Encoding Membrane-Potential-Based Memory within a Microbial Community

Bacterial epigenetics and its implication for agriculture, probiotics development, and biotechnology design

In their natural habitats, organisms encounter numerous external stimuli and must be able to sense and adapt to those stimuli to survive. Unlike mutations, epigenetic changes do not alter the underlying DNA sequence. Instead, they create modifications that promote or silence gene expression. Bacillus subtilis has long been a model organism in studying genetics and development. It is beneficial for numerous biotechnological applications where it is included as a probiotic, in fermentation, or in bio-concrete design. This bacterium has also emerged recently as a model organism for studying bacterial epigenetic adaptation. In this review, we examine the evolving knowledge of epigenetic regulation (restriction-modification systems (RM), orphan methyltransferases, and chromosome condensation) in B. subtilis and related bacteria, and utilize it as a case study to test their potential roles and future applications in genetic engineering and microbial biotechnology. Finally, we suggest how the implementation of these fundamental findings promotes the design of synthetic epigenetic memory circuits and their future applications in agriculture, medicine, and biotechnology.

Persistent glucose consumption under antibiotic treatment protects bacterial community

Antibiotics typically induce major physiological changes in bacteria. However, their effect on nutrient consumption remains unclear. Here we found that Escherichia coli communities can sustain normal levels of glucose consumption under a broad range of antibiotics. The community-living resulted in a low membrane potential in the bacteria, allowing slow antibiotic accumulation on treatment and better adaptation. Through multi-omics analysis, we identified a prevalent adaptive response characterized by the upregulation of lipid synthesis, which substantially contributes to sustained glucose consumption. The consumption was maintained by the periphery region of the community, thereby restricting glucose penetration into the community interior. The resulting spatial heterogeneity in glucose availability protected the interior from antibiotic accumulation in a membrane potential-dependent manner, ensuring rapid recovery of the community postantibiotic treatment. Our findings unveiled a community-level antibiotic response through spatial regulation of metabolism and suggested new strategies for antibiotic therapies.

Oscillatory phenomena in electrophysiological networks: The coupling between cell bioelectricity and transcription

Morphogenetic regulation during embryogenesis and regeneration rely on information transfer and coordination between different regions. Here, we explore theoretically the coupling between bioelectrical and transcriptional oscillations at the individual cell and multicellular levels. The simulations, based on a set of ion channels and intercellular gap junctions, show that bioelectrical and transcriptional waves can electrophysiologically couple distant regions of a model network in phase and antiphase oscillatory states that include synchronization phenomena. In this way, different multicellular regionalizations can be encoded by cell potentials that oscillate between depolarized and polarized states, thus allowing a spatio-temporal coding. Because the electric potential patterns characteristic of development and regeneration are correlated with the spatial distributions of signaling ions and molecules, bioelectricity can act as a template for slow biochemical signals following a hierarchy of experimental times. In particular, bioelectrical gradients that couple cell potentials to transcription rates give to each single cell a rough idea of its location in the multicellular ensemble, thus controlling local differentiation processes that switch on and off crucial parts of the genome.

The sensual cell: Feeling and affect in unicellular species

Our previous efforts to probe the complex, rich experiential lives of unicellular species have focused on the origins of consciousness (Reber, 2019) and the biomolecular processes that underlie sentience (Reber et al., 2023). Implied, but unexplored, was the assumption that these cognitive functions and associated unicellular organismal behaviors were linked with and often driven by affect, feelings, sensual experiences. In this essay we dig more deeply into these valenced (We're using the term valence here to cover the aspects of sensory experiences that have evaluative elements, are experienced as positive or negative ─ those where this affective, internal representation is an essential element in how the input is interpreted and responded to.) self-referencing features. In the first part, we examine the empirical evidence for various sensual experiences that have been identified. In the second part, we look at other features of prokaryote life that appear to also have affective, valenced elements but where the data to support the proposition aren't as strong. We engage in some informed speculation about these phenomena.

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.

