Design principles of tissue organisation: How single cells coordinate across scales

Cells act as building blocks of multicellular organisms, forming higher-order structures at different biological scales. Niches, tissues and, ultimately, entire organisms consist of single cells that remain in constant communication. Emergence of developmental patterns and tissue architecture thus relies on single cells acting as a collective, coordinating growth, migration, cell fate transitions and cell type sorting. For this, information has to be transmitted forward from cells to tissues and fed back to the individual cell to allow dynamic and robust coordination. Here, we define the design principles of tissue organisation integrating chemical, genetic and mechanical cues. We also review the state-of-the-art technologies used for dissecting collective cellular behaviours at single cell– and tissue-level resolution. We finally outline future challenges that lie in a comprehensive understanding of how single cells coordinate across biological scales to insure robust development, homoeostasis and regeneration of tissues.     

Dynamics on the manifold: Identifying computational dynamical activity from neural population recordings

The question of how the collective activity of neural populations gives rise to complex behaviour is fundamental to neuroscience. At the core of this question lie considerations about how neural circuits can perform computations that enable sensory perception, decision making, and motor control. It is thought that such computations are implemented through the dynamical evolution of distributed activity in recurrent circuits. Thus, identifying dynamical structure in neural population activity is a key challenge towards a better understanding of neural computation. At the same time, interpreting this structure in light of the computation of interest is essential for linking the time-varying activity patterns of the neural population to ongoing computational processes. Here, we review methods that aim to quantify structure in neural population recordings through a dynamical system defined in a low-dimensional latent variable space. We discuss advantages and limitations of different modelling approaches and address future challenges for the field.     

Keeping your options open: Maintenance of thermal plasticity during adaptation to a stable environment

Phenotypic plasticity may allow species to cope with environmental variation. The study of thermal plasticity and its evolution helps understanding how populations respond to variation in temperature. In the context of climate change, it is essential to realize the impact of historical differences in the ability of populations to exhibit a plastic response to thermal variation and how it evolves during colonization of new environments. We have analyzed the real‐time evolution of thermal reaction norms of adult and juvenile traits in Drosophila subobscura populations from three locations of Europe in the laboratory. These populations were kept at a constant temperature of 18ºC, and were periodically assayed at three experimental temperatures (13ºC, 18ºC, and 23ºC). We found initial differentiation between populations in thermal plasticity as well as evolutionary convergence in the shape of reaction norms for some adult traits, but not for any of the juvenile traits. Contrary to theoretical expectations, an overall better performance of high latitude populations across temperatures in early generations was observed. Our study shows that the evolution of thermal plasticity is trait specific, and that a new stable environment did not limit the ability of populations to cope with environmental challenges.     

Overview of Mathematical Approaches Used to Model Bacterial Chemotaxis II: Bacterial Populations

We review the application of mathematical modeling to understanding the behavior of populations of chemotactic bacteria. The application of continuum mathematical models, in particular generalized Keller–Segel models, is discussed along with attempts to incorporate the microscale (individual) behavior on the macroscale, modeling the interaction between different species of bacteria, the interaction of bacteria with their environment, and methods used to obtain experimentally verified parameter values. We allude briefly to the role of modeling pattern formation in understanding collective behavior within bacterial populations. Various aspects of each model are discussed and areas for possible future research are postulated.     

Stochastic Models of Lymphocyte Proliferation and Death

Quantitative understanding of the kinetics of lymphocyte proliferation and death upon activation with an antigen is crucial for elucidating factors determining the magnitude, duration and efficiency of the immune response. Recent advances in quantitative experimental techniques, in particular intracellular labeling and multi-channel flow cytometry, allow one to measure the population structure of proliferating and dying lymphocytes for several generations with high precision. These new experimental techniques require novel quantitative methods of analysis. We review several recent mathematical approaches used to describe and analyze cell proliferation data. Using a rigorous mathematical framework, we show that two commonly used models that are based on the theories of age-structured cell populations and of branching processes, are mathematically identical. We provide several simple analytical solutions for a model in which the distribution of inter-division times follows a gamma distribution and show that this model can fit both simulated and experimental data. We also show that the estimates of some critical kinetic parameters, such as the average inter-division time, obtained by fitting models to data may depend on the assumed distribution of inter-division times, highlighting the challenges in quantitative understanding of cell kinetics.     

