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.

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
<ol>
	<li>Prepare 1 L of M8 minimal salts base (5x) by dissolving 64 g of Na2HPO4&#183;7H2O, 15 g of KH2PO4, and 2.5 g NaCl in 800 mL of ultrapure water (UPW, resistivity 18 M&#937;/cm) in a 2 L bottle. pH to 7.6. Complete volume to 1 L with UPW. Autoclave for 45 min.</li>
	<li>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.</li>
	<li>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.</li>
	<li>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 &#956;m sterile filter into a sterile 500 mL media storage bottle.</li>
</ol>
Day 1:
2. Preparation of bacterial overnight cultures
<ol>
	<li>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 &#176;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.</li>
</ol>
Day 2:
3. Subculture of bacterial strains
<ol>
	<li>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 &#176;C until cultures reach mid-log phase (OD600 = ~0.3 - 0.5).</li>
</ol>
4. Preparation of materials for pad molds
<ol>
	<li>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&#176; angle. Heat the end of another flat, rounded laboratory spatula and slightly bend the last 10 mm to a 45 &#176;C angle.</li>
	<li>Cut off the four corners of the silicone molds so that the molds fit inside a 35 mm dish.</li>
	<li>Sterilize the spatulas and a pair of tweezers by adding 70% ethanol and passing them through the flame of the Bunsen burner.</li>
	<li>Clean the dish and silicone molds with 70% ethanol and dry them with lint-free wipes.</li>
</ol>
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.
<ol>
	<li>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 &#176;C water bath for at least 15 min.</li>
	<li>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.</li>
	<li>Once cool, pipette 915 &#181;L of molten agarose into the mold. Leave the lid ajar and let the pad dry at room temperature for 30 min.</li>
	<li>Cover the dish with the lid and leave at room temperature for an additional 2 h.</li>
	<li>Prepare humidity wipes by tightly rolling up a lint-free wipe. Place the rolled wipe inside a sterile Petri dish and evenly add 500 &#181;L of sterile water across the wipe. Warm to 37 &#176;C for 1 h.</li>
	<li>Warm the pad and a sterile 35 mm dish to 37 &#176;C for 1 h.</li>
</ol>
6. Preparation of bacterial cells and inoculating pads
<ol>
	<li>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 &#176;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.</li>
	<li>Pipette 1 &#181;L of coculture evenly across the bottom of a pre-warmed, sterile 35 mm glass coverslip dish.</li>
	<li>Remove the silicone cutout from the mold using sterile tweezers.</li>
	<li>Remove the pad from the dish using sterile spatulas.
	<ol>
		<li>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.</li>
	</ol>
	</li>
	<li>Transfer the pad to the dish with the bacterial cells, bottom-side-down, by sliding the 90&#176; angled spatula under the pad and placing it on top of the inoculated coverslip. Use the 90&#176; angled spatula to make the pad flush against the coverslip and gently press out any air bubbles.</li>
	<li>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.</li>
</ol>
7. Setting up the microscope for live imaging
<ol>
	<li>Warm environmental chamber to 37 &#176;C at least 2 h prior to experimental set-up.</li>
	<li>Turn on all components including microscope, computer, and light sources for brightfield and fluorescence imaging.</li>
	<li>Open the imaging software and make sure that light sources are connected and running.</li>
	<li>Perform K&#246;hler illumination27&#160;to align all image planes.
	<ol>
		<li>First, bring marked coverslip into focus with a 20x objective using a &#8220;dummy&#8221; dish. Make sure the condenser turret is set to the &#8220;open&#8221; position. 
		NOTE: K&#246;hler illumination should be performed for each unique objective/sample to properly align image planes. However, focus and alignment with the &#8220;dummy&#8221; dish on lower magnification expedites set-up on live samples at higher magnification to limit time between set-up and experiment start time.</li>
		<li>Focus the condenser.
		<ol>
			<li>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.</li>
			<li>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.</li>
		</ol>
		</li>
		<li>Align the condenser.
		<ol>
			<li>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.</li>
		</ol>
		</li>
		<li>Focus the lamp filament and adjust the condenser aperture.
		<ol>
			<li>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.</li>
			<li>Turn the Bertrand lens focus knob until the rings look crisp.</li>
			<li>Remove the Bertrand lens from the light path.</li>
		</ol>
		</li>
		<li>Open the field diaphragm until the octagon is just outside of the FOV.</li>
		<li>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.</li>
		<li>Perform K&#246;hler illumination on the 100x objective with the bacterial sample dish.</li>
	</ol>
	</li>
	<li>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.</li>
	<li>Click the Phase option in the imaging software.</li>
	<li>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.</li>
	<li>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.</li>
	<li>If using fluorescence, adjust the camera settings in each corresponding channel (i.e., TxRed, GFP), by clicking on the fluorescent channel of interest.
	<ol>
		<li>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).</li>
		<li>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.</li>
	</ol>
	</li>
	<li>Choose the XY positions of interest by clicking on the XY option in the acquisition controls menu.
	<ol>
		<li>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.</li>
	</ol>
	</li>
	<li>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.</li>
	<li>Rotate the fine adjustment knobs to focus on the bacterial cells.</li>
	<li>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.</li>
	<li>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.</li>
	<li>Begin imaging once the microscope and acquisition settings are set up.</li>
</ol>
8. Optional: Modifications for live/dead imaging
<ol>
	<li>Melt 2% agarose in 10 mL of M8T and let cool in 50 &#176;C water bath for at least 15 min.</li>
	<li>Add 1 mM of propidium iodide to the molten agarose.</li>
	<li>Once cooled, pipette 915 &#956;L of agarose in the prepared mold.</li>
	<li>Leave the lid ajar and let pad dry at room temperature for 30 min. Protect from light.</li>
	<li>Cover the dish with the lid and leave at room temperature for an additional 2 h.</li>
	<li>Prepare humidity wipes.
	<ol>
		<li>Roll a lint-free paper wipe up tightly.</li>
		<li>Place the wipe in a sterile Petri dish and add 500 &#181;L of sterile water to the wipe.</li>
		<li>Incubate at 37 &#176;C for 1 h.</li>
	</ol>
	</li>
	<li>Incubate the pad and a sterile 35 mm dish at 37 &#176;C for 1 h.</li>
	<li>Proceed to inoculate the dish as indicated in section 6: Preparation of bacterial cells and inoculating pads.</li>
</ol>
9. Data analysis
<ol>
	<li>Identification of cells
	<ol>
		<li>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.</li>
		<li>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.
		<ol>
			<li>Manually define ROI
			<ol>
				<li>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.</li>
			</ol>
			</li>
			<li>Identify binary ROIs
			<ol>
				<li>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.</li>
				<li>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&#160;intensities constitute the background.</li>
			</ol>
			</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Cell tracking
	<ol>
		<li>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.</li>
		<li>Repeat in all sequential frames for which cells are to be tracked.</li>
		<li>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.</li>
		<li>Once cells have been tracked through all selected frames, export the data to be analyzed.</li>
		<li>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).</li>
	</ol>
	</li>
	<li>Fluorescence quantification
	<ol>
		<li>Define ROIs for fluorescent bacterial cells as described in step 9.1.</li>
		<li>Repeat tracing or movement of ROIs for bacterial cells or clusters in the remaining fluorescent frames.</li>
		<li>Export the generated table to a spreadsheet file for analysis of fluorescent intensity.</li>
		<li>In the data spreadsheet, look for the column with &#8220;Mean Intensity&#8221; which represents the average fluorescence intensity for the traced bacterial cell(s) ROI.</li>
		<li>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.</li>
	</ol>
	</li>
</ol>