Electrical Impedance Spectroscopy with Bacterial Biofilms: Neuronal-like Behavior

Negative capacitance at low frequencies for spiking neurons was first demonstrated in 1941 (K. S. Cole) by using extracellular electrodes. The phenomenon subsequently was explained by using the Hodgkin-Huxley model and is due to the activity of voltage-gated potassium ion channels. We show that Escherichia coli (E. coli) biofilms exhibit significant stable negative capacitances at low frequencies when they experience a small DC bias voltage in electrical impedance spectroscopy experiments. Using a frequency domain Hodgkin-Huxley model, we characterize the conditions for the emergence of this feature and demonstrate that the negative capacitance exists only in biofilms containing living cells. Furthermore, we establish the importance of the voltage-gated potassium ion channel, Kch, using knock-down mutants. The experiments provide further evidence for voltage-gated ion channels in E. coli and a new, low-cost method to probe biofilm electrophysiology, e.g., to understand the efficacy of antibiotics. We expect that the majority of bacterial biofilms will demonstrate negative capacitances.

Bacterial phenotypic heterogeneity through the lens of single-cell RNA sequencing

Bacterial transcription is not monolithic. Microbes exist in a wide variety of cell states that help them adapt to their environment, acquire and produce essential nutrients, and engage in both competition and cooperation with their neighbors. While we typically think of bacterial adaptation as a group behavior, where all cells respond in unison, there is often a mixture of phenotypic responses within a bacterial population, where distinct cell types arise. A primary phenomenon driving these distinct cell states is transcriptional heterogeneity. Given that bacterial mRNA transcripts are extremely short-lived compared to eukaryotes, their transcriptional state is closely associated with their physiology, and thus the transcriptome of a bacterial cell acts as a snapshot of the behavior of that bacterium. Therefore, the application of single-cell transcriptomics to microbial populations will provide novel insight into cellular differentiation and bacterial ecology. In this review, we provide an overview of transcriptional heterogeneity in microbial systems, discuss the findings already provided by single-cell approaches, and plot new avenues of inquiry in transcriptional regulation, cellular biology, and mechanisms of heterogeneity that are made possible when microbial communities are analyzed at single-cell resolution.

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.

A heritable iron memory enables decision-making in Escherichia coli

The importance of memory in bacterial decision-making is relatively unexplored. We show here that a prior experience of swarming is remembered when Escherichia coli encounters a new surface, improving its future swarming efficiency. We conducted >10,000 single-cell swarm assays to discover that cells store memory in the form of cellular iron levels. This "iron" memory preexists in planktonic cells, but the act of swarming reinforces it. A cell with low iron initiates swarming early and is a better swarmer, while the opposite is true for a cell with high iron. The swarming potential of a mother cell, which tracks with its iron memory, is passed down to its fourth-generation daughter cells. This memory is naturally lost by the seventh generation, but artificially manipulating iron levels allows it to persist much longer. A mathematical model with a time-delay component faithfully recreates the observed dynamic interconversions between different swarming potentials. We demonstrate that cellular iron levels also track with biofilm formation and antibiotic tolerance, suggesting that iron memory may impact other physiologies.

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.

Thioflavin-T does not report on electrochemical potential and memory of dormant or germinating bacterial spores

IMPORTANCE

Bacillus and Clostridium spores cause food spoilage and disease because of spores' dormancy and resistance to microbicides. However, when spores "come back to life" in germination, their resistance properties are lost. Thus, understanding the mechanisms of spore germination could facilitate the development of "germinate to eradicate" strategies. One germination feature is the memory of a pulsed germinant stimulus leading to greater germination following a second pulse. Recent observations of increases in spore binding of the potentiometric dye thioflavin-T early in their germination of spores led to the suggestion that increasing electrochemical potential is how spores "remember" germinant pulses. However, new work finds no increased thioflavin-T binding in the physiological germination of Coatless spores or of intact spores germinating with dodecylamine, even though spore memory is seen in both cases. Thus, using thioflavin-T uptake by germinating spores to assess the involvement of electrochemical potential in memory of germinant exposure, as suggested recently, is questionable.

Correcting instructive electric potential patterns in multicellular systems: External actions and endogenous processes

BACKGROUND

Transmembrane electrical potential differences in cells modulate the spatio-temporal distribution of signaling ions and molecules that are instructive for downstream signaling pathways in multicellular systems. The local coupling between bioelectricity and protein transcription patterns allows dynamic subsystems (modules) of cells that share the same bioelectrical state to show similar biochemical downstream processes.

