Jingchen Feng

Growth feedback as a basis for persister bistability

Significance The phenomenon of persistence is important both at a fundamental level in serving as a striking example of adaptive phenotypic variability and from the applied perspective as it contributes to the antibiotic resistance of bacteria in general and biofilms in particular. Our paper presents a unique quantitatively successful model of persistence in Escherichia coli and helps explain many puzzling observations in the literature. It will serve as a guide for further work, both experimental and theoretical. The primary molecular actors in our approach are a toxin–antitoxin pair HipBA, and we use very recent structural data to formulate a comprehensive approach to this problem and to guide further work. Finally, our effort is consistent with recent ideas regarding the fact that many toxin–antitoxin pairs may contribute in a parallel manner to the persister state. A small fraction of cells in many bacterial populations, called persisters, are much less sensitive to antibiotic treatment than the majority. Persisters are in a dormant metabolic state, even while remaining genetically identical to the actively growing cells. Toxin and antitoxin modules in bacteria are believed to be one possible cause of persistence. A two-gene operon, HipBA, is one of many chromosomally encoded toxin and antitoxin modules in Escherichia coli and the HipA7 allelic variant was the first validated high-persistence mutant. Here, we present a stochastic model that can generate bistability of the HipBA system, via the reciprocal coupling of free HipA to the cellular growth rate. The actively growing state and the dormant state each correspond to a stable state of this model. Fluctuations enable transitions from one to the other. This model is fully in agreement with experimental data obtained with synthetic promoter constructs.

Micromechanics of cellularized biopolymer networks.

Significance Mechanical interactions between cells, mediated by the elastic response of the extracellular matrix to active applied forces, play a critical role in developmental biology, wound healing, and cancer progression. This work applies sophisticated technical means, both in experiment and computational modeling, to investigate the micron-scale mechanics of a popular model of this medium, a collagen gel. The results obtained show clearly that on the cellular scale, there are significant spatial variations in the micromechanics due to network heterogeneities. Collagen gels are widely used in experiments on cell mechanics because they mimic the extracellular matrix in physiological conditions. Collagen gels are often characterized by their bulk rheology; however, variations in the collagen fiber microstructure and cell adhesion forces cause the mechanical properties to be inhomogeneous at the cellular scale. We study the mechanics of type I collagen on the scale of tens to hundreds of microns by using holographic optical tweezers to apply pN forces to microparticles embedded in the collagen fiber network. We find that in response to optical forces, particle displacements are inhomogeneous, anisotropic, and asymmetric. Gels prepared at 21 °C and 37 °C show qualitative difference in their micromechanical characteristics. We also demonstrate that contracting cells remodel the micromechanics of their surrounding extracellular matrix in a strain- and distance-dependent manner. To further understand the micromechanics of cellularized extracellular matrix, we have constructed a computational model which reproduces the main experiment findings.

Alignment and nonlinear elasticity in biopolymer gels

We present a Landau-type theory for the nonlinear elasticity of biopolymer gels with a part of the order parameter describing induced nematic order of fibers in the gel. We attribute the nonlinear elastic behavior of these materials to fiber alignment induced by strain. We suggest an application to contact guidance of cell motility in tissue. We compare our theory to simulation of a disordered lattice model for biopolymers. We treat homogeneous deformations such as simple shear, hydrostatic expansion, and simple extension, and obtain good agreement between theory and simulation. We also consider a localized perturbation which is a simple model for a contracting cell in a medium.

Nonlinear elasticity of disordered fiber networks

Disordered biopolymer gels have striking mechanical properties including strong nonlinearities. In the case of athermal gels (such as collagen-I) the nonlinearity has long been associated with a crossover from a bending dominated to a stretching dominated regime of elasticity. The physics of this crossover is related to the existence of a central-force isostatic point and to the fact that for most gels the bending modulus is small. This crossover induces scaling behavior for the elastic moduli. In particular, for linear elasticity such a scaling law has been demonstrated [Broedersz et al. Nat. Phys., 2011 7, 983]. In this work we generalize the scaling to the nonlinear regime with a two-parameter scaling law involving three critical exponents. We test the scaling law numerically for two disordered lattice models, and find a good scaling collapse for the shear modulus in both the linear and nonlinear regimes. We compute all the critical exponents for the two lattice models and discuss the applicability of our results to real systems.

