Social experience organizes parallel networks in sensory and limbic forebrain

Successful social behavior can directly influence an individual's reproductive success. Therefore, many organisms readily modify social behavior based on past experience. The neural changes induced by social experience, however, remain to be fully elucidated. We hypothesize that social modulation of neural systems not only occurs at the level of individual nuclei, but also of functional networks, and their relationships with behavior. We used the green anole lizard (Anolis carolinensis), which displays stereotyped, visually triggered social behaviors particularly suitable for comparisons of multiple functional networks in a social context, to test whether repeated aggressive interactions modify behavior and metabolic activity in limbic-hypothalamic and sensory forebrain regions, assessed by quantitative cytochrome oxidase (a slowly accumulating endogenous metabolic marker) histochemistry. We found that aggressive interactions potentiate aggressive behavior, induce changes in activities of individual nuclei, and organize context-specific functional neural networks. Surprisingly, this experiential effect is not only present in a limbic-hypothalamic network, but also extends to a sensory forebrain network directly relevant to the behavioral expression. Our results suggest that social experience modulates organisms' social behavior via modifying sensory and limbic neural systems in parallel both at the levels of individual regions and networks, potentially biasing perceptual as well as limbic processing.     

Synchronizing a multicellular system by external input: an artificial control strategy

MOTIVATION: Although there are significant advances on elucidating the collective behaviors on biological organisms in recent years, the essential mechanisms by which the collective rhythms arise remain to be fully understood, and further how to synchronize multicellular networks by artificial control strategy has not yet been well explored. RESULTS: A control strategy is developed to synchronize gene regulatory networks in a multicellular system when spontaneous synchronization cannot be achieved. We first construct an impulsive control system to model the process of periodically injecting coupling substances with constant or random impulsive control amounts into the common extracellular medium, and further study its effects on the dynamics of individual cells. We derive the threshold of synchronization induced by the periodic substance input. Therefore, we can synchronize the multicellular network to a specific collective behavior by changing the frequency and amplitude of the periodic stimuli. Moreover, a two-stage scheme is proposed to facilitate the synchronization in this paper. We show that the presence of the external input may also initiate different dynamics. The multicellular network of coupled repressilators is used to show the effectiveness of the proposed method. The results not only provide a perspective to understand the interactions between external stimuli and intrinsic physiological rhythms, but also may lead to development of realistic artificial control strategy and medical therapy. AVAILABILITY: CONTACT: aihara@sat.t.u-tokyo.ac.jp.     

The Matrix Reloaded: How Sensing the Extracellular Matrix Synchronizes Bacterial Communities

In response to chemical communication, bacterial cells often organize themselves into complex multicellular communities that carry out specialized tasks. These communities are frequently referred to as biofilms, which involve the collective behavior of different cell types. Like cells of multicellular eukaryotes, the biofilm cells are surrounded by self-produced polymers that constitute the extracellular matrix (ECM), which binds them to each other and to the surface. In multicellular eukaryotes, it has been evident for decades that cell-ECM interactions control multiple cellular processes during development. While cells both in biofilms and in multicellular eukaryotes are surrounded by ECM and activate various genetic programs, until recently it has been unclear whether cell-ECM interactions are recruited in bacterial communicative behaviors. In this review, we describe the examples reported thus far for ECM involvement in control of cell behavior throughout the different stages of biofilm formation. The studies presented in this review have provided a newly emerging perspective of the bacterial ECM as an active player in regulation of biofilm development.     

Modeling cell apoptosis for simulating three-dimensional multicellular morphogenesis based on a reversible network reconnection framework

