Bacterial Ventures into Multicellularity: Collectivism through Individuality

Multicellular eukaryotes can perform functions that exceed the possibilities of an individual cell. These functions emerge through interactions between differentiated cells that are precisely arranged in space. Bacteria also form multicellular collectives that consist of differentiated but genetically identical cells. How does the functionality of these collectives depend on the spatial arrangement of the differentiated bacteria? In a previous issue of PLOS Biology, van Gestel and colleagues reported an elegant example of how the spatial arrangement of differentiated cells gives rise to collective behavior in Bacillus subtilus colonies, further demonstrating the similarity of bacterial collectives to higher multicellular organisms.Introductory textbooks tend to depict bacteria as rather primitive and simple life forms: the billions of cells in a population are all supposedly performing the exact same processes, independent of each other. According to this perspective, the properties of the population are thus nothing more than the sum of the properties of the individual cells. A brief look at the recent literature shows that life at the micro scale is much more complex and far more interesting. Even though cells in a population share the same genetic material and are exposed to similar environmental signals, they are individuals: they can greatly differ from each other in their properties and behaviors [1,2].One source of such phenotypic variation is that individual cells experience different microenvironments and regulate their genes in response. However, and intriguingly, phenotypic differences can also arise in the absence of environmental variation [3]. The stochastic nature of biochemical reactions makes variation between individuals unavoidable: reaction rates in cells will fluctuate because of the typical small number of the molecules involved, leading to slight differences in the molecular composition between individual cells [4]. While cells cannot prevent fluctuations from occurring, the effect of these extracellular and intracellular perturbations on a cell’s phenotype can be controlled by changing the biochemical properties of molecules or the architecture of gene regulatory networks [4,5]. The degree of phenotypic variation could thus evolve in response to natural selection. This raises the question of whether the high degree of phenotypic variation observed in some traits could offer benefits to the bacteria [5].One potential benefit of phenotypic variation is bet hedging. Bet hedging refers to a situation in which a fraction of the cells express alternative programs, which typically reduce growth in the current conditions but at the same time allow for increased growth or survival when the environment abruptly changes [6–8]. Another potential benefit can arise through the division of labor: phenotypic variation can lead to the formation of interacting subpopulations that specialize in complementary tasks [9]. As a result, the population as a whole can perform existing functions more efficiently or attain new functionality [10]. Division of labor enables groups of bacteria to engage in two tasks that are incompatible with each other but that are both required to attain a certain biological function.One of the most famous examples of division of labor in bacteria is the specialization of multicellular cyanobacteria into photosynthesizing and nitrogen-fixing subpopulations [11]. Here, the driving force behind the division of labor is the biochemical incompatibility between photosynthesis and nitrogen fixation, as the oxygen produced during photosynthesis permanently damages the enzymes involved in nitrogen fixation [12]. Other examples include the division of labor between two subpopulations of Salmonella Typhimurium (Tm) during infections [9] and the formation of multicellular fruiting bodies in Myxococcus xanthus [13]. Division of labor is not restricted to interactions between only two subpopulations; for example, the soil-dwelling bacteria Bacillus subtilis can differentiate into at least five different cell types [14]. Multiple types can simultaneously be present in Bacillus biofilms and colonies, each contributing different essential tasks [14,15].An important question is whether a successful division of labor requires the different subpopulations to coordinate their behavior and spatial arrangement. For some systems, it turns out that spatial coordination is not required. For example, the division of labor in clonal groups of Salmonella Tm does not require that the two cell types are spatially arranged in a particular way [9]. In other systems, spatial coordination between the different cell types seems to be beneficial. For example, differentiation into nitrogen-fixing and photosynthetic cells in multicellular cyanobacteria is spatially regulated in a way that facilitates sharing of nitrogen and carbon [16]. In general, when cell differentiation is combined with coordination of behavior between cells, this can allow for the development of complex, group-level behaviors that cannot easily be deduced from the behavior of individual cells [17–20]. In these cases, a population can no longer be treated as an assembly of independent individuals but must be seen as a union that together shows collective behavior.The study by van Gestel et al. [21] in a previous issue of PLOS Biology offers an exciting perspective on how collective behavior can arise from processes operating at the level of single cells. Van Gestel and colleagues [21] analyzed how groups of B. subtilis cells migrate across solid surfaces in a process known as sliding motility. The authors found that migration requires both individuality—the expression of different phenotypes in clonal populations—and spatial coordination between cells. Migration depends critically on the presence of two cell types: surfactin-producing cells, which excrete a surfactant that reduce surface tension, and matrix-producing cells, which excrete extracellular polysaccharides and proteins that form a connective extracellular matrix (Fig 1B) [14]. These two cell types are not randomly distributed across the bacterial group but are rather spatially organized (Fig 1C). The matrix-producing cells form bundles of interconnected and highly aligned cells, which the authors refer to as “van Gogh” bundles. The surfactant producing cells are not present in the van Gogh bundle but are essential for the formation of the bundles [21].Open in a separate windowFig 1Collective behavior through the spatial organization of differentiated cells.(A) Initially cells form a homogenous population. (B) Differentiation: cells start to differentiate into surfactin- (orange) and matrix- (blue) producing cells. The two cell types perform two complementary and essential tasks, resulting in a division of labor. (C) Spatial organization: the matrix-producing cells form van Gogh bundles, consisting of highly aligned and interconnected cells. Surfactin-producing cells are excluded from the bundles and have no particular spatial arrangement. (D) Collective behavior: growth of cells in the van Gogh bundles leads to buckling of these bundles, resulting in colony expansion. The buckling and resulting expansion depend critically on the presence of the two cell types and on their spatial arrangement.The ability to migrate is a collective behavior that can be linked to the biophysical properties of the multicellular van Gogh bundles. The growth of cells in these bundles causes them to buckle, which in turn drives colony migration (Fig 1D) [21]. This is a clear example of an emergent (group-level) phenotype: the buckling of the van Gogh bundles and the resulting colony motility cannot easily be deduced from properties of individual cells. Rather, to understand colony migration we have to understand the interactions between the two cells type as well as their spatial organization. Building on a rich body of work on the regulation of gene expression and cellular differentiation in Bacillus [14], van Gestel et al. [21] are able to show how these molecular mechanisms lead to the formation of specialized cell types that, through coordinated spatial arrangement, provide the group the ability to move (Fig 1). The study thus uniquely bridges the gap between molecular mechanisms and collective behavior in bacterial multicellularity.This study raises a number of intriguing questions. A first question pertains to the molecular mechanisms underlying the spatial coordination of the two cell types. Can the spatial organization be explained based on known mechanisms of the regulation of gene expression in this organism or does the formation of these patterns depend on hitherto uncharacterized gene regulation based on spatial gradients or cell–cell interaction? A second question is about the selective forces that lead to the evolution of collective migration of this organism. The authors raise the interesting hypothesis that van Gogh bundles evolved to allow for migration. Although this explanation is very plausible, it also raises the question of how selection acting on a property at the level of the group can lead to adaptation at the individual cell level. Possible mechanisms for such selective processes have been described within the framework of multilevel selection theory. However, there are still many questions regarding how, and to what extent, multilevel selection operates in the natural world [22–24]. The system described by van Gestel and colleagues [21] offers exciting opportunities to address these questions using a highly studied and experimentally amenable model organism.Bacterial collectives (e.g., colonies or biofilms) have been likened to multicellular organisms partly because of the presence of cell differentiation and the importance of an extracellular matrix [25,26]. Higher multicellular organisms share these properties; however, they are more than simple lumps of interconnected, differentiated cells. Rather, the functioning of multicellular organisms critically depends on the precise spatial organization of these cells [27]. Even though spatial organization has been suggested before in B. subtilis biofilms [28], there was a gap in our understanding of how spatial organization of unicellular cells can lead to group-level function. The van Gogh bundles in the article by van Gestel et al. [21] provide direct evidence on how differentiated cells can spatially organize themselves to give rise to group-level behavior. This shows once more that bacteria are not primitive “bags of chemicals” but rather are more like us “multicellulars” than we might have expected.     