<ol>
	<li>Lamichhane, J. R., Venturi, V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Synergisms+between+microbial+pathogens+in+plant+disease+complexes:+a+growing+trend.">Synergisms between microbial pathogens in plant disease complexes: a growing trend.</a> Frontiers in Plant Science. 6, 385 (2015).</li><li>Cursino, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Identification+of+an+operon,+Pil-Chp,+that+controls+twitching+motility+and+virulence+in+Xylella+fastidiosa.">Identification of an operon, Pil-Chp, that controls twitching motility and virulence in Xylella fastidiosa.</a> Molecular Plant-Microbe Interactions. 24 (10), 1198-1206 (2011).</li><li>Limoli, D. H., Hoffman, L. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Help,+hinder,+hide+and+harm:+what+can+we+learn+from+the+interactions+between+Pseudomonas+aeruginosa+and+Staphylococcus+aureus+during+respiratory+infections.">Help, hinder, hide and harm: what can we learn from the interactions between Pseudomonas aeruginosa and Staphylococcus aureus during respiratory infections.</a> Thorax. 74, 684-692 (2019).</li><li>Gabrilska, R. A., Rumbaugh, K. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Biofilm+models+of+polymicrobial+infection.">Biofilm models of polymicrobial infection.</a> Future Microbiology. 10 (12), 1997-2015 (2015).</li><li>Nobile, C. J., Mitchell, A. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microbial+biofilms:+e+pluribus+unum.">Microbial biofilms: e pluribus unum.</a> Current Biology. 17 (10), 349-353 (2007).</li><li>Marino, P. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Community+analysis+of+dental+plaque+and+endotracheal+tube+biofilms+from+mechanically+ventilated+patients.">Community analysis of dental plaque and endotracheal tube biofilms from mechanically ventilated patients.</a> Journal of Critical Care. 39, 149-155 (2017).</li><li>Frank, D. N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microbial+diversity+in+chronic+open+wounds.">Microbial diversity in chronic open wounds.</a> Wound Repair and Regeneration. 17, 163-172 (2009).</li><li>Fazli, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nonrandom+distribution+of+Pseudomonas+aeruginosa+and+Staphylococcus+aureus+in+chronic+wounds.">Nonrandom distribution of Pseudomonas aeruginosa and Staphylococcus aureus in chronic wounds.</a> Journal of Clinical Microbiology. 47 (12), 4084-4089 (2009).</li><li>Shimizu, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Pathogens+in+COPD+exacerbations+identified+by+comprehensive+real-time+PCR+plus+older+methods.">Pathogens in COPD exacerbations identified by comprehensive real-time PCR plus older methods.</a> International Journal of Chronic Obstructive Pulmonary Disease. 10, 2009-2016 (2015).</li><li>Behnia, M., Logan, S. C., Fallen, L., Catalano, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nosocomial+and+ventilator-associated+pneumonia+in+a+community+hospital+intensive+care+unit:+a+retrospective+review+and+analysis.">Nosocomial and ventilator-associated pneumonia in a community hospital intensive care unit: a retrospective review and analysis.</a> BMC Research Notes. 7, 232 (2014).</li><li>Maliniak, M. L., Stecenko, A. A., McCarty, N. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+longitudinal+analysis+of+chronic+MRSA+and+Pseudomonas+aeruginosa+co-infection+in+cystic+fibrosis:+a+single-center+study.">A longitudinal analysis of chronic MRSA and Pseudomonas aeruginosa co-infection in cystic fibrosis: a single-center study.</a> Journal of Cystic Fibrosis. 15 (3), 350-356 (2016).</li><li>Limoli, D. H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Staphylococcus+aureus+and+Pseudomonas+aeruginosa+co-infection+is+associated+with+cystic+fibrosis-related+diabetes+and+poor+clinical+outcomes.">Staphylococcus aureus and Pseudomonas aeruginosa co-infection is associated with cystic fibrosis-related diabetes and poor clinical outcomes.</a> European Journal of Clinical Microbiology &amp; Infectious Diseases. 35 (6), 947-953 (2016).</li><li>Hotterbeekx, A., Kumar-Singh, S., Goossens, H., Malhotra-Kumar, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In+vivo+and+in+vitro+interactions+between+Pseudomonas+aeruginosa+and+Staphylococcus+spp.">In vivo and in vitro interactions between Pseudomonas aeruginosa and Staphylococcus spp.</a> Frontiers in Cellular and Infection Microbiology. 7 (106), (2017).</li><li>Smith, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Aspergillus+fumigatus+enhances+elastase+production+in+Pseudomonas+aeruginosa+co-cultures.">Aspergillus fumigatus enhances elastase production in Pseudomonas aeruginosa co-cultures.