Multicellular Computing Using Conjugation for Wiring

Recent efforts in synthetic biology have focussed on the implementation of logical functions within living cells. One aim is to facilitate both internal “re-programming” and external control of cells, with potential applications in a wide range of domains. However, fundamental limitations on the degree to which single cells may be re-engineered have led to a growth of interest in multicellular systems, in which a “computation” is distributed over a number of different cell types, in a manner analogous to modern computer networks. Within this model, individual cell type perform specific sub-tasks, the results of which are then communicated to other cell types for further processing. The manner in which outputs are communicated is therefore of great significance to the overall success of such a scheme. Previous experiments in distributed cellular computation have used global communication schemes, such as quorum sensing (QS), to implement the “wiring” between cell types. While useful, this method lacks specificity, and limits the amount of information that may be transferred at any one time. We propose an alternative scheme, based on specific cell-cell conjugation. This mechanism allows for the direct transfer of genetic information between bacteria, via circular DNA strands known as plasmids. We design a multi-cellular population that is able to compute, in a distributed fashion, a Boolean XOR function. Through this, we describe a general scheme for distributed logic that works by mixing different strains in a single population; this constitutes an important advantage of our novel approach. Importantly, the amount of genetic information exchanged through conjugation is significantly higher than the amount possible through QS-based communication. We provide full computational modelling and simulation results, using deterministic, stochastic and spatially-explicit methods. These simulations explore the behaviour of one possible conjugation-wired cellular computing system under different conditions, and provide baseline information for future laboratory implementations.     

Learning the rules of collective cell migration using deep attention networks

Collective, coordinated cellular motions underpin key processes in all multicellular organisms, yet it has been difficult to simultaneously express the ‘rules’ behind these motions in clear, interpretable forms that effectively capture high-dimensional cell-cell interaction dynamics in a manner that is intuitive to the researcher. Here we apply deep attention networks to analyze several canonical living tissues systems and present the underlying collective migration rules for each tissue type using only cell migration trajectory data. We use these networks to learn the behaviors of key tissue types with distinct collective behaviors—epithelial, endothelial, and metastatic breast cancer cells—and show how the results complement traditional biophysical approaches. In particular, we present attention maps indicating the relative influence of neighboring cells to the learned turning decisions of a ‘focal cell’–the primary cell of interest in a collective setting. Colloquially, we refer to this learned relative influence as ‘attention’, as it serves as a proxy for the physical parameters modifying the focal cell’s future motion as a function of each neighbor cell. These attention networks reveal distinct patterns of influence and attention unique to each model tissue. Endothelial cells exhibit tightly focused attention on their immediate forward-most neighbors, while cells in more expansile epithelial tissues are more broadly influenced by neighbors in a relatively large forward sector. Attention maps of ensembles of more mesenchymal, metastatic cells reveal completely symmetric attention patterns, indicating the lack of any particular coordination or direction of interest. Moreover, we show how attention networks are capable of detecting and learning how these rules change based on biophysical context, such as location within the tissue and cellular crowding. That these results require only cellular trajectories and no modeling assumptions highlights the potential of attention networks for providing further biological insights into complex cellular systems.     

Cancer Cell Invasion in Three-dimensional Collagen Is Regulated Differentially by Gα13 Protein and Discoidin Domain Receptor 1-Par3 Protein Signaling