New Tools for Comparing Microscopy Images: Quantitative Analysis of Cell Types in Bacillus subtilis

Fluorescence microscopy is a method commonly used to examine individual differences between bacterial cells, yet many studies still lack a quantitative analysis of fluorescence microscopy data. Here we introduce some simple tools that microbiologists can use to analyze and compare their microscopy images. We show how image data can be converted to distribution data. These data can be subjected to a cluster analysis that makes it possible to objectively compare microscopy images. The distribution data can further be analyzed using distribution fitting. We illustrate our methods by scrutinizing two independently acquired data sets, each containing microscopy images of a doubly labeled Bacillus subtilis strain. For the first data set, we examined the expression of srfA and tapA, two genes which are expressed in surfactin-producing and matrix-producing cells, respectively. For the second data set, we examined the expression of eps and tapA; these genes are expressed in matrix-producing cells. We show that srfA is expressed by all cells in the population, a finding which contrasts with a previously reported bimodal distribution of srfA expression. In addition, we show that eps and tapA do not always have the same expression profiles, despite being expressed in the same cell type: both operons are expressed in cell chains, while single cells mainly express eps. These findings exemplify that the quantification and comparison of microscopy data can yield insights that otherwise would go unnoticed.     

Cell Lineages and the Logic of Proliferative Control

It is widely accepted that the growth and regeneration of tissues and organs is tightly controlled. Although experimental studies are beginning to reveal molecular mechanisms underlying such control, there is still very little known about the control strategies themselves. Here, we consider how secreted negative feedback factors (“chalones”) may be used to control the output of multistage cell lineages, as exemplified by the actions of GDF11 and activin in a self-renewing neural tissue, the mammalian olfactory epithelium (OE). We begin by specifying performance objectives—what, precisely, is being controlled, and to what degree—and go on to calculate how well different types of feedback configurations, feedback sensitivities, and tissue architectures achieve control. Ultimately, we show that many features of the OE—the number of feedback loops, the cellular processes targeted by feedback, even the location of progenitor cells within the tissue—fit with expectations for the best possible control. In so doing, we also show that certain distinctions that are commonly drawn among cells and molecules—such as whether a cell is a stem cell or transit-amplifying cell, or whether a molecule is a growth inhibitor or stimulator—may be the consequences of control, and not a reflection of intrinsic differences in cellular or molecular character.     

