Self-organization: the fundament of cell biology

Two-Terminal Neuromorphic Devices for Spiking Neural Networks: Neurons, Synapses, and Array Integration

The ever-increasing volume of complex data poses significant challenges to conventional sequential global processing methods, highlighting their inherent limitations. This computational burden has catalyzed interest in neuromorphic computing, particularly within artificial neural networks (ANNs). In pursuit of advancing neuromorphic hardware, researchers are focusing on developing computation strategies and constructing high-density crossbar arrays utilizing history-dependent, multistate nonvolatile memories tailored for multiply-accumulate (MAC) operations. However, the real-time collection and processing of massive, dynamic data sets require an innovative computational paradigm akin to that of the human brain. Spiking neural networks (SNNs), representing the third generation of ANNs, are emerging as a promising solution for real-time spatiotemporal information processing due to their event-based spatiotemporal capabilities. The ideal hardware supporting SNN operations comprises artificial neurons, artificial synapses, and their integrated arrays. Currently, the structural complexity of SNNs and spike-based methodologies requires hardware components with biomimetic behaviors that are distinct from those of conventional memristors used in deep neural networks. These distinctive characteristics required for neuron and synapses devices pose significant challenges. Developing effective building blocks for SNNs, therefore, necessitates leveraging the intrinsic properties of the materials constituting each unit and overcoming the integration barriers. This review focuses on the progress toward memristor-based spiking neural network neuromorphic hardware, emphasizing the role of individual components such as memristor-based neurons, synapses, and array integration along with relevant biological insights. We aim to provide valuable perspectives to researchers working on the next generation of brain-like computing systems based on these foundational elements.

Law and Order of Colloidal Tectonics: From Molecules to Self-Assembled Colloids

Since biochemists and biologists have progressed in understanding the mechanisms involved in living organisms, biological systems have become a source of inspiration for chemists. In this context, the concept of colloidal tectonics, describing the spontaneous formation of colloidal particles or supracolloidal structures in which the building blocks are called "tectons", has emerged. Therefore, a bottom-up edification of tectons towards (supra) colloidal structures is allowed. Each (supra) colloidal system has at least one of the following properties: amphiphilicity, predictability, versatility, commutability, and reversibility. However, for these systems to perform even more interesting functions, it is necessary for tectons to have very precise chemical and physical properties so that new properties emerge in (supra) colloidal systems. In this way, colloidal tectonics enables engineering at the nano- and micrometric level and contributes to the development of smart bioinspired systems with applications in catalysis, drug delivery, etc. In this review, an overview of the concept of colloidal tectonics is illustrated by some biotic systems. The design of abiotic (supra) colloidal systems and their applications in various fields are also addressed (notably Pickering emulsions for catalysis or drug delivery). Finally, theoretical directions for the design of novel self-assembled (supra) colloidal systems are discussed.

Creative processes during vertebrate organ morphogenesis: Biophysical self-organization at the supracellular scale

Here, we review recent developments in the literature that provide insight into self-organization at supracellular scales in vertebrate organ morphogenesis. We briefly present a historical and conceptual analysis of the term "self-organization." Based on this analysis, we suggest that self-organizing processes, at their root, possess a form of causal relationship, reciprocal causality, that is markedly distinct from linear causal chains. We survey the extent to which reciprocal causality can be used to interpret or clarify supracellular studies in development and disease. Finally, we explore how reciprocal causality can exist across length-scales, identifying situations where multiple scales require simultaneous analysis.

