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Almodaimegh, A.

Publications and source records attributed to Almodaimegh, A..

2 recordsLinked to original sources

Motile and matrix-producing cells drive distinct modes of cell-scale motion in Bacillus subtilis colonies

The physics of cell motion and growth drives the expansion of groups of cells including bacterial colonies. Under different conditions, many species of bacteria grow with strikingly different dynamics, which can arise from the physics of constituent cells. For example, on low-percentage agar substrates, colonies often expand rapidly via motility as swarms, while on higher percentage substrates, biofilms expand slowly due to growth and pressure. However, in bacterial species Bacillus subtilis, both swarm and biofilm phenotypes contain differentiated cells in both the motile state and the matrix-producing state, provoking the question: how does phenotypic heterogeneity influence the cell-level motions that drive development? To answer this question, we used a bead-tracking assay in which we follow the motion of cell-sized fluorescent beads embedded in growing B. subtilis colonies. By being pushed due to their interactions with cells, beads passively report on local cell motion. We found that, in rapidly expanding swarms, bead motion was bimodal: some beads moved rapidly and diffusively, while others appeared to be slow or stationary. However, after following the seemingly trapped beads over many hours, we found that the beads in fact moved slowly and ballistically. In biofilms grown on higher percentage agar, we found that some beads were trapped, moving sub-diffusively over the course of biofilm growth, while others moved ballistically. We hypothesized that slow, ballistic bead motion in both swarms and biofilms was driven by groups of radially expanding matrix-producing cells. To test this hypothesis, we performed bead tracking experiments in colonies formed by regulatory mutant strains that were locked into motility or matrix production. In swarms of motile-only cells, we observed fast, diffusive bead motion with no population of slow, ballistic beads. In matrix-only biofilms, we observed that ballistic motion was heavily favored compared to wild type. These results support the hypothesis that expanding clusters of matrix cells drive slow, ballistic motion at the cellular scale during colony growth. Our results demonstrate that heterogeneous cell phenotypes contribute to heterogeneous local physics in bacterial colonies, influencing the distributions of cellular phenotypes.

biophysics↗

An Agent-Based Model of Metabolic Signaling Oscillations in Bacillus subtilis Biofilms

Microbes of nearly every species can form biofilms, communities of cells bound together by a self-produced matrix. It is not understood how variation at the cellular level impacts putatively beneficial, colony-level behaviors, such as cell-to-cell signaling. Here we investigate this problem with an agent-based computational model of metabolically driven electrochemical signaling in Bacillus subtilis biofilms. In this process, glutamate-starved interior cells release potassium, triggering a depolarizing wave that spreads to exterior cells and limits their glutamate uptake. More nutrients diffuse to the interior, temporarily reducing glutamate stress and leading to oscillations. In our model, each cell has a membrane potential coupled to metabolism. As a simulated biofilm grows, collective membrane potential oscillations arise spontaneously as cells deplete nutrients and trigger potassium release, reproducing experimental observations. We further validate our model by comparing spatial signaling patterns and cellular signaling rates with those observed experimentally. By oscillating external glutamate and potassium, we find that biofilms synchronize to external potassium more strongly than to glutamate, providing a potential mechanism for previously observed biofilm synchronization. By tracking cellular glutamate concentrations, we find that oscillations evenly distribute nutrients in space: non-oscillating biofilms have an external layer of well-fed cells surrounding a starved core, whereas oscillating biofilms exhibit a relatively uniform distribution of glutamate. Our work shows the potential of agent-based models to connect cellular properties to collective phenomena and facilitates studies of how inheritance of cellular traits can affect the evolution of group behaviors.

microbiology↗