Natural Killer Cell Signal Integration Balances Synapse Symmetry and Migration

Natural killer (NK) cells discern the health of other cells by recognising the balance of activating and inhibitory ligands expressed by each target cell. However, how the integration of activating and inhibitory signals relates to formation of the NK cell immune synapse remains a central question in our understanding of NK cell recognition. Here we report that ligation of LFA-1 on NK cells induced asymmetrical cell spreading and migration. In contrast, ligation of the activating receptor NKG2D induced symmetrical spreading of ruffled lamellipodia encompassing a dynamic ring of f-actin, concurrent with polarization towards a target cell and a “stop” signal. Ligation of both LFA-1 and NKG2D together resulted in symmetrical spreading but co-ligation of inhibitory receptors reverted NK cells to an asymmetrical migratory configuration leading to inhibitory synapses being smaller and more rapidly disassembled. Using micropatterned activating and inhibitory ligands, signals were found to be continuously and locally integrated during spreading. Together, these data demonstrate that NK cells spread to form large, stable, symmetrical synapses if activating signals dominate, whereas asymmetrical migratory “kinapses” are favoured if inhibitory signals dominate. This clarifies how the integration of activating and inhibitory receptor signals is translated to an appropriate NK cell response.     

Seeds of Locally Aligned Motion and Stress Coordinate a Collective Cell Migration

We find how collective migration emerges from mechanical information transfer between cells. Local alignment of cell velocity and mechanical stress orientation—a phenomenon dubbed “plithotaxis”—plays a crucial role in inducing coordinated migration. Leader cells at the monolayer edge better align velocity and stress to migrate faster toward the open space. Local seeds of enhanced motion then generate stress on neighboring cells to guide their migration. Stress-induced motion propagates into the monolayer as well as along the monolayer boundary to generate increasingly larger clusters of coordinately migrating cells that move faster with enhanced alignment of velocity and stress. Together, our analysis provides a model of long-range mechanical communication between cells, in which plithotaxis translates local mechanical fluctuations into globally collective migration of entire tissues.     

Colony Organization in the Green Alga Botryococcus braunii (Race B) Is Specified by a Complex Extracellular Matrix

Botryococcus braunii is a colonial green alga whose cells associate via a complex extracellular matrix (ECM) and produce prodigious amounts of liquid hydrocarbons that can be readily converted into conventional combustion engine fuels. We used quick-freeze deep-etch electron microscopy and biochemical/histochemical analysis to elucidate many new features of B. braunii cell/colony organization and composition. Intracellular lipid bodies associate with the chloroplast and endoplasmic reticulum (ER) but show no evidence of being secreted. The ER displays striking fenestrations and forms a continuous subcortical system in direct contact with the cell membrane. The ECM has three distinct components. (i) Each cell is surrounded by a fibrous β-1, 4- and/or β-1, 3-glucan-containing cell wall. (ii) The intracolonial ECM space is filled with a cross-linked hydrocarbon network permeated with liquid hydrocarbons. (iii) Colonies are enclosed in a retaining wall festooned with a fibrillar sheath dominated by arabinose-galactose polysaccharides, which sequesters ECM liquid hydrocarbons. Each cell apex associates with the retaining wall and contributes to its synthesis. Retaining-wall domains also form “drapes” between cells, with some folding in on themselves and penetrating the hydrocarbon interior of a mother colony, partitioning it into daughter colonies. We propose that retaining-wall components are synthesized in the apical Golgi apparatus, delivered to apical ER fenestrations, and assembled on the surfaces of apical cell walls, where a proteinaceous granular layer apparently participates in fibril morphogenesis. We further propose that hydrocarbons are produced by the nonapical ER, directly delivered to the contiguous cell membrane, and pass across the nonapical cell wall into the hydrocarbon-based ECM.     

Disentangling Membrane Dynamics and Cell Migration; Differential Influences of F-actin and Cell-Matrix Adhesions

Cell migration is heavily interconnected with plasma membrane protrusion and retraction (collectively termed “membrane dynamics”). This makes it difficult to distinguish regulatory mechanisms that differentially influence migration and membrane dynamics. Yet such distinctions may be valuable given evidence that cancer cell invasion in 3D may be better predicted by 2D membrane dynamics than by 2D cell migration, implying a degree of functional independence between these processes. Here, we applied multi-scale single cell imaging and a systematic statistical approach to disentangle regulatory associations underlying either migration or membrane dynamics. This revealed preferential correlations between membrane dynamics and F-actin features, contrasting with an enrichment of links between cell migration and adhesion complex properties. These correlative linkages were often non-linear and therefore context-dependent, strengthening or weakening with spontaneous heterogeneity in cell behavior. More broadly, we observed that slow moving cells tend to increase in area, while fast moving cells tend to shrink, and that the size of dynamic membrane domains is independent of cell area. Overall, we define macromolecular features preferentially associated with either cell migration or membrane dynamics, enabling more specific interrogation and targeting of these processes in future.     

A two-step search and run response to gradients shapes leukocyte navigation in vivo

Migrating cells must interpret chemical gradients to guide themselves within tissues. A long-held principle is that gradients guide cells via reorientation of leading-edge protrusions. However, recent evidence indicates that protrusions can be dispensable for locomotion in some contexts, raising questions about how cells interpret endogenous gradients in vivo and whether other mechanisms are involved. Using laser wound assays in zebrafish to elicit acute endogenous gradients and quantitative analyses, we demonstrate a two-stage process for leukocyte chemotaxis in vivo: first a “search” phase, with stimulation of actin networks at the leading edge, cell deceleration, and turning. This is followed by a “run” phase, with fast actin flows, cell acceleration, and persistence. When actin dynamics are perturbed, cells fail to resolve the gradient, suggesting that pure spatial sensing of the gradient is insufficient for navigation. Our data suggest that cell contractility and actin flows provide memory for temporal sensing, while expansion of the leading edge serves to enhance gradient sampling.     

