The authors thank F. Cornet for providing the hupA-mCherry strain, A. Dedieu for technical assistance with cytometry, and A. Ducret for help with MicrobeJ. Funding: C. Lesterlin acknowledges Inserm and CNRS institutions as well as the ATIP-Avenir program, the Schlumberger Foundation for Education and Research (FSER 2019), the ANR funding for PlasMed research program (ANR-18-CE35-0008) as well as FINOVI for funding to J. Cayron; La Ligue contre le cancer for funding of the flow cytometer equipment. Author contributions: C.L. and J.C. designed the procedure and wrote the paper; J.C. performed the experiments and analyzed the data.

1. Cell culture, stress-induction, and sampling procedure
NOTE: Use sterile culture glassware, pipette tips, and growth medium filtered at 0.22 &#181;m to avoid background particles. Here, cell cultures are grown in low autofluorescence rich defined medium (see Table of Materials)7,8.
<ol>
	<li>Streak the bacterial strain of interest from a frozen glycerol stock on a Luria-Broth (LB) agarose plate (with selective antibiotic if required) and incubate at 37 &#176;C overnight (17 h). 
	NOTE: The example experiment presented here uses Escherichia coli MG1655 hupA-mCherry. This strain produces the fluorescently tagged subunit &#945; of the HU nucleoid associated protein, thus allowing light microscopy visualization of the chromosome in live cells9.</li>
	<li>Inoculate 5 mL of medium with a single colony and grow at 37 &#176;C with shaking at 140 rotation per minute (rpm) overnight (17 h). Flasks (&#8805;50 mL) or large diameter (&#8805;2 cm) test tubes must be used to ensure satisfactory aeration of the agitated culture.</li>
	<li>The following morning measure the optical density at 600 nm (OD600nm) and dilute the culture into a test tube containing fresh medium to an OD600nm of 0.01. The total volume of the culture needs to be adjusted depending on the number of time points to be analyzed during the experiment.</li>
	<li>Load a 200 &#181;L sample of the culture into a microplate (0.2 mL per well of working volume with a clear transparent bottom) and place it in an automated plate reader (see Table of Materials) for OD600nm monitoring during incubation at 37 &#176;C.</li>
	<li>Incubate the inoculated test tube at 37 &#176;C with shaking (140 rpm) to OD600nm = 0.2, corresponding to full exponential phase in rich medium. 
	NOTE: It is critical to grow the cells for at least 4&#8722;5 generations before achieving proper exponential growth. The initial inoculum used in step 1.3 (OD600nm = 0.01) needs to be adapted in the case of growth in poorer medium (i.e., where the exponential phase is reached below OD 0.2), or if more generations are wanted (e.g., for specific physiological studies or to extended stress treatments).</li>
	<li>At OD600nm = 0.2, take the following culture samples corresponding to the t0 time point (exponentially growing cells before stress induction): (1) A 150 &#181;L sample to be immediately loaded in the microfluidic apparatus for time-lapse microscopy imaging (see section 2); (2) A 200 &#181;L sample for the dilution and plating assay (see section 3); (3) A 250 &#181;L sample to be put on ice for flow cytometry analysis (section 4); (4) A 10 &#181;L sample to be immediately deposited on an agarose-mounted slide for microscopy snapshot imaging (see section 5).</li>
	<li>Expose the cell culture remaining in the test tube to the specific stress treatment you want to investigate and incubate at 37 &#176;C with shaking (140 rpm). 
	NOTE: The culture growing in the automated plate reader for OD600nm monitoring should also be subjected to the stress treatment.</li>
	<li>At relevant time points after the stress treatment (t1, t2, t3, etc.), take the following cell samples from the stressed culture: (1) A 200 &#181;L sample for the dilution and plating assay (see section 2); (2) A 250 &#181;L sample to put on ice for flow cytometry analysis (section 3); (4) A 10 &#181;L sample to be immediately deposited on an agarose-mounted slide for microscopy snapshot imaging (see section 4). 
	NOTE: Each stress-inducing treatment has an efficiency that is dose- and time-dependent. Thus, it might be necessary to run preliminary tests to determine the dose and duration of treatment to be used for optimal results. This can be done by performing OD monitoring using an automated plate reader (potentially associated with plating assays) of a cell culture treated with a range of doses and exposure times. In the experiment presented here, the cell culture was treated with the cell division-inhibiting antibiotic cephalexin (Ceph.) at 5 &#181;g/mL final concentration for 60 min. Cephalexin was then washed away by pelleting the cells in a 15 mL tube using centrifugation (475 g, 5 min), removing the supernatant, resuspending the cell pellet in an equal volume of fresh medium by gentle pipetting, and transferring into a clean tube. The washed cells were incubated at 37 &#176;C with shaking (140 rpm) to allow recovery. The sample was taken at t60 (60 min after cephalexin addition corresponding to the &#39;cephalexin-60min-treated&#39; sample), t120 (60 min after washing), and t180 (120 min after washing).</li>
</ol>
2. Plating assay
NOTE: The plating assay allows for measuring the concentration of cells able to generate a CFU in the culture samples. This procedure reveals the rate at which one cell divides into two viable cells and allows to detect cell division arrests (e.g., increase of the bacterial generation time of cell lysis).
<ol>
	<li>Prepare 10-fold serial dilutions up to 10-7 of the 200 &#181;L of culture sample in fresh medium. Plate 100 &#181;L of the appropriate dilution on non-selective LB agarose plates in order to obtain between 3&#8722;300 colonies after overnight incubation at 37 &#176;C. 
	NOTE: Serial dilution in fresh medium must be performed rapidly to limit bacterial divisions. Alternatively, researchers might consider using a saline solution without a carbon source to prevent cell divisions during the dilution process.</li>
	<li>The next day, count the number of colonies to determine the concentration of viable cells (CFU/mL) in each culture sample. Plot the CFU/mL as a function of time for untreated and treated cell cultures.</li>
</ol>
3. Flow cytometry
NOTE: The following section describes the preparation of cell samples for flow cytometry analysis. This analysis technique reveals the distribution of cell size and DNA content for a large number of cells. When possible, it is recommended to process the flow cytometry samples immediately. Alternatively, samples can be kept on ice (for up to 6 h) and analyzed simultaneously at the end of the day, once plating and microscopy imaging have been performed.
<ol>
	<li>Dilute the 250 &#181;L of culture sample to obtain 250 &#181;L at a concentration of ~15,000 cells/&#181;L (corresponding to an OD600nm ~0.06) in fresh medium at 4 &#176;C. 
	NOTE: Incubation on ice will limit the growth and morphological modification of the cells. Alternatively, the user might consider performing fixation of the cells in 75% ethanol, as usually recommended for flow cytometry10.</li>
	<li>For DNA staining, mix the bacterial sample with a 10 &#181;g/mL solution of DNA fluorescent dye (ratio 1:1) and incubate in the dark for 15 min before analyzing the sample.</li>