Morphogenesis in multicellular organisms is accompanied by apoptotic cell behaviors: cell shrinkage and cell disappearance. The mechanical effects of these behaviors are spatiotemporally regulated within multicellular dynamics to achieve proper tissue sizes and shapes in three-dimensional (3D) space. To analyze 3D multicellular dynamics, 3D vertex models have been suggested, in which a reversible network reconnection (RNR) model has successfully expressed 3D cell rearrangements during large deformations. To analyze the effects of apoptotic cell behaviors on 3D multicellular morphogenesis, we modeled cell apoptosis based on the RNR model framework. Cell shrinkage was modeled by the potential energy as a function of individual cell times during the apoptotic phase. Cell disappearance was modeled by merging neighboring polyhedrons at their boundary surface according to the topological rules of the RNR model. To establish that the apoptotic cell behaviors could be expressed as modeled, we simulated morphogenesis driven by cell apoptosis in two types of tissue topology: 3D monolayer cell sheet and 3D compacted cell aggregate. In both types of tissue topology, the numerical simulations successfully illustrated that cell aggregates gradually shrank because of successive cell apoptosis. During tissue shrinkage, the number of cells in aggregates decreased while maintaining individual cell size and shape. Moreover, in case of localizing apoptotic cells within a part of the 3D monolayer cell aggregate, the cell apoptosis caused the global tissue bending by pulling on surrounding cells. In case of localizing apoptotic cells on the surface of the 3D compacted cell aggregate, the cell apoptosis caused successive, directional cell rearrangements from the inside to the surface. Thus, the proposed model successfully provided a basis for expressing apoptotic cell behaviors during 3D multicellular morphogenesis based on an RNR model framework.     

Translating cell polarity into tissue elongation

Planar cell polarity, the orientation of single-cell asymmetries within the plane of a multicellular tissue, is essential to generating the shape and dimensions of organs and organisms. Planar polarity systems align cell behavior with the body axes and orient the cellular processes that lead to tissue elongation. Using Drosophila as a model system, significant progress has been made toward understanding how planar polarity is generated by biochemical and mechanical signals. Recent studies using time-lapse imaging reveal that cells engage in a number of active behaviors whose orientation and dynamics translate planar cell polarity into tissue elongation. Here we review recent progress in understanding the cellular mechanisms that link planar polarity to large-scale changes in tissue structure.     

Mechanical biochemistry of proteins one molecule at a time

The activity of proteins and their complexes often involves the conversion of chemical energy (stored or supplied) into mechanical work through conformational changes. Mechanical forces are also crucial for the regulation of the structure and function of cells and tissues. Thus, the shape of eukaryotic cells (and by extension, that of the multicellular organisms they form) is the result of cycles of mechanosensing, mechanotransduction, and mechanoresponse. Recently developed single-molecule atomic force microscopy techniques can be used to manipulate single molecules, both in real time and under physiological conditions, and are ideally suited to directly quantify the forces involved in both intra- and intermolecular protein interactions. In combination with molecular biology and computer simulations, these techniques have been applied to characterize the unfolding and refolding reactions in a variety of proteins. Single-molecule mechanical techniques are providing fundamental information on the structure and function of proteins and are becoming an indispensable tool to understand how these molecules fold and work.     

Communication in bacteria: an ecological and evolutionary perspective

Individual bacteria can alter their behaviour through chemical interactions between organisms in microbial communities - this is generally referred to as quorum sensing. Frequently, these interactions are interpreted in terms of communication to mediate coordinated, multicellular behaviour. We show that the nature of interactions through quorum-sensing chemicals does not simply involve cooperative signals, but entails other interactions such as cues and chemical manipulations. These signals might have a role in conflicts within and between species. The nature of the chemical interaction is important to take into account when studying why and how bacteria react to the chemical substances that are produced by other bacteria.     

Social and developmental biology of the myxobacteria.

Myxobacteria are soil bacteria whose unusually social behavior distinguishes them from other groups of procaryotes. Perhaps the most remarkable aspect of their social behavior occurs during development, when tens of thousands of cells aggregate and form a colorful fruiting body. Inside the fruiting body the vegetative cells convert into dormant, resistant myxospores. However, myxobacterial social behavior is not restricted to the developmental cycle, and three other social behaviors have been described. Vegetative cells have a multigene social motility system in which cell-cell contact is essential for gliding in multicellular swarms. Cell growth on protein is cooperative in that the growth rate increases with the cell density. Rippling is a periodic behavior in which the cells align themselves in ridges and move in waves. These social behaviors indicate that myxobacterial colonies are not merely collections of individual cells but are societies in which cell behavior is synchronized by cell-cell interactions. The molecular basis of these social behaviors is becoming clear through the use of a combination of behavioral, biochemical, and genetic experimental approaches.     

