Membrane Targeted Azobenzene Drives Optical Modulation of Bacterial Membrane Potential.

Recent studies have shown that bacterial membrane potential is dynamic and plays signaling roles. Yet, little is still known about the mechanisms of membrane potential dynamics regulation-owing to a scarcity of appropriate research tools. Optical modulation of bacterial membrane potential could fill this gap and provide a new approach for studying and controlling bacterial physiology and electrical signaling. Here, the authors show that a membrane-targeted azobenzene (Ziapin2) can be used to photo-modulate the membrane potential in cells of the Gram-positive bacterium Bacillus subtilis. It is found that upon exposure to blue-green light (λ = 470 nm), isomerization of Ziapin2 in the bacteria membrane induces hyperpolarization of the potential. To investigate the origin of this phenomenon, ion-channel-deletion strains and ion channel blockers are examined. The authors found that in presence of the chloride channel blocker idanyloxyacetic acid-94 (IAA-94) or in absence of KtrAB potassium transporter, the hyperpolarization response is attenuated. These results reveal that the Ziapin2 isomerization can induce ion channel opening in the bacterial membrane and suggest that Ziapin2 can be used for studying and controlling bacterial electrical signaling. This new optical tool could contribute to better understand various microbial phenomena, such as biofilm electric signaling and antimicrobial resistance.

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.