</a> Medical Mycology. 53, 645-655 (2015).</li><li>Michelson, C. F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Staphylococcus+aureus+alters+growth+activity,+autolysis,+and+antibiotic+tolerance+in+a+human+host-adapted+Pseudomonas+aeruginosa+lineage.">Staphylococcus aureus alters growth activity, autolysis, and antibiotic tolerance in a human host-adapted Pseudomonas aeruginosa lineage.</a> Journal of Bacteriology. 196 (22), 3903-3911 (2014).</li><li>Ngamdee, W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Competition+between+Burkholderia+pseudomallei+and+B.+thailandensis.">Competition between Burkholderia pseudomallei and B. thailandensis.</a> BMC Microbiology. 15, 56 (2015).</li><li>Heir, E., M&#248;retr&#248;, T., Simessen, A., Langsrud, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Listeria+monocytogenes+strains+show+larger+variations+in+competitive+growth+in+mixed+culture+biofilms+and+suspensions+with+bacteria+from+food+processing+environments.">Listeria monocytogenes strains show larger variations in competitive growth in mixed culture biofilms and suspensions with bacteria from food processing environments.</a> International Journal of Food Microbiology. 275, 46-55 (2018).</li><li>Lutz, C., Thomas, T., Steinberg, P., Kjelleberg, S., Egan, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effect+of+interspecific+competition+on+trait+variation+in+Phaeobacter+inhibens+biofilms.">Effect of interspecific competition on trait variation in Phaeobacter inhibens biofilms.</a> Environmental Microbiology. 18 (5), 1635-1645 (2016).</li><li>Meisner, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=FtsEX+is+required+for+CwlO+peptidoglycan+hydrolase+activity+during+cell+wall+elongation+in+Bacillus+subtilis.">FtsEX is required for CwlO peptidoglycan hydrolase activity during cell wall elongation in Bacillus subtilis.</a> Molecular Microbiology. 89 (6), 1069-1083 (2013).</li><li>Coates, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Antibiotic-induced+population+fluctuations+and+stochastic+clearance+of+bacteria.">Antibiotic-induced population fluctuations and stochastic clearance of bacteria.</a> eLife. 7, 32976 (2018).</li><li>Korber, D. R., Lawrence, J. R., Sutton, B., Caldwell, D. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effect+of+laminar+flow+velocity+on+the+kinetics+of+surface+recolonization+by+Mot++and+Mot-+Pseudomonas+fluorescens.">Effect of laminar flow velocity on the kinetics of surface recolonization by Mot+ and Mot- Pseudomonas fluorescens.</a> Microbial Ecology. 18, 1-19 (1989).</li><li>Lawrence, J. R., Korber, D. R., Caldwell, D. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Behavioral+analysis+of+Vibrio+parahaemolyticus+variants+in+high-+and+low-+viscosity+microenvironments+by+use+of+digital+image+processing.">Behavioral analysis of Vibrio parahaemolyticus variants in high- and low- viscosity microenvironments by use of digital image processing.</a> Journal of Bacteriology. 174 (17), 5732-5739 (1992).</li><li>Lawrence, J. R., Wolfaardt, G. M., Korber, D. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Determination+of+diffusion+coefficients+in+biofilms+by+confocal+laser+microscopy.">Determination of diffusion coefficients in biofilms by confocal laser microscopy.</a> Applied and Environmental Microbiology. 60 (4), 1166-1173 (1994).</li><li>Limoli, D. H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Interspecies+interactions+induce+exploratory+motility+in+Pseudomonas+aeruginosa.">Interspecies interactions induce exploratory motility in Pseudomonas aeruginosa.</a> eLife. 8, 47365 (2019).</li><li>Burrows, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Pseudomonas+aeruginosa+twitching+motility:+type+IV+pili+in+action.">Pseudomonas aeruginosa twitching motility: type IV pili in action.</a> Annual Review of Microbiology. 66 (1), 493-520 (2012).</li><li>Lee, C. K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multigenerational+memory+and+adaptive+adhesion+in+early+bacterial+biofilm+communities.">Multigenerational memory and adaptive adhesion in early bacterial biofilm communities.</a> PNAS. 115 (17), 4471-4476 (2018).</li><li>Tolosa, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Enhanced+field-of-view+integral+imaging+display+using+multi-K&#246;hler+illumination.">Enhanced field-of-view integral imaging display using multi-K&#246;hler illumination.</a> Optical Society of America. 22 (26), 31853-31863 (2014).</li></ol>

