Login processing...

Trial ends in Request Full Access Tell Your Colleague About Jove

Immunology and Infection

Kinetic Visualization of Single-Cell Interspecies Bacterial Interactions

doi: 10.3791/61376 Published: August 5, 2020
Kaitlin D Yarrington*1, Andrea Sánchez Peña*1, Dominique H Limoli1
* These authors contributed equally


Polymicrobial communities are ubiquitous in nature, yet studying their interactions at the single-cell level is difficult. Thus, a microscopy-based method has been developed for observing interspecies interactions between two bacterial pathogens. The use of this method to interrogate interactions between a motile Gram-negative pathogen, Pseudomonas aeruginosa and a non-motile Gram-positive pathogen, Staphylococcus aureus is demonstrated here. This protocol consists of co-inoculating each species between a coverslip and an agarose pad, which maintains the cells in a single plane and allows for visualization of bacterial behaviors in both space and time.

Furthermore, the time-lapse microscopy demonstrated here is ideal for visualizing the early interactions that take place between two or more bacterial species, including changes in bacterial species motility in monoculture and in coculture with other species. Due to the nature of the limited sample space in the microscopy setup, this protocol is less applicable for studying later interactions between bacterial species once cell populations are too high. However, there are several different applications of the protocol which include the use of staining for imaging live and dead bacterial cells, quantification of gene or protein expression through fluorescent reporters, and tracking bacterial cell movement in both single species and multispecies experiments.


Polymicrobial communities are common in nature, spanning a variety of environmental1,2,3 and human niches4,5. Some of the most notorious polymicrobial infections in human disease include dental biofilms6, chronic wounds7,8, and respiratory infections in individuals with chronic obstructive pulmonary disease9, ventilator-associated pneumonia10, and the genetic disease cystic fibrosis (CF)11,12. These infections are often composed of diverse microbial species; however, a recent focus on the interactions between the Gram-positive bacterium Staphylococcus aureus and the Gram-negative bacterium Pseudomonas aeruginosa has emerged. Studies including patients coinfected with these organisms and in vitro analyses reveal both competitive and cooperative interactions that can have profound and unexpected influences on disease progression, microbial survival, virulence, metabolism, and antibiotic susceptibility (reviewed in detail by Hotterbeekx et al. 201713 and Limoli and Hoffman 20193).

The growing interest in interspecies interactions during infection has yielded a variety of methods for studying polymicrobial community behaviors. Typically, these studies have utilized plate or broth-based assays to investigate the phenotypic differences between monoculture and coculture. For example, coculturing P. aeruginosa and S. aureus on solid surfaces has allowed for visualization of growth inhibition or changes in colony phenotype, pigment, or polysaccharide production14,15,16. Mixed species biofilms, on biotic or abiotic surfaces, as well as coculturing bacterial species in liquid culture also has enabled measurement of changes in growth, metabolism, antibiotic tolerance, competition and viability, in addition to gene and protein expression17,18. While these bulk culture experiments have revealed insight into how P. aeruginosa and S. aureus might influence one another on the community-scale, they are unable to answer important questions about the interactions that take place at the single-cell level. The method presented here adds to the approaches for studying interspecies interactions by focusing on the changes in movement, cell viability, and gene expression of single cells within a cocultured community over time.

Single-cell interactions can widely differ from the interactions that take place in a bulk community of cells. Through single-cell analysis, heterogeneity within a community can be quantified to study how spatial placement of cells influence community dynamics or how gene and protein expression levels change within individual members of a group. Tracking cells can also provide insight into how single cells move and behave over time, through multiple generations. By tracking cell movement and changes in gene expression concurrently, correlations can be made between gene fluctuations and corresponding phenotypes. Previous protocols for studying individual bacterial species at the single-cell level have been described. These studies take advantage of live-imaging cells over time in a single plane, and have been useful for observing phenotypes like cell division and antibiotic susceptibility19,20. Additional live-imaging microscopy has been utilized to monitor growth, motility, surface colonization and biofilm formation of single bacterial species21,22,23. However, while these studies have been insightful for understanding the physiology of bacteria in monoculture, experiments for observing single-cell behavior of multiple bacterial species over time in coculture are limited.

Here, previous protocols used for single-species imaging have been adapted to study interactions between P. aeruginosa and S. aureus. These organisms can be differentiated under phase contrast based on their cell morphologies (P. aeruginosa are bacilli and S. aureus are cocci). Development of this method recently enabled the visualization of previously undescribed motility behaviors of P. aeruginosa in the presence of S. aureus24. P. aeruginosa was found to be capable of sensing S. aureus from a distance and responding with increased and directional single-cell movements towards clusters of S. aureus cells. P. aeruginosa movement towards S. aureus was found to require the type IV pili (TFP), hair-like projections whose coordinated extension and retraction generate a movement called twitching motility25.

