeba-inspired robot that switches between qualitatively different behaviors with decentralized stiffness control

The goal of this research is to understand the underlying mechanism of the behavioral diversity of animals and then use the findings to build truly adaptive robots. Behavioral diversity is an inherent feature of all animals, and it is also important for robots to perform adaptively in unknown and dynamically changing environments. This feature enables animals to select adaptive behavior from among versatile behaviors. However, most designers have avoided or ignored behavioral diversity while constructing artificial systems, with the aim of achieving highly optimized performance in specific environments for given tasks; this leads to vulnerability of these systems to environmental changes. To understand how behavioral diversity can be embedded into artificial systems, we focus on a large amoeba-like unicellular organism, i.e., the plasmodium of true slime mold ( Physarum polycephalum), in this study. Despite the absence of a central nervous system, the plasmodium exhibits various types of locomotion (i.e., exploratory, taxis, and escape behaviors) and switches its behavior depending on the environment. Inspired by this primitive yet intelligent living organism, we build a modular robot that exhibits exploratory and taxis locomotions, and spontaneously switches between them in a fully decentralized manner according to the situation encountered. The results are expected to shed new light on a design scheme for life-like robots that exhibit amazingly versatile and adaptive behaviors.

Amoeba-inspired SAT Solver

†Flucto-order Functions Research Team, RIKEN Advanced Science Institute,‡Tokyo Tech-RIKEN International School, Tokyo Institute of Technology,2-1, Hirosawa, Wako, Saitama 351-0198, Japan£Photonic Network Research Institute, National Institute of Information and Communications Technology,4-2-1 Nukui-kita, Koganei, Tokyo 184-8795, Japan§Graduate School of Engineering, The University of Tokyo,2-11-16 Yayoi, Bunkyo-ku, Tokyo 113-8656, Japan¶Interdisciplinary Graduate School of Medical and Engineering, University of Yamanashi,Kofu 400-8511, JapanEmail: masashi.aono@riken.jpAbstract—We propose a biologically-inspired comput-ing algorithm called “AmoebaSAT” for solving an NP-completecombinatorialoptimizationproblem,theBooleansatisfiability problem (SAT). AmoebaSAT is a hybrid oftwo dynamics; chaotic oscillatory dynamics for exploringthe state space are combined with spatiotemporal controldynamics for bouncing back logically-false state transi-tions. For the former, we employ the logistic map as a unitfor generating chaotic fluctuation. The control principle ofthe latter that we call “bounceback control” is designed tostabilize a state only when it represents a solution, i.e., asatisfiable assignment. We show that, for some benchmarkprobleminstances,AmoebaSATfindsasolutionfasterthana well-known algorithm called “WalkSAT”, which is con-sidered to be one of the fastest algorithms.1. IntroductionThere has been growing interest in biologically-inspiredalgorithms for solving computationally demanding prob-lems in a fashion similar to search dynamics of variousbiological systems such as neural networks, evolutionaryprocesses, ants, and swarms [1]. AmoebaSAT extracts theessence of spatiotemporal oscillatory dynamics of a single-celled amoeboid organism, the true slime mold Physarumpolycephalum, which is capable of searching for a solu-tion to some optimization problems [2]. When placed un-der our previously studied spatiotemporal control whichapplies aversive light stimuli locally and dynamically de-pending on the shape of the organism, the organism ex-hibits chaotic oscillatory dynamics and finds a solution tothe traveling salesman problem by changing its shape intothe optimal one for which the area of the body is maxi-mized and the risk of being illuminated is minimized [3].Inspiredbythisscheme,wedefineAmoebaSATasahybridof chaotic oscillatory dynamics and spatiotemporal controldynamics.The SAT is the problem of determining if a givenBoolean formula of N variables x

