Signal Percolation within a Bacterial Community

Synthetic microbiology in sustainability applications

Microorganisms are a promising means to address many societal sustainability challenges owing to their ability to thrive in diverse environments and interface with the microscale chemical world via diverse metabolic capacities. Synthetic biology can engineer microorganisms by rewiring their regulatory networks or introducing new functionalities, enhancing their utility for target applications. In this Review, we provide a broad, high-level overview of various research efforts addressing sustainability challenges through synthetic biology, emphasizing foundational microbiological research questions that can accelerate the development of these efforts. We introduce an organizational framework that categorizes these efforts along three domains - factory, farm and field - that are defined by the extent to which the engineered microorganisms interface with the natural external environment. Different application areas within the same domain share many fundamental challenges, highlighting productive opportunities for cross-disciplinary collaborations between researchers working in historically disparate fields.

Evidence of scale-free clusters of vegetation in tropical rainforests

Tropical rainforests exhibit a rich repertoire of spatial patterns emerging from the intricate relationship between the microscopic interaction between species. In particular, the distribution of vegetation clusters can shed much light on the underlying process that regulates the ecosystem. Analyzing the distribution of vegetation clusters at different resolution scales, we show the first robust evidence of scale-invariant clusters of vegetation, suggesting the coexistence of multiple intertwined scales in the collective dynamics of tropical rainforests. We use field data and computational simulations to confirm our hypothesis, proposing a predictor that could be particularly interesting to monitor the ecological resilience of the world's "green lungs."

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.

Active pH regulation facilitates Bacillus subtilis biofilm development in a minimally buffered environment

Biofilms provide individual bacteria with many advantages, yet dense cellular proliferation can also create intrinsic metabolic challenges including excessive acidification. Because such pH stress can be masked in buffered laboratory media-such as MSgg commonly used to study Bacillus subtilis biofilms-it is not always clear how such biofilms cope with minimally buffered natural environments. Here, we report how B. subtilis biofilms overcome this intrinsic metabolic challenge through an active pH regulation mechanism. Specifically, we find that these biofilms can modulate their extracellular pH to the preferred neutrophile range, even when starting from acidic and alkaline initial conditions, while planktonic cells cannot. We associate this behavior with dynamic interplay between acetate and acetoin biosynthesis and show that this mechanism is required to buffer against biofilm acidification. Furthermore, we find that buffering-deficient biofilms exhibit dysregulated biofilm development when grown in minimally buffered conditions. Our findings reveal an active pH regulation mechanism in B. subtilis biofilms that could lead to new targets to control unwanted biofilm growth.IMPORTANCEpH is known to influence microbial growth and community dynamics in multiple bacterial species and environmental contexts. Furthermore, in many bacterial species, rapid cellular proliferation demands the use of overflow metabolism, which can often result in excessive acidification. However, in the case of bacterial communities known as biofilms, these acidification challenges can be masked when buffered laboratory media are employed to stabilize the pH environment for optimal growth. Our study reveals that B. subtilis biofilms use an active pH regulation mechanism to mitigate both growth-associated acidification and external pH challenges. This discovery provides new opportunities for understanding microbial communities and could lead to new methods for controlling biofilm growth outside of buffered laboratory conditions.

Interfacial morphodynamics of proliferating microbial communities

In microbial communities, various cell types often coexist by occupying distinct spatial domains. What determines the shape of the interface between such domains-which in turn influences the interactions between cells and overall community function? Here, we address this question by developing a continuum model of a 2D spatially-structured microbial community with two distinct cell types. We find that, depending on the balance of the different cell proliferation rates and substrate friction coefficients, the interface between domains is either stable and smooth, or unstable and develops finger-like protrusions. We establish quantitative principles describing when these different interfacial behaviors arise, and find good agreement both with the results of previous experimental reports as well as new experiments performed here. Our work thus helps to provide a biophysical basis for understanding the interfacial morphodynamics of proliferating microbial communities, as well as a broader range of proliferating active systems.

Spatial biology of Ising-like synthetic genetic networks

BACKGROUND

Understanding how spatial patterns of gene expression emerge from the interaction of individual gene networks is a fundamental challenge in biology. Developing a synthetic experimental system with a common theoretical framework that captures the emergence of short- and long-range spatial correlations (and anti-correlations) from interacting gene networks could serve to uncover generic scaling properties of these ubiquitous phenomena.

RESULTS

Here, we combine synthetic biology, statistical mechanics models, and computational simulations to study the spatial behavior of synthetic gene networks (SGNs) in Escherichia coli quasi-2D colonies growing on hard agar surfaces. Guided by the combined mechanisms of the contact process lattice simulation and two-dimensional Ising model (CPIM), we describe the spatial behavior of bi-stable and chemically coupled SGNs that self-organize into patterns of long-range correlations with power-law scaling or short-range anti-correlations. These patterns, resembling ferromagnetic and anti-ferromagnetic configurations of the Ising model near critical points, maintain their scaling properties upon changes in growth rate and cell shape.

CONCLUSIONS

Our findings shed light on the spatial biology of coupled and bistable gene networks in growing cell populations. This emergent spatial behavior could provide insights into the study and engineering of self-organizing gene patterns in eukaryotic tissues and bacterial consortia.

Planetary Scale Information Transmission in the Biosphere and Technosphere: Limits and Evolution

Information transmission via communication between agents is ubiquitous on Earth, and is a vital facet of living systems. In this paper, we aim to quantify this rate of information transmission associated with Earth's biosphere and technosphere (i.e., a measure of global information flow) by means of a heuristic order-of-magnitude model. By adopting ostensibly conservative values for the salient parameters, we estimate that the global information transmission rate for the biosphere might be ∼1024 bits/s, and that it may perhaps exceed the corresponding rate for the current technosphere by ∼9 orders of magnitude. However, under the equivocal assumption of sustained exponential growth, we find that information transmission in the technosphere can potentially surpass that of the biosphere ∼90 years in the future, reflecting its increasing dominance.