Cancer cells can invade in three-dimensional collagen as single cells or as a cohesive group of cells that require coordination of cell-cell junctions and the actin cytoskeleton. To examine the role of Gα₁₃, a G₁₂ family heterotrimeric G protein, in regulating cellular invasion in three-dimensional collagen, we established a novel method to track cell invasion by membrane type 1 matrix metalloproteinase-expressing cancer cells. We show that knockdown of Gα₁₃ decreased membrane type 1 matrix metalloproteinase-driven proteolytic invasion in three-dimensional collagen and enhanced E-cadherin-mediated cell-cell adhesion. E-cadherin knockdown reversed Gα₁₃ siRNA-induced cell-cell adhesion but failed to reverse the effect of Gα₁₃ siRNA on proteolytic invasion. Instead, concurrent knockdown of E-cadherin and Gα₁₃ led to an increased number of single cells rather than groups of cells. Significantly, knockdown of discoidin domain receptor 1 (DDR1), a collagen-binding protein that also co-localizes to cell-cell junctions, reversed the effects of Gα₁₃ knockdown on cell-cell adhesion and proteolytic invasion in three-dimensional collagen. Knockdown of the polarity protein Par3, which can function downstream of DDR1, also reversed the effects of Gα₁₃ knockdown on cell-cell adhesion and proteolytic invasion in three-dimensional collagen. Overall, we show that Gα₁₃ and DDR1-Par3 differentially regulate cell-cell junctions and the actin cytoskeleton to mediate invasion in three-dimensional collagen.     

Influence of confinement on the spreading of bacterial populations

The spreading of bacterial populations is central to processes in agriculture, the environment, and medicine. However, existing models of spreading typically focus on cells in unconfined settings—despite the fact that many bacteria inhabit complex and crowded environments, such as soils, sediments, and biological tissues/gels, in which solid obstacles confine the cells and thereby strongly regulate population spreading. Here, we develop an extended version of the classic Keller-Segel model of bacterial spreading via motility that also incorporates cellular growth and division, and explicitly considers the influence of confinement in promoting both cell-solid and cell-cell collisions. Numerical simulations of this extended model demonstrate how confinement fundamentally alters the dynamics and morphology of spreading bacterial populations, in good agreement with recent experimental results. In particular, with increasing confinement, we find that cell-cell collisions increasingly hinder the initial formation and the long-time propagation speed of chemotactic pulses. Moreover, also with increasing confinement, we find that cellular growth and division plays an increasingly dominant role in driving population spreading—eventually leading to a transition from chemotactic spreading to growth-driven spreading via a slower, jammed front. This work thus provides a theoretical foundation for further investigations of the influence of confinement on bacterial spreading. More broadly, these results help to provide a framework to predict and control the dynamics of bacterial populations in complex and crowded environments.     

Microfabricated Post-Array-Detectors (mPADs): an Approach to Isolate Mechanical Forces

In this video, we will present our approach to measure cellular traction forces using a microfabricated array of posts. Traction forces are generated through myosin-actin interactions and play an important role in our physiology. During development, they enable cells to move from one location to the next in order to form the early structures of tissue. Traction forces help in the healing processes. They are necessary for the proper closure of wounds or the migration and crawling of leukocytes through our body. These same forces can be detrimental to our health in the case of cancer metastasis or vascular growth towards a tumor. The most common method by which to study cells in vitro has been to use a glass or polystyrene dish. However, the rigidity of the substrates makes it impossible to physically measure cell traction forces, and there are relatively few methods to study traction forces. Our lab has developed a technique to overcome these limitations. The method is based on a vertical array of flexible cantilevers, the stiffness and size scale of which are such that individual cells spread across many cantilevers and deflect them in the process. The pillars we use are 3 μm in diameter, 10 μm tall, and are configured in a regular array with 9 μm center-to-center spacing. But these physical dimensions can be readily varied to accommodate a variety of studies. We start with a silicon master, but the final posts are made out of silicone rubber called poly (dimethyl siloxane), or PDMS. We can measure the deflections under a microscope and calculate the magnitude and direction of traction forces required to produce the observed deflections. We call these substrates microfabricated post-array-detectors, or mPADs. Here, we will show you how we fabricate and use the mPADs to assess modulations of cellular contractility.     

