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, 72 (7), 4987-94

Collective Bacterial Dynamics Revealed Using a Three-Dimensional Population-Scale Defocused Particle Tracking Technique

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Collective Bacterial Dynamics Revealed Using a Three-Dimensional Population-Scale Defocused Particle Tracking Technique

Mingming Wu et al. Appl Environ Microbiol.

Abstract

An ability to monitor bacterial locomotion and collective dynamics is crucial to our understanding of a number of well-characterized phenotypes including biofilm formation, chemotaxis, and virulence. Here, we report the tracking of multiple swimming Escherichia coli cells in three spatial dimensions and at single-cell resolution using a novel three-dimensional (3D) defocused particle tracking (DPT) method. The 3D trajectories were generated for wild-type Escherichia coli strain RP437 as well as for isogenic derivatives that display smooth swimming due to a cheA deletion (strain RP9535) or incessant tumbling behavior due to a cheZ deletion (strain RP1616). The 3D DPT method successfully differentiated these three modes of locomotion and allowed direct calculation of the diffusion coefficient for each strain. As expected, we found that the smooth swimmer diffused more readily than the wild type, and both the smooth swimmer and the wild-type cells exhibited diffusion coefficients that were at least two orders of magnitude larger than that of the tumbler. Finally, we found that the diffusion coefficient increased with increasing cell density, a phenomenon that can be attributed to the hydrodynamic disturbances caused by neighboring bacteria.

Figures

FIG. 1.
FIG. 1.
Microscope image of swimming E. coli strain RP437 (wild type for motility and chemotaxis). The image size is 449 μm by 335 μm. The bright oblong spots depict cells that are in the plane of focus. The rings depict cells that are out of the plane of focus. The ring size is directly proportional to the distance of the cell to the focal plane and is used to obtain the z dimension.
FIG. 2.
FIG. 2.
Swimming trajectories of wild-type RP437 derived from a sequence of images using ImagePro Plus (Media Cybernetics, Inc.) image processing software. The typical time between consecutive images was 150 ms, and each time sequence consisted of 300 images. Using an in-house software package, we determined the locations and the ring size for each bacterium shown in Fig. 1. This information was then translated into the coordinates (x, y, and z) for each bacterial cell in the image, and the process was repeated for all the images in a time series. The 3D trajectories of each bacterial cell generated using the nearest-neighbor method (A) and the projection of the 3D trajectory to the x-y plane (B). Different colors represent different trajectories.
FIG. 3.
FIG. 3.
Swimming trajectories of smooth swimmers (RP9535) and tumblers (RP1616). 3D trajectories (A) and 2D projection (B) for strain RP9535. 3D trajectories (C) and 2D projection (D) for strain RP1616. Different colors represent different trajectories.
FIG. 4.
FIG. 4.
The population average of the square distance to the origin as a function of time (t) for the wild-type RP437 strain (circle) and its isogenic derivatives RP9535 (triangle) and RP1616 (diamond) at a cell concentration of 107 cells/ml. The solid lines for RP9535 and RP437 are fits to equation 1 (see text). The solid line for RP1616 is a fit to a linear function. The diffusion coefficients D and the characteristic times τ were extracted from the fits. For RP437, D = 53.2 μm2/s and τ = 1.8 s; for RP9535, D = 458.0 μm2/s and τ = 6.6 s; for RP1616, D = 2.0 μm2/s.
FIG. 5.
FIG. 5.
Velocity auto-correlation of wild-type E. coli strain RP437 for velocity components along the x, y, and z directions (red, vx; blue, vy; green, vz). The solid lines depict fits to an exponential decay function.

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