Cell-autonomous diversification in bacteria arises from calcium dynamics self-organizing at a critical point

How dynamic bacterial calcium is regulated, with kinetics faster than typical mechanisms of cellular adaptation, is unknown. We discover bacterial calcium fluctuations are temporal-fractals resulting from a property known as self-organized criticality (SOC). SOC processes are poised at a phase transition separating ordered and chaotic dynamical regimes and are observed in many natural and anthropogenic systems. SOC in bacterial calcium emerges due to calcium channel coupling mediated via membrane voltage. Environmental or genetic perturbations modify calcium dynamics and the critical exponent suggesting a continuum of critical attractors. Moving along this continuum alters the collective information capacity of bacterial populations. We find that the stochastic transition from motile to sessile lifestyle is partially mediated by SOC-governed calcium fluctuations through the regulation of c-di-GMP. In summary, bacteria co-opt the physics of phase transitions to maintain dynamic calcium equilibrium, and this enables cell-autonomous population diversification during surface colonization by leveraging the stochasticity inherent at a boundary between phases.

Microbial models of development: Inspiration for engineering self-assembled synthetic multicellularity

While the field of synthetic developmental biology has traditionally focused on the study of the rich developmental processes seen in metazoan systems, an attractive alternate source of inspiration comes from microbial developmental models. Microbes face unique lifestyle challenges when forming emergent multicellular collectives. As a result, the solutions they employ can inspire the design of novel multicellular systems. In this review, we dissect the strategies employed in multicellular development by two model microbial systems: the cellular slime mold Dictyostelium discoideum and the biofilm-forming bacterium Bacillus subtilis. Both microbes face similar challenges but often have different solutions, both from metazoan systems and from each other, to create emergent multicellularity. These challenges include assembling and sustaining a critical mass of participating individuals to support development, regulating entry into development, and assigning cell fates. The mechanisms these microbial systems exploit to robustly coordinate development under a wide range of conditions offer inspiration for a new toolbox of solutions to the synthetic development community. Additionally, recreating these phenomena synthetically offers a pathway to understanding the key principles underlying how these behaviors are coordinated naturally.

Aqueous habitats and carbon inputs shape the microscale geography and interaction ranges of soil bacteria

Earth's diverse soil microbiomes host bacteria within dynamic and fragmented aqueous habitats that occupy complex pore spaces and restrict the spatial range of ecological interactions. Yet, the spatial distributions of bacterial cells in soil communities remain underexplored. Here, we propose a modelling framework representing submillimeter-scale distributions of soil bacteria based on physical constraints supported by individual-based model results and direct observations. The spatial distribution of bacterial cell clusters modulates various metabolic interactions and soil microbiome functioning. Dry soils with long diffusion times limit localized interactions of the sparse communities. Frequently wet soils enable long-range trophic interactions between dense cell clusters through connected aqueous pathways. Biomes with high carbon inputs promote large and dense cell clusters where anoxic microsites form even in aerated soils. Micro-geographic considerations of difficult-to-observe microbial processes can improve the interpretation of data from bulk soil samples.

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.

Membrane Targeted Azobenzene Drives Optical Modulation of Bacterial Membrane Potential

Recent studies have shown that bacterial membrane potential is dynamic and plays signaling roles. Yet, little is still known about the mechanisms of membrane potential dynamics regulation-owing to a scarcity of appropriate research tools. Optical modulation of bacterial membrane potential could fill this gap and provide a new approach for studying and controlling bacterial physiology and electrical signaling. Here, the authors show that a membrane-targeted azobenzene (Ziapin2) can be used to photo-modulate the membrane potential in cells of the Gram-positive bacterium Bacillus subtilis. It is found that upon exposure to blue-green light (λ = 470 nm), isomerization of Ziapin2 in the bacteria membrane induces hyperpolarization of the potential. To investigate the origin of this phenomenon, ion-channel-deletion strains and ion channel blockers are examined. The authors found that in presence of the chloride channel blocker idanyloxyacetic acid-94 (IAA-94) or in absence of KtrAB potassium transporter, the hyperpolarization response is attenuated. These results reveal that the Ziapin2 isomerization can induce ion channel opening in the bacterial membrane and suggest that Ziapin2 can be used for studying and controlling bacterial electrical signaling. This new optical tool could contribute to better understand various microbial phenomena, such as biofilm electric signaling and antimicrobial resistance.

Living electronics: A catalogue of engineered living electronic components

Biology leverages a range of electrical phenomena to extract and store energy, control molecular reactions and enable multicellular communication. Microbes, in particular, have evolved genetically encoded machinery enabling them to utilize the abundant redox-active molecules and minerals available on Earth, which in turn drive global-scale biogeochemical cycles. Recently, the microbial machinery enabling these redox reactions have been leveraged for interfacing cells and biomolecules with electrical circuits for biotechnological applications. Synthetic biology is allowing for the use of these machinery as components of engineered living materials with tuneable electrical properties. Herein, we review the state of such living electronic components including wires, capacitors, transistors, diodes, optoelectronic components, spin filters, sensors, logic processors, bioactuators, information storage media and methods for assembling these components into living electronic circuits.

Characterizing the Impact of Communication on Cellular and Collective Behavior Using a Three-Dimensional Multiscale Cellular Model

Communication between cells enables the coordination that drives structural and functional complexity in biological systems. Both single and multicellular organisms have evolved diverse communication systems for a range of purposes, including synchronization of behavior, division of labor, and spatial organization. Synthetic systems are also increasingly being engineered to utilize cell-cell communication. While research has elucidated the form and function of cell-cell communication in many biological systems, our knowledge is still limited by the confounding effects of other biological phenomena at play and the bias of the evolutionary background. In this work, our goal is to push forward the context-free understanding of what impact cell-cell communication can have on cellular and population behavior to more fully understand the extent to which cell-cell communication systems can be utilized, modified, and engineered. We use an in silico model of 3D multiscale cellular populations, with dynamic intracellular networks interacting via diffusible signals. We focus on two key communication parameters: the effective interaction distance at which cells are able to interact and the receptor activation threshold. We found that cell-cell communication can be divided into six different forms along the parameter axes, three asocial and three social. We also show that cellular behavior, tissue composition, and tissue diversity are all highly sensitive to both the general form and specific parameters of communication even when the cellular network has not been biased towards that behavior.