Tube formation by complex cellular processes in Ciona intestinalis notochord

In the course of embryogenesis multicellular structures and organs are assembled from constituent cells. One structural component common to many organs is the tube, which consists most simply of a luminal space surrounded by a single layer of epithelial cells. The notochord of ascidian Ciona forms a tube consisting of only 40 cells, and serves as a hydrostatic “skeleton” essential for swimming. While the early processes of convergent extension in ascidian notochord development have been extensively studied, the later phases of development, which include lumen formation, have not been well characterized. Here we used molecular markers and confocal imaging to describe tubulogenesis in the developing Ciona notochord. We found that during tubulogenesis each notochord cell established de novo apical domains, and underwent a mesenchymal–epithelial transition to become an unusual epithelial cell with two opposing apical domains. Concomitantly, extracellular luminal matrix was produced and deposited between notochord cells. Subsequently, each notochord cell simultaneously executed two types of crawling movements bi-directionally along the anterior/posterior axis on the inner surface of notochordal sheath. Lamellipodia-like protrusions resulted in cell lengthening along the anterior/posterior axis, while the retraction of trailing edges of the same cell led to the merging of the two apical domains. As a result, the notochord cells acquired endothelial-like shape and formed the wall of the central lumen. Inhibition of actin polymerization prevented the cell movement and tube formation. Ciona notochord tube formation utilized an assortment of common and fundamental cellular processes including cell shape change, apical membrane biogenesis, cell/cell adhesion remodeling, dynamic cell crawling, and lumen matrix secretion.     

Flotillins Directly Interact with γ-Catenin and Regulate Epithelial Cell-Cell Adhesion

Flotillin-1 and flotillin-2 are two homologous, membrane raft associated proteins. Although it has been reported that flotillins are involved in cell adhesion processes and play a role during breast cancer progression, thus making them interesting future therapeutic targets, their precise function has not been well elucidated. The present study investigates the function of these proteins in cell-cell adhesion in non-malignant cells. We have used the non-malignant epithelial MCF10A cells to study the interaction network of flotillins within cell-cell adhesion complexes. RNA interference was used to examine the effect of flotillins on the structure of adherens junctions and on the association of core proteins, such as E-cadherin, with membrane rafts. We here show that the cadherin proteins of the adherens junction associate with flotillin-2 in MCF10A cells and in various human cell lines. In vitro, flotillin-1 and flotillin-2 directly interact with γ-catenin which is so far the only protein known to be present both in the adherens junction and the desmosome. Mapping of the interaction domain within the γ-catenin sequence identified the Armadillo domains 6–8, especially ARM domain 7, to be important for the association with flotillins. Furthermore, depletion of flotillins significantly influenced the morphology of the adherens junction in human epithelial MCF10A cells and altered the association of E-cadherin and γ-catenin with membrane rafts. Taken together, these observations suggest a functional role for flotillins, especially flotillin-2, in cell-cell adhesion in non-malignant epithelial cells.     

Epithelial apoptosis

Apoptosis is an essential part of the normal cellular phenotype repertoire. In the absence of appropriate survival factors, apoptosis is activated through specific signalling cassettes. Epithelia form distinctive three-dimensional cohesive structures that depend on adhesive interactions in order for these tissues to carry out their specialised roles, such as secretion and reproduction. The cellular programme that triggers apoptosis in epithelial cells has not yet been shown to differ from that in other cell types, yet the unique characteristics of epithelia endow them with specific determinants for survival. In particular, cell-matrix and cell-cell interactions are required to prevent entry of epithelial cells into apoptosis, and soluble factors that have profound effects on epithelia, such as steroid hormones or hepatocyte growth factor, also influence their survival. The regenerative capacity of certain epithelia is controlled by intrinsic expression of survival genes within stem cell populations, and may regulate the susceptibility of different epithelial tissues to undergo carcinogenesis.     

Fat-Dachsous Signaling Coordinates Cartilage Differentiation and Polarity during Craniofacial Development

