The microbiologist’s guide to membrane potential dynamics

All cellular membranes have the functionality of generating and maintaining the gradients of electrical and electrochemical potentials. Such potentials were generally thought to be an essential but homeostatic contributor to complex bacterial behaviors. Recent studies have revised this view, and we now know that bacterial membrane potential is dynamic and plays signaling roles in cell–cell interaction, adaptation to antibiotics, and sensation of cellular conditions and environments. These discoveries argue that bacterial membrane potential dynamics deserve more attention. Here, we review the recent studies revealing the signaling roles of bacterial membrane potential dynamics. We also introduce basic biophysical theories of the membrane potential to the microbiology community and discuss the needs to revise these theories for applications in bacterial electrophysiology

Interrogating metabolism as an electron flow system

Metabolism is generally considered as a neatly organised system of modular pathways, shaped by evolution under selection for optimal cellular growth. This view falls short of explaining and predicting a number of key observations about the structure and dynamics of metabolism. We highlight these limitations of a pathway-centric view on metabolism and summarise studies suggesting how these could be overcome by viewing metabolism as a thermodynamically and kinetically constrained, dynamical flow system. Such a systems-level, first-principles based view of metabolism can open up new avenues of metabolic engineering and cures for metabolic diseases and allow better insights to a myriad of physiological processes that are ultimately linked to metabolism. Towards further developing this view, we call for a closer interaction among physical and biological disciplines and an increased use of electrochemical and biophysical approaches to interrogate cellular metabolism together with the microenvironment in which it exists

The dynamics of single-to-multi layer transition in bacterial swarms

Wet self-propelled rods at high densities can exhibit a state of mesoscale turbulence: a disordered lattice of vortices with chaotic dynamics and a characteristic length scale. Such a state is commonly studied by a two-dimensional continuum model. However, less is known about the dynamic behaviour of self-propelled rods in three- or quasi-two- dimensions, which can be found in biological systems, for example, during the formation of bacterial aggregates and biolms. In this study, we characterised the formation of multi-layered islands in a monolayer of swarming cells using the rod-shaped bacteria B. subtilis as a model system. We focused on understanding how bacteria form multiple layers and how the presence of stress aects the multiple layer formation. Following our previous study where we reported that the initiation of the multilayer formation can be accounted by the framework of motility-induced phase separation (MIPS), this study analysed how this phase separation is impacted by the presence of stress, specially under the exposure to a gradient of antibiotic. The analyses show that in the presence of an antibiotic gradient, the multi-layer formation happens by a nucleation and growth of well-defined multilayered clusters instead of by the uncontrolled emergence of the multilayer, resembling the traditional thermodynamic processes of binodal and spinodal decomposition respectively. Finally, the multilayer gives place to waves of bacteria that can travel towards high concentrations of antibiotics and that resemble travelling waves predicted by simulations of mixtures of passive and active particles

Swarming bacteria undergo localized dynamic phase transition to form stress-induced biofilms

Self-organized multicellular behaviors enable cells to adapt and tolerate stressors to a greater degree than isolated cells. However, whether and how cellular communities alter their collective behaviors adaptively upon exposure to stress is largely unclear. Here, we investigate this question using Bacillus subtilis, a model system for bacterial multicellularity. We discover that, upon exposure to a spatial gradient of kanamycin, swarming bacteria activate matrix genes and transit to biofilms. The initial stage of this transition is underpinned by a stress-induced multilayer formation, emerging from a biophysical mechanism reminiscent of motility-induced phase separation (MIPS). The physical nature of the process suggests that stressors which suppress the expansion of swarms would induce biofilm formation. Indeed, a simple physical barrier also induces a swarm-to-biofilm transition. Based on the gained insight, we propose a strategy of antibiotic treatment to inhibit the transition from swarms to biofilms by targeting the localized phase transition

Biofilm and swarming emergent behaviours controlled through the aid of biophysical understanding and tools