These studies demonstrate the utility of this method for interrogating earlier interactions between species. However, imaging at high cell densities at later interaction time points is difficult given that single layers of cells can no longer be identified, which mostly poses issues during post-imaging analysis. Given this limitation, the method is best suited for earlier interactions that could then be followed up with traditional macroscopic assays at higher cell densities representative of later interactions. Additional limitations of this method include the low-throughput nature, since only one sample can be imaged at a time and the cost of the microscope, camera, and environmental chamber. Moreover, fluorescence microscopy poses risks to the bacterial cells like phototoxicity and photobleaching, therefore limiting the frequency that fluorescence images can be acquired. Lastly, the agarose pads used in this method are highly susceptible to changes in the environment, making it critical to control for conditions like temperature and humidity, given that the pads can start to shrink or expand if the conditions are not correct. Finally, while this method does not mimic the host environment, it provides clues for how different bacterial species respond on surfaces, which can be followed-up in assays designed to mimic environmental/host conditions.

This method differs from previous studies tracking single-cell movement, in that cells are inoculated between a coverslip and agarose pad, restricting cells to the surface. This enables cell tracking over time in a single plane; however, limits cycles of transient surface engagement observed when cells are submerged in liquid26. An additional benefit of imaging bacteria under an agarose pad is that it mimics macroscopic plate-based sub-surface inoculation assays classically used to examine P. aeruginosa twitching motility25. In this assay, bacterial cells are inoculated between the bottom of a Petri dish and the agar, keeping the cells in a single plane as they move across the bottom of the dish outward from the point of inoculation, much like this microscopy protocol.

The time-lapse microscopy protocol for visualizing interspecies interactions presented here consists of 1) preparing the bacterial sample and agarose pad, 2) selecting microscope settings for imaging acquisition and 3) post-imaging analysis. Detailed visualization of cell movement and tracking can be performed by acquisition of images at short time intervals by phase contrast. Fluorescence microscopy can also be utilized to determine cell viability or gene expression over time. Here, we show one example of adaptation for fluorescence microscopy through the addition of viability dyes to the agarose pads.

Subscription Required. Please recommend JoVE to your librarian.


NOTE: A full description and catalog numbers for all supplies in this protocol can be found in the Table of Materials.

1. Preparation of M8T minimal media

  1. Prepare 1 L of M8 minimal salts base (5x) by dissolving 64 g of Na2HPO4·7H2O, 15 g of KH2PO4, and 2.5 g NaCl in 800 mL of ultrapure water (UPW, resistivity 18 MΩ/cm) in a 2 L bottle. pH to 7.6. Complete volume to 1 L with UPW. Autoclave for 45 min.
  2. Prepare 500 mL of a glucose solution (20% w/v) by dissolving 100 g of glucose in 400 mL of UPW in a 1 L bottle. Complete solution to 500 mL with UPW. Autoclave for 45 min.
  3. Prepare 500 mL of a tryptone solution (20% w/v) by dissolving 100 g of tryptone in 400 mL of UPW. Complete to 500 mL with UPW. Autoclave for 45 min.
  4. Prepare 1 L of M8 + 10% tryptone (M8T) minimal media by adding 200 mL of 5x M8 minimal salts (1x final), 10 mL of 20% glucose (0.2% final), 1 mL of 1 M MgSO4 (1 mM final), and 50 mL of 20% tryptone (1% final) to 600 mL of UPW. Complete to 1 L with UPW. Filter through a 0.2 μm sterile filter into a sterile 500 mL media storage bottle.

Day 1:

2. Preparation of bacterial overnight cultures

  1. Inoculate 5 mL of M8T minimal media with a single colony of P. aeruginosa or S. aureus (including antibiotics when appropriate) and incubate overnight at 37 °C with aeration for no longer than 16 h.
    NOTE: The bacterial pathogens P. aeruginosa and S. aureus were used for this method, because they are commonly coisolated from chronic infections, and studying their interactions is important to understand how they contribute to patient outcomes during polymicrobial infections. Other bacterial species could be used depending on the focus of the study.

Day 2:

3. Subculture of bacterial strains

  1. Subculture P. aeruginosa 1:500 and S. aureus 1:1000 in 5 mL of fresh M8T (include antibiotics when appropriate). Incubate with aeration at 37 °C until cultures reach mid-log phase (OD600 = ~0.3 - 0.5).

4. Preparation of materials for pad molds

  1. Prepare metal spatulas by heating the end of a flat, rounded laboratory spatula with a Bunsen burner until half of the flat end can be bent to a 90° angle. Heat the end of another flat, rounded laboratory spatula and slightly bend the last 10 mm to a 45 °C angle.
  2. Cut off the four corners of the silicone molds so that the molds fit inside a 35 mm dish.
  3. Sterilize the spatulas and a pair of tweezers by adding 70% ethanol and passing them through the flame of the Bunsen burner.
  4. Clean the dish and silicone molds with 70% ethanol and dry them with lint-free wipes.

5. Preparation of agarose pads

NOTE: The pads are prepared with the M8T minimal media as the nutrient source for the bacteria used in this protocol. However, the nutrients used in the pads can be modified for different organisms.

  1. Melt 2% low-melt agarose in 10 mL of M8T in a clean 50 mL Erlenmeyer flask. Microwave in short intervals (2-5 s) until the agarose is in solution in order to prevent the contents of the flask from boiling over. Once melted, let cool in a 50 °C water bath for at least 15 min.
  2. Prepare molds by aligning the silicone cutout with the opening in the 35 mm dish and tap lightly with spatula to secure the silicone to the dish, and to remove all air bubbles between the mold and the dish.
  3. Once cool, pipette 915 µL of molten agarose into the mold. Leave the lid ajar and let the pad dry at room temperature for 30 min.
  4. Cover the dish with the lid and leave at room temperature for an additional 2 h.
  5. Prepare humidity wipes by tightly rolling up a lint-free wipe. Place the rolled wipe inside a sterile Petri dish and evenly add 500 µL of sterile water across the wipe. Warm to 37 °C for 1 h.
  6. Warm the pad and a sterile 35 mm dish to 37 °C for 1 h.