	<li>Pass the sample into the flow cytometer with a ~120,000 cells/min flow rate. Acquire forward-scattered (FSC) and side-scattered (SSC) light as well as DNA fluorescent dye fluorescence signal (FL-1) with the appropriate settings.</li>
	<li>Plot the FSC and FL-1 cell density histograms to represent the distribution of cell size and DNA content in the cell population.</li>
</ol>
4. Snapshot microscopy imaging
NOTE: The following part describes the preparation of microscopy slides and image acquisition for population snapshot analysis. This procedure will provide information regarding the morphology of the cells (cell length, width, shape) and the intracellular organization of the nucleoid DNA.
<ol>
	<li>Preheat the thermostated microscope chamber at 37 &#176;C to stabilize the temperature before starting the observations. This chamber allows for temperature modulation of the microscope optics and sample stage during time-lapse experiments.</li>
	<li>Prepare the agarose-mounted slides as described in Lesterlin and Dubarry7.
	<ol>
		<li>Remove the plastic film from the bottom of the blue frame (see Table of Materials), leaving the hollowed plastic film on the other side. Stick the blue frame on a microscope glass slide.</li>
		<li>Pipette ~150 &#181;L of melted 1% agarose medium solution and pour within the blue frame compartment. Rapidly cover with a clean coverslip to remove the excess liquid and wait a few min for the agarose pad to solidify at room temperature.</li>
		<li>When the cell sample is ready, remove the coverslip and the plastic film from the blue frame. Pour 10 &#181;L of cell sample on the agarose pad and tilt the glass slide gently to spread the droplet. When all the liquid has been adsorbed, stick a clean coverslip on the blue frame to seal the sample. The microscopy slide is now ready for microscopy.</li>
	</ol>
	</li>
	<li>Place the slide on the microscope stage and perform image acquisition using transmitted light (with a phase contrast objective) and with light source excitation at the appropriate wavelengths (560 nm for mCherry).</li>
	<li>Select fields of view that contain isolated cells in order to facilitate automated cell detection during image analysis. Make sure that at least 300 cells are imaged to allow robust statistical analysis of the cell population.</li>
</ol>
5. Microfluidics time-lapse microscopy imaging
NOTE: The following part explains the preparation of the microfluidic plates (see Table of Materials), cell loading, microfluidics program, and time-lapse image acquisition. This imaging procedure reveals the behavior of individual cells in real-time.
<ol>
	<li>Remove the conservation solution from the microfluidic plate and replace it with fresh medium preheated to 37 &#176;C, as described in the microfluidic software user guide.</li>
	<li>Seal the microfluidic plate to the manifold system and click on the Priming button.</li>
	<li>Place the microfluidic plate with the manifold system on the microscope stage and preheat at 37 &#176;C for ~2 h before starting the microscopy acquisition. 
	NOTE: This preheating step is critical to avoid the dilation of the microfluidic chamber, which would alter the focusing of the microscope during the time-lapse experiment and compromise image acquisition.</li>
	<li>Seal off the microfluidic plate. Replace the medium from well 8 with 150 &#181;L of culture sample and replace the medium from well 1 to 5 by the desired medium with or without the stress-inducing reagent.</li>
	<li>Seal the microfluidic plate and place it on the microscope stage.</li>
	<li>On&#160;the microfluidic software (see Table of Materials)&#160;run the cell loading procedure. Check that the loading of the cells is satisfactory by looking under the microscope in transmitted light. Run the cell loading procedure a second time if the cell density in the chamber is insufficient.</li>
	<li>Perform carefully focus in transmitted light mode and select several fields of view that show isolated bacteria. It is important to select fields that are not overcrowded to be able to monitor the growth of isolated cells over time (~10&#8722;20 cells per 100 &#181;m2 is recommended). This will also facilitate cell detection during image analysis.</li>
	<li>On the microfluidic software, click on the Create a Protocol button. Program the injection of growth medium for 1&#8722;2 generation time equivalents to allow for the cells to adapt (optional). Then program the injection of the stress-inducing medium during 10 min at 2 psi, followed by injection at 1 psi for the wanted duration of the stress treatment. If you intend to analyze the recovery of the cells after stress, program the injection of fresh growth medium for the wanted duration. 
	NOTE: In the experiment presented here, cephalexin was injected for 10 min at 2 psi, followed by 50 min at 1 psi. Then, fresh growth medium was injected at 2 psi for 10 min, followed by 3 h at 1 psi.</li>
	<li>Perform microscopy imaging in time-lapse mode with 1 frame every 10 min using phase contrast in transmitted light and a 560 nm excitation light source for the mCherry signal if required. 
	NOTE: It is important to start microscopic image acquisition at the same time as the start of the microfluidic injection protocol.</li>
</ol>
6. Image analysis
NOTE: This section briefly describes the key steps of processing and analyzing snapshot and time-lapse microscopy images. Opening and visualization of microscopy images is done with the open source ImageJ/Fiji (https://fiji.sc/)11. Quantitative image analysis is performed using the open source ImageJ/Fiji software together with the free MicrobeJ plugin12 (https://microbej.com). This protocol uses the MicrobeJ 5.13I version.
<ol>
	<li>Open the Fiji software and the MicrobeJ plugin.</li>
	<li>For snapshot analysis, drop all images corresponding to one microscope slide (one sample) into the MicrobeJ loading bar to concatenate images and save the obtained image stacks file. For time-lapse data, just drop the image stack into the loading bar of MicrobeJ.</li>
	<li>Run the automated detection of the cells&#39; outlines based on the segmentation of phase contrast image and, if relevant, of the nucleoids based on the segmentation of the stained DNA fluorescence signal. Check the accuracy of the cell detection visually and use the MicrobeJ editing tool for correction if needed. Save the result file obtained. 
	NOTE: The settings used for detection of E. coli cells are indicated in the Table of Materials (see Comments/Description column of MicrobeJ). For other bacterial species (especially for non-rod-shape bacteria), the user must refine the settings before detection (see MicrobeJ tutorial). For time-lapse images, running a semi-automated detection of the cells using the MicrobeJ editing tool might be preferred to allow focusing on the fate of individual cells (see MicrobeJ tutorial).</li>
	<li>Click on the icon ResultJ to complete the analysis and obtain the ResultJ window. Many different types of output graphs can be generated from that point. Plot the normalized histograms of cell shape/length and mean nucleoid number per cell.</li>
</ol>