METHODS

We simulate theoretically how the integration-segregation pattern formed by the different multicellular modules that define a biosystem can be controlled by multicellular potentials. To this end, we couple together the model equations of the bioelectrical network to those of the genetic network.

RESULTS

The coupling provided by the intercellular junctions and the external microenvironment allows the restoration of the target bioelectrical pattern by changing the transcription rate of specific ion channels, the post-translational blocking of these channels, and changes in the environmental ionic concentrations.

CONCLUSIONS

The simulations show that the single-cell feedback between bioelectrical and transcriptional processes, together with the coupling provided by the intercellular junctions and the environment, can correct large-scale patterns by means of suitable external actions.

GENERAL SIGNIFICANCE

This study provides a theoretical advancement in the understanding of how the multicellular bioelectric coupling may guide repolarizing interventions for regenerating a tissue, with potential implications in biomedicine.

Future medicine: from molecular pathways to the collective intelligence of the body

The remarkable anatomical homeostasis exhibited by complex living organisms suggests that they are inherently reprogrammable information-processing systems that offer numerous interfaces to their physiological and anatomical problem-solving capacities. We briefly review data suggesting that the multiscale competency of living forms affords a new path for biomedicine that exploits the innate collective intelligence of tissues and organs. The concept of tissue-level allostatic goal-directedness is already bearing fruit in clinical practice. We sketch a roadmap towards 'somatic psychiatry' by using advances in bioelectricity and behavioral neuroscience to design methods that induce self-repair of structure and function. Relaxing the assumption that cellular control mechanisms are static, exploiting powerful concepts from cybernetics, behavioral science, and developmental biology may spark definitive solutions to current biomedical challenges.

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.

Bacterial memory in antibiotic resistance evolution and nanotechnology in evolutionary biology

Bacterial memory refers to the phenomenon in which past experiences influence current behaviors in response to changing environments. It serves as a crucial process that enables adaptation and evolution. We first summarize the state-of-art approaches regarding history-dependent behaviors that impact growth dynamics and underlying mechanisms. Then, the phenotypic and genotypic origins of memory and how encoded memory modulates drug tolerance/resistance are reviewed. We also provide a summary of possible memory effects induced by antimicrobial nanoparticles. The regulatory networks and genetic underpinnings responsible for memory building partially overlap with nanoparticle and drug exposures, which may raise concerns about the impact of nanotechnology on adaptation. Finally, we provide a perspective on the use of nanotechnology to harness bacterial memory based on its unique mode of actions on information processing and transmission in bacteria. Exploring bacterial memory mechanisms provides valuable insights into acclimation, evolution, and the potential applications of nanotechnology in harnessing memory.

Artificial intelligence vs. evolving super-complex tumor intelligence: critical viewpoints

Recent developments in various domains have led to a growing interest in the potential of artificial intelligence to enhance our lives and environments. In particular, the application of artificial intelligence in the management of complex human diseases, such as cancer, has garnered significant attention. The evolution of artificial intelligence is thought to be influenced by multiple factors, including human intervention and environmental factors. Similarly, tumors, being heterogeneous and complex diseases, continue to evolve due to changes in the physical, chemical, and biological environment. Additionally, the concept of cellular intelligence within biological systems has been recognized as a potential attribute of biological entities. Therefore, it is plausible that the tumor intelligence present in cancer cells of affected individuals could undergo super-evolution due to changes in the pro-tumor environment. Thus, a comparative analysis of the evolution of artificial intelligence and super-complex tumor intelligence could yield valuable insights to develop better artificial intelligence-based tools for cancer management.

Modeling control and transduction of electrochemical gradients in acid-stressed bacteria

Transmembrane electrochemical gradients drive solute uptake and constitute a substantial fraction of the cellular energy pool in bacteria. These gradients act not only as "homeostatic contributors," but also play a dynamic and keystone role in several bacterial functions, including sensing, stress response, and metabolism. At the system level, multiple gradients interact with ion transporters and bacterial behavior in a complex, rapid, and emergent manner; consequently, experiments alone cannot untangle their interdependencies. Electrochemical gradient modeling provides a general framework to understand these interactions and their underlying mechanisms. We quantify the generation, maintenance, and interactions of electrical, proton, and potassium potential gradients under lactic acid-stress and lactic acid fermentation. Further, we elucidate a gradient-mediated mechanism for intracellular pH sensing and stress response. We demonstrate that this gradient model can yield insights on the energetic limitations of membrane transport, and can predict bacterial behavior across changing environments.