Reflections upon a new definition of life

What is life? Multiple definitions have been proposed to answer this question, but unfortunately, none of them has reached the consensus of the scientific community. Here, the strategy used to define what life is was based on first establishing which characteristics are common to all living systems (organic nature, entropy-producing system, self-organizing, reworkable pre-program, capacity to interact and adapt, reproduction and evolution) and from them constructing the definition taking into account that reproduction and evolution are not essential for life. On this basis, life is defined as an interactive process occurring in entropy-producing, adaptive, and informative (organic) systems. An unforeseen consequence of the inseparable duality between the system (living being) and the process (life) is the interchangeability of the elements of the definition to obtain other equally valid alternatives. In addition, in the light of this definition, cases of temporarily lifeless living systems (viruses, dormant seeds, and ultracold cells) are analyzed, as well as the status of artificial life entities and the hypothetical nature of extraterrestrial life. All living systems are perishable because the passage of time leads to increasing entropy. Life must create order by continuously producing disorder and exporting it to the environment and so we move and stay in the phase transition between order and chaos, far from equilibrium, thanks to the input of energy from the outside. However, the passage of time eventually leads us to an end in which life disappears and entropy increases.

Is immunology doing well? A look at 100 immune-mediated inflammatory diseases for 100 years of the Journal

It is now 60 years since Ian Mackay and Macfarlane Burnet published their seminal text "The Autoimmune Diseases" in which they examined the full scope of human inflammatory pathology as a manifestation of the underlying structure and function of the immune system. Here I revisit this approach to ask to what extent has the promise of Mackay and Burnet's work been exploited in clinical medicine as currently practiced. In other words, is immunology doing well? Despite spectacular headline contributions of immunology in clinical medicine, I present evidence suggesting a performance ceiling in our capacity to answer the relatively straightforward questions that patients frequently ask about their own diseases and find that this ceiling exists across almost all of the 100 immune-mediated inflammatory diseases examined. I propose that these questions are difficult, not so much because the immune system is overwhelmingly complex but rather that we have more to learn about the relatively simple agents and rules that may underpin self-organizing complex interacting systems as revealed in studies from other disciplines. The way that the immune system has evolved to exploit the ancient machinery determining three independent cell fate timers as described in this Journal would be a great place to start to decode the self-organizing principles that underpin the emergent pathology that we observe in the clinic.

Automatic detection of spatio-temporal signaling patterns in cell collectives

Increasing experimental evidence points to the physiological importance of space-time correlations in signaling of cell collectives. From wound healing to epithelial homeostasis to morphogenesis, coordinated activation of biomolecules between cells allows the collectives to perform more complex tasks and to better tackle environmental challenges. To capture this information exchange and to advance new theories of emergent phenomena, we created ARCOS, a computational method to detect and quantify collective signaling. We demonstrate ARCOS on cell and organism collectives with space-time correlations on different scales in 2D and 3D. We made a new observation that oncogenic mutations in the MAPK/ERK and PIK3CA/Akt pathways of MCF10A epithelial cells hyperstimulate intercellular ERK activity waves that are largely dependent on matrix metalloproteinase intercellular signaling. ARCOS is open-source and available as R and Python packages. It also includes a plugin for the napari image viewer to interactively quantify collective phenomena without prior programming experience.

Engineering metabolic cycle-inspired hydrogels with enzyme-fueled programmable transient volume changes

An enzyme-fueled transient volume phase transition (TVPT) of hydrogels under out-of-equilibrium conditions is reported. The approach takes inspiration from the metabolic cycle, comprising nutrient intake and anabolism/catabolism followed by waste excretion. The incorporation of methacrylic acid and acrylated trypsin in a polymeric hydrogel allowed the TVPT of the gel to be fueled by lysozyme. With the intake of lysozyme as fuel, the construction/destruction of electrostatic cross-linkages induced transient shrinkage/swelling of the gel accompanied by the depletion of lysozyme activity. The system's transient response could be flexibly programmed by adjusting not only the fuel concentration but the chemical composition of materials. The lysozyme-fueled TVPT of the gel could be exploited to transient changes in the mechanical properties of the gel. Our work opens a route toward a new class of stimuli-responsive hydrogels for biomedical applications.