Locust Collective Motion and Its Modeling

Over the past decade, technological advances in experimental and animal tracking techniques have motivated a renewed theoretical interest in animal collective motion and, in particular, locust swarming. This review offers a comprehensive biological background followed by comparative analysis of recent models of locust collective motion, in particular locust marching, their settings, and underlying assumptions. We describe a wide range of recent modeling and simulation approaches, from discrete agent-based models of self-propelled particles to continuous models of integro-differential equations, aimed at describing and analyzing the fascinating phenomenon of locust collective motion. These modeling efforts have a dual role: The first views locusts as a quintessential example of animal collective motion. As such, they aim at abstraction and coarse-graining, often utilizing the tools of statistical physics. The second, which originates from a more biological perspective, views locust swarming as a scientific problem of its own exceptional merit. The main goal should, thus, be the analysis and prediction of natural swarm dynamics. We discuss the properties of swarm dynamics using the tools of statistical physics, as well as the implications for laboratory experiments and natural swarms. Finally, we stress the importance of a combined-interdisciplinary, biological-theoretical effort in successfully confronting the challenges that locusts pose at both the theoretical and practical levels.     

Advances and challenges in programming pattern formation using living cells

Spatial patterning of cell populations is a ubiquitous phenomenon in nature. Patterns occur at various length and time scales and exhibit immense diversity. In addition to offering a deeper understanding of the emergence of patterns in nature, the ability to program synthetic patterns using living cells has the potential for broad applications. To date, however, progress in engineering pattern formation has been hampered by technical challenges. In this Review, we discuss recent advances in programming pattern formation in terms of biological insights, experimental and computational tool development, and potential applications.     

Deer,wolves, and people: costs,benefits and challenges of living together

Human‐driven species annihilations loom as a major crisis. However the recovery of deer and wolf populations in many parts of the northern hemisphere has resulted in conflicts and controversies rather than in relief. Both species interact in complex ways with their environment, each other, and humans. We review these interactions in the context of the ecological and human costs and benefits associated with these species. We integrate scattered information to widen our perspective on the nature and perception of these costs and benefits and how they link to each other and ongoing controversies regarding how we manage deer and wolf populations. After revisiting the ecological roles deer and wolves play in contemporary ecosystems, we explore how they interact, directly and indirectly, with human groups including farmers, foresters, shepherds, and hunters. Interactions with deer and wolves generate various axes of tension, posing both ecological and sociological challenges. Resolving these tensions and conflicts requires that we address key questions using integrative approaches: what are the ecological consequences of deer and wolf recovery? How do they influence each other? What are the social and socio‐ecological consequences of large deer populations and wolf presence? Finally, what key obstacles must be overcome to allow deer, wolves and people to coexist? Reviewing contemporary ecological and sociological results suggests insights and ways to improve our understanding and resolve long‐standing challenges to coexistence. We should begin by agreeing to enhance aggregate benefits while minimizing the collective costs we incur by interacting with deer and wolves. We should also view these species, and ourselves, as parts of integrated ecosystems subject to long‐term dynamics. If co‐existence is our goal, we need deer and wolves to persevere in ways that are compatible with human interests. Our human interests, however, should be inclusive and fairly value all the costs and benefits deer and wolves entail including their intrinsic value. Shifts in human attitudes and cultural learning that are already occurring will reshape our ecological interactions with deer and wolves.     

Is MHC enough for understanding wildlife immunogenetics?

Along with reproductive success and predation, infectious disease is a major demographic and evolutionary driver of natural populations. To understand the evolutionary impacts of disease, research has focussed on the major histocompatibility complex (MHC), a genetic region involved in antigen presentation. There is a pressing need for the broader research currently conducted on traditional vertebrate models to be transferred to wildlife. Incorporating such knowledge will enable a broader understanding of the levels at which natural selection can act on immunity. We propose two new approaches to wildlife immunogenetics and discuss the challenges of conducting such studies. At a time when novel pathogens are increasingly emerging in natural populations, these new approaches are integral to understanding disease dynamics and assessing epidemic risks.     