Cells in the system of multicelular organism from positions of non-linear dynamics

The organism physiological systems forming a hierarchic network with mutual dependence and subordination can be considered as systems with non-linear dynamics including positive and negative feedbacks. In the course of evolution there occurred selection of robust, flexible, modular systems capable for adaptive self-organization by non-linear interaction of components, which leads to formation of the ordered in space and time robust and plastic organization of the whole. Cells of multicellular organisms are capable for coordinated “social” behavior with formation of ordered cell assemblies, which provides a possibility of morphological and functional variability correlating with manifestations of the large spectrum of adaptive reactions. The multicellular organism is the multilevel system with hierarchy of numerous subsystems capable for adaptive self-organization; disturbance of their homeostasis can lead to pathological changes. The healthy organism regulates homeostasis, self-renewal, differentiation, and apoptosis of cells serving its parts and construction blocks by preserving its integrity and controlling behavior of cells. The systemic approach taking into account biological regularities of the appearance and development of functions in evolution of multicellular organisms opens new possibilities for diagnostics and treatment of many diseases.     

Direct cell-cell communications and social behavior of cells in mammals,protists, and bacteria. Possible causes of multicellularity

Comparison of current data on direct cell-cell communications in mammals, protists, and bacteria suggests that the emergence of the signaling systems of self-organization underlay the emergence of multicellular organisms. Biogenic amines, regulators of coordinated behavior and aggregation in bacteria, have been found in protists and multicellular organisms. In metazoans, biogenic amines have become specific neurotransmitters. At the same time, the studies on synchronization of protein synthesis rhythm in mammalian cell cultures demonstrated that noradrenaline and serotonin have conserved their ancient function of cell-cell cooperation in mammals, which is manifested as coordinated social behavior of cells in population in the case of bacteria and multicellular organisms.     

About lipids and toxins

Many mono or multicellular organisms secrete soluble proteins, referred to as protein toxins, which alter the behavior of foreign, or target cells, possibly leading to their death. These toxins affect either the cell membrane by forming pores or modifying lipids, or some intracellular target. To reach this target, they must cross one of the cellular membranes, generally that of an intracellular organelle. As described in this minireview, lipids play crucial roles in the intoxication process of most if not all toxins, by allowing/promoting binding, endocytosis, trafficking and/or translocation into the cytoplasm.     

Genetic model organisms in the study of N-glycans

Recently the genomic sequences of three multicellular eukaryotes, Caenorhabditis elegans, Drosophila melanogaster and Arabidopsis thaliana, have been elucidated. A number of cDNAs encoding glycosyltransferases demonstrated to have a role in N-linked glycosylation have already been cloned from these organisms, e.g., GlcNAc transferases and alpha 1,3-fucosyltransferases. However, many more homologues of glycosyltransferases and other glycan modifying enzymes have been predicted by analysis of the genome sequences, but the predictions of full length open reading frames appear to be particularly poor in Caenorhabditis. The use of these organisms as models in glycobiology may be hampered since they all have N-linked glycosylation repertoires unlike those of mammals. Arabidopsis and Drosophila have glycosylation similar to that of other plants or insects, while our new data from MALDI-TOF analysis of PNGase A-released neutral N-glycans of Caenorhabditis indicate that there exists a range of pauci- and oligomannosidic structures, with up to four fucose residues and up to two O-methyl groups. With all these three 'genetic model organisms', however, much more work is required for a full understanding of their glycobiology.     

Using multilayer network analysis to explore the temporal dynamics of collective behavior

Social organisms often show collective behaviors such as group foraging or movement.Collective behaviors can emerge from interactions between group members and may depend on the behavior of key individuals.When social interactions change over time,collective behaviors may change because these behaviors emerge from interactions among individuals.Despite the importance of,and growing interest in,the temporal dynamics of social interactions,it is not clear how to quantify changes in interactions over time or measure their stability.Furthermore,the temporal scale at which we should observe changes in social networks to detect biologically meaningful changes is not always apparent.Here we use multilayer network analysis to quantify temporal dynamics of social networks of the social spider Stegodyphus dumicola and determine how these dynamics relate to individual and group behaviors.We found that social interactions changed over time at a constant rate.Variation in both network structure and the identity of a keystone individual was not related to the mean or variance of the collective prey attack speed.Individuals that maintained a large and stable number of connections,despite changes in network structure,were the boldest individuals in the group.Therefore,social interactions and boldness are linked across time,but group collective behavior is not influenced by the stability of the social network.Our work demonstrates that dynamic social networks can be modeled in a multilayer framework.This approach may reveal biologically important temporal changes to social structure in other systems.     

