Collective motion enhances chemotaxis in a two-dimensional bacterial swarm

In a dilute liquid environment in which cell-cell interaction is negligible, flagellated bacteria, such as Escherichia coli, perform chemotaxis by biased random walks alternating between run-and-tumble. In a two-dimensional crowded environment, such as a bacterial swarm, the typical behavior of run-and-tumble is absent, and this raises the question whether and how bacteria can perform chemotaxis in a swarm. Here, by examining the chemotactic behavior as a function of the cell density, we showed that chemotaxis is surprisingly enhanced because of cell crowding in a bacterial swarm, and this enhancement is correlated with increase in the degree of cell body alignment. Cells tend to form clusters that move collectively in a swarm with increased effective run length, and we showed analytically that this resulted in increased drift velocity toward attractants. We also explained the enhancement by stochastically simulating bacterial chemotaxis in a swarm. We found that cell crowding in a swarm enhances chemotaxis if the cell-cell interactions used in the simulation induce cell-cell alignment, but it impedes chemotaxis if the interactions are collisions that randomize cell moving direction. Therefore, collective motion in a bacterial swarm enhances chemotaxis.     

Is Catalytic Activity of Chaperones a Selectable Trait for the Emergence of Heat Shock Response?

Although heat shock response is ubiquitous in bacterial cells, the underlying physical chemistry behind heat shock response remains poorly understood. To study the response of cell populations to heat shock we employ a physics-based ab initio model of living cells where protein biophysics (i.e., folding and protein-protein interactions in crowded cellular environments) and important aspects of proteins homeostasis are coupled with realistic population dynamics simulations. By postulating a genotype-phenotype relationship we define a cell division rate in terms of functional concentrations of proteins and protein complexes, whose Boltzmann stabilities of folding and strengths of their functional interactions are exactly evaluated from their sequence information. We compare and contrast evolutionary dynamics for two models of chaperon action. In the active model, foldase chaperones function as nonequilibrium machines to accelerate the rate of protein folding. In the passive model, holdase chaperones form reversible complexes with proteins in their misfolded conformations to maintain their solubility. We find that only cells expressing foldase chaperones are capable of genuine heat shock response to the increase in the amount of unfolded proteins at elevated temperatures. In response to heat shock, cells’ limited resources are redistributed differently for active and passive models. For the active model, foldase chaperones are overexpressed at the expense of downregulation of high abundance proteins, whereas for the passive model; cells react to heat shock by downregulating their high abundance proteins, as their low abundance proteins are upregulated.     

Chemotactic migration of bacteria in porous media

Chemotactic migration of bacteria—their ability to direct multicellular motion along chemical gradients—is central to processes in agriculture, the environment, and medicine. However, current understanding of migration is based on studies performed in bulk liquid, despite the fact that many bacteria inhabit tight porous media such as soils, sediments, and biological gels. Here, we directly visualize the chemotactic migration of Escherichia coli populations in well-defined 3D porous media in the absence of any other imposed external forcing (e.g., flow). We find that pore-scale confinement is a strong regulator of migration. Strikingly, cells use a different primary mechanism to direct their motion in confinement than in bulk liquid. Furthermore, confinement markedly alters the dynamics and morphology of the migrating population—features that can be described by a continuum model, but only when standard motility parameters are substantially altered from their bulk liquid values to reflect the influence of pore-scale confinement. Our work thus provides a framework to predict and control the migration of bacteria, and active matter in general, in complex environments.     

Studies of effects of macromolecular crowding and confinement on protein folding and protein stability

In cells, proteins execute specific tasks in crowded environments; these environments influence their stability and dynamics. Similarly, for an enzyme molecule encapsulated in an inorganic cavity as in biosensors or biocatalysts, confinement or excluded volume plays an important role in its stability and dynamics. In this article we present results of our experimental and theoretical investigations of the confinement and macromolecular crowding effects on protein. On the experimental side we study the stability of encapsulated cytochrome c against unfolding induced by the presence of denaturants, such as urea. Results show that, as the pore size in which protein is trapped is reduced, protein shows higher stability against denaturant-induced unfolding. On the theoretical side, after reviewing our previous study of the confinement effects on the equilibrium and dynamic properties of protein using a minimalist (two-dimensional lattice, Monte Carlo, Brownian dynamics) model, we have extended the model so that the effects of macromolecular crowding on such properties can be studied. Our simulations show that both folding and unfolding times increase with the number of crowders in solution, however, the equilibrium constant is affected such that the equilibrium is shifted towards the folded state. Furthermore, our results show that, for a fixed number of crowders as the size of crowder (or excluded volume) increases, the average size of protein at equilibrium decreases.     

