Reversals and collisions optimize protein exchange in bacterial swarms

Abstract

Swarming groups of bacteria coordinate their behavior by self-organizing as a population to move over surfaces in search of nutrients and optimal niches for colonization. Many open questions remain about the cues used by swarming bacteria to achieve this self-organization. While chemical cue signaling known as quorum sensing is well described, swarming bacteria often act and coordinate on time scales that could not be achieved via these extracellular quorum sensing cues. Here, cell-cell contact-dependent protein exchange is explored as a mechanism of intercellular signaling for the bacterium Myxococcus xanthus. Detailed biologically calibrated computational model is used to study how M. xanthus optimizes the connection rate between cells and maximizes spread of an extracellular protein within the population. The maximum rate of protein spreading is observed for cells that reverse direction optimally for swarming. Cells that reverse too slowly or too fast fail to spread extracellular protein efficiently. In particular, a specific range of cell reversal frequencies was observed to maximize the cell-cell connection rate and minimize the time of protein spreading. Furthermore, our findings suggest that pre-designed motion reversal can be employed to enhance the collective behavior of biological synthetic active systems.

Multi-Scale Mathematical Modeling of Prion Aggregate Dynamics and Phenotypes in Yeast Colonies

“…The generalized Morse potential functions implemented in SCE modeling approach are commonly used in physics and chemistry to model intermolecular interactions [119] and in biology to represent volume exclusion of neighboring regions of the cytoskeleton [94,95,[120][121][122][123][124][125]. While it is difficult to associate specific potential functions directly with specific cytoskeletal components of cells, computational studies of bulk properties at the tissue level have suggested that the precise functional form of the potential used in modeling has a small impact on overall system dynamics [97,117].…”

“…The subcellular element (SCE) modeling approach has been successful in modeling mechanical properties of individual cells as well as their components and determining individual cell impact on the emerging properties of growing multicellular tissue as well as describing cellular interactions with mediums such as the extracellular matrix and fluids [76,84,86,89,90,95,96,111,117,120,122,[124][125][126][127]. The general modeling framework was initially developed by Newman et al [89] for simulating the detailed dynamics of cell shapes as an emergent response to mechanical stimuli.…”

Cell-Based Model of the Generation and Maintenance of the Shape and Structure of the Multilayered Shoot Apical Meristem of Arabidopsis thaliana

“…The sub-cellular element (SCE) modeling approach is an established cellbased framework for modeling mechanical properties of individual cells as well as their components and determining their impact on the emerging properties of growing multi-cellular tissue as well as describing cellular interactions with mediums such as the ECM and fluids (Sandersius et al 2011a;Van Liedekerke et al 2015;Diaz de la Loza and Thompson 2017;Tanaka 2015;Milde et al 2014;Sandersius et al 2011b;Christley et al 2010;Fletcher et al 2017;Brodland 2015;Newman 2005;Sandersius and Newman 2008;Newman 2007;Amiri et al 2017;Wu et al 2014;Nematbakhsh et al 2017;Sweet et al 2011). The general approach was initially developed by Newman et al (2005) for simulating the detailed dynamics of cell shapes as an emergent response to mechanical stimuli.…”

“…The generalized Morse potential functions implemented in our model are commonly used in physics and chemistry to model inter-molecular interactions (Schiff 1968) and in biology to represent volume exclusion of neighboring regions of the cytoskeleton (Sweet et al 2011;Wu et al 2014;Amiri et al 2017;Nematbakhsh et al 2017;Christley et al 2010;Gord et al 2014). It is difficult to associate specific potential functions directly with specific cytoskeletal components of cells.…”

Quantifying the Biophysical Impact of Budding Cell Division on the Spatial Organization of Growing Yeast Colonies

“…The morphological characteristics exhibited by growing microbial communities arise from complex interactions between genetic, epigenetic, environmental and cellular determinants [1][2][3][4][5][6][7][8][9][10][11][12][13][14] (Figure 1). For example, the emergence of large regions of a single genotype in bacterial colonies is most often associated with the chance loss of certain genes as individuals die or do not reproduce due to nutrient limitation [8,9,11].…”