We thank Matt Parsek at the University of Washington (Seattle, WA) for providing P. aeruginosa and E. coli strains and Roger Nokes at the University of Canterbury (New Zealand) for providing access to Streams software. This work was supported by grant R01AI081983 from the National Institutes of Health, National Institute of Allergy and Infectious Diseases. Confocal imaging was performed at the Northwestern Biological Imaging Facility (BIF).

1. Flow Cell Setup and Inoculation
NOTE: Use a double-inlet microfluidic flow cell described in Song et al., 201414 to grow biofilms. This flow cell is able to create well-defined smooth chemical gradients. The flow cell design is shown in Figure 1 and flow cell fabrication was previously described in Song et al., 201414. Here we detail our methods by using P. aeruginosa and E. coli to form biofilms, but other species may be suitable too. We used P. aeruginosa PAO1-gfp, which constitutively expresses a green fluorescent protein (GFP), as a model organism for biofilm development. Additionally, we used E. coli DH5&#945; to form mixed-species biofilms with P. aeruginosa. P. aeruginosa and E. coli strains were grown on LB agar plates.
<ol>
	<li>Prepare the flow cell using polydimethylsiloxane (PDMS) bound to a glass coverslip via oxygen plasma treatment as described in14. The dimensions of the flow cell chamber are 23 mm &#215; 13 mm &#215; 0.24 mm (length &#215; width &#215; depth).</li>
	<li>Prepare modified FAB growth medium15. To observe biofilm growth under a nutritional gradient within the flow cell, introduce modified FAB medium15 with 0.6 &#956;M glucose in one inlet and introduce FAB medium without any carbon source through the other inlet. Filter-sterilize (pore size = 0.2 &#956;m) the glucose stock solution (60 mM) before adding it to the FAB medium. Also autoclave the FAB medium with cycle 1 (liquid, 15 min; 121 &#176;C, 17 psi) before use.</li>
	<li>Sterilize the flow system. Prior to inoculation, autoclave the entire flow path (medium bottles, tubing, bubble traps, flow cells) using cycle 1, except for the plastic three-way valves (disposable and pre-sterilized) located upstream of the flow cell. (Three-ways valves are used for injecting cell culture, fluorescent tracer and microbeads.) To avoid contamination during assembly, cover all the tubing and connector openings with aluminum foil or autoclave bags before autoclaving.</li>
	<li>Connect the flow system. Assemble the components of the flow cell system carefully (see video for flow system assembly) and deliver growth medium to the flow cell via a peristaltic pump that precisely controls the flow rate.</li>
	<li>Prepare cell culture for inoculation by transferring a colony of P. aeruginosa or E. coli from LB plates to 3 ml of LB broth and shake the culture O/N at 225 rpm and 37 &#176;C. Dilute the O/N cell cultures in 1 ml sterilized water to a final OD600 = 0.01 as the inoculum. (Culture and dilute the bacteria in a laminar flow hood to avoid contamination.)</li>
	<li>For the experiments with mixed-species biofilms, dilute the two bacterial cultures to a ratio of 1:1 in 1 ml with an equivalent OD600 = 0.01 for each bacterium.</li>
	<li>Inoculate the flow cell. Inject 1 ml of the inoculum to the flow cell inlet from the three-way valve. After the injection, pause the flow for 1 hr to allow bacterial cells to attach to the cover glass. (Make sure that the flow cell is placed with the coverslip side down to allow suspended cells to settle onto the coverslip.)</li>
	<li>After 1 hr, resume the flow and pump the growth medium to the flow cell at a constant rate of 0.03 ml/min for each inlet for 3 days.</li>
</ol>
2. Characterizing Biofilm Development in Response to Nutrient Gradients Using Confocal Microscopy

NOTE: P. aeruginosa can be imaged with constitutively-expressed GFP, but E. coli in mixed-species biofilms must be imaged by counterstaining.