The authors declare that they have nothing to disclose.

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 s...

Polymicrobial communities are common&#160;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&#160;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.

<table><tbody><tr><td>&lt;strong&gt;Agarose pads&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>35 mm Glass Bottom Dish with 20 mm Micro-well #1.5 Cover Glass</td><td>Cellvis</td><td>D35-20-1.5-N</td><td>One for agarose pad molds, one for experiment</td></tr><tr><td>KimWipes</td><td>Kimberly-Clark Professional</td><td>06-666A</td><td></td></tr><tr><td>Low-Melt Agarose</td><td>Nu-Sieve GTG/Lonza</td><td>50081</td><td>For making agarose pads</td></tr><tr><td>Round-Bottom Spatulas</td><td>VWR</td><td>82027-492</td><td></td></tr><tr><td>Round-Tapered Spatulas</td><td>VWR</td><td>82027-530</td><td></td></tr><tr><td>Silicon Isolators, Press-to-Seal, 1 well, D diameter 2.0 mm 20 mm, silicone/adhesive</td><td>Sigma-Aldrich</td><td>S6685-25EA</td><td>For agarose pad molds</td></tr><tr><td>Sterile Petri Plates, 85 mm</td><td>Kord-Valmark /sold by RPI</td><td>2900</td><td></td></tr><tr><td>Tweezers</td><td>VWR</td><td>89259-944</td><td></td></tr><tr><td>&lt;strong&gt;M8T Minimal Media&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>D (+) Glucose</td><td>RPI</td><td>G32045</td><td></td></tr><tr><td>KH&lt;sub&gt;2&lt;/sub&gt;PO&lt;sub&gt;4&lt;/sub&gt;</td><td>RPI</td><td>P250500</td><td></td></tr><tr><td>MgSO&lt;sub&gt;4&lt;/sub&gt;</td><td>Sigma-Aldrich</td><td>208094</td><td></td></tr><tr><td>NaCl</td><td>RPI</td><td>S23025</td><td></td></tr><tr><td>Na&lt;sub&gt;2&lt;/sub&gt;HPO&lt;sub&gt;4&lt;/sub&gt;.7H&lt;sub&gt;2&lt;/sub&gt;O</td><td>Sigma-Aldrich</td><td>230391</td><td></td></tr><tr><td>Tryptone</td><td>BD Biosciences</td><td>DF0123173</td><td></td></tr><tr><td>Microscope</td><td></td><td></td><td></td></tr><tr><td>Andor Sona 4.2B-11</td><td>Andor</td><td>77026135</td><td>Camera. 4.2 Megapixel Back-illuminated sCMOS, 11 &amp;mu;m pixel, 95% QE, 48 fps, USB 3.0, F-mount.</td></tr><tr><td>Filter Cube GFP</td><td>Nikon</td><td>96372</td><td>Filter cube</td></tr><tr><td>Filter Cube TxRed</td><td>Nikon</td><td>96375</td><td>Filter cube</td></tr><tr><td>H201-NIKON-TI-S-ER</td><td>Okolab</td><td>77057447</td><td>Stagetop incubator</td></tr><tr><td>Nikon NIS-Elements AR with GA3 and 2D and 3D tracking</td><td>Nikon</td><td>77010609, MQS43110, 77010603, MQS42950</td><td>Software for data analysis</td></tr><tr><td>Nikon Ti2 Eclipse</td><td>Nikon</td><td>Model Ti2-E</td><td>Microscope</td></tr><tr><td>CFI Plan Apo &amp;#411;20x objective (0.75NA)</td><td>Nikon</td><td>MRD00205</td><td>Objective</td></tr><tr><td>CFI Plan Apo &amp;#411;100x oil Ph3 DM objective (1.45NA)</td><td>Nikon</td><td>MRD31905</td><td>Objective</td></tr><tr><td>ThermoBox with built-in fan heaters</td><td>Tokai Hit</td><td>TI2TB-E-BK</td><td>Enclosure</td></tr><tr><td>&lt;strong&gt;Bacterial Strains&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>&lt;em&gt;Pseudomonas aeruginosa&lt;/em&gt; PA14 (WT)</td><td></td><td>PMID: 7604262</td><td>Non-mucoid prototroph</td></tr><tr><td>&lt;em&gt;Pseudomonas aeruginosa&lt;/em&gt; PA14 (WT) pSMC21 (&lt;em&gt;Ptac-GFP&lt;/em&gt;)</td><td></td><td>PMID: 9361441</td><td></td></tr><tr><td>&lt;em&gt;Pseudomonas aeruginosa&lt;/em&gt; PAO1 (WT) p&lt;em&gt;PrpoD-mKate2&lt;/em&gt;</td><td></td><td>PMID: 26041805</td><td></td></tr><tr><td>&lt;em&gt;Staphylococcus aureus&lt;/em&gt; USA300 LAC (WT)</td><td></td><td>PMID: 23404398</td><td>USA300 CA-Methicillin resistant strain LAC without plasmids</td></tr><tr><td>&lt;em&gt;Staphylococcus aureus&lt;/em&gt; USA300 LAC (WT) pCM29 (&lt;em&gt;sarAP1-sGFP&lt;/em&gt;)</td><td></td><td>PMID: 20829608</td><td></td></tr><tr><td>&lt;em&gt;Staphylococcus aureus&lt;/em&gt; USA300 LAC &amp;#916;&lt;em&gt;agrBDCA&lt;/em&gt;</td><td></td><td>PMID: 31713513</td><td></td></tr><tr><td>&lt;strong&gt;Viability Stain&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>Propidium Iodide</td><td>Invitrogen</td><td>L7012</td><td>LIVE/DEAD&amp;trade; BacLight&amp;trade; Bacterial Viability Kit</td></tr></tbody></table>

