Optogenetic Control of Bacterial Cell-Cell Adhesion Dynamics: Unraveling the Influence on Biofilm Architecture and Functionality.

The transition of bacteria from an individualistic to a biofilm lifestyle profoundly alters their biology. During biofilm development, the bacterial cell-cell adhesions are a major determinant of initial microcolonies, which serve as kernels for the subsequent microscopic and mesoscopic structure of the biofilm, and determine the resulting functionality. In this study, the significance of bacterial cell-cell adhesion dynamics on bacterial aggregation and biofilm maturation is elucidated. Using photoswitchable adhesins between bacteria, modifying the dynamics of bacterial cell-cell adhesions with periodic dark-light cycles is systematic. Dynamic cell-cell adhesions with liquid-like behavior improve bacterial aggregation and produce more compact microcolonies than static adhesions with solid-like behavior in both experiments and individual-based simulations. Consequently, dynamic cell-cell adhesions give rise to earlier quorum sensing activation, better intermixing of different bacterial populations, improved biofilm maturation, changes in the growth of cocultures, and higher yields in fermentation. The here presented approach of tuning bacterial cell-cell adhesion dynamics opens the door for regulating the structure and function of biofilms and cocultures with potential biotechnological applications.

Branched actin cortices reconstituted in vesicles sense membrane curvature.

The actin cortex is a complex cytoskeletal machinery that drives and responds to changes in cell shape. It must generate or adapt to plasma membrane curvature to facilitate diverse functions such as cell division, migration, and phagocytosis. Due to the complex molecular makeup of the actin cortex, it remains unclear whether actin networks are inherently able to sense and generate membrane curvature, or whether they rely on their diverse binding partners to accomplish this. Here, we show that curvature sensing is an inherent capability of branched actin networks nucleated by Arp2/3 and VCA. We develop a robust method to encapsulate actin inside giant unilamellar vesicles (GUVs) and assemble an actin cortex at the inner surface of the GUV membrane. We show that actin forms a uniform and thin cortical layer when present at high concentration and distinct patches associated with negative membrane curvature at low concentration. Serendipitously, we find that the GUV production method also produces dumbbell-shaped GUVs, which we explain using mathematical modeling in terms of membrane hemifusion of nested GUVs. We find that branched actin networks preferentially assemble at the neck of the dumbbells, which possess a micrometer-range convex curvature comparable with the curvature of the actin patches found in spherical GUVs. Minimal branched actin networks can thus sense membrane curvature, which may help mammalian cells to robustly recruit actin to curved membranes to facilitate diverse cellular functions such as cytokinesis and migration.

Membrane area gain and loss during cytokinesis.

In cytokinesis of animal cells, the cell is symmetrically divided into two. Since the cell's volume is conserved, the projected area has to increase to allow for the change of shape. Here we aim to predict how membrane gain and loss adapt during cytokinesis. We work with a kinetic model in which membrane turnover depends on membrane tension and cell shape. We apply this model to a series of calculated vesicle shapes as a proxy for the shape of dividing cells. We find that the ratio of kinetic turnover parameters changes nonmonotonically with cell shape, determined by the dependence of exocytosis and endocytosis on membrane curvature. Our results imply that controlling membrane turnover will be crucial for the successful division of artificial cells.

A gastruloid model of the interaction between embryonic and extra-embryonic cell types.

Stem-cell derived in vitro systems, such as organoids or embryoids, hold great potential for modeling in vivo development. Full control over their initial composition, scalability, and easily measurable dynamics make those systems useful for studying specific developmental processes in isolation. Here we report the formation of gastruloids consisting of mouse embryonic stem cells (mESCs) and extraembryonic endoderm (XEN) cells. These XEN-enhanced gastruloids (XEGs) exhibit the formation of neural epithelia, which are absent in gastruloids derived from mESCs only. By single-cell RNA-seq, imaging, and differentiation experiments, we demonstrate the neural characteristics of the epithelial tissue. We further show that the mESCs induce the differentiation of the XEN cells to a visceral endoderm-like state. Finally, we demonstrate that local inhibition of WNT signaling and production of a basement membrane by the XEN cells underlie the formation of the neuroepithelial tissue. In summary, we establish XEGs to explore heterotypic cellular interactions and their developmental consequences in vitro.

CRISPR-based DNA and RNA detection with liquid-liquid phase separation.