Biological evolution requires an emergent, self-organizing principle

In this perspective review, we assess fundamental flaws in Darwinian evolution, including its modern versions. Fixed mutations 'explain' microevolution but not macroevolution including speciation events and the origination of all the major body plans of the Cambrian explosion. Complex, multifactorial change is required for speciation events and inevitably requires self-organization beyond what is accomplished by known mechanisms. The assembly of ribosomes and ATP synthase are specific examples. We propose their origin is a model for what is unexplained in biological evolution. Probability of evolution is modeled in Section 9 and values are absurdly improbable. Speciation and higher taxonomic changes become exponentially less probable as the number of required, genetically-based events increase. Also, the power required of the proposed selection mechanism (survival of the fittest) is nil for any biological advance requiring multiple changes, because they regularly occur in multiple generations (different genomes) and would not be selectively conserved by the concept survival of the fittest (a concept ultimately centered on the individual). Thus, survival of the fittest cannot 'explain' the origin of the millions of current and extinct species. We also focus on the inadequacies of laboratory chemistry to explain the complex, required biological self-organization seen in cells. We propose that a 'bioelectromagnetic' field/principle emerges in living cells. Synthesis by self-organization of massive molecular complexes involves biochemical responses to this emergent field/principle. There are ramifications for philosophy, science, and religion. Physics and mathematics must be more strongly integrated with biology and integration should receive dedicated funding with special emphasis for medical applications; treatment of cancer and genetic diseases are examples.

A revised central dogma for the 21st century:all biology is cognitive information processing

Crick's Central Dogma has been a foundational aspect of 20th century biology, describing an implicit relationship governing the flow of information in biological systems in biomolecular terms. Accumulating scientific discoveries support the need for a revised Central Dogma to buttress evolutionary biology's still-fledgling migration from a Neodarwinian canon. A reformulated Central Dogma to meet contemporary biology is proposed: all biology is cognitive information processing. Central to this contention is the recognition that life is the self-referential state, instantiated within the cellular form. Self-referential cells act to sustain themselves and to do so, cells must be in consistent harmony with their environment. That consonance is achieved by the continuous assimilation of environmental cues and stresses as information to self-referential observers. All received cellular information must be analyzed to be deployed as cellular problem-solving to maintain homeorhetic equipoise. However, the effective implementation of information is definitively a function of orderly information management. Consequently, effective cellular problem-solving is information processing and management. The epicenter of that cellular information processing is its self-referential internal measurement. All further biological self-organization initiates from this obligate activity. As the internal measurement by cells of information is self-referential by definition, self-reference is biological self-organization, underpinning 21st century Cognition-Based Biology.

First Organoid Intelligence (OI) workshop to form an OI community

The brain is arguably the most powerful computation system known. It is extremely efficient in processing large amounts of information and can discern signals from noise, adapt, and filter faulty information all while running on only 20 watts of power. The human brain's processing efficiency, progressive learning, and plasticity are unmatched by any computer system. Recent advances in stem cell technology have elevated the field of cell culture to higher levels of complexity, such as the development of three-dimensional (3D) brain organoids that recapitulate human brain functionality better than traditional monolayer cell systems. Organoid Intelligence (OI) aims to harness the innate biological capabilities of brain organoids for biocomputing and synthetic intelligence by interfacing them with computer technology. With the latest strides in stem cell technology, bioengineering, and machine learning, we can explore the ability of brain organoids to compute, and store given information (input), execute a task (output), and study how this affects the structural and functional connections in the organoids themselves. Furthermore, understanding how learning generates and changes patterns of connectivity in organoids can shed light on the early stages of cognition in the human brain. Investigating and understanding these concepts is an enormous, multidisciplinary endeavor that necessitates the engagement of both the scientific community and the public. Thus, on Feb 22-24 of 2022, the Johns Hopkins University held the first Organoid Intelligence Workshop to form an OI Community and to lay out the groundwork for the establishment of OI as a new scientific discipline. The potential of OI to revolutionize computing, neurological research, and drug development was discussed, along with a vision and roadmap for its development over the coming decade.