Organogenesis requires coordinated regulation of cellular differentiation and morphogenesis. Cartilage cells in the vertebrate skeleton form polarized stacks, which drive the elongation and shaping of skeletal primordia. Here we show that an atypical cadherin, Fat3, and its partner Dachsous-2 (Dchs2), control polarized cell-cell intercalation of cartilage precursors during craniofacial development. In zebrafish embryos deficient in Fat3 or Dchs2, chondrocytes fail to stack and misregulate expression of sox9a. Similar morphogenetic defects occur in rerea/atr2a ^−/− mutants, and Fat3 binds REREa, consistent with a model in which Fat3, Dchs2 and REREa interact to control polarized cell-cell intercalation and simultaneously control differentiation through Sox9. Chimaeric analyses support such a model, and reveal long-range influences of all three factors, consistent with the activation of a secondary signal that regulates polarized cell-cell intercalation. This coordinates the spatial and temporal morphogenesis of chondrocytes to shape skeletal primordia and defects in these processes underlie human skeletal malformations. Similar links between cell polarity and differentiation mechanisms are also likely to control organ formation in other contexts.     

Cellular “bauplans”: Evolving unicellular forms by means of Julia sets and Pickover biomorphs

The universe of cellular forms has received scarce attention by mainstream neo-Darwinian views. The possibility that a fundamental trait of biological order may consist upon, or be guided by, developmental processes not completely amenable to natural selection was more akin to previous epochs of biological thought, i.e. the “bauplan” discussion. Thirty years ago, however, Lynn and Tucker studied the biological mechanisms responsible for defining organelles position inside cells. The fact that differentiated structures performing a specific function within the eukaryotic cell (i.e. mitochondrion, vacuole, or chloroplast) were occupying specific positions in the protoplasm was the observational and experimental support of the ‘morphogenetic field’ notion at the cellular level. In the present paper we study the morphogenetic field evolution yielding from an initial population of undifferentiated cells to diversified unicellular organisms as well as specialized eukaryotic cell types. The cells are represented as Julia sets and Pickover biomorphs, simulating the effect of Darwinian natural selection with a simple genetic algorithm. The morphogenetic field “defines” the locations where cells are differentiated or sub-cellular components (or organelles) become organized. It may be realized by different possibilities, one of them by diffusing chemicals along the Turing model. We found that Pickover cells show a higher diversity of size and form than those populations evolved as Julia sets. Another novelty is the way that cellular organelles and cell nucleus fill in the cell, always in dependence on the previous cell definition as Julia set or Pickover biomorph. Our findings support the existence of specific attractors representing the functional and stable form of a differentiated cell—genuine cellular bauplans. The configuration of the morphogenetic field is “attracted” towards one or another attractor depending on the environmental influences as modeled by a particular fitness function. The model promotes the classical discussions of D’Arcy Thompson and the more recent views of Waddington, Goodwin and others that consider organisms as dynamical systems that evolve through a ‘master plan’ of transformations, amenable to natural selection. Intriguingly, the model also connects with current developments on mechanobiology, highlighting the informational–developmental role that cytoskeletons may play.     

Binding between the Junctional Proteins Afadin and PLEKHA7 and Implication in the Formation of Adherens Junction in Epithelial Cells

Adherens junction (AJ) is a specialized cell-cell junction structure that plays a role in mechanically connecting adjacent cells to resist strong contractile forces and to maintain tissue structure, particularly in the epithelium. AJ is mainly comprised of cell adhesion molecules cadherin and nectin and their associating cytoplasmic proteins including β-catenin, α-catenin, p120^ctn, and afadin. Our series of studies have revealed that nectin first forms cell-cell adhesion and then recruits cadherin to form AJ. The recruitment of cadherin by nectin is mediated by the binding of α-catenin and p120^ctn to afadin. Recent studies showed that PLEKHA7 binds to p120^ctn, which is associated with E-cadherin, and maintains the integrity of AJ in epithelial cells. In this study, we showed that PLEKHA7 bound to afadin in addition to p120^ctn and was recruited to the nectin-3α-based cell-cell adhesion site in a manner dependent on afadin, but not on p120^ctn. The binding of PLEKHA7 to afadin was required for the proper formation of AJ, but not for the formation of tight junction, in EpH4 mouse mammary gland epithelial cells. These results indicate that PLEKHA7 plays a cooperative role with nectin and afadin in the proper formation of AJ in epithelial cells.     

