Abstract
Bacteria sense chemicals, surfaces and other cells and move toward some and away from others. Studying how single bacterial cells in a population move requires sophisticated tracking and imaging techniques. We have established quantitative methodology for label-free imaging and tracking of individual bacterial cells simultaneously within the bulk liquid and at solid-liquid interfaces by utilizing the imaging modes of digital holographic microscopy (DHM) in 3D, differential interference contrast (DIC) and total internal reflectance microscopy (TIRM) in 2D combined with analysis protocols employing bespoke software. To exemplify and validate this methodology, we investigated the swimming behavior of Pseudomonas aeruginosa wild type and isogenic flagellar stator mutants (motAB and motCD) respectively within the bulk liquid and at the surface at the single cell and population levels. Multiple motile behaviours were observed that could be differentiated by speed and directionality. Both stator mutants swam slower and were unable to adjust to the near surface environment as effectively as the wildtype highlighting differential roles for the stators in adapting to near surface environments. A significant reduction in run speed was observed for the P. aeruginosa mot mutants, which decreased further on entering the near-surface environment. These results are consistent with the mot stators playing key roles in responding to the near-surface environment.
Importance We have established a methodology to enable the movement of individual bacterial cells to be followed within a 3D space without requiring any labelling. Such an approach is important to observe and understand how bacteria interact with surfaces and form biofilm. We investigated the swimming behavior of Pseudomonas aeruginosa, which has two flagellar stators that drive its swimming motion. Mutants that only had either one of the two stators swam slower and were unable to adjust to the near surface environment as effectively as the wildtype. These results are consistent with the mot stators playing key roles in responding to the near-surface environment, and could be used by bacteria to sense when it is near a surface.
Footnotes
↵1 KMSD has widely been used to characterise the movement of particles, enabling directed, Brownian and confined movement to be defined. A number of different examples of bacterial tracks and the associated KMSD measurements are shown in Fig. SI5. Tracks travelling directionally were observed to produce a linear relationship between the log of MSD over the log of time intervals with a slope approaching 2 (Fig. S5A). A track characterised by frequent oscillations had a reduced KMSD of 1.56 (Fig. S5B), whilst the drifting of a non-motile bacterium had a KMSD closer to 1 (Fig. S5C). A bacterium attached to the surface and therefore confined has a KMSD of approximately 0 (Fig. S5D). A KMSD below 2 was also observed for a bacterium travelling in circular trajectories (Fig. S5E) or spinning (Fig. S5F). In this case a linear relationship between the ln of MSD and ln of δt was observed up to the time interval associated with a complete oscillation, whereupon a plateau in the log MSD was observed at a position determined by the diameter of the curved path (Fig. S5F). In cases where the bacterium experienced oscillating movement over short time scales (fluctuating motion) and directional movement over larger times scales (mean motion) two slopes were observed on the log-log plot of MSD and δt (Fig. S5G), whereupon the two slopes were indicative of the directionality of the two movement types. As directional movement of the bacteria was of interest for comparing trajectories and the oscillating movement of the bacteria over short time frames was undersampled (Fig. S1) the KMSD value was calculated over δt values of 50 to 1000 ms. Changes in the bacterial movement during a single track caused by reversal events or attachment or detachment events resulted in spurious measurements of KMSD (Fig. S5H-I). For this reason tracks were split when attachment, detachment or reversal events were observed prior to KMSD analysis.