6. Preparation of bacterial cells and inoculating pads

  1. Measure the OD600 of each subculture and dilute P. aeruginosa to an OD600 = 0.03 and S. aureus to an OD600 = 0.10 in M8T prewarmed to 37 °C. Mix P. aeruginosa and S. aureus in a 1:1 ratio and vortex.
    NOTE: If strains require antibiotics, the antibiotics can be added to the overnight and subculture, but should not be added when mixing species for imaging if it affects the other species in the coculture. Plasmid stability and the effects of antibiotics on all species in the coculture will need to be determined for each organism/plasmid being used.
  2. Pipette 1 µL of coculture evenly across the bottom of a pre-warmed, sterile 35 mm glass coverslip dish.
  3. Remove the silicone cutout from the mold using sterile tweezers.
  4. Remove the pad from the dish using sterile spatulas.
    1. Slip the slightly bent spatula under the edge of the pad, while holding the mold upside down, to drop it out onto a sterile Petri plate lid.
      NOTE: Take care not to force the pad out or it will rip. Keep track of which side of the pad is the bottom.
  5. Transfer the pad to the dish with the bacterial cells, bottom-side-down, by sliding the 90° angled spatula under the pad and placing it on top of the inoculated coverslip. Use the 90° angled spatula to make the pad flush against the coverslip and gently press out any air bubbles.
  6. Remove excess moisture from moist wipes then place around the edge of the dish, making sure it does not touch the pad. The sample is now ready for imaging.

7. Setting up the microscope for live imaging

  1. Warm environmental chamber to 37 °C at least 2 h prior to experimental set-up.
  2. Turn on all components including microscope, computer, and light sources for brightfield and fluorescence imaging.
  3. Open the imaging software and make sure that light sources are connected and running.
  4. Perform Köhler illumination27 to align all image planes.
    1. First, bring marked coverslip into focus with a 20x objective using a “dummy” dish. Make sure the condenser turret is set to the “open” position.
      NOTE: Köhler illumination should be performed for each unique objective/sample to properly align image planes. However, focus and alignment with the “dummy” dish on lower magnification expedites set-up on live samples at higher magnification to limit time between set-up and experiment start time.
    2. Focus the condenser.
      1. Close the field diaphragm.
        NOTE: An octagon-shaped aperture should appear. If the condenser is completely out of focus, the entire field of view (FOV) will appear dark.
      2. Rotate the condenser focusing knobs until the octagon edges are crisp.
        NOTE: The light intensity will increase as the image planes approach the correct alignment.
    3. Align the condenser.
      1. Center the field condenser by adjusting the aligning knobs.
        NOTE: The octagon should be centered to the middle of the FOV. The aligning knobs differ depending on the microscope. For example, some microscope condensers have knobs, while others have screws requiring a screw driver.
    4. Focus the lamp filament and adjust the condenser aperture.
      1. Place a phase telescope or Bertrand lens into the light path to observe the back focal plane of the objective.
        NOTE: There should be two concentric circles.
      2. Turn the Bertrand lens focus knob until the rings look crisp.
      3. Remove the Bertrand lens from the light path.
    5. Open the field diaphragm until the octagon is just outside of the FOV.
    6. Change to the 100x objective and slide the matching phase ring into place before adding a drop of immersion oil, and place the prepared sample dish on top.
    7. Perform Köhler illumination on the 100x objective with the bacterial sample dish.
  5. Focus on the bacteria using the fine adjustment only. Once the bacteria in the FOV are focused through the eyepiece, switch the light path to the camera by pressing the camera button on the microscope.
  6. Click the Phase option in the imaging software.
  7. Adjust the percentage of DIA LED light emitted by selecting the light source in the software and either manually entering the desired percentage of light to be used or sliding the bar on the light percentage scale.
  8. Adjust the DIA LED light exposure time by clicking on the light source and either manually entering the desired exposure time or selecting an exposure time from the provided drop-down menu.
    NOTE: The exposure time will vary depending on the camera being used.
  9. If using fluorescence, adjust the camera settings in each corresponding channel (i.e., TxRed, GFP), by clicking on the fluorescent channel of interest.
    1. Set the percentage of fluorescence light emitted, then adjust the exposure time (as performed in steps 7.7 and 7.8 for DIA LED light).
    2. Alternatively, change the bit depth to adjust the dynamic range by selecting one of the other bit depth options in the visualization controls drop-down menu.
  10. Choose the XY positions of interest by clicking on the XY option in the acquisition controls menu.
    1. Move the stage position with the joy stick, or by clicking and dragging the FOV on the screen, and click on the empty box to save the X and Y coordinates of a specific position.
      NOTE: Selection of no more than three different XY positions, as close together as possible, is recommended for time-lapse acquisition.
  11. Turn on the perfect focus system (PFS) by either clicking the PFS box on the XY tab of the acquisition control menu or pressing the PFS button on the joy stick control panel.
  12. Rotate the fine adjustment knobs to focus on the bacterial cells.
  13. Click the PFS button for each XY position, once cells are in the desired plane of focus.
    NOTE: PFS compensates for drift in the Z-axis during time-lapse experiments. This is necessary to maintain focus of bacterial cells over time. Different manufactures have different compensation systems.
  14. Choose the image acquisition conditions including acquisition interval and frequency for each channel (e.g., phase contrast and each fluorophore) by selecting from the options in the acquisition controls menu.
    NOTE: For the experiments presented here, phase contrast images are acquired at intervals every 5-10 s while fluorescence images in the GFP and TxRed channels are acquired every 20 min.
  15. Begin imaging once the microscope and acquisition settings are set up.

