Dataset: Dynamic Mode Structure of Active Turbulence Modeling Results from 2019-2022 (VIC project)

Culturing:

Wild-type Bacillus subtilis bacteria (strain OI1084) were taken from −80°C frozen stock and streaked onto 1.5% agar plates prepared with Terrific Broth (TB, Sigma). Plates were incubated at 25°C for 24 hours, after which time a single colony from the plate was used to inoculate an overnight liquid TB culture at 30°C with shaking (200 rpm). The bacterial suspension was then subcultured (1.5 ml of cell culture into 60 ml of pre-warmed TB) and grown at 35°C and 200 rpm for 6 hours to mid-log phase (OD600 ≈ 0.2). Immediately prior to experiments, dense cell suspensions (∼ 1010 cells.ml−1) were prepared by centrifugation at 5000 g for 5 minutes, and the pellet was resuspended with 2 μl of fresh TB media.

 

Microfluidics and image analysis

Polydimethlysiloxane (PDMS) microfluidic channels were fabricated through soft lithography and plasma bonded to No. 1 thickness glass coverslips. The PDMS channels were thinly cast to ensure ample diffusion of oxygen to the bacterial suspension and prolonged cell activity. Dense cell suspensions were gently loaded into the microfluidic devices via pipette, and the channel inlet and outlet were sealed with wax to prevent residual flows. For all experiments, bacterial suspensions were imaged with brightfield illumination on an inverted microscope (Nikon Ti-E) using a sCMOS camera (Zyla 5.5, Andor Technology). Time-resolved velocity fields, u(x, t), of the bacterial suspensions were measured by performing Particle Image Velocimetry (PIV) using PIVLab implemented in MATLAB. The subsequent velocity fields were then lightly smoothed using a Guassian kernel with a standard deviation of one PIV pixel (1.73 μm) in space and one frame (9.5 ms) in time. Vorticity fields, ω(x, t), were computed from measured velocity fields using central differencing (MATLAB).

 

Bulk suspensions with decaying activity (quasi-2D)

To capture the bulk dynamics of dense bacterial suspensions in the absence of lateral wall effects, large microfluidic chambers (2 mm ×2 mm ×26 μm) were prepared, where the side length corresponds to ≈80 correlation lengths of the turbulent bacterial suspension. Imaging was performed with a 20 × objective (0.45 NA) at 105.5 fps. Bacterial activity was varied using a previously established approach. Briefly, the cell suspensions were imaged periodically over the course of 30 minutes, during which time the cell swimming speed naturally decayed due to oxygen depletion, where the decay rate of cell activity was controlled via the thickness of the PDMS device. Without the need to manipulate the cell suspension, this approach ensured that the bacterial concentration was constant across varying activity levels. Seven data sets were captured in total, which consisted of 6, 300 frames each (≈ 1 min per video) and a 2 − 3 min delay between acquisitions. Data analysis was restricted to the central portion of the chamber, ≈ 30 correlation lengths from the lateral boundaries.

 

Cell suspensions under varying confinement

To quantify POD modes for bacterial suspensions under varying degrees of confinement experiments from Wioland et al (2016). were replicated with minor modifications. Microfluidic devices (19 µm deep) were fabricated, which comprised a series of racetrack geometries connected by narrow inlets (30 µm wide). Nine racetrack widths were chosen between 30 µm ≤ W ≤ 171 µm in fractional increments of our measured characteristic vortex size (38 µm) taken as the minimum point in the spatial ACF in quasi-2D conditions (Fig. 1C, dotted red line). Cell suspensions were imaged at 40× (0.6 NA) magnification and 100 fps for 10 s per channel width. All confined microfluidic geometries were simultaneously loaded with the same cell suspension and imaged within the first 10 min of loading to ensure consistent bacterial activity. Experiments were 8 repeated across multiple days with freshly cultured bacteria to verify repeatability. The net flow ψ was calculated following the definition in [18]: ψ = |(Σu · eˆx) / (Σ||u||)|, where eˆx is the unit vector along the principal channel direction and the sum is over all PIV sub-windows over 5 s (500 frames) of video. ψ = 1 indicates uni-directional circulation flow around the racetrack, and ψ = 0 corresponds to a globally stationary suspension. The stream-wise flow profiles, F(y), were generated from the velocity field by averaging over time and space as F(y) = hu(x, y, t) · eˆxi(x,t) , where eˆx was chosen as defined in [18], such that F(y) is on average positive.