Stress-induced plasticity of dynamic collagen networks

The structure and mechanics of tissues is constantly perturbed by endogenous forces originated from cells, and at the same time regulate many important cellular functions such as migration, differentiation, and growth. Here we show that 3D collagen gels, major components of connective tissues and extracellular matrix (ECM), are significantly and irreversibly remodeled by cellular traction forces, as well as by macroscopic strains. To understand this ECM plasticity, we develop a computational model that takes into account the sliding and merging of ECM fibers. We have confirmed the model predictions with experiment. Our results suggest the profound impacts of cellular traction forces on their host ECM during development and cancer progression, and suggest indirect mechanical channels of cell-cell communications in 3D fibrous matrices.The structure and mechanics of tissues is constantly perturbed by endogenous forces originated from cells. Here the authors show that 3D collagen gels, major components of connective tissues and extracellular matrix, are significantly and irreversibly remodelled by cellular traction forces and by macroscopic strains.

Phenomenological modeling of durotaxis

Cells exhibit qualitatively different behaviors on substrates with different rigidities. The fact that cells are more polarized on the stiffer substrate motivates us to construct a two-dimensional cell with the distribution of focal adhesions dependent on substrate rigidities. This distribution affects the forces exerted by the cell and thereby determines its motion. Our model reproduces the experimental observation that the persistence time is higher on the stiffer substrate. This stiffness-dependent persistence will lead to durotaxis, the preference in moving towards stiffer substrates. This propensity is characterized by the durotaxis index first defined in experiments. We derive and validate a two-dimensional corresponding Fokker-Planck equation associated with our model. Our approach highlights the possible role of the focal adhesion arrangement in durotaxis.

RACIPE: a computational tool for modeling gene regulatory circuits using randomization

BackgroundOne of the major challenges in traditional mathematical modeling of gene regulatory circuits is the insufficient knowledge of kinetic parameters. These parameters are often inferred from existing experimental data and/or educated guesses, which can be time-consuming and error-prone, especially for large networks.ResultsWe present a user-friendly computational tool for the community to use our newly developed method named random circuit perturbation (RACIPE), to explore the robust dynamical features of gene regulatory circuits without the requirement of detailed kinetic parameters. Taking the network topology as the only input, RACIPE generates an ensemble of circuit models with distinct randomized parameters and uniquely identifies robust dynamical properties by statistical analysis. Here, we discuss the implementation of the software and the statistical analysis methods of RACIPE-generated data to identify robust gene expression patterns and the functions of genes and regulatory links. Finally, we apply the tool on coupled toggle-switch circuits and a published circuit of B-lymphopoiesis.ConclusionsWe expect our new computational tool to contribute to a more comprehensive and unbiased understanding of mechanisms underlying gene regulatory networks. RACIPE is a free open source software distributed under (Apache 2.0) license and can be downloaded from GitHub (https://github.com/simonhb1990/RACIPE-1.0).

Stiffness Sensing and Cell Motility: Durotaxis and Contact Guidance

Mechanical properties of the substrate plays a vital role in cell motility. Cells are shown to migrate up stiffness gradient (durotaxis) and along aligned fibers in the substrate (contact guidance). Here we present a simple mechanical model for cell migration, by placing a cell on lattice models for biopolymer gels and hydrogels. In our model cells attach to the substrate via focal adhesions (FAs). As the cells contract, forces are generated at the FAs, determining their maturation and detachment. At the same time, the cell also allowed to move and rotate to maintain force and torque balance. Our model, in which the cells only take the information of forces at the FAs, without a prior knowledge of the substrate stiffness or geometry, is able to reproduce both durotaxis and contact guidance.

Hindrances to precise recovery of cellular forces in fibrous biopolymer networks

How cells move through the three-dimensional extracellular matrix (ECM) is of increasing interest in attempts to understand important biological processes such as cancer metastasis. Just as in motion on flat surfaces, it is expected that experimental measurements of cell-generated forces will provide valuable information for uncovering the mechanisms of cell migration. However, the recovery of forces in fibrous biopolymer networks may suffer from large errors. Here, within the framework of lattice-based models, we explore possible issues in force recovery by solving the inverse problem: how can one determine the forces cells exert to their surroundings from the deformation of the ECM? Our results indicate that irregular cell traction patterns, the uncertainty of local fiber stiffness, the non-affine nature of ECM deformations and inadequate knowledge of network topology will all prevent the precise force determination. At the end, we discuss possible ways of overcoming these difficulties.