kinetic visualization of single-cell interspecies bacterial interactions

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.

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...

Watch this Scientific Journal Video about Kinetic Visualization of Single-Cell Interspecies Bacterial Interactions at JoVE.com

Kinetic Visualization of Single-Cell Interspecies Bacterial Interactions

This live-bacterial cell imaging protocol allows for visualization of interactions between multiple bacterial species at the single-cell level over time. Time-lapse imaging allows for observation of each bacterial species in monoculture or coculture to interrogate interspecies interactions in multispecies bacterial communities, including individual cell motility and viability.

Polymicrobial communities are ubiquitous in nature, yet studying their interactions at the single-cell level is difficult. Thus, a microscopy-based method ...

kinetic-visualization-single-cell-interspecies-bacterial

Research

JoVE Journal

Immunology and Infection

6.7K Views.  University of Iowa. This live-bacterial cell imaging protocol allows for visualization of interactions between multiple bacterial species at the single-cell level over time. Time-lapse imaging allows for observation of each bacterial species in monoculture or coculture to interrogate interspecies interactions in multispecies bacterial communities, including individual cell motility and viability.

Video: Kinetic Visualization of Single-Cell Interspecies Bacterial Interactions

Visualizing Protein-DNA Interactions in Live Bacterial Cells Using Photoactivated Single-molecule Tracking

Protein-DNA interactions are at the heart of many fundamental cellular processes. For example, DNA replication, transcription, repair, and chromosome organization are governed by DNA-binding proteins that recognize specific DNA structures or sequences. In vitro experiments have helped to generate detailed models for the function of many types of DNA-binding proteins, yet, the exact mechanisms of these processes and their organization in the complex environment of the living cell remain far less understood. We recently introduced a method for quantifying DNA-repair activities in live Escherichia coli cells using Photoactivated Localization Microscopy (PALM) combined with single-molecule tracking. Our general approach identifies individual DNA-binding events by the change in the mobility of a single protein upon association with the chromosome. The fraction of bound molecules provides a direct quantitative measure for the protein activity and abundance of substrates or binding sites at the single-cell level. Here, we describe the concept of the method and demonstrate sample preparation, data acquisition, and data analysis procedures.

Photoactivated localization microscopy (PALM) combined with single-molecule tracking allows direct observation and quantification of protein-DNA interactions in live Escherichia coli cells.

