Beyond homeostasis: a predictive-dynamic framework for understanding cellular behavior

Spatio-temporal organization of the E. coli chromosome from base to cellular length scales

Escherichia coli has been a vital model organism for studying chromosomal structure, thanks, in part, to its small and circular genome (4.6 million base pairs) and well-characterized biochemical pathways. Over the last several decades, we have made considerable progress in understanding the intricacies of the structure and subsequent function of the E. coli nucleoid. At the smallest scale, DNA, with no physical constraints, takes on a shape reminiscent of a randomly twisted cable, forming mostly random coils but partly affected by its stiffness. This ball-of-spaghetti-like shape forms a structure several times too large to fit into the cell. Once the physiological constraints of the cell are added, the DNA takes on overtwisted (negatively supercoiled) structures, which are shaped by an intricate interplay of many proteins carrying out essential biological processes. At shorter length scales (up to about 1 kb), nucleoid-associated proteins organize and condense the chromosome by inducing loops, bends, and forming bridges. Zooming out further and including cellular processes, topological domains are formed, which are flanked by supercoiling barriers. At the megabase-scale both large, highly self-interacting regions (macrodomains) and strong contacts between distant but co-regulated genes have been observed. At the largest scale, the nucleoid forms a helical ellipsoid. In this review, we will explore the history and recent advances that pave the way for a better understanding of E. coli chromosome organization and structure, discussing the cellular processes that drive changes in DNA shape, and what contributes to compaction and formation of dynamic structures, and in turn how bacterial chromatin affects key processes such as transcription and replication.

Emerging cancer therapies: targeting physiological networks and cellular bioelectrical differences with non-thermal systemic electromagnetic fields in the human body - a comprehensive review

A steadily increasing number of publications support the concept of physiological networks, and how cellular bioelectrical properties drive cell proliferation and cell synchronization. All cells, especially cancer cells, are known to possess characteristic electrical properties critical for physiological behavior, with major differences between normal and cancer cell counterparts. This opportunity can be explored as a novel treatment modality in Oncology. Cancer cells exhibit autonomous oscillations, deviating from normal rhythms. In this context, a shift from a static view of cellular processes is required for a better understanding of the dynamic connections between cellular metabolism, gene expression, cell signaling and membrane polarization as states in constant flux in realistic human models. In oncology, radiofrequency electromagnetic fields have produced sustained responses and improved quality of life in cancer patients with minimal side effects. This review aims to show how non-thermal systemic radiofrequency electromagnetic fields leads to promising therapeutic responses at cellular and tissue levels in humans, supporting this newly emerging cancer treatment modality with early favorable clinical experience specifically in advanced cancer.

Living cognition and the nature of organisms

There is no consensus about what cognition is. Different perspectives conceptualize it in different ways. In the same vein, there is no agreement about which systems are truly cognitive. This begs the question, what makes a process or a system cognitive? One of the most conspicuous features of cognition is that it is a set of processes. Cognition, in the end, is a collection of processes such as perception, memory, learning, decision-making, problem-solving, goal-directedness, attention, anticipation, communication, and maybe emotion. There is a debate about what they mean, and which systems possess these processes. One aspect of this problem concerns the level at which cognition and the single processes are conceptualized. To make this scenario clear, evolutionary and self-maintenance arguments are taken. Given the evolutive landscape, one sees processes shared by all organisms and their derivations in specific taxa. No matter which side of the complexity spectrum one favors, the similarities of the simple processes with the complex ones cannot be ignored, and the differences of some complex processes with their simple versions cannot be blurred. A final cognitive framework must make sense of both sides of the spectrum, their differences and similarities. Here, we discuss from an evolutionary perspective the basic elements shared by all living beings and whether these may be necessary and sufficient for understanding the cognitive process. Following these considerations, cognition can be expanded to every living being. Cognition is the set of informational and dynamic processes an organism must interact with and grasp aspects of its world. Understood at their most basic level, perception, memory, learning, problem-solving, decision-making, action, and other cognitive processes are basic features of biological functioning.

