Mathematical analysis of a quorum sensing induced biofilm dispersal model and numerical simulation of hollowing effects

A pore-scale reactive transport modeling study for quorum sensing-driven biofilm dispersal in heterogeneous porous media

Microorganisms regulate the expression of energetically expensive phenotypes via a collective decision-making mechanism known as quorum sensing (QS). This study investigates the intricate dynamics of biofilm growth and QS-controlled biofilm dispersal in heterogeneous porous media, employing a pore-scale reactive transport modeling approach. Model simulations carried out under various fluid flow conditions and biofilm growth scenarios reveal that QS processes are influenced not only by the biomass density of biofilm colonies but also by a complex interplay between pore architecture, flow velocity, and the rates of biofilm growth and dispersal. This study demonstrates that pore architecture controls the initiation of QS processes and advection gives rise to oscillatory growth of biofilms. Such oscillation is suppressed if biofilm dynamics are in favor of sustaining a sufficiently high signal concentration, such as fast growth or slow dispersal rates. By establishing a mathematical framework, this study contributes to the fundamental understanding of QS-controlled biofilm dynamics in complex environments.

Simulation Based Exploration of Bacterial Cross Talk Between Spatially Separated Colonies in a Multispecies Biofilm Community

We present a simple mesoscopic model for bacterial cross-talk between growing biofilm colonies. The simulation setup mimics a novel microfludic biofilm growth reactor which allows a 2D description. The model is a stiff quasilinear system of diffusion-reaction equations with simultaneously a super-diffusion singularity and a degeneracy (as in the porous medium equation) that leads to the formation of sharp interfaces with finite speed of propagation and gradient blow up. We use a finite volume method with arithmetic flux averaging, and a time adaptive stiff time integrator. We find that signal and nutrient transport between colonies can greatly control and limit biofilm response to induction signals, leading to spatially heterogeneous biofilm behavior.

Bacteria Floc, but Do They Flock? Insights from Population Interaction Models of Quorum Sensing

Quorum sensing (QS) enables coordinated, population-wide behavior. QS-active bacteria "communicate" their number density using autoinducers which they synthesize, collect, and interpret. Tangentially, chemotactic bacteria migrate, seeking out nutrients and other molecules. It has long been hypothesized that bacterial behaviors, such as chemotaxis, were the primordial progenitors of complex behaviors of higher-order organisms. Recently, QS was linked to chemotaxis, yet the notion that these behaviors can together contribute to higher-order behaviors has not been shown. Here, we mathematically link flocking behavior, commonly observed in fish and birds, to bacterial chemotaxis and QS by constructing a phenomenological model of population-scale QS-mediated phenomena. Specifically, we recast a previously developed mathematical model of flocking and found that simulated bacterial behaviors aligned well with well-known QS behaviors. This relatively simple system of ordinary differential equations affords analytical analysis of asymptotic behavior and describes cell position and velocity, QS-mediated protein expression, and the surrounding concentrations of an autoinducer. Further, heuristic explorations of the model revealed that the emergence of "migratory" subpopulations occurs only when chemotaxis is directly linked to QS. That is, behaviors were simulated when chemotaxis was coupled to QS and when not. When coupled, the bacterial flocking model predicts the formation of two distinct groups of cells migrating at different speeds in their journey toward an attractant. This is qualitatively similar to phenomena spotted in our Escherichiacoli chemotaxis experiments as well as in analogous work observed over 50 years ago.IMPORTANCE Our modeling efforts show how cell density can affect chemotaxis; they help to explain the roots of subgroup formation in bacterial populations. Our work also reinforces the notion that bacterial mechanisms are at times exhibited in higher-order organisms.

Information transmission in microbial and fungal communication: from classical to quantum

Microbes have their own communication systems. Secretion and reception of chemical signaling molecules and ion-channels mediated electrical signaling mechanism are yet observed two special ways of information transmission in microbial community. In this article, we address the aspects of various crucial machineries which set the backbone of microbial cell-to-cell communication process such as quorum sensing mechanism (bacterial and fungal), quorum sensing regulated biofilm formation, gene expression, virulence, swarming, quorum quenching, role of noise in quorum sensing, mathematical models (therapy model, evolutionary model, molecular mechanism model and many more), synthetic bacterial communication, bacterial ion-channels, bacterial nanowires and electrical communication. In particular, we highlight bacterial collective behavior with classical and quantum mechanical approaches (including quantum information). Moreover, we shed a new light to introduce the concept of quantum synthetic biology and possible cellular quantum Turing test.

Continuum and discrete approach in modeling biofilm development and structure: a review

The scientific community has recognized that almost 99% of the microbial life on earth is represented by biofilms. Considering the impacts of their sessile lifestyle on both natural and human activities, extensive experimental activity has been carried out to understand how biofilms grow and interact with the environment. Many mathematical models have also been developed to simulate and elucidate the main processes characterizing the biofilm growth. Two main mathematical approaches for biomass representation can be distinguished: continuum and discrete. This review is aimed at exploring the main characteristics of each approach. Continuum models can simulate the biofilm processes in a quantitative and deterministic way. However, they require a multidimensional formulation to take into account the biofilm spatial heterogeneity, which makes the models quite complicated, requiring significant computational effort. Discrete models are more recent and can represent the typical multidimensional structural heterogeneity of biofilm reflecting the experimental expectations, but they generate computational results including elements of randomness and introduce stochastic effects into the solutions.

Three-Dimensional Numerical Simulations of Biofilm Dynamics with Quorum Sensing in a Flow Cell

We develop a multiphasic hydrodynamic theory for biofilms taking into account interactions among various bacterial phenotypes, extracellular polymeric substance (EPS), quorum sensing (QS) molecules, solvent, and antibiotics. In the model, bacteria are classified into down-regulated QS, up-regulated QS, and non-QS cells based on their QS ability. The model is first benchmarked against an experiment yielding an excellent fit to experimental measurements on the concentration of QS molecules and the cell density during biofilm development. It is then applied to study development of heterogeneous structures in biofilms due to interactions of QS regulation, hydrodynamics, and antimicrobial treatment. Our 3D numerical simulations have confirmed that (i). QS is beneficial for biofilm development in a long run by building a robust EPS population to protect the biofilm; (ii). biofilms located upstream can induce QS downstream when the colonies are close enough spatially; (iii). QS induction may not be fully operational and can even be compromised in strong laminar flows; (v). the hydrodynamic stress alters the biofilm morphology. Through further numerical investigations, our model suggests that (i). QS-regulated EPS production contributes to the structural formation of heterogeneous biofilms; (ii) QS down-regulated cells tend to grow at the surface of the biofilm while QS up-regulated ones tend to grow in the bulk; (iii) when nutrient supply is sufficient, QS induction might be more effective upstream than downstream; (iv) QS may be of little benefit in a short timescale in term of fighting against invading strain/species; (v) the material properties of biomass (bacteria and EPS) have strong impact on the dilution of QS molecules under strong shear flow. In addition, with this modeling framework, hydrodynamic details and rheological quantities associated with biofilm formation under QS regulation can be resolved.