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W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Coupling+the+initiation+of+chromosome+replication+to+cell+size+in+Escherichia+coli.">Coupling the initiation of chromosome replication to cell size in Escherichia coli.</a> Current Opinion in Microbiology. 6 (2), 146-150 (2003).</li><li>Patterson, D., Gillespie, D. <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+Elevated+Temperatures+on+Protein+Synthesis+in+Escherichia+coli.">Effect of Elevated Temperatures on Protein Synthesis in Escherichia coli.</a> Journal of Bacteriology. 112 (3), 1177 (1972).</li><li>Begg, K. J., Donachie, W. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cell+shape+and+division+in+Escherichia+coli:+experiments+with+shape+and+division+mutants.">Cell shape and division in Escherichia coli: experiments with shape and division mutants.</a> Journal of Bacteriology. 163 (2), 615-622 (1985).</li><li>Van De Putte, P., Van Dillewijn, J., Roersch, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Selection+of+Mutants+of+Escherichia+Coli+with+Impaired+Cell+Division+at+Elevated+Temperature.">The Selection of Mutants of Escherichia Coli with Impaired Cell Division at Elevated Temperature.</a> Mutation Research. 106, 121-128 (1964).</li><li>Walker, A. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Initial+characterization+of+temperature-sensitive+cell+division+mutants+of+Escherichia+coli.">Initial characterization of temperature-sensitive cell division mutants of Escherichia coli.</a> Biochemical and Biophysical Research Communications. 47 (5), 1074-1079 (1972).</li><li>Lesterlin, C., Duabrry, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Investigating+Bacterial+Chromosome+Architecture.">Investigating Bacterial Chromosome Architecture.</a> Chromosome Architecture. 1431, 61-72 (2016).</li><li>Stracy, 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=Live-cell+superresolution+microscopy+reveals+the+organization+of+RNA+polymerase+in+the+bacterial+nucleoid.">Live-cell superresolution microscopy reveals the organization of RNA polymerase in the bacterial nucleoid.</a> Proceedings of the National Academy of Sciences. 112 (32), E4390-E4399 (2015).</li><li>Fisher, J. 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=Four-dimensional+imaging+of+E.+coli+nucleoid+organization+and+dynamics+in+living+cells.">Four-dimensional imaging of E. coli nucleoid organization and dynamics in living cells.</a> Cell. 153 (4), 882-895 (2013).</li><li>Lesterlin, C., Pages, C., Dubarry, N., Dasgupta, S., Cornet, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Asymmetry+of+chromosome+Replichores+renders+the+DNA+translocase+activity+of+FtsK+essential+for+cell+division+and+cell+shape+maintenance+in+Escherichia+coli.">Asymmetry of chromosome Replichores renders the DNA translocase activity of FtsK essential for cell division and cell shape maintenance in Escherichia coli.</a> PLoS genetics. 4 (12), e1000288 (2008).</li><li>Schindelin, 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=Fiji+-+an+Open+Source+platform+for+biological+image+analysis.">Fiji - an Open Source platform for biological image analysis.</a> Nature Methods. 9 (7), (2019).</li><li>Ducret, A., Quardokus, E. 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The authors declared no competing interests.

It is essential to pay attention to the growth state of the cells during the procedure. Grow the cells over several generations before reaching a full exponential phase. For the success of this method, it is important that all cells samples are collected simultaneously, and it is best to analyze only one treated and one untreated culture at the same time. Cell samples for microscopy imaging must be maintained at the experimental temperature throughout the procedure. It is then essential to preheat the microscope chamber and microfluidic chamber before the beginning of the experiment. If cell samples for flow cytometry cannot be analyzed readily, they can be kept on ice for up to 6 h. Incubation on ice will limit the growth and morphological modification of the cells. Alternatively, the user might consider using fixation of the cells in ethanol 75%, which is usually recommended for flow cytometry10. If the protocol requires washing the stress inductor from the medium, centrifuge and pipette cells very carefully to avoid damaging the potential aberrant cells.
Both flow cytometry and snapshot analysis give access to cell size and DNA content parameters, with snapshots providing additional observation of the cell morphology. DNA staining with DAPI10 (4&#39;,6-diamidino-2-phenylindole) or other stable DNA dyes can be performed if no fluorescent fusion is available to observe the nucleoids in the organism of interest. If flow cytometry analysis cannot be performed, it is important to image and analyze a large number of cells by microscopy.
Microscopy imaging can also be performed using strains carrying fluorescent fusions to proteins involved in specific pathways of interest. This would help reveal the effect of stress on a variety of cellular processes such as replication, transcription, cell wall synthesis, or cell division. The method can be applied to a range of bacterial species, the only requirement being that the microfluidic apparatus must be compatible with the morphology of the cells. Standard microfluidic plates are convenient for rod-shape bacteria with a cell width between 0.7 &#181;m and 4.5 &#181;m. However, cocci, ovococci, or other bacterial strains with peculiar shapes need to be tested. Alternatively, if microfluidic experiments cannot be performed due to the unavailability of the equipment or incompatible bacterial strains, time-lapse imaging can be performed on agarose-mounted slides for a maximum duration of 2h.
The overall advantage of this multi-scale analysis is to provide a global vision of the effect of stress induction on several aspects of bacterial growth ability (i.e., mass synthesis, cell viability, cell morphology, membrane integrity, DNA content) and the way these evolve with time in a bacterial population growing under stress conditions. It also allows analyzing the restoration of normal growth at the single-cell level and population level. The approach is applicable to a wide range of bacterial species and to virtually any kind of stress treatment, such as exposure to antibiotic or other antimicrobial compounds, analysis of the influence of interaction with other organisms in multispecies populations, or the effect of genetic mutation.

