Barrier Crossing in Escherichia coli Chemotaxis

High-throughput cell migration assay under combinatorial chemical environments by a novel 24-well-plate based device

The quantitative studies of cell proliferation and migration under different chemical environments are important for both scientists and clinicians searching for new therapeutics. In this study, we developed a new device to pattern several types of cells in 24-well-plate and demonstrated its' application in cancer cell proliferation and migration assay. The new device combined 3D-printed-silica-part for multi cell types loading with PDMS-through-hole-layer-part for cell micro-patterning which was matched with commercial 24-well-plate. This 24-well-plate based device is flexible and feasible in many applications and can be used in one piece or multi pieces. Besides the application for two types of cells proliferation and migration assay in one chemical condition, as a demonstration, the migration behaviors of four types of cells under 24 types of EGF + bFGF combinatorial conditions were studied. We believed this device could be widely used in clinical searching for new anti-cancer therapeutics and other related studies.

Spatial coordination in a mutually beneficial bacterial community enhances its antibiotic resistance

Microbial communities can survive in complex and variable environments by using different cooperative strategies. However, the behaviors of these mutuality formed communities remain poorly understood, particularly with regard to the characteristics of spatial cooperation. Here, we selected two Escherichia coli strains, designated as the nutrition provider and the antibiotic protector, respectively, for construction of a mutually beneficial bacterial community that could be used to study these behaviors. We found that in addition to the functional mutualism, the two strains also cooperated through their spatial distribution. Under antibiotic pressure, the bacterial distribution changed to yield different spatial distributions, which resulted in community growth advantages beyond functional cooperation. The mutualistic behavior of these two strains suggested that similar communities could also use variations in spatial distribution to improve their survival rates in a natural environment or under the action of antibiotics.

Autonomous microfluidic actuators for periodic sequential flow generation

Control of periodic sequential flows of multisolutions is invaluable in a variety of technology and science applications, but it requires complex and expensive external controllers. Here, we present microfluidic systems that autonomously regulate periodic sequential flows without any user instructions or dynamic external controllers. The systems consist of astable and monostable actuators that mimic the functions of analog electronic circuits. With a constant water head pressure of the input solution acting as the sole driving force, these systems generate periodic sequential flows in a predetermined and sophisticated manner. We validate our technology with the applications that have been previously addressed only by dynamic external controllers: dynamic staining of cell nuclei and playing a touchscreen piano. Our approach provides a useful and effective alternative to dynamic external controllers.

Escape band in Escherichia coli chemotaxis in opposing attractant and nutrient gradients

It is commonly believed that bacterial chemotaxis helps cells find food. However, not all attractants are nutrients, and not all nutrients are strong attractants. Here, by using microfluidic experiments, we studied Escherichia coli chemotaxis behavior in the presence of a strong chemoattractant (e.g., aspartate or methylaspartate) gradient and an opposing gradient of diluted tryptone broth (TB) growth medium. Our experiments showed that cells initially accumulate near the strong attractant source. However, after the peak cell density (h) reaches a critical value [Formula: see text], the cells form a "escape band" (EB) that moves toward the chemotactically weaker but metabolically richer nutrient source. By using various mutant strains and varying experimental conditions, we showed that the competition between Tap and Tar receptors is the key molecular mechanism underlying the formation of the escape band. A mathematical model combining chemotaxis signaling and cell growth was developed to explain the experiments quantitatively. The model also predicted that the width w and the peak position [Formula: see text] of EB satisfy two scaling relations: [Formula: see text] and [Formula: see text], where l is the channel length. Both scaling relations were verified by experiments. Our study shows that the combination of nutrient consumption, population growth, and chemotaxis with multiple receptors allows cells to search for optimal growth condition in complex environments with conflicting sources.