The ability to detect specific nucleic acid sequences allows for a wide range of applications such as the identification of pathogens, clinical diagnostics, and genotyping. CRISPR-Cas proteins Cas12a and Cas13a are RNA-guided endonucleases that bind and cleave specific DNA and RNA sequences, respectively. After recognition of a target sequence, both enzymes activate indiscriminate nucleic acid cleavage, which has been exploited for sequence-specific molecular diagnostics of nucleic acids. Here, we present a label-free detection approach that uses a readout based on solution turbidity caused by liquid-liquid phase separation (LLPS). Our approach relies on the fact that the LLPS of oppositely charged polymers requires polymers to be longer than a critical length. This length dependence is predicted by the Voorn-Overbeek model, which we describe in detail and validate experimentally in mixtures of polynucleotides and polycations. We show that the turbidity resulting from LLPS can be used to detect the presence of specific nucleic acid sequences by employing the programmable CRISPR-nucleases Cas12a and Cas13a. Because LLPS of polynucleotides and polycations causes solutions to become turbid, the detection of specific nucleic acid sequences can be observed with the naked eye. We furthermore demonstrate that there is an optimal polynucleotide concentration for detection. Finally, we provide a theoretical prediction that hints towards possible improvements of an LLPS-based detection assay. The deployment of LLPS complements CRISPR-based molecular diagnostic applications and facilitates easy and low-cost nucleotide sequence detection.

More than just a barrier: using physical models to couple membrane shape to cell function.

The correct execution of many cellular processes, such as division and motility, requires the cell to adopt a specific shape. Physically, these shapes are determined by the interplay of the plasma membrane and internal cellular driving factors. While the plasma membrane defines the boundary of the cell, processes inside the cell can result in the generation of forces that deform the membrane. These processes include protein binding, the assembly of protein superstructures, and the growth and contraction of cytoskeletal networks. Due to the complexity of the cell, relating observed membrane deformations back to internal processes is a challenging problem. Here, we review cell shape changes in endocytosis, cell adhesion, cell migration and cell division and discuss how by modeling membrane deformations we can investigate the inner working principles of the cell.

Mechanics of epithelial tissue formation.

A key process in the life of any multicellular organism is its development from a single egg into a full grown adult. The first step in this process often consists of forming a tissue layer out of randomly placed cells on the surface of the egg. We present a model for generating such a tissue, based on mechanical interactions between the cells, and find that the resulting cellular pattern corresponds to the Voronoi tessellation of the nuclei of the cells. Experimentally, we obtain the same result in both fruit flies and flour beetles, with a distribution of cell shapes that matches that of the model, without any adjustable parameters. Finally, we show that this pattern is broken when the cells grow at different rates.

Printing of Patterned, Engineered E. coli Biofilms with a Low-Cost 3D Printer.

Biofilms can grow on virtually any surface available, with impacts ranging from endangering the lives of patients to degrading unwanted water contaminants. Biofilm research is challenging due to the high degree of biofilm heterogeneity. A method for the production of standardized, reproducible, and patterned biofilm-inspired materials could be a boon for biofilm research and allow for completely new engineering applications. Here, we present such a method, combining 3D printing with genetic engineering. We prototyped a low-cost 3D printer that prints bioink, a suspension of bacteria in a solution of alginate that solidifies on a calcium-containing substrate. We 3D-printed Escherichia coli in different shapes and in discrete layers, after which the cells survived in the printing matrix for at least 1 week. When printed bacteria were induced to form curli fibers, the major proteinaceous extracellular component of E. coli biofilms, they remained adherent to the printing substrate and stably spatially patterned even after treatment with a matrix-dissolving agent, indicating that a biofilm-mimicking structure had formed. This work is the first demonstration of patterned, biofilm-inspired living materials that are produced by genetic control over curli formation in combination with spatial control by 3D printing. These materials could be used as living, functional materials in applications such as water filtration, metal ion sequestration, or civil engineering, and potentially as standardizable models for certain curli-containing biofilms.

Mechanical force induces mitochondrial fission.

Eukaryotic cells are densely packed with macromolecular complexes and intertwining organelles, continually transported and reshaped. Intriguingly, organelles avoid clashing and entangling with each other in such limited space. Mitochondria form extensive networks constantly remodeled by fission and fusion. Here, we show that mitochondrial fission is triggered by mechanical forces. Mechano-stimulation of mitochondria - via encounter with motile intracellular pathogens, via external pressure applied by an atomic force microscope, or via cell migration across uneven microsurfaces - results in the recruitment of the mitochondrial fission machinery, and subsequent division. We propose that MFF, owing to affinity for narrow mitochondria, acts as a membrane-bound force sensor to recruit the fission machinery to mechanically strained sites. Thus, mitochondria adapt to the environment by sensing and responding to biomechanical cues. Our findings that mechanical triggers can be coupled to biochemical responses in membrane dynamics may explain how organelles orderly cohabit in the crowded cytoplasm.