Emergent spatiotemporal population dynamics with cell-length control of synthetic microbial consortia

The increased complexity of synthetic microbial biocircuits highlights the need for distributed cell functionality due to concomitant increases in metabolic and regulatory burdens imposed on single-strain topologies. Distributed systems, however, introduce additional challenges since consortium composition and spatiotemporal dynamics of constituent strains must be robustly controlled to achieve desired circuit behaviors. Here, we address these challenges with a modeling-based investigation of emergent spatiotemporal population dynamics using cell-length control in monolayer, two-strain bacterial consortia. We demonstrate that with dynamic control of a strain’s division length, nematic cell alignment in close-packed monolayers can be destabilized. We find that this destabilization confers an emergent, competitive advantage to smaller-length strains—but by mechanisms that differ depending on the spatial patterns of the population. We used complementary modeling approaches to elucidate underlying mechanisms: an agent-based model to simulate detailed mechanical and signaling interactions between the competing strains, and a reductive, stochastic lattice model to represent cell-cell interactions with a single rotational parameter. Our modeling suggests that spatial strain-fraction oscillations can be generated when cell-length control is coupled to quorum-sensing signaling in negative feedback topologies. Our research employs novel methods of population control and points the way to programming strain fraction dynamics in consortial synthetic biology.     

Protein folding in confined and crowded environments

Confinement and crowding are two major factors that can potentially impact protein folding in cellular environments. Theories based on considerations of excluded volumes predict disparate effects on protein folding stability for confinement and crowding: confinement can stabilize proteins by over 10k_BT but crowding has a very modest effect on stability. On the other hand, confinement and crowding are both predicted to favor conformations of the unfolded state which are compact, and consequently may increase the folding rate. These predictions are largely borne out by experimental studies of protein folding under confined and crowded conditions in the test tube. Protein folding in cellular environments is further complicated by interactions with surrounding surfaces and other factors. Concerted theoretical modeling and test-tube and in vivo experiments promise to elucidate the complexity of protein folding in cellular environments.     

Physical constraints on early blastomere packings

At very early embryonic stages, when embryos are composed of just a few cells, establishing the correct packing arrangements (contacts) between cells is essential for the proper development of the organism. As early as the 4-cell stage, the observed cellular packings in different species are distinct and, in many cases, differ from the equilibrium packings expected for simple adherent and deformable particles. It is unclear what are the specific roles that different physical parameters, such as the forces between blastomeres, their division times, orientation of cell division and embryonic confinement, play in the control of these packing configurations. Here we simulate the non-equilibrium dynamics of cells in early embryos and systematically study how these different parameters affect embryonic packings at the 4-cell stage. In the absence of embryo confinement, we find that cellular packings are not robust, with multiple packing configurations simultaneously possible and very sensitive to parameter changes. Our results indicate that the geometry of the embryo confinement determines the packing configurations at the 4-cell stage, removing degeneracy in the possible packing configurations and overriding division rules in most cases. Overall, these results indicate that physical confinement of the embryo is essential to robustly specify proper cellular arrangements at very early developmental stages.     

Individual risk perception and empirical social structures shape the dynamics of infectious disease outbreaks

The dynamics of a spreading disease and individual behavioral changes are entangled processes that have to be addressed together in order to effectively manage an outbreak. Here, we relate individual risk perception to the adoption of a specific set of control measures, as obtained from an extensive large-scale survey performed via Facebook—involving more than 500,000 respondents from 64 countries—showing that there is a “one-to-one” relationship between perceived epidemic risk and compliance with a set of mitigation rules. We then develop a mathematical model for the spreading of a disease—sharing epidemiological features with COVID-19—that explicitly takes into account non-compliant individual behaviors and evaluates the impact of a population fraction of infectious risk-deniers on the epidemic dynamics. Our modeling study grounds on a wide set of structures, including both synthetic and more than 180 real-world contact patterns, to evaluate, in realistic scenarios, how network features typical of human interaction patterns impact the spread of a disease. In both synthetic and real contact patterns we find that epidemic spreading is hindered for decreasing population fractions of risk-denier individuals. From empirical contact patterns we demonstrate that connectivity heterogeneity and group structure significantly affect the peak of hospitalized population: higher modularity and heterogeneity of social contacts are linked to lower peaks at a fixed fraction of risk-denier individuals while, at the same time, such features increase the relative impact on hospitalizations with respect to the case where everyone correctly perceive the risks.     