The scaling of goals from cellular to anatomical homeostasis: an evolutionary simulation, experiment and analysis

Complex living agents consist of cells, which are themselves competent sub-agents navigating physiological and metabolic spaces. Behaviour science, evolutionary developmental biology and the field of machine intelligence all seek to understand the scaling of biological cognition: what enables individual cells to integrate their activities to result in the emergence of a novel, higher-level intelligence with large-scale goals and competencies that belong to it and not to its parts? Here, we report the results of simulations based on the TAME framework, which proposes that evolution pivoted the collective intelligence of cells during morphogenesis of the body into traditional behavioural intelligence by scaling up homeostatic competencies of cells in metabolic space. In this article, we created a minimal in silico system (two-dimensional neural cellular automata) and tested the hypothesis that evolutionary dynamics are sufficient for low-level setpoints of metabolic homeostasis in individual cells to scale up to tissue-level emergent behaviour. Our system showed the evolution of the much more complex setpoints of cell collectives (tissues) that solve a problem in morphospace: the organization of a body-wide positional information axis (the classic French flag problem in developmental biology). We found that these emergent morphogenetic agents exhibit a number of predicted features, including the use of stress propagation dynamics to achieve the target morphology as well as the ability to recover from perturbation (robustness) and long-term stability (even though neither of these was directly selected for). Moreover, we observed an unexpected behaviour of sudden remodelling long after the system stabilizes. We tested this prediction in a biological system-regenerating planaria-and observed a very similar phenomenon. We propose that this system is a first step towards a quantitative understanding of how evolution scales minimal goal-directed behaviour (homeostatic loops) into higher-level problem-solving agents in morphogenetic and other spaces.

Learning to swim efficiently in a nonuniform flow field

Microswimmers can acquire information on the surrounding fluid by sensing mechanical queues. They can then navigate in response to these signals. We analyze this navigation by combining deep reinforcement learning with direct numerical simulations to resolve the hydrodynamics. We study how local and nonlocal information can be used to train a swimmer to achieve particular swimming tasks in a nonuniform flow field, in particular, a zigzag shear flow. The swimming tasks are (1) learning how to swim in the vorticity direction, (2) learning how to swim in the shear-gradient direction, and (3) learning how to swim in the shear-flow direction. We find that access to laboratory frame information on the swimmer's instantaneous orientation is all that is required in order to reach the optimal policy for tasks (1) and (2). However, information on both the translational and rotational velocities seems to be required to accomplish task (3). Inspired by biological microorganisms, we also consider the case where the swimmers sense local information, i.e., surface hydrodynamic forces, together with a signal direction. This might correspond to gravity or, for microorganisms with light sensors, a light source. In this case, we show that the swimmer can reach a comparable level of performance to that of a swimmer with access to laboratory frame variables. We also analyze the role of different swimming modes, i.e., pusher, puller, and neutral.

Realizing Molecular Machine Learning through Communications for Biological AI: Future Directions and Challenges

Artificial Intelligence (AI) and Machine Learning (ML) are weaving their way into the fabric of society, where they are playing a crucial role in numerous facets of our lives. As we witness the increased deployment of AI and ML in various types of devices, we benefit from their use into energy-efficient algorithms for low powered devices. In this paper, we investigate a scale and medium that is far smaller than conventional devices as we move towards molecular systems that can be utilized to perform machine learning functions, i.e., Molecular Machine Learning (MML). Fundamental to the operation of MML is the transport, processing, and interpretation of information propagated by molecules through chemical reactions. We begin by reviewing the current approaches that have been developed for MML, before we move towards potential new directions that rely on gene regulatory networks inside biological organisms as well as their population interactions to create neural networks. We then investigate mechanisms for training machine learning structures in biological cells based on calcium signaling and demonstrate their application to build an Analog to Digital Converter (ADC). Lastly, we look at potential future directions as well as challenges that this area could solve.

