Cell signaling as a cognitive process

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.

Cellular forgetting, desensitisation, stress and ageing in signalling networks. When do cells refuse to learn more?

Recent findings show that single, non-neuronal cells are also able to learn signalling responses developing cellular memory. In cellular learning nodes of signalling networks strengthen their interactions e.g. by the conformational memory of intrinsically disordered proteins, protein translocation, miRNAs, lncRNAs, chromatin memory and signalling cascades. This can be described by a generalized, unicellular Hebbian learning process, where those signalling connections, which participate in learning, become stronger. Here we review those scenarios, where cellular signalling is not only repeated in a few times (when learning occurs), but becomes too frequent, too large, or too complex and overloads the cell. This leads to desensitisation of signalling networks by decoupling signalling components, receptor internalization, and consequent downregulation. These molecular processes are examples of anti-Hebbian learning and 'forgetting' of signalling networks. Stress can be perceived as signalling overload inducing the desensitisation of signalling pathways. Ageing occurs by the summative effects of cumulative stress downregulating signalling. We propose that cellular learning desensitisation, stress and ageing may be placed along the same axis of more and more intensive (prolonged or repeated) signalling. We discuss how cells might discriminate between repeated and unexpected signals, and highlight the Hebbian and anti-Hebbian mechanisms behind the fold-change detection in the NF-κB signalling pathway. We list drug design methods using Hebbian learning (such as chemically-induced proximity) and clinical treatment modalities inducing (cancer, drug allergies) desensitisation or avoiding drug-induced desensitisation. A better discrimination between cellular learning, desensitisation and stress may open novel directions in drug design, e.g. helping to overcome drug resistance.

10-min exposure to a 2.5% hypercapnic environment increases cerebral blood blow but does not impact executive function

Space travel and exploration are associated with increased ambient CO2 (i.e., a hypercapnic environment). Some work reported that the physiological changes (e.g., increased cerebral blood flow [CBF]) associated with a chronic hypercapnic environment contributes to a "space fog" that adversely impacts cognition and psychomotor performance, whereas other work reported no change or a positive change. Here, we employed the antisaccade task to evaluate whether transient exposure to a hypercapnic environment influences top-down executive function (EF). Antisaccades require a goal-directed eye movement mirror-symmetrical to a target and are an ideal tool for identifying subtle EF changes. Healthy young adults (aged 19-25 years) performed blocks of antisaccade trials prior to (i.e., pre-intervention), during (i.e., concurrent) and after (i.e., post-intervention) 10-min of breathing factional inspired CO2 (FiCO2) of 2.5% (i.e., hypercapnic condition) and during a normocapnic (i.e., control) condition. In both conditions, CBF, ventilatory and cardiorespiratory responses were measured. Results showed that the hypercapnic condition increased CBF, ventilation and end-tidal CO2 and thus demonstrated an expected physiological adaptation to increased FiCO2. Notably, however, null hypothesis and equivalence tests indicated that concurrent and post-intervention antisaccade reaction times were refractory to the hypercapnic environment; that is, transient exposure to a FiCO2 of 2.5% did not produce a real-time or lingering influence on an oculomotor-based measure of EF. Accordingly, results provide a framework that - in part - establishes the FiCO2 percentage and timeline by which high-level EF can be maintained. Future work will explore CBF and EF dynamics during chronic hypercapnic exposure as more direct proxy for the challenges of space flight and exploration.

PI3K signaling through a biochemical systems lens

Following 3 decades of extensive research into PI3K signaling, it is now evidently clear that the underlying network does not equate to a simple ON/OFF switch. This is best illustrated by the multifaceted nature of the many diseases associated with aberrant PI3K signaling, including common cancers, metabolic disease, and rare developmental disorders. However, we are still far from a complete understanding of the fundamental control principles that govern the numerous phenotypic outputs that are elicited by activation of this well-characterized biochemical signaling network, downstream of an equally diverse set of extrinsic inputs. At its core, this is a question on the role of PI3K signaling in cellular information processing and decision making. Here, we review the determinants of accurate encoding and decoding of growth factor signals and discuss outstanding questions in the PI3K signal relay network. We emphasize the importance of quantitative biochemistry, in close integration with advances in single-cell time-resolved signaling measurements and mathematical modeling.

Neurotrophic effects of intermittent fasting, calorie restriction and exercise: a review and annotated bibliography

In the last decades, important progress has been achieved in the understanding of the neurotrophic effects of intermittent fasting (IF), calorie restriction (CR) and exercise. Improved neuroprotection, synaptic plasticity and adult neurogenesis (NSPAN) are essential examples of these neurotrophic effects. The importance in this respect of the metabolic switch from glucose to ketone bodies as cellular fuel has been highlighted. More recently, calorie restriction mimetics (CRMs; resveratrol and other polyphenols in particular) have been investigated thoroughly in relation to NSPAN. In the narrative review sections of this manuscript, recent findings on these essential functions are synthesized and the most important molecules involved are presented. The most researched signaling pathways (PI3K, Akt, mTOR, AMPK, GSK3β, ULK, MAPK, PGC-1α, NF-κB, sirtuins, Notch, Sonic hedgehog and Wnt) and processes (e.g., anti-inflammation, autophagy, apoptosis) that support or thwart neuroprotection, synaptic plasticity and neurogenesis are then briefly presented. This provides an accessible entry point to the literature. In the annotated bibliography section of this contribution, brief summaries are provided of about 30 literature reviews relating to the neurotrophic effects of interest in relation to IF, CR, CRMs and exercise. Most of the selected reviews address these essential functions from the perspective of healthier aging (sometimes discussing epigenetic factors) and the reduction of the risk for neurodegenerative diseases (Alzheimer's disease, Huntington's disease, Parkinson's disease) and depression or the improvement of cognitive function.

The brain is not mental! coupling neuronal and immune cellular processing in human organisms

Significant efforts have been made in the past decades to understand how mental and cognitive processes are underpinned by neural mechanisms in the brain. This paper argues that a promising way forward in understanding the nature of human cognition is to zoom out from the prevailing picture focusing on its neural basis. It considers instead how neurons work in tandem with other type of cells (e.g., immune) to subserve biological self-organization and adaptive behavior of the human organism as a whole. We focus specifically on the immune cellular processing as key actor in complementing neuronal processing in achieving successful self-organization and adaptation of the human body in an ever-changing environment. We overview theoretical work and empirical evidence on "basal cognition" challenging the idea that only the neuronal cells in the brain have the exclusive ability to "learn" or "cognize." The focus on cellular rather than neural, brain processing underscores the idea that flexible responses to fluctuations in the environment require a carefully crafted orchestration of multiple cellular and bodily systems at multiple organizational levels of the biological organism. Hence cognition can be seen as a multiscale web of dynamic information processing distributed across a vast array of complex cellular (e.g., neuronal, immune, and others) and network systems, operating across the entire body, and not just in the brain. Ultimately, this paper builds up toward the radical claim that cognition should not be confined to one system alone, namely, the neural system in the brain, no matter how sophisticated the latter notoriously is.