The overall purpose of this protocol is to analyze the behavior of bacterial cells exposed to stress treatments at the population and at the single-cell levels. Bacterial growth and viability are traditionally addressed at the population level using optical density monitoring (OD600nm), which is a proxy of bacterial cell mass synthesis, or by plating assays to determine the concentration of viable cells in the culture (colony forming unit per milliliter, CFU/mL). Under normal (unstressed) growing conditions, OD600nm and CFU/mL measurements are strictly correlated because bacterial doubling time depends directly on cell mass increase1,2. However, this correlation is often disrupted under conditions that affect cell mass synthesis3, cell division4, or that trigger cell lysis. A simple example is provided by stress treatments that inhibit cell division, which result in the formation of filamentous bacterial cells5,6. Filamentous cells elongate normally because cell mass synthesis is unaffected, but they are unable to divide into viable cells. The culture optical density will consequently increase over time at a normal rate but not the concentration of viable cells determined by plating assays (CFU/mL). In this case, as in many others, optical density and plating measurements are informative but fail to provide a comprehensive understanding of the observed stress-induced effect. These ensemble assays need to be combined with single-cell analysis techniques to allow an in-depth characterization of stress-induced growth deficiencies.
Here, a procedure that combines four complementary experimental approaches is described: (1) traditional plating assays and basic optical density monitoring to monitor cell viability and cell mass synthesis, respectively; (2) flow cytometry to evaluate cell size and DNA content parameters on a large numbers of cells; (3) microscopy snapshot imaging to analyze cell morphology; and (4) time-lapse single-cell imaging in microfluidic chambers for examination of the temporal dynamics of cell fate. This multi-scale framework allows interpreting the global effects on cell growth and viability in the light of the behavior of individual cells. This procedure can be applied to decipher the response of diverse bacterial species to virtually any stress of interest, including growth under particular conditions (i.e., growth medium, pH, temperature, salt concentration), or exposure to antibiotics or other antimicrobial compounds.

<table><tbody><tr><td>Agarose</td><td>BioRad</td><td>1613100</td><td>Certified molecular biology agarose</td></tr><tr><td>Attune NxT Acoustic Focusing Cytometer</td><td>ThermoFisher scientific</td><td>A24858</td><td>Cytometer</td></tr><tr><td>CellASIC ONIX Microfluidic System</td><td>Merck Millipore</td><td>CAX2-S0000</td><td>Microfluidic system</td></tr><tr><td>CellASIC ONIX2 FG</td><td>Merck Millipore</td><td>ONIX2 1.0.1</td><td>Microfluidic software</td></tr><tr><td>CellASIC ONIX2 Manifold Basic</td><td>Merck Millipore</td><td>CAX2-MBC20</td><td>Manifold system</td></tr><tr><td>CytoOne 96-well plate with lid</td><td>Starlab</td><td>CC7672-7596</td><td>Microplate with 0,2 mL well working volume and clear flat bottom, for automated plate reader</td></tr><tr><td>&lt;em&gt;E. coli&lt;/em&gt; strain carrying a chromosomal insertion for a &lt;em&gt;hupA-mCherry&lt;/em&gt; fusion</td><td></td><td></td><td>Created by P1 transduction of hupA-mCherry in E. coli MG1655</td></tr><tr><td>Fiji</td><td>ImageJ</td><td>https://fiji.sc/</td><td>Image software. Cite Schindelin et al. if used in publication</td></tr><tr><td>Gene Frame</td><td>Thermo Scientific</td><td>AB-0578</td><td>Blue frame (125 &amp;mu;L, 1,7 x 2,8 cm)</td></tr><tr><td>Luria-Broth agarose medium</td><td>MP Biomedicals</td><td>3002232</td><td>Growth medium for plating assay</td></tr><tr><td>MicrobeJ</td><td>Imagej/Fiji plugin</td><td>https://www.microbej.com/</td><td>Microscopy image analysis plugin. Cite Ducret &lt;em&gt;et al&lt;/em&gt;. If used in publication; Detection settings: For bacteria : Area (&amp;mu;m2): 0,1-max; Length (&amp;mu;m): 0,5-max; Width (&amp;mu;m): 0,6-max; Range (&amp;mu;m): 0,5-max; Angularity (rad): 0-0,3; 0-max for all other parameters. For nucleoid: Tolerance: 500; Threshold: Local; 0-max for all other parameters</td></tr><tr><td>Microfluidic Plates CellASIC ONIX</td><td>Merck Millipore</td><td>B04A-03-5PK</td><td>Plate for Microfluidic system</td></tr><tr><td>Microscope Nikon eclipse Ti</td><td>Nikon</td><td></td><td>Fluorescence microscope</td></tr><tr><td>MOPS EZ Rich Defined Medium (RDM)</td><td>Teknova</td><td>M2105</td><td>Growth rich medium, 10x MOPS Mixture, 0,132 M K2HPO4, 10x AGCU, 5x Supplement EZ, 20% Glucose. Filtered at 0,22 &amp;mu;m</td></tr><tr><td>SYTO9 Green Fluorescent Nucleic Acid Stain</td><td>ThermoFisher scientific</td><td>S34854</td><td>DNA fluorescent dye</td></tr><tr><td>TECAN Infinite M1000</td><td>TECAN</td><td>30034301</td><td>Automated plate reader</td></tr></tbody></table>