<ol>
	<li>Observe the 3-day biofilms using confocal microscopy. For the representative results, observe biofilms using a confocal microscope with a 63X objective. Prior to imaging, mark the double-inlet flow cell with a grid on the cover glass side. (The purpose of this grid is to allow the experimenter to locate the imaging regions within the flow cell chamber.)</li>
	<li>To counterstain, dilute 10 &#956;l of cell-permeant red fluorescent nucleic acid stain, such as green fluorescent nucleic acid stain such as STYO 62, stock solution (1 mM) in 990 &#956;l sterilized water and then slowly inject the diluted stain using a syringe into the flow cell chamber from the upstream three-way valve. Keep the flow cell stagnant and in the dark for 30 min, then resume the flow to wash out the unbound stain for 15 min.</li>
	<li>Perform confocal imaging. Activate the 488 nm Argon laser for excitation and the emission collecting channels for GFP (500-535 nm) and nucleic acid stain (for green fluorescent nucleic acid stain, 650-750 nm). Adjust gains and offsets for both channels to have bright and clean images. Select xyz and simultaneous imaging mode. Use the z-control knob to identify the bottom and top of the biofilm in the field. Set the z-step to 0.5 &#956;m for acquiring a 3-D image stack. (To ensure high image quality, use a line average of four for image acquisition.)</li>
	<li>To map the spatial patterns of biofilm development within the flow cell, image biofilms at three or more longitudinal (x) distances along the flow cell inlet, and at three transverse (y) positions relative to the imposed nutritional gradient, as shown in Figure 1.</li>
</ol>
3. Characterizing Internal Solute Transport by Injections of Conservative Fluorescent Tracer
NOTE: A conservative fluorescent tracer, such as Cy5, can be used to characterize solute transport patterns within the biofilm.
<ol>
	<li>Dissolve Cy5 (Mono-Reactive NHS Ester) in water to a final concentration of 10 mg/ml as a stock solution. Store the Cy5 stock solution in a -20 &#176;C freezer. 
	NOTE: As Cy5 is light-sensitive, store, dilute and inject Cy5 solutions in the dark.</li>
	<li>Prior to the injections of the fluorescent tracer, take a 3-D image stack of the 3-day biofilm with confocal microscopy (with a 63X objective). (Wide regions of biofilm colonies are ideal for time-series observations of dye transport.) Also choose a z-plane with well-separated colonies for imaging (as shown in Figure 5A).</li>
	<li>For each Cy5 injection experiment, dilute 2 &#956;l of the Cy5 stock solution in 998 &#956;l sterilized water to yield an injection solution having a Cy5 concentration of 20 &#956;g/ml.</li>
	<li>Stop the pump to pause the flow and inject the Cy5 solution into the upstream of the flow cell using a syringe via the 3-way valve. (It is important to prevent air bubbles from entering the flow path while injecting. Bubble traps should be kept open during the back injection.)</li>
	<li>After injecting the Cy5 solution, close the bubble traps, adjust the 3-way valve, and restart the pump to deliver the injected Cy5 solution into the flow cell.</li>
	<li>Switch confocal imaging mode to xyt. Activate Cy5 and GFP channels under simultaneous imaging mode. Adjust confocal settings on Cy5 intensity (laser intensity, gain and offset) to avoid saturating signals, which is critical for quantification. (High temporal resolution is preferred for visualizing dye penetration. However, fast scanning decreases image quality.) Choose proper scanning speed and line average to balance the time resolution of imaging and the image quality. For this protocol use a line average of four and a frame rate of 0.15 Hz.</li>
	<li>Resume the flow to deliver Cy5 into the flow cell (still at a flow rate of 0.03 ml/min). Simultaneously start time-series confocal imaging.</li>
	<li>Quantify Cy5 penetration by radially averaging Cy5 intensity within a 2-D circular biofilm colony. To average, first identify the edge of a biofilm cluster, then generate a distance map for a 2-D section of the cluster, and finally average radial patterns of Cy5 intensities to generate a penetration curve (see Figure&#160;6).
	<ol>
		<li>To computationally realize step 3.8, use BioSPA (Biofilm Spatial Pattern Analysis) software package (unpublished, software package and manual available upon request) or other image analysis programs.</li>
		<li>To use BioSPA, first import an image set into BioSPA. Then select proper threshold for GFP and Cy5 channels to make binary images. In the analysis/calculation menu, select Advanced Analysis and then Diffusion Analysis. Use the GFP channel to define the edge of a cluster and use the polygon tool to select one cluster as the region of interest (ROI).</li>
		<li>Double click the selected biofilm cluster to perform diffusion analysis. Save the diffusion analysis results and calibrate Cy5 intensity to Cy5 concentration using a calibration curve.
		<ol>
			<li>To generate Cy5 concentration calibration curve, measure Cy5 intensities over a Cy5 concentration gradient under confocal microscopy. (Cy5 intensity and concentration have a linear relationship.)</li>
		</ol>
		</li>
	</ol>
	</li>
</ol>
4. Characterizing the Surrounding Flow Field by Tracking Fluorescent Particles
NOTE: Fluorescent particles, such as fluorescent microbeads, can be used to characterize the flow field around biofilms. Flow field around biofilms can be calculated from the time-series observations of particle positions using particle tracking velocimetry software. The results shown here were obtained with the Streams 2.02 software package16 (software download and user&#8217;s guide available at <a href="http://www.civil.canterbury.ac.nz/streams.shtml">http://www.civil.canterbury.ac.nz/streams.shtml</a>).
<ol>
	<li>Dilute the fluorescent microbeads (diameter ~1 &#956;m) in sterilized water to a final solid concentration of 0.2% and a final volume of 0.5 ml. Vortex to make sure that the microbeads are well dispersed.</li>
	<li>Inject and deliver the diluted fluorescent microbeads into the flow cell following procedures from steps 3.3 to 3.5. To allow an accurate tracking of the particle path, use a relatively low flow rate (0.01 ml/hr for the particle tracking results in this paper).</li>
	<li>Switch confocal settings to xyt mode to track particle movement at one z-slice and take time-series images. (A frame rate of 1 Hz was used for the representative results shown in this paper.) Repeat particle injection and image at different z locations to generate 3-D flow field.</li>
	<li>Pre-process the time-series confocal images by subtracting the background fluorescence signal (the signal in the first acquired image of the image set) using ImageJ (software download and manual available on <a href="http://imagej.nih.gov/ij/">http://imagej.nih.gov/ij/</a>) or other programs.</li>
	<li>In ImageJ, open the first image of an image set and then import the image set. Under Process / Image Calculator, subtract the first image from the image set. Save the pre-processed image set.</li>
	<li>To calculate flow vectors, import time-series confocal images in Streams 2.02. Under &#8220;Open process view&#8221;, select and execute &#8220;Identify particles&#8221;. Use proper threshold to identify particles. Use 0.5 and 5 &#956;m as minimum and maximum diameter thresholds for 1 &#956;m particles.</li>
	<li>Then under &#8220;Open process view&#8221;, select and execute &#8220;PTV analysis pipeline&#8221; to generate particle paths. Check the particle paths to see if they represent particle movement. Finally, select and execute &#8220;Create velocity field&#8221; to generate a flow vector map.</li>
</ol>

