![]() Dhar, Jayabrata ![]() ![]() ![]() in Nature Physics (2022) The variation associated with different observable characteristics—phenotypes—at the cellular scale underpins homeostasis and the fitness of living systems. However, if and how these noisy phenotypic ... [more ▼] The variation associated with different observable characteristics—phenotypes—at the cellular scale underpins homeostasis and the fitness of living systems. However, if and how these noisy phenotypic traits shape properties at the population level remains poorly understood. Here we report that phenotypic noise self-regulates with growth and coordinates collective structural organization, the kinetics of topological defects and the emergence of active transport around confluent colonies. We do this by cataloguing key phenotypic traits in bacteria growing under diverse conditions. Our results reveal a statistically precise critical time for the transition from a monolayer biofilm to a multilayer biofilm, despite the strong noise in the cell geometry and the colony area at the onset of the transition. This reveals a mitigation mechanism between the noise in the cell geometry and the growth rate that dictates the narrow critical time window. By uncovering how rectification of phenotypic noise homogenizes correlated collective properties across colonies, our work points at an emergent strategy that confluent systems employ to tune active transport, buffering inherent heterogeneities associated with natural cellular environment settings. [less ▲] Detailed reference viewed: 54 (6 UL)![]() Dhar, Jayabrata ![]() ![]() ![]() E-print/Working paper (2021) Phenotypic noise underpins homeostasis and fitness of individual cells. Yet, the extent to which noise shapes cell-to-population properties in microbial active matter remains poorly understood. By ... [more ▼] Phenotypic noise underpins homeostasis and fitness of individual cells. Yet, the extent to which noise shapes cell-to-population properties in microbial active matter remains poorly understood. By quantifying variability in confluent \textit{E.coli} strains, we catalogue noise across different phenotypic traits. The noise, measured over different temperatures serving as proxy for cellular activity, spanned more than two orders of magnitude. The maximum noise was associated with the cell geometry and the critical colony area at the onset of mono-to-multilayer transition (MTMT), while the lower bound was set by the critical time of the MTMT. Our results, supported by a hydrodynamic model, suggest that a trade-off between the noise in the cell geometry and the growth rate can lead to the self-regulation of the MTMT timing. The MTMT cascades synchronous emergence of hydrodynamic fields, actively enhancing the micro-environmental transport. Our results highlight how interplay of phenotypic noise triggers emergent deterministic properties, and reveal the role of multifield topology--of the colony structure and hydrodynamics--to insulate confluent systems from the inherent noise associated with natural cell-environment settings. [less ▲] Detailed reference viewed: 45 (5 UL)![]() ; ; Sengupta, Anupam ![]() in Physical Review Letters (2019), 123(17-25), The transition from monolayers to multilayered structures in bacterial colonies is a fundamental step in biofilm development. Observed across different morphotypes and species, this transition is ... [more ▼] The transition from monolayers to multilayered structures in bacterial colonies is a fundamental step in biofilm development. Observed across different morphotypes and species, this transition is triggered within freely growing bacterial microcolonies comprising a few hundred cells. Using a combination of numerical simulations and analytical modeling, here we demonstrate that this transition originates from the competition between growth-induced in-plane active stresses and vertical restoring forces, due to the cell-substrate interactions. Using a simple chainlike colony of laterally confined cells, we show that the transition sets when individual cells become unstable to rotations; thus it is localized and mechanically deterministic. Asynchronous cell division renders the process stochastic, so that all the critical parameters that control the onset of the transition are continuously distributed random variables. Here we demonstrate that the occurrence of the first division in the colony can be approximated as a Poisson process in the limit of large cell numbers. This allows us to approximately calculate the probability distribution function of the position and time associated with the first extrusion. The rate of such a Poisson process can be identified as the order parameter of the transition, thus highlighting its mixed deterministic-stochastic nature. [less ▲] Detailed reference viewed: 93 (3 UL) |
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