Exon-Skipping Strategy by Ratio Modulation between Cytoprotective versus Pro-Apoptotic Clusterin Forms Increased Sensitivity of LNCaP to Cell Death

Background

In prostate cancer the secreted form of clusterin (sCLU) has been described as an anti-apoptotic protein whose expression is increased after therapeutic intervention, whereas, the nuclear protein form nCLU was reported to have pro-apoptotic properties.

Methodology

In order to provide new therapeutic approaches targeting CLU, we developed a strategy based on exon skipping by using a lentiviral construct to preferentially induce the nuclear spliced form of the protein. The molecular construct was transduced in LNCaP cells for testing the modulation of sensitivity of the transduced cells to pro-apoptotic stress.

Results and Conclusions

We showed an increase of nCLU/sCLU expression ratio in the prostate cancer cell line “LNCaP” after lentiviral vector-U7 nCLU transduction. Moreover, we showed a significant inhibition of cell proliferation in nCLU-U7 LNCaP cells after treatment with cisplatin and after exposure to ionizing radiation compared to control cells. Finally, we showed that nCLU-U7 LNCaP cells exposure to UV-C significantly reduced an increase of cell death compared to control. Finally, we showed that modulating nCLU expression had profound impact on Ku70/Bax interaction as well as Rad17 expression which could be a key mechanism in sensitizing cells to cell death. In conclusion, this is the first report showing that increasing of nCLU/sCLU expression ratio by using an “on demand alternative splicing” strategy successfully increased sensitivity to radiotherapy and chemotherapy of prostate cancer cells.     

A Quantitative Comparison of Human HT-1080 Fibrosarcoma Cells and Primary Human Dermal Fibroblasts Identifies a 3D Migration Mechanism with Properties Unique to the Transformed Phenotype

Here, we describe an engineering approach to quantitatively compare migration, morphologies, and adhesion for tumorigenic human fibrosarcoma cells (HT-1080s) and primary human dermal fibroblasts (hDFs) with the aim of identifying distinguishing properties of the transformed phenotype. Relative adhesiveness was quantified using self-assembled monolayer (SAM) arrays and proteolytic 3-dimensional (3D) migration was investigated using matrix metalloproteinase (MMP)-degradable poly(ethylene glycol) (PEG) hydrogels (“synthetic extracellular matrix” or “synthetic ECM”). In synthetic ECM, hDFs were characterized by vinculin-containing features on the tips of protrusions, multipolar morphologies, and organized actomyosin filaments. In contrast, HT-1080s were characterized by diffuse vinculin expression, pronounced β1-integrin on the tips of protrusions, a cortically-organized F-actin cytoskeleton, and quantitatively more rounded morphologies, decreased adhesiveness, and increased directional motility compared to hDFs. Further, HT-1080s were characterized by contractility-dependent motility, pronounced blebbing, and cortical contraction waves or constriction rings, while quantified 3D motility was similar in matrices with a wide range of biochemical and biophysical properties (including collagen) despite substantial morphological changes. While HT-1080s were distinct from hDFs for each of the 2D and 3D properties investigated, several features were similar to WM239a melanoma cells, including rounded, proteolytic migration modes, cortical F-actin organization, and prominent uropod-like structures enriched with β1-integrin, F-actin, and melanoma cell adhesion molecule (MCAM/CD146/MUC18). Importantly, many of the features observed for HT-1080s were analogous to cellular changes induced by transformation, including cell rounding, a disorganized F-actin cytoskeleton, altered organization of focal adhesion proteins, and a weakly adherent phenotype. Based on our results, we propose that HT-1080s migrate in synthetic ECM with functional properties that are a direct consequence of their transformed phenotype.     

Inhibition of Cell Migration and Cell Division Correlates with Distinct Effects of Microtubule Inhibiting Drugs

Drugs that target microtubules are thought to inhibit cell division and cell migration by suppressing dynamic instability, a “search and capture” behavior that allows microtubules to probe their environment. Here, we report that subtoxic drug concentrations are sufficient to inhibit plus-end microtubule dynamic instability and cell migration without affecting cell division or microtubule assembly. The higher drug concentrations needed to inhibit cell division act through a novel mechanism that generates microtubule fragments by stimulating microtubule minus-end detachment from their organizing centers. The frequency of microtubule detachment in untreated cells increases at prophase suggesting that it is a regulated cellular process important for spindle assembly and function. We conclude that drugs produce differential dose-dependent effects at microtubule plus and minus-ends to inhibit different microtubule-mediated functions.     