Protein-DNA interactions are at the heart of many fundamental cellular processes. For example, DNA replication, transcription, repair, and chromosome ...

Visualizing Single Molecular Complexes In Vivo Using Advanced Fluorescence Microscopy

Full insight into the mechanisms of living cells can be achieved only by investigating the key processes that elicit and direct events at a cellular level. To date the shear complexity of biological systems has caused precise single-molecule experimentation to be far too demanding, instead focusing on studies of single systems using relatively crude bulk ensemble-average measurements. However, many important processes occur in the living cell at the level of just one or a few molecules; ensemble measurements generally mask the stochastic and heterogeneous nature of these events. Here, using advanced optical microscopy and analytical image analysis tools we demonstrate how to monitor proteins within a single living bacterial cell to a precision of single molecules and how we can observe dynamics within molecular complexes in functioning biological machines. The techniques are directly relevant physiologically. They are minimally-perturbative and non-invasive to the biological sample under study and are fully attuned for investigations in living material, features not readily available to other single-molecule approaches of biophysics. In addition, the biological specimens studied all produce fluorescently-tagged protein at levels which are almost identical to the unmodified cell strains ("genomic encoding"), as opposed to the more common but less ideal approach for generating significantly more protein than would occur naturally ('plasmid expression'). Thus, the actual biological samples which will be investigated are significantly closer to the natural organisms, and therefore the observations more relevant to real physiological processes.

Visualizing Single Molecular Complexes In Vivo Using Advanced Fluorescence Microscopy

Here we demonstrate the protocols for performing single-molecule fluorescence microscopy on living bacterial cells to enable functional molecular complexes to be detected, tracked and quantified.

Full insight into the mechanisms of living cells can be achieved only by investigating the key processes that elicit and direct events at a cellular ...

Biology

Visualization of Twitching Motility and Characterization of the Role of the PilG in Xylella fastidiosa

Xylella fastidiosa is a Gram-negative non-flagellated bacterium that causes a number of economically important diseases of plants. The twitching motility provides X. fastidiosa a means for long-distance intra-plant movement and colonization, contributing toward pathogenicity in X. fastidiosa. The twitching motility of X. fastidiosa is operated by type IV pili. Type IV pili of Xylella fastidiosa are regulated by pilG, a chemotaxis regulator in Pil-Chp operon encoding proteins that are involved with signal transduction pathways. To elucidate the roles of pilG in the twitching motility of X. fastidiosa, a pilG-deficient mutant Xf&#916;pilG and its complementary strain Xf&#916;pilG-C containing native pilG were developed. A microfluidic chambers integrated with a time-lapse image recording system was used to observe twitching motility in Xf&#916;pilG, Xf&#916;pilG-C and its wild type strain. Using this recording system, it permits long-term spatial and temporal observations of aggregation, migration of individual cells and populations of bacteria via twitching motility. X. fastidiosa wild type and complementary Xf&#916;pilG-C strain showed typical twitching motility characteristics directly observed in the microfluidic flow chambers, whereas mutant Xf&#916;pliG exhibited the twitching deficient phenotype. This study demonstrates that pilG contributes to the twitching motility of X. fastidiosa. The microfluidic flow chamber is used as a means for observing twitching motility.

Visualization of Twitching Motility and Characterization of the Role of the PilG in Xylella fastidiosa

In this study, a nano-microfluidic flow chamber was employed to visualize and functionally characterize the twitching motility of Xylella fastidiosa, a bacterium that causes Pierce&#39;s disease in grapevine.

Xylella fastidiosa is a Gram-negative non-flagellated bacterium that causes a number of economically important diseases of plants. The twitching motility ...

Induction of Cellular Differentiation and Single Cell Imaging of Vibrio parahaemolyticus Swimmer and Swarmer Cells

The ability to study the intracellular localization of proteins is essential for the understanding of many cellular processes. In turn, this requires the ability to obtain single cells for fluorescence microscopy, which can be particularly challenging when imaging cells that exist within bacterial communities. For example, the human pathogen Vibrio parahaemolyticus exists as short rod-shaped swimmer cells in liquid conditions that upon surface contact differentiate into a subpopulation of highly elongated swarmer cells specialized for growth on solid surfaces. This paper presents a method to perform single cell fluorescence microscopy analysis of V. parahaemolyticus in its two differential states. This protocol very reproducibly induces differentiation of V. parahaemolyticus into a swarmer cell life-cycle and facilitates their proliferation over solid surfaces. The method produces flares of differentiated swarmer cells extending from the edge of the swarm-colony. Notably, at the very tip of the swarm-flares, swarmer cells exist in a single layer of cells, which allows for their easy transfer to a microscope slide and subsequent fluorescence microscopy imaging of single cells. Additionally, the workflow of image analysis for demographic representation of bacterial societies is presented. As a proof of principle, the analysis of the intracellular localization of chemotaxis signaling arrays in swimmer and swarmer cells of V. parahaemolyticus is described.

