Bacterial social interactions drive the emergence of differential spatial colony structures

Self-organization of bacterial communities against environmental pH variation: Controlled chemotactic motility arranges cell population structures in biofilms

As with many living organisms, bacteria often live on the surface of solids, such as foods, organisms, buildings and soil. Compared with dispersive behavior in liquid, bacteria on surface environment exhibit significantly restricted mobility. They have access to only limited resources and cannot be liberated from the changing environment. Accordingly, appropriate collective strategies are necessarily required for long-term growth and survival. However, in spite of our deepening knowledge of the structure and characteristics of individual cells, strategic self-organizing dynamics of their community is poorly understood and therefore not yet predictable. Here, we report a morphological change in Bacillus subtilis biofilms due to environmental pH variations, and present a mathematical model for the macroscopic spatio-temporal dynamics. We show that an environmental pH shift transforms colony morphology on hard agar media from notched 'volcano-like' to round and front-elevated 'crater-like'. We discover that a pH-dependent dose-response relationship between nutritional resource level and quantitative bacterial motility at the population level plays a central role in the mechanism of the spatio-temporal cell population structure design in biofilms.

Artificial Symmetry-Breaking for Morphogenetic Engineering Bacterial Colonies

Morphogenetic engineering is an emerging field that explores the design and implementation of self-organized patterns, morphologies, and architectures in systems composed of multiple agents such as cells and swarm robots. Synthetic biology, on the other hand, aims to develop tools and formalisms that increase reproducibility, tractability, and efficiency in the engineering of biological systems. We seek to apply synthetic biology approaches to the engineering of morphologies in multicellular systems. Here, we describe the engineering of two mechanisms, symmetry-breaking and domain-specific cell regulation, as elementary functions for the prototyping of morphogenetic instructions in bacterial colonies. The former represents an artificial patterning mechanism based on plasmid segregation while the latter plays the role of artificial cell differentiation by spatial colocalization of ubiquitous and segregated components. This separation of patterning from actuation facilitates the design-build-test-improve engineering cycle. We created computational modules for CellModeller representing these basic functions and used it to guide the design process and explore the design space in silico. We applied these tools to encode spatially structured functions such as metabolic complementation, RNAPT7 gene expression, and CRISPRi/Cas9 regulation. Finally, as a proof of concept, we used CRISPRi/Cas technology to regulate cell growth by controlling methionine synthesis. These mechanisms start from single cells enabling the study of morphogenetic principles and the engineering of novel population scale structures from the bottom up.

A mechanistic Individual-based Model of microbial communities

Accurate predictive modelling of the growth of microbial communities requires the credible representation of the interactions of biological, chemical and mechanical processes. However, although biological and chemical processes are represented in a number of Individual-based Models (IbMs) the interaction of growth and mechanics is limited. Conversely, there are mechanically sophisticated IbMs with only elementary biology and chemistry. This study focuses on addressing these limitations by developing a flexible IbM that can robustly combine the biological, chemical and physical processes that dictate the emergent properties of a wide range of bacterial communities. This IbM is developed by creating a microbiological adaptation of the open source Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). This innovation should provide the basis for "bottom up" prediction of the emergent behaviour of entire microbial systems. In the model presented here, bacterial growth, division, decay, mechanical contact among bacterial cells, and adhesion between the bacteria and extracellular polymeric substances are incorporated. In addition, fluid-bacteria interaction is implemented to simulate biofilm deformation and erosion. The model predicts that the surface morphology of biofilms becomes smoother with increased nutrient concentration, which agrees well with previous literature. In addition, the results show that increased shear rate results in smoother and more compact biofilms. The model can also predict shear rate dependent biofilm deformation, erosion, streamer formation and breakup.

Population-Dynamic Modeling of Bacterial Horizontal Gene Transfer by Natural Transformation

Natural transformation is a major mechanism of horizontal gene transfer (HGT) and plays an essential role in bacterial adaptation, evolution, and speciation. Although its molecular underpinnings have been increasingly revealed, natural transformation is not well characterized in terms of its quantitative ecological roles. Here, by using Neisseria gonorrhoeae as an example, we developed a population-dynamic model for natural transformation and analyzed its dynamic characteristics with nonlinear tools and simulations. Our study showed that bacteria capable of natural transformation can display distinct population behaviors ranging from extinction to coexistence and to bistability, depending on their HGT rate and selection coefficient. With the model, we also illustrated the roles of environmental DNA sources-active secretion and passive release-in impacting population dynamics. Additionally, by constructing and utilizing a stochastic version of the model, we examined how noise shapes the steady and dynamic behaviors of the system. Notably, we found that distinct waiting time statistics for HGT events, namely a power-law distribution, an exponential distribution, and a mix of the both, are associated with the dynamics in the regimes of extinction, coexistence, and bistability accordingly. This work offers a quantitative illustration of natural transformation by revealing its complex population dynamics and associated characteristics, therefore advancing our ecological understanding of natural transformation as well as HGT in general.