Amoeba-inspired algorithm for cognitive medium access

tug-of-war (TOW) is a unique parallel search algorithm for solving the multi-armed bandit problem (BP), which was inspired by the photoavoidance behavior of a single-celled amoeboid organism, the true slime mold Physarum polycephalum (1-4). The cognitive medium access (CMA) problem, which refers to multiuser channel allocations of the cognitive radio, can be interpreted as a multi-armed bandit problem (CBP) (5, 6). Unlike the normal BP, the CBP considers a competitive situation in which more than one user selects a channel whose reward probability (probability of which channel is free) varies depending on the number and combination of the selecting users as indicated in a payoff matrix. Depending on the payoff matrix, the CBP provides a hard problem instance in which the users should not be attracted to the Nash equilibrium to achieve the maximum, which is the most desirable state to obtain the maximum total score (throughput) for all the users. In this study, we propose two variants of the TOW model (solid type and liquid type) for the CBP toward developing a CMA protocol using a distributed control in uncertain environments. Using the minimum CBP cases where both the users choose a channel from the two considered channels, we show that the performance of our solid-type TOW model is better than that of the well-known upper confidence bound 1 (UCB1)-tuned algorithm, particularly for the hard problem instances. aim of this study is to explore how the users can achieve the social maximum in a decentralized manner. We also show that our liquid-type TOW model, which introduces direct interactions among the users for avoiding mutual collisions, makes it possible to achieve the social maximum for general CBP instances.

Amoebozoa possess lineage-specific globin gene repertoires gained by individual horizontal gene transfers.

The Amoebozoa represent a clade of unicellular amoeboid organisms that display a wide variety of lifestyles, including free-living and parasitic species. For example, the social amoeba Dictyostelium discoideum has the ability to aggregate into a multicellular fruiting body upon starvation, while the pathogenic amoeba Entamoeba histolytica is a parasite of humans. Globins are small heme proteins that are present in almost all extant organisms. Although several genomes of amoebozoan species have been sequenced, little is known about the phyletic distribution of globin genes within this phylum. Only two flavohemoglobins (FHbs) of D. discoideum have been reported and characterized previously while the genomes of Entamoeba species are apparently devoid of globin genes. We investigated eleven amoebozoan species for the presence of globin genes by genomic and phylogenetic in silico analyses. Additional FHb genes were identified in the genomes of four social amoebas and the true slime mold Physarum polycephalum. Moreover, a single-domain globin (SDFgb) of Hartmannella vermiformis, as well as two truncated hemoglobins (trHbs) of Acanthamoeba castellanii were identified. Phylogenetic evidence suggests that these globin genes were independently acquired via horizontal gene transfer from some ancestral bacteria. Furthermore, the phylogenetic tree of amoebozoan FHbs indicates that they do not share a common ancestry and that a transfer of FHbs from bacteria to amoeba occurred multiple times.

Amoeba-inspired Tug-of-War algorithms for exploration–exploitation dilemma in extended Bandit Problem

The true slime mold Physarum polycephalum, a single-celled amoeboid organism, is capable of efficiently allocating a constant amount of intracellular resource to its pseudopod-like branches that best fit the environment where dynamic light stimuli are applied. Inspired by the resource allocation process, the authors formulated a concurrent search algorithm, called the Tug-of-War (TOW) model, for maximizing the profit in the multi-armed Bandit Problem (BP). A player (gambler) of the BP should decide as quickly and accurately as possible which slot machine to invest in out of the N machines and faces an “exploration–exploitation dilemma.” The dilemma is a trade-off between the speed and accuracy of the decision making that are conflicted objectives. The TOW model maintains a constant intracellular resource volume while collecting environmental information by concurrently expanding and shrinking its branches. The conservation law entails a nonlocal correlation among the branches, i.e., volume increment in one branch is immediately compensated by volume decrement(s) in the other branch(es). Owing to this nonlocal correlation, the TOW model can efficiently manage the dilemma. In this study, we extend the TOW model to apply it to a stretched variant of BP, the Extended Bandit Problem (EBP), which is a problem of selecting the best M-tuple of the N machines. We demonstrate that the extended TOW model exhibits better performances for 2-tuple-3-machine and 2-tuple-4-machine instances of EBP compared with the extended versions of well-known algorithms for BP, the ϵ-Greedy and SoftMax algorithms, particularly in terms of its short-term decision-making capability that is essential for the survival of the amoeba in a hostile environment.