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.

Assessing the effects of antipsychotic medications on schizophrenia functional analysis: a postmortem proteome study

Antipsychotic drugs (APDs) are effective in treating positive symptoms of schizophrenia (SCZ). However, they have a substantial impact on postmortem studies. As most cohorts lack samples from drug-naive patients, many studies, rather than understanding SCZ pathophysiology, are analyzing the drug effects. We hypothesized that comparing SCZ-altered and APD-influenced signatures derived from the same cohort can provide better insight into SCZ pathophysiology. For this, we performed LCMS-based proteomics on dorsolateral prefrontal cortex (DLPFC) samples from control and SCZ subjects and used statistical approaches to identify SCZ-altered and APD-influenced proteomes, validated experimentally using independent cohorts and published datasets. Functional analysis of both proteomes was contrasted at the biological-pathway, cell-type, subcellular-synaptic, and drug-target levels. In silico validation revealed that the SCZ-altered proteome was conserved across several studies from the DLPFC and other brain areas. At the pathway level, SCZ influenced changes in homeostasis, signal-transduction, cytoskeleton, and dendrites, whereas APD influenced changes in synaptic-signaling, neurotransmitter-regulation, and immune-system processes. At the cell-type level, the SCZ-altered and APD-influenced proteomes were associated with two distinct striatum-projecting layer-5 pyramidal neurons regulating dopaminergic-secretion. At the subcellular synaptic level, compensatory pre- and postsynaptic events were observed. At the drug-target level, dopaminergic processes influenced the SCZ-altered upregulated-proteome, whereas nondopaminergic and a diverse array of non-neuromodulatory mechanisms influenced the downregulated-proteome. Previous findings were not independent of the APD effect and thus require re-evaluation. We identified a hyperdopaminergic cortex and drugs targeting the cognitive SCZ-symptoms and discussed their influence on SCZ pathology in the context of the cortico-striatal pathway.

Cellular sentience as the primary source of biological order and evolution

All life is cellular, starting some 4 billion years ago with the emergence of the first cells. In order to survive their early evolution in the face of an extremely challenging environment, the very first cells invented cellular sentience and cognition, allowing them to make relevant decisions to survive through creative adaptations in a continuously running evolutionary narrative. We propose that the success of cellular life has crucially depended on a biological version of Maxwell's demons which permits the extraction of relevant sensory information and energy from the cellular environment, allowing cells to sustain anti-entropic actions. These sensor-effector actions allowed for the creative construction of biological order in the form of diverse organic macromolecules, including crucial polymers such as DNA, RNA, and cytoskeleton. Ordered biopolymers store analogue (structures as templates) and digital (nucleotide sequences of DNA and RNA) information that functioned as a form memory to support the development of organisms and their evolution. Crucially, all cells are formed by the division of previous cells, and their plasma membranes are physically and informationally continuous across evolution since the beginning of cellular life. It is argued that life is supported through life-specific principles which support cellular sentience, distinguishing life from non-life. Biological order, together with cellular cognition and sentience, allow the creative evolution of all living organisms as the authentic authors of evolutionary novelty.

High-Throughput, Living Single-Cell, Multiple Secreted Biomarker Profiling Using Microfluidic Chip and Machine Learning for Tumor Cell Classification

Secreted proteins provide abundant functional information on living cells and can be used as important tumor diagnostic markers, of which profiling at the single-cell level is helpful for accurate tumor cell classification. Currently, achieving living single-cell multi-index, high-sensitivity, and quantitative secretion biomarker profiling remains a great challenge. Here, a high-throughput living single-cell multi-index secreted biomarker profiling platform is proposed, combined with machine learning, to achieve accurate tumor cell classification. A single-cell culture microfluidic chip with self-assembled graphene oxide quantum dots (GOQDs) enables high-activity single-cell culture, ensuring normal secretion of biomarkers and high-throughput single-cell separation, providing sufficient statistical data for machine learning. At the same time, the antibody barcode chip with self-assembled GOQDs performs multi-index, highly sensitive, and quantitative detection of secreted biomarkers, in which each cell culture chamber covers a whole barcode array. Importantly, by combining the K-means strategy with machine learning, thousands of single tumor cell secretion data are analyzed, enabling tumor cell classification with a recognition accuracy of 95.0%. In addition, further profiling of the grouping results reveals the unique secretion characteristics of subgroups. This work provides an intelligent platform for high-throughput living single-cell multiple secretion biomarker profiling, which has broad implications for cancer investigation and biomedical research.

Intermittent ERK oscillations downstream of FGF in mouse embryonic stem cells

Signal transduction networks generate characteristic dynamic activities to process extracellular signals and guide cell fate decisions such as to divide or differentiate. The differentiation of pluripotent cells is controlled by FGF/ERK signaling. However, only a few studies have addressed the dynamic activity of the FGF/ERK signaling network in pluripotent cells at high time resolution. Here, we use live cell sensors in wild-type and Fgf4-mutant mouse embryonic stem cells to measure dynamic ERK activity in single cells, for defined ligand concentrations and differentiation states. These sensors reveal pulses of ERK activity. Pulsing patterns are heterogeneous between individual cells. Consecutive pulse sequences occur more frequently than expected from simple stochastic models. Sequences become more prevalent with higher ligand concentration, but are rarer in more differentiated cells. Our results suggest that FGF/ERK signaling operates in the vicinity of a transition point between oscillatory and non-oscillatory dynamics in embryonic stem cells. The resulting heterogeneous dynamic signaling activities add a new dimension to cellular heterogeneity that may be linked to divergent fate decisions in stem cell cultures.

Summary: High time-resolution measurements reveal previously unseen signaling dynamics in single pluripotent cells, which alternate between oscillatory and non-oscillatory ERK activity. ERK dynamics change with ligand concentration, cell cycle and differentiation state.