A genetic strategy for the dynamic and graded control of cell mechanics, motility, and matrix remodeling

Cellular mechanical properties have emerged as central regulators of many critical cell behaviors, including proliferation, motility, and differentiation. Although investigators have developed numerous techniques to influence these properties indirectly by engineering the extracellular matrix (ECM), relatively few tools are available to directly engineer the cells themselves. Here we present a genetic strategy for obtaining graded, dynamic control over cellular mechanical properties by regulating the expression of mutant mechanotransductive proteins from a single copy of a gene placed under a repressible promoter. With the use of constitutively active mutants of RhoA GTPase and myosin light chain kinase, we show that varying the expression level of either protein produces graded changes in stress fiber assembly, traction force generation, cellular stiffness, and migration speed. Using this approach, we demonstrate that soft ECMs render cells maximally sensitive to changes in RhoA activity, and that by modulating the ability of cells to engage and contract soft ECMs, we can dynamically control cell spreading, migration, and matrix remodeling. Thus, in addition to providing quantitative relationships between mechanotransductive signaling, cellular mechanical properties, and dynamic cell behaviors, this strategy enables us to control the physical interactions between cells and the ECM and thereby dictate how cells respond to matrix properties.     

Self-organization in the ontogeny of multicellular organisms: a computer simulation

The progress in understanding the patterns of evolution of ontogeny is hindered by the fact that many features of ontogeny are counterintuitive (as well as the features of other processes related to self-organization, self-assembly, and spontaneous increase in complexity). The basic principle of ontogeny of multicellular organisms is that it is the process of self-assembly of ordered multicellular structures by means of coordinated behavior of many individual modules (cells), each of which follows the same set of"rules" encoded in the genome. These rules are based on the genetic regulatory networks. We hypothesize that many specific features of ontogeny that seem nontrivial or enigmatic are, in fact, the inevitable consequences of this basic principle. If so, they do not need special explanations. In order to verify this hypothesis, we developed the computer program "Evo-Devo" based on the above principle. The program is designed to model the self-assembly of ordered multicellular structures from an aggregation of dividing cells that originate from a single original cell (zygote). Each cell follows a set of rules of behavior ("genotype") that can be specified arbitrarily by the experimenter, and is the same for all cells in the embryo (each cell is programmed in exactly the same way as all other cells). It is not allowed to specify rules for groups of cells or for the whole embryo: only local rules that should be followed at the level of a single cell are possible. The analysis of phenotypic implementation of different genotypes revealed several features which are present in the ontogeny of real organisms and are regularly reproduced in the model. These include: inherent stochasticity; inescapable necessity of development of stabilizing adaptations based on negative feedback in order to decrease this stochasticity; equifinality (noise resistance) resulting from these adaptations; the ability of ontogeny to respond to major perturbations by generating new morphological structures that differ from the "normal" ones, but have similar level of complexity; the similarity of phenotypic manifestations of different mutations; channeling of possible evolutionary transformations of ontogeny; Waddington's creodes; high probability of destabilization of ontogeny (e.g., because of mutations); the possibility of a new morphological character to appear initially as a rare anomaly (low penetrance of many mutations); pleiotropy of mutations affecting ontogeny; spontaneous emergence of morphogenetic correlations; integrity of the developing organism. The fact that these features are regularly reproduced in the model implies that they are probably the inevitable consequences of the basic principle of ontogeny of multicellular organisms formulated above.     

