Metabolic basis of brain-like electrical signalling in bacterial communities

Emergence of ion-channel-mediated electrical oscillations in Escherichia coli biofilms

Bacterial biofilms are communities of bacteria usually attached to solid strata and often differentiated into complex structures. Communication across biofilms has been shown to involve chemical signaling and, more recently, electrical signaling in Gram-positive biofilms. We report for the first time, community-level synchronized membrane potential dynamics in three-dimensional Escherichia coli biofilms. Two hyperpolarization events are observed in response to light stress. The first requires mechanically sensitive ion channels (MscK, MscL, and MscS) and the second needs the Kch-potassium channel. The channels mediated both local spiking of single E. coli biofilms and long-range coordinated electrical signaling in E. coli biofilms. The electrical phenomena are explained using Hodgkin-Huxley and 3D fire-diffuse-fire agent-based models. These data demonstrate that electrical wavefronts based on potassium ions are a mechanism by which signaling occurs in Gram-negative biofilms and as such may represent a conserved mechanism for communication across biofilms.

Toward measurements of absolute membrane potential in Bacillus subtilis using fluorescence lifetime

Membrane potential (MP) changes can provide a simple readout of bacterial functional and metabolic state or stress levels. While several optical methods exist for measuring fast changes in MP in excitable cells, there is a dearth of such methods for absolute and precise measurements of steady-state MPs in bacterial cells. Conventional electrode-based methods for the measurement of MP are not suitable for calibrating optical methods in small bacterial cells. While optical measurement based on Nernstian indicators have been successfully used, they do not provide absolute or precise quantification of MP or its changes. We present a novel, calibrated MP recording approach to address this gap. In this study, we used a fluorescence lifetime-based approach to obtain a single-cell-resolved distribution of the membrane potential and its changes upon extracellular chemical perturbation in a population of bacterial cells for the first time. Our method is based on 1) a unique VoltageFluor (VF) optical transducer, whose fluorescence lifetime varies as a function of MP via photoinduced electron transfer and 2) a quantitative phasor-FLIM analysis for high-throughput readout. This method allows MP changes to be easily visualized, recorded and quantified. By artificially modulating potassium concentration gradients across the membrane using an ionophore, we have obtained a Bacillus subtilis-specific MP versus VF lifetime calibration and estimated the MP for unperturbed B. subtilis cells to be -65 mV (in minimal salts glycerol glutamate [MSgg]), -127 mV (in M9), and that for chemically depolarized cells as -14 mV (in MSgg). We observed a population-level MP heterogeneity of ∼6-10 mV indicating a considerable degree of diversity of physiological and metabolic states among individual cells. Our work paves the way for deeper insights into bacterial electrophysiology and bioelectricity research.

The Multiscale Wisdom of the Body: Collective Intelligence as a Tractable Interface for Next-Generation Biomedicine

The dominant paradigm in biomedicine focuses on genetically-specified components of cells and their biochemical dynamics, emphasizing bottom-up emergence of complexity. Here, I explore the biomedical implications of a complementary emerging field: diverse intelligence. Using tools from behavioral science and multiscale neuroscience, we can study development, regenerative repair, and cancer suppression as behaviors of a collective intelligence of cells navigating the spaces of possible morphologies and transcriptional and physiological states. A focus on the competencies of living material-from molecular to organismal scales-reveals a new landscape for interventions. Such top-down approaches take advantage of the memories and homeodynamic goal-seeking behavior of cells and tissues, offering the same massive advantages in biomedicine and bioengineering that reprogrammable hardware has provided information technologies. The bioelectric networks that bind individual cells toward large-scale anatomical goals are an especially tractable interface to organ-level plasticity, and tools to modulate them already exist. This suggests a research program to understand and tame the software of life for therapeutic gain by understanding the many examples of basal cognition that operate throughout living bodies.

Bacterial Autonomous Intelligent Microrobots for Biomedical Applications

Micro/nanorobots are being increasingly utilized as new diagnostic and therapeutic platforms in the biomedical field, enabling remote navigation to hard-to-reach tissues and the execution of various medical procedures. Although significant progress has been made in the development of biomedical micro/nanorobots, how to achieve closed-loop control of them from sensing, memory, and precise trajectory planning to feedback to carry out biomedical tasks remains a challenge. Bacteria with self-propulsion and autonomous intelligence properties are well suited to be engineered as microrobots to achieve closed-loop control for biomedical applications. By virtue of synthetic biology, bacterial microrobots possess an expanded genetic toolbox, allowing them to load input sensors to respond or remember external signals. To achieve accurate control in the complex physiological environment, the development of bacterial microrobots should be matched with the corresponding control system design. In this review, a detailed summary of the sensing and control mechanisms of bacterial microrobots is presented. The engineering and applications of bacterial microrobots in the biomedical field are highlighted. Their future directions of bacterial autonomous intelligent microrobots for precision medicine are forecasted.

Microbes, macrophages, and melanin: a unifying theory of disease as exemplified by cancer

It is widely accepted that cancer mostly arises from random spontaneous mutations triggered by environmental factors. Our theory challenges the idea of the random somatic mutation theory (SMT). The SMT does not fit well with Charles Darwin's theory of evolution in that the same relatively few mutations would occur so frequently and that these mutations would lead to death rather than survival of the fittest. However, it would fit well under the theory of evolution, if we were to look at it from the vantage point of pathogens and their supporting microbial communities colonizing humans and mutating host cells for their own benefit, as it does give them an evolutionary advantage and they are capable of selecting genes to mutate and of inserting their own DNA or RNA into hosts. In this article, we provide evidence that tumors are actually complex microbial communities composed of various microorganisms living within biofilms encapsulated by a hard matrix; that these microorganisms are what cause the genetic mutations seen in cancer and control angiogenesis; that these pathogens spread by hiding in tumor cells and M2 or M2-like macrophages and other phagocytic immune cells and traveling inside them to distant sites camouflaged by platelets, which they also reprogram, and prepare the distant site for metastasis; that risk factors for cancer are sources of energy that pathogens are able to utilize; and that, in accordance with our previous unifying theory of disease, pathogens utilize melanin for energy for building and sustaining tumors and metastasis. We propose a paradigm shift in our understanding of what cancer is, and, thereby, a different trajectory for avenues of treatment and prevention.