Stress sharing as cognitive glue for collective intelligences: A computational model of stress as a coordinator for morphogenesis

Individual cells have numerous competencies in physiological and metabolic spaces. However, multicellular collectives can reliably navigate anatomical morphospace towards much larger, reliable endpoints. Understanding the robustness and control properties of this process is critical for evolutionary developmental biology, bioengineering, and regenerative medicine. One mechanism that has been proposed for enabling individual cells to coordinate toward specific morphological outcomes is the sharing of stress (where stress is a physiological parameter that reflects the current amount of error in the context of a homeostatic loop). Here, we construct and analyze a multiscale agent-based model of morphogenesis in which we quantitatively examine the impact of stress sharing on the ability to reach target morphology. We found that stress sharing improves the morphogenetic efficiency of multicellular collectives; populations with stress sharing reached anatomical targets faster. Moreover, stress sharing influenced the future fate of distant cells in the multi-cellular collective, enhancing cells' movement and their radius of influence, consistent with the hypothesis that stress sharing works to increase cohesiveness of collectives. During development, anatomical goal states could not be inferred from observation of stress states, revealing the limitations of knowledge of goals by an extern observer outside the system itself. Taken together, our analyses support an important role for stress sharing in natural and engineered systems that seek robust large-scale behaviors to emerge from the activity of their competent components.

Modeling autopoiesis and cognition with reaction networks

Maturana and Varela defined an autopoietic system as a self-regenerating network of processes. We reinterpret and elaborate this conception starting from a process ontology and its formalization in terms of reaction networks and chemical organization theory. An autopoietic organization can be modelled as a network of "molecules" (components) undergoing reactions, which is (operationally) closed and self-maintaining. Such organizations, being attractors of a dynamic system, tend to self-organize-thus providing a model for the origin of life. However, in order to survive in a variable environment, they must also be resilient, i.e. able to compensate perturbations. According to the "good regulator theorem" this requires some form of cognition, i.e. knowing which action to perform for which perturbation. Such cognition becomes more effective as it learns to anticipate perturbations by discovering invariant patterns in its interactions with the environment. Nevertheless, the resulting predictive model remains a subjective construction. Such implicit model cannot be interpreted as an objective representation of external reality, because the autopoietic system does not have direct access to that reality, and there is in general no isomorphism between internal and external processes.

Cellular signaling pathways as plastic, proto-cognitive systems: Implications for biomedicine

Many aspects of health and disease are modeled using the abstraction of a "pathway"-a set of protein or other subcellular activities with specified functional linkages between them. This metaphor is a paradigmatic case of a deterministic, mechanistic framework that focuses biomedical intervention strategies on altering the members of this network or the up-/down-regulation links between them-rewiring the molecular hardware. However, protein pathways and transcriptional networks exhibit interesting and unexpected capabilities such as trainability (memory) and information processing in a context-sensitive manner. Specifically, they may be amenable to manipulation via their history of stimuli (equivalent to experiences in behavioral science). If true, this would enable a new class of biomedical interventions that target aspects of the dynamic physiological "software" implemented by pathways and gene-regulatory networks. Here, we briefly review clinical and laboratory data that show how high-level cognitive inputs and mechanistic pathway modulation interact to determine outcomes in vivo. Further, we propose an expanded view of pathways from the perspective of basal cognition and argue that a broader understanding of pathways and how they process contextual information across scales will catalyze progress in many areas of physiology and neurobiology. We argue that this fuller understanding of the functionality and tractability of pathways must go beyond a focus on the mechanistic details of protein and drug structure to encompass their physiological history as well as their embedding within higher levels of organization in the organism, with numerous implications for data science addressing health and disease. Exploiting tools and concepts from behavioral and cognitive sciences to explore a proto-cognitive metaphor for the pathways underlying health and disease is more than a philosophical stance on biochemical processes; at stake is a new roadmap for overcoming the limitations of today's pharmacological strategies and for inferring future therapeutic interventions for a wide range of disease states.

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.

Escherichia coli YigI is a Conserved Gammaproteobacterial Acyl-CoA Thioesterase Permitting Metabolism of Unusual Fatty Acid Substrates

Thioesterases play a critical role in metabolism, membrane biosynthesis, and overall homeostasis for all domains of life. In this present study, we characterize a putative thioesterase from Escherichia coli MG1655 and define its role as a cytosolic enzyme. Building on structure-guided functional predictions, we show that YigI is a medium- to long-chain acyl-CoA thioesterase that is involved in the degradation of conjugated linoleic acid (CLA) in vivo, showing overlapping specificity with two previously defined E. coli thioesterases TesB and FadM. We then bioinformatically identify the regulatory relationships that induce YigI expression, which include: an acidic environment, high oxygen availability, and exposure to aminoglycosides. Our findings define a role for YigI and shed light on why the E. coli genome harbors numerous thioesterases with closely related functions. IMPORTANCE Previous research has shown that long chain acyl-CoA thioesterases are needed for E. coli to grow in the presence of carbon sources such as conjugated linoleic acid, but that E. coli must possess at least one such enzyme that had not previously been characterized. Building off structure-guided function predictions, we showed that the poorly annotated protein YigI is indeed the previously unidentified third acyl CoA thioesterase. We found that the three potentially overlapping acyl-CoA thioesterases appear to be induced by nonoverlapping conditions and use that information as a starting point for identifying the precise reactions catalyzed by each such thioesterase, which is an important prerequisite for their industrial application and for more accurate metabolic modeling of E. coli.