Optimal methylation noise for best chemotactic performance of E. coli

In response to a concentration gradient of chemoattractant, E. coli bacterium modulates the rotational bias of flagellar motors which control its run-and-tumble motion, to migrate towards regions of high chemoattractant concentration. Presence of stochastic noise in the biochemical pathway of the cell has important consequences on the switching mechanism of motor bias, which in turn affects the runs and tumbles of the cell in a significant way. We model the intracellular reaction network in terms of coupled time evolution of three stochastic variables-kinase activity, methylation level, and CheY-P protein level-and study the effect of methylation noise on the chemotactic performance of the cell. In presence of a spatially varying nutrient concentration profile, a good chemotactic performance allows the cell to climb up the concentration gradient quickly and localize in the nutrient-rich regions in the long time limit. Our simulations show that the best performance is obtained at an optimal noise strength. While it is expected that chemotaxis will be weaker for very large noise, it is counterintuitive that the performance worsens even when noise level falls below a certain value. We explain this striking result by detailed analysis of CheY-P protein level statistics for different noise strengths. We show that when the CheY-P level falls below a certain (noise-dependent) threshold the cell tends to move down the concentration gradient of the nutrient, which has a detrimental effect on its chemotactic response. This threshold value decreases as noise is increased, and this effect is responsible for noise-induced enhancement of chemotactic performance. In a harsh chemical environment, when the nutrient degrades with time, the amount of nutrient intercepted by the cell trajectory is an effective performance criterion. In this case also, depending on the nutrient lifetime, we find an optimum noise strength when the performance is at its best.

Markovian robots: Minimal navigation strategies for active particles

We explore minimal navigation strategies for active particles in complex, dynamical, external fields, introducing a class of autonomous, self-propelled particles which we call Markovian robots (MR). These machines are equipped with a navigation control system (NCS) that triggers random changes in the direction of self-propulsion of the robots. The internal state of the NCS is described by a Boolean variable that adopts two values. The temporal dynamics of this Boolean variable is dictated by a closed Markov chain-ensuring the absence of fixed points in the dynamics-with transition rates that may depend exclusively on the instantaneous, local value of the external field. Importantly, the NCS does not store past measurements of this value in continuous, internal variables. We show that despite the strong constraints, it is possible to conceive closed Markov chain motifs that lead to nontrivial motility behaviors of the MR in one, two, and three dimensions. By analytically reducing the complexity of the NCS dynamics, we obtain an effective description of the long-time motility behavior of the MR that allows us to identify the minimum requirements in the design of NCS motifs and transition rates to perform complex navigation tasks such as adaptive gradient following, detection of minima or maxima, or selection of a desired value in a dynamical, external field. We put these ideas in practice by assembling a robot that operates by the proposed minimalistic NCS to evaluate the robustness of MR, providing a proof of concept that is possible to navigate through complex information landscapes with such a simple NCS whose internal state can be stored in one bit. These ideas may prove useful for the engineering of miniaturized robots.

Adaptation of Living Systems

Adaptation refers to the biological phenomenon where living systems change their internal states in response to changes in their environments in order to maintain certain key functions critical for their survival and fitness. Adaptation is one of the most ubiquitous and arguably one of the most fundamental properties of living systems. It occurs throughout all biological scales, from adaptation of populations of species over evolutionary time to adaptation of a single cell to different environmental stresses during its life span. In this article, we review some of the recent progress made in understanding molecular mechanisms of cellular level adaptation. We take the minimalist (or the physicist) approach and study the simplest systems that exhibit generic adaptive behaviors. We focus on understanding the basic biochemical interaction networks in living matter that are responsible for adaptation dynamics. By combining theoretical modeling with quantitative experimentation, we demonstrate universal features in adaptation as well as important differences in different cellular systems, including chemotaxis in bacterium cells (Escherichia coli) and eukaryotic cells (Dictyostelium). Future work in extending the modeling framework to study adaptation in more complex systems such as sensory neurons are discussed.

Experimental investigation of mesoscopic heterogeneous motion of laser-activated self-propelling Janus particles in suspension

The mesoscopic collective motion of self-propelling active particle suspension is experimentally investigated. The active particles are silica micro spheres with Au hemisphere coating, and their propelling strength is activated by laser irradiation. The suspension is driven from equilibrium to near equilibrium and far from equilibrium by tuning the excitation laser intensity. By use of the long-term particle tracking technique, the time evolution of a large amount of active particles is resolvable. For low laser intensity, the suspension is driven to near equilibrium state with homogeneous superdiffusion motion. The strength of enhanced superdiffusion is monotonically related to the laser intensity. For high laser intensity, the motility-induced phase separation with the coexistence of dense cluster and very dilute individual particle are observed. It leads to highly heterogeneous dynamic with less mobile jammed cluster and fast-moving particles and subsequently suppresses the enhanced superdiffusion. Such heterogeneous dynamics is similar to many far from equilibrium systems. Finally, the degree away from equilibrium (Gaussian dynamics) triggered by propelling strength is quantified by non-Gaussian parameters.