8. Optional: Modifications for live/dead imaging

  1. Melt 2% agarose in 10 mL of M8T and let cool in 50 °C water bath for at least 15 min.
  2. Add 1 mM of propidium iodide to the molten agarose.
  3. Once cooled, pipette 915 μL of agarose in the prepared mold.
  4. Leave the lid ajar and let pad dry at room temperature for 30 min. Protect from light.
  5. Cover the dish with the lid and leave at room temperature for an additional 2 h.
  6. Prepare humidity wipes.
    1. Roll a lint-free paper wipe up tightly.
    2. Place the wipe in a sterile Petri dish and add 500 µL of sterile water to the wipe.
    3. Incubate at 37 °C for 1 h.
  7. Incubate the pad and a sterile 35 mm dish at 37 °C for 1 h.
  8. Proceed to inoculate the dish as indicated in section 6: Preparation of bacterial cells and inoculating pads.

9. Data analysis

  1. Identification of cells
    1. Open image file in the imaging software and crop the file to only include the frames to be used for tracking, zoomed in to the cells of interest, and only in the phase contrast channel.
      NOTE: The cropped file can be saved as a new file in which tracking data can be stored without interfering with the original file.
    2. Select the option to choose regions of interest (ROI) in the analysis controls menu and define ROIs by tracing either individual bacterial cells or clusters of cells in the first frame to be used for analysis.
      NOTE: The ROIs can either be defined manually or as binaries.
      1. Manually define ROI
        1. Trace the perimeter of each individual bacterial cell or clusters of cells to manually define the ROIs.
          NOTE: In the analysis software, P. aeruginosa, or other rod-shaped cells, can be manually traced by selecting the Ellipse ROI and drawing an ellipse adjusted to the size of the bacterial cell. Alternatively, the Polygon ROI option can be selected to trace non-traditional-shaped ROIs, such as clusters of cells.
      2. Identify binary ROIs
        1. Click the Binary to ROI option in order to define binary ROIs.
          NOTE: Objects are defined in a binary layer based on separation of the darker-pixelated bacterial cells from the lighter-pixelated background in the phase contrast channel.
        2. To threshold the cells, select the Threshold option in the analysis controls menu. Select the channel of interest and slide the bars in the fluorescence histogram to adjust the threshold interval values.
          NOTE: Binary object identification for ROIs can also be defined in fluorescent images by thresholding the bacterial cells. Thresholding establishes which fluorescence intensities are considered objects and what fluorescence intensities constitute the background.
  2. Cell tracking
    1. To manually track ROIs, select the next frame in the imaging sequence and adjust the position of the ROIs by clicking and dragging each ROI to align with the new position of the original bacterial cell.
      NOTE: If the bacterial cells have not changed position, the ROIs do not need to be moved.
    2. Repeat in all sequential frames for which cells are to be tracked.
    3. As cells divide, define the daughter cells as new ROIs, as described in step 9.1, and begin tracking the newly divided cells.
      NOTE: If cells are identified as binaries, use the Track Binaries function to automatically track ROIs in selected frames.
    4. Once cells have been tracked through all selected frames, export the data to be analyzed.
    5. Open the data spreadsheet and identify the measurements required for analysis (i.e., object speed, acceleration, or path length).
      NOTE: In the case of measuring directedness, the Path Length and Line Length measurements are required. The Line Length is a measurement of the Euclidian distance, or the straight distance from the track origin to the edge of the S. aureus colony. The Path Length is a measurement of the accumulated distance, or the sum of track segments from all frames. Directedness can be calculated as a ratio of the Euclidian distance, D(E), (Line Length), over the accumulated distance, D(A), (Path Length).
  3. Fluorescence quantification
    1. Define ROIs for fluorescent bacterial cells as described in step 9.1.
    2. Repeat tracing or movement of ROIs for bacterial cells or clusters in the remaining fluorescent frames.
    3. Export the generated table to a spreadsheet file for analysis of fluorescent intensity.
    4. In the data spreadsheet, look for the column with “Mean Intensity” which represents the average fluorescence intensity for the traced bacterial cell(s) ROI.
    5. Graph the Mean Intensity values to look at the changes in fluorescence over time.
      NOTE: The changes in fluorescence over time represent the fluctuation of gene expression for the fluorescently labeled gene of interest.

Subscription Required. Please recommend JoVE to your librarian.