Bacteria can organise themselves into communities in the forms of biofilms and swarms. Through chemical and physical interactions between cells, these communities exhibit emergent properties that individual cells alone do not have. While bacterial communities have been mainly studied in the context of biochemistry and molecular biology, recent years have seen rapid advancements in the biophysical understanding of emergent phenomena through physical interactions in biofilms and swarms. Moreover, new technologies to control bacterial emergent behaviours by physical means are emerging in synthetic biology. Such technologies are particularly promising for developing engineered living materials (ELM) and devices and controlling contamination and biofouling. In this minireview, we overview recent studies unveiling physical and mechanical cues that trigger and affect swarming and biofilm development. In particular, we focus on cell shape, motion and density as the key parameters for mechanical cell–cell interactions within a community. We then showcase recent studies that use physical stimuli for patterning bacterial communities, altering collective behaviours and preventing biofilm formation. Finally, we discuss the future potential extension of biophysical and bioengineering research on microbial communities through computational modelling and deeper investigation of mechano-electrophysiological coupling

Impact of spatial organization on a novel auxotrophic interaction among soil microbes

A key prerequisite to achieve a deeper understanding of microbial communities and to engineer synthetic ones is to identify the individual metabolic interactions among key species and how these interactions are affected by different environmental factors. Deciphering the physiological basis of species–species and species–environment interactions in spatially organized environments requires reductionist approaches using ecologically and functionally relevant species. To this end, we focus here on a defined system to study the metabolic interactions in a spatial context among the plant-beneficial endophytic fungus Serendipita indica, and the soil-dwelling model bacterium Bacillus subtilis. Focusing on the growth dynamics of S. indica under defined conditions, we identified an auxotrophy in this organism for thiamine, which is a key co-factor for essential reactions in the central carbon metabolism. We found that S. indica growth is restored in thiamine-free media, when co-cultured with B. subtilis. The success of this auxotrophic interaction, however, was dependent on the spatial and temporal organization of the system; the beneficial impact of B. subtilis was only visible when its inoculation was separated from that of S. indica either in time or space. These findings describe a key auxotrophic interaction in the soil among organisms that are shown to be important for plant ecosystem functioning, and point to the potential importance of spatial and temporal organization for the success of auxotrophic interactions. These points can be particularly important for engineering of minimal functional synthetic communities as plant seed treatments and for vertical farming under defined conditions

Electrotaxis behavior of droplets composed of aqueous Belousov-Zhabotinsky solutions suspended in oil phase

Taxis is ubiquitous in biological and physical chemistry systems as a response to various external stimulations. We prepared aqueous droplets containing Belousov-Zhabotinsky (BZ) solutions suspended on an oleic acid oil phase subject to DC electric field and found that these BZ droplets undergo chemically driven translational motion towards the negative electrode under DC electric field. This electrotaxis phenomenon originates from the field-induced inhomogeneous distribution of reactants, in particular Br- ions, and consequently the biased location of the leading centers towards the positive electrode. We define the ’leading center’ (LC) as a specific location within the droplet where the BZ chemical wave (target pattern) is initiated. The chemical wave generated from the LC propagates passing the droplet center of mass and creates a gradient of interfacial tension when reaching the droplet-oil interface on the other side, resulting in a momentum exchange between the droplet and oil phases which drives the droplet motion in the direction of the electric field. A greater electric field strength renders a more substantial electrotaxis effect

An agent-based model of the interrelation between the COVID-19 outbreak and economic activities

As of July 2020, COVID-19 caused by SARS-COV-2 is spreading worldwide, causing severe economic damage. While minimizing human contact is effective in managing outbreaks, it causes severe economic losses. Strategies to solve this dilemma by considering the interrelation between the spread of the virus and economic activities are urgently needed to mitigate the health and economic damage. Here, we propose an abstract agent-based model of the COVID-19 outbreak that accounts for economic activities. The computational simulation of the model recapitulates the trade-off between the health and economic damage associated with voluntary restraint measures. Based on the simulation results, we discuss how the macroscopic dynamics of infection and economics emerge from individuals’ behaviours. We believe our model can serve as a platform for discussing solutions to the above-mentioned dilemma