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>Agarose pads</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>M8T Minimal Media</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>D (+) Glucose</td>
			<td>RPI</td>
			<td>G32045</td>
			<td></td>
		</tr>
		<tr>
			<td>KH2PO4</td>
			<td>RPI</td>
			<td>P250500</td>
			<td></td>
		</tr>
		<tr>
			<td>MgSO4</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>Na2HPO4.7H2O</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 &#956;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 &#411;20x objective (0.75NA)</td>
			<td>Nikon</td>
			<td>MRD00205</td>
			<td>Objective</td>
		</tr>
		<tr>
			<td>CFI Plan Apo &#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>Bacterial Strains</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Pseudomonas aeruginosa PA14 (WT)</td>
			<td></td>
			<td>PMID: 7604262</td>
			<td>Non-mucoid prototroph</td>
		</tr>
		<tr>
			<td>Pseudomonas aeruginosa PA14 (WT) pSMC21 (Ptac-GFP)</td>
			<td></td>
			<td>PMID: 9361441</td>
			<td></td>
		</tr>
		<tr>
			<td>Pseudomonas aeruginosa PAO1 (WT) pPrpoD-mKate2</td>
			<td></td>
			<td>PMID: 26041805</td>
			<td></td>
		</tr>
		<tr>
			<td>Staphylococcus aureus USA300 LAC (WT)</td>
			<td></td>
			<td>PMID: 23404398</td>
			<td>USA300 CA-Methicillin resistant strain LAC without plasmids</td>
		</tr>
		<tr>
			<td>Staphylococcus aureus USA300 LAC (WT) pCM29 (sarAP1-sGFP)</td>
			<td></td>
			<td>PMID: 20829608</td>
			<td></td>
		</tr>
		<tr>
			<td>Staphylococcus aureus USA300 LAC &#9651;agrBDCA</td>
			<td></td>
			<td>PMID: 31713513</td>
			<td></td>
		</tr>
		<tr>
			<td>Viability Stain</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Propidium Iodide</td>
			<td>Invitrogen</td>
			<td>L7012</td>
			<td>LIVE/DEAD&#8482; BacLight&#8482; 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

Saliva, Salivary Gland, and Hemolymph Collection from Ixodes scapularis Ticks

Ticks are found worldwide and afflict humans with many tick-borne illnesses. Ticks are vectors for pathogens that cause Lyme disease and tick-borne relapsing fever (Borrelia spp.), Rocky Mountain Spotted fever (Rickettsia rickettsii), ehrlichiosis (Ehrlichia chaffeensis and E. equi), anaplasmosis (Anaplasma phagocytophilum), encephalitis (tick-borne encephalitis virus), babesiosis (Babesia spp.), Colorado tick fever (Coltivirus), and tularemia (Francisella tularensis) 1-8. To be properly transmitted into the host these infectious agents differentially regulate gene expression, interact with tick proteins, and migrate through the tick 3,9-13. For example, the Lyme disease agent, Borrelia burgdorferi, adapts through differential gene expression to the feast and famine stages of the tick's enzootic cycle 14,15. Furthermore, as an Ixodes tick consumes a bloodmeal Borrelia replicate and migrate from the midgut into the hemocoel, where they travel to the salivary glands and are transmitted into the host with the expelled saliva 9,16-19.
As a tick feeds the host typically responds with a strong hemostatic and innate immune response 11,13,20-22. Despite these host responses, I. scapularis can feed for several days because tick saliva contains proteins that are immunomodulatory, lytic agents, anticoagulants, and fibrinolysins to aid the tick feeding 3,11,20,21,23. The immunomodulatory activities possessed by tick saliva or salivary gland extract (SGE) facilitate transmission, proliferation, and dissemination of numerous tick-borne pathogens 3,20,24-27. To further understand how tick-borne infectious agents cause disease it is essential to dissect actively feeding ticks and collect tick saliva. This video protocol demonstrates dissection techniques for the collection of hemolymph and the removal of salivary glands from actively feeding I. scapularis nymphs after 48 and 72 hours post mouse placement. We also demonstrate saliva collection from an adult female I. scapularis tick.

Saliva, Salivary Gland, and Hemolymph Collection from Ixodes scapularis Ticks

The collection of infected tick hemolymph, salivary glands, and saliva is important to study how tick-borne pathogens cause disease. In this protocol we demonstrate how to collect hemolymph and salivary glands from feeding Ixodes scapularis nymphs. We also demonstrate saliva collection from female I. scapularis adults.

Ticks are found worldwide and afflict humans with many tick-borne illnesses. Ticks are vectors for pathogens that cause Lyme disease and tick-borne ...