Iron Memory in E. coli

The importance of memory in bacterial decision-making is relatively unexplored. We show here that a prior experience of swarming is remembered when E. coli encounters a new surface, improving its future swarming efficiency. We conducted >10,000 single-cell swarm assays to discover that cells store memory in the form of cellular iron levels. This memory pre-exists in planktonic cells, but the act of swarming reinforces it. A cell with low iron initiates swarming early and is a better swarmer, while the opposite is true for a cell with high iron. The swarming potential of a mother cell, whether low or high, is passed down to its fourth-generation daughter cells. This memory is naturally lost by the seventh generation, but artificially manipulating iron levels allows it to persist much longer. A mathematical model with a time-delay component faithfully recreates the observed dynamic interconversions between different swarming potentials. We also demonstrate that iron memory can integrate multiple stimuli, impacting other bacterial behaviors such as biofilm formation and antibiotic tolerance.

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.

Nanoenabled Trainable Systems: From Biointerfaces to Biomimetics

In the dynamic biological system, cells and tissues adapt to diverse environmental conditions and form memories, an essential aspect of training for survival and evolution. An understanding of the biological training principles will inform the design of biomimetic materials whose properties evolve with the environment and offer routes to programmable soft materials, neuromorphic computing, living materials, and biohybrid robotics. In this perspective, we examine the mechanisms by which cells are trained by environmental cues. We outline the artificial platforms that enable biological training and examine the relationship between biological training and biomimetic materials design. We place emphasis on nanoscale material platforms which, given their applicability to chemical, mechanical and electrical stimulation, are critical to bridging natural and synthetic systems.

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.

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.

Novel prokaryotic system employing previously unknown nucleic acids-based receptors

The present study describes a previously unknown universal system that orchestrates the interaction of bacteria with the environment, named the Teazeled receptor system (TR-system). The identical system was recently discovered within eukaryotes. The system includes DNA- and RNA-based molecules named "TezRs", that form receptor's network located outside the membrane, as well as reverse transcriptases and integrases. TR-system takes part in the control of all major aspects of bacterial behavior, such as intra cellular communication, growth, biofilm formation and dispersal, utilization of nutrients including xenobiotics, virulence, chemo- and magnetoreception, response to external factors (e.g., temperature, UV, light and gas content), mutation events, phage-host interaction, and DNA recombination activity. Additionally, it supervises the function of other receptor-mediated signaling pathways. Importantly, the TR-system is responsible for the formation and maintenance of cell memory to preceding cellular events, as well the ability to "forget" preceding events. Transcriptome and biochemical analysis revealed that the loss of different TezRs instigates significant alterations in gene expression and proteins synthesis.

Light/Dark and Temperature Cycling Modulate Metabolic Electron Flow in Pseudomonas aeruginosa Biofilms

Sunlight drives phototrophic metabolism, which affects redox conditions and produces substrates for nonphototrophs. These environmental parameters fluctuate daily due to Earth’s rotation, and nonphototrophic organisms can therefore benefit from the ability to respond to, or even anticipate, such changes. Circadian rhythms, such as daily changes in body temperature, in host organisms can also affect local conditions for colonizing bacteria. Here, we investigated the effects of light/dark and temperature cycling on biofilms of the opportunistic pathogen Pseudomonas aeruginosa PA14. We grew biofilms in the presence of a respiratory indicator dye and found that enhanced dye reduction occurred in biofilm zones that formed during dark intervals and at lower temperatures. This pattern formation occurred with cycling of blue, red, or far-red light, and a screen of mutants representing potential sensory proteins identified two with defects in pattern formation, specifically under red light cycling. We also found that the physiological states of biofilm subzones formed under specific light and temperature conditions were retained during subsequent condition cycling. Light/dark and temperature cycling affected expression of genes involved in primary metabolic pathways and redox homeostasis, including those encoding electron transport chain components. Consistent with this, we found that cbb₃-type oxidases contribute to dye reduction under light/dark cycling conditions. Together, our results indicate that cyclic changes in light exposure and temperature have lasting effects on redox metabolism in biofilms formed by a nonphototrophic, pathogenic bacterium.