Pulsed Interaction Signals as a Route to Biological Pattern Formation

We identify a mechanism for biological spatial pattern formation arising when the signals that mediate interactions between individuals in a population have pulsed character. Our general population-signal framework shows that while for a slow signal-dynamics limit no pattern formation is observed for any values of the model parameters, for a fast limit, on the contrary, pattern formation can occur. Furthermore, at these limits, our framework reduces, respectively, to reaction-diffusion and spatially nonlocal models, thus bridging these approaches.

Advances in linking single-cell bacterial stress response to population-level survival

Stress response mechanisms can allow bacteria to survive a myriad of challenges, including nutrient changes, antibiotic encounters, and antagonistic interactions with other microbes. Expression of these stress response pathways, in addition to other cell features such as growth rate and metabolic state, can be heterogeneous across cells and over time. Collectively, these single-cell-level phenotypes contribute to an overall population-level response to stress. These include diversifying actions, which can be used to enable bet-hedging, and coordinated actions, such as biofilm production, horizontal gene transfer, and cross-feeding. Here, we highlight recent results and emerging technologies focused on both single-cell and population-level responses to stressors, and we draw connections about the combined impact of these effects on survival of bacterial communities.

Thermal Endurance by a Hot-Spring-Dwelling Phylogenetic Relative of the Mesophilic Paracoccus

High temperature growth/survival was revealed in a phylogenetic relative (SMMA_5) of the mesophilic Paracoccus isolated from the 78 to 85°C water of a Trans-Himalayan sulfur-borax spring. After 12 h at 50°C, or 45 min at 70°C, in mineral salts thiosulfate (MST) medium, SMMA_5 retained ~2% colony forming units (CFUs), whereas comparator Paracoccus had 1.5% and 0% CFU left at 50°C and 70°C, respectively. After 12 h at 50°C, the thermally conditioned sibling SMMA_5_TC exhibited an ~1.5 time increase in CFU count; after 45 min at 70°C, SMMA_5_TC had 7% of the initial CFU count. 1,000-times diluted Reasoner's 2A medium, and MST supplemented with lithium, boron, or glycine-betaine, supported higher CFU-retention/CFU-growth than MST. Furthermore, with or without lithium/boron/glycine-betaine, a higher percentage of cells always remained metabolically active, compared with what percentage formed single colonies. SMMA_5, compared with other Paracoccus, contained 335 unique genes: of these, 186 encoded hypothetical proteins, and 83 belonged to orthology groups, which again corresponded mostly to DNA replication/recombination/repair, transcription, secondary metabolism, and inorganic ion transport/metabolism. The SMMA_5 genome was relatively enriched in cell wall/membrane/envelope biogenesis, and amino acid metabolism. SMMA_5 and SMMA_5_TC mutually possessed 43 nucleotide polymorphisms, of which 18 were in protein-coding genes with 13 nonsynonymous and seven radical amino acid replacements. Such biochemical and biophysical mechanisms could be involved in thermal stress mitigation which streamline the cells' energy and resources toward system-maintenance and macromolecule-stabilization, thereby relinquishing cell-division for cell-viability. Thermal conditioning apparently helped inherit those potential metabolic states which are crucial for cell-system maintenance, while environmental solutes augmented the indigenous stability-conferring mechanisms. IMPORTANCE For a holistic understanding of microbial life's high-temperature adaptation, it is imperative to explore the biology of the phylogenetic relatives of mesophilic bacteria which get stochastically introduced to geographically and geologically diverse hot spring systems by local geodynamic forces. Here, in vitro endurance of high heat up to the extent of growth under special (habitat-inspired) conditions was discovered in a hot-spring-dwelling phylogenetic relative of the mesophilic Paracoccus species. Thermal conditioning, extreme oligotrophy, metabolic deceleration, presence of certain habitat-specific inorganic/organic solutes, and potential genomic specializations were found to be the major enablers of this conditional (acquired) thermophilicity. Feasibility of such phenomena across the taxonomic spectrum can well be paradigm changing for the established scopes of microbial adaptation to the physicochemical extremes. Applications of conditional thermophilicity in microbial process biotechnology may be far reaching and multifaceted.

Network location and clustering of genetic mutations determine chronicity in a stylized model of genetic diseases

In a highly simplified view, a disease can be seen as the phenotype emerging from the interplay of genetic predisposition and fluctuating environmental stimuli. We formalize this situation in a minimal model, where a network (representing cellular regulation) serves as an interface between an input layer (representing environment) and an output layer (representing functional phenotype). Genetic predisposition for a disease is represented as a loss of function of some network nodes. Reduced, but non-zero, output indicates disease. The simplicity of this genetic disease model and its deep relationship to percolation theory allows us to understand the interplay between disease, network topology and the location and clusters of affected network nodes. We find that our model generates two different characteristics of diseases, which can be interpreted as chronic and acute diseases. In its stylized form, our model provides a new view on the relationship between genetic mutations and the type and severity of a disease.