Visualization of Bacterial Toxin Induced Responses Using Live Cell Fluorescence Microscopy

Bacterial toxins bind to cholesterol in membranes, forming pores that allow for leakage of cellular contents and influx of materials from the external environment. The cell can either recover from this insult, which requires active membrane repair processes, or else die depending on the amount of toxin exposure and cell type1. In addition, these toxins induce strong inflammatory responses in infected hosts through activation of immune cells, including macrophages, which produce an array of pro-inflammatory cytokines2. Many Gram positive bacteria produce cholesterol binding toxins which have been shown to contribute to their virulence through largely uncharacterized mechanisms.
Morphologic changes in the plasma membrane of cells exposed to these toxins include their sequestration into cholesterol-enriched surface protrusions, which can be shed into the extracellular space, suggesting an intrinsic cellular defense mechanism3,4. This process occurs on all cells in the absence of metabolic activity, and can be visualized using EM after chemical fixation4. In immune cells such as macrophages that mediate inflammation in response to toxin exposure, induced membrane vesicles are suggested to contain cytokines of the IL-1 family and may be responsible both for shedding toxin and disseminating these pro-inflammatory cytokines5,6,7. A link between IL-1&beta; release and a specific type of cell death, termed pyroptosis has been suggested, as both are caspase-1 dependent processes8. To sort out the complexities of this macrophage response, which includes toxin binding, shedding of membrane vesicles, cytokine release, and potentially cell death, we have developed labeling techniques and fluorescence microscopy methods that allow for real time visualization of toxin-cell interactions, including measurements of dysfunction and death (Figure 1). Use of live cell imaging is necessary due to limitations in other techniques. Biochemical approaches cannot resolve effects occurring in individual cells, while flow cytometry does not offer high resolution, real-time visualization of individual cells. The methods described here can be applied to kinetic analysis of responses induced by other stimuli involving complex phenotypic changes in cells.

Methods for purifying the cholesterol binding toxin streptolysin O from recombinant E. coli and visualization of toxin binding to live eukaryotic cells are described. Localized delivery of toxin induces rapid and complex changes in targeted cells revealing novel aspects of toxin biology.

Bacterial toxins bind to cholesterol in membranes, forming pores that allow for leakage of cellular contents and influx of materials from the external ...

Single Cell Measurements of Vacuolar Rupture Caused by Intracellular Pathogens

Shigella flexneri are pathogenic bacteria that invade host cells entering into an endocytic vacuole. Subsequently, the rupture of this membrane-enclosed compartment allows bacteria to move within the cytosol, proliferate and further invade neighboring cells. Mycobacterium tuberculosis is phagocytosed by immune cells, and has recently been shown to rupture phagosomal membrane in macrophages. We developed a robust assay for tracking phagosomal membrane disruption after host cell entry of Shigella flexneri or Mycobacterium tuberculosis. The approach makes use of CCF4, a FRET reporter sensitive to &beta;-lactamase that equilibrates in the cytosol of host cells. Upon invasion of host cells by bacterial pathogens, the probe remains intact as long as the bacteria reside in membrane-enclosed compartments. After disruption of the vacuole, &beta;-lactamase activity on the surface of the intracellular pathogen cleaves CCF4 instantly leading to a loss of FRET signal and switching its emission spectrum. This robust ratiometric assay yields accurate information about the timing of vacuolar rupture induced by the invading bacteria, and it can be coupled to automated microscopy and image processing by specialized algorithms for the detection of the emission signals of the FRET donor and acceptor. Further, it allows investigating the dynamics of vacuolar disruption elicited by intracellular bacteria in real time in single cells. Finally, it is perfectly suited for high-throughput analysis with a spatio-temporal resolution exceeding previous methods. Here, we provide the experimental details of exemplary protocols for the CCF4 vacuolar rupture assay on HeLa cells and THP-1 macrophages for time-lapse experiments or end points experiments using Shigella flexneri as well as multiple mycobacterial strains such as Mycobacterium marinum, Mycobacterium bovis, and Mycobacterium tuberculosis.

We describe a method for tracking the endomembrane rupture elicited by the intracellular bacteria Shigella flexneri and Mycobacterium tuberculosis upon host cell invasion. Our assay makes use of CCF4, a host cytoplasmic FRET probe in live or fixed cells. This reporter is degraded by an enzyme activity present on the bacterial surface.

Shigella flexneri are pathogenic bacteria that invade host cells entering into an endocytic vacuole. Subsequently, the rupture of this membrane-enclosed ...