Endless forms most beautiful 2.0: teleonomy and the bioengineering of chimaeric and synthetic organisms

The rich variety of biological forms and behaviours results from one evolutionary history on Earth, via frozen accidents and selection in specific environments. This ubiquitous baggage in natural, familiar model species obscures the plasticity and swarm intelligence of cellular collectives. Significant gaps exist in our understanding of the origin of anatomical novelty, of the relationship between genome and form, and of strategies for control of large-scale structure and function in regenerative medicine and bioengineering. Analysis of living forms that have never existed before is necessary to reveal deep design principles of life as it can be. We briefly review existing examples of chimaeras, cyborgs, hybrots and other beings along the spectrum containing evolved and designed systems. To drive experimental progress in multicellular synthetic morphology, we propose teleonomic (goal-seeking, problem-solving) behaviour in diverse problem spaces as a powerful invariant across possible beings regardless of composition or origin. Cybernetic perspectives on chimaeric morphogenesis erase artificial distinctions established by past limitations of technology and imagination. We suggest that a multi-scale competency architecture facilitates evolution of robust problem-solving, living machines. Creation and analysis of novel living forms will be an essential testbed for the emerging field of diverse intelligence, with numerous implications across regenerative medicine, robotics and ethics.

Measurement of the low-frequency charge noise of bacteria

Bacteria meticulously regulate their intracellular ion concentrations and create ionic concentration gradients across the bacterial membrane. These ionic concentration gradients provide free energy for many cellular processes and are maintained by transmembrane transport. Given the physical dimensions of a bacterium and the stochasticity in transmembrane transport, intracellular ion concentrations and hence the charge state of a bacterium are bound to fluctuate. Here we investigate the charge noise of hundreds of nonmotile bacteria by combining electrical measurement techniques from condensed matter physics with microfluidics. In our experiments, bacteria in a microchannel generate charge density fluctuations in the embedding electrolyte due to random influx and efflux of ions. Detected as electrical resistance noise, these charge density fluctuations display a power spectral density proportional to 1/f^{2} for frequencies 0.05Hz≤f≤1Hz. Fits to a simple noise model suggest that the steady-state charge of a bacterium fluctuates by ±1.30×10^{6}e(e≈1.60×10^{-19}C), indicating that bacterial ion homeostasis is highly dynamic and dominated by strong charge noise. The rms charge noise can then be used to estimate the fluctuations in the membrane potential; however, the estimates are unreliable due to our limited understanding of the intracellular concentration gradients.

Magnetoelectric Polymer Membrane-Based Electrical Microenvironment with Magnetically Controlled Antibacterial Activity

The "hard to clean" parts of food processing devices (e.g., the corners of pipes) are difficult to disinfect. This challenge might be overcome through the application of a positive electrical environment. However, the chemical modification of a material surface is complex and difficult. In this work, we developed a smart electroactive Tb_xDy_1-xFe alloy/poly(vinylidene fluoride-trifluoroethylene) (TD/P(VDF-TrFE)) magnetoelectric coating to endow stainless steel with the function of a smart adjustable electrical environment, which was realized by the introduction of a magnetic field of various intensities (0-1800 Oe). An antibacterial assay showed that the polarized coating@stainless steel (P-CS) exhibited antibacterial effects, with the highest antibacterial effect observed at 1800 Oe. Furthermore, in this study, we have, for the first time, explored the antibacterial mechanism of TD/P(VDF-TrFE)-assisted electrical stimulation based on the bacterial intracellular reactive oxygen species (ROS) level, cell respiratory chain, and membrane potential. The results showed that a microelectric field was formed on the P-CS sample in an aqueous solution, which not only generated ROS on the cathode surface but also caused H⁺ consumption in the electrochemical gradient of the bacterial membrane, leading to OH^- production and inhibition of adenosine triphosphate (ATP) synthesis. In addition, the electric field also induced hyperpolarization of the membrane potential in Escherichia coli cells via a K⁺ efflux, thus inducing rearrangement of the outer membrane. In conclusion, an adjustable surface potential was established through the introduction of magnetoelectric polymer coatings, which endowed stainless steel with magnetically controlled antibacterial effects.

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.

Representing Stimulus Information in an Energy Metabolism Pathway

We explored a computational model of astrocytic energy metabolism and demonstrated the theoretical plausibility that this type of pathway might be capable of coding information about stimuli in addition to its known functions in cellular energy and carbon budgets. Simulation results indicate that glycogenolytic glycolysis triggered by activation of adrenergic receptors can capture the intensity and duration features of a neuromodulator waveform and can respond in a dose-dependent manner, including non-linear state changes that are analogous to action potentials. We show how this metabolic pathway can translate information about external stimuli to production profiles of energy-carrying molecules such as lactate with a precision beyond simple signal transduction or non-linear amplification. The results suggest the operation of a metabolic state-machine from the spatially discontiguous yet interdependent metabolite elements. Such metabolic pathways might be well-positioned to code an additional level of salient information about a cell's environmental demands to impact its function. Our hypothesis has implications for the computational power and energy efficiency of the brain.