Fundamental Clock of Biological Aging: Convergence of Molecular, Neurodegenerative, Cognitive and Psychiatric Pathways: Non-Equilibrium Thermodynamics Meet Psychology

In humans, age-associated degrading changes, widely observed in molecular and cellular processes underly the time-dependent decline in spatial navigation, time perception, cognitive and psychological abilities, and memory. Cross-talk of biological, cognitive, and psychological clocks provides an integrative contribution to healthy and advanced aging. At the molecular level, genome, proteome, and lipidome instability are widely recognized as the primary causal factors in aging. We narrow attention to the roles of protein aging linked to prevalent amino acids chirality, enzymatic and spontaneous (non-enzymatic) post-translational modifications (PTMs ^SP), and non-equilibrium phase transitions. The homochirality of protein synthesis, resulting in the steady-state non-equilibrium condition of protein structure, makes them prone to multiple types of enzymatic and spontaneous PTMs, including racemization and isomerization. Spontaneous racemization leads to the loss of the balanced prevalent chirality. Advanced biological aging related to irreversible PTMs ^SP has been associated with the nontrivial interplay between somatic (molecular aging) and mental (psychological aging) health conditions. Through stress response systems (SRS), the environmental and psychological stressors contribute to the age-associated “collapse” of protein homochirality. The role of prevalent protein chirality and entropy of protein folding in biological aging is mainly overlooked. In a more generalized context, the time-dependent shift from enzymatic to the non-enzymatic transformation of biochirality might represent an important and yet underappreciated hallmark of aging. We provide the experimental arguments in support of the racemization theory of aging.

Ultrarapid cryo-arrest of living cells on a microscope enables multiscale imaging of out-of-equilibrium molecular patterns

Imaging molecular patterns in cells by fluorescence micro- or nanoscopy has the potential to relate collective molecular behavior to cellular function. However, spatial and spectroscopic resolution is fundamentally limited by motional blur caused by finite photon fluxes and photobleaching. At physiological temperatures, photochemical reactivity does not only limit imaging at multiple scales but is also toxic to biochemical reactions that maintain cellular organization. Here, we present cryoprotectant-free ultrarapid cryo-arrest directly on a multimodal fluorescence microscope that preserves the out-of-equilibrium molecular organization of living cells. This allows the imaging of dynamic processes before cryo-arrest in combination with precise molecular pattern determination at multiple scales within the same cells under cryo-arrest. We both experimentally and theoretically show that ultrarapid cryo-arrest overcomes the fundamental resolution barrier imposed by motional blur and photochemical reactivity, enabling observation of native molecular distributions and reaction patterns that are not resolvable at physiological temperatures.

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.

Cell-cell communication through FGF4 generates and maintains robust proportions of differentiated cell types in embryonic stem cells

During embryonic development and tissue homeostasis, reproducible proportions of differentiated cell types are specified from populations of multipotent precursor cells. Molecular mechanisms that enable both robust cell-type proportioning despite variable initial conditions in the precursor cells, and the re-establishment of these proportions upon perturbations in a developing tissue remain to be characterized. Here, we report that the differentiation of robust proportions of epiblast-like and primitive endoderm-like cells in mouse embryonic stem cell cultures emerges at the population level through cell-cell communication via a short-range fibroblast growth factor 4 (FGF4) signal. We characterize the molecular and dynamical properties of the communication mechanism and show how it controls both robust cell-type proportioning from a wide range of experimentally controlled initial conditions, as well as the autonomous re-establishment of these proportions following the isolation of one cell type. The generation and maintenance of reproducible proportions of discrete cell types is a new function for FGF signaling that might operate in a range of developing tissues.

TNF controls a speed-accuracy tradeoff in the cell death decision to restrict viral spread

Rapid death of infected cells is an important antiviral strategy. However, fast decisions that are based on limited evidence can be erroneous and cause unnecessary cell death and subsequent tissue damage. How cells optimize their death decision making strategy to maximize both speed and accuracy is unclear. Here, we show that exposure to TNF, which is secreted by macrophages during viral infection, causes cells to change their decision strategy from "slow and accurate" to "fast and error-prone". Mathematical modeling combined with experiments in cell culture and whole organ culture show that the regulation of the cell death decision strategy is critical to prevent HSV-1 spread. These findings demonstrate that immune regulation of cellular cognitive processes dynamically changes a tissues' tolerance for self-damage, which is required to protect against viral spread.

Adaptive behaviour and learning in slime moulds: the role of oscillations

The slime mould Physarum polycephalum, an aneural organism, uses information from previous experiences to adjust its behaviour, but the mechanisms by which this is accomplished remain unknown. This article examines the possible role of oscillations in learning and memory in slime moulds. Slime moulds share surprising similarities with the network of synaptic connections in animal brains. First, their topology derives from a network of interconnected, vein-like tubes in which signalling molecules are transported. Second, network motility, which generates slime mould behaviour, is driven by distinct oscillations that organize into spatio-temporal wave patterns. Likewise, neural activity in the brain is organized in a variety of oscillations characterized by different frequencies. Interestingly, the oscillating networks of slime moulds are not precursors of nervous systems but, rather, an alternative architecture. Here, we argue that comparable information-processing operations can be realized on different architectures sharing similar oscillatory properties. After describing learning abilities and oscillatory activities of P. polycephalum, we explore the relation between network oscillations and learning, and evaluate the organism's global architecture with respect to information-processing potential. We hypothesize that, as in the brain, modulation of spontaneous oscillations may sustain learning in slime mould. This article is part of the theme issue 'Basal cognition: conceptual tools and the view from the single cell'.

Network-Based Analysis of Cognitive Impairment and Memory Deficits from Transcriptome Data

Aging is an inevitable process that negatively affects all living organisms and their vital functions. The brain is one of the most important organs in living beings and is primarily impacted by aging. The molecular mechanisms of learning, memory and cognition are altered over time, and the impairment in these mechanisms can lead to neurodegenerative diseases. Transcriptomics can be used to study these impairments to acquire more detailed information on the affected molecular mechanisms. Here we analyzed learning- and memory-related transcriptome data by mapping it on the organism-specific protein-protein interactome network. Subnetwork discovery algorithms were applied to discover highly dysregulated subnetworks, which were complemented with co-expression-based interactions. The functional analysis shows that the identified subnetworks are enriched with genes having roles in synaptic plasticity, gliogenesis, neurogenesis and cognition, which are reported to be related to memory and learning. With a detailed analysis, we show that the results from different subnetwork discovery algorithms or from different transcriptomic datasets can be successfully reconciled, leading to a memory-learning network that sheds light on the molecular mechanisms behind aging and memory-related impairments.