Imaging InlC Secretion to Investigate Cellular Infection by the Bacterial Pathogen Listeria monocytogenes

Bacterial intracellular pathogens can be conceived as molecular tools to dissect cellular signaling cascades due to their capacity to exquisitely manipulate and subvert cell functions which are required for the infection of host target tissues. Among these bacterial pathogens, Listeria monocytogenes is a Gram positive microorganism that has been used as a paradigm for intracellular parasitism in the characterization of cellular immune responses, and which has played instrumental roles in the discovery of molecular pathways controlling cytoskeletal and membrane trafficking dynamics. In this article, we describe a robust microscopical assay for the detection of late cellular infection stages of L. monocytogenes based on the fluorescent labeling of InlC, a secreted bacterial protein which accumulates in the cytoplasm of infected cells; this assay can be coupled to automated high-throughput small interfering RNA screens in order to characterize cellular signaling pathways involved in the up- or down-regulation of infection.

Imaging InlC Secretion to Investigate Cellular Infection by the Bacterial Pathogen Listeria monocytogenes

Listeria monocytogenes is a Gram positive bacterial pathogen frequently used as a major model for the study of intracellular parasitism. Imaging late L. monocytogenes infection stages within the context of small-interfering RNA screens allows for the global study of cellular pathways required for bacterial infection of target host cells.

Bacterial intracellular  pathogens can be conceived as molecular tools to dissect cellular signaling  cascades due to their capacity to exquisitely ...

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 ...

Generation and Multi-phenotypic High-content Screening of Coxiella burnetii Transposon Mutants

Invasion and colonization of host cells by bacterial pathogens depend on the activity of a large number of prokaryotic proteins, defined as virulence factors, which can subvert and manipulate key host functions. The study of host/pathogen interactions is therefore extremely important to understand bacterial infections and develop alternative strategies to counter infectious diseases. This approach however, requires the development of new high-throughput assays for the unbiased, automated identification and characterization of bacterial virulence determinants. Here, we describe a method for the generation of a GFP-tagged mutant library by transposon mutagenesis and the development of high-content screening approaches for the simultaneous identification of multiple transposon-associated phenotypes. Our working model is the intracellular bacterial pathogen Coxiellaburnetii, the etiological agent of the zoonosis Q fever, which is associated with severe outbreaks with a consequent health and economic burden. The obligate intracellular nature of this pathogen has, until recently, severely hampered the identification of bacterial factors involved in host pathogen interactions, making of Coxiella the ideal model for the implementation of high-throughput/high-content approaches.

Generation and Multi-phenotypic High-content Screening of Coxiella burnetii Transposon Mutants

Coxiella burnetii is an obligate intracellular Gram-negative bacterium responsible for the zoonotic disease Q fever. Here we describe methods for the generation of Coxiella fluorescent transposon mutants as well as the automated identification and analysis of the resulting internalization, replication and cytotoxic phenotypes.

Invasion and colonization of host cells by bacterial pathogens depend on the activity of a large number of prokaryotic proteins, defined as virulence ...

Evaluation of the Efficacy And Toxicity of RNAs Targeting HIV-1 Production for Use in Gene or Drug Therapy

Small RNA therapies targeting post-integration steps in the HIV-1 replication cycle are among the top candidates for gene therapy and have the potential to be used as drug therapies for HIV-1 infection. Post-integration inhibitors include ribozymes, short hairpin (sh) RNAs, small interfering (si) RNAs, U1 interference (U1i) RNAs and RNA aptamers. Many of these have been identified using transient co-transfection assays with an HIV-1 expression plasmid and some have advanced to clinical trials. In addition to measures of efficacy, small RNAs have been evaluated for their potential to affect the expression of human RNAs, alter cell growth and/or differentiation, and elicit innate immune responses. In the protocols described here, a set of transient transfection assays designed to evaluate the efficacy and toxicity of RNA molecules targeting post-integration steps in the HIV-1 replication cycle are described. We have used these assays to identify new ribozymes and optimize the format of shRNAs and siRNAs targeting HIV-1 RNA. The methods provide a quick set of assays that are useful for screening new anti-HIV-1 RNAs and could be adapted to screen other post-integration inhibitors of HIV-1 replication.

Methods to evaluate the efficacy and toxicity of RNA molecules targeting post-integration steps of the HIV-1 replication cycle are described. These methods are useful for screening new molecules and optimizing the format of existing ones.

Small RNA therapies targeting post-integration steps in the HIV-1 replication cycle are among the top candidates for gene therapy and have the potential ...