The Reticular Cell Network: A Robust Backbone for Immune Responses

Lymph nodes are meeting points for circulating immune cells. A network of reticular cells that ensheathe a mesh of collagen fibers crisscrosses the tissue in each lymph node. This reticular cell network distributes key molecules and provides a structure for immune cells to move around on. During infections, the network can suffer damage. A new study has now investigated the network’s structure in detail, using methods from graph theory. The study showed that the network is remarkably robust to damage: it can still support immune responses even when half of the reticular cells are destroyed. This is a further important example of how network connectivity achieves tolerance to failure, a property shared with other important biological and nonbiological networks.Lymph nodes are critical sites for immune cells to connect, exchange information, and initiate responses to foreign invaders. More than 90% of the cells in each lymph node—the T and B lymphocytes of the adaptive immune system—only reside there temporarily and are constantly moving around as they search for foreign substances (antigen). When there is no infection, T and B cells migrate within distinct regions. But lymph node architecture changes dramatically when antigen is found, and an immune response is mounted. New blood vessels grow and recruit vast numbers of lymphocytes from the blood circulation. Antigen-specific cells divide and mature into “effector” immune cells. The combination of these two processes—increased influx of cells from outside and proliferation within—can make a lymph node grow 10-fold within only a few days [1]. Accordingly, the structural backbone supporting lymph node function cannot be too rigid; otherwise, it would impede this rapid organ expansion. This structural backbone is provided by a network of fibroblastic reticular cells (FRCs) [2], which secrete a form of collagen (type III alpha 1) that produces reticular fibers—thin, threadlike structures with a diameter of less than 1 μm. Reticular fibers cross-link and form a spider web–like structure. The FRCs surrounding this structure form the reticular cell network (Fig 1), which was first observed in the 1930s [3]. Interestingly, experiments in which the FRCs were destroyed showed that the collagen fiber network remained intact [4].Open in a separate windowFig 1Structure of the reticular cell network.The reticular cell network is formed by fibroblastic reticular cells (FRCs) whose cell membranes ensheathe a core of collagen fibers that acts as a conduit system for the distribution of small molecules [5]. In most other tissues, collagen fibers instead reside outside cell membranes, where they form the extracellular matrix. Inset: graph structure representing the FRCs in the depicted network as “nodes” (circles) and the direct connections between them as “edges” (lines). Shape and length of the fibers are not represented in the graph.Reticular cell networks do not only support lymph node structure; they are also important players in the immune response. Small molecules from the tissue environment or from pathogens, such as viral protein fragments, can be distributed within the lymph node through the conduit system formed by the reticular fibers [5]. Some cytokines and chemokines that are vital for effective T cell migration—and the nitric oxide that inhibits T cell proliferation [6]—are even produced by the FRCs themselves. Moreover, the network is thought of as a “road system” for lymphocyte migration [7]: in 2006, a seminal study found that lymphocytes roaming through lymph nodes were in contact with network fibers most of the time [8]. A few years before, it had become possible to observe lymphocyte migration in vivo by means of two-photon microscopy [9]. Movies from these experiments strikingly demonstrated that individual cells were taking very different paths, engaging in what appeared to be a “random walk.” But these movies did not show the structures surrounding the migrating cells, which created an impression of motion in empty space. Appreciating the role of the reticular cell network in this pattern of motion [8] suggested that the complex cell trajectories reflect the architecture of the network along which the cells walk.Given its important functions, it is surprising how little we know about the structure of the reticular cell network—compared to, for instance, our wealth of knowledge on neuron connectivity in the brain. In part this is because the reticular cells are hard to visualize. In vivo techniques like two-photon imaging do not provide sufficient resolution to reliably capture the fine-threaded mesh. Instead, thin tissue sections are stained with fluorescent antibodies that bind to the reticular fibers and are imaged with high-resolution confocal microscopy to reveal the network structure. One study [10] applied this method to determine basic parameters such as branch length and the size of gaps between fibers. Here, we discuss a recent study by Novkovic et al. [11] that took a different approach to investigating properties of the reticular cell network structure: they applied methods from graph theory.Graph theory is a classic subject in mathematics that is often traced back to Leonhard Euler’s stroll through 18th-century Königsberg, Prussia. Euler could not find a circular route that crossed each of the city’s seven bridges exactly once, and wondered how he could prove that such a route does not exist. He realized that this problem could be phrased in terms of a simple diagram containing points (parts of the city) and lines between them (bridges). Further detail, such as the layout of city’s streets, was irrelevant. This was the birth of graph theory—the study of objects consisting of points (nodes) connected by lines (edges). Graph theory has diverse applications ranging from logistics to molecular biology. Since the beginning of this century, there has been a strong interest in applying graph theory to understand the structure of networks that occur in nature—including biological networks, such as neurons in the brain, and more recently, social networks like friendships on Facebook. Various mathematical models of network structures have been developed in an attempt to understand network properties that are relevant in different contexts, such as the speed at which information spreads or the amount of damage that a network can tolerate before breaking into disconnected parts. Three well-known network topologies are random, small-world, and scale-free networks (Box 1). Novkovic et al. modeled reticular cell networks as graphs by considering each FRC to be a node and the fiber connections between FRCs to be edges (Fig 1).