A self-organized synthetic morphogenic liposome responds with shape changes to local light cues

Reconstituting artificial proto-cells capable of transducing extracellular signals into cytoskeletal changes can reveal fundamental principles of how non-equilibrium phenomena in cellular signal transduction affect morphogenesis. Here, we generated a Synthetic Morphogenic Membrane System (SynMMS) by encapsulating a dynamic microtubule (MT) aster and a light-inducible signaling system driven by GTP/ATP chemical potential into cell-sized liposomes. Responding to light cues in analogy to morphogens, this biomimetic design embodies basic principles of localized Rho-GTPase signal transduction that generate an intracellular MT-regulator signaling gradient. Light-induced signaling promotes membrane-deforming growth of MT-filaments by dynamically elevating the membrane-proximal tubulin concentration. The resulting membrane deformations enable recursive coupling of the MT-aster with the signaling system, which generates global self-organized morphologies that reorganize towards local external cues in dependence on prior shape. SynMMS thereby signifies a step towards bio-inspired engineering of self-organized cellular morphogenesis.

The authors generated a Synthetic Morphogenic Membrane System by encapsulating a dynamic microtubule aster and a light-inducible signaling system driven by GTP/ATP chemical potential into cell-sized liposomes. This reconstitution of artificial proto-cells reveals how non-equilibrium phenomena affect cellular information processing in morphogenesis.

Biomolecular Basis of Cellular Consciousness via Subcellular Nanobrains

Cells emerged at the very beginning of life on Earth and, in fact, are coterminous with life. They are enclosed within an excitable plasma membrane, which defines the outside and inside domains via their specific biophysical properties. Unicellular organisms, such as diverse protists and algae, still live a cellular life. However, fungi, plants, and animals evolved a multicellular existence. Recently, we have developed the cellular basis of consciousness (CBC) model, which proposes that all biological awareness, sentience and consciousness are grounded in general cell biology. Here we discuss the biomolecular structures and processes that allow for and maintain this cellular consciousness from an evolutionary perspective.

Robustness and timing of cellular differentiation through population-based symmetry breaking

During mammalian development and homeostasis, cells often transition from a multilineage primed state to one of several differentiated cell types that are marked by the expression of mutually exclusive genetic markers. These observations have been classically explained by single-cell multistability as the dynamical basis of differentiation, where robust cell-type proportioning relies on pre-existing cell-to-cell differences. We propose a conceptually different dynamical mechanism in which cell types emerge and are maintained collectively by cell-cell communication as a novel inhomogeneous state of the coupled system. Differentiation can be triggered by cell number increase as the population grows in size, through organisation of the initial homogeneous population before the symmetry-breaking bifurcation point. Robust proportioning and reliable recovery of the differentiated cell types following a perturbation is an inherent feature of the inhomogeneous state that is collectively maintained. This dynamical mechanism is valid for systems with steady-state or oscillatory single-cell dynamics. Therefore, our results suggest that timing and subsequent differentiation in robust cell-type proportions can emerge from the cooperative behaviour of growing cell populations during development.

Reconsidering the evidence for learning in single cells

The question of whether single cells can learn led to much debate in the early 20th century. The view prevailed that they were capable of non-associative learning but not of associative learning, such as Pavlovian conditioning. Experiments indicating the contrary were considered either non-reproducible or subject to more acceptable interpretations. Recent developments suggest that the time is right to reconsider this consensus. We exhume the experiments of Beatrice Gelber on Pavlovian conditioning in the ciliate Paramecium aurelia, and suggest that criticisms of her findings can now be reinterpreted. Gelber was a remarkable scientist whose absence from the historical record testifies to the prevailing orthodoxy that single cells cannot learn. Her work, and more recent studies, suggest that such learning may be evolutionarily more widespread and fundamental to life than previously thought and we discuss the implications for different aspects of biology.

Single Cell Systems Analysis: Decision Geometry In Outliers

MOTIVATION

Anti-cancer therapeutics of the highest calibre currently focus on combinatorial targeting of specific oncoproteins and tumour suppressors. Clinical relapse depends upon intratumoral heterogeneity which serves as substrate variation during evolution of resistance to therapeutic regimens.

RESULTS

The present review advocates single cell systems biology as the optimal level of analysis for remediation of clinical relapse. Graph theory approaches to understanding decision-making in single cells may be abstracted one level further, to the geometry of decision-making in outlier cells, in order to define evolution-resistant cancer biomarkers. Systems biologists currently working with omics data are invited to consider phase portrait analysis as a mediator between graph theory and deep learning approaches. Perhaps counter-intuitively, the tangible clinical needs of cancer patients may depend upon the adoption of higher level mathematical abstractions of cancer biology.

SUPPLEMENTARY INFORMATION

supplementary data available at Bioinformatics online.

Processing Temporal Growth Factor Patterns by an Epidermal Growth Factor Receptor Network Dynamically Established in Space

The proto-oncogenic epidermal growth factor (EGF) receptor (EGFR) is a tyrosine kinase whose sensitivity and response to growth factor signals that vary over time and space determine cellular behavior within a developing tissue. The molecular reorganization of the receptors on the plasma membrane and the enzyme-kinetic mechanisms of phosphorylation are key determinants that couple growth factor binding to EGFR signaling. To enable signal initiation and termination while simultaneously accounting for suppression of aberrant signaling, a coordinated coupling of EGFR kinase and protein tyrosine phosphatase activity is established through space by vesicular dynamics. The dynamical operation mode of this network enables not only time-varying growth factor sensing but also adaptation of the response depending on cellular context. By connecting spatially coupled enzymatic kinase/phosphatase processes and the corresponding dynamical systems description of the EGFR network, we elaborate on the general principles necessary for processing complex growth factor signals.

Co-culture of hWJMSCs and pACs in double biomimetic ACECM oriented scaffold enhances mechanical properties and accelerates articular cartilage regeneration in a caprine model

Background

The dedifferentiation of chondrocytes and the unstable chondrogenic differentiation status of pluripotent mesenchymal stem cells (MSCs) are immense issues in cell-based articular cartilage repair and regenerative strategies. Here, to improve the cartilage characteristics of seed cells, a double biomimetic acellular cartilage extracellular matrix (ACECM)-oriented scaffold was used to mimic the cartilage microenvironment for human umbilical cord Wharton’s jelly-derived MSCs (hWJMSCs) and primary cartilage cells (pACs) to regenerate hyaline cartilage.