Exploiting Information and Control Theory for Directing Gene Expression in Cell Populations

Microbial populations can adapt to adverse environmental conditions either by appropriately sensing and responding to the changes in their surroundings or by stochastically switching to an alternative phenotypic state. Recent data point out that these two strategies can be exhibited by the same cellular system, depending on the amplitude/frequency of the environmental perturbations and on the architecture of the genetic circuits involved in the adaptation process. Accordingly, several mitigation strategies have been designed for the effective control of microbial populations in different contexts, ranging from biomedicine to bioprocess engineering. Technically, such control strategies have been made possible by the advances made at the level of computational and synthetic biology combined with control theory. However, these control strategies have been applied mostly to synthetic gene circuits, impairing the applicability of the approach to natural circuits. In this review, we argue that it is possible to expand these control strategies to any cellular system and gene circuits based on a metric derived from this information theory, i.e., mutual information (MI). Indeed, based on this metric, it should be possible to characterize the natural frequency of any gene circuits and use it for controlling gene circuits within a population of cells.

Naturalising Agent Causation

The idea of agent causation—that a system such as a living organism can be a cause of things in the world—is often seen as mysterious and deemed to be at odds with the physicalist thesis that is now commonly embraced in science and philosophy. Instead, the causal power of organisms is attributed to mechanistic components within the system or derived from the causal activity at the lowest level of physical description. In either case, the ‘agent’ itself (i.e., the system as a whole) is left out of the picture entirely, and agent causation is explained away. We argue that this is not the right way to think about causation in biology or in systems more generally. We present a framework of eight criteria that we argue, collectively, describe a system that overcomes the challenges concerning agent causality in an entirely naturalistic and non-mysterious way. They are: (1) thermodynamic autonomy, (2) persistence, (3) endogenous activity, (4) holistic integration, (5) low-level indeterminacy, (6) multiple realisability, (7) historicity, (8) agent-level normativity. Each criterion is taken to be dimensional rather than categorical, and thus we conclude with a short discussion on how researchers working on quantifying agency may use this multidimensional framework to situate and guide their research.

Distinct heterochromatin-like domains promote transcriptional memory and silence parasitic genetic elements in bacteria

There is increasing evidence that prokaryotes maintain chromosome structure, which in turn impacts gene expression. We recently characterized densely occupied, multi-kilobase regions in the E. coli genome that are transcriptionally silent, similar to eukaryotic heterochromatin. These extended protein occupancy domains (EPODs) span genomic regions containing genes encoding metabolic pathways as well as parasitic elements such as prophages. Here, we investigate the contributions of nucleoid-associated proteins (NAPs) to the structuring of these domains, by examining the impacts of deleting NAPs on EPODs genome-wide in E. coli and B. subtilis. We identify key NAPs contributing to the silencing of specific EPODs, whose deletion opens a chromosomal region for RNA polymerase binding at genes contained within that region. We show that changes in E. coli EPODs facilitate an extra layer of transcriptional regulation, which prepares cells for exposure to exotic carbon sources. Furthermore, we distinguish novel xenogeneic silencing roles for the NAPs Fis and Hfq, with the presence of at least one being essential for cell viability in the presence of domesticated prophages. Our findings reveal previously unrecognized mechanisms through which genomic architecture primes bacteria for changing metabolic environments and silences harmful genomic elements.

Biological Prescience: The Role of Anticipation in Organismal Processes

Anticipation is the act of using information about the past and present to make predictions about future scenarios. As a concept, it is predominantly associated with the psychology of the human mind; however, there is accumulating evidence that diverse taxa without complex neural systems, and even biochemical networks themselves, can respond to perceived future conditions. Although anticipatory processes, such as circadian rhythms, stress priming, and cephalic responses, have been extensively studied over the last three centuries, newer research on anticipatory genetic networks in microbial species shows that anticipatory processes are widespread, evolutionarily old, and not simply reserved for neurological complex organisms. Overall, data suggest that anticipatory responses represent a unique type of biological processes that can be distinguished based on their organizational properties and mechanisms. Unfortunately, an empirically based biologically explicit framework for describing anticipatory processes does not currently exist. This review attempts to fill this void by discussing the existing examples of anticipatory processes in non-cognitive organisms, providing potential criteria for defining anticipatory processes, as well as their putative mechanisms, and drawing attention to the often-overlooked role of anticipation in the evolution of physiological systems. Ultimately, a case is made for incorporating an anticipatory framework into the existing physiological paradigm to advance our understanding of complex biological processes.