Complexity and self-organization in the evolution of cell polarization

Cellular life exhibits order and complexity, which typically increase over the course of evolution. Cell polarization is a well-studied example of an ordering process that breaks the internal symmetry of a cell by establishing a preferential axis. Like many cellular processes, polarization is driven by self-organization, meaning that the macroscopic pattern emerges as a consequence of microscopic molecular interactions at the biophysical level. However, the role of self-organization in the evolution of complex protein networks remains obscure. In this Review, we provide an overview of the evolution of polarization as a self-organizing process, focusing on the model species Saccharomyces cerevisiae and its fungal relatives. Moreover, we use this model system to discuss how self-organization might relate to evolutionary change, offering a shift in perspective on evolution at the microscopic scale.

Cellular self-organization: An overdrive in Cambrian diversity?

During the early Cambrian period metazoan life forms diverged at an accelerated rate to occupy multiple ecological niches on earth. A variety of explanations have been proposed to address this major evolutionary phenomenon termed the "Cambrian explosion." While most hypotheses address environmental, developmental, and ecological factors that facilitated evolutionary innovations, the biological basis for accelerated emergence of species diversity in the Cambrian period remains largely conjectural. Herein, we posit that morphogenesis by self-organization enables the uncoupling of genomic mutational landscape from phenotypic diversification. Evidence is provided for a two-tiered interpretation of genomic changes in metazoan animals wherein mutations not only impact upon function of individual cells, but also alter the self-organization outcome during developmental morphogenesis. We provide evidence that the morphological impacts of mutations on self-organization could remain repressed if associated with an unmet negative energetic cost. We posit that accelerated morphological diversification in transition to the Cambrian period has occurred by emergence of dormant (i.e., reserved) morphological novelties whose molecular underpinnings were seeded in the Precambrian period.

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.

Dynamic self-organization of migrating cells under constraints by spatial confinement and epithelial integrity

Understanding how migrating cells can establish both dynamic structures and coherent dynamics may provide mechanistic insights to study how living systems acquire complex structures and functions. Recent studies revealed that intercellular contact communication plays a crucial role for establishing cellular dynamic self-organization (DSO) and provided a theoretical model of DSO for migrating solitary cells in a free space. However, to apply those understanding to situations in living organisms, we need to know the role of cell-cell communication for tissue dynamics under spatial confinements and epithelial integrity. Here, we expand the previous numerical studies on DSO to migrating cells subjected spatial confinement and/or epithelial integrity. An epithelial monolayer is simulated by combining the model of cellular DSO and the cellular vertex model in two dimensions for apical integrity. Under confinement to a small space, theoretical models of both solitary and epithelial cells exhibit characteristic coherent dynamics, including apparent swirling. We also find that such coherent dynamics can allow the cells to overcome the strong constraint due to spatial confinement and epithelial integrity. Furthermore, we demonstrate how epithelial cell clusters behave without spatial confinement and find various cluster dynamics, including spinning, migration and elongation.

Progressive Local Accumulation of Self-Assembled Nanoreactors in a Hydrogel Matrix through Repetitive Injections of ATP

Cellular functions are regulated with high spatial control through the local activation of chemical processes in a complex inhomogeneous matrix. The development of synthetic macroscopic systems with a similar capacity allows fundamental studies aimed at understanding the relationship between local molecular events and the emergence of functional properties at the macroscopic level. Here, we show that a kinetically stable inhomogeneous hydrogel matrix is spontaneously formed upon the local injection of ATP. Locally, ATP templates the self-assembly of amphiphiles into large nanoreactors with a much lower diffusion rate compared to unassembled amphiphiles. The local depletion of unassembled amphiphiles near the injection point installs a concentration gradient along which unassembled amphiphiles diffuse from the surroundings to the center. This allows for a progressive local accumulation of self-assembled nanoreactors in the matrix upon repetitive cycles of ATP injection separated by time intervals during which diffusion of unassembled amphiphiles takes place. Contrary to the homogeneous matrix containing the same components, in the inhomogeneous matrix the local upregulation of a chemical reaction occurs. Depending on the way the same amount of injected ATP is administered to the hydrogel matrix different macroscopic distributions of nanoreactors are obtained, which affect the location in the matrix where the chemical reaction is upregulated.