Curvature variation controls particle aggregation on fluid vesicles.

Cellular membranes exhibit a large variety of shapes, strongly coupled to their function. Many biological processes involve dynamic reshaping of membranes, usually mediated by proteins. This interaction works both ways: while proteins influence the membrane shape, the membrane shape affects the interactions between the proteins. To study these membrane-mediated interactions on closed and anisotropically curved membranes, we use colloids adhered to ellipsoidal membrane vesicles as a model system. We find that two particles on a closed system always attract each other, and tend to align with the direction of largest curvature. Multiple particles form arcs, or, at large enough numbers, a complete ring surrounding the vesicle in its equatorial plane. The resulting vesicle shape resembles a snowman. Our results indicate that these physical interactions on membranes with anisotropic shapes can be exploited by cells to drive macromolecules to preferred regions of cellular or intracellular membranes, and utilized to initiate dynamic processes such as cell division. The same principle could be used to find the midplane of an artificial vesicle, as a first step towards dividing it into two equal parts.

Pointlike Inclusion Interactions in Tubular Membranes.

Membrane tubes and tubular networks are ubiquitous in living cells. Inclusions like proteins are vital for both the stability and the dynamics of such networks. These inclusions interact via the curvature deformations they impose on the membrane. We analytically study the resulting membrane mediated interactions in strongly curved tubular membranes. We model inclusions as constraints coupled to the curvature tensor of the membrane tube. First, as special test cases, we analyze the interaction between ring- and rod-shaped inclusions. Using Monte Carlo simulations, we further show how pointlike inclusions interact to form linear aggregates. To minimize the curvature energy of the membrane, inclusions self-assemble into either line- or ringlike patterns. Our results show that the global curvature of the membrane strongly affects the interactions between proteins embedded in it, and can lead to the spontaneous formation of biologically relevant structures.

Lipid membrane-mediated attraction between curvature inducing objects.

The interplay of membrane proteins is vital for many biological processes, such as cellular transport, cell division, and signal transduction between nerve cells. Theoretical considerations have led to the idea that the membrane itself mediates protein self-organization in these processes through minimization of membrane curvature energy. Here, we present a combined experimental and numerical study in which we quantify these interactions directly for the first time. In our experimental model system we control the deformation of a lipid membrane by adhering colloidal particles. Using confocal microscopy, we establish that these membrane deformations cause an attractive interaction force leading to reversible binding. The attraction extends over 2.5 times the particle diameter and has a strength of three times the thermal energy (-3.3 kBT). Coarse-grained Monte-Carlo simulations of the system are in excellent agreement with the experimental results and prove that the measured interaction is independent of length scale. Our combined experimental and numerical results reveal membrane curvature as a common physical origin for interactions between any membrane-deforming objects, from nanometre-sized proteins to micrometre-sized particles.

Erratum: Collective dynamics of soft active particles [Phys. Rev. E 91, 032706 (2015)].

This corrects the article DOI: 10.1103/PhysRevE.91.032706.

Collective dynamics of soft active particles.

We present a model of soft active particles that leads to a rich array of collective behavior found also in dense biological swarms of bacteria and other unicellular organisms. Our model uses only local interactions, such as Vicsek-type nearest-neighbor alignment, short-range repulsion, and a local boundary term. Changing the relative strength of these interactions leads to migrating swarms, rotating swarms, and jammed swarms, as well as swarms that exhibit run-and-tumble motion, alternating between migration and either rotating or jammed states. Interestingly, although a migrating swarm moves slower than an individual particle, the diffusion constant can be up to three orders of magnitude larger, suggesting that collective motion can be highly advantageous, for example, when searching for food.

Mechanical signaling via nonlinear wavefront propagation in a mechanically excitable medium.

Models that invoke nonlinear wavefront propagation in a chemically excitable medium are rife in the biological literature. Indeed, the idea that wavefront propagation can serve as a signaling mechanism has often been invoked to explain synchronization of developmental processes. In this paper we suggest a kind of signaling based not on diffusion of a chemical species but on the propagation of mechanical stress. We construct a theoretical approach to describe mechanical signaling as a nonlinear wavefront propagation problem and study its dependence on key variables such as the effective elasticity and damping of the medium.