Representative Results

Successful use of the described method will result in a series of frames that generate a video in which the interspecies interactions can be observed over time. The schematic in Figure 1 provides a visual to highlight the key steps involved in preparing materials for imaging. Use of this method has allowed the demonstration of P. aeruginosa cells exhibiting different behaviors in monoculture versus in coculture with S. aureus. Compared to the P. aeruginosa cells in monoculture that remain grouped in rafts, when in coculture with S. aureus, P. aeruginosa has increased single-cell motility towards S. aureus colonies (Figure 2A-2B). Fluorescently labeled bacterial strains also allow for visualizing mixed populations of bacterial species. Using GFP-labeled P. aeruginosa permitted the observation that after P. aeruginosa single cells increase in motility, they will surround and eventually invade S. aureus colonies (Figure 2C). Utilization of fluorescently-marked cells also allows for visualization of P. aeruginosa cell invasion into the S. aureus colonies for the first time (Figure 2C, bottom).

While the protocol yields high quality images for observing interspecies interactions, there are several common problems that can lead to poor quality frame sequences. Inconsistent humidity over the duration of the experiment and incorrectly dried pads are two common problems that lead to drift resulting from the pad shifting and dragging the cells with it out of the FOV (Figure 3A). Changes in humidity affect the dryness of the agarose pads. Increased humidity makes the pads too wet, allowing moisture to settle between the pad and the bottom of the glass-bottom dish. The moisture leaves a layer of liquid thick enough for motile cells to swarm or swim through and does not keep bacterial cells in a single plane. Meanwhile, decreases in humidity dry out the pad faster, which cause cells to drift early on. Another common mistake when using this method with fluorescence is acquiring fluorescent images too frequently or exposing bacterial cells to fluorescent light for too long. Short acquisition intervals for fluorescent images repeatedly excite fluorophores with high intensity light of a specific wavelength. Excited fluorophores then react with oxygen, causing degradation of the fluorophore. The resulting photobleaching depletes fluorescence until more of the fluorophore can be expressed and folded, but does not harm the bacterial cells themselves (Figure 3B). Loss of fluorescence, however, does interfere with measurements of gene/protein expression, leaving the cells markerless until the fluorophore can be fully synthesized and excited again. Moreover, the oxygen interacting with excited fluorophores can form reactive oxygen species (ROS). These ROS radicals then damage bacterial cells, ultimately becoming toxic and resulting in cell death within a few cell divisions (Figure 3C). The processes of photobleaching and phototoxicity can be easily seen as cells will first lose their fluorescence completely, and in subsequent frames, the cells will stop dividing and may eventually die (Figure 3B-3C). One final common issue when setting up the experiment is starting with too many cells per FOV or with cells too close to each other, which is generally less than 20 µm apart. Crowded cells in the first frame will yield clusters of dividing cells that simply merge into each other as they grow rather than interact. Additionally, cells that begin too close in proximity may not have sufficient time to establish a gradient of secreted signals to which the other species can respond (Figure 3D) whereas distant bacterial cells may not have the chance to encounter one another within the duration of the experiment.

Figure 4 shows an example of how bacterial cell viability can be visualized with this protocol by adding propidium iodide to the agarose pads. Propidium iodide is impermeable to live cells, but can enter cells with damaged membranes and bind to nucleic acids. Here mid-log GFP-labeled WT S. aureus were treated with media alone or with cell-free supernatant derived from P. aeruginosa and imaged immediately following treatment. Three different channels were imaged: Phase, TxRed and GFP. Bright green cells indicate live cells actively expressing GFP as seen for the S. aureus treated only with media (Figure 4A), and red cells indicate dead propidium iodide-stained S. aureus cells, after being treated with P. aeruginosa supernatant (Figure 4B). While only one time point is shown, this method can be adapted to determine cell viability during time-lapse live imaging.

Several post-imaging analyses can be performed to quantify aspects of interspecies interactions. For example, cell tracking can provide measurements for the directedness of P. aeruginosa single cell movements towards a cluster of S. aureus. The movements of individual P. aeruginosa cells are tracked from the frame a cell leaves the raft through the frame in which the cell reaches the S. aureus cluster (Figure 5A). The distance between the P. aeruginosa raft and the S. aureus cluster provide the Euclidian distance, D(E), while the total track lengths provide the accumulated distance, D(A) (Figure 5B). Directedness of each cell is calculated as a ratio of D(E)/D(A). In the coculture experiments, WT P. aeruginosa moved towards WT S. aureus with significantly higher directedness than towards S. aureus ΔagrBDCA, a mutant lacking Agr-regulated secreted factors, previously determined to be necessary for directional motility towards S. aureus24 (Figure 5C).

Figure 1
Figure 1: Schematic of the imaging setup protocol.
Overview of critical steps for preparation of bacterial cultures and agarose pads. Created with BioRender.com. Please click here to view a larger version of this figure.

Figure 2
Figure 2: Time-lapse, live-imaging microscopy shows differences in P. aeruginosa behavior when cocultured with S. aureus.
Representative snap shots of P. aeruginosa (bacilli, green) in monoculture (A) and in coculture with S. aureus (cocci, unmarked) (B). (C) Fluorescently-labeled bacteria allow for visualization of P. aeruginosa single cells invading S. aureus clusters. Phase contrast and GFP channel overlay (top) and GFP channel alone (bottom). Please click here to view a larger version of this figure.

