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Cyanobacterial Phototaxis Modeling For Active Matter System

Flocks of birds, schools of fish, motor-cytoskeletal filament combinations, swimming bacteria, and driven granular media are all examples of systems of interacting motile units that demonstrate collective behavior. These are all active matter systems because each unit gets energy from an internal energy store and converts it into work done on the environment. We examine a model for cyanobacterial phototaxis, highlighting the distinctions between it and other models for collective behavior in active matter systems. Mechanical forces are mediated by physical attachments and the creation of "slime," a complex combination of non-diffusible polysaccharides deposited by cells that serve to reduce friction locally and dominate interactions between individual cells during phototaxis. The slime, in particular, provides a component to the contact that is local in the area but non-local in time, similar to the pheromones left behind in ant trails.

Researchers from the Institute of Mathematical Science in Chennai, India, say that the time-delayed part of bacterial interactions makes them a new kind of active system. They call this "damp" vibrant matter, and they say it's a new way to think about the world.

Living Systems Collective Movement

One of the most well-studied instances of collective motion in biological systems is bird flocking. Although the system's emergent behavior is highly complicated, most agent-based models that capture these phenomena are rather basic, with each agent making choices based only on visual signals. These judgments are often dependent on the movement of other agents in the immediate vicinity. They are presumed to be unaffected by environmental variables. Various models have also incorporated different aspects of visual information processing, such as variability in the field of view, an explicit attraction to facilitate flock cohesion, and the role of social hierarchy within the flocks to capture features of the emergent behavior observed in natural bird flocks. Individual-based models have also been used to explain the patterns of bacterial colony development. Cell choices are not influenced by other people in the vicinity but simply by local environmental signals. Cells are sometimes depicted as "walkers" in this context, with the potential to split or travel to other neighboring locations based on local nutrition availability. The nature of the medium may also be integrated into these models via the velocity of nutrient diffusion and the ease with which cells can move to new locations, both of which can be empirically matched in agar concentration. According to these models, changes in the medium's global characteristics lead to different dynamics in local environments, which leads to new forms and structures of colonies.

Cyanobacterial Phototaxis

Individuals in cyanobacterial phototaxis can perceive light, but their movement is dependent on physical interactions between cells and the immediate environment. Transient attachments allow individual cells to connect to and exert physical pressure on neighboring cells. Cells also exude slime, which has the potential to alter the nearby environmental landscape. These attachments are modeled as local physical interactions in an active matter framework, comparable to the field of vision for birds or fish. In contrast, the slime is modeled as an environmental element, similar to hydrodynamic interactions in fish or local environmental factors in bacterial colony formation. This model keeps people's short-term interactions in mind and considers how long-term environmental memory affects mobility in their area.

Cyanobacterial Phototaxis Modeling

Several methodologies have been used to describe cyanobacterial phototaxis, including cellular automata models, reaction-diffusion models, and active matter models. Individual cells stochastically update their direction of travel dependent on the location of other cells in their proximity in one of the earliest agent-based models of cyanobacterial motility. Cell aggregations were seen in simulations of this model, which matched observations of the early phases of phototaxis. This model added more complicated physical interactions between cells and other things in the environment, like slime and light from outside.

Furthermore, the model integrates soft-core interactions to provide a repulsive force that discourages cell overlaps. Cell-cell interactions are mediated by a sigmoidal force term that varies with the distance between the cell centers. Each agent adds to the environment by "depositing" a non-diffusible resource in their area. This reduces the friction of agents that follow.

As a result, direct interactions between agents in this paradigm are mechanical and immediate, but indirect interactions between agents are local and temporally delayed. As a result, the researchers propose that this is a "damp" active matter system, as neither the "wet" nor the "dry" frameworks can adequately explain it. This modeling framework enables researchers to look into how individual cells respond to complex stimuli landscapes in the context of collective behavior. This phototactic cyanobacteria model reproduces qualitative elements of empirically reported colony morphologies at light wavelengths and intensities. They also investigated how individual information processing influences emergent collective behavior. When there are a lot of different light sources, individual cells may be able to see and react to a single light source right away, or they may be able to sense and combine the responses of several light sources simultaneously.

Conclusion

This research might help explain how individual bacteria in natural settings can perceive and interpret several stimuli simultaneously and then combine their responses to them. Another significant benefit of active matter models is that varied decision-making capacities may be attributed to people. Indeed, the researchers demonstrated how easily their model could integrate variation, allowing them to replicate natural populations. In contrast to quorum sensing, they proposed that this "damp" active matter framework might be another model of consensus-building that leads to collective behavior in bacterial groupings. These models might help us understand how bacterial populations, particularly in biological systems, react to complicated inputs through varied individual-level decision-making, which can then be merged and coordinated to create collective behavior. Model features and experimental data could be more closely linked to getting more information about how groups of organisms work together in a natural setting.

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