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The authors have nothing to disclose.

We demonstrated a suite of methods to characterize three important biofilm-environment interactions: biofilm response to chemical gradients, effects of biofilm growth on the surrounding flow microenvironment, and biofilm heterogeneity resulting from internal transport limitations.
We first showed the use of a novel microfluidic flow cell to impose a well-defined chemical gradient for biofilm development. To generate a well-defined chemical gradient within the flow cell, it is important to main...

Microorganisms attach to surfaces and form biofilms &#8212; cell aggregates enclosed in an extracellular-polymer matrix1. Biofilms behave very differently from individual microbial cells, because biofilms have dramatic spatial heterogeneity resulting from a combination of internal solute transport limitations and spatial variations in cellular metabolism2,3. Oxygen and nutrient concentrations drastically decrease at the interface between biofilm and surrounding fluid and get further depleted within in the biofilm2. Spatial variations in biofilm respiration and protein synthesis can also occur as a response to localized oxygen and nutrient availability2.
In aquatic and soil environments, most bacteria dwell in biofilms. Natural biofilms carry out important biogeochemical processes including cycling carbon and nitrogen and reducing metals4,5. Clinically, biofilm formation is responsible for prolonged pulmonary and urinary infections6. Biofilm-associated infections are highly problematic because cells in biofilms have extremely high resistance to antimicrobials compared to their planktonic counterparts6. Because biofilms are important in diverse settings, a substantial amount of research has been focused on understanding the environmental factors that control biofilm activities and the spatial heterogeneity in biofilms and the surrounding microenvironment.
Previous studies have found that biofilm development is strongly regulated by a number of environmental factors: biofilms develop different morphologies under various flow conditions; oxygen and nutrient availability influence biofilm morphology; and hydrodynamic shear stress affects the attachment of planktonic cells to surfaces and the detachment of cells from biofilms7-9. Furthermore, external flow condition influences the delivery of substrates into and within biofilms10. The growth of biofilms also alters surrounding physical and chemical conditions. For example, biofilm growth leads to local depletion of oxygen and nutrients2; biofilms accumulate inorganic and organic compounds from the surrounding environment11; and biofilm clusters divert flow and increase surface friction12,13. Because biofilms interact with their surrounding environment in very complex ways, it is critical to simultaneously obtain information on biofilm properties and environmental conditions, and multi-disciplinary approaches need to be used to comprehensively characterize biofilm-environment interactions.
Here we present a series of integrated methods to characterize spatial patterns in microbial growth within mono-species and dual-species biofilms under an imposed nutritional gradient, and to observe the resulting modification of the local chemical and fluid microenvironment. We first describe the use of a recently developed double-inlet microfluidic flow cell to observe biofilm growth under well-defined chemical gradients. We then demonstrate the use of this microfluidic flow cell to observe the growth of two species of bacteria, Pseudomonas aeruginosa and Escherichia coli, in biofilms under a range of nutritional conditions. We show how in situ visualization of fluorescent tracer propagation into biofilm colonies can be used to quantitatively assess patterns of solute transport in biofilms. Finally, we show how microscale particle tracking velocimetry, performed under confocal microscopy, can be used to obtain local flow field around the growing biofilms.