Robust Inference of Cell-to-Cell Expression Variations from Single- and K-Cell Profiling

Quantifying heterogeneity in gene expression among single cells can reveal information inaccessible to cell-population averaged measurements. However, the expression level of many genes in single cells fall below the detection limit of even the most sensitive technologies currently available. One proposed approach to overcome this challenge is to measure random pools of k cells (e.g., 10) to increase sensitivity, followed by computational “deconvolution” of cellular heterogeneity parameters (CHPs), such as the biological variance of single-cell expression levels. Existing approaches infer CHPs using either single-cell or k-cell data alone, and typically within a single population of cells. However, integrating both single- and k-cell data may reap additional benefits, and quantifying differences in CHPs across cell populations or conditions could reveal novel biological information. Here we present a Bayesian approach that can utilize single-cell, k-cell, or both simultaneously to infer CHPs within a single condition or their differences across two conditions. Using simulated as well as experimentally generated single- and k-cell data, we found situations where each data type would offer advantages, but using both together can improve precision and better reconcile CHP information contained in single- and k-cell data. We illustrate the utility of our approach by applying it to jointly generated single- and k-cell data to reveal CHP differences in several key inflammatory genes between resting and inflammatory cytokine-activated human macrophages, delineating differences in the distribution of ‘ON’ versus ‘OFF’ cells and in continuous variation of expression level among cells. Our approach thus offers a practical and robust framework to assess and compare cellular heterogeneity within and across biological conditions using modern multiplexed technologies.     

Single Cell Analysis of a Bacterial Sender-Receiver System

Monitoring gene expression dynamics on the single cell level provides important information on cellular heterogeneity and stochasticity, and potentially allows for more accurate quantitation of gene expression processes. We here study bacterial senders and receivers genetically engineered with components of the quorum sensing system derived from Aliivibrio fischeri on the single cell level using microfluidics-based bacterial chemostats and fluorescence video microscopy. We track large numbers of bacteria over extended periods of time, which allows us to determine bacterial lineages and filter out subpopulations within a heterogeneous population. We quantitatively determine the dynamic gene expression response of receiver bacteria to varying amounts of the quorum sensing inducer N-3-oxo-C6-homoserine lactone (AHL). From this we construct AHL response curves and characterize gene expression dynamics of whole bacterial populations by investigating the statistical distribution of gene expression activity over time. The bacteria are found to display heterogeneous induction behavior within the population. We therefore also characterize gene expression in a homogeneous bacterial subpopulation by focusing on single cell trajectories derived only from bacteria with similar induction behavior. The response at the single cell level is found to be more cooperative than that obtained for the heterogeneous total population. For the analysis of systems containing both AHL senders and receiver cells, we utilize the receiver cells as ‘bacterial sensors’ for AHL. Based on a simple gene expression model and the response curves obtained in receiver-only experiments, the effective AHL concentration established by the senders and their ‘sending power’ is determined.     

Tumour promoter-mediated reversible inhibition of cell-cell communication (electrical coupling) : Relationship with phorbol ester binding and de novo macromolecule synthesis

A tumour promoter, 12-O-tetradecanoyl phorbol-13-acetate (TPA), reversibly inhibits the onset and maintenance of cell-cell communication measured by electrophysiological method. We have now studied the mechanism by which TPA inhibits communication of human cells (FL) in culture. Using [³H]phorbol-12,13-dibutyrate ([³H]PDBu), we found a class of specific, high-affinity, saturable binding sites in intact FL cells; they have a dissociation constant of 15.4 nM, and at saturation about 3 × 10⁵ PDBu molecules were bound to each cell. The binding of [³H]PDBu to FL cells was inhibited by TPA, phorbol-12-13-didecanoate and mezerein, whereas phorbol and 4α-phorbol-12-13-didecanoate had no effect. There is a close correlation between the ability of the former compounds to inhibit [³H]PDBu binding and their capacity to inhibit cell-cell communication. When FL cells are dispersed with EDTA and plated onto a culture dish, they start to couple electrically within 2 h; such cell coupling was not affected by the presence of cycloheximide or actinomycin D. TPA inhibits the formation of electrical cell coupling as well as its maintenance, even in the presence of cycloheximide; the recovery of cell-cell communication after the removal of TPA was not significantly affected by the addition of cycloheximide or actinomycin D. Taken together, these results suggest that TPA-mediated reversible inhibition of intercellular communication is mediated by specific binding of TPA to cellular receptors and that macromolecular synthesis is not necessary.     