Bioelectronic tools for understanding the universal language of electrical signaling across species and kingdoms

Modern bioelectronic tools are rapidly advancing to detect electric potentials within networks of electrogenic cells, such as cardiomyocytes, neurons, and pancreatic beta cells. However, it is becoming evident that electrical signaling is not limited to the animal kingdom but may be a universal form of cell-cell communication. In this review, we discuss the existing evidence of, and tools used to collect, subcellular, single-cell and network-level electrical signals across kingdoms, including bacteria, plants, fungi, and even viruses. We discuss how cellular networks employ altered electrical "circuitry" and intercellular mechanisms across kingdoms, and we assess the functionality and scalability of cutting-edge nanobioelectronics to collect electrical signatures regardless of cell size, shape, or function. Researchers today aim to design micro- and nano-topographic structures which harness mechanosensitive membrane and cytoskeletal pathways that enable tight electrical coupling to subcellular compartments within high-throughput recording systems. Finally, we identify gaps in current knowledge of inter-species and inter-kingdom electrical signaling and propose critical milestones needed to create a central theory of electrical signaling across kingdoms. Our discussion demonstrates the need for high resolution, high throughput tools which can probe multiple, diverse cell types at once in their native or experimentally-modeled environments. These advancements will not only reveal the underlying biophysical laws governing the universal language of electrical communication, but can enable bidirectional electrical communication and manipulation of biological systems.

Temporal dynamics of the biofilm-mediated open circuit potentials: Understanding the fundamentals via a combined thermodynamic and kinetic modeling approach

This study provides in-depth insights into the thermodynamics of electrochemical processes that govern the generation and temporal modulation of open-circuit potentials in biofilms and presents the foundation and applications of open-circuit potential methods to study the bioelectrochemical behaviors of biofilms. This investigation was guided by an overarching hypothesis that models should adequately explain the open-circuit potential patterns generated by biofilms when environmental conditions change; and from this work, a generalized model of electrochemical processes endemic to the biofilm electrode was developed and validated. The proposed model accounts for open system thermodynamics and the kinetics of bioelectrochemical transformations, and the model is simplified to enable applicability to a wide range of processes that are possible within biofilms. As such, the model can account for different parameters associated with various biofilm systems and is extendable to include numerous other experimental conditions. The model predictions were compared to the experimental data generated by 48 equidistantly located microbial potentiometric sensor electrodes in a chamber capable of simulating naturally occurring water matrix, which was exposed to environmental conditions. By combining electrochemical-cell thermodynamics and kinetics approaches, the model explained the temporal dependences of the open circuit potentials in aerobic and anaerobic conditions and the interconversion of two regimes commonly observed in natural systems. At the same time, it enables extraction of the relevant kinetic parameters from experimentally measured time evolution of the open circuit potentials.

Open problems in synthetic multicellularity

Multicellularity is one of the major evolutionary transitions, and its rise provided the ingredients for the emergence of a biosphere inhabited by complex organisms. Over the last decades, the potential for bioengineering multicellular systems has been instrumental in interrogating nature and exploring novel paths to regeneration, disease, cognition, and behaviour. Here, we provide a list of open problems that encapsulate many of the ongoing and future challenges in the field and suggest conceptual approaches that may facilitate progress.

Towards measurements of absolute membrane potential in Bacillus subtilis using fluorescence lifetime

Membrane potential (MP) changes can provide a simple readout of bacterial functional and metabolic state or stress levels. While several optical methods exist for measuring fast changes in MP in excitable cells, there is a dearth of such methods for absolute and precise measurements of steady-state membrane potentials (MPs) in bacterial cells. Conventional electrode-based methods for the measurement of MP are not suitable for calibrating optical methods in small bacterial cells. While optical measurement based on Nernstian indicators have been successfully used, they do not provide absolute or precise quantification of MP or its changes. We present a novel, calibrated MP recording approach to address this gap. In this study, we used a fluorescence lifetime-based approach to obtain a single-cell resolved distribution of the membrane potential and its changes upon extracellular chemical perturbation in a population of bacterial cells for the first time. Our method is based on (i) a unique VoltageFluor (VF) optical transducer, whose fluorescence lifetime varies as a function of MP via photoinduced electron transfer (PeT) and (ii) a quantitative phasor-FLIM analysis for high-throughput readout. This method allows MP changes to be easily visualized, recorded and quantified. By artificially modulating potassium concentration gradients across the membrane using an ionophore, we have obtained a Bacillus subtilis-specific MP versus VF lifetime calibration and estimated the MP for unperturbed B. subtilis cells to be -65 mV (in MSgg), 127 mV (in M9) and that for chemically depolarized cells as -14 mV (in MSgg). We observed a population level MP heterogeneity of ~6-10 mV indicating a considerable degree of diversity of physiological and metabolic states among individual cells. Our work paves the way for deeper insights into bacterial electrophysiology and bioelectricity research.

An Agent-Based Model of Metabolic Signaling Oscillations in Bacillus subtilis Biofilms

Microbes of nearly every species can form biofilms, communities of cells bound together by a self-produced matrix. It is not understood how variation at the cellular level impacts putatively beneficial, colony-level behaviors, such as cell-to-cell signaling. Here we investigate this problem with an agent-based computational model of metabolically driven electrochemical signaling in Bacillus subtilis biofilms. In this process, glutamate-starved interior cells release potassium, triggering a depolarizing wave that spreads to exterior cells and limits their glutamate uptake. More nutrients diffuse to the interior, temporarily reducing glutamate stress and leading to oscillations. In our model, each cell has a membrane potential coupled to metabolism. As a simulated biofilm grows, collective membrane potential oscillations arise spontaneously as cells deplete nutrients and trigger potassium release, reproducing experimental observations. We further validate our model by comparing spatial signaling patterns and cellular signaling rates with those observed experimentally. By oscillating external glutamate and potassium, we find that biofilms synchronize to external potassium more strongly than to glutamate, providing a potential mechanism for previously observed biofilm synchronization. By tracking cellular glutamate concentrations, we find that oscillations evenly distribute nutrients in space: non-oscillating biofilms have an external layer of well-fed cells surrounding a starved core, whereas oscillating biofilms exhibit a relatively uniform distribution of glutamate. Our work shows the potential of agent-based models to connect cellular properties to collective phenomena and facilitates studies of how inheritance of cellular traits can affect the evolution of group behaviors.