Ion-mediated RNA structural collapse: effect of spatial confinement

RNAs are negatively charged molecules that reside in cellular environments with macromolecular crowding. Macromolecular confinement can influence the ion effects in RNA folding. In this work, using the recently developed tightly bound ion model for ion fluctuation and correlation, we investigate the effect of confinement on ion-mediated RNA structural collapse for a simple model system. We find that for both Na(+) and Mg(2+), the ion efficiencies in mediating structural collapse/folding are significantly enhanced by the structural confinement. This enhancement of ion efficiency is attributed to the decreased electrostatic free-energy difference between the compact conformation ensemble and the (restricted) extended conformation ensemble due to the spatial restriction.     

Distinct roles for two receptor tyrosine kinases in epithelial branching morphogenesis in Drosophila

Branching morphogenesis is a widespread mechanism used to increase the surface area of epithelial organs. Many signaling systems steer development of branched organs, but it is still unclear which cellular processes are regulated by the different pathways. We have used the development of the air sacs of the dorsal thorax of Drosophila to study cellular events and their regulation via cell-cell signaling. We find that two receptor tyrosine kinases play important but distinct roles in air sac outgrowth. Fgf signaling directs cell migration at the tip of the structure, while Egf signaling is instrumental for cell division and cell survival in the growing epithelial structure. Interestingly, we find that Fgf signaling requires Ras, the Mapk pathway, and Pointed to direct migration, suggesting that both cytoskeletal and nuclear events are downstream of receptor activation. Ras and the Mapk pathway are also needed for Egf-regulated cell division/survival, but Pointed is dispensable.     

In-Cell NMR Characterization of the Secondary Structure Populations of a Disordered Conformation of α-Synuclein within E. coli Cells

α-Synuclein is a small protein strongly implicated in the pathogenesis of Parkinson’s disease and related neurodegenerative disorders. We report here the use of in-cell NMR spectroscopy to observe directly the structure and dynamics of this protein within E. coli cells. To improve the accuracy in the measurement of backbone chemical shifts within crowded in-cell NMR spectra, we have developed a deconvolution method to reduce inhomogeneous line broadening within cellular samples. The resulting chemical shift values were then used to evaluate the distribution of secondary structure populations which, in the absence of stable tertiary contacts, are a most effective way to describe the conformational fluctuations of disordered proteins. The results indicate that, at least within the bacterial cytosol, α-synuclein populates a highly dynamic state that, despite the highly crowded environment, has the same characteristics as the disordered monomeric form observed in aqueous solution.     

Plasticity is a locally adapted trait with consequences for ecological dynamics in novel environments

Phenotypic plasticity is predicted to evolve in more variable environments, conferring an advantage on individual lifetime fitness. It is less clear what the potential consequences of that plasticity will have on ecological population dynamics. Here, we use an invertebrate model system to examine the effects of environmental variation (resource availability) on the evolution of phenotypic plasticity in two life history traits—age and size at maturation—in long‐running, experimental density‐dependent environments. Specifically, we then explore the feedback from evolution of life history plasticity to subsequent ecological dynamics in novel conditions. Plasticity in both traits initially declined in all microcosm environments, but then evolved increased plasticity for age‐at‐maturation, significantly so in more environmentally variable environments. We also demonstrate how plasticity affects ecological dynamics by creating founder populations of different plastic phenotypes into new microcosms that had either familiar or novel environments. Populations originating from periodically variable environments that had evolved greatest plasticity had lowest variability in population size when introduced to novel environments than those from constant or random environments. This suggests that while plasticity may be costly it can confer benefits by reducing the likelihood that offspring will experience low survival through competitive bottlenecks in variable environments. In this study, we demonstrate how plasticity evolves in response to environmental variation and can alter population dynamics—demonstrating an eco‐evolutionary feedback loop in a complex animal moderated by plasticity in growth.     