Genes and knowledge: Response to Baverstock, K. the gene an appraisal. https://doi.org/10.1016/j.pbiomolbio.2021.04.005

This response aims to expand on some of the issues raised by Keith Baverstock's The Gene: An Appraisal, especially on the evolution and nature of knowledge in living things. In contrast to the simple associationism envisaged in "genetic information", it emphasises the dynamic complexity and changeability of most natural environments, and, therefore, predictability based on underlying statistical structures. That seems to be the basis of the "cognitive" functions increasingly being reported about cellular, as well as more evolved, functions, and of the autonomous agency of organisms thriving creatively in complex environments.

Allostatic Changes in the cAMP System Drive Opioid-Induced Adaptation in Striatal Dopamine Signaling

Opioids are powerful addictive agents that alter dopaminergic influence on reward signaling in medium spiny neurons (MSNs) of the nucleus accumbens. Repeated opioid exposure triggers adaptive changes, shifting reward valuation to the allostatic state underlying tolerance. However, the cellular substrates and molecular logic underlying such allostatic changes are not well understood. Here, we report that the plasticity of dopamine-induced cyclic AMP (cAMP) signaling in MSNs serves as a cellular substrate for drug-induced allostatic adjustments. By recording cAMP responses to optically evoked dopamine in brain slices from mice subjected to various opioid exposure paradigms, we define profound neuronal-type-specific adaptations. We find that opioid exposure pivots the initial hyper-responsiveness of D1-MSNs toward D2-MSN dominance as dependence escalates. Presynaptic dopamine transporters and postsynaptic phosphodiesterases critically enable cell-specific adjustments of cAMP that control the balance between opponent D1-MSN and D2-MSN channels. We propose a quantitative model of opioid-induced allostatic adjustments in cAMP signal strength that balances circuit activity.

Muntean et al. examine how opioid exposure influences cyclic AMP (cAMP) responses to dopamine in striatal medium spiny neurons (MSNs). They describe allostatic adaptations in the processing of dopaminergic signals by D1-MSN and D2-MSN populations as opioid administration progresses from acute exposure to chronic use, and they define molecular elements contributing to the process.

Theoretical, and epistemological challenges in scientific investigations of complex emotional states in animals

This review brings to light critical epistemological and theoretical considerations when studying complex emotional states in animals. We discuss anthropomorphic and Umwelt perspectives of nonhuman animals and the ways in which distinct theories of consciousness and neural processing may restrict the potential for the development of knowledge on the topic. Within the same line of argumentation, we consider influences of the debate between monism and dualism and psychology's behaviorism and cognitive theories. Finally, we contrast the affective consciousness, higher-order emotional consciousness, and constructed emotion theories to further our understanding of complex emotional states in animals.

Learning action-oriented models through active inference

Converging theories suggest that organisms learn and exploit probabilistic models of their environment. However, it remains unclear how such models can be learned in practice. The open-ended complexity of natural environments means that it is generally infeasible for organisms to model their environment comprehensively. Alternatively, action-oriented models attempt to encode a parsimonious representation of adaptive agent-environment interactions. One approach to learning action-oriented models is to learn online in the presence of goal-directed behaviours. This constrains an agent to behaviourally relevant trajectories, reducing the diversity of the data a model need account for. Unfortunately, this approach can cause models to prematurely converge to sub-optimal solutions, through a process we refer to as a bad-bootstrap. Here, we exploit the normative framework of active inference to show that efficient action-oriented models can be learned by balancing goal-oriented and epistemic (information-seeking) behaviours in a principled manner. We illustrate our approach using a simple agent-based model of bacterial chemotaxis. We first demonstrate that learning via goal-directed behaviour indeed constrains models to behaviorally relevant aspects of the environment, but that this approach is prone to sub-optimal convergence. We then demonstrate that epistemic behaviours facilitate the construction of accurate and comprehensive models, but that these models are not tailored to any specific behavioural niche and are therefore less efficient in their use of data. Finally, we show that active inference agents learn models that are parsimonious, tailored to action, and which avoid bad bootstraps and sub-optimal convergence. Critically, our results indicate that models learned through active inference can support adaptive behaviour in spite of, and indeed because of, their departure from veridical representations of the environment. Our approach provides a principled method for learning adaptive models from limited interactions with an environment, highlighting a route to sample efficient learning algorithms.