Figure 3
Figure 3: Representative snap shots of common imaging issues that lead to poor image acquisition.
(A) Improperly dried pads and inconsistent humidity lead to drifting of cells across the FOV over the duration of imaging. The position of the founding cell is marked in each frame (green rod). (B) Photobleaching from exposure to light for too long will deplete detectable levels of fluorescence for a period of time, but does not kill the cells. (C) Phototoxicity as a result of frequent exposure to light leads to cell death. The first signs of phototoxicity are seen when cells stop fluorescing and fail to divide. (D) High initial inoculum crowds cells in the FOV and prevents observation of interspecies interactions. Please click here to view a larger version of this figure.

Figure 4
Figure 4: Comparison of live versus dead S. aureus cells.
Representative snap shots for GFP-labeled WT S. aureus treated with either medium alone (A) or cell-free P. aeruginosa supernatant (B). Cells were immediately imaged following treatment. Live cells (green) actively express GFP and exclude propidium iodide, while dead cells (red) lose GFP fluorescence and membrane permeabilization allows propidium iodide to enter the cells and bind nucleic acids. Please click here to view a larger version of this figure.

Figure 5
Figure 5: Cell tracking analysis of P. aeruginosa in coculture with S. aureus.
Previously, this method was used method to perform cell tracking of WT P. aeruginosa in coculture with either WT or ΔagrBDCA S. aureus. (A) Representation of P. aeruginosa single-cell tracks in a coculture with S. aureus ΔagrBDCA. (B) Schematic for the Euclidian distance (D(E)) and accumulated distance (D(A)) measurements used to determine directedness ((D(E)/D(A)). (C) Directedness measurements of single WT P. aeruginosa cells in coculture with WT and ΔagrBDCA S. aureus. This figure has been modified from Limoli et al. 201924. Please click here to view a larger version of this figure.

Supplemental File. Please click here to view a larger version of this figure.

Subscription Required. Please recommend JoVE to your librarian.


The methods presented here describe a protocol for live-cell imaging of bacterial species interactions at the single-cell level with modifications for other applications including cell tracking and monitoring cell viability. This method opens new avenues for studying single-cell behaviors of microorganisms in coculture with other species over time. Specifically, the protocol demonstrates the usefulness of this coculture method in observing bacterial surface behaviors, particularly when studying organisms that have both surface and liquid-associated appendages for motility. For example, by limiting bacterial movement to a surface in a single plane of focus, the increased and directional pili-mediated motility of P. aeruginosa in response to S. aureus can be visualized.

As previously mentioned, achieving optimal results with this imaging method requires consideration of several conditions, including temperature and humidity of the sample and imaging instruments (i.e., objectives and stage). For more tips and troubleshooting, see the Supplemental File 1. A critical step in successful use of the protocol is preparation of the agarose pads, as inadequately drying pads is one of the most common problems. As shown in Figure 3A, if the pads are not dried long enough, drift appears at the beginning of the time-lapse imaging, whereas pads that are dried for too long start to shrink and the cells drift out of the FOV a few hours into imaging. Ensuring that all materials are pre-warmed and maintained at uniform temperature and humidity over the duration of the experiment, through use of a stage-top incubator and damp lint-free wipes, will help reduce drift. It is also advised that a backup pad is always made in case the first pad is not dried properly or tears during transfer from the mold to the sample dish. Additionally, it is important to use a low-autofluorescence medium, both for growing bacterial cultures and for making the pads in order to minimize the background fluorescence from the medium when imaging the cells. It is recommended to use minimal media for microscopy, since rich media often have high autofluorescence. Starting with a low-density inoculum and even spatial distribution of cells in the FOV are also key factors in this method. Specifically, in prior studies evaluating P. aeruginosa and S. aureus interactions, this allowed the bacteria to generate a sufficient gradient of secreted factors that can then be detected by the other species present (Figure 2B).

Despite the benefits of this method, there are also limitations including its price, low-throughput nature, fluorescence restrictions, and high dependence on controlling environmental conditions. Figure 3B-3C show the major limitations of using fluorescence microscopy. As discussed in the results section, if the fluorescent images are captured in short intervals, photobleaching and phototoxicity can occur. In order to avoid these two outcomes, fluorescent image intervals should be taken far enough apart and with as low fluorescent light exposure time as possible to still adequately visualize the fluorophore. Additionally, when determining the interval for fluorescence imaging, it is important to consider the maturation time of each fluorophore. The fluorophores used in the P. aeruginosa and S. aureus strains shown in Figure 2, Figure 3 and Figure 4, for example, have a maturation time of about 20 minutes and can therefore be excited every 20 minutes without concern of potential photobleaching effects. Meanwhile, another disadvantage of this method is that it does not allow for observations of late interspecies interactions once cells reach a high cell density. In order to visualize individual bacterial cells, they must remain in a single plane of focus. However, once the population reaches a high cell density, the cells begin to grow in more than one plane.