multi-scale analysis of bacterial growth under stress treatments

Analysis of the bacterial ability to grow and survive under stress conditions is essential for a wide range of microbiology studies. It is relevant to characterize the response of bacterial cells to stress-inducing treatments such as exposure to antibiotics or other antimicrobial compounds, irradiation, non-physiological pH, temperature, or salt concentration. Different stress treatments might disturb different cellular processes, including cell division, DNA replication, protein synthesis, membrane integrity, or cell cycle regulation. These effects are usually associated with specific phenotypes at the cellular scale. Therefore, understanding the extent and causality of stress-induced growth or viability deficiencies requires a careful analysis of several parameters, both at the single-cell and at the population levels. The experimental strategy presented here combines traditional optical density monitoring and plating assays with single-cell analysis techniques such as flow cytometry and real time microscopy imaging in live cells. This multiscale framework allows a time-resolved description of the impact of stress conditions on the fate of a bacterial population.

The procedure described was used to analyze the behavior of Escherichia coli K12 cells during transient exposure to cephalexin, an antibiotic that specifically inhibits cell division (Figure 1A)13. The hupA-mCherry E. coli strain that produces the fluorescently labeled HU protein associated with the chromosomal DNA was used to investigate the dynamics of the chromosome throughout this treatment8,9. The exponentially growing hupA-mCherry E. coli cells were analyzed before (t0) and 60 min after incubation with cephalexin (t60). Then, the antibiotic was washed away and the recovery of the cell population after 1 h (t120) and 2 h (t180) was analyzed (Figure 1B).
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/60576/60576fig1.jpg" /> 
Figure 1: Procedure for the analysis of bacterial response to stress treatments. (A) Schematic of the method. (B) Cartoon illustrating the cell morphology during normal growth in rich medium and during transient exposure to cephalexin (Ceph.), from addition at (t0) and after cephalexin washing from (t60) to (t180). <a href="https://www.jove.com/files/ftp_upload/60576/60576fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
The parallel evolution of OD and CFU/mL is a first indicator that helps to understand the effect of the stress treatments. These two parameters are strictly correlated during unperturbed growth but are often uncoupled and evolve independently under stress. Cell cultures growing in the presence of cephalexin exhibited similar OD600nm increases as the unstressed cultures (Figure 2A), showing that the drug did not affect cell mass synthesis. However, the concentration of viable cells did not increase when cephalexin was present due to strict inhibition of cell division (Figure 2B). Cells started dividing again when cephalexin was removed and eventually reached a concentration equivalent to the unstressed culture at (t180). These results reflect the bacteriostatic effect of cephalexin, which induces a fully reversible inhibition of cell division. Different stresses will result in different uncoupling of the OD and CFU/mL curves, depending of the effect induced (e.g., modification of the cell morphology such as filamentation or bulging, cell death with or without lysis). A non-exhaustive list of possible outcome results indicative of different stress-induced effects is presented in Figure 2C.
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/60576/60576fig2.jpg" /> 
Figure 2: Bacterial growth monitoring of untreated and cephalexin-treated cells at the population level. (A) Optical density monitoring (OD600nm/mL). (B) Concentration of viable cell (CFU/mL) within untreated and cephalexin-60min-treated cultures. Error bars indicate the standard deviation for an experimental triplicate. (C) Schematics of possible results and associated stress effects. <a href="https://www.jove.com/files/ftp_upload/60576/60576fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Single-cell analysis is essential to accurately interpret the stress response observed at the population level. Flow cytometry allows the examination of cell size and DNA content of several thousands of cells14,15 (Figure 3). Exposure to cephalexin provoked the parallel increase of cell size and DNA content (t60). When cephalexin was removed, the population cell size and DNA content gradually decreased to become similar to the unstressed population at t180. These results show that cephalexin did not inhibit DNA replication and provoked the formation of filamentous cells that contained several chromosome equivalents. These filaments divided into cells with normal cell size and DNA content when the drug was washed away. Flow cytometry results would be very different for stresses that inhibit DNA synthesis, which lead to the formation of filamentous cells containing only one non-replicating chromosome. In that case, cell size would increase similarly but would not be associated with increase in DNA content.
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/60576/60576fig3.jpg" /> 
Figure 3: Representative flow cytometry analysis of untreated and cephalexin-60min-treated cells. (A) Cell size distribution histograms (FSC-H). (B) DNA content histograms (FL1-SYTO9). n = 120,000 cells analyzed. <a href="https://www.jove.com/files/ftp_upload/60576/60576fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Snapshot microscopy imaging was used to examine the cell morphology and the intracellular organization of the DNA shown by HU-mCherry localization (Figure 4A). Cephalexin provoked the formation of long cells with normal cell width and no division septa. These smooth filaments contained regularly spaced DNA structures called nucleoids, confirming that cephalexin did not affect chromosome replication and segregation. Quantitative image analysis largely confirmed the cell size and DNA content increase previously observed with flow cytometry (Figure 4B,C). Results would be very different for stresses that induce DNA-damage, which lead to the formation of filamentous cells in which replication continues but segregation is impaired. In that case, cell size and DNA content would increase similarly, but cells would harbor a single unstructured mass of DNA. Snapshot images could also reveal other kind of aberrant cell shapes or the presence of mini, anucleate, or lysed cells (ghost cells).
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/60576/60576fig4.jpg" /> 
Figure 4: Microscopy snapshot analysis of untreated and cephalexin-60min-treated cells. (A) Representative microscopy images showing phase contrast (grey) and HU-mCherry signal (red). (B) Cell length distribution histograms. Scale Bar = 5 &#181;m. (C) Histograms of the number of nucleoid per cell. Between 800 and 2,000 cells were analyzed for each sample. <a href="https://www.jove.com/files/ftp_upload/60576/60576fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Time-lapse microscopy associated with the microfluidic apparatus16 helped to determine the phenotypes previously observed and provides additional insights regarding the development and causality of the growth deficiency. Time-lapse images (Figure 5A and Movie 1) confirmed that cell elongation (cell mass synthesis), and chromosome replication and segregation were not inhibited by exposure to cephalexin. In addition, it revealed the process of recovery when cephalexin was removed. Analysis of the filamentous cell lineage showed that cell division restarts ~20 min after washing away the drug (Figure 5B). The resulting divided cells were viable, because they in turn divided, eventually leading to the formation of 33 cells exhibiting normal size and DNA content. This allowed calculation of an overall generation time of ~31 min over the 180 min of the experiment, which is similar to the generation time calculated for the unstressed population from CFU/mL measurements (~33 min).
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/60576/60576fig5.jpg" /> 
Figure 5: Microscopy time-lapse analysis of cephalexin-60min-treated cells. (A) Representative microscopy images showing phase contrast (grey) and HU-mCherry signal (red). The monitored filamentous cell is indicated by the white outline, and divided cells by different colors. Scale Bar = 5 &#181;m. (B) Schematic representation of the filamentous cell lineage corresponding to panel (A) and to Movie 1. <a href="https://www.jove.com/files/ftp_upload/60576/60576fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Movie 1" src="/files/ftp_upload/60576/60576vid1.jpg" /> 
Movie 1: Microfluidic movie of E. coli HU-mCherry treated with cephalexin. Cephalexin was injected after 60 min, followed by injection of fresh RDM medium for 3 h. Time indicated in yellow (1 frame every 10 min). Scale Bar = 5 &#181;m. <a href="https://www.jove.com/files/ftp_upload/60576/Movie1.mp4" target="_blank">Please click here to view this video (Right click to download).</a>