A New Method for Qualitative Multi-scale Analysis of Bacterial Biofilms on Filamentous Fungal Colonies Using Confocal and Electron Microscopy

Bacterial biofilms frequently form on fungal surfaces and can be involved in numerous bacterial-fungal interaction processes, such as metabolic cooperation, competition, or predation. The study of biofilms is important in many biological fields, including environmental science, food production, and medicine. However, few studies have focused on such bacterial biofilms, partially due to the difficulty of investigating them. Most of the methods for qualitative and quantitative biofilm analyses described in the literature are only suitable for biofilms forming on abiotic surfaces or on homogeneous and thin biotic surfaces, such as a monolayer of epithelial cells.
While laser scanning confocal microscopy (LSCM) is often used to analyze in situ and in vivo biofilms, this technology becomes very challenging when applied to bacterial biofilms on fungal hyphae, due to the thickness and the three dimensions of the hyphal networks. To overcome this shortcoming, we developed a protocol combining microscopy with a method to limit the accumulation of hyphal layers in fungal colonies. Using this method, we were able to investigate the development of bacterial biofilms on fungal hyphae at multiple scales using both LSCM and scanning electron microscopy (SEM). This report describes the protocol, including microorganism cultures, bacterial biofilm formation conditions, biofilm staining, and LSCM and SEM visualizations.

This protocol describes a new method to grow and qualitatively analyze bacterial biofilms on fungal hyphae by confocal and electron microscopy.

Bacterial biofilms frequently form on fungal surfaces and can be involved in numerous bacterial-fungal interaction processes, such as metabolic ...

Quantification of Efferocytosis by Single-cell Fluorescence Microscopy

Studying the regulation of efferocytosis requires methods that are able to accurately quantify the uptake of apoptotic cells and to probe the signaling and cellular processes that control efferocytosis. This quantification can be difficult to perform as apoptotic cells are often efferocytosed piecemeal, thus necessitating methods which can accurately delineate between the efferocytosed portion of an apoptotic target versus residual unengulfed cellular fragments. The approach outlined herein utilizes dual-labeling approaches to accurately quantify the dynamics of efferocytosis and efferocytic capacity of efferocytes such as macrophages. The cytosol of the apoptotic cell is labeled with a cell-tracking dye to enable monitoring of all apoptotic cell-derived materials, while surface biotinylation of the apoptotic cell allows for differentiation between internalized and non-internalized apoptotic cell fractions. The efferocytic capacity of efferocytes is determined by taking fluorescent images of live or fixed cells and quantifying the amount of bound versus internalized targets, as differentiated by streptavidin staining. This approach offers several advantages over methods such as flow cytometry, namely the accurate delineation of non-efferocytosed versus efferocytosed apoptotic cell fractions, the ability to measure efferocytic dynamics by live-cell microscopy, and the capacity to perform studies of cellular signaling in cells expressing fluorescently-labeled transgenes. Combined, the methods outlined in this protocol serve as the basis for a flexible experimental approach that can be used to accurately quantify efferocytic activity and interrogate cellular signaling pathways active during efferocytosis.

Efferocytosis, the phagocytic removal of apoptotic cells, is required to maintain homeostasis and is facilitated by receptors and signaling pathways that allow for the recognition, engulfment, and internalization of apoptotic cells. Herein, we present a fluorescence microscopy protocol for the quantification of efferocytosis and the activity of efferocytic signaling pathways.

Studying the regulation of efferocytosis requires methods that are able to accurately quantify the uptake of apoptotic cells and to probe the signaling ...

Isolation of Single Intracellular Bacterial Communities Generated from a Murine Model of Urinary Tract Infection for Downstream Single-cell Analysis

In this article, we outline a procedure used to isolate individual intracellular bacterial communities from a mouse that has been experimentally infected in the urinary tract. The protocol can be broadly divided into three sections: the infection, bladder epithelial cell harvesting, and mouth micropipetting to isolate individual infected epithelial cells. The isolated epithelial cell contains viable bacterial cells and is nearly free of contaminating extracellular bacteria, making it ideal for downstream single-cell analysis. The time taken from the start of infection to obtaining a single intracellular bacterial community is about 8 h. This protocol is inexpensive to deploy and uses widely available materials, and we anticipate that it can also be utilized in other infection models to isolate single infected cells from cell mixtures even if those infected cells are rare. However, due to a potential risk in mouth micropipetting, this procedure is not recommended for highly infectious agents.

This protocol describes a simple method of isolating single, infected-bladder epithelial cells from a murine model of urinary tract infection.

In this article, we outline a procedure used to isolate individual intracellular bacterial communities from a mouse that has been experimentally infected ...