This method can be modified to study different phenotypes such as cell viability (Figure 4) and expression of genes of interest (data not shown). Figure 4 shows an example of how the method has been adapted to visualize bacterial viability by adding propidium iodide to the agarose pads. Another application of this method is measuring bacterial gene/protein expression in coculture with another organism through fluorescent reporters. For example, multiple fluorophores can be incorporated into a plasmid vector or the bacterial chromosome to simultaneously study the expression of different genes or proteins. Here it is important to select fluorophores that do not have overlapping excitation and emission spectra. Lastly, the use of bacterial cell tracking in post-imaging analysis enables the directionality (Figure 5), speed and acceleration, among other measurements, to be calculated as well24.

Overall, this coculture imaging method adapted from previously described monoculture protocols enhances the ability to visualize behaviors of multiple bacterial species in coculture. This method offers the opportunity to study microbes from a mixed-culture perspective, which will increase understanding of how each species alters its behaviors in a single-cell manner, ultimately providing new insight into how bacterial species interact in polymicrobial environments.

Subscription Required. Please recommend JoVE to your librarian.


The authors declare that they have nothing to disclose.


This work was supported by funding from the Cystic Fibrosis Foundation Postdoc-to-Faculty Transition Award LIMOLI18F5 (DHL), Cystic Fibrosis Foundation Junior Faculty Recruitment Award LIMOLI19R3 (DHL), and NIH T32 Training Grant 5T32HL007638-34 (ASP). We thank Jeffrey Meisner, Minsu Kim, and Ethan Garner for sharing initial protocols and advice for imaging and making pads.


Name Company Catalog Number Comments
Agarose pads
35 mm Glass Bottom Dish with 20 mm Micro-well #1.5 Cover Glass Cellvis D35-20-1.5-N One for agarose pad molds, one for experiment
KimWipes Kimberly-Clark Professional 06-666A
Low-Melt Agarose Nu-Sieve GTG/Lonza 50081 For making agarose pads
Round-Bottom Spatulas VWR 82027-492
Round-Tapered Spatulas VWR 82027-530
Silicon Isolators, Press-to-Seal, 1 well, D diameter 2.0 mm 20 mm, silicone/adhesive Sigma-Aldrich S6685-25EA For agarose pad molds
Sterile Petri Plates, 85 mm Kord-Valmark /sold by RPI 2900
Tweezers VWR 89259-944
M8T Minimal Media
D (+) Glucose RPI G32045
KH2PO4 RPI P250500
MgSO4 Sigma-Aldrich 208094
NaCl RPI S23025
Na2HPO4.7H2O Sigma-Aldrich 230391
Tryptone BD Biosciences DF0123173
Andor Sona 4.2B-11 Andor 77026135 Camera. 4.2 Megapixel Back-illuminated sCMOS, 11 μm pixel, 95% QE, 48 fps, USB 3.0, F-mount.
Filter Cube GFP Nikon 96372 Filter cube
Filter Cube TxRed Nikon 96375 Filter cube
H201-NIKON-TI-S-ER Okolab 77057447 Stagetop incubator
Nikon NIS-Elements AR with GA3 and 2D and 3D tracking Nikon 77010609, MQS43110, 77010603, MQS42950 Software for data analysis
Nikon Ti2 Eclipse Nikon Model Ti2-E Microscope
CFI Plan Apo ƛ20x objective (0.75NA) Nikon MRD00205 Objective
CFI Plan Apo ƛ100x oil Ph3 DM objective (1.45NA) Nikon MRD31905 Objective
ThermoBox with built-in fan heaters Tokai Hit TI2TB-E-BK Enclosure
Bacterial Strains
Pseudomonas aeruginosa PA14 (WT) PMID: 7604262 Non-mucoid prototroph
Pseudomonas aeruginosa PA14 (WT) pSMC21 (Ptac-GFP) PMID: 9361441
Pseudomonas aeruginosa PAO1 (WT) pPrpoD-mKate2 PMID: 26041805
Staphylococcus aureus USA300 LAC (WT) PMID: 23404398 USA300 CA-Methicillin resistant strain LAC without plasmids
Staphylococcus aureus USA300 LAC (WT) pCM29 (sarAP1-sGFP) PMID: 20829608
Staphylococcus aureus USA300 LAC ΔagrBDCA PMID: 31713513
Viability Stain
Propidium Iodide Invitrogen L7012 LIVE/DEAD™ BacLight™ Bacterial Viability Kit