Efflux-linked accelerated evolution of antibiotic resistance at a population edge

Efflux is a common mechanism of resistance to antibiotics. We show that efflux itself promotes accumulation of antibiotic-resistance mutations (ARMs). This phenomenon was initially discovered in a bacterial swarm where the linked phenotypes of high efflux and high mutation frequencies spatially segregated to the edge, driven there by motility. We have uncovered and validated a global regulatory network connecting high efflux to downregulation of specific DNA-repair pathways even in non-swarming states. The efflux-DNA repair link was corroborated in a clinical "resistome" database: genomes with mutations that increase efflux exhibit a significant increase in ARMs. Accordingly, efflux inhibitors decreased evolvability to antibiotic resistance. Swarms also revealed how bacterial populations serve as a reservoir of ARMs even in the absence of antibiotic selection pressure. High efflux at the edge births mutants that, despite compromised fitness, survive there because of reduced competition. This finding is relevant to biofilms where efflux activity is high.

Morphological instability and roughening of growing 3D bacterial colonies

The morphogenesis of two-dimensional bacterial colonies has been well studied. However, little is known about the colony morphologies of bacteria growing in three dimensions, despite the prevalence of three-dimensional environments (e.g., soil, inside hosts) as natural bacterial habitats. Using experiments on bacteria in granular hydrogel matrices, we find that dense multicellular colonies growing in three dimensions undergo a common morphological instability and roughen, adopting a characteristic broccoli-like morphology when they exceed a critical size. Analysis of a continuum “active fluid” model of the expanding colony reveals that this behavior originates from an interplay of competition for nutrients with growth-driven colony expansion, both of which vary spatially. These results shed light on the fundamental biophysical principles underlying growth in three dimensions.

How do growing bacterial colonies get their shapes? While colony morphogenesis is well studied in two dimensions, many bacteria grow as large colonies in three-dimensional (3D) environments, such as gels and tissues in the body or subsurface soils and sediments. Here, we describe the morphodynamics of large colonies of bacteria growing in three dimensions. Using experiments in transparent 3D granular hydrogel matrices, we show that dense colonies of four different species of bacteria generically become morphologically unstable and roughen as they consume nutrients and grow beyond a critical size—eventually adopting a characteristic branched, broccoli-like morphology independent of variations in the cell type and environmental conditions. This behavior reflects a key difference between two-dimensional (2D) and 3D colonies; while a 2D colony may access the nutrients needed for growth from the third dimension, a 3D colony inevitably becomes nutrient limited in its interior, driving a transition to unstable growth at its surface. We elucidate the onset of the instability using linear stability analysis and numerical simulations of a continuum model that treats the colony as an “active fluid” whose dynamics are driven by nutrient-dependent cellular growth. We find that when all dimensions of the colony substantially exceed the nutrient penetration length, nutrient-limited growth drives a 3D morphological instability that recapitulates essential features of the experimental observations. Our work thus provides a framework to predict and control the organization of growing colonies—as well as other forms of growing active matter, such as tumors and engineered living materials—in 3D environments.

Electrochemical potential enables dormant spores to integrate environmental signals

The dormant state of bacterial spores is generally thought to be devoid of biological activity. We show that despite continued dormancy, spores can integrate environmental signals over time through a preexisting electrochemical potential. Specifically, we studied thousands of individual Bacillus subtilis spores that remain dormant when exposed to transient nutrient pulses. Guided by a mathematical model of bacterial electrophysiology, we modulated the decision to exit dormancy by genetically and chemically targeting potassium ion flux. We confirmed that short nutrient pulses result in step-like changes in the electrochemical potential of persistent spores. During dormancy, spores thus gradually release their stored electrochemical potential to integrate extracellular information over time. These findings reveal a decision-making mechanism that operates in physiologically inactive cells.

Multi-scale phase separation by explosive percolation with single-chromatin loop resolution

The 2 m-long human DNA is tightly intertwined into the cell nucleus of the size of 10 μm. The DNA packing is explained by folding of chromatin fiber. This folding leads to the formation of such hierarchical structures as: chromosomal territories, compartments; densely-packed genomic regions known as Topologically Associating Domains (TADs), or Chromatin Contact Domains (CCDs), and loops. We propose models of dynamical human genome folding into hierarchical components in human lymphoblastoid, stem cell, and fibroblast cell lines. Our models are based on explosive percolation theory. The chromosomes are modeled as graphs where CTCF chromatin loops are represented as edges. The folding trajectory is simulated by gradually introducing loops to the graph following various edge addition strategies that are based on topological network properties, chromatin loop frequencies, compartmentalization, or epigenomic features. Finally, we propose the genome folding model - a biophysical pseudo-time process guided by a single scalar order parameter. The parameter is calculated by Linear Discriminant Analysis of chromatin features. We also include dynamics of loop formation by using Loop Extrusion Model (LEM) while adding them to the system. The chromatin phase separation, where fiber folds in 3D space into topological domains and compartments, is observed when the critical number of contacts is reached. We also observe that at least 80% of the loops are needed for chromatin fiber to condense in 3D space, and this is constant through various cell lines. Overall, our in-silico model integrates the high-throughput 3D genome interaction experimental data with the novel theoretical concept of phase separation, which allows us to model event-based time dynamics of chromatin loop formation and folding trajectories.

Recovery of neural dynamics criticality in personalized whole-brain models of stroke

The critical brain hypothesis states that biological neuronal networks, because of their structural and functional architecture, work near phase transitions for optimal response to internal and external inputs. Criticality thus provides optimal function and behavioral capabilities. We test this hypothesis by examining the influence of brain injury (strokes) on the criticality of neural dynamics estimated at the level of single participants using directly measured individual structural connectomes and whole-brain models. Lesions engender a sub-critical state that recovers over time in parallel with behavior. The improvement of criticality is associated with the re-modeling of specific white-matter connections. We show that personalized whole-brain dynamical models poised at criticality track neural dynamics, alteration post-stroke, and behavior at the level of single participants.

The authors investigate the influence of brain injury (strokes) on the criticality of neural dynamics using directly measured connectomes and whole-brain models. They show that lesions engender a sub-critical state that recovers over time in parallel with behavior.