Toxoplasma gondii Development of Its Replicative Niche: in Its Host Cell and Beyond

Intracellular pathogens can replicate efficiently only after they manipulate and modify their host cells to create an environment conducive to replication. While diverse cellular pathways are targeted by different pathogens, metabolism, membrane and cytoskeletal architecture formation, and cell death are the three primary cellular processes that are modified by infections. Toxoplasma gondii is an obligate intracellular protozoan that infects ∼30% of the world''s population and causes severe and life-threatening disease in developing fetuses, in immune-comprised patients, and in certain otherwise healthy individuals who are primarily found in South America. The high prevalence of Toxoplasma in humans is in large part a result of its ability to modulate these three host cell processes. Here, we highlight recent work defining the mechanisms by which Toxoplasma interacts with these processes. In addition, we hypothesize why some processes are modified not only in the infected host cell but also in neighboring uninfected cells.     

Collective Signal Processing in Cluster Chemotaxis: Roles of Adaptation,Amplification, and Co-attraction in Collective Guidance

Single eukaryotic cells commonly sense and follow chemical gradients, performing chemotaxis. Recent experiments and theories, however, show that even when single cells do not chemotax, clusters of cells may, if their interactions are regulated by the chemoattractant. We study this general mechanism of “collective guidance” computationally with models that integrate stochastic dynamics for individual cells with biochemical reactions within the cells, and diffusion of chemical signals between the cells. We show that if clusters of cells use the well-known local excitation, global inhibition (LEGI) mechanism to sense chemoattractant gradients, the speed of the cell cluster becomes non-monotonic in the cluster’s size—clusters either larger or smaller than an optimal size will have lower speed. We argue that the cell cluster speed is a crucial readout of how the cluster processes chemotactic signals; both amplification and adaptation will alter the behavior of cluster speed as a function of size. We also show that, contrary to the assumptions of earlier theories, collective guidance does not require persistent cell-cell contacts and strong short range adhesion. If cell-cell adhesion is absent, and the cluster cohesion is instead provided by a co-attraction mechanism, e.g. chemotaxis toward a secreted molecule, collective guidance may still function. However, new behaviors, such as cluster rotation, may also appear in this case. Co-attraction and adaptation allow for collective guidance that is robust to varying chemoattractant concentrations while not requiring strong cell-cell adhesion.     

αE-catenin regulates cell-cell adhesion and membrane blebbing during zebrafish epiboly

αE-catenin is an actin-binding protein associated with the E-cadherin-based adherens junction that regulates cell-cell adhesion. Recent studies identified additional E-cadherin-independent roles of αE-catenin in regulating plasma membrane dynamics and cell migration. However, little is known about the roles of αE-catenin in these different cellular processes in vivo during early vertebrate development. Here, we examined the functions of αE-catenin in cell-cell adhesion, cell migration and plasma membrane dynamics during morphogenetic processes that drive epiboly in early Danio rerio (zebrafish) development. We show that depletion of αE-catenin caused a defect in radial intercalation that was associated with decreased cell-cell adhesion, in a similar manner to E-cadherin depletion. Depletion of αE-catenin also caused deep cells to have protracted plasma membrane blebbing, and a defect in plasma membrane recruitment of ERM proteins that are involved in controlling membrane-to-cortex attachment and membrane blebbing. Significantly, depletion of both E-cadherin and αE-catenin suppressed plasma membrane blebbing. We suggest that during radial intercalation the activities of E-cadherin and αE-catenin in the maintenance of membrane-to-cortex attachment are balanced, resulting in stabilization of cell-cell adhesion and suppression of membrane blebbing, thereby enabling proper radial intercalation.