Regenerative Adaptation to Electrochemical Perturbation in Planaria: A Molecular Analysis of Physiological Plasticity

Anatomical homeostasis results from dynamic interactions between gene expression, physiology, and the external environment. Owing to its complexity, this cellular and organism-level phenotypic plasticity is still poorly understood. We establish planarian regeneration as a model for acquired tolerance to environments that alter endogenous physiology. Exposure to barium chloride (BaCl₂) results in a rapid degeneration of anterior tissue in Dugesia japonica. Remarkably, continued exposure to fresh solution of BaCl₂ results in regeneration of heads that are insensitive to BaCl₂. RNA-seq revealed transcriptional changes in BaCl₂-adapted heads that suggests a model of adaptation to excitotoxicity. Loss-of-function experiments confirmed several predictions: blockage of chloride and calcium channels allowed heads to survive initial BaCl₂ exposure, inducing adaptation without prior exposure, whereas blockade of TRPM channels reversed adaptation. Such highly adaptive plasticity may represent an attractive target for biomedical strategies in a wide range of applications beyond its immediate relevance to excitotoxicity preconditioning.

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Exposure to BaCl₂ causes the heads of Dugesia japonica to degenerate

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Prolonged exposure to BaCl₂ results in regeneration of a BaCl₂-insensitive head

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Ion channel expression is altered in the head to compensate for excitotoxic stress

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TRPMa is upregulated in BaCl₂-treated animals; blocking TRPM prevents adaptation

The power of predictions: An emerging paradigm for psychological research

The last two decades of neuroscience research has produced a growing number of studies that suggest the various psychological phenomena are produced by predictive processes in the brain. When considered together, these studies form a coherent, neurobiologically-inspired research program for guiding psychological research about the mind and behavior. In this paper, we briefly consider the common assumptions and hypotheses that unify an emerging framework and discuss its ramifications, both for improving the replicability and robustness of psychological research and for innovating psychological theory by suggesting an alternative ontology of the human mind.

A cAMP/CRP-controlled mechanism for the incorporation of extracellular ADP-glucose in Escherichia coli involving NupC and NupG nucleoside transporters

ADP-glucose is the precursor of glycogen biosynthesis in bacteria, and a compound abundant in the starchy plant organs ingested by many mammals. Here we show that the enteric species Escherichia coli is capable of scavenging exogenous ADP-glucose for use as a glycosyl donor in glycogen biosynthesis and feed the adenine nucleotide pool. To unravel the molecular mechanisms involved in this process, we screened the E. coli single-gene deletion mutants of the Keio collection for glycogen content in ADP-glucose-containing culture medium. In comparison to wild-type (WT) cells, individual ∆nupC and ∆nupG mutants lacking the cAMP/CRP responsive inner-membrane nucleoside transporters NupC and NupG displayed reduced glycogen contents and slow ADP-glucose incorporation. In concordance, ∆cya and ∆crp mutants accumulated low levels of glycogen and slowly incorporated ADP-glucose. Two-thirds of the glycogen-excess mutants identified during screening lacked functions that underlie envelope biogenesis and integrity, including the RpoE specific RseA anti-sigma factor. These mutants exhibited higher ADP-glucose uptake than WT cells. The incorporation of either ∆crp, ∆nupG or ∆nupC null alleles sharply reduced the ADP-glucose incorporation and glycogen content initially witnessed in ∆rseA cells. Overall, the data showed that E. coli incorporates extracellular ADP-glucose through a cAMP/CRP-regulated process involving the NupC and NupG nucleoside transporters that is facilitated under envelope stress conditions.

Biological evolution as defense of 'self'

Although the origin of self-referential consciousness is unknown, it can be argued that the instantiation of self-reference was the commencement of the living state as phenomenal experientiality. As self-referential cognition is demonstrated by all living organisms, life can be equated with the sustenance of cellular homeostasis in the continuous defense of 'self'. It is proposed that the epicenter of 'self' is perpetually embodied within the basic cellular form in which it was instantiated. Cognition-Based Evolution argues that all of biological and evolutionary development represents the perpetual autopoietic defense of self-referential basal cellular states of homeostatic preference. The means by which these states are attained and maintained is through self-referential measurement of information and its communication. The multicellular forms, either as biofilms or holobionts, represent the cellular attempt to achieve maximum states of informational distinction and energy efficiency through individual and collective means. In this frame, consciousness, self-consciousness and intelligence can be identified as forms of collective cellular phenotype directed towards the defense of fundamental cellular self-reference.