Localized electrical stimulation triggers cell-type-specific proliferation in biofilms

Biological systems ranging from bacteria to mammals utilize electrochemical signaling. Although artificial electrochemical signals have been utilized to characterize neural tissue responses, the effects of such stimuli on non-neural systems remain unclear. To pursue this question, we developed an experimental platform that combines a microfluidic chip with a multielectrode array (MiCMA) to enable localized electrochemical stimulation of bacterial biofilms. The device also allows for the simultaneous measurement of the physiological response within the biofilm with single-cell resolution. We find that the stimulation of an electrode locally changes the ratio of the two major cell types comprising Bacillus subtilis biofilms, namely motile and extracellular-matrix-producing cells. Specifically, stimulation promotes the proliferation of motile cells but not matrix cells, even though these two cell types are genetically identical and reside in the same microenvironment. Our work thus reveals that an electronic interface can selectively target bacterial cell types, enabling the control of biofilm composition and development.

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.

How bacteria use electric fields to reach surfaces

Electrotaxis is the property of cells to sense electric fields and use them to orient their displacement. This property has been widely investigated with eukaryotic cells but it remains unclear whether or not bacterial cells can sense an electric field. Here, a specific experimental set-up was designed to form microbial electroactive biofilms while differentiating the effect of the electric field from that of the polarised electrode surface. Application of an electric field during exposure of the electrodes to the inoculum was shown to be required for an electroactive biofilm to form afterwards. Similar biofilms were formed in both directions of the electric field. This result is attributed to the capacity of the cells to detect the K+ and Na+ ion gradients that the electric field creates at the electrode surface. This microbial property should now be considered as a key factor in the formation of electroactive biofilms and possible implications in the biomedical domain are discussed.

From spikes to intercellular waves: Tuning intercellular calcium signaling dynamics modulates organ size control

Information flow within and between cells depends significantly on calcium (Ca²⁺) signaling dynamics. However, the biophysical mechanisms that govern emergent patterns of Ca²⁺ signaling dynamics at the organ level remain elusive. Recent experimental studies in developing Drosophila wing imaginal discs demonstrate the emergence of four distinct patterns of Ca²⁺ activity: Ca²⁺ spikes, intercellular Ca²⁺ transients, tissue-level Ca²⁺ waves, and a global “fluttering” state. Here, we used a combination of computational modeling and experimental approaches to identify two different populations of cells within tissues that are connected by gap junction proteins. We term these two subpopulations “initiator cells,” defined by elevated levels of Phospholipase C (PLC) activity, and “standby cells,” which exhibit baseline activity. We found that the type and strength of hormonal stimulation and extent of gap junctional communication jointly determine the predominate class of Ca²⁺ signaling activity. Further, single-cell Ca²⁺ spikes are stimulated by insulin, while intercellular Ca²⁺ waves depend on Gαq activity. Our computational model successfully reproduces how the dynamics of Ca²⁺ transients varies during organ growth. Phenotypic analysis of perturbations to Gαq and insulin signaling support an integrated model of cytoplasmic Ca²⁺ as a dynamic reporter of overall tissue growth. Further, we show that perturbations to Ca²⁺ signaling tune the final size of organs. This work provides a platform to further study how organ size regulation emerges from the crosstalk between biochemical growth signals and heterogeneous cell signaling states.

Calcium (Ca²⁺) is a universal second messenger that regulates a myriad of cellular processes such as cell division, cell proliferation and apoptosis. Multiple patterns of Ca²⁺ signaling including single-cell spikes, multicellular Ca²⁺ transients, large-scale Ca²⁺ waves, and global “fluttering” have been observed in epithelial systems during organ development. Key molecular players and biophysical mechanisms involved in formation of these patterns during organ development are not well understood. In this work, we developed a generalized multicellular model of Ca²⁺ that captures all the key categories of Ca²⁺ activity as a function of key hormonal signals. Integration of model predictions and experiments reveals two subclasses of cell populations and demonstrates that Ca²⁺ signaling activity at the organ scale is defined by a general decrease in gap junction communication as an organ grows. Our experiments also reveal that a “goldilocks zone” of optimal Ca²⁺ activity is required to achieve optimal growth at the organ level.

Towards the Idea of Molecular Brains

How can single cells without nervous systems perform complex behaviours such as habituation, associative learning and decision making, which are considered the hallmark of animals with a brain? Are there molecular systems that underlie cognitive properties equivalent to those of the brain? This review follows the development of the idea of molecular brains from Darwin’s “root brain hypothesis”, through bacterial chemotaxis, to the recent discovery of neuron-like r-protein networks in the ribosome. By combining a structural biology view with a Bayesian brain approach, this review explores the evolutionary labyrinth of information processing systems across scales. Ribosomal protein networks open a window into what were probably the earliest signalling systems to emerge before the radiation of the three kingdoms. While ribosomal networks are characterised by long-lasting interactions between their protein nodes, cell signalling networks are essentially based on transient interactions. As a corollary, while signals propagated in persistent networks may be ephemeral, networks whose interactions are transient constrain signals diffusing into the cytoplasm to be durable in time, such as post-translational modifications of proteins or second messenger synthesis. The duration and nature of the signals, in turn, implies different mechanisms for the integration of multiple signals and decision making. Evolution then reinvented networks with persistent interactions with the development of nervous systems in metazoans. Ribosomal protein networks and simple nervous systems display architectural and functional analogies whose comparison could suggest scale invariance in information processing. At the molecular level, the significant complexification of eukaryotic ribosomal protein networks is associated with a burst in the acquisition of new conserved aromatic amino acids. Knowing that aromatic residues play a critical role in allosteric receptors and channels, this observation suggests a general role of π systems and their interactions with charged amino acids in multiple signal integration and information processing. We think that these findings may provide the molecular basis for designing future computers with organic processors.

