Rapid, High-Throughput Tracking of Bacterial Motility in 3D via Phase-Contrast Holographic Video Microscopy

Cheong, Fook Chiong; Wong, Judith Chui Ching; Gao, Yunfeng; Nai, Mui Hoon; Cui, Yukun; Park, Sungsu; Kenney, Linda J.; Lim, Chwee Teck

doi:10.1016/j.bpj.2015.01.018

Cited by 36 publications

(27 citation statements)

References 46 publications

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“…Its well known run-and-tumble swimming motion and chemotaxis strategy has been thoroughly studied [2][3][4][5][6][7]. Nowadays, modern imaging techniques allow for high-throughput recording of bacterial trajectories [8][9][10][11][12][13][14][15]. The method of labeling flagella by fluorescent markers allows to unravel the diverse swimming mechanisms of microorganisms [16,17].…”

Section: Introductionmentioning

confidence: 99%

Statistical parameter inference of bacterial swimming strategies

et al. 2018

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We provide a detailed stochastic description of the swimming motion of an E.coli bacterium in two dimension, where we resolve tumble events in time. For this purpose, we set up two Langevin equations for the orientation angle and speed dynamics. Calculating moments, distribution and autocorrelation functions from both Langevin equations and matching them to the same quantities determined from data recorded in experiments, we infer the swimming parameters of E.coli. They are the tumble rate λ, the tumble time r −1 , the swimming speed v 0 , the strength of speed fluctuations σ, the relative height of speed jumps η, the thermal value for the rotational diffusion coefficient D 0 , and the enhanced rotational diffusivity during tumbling D T . Conditioning the observables on the swimming direction relative to the gradient of a chemoattractant, we infer the chemotaxis strategies of E.coli. We confirm the classical strategy of a lower tumble rate for swimming up the gradient but also a smaller mean tumble angle (angle bias). The latter is realized by shorter tumbles as well as a slower diffusive reorientation. We also find that speed fluctuations are increased by about 30% when swimming up the gradient compared to the reversed direction.

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Section: Introductionmentioning

confidence: 99%

Statistical parameter inference of bacterial swimming strategies

et al. 2018

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“…The first scheme was employed in the discovery of the reverse, forward, and flick navigational strategy of Vibrio alginolyticus (12), and the second was used in a systematic analysis of E. coli tumbles (13). Finally, a growing body of work is employing holographic video microscopy (e.g., (14)).…”

Section: Introductionmentioning

confidence: 99%

Visualizing Flagella while Tracking Bacteria

Turner

Ping²,

Neubauer

et al. 2016

Biophysical Journal

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A complete description of the swimming behavior of a bacterium requires measurement of the displacement and orientation of the cell body together with a description of the movement of the flagella. We rebuilt a tracking microscope so that we could visualize flagellar filaments of tracked cells by fluorescence. We studied Escherichia coli (cells of various lengths, including swarm cells), Bacillus subtilis (wild-type and a mutant with fewer flagella), and a motile Streptococcus (now Enterococcus). The run-and-tumble statistics were nearly the same regardless of cell shape, length, and flagellation; however, swarm cells rarely tumbled, and cells of Enterococcus tended to swim in loops when moving slowly. There were events in which filaments underwent polymorphic transformations but remained in bundles, leading to small deflections in direction of travel. Tumble speeds were ∼2/3 as large as run speeds, and the rates of change of swimming direction while running or tumbling were smaller when cells swam more rapidly. If a smaller fraction of filaments were involved in tumbles, the tumble intervals were shorter and the angles between runs were smaller.

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“…A higher throughput can be achieved by extracting 3D positions from 2D microscopy images that show multiple bacteria, but existing approaches, consisting of digital holographic microscopy and a number of defocussed imaging methods, exhibit a trade-off between performance and ease of use. Digital holographic microscopy, on the one hand, allows 3D imaging at high speed, but is not accessible to most microbiological laboratories because its application to bacteria is technically demanding and requires a customized experimental set-up 16 17 18 19 . Current defocussed imaging methods, on the other hand, offer technical simplicity by using the diameter of the largest observed diffraction ring as a linear measure of an object's distance from the focal plane 20 .…”

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confidence: 99%

High-throughput 3D tracking of bacteria on a standard phase contrast microscope

et al. 2015

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Bacteria employ diverse motility patterns in traversing complex three-dimensional (3D) natural habitats. 2D microscopy misses crucial features of 3D behaviour, but the applicability of existing 3D tracking techniques is constrained by their performance or ease of use. Here we present a simple, broadly applicable, high-throughput 3D bacterial tracking method for use in standard phase contrast microscopy. Bacteria are localized at micron-scale resolution over a range of 350 × 300 × 200 μm by maximizing image cross-correlations between their observed diffraction patterns and a reference library. We demonstrate the applicability of our technique to a range of bacterial species and exploit its high throughput to expose hidden contributions of bacterial individuality to population-level variability in motile behaviour. The simplicity of this powerful new tool for bacterial motility research renders 3D tracking accessible to a wider community and paves the way for investigations of bacterial motility in complex 3D environments.

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Rapid, High-Throughput Tracking of Bacterial Motility in 3D via Phase-Contrast Holographic Video Microscopy

Cited by 36 publications

References 46 publications

Statistical parameter inference of bacterial swimming strategies

Statistical parameter inference of bacterial swimming strategies

Visualizing Flagella while Tracking Bacteria

High-throughput 3D tracking of bacteria on a standard phase contrast microscope

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