A bacterial signaling system regulates noise to enable bet hedging

Phenotypic diversity helps populations persist in changing and often unpredictable environments. One diversity-generating strategy is for individuals to switch randomly between phenotypic states such that one subpopulation has high fitness in the present environment, and another subpopulation has high fitness in an environment that might be encountered in the future. This sort of biological bet hedging can be found in all domains of life. Here, we discuss a recently described example from the bacterium Escherichia coli. When exposed to both oxygen and trimethylamine oxide (TMAO), E. coli hedges its bets on the possibility of oxygen loss by generating high cell-to-cell variability in the expression of the TMAO respiratory system. If oxygen is rapidly depleted from the environment, only those cells that had been expressing the TMAO respiratory system at high levels can continue to grow. This particular bet-hedging scheme possesses some unusual characteristics, most notably the decoupling of gene expression noise from the mean expression level. This decoupling allows bacteria to sense oxygen and regulate the amount of variability in TMAO reductase expression (that is, to turn bet hedging on or off) without having to adjust the mean TMAO reductase expression level. In this review, we discuss the features of the TMAO signaling pathway that permit the decoupling of gene expression noise from the mean and the regulation of bet hedging. We also highlight some open questions regarding the TMAO respiratory system and its regulatory architecture that may be relevant to many signaling systems.

Dual role of starvation signaling in promoting growth and recovery

Growing cells are subject to cycles of nutrient depletion and repletion. A shortage of nutrients activates a starvation program that promotes growth in limiting conditions. To examine whether nutrient-deprived cells prepare also for their subsequent recovery, we followed the transcription program activated in budding yeast transferred to low-phosphate media and defined its contribution to cell growth during phosphate limitation and upon recovery. An initial transcription wave was induced by moderate phosphate depletion that did not affect cell growth. A second transcription wave followed when phosphate became growth limiting. The starvation program contributed to growth only in the second, growth-limiting phase. Notably, the early response, activated at moderate depletion, promoted recovery from starvation by increasing phosphate influx upon transfer to rich medium. Our results suggest that cells subject to nutrient depletion prepare not only for growth in the limiting conditions but also for their predicted recovery once nutrients are replenished.

Biological information systems: Evolution as cognition-based information management

An alternative biological synthesis is presented that conceptualizes evolutionary biology as an epiphenomenon of integrated self-referential information management. Since all biological information has inherent ambiguity, the systematic assessment of information is required by living organisms to maintain self-identity and homeostatic equipoise in confrontation with environmental challenges. Through their self-referential attachment to information space, cells are the cornerstone of biological action. That individualized assessment of information space permits self-referential, self-organizing niche construction. That deployment of information and its subsequent selection enacted the dominant stable unicellular informational architectures whose biological expressions are the prokaryotic, archaeal, and eukaryotic unicellular forms. Multicellularity represents the collective appraisal of equivocal environmental information through a shared information space. This concerted action can be viewed as systematized information management to improve information quality for the maintenance of preferred homeostatic boundaries among the varied participants. When reiterated in successive scales, this same collaborative exchange of information yields macroscopic organisms as obligatory multicellular holobionts. Cognition-Based Evolution (CBE) upholds that assessment of information precedes biological action, and the deployment of information through integrative self-referential niche construction and natural cellular engineering antecedes selection. Therefore, evolutionary biology can be framed as a complex reciprocating interactome that consists of the assessment, communication, deployment and management of information by self-referential organisms at multiple scales in continuous confrontation with environmental stresses.

The theory of constructed emotion: an active inference account of interoception and categorization

The science of emotion has been using folk psychology categories derived from philosophy to search for the brain basis of emotion. The last two decades of neuroscience research have brought us to the brink of a paradigm shift in understanding the workings of the brain, however, setting the stage to revolutionize our understanding of what emotions are and how they work. In this article, we begin with the structure and function of the brain, and from there deduce what the biological basis of emotions might be. The answer is a brain-based, computational account called the theory of constructed emotion.

Craving for the future: the brain as a nutritional prediction system

In the last decades, predictive coding has emerged as an important framework for understanding how the brain processes information. It states that the brain is constantly inferring and predicting sensory data from statistical regularities in its environment. While this framework has been largely applied to sensory processing and motor control, we argue here that it could also serve as framework for a better understanding of how animals regulate nutrient homeostasis. Mechanisms that underlie nutrient homeostasis are commonly described in terms of negative feedback control, which compares current states with a reference point, called setpoint, and counteracts any mismatches. Using concepts from control theory, we explain shortcomings of negative feedback as a purely reactive controller, and how feed-forward mechanisms could be incorporated into feedback control to improve the performance of the control system. We then provide numerous examples to show that many insects, as well as mammals, make use of feed-forward, anticipatory mechanisms that go beyond the prevailing view of homeostasis being achieved through reactive negative feedback. The emerging picture is that the brain incorporates predictive signals as well as negative feedback to regulate nutrient homeostasis.