Induction of Cellular Differentiation and Single Cell Imaging of Vibrio parahaemolyticus Swimmer and Swarmer Cells

This protocol enables single cell microscopy of the differentially distinct Vibrio parahaemolyticus swimmer and swarmer cells. The method produces a population of swarmer cells easily available for single cell analysis and covers preparation of cell cultures, induction of swarmer differentiation, sample preparation, and image analysis.

The ability to study the intracellular localization of proteins is essential for the understanding of many cellular processes. In turn, this requires the ...

Generating Controlled, Dynamic Chemical Landscapes to Study Microbial Behavior

We demonstrate a method for the generation of controlled, dynamic chemical pulses&#8213;where localized chemoattractant becomes suddenly available at the microscale&#8213;to create micro-environments for microbial chemotaxis experiments. To create chemical pulses, we developed a system to introduce amino acid sources near-instantaneously by photolysis of caged amino acids within a polydimethylsiloxane (PDMS) microfluidic chamber containing a bacterial suspension. We applied this method to the chemotactic bacterium, Vibrio ordalii, which can actively climb these dynamic chemical gradients while being tracked by video microscopy. Amino acids, rendered biologically inert (&#39;caged&#39;) by chemical modification with a photoremovable protecting group, are uniformly present in the suspension but not available for consumption until their sudden release, which occurs at user-defined points in time and space by means of a near-UV-A focused LED beam. The number of molecules released in the pulse can be determined by a calibration relationship between exposure time and uncaging fraction, where the absorption spectrum after photolysis is characterized by using UV-Vis spectroscopy. A nanoporous polycarbonate (PCTE) membrane can be integrated into the microfluidic device to allow the continuous removal by flow of the uncaged compounds and the spent media. A strong, irreversible bond between the PCTE membrane and the PDMS microfluidic structure is achieved by coating the membrane with a solution of 3-aminopropyltriethoxysilane (APTES) followed by plasma activation of the surfaces to be bonded. A computer-controlled system can generate user-defined sequences of pulses at different locations and with different intensities, so as to create resource landscapes with prescribed spatial and temporal variability. In each chemical landscape, the dynamics of bacterial movement at the individual scale and their accumulation at the population level can be obtained, thereby allowing the quantification of chemotactic performance and its effects on bacterial aggregations in ecologically relevant environments.

A protocol for the generation of dynamic chemical landscapes by photolysis within microfluidic and millifluidic setups is presented. This methodology is suitable to study diverse biological processes, including the motile behavior, nutrient uptake, or adaptation to chemicals of microorganisms, both at the single cell and population level.

We demonstrate a method for the generation of controlled, dynamic chemical pulses&#8213;where localized chemoattractant becomes suddenly available at the ...

Bioengineering

Single-cell Microfluidic Analysis of Bacillus subtilis

Microfluidic technology overcomes many of the limitations to traditional analytical methods in microbiology. Unlike bulk-culture methods, it offers single-cell resolution and long observation times spanning hundreds of generations; unlike agarose pad-based microscopy, it has uniform growth conditions that can be tightly controlled. Because the continuous flow of growth medium isolates the cells in a microfluidic device from unpredictable variations in the local chemical environment caused by cell growth and metabolism, authentic changes in gene expression and cell growth in response to specific stimuli can be more confidently observed. Bacillus subtilis is used here as a model bacterial species to demonstrate a &#34;mother machine&#34;-type method for cellular analysis. We show how to construct and plumb a microfluidic device, load it with cells, initiate microscopic imaging, and expose cells to a stimulus by switching from one growth medium to another. A stress-responsive reporter is used as an example to reveal the type of data that may be obtained by this method. We also briefly discuss further applications of this method for other types of experiments, such as analysis of bacterial sporulation.

Single-cell Microfluidic Analysis of Bacillus subtilis

We present a method for the microfluidic analysis of individual bacterial cell lineages using Bacillus subtilis as an example. The method overcomes shortcomings of traditional analytical methods in microbiology by allowing observation of hundreds of cell generations under tightly controllable and uniform growth conditions.

Microfluidic technology overcomes many of the limitations to traditional analytical methods in microbiology. Unlike bulk-culture methods, it offers ...

Quantification of Interbacterial Competition using Single-Cell Fluorescence Imaging

Interbacterial competition can directly impact the structure and function of microbiomes. This work describes a fluorescence microscopy approach that can be used to visualize and quantify competitive interactions between different bacterial strains at the single-cell level. The protocol described here provides methods for advanced approaches in slide preparation on both upright and inverted epifluorescence microscopes, live-cell and time-lapse imaging techniques, and quantitative image analysis using the open-source software FIJI. The approach in this manuscript outlines the quantification of competitive interactions between symbiotic Vibrio fischeri populations by measuring the change in area over time for two coincubated strains that are expressing different fluorescent proteins from stable plasmids. Alternative methods are described for optimizing this protocol in bacterial model systems that require different growth conditions. Although the assay described here uses conditions optimized for V. fischeri, this approach is highly reproducible and can easily be adapted to study competition among culturable isolates from diverse microbiomes.