Melt electro-written scaffolds with box-architecture support orthogonally oriented collagen

Melt electro-writing (MEW) is a state-of-the-art technique that supports fabrication of 3D, precisely controlled and reproducible fiber structures. A standard MEW scaffold design is a box-structure, where a repeat layer of 90° boxes is produced from a single fiber. In 3D form (i.e. multiple layers), this structure has the potential to mimic orthogonal arrangements of collagen, as observed in the corneal stroma. In this study, we determined the response of human primary corneal stromal cells and their deposited fibrillar collagen (detected using a CNA35 probe) following six weeksin vitroculture on these box-structures made from poly(ϵ-caprolactone) (PCL). Comparison was also made to glass substrates (topography-free) and electrospun PCL fibers (aligned topography). Cell orientation and collagen deposition were non-uniform on glass substrates. Electrospun scaffolds supported an excellent parallel arrangement of cells and deposited collagen to the underlying architecture of aligned fibers, but there was no evidence of bidirectional collagen. In contrast, MEW scaffolds encouraged the formation of a dense, interconnected cellular network and deposited fibrillar collagen layers with a distinct orthogonal-arrangement. Collagen fibrils were particularly dominant through the middle layers of the MEW scaffolds' total thickness and closer examination revealed these fibrils to be concentrated within the pores' central regions. With the demand for donor corneas far exceeding the supply-leaving many with visual impairment-the application of MEW as a potential technique to recreate the corneal stroma with spontaneous, bidirectional collagen organization warrants further study.

Forward and feedback control mechanisms of developmental tissue growth

The size and proportions of animals are tightly controlled during development. How this is achieved remains poorly understood. The control of organ size entails coupling of cellular growth and cell division on one hand, and the measure of organ size on the other. In this review we focus on three layers of growth control consisting of genetic patterning, notably chemical gradients, mechanics and energetics which are complemented by a systemic control unit that modulates growth in response to the nutritional conditions and coordinates growth between different organs so as to maintain proportions. Growth factors, often present as concentration dependent chemical gradients, are positive inducers of cellular growth that may be considered as deterministic cues, hence acting as organ-intrinsic controllers of growth. However, the exponential growth dynamics in many developing tissues necessitate more stringent growth control in the form of negative feedbacks. Feedbacks endow biological systems with the capacity to quickly respond to perturbations and to correct the growth trajectory to avoid overgrowth. We propose to integrate chemical, mechanical and energetic control over cellular growth in a framework that emphasizes the self-organizing properties of organ-autonomous growth control in conjunction with systemic organ non-autonomous feedback on growth.

From Oncological Paradigms to Non-Communicable Disease Pandemic. The Need of Recovery Human Biology Evolution

The paradigm of the Somatic Mutation Theory (SMT) is failing, and a new paradigm is underway but not yet established. What is being challenged is a conceptual approach that involves the entire human biology and the development of chronic diseases. The behavior of breast and other solid cancers is compatible with the concept that the primary tumor is able to control its microscopic metastases, in the same way that an organ (e.g., the liver) is able to control its physiological size. This finding suggested that cancer and its metastases may behave as an organoid. The new paradigm under construction considers the origin of tumors as a disturbance in the communication network between tissue cell populations and between cells and extracellular matrix, and supports a systemic approach to the study of both healthy and pathologic tissues. The commentary provides a rationale for the role of physical exercise in the control of tumor dormancy according to a human evolutionary perspective.