  1. Lamichhane, J. R., Venturi, V. Synergisms between microbial pathogens in plant disease complexes: a growing trend. Frontiers in Plant Science. 6, 385 (2015).
  2. Cursino, L., et al. Identification of an operon, Pil-Chp, that controls twitching motility and virulence in Xylella fastidiosa. Molecular Plant-Microbe Interactions. 24, (10), 1198-1206 (2011).
  3. Limoli, D. H., Hoffman, L. R. Help, hinder, hide and harm: what can we learn from the interactions between Pseudomonas aeruginosa and Staphylococcus aureus during respiratory infections. Thorax. 74, 684-692 (2019).
  4. Gabrilska, R. A., Rumbaugh, K. P. Biofilm models of polymicrobial infection. Future Microbiology. 10, (12), 1997-2015 (2015).
  5. Nobile, C. J., Mitchell, A. P. Microbial biofilms: e pluribus unum. Current Biology. 17, (10), 349-353 (2007).
  6. Marino, P. J., et al. Community analysis of dental plaque and endotracheal tube biofilms from mechanically ventilated patients. Journal of Critical Care. 39, 149-155 (2017).
  7. Frank, D. N., et al. Microbial diversity in chronic open wounds. Wound Repair and Regeneration. 17, 163-172 (2009).
  8. Fazli, M., et al. Nonrandom distribution of Pseudomonas aeruginosa and Staphylococcus aureus in chronic wounds. Journal of Clinical Microbiology. 47, (12), 4084-4089 (2009).
  9. Shimizu, K., et al. Pathogens in COPD exacerbations identified by comprehensive real-time PCR plus older methods. International Journal of Chronic Obstructive Pulmonary Disease. 10, 2009-2016 (2015).
  10. Behnia, M., Logan, S. C., Fallen, L., Catalano, P. Nosocomial and ventilator-associated pneumonia in a community hospital intensive care unit: a retrospective review and analysis. BMC Research Notes. 7, 232 (2014).
  11. Maliniak, M. L., Stecenko, A. A., McCarty, N. A. A longitudinal analysis of chronic MRSA and Pseudomonas aeruginosa co-infection in cystic fibrosis: a single-center study. Journal of Cystic Fibrosis. 15, (3), 350-356 (2016).
  12. Limoli, D. H., et al. Staphylococcus aureus and Pseudomonas aeruginosa co-infection is associated with cystic fibrosis-related diabetes and poor clinical outcomes. European Journal of Clinical Microbiology & Infectious Diseases. 35, (6), 947-953 (2016).
  13. Hotterbeekx, A., Kumar-Singh, S., Goossens, H., Malhotra-Kumar, S. In vivo and in vitro interactions between Pseudomonas aeruginosa and Staphylococcus spp. Frontiers in Cellular and Infection Microbiology. 7, (106), (2017).
  14. Smith, K., et al. Aspergillus fumigatus enhances elastase production in Pseudomonas aeruginosa co-cultures. Medical Mycology. 53, 645-655 (2015).
  15. Michelson, C. F., et al. Staphylococcus aureus alters growth activity, autolysis, and antibiotic tolerance in a human host-adapted Pseudomonas aeruginosa lineage. Journal of Bacteriology. 196, (22), 3903-3911 (2014).
  16. Ngamdee, W., et al. Competition between Burkholderia pseudomallei and B. thailandensis. BMC Microbiology. 15, 56 (2015).
  17. Heir, E., Møretrø, T., Simessen, A., Langsrud, S. Listeria monocytogenes strains show larger variations in competitive growth in mixed culture biofilms and suspensions with bacteria from food processing environments. International Journal of Food Microbiology. 275, 46-55 (2018).
  18. Lutz, C., Thomas, T., Steinberg, P., Kjelleberg, S., Egan, S. Effect of interspecific competition on trait variation in Phaeobacter inhibens biofilms. Environmental Microbiology. 18, (5), 1635-1645 (2016).
  19. Meisner, J., et al. FtsEX is required for CwlO peptidoglycan hydrolase activity during cell wall elongation in Bacillus subtilis. Molecular Microbiology. 89, (6), 1069-1083 (2013).
  20. Coates, J., et al. Antibiotic-induced population fluctuations and stochastic clearance of bacteria. eLife. 7, 32976 (2018).
  21. Korber, D. R., Lawrence, J. R., Sutton, B., Caldwell, D. E. Effect of laminar flow velocity on the kinetics of surface recolonization by Mot+ and Mot- Pseudomonas fluorescens. Microbial Ecology. 18, 1-19 (1989).
  22. Lawrence, J. R., Korber, D. R., Caldwell, D. E. Behavioral analysis of Vibrio parahaemolyticus variants in high- and low- viscosity microenvironments by use of digital image processing. Journal of Bacteriology. 174, (17), 5732-5739 (1992).
  23. Lawrence, J. R., Wolfaardt, G. M., Korber, D. R. Determination of diffusion coefficients in biofilms by confocal laser microscopy. Applied and Environmental Microbiology. 60, (4), 1166-1173 (1994).
  24. Limoli, D. H., et al. Interspecies interactions induce exploratory motility in Pseudomonas aeruginosa. eLife. 8, 47365 (2019).
  25. Burrows, L. Pseudomonas aeruginosa twitching motility: type IV pili in action. Annual Review of Microbiology. 66, (1), 493-520 (2012).
  26. Lee, C. K., et al. Multigenerational memory and adaptive adhesion in early bacterial biofilm communities. PNAS. 115, (17), 4471-4476 (2018).
  27. Tolosa, A., et al. Enhanced field-of-view integral imaging display using multi-Köhler illumination. Optical Society of America. 22, (26), 31853-31863 (2014).
This article has been published
Video Coming Soon

Cite this Article

Yarrington, K. D., Sánchez Peña, A., Limoli, D. H. Kinetic Visualization of Single-Cell Interspecies Bacterial Interactions. J. Vis. Exp. (162), e61376, doi:10.3791/61376 (2020).More

Yarrington, K. D., Sánchez Peña, A., Limoli, D. H. Kinetic Visualization of Single-Cell Interspecies Bacterial Interactions. J. Vis. Exp. (162), e61376, doi:10.3791/61376 (2020).

Copy Citation Download Citation Reprints and Permissions
View Video

Get cutting-edge science videos from JoVE sent straight to your inbox every month.

Waiting X
simple hit counter