Watch this Scientific Journal Video about Multi-scale Analysis of Bacterial Growth Under Stress Treatments at JoVE.com

Multi-scale Analysis of Bacterial Growth Under Stress Treatments

This protocol allows a time-resolved description of bacterial growth under stress conditions at the single-cell and the cell population levels.

Analysis of the bacterial ability to grow and survive under stress conditions is essential for a wide range of microbiology studies. It is relevant to ...

multi-scale-analysis-of-bacterial-growth-under-stress-treatments

Research

JoVE Journal

Immunology and Infection

9.3K Views.  University of Lyon 1, CNRS, Inserm. This protocol allows a time-resolved description of bacterial growth under stress conditions at the single-cell and the cell population levels.

Video: Multi-scale Analysis of Bacterial Growth Under Stress Treatments

Introducing Shear Stress in the Study of Bacterial Adhesion

During bacterial infections a sequence of interactions occur between the pathogen and its host. Bacterial adhesion to the host cell surface is often the initial and determining step of the pathogenesis. Although experimentally adhesion is mostly studied in static conditions adhesion actually takes place in the presence of flowing liquid. First encounters between bacteria and their host often occur at the mucosal level, mouth, lung, gut, eye, etc. where mucus flows along the surface of epithelial cells. Later in infection, pathogens occasionally access the blood circulation causing life-threatening illnesses such as septicemia, sepsis and meningitis. A defining feature of these infections is the ability of these pathogens to interact with endothelial cells in presence of circulating blood. The presence of flowing liquid, mucus or blood for instance, determines adhesion because it generates a mechanical force on the pathogen. To characterize the effect of flowing liquid one usually refers to the notion of shear stress, which is the tangential force exerted per unit area by a fluid moving near a stationary wall, expressed in dynes/cm2. Intensities of shear stress vary widely according to the different vessels type, size, organ, location etc. (0-100 dynes/cm2). Circulation in capillaries can reach very low shear stress values and even temporarily stop during periods ranging between a few seconds to several minutes 1. On the other end of the spectrum shear stress in arterioles can reach 100 dynes/cm2 2. The impact of shear stress on different biological processes has been clearly demonstrated as for instance during the interaction of leukocytes with the endothelium 3. To take into account this mechanical parameter in the process of bacterial adhesion we took advantage of an experimental procedure based on the use of a disposable flow chamber 4. Host cells are grown in the flow chamber and fluorescent bacteria are introduced in the flow controlled by a syringe pump. We initially focused our investigations on the bacterial pathogen Neisseria meningitidis, a Gram-negative bacterium responsible for septicemia and meningitis. The procedure described here allowed us to study the impact of shear stress on the ability of the bacteria to: adhere to cells 1, to proliferate on the cell surface 5and to detach to colonize new sites 6 (Figure 1). Complementary technical information can be found in reference 7. Shear stress values presented here were chosen based on our previous experience1 and to represent values found in the literature. The protocol should be applicable to a wide range of pathogens with specific adjustments depending on the objectives of the study.

During the infection process, a key step is the adhesion of pathogens with host cells. In most instances this adhesion step occurs in the presence of mechanical stress generated by flowing liquid. We describe a technique that introduces shear stress as an important parameter in the study of bacterial adhesion.

During bacterial infections a sequence of interactions occur between the pathogen and its host. Bacterial adhesion to the host cell surface is often the ...

Stress-induced Antibiotic Susceptibility Testing on a Chip

We have developed a rapid microfluidic method for antibiotic susceptibility testing in a stress-based environment. Fluid is passed at high speeds over bacteria immobilized on the bottom of a microfluidic channel. In the presence of stress and antibiotic, susceptible strains of bacteria die rapidly. However, resistant bacteria survive these stressful conditions. The hypothesis behind this method is new: stress activation of biochemical pathways, which are targets of antibiotics, can accelerate antibiotic susceptibility testing. As compared to standard antibiotic susceptibility testing methods, the rate-limiting step -&#160;bacterial growth -&#160;is omitted during antibiotic application. The technical implementation of the method is in a combination of standard techniques and innovative approaches. The standard parts of the method include bacterial culture protocols, defining microfluidic channels in polydimethylsiloxane&#160;(PDMS), cell viability monitoring with fluorescence, and batch image processing for bacteria counting. Innovative parts of the method are in the use of culture media flow for mechanical stress application, use of enzymes to damage but not kill the bacteria, and use of microarray substrates for bacterial attachment. The developed platform can be used in antibiotic and nonantibiotic related drug development and testing. As compared to the standard bacterial suspension experiments, the effect of the drug can be turned on and off repeatedly over controlled time periods. Repetitive observation of the same bacterial population is possible over the course of the same experiment.