Cellular Memory of HipA-Induced Growth Arrest: The Length of Cell Growth Arrest Becomes Shorter for Each Successive Induction

Toxin-antitoxin (TA) systems are genetic modules found commonly in bacterial genomes. HipA is a toxin protein encoded from the hipBA TA system in the genome of Escherichia coli. Ectopic expression of hipA induces cell growth arrest. Unlike the cell growth arrest caused by other TA toxins, cells resume growth from the HipA-induced cell growth arrest phase after a defined period of time. In this article, we describe the change in the length of growth arrest while cells undergo repeated cycles of hipA induction, growth arrest and regrowth phases. In the multiple conditions tested, we observed that the length of growth arrest became successively shorter for each round of induction. We verified that this was not due to the appearance of HipA-resistant mutants. Additionally, we identified conditions, such as the growth phase of the starting culture and growth vessels, that alter the length of growth arrest. Our results showed that the length of HipA-induced growth arrest was dependent on environmental factors-in particular, the past growth environment of cells, such as a previous hipA induction. These effects lasted even after multiple rounds of cell divisions, indicating the presence of cellular "memory" that impacts cells' response to HipA-induced toxicity.

Current Progress of Interfacing Organic Semiconducting Materials with Bacteria

Microbial bioelectronics require interfacing microorganisms with electrodes. The resulting abiotic/biotic platforms provide the basis of a range of technologies, including energy conversion and diagnostic assays. Organic semiconductors (OSCs) provide a unique strategy to modulate the interfaces between microbial systems and external electrodes, thereby improving the performance of these incipient technologies. In this review, we explore recent progress in the field on how OSCs, and related materials capable of charge transport, are being used within the context of microbial systems, and more specifically bacteria. We begin by examining the electrochemical communication modes in bacteria and the biological basis for charge transport. Different types of synthetic organic materials that have been designed and synthesized for interfacing and interrogating bacteria are discussed next, followed by the most commonly used characterization techniques for evaluating transport in microbial, synthetic, and hybrid systems. A range of applications is subsequently examined, including biological sensors and energy conversion systems. The review concludes by summarizing what has been accomplished so far and suggests future design approaches for OSC bioelectronics materials and technologies that hybridize characteristic properties of microbial and OSC systems.

Beyond Neurons: Long Distance Communication in Development and Cancer

Cellular communication is important in all aspects of tissue and organism functioning, from the level of single cells, two discreet populations, and distant tissues of the body. Long distance communication networks integrate individual cells into tissues to maintain a complex organism during development, but when communication between cells goes awry, disease states such as cancer emerge. Herein we discuss the growing body of evidence suggesting that communication methods known to be employed by neurons, also exist in other cell types. We identify three major areas of long-distance communication: bioelectric signaling, tunneling nanotubes (TNTs), and macrophage modulation of networks, and draw comparisons about how these systems operate in the context of development and cancer. Bioelectric signaling occurs between cells through exchange of ions and tissue-level electric fields, leading to changes in biochemical gradients and molecular signaling pathways to control normal development and tumor growth and invasion in cancer. TNTs transport key morphogens and other cargo long distances, mediating electrical coupling, tissue patterning, and malignancy of cancer cells. Lastly macrophages maintain long distance signaling networks through trafficking of vesicles during development, providing communication relays and priming favorable microenvironments for cancer metastasis. By drawing comparisons between non-neural long distance signaling in the context of development and cancer we aim to encourage crosstalk between the two fields to cultivate new hypotheses and potential therapeutic strategies.

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.