Chemically Fueled Self-Assembly in Biology and Chemistry

Life is a non-equilibrium state of matter maintained at the expense of energy. Nature uses predominantly chemical energy stored in thermodynamically activated, but kinetically stable, molecules. These high-energy molecules are exploited for the synthesis of other biomolecules, for the activation of biological machinery such as pumps and motors, and for the maintenance of structural order. Knowledge of how chemical energy is transferred to biochemical processes is essential for the development of artificial systems with life-like processes. Here, we discuss how chemical energy can be used to control the structural organization of organic molecules. Four different strategies have been identified according to a distinguishable physical-organic basis. For each class, one example from biology and one from chemistry are discussed in detail to illustrate the practical implementation of each concept and the distinct opportunities they offer. Specific attention is paid to the discussion of chemically fueled non-equilibrium self-assembly. We discuss the meaning of non-equilibrium self-assembly, its kinetic origin, and strategies to develop synthetic non-equilibrium systems.

Going your own way: Self-guidance mechanisms in cell migration

How cells and tissues migrate from one location to another is a question of significant biological and medical relevance. Migration is generally thought to be controlled by external hardwired guidance cues, which cells follow by polarizing their internal locomotory machinery in the imposed direction. However, a number of recently discovered 'self-guidance' mechanisms have revealed that migrating cells have more control over the path they follow than previously thought. Here, directional information is generated by the migrating cells themselves via a dynamic interplay of cell-intrinsic and -extrinsic regulators. In this review, we discuss how self-guidance can emerge from mechanisms acting at different levels of scale and how these enable cells to rapidly adapt to environmental challenges.

F-Actin Cytoskeleton Network Self-Organization Through Competition and Cooperation

Many fundamental cellular processes such as division, polarization, endocytosis, and motility require the assembly, maintenance, and disassembly of filamentous actin (F-actin) networks at specific locations and times within the cell. The particular function of each network is governed by F-actin organization, size, and density as well as by its dynamics. The distinct characteristics of different F-actin networks are determined through the coordinated actions of specific sets of actin-binding proteins (ABPs). Furthermore, a cell typically assembles and uses multiple F-actin networks simultaneously within a common cytoplasm, so these networks must self-organize from a common pool of shared globular actin (G-actin) monomers and overlapping sets of ABPs. Recent advances in multicolor imaging and analysis of ABPs and their associated F-actin networks in cells, as well as the development of sophisticated in vitro reconstitutions of networks with ensembles of ABPs, have allowed the field to start uncovering the underlying principles by which cells self-organize diverse F-actin networks to execute basic cellular functions.

The self-organization model reveals systematic characteristics of aging

BACKGROUND

Aging is a fundamental biological process, where key bio-markers interact with each other and synergistically regulate the aging process. Thus aging dysfunction will induce many disorders. Finding aging markers and re-constructing networks based on multi-omics data (i.e. methylation, transcriptional and so on) are informative to study the aging process. However, optimizing the model to predict aging have not been performed systemically, although it is critical to identify potential molecular mechanism of aging related diseases.

METHODS

This paper aims to model the aging self-organization system using a series of supervised learning methods, and study complex molecular mechanisms of aging at system level: i.e. optimizing the aging network; summarizing interactions between aging markers; accumulating patterns of aging markers within module; finding order-parameters in the aging self-organization system.

RESULTS

In this work, the normal aging process is modeled based on multi-omics profiles across different tissues. In addition, the computational pipeline aims to model aging self-organizing systems and study the relationship between aging and related diseases (i.e. cancers), thus provide useful indicators of aging related diseases and could help to improve prediction abilities of diagnostics.

CONCLUSIONS

The aging process could be studied thoroughly by modelling the self-organization system, where key functions and the crosstalk between aging and cancers were identified.