Box 1. Graph Theory and the Robustness of Real Networks

After the publication of several landmark papers on network topology at the end of the previous century, the science of complex networks has grown explosively. One of these papers described “small-world” networks [16] and demonstrated that several natural networks have the amazing property that the average length of shortest paths between arbitrary nodes is unexpectedly small (making it a “small world”), even if most of the network nodes are clustered (that is, when neighbors of neighbors tend to be neighbors). The Barabasi group published a series of papers describing “scale-free” networks [17,18] and demonstrated that scale-free networks are extremely robust to random deletions of nodes—the vast majority of the nodes can be deleted before the network falls apart [15]. In scale-free networks, the number of edges per node is distributed according to a power law, implying that most nodes have very few connections, and a few nodes are hubs having very many connections. Thus, the topology of complex networks can be scale-free, small-world, or neither, such as with random networks [19]. Novkovic et al. [11] describe the clustering of the edges of neighbors and the average shortest path–length between arbitrary nodes, finding that reticular cell networks have small-world properties. Whether or not these networks have scale-free properties is not explicitly examined in the paper, but given that they are embedded in a three-dimensional space, that they “already” lose functionality when about 50% of the FRCs are ablated, and that the number of connected protrusions per FRC is not distributed according to a power law (see the data underlying their Figure 2g), reticular cell networks are not likely to be scale-free. Thus, the enhanced robustness of reticular cell networks is most likely due to their high local connectivity: Networks lose functionality when they fall apart in disconnected components, and high clustering means that the graph is unlikely to split apart when a single node is removed, because the neighbors of that node tend to stay connected [14]. Additionally, since the reticular cell network has a spatial structure (unlike the internet or the Facebook social network), its high degree of clustering is probably due to the preferential attachment to nearby FRCs when the network develops, which agrees well with Novkovic et al.’s recent classification as a small-world network with lattice-like properties [11].Some virus infections are known to damage reticular cell networks [12], either through infection of the FRCs or as a bystander effect of inflammation. It is therefore important to understand to what extent the network structure is able to survive partial destruction. Novkovic et al. first approached this question by performing computer simulations, in which they randomly removed FRC nodes from the networks they had reconstructed from microscopy images. They found that they had to remove at least half of the nodes to break the network apart into disconnected parts. To study the effect of damage on the reticular cell network in vivo rather than in silico, Novkovic et al. used an experimental technique called conditional cell ablation. In this technique, a gene encoding the diphtheria toxin receptor (DTR) is inserted after a specific promoter that leads it to be expressed in a particular cell type of interest. Administration of diphtheria toxin kills DTR-expressing cells, leaving other cells unaffected. By expressing DTR under the control of the FRC-specific Ccl19 promoter, Novkovic et al. were able to selectively destroy the reticular cell network and then watch it grow back over time. Regrowth took about four weeks, and the resulting network properties were no different from a network formed naturally during development. Thus, it seems that the reticular cell network structure is imprinted and reemerges even after severe damage. This finding ties in nicely with previous data from the same group [13], showing that reticular cell networks form even in the absence of lymphotoxin-beta receptor, an otherwise key player in many aspects of lymphoid tissue development. Together, these data make a compelling case that network formation is a robust fundamental trait of FRCs.Next, Novkovic et al. varied the dose of diphtheria toxin such that only a fraction of FRCs were destroyed, effectively removing a random subset of the network nodes. They measured in two ways how FRC loss affects the immune system: they tracked T cell migration using two-photon microscopy and they determined the amount of antiviral T cells produced by the mice after an infection. Remarkably, as predicted by their computer simulations, lymph nodes appeared capable of tolerating the loss of up to half of FRCs with little effect on either T cell migration or the numbers of activated antiviral T cells. Only when more than half of the FRCs were destroyed did T cell motion slow down significantly and the mice were no longer able to mount effective antiviral immune responses. Such a tolerance of damage is impressive—for comparison, consider what would happen if one were to close half of London’s subway stations!Robustness to damage is of interest for many different networks, from power grids to the internet [14]. In particular, the “scale-free” architecture that features rare, strongly connected “hub” nodes is highly robust to random damage [15]. Novkovic et al. did not address whether the reticular cell network is scale-free, but it is likely that it isn’t (Box 1). Instead, the network’s robustness probably arises from its high degree of clustering, which means that the neighbors of each node are likely to be themselves also neighbors. If a node is removed from a clustered network, then there is still likely a short detour available by going through two of the neighbors. Therefore, one would have to randomly remove a large fraction of the nodes before the network structure breaks down. High clustering in the network could be a consequence of the fact that multiple fibers extend from each FRC and establish connections to many FRCs in its vicinity. A question not yet addressed by Novkovic et al. is how robust reticular cell networks would be to nonrandom damage, such as a locally spreading viral infection. In fact, scale-free networks are drastically more vulnerable to targeted rather than random damage: the United States flight network can come to a grinding halt by closing a few hub airports [15]. Less is known about the robustness to nonrandom damage for other network architectures, and the findings by Novkovic et al. motivate future research in this direction.Novkovic et al. did not yet explicitly identify all mechanisms that hamper T cell responses when more than half of the FRCs are depleted. But given the reticular cell network’s many different functions, this could occur in several ways. For instance, severe depletion might prevent the secretion of important molecules, halt the migration of T cells, prevent the anchoring of antigen-presenting dendritic cells (DCs) on the network, or cause structural disarray in the tissue. In addition to the effects on T cell migration, Novkovic et al. also showed that the amount of DCs in fact decreased when FRCs were depleted, emphasizing that several mechanisms are likely at play. Disentangling these mechanisms will require substantial additional research efforts.The current reticular cell network reconstruction by Novkovic et al. is based on thin tissue slices. It will be exciting to study the network architecture when it can be visualized in the whole organ. Some aspects of the network may then look different. For instance, those FRCs that are near the border of a slice will have their degree of connectivity underestimated, as not all of their neighbors in the network can be seen. Further refinements of the network analysis may also consider that reticular fibers are real physical objects situated in a three-dimensional space (unlike abstract connections such as friendships). Migrating T cells may travel quicker via a short, straight fiber than on a long, curved one, but the network graph does not make this distinction. More generally, it would be interesting to understand conceptually how reticular cell networks help foster immune cell migration. While at first it appears obvious that having a “road system” should make it easier for cells to roam lymph node tissue, three different theoretical studies have in fact all concluded that effective T cell migration should also be possible in the absence of a network [20–22]. A related question is whether T cells are constrained to move only on the network or are merely using it for loose guidance. For instance, could migrating T cells be in contact with two or more network fibers at once or with none at all? This would make the relationship between cell migration and network structure more complex than the graph structure alone suggests.There is also some evidence that T cells can migrate according to what is called a Lévy walk [23]—a kind of random walk where frequent short steps are interspersed with few very long steps, a search strategy that appears to occur frequently in nature (though this is debated [24]). While there is so far no evidence that T cells perform a Lévy walk when roaming the lymph node [25], this may be in part due to limitations of two-photon imaging, and one could speculate that reticular cell networks might in fact be constructed in a way that facilitates this or another efficient kind of “search strategy.” Resolving this question will require substantial improvements in imaging technology, allowing individual T cells to be tracked across an entire lymph node.No doubt further studies will address these and other questions, and provide further insights on how reticular cell networks benefit immune responses. Such advances may help us design better treatments against infections that damage the network. It may also help us understand how we can best administer vaccines or tumor immune therapy treatments in a way that ensures optimal delivery to immune cells in the lymph node. As is nicely illustrated by the study of Novkovic et al., mathematical methods may well play key roles in this quest.     