We have developed a microfluidic platform for rapid antibiotic susceptibility testing. Fluid is passed at high speeds over bacteria immobilized on the bottom of a microfluidic channel. In the presence of stress and antibiotic, susceptible strains of bacteria die rapidly. However, resistant bacteria can survive these stressful conditions.

We have developed a rapid microfluidic method for antibiotic susceptibility testing in a stress-based environment. Fluid is passed at high speeds over ...

Bioengineering

ScanLag: High-throughput Quantification of Colony Growth and Lag Time

Growth dynamics are fundamental characteristics of microorganisms. Quantifying growth precisely is an important goal in microbiology. Growth dynamics are affected both by the doubling time of the microorganism and by any delay in growth upon transfer from one condition to another, the lag. The ScanLag method enables the characterization of these two independent properties at the level of colonies originating each from a single cell, generating a two-dimensional distribution of the lag time and of the growth time. In ScanLag, measurement of the time it takes for colonies on conventional nutrient agar plates to be detected is automated on an array of commercial scanners controlled by an in house application. Petri dishes are placed on the scanners, and the application acquires images periodically. Automated analysis of colony growth is then done by an application that returns the appearance time and growth rate of each colony. Other parameters, such as the shape, texture and color of the colony, can be extracted for multidimensional mapping of sub-populations of cells. Finally, the method enables the retrieval of rare variants with specific growth phenotypes for further characterization. The technique could be applied in bacteriology for the identification of long lag that can cause persistence to antibiotics, as well as a general low cost technique for phenotypic screens.

ScanLag is a high-throughput method for measuring the delay in growth, namely lag time, as well as the growth rate of colonies for thousands of cells in parallel. Screening using ScanLag enables the discrimination between long lag-time and slow growth at the level of a single variant.

Growth dynamics are fundamental characteristics of microorganisms. Quantifying growth precisely is an important goal in microbiology. Growth dynamics are ...

Extraction and Visualization of Protein Aggregates after Treatment of Escherichia coli with a Proteotoxic Stressor

The exposure of living organisms to environmental and cellular stresses often causes disruptions in protein homeostasis and can result in protein aggregation. The accumulation of protein aggregates in bacterial cells can lead to significant alterations in the cellular phenotypic behavior, including a reduction in growth rates, stress resistance, and virulence. Several experimental procedures exist for the examination of these stressor-mediated phenotypes. This paper describes an optimized assay for the extraction and visualization of aggregated and soluble proteins from different Escherichia coli strains after treatment with a silver-ruthenium-containing antimicrobial. This compound is known to generate reactive oxygen species and causes widespread protein aggregation. 
The method combines a centrifugation-based separation of protein aggregates and soluble proteins from treated and untreated cells with subsequent separation and visualization by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and Coomassie staining. This approach is simple, fast, and allows a qualitative comparison of protein aggregate formation in different E. coli strains. The methodology has a wide range of applications, including the possibility to investigate the impact of other proteotoxic antimicrobials on in vivo protein aggregation in a wide range of bacteria. Moreover, the protocol can be used to identify genes that contribute to increased resistance to proteotoxic substances. Gel bands can be used for the subsequent identification of proteins that are particularly prone to aggregation.

Extraction and Visualization of Protein Aggregates after Treatment of Escherichia coli with a Proteotoxic Stressor

This protocol describes the extraction and visualization of aggregated and soluble proteins from Escherichia coli after treatment with a proteotoxic antimicrobial. Following this procedure allows a qualitative comparison of protein aggregate formation in vivo in different bacterial strains and/or between treatments.

The exposure of living organisms to environmental and cellular stresses often causes disruptions in protein homeostasis and can result in protein ...

Biochemistry

Assembly and Tracking of Microbial Community Development within a Microwell Array Platform

The development of microbial communities depends on a combination of complex deterministic and stochastic factors that can dramatically alter the spatial distribution and activities of community members. We have developed a microwell array platform that can be used to rapidly assemble and track thousands of bacterial communities in parallel. This protocol highlights the utility of the platform and describes its use for optically monitoring the development of simple, two-member communities within an ensemble of arrays within the platform. This demonstration uses two mutants of Pseudomonas aeruginosa, part of a series of mutants developed to study Type VI secretion pathogenicity. Chromosomal inserts of either mCherry or GFP genes facilitate the constitutive expression of fluorescent proteins with distinct emission wavelengths that can be used to monitor community member abundance and location within each microwell. This protocol describes a detailed method for assembling mixtures of bacteria into the wells of the array and using time-lapse fluorescence imaging and quantitative image analysis to measure the relative growth of each member population over time. The seeding and assembly of the microwell platform, the imaging procedures necessary for the quantitative analysis of microbial communities within the array, and the methods that can be used to reveal interactions between microbial species area all discussed.

The development of microbial communities depends on a combination of factors, including environmental architecture, member abundance, traits, and interactions. This protocol describes a synthetic, microfabricated environment for the simultaneous tracking of thousands of communities contained in femtoliter wells, where key factors such as niche size and confinement can be approximated.

The development of microbial communities depends on a combination of complex deterministic and stochastic factors that can dramatically alter the spatial ...

Immunofluorescence Analysis of Stress Granule Formation After Bacterial Challenge of Mammalian Cells

Fluorescent imaging of cellular components is an effective tool to investigate host-pathogen interactions. Pathogens can affect many different features of infected cells, including organelle ultrastructure, cytoskeletal network organization, as well as cellular processes such as Stress Granule (SG) formation. The characterization of how pathogens subvert host processes is an important and integral part of the field of pathogenesis. While variable phenotypes may be readily visible, the precise analysis of the qualitative and quantitative differences in the cellular structures induced by pathogen challenge is essential for defining statistically significant differences between experimental and control samples. SG formation is an evolutionarily conserved stress response that leads to antiviral responses and has long been investigated using viral infections1. SG formation also affects signaling cascades and may have other still unknown consequences2. The characterization of this stress response to pathogens other than viruses, such as bacterial pathogens, is currently an emerging area of research3. For now, quantitative and qualitative analysis of SG formation is not yet routinely used, even in the viral systems. Here we describe a simple method for inducing and characterizing SG formation in uninfected cells and in cells infected with a cytosolic bacterial pathogen, which affects the formation of SGs in response to various exogenous stresses. Analysis of SG formation and composition is achieved by using a number of different SG markers and the spot detector plug-in of ICY, an open source image analysis tool.