Coupled cycling and regulation of metazoan morphogenesis

Metazoan animals are characterized by restricted phenotypic heterogeneity (i.e. morphological disparity) of organisms within various species, a feature that contrasts sharply with intra-species morphological diversity observed in the plant kingdom. Robust emergence of morphogenic blueprint in metazoan animals reflects restricted autonomy of individual cells in adoption of fate outcomes such as differentiation. Fates of individual cells are linked to and influenced by fates of neighboring cells at the population level. Such coupling is a common property of all self-organising systems and propels emergence of order from simple interactions between individual cells without supervision by external directing forces. As a consequence of coupling, expected functional relationship between the constituent cells of an organ system is robustly established concurrent with multiple rounds of cell division during morphogenesis. Notably, the molecular regulation of multicellular coupling during morphogenic self-organisation remains largely unexplored. Here, we review the existing literature on multicellular self-organisation with particular emphasis on recent discovery that β-catenin is the key coupling factor that programs emergence of multi-cellular self-organisation by regulating synchronised cycling of individual cells.

Genetically inspired in vitro reconstitution of Saccharomyces cerevisiae actin cables from seven purified proteins

A major goal of synthetic biology is to define the minimal cellular machinery required to assemble a biological structure in its simplest form. Here, we focused on Saccharomyces cerevisiae actin cables, which provide polarized tracks for intracellular transport and maintain defined lengths while continuously undergoing rapid assembly and turnover. Guided by the genetic requirements for proper cable assembly and dynamics, we show that seven evolutionarily conserved S. cerevisiae proteins (actin, formin, profilin, tropomyosin, capping protein, cofilin, and AIP1) are sufficient to reconstitute the formation of cables that undergo polarized turnover and maintain steady-state lengths similar to actin cables in vivo. Further, the removal of individual proteins from this simple in vitro reconstitution system leads to cable defects that closely approximate in vivo cable phenotypes caused by disrupting the corresponding genes. Thus, a limited set of molecular components is capable of self-organizing into dynamic, micron-scale actin structures with features similar to cables in living cells.

A guide to supramolecular polymerizations

Supramolecular polymers are non-covalent assemblies of unimeric building blocks connected by secondary interactions and hold great promises due to their dynamic nature.

Intracellular organization in cell polarity - placing organelles into the polarity loop

Many studies have investigated the processes that support polarity establishment and maintenance in cells. On the one hand, polarity complexes at the cell cortex and their downstream signaling pathways have been assigned as major regulators of polarity. On the other hand, intracellular organelles and their polarized trafficking routes have emerged as important components of polarity. In this Review, we argue that rather than trying to identify the prime 'culprit', now it is time to consider all these players as a collective. We highlight that understanding the intimate coordination between the polarized cell cortex and the intracellular compass that is defined by organelle positioning is essential to capture the concept of polarity. After briefly reviewing how polarity emerges from a dynamic maintenance of cellular asymmetries, we highlight how intracellular organelles and their associated trafficking routes provide diverse feedback for dynamic cell polarity maintenance. We argue that the asymmetric organelle compass is an indispensable element of the polarity network.

The Systemic-Evolutionary Theory of the Origin of Cancer (SETOC): A New Interpretative Model of Cancer as a Complex Biological System

The Systemic–Evolutionary Theory of Cancer (SETOC) is a recently proposed theory based on two important concepts: (i) Evolution, understood as a process of cooperation and symbiosis (Margulian-like), and (ii) The system, in terms of the integration of the various cellular components, so that the whole is greater than the sum of the parts, as in any complex system. The SETOC posits that cancer is generated by the de-emergence of the “eukaryotic cell system” and by the re-emergence of cellular subsystems such as archaea-like (genetic information) and/or prokaryotic-like (mitochondria) subsystems, featuring uncoordinated behaviors. One of the consequences is a sort of “cellular regression” towards ancestral or atavistic biological functions or behaviors similar to those of protists or unicellular organisms in general. This de-emergence is caused by the progressive breakdown of the endosymbiotic cellular subsystem integration (mainly, information = nucleus and energy = mitochondria) as a consequence of long-term injuries. Known cancer-promoting factors, including inflammation, chronic fibrosis, and chronic degenerative processes, cause prolonged damage that leads to the breakdown or failure of this form of integration/endosymbiosis. In normal cells, the cellular “subsystems” must be fully integrated in order to maintain the differentiated state, and this integration is ensured by a constant energy intake. In contrast, when organ or tissue damage occurs, the constant energy intake declines, leading, over time, to energy shortage, failure of endosymbiosis, and the de-differentiated state observed in dysplasia and cancer.