Bioluminescence and Photoreception in Unicellular Organisms: Light-Signalling in a Bio-Communication Perspective

Bioluminescence, the emission of light catalysed by luciferases, has evolved in many taxa from bacteria to vertebrates and is predominant in the marine environment. It is now well established that in animals possessing a nervous system capable of integrating light stimuli, bioluminescence triggers various behavioural responses and plays a role in intra- or interspecific visual communication. The function of light emission in unicellular organisms is less clear and it is currently thought that it has evolved in an ecological framework, to be perceived by visual animals. For example, while it is thought that bioluminescence allows bacteria to be ingested by zooplankton or fish, providing them with favourable conditions for growth and dispersal, the luminous flashes emitted by dinoflagellates may have evolved as an anti-predation system against copepods. In this short review, we re-examine this paradigm in light of recent findings in microorganism photoreception, signal integration and complex behaviours. Numerous studies show that on the one hand, bacteria and protists, whether autotrophs or heterotrophs, possess a variety of photoreceptors capable of perceiving and integrating light stimuli of different wavelengths. Single-cell light-perception produces responses ranging from phototaxis to more complex behaviours. On the other hand, there is growing evidence that unicellular prokaryotes and eukaryotes can perform complex tasks ranging from habituation and decision-making to associative learning, despite lacking a nervous system. Here, we focus our analysis on two taxa, bacteria and dinoflagellates, whose bioluminescence is well studied. We propose the hypothesis that similar to visual animals, the interplay between light-emission and reception could play multiple roles in intra- and interspecific communication and participate in complex behaviour in the unicellular world.

Beyond Homeostasis: Potassium and Pathogenesis during Bacterial Infections

Potassium is an essential mineral nutrient required by all living cells for normal physiological function. Therefore, maintaining intracellular potassium homeostasis during bacterial infection is a requirement for the survival of both host and pathogen. However, pathogenic bacteria require potassium transport to fulfill nutritional and chemiosmotic requirements, and potassium has been shown to directly modulate virulence gene expression, antimicrobial resistance, and biofilm formation. Host cells also require potassium to maintain fundamental biological processes, such as renal function, muscle contraction, and neuronal transmission; however, potassium flux also contributes to critical immunological and antimicrobial processes, such as cytokine production and inflammasome activation. Here, we review the role and regulation of potassium transport and signaling during infection in both mammalian and bacterial cells and highlight the importance of potassium to the success and survival of each organism.

Toward Bacterial Bioelectric Signal Transduction

Bacteria are electrically powered organisms; cells maintain an electrical potential across their plasma membrane as a source of free energy to drive essential processes. In recent years, however, bacterial membrane potential has been increasingly recognized as dynamic. Those dynamics have been implicated in diverse physiological functions and behaviors, including cell division and cell-to-cell signaling. In eukaryotic cells, such dynamics play major roles in coupling bioelectrical stimuli to changes in internal cell states. Neuroscientists and physiologists have established detailed molecular pathways that transduce eukaryotic membrane potential dynamics to physiological and gene expression responses. We are only just beginning to explore these intracellular responses to bioelectrical activity in bacteria. In this review, we summarize progress in this area, including evidence of gene expression responses to stimuli from electrodes and mechanically induced membrane potential spikes. We argue that the combination of provocative results, missing molecular detail, and emerging tools makes the investigation of bioelectrically induced long-term intracellular responses an important and rewarding effort in the future of microbiology.

Machine Learning Establishes Single-Cell Calcium Dynamics as an Early Indicator of Antibiotic Response

Changes in bacterial physiology necessarily precede cell death in response to antibiotics. Herein we investigate the early disruption of Ca²⁺ homeostasis as a marker for antibiotic response. Using a machine learning framework, we quantify the temporal information encoded in single-cell Ca²⁺ dynamics. We find Ca²⁺ dynamics distinguish kanamycin sensitive and resistant cells before changes in gross cell phenotypes such as cell growth or protein stability. The onset time (pharmacokinetics) and probability (pharmacodynamics) of these aberrant Ca²⁺ dynamics are dose and time-dependent, even at the resolution of single-cells. Of the compounds profiled, we find Ca²⁺ dynamics are also an indicator of Polymyxin B activity. In Polymyxin B treated cells, we find aberrant Ca²⁺ dynamics precedes the entry of propidium iodide marking membrane permeabilization. Additionally, we find modifying membrane voltage and external Ca²⁺ concentration alters the time between these aberrant dynamics and membrane breakdown suggesting a previously unappreciated role of Ca²⁺ in the membrane destabilization during Polymyxin B treatment. In conclusion, leveraging live, single-cell, Ca²⁺ imaging coupled with machine learning, we have demonstrated the discriminative capacity of Ca²⁺ dynamics in identifying antibiotic-resistant 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.

The Dynamic Ion Motive Force Powering the Bacterial Flagellar Motor

The bacterial flagellar motor (BFM) is a rotary molecular motor embedded in the cell membrane of numerous bacteria. It turns a flagellum which acts as a propeller, enabling bacterial motility and chemotaxis. The BFM is rotated by stator units, inner membrane protein complexes that stochastically associate to and dissociate from individual motors at a rate which depends on the mechanical and electrochemical environment. Stator units consume the ion motive force (IMF), the electrochemical gradient across the inner membrane that results from cellular respiration, converting the electrochemical energy of translocated ions into mechanical energy, imparted to the rotor. Here, we review some of the main results that form the base of our current understanding of the relationship between the IMF and the functioning of the flagellar motor. We examine a series of studies that establish a linear proportionality between IMF and motor speed, and we discuss more recent evidence that the stator units sense the IMF, altering their rates of dynamic assembly. This, in turn, raises the question of to what degree the classical dependence of motor speed on IMF is due to stator dynamics vs. the rate of ion flow through the stators. Finally, while long assumed to be static and homogeneous, there is mounting evidence that the IMF is dynamic, and that its fluctuations control important phenomena such as cell-to-cell signaling and mechanotransduction. Within the growing toolbox of single cell bacterial electrophysiology, one of the best tools to probe IMF fluctuations may, ironically, be the motor that consumes it. Perfecting our incomplete understanding of how the BFM employs the energy of ion flow will help decipher the dynamical behavior of the bacterial IMF.