Electrical Signaling Beyond Neurons

Neural action potentials (APs) are difficult to interpret as signal encoders and/or computational primitives. Their relationships with stimuli and behaviors are obscured by the staggering complexity of nervous systems themselves. We can reduce this complexity by observing that "simpler" neuron-less organisms also transduce stimuli into transient electrical pulses that affect their behaviors. Without a complicated nervous system, APs are often easier to understand as signal/response mechanisms. We review examples of nonneural stimulus transductions in domains of life largely neglected by theoretical neuroscience: bacteria, protozoans, plants, fungi, and neuron-less animals. We report properties of those electrical signals-for example, amplitudes, durations, ionic bases, refractory periods, and particularly their ecological purposes. We compare those properties with those of neurons to infer the tasks and selection pressures that neurons satisfy. Throughout the tree of life, nonneural stimulus transductions time behavioral responses to environmental changes. Nonneural organisms represent the presence or absence of a stimulus with the presence or absence of an electrical signal. Their transductions usually exhibit high sensitivity and specificity to a stimulus, but are often slow compared to neurons. Neurons appear to be sacrificing the specificity of their stimulus transductions for sensitivity and speed. We interpret cellular stimulus transductions as a cell's assertion that it detected something important at that moment in time. In particular, we consider neural APs as fast but noisy detection assertions. We infer that a principal goal of nervous systems is to detect extremely weak signals from noisy sensory spikes under enormous time pressure. We discuss neural computation proposals that address this goal by casting neurons as devices that implement online, analog, probabilistic computations with their membrane potentials. Those proposals imply a measurable relationship between afferent neural spiking statistics and efferent neural membrane electrophysiology.

Aging as a loss of morphostatic information: A developmental bioelectricity perspective

Maintaining order at the tissue level is crucial throughout the lifespan, as failure can lead to cancer and an accumulation of molecular and cellular disorders. Perhaps, the most consistent and pervasive result of these failures is aging, which is characterized by the progressive loss of function and decline in the ability to maintain anatomical homeostasis and reproduce. This leads to organ malfunction, diseases, and ultimately death. The traditional understanding of aging is that it is caused by the accumulation of molecular and cellular damage. In this article, we propose a complementary view of aging from the perspective of endogenous bioelectricity which has not yet been integrated into aging research. We propose a view of aging as a morphostasis defect, a loss of biophysical prepattern information, encoding anatomical setpoints used for dynamic tissue and organ homeostasis. We hypothesize that this is specifically driven by abrogation of the endogenous bioelectric signaling that normally harnesses individual cell behaviors toward the creation and upkeep of complex multicellular structures in vivo. Herein, we first describe bioelectricity as the physiological software of life, and then identify and discuss the links between bioelectricity and life extension strategies and age-related diseases. We develop a bridge between aging and regeneration via bioelectric signaling that suggests a research program for healthful longevity via morphoceuticals. Finally, we discuss the broader implications of the homologies between development, aging, cancer and regeneration and how morphoceuticals can be developed for aging.

Collective intelligence: A unifying concept for integrating biology across scales and substrates

A defining feature of biology is the use of a multiscale architecture, ranging from molecular networks to cells, tissues, organs, whole bodies, and swarms. Crucially however, biology is not only nested structurally, but also functionally: each level is able to solve problems in distinct problem spaces, such as physiological, morphological, and behavioral state space. Percolating adaptive functionality from one level of competent subunits to a higher functional level of organization requires collective dynamics: multiple components must work together to achieve specific outcomes. Here we overview a number of biological examples at different scales which highlight the ability of cellular material to make decisions that implement cooperation toward specific homeodynamic endpoints, and implement collective intelligence by solving problems at the cell, tissue, and whole-organism levels. We explore the hypothesis that collective intelligence is not only the province of groups of animals, and that an important symmetry exists between the behavioral science of swarms and the competencies of cells and other biological systems at different scales. We then briefly outline the implications of this approach, and the possible impact of tools from the field of diverse intelligence for regenerative medicine and synthetic bioengineering.

From reinforcement learning to agency: Frameworks for understanding basal cognition

Organisms play, explore, and mimic those around them. Is there a purpose to this behavior? Are organisms just behaving, or are they trying to achieve goals? We believe this is a false dichotomy. To that end, to understand organisms, we attempt to unify two approaches for understanding complex agents, whether evolved or engineered. We argue that formalisms describing multiscale competencies and goal-directedness in biology (e.g., TAME), and reinforcement learning (RL), can be combined in a symbiotic framework. While RL has been largely focused on higher-level organisms and robots of high complexity, TAME is naturally capable of describing lower-level organisms and minimal agents as well. We propose several novel questions that come from using RL/TAME to understand biology as well as ones that come from using biology to formulate new theory in AI. We hope that the research programs proposed in this piece shape future efforts to understand biological organisms and also future efforts to build artificial agents.

The bacterial tubulin homolog FtsZ generates electrical oscillations

FtsZ, a major cytoskeletal protein in all bacteria and archaea, forms a ring that directs cytokinesis. Bacterial FtsZ is considered the ancestral homolog of the eukaryotic microtubule (MT)-forming tubulins, sharing GTPase activity and the ability to assemble into protofilaments, rings, and sheets, but not MTs. Previous studies from our laboratory demonstrated that structures of isolated brain MTs spontaneously generate electrical oscillations and bursts of electrical activity similar to action potentials. No information about whether the prokaryotic tubulins may share similar properties is available. Here, we obtained by ammonium sulfate precipitation an enriched protein fraction of the endogenous FtsZ from wild-type Escherichia coli ATCC 25922 without any transfection or overexpression of the protein. As revealed by electron microscopy, FtsZ was detected by dot blot analysis and immunofluorescence that assembled into filaments and sheets in a polymerization buffer. We used the patch-clamp technique to explore the electrical properties of sheets of FtsZ and bacterial cells. Electrical recordings at various holding potentials ranging from ±200 mV showed a complex oscillatory behavior, with several peak frequencies between 12 and 110 Hz in the power spectra and a linear mean current response. To confirm the oscillatory electrical behavior of FtsZ we also conducted experiments with commercial recombinant FtsZ, with similar results. We also detected, by local field potentials, similar electrical oscillations in K+-depolarized pellets of E. coli cultures. FtsZ oscillations had a wider range of frequency peaks than MT sheets from eukaryotic origin. The findings indicate that the bacterial cytoskeleton generates electrical oscillators that may play a relevant role in cell division and unknown signaling mechanisms in bacterial populations.