Cough-Anal Reflex May Be the Expression of a Pre-Programmed Postural Action

When coughing, an involuntary contraction of the external anal sphincter occurs, in order to prevent unwanted leakages or sagging of the pelvis muscular wall. Literature originally described such cough-anal response as a reflex elicited by cough, therefore identifying a precise cause-effect relationship. However, recent studies report that the anal contraction actually precedes the rise in abdominal pressure during cough expiratory effort, so that the sphincter activity should be pre-programmed. In recent years, an important family of pre-programmed muscle activities has been well documented to precede voluntary movements: these anticipatory actions play a fundamental role in whole body and segmental postural control, hence they are referred to as anticipatory postural adjustments (APAs). On these basis, we searched in literature for similarities between APAs and the cough-anal response, observing that both follow the same predictive homeostatic principle, namely that anticipatory collateral actions are needed to prevent the unwanted mechanical consequences induced by the primary movement. We thus propose that the cough-anal response also belongs to the family of pre-programmed actions, as it may be interpreted as an APA acting on the abdominal-thoracic compartment; in other words, the cough-anal response may actually be an Anticipatory Sphincter Adjustment, the visceral counterpart of APAs.

A systematic approach to cancer: evolution beyond selection

Cancer is typically scrutinized as a pathological process characterized by chromosomal aberrations and clonal expansion subject to stochastic Darwinian selection within adaptive cellular ecosystems. Cognition based evolution is suggested as an alternative approach to cancer development and progression in which neoplastic cells of differing karyotypes and cellular lineages are assessed as self-referential agencies with purposive participation within tissue microenvironments. As distinct self-aware entities, neoplastic cells occupy unique participant/observer status within tissue ecologies. In consequence, neoplastic proliferation by clonal lineages is enhanced by the advantaged utilization of ecological resources through flexible re-connection with progenitor evolutionary stages.

On Having No Head: Cognition throughout Biological Systems

The central nervous system (CNS) underlies memory, perception, decision-making, and behavior in numerous organisms. However, neural networks have no monopoly on the signaling functions that implement these remarkable algorithms. It is often forgotten that neurons optimized cellular signaling modes that existed long before the CNS appeared during evolution, and were used by somatic cellular networks to orchestrate physiology, embryonic development, and behavior. Many of the key dynamics that enable information processing can, in fact, be implemented by different biological hardware. This is widely exploited by organisms throughout the tree of life. Here, we review data on memory, learning, and other aspects of cognition in a range of models, including single celled organisms, plants, and tissues in animal bodies. We discuss current knowledge of the molecular mechanisms at work in these systems, and suggest several hypotheses for future investigation. The study of cognitive processes implemented in aneural contexts is a fascinating, highly interdisciplinary topic that has many implications for evolution, cell biology, regenerative medicine, computer science, and synthetic bioengineering.

Cognition, Information Fields and Hologenomic Entanglement: Evolution in Light and Shadow

As the prime unification of Darwinism and genetics, the Modern Synthesis continues to epitomize mainstay evolutionary theory. Many decades after its formulation, its anchor assumptions remain fixed: conflict between macro organic organisms and selection at that level represent the near totality of any evolutionary narrative. However, intervening research has revealed a less easily appraised cellular and microbial focus for eukaryotic existence. It is now established that all multicellular eukaryotic organisms are holobionts representing complex collaborations between the co-aligned microbiome of each eukaryote and its innate cells into extensive mixed cellular ecologies. Each of these ecological constituents has demonstrated faculties consistent with basal cognition. Consequently, an alternative hologenomic entanglement model is proposed with cognition at its center and conceptualized as Pervasive Information Fields within a quantum framework. Evolutionary development can then be reconsidered as being continuously based upon communication between self-referential constituencies reiterated at every scope and scale. Immunological reactions support and reinforce self-recognition juxtaposed against external environmental stresses.

The origins of mutational robustness

Biological systems are resistant to genetic changes; a property known as mutational robustness, the origin of which remains an open question. In recent years, researchers have explored emergent properties of biological systems and mechanisms of genetic redundancy to reveal how mutational robustness emerges and persists. Several mechanisms have been proposed to explain the origin of mutational robustness, including molecular chaperones and gene duplication. The latter has received much attention, but its role in robustness remains controversial. Here, I examine recent findings linking genetic redundancy through gene duplication and mutational robustness. Experimental evolution and genome resequencing have made it possible to test the role of gene duplication in tolerating mutations at both the coding and regulatory levels. This evidence as well as previous findings on regulatory reprogramming of duplicates support the role of gene duplication in the origin of robustness.