Methods

A double biomimetic ACECM-oriented scaffold was created from the cartilage extracellular matrix of pig articular cartilage using pulverization decellularization freeze-drying procedures. hWJMSCs and pACs were co-cultured at ratios of 50:50 (co-culture group, ACCC), 0:100 (ACAC group) and 100:0 (ACWJ group) in the ACECM-oriented scaffold, and the co-culture system was implanted in a caprine model for 6 months or 9 months to repair full-thickness articular cartilage defects. The control groups, which had no cells, comprised the blank control (BC) group and the ACECM-oriented scaffold (AC) group. Gross morphology and magnetic resonance imaging (MRI) as well as histological and biomechanical evaluations were used to characterize the cartilage of the repair area.

Results

Relative to the control groups, both the gross morphology and histological staining results demonstrated that the neotissue of the ACCC group was more similar to native cartilage and better integrated with the surrounding tissue. Measurements of glycosaminoglycan content and Young’s modulus showed that the repair areas had more abundant cartilage-specific content and significantly higher mechanical strength in the ACCC group than in the control groups, especially at 9 months. On MRI, the T2-weighted signal of the repair area was homogeneous, and the oedema signal disappeared almost completely in the ACCC group at 9 months. HLA-ABC immunofluorescence staining demonstrated that hWJMSCs participated in the repair and regeneration of articular cartilage and escaped surveillance and clearance by the caprine immune system.

Conclusion

The structure and components of double biomimetic ACECM-oriented scaffolds provided a cartilage-like microenvironment for co-cultured seed cells and enhanced the biomechanics and compositions of neotissue. This co-culture system has the potential to overcome the dedifferentiation of passage chondrocytes and the unstable chondrogenic differentiation status of MSCs.

Profiling Cell Signaling Networks at Single-cell Resolution

Signaling networks process intra- and extracellular information to modulate the functions of a cell. Deregulation of signaling networks results in abnormal cellular physiological states and often drives diseases. Network responses to a stimulus or a drug treatment can be highly heterogeneous across cells in a tissue because of many sources of cellular genetic and non-genetic variance. Signaling network heterogeneity is the key to many biological processes, such as cell differentiation and drug resistance. Only recently, the emergence of multiplexed single-cell measurement technologies has made it possible to evaluate this heterogeneity. In this review, we categorize currently established single-cell signaling network profiling approaches by their methodology, coverage, and application, and we discuss the advantages and limitations of each type of technology. We also describe the available computational tools for network characterization using single-cell data and discuss potential confounding factors that need to be considered in single-cell signaling network analyses.

Modeling somatic computation with non-neural bioelectric networks

The field of basal cognition seeks to understand how adaptive, context-specific behavior occurs in non-neural biological systems. Embryogenesis and regeneration require plasticity in many tissue types to achieve structural and functional goals in diverse circumstances. Thus, advances in both evolutionary cell biology and regenerative medicine require an understanding of how non-neural tissues could process information. Neurons evolved from ancient cell types that used bioelectric signaling to perform computation. However, it has not been shown whether or how non-neural bioelectric cell networks can support computation. We generalize connectionist methods to non-neural tissue architectures, showing that a minimal non-neural Bio-Electric Network (BEN) model that utilizes the general principles of bioelectricity (electrodiffusion and gating) can compute. We characterize BEN behaviors ranging from elementary logic gates to pattern detectors, using both fixed and transient inputs to recapitulate various biological scenarios. We characterize the mechanisms of such networks using dynamical-systems and information-theory tools, demonstrating that logic can manifest in bidirectional, continuous, and relatively slow bioelectrical systems, complementing conventional neural-centric architectures. Our results reveal a variety of non-neural decision-making processes as manifestations of general cellular biophysical mechanisms and suggest novel bioengineering approaches to construct functional tissues for regenerative medicine and synthetic biology as well as new machine learning architectures.

From non-excitable single-cell to multicellular bioelectrical states supported by ion channels and gap junction proteins: Electrical potentials as distributed controllers

Endogenous bioelectric patterns within tissues are an important driver of morphogenesis and a tractable component of a number of disease states. Developing system-level understanding of the dynamics by which non-neural bioelectric circuits regulate complex downstream cascades is a key step towards both, an evolutionary understanding of ion channel genes, and novel strategies in regenerative medicine. An important capability gap is deriving rational modulation strategies targeting individual cells' bioelectric states to achieve global (tissue- or organ-level) outcomes. Here, we develop an ion channel-based model that describes multicellular states on the basis of spatio-temporal patterns of electrical potentials in aggregates of non-excitable cells. The model is of biological interest because modern techniques allow to associate bioelectrical signals with specific ion channel proteins in the cell membrane that are central to embryogenesis, regeneration, and tumorigenesis. As a complementary approach to the usual biochemical description, we have studied four biophysical questions: (i) how can single-cell bioelectrical states be established; (ii) how can a change in the cell potential caused by a transient perturbation of the cell state be maintained after the stimulus is gone (bioelectrical memory); (iii) how can a single-cell contribute to the control of multicellular ensembles based on the spatio-temporal pattern of electrical potentials; and (iv) how can oscillatory patterns arise from the single-cell bioelectrical dynamics. Experimentally, endogenous bioelectric gradients have emerged as instructive agents for morphogenetic processes. In this context, the simulations can guide new procedures that may allow a distributed control of the multicellular ensemble.

The Cognitive Lens: a primer on conceptual tools for analysing information processing in developmental and regenerative morphogenesis

Brains exhibit plasticity, multi-scale integration of information, computation and memory, having evolved by specialization of non-neural cells that already possessed many of the same molecular components and functions. The emerging field of basal cognition provides many examples of decision-making throughout a wide range of non-neural systems. How can biological information processing across scales of size and complexity be quantitatively characterized and exploited in biomedical settings? We use pattern regulation as a context in which to introduce the Cognitive Lens-a strategy using well-established concepts from cognitive and computer science to complement mechanistic investigation in biology. To facilitate the assimilation and application of these approaches across biology, we review tools from various quantitative disciplines, including dynamical systems, information theory and least-action principles. We propose that these tools can be extended beyond neural settings to predict and control systems-level outcomes, and to understand biological patterning as a form of primitive cognition. We hypothesize that a cognitive-level information-processing view of the functions of living systems can complement reductive perspectives, improving efficient top-down control of organism-level outcomes. Exploration of the deep parallels across diverse quantitative paradigms will drive integrative advances in evolutionary biology, regenerative medicine, synthetic bioengineering, cognitive neuroscience and artificial intelligence. This article is part of the theme issue 'Liquid brains, solid brains: How distributed cognitive architectures process information'.