Bioelectric networks: the cognitive glue enabling evolutionary scaling from physiology to mind

Each of us made the remarkable journey from mere matter to mind: starting life as a quiescent oocyte ("just chemistry and physics"), and slowly, gradually, becoming an adult human with complex metacognitive processes, hopes, and dreams. In addition, even though we feel ourselves to be a unified, single Self, distinct from the emergent dynamics of termite mounds and other swarms, the reality is that all intelligence is collective intelligence: each of us consists of a huge number of cells working together to generate a coherent cognitive being with goals, preferences, and memories that belong to the whole and not to its parts. Basal cognition is the quest to understand how Mind scales-how large numbers of competent subunits can work together to become intelligences that expand the scale of their possible goals. Crucially, the remarkable trick of turning homeostatic, cell-level physiological competencies into large-scale behavioral intelligences is not limited to the electrical dynamics of the brain. Evolution was using bioelectric signaling long before neurons and muscles appeared, to solve the problem of creating and repairing complex bodies. In this Perspective, I review the deep symmetry between the intelligence of developmental morphogenesis and that of classical behavior. I describe the highly conserved mechanisms that enable the collective intelligence of cells to implement regulative embryogenesis, regeneration, and cancer suppression. I sketch the story of an evolutionary pivot that repurposed the algorithms and cellular machinery that enable navigation of morphospace into the behavioral navigation of the 3D world which we so readily recognize as intelligence. Understanding the bioelectric dynamics that underlie construction of complex bodies and brains provides an essential path to understanding the natural evolution, and bioengineered design, of diverse intelligences within and beyond the phylogenetic history of Earth.

[Anaesthesia, a process common to all living organisms]

Because of their interest in medicine, most studies of anaesthesia focus on the nervous system of metazoans, and the fact that any life form can be anaesthetised is often underlooked. If electrical signalling is an essential phenomenon for the success of animals, it appears to be widespread beyond metazoans. Indeed, anaesthesia targets Na+/Ca2+ voltage-gated channels that exist in a wide variety of species and originate from ancestral channels that predate eukaryotes in the course of evolution. The fact that the anaesthetic capacity that leads to loss of sensitivity is common to all phyla may lead to two hypotheses: to be investigated is the evolutionary maintenance of the ability to be anaesthetised due to an adaptive advantage or to a simple intrinsic defect in ion channels? The study of anaesthesia in organisms phylogenetically distant from animals opens up promising prospects for the discovery of new anaesthetic treatments. Moreover, it should also lead to a better understanding of a still poorly understood phenomenon that yet unifies all living organisms. We hope that this new understanding of the unity of life will help humans to assume their responsibilities towards all species, at a time when we are threatening biodiversity with mass extinction.

Bioelectrical State of Bacteria Is Linked to Growth Dynamics and Response to Neurotransmitters: Perspectives for the Investigation of the Microbiota-Brain Axis

Inter-cellular communication is mediated by a sum of biochemical, biophysical, and bioelectrical signals. This might occur not only between cells belonging to the same tissue and/or animal species but also between cells that are, from an evolutionary point of view, far away. The possibility that bioelectrical communication takes place between bacteria and nerve cells has opened exciting perspectives in the study of the gut microbiota-brain axis. The aim of this paper is (i) to establish a reliable method for the assessment of the bioelectrical state of two bacterial strains: Bacillus subtilis (B. subtilis) and Limosilactobacillus reuteri (L. reuteri); (ii) to monitor the bacterial bioelectrical profile throughout its growth dynamics; and (iii) to evaluate the effects of two neurotransmitters (glutamate and γ-aminobutyric acid-GABA) on the bioelectrical signature of bacteria. Our results show that membrane potential (Vmem) and the proliferative capacity of the population are functionally linked in B. subtilis in each phase of the cell cycle. Remarkably, we demonstrate that bacteria respond to neural signals by changing Vmem properties. Finally, we show that Vmem changes in response to neural stimuli are present also in a microbiota-related strain L. reuteri. Our proof-of-principle data reveal a new methodological approach for the better understanding of the relation between bacteria and the brain, with a special focus on gut microbiota. Likewise, this approach will open exciting perspectives in the study of the inter-cellular mechanisms which regulate the bi-directional communication between bacteria and neurons and, ultimately, for designing gut microbiota-brain axis-targeted treatments for neuropsychiatric diseases.

Computational capabilities of a multicellular reservoir computing system

The capacity of cells to process information is currently used to design cell-based tools for ecological, industrial, and biomedical applications such as detecting dangerous chemicals or for bioremediation. In most applications, individual cells are used as the information processing unit. However, single cell engineering is limited by the necessary molecular complexity and the accompanying metabolic burden of synthetic circuits. To overcome these limitations, synthetic biologists have begun engineering multicellular systems that combine cells with designed subfunctions. To further advance information processing in synthetic multicellular systems, we introduce the application of reservoir computing. Reservoir computers (RCs) approximate a temporal signal processing task via a fixed-rule dynamic network (the reservoir) with a regression-based readout. Importantly, RCs eliminate the need of network rewiring, as different tasks can be approximated with the same reservoir. Previous work has already demonstrated the capacity of single cells, as well as populations of neurons, to act as reservoirs. In this work, we extend reservoir computing in multicellular populations with the widespread mechanism of diffusion-based cell-to-cell signaling. As a proof-of-concept, we simulated a reservoir made of a 3D community of cells communicating via diffusible molecules and used it to approximate a range of binary signal processing tasks, focusing on two benchmark functions-computing median and parity functions from binary input signals. We demonstrate that a diffusion-based multicellular reservoir is a feasible synthetic framework for performing complex temporal computing tasks that provides a computational advantage over single cell reservoirs. We also identified a number of biological properties that can affect the computational performance of these processing systems.