Growth rate effects on fundamental transport properties of bacterial populations

In many natural environments, bacterial populations experience suboptimal growth due to the competition with other microorganisms for limited resources. The chemotactic response provides a mechanism by which bacterial populations can improve their situation by migrating toward more favorable growth conditions. For bacteria cultured under suboptimal growth conditions, evidence for an enhanced chemotactic response has been observed previously. In this article, for the first time, we have quantitatively characterized this behavior in terms of two macroscopic transport coefficients, the random motility and chemotactic sensitivity coefficients, measured in the stopped-flow diffusion chamber assay. Escherichia coli cultured over a range of growth rates in a chemostat exhibits a dramatic increase in the chemotactic sensitivity coefficient for D-fucose at low growth rates, while the random motility coefficient remains relatively constant by comparison. The change in the chemotactic sensitivity coefficient is accounted for by an independently measured increase in the number of galactose-binding proteins which mediate the chemotactic signal. This result is consistent with the relationship between macroscopic and microscopic parameters for chemotaxis, which was proposed in the mathematical model of Rivero and co-workers. (c) 1993 John Wiley & Sons, Inc.     

Cell cycle modelling

Models able to describe the events of cellular growth and division and the dynamics of cell populations are useful for the understanding of functional control mechanisms and for the theoretical support for automated analysis of flow cytometric data and of cell volume distributions. This paper reports on models that we have developed with this aim for different kinds of cells. The models are composed by two subsystems: one describes the growth dynamics of RNA and protein, and the second accounts for DNA replication and cell division, and describe in a rather unitary frame the cell cycle of eukaryotic cells, like mammalian cells and yeast, and of prokaryotic cells. The model is also used to study the effects of various sources of variability on the statistical properties of cell populations, and we find that in microbial cells the main source of variability appears to be an inaccuracy of the molecular mechanism that monitors cell size. In normal mammalian cells another source of variability, that depends upon the interaction with growth factors which give competence, is apparent. An extended version of the model, which comprises also this additional variability, is presented and used to describe the properties of mammalian cell growth.     

BIO-LGCA: A cellular automaton modelling class for analysing collective cell migration

Collective dynamics in multicellular systems such as biological organs and tissues plays a key role in biological development, regeneration, and pathological conditions. Collective tissue dynamics—understood as population behaviour arising from the interplay of the constituting discrete cells—can be studied with on- and off-lattice agent-based models. However, classical on-lattice agent-based models, also known as cellular automata, fail to replicate key aspects of collective migration, which is a central instance of collective behaviour in multicellular systems. To overcome drawbacks of classical on-lattice models, we introduce an on-lattice, agent-based modelling class for collective cell migration, which we call biological lattice-gas cellular automaton (BIO-LGCA). The BIO-LGCA is characterised by synchronous time updates, and the explicit consideration of individual cell velocities. While rules in classical cellular automata are typically chosen ad hoc, rules for cell-cell and cell-environment interactions in the BIO-LGCA can also be derived from experimental cell migration data or biophysical laws for individual cell migration. We introduce elementary BIO-LGCA models of fundamental cell interactions, which may be combined in a modular fashion to model complex multicellular phenomena. We exemplify the mathematical mean-field analysis of specific BIO-LGCA models, which allows to explain collective behaviour. The first example predicts the formation of clusters in adhesively interacting cells. The second example is based on a novel BIO-LGCA combining adhesive interactions and alignment. For this model, our analysis clarifies the nature of the recently discovered invasion plasticity of breast cancer cells in heterogeneous environments.     

Arrayed cellular environments for stem cells and regenerative medicine

The behavior and composition of both multipotent and pluripotent stem cell populations are exquisitely controlled by a complex, spatiotemporally variable interplay of physico-chemical, extracellular matrix, cell-cell interaction, and soluble factor cues that collectively define the stem cell niche. The push for stem cell-based regenerative medicine models and therapies has fuelled demands for increasingly accurate cellular environmental control and enhanced experimental throughput, driving an evolution of cell culture platforms away from conventional culture formats toward integrated systems. Arrayed cellular environments typically provide a set of discrete experimental elements with variation of one or several classes of stimuli across elements of the array. These are based on high-content/high-throughput detection, small sample volumes, and multiplexing of environments to increase experimental parameter space, and can be used to address a range of biological processes at the cell population, single-cell, or subcellular level. Arrayed cellular environments have the capability to provide an unprecedented understanding of the molecular and cellular events that underlie expansion and specification of stem cell and therapeutic cell populations, and thus generate successful regenerative medicine outcomes. This review focuses on recent key developments of arrayed cellular environments and their contribution and potential in stem cells and regenerative medicine.     