Modularity, criticality, and evolvability of a developmental gene regulatory network

The existence of discrete phenotypic traits suggests that the complex regulatory processes which produce them are functionally modular. These processes are usually represented by networks. Only modular networks can be partitioned into intelligible subcircuits able to evolve relatively independently. Traditionally, functional modularity is approximated by detection of modularity in network structure. However, the correlation between structure and function is loose. Many regulatory networks exhibit modular behaviour without structural modularity. Here we partition an experimentally tractable regulatory network—the gap gene system of dipteran insects—using an alternative approach. We show that this system, although not structurally modular, is composed of dynamical modules driving different aspects of whole-network behaviour. All these subcircuits share the same regulatory structure, but differ in components and sensitivity to regulatory interactions. Some subcircuits are in a state of criticality, while others are not, which explains the observed differential evolvability of the various expression features in the system.

Analysis of the Human Kinome and Phosphatome by Mass Cytometry Reveals Overexpression-Induced Effects on Cancer-Related Signaling

Kinase and phosphatase overexpression drives tumorigenesis and drug resistance. We previously developed a mass-cytometry-based single-cell proteomics approach that enables quantitative assessment of overexpression effects on cell signaling. Here, we applied this approach in a human kinome- and phosphatome-wide study to assess how 649 individually overexpressed proteins modulated cancer-related signaling in HEK293T cells in an abundance-dependent manner. Based on these data, we expanded the functional classification of human kinases and phosphatases and showed that the overexpression effects include non-catalytic roles. We detected 208 previously unreported signaling relationships. The signaling dynamics analysis indicated that the overexpression of ERK-specific phosphatases sustains proliferative signaling. This suggests a phosphatase-driven mechanism of cancer progression. Moreover, our analysis revealed a drug-resistant mechanism through which overexpression of tyrosine kinases, including SRC, FES, YES1, and BLK, induced MEK-independent ERK activation in melanoma A375 cells. These proteins could predict drug sensitivity to BRAF-MEK concurrent inhibition in cells carrying BRAF mutations.

Adhesion Stabilized en Masse Intracellular Electrical Recordings from Multicellular Assemblies

Coordinated collective electrochemical signals in multicellular assemblies, such as ion fluxes, membrane potentials, electrical gradients, and steady electric fields, play an important role in cell and tissue spatial organization during many physiological processes like wound healing, inflammatory responses, and hormone release. This mass of electric actions cumulates in an en masse activity within cell collectives which cannot be deduced from considerations at the individual cell level. However, continuously sampling en masse collective electrochemical actions of the global electrochemical activity of large-scale electrically coupled cellular assemblies with intracellular resolution over long time periods has been impeded by a lack of appropriate recording techniques. Here we present a bioelectrical interface consisting of low impedance vertical gold nanoelectrode interfaces able to penetrate the cellular membrane in the course of cellular adhesion, thereby allowing en masse recordings of intracellular electrochemical potentials that transverse electrically coupled NRK fibroblast, C2C12 myotube assemblies, and SH-SY5Y neuronal networks of more than 200,000 cells. We found that the intracellular electrical access of the nanoelectrodes correlates with substrate adhesion dynamics and that penetration, stabilization, and sealing of the electrode-cell interface involves recruitment of surrounding focal adhesion complexes and the anchoring of actin bundles, which form a caulking at the electrode base. Intracellular recordings were stable for several days, and monitoring of both basal activity as well as pharmacologically altered electric signals with high signal-to-noise ratios and excellent electrode coupling was performed.

Synchronization of Bioelectric Oscillations in Networks of Nonexcitable Cells: From Single-Cell to Multicellular States

Biological networks use collective oscillations for information processing tasks. In particular, oscillatory membrane potentials have been observed in nonexcitable cells and bacterial communities where specific ion channel proteins contribute to the bioelectric coordination of large populations. We aim at describing theoretically the oscillatory spatiotemporal patterns that emerge at the multicellular level from the single-cell bioelectric dynamics. To this end, we focus on two key questions: (i) What single-cell properties are relevant to multicellular behavior? (ii) What properties defined at the multicellular level can allow an external control of the bioelectric dynamics? In particular, we explore the interplay between transcriptional and translational dynamics and membrane potential dynamics in a model multicellular ensemble, describe the spatiotemporal patterns that arise when the average electric potential allows groups of cells to act as a coordinated multicellular patch, and characterize the resulting synchronization phenomena. The simulations concern bioelectric networks and collective communication across different scales based on oscillatory and synchronization phenomena, thus shedding light on the physiological dynamics of a wide range of endogenous contexts across embryogenesis and regeneration.

Integrated Information as a Measure of Cognitive Processes in Coupled Genetic Repressilators

Intercellular communication and its coordination allow cells to exhibit multistability as a form of adaptation. This conveys information processing from intracellular signaling networks enabling self-organization between other cells, typically involving mechanisms associated with cognitive systems. How information is integrated in a functional manner and its relationship with the different cell fates is still unclear. In parallel, drawn originally from studies on neuroscience, integrated information proposes an approach to quantify the balance between integration and differentiation in the causal dynamics among the elements in any interacting system. In this work, such an approach is considered to study the dynamical complexity in a genetic network of repressilators coupled by quorum sensing. Several attractors under different conditions are identified and related to proposed measures of integrated information to have an insight into the collective interaction and functional differentiation in cells. This research particularly accounts for the open question about the coding and information transmission in genetic systems.

Reappraising the exteriorization of the mammalian testes through evolutionary physiology

A number of theories have been proposed to explain the exteriorization of the testicles in most mammalian species. None of these provide a consistent account for the wide variety of testicular locations found across the animal kingdom. It is proposed that testicular location is the result of coordinate action of testicular tissue ecologies to sustain preferential states of homeostatic equipoise throughout evolutionary development in response to the advent of endothermy.