Down-Regulation of Platelet Endothelial Cell Adhesion Molecule-1 Results in Thrombospondin-1 Expression and Concerted Regulation of Endothelial Cell Phenotype

bEND.3 cells are polyoma middle T-transformed mouse brain endothelial cells that express very little or no thrombospondin-1, a natural inhibitor of angiogenesis, but express high levels of platelet endothelial cell adhesion molecule-1 (PECAM-1) that localizes to sites of cell–cell contact. Here, we have examined the role of PECAM-1 in regulation of bEND.3 cell proliferation, migration, morphogenesis, and hemangioma formation. We show that down-regulating PECAM-1 expression by antisense transfection of bEND.3 cells has a dramatic effect on their morphology, proliferation, and morphogenesis on Matrigel. There is an optimal level for PECAM-1 expression such that high levels of PECAM-1 inhibit, whereas moderate levels of PECAM-1 stimulate, endothelial cell morphogenesis. The down-regulation of PECAM-1 in bEND.3 cells resulted in reexpression of endogenous thrombospondin-1 and its antiangiogenic receptor CD36. The expression of the vascular endothelial growth factor receptors flk-1 and flt-1, as well as integrins and metalloproteinases (which are involved in angiogenesis), were also affected. These observations are consistent with the changes observed in proliferation, migration, and adhesion characteristics of the antisense-transfected bEND.3 cells as well as with their lack of ability to form hemangiomas in mice. Thus, a reciprocal relationship exists between thrombospondin-1 and PECAM-1 expression, such that these two molecules appear to be constituents of a “switch” that regulates in concert many components of the angiogenic and differentiated phenotypes of endothelial cells.     

Cell interactions and histogenesis in embryonic neural aggregates

Mixtures of cell suspensions from the optic lobe of 3-day-old and 6-day-old chick embryos form aggregates which show many ‘rosettes’ resulting from the invagination of peripheral ‘placodes’. However, in aggregates formed exclusively by optic lobe cells of either 3-day-old or 6-day-old embryos no rosettes are observed. By means of radioautographic studies of the combined aggregates, it was shown that rosettes are formed almost exclusively by cells from 3-day-old optic lobe, while those of 6-day-old embryos are predominantly found at the periphery of the aggregates. Cells from 3-day old optic lobe also form rosettes when cultured in combination with wing cells. Similar observations were done in aggregates formed by mixtures of 3-day-old optic lobe and 6-day-old liver cells. The cells from the optic lobe of 3-day-old embryos forming the concave surface of invaginating placodes and rosettes in the ‘combined’ aggregates appear polarized and wedge- or ‘bottle’-shaped. They are aligned in a highly ordered way, and abundant zonula adhaerentes, usually parallel to the cell major axis, are found at the cell apex where bundles of longitudinally oriented microtubules are present. The 3-day-old optic lobe cell which form the convex external surface of the ‘pure’ aggregates have a similar shape and organization, but in this situation apical cell bulges with randomly oriented microtubules interdigitate with those from neighbouring cells, and are joined by zonula adhaerentes usually perpendicular to the longitudinal axis of the cell.     

Collective Cell Migration Drives Morphogenesis of the Kidney Nephron

Tissue organization in epithelial organs is achieved during development by the combined processes of cell differentiation and morphogenetic cell movements. In the kidney, the nephron is the functional organ unit. Each nephron is an epithelial tubule that is subdivided into discrete segments with specific transport functions. Little is known about how nephron segments are defined or how segments acquire their distinctive morphology and cell shape. Using live, in vivo cell imaging of the forming zebrafish pronephric nephron, we found that the migration of fully differentiated epithelial cells accounts for both the final position of nephron segment boundaries and the characteristic convolution of the proximal tubule. Pronephric cells maintain adherens junctions and polarized apical brush border membranes while they migrate collectively. Individual tubule cells exhibit basal membrane protrusions in the direction of movement and appear to establish transient, phosphorylated Focal Adhesion Kinase–positive adhesions to the basement membrane. Cell migration continued in the presence of camptothecin, indicating that cell division does not drive migration. Lengthening of the nephron was, however, accompanied by an increase in tubule cell number, specifically in the most distal, ret1-positive nephron segment. The initiation of cell migration coincided with the onset of fluid flow in the pronephros. Complete blockade of pronephric fluid flow prevented cell migration and proximal nephron convolution. Selective blockade of proximal, filtration-driven fluid flow shifted the position of tubule convolution distally and revealed a role for cilia-driven fluid flow in persistent migration of distal nephron cells. We conclude that nephron morphogenesis is driven by fluid flow–dependent, collective epithelial cell migration within the confines of the tubule basement membrane. Our results establish intimate links between nephron function, fluid flow, and morphogenesis.     