Real-time monitoring of epithelial cell-cell and cell-substrate interactions by infrared surface plasmon spectroscopy

The development of novel technologies capable of monitoring the dynamics of cell-cell and cell-substrate interactions in real time and a label-free manner is vital for gaining deeper insights into these most fundamental cellular processes. However, the label-free technologies available today provide only limited information on these processes. Here, we report a new (to our knowledge) infrared surface plasmon resonance (SPR)-based methodology that can resolve distinct phases of cell-cell and cell-substrate adhesion of polarized Madin Darby canine kidney epithelial cells. Due to the extended penetration depth of the infrared SP wave, the dynamics of cell adhesion can be detected with high accuracy and high temporal resolution. Analysis of the temporal variation of the SPR reflectivity spectrum revealed the existence of multiple phases in epithelial cell adhesion: initial contact of the cells with the substrate (cell deposition), cell spreading, formation of intercellular contacts, and subsequent generation of cell clusters. The final formation of a continuous cell monolayer could also be sensed. The SPR measurements were validated by optical microscopy imaging. However, in contrast to the SPR method, the optical analyses were laborious and less quantitative, and hence provided only limited information on the dynamics and phases of cell adhesion.     

Coherent Motion of Monolayer Sheets under Confinement and Its Pathological Implications

Coherent angular rotation of epithelial cells is thought to contribute to many vital physiological processes including tissue morphogenesis and glandular formation. However, factors regulating this motion, and the implications of this motion if perturbed, remain incompletely understood. In the current study, we address these questions using a cell-center based model in which cells are polarized, motile, and interact with the neighboring cells via harmonic forces. We demonstrate that, a simple evolution rule in which the polarization of any cell tends to orient with its velocity vector can induce coherent motion in geometrically confined environments. In addition to recapitulating coherent rotational motion observed in experiments, our results also show the presence of radial movements and tissue behavior that can vary between solid-like and fluid-like. We show that the pattern of coherent motion is dictated by the combination of different physical parameters including number density, cell motility, system size, bulk cell stiffness and stiffness of cell-cell adhesions. We further observe that perturbations in the form of cell division can induce a reversal in the direction of motion when cell division occurs synchronously. Moreover, when the confinement is removed, we see that the existing coherent motion leads to cell scattering, with bulk cell stiffness and stiffness of cell-cell contacts dictating the invasion pattern. In summary, our study provides an in-depth understanding of the origin of coherent rotation in confined tissues, and extracts useful insights into the influence of various physical parameters on the pattern of such movements.     

Functional Fluorescent Ca2+ Indicator Proteins in Transgenic Mice under TET Control

Genetically encoded fluorescent calcium indicator proteins (FCIPs) are promising tools to study calcium dynamics in many activity-dependent molecular and cellular processes. Great hopes—for the measurement of population activity, in particular—have therefore been placed on calcium indicators derived from the green fluorescent protein and their expression in (selected) neuronal populations. Calcium transients can rise within milliseconds, making them suitable as reporters of fast neuronal activity. We here report the production of stable transgenic mouse lines with two different functional calcium indicators, inverse pericam and camgaroo-2, under the control of the tetracycline-inducible promoter. Using a variety of in vitro and in vivo assays, we find that stimuli known to increase intracellular calcium concentration (somatically triggered action potentials (APs) and synaptic and sensory stimulation) can cause substantial and rapid changes in FCIP fluorescence of inverse pericam and camgaroo-2.     

The crowd you're in with: Effects of different types of crowding agents on protein aggregation

The intracellular environment contains high concentrations of macromolecules occupying up to 30% of the total cellular volume. Presence of these macromolecules decreases the effective volume available for the proteins in the cell and thus increases the effective protein concentrations and stabilizes the compact protein conformations. Macromolecular crowding created by various macromolecules such as proteins, nucleic acids, and carbohydrates has been shown to have a significant effect on a variety of cellular processes including protein aggregation. Most studies of macromolecular crowding have used neutral, flexible polysaccharides that function primarily via excluded volume effect as model crowding agents. Here we have examined the effects of more rigid polysaccharides on protein structure and aggregation. Our results indicate that rigid and flexible polysaccharides influence protein aggregation via different mechanisms and suggest that, in addition to excluded volume effect, changes in solution viscosity and non-specific protein–polymer interactions influence the structure and dynamics of proteins in crowded environments.