Gene Editing of α6 Integrin Inhibits Muscle Invasive Networks and Increases Cell-Cell Biophysical Properties in Prostate Cancer

Human prostate cancer confined to the gland is indolent (low-risk), but tumors outside the capsule are aggressive (high-risk). Extracapsular extension requires invasion within and through a smooth muscle-structured environment. Because integrins respond to biomechanical cues, we used a gene editing approach to determine if a specific region of laminin-binding α6β1 integrin was required for smooth muscle invasion both in vitro and in vivo. Human tissue specimens showed prostate cancer invasion through smooth muscle and tumor coexpression of α6 integrin and E-cadherin in a cell-cell location and α6 integrin in a cell-extracellular matrix (ECM) distribution. Prostate cancer cells expressing α6 integrin (DU145 α6WT) produced a 3D invasive network on laminin-containing Matrigel and invaded into smooth muscle both in vitro and in vivo. In contrast, cells without α6 integrin (DU145 α6KO) and cells expressing an integrin mutant (DU145 α6AA) did not produce invasive networks, could not invade muscle both in vitro and in vivo, and surprisingly formed 3D cohesive clusters. Using electric cell-substrate impedance testing, cohesive clusters had up to a 30-fold increase in normalized resistance at 400 Hz (cell-cell impedance) as compared with the DU145 α6WT cells. In contrast, measurements at 40,000 Hz (cell-ECM coverage) showed that DU145 α6AA cells were two-fold decreased in normalized resistance and were defective in restoring resistance after a 1 μmol/L S1P challenge as compared with the DU145 α6WT cells. The results suggest that gene editing of a specific α6 integrin extracellular region, not required for normal tissue function, can generate a new biophysical cancer phenotype unable to invade the muscle, presenting a new therapeutic strategy for metastasis prevention in prostate cancer. SIGNIFICANCE: This study shows an innovative strategy to block prostate cancer metastasis and invasion in the muscle through gene editing of a specific α6 integrin extracellular region.

Minimal coarse-grained models for molecular self-organisation in biology

The molecular machinery of life is largely created via self-organisation of individual molecules into functional assemblies. Minimal coarse-grained models, in which a whole macromolecule is represented by a small number of particles, can be of great value in identifying the main driving forces behind self-organisation in cell biology. Such models can incorporate data from both molecular and continuum scales, and their results can be directly compared to experiments. Here we review the state of the art of models for studying the formation and biological function of macromolecular assemblies in living organisms. We outline the key ingredients of each model and their main findings. We illustrate the contribution of this class of simulations to identifying the physical mechanisms behind life and diseases, and discuss their future developments.

Modeling Membrane Curvature Generation due to Membrane⁻Protein Interactions

To alter and adjust the shape of the plasma membrane, cells harness various mechanisms of curvature generation. Many of these curvature generation mechanisms rely on the interactions between peripheral membrane proteins, integral membrane proteins, and lipids in the bilayer membrane. Mathematical and computational modeling of membrane curvature generation has provided great insights into the physics underlying these processes. However, one of the challenges in modeling these processes is identifying the suitable constitutive relationships that describe the membrane free energy including protein distribution and curvature generation capability. Here, we review some of the commonly used continuum elastic membrane models that have been developed for this purpose and discuss their applications. Finally, we address some fundamental challenges that future theoretical methods need to overcome to push the boundaries of current model applications.