<table border="0" cellpadding="0" cellspacing="0" width="586">
	<tbody>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">Name of Material/ Equipment</td>
			<td style="width:89px;">Company</td>
			<td style="width:104px;">Catalog Number</td>
			<td style="width:167px;">Comments/Description</td>
		</tr>
		<tr height="50">
			<td height="50" style="height:50px;">Peristaltic Pump</td>
			<td style="width:89px;">Gilson</td>
			<td style="width:104px;">Miniplus 3</td>
			<td style="width:167px;">Flow cell setup and inoculation</td>
		</tr>
		<tr height="50">
			<td height="50" style="height:50px;width:227px;">PUMP TUBING 0.50MM OVC, Orange/Yellow</td>
			<td style="width:89px;">Gilson</td>
			<td style="width:104px;">F117934</td>
			<td style="width:167px;">Flow cell setup and inoculation</td>
		</tr>
		<tr height="50">
			<td height="50" style="height:50px;width:227px;">Three-way Stopcock w/ Swivel male Luer lock</td>
			<td style="width:89px;">Smiths Medical&#160;</td>
			<td style="width:104px;">MX9311L</td>
			<td style="width:167px;">Flow cell setup and inoculation</td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:227px;">Sylgard 184 Solar Cell Encapsulation for Making Solar Panels</td>
			<td style="width:89px;">ML Solar LLC</td>
			<td style="width:104px;"></td>
			<td style="width:167px;">Flow cell setup and inoculation</td>
		</tr>
		<tr height="50">
			<td height="50" style="height:50px;width:227px;">Pyrex Medium Bottle, 1L, GL45</td>
			<td style="width:89px;">VWR</td>
			<td>16157-191</td>
			<td style="width:167px;">Flow cell setup and inoculation</td>
		</tr>
		<tr height="50">
			<td height="50" style="height:50px;width:227px;">C-FLEX Tubing</td>
			<td style="width:89px;">Cole-Parmer</td>
			<td style="width:104px;">06422-02</td>
			<td style="width:167px;">Flow cell setup and inoculation</td>
		</tr>
		<tr height="50">
			<td height="50" style="height:50px;width:227px;">1 mL TB Syringe</td>
			<td style="width:89px;">BD</td>
			<td style="width:104px;">309659</td>
			<td style="width:167px;">Flow cell setup and inoculation</td>
		</tr>
		<tr height="50">
			<td height="50" style="height:50px;width:227px;">Polymer Tubing</td>
			<td style="width:89px;">IDEX</td>
			<td style="width:104px;">1520G</td>
			<td style="width:167px;">Flow cell setup and inoculation</td>
		</tr>
		<tr height="50">
			<td height="50" style="height:50px;width:227px;">Sterile Intramedic Luer Stub Adapter</td>
			<td style="width:89px;">Clay Adams</td>
			<td style="width:104px;">427564</td>
			<td style="width:167px;">Flow cell setup and inoculation</td>
		</tr>
		<tr height="50">
			<td height="50" style="height:50px;width:227px;">PrecisionGlide Needle</td>
			<td style="width:89px;">BD</td>
			<td style="width:104px;">305195</td>
			<td style="width:167px;">Flow cell setup and inoculation</td>
		</tr>
		<tr height="50">
			<td height="50" style="height:50px;width:227px;">Spectrophotometer</td>
			<td style="width:89px;">HACH</td>
			<td style="width:104px;"></td>
			<td style="width:167px;">Flow cell setup and inoculation</td>
		</tr>
		<tr height="50">
			<td height="50" style="height:50px;width:227px;">Syringe filters- sterile (0.2 &#956;m)</td>
			<td style="width:89px;">Fisherbrand</td>
			<td style="width:104px;">09-719A</td>
			<td style="width:167px;">Flow cell setup and inoculation</td>
		</tr>
		<tr height="50">
			<td height="50" style="height:50px;width:227px;">MAXQ Shaker</td>
			<td style="width:89px;">Thermo Scientific</td>
			<td style="width:104px;"></td>
			<td style="width:167px;">Flow cell setup and inoculation</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">Ammonium sulfate</td>
			<td style="width:89px;">Sigma Aldrich</td>
			<td style="width:104px;">A4418</td>
			<td>Growth media</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">Sodium phosphate dibasic anhydrous</td>
			<td style="width:89px;">Sigma Aldrich</td>
			<td style="width:104px;">RES20908-A7</td>
			<td>Growth media</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">Monobasic potassium phosphate</td>
			<td style="width:89px;">Sigma Aldrich</td>
			<td style="width:104px;">P5655</td>
			<td>Growth media</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">Sodium chloride</td>