Characterizing Cell–Cell Interactions Induced Spatial Organization of Cell Phenotypes: Application to Density-Dependent Protein Nucleocytoplasmic Distribution

Cell–cell interactions play an important role in spatial organization (pattern formation) during the development of multicellular organisms. An understanding of these biological roles requires identifying cell phenotypes that are regulated by cell–cell interactions and characterizing the spatial organizations of the phenotypes. However, conventional methods for assaying cell–cell interactions are mainly applicable at a cell population level. These measures are incapable of elucidating the spatial organizations of the phenotypes, resulting in an incomplete view of cell–cell interactions. To overcome this issue, we developed an automated image-based method to investigate cell–cell interactions based on spatial localizations of cells. We demonstrated this method in cultured cells using cell density-dependent nucleocytoplasmic distribution of β-catenin and aryl hydrocarbon receptor as the phenotype. This novel method was validated by comparing with a conventional population-based method, and proved to be more sensitive and reliable. The application of the method characterized how the phenotypes were spatially organized in a population of cultured cells. We further showed that the spatial organization was governed by cell density and was protein-specific. This automated method is very simple, and will be applicable to study cell–cell interactions in different systems from prokaryotic colonies to multicellular organisms. We envision that the ability to extract and interpret how cell–cell interactions determine the spatial organization of a cell phenotype will provide new insights into biology that may be missed by traditional population-averaged studies.     

The Evolutionary Origin of Somatic Cells under the Dirty Work Hypothesis

Reproductive division of labor is a hallmark of multicellular organisms. However, the evolutionary pressures that give rise to delineated germ and somatic cells remain unclear. Here we propose a hypothesis that the mutagenic consequences associated with performing metabolic work favor such differentiation. We present evidence in support of this hypothesis gathered using a computational form of experimental evolution. Our digital organisms begin each experiment as undifferentiated multicellular individuals, and can evolve computational functions that improve their rate of reproduction. When such functions are associated with moderate mutagenic effects, we observe the evolution of reproductive division of labor within our multicellular organisms. Specifically, a fraction of the cells remove themselves from consideration as propagules for multicellular offspring, while simultaneously performing a disproportionately large amount of mutagenic work, and are thus classified as soma. As a consequence, other cells are able to take on the role of germ, remaining quiescent and thus protecting their genetic information. We analyze the lineages of multicellular organisms that successfully differentiate and discover that they display unforeseen evolutionary trajectories: cells first exhibit developmental patterns that concentrate metabolic work into a subset of germ cells (which we call “pseudo-somatic cells”) and later evolve to eliminate the reproductive potential of these cells and thus convert them to actual soma. We also demonstrate that the evolution of somatic cells enables phenotypic strategies that are otherwise not easily accessible to undifferentiated organisms, though expression of these new phenotypic traits typically includes negative side effects such as aging.     

The behavior of parasitic flatworms in vivo: what is the role of the brain?

The ecological interactions that contribute to successful host-parasite relationships are complex and involve all levels of biotic organization between the participants. At the level of parasites living within their hosts, it is felt that the parasite's environment is predictable because of host mechanisms maintaining biochemical and physiological homeostasis. It is hypothesized that fixed behavior patterns in the parasites will evolve under these specialized conditions. Current thinking on fixed behaviors in invertebrates holds that they are generated by specialized neural circuits in the brain. Therefore, it can be expected that the brains of parasitic flatworms will have important roles in the control of the organisms' behaviors. However, in the tapeworm Hymenolepis diminuta, complex fixed patterns of behavior, associated with locomotion and migration, are not affected by the removal of the worm's brain. This suggests peripheral, and not central, control of fixed behaviors. In Fasciola hepatica, at least 6 distinct fixed patterns of behavior are responsible for guiding the worm to its final habitat in the liver. Giant neurons and other phylogenetically advanced features develop in the adult worm's brain after the expression of the sequence of distinct migration behaviors. Yet, there is no apparent new locomotory behavior, corresponding to the new advanced brain, as the parasite assumes its placid life-style as a hematophage in the bile duct. Removal of the adult brain of this parasite also does not appear to affect worm locomotory activity. Thus, the regulation and control of locomotion may not be the only important roles for the brains of parasitic flatworms. It is suggested that neuroethological approaches may hold the key to understanding the biology of these parasites.