There's Plenty of Room Right Here: Biological Systems as Evolved, Overloaded, Multi-Scale Machines

The applicability of computational models to the biological world is an active topic of debate. We argue that a useful path forward results from abandoning hard boundaries between categories and adopting an observer-dependent, pragmatic view. Such a view dissolves the contingent dichotomies driven by human cognitive biases (e.g., a tendency to oversimplify) and prior technological limitations in favor of a more continuous view, necessitated by the study of evolution, developmental biology, and intelligent machines. Form and function are tightly entwined in nature, and in some cases, in robotics as well. Thus, efforts to re-shape living systems for biomedical or bioengineering purposes require prediction and control of their function at multiple scales. This is challenging for many reasons, one of which is that living systems perform multiple functions in the same place at the same time. We refer to this as "polycomputing"-the ability of the same substrate to simultaneously compute different things, and make those computational results available to different observers. This ability is an important way in which living things are a kind of computer, but not the familiar, linear, deterministic kind; rather, living things are computers in the broad sense of their computational materials, as reported in the rapidly growing physical computing literature. We argue that an observer-centered framework for the computations performed by evolved and designed systems will improve the understanding of mesoscale events, as it has already done at quantum and relativistic scales. To develop our understanding of how life performs polycomputing, and how it can be convinced to alter one or more of those functions, we can first create technologies that polycompute and learn how to alter their functions. Here, we review examples of biological and technological polycomputing, and develop the idea that the overloading of different functions on the same hardware is an important design principle that helps to understand and build both evolved and designed systems. Learning to hack existing polycomputing substrates, as well as to evolve and design new ones, will have massive impacts on regenerative medicine, robotics, and computer engineering.

Signaling oscillations: Molecular mechanisms and functional roles

Mounting evidence shows that oscillatory activity is widespread in cell signaling. Here, we review some of this recent evidence, focusing on both the molecular mechanisms that potentially underlie such dynamical behavior, and the potential advantages that signaling oscillations might have in cell function. The biological processes considered include cellular differentiation and tissue maintenance, intermittent responses in pluripotent stem cells, and collective cell migration during wound healing. With the aid of mathematical modeling, we review recent examples in which delayed negative feedback has been seen to act as a unifying principle that underpins this wide variety of phenomena.

Multispecies biofilms in fermentation: Biofilm formation, microbial interactions, and communication

Food fermentation is driven by microorganisms, which usually coexist as multispecies biofilms. The activities and interactions of functional microorganisms and pathogenic bacteria in biofilms have important implications for the quality and safety of fermented foods. It was verified that the biofilm lifestyle benefited the fitness of microorganisms in harsh environments and intensified the cooperation and competition between biofilm members. This review focuses on multispecies biofilm formation, microbial interactions and communication in biofilms, and the application of multispecies biofilms in food fermentation. Microbial aggregation and adhesion are important steps in the early stage of multispecies biofilm formation. Different biofilm-forming abilities and strategies among microorganisms lead to several types of multispecies biofilm formation. The spatial distribution of multispecies biofilms reflects microbial interactions and biofilm function. Then, we discuss the intrinsic factors and external manifestations of multispecies biofilm system succession. Several typical interspecies cooperation and competition modes and mechanisms of microbial communication were reviewed in this review. The main limitations of the studies included in this review are the relatively small number of studies of biofilms formed by functional microorganisms during fermentation and the lack of direct evidence for the formation process of multispecies biofilms and microbial interactions and communication within biofilms. This review aims to provide the food industry with a sufficient understanding of multispecies biofilms in food fermentation. Practical Application: Meanwhile, it offers a reference value for better controlling and utilizing biofilms during food fermentation process, and the improvement of the yield, quality, and safety of fermented products including Chinese Baijiu, cheeese,kefir, soy sauce, kombucha, and fermented olive.

Ion Transporting Proteins and Cancer: Progress and Perspectives

Ion transporting proteins (ITPs) comprise a wide range of ion channels, exchangers, pumps and ionotropic receptors many of which are expressed in tumours and contribute dynamically to the different components and stages of the complex cancer process, from initiation to metastasis. In this promising major field of biomedical research, several candidate ITPs have emerged as clinically viable. Here, we consider a series of general issues concerning the oncological potential of ITPs focusing on voltage-gated sodium channels as a 'case study'. First, we outline some key properties of 'cancer' as a whole. These include epigenetics, stemness, metastasis, heterogeneity, neuronal characteristics and bioelectricity. Cancer specificity of ITP expression is evaluated in relation to tissue restriction, splice variance, functional specificity and macro-molecular complexing. As regards clinical potential, diagnostics is covered with emphasis on enabling early detection. For therapeutics, we deal with molecular approaches, drug repurposing and combinations. Importantly, we emphasise the need for carefully designed clinical trials. We highlight also the area of 'social responsibility' and the need to involve the public (cancer patients and healthy individuals) in the work of cancer research professionals as well as clinicians. In advising patients how best to manage cancer, and live with it, we offer the following four principles: Awareness and prevention, early detection, specialist, integrated care, and psychological support. Finally, we highlight four key prerequisites for commercialisation of ITP-based technologies against cancer. We conclude that ITPs offer significant potential as regards both understanding the intricacies of the complex process of cancer and for developing much needed novel therapies.

Biofilm Growth under Elastic Confinement

Bacteria often form surface-bound communities, embedded in a self-produced extracellular matrix, called biofilms. Quantitative studies of bioflim growth have typically focused on unconfined expansion above solid or semisolid surfaces, leading to exponential radial growth. This geometry does not accurately reflect the natural or biomedical contexts in which biofilms grow in confined spaces. Here, we consider one of the simplest confined geometries: a biofilm growing laterally in the space between a solid surface and an overlying elastic sheet. A poroelastic framework is utilized to derive the radial growth rate of the biofilm; it reveals an additional self-similar expansion regime, governed by the Poisson's ratio of the matrix, leading to a finite maximum radius, consistent with our experimental observations of growing Bacillus subtilis biofilms confined by polydimethylsiloxane.