Understanding human DNA sequence variation

Over the past century researchers have identified normal genetic variation and studied that variation in diverse human populations to determine the amounts and distributions of that variation. That information is being used to develop an understanding of the demographic histories of the different populations and the species as a whole, among other studies. With the advent of DNA-based markers in the last quarter century, these studies have accelerated. One of the challenges for the next century is to understand that variation. One component of that understanding will be population genetics. We present here examples of many of the ways these new data can be analyzed from a population perspective using results from our laboratory on multiple individual DNA-based polymorphisms, many clustered in haplotypes, studied in multiple populations representing all major geographic regions of the world. These data support an "out of Africa" hypothesis for human dispersal around the world and begin to refine the understanding of population structures and genetic relationships. We are also developing baseline information against which we can compare findings at different loci to aid in the identification of loci subject, now and in the past, to selection (directional or balancing). We do not yet have a comprehensive understanding of the extensive variation in the human genome, but some of that understanding is coming from population genetics.     

Bistable Perception Modeled as Competing Stochastic Integrations at Two Levels

We propose a novel explanation for bistable perception, namely, the collective dynamics of multiple neural populations that are individually meta-stable. Distributed representations of sensory input and of perceptual state build gradually through noise-driven transitions in these populations, until the competition between alternative representations is resolved by a threshold mechanism. The perpetual repetition of this collective race to threshold renders perception bistable. This collective dynamics – which is largely uncoupled from the time-scales that govern individual populations or neurons – explains many hitherto puzzling observations about bistable perception: the wide range of mean alternation rates exhibited by bistable phenomena, the consistent variability of successive dominance periods, and the stabilizing effect of past perceptual states. It also predicts a number of previously unsuspected relationships between observable quantities characterizing bistable perception. We conclude that bistable perception reflects the collective nature of neural decision making rather than properties of individual populations or neurons.     

Reflections on a giant of brain science

Walter J. Freeman was a giant of the field of neuroscience whose visionary work contributed various experimental and theoretical breakthroughs to brain research in the past 60 years. He has pioneered a number of Electroencephalogram and Electrocorticogram tools and approaches that shaped the field, while “Freeman Neurodynamics” is a theoretical concept that is widely known, used, and respected among neuroscientists all over the world. His recent death is a profound loss to neuroscience and biomedical engineering. Many of his revolutionary ideas on brain dynamics have been ahead of their time by decades. We summarize his following groundbreaking achievements: (1) Mass Action in the Nervous System, from microscopic (single cell) recordings, through mesoscopic populations, to large-scale collective brain patterns underlying cognition; (2) Freeman–Kachalsky model of multi-scale, modular brain dynamics; (3) cinematic theory of cognitive dynamics; (4) phase transitions in cortical dynamics modeled with random graphs and quantum field theory; (5) philosophical aspects of intentionality, consciousness, and the unity of brain–mind–body. His work has been admired by many of his neuroscientist colleagues and followers. At the same time, his multidisciplinary approach combining advanced concepts of control theory and the mathematics of nonlinear systems and chaos, poses significant challenges to those who wish to thoroughly understand his message. The goal of this commemorative paper is to review key aspects of Freeman’s neurodynamics and to provide some handles to gain better understanding about Freeman’s extraordinary intellectual achievement.     

Mechanobiology of leader–follower dynamics in epithelial cell migration

Collective cell migration is fundamental to biological form and function. It is also relevant to the formation and repair of organs and to various pathological situations, including metastatic propagation of cancer. Technological, experimental, and computational advancements have allowed the researchers to explore various aspects of collective migration, spanning from biochemical signalling to inter-cellular force transduction. Here, we summarize our current understanding of the mechanobiology of collective cell migration, limiting to epithelial tissues. On the basis of recent studies, we describe how cells sense and respond to guidance signals to orchestrate various modes of migration and identify the determining factors dictating leader–follower interactions. We highlight how the inherent mechanics of dense epithelial monolayers at multicellular length scale might instruct individual cells to behave collectively. On the basis of these findings, we propose that mechanical resilience, obtained by a certain extent of cell jamming, allows the epithelium to perform efficient collective migration during wound healing.     

Modelling microtubule patterns

The cellular cytoskeleton is well studied in terms of its biological and physical properties, making it an attractive subject for systems approaches. Here, we describe the experimental and theoretical strategies used to study the collective behaviour of microtubules and motors. We illustrate how this led to the beginning of an understanding of dynamic cellular patterns that have precise functions.     