Bioelectric signaling: Reprogrammable circuits underlying embryogenesis, regeneration, and cancer

How are individual cell behaviors coordinated toward invariant large-scale anatomical outcomes in development and regeneration despite unpredictable perturbations? Endogenous distributions of membrane potentials, produced by ion channels and gap junctions, are present across all tissues. These bioelectrical networks process morphogenetic information that controls gene expression, enabling cell collectives to make decisions about large-scale growth and form. Recent progress in the analysis and computational modeling of developmental bioelectric circuits and channelopathies reveals how cellular collectives cooperate toward organ-level structural order. These advances suggest a roadmap for exploiting bioelectric signaling for interventions addressing developmental disorders, regenerative medicine, cancer reprogramming, and synthetic bioengineering.

A Meta-Analysis of Bioelectric Data in Cancer, Embryogenesis, and Regeneration

Developmental bioelectricity is the study of the endogenous role of bioelectrical signaling in all cell types. Resting potentials and other aspects of ionic cell physiology are known to be important regulatory parameters in embryogenesis, regeneration, and cancer. However, relevant quantitative measurement and genetic phenotyping data are distributed throughout wide-ranging literature, hampering experimental design and hypothesis generation. Here, we analyze published studies on bioelectrics and transcriptomic and genomic/phenotypic databases to provide a novel synthesis of what is known in three important aspects of bioelectrics research. First, we provide a comprehensive list of channelopathies-ion channel and pump gene mutations-in a range of important model systems with developmental patterning phenotypes, illustrating the breadth of channel types, tissues, and phyla (including man) in which bioelectric signaling is a critical endogenous aspect of embryogenesis. Second, we perform a novel bioinformatic analysis of transcriptomic data during regeneration in diverse taxa that reveals an electrogenic protein to be the one common factor specifically expressed in regeneration blastemas across Kingdoms. Finally, we analyze data on distinct V_mem signatures in normal and cancer cells, revealing a specific bioelectrical signature corresponding to some types of malignancies. These analyses shed light on fundamental questions in developmental bioelectricity and suggest new avenues for research in this exciting field.

Behavior of information flow near criticality

Recent experiments have indicated that many biological systems self-organize near their critical point, which hints at a common design principle. While it has been suggested that information transmission is optimized near the critical point, it remains unclear how information transmission depends on the dynamics of the input signal, the distance over which the information needs to be transmitted, and the distance to the critical point. Here we employ stochastic simulations of a driven two-dimensional Ising system and study the instantaneous mutual information and the information transmission rate between a driven input spin and an output spin. The instantaneous mutual information varies nonmonotonically with the temperature but increases monotonically with the correlation time of the input signal. In contrast, there exists not only an optimal temperature but also an optimal finite input correlation time that maximizes the information transmission rate. This global optimum arises from a fundamental trade-off between the need to maximize the frequency of independent input messages, the necessity to respond fast to changes in the input, and the need to respond reliably to these changes. The optimal temperature lies above the critical point but moves toward it as the distance between the input and output spin is increased.

Life, death, and self: Fundamental questions of primitive cognition viewed through the lens of body plasticity and synthetic organisms

Central to the study of cognition is being able to specify the Subject that is making decisions and owning memories and preferences. However, all real cognitive agents are made of parts (such as brains made of cells). The integration of many active subunits into a coherent Self appearing at a larger scale of organization is one of the fundamental questions of evolutionary cognitive science. Typical biological model systems, whether basal or advanced, have a static anatomical structure which obscures important aspects of the mind-body relationship. Recent advances in bioengineering now make it possible to assemble, disassemble, and recombine biological structures at the cell, organ, and whole organism levels. Regenerative biology and controlled chimerism reveal that studies of cognition in intact, "standard", evolved animal bodies are just a narrow slice of a much bigger and as-yet largely unexplored reality: the incredible plasticity of dynamic morphogenesis of biological forms that house and support diverse types of cognition. The ability to produce living organisms in novel configurations makes clear that traditional concepts, such as body, organism, genetic lineage, death, and memory are not as well-defined as commonly thought, and need considerable revision to account for the possible spectrum of living entities. Here, I review fascinating examples of experimental biology illustrating that the boundaries demarcating somatic and cognitive Selves are fluid, providing an opportunity to sharpen inquiries about how evolution exploits physical forces for multi-scale cognition. Developmental (pre-neural) bioelectricity contributes a novel perspective on how the dynamic control of growth and form of the body evolved into sophisticated cognitive capabilities. Most importantly, the development of functional biobots - synthetic living machines with behavioral capacity - provides a roadmap for greatly expanding our understanding of the origin and capacities of cognition in all of its possible material implementations, especially those that emerge de novo, with no lengthy evolutionary history of matching behavioral programs to bodyplan. Viewing fundamental questions through the lens of new, constructed living forms will have diverse impacts, not only in basic evolutionary biology and cognitive science, but also in regenerative medicine of the brain and in artificial intelligence.

Computation in bacterial communities

Bacteria across many scales are involved in a dynamic process of information exchange to coordinate activity and community structure within large and diverse populations. The molecular components bacteria use to communicate have been discovered and characterized, and recent efforts have begun to understand the potential for bacterial signal exchange to gather information from the environment and coordinate collective behaviors. Such computations made by bacteria to coordinate the action of a population of cells in response to information gathered by a multitude of inputs is a form of collective intelligence. These computations must be robust to fluctuations in both biological, chemical, and physical parameters as well as to operate with energetic efficiency. Given these constraints, what are the limits of computation by bacterial populations and what strategies have evolved to ensure bacterial communities efficiently work together? Here the current understanding of information exchange and collective decision making that occur in microbial populations will be reviewed. Looking toward the future, we consider how a deeper understanding of bacterial computation will inform future direction in microbiology, biotechnology, and biophysics.