Biofunctionalized Materials Featuring Feedforward and Feedback Circuits Exemplified by the Detection of Botulinum Toxin A

Feedforward and feedback loops are key regulatory elements in cellular signaling and information processing. Synthetic biology exploits these elements for the design of molecular circuits that enable the reprogramming and control of specific cellular functions. These circuits serve as a basis for the engineering of complex cellular networks, opening the door for numerous medical and biotechnological applications. Here, a similar principle is applied. Feedforward and positive feedback circuits are incorporated into biohybrid polymer materials in order to develop signal-sensing and signal-processing devices. This concept is exemplified by the detection of the proteolytic activity of the botulinum neurotoxin A. To this aim, site-specific proteases are incorporated into receiver, transmitter, and output materials, and their release, diffusion, and/or activation are wired according to a feedforward or a positive feedback circuit. The development of a quantitative mathematical model enables analysis and comparison of the performance of both systems. The flexible design could be easily adapted to detect other toxins or molecules of interest. Furthermore, cellular signaling or gene regulatory pathways could provide additional blueprints for the development of novel biohybrid circuits. Such information-processing, material-embedded biological circuits hold great promise for a variety of analytical, medical, or biotechnological applications.

Coculture of hWJMSCs and pACs in Oriented Scaffold Enhances Hyaline Cartilage Regeneration In Vitro

Seed cells of articular cartilage tissue engineering face many obstacles in their application because of the dedifferentiation of chondrocytes or unstable chondrogenic differentiation status of pluripotent stem cells. To overcome mentioned dilemmas, a simulation of the articular cartilage microenvironment was constructed by primary articular cartilage cells (pACs) and acellular cartilage extracellular matrix- (ACECM-) oriented scaffold cocultured with human umbilical cord Wharton's jelly-derived mesenchymal stem cells (hWJMSCs) in vitro. The coculture groups showed more affluent cartilage special matrix ingredients including collagen II and aggrecan based on the results of histological staining and western blotting and cut down as many pACs as possible. The RT-PCR and cell viability experiments also demonstrated that hWJMSCs were successfully induced to differentiate into chondrocytes when cultured in the simulated cartilage microenvironment, as confirmed by the significant upregulation of collagen II and aggrecan, while the cell proliferation activity of pACs was significantly improved by cell-cell interactions. Therefore, compared with monoculture and chondrogenic induction of inducers, coculture providing a simulated native articular microenvironment was a potential and temperate way to regulate the biological behaviors of pACs and hWJMSCs to regenerate the hyaline articular cartilage.

Sentience and Consciousness in Single Cells: How the First Minds Emerged in Unicellular Species

A reductionistic, bottom-up, cellular-based concept of the origins of sentience and consciousness has been put forward. Because all life is based on cells, any evolutionary theory of the emergence of sentience and consciousness must be grounded in mechanisms that take place in prokaryotes, the simplest unicellular species. It has been posited that subjective awareness is a fundamental property of cellular life. It emerges as an inherent feature of, and contemporaneously with, the very first life-forms. All other varieties of mentation are the result of evolutionary mechanisms based on this singular event. Therefore, all forms of sentience and consciousness evolve from this original instantiation in prokaryotes. It has also been identified that three cellular structures and mechanisms that likely play critical roles here are excitable membranes, oscillating cytoskeletal polymers, and structurally flexible proteins. Finally, basic biophysical principles are proposed to guide those processes that underly the emergence of supracellular sentience from cellular sentience in multicellular organisms.

Quantification of protein mobility and associated reshuffling of cytoplasm during chemical fixation

To understand cellular functionalities, it is essential to unravel spatio-temporal patterns of molecular distributions and interactions within living cells. The technological progress in fluorescence microscopy now allows in principle to measure these patterns with sufficient spatial resolution. However, high resolution imaging comes with long acquisition times and high phototoxicity. Therefore, physiological live cell imaging is often unfeasible and chemical fixation is employed. Yet, fixation methods have not been rigorously investigated, in terms of pattern preservation, at the resolution at which cells can now be imaged. A key parameter for this is the time required until fixation is complete. During this time, cells are under unphysiological conditions and patterns decay. We demonstrate here that formaldehyde fixation takes more than one hour for cytosolic proteins in cultured cells. Other small aldehydes, glyoxal and acrolein, did not perform better. Associated with this, we found a distinct displacement of proteins and lipids, including their loss from cells. Fixations using glutaraldehyde were faster than four minutes and retained most cytoplasmic proteins. Surprisingly, autofluorescence produced by glutaraldehyde was almost completely absent with supplementary addition of formaldehyde without compromising fixation speed. These findings indicate, which cellular processes can actually be reliably imaged after a certain chemical fixation.

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.

Interdependence between EGFR and Phosphatases Spatially Established by Vesicular Dynamics Generates a Growth Factor Sensing and Responding Network

The proto-oncogenic epidermal growth factor receptor (EGFR) is a tyrosine kinase whose sensitivity to growth factors and signal duration determines cellular behavior. We resolve how EGFR's response to epidermal growth factor (EGF) originates from dynamically established recursive interactions with spatially organized protein tyrosine phosphatases (PTPs). Reciprocal genetic PTP perturbations enabled identification of receptor-like PTPRG/J at the plasma membrane and ER-associated PTPN2 as the major EGFR dephosphorylating activities. Imaging spatial-temporal PTP reactivity revealed that vesicular trafficking establishes a spatially distributed negative feedback with PTPN2 that determines signal duration. On the other hand, single-cell dose-response analysis uncovered a reactive oxygen species-mediated toggle switch between autocatalytically activated monomeric EGFR and the tumor suppressor PTPRG that governs EGFR's sensitivity to EGF. Vesicular recycling of monomeric EGFR unifies the interactions with these PTPs on distinct membrane systems, dynamically generating a network architecture that can sense and respond to time-varying growth factor signals.

MaxSynBio: Avenues Towards Creating Cells from the Bottom Up

A large German research consortium mainly within the Max Planck Society ("MaxSynBio") was formed to investigate living systems from a fundamental perspective. The research program of MaxSynBio relies solely on the bottom-up approach to synthetic biology. MaxSynBio focuses on the detailed analysis and understanding of essential processes of life through modular reconstitution in minimal synthetic systems. The ultimate goal is to construct a basic living unit entirely from non-living components. The fundamental insights gained from the activities in MaxSynBio could eventually be utilized for establishing a new generation of biotechnological processes, which would be based on synthetic cell constructs that replace the natural cells currently used in conventional biotechnology.