CAS/Crk Coupling Serves as a “Molecular Switch” for Induction of Cell Migration

Abstract. Carcinoma cells selected for their ability to migrate in vitro showed enhanced invasive properties in vivo. Associated with this induction of migration was the anchorage-dependent phosphorylation of p130CAS (Crk-associated substrate), leading to its coupling to the adaptor protein c-CrkII (Crk). In fact, expression of CAS or its adaptor protein partner Crk was sufficient to promote cell migration, and this depended on CAS tyrosine phosphorylation facilitating an SH2-mediated complex with Crk. Cytokine-stimulated cell migration was blocked by CAS lacking the Crk binding site or Crk containing a mutant SH2 domain. This migration response was characterized by CAS/Crk localization to membrane ruffles and blocked by the dominant-negative GTPase, Rac, but not Ras. Thus, CAS/Crk assembly serves as a “molecular switch” for the induction of cell migration and appears to contribute to the invasive property of tumors.     

Spontaneous Epithelial-Mesenchymal Transition and Resistance to HER-2-Targeted Therapies in HER-2-Positive Luminal Breast Cancer

Resistance to trastuzumab, a rationally designed HER-2-targeting antibody, remains a major hurdle in the management of HER-2-positive breast cancer. Preclinical studies suggest the mechanisms of trastuzumab resistance are numerous. Unfortunately, the majority of these studies are based around HER-2-positive (HER-2+) luminal cell lines. The role of epithelial to mesenchymal transition (EMT), a genetic program that confers a basal phenotype, may represent a novel mechanism of escape for HER-2+ luminal cells from trastuzumab treatment. Here we investigated this possibility using a model of clonal selection in HER-2+ luminal breast cancer cells. Following a random isolation and expansion of “colony clusters” from SKBR-3 cell lines, several colony clusters underwent a spontaneous EMT in-vitro. In addition to expression of conventional EMT markers, all mesenchymal colony clusters displayed a predominant CD44+/CD24- phenotype with decreased HER-2 expression and elevated levels of a β1-integrin isoform with a high degree of N-glycosylation. Treatment with a β1-integrin function-blocking antibody, AIIB2, preferentially decreased the N-glycosylated form of β1-integrin, impaired mammosphere formation and restored epithelial phenotype in mesenchymal colony clusters. Using this model we provide the first clear evidence that resistance to trastuzumab (and lapatinib) can occur spontaneously as HER-2+ cells shift from a luminal to a basal/mesenchymal phenotype following EMT. While the major determinant of trastuzumab resistance in mesenchymal colony clusters is likely the down regulation of the HER-2 protein, our evidence suggests that multiple factors may contribute, including expression of N-glycosylated β1-integrin.     

Interleukin-15 Dendritic Cells Harness NK Cell Cytotoxic Effector Function in a Contact- and IL-15-Dependent Manner

The contribution of natural killer (NK) cells to the treatment efficacy of dendritic cell (DC)-based cancer vaccines is being increasingly recognized. Much current efforts to optimize this form of immunotherapy are therefore geared towards harnessing the NK cell-stimulatory ability of DCs. In this study, we investigated whether generation of human monocyte-derived DCs with interleukin (IL)-15 followed by activation with a Toll-like receptor stimulus endows these DCs, commonly referred to as “IL-15 DCs”, with the capacity to stimulate NK cells. In a head-to-head comparison with “IL-4 DCs” used routinely for clinical studies, IL-15 DCs were found to induce a more activated, cytotoxic effector phenotype in NK cells, in particular in the CD56^bright NK cell subset. With the exception of GM-CSF, no significant enhancement of cytokine/chemokine secretion was observed following co-culture of NK cells with IL-15 DCs. IL-15 DCs, but not IL-4 DCs, promoted NK cell tumoricidal activity towards both NK-sensitive and NK-resistant targets. This effect was found to require cell-to-cell contact and to be mediated by DC surface-bound IL-15. This study shows that DCs can express a membrane-bound form of IL-15 through which they enhance NK cell cytotoxic function. The observed lack of membrane-bound IL-15 on “gold-standard” IL-4 DCs and their consequent inability to effectively promote NK cell cytotoxicity may have important implications for the future design of DC-based cancer vaccine studies.     

Where to Go: Breaking the Symmetry in Cell Motility

Cell migration in the “correct” direction is pivotal for many biological processes. Although most work is devoted to its molecular mechanisms, the cell’s preference for one direction over others, thus overcoming intrinsic random motility, epitomizes a profound principle that underlies all complex systems: the choice of one axis, in structure or motion, from a uniform or symmetric set of options. Explaining directional motility by an external chemo-attractant gradient does not solve but only shifts the problem of causation: whence the gradient? A new study in PLOS Biology shows cell migration in a self-generated gradient, offering an opportunity to take a broader look at the old dualism of extrinsic instruction versus intrinsic symmetry-breaking in cell biology.

When you come to a fork in the road, take it.–Yogi Berra 1925–2015