The syncytial Drosophila embryo as a mechanically excitable medium.

Mitosis in the early syncytial Drosophila embryo is highly correlated in space and time, as manifested in mitotic wavefronts that propagate across the embryo. In this paper we investigate the idea that the embryo can be considered a mechanically-excitable medium, and that mitotic wavefronts can be understood as nonlinear wavefronts that propagate through this medium. We study the wavefronts via both image analysis of confocal microscopy videos and theoretical models. We find that the mitotic waves travel across the embryo at a well-defined speed that decreases with replication cycle. We find two markers of the wavefront in each cycle, corresponding to the onsets of metaphase and anaphase. Each of these onsets is followed by displacements of the nuclei that obey the same wavefront pattern. To understand the mitotic wavefronts theoretically we analyze wavefront propagation in excitable media. We study two classes of models, one with biochemical signaling and one with mechanical signaling. We find that the dependence of wavefront speed on cycle number is most naturally explained by mechanical signaling, and that the entire process suggests a scenario in which biochemical and mechanical signaling are coupled.

Heart-specific stiffening in early embryos parallels matrix and myosin expression to optimize beating.

In development and differentiation, morphological changes often accompany mechanical changes [1], but it is unclear whether or when cells in embryos sense tissue elasticity. The earliest embryo is uniformly pliable, while adult tissues vary widely in mechanics from soft brain and stiff heart to rigid bone [2]. However, cell sensitivity to microenvironment elasticity is debated based in part on results from complex three-dimensional culture models [3]. Regenerative cardiology provides strong motivation to clarify any cell-level sensitivities to tissue elasticity because rigid postinfarct regions limit pumping by the adult heart [4]. Here, we focus on the spontaneously beating embryonic heart and sparsely cultured cardiomyocytes, including cells derived from pluripotent stem cells. Tissue elasticity, Et, increases daily for heart to 1-2 kPa by embryonic day 4 (E4), and although this is ~10-fold softer than adult heart, the beating contractions of E4 cardiomyocytes prove optimal at ~Et,E4 both in vivo and in vitro. Proteomics reveals daily increases in a small subset of proteins, namely collagen plus cardiac-specific excitation-contraction proteins. Rapid softening of the heart's matrix with collagenase or stiffening it with enzymatic crosslinking suppresses beating. Sparsely cultured E4 cardiomyocytes on collagen-coated gels likewise show maximal contraction on matrices with native E4 stiffness, highlighting cell-intrinsic mechanosensitivity. While an optimal elasticity for striation proves consistent with the mathematics of force-driven sarcomere registration, contraction wave speed is linear in Et as theorized for excitation-contraction coupled to matrix elasticity. Pluripotent stem cell-derived cardiomyocytes also prove to be mechanosensitive to matrix and thus generalize the main observation that myosin II organization and contractile function are optimally matched to the load contributed by matrix elasticity.

A new way of tracking motion, shape, and divisions.

The process of detecting and tracking biological features such as bacteria and nuclei is complicated by the fact that they constantly change their shape. Shape changes happen both continuously as the biological features grow and discontinuously as they divide or die. In this paper I present a new method of tracking such features for the case that they can be reasonably approximated by a relatively simple mathematical shape such as a cylinder or an ellipse. Using contour plots with multiple levels to detect the features and their shapes, rather than the commonly used single contour detection technique, this method can efficiently detect multiple features even if they have large differences in brightness, as well as reliably track divisions when both brightness and size drop dramatically.

Kinesin recycling in stationary membrane tubes.

Collections of motors dynamically organize to extract membrane tubes. These tubes grow but often pause or change direction as they traverse an underlying microtubule (MT) network. In vitro, membrane tubes also stall: they stop growing in length despite a large group of motors available at the tip to pull them forward. In these stationary membrane tubes in vitro, we find that clusters of processive kinesin motors form and reach the tip of the tube at regular time intervals. The average times between cluster arrivals depends on the time over which motors depart from the tip, suggesting that motors are recycled toward the tip. Numerical simulations of the motor dynamics in the membrane tube and on the MTs show that the presence of cooperative binding between motors quantitatively accounts for the clustering observed experimentally. Cooperative binding along the length of the MT and a nucleation point at a distance behind the tip define the recycling period. Based on comparison of the numerical results and experimental data, we estimate a cooperative binding probability and concentration regime where the recycling phenomenon occurs.