Senomic view of the cell: Senome versus Genome

In the legacy of Thomas Henry Huxley, and his 'epigenetic' philosophy of biology, cells are proposed to represent a trinity of three memory-storing media: Senome, Epigenome, and Genome that together comprise a cell-wide informational architecture. Our current preferential focus on the Genome needs to be complemented by a similar focus on the Epigenome and a here proposed Senome, representing the sum of all the sensory experiences of the cognitive cell and its sensing apparatus. Only then will biology be in a position to embrace the whole complexity of the eukaryotic cell, understanding its true nature which allows the communicative assembly of cells in the form of sentient multicellular organisms.

How Organisms Gained Causal Independence and How It Might Be Quantified

Two broad features are jointly necessary for autonomous agency: organisational closure and the embodiment of an objective-function providing a ‘goal’: so far only organisms demonstrate both. Organisational closure has been studied (mostly in abstract), especially as cell autopoiesis and the cybernetic principles of autonomy, but the role of an internalised ‘goal’ and how it is instantiated by cell signalling and the functioning of nervous systems has received less attention. Here I add some biological ‘flesh’ to the cybernetic theory and trace the evolutionary development of step-changes in autonomy: (1) homeostasis of organisationally closed systems; (2) perception-action systems; (3) action selection systems; (4) cognitive systems; (5) memory supporting a self-model able to anticipate and evaluate actions and consequences. Each stage is characterised by the number of nested goal-directed control-loops embodied by the organism, summarised as will-nestedness N. Organism tegument, receptor/transducer system, mechanisms of cellular and whole-organism re-programming and organisational integration, all contribute to causal independence.

CONCLUSION

organisms are cybernetic phenomena whose identity is created by the information structure of the highest level of causal closure (maximum N), which has increased through evolution, leading to increased causal independence, which might be quantifiable by ‘Integrated Information Theory’ measures.

Label-Free Optofluidic Nanobiosensor Enables Real-Time Analysis of Single-Cell Cytokine Secretion

Single-cell analysis of cytokine secretion is essential to understand the heterogeneity of cellular functionalities and develop novel therapies for multiple diseases. Unraveling the dynamic secretion process at single-cell resolution reveals the real-time functional status of individual cells. Fluorescent and colorimetric-based methodologies require tedious molecular labeling that brings inevitable interferences with cell integrity and compromises the temporal resolution. An innovative label-free optofluidic nanoplasmonic biosensor is introduced for single-cell analysis in real time. The nanobiosensor incorporates a novel design of a multifunctional microfluidic system with small volume microchamber and regulation channels for reliable monitoring of cytokine secretion from individual cells for hours. Different interleukin-2 secretion profiles are detected and distinguished from single lymphoma cells. The sensor configuration combined with optical spectroscopic imaging further allows us to determine the spatial single-cell secretion fingerprints in real time. This new biosensor system is anticipated to be a powerful tool to characterize single-cell signaling for basic and clinical research.

Making lineage decisions with biological noise: Lessons from the early mouse embryo

Understanding how individual cells make fate decisions that lead to the faithful formation and homeostatic maintenance of tissues is a fundamental goal of contemporary developmental and stem cell biology. Seemingly uniform populations of stem cells and multipotent progenitors display a surprising degree of heterogeneity, primarily originating from the inherent stochastic nature of molecular processes underlying gene expression. Despite this heterogeneity, lineage decisions result in tissues of a defined size and with consistent proportions of differentiated cell types. Using the early mouse embryo as a model we review recent developments that have allowed the quantification of molecular intercellular heterogeneity during cell differentiation. We first discuss the relationship between these heterogeneities and developmental cellular potential. We then review recent theoretical approaches that formalize the mechanisms underlying fate decisions in the inner cell mass of the blastocyst stage embryo. These models build on our extensive knowledge of the genetic control of fate decisions in this system and will become essential tools for a rigorous understanding of the connection between noisy molecular processes and reproducible outcomes at the multicellular level. We conclude by suggesting that cell-to-cell communication provides a mechanism to exploit and buffer intercellular variability in a self-organized process that culminates in the reproducible formation of the mature mammalian blastocyst stage embryo that is ready for implantation into the maternal uterus. This article is categorized under: Gene Expression and Transcriptional Hierarchies > Cellular Differentiation Establishment of Spatial and Temporal Patterns > Regulation of Size, Proportion, and Timing Gene Expression and Transcriptional Hierarchies > Gene Networks and Genomics Gene Expression and Transcriptional Hierarchies > Quantitative Methods and Models.

Four domains: The fundamental unicell and Post-Darwinian Cognition-Based Evolution

Contemporary research supports the viewpoint that self-referential cognition is the proper definition of life. From that initiating platform, a cohesive alternative evolutionary narrative distinct from standard Neodarwinism can be presented. Cognition-Based Evolution contends that biological variation is a product of a self-reinforcing information cycle that derives from self-referential attachment to biological information space-time with its attendant ambiguities. That information cycle is embodied through obligatory linkages among energy, biological information, and communication. Successive reiterations of the information cycle enact the informational architectures of the basic unicellular forms. From that base, inter-domain and cell-cell communications enable genetic and cellular variations through self-referential natural informational engineering and cellular niche construction. Holobionts are the exclusive endpoints of that self-referential cellular engineering as obligatory multicellular combinations of the essential Four Domains: Prokaryota, Archaea, Eukaryota and the Virome. Therefore, it is advocated that these Four Domains represent the perpetual object of the living circumstance rather than the visible macroorganic forms. In consequence, biology and its evolutionary development can be appraised as the continual defense of instantiated cellular self-reference. As the survival of cells is as dependent upon limitations and boundaries as upon any freedom of action, it is proposed that selection represents only one of many forms of cellular constraint that sustain self-referential integrity.

Investigation of Cytotoxic Activity of Mitoxantrone at the Individual Cell Level by Using Ionic-Liquid-Tag-Enhanced Mass Spectrometry

A novel mitoxantrone conjugate was synthesized by coupling mitoxantrone with ionic liquid tags, and cytotoxic behavior of the designed conjugate was studied in normal and cancer cell lines. The synthesized mitoxantrone conjugate was oil at physiological temperatures and demonstrated high aqueous solubility. Sensitivity of electrospray ionization mass spectrometry (ESI-MS) to the mitoxantrone conjugate was improved by an order of magnitude, in comparison with original mitoxantrone dihydrochloride. The observed ESI-MS signals were shifted to a "clearer" lower-mass region of the spectrum, which allowed investigation of the drug at the level of individual cells. The ionic liquid tags proposed in the present work consist of an easily available imidazolium salt residue and show a number of key advantages from the points of view of drug conjugate synthesis, drug delivery and analytic detection.