We describe a method for the qualitative and quantitative analysis of stress granule formation in mammalian cells after the cells are challenged with bacteria and a number of different stresses. This protocol can be applied to investigate the cellular stress granule response in a wide range of host-bacterial interactions.

Fluorescent imaging of cellular components is an effective tool to investigate host-pathogen interactions. Pathogens can affect many different features of ...

Precise, High-throughput Analysis of Bacterial Growth

Bacterial growth is a central concept in the development of modern microbial physiology, as well as in the investigation of cellular dynamics at the systems level. Recent studies have reported correlations between bacterial growth and genome-wide events, such as genome reduction and transcriptome reorganization. Correctly analyzing bacterial growth is crucial for understanding the growth-dependent coordination of gene functions and cellular components. Accordingly, the precise quantitative evaluation of bacterial growth in a high-throughput manner is required. Emerging technological developments offer new experimental tools that allow updates of the methods used for studying bacterial growth. The protocol introduced here employs a microplate reader with a highly optimized experimental procedure for the reproducible and precise evaluation of bacterial growth. This protocol was used to evaluate the growth of several previously described Escherichia coli strains. The main steps of the protocol are as follows: the preparation of a large number of cell stocks in small vials for repeated tests with reproducible results, the use of 96-well plates for high-throughput growth evaluation, and the manual calculation of two major parameters (i.e., maximal growth rate and population density) representing the growth dynamics. In comparison to the traditional colony-forming unit (CFU) assay, which counts the cells that are cultured in glass tubes over time on agar plates, the present method is more efficient and provides more detailed temporal records of growth changes, but has a stricter detection limit at low population densities. In summary, the described method is advantageous for the precise and reproducible high-throughput analysis of bacterial growth, which can be used to draw conceptual conclusions or to make theoretical observations.

Quantitative evaluation of bacterial growth is essential to understanding microbial physiology as a systems-level phenomenon. A protocol for experimental manipulation and an analytical approach are introduced, allowing for precise, high-throughput analysis of bacterial growth, which is a key subject of interest in systems biology.

Bacterial growth is a central concept in the development of modern microbial physiology, as well as in the investigation of cellular dynamics at the ...

Biology

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 ...

High-Throughput Live Imaging of Microcolonies to Measure Heterogeneity in Growth and Gene Expression

Precise measurements of between- and within-strain heterogeneity in microbial growth rates are essential for understanding genetic and environmental inputs into stress tolerance, pathogenicity, and other key components of fitness. This manuscript describes a microscope-based assay that tracks approximately 105&#160;Saccharomyces cerevisiae microcolonies per experiment. After automated time-lapse imaging of yeast immobilized in a multiwell plate, microcolony growth rates are easily analyzed with custom image-analysis software. For each microcolony, expression and localization of fluorescent proteins and survival of acute stress can also be monitored. This assay allows precise estimation of strains&#39; average growth rates, as well as comprehensive measurement of heterogeneity in growth, gene expression, and stress tolerance within clonal populations.

Yeast growth phenotypes are precisely measured through highly parallel time-lapse imaging of immobilized cells growing into microcolonies. Simultaneously, stress tolerance, protein expression, and protein localization can be monitored, generating integrated datasets to study how environmental and genetic differences, as well as gene-expression heterogeneity among isogenic cells, modulate growth.

Precise measurements of between- and within-strain heterogeneity in microbial growth rates are essential for understanding genetic and environmental ...

Measuring the Migration and Biofilm Formation of Various Bacteria

As microbes that thrive in the host body primarily have adaptive abilities that facilitate their survival, methods for classifying and identifying their nature would be beneficial in facilitating their characterization. Currently, most studies focus only on one specific characterization method; however, the isolation and identification of microorganisms from the host is a continuous process and usually requires several combinatorial characterization methods. Herein, we describe methods of identifying the microbial biofilm-forming ability, the microbial respiration state, and their chemotaxis behavior. The methods are used to identify five microbes, three of which were isolated from the bone tissue of Sprague-Dawley (SD) rats (Corynebacterium stationis, Staphylococcus cohnii subsp. urealyticus, and Enterococcus faecalis) and two from the American Type Culture Collection (ATCC)-Staphylococcus aureus ATCC 25923&#160;and Enterococcus faecalis V583. The microbes isolated from the SD rat bone tissue include the gram-positive microbes. These microbes have adapted to thrive under stressful and nutrient-limiting environments within the bone matrix. This article aims to provide the readers with the specific know-how of determining the nature and behavior of the isolated microbes within a laboratory setting.

Here, we present a practical method for the isolation and identification of microorganisms within the host. In this way, the physicochemical properties of microorganisms and possible ways of living in the host are clearly described.

As microbes that thrive in the host body primarily have adaptive abilities that facilitate their survival, methods for classifying and identifying their ...

Multi-scale Analysis of Bacterial Growth Under Stress Treatments

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Rozdziały w tym wideo

Introducing Shear Stress in the Study of Bacterial Adhesion

Stress-induced Antibiotic Susceptibility Testing on a Chip

ScanLag: High-throughput Quantification of Colony Growth and Lag Time

Extraction and Visualization of Protein Aggregates after Treatment of Escherichia coli with a Proteotoxic Stressor

Assembly and Tracking of Microbial Community Development within a Microwell Array Platform

Immunofluorescence Analysis of Stress Granule Formation After Bacterial Challenge of Mammalian Cells

Precise, High-throughput Analysis of Bacterial Growth

Single-cell Microfluidic Analysis of Bacillus subtilis

High-Throughput Live Imaging of Microcolonies to Measure Heterogeneity in Growth and Gene Expression

Measuring the Migration and Biofilm Formation of Various Bacteria