Technological Approach to Mind Everywhere: An Experimentally-Grounded Framework for Understanding Diverse Bodies and Minds

Synthetic biology and bioengineering provide the opportunity to create novel embodied cognitive systems (otherwise known as minds) in a very wide variety of chimeric architectures combining evolved and designed material and software. These advances are disrupting familiar concepts in the philosophy of mind, and require new ways of thinking about and comparing truly diverse intelligences, whose composition and origin are not like any of the available natural model species. In this Perspective, I introduce TAME-Technological Approach to Mind Everywhere-a framework for understanding and manipulating cognition in unconventional substrates. TAME formalizes a non-binary (continuous), empirically-based approach to strongly embodied agency. TAME provides a natural way to think about animal sentience as an instance of collective intelligence of cell groups, arising from dynamics that manifest in similar ways in numerous other substrates. When applied to regenerating/developmental systems, TAME suggests a perspective on morphogenesis as an example of basal cognition. The deep symmetry between problem-solving in anatomical, physiological, transcriptional, and 3D (traditional behavioral) spaces drives specific hypotheses by which cognitive capacities can increase during evolution. An important medium exploited by evolution for joining active subunits into greater agents is developmental bioelectricity, implemented by pre-neural use of ion channels and gap junctions to scale up cell-level feedback loops into anatomical homeostasis. This architecture of multi-scale competency of biological systems has important implications for plasticity of bodies and minds, greatly potentiating evolvability. Considering classical and recent data from the perspectives of computational science, evolutionary biology, and basal cognition, reveals a rich research program with many implications for cognitive science, evolutionary biology, regenerative medicine, and artificial intelligence.

When left does not seem right: epigenetic and bioelectric differences between left- and right-sided breast cancer

Background

During embryogenesis lateral symmetry is broken, giving rise to Left/Right (L/R) breast tissues with distinct identity. L/R-sided breast tumors exhibit consistently-biased incidence, gene expression, and DNA methylation. We postulate that a differential L/R tumor-microenvironment crosstalk generates different tumorigenesis mechanisms.

Methods

We performed in-silico analyses on breast tumors of public datasets, developed xenografted tumors, and conditioned MDA-MB-231 cells with L/R mammary extracts.

Results

We found L/R differential DNA methylation involved in embryogenic and neuron-like functions. Focusing on ion-channels, we discovered significant L/R epigenetic and bioelectric differences. Specifically, L-sided cells presented increased methylation of hyperpolarizing ion channel genes and increased Ca²⁺ concentration and depolarized membrane potential, compared to R-ones. Functional consequences were associated with increased proliferation in left tumors, assessed by KI67 expression and mitotic count.

Conclusions

Our findings reveal considerable L/R asymmetry in cancer processes, and suggest specific L/R epigenetic and bioelectric differences as future targets for cancer therapeutic approaches in the breast and many other paired organs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s10020-022-00440-5.

Evolution of glutamatergic signaling and synapses

Glutamate (Glu) is the primary excitatory transmitter in the mammalian brain. But, we know little about the evolutionary history of this adaptation, including the selection of l-glutamate as a signaling molecule in the first place. Here, we used comparative metabolomics and genomic data to reconstruct the genealogy of glutamatergic signaling. The origin of Glu-mediated communications might be traced to primordial nitrogen and carbon metabolic pathways. The versatile chemistry of L-Glu placed this molecule at the crossroad of cellular biochemistry as one of the most abundant metabolites. From there, innovations multiplied. Many stress factors or injuries could increase extracellular glutamate concentration, which led to the development of modular molecular systems for its rapid sensing in bacteria and archaea. More than 20 evolutionarily distinct families of ionotropic glutamate receptors (iGluRs) have been identified in eukaryotes. The domain compositions of iGluRs correlate with the origins of multicellularity in eukaryotes. Although L-Glu was recruited as a neuro-muscular transmitter in the early-branching metazoans, it was predominantly a non-neuronal messenger, with a possibility that glutamatergic synapses evolved more than once. Furthermore, the molecular secretory complexity of glutamatergic synapses in invertebrates (e.g., Aplysia) can exceed their vertebrate counterparts. Comparative genomics also revealed 15+ subfamilies of iGluRs across Metazoa. However, most of this ancestral diversity had been lost in the vertebrate lineage, preserving AMPA, Kainate, Delta, and NMDA receptors. The widespread expansion of glutamate synapses in the cortical areas might be associated with the enhanced metabolic demands of the complex brain and compartmentalization of Glu signaling within modular neuronal ensembles.

Stability and robustness properties of bioelectric networks: A computational approach

Morphogenesis during development and regeneration requires cells to communicate and cooperate toward the construction of complex anatomical structures. One important set of mechanisms for coordinating growth and form occurs via developmental bioelectricity-the dynamics of cellular networks driving changes of resting membrane potential which interface with transcriptional and biomechanical downstream cascades. While many molecular details have been elucidated about the instructive processes mediated by ion channel-dependent signaling outside of the nervous system, future advances in regenerative medicine and bioengineering require the understanding of tissue, organ, or whole body-level properties. A key aspect of bioelectric networks is their robustness, which can drive correct, invariant patterning cues despite changing cell number and anatomical configuration of the underlying tissue network. Here, we computationally analyze the minimal models of bioelectric networks and use the example of the regenerating planarian flatworm, to reveal important system-level aspects of bioelectrically derived patterns. These analyses promote an understanding of the robustness of circuits controlling regeneration and suggest design properties that can be exploited for synthetic bioengineering.

IonoBiology: The functional dynamics of the intracellular metallome, with lessons from bacteria

Metal ions are essential for life and represent the second most abundant constituent (after water) of any living cell. While the biological importance of inorganic ions has been appreciated for over a century, we are far from a comprehensive understanding of the functional roles that ions play in cells and organisms. In particular, recent advances are challenging the traditional view that cells maintain constant levels of ion concentrations (ion homeostasis). In fact, the ionic composition (metallome) of cells appears to be purposefully dynamic. The scientific journey that started over 60 years ago with the seminal work by Hodgkin and Huxley on action potentials in neurons is far from reaching its end. New evidence is uncovering how changes in ionic composition regulate unexpected cellular functions and physiology, especially in bacteria, thereby hinting at the evolutionary origins of the dynamic metallome. It is an exciting time for this field of biology, which we discuss and refer to here as IonoBiology.

Bringing Microbiology to Light: Toward All-Optical Electrophysiology in Bacteria

The observation of neuron-like behavior in bacteria, such as the occurrence of electric spiking and extended bioelectric signaling, points to the role of membrane dynamics in prokaryotes. Electrophysiology of bacteria, however, has been overlooked for long time, due to the difficulties in monitoring bacterial bioelectric phenomena with those probing techniques that are commonly used for eukaryotes. Optical technologies can allow a paradigm shift in the field of electrophysiology of bacteria, as they would permit to elicit and monitor signaling rapidly, remotely, and with high spatiotemporal precision. In this perspective, we discuss about the potentiality of light interrogation methods in microbiology, encouraging the development of all-optical electrophysiology of bacteria.

