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Microbial Motility in 3-D Extending the Reach of Phase Contrast Microscopy to Track the Three- Dimensional Motility of Microbes from Woods Hole, MA

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Microbial Motility in 3-D Extending the Reach of Phase Contrast Microscopy to Track the Three- Dimensional Motility of Microbes from Woods Hole, MA Microbial Motility in 3-D Extending the reach of phase contrast microscopy to track the three- dimensional motility of microbes from Woods Hole, MA. Max Villa, Microbial Diversity 2016, Marine Biological Lab, Woods Hole, MA, Home Institution: Duke University, Durham, NC Abstract Bacteria solve complex 3D optimization problems to search for energy sources in oligotrophic environments. However, until now, accessing their 3D motility patterns has been limited to expensive and complex microscopy systems. Herein, a recent algorithm that using the diffraction patterns of out-of-focus bacteria to determine their Z-location is implemented and applied to a diverse collection of marine bacteria isolated from around Woods Hole, MA. Introduction We fundamentally rely on the concept of search. Google, Yahoo, Baidu and others have made search a modern necessity and changed our vernacular (“you can google it”). Microbial chemo- and phototaxis (“search”) in oligotrophic marine environments is essential to survival and to our understanding of how microbes influence the ecology of their environment. Patterns of microbial motility can help us better understand how bacteria sense and respond to chemical cues in their microenvironment.1,2, 3 Studying motility in the context of populations can provide insights into variations in their behavior across the population, so-called ‘bacterial individuality’.4,5 Finally, few models exist to quantitatively connect genetics to behavior. 6 High throughput tracking of bacteria is an ideal system for efficiently producing large datasets to probe the connection between behavior and genetics. A deep understanding of diverse microbial motility should lead to more predictive models of how microbes shape our environment. Furthermore, insight into biological solutions to hard optimization problems could yield new algorithms for robotics and computation.7 Microbial motility exists in three-dimensional space. Observation of full 3D movement would lead to more accurate track measurements such as velocity and turning angle. However capturing three-dimensional motility must overcome the limitation of shallow depth-of-field inherent in high NA objectives. Many microbiologists are familiar with the experience of observing motile cells move in and out of the focal plane, capturing movement for a few seconds and then zipping out of focus. This challenge was first overcome in 1972 by Berg and Brown using a custom microscope that automatically tracked the focal position of a microbe as it moved throughout a sample chamber.1 This led to the first glimpse of true 3D microbial motility in a set of chemotaxis experiments. While a technical tour-de-force, this method could only track one microbe at a time. By comparison, later methods such as digital holographic microscopy (DHM) could track the 3D position of multiple microbes simultaneously.8 DHM works by illuminating the sample with a collimated light source, typically using a laser, and using the 2D interference patterns from the incoming and scattered light to calculate an image in 3D space. Yet another approach to track bacteria in 3D is a so-called “de-focussed” imaging method. This approach follows from the observation that a microbe observed by phase contrast outside of the focal plane produces a specific diffraction pattern that reflects its z-position away from the focal plane. Taute et al. recently developed an algorithm that translates the diffraction rings into 3D motility tracks with improved z- resolution than previous de-focussed methods.4 This approach combines high throughput acquisition of multiple bacteria simultaneously with a setup most labs are familiar with – phase contrast microscopy. The goals of this project are to (i) implement a 3D tracking method with phase at MBL, (ii) apply tracking method to a diverse sample of marine bacteria, and (iii) compare motility patterns with quantitative metrics. Many bacterial taxa have not been well characterized in terms of their 3D motility. It was therefore hypothesized that if enough diverse taxa were tracked in 3D, perhaps novel motility patterns would be observed. Methods Isolation and culture A variety of strains and environmental samples from the surrounding Woods Hole were investigated (Table 1). The Bacillus and Vibrio strains originated from the isolations performed during the laboratory section of the course following the spore-forming and bioluminescent enrichments, respectively. Putative Thiovulum strains (SWT) were found in a section of sediment that was placed in the seawater table. An unknown sulfur oxidizing bacteria (GC1) was isolated from sediment found in Sippewissett marsh after a biofilm formed on the side of the culture tube. Genetic Analysis Colony PCR was performed on isolates following the laboratory manual. Forward and Reverse reads were aligned using CLUSTAL Omega and concatenated