Conservation genetics in a globally changing environment: present problems,paradoxes and future challenges

Despite recent advances in conservation genetics and related disciplines and the growing impact that conservation genetics is having in conservation biology, our knowledge on several key issues in the field is still insufficient. Here we identify some of these issues together with addressing several paradoxes which have to be solved before conservation genetics can face new challenges that are appearing in the transitory phase from the population genetics into the population genomics era. Most of these issues, paradoxes and challenges, like the central dogma of conservation genetics, the computational, theoretical and laboratory experiment achievements and limitations in the conservation genetics field have been discussed. Further knowledge on the consequences of inbreeding and outbreeding depression in wild populations as well as the capacity of small populations to adapt to local environmental conditions is also urgently needed. The integration of experimental, theoretical and applied conservation genetics will contribute to improve our understanding of methodological and applied aspects of conservation genetics.     

Scoring the collective effects of SNPs: association of minor alleles with complex traits in model organisms

It has long been assumed that most parts of a genome and most genetic variations or SNPs are non-functional with regard to reproductive fitness.However,the collective effects of SNPs have yet to be examined by experimental science.We here developed a novel approach to examine the relationship between traits and the total amount of SNPs in panels of genetic reference populations.We identified the minor alleles(MAs)in each panel and the MA content(MAC)that each inbred strain carried for a set of SNPs with genotypes determined in these panels.MAC was nearly linearly linked to quantitative variations in numerous traits in model organisms,including life span,tumor susceptibility,learning and memory,sensitivity to alcohol and anti-psychotic drugs,and two correlated traits poor reproductive fitness and strong immunity.These results suggest that the collective effects of SNPs are functional and do affect reproductive fitness.     

Frontiers in population ecology of microtine rodents: A pluralistic approach to the study of population ecology

Current challenges for the study of population ecology of microtine rodents are reviewed. Comparisons with other taxonomic groups (other mammals, birds and insects) are given throughout. A major challenge is to link patterns and processes (i.e. mechanisms) better than is the case today. Other major challenges include the furthering of our understanding of the interaction between deterministic and stochastic processes, and as part thereof, the interaction between density-dependent and density-independent processes. The applicability of comparative studies on populations exhibiting different temporal dynamical patterns is, in this connection, emphasized. Understanding spatiotemporal dynamical patterns is another major challenge, not the least from a methodological point of view. Long-term and large-scale ecological data on population dynamics (in space and time) are critical for this purpose. Looking for consistency between hypothesized mechanisms and observed patterns is emphasized as a good platform for further empirical and theoretical work. The intellectual feedback process between different approaches to the study of microtine population ecology (observational studies, experimental manipulative studies, statistical modeling and mathematical modeling) are discussed. We recommend a pluralistic approach (involving both observational and experimental as well as theoretical studies) to the study of small rodent ecology.     

Testing Pancreatic Islet Function at the Single Cell Level by Calcium Influx with Associated Marker Expression

Studying the response of islet cells to glucose stimulation is important for understanding cell function in healthy and disease states. Most functional assays are performed on whole islets or cell populations, resulting in averaged observations and loss of information at the single cell level. We demonstrate methods to examine calcium fluxing in individual cells of intact islets in response to multiple glucose challenges. Wild-type mouse islets predominantly contained cells that responded to three (out of three) sequential high glucose challenges, whereas cells of diabetic islets (db/db or NOD) responded less frequently or not at all. Imaged islets were also immunostained for endocrine markers to associate the calcium flux profile of individual cells with gene expression. Wild-type mouse islet cells that robustly fluxed calcium expressed β cell markers (INS/NKX6.1), whereas islet cells that inversely fluxed at low glucose expressed α cell markers (GCG). Diabetic mouse islets showed a higher proportion of dysfunctional β cells that responded poorly to glucose challenges. Most of the failed calcium influx responses in β cells were observed in the second and third high glucose challenges, emphasizing the importance of multiple sequential glucose challenges for assessing the full function of islet cells. Human islet cells were also assessed and showed functional α and β cells. This approach to analyze islet responses to multiple glucose challenges in correlation with gene expression assays expands the understanding of β cell function and the diseased state.