Tug-of-war between actomyosin-driven antagonistic forces determines the positioning symmetry in cell-sized confinement

Symmetric or asymmetric positioning of intracellular structures including the nucleus and mitotic spindle steers various biological processes such as cell migration, division, and embryogenesis. In typical animal cells, both a sparse actomyosin meshwork in the cytoplasm and a dense actomyosin cortex underneath the cell membrane participate in the intracellular positioning. However, it remains unclear how these coexisting actomyosin structures regulate the positioning symmetry. To reveal the potential mechanism, we construct an in vitro model composed of cytoplasmic extracts and nucleus-like clusters confined in droplets. Here we find that periodic centripetal actomyosin waves contract from the droplet boundary push clusters to the center in large droplets, while network percolation of bulk actomyosin pulls clusters to the edge in small droplets. An active gel model quantitatively reproduces molecular perturbation experiments, which reveals that the tug-of-war between two distinct actomyosin networks with different maturation time-scales determines the positioning symmetry.

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.

Spiral Wave Propagation in Communities with Spatially Correlated Heterogeneity

Many multicellular communities propagate signals in a directed manner via excitable waves. Cell-to-cell heterogeneity is a ubiquitous feature of multicellular communities, but the effects of heterogeneity on wave propagation are still unclear. Here, we use a minimal FitzHugh-Nagumo-type model to investigate excitable wave propagation in a two-dimensional heterogeneous community. The model shows three dynamic regimes in which waves either propagate directionally, die out, or spiral indefinitely, and we characterize how these regimes depend on the heterogeneity parameters. We find that in some parameter regimes, spatial correlations in the heterogeneity enhance directional propagation and suppress spiraling. However, in other regimes, spatial correlations promote spiraling, a surprising feature that we explain by demonstrating that these spirals form by a second, distinct mechanism. Finally, we characterize the dynamics using techniques from percolation theory. Despite the fact that percolation theory does not completely describe the dynamics quantitatively because it neglects the details of the excitable propagation, we find that it accounts for the transitions between the dynamic regimes and the general dependency of the spiral period on the heterogeneity and thus provides important insights. Our results reveal that the spatial structure of cell-to-cell heterogeneity can have important consequences for signal propagation in cellular communities.

Interplay between morphogen-directed positional information systems and physiological signaling

The development of an organism from an undifferentiated single cell into a spatially complex structure requires spatial patterning of cell fates across tissues. Positional information, proposed by Lewis Wolpert in 1969, has led to the characterization of many components involved in regulating morphogen signaling activity. However, how morphogen gradients are established, maintained, and interpreted by cells still is not fully understood. Quantitative and systems-based approaches are increasingly needed to define general biological design rules that govern positional information systems in developing organisms. This short review highlights a selective set of studies that have investigated the roles of physiological signaling in modulating and mediating morphogen-based pattern formation. Similarities between neural transmission and morphogen-based pattern formation mechanisms suggest underlying shared principles of active cell-based communication. Within larger tissues, neural networks provide directed information, via physiological signaling, that supplements positional information through diffusion. Further, mounting evidence demonstrates that physiological signaling plays a role in ensuring robustness of morphogen-based signaling. We conclude by highlighting several outstanding questions regarding the role of physiological signaling in morphogen-based pattern formation. Elucidating how physiological signaling impacts positional information is critical for understanding the close coupling of developmental and cellular processes in the context of development, disease, and regeneration.

Potassium channel blocker inhibits the formation and electroactivity of Geobacter biofilm

Bacteria in biofilms are able to utilize potassium ion channel-mediated electrical signaling to achieve cell-cell communication. However, it remains unclear whether these signals play a role in Geobacter sp. when surrounded by an intense electric field. This study used a potassium channel blocker (tetraethylammonium, TEA) that interfered with the release of K⁺ but not bacterial growth to demonstrate that potassium ion channel-mediated electrical signaling affected the formation and electroactivity of Geobacter sulfurreducens. The results showed that 5 mM TEA slowed the formation of Geobacter sulfurreducens biofilm, and the current density was ~50% lower than in the control. The electrochemical analyses showed that the electroactivity of the biofilms with TEA addition was inferior. In particular, the micrometer- scale biofilm with TEA exhibited fewer high current peaks, and the species of outermost groups that participated in the electron transfer in Geobacter sulfurreducens biofilms was different from the control. This work provides initial evidence to reveal the role of potassium channels in Geobacter sulfurreducens electroactive biofilms.

How RCK domains regulate gating of K+ channels

Potassium channels play a crucial role in the physiology of all living organisms. They maintain the membrane potential and are involved in electrical signaling, pH homeostasis, cell-cell communication and survival under osmotic stress. Many prokaryotic potassium channels and members of the eukaryotic Slo channels are regulated by tethered cytoplasmic domains or associated soluble proteins, which belong to the family of regulator of potassium conductance (RCK). RCK domains and subunits form octameric rings, which control ion gating. For years, a common regulatory mechanism was suggested: ligand-induced conformational changes in the octameric ring would pull open a gate in the pore via flexible linkers. Consistently, ligand-dependent conformational changes were described for various RCK gating rings. Yet, recent structural and functional data of complete ion channels uncovered that the following signal transduction to the pore domains is divers. The different RCK-regulated ion channels show remarkably heterogeneous mechanisms with neither the connection from the RCK domain to the pore nor the gate being conserved. Some channels even lack the flexible linkers, while in others the gate cannot easily be assigned. In this review we compare available structures of RCK-gated potassium channels, highlight the similarities and differences of channel gating, and delineate existing inconsistencies.