Minimal physicalism as a scale-free substrate for cognition and consciousness

Theories of consciousness and cognition that assume a neural substrate automatically regard phylogenetically basal, nonneural systems as nonconscious and noncognitive. Here, we advance a scale-free characterization of consciousness and cognition that regards basal systems, including synthetic constructs, as not only informative about the structure and function of experience in more complex systems but also as offering distinct advantages for experimental manipulation. Our "minimal physicalist" approach makes no assumptions beyond those of quantum information theory, and hence is applicable from the molecular scale upwards. We show that standard concepts including integrated information, state broadcasting via small-world networks, and hierarchical Bayesian inference emerge naturally in this setting, and that common phenomena including stigmergic memory, perceptual coarse-graining, and attention switching follow directly from the thermodynamic requirements of classical computation. We show that the self-representation that lies at the heart of human autonoetic awareness can be traced as far back as, and serves the same basic functions as, the stress response in bacteria and other basal systems.

Associative Conditioning Is a Robust Systemic Behavior in Unicellular Organisms: An Interspecies Comparison

The capacity to learn new efficient systemic behavior is a fundamental issue of contemporary biology. We have recently observed, in a preliminary analysis, the emergence of conditioned behavior in some individual amoebae cells. In these experiments, cells were able to acquire new migratory patterns and remember them for long periods of their cellular cycle, forgetting them later on. Here, following a similar conceptual framework of Pavlov's experiments, we have exhaustively studied the migration trajectories of more than 2000 individual cells belonging to three different species: Amoeba proteus, Metamoeba leningradensis, and Amoeba borokensis. Fundamentally, we have analyzed several relevant properties of conditioned cells, such as the intensity of the responses, the directionality persistence, the total distance traveled, the directionality ratio, the average speed, and the persistence times. We have observed that cells belonging to these three species can modify the systemic response to a specific stimulus by associative conditioning. Our main analysis shows that such new behavior is very robust and presents a similar structure of migration patterns in the three species, which was characterized by the presence of conditioning for long periods, remarkable straightness in their trajectories and strong directional persistence. Our experimental and quantitative results, compared with other studies on complex cellular responses in bacteria, protozoa, fungus-like organisms and metazoans that we discus here, allow us to conclude that cellular associative conditioning might be a widespread characteristic of unicellular organisms. This new systemic behavior could be essential to understand some key principles involved in increasing the cellular adaptive fitness to microenvironments.

Ag-Based Synergistic Antimicrobial Composites. A Critical Review

The emerging problem of the antibiotic resistance development and the consequences that the health, food and other sectors face stimulate researchers to find safe and effective alternative methods to fight antimicrobial resistance (AMR) and biofilm formation. One of the most promising and efficient groups of materials known for robust antimicrobial performance is noble metal nanoparticles. Notably, silver nanoparticles (AgNPs) have been already widely investigated and applied as antimicrobial agents. However, it has been proposed to create synergistic composites, because pathogens can find their way to develop resistance against metal nanophases; therefore, it could be important to strengthen and secure their antipathogen potency. These complex materials are comprised of individual components with intrinsic antimicrobial action against a wide range of pathogens. One part consists of inorganic AgNPs, and the other, of active organic molecules with pronounced germicidal effects: both phases complement each other, and the effect might just be the sum of the individual effects, or it can be reinforced by the simultaneous application. Many organic molecules have been proposed as potential candidates and successfully united with inorganic counterparts: polysaccharides, with chitosan being the most used component; phenols and organic acids; and peptides and other agents of animal and synthetic origin. In this review, we overview the available literature and critically discuss the findings, including the mechanisms of action, efficacy and application of the silver-based synergistic antimicrobial composites. Hence, we provide a structured summary of the current state of the research direction and give an opinion on perspectives on the development of hybrid Ag-based nanoantimicrobials (NAMs).

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.

Synthetic living machines: A new window on life

Increased control of biological growth and form is an essential gateway to transformative medical advances. Repairing of birth defects, restoring lost or damaged organs, normalizing tumors, all depend on understanding how cells cooperate to make specific, functional large-scale structures. Despite advances in molecular genetics, significant gaps remain in our understanding of the meso-scale rules of morphogenesis. An engineering approach to this problem is the creation of novel synthetic living forms, greatly extending available model systems beyond evolved plant and animal lineages. Here, we review recent advances in the emerging field of synthetic morphogenesis, the bioengineering of novel multicellular living bodies. Emphasizing emergent self-organization, tissue-level guided self-assembly, and active functionality, this work is the essential next generation of synthetic biology. Aside from useful living machines for specific functions, the rational design and analysis of new, coherent anatomies will greatly increase our understanding of foundational questions in evolutionary developmental and cell biology.