manually before a BLAST search was performed. Microscopy All microscopy was performed on a Zeiss Observer.Z1 inverted scope with a N-Acroplan 40x 0.65 NA Ph2 (420961-9911). Imaging chambers were created by adding three layers of parafilm on either side of a microslide and adding a 500 µm thick coverslip on top. The slide-parafilm-coverslip chamber was heated briefly on a hotplate on low to seal the coverslip to the parafilm. After allowing to chamber to cool, a dilute cell suspension (OD ~0.001) was added to the chamber and sealed with Valap (equal parts vaseline, lanolin, and paraffin) to prevent evaporation. The objective lens is optimized for a coverslip thickness of 170 microns. Therefore the thicker 500 micron coverslip will introduce spherical aberrations that result in an asymmetric diffraction pattern about the focal plane. This is important so the algorithm can distinguish between cells above and below the focal plane. A reference stack was generated by taking a z-stack of 1 µm beads embedded in a 1% polyacrylamide gel. However, the averaged reference stack that was provided with the software worked well and was used instead. The reference stack will depend on the optical components and size of bacteria to be imaged and is thus ideally generated by the user for his/her experimental conditions. Time-lapse videos of bacterial motility were recorded at the maximal frame rate in ‘burst mode’ with the Zen imaging software, translating to an imaging interval of 0.0078 seconds. One thousand frames were recorded per each time lapse and exported as a .tif stack. Chemotaxis experiments Briefly, the Vibrio samples were resuspended in seawater and added to an imaging chamber. Then a flattened glass capillary tube was filled with SWC medium and inserted into the side of the chamber. Time lapse acquisition proceeded as described above. Motility Tracking Stacks were resized and converted to 16-bit using a custom ImageJ macro (provided in the appendix). Then they were loaded into MATLAB and the 3D Tracking software (available through K. Taute on request) background corrects the stack, and performs tracking. At each time step, bacteria are located in the x-y plane and each 2D diffraction pattern is compared to a diffraction pattern from the reference stack via a cross-correlation function. If threshold values are met, a new microbe position in x-y-z is added to a table for each track. The resultant output is tables of x-y-z values as a function of frame for each bacterial track. Velocity calculation from 3-D positional information was performed using a custom MATLAB script (provided in the appendix). Results Several different patterns of microbial motility were observed. All taxa displayed beautiful arcing dives and ascents. Variation in motility behavior within a population was also apparent in nearly all runs. The characteristic “flicks” of Vibrios was present; where bacteria make a sharp turn, reverse motion along the same path, and then redirection along another arcing turn. Vibrios also would occasionally display false and complete looping behavior (Fig. G). Some of the Vibrio runs were much longer than the field of view. As expected, but cool nonetheless, when Vibrios near a chemical gradient the frequency of the redirection increases, resulting in fast switching forward and reverse motility (Figure 3L and 3M). By contrast the Bacillus species had a more “run and tumble” motility (Fig. A), wherein longer runs are terminated by bacterial tumbling and redirection. Interestingly, the large sulfur bacteria displayed a motility pattern wherein runs were terminated by sharp redirects at what appears to be 90° angles (Fig. E). Furthermore, the large sulfur bacteria displayed a helical procession about the velocity vector, visualized by the helical motion blur in the images – despite a 10 millisecond frame interval. The sulfur bacteria were also the fastest of the bacteria examined, moving at a rate of more than 400 microns/second. Sample Code BLAST hit Source Enrichment Culture Medium Cult. Temp. [° C] MV6 Bacillus altitudinis Trunk River pond Pasteurization 5YE 30 MV8 Bacillus stratosphericus Trunk River pond Pasteurization 5YE 30 HHM1 Vibrio Cholerae Trunk river outflow Plating on SWC SWC 30 GC1 - Sippewissett Sediment - Sippewissett - seawater SWT - Trunk river pond - Environmental Seawater table sample Table 1 | Strain information and culture conditions. Figure 1 | Principle of 3D tracking using Phase Contrast microscopy. (A) Z-stack of a 1 um bead viewed side-on. The asymmetric diffraction pattern can be observed. (B) Extracted slice from the bead stack shown in A above the focal plane (FP). (C) Extracted slice from the bead stack shown in A below the focal plane (FP). A reference stack such as this is used to compare with the diffraction patterns of a similiarly sized bacterium and deduce the z-position of the bacterium with respect to the focal plane. Figure 2 | Tracking validation in x-y-z. (A) Inverted maximum intensity Z-projection of motile Vibrios. (B) 3D tracking output of the stack shown in A, viewed in the x-y plane. (C) Overlay of tracking output from (B) on the Z-projection in (A) showing good correlation between calculated and actual tracks in x-y.
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