A Two-Dimensional Model of Potassium Signaling and Oscillatory Growth in a Biofilm

Biofilms are complex communities of bacteria that exhibit a variety of collective behaviors. These behaviors improve their ability to survive in many different environments. One of these collective behaviors seen in Bacillus subtilis is the ability for starving cells to stop the growth of other cells using potassium signaling and voltage changes. This signaling produces an oscillatory growth pattern so that during periods of low growth the nutrients diffuse deeper into the biofilm and reach the nutrient-starved, interior regions of the biomass. In this paper, we develop a mathematical model to describe this oscillatory behavior, and we use this model to develop a two-dimensional simulation that reproduces many of the important features seen in the experimental data. This simulation allows us to examine the spatial patterning of the oscillatory behavior to better understand the relationships between the various regions of the biofilm. Studying the spatial components of the metabolic and voltage oscillations could allow for the development of new control techniques for biofilms with complex shapes.

Molecular Mechanisms for Bacterial Potassium Homeostasis

Potassium ion homeostasis is essential for bacterial survival, playing roles in osmoregulation, pH homeostasis, regulation of protein synthesis, enzyme activation, membrane potential adjustment and electrical signaling. To accomplish such diverse physiological tasks, it is not surprising that a single bacterium typically encodes several potassium uptake and release systems. To understand the role each individual protein fulfills and how these proteins work in concert, it is important to identify the molecular details of their function. One needs to understand whether the systems transport ions actively or passively, and what mechanisms or ligands lead to the activation or inactivation of individual systems. Combining mechanistic information with knowledge about the physiology under different stress situations, such as osmostress, pH stress or nutrient limitation, one can identify the task of each system and deduce how they are coordinated with each other. By reviewing the general principles of bacterial membrane physiology and describing the molecular architecture and function of several bacterial K⁺-transporting systems, we aim to provide a framework for microbiologists studying bacterial potassium homeostasis and the many K⁺-translocating systems that are still poorly understood.

Reframing cognition: getting down to biological basics

The premise of this two-part theme issue is simple: the cognitive sciences should join the rest of the life sciences in how they approach the quarry within their research domain. Specifically, understanding how organisms on the lower branches of the phylogenetic tree become familiar with, value and exploit elements of an ecological niche while avoiding harm can be expected to aid understanding of how organisms that evolved later (including Homo sapiens) do the same or similar things. We call this approach basal cognition. In this introductory essay, we explain what the approach involves. Because no definition of cognition exists that reflects its biological basis, we advance a working definition that can be operationalized; introduce a behaviour-generating toolkit of capacities that comprise the function (e.g. sensing/perception, memory, valence, learning, decision making, communication), each element of which can be studied relatively independently; and identify a (necessarily incomplete) suite of common biophysical mechanisms found throughout the domains of life involved in implementing the toolkit. The articles in this collection illuminate different aspects of basal cognition across different forms of biological organization, from prokaryotes and single-celled eukaryotes-the focus of Part 1-to plants and finally to animals, without and with nervous systems, the focus of Part 2. By showcasing work in diverse, currently disconnected fields, we hope to sketch the outline of a new multidisciplinary approach for comprehending cognition, arguably the most fascinating and hard-to-fathom evolved function on this planet. Doing so has the potential to shed light on problems in a wide variety of research domains, including microbiology, immunology, zoology, biophysics, botany, developmental biology, neurobiology/science, regenerative medicine, computational biology, artificial life and synthetic bioengineering. This article is part of the theme issue 'Basal cognition: conceptual tools and the view from the single cell'.

Spontaneous electrical low-frequency oscillations: a possible role in Hydra and all living systems

As one of the first model systems in biology, the basal metazoan Hydra has been revealing fundamental features of living systems since it was first discovered by Antonie van Leeuwenhoek in the early eighteenth century. While it has become well-established within cell and developmental biology, this tiny freshwater polyp is only now being re-introduced to modern neuroscience where it has already produced a curious finding: the presence of low-frequency spontaneous neural oscillations at the same frequency as those found in the default mode network in the human brain. Surprisingly, increasing evidence suggests such spontaneous electrical low-frequency oscillations (SELFOs) are found across the wide diversity of life on Earth, from bacteria to humans. This paper reviews the evidence for SELFOs in diverse phyla, beginning with the importance of their discovery in Hydra, and hypothesizes a potential role as electrical organism organizers, which supports a growing literature on the role of bioelectricity as a 'template' for developmental memory in organism regeneration. This article is part of the theme issue 'Basal cognition: conceptual tools and the view from the single cell'.

Valuing what happens: a biogenic approach to valence and (potentially) affect

Valence is half of the pair of properties that constitute core affect, the foundation of emotion. But what is valence, and where is it found in the natural world? Currently, this question cannot be answered. The idea that emotion is the body's way of driving the organism to secure its survival, thriving and reproduction runs like a leitmotif from the pathfinding work of Antonio Damasio through four book-length neuroscientific accounts of emotion recently published by the field's leading practitioners. Yet while Damasio concluded 20 years ago that the homeostasis-affect linkage is rooted in unicellular life, no agreement exists about whether even non-human animals with brains experience emotions. Simple neural animals-those less brainy than bees, fruit flies and other charismatic invertebrates-are not even on the radar of contemporary affective research, to say nothing of aneural organisms. This near-sightedness has effectively denied the most productive method available for getting a grip on highly complex biological processes to a scientific domain whose importance for understanding biological decision-making cannot be underestimated. Valence arguably is the fulcrum around which the dance of life revolves. Without the ability to discriminate advantage from harm, life very quickly comes to an end. In this paper, we review the concept of valence, where it came from, the work it does in current leading theories of emotion, and some of the odd features revealed via experiment. We present a biologically grounded framework for investigating valence in any organism and sketch a preliminary pathway to a computational model. This article is part of the theme issue 'Basal cognition: conceptual tools and the view from the single cell'.