The cognitive cell: bacterial behavior reconsidered

Research on how bacteria adapt to changing environments underlies the contemporary biological understanding of signal transduction (ST), and ST provides the foundation of the information-processing approach that is the hallmark of the ‘cognitive revolution,’ which began in the mid-20th century. Yet cognitive scientists largely remain oblivious to research into microbial behavior that might provide insights into problems in their own domains, while microbiologists seem equally unaware of the potential importance of their work to understanding cognitive capacities in multicellular organisms, including vertebrates. Evidence in bacteria for capacities encompassed by the concept of cognition is reviewed. Parallels exist not only at the heuristic level of functional analogue, but also at the level of molecular mechanism, evolution and ecology, which is where fruitful cross-fertilization among disciplines might be found.

Balanced trade-offs between alternative strategies shape the response of C. elegans reproduction to chronic heat stress

To ensure long-term reproductive success organisms have to cope with harsh environmental extremes. A reproductive strategy that simply maximizes offspring production is likely to be disadvantageous because it could lead to a catastrophic loss of fecundity under unfavorable conditions. To understand how an appropriate balance is achieved, we investigated reproductive performance of C. elegans under conditions of chronic heat stress. We found that following even prolonged exposure to temperatures at which none of the offspring survive, worms could recover and resume reproduction. The likelihood of producing viable offspring falls precipitously after exposure to temperatures greater than 28°C primarily due to sperm damage. Surprisingly, we found that worms that experienced higher temperatures can recover considerably better, provided they did not initiate ovulation. Therefore mechanisms controlling this process must play a crucial role in determining the probability of recovery. We show, however, that suppressing ovulation is only beneficial under relatively long stresses, whereas it is a disadvantageous strategy under shorter stresses of the same intensity. This is because the benefit of shutting down egg laying, and thus protecting the reproductive system, is negated by the cost associated with implementing this strategy--it takes considerable time to recover and produce offspring. We interpret these balanced trade-offs as a dynamic response of the C. elegans reproductive system to stress and an adaptation to life in variable and unpredictable conditions.

Near-real-time analysis of the phenotypic responses of Escherichia coli to 1-butanol exposure using Raman Spectroscopy

Raman spectroscopy was used to study the time course of phenotypic responses of Escherichia coli (DH5α) to 1-butanol exposure (1.2% [vol/vol]). Raman spectroscopy is of interest for bacterial phenotyping because it can be performed (i) in near real time, (ii) with minimal sample preparation (label-free), and (iii) with minimal spectral interference from water. Traditional off-line analytical methodologies were applied to both 1-butanol-treated and control cells to draw correlations with Raman data. Here, distinct sets of Raman bands are presented that characterize phenotypic traits of E. coli with maximized correlation to off-line measurements. In addition, the observed time course phenotypic responses of E. coli to 1.2% (vol/vol) 1-butanol exposure included the following: (i) decreased saturated fatty acids levels, (ii) retention of unsaturated fatty acids and low levels of cyclopropane fatty acids, (iii) increased membrane fluidity following the initial response of increased rigidity, and (iv) no changes in total protein content or protein-derived amino acid composition. For most phenotypic traits, correlation coefficients between Raman spectroscopy and traditional off-line analytical approaches exceeded 0.75, and major trends were captured. The results suggest that near-real-time Raman spectroscopy is suitable for approximating metabolic and physiological phenotyping of bacterial cells subjected to toxic environmental conditions.

Bacterial adaptation through loss of function

The metabolic capabilities and regulatory networks of bacteria have been optimized by evolution in response to selective pressures present in each species' native ecological niche. In a new environment, however, the same bacteria may grow poorly due to regulatory constraints or biochemical deficiencies. Adaptation to such conditions can proceed through the acquisition of new cellular functionality due to gain of function mutations or via modulation of cellular networks. Using selection experiments on transposon-mutagenized libraries of bacteria, we illustrate that even under conditions of extreme nutrient limitation, substantial adaptation can be achieved solely through loss of function mutations, which rewire the metabolism of the cell without gain of enzymatic or sensory function. A systematic analysis of similar experiments under more than 100 conditions reveals that adaptive loss of function mutations exist for many environmental challenges. Drawing on a wealth of examples from published articles, we detail the range of mechanisms through which loss-of-function mutations can generate such beneficial regulatory changes, without the need for rare, specific mutations to fine-tune enzymatic activities or network connections. The high rate at which loss-of-function mutations occur suggests that null mutations play an underappreciated role in the early stages of adaption of bacterial populations to new environments.