This manuscript describes a method for using single-cell fluorescence microscopy to visualize and quantify bacterial competition in coculture.

Interbacterial competition can directly impact the structure and function of microbiomes. This work describes a fluorescence microscopy approach that can ...

Visualizing Bacterial Motility Based on a Color Reaction

Bacterial motility is crucial for bacterial pathogenicity, biofilm formation, and drug resistance. Bacterial motility is crucial for the invasion and/or dissemination of many pathogenic species. Therefore, it is important to detect bacterial motility. Bacterial growth conditions, such as oxygen, pH, and temperature, can affect bacterial growth and the expression of bacterial flagella. This can lead to reduced motility or even loss of motility, resulting in the inaccurate evaluation of bacterial motility. Based on the color reaction of 2,3,5-triphenyl tetrazolium chloride (TTC) by intracellular dehydrogenases of living bacteria, TTC was added to traditional semisolid agar for bacterial motility detection. The results showed that this TTC semisolid agar method for the detection of bacterial motility is simple, easy to operate, and does not involve large and expensive instruments. The results also showed that the highest motility was observed in semisolid medium prepared with 0.3% agar. Compared with the traditional semisolid medium, the results are easier to evaluate and more accurate.

Here, we present a protocol to detect bacterial motility based on a color reaction. Key advantages of this method are that it is easy to evaluate and more accurate, and does not require specialized equipment.

Bacterial motility is crucial for bacterial pathogenicity, biofilm formation, and drug resistance. Bacterial motility is crucial for the invasion and/or ...

Live Cell Single-Molecule Imaging-Based Quantification of Protein Interactions

Single-Molecule Measurement of Protein Interaction Dynamics Within Biomolecular Condensates

Biomolecular condensates formed via liquid-liquid phase separation (LLPS) have been considered critical in cellular organization and an increasing number of cellular functions. Characterizing LLPS in live cells is also important because aberrant condensation has been linked to numerous diseases, including cancers and neurodegenerative disorders. LLPS is often driven by selective, transient, and multivalent interactions between intrinsically disordered proteins. Of great interest are the interaction dynamics of proteins participating in LLPS, which are well-summarized by measurements of their binding residence time (RT), that is, the amount of time they spend bound within condensates. Here, we present a method based on live-cell single-molecule imaging that allows us to measure the mean RT of a specific protein within condensates. We simultaneously visualize individual protein molecules and the condensates with which they associate, use single-particle tracking (SPT) to plot single-molecule trajectories, and then fit the trajectories to a model of protein-droplet binding to extract the mean RT of the protein. Finally, we show representative results where this single-molecule imaging method was applied to compare the mean RTs of a protein at its LLPS condensates when fused and unfused to an oligomerizing domain. This protocol is broadly applicable to measuring the interaction dynamics of any protein that participates in LLPS.

Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells

Many intrinsically disordered proteins have been shown to participate in the formation of highly dynamic biomolecular condensates, a behavior important for numerous cellular processes. Here, we present a single-molecule imaging-based method for quantifying the dynamics by which proteins interact with each other in biomolecular condensates in live cells.

Biomolecular condensates formed via liquid-liquid phase separation (LLPS) have been considered critical in cellular organization and an increasing number ...

FLIM-FRET Imaging for Characterization of Protein-Protein Interactions in Live Bacteria

Source: Manko, H. et al., <a href="https://app.jove.com/v/61602">FLIM-FRET Measurements of Protein-Protein Interactions in Live Bacteria.</a> J. Vis. Exp. (2020)
The video describes the FLIM-FRET imaging technique to determine the protein-protein interaction in live bacteria expressing cytoplasmic proteins labeled with fluorescent proteins, a donor eGFP, and acceptor mCherry. The combined technique also allows the quantification of the interacting proteins.

Source: Manko, H. et al., FLIM-FRET Measurements of Protein-Protein Interactions in Live Bacteria. J. Vis. Exp. (2020)
The video describes the FLIM-FRET ...

Kinetic Visualization of Single-Cell Interspecies Bacterial Interactions

Summary

Explore More Videos

Chapters in this video

Visualizing Protein-DNA Interactions in Live Bacterial Cells Using Photoactivated Single-molecule Tracking

Visualizing Single Molecular Complexes In Vivo Using Advanced Fluorescence Microscopy

Visualization of Twitching Motility and Characterization of the Role of the PilG in Xylella fastidiosa

Induction of Cellular Differentiation and Single Cell Imaging of Vibrio parahaemolyticus Swimmer and Swarmer Cells

Generating Controlled, Dynamic Chemical Landscapes to Study Microbial Behavior

Single-cell Microfluidic Analysis of Bacillus subtilis

Quantification of Interbacterial Competition using Single-Cell Fluorescence Imaging

Visualizing Bacterial Motility Based on a Color Reaction

Single-Molecule Measurement of Protein Interaction Dynamics Within Biomolecular Condensates

FLIM-FRET Imaging for Characterization of Protein-Protein Interactions in Live Bacteria