Fate of Duplicated Neural Structures

Statistical physics determines the abundance of different arrangements of matter depending on cost-benefit balances. Its formalism and phenomenology percolate throughout biological processes and set limits to effective computation. Under specific conditions, self-replicating and computationally complex patterns become favored, yielding life, cognition, and Darwinian evolution. Neurons and neural circuits sit at a crossroads between statistical physics, computation, and (through their role in cognition) natural selection. Can we establish a statistical physics of neural circuits? Such theory would tell what kinds of brains to expect under set energetic, evolutionary, and computational conditions. With this big picture in mind, we focus on the fate of duplicated neural circuits. We look at examples from central nervous systems, with stress on computational thresholds that might prompt this redundancy. We also study a naive cost-benefit balance for duplicated circuits implementing complex phenotypes. From this, we derive phase diagrams and (phase-like) transitions between single and duplicated circuits, which constrain evolutionary paths to complex cognition. Back to the big picture, similar phase diagrams and transitions might constrain I/O and internal connectivity patterns of neural circuits at large. The formalism of statistical physics seems to be a natural framework for this worthy line of research.

From Microbial Communities to Distributed Computing Systems

A distributed biological system can be defined as a system whose components are located in different subpopulations, which communicate and coordinate their actions through interpopulation messages and interactions. We see that distributed systems are pervasive in nature, performing computation across all scales, from microbial communities to a flock of birds. We often observe that information processing within communities exhibits a complexity far greater than any single organism. Synthetic biology is an area of research which aims to design and build synthetic biological machines from biological parts to perform a defined function, in a manner similar to the engineering disciplines. However, the field has reached a bottleneck in the complexity of the genetic networks that we can implement using monocultures, facing constraints from metabolic burden and genetic interference. This makes building distributed biological systems an attractive prospect for synthetic biology that would alleviate these constraints and allow us to expand the applications of our systems into areas including complex biosensing and diagnostic tools, bioprocess control and the monitoring of industrial processes. In this review we will discuss the fundamental limitations we face when engineering functionality with a monoculture, and the key areas where distributed systems can provide an advantage. We cite evidence from natural systems that support arguments in favor of distributed systems to overcome the limitations of monocultures. Following this we conduct a comprehensive overview of the synthetic communities that have been built to date, and the components that have been used. The potential computational capabilities of communities are discussed, along with some of the applications that these will be useful for. We discuss some of the challenges with building co-cultures, including the problem of competitive exclusion and maintenance of desired community composition. Finally, we assess computational frameworks currently available to aide in the design of microbial communities and identify areas where we lack the necessary tools.

Engineering and modeling of multicellular morphologies and patterns

Synthetic multicellular (MC) systems have the capacity to increase our understanding of biofilms and higher organisms, and to serve as engineering platforms for developing complex products in the areas of medicine, biosynthesis and smart materials. Here we provide an interdisciplinary perspective and review on emerging approaches to engineer and model MC systems. We lay out definitions for key terms in the field and identify toolboxes of standardized parts which can be combined into various MC algorithms to achieve specific outcomes. Many essential parts and algorithms have been demonstrated in some form. As key next milestones for the field, we foresee the improvement of these parts and their adaptation to more biological systems, the demonstration of more complex algorithms, the advancement of quantitative modeling approaches and compilers to support rational MC engineering, and implementation of MC engineering for practical applications.

Encoding Membrane-Potential-Based Memory within a Microbial Community

Cellular membrane potential plays a key role in the formation and retrieval of memories in the metazoan brain, but it remains unclear whether such memory can also be encoded in simpler organisms like bacteria. Here, we show that single-cell-level memory patterns can be imprinted in bacterial biofilms by light-induced changes in the membrane potential. We demonstrate that transient optical perturbations generate a persistent and robust potassium-channel-mediated change in the membrane potential of bacteria within the biofilm. The light-exposed cells respond in an anti-phase manner, relative to unexposed cells, to both natural and induced oscillations in extracellular ion concentrations. This anti-phase response, which persists for hours following the transient optical stimulus, enables a direct single-cell resolution visualization of spatial memory patterns within the biofilm. The ability to encode robust and persistent membrane-potential-based memory patterns could enable computations within prokaryotic communities and suggests a parallel between neurons and bacteria.

Liquid brains, solid brains

Cognitive networks have evolved a broad range of solutions to the problem of gathering, storing and responding to information. Some of these networks are describable as static sets of neurons linked in an adaptive web of connections. These are 'solid' networks, with a well-defined and physically persistent architecture. Other systems are formed by sets of agents that exchange, store and process information but without persistent connections or move relative to each other in physical space. We refer to these networks that lack stable connections and static elements as 'liquid' brains, a category that includes ant and termite colonies, immune systems and some microbiomes and slime moulds. What are the key differences between solid and liquid brains, particularly in their cognitive potential, ability to solve particular problems and environments, and information-processing strategies? To answer this question requires a new, integrative framework. This article is part of the theme issue 'Liquid brains, solid brains: How distributed cognitive architectures process information'.

Understanding the evolution of interspecies interactions in microbial communities

Microbial communities are complex multi-species assemblages that are characterized by a multitude of interspecies interactions, which can range from mutualism to competition. The overall sign and strength of interspecies interactions have important consequences for emergent community-level properties such as productivity and stability. It is not well understood how interspecies interactions change over evolutionary timescales. Here, we review the empirical evidence that evolution is an important driver of microbial community properties and dynamics on timescales that have traditionally been regarded as purely ecological. Next, we briefly discuss different modelling approaches to study evolution of communities, emphasizing the similarities and differences between evolutionary and ecological perspectives. We then propose a simple conceptual model for the evolution of interspecies interactions in communities. Specifically, we propose that to understand the evolution of interspecies interactions, it is important to distinguish between direct and indirect fitness effects of a mutation. We predict that in well-mixed environments, traits will be selected exclusively for their direct fitness effects, while in spatially structured environments, traits may also be selected for their indirect fitness effects. Selection of indirectly beneficial traits should result in an increase in interaction strength over time, while selection of directly beneficial traits should not have such a systematic effect. We tested our intuitions using a simple quantitative model and found support for our hypotheses. The next step will be to test these hypotheses experimentally and provide input for a more refined version of the model in turn, thus closing the scientific cycle of models and experiments. This article is part of the theme issue 'Conceptual challenges in microbial community ecology'.