			<td style="width:89px;">Sigma Aldrich</td>
			<td style="width:104px;">S7653</td>
			<td>Growth media</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">Magnisium chloride</td>
			<td style="width:89px;">Sigma Aldrich</td>
			<td style="width:104px;">M8266</td>
			<td>Growth media</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">Calcium chloride</td>
			<td style="width:89px;">Sigma Aldrich</td>
			<td style="width:104px;">C5670</td>
			<td>Growth media</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">Calcium sulfate dihydrate</td>
			<td style="width:89px;">Sigma Aldrich</td>
			<td style="width:104px;">C3771</td>
			<td>Growth media</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">Iron(II) sulfate heptahydrate</td>
			<td style="width:89px;">Sigma Aldrich</td>
			<td style="width:104px;">215422</td>
			<td>Growth media</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">Manganese(II) sulfate monohydrate</td>
			<td style="width:89px;">Sigma Aldrich</td>
			<td style="width:104px;">M7634</td>
			<td>Growth media</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">Copper(II) sulfate</td>
			<td style="width:89px;">Sigma Aldrich</td>
			<td style="width:104px;">451657</td>
			<td>Growth media</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">Zinc sulfate heptahydrate</td>
			<td style="width:89px;">Sigma Aldrich</td>
			<td style="width:104px;">Z0251</td>
			<td>Growth media</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">Cobalt(II) sulfate heptahydrate</td>
			<td style="width:89px;">Sigma Aldrich</td>
			<td style="width:104px;">C6768</td>
			<td>Growth media</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">Sodium molybdate</td>
			<td style="width:89px;">Sigma Aldrich</td>
			<td style="width:104px;">243655</td>
			<td>Growth media</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">Boric acid</td>
			<td style="width:89px;">Sigma Aldrich</td>
			<td style="width:104px;">B6768</td>
			<td>Growth media</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">Dextrose</td>
			<td style="width:89px;">Sigma Aldrich</td>
			<td style="width:104px;">D9434</td>
			<td>Growth media</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">Luria Bertani Broth</td>
			<td style="width:89px;">Sigma Aldrich</td>
			<td style="width:104px;">L3022</td>
			<td>Growth media</td>
		</tr>
		<tr height="25">
			<td height="25" style="height:25px;width:227px;">TCS SP2 Confocal Microscopy</td>
			<td style="width:89px;">Leica</td>
			<td style="width:104px;"></td>
			<td>Fluorescent imaging</td>
		</tr>
		<tr height="46">
			<td height="46" style="height:47px;width:227px;">SYTO 62</td>
			<td style="width:89px;">Life Technology</td>
			<td style="width:104px;">S11344</td>
			<td>Fluorescent imaging</td>
		</tr>
		<tr height="52">
			<td height="52" style="height:52px;width:227px;">Cy5</td>
			<td style="width:89px;">GE Healthcare Life Sciences</td>
			<td style="width:104px;">PA15100</td>
			<td>Fluorescent imaging</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">Red Fluorescent (580/605) FluoSphere</td>
			<td style="width:89px;">Life Technology</td>
			<td style="width:104px;">F-8801</td>
			<td>Fluorescent imaging</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">BioSPA</td>
			<td style="width:89px;">Packman Lab</td>
			<td style="width:104px;"></td>
			<td>Image Processing</td>
		</tr>
		<tr height="25">
			<td height="25" style="height:25px;width:227px;">ImageJ</td>
			<td style="width:89px;">NIH</td>
			<td style="width:104px;"></td>
			<td>Image Processing</td>
		</tr>
		<tr height="25">
			<td height="25" style="height:25px;width:227px;">Volocity</td>
			<td style="width:89px;">PerkinElmer</td>
			<td style="width:104px;"></td>
			<td>Image Processing</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">Streams 2.02</td>
			<td style="width:89px;">University of Cantebury</td>
			<td style="width:104px;"></td>
			<td>Image Processing</td>
		</tr>
	</tbody>
</table>

methods for characterizing the co-development of biofilm and habitat heterogeneity

Biofilms are surface-attached microbial communities that have complex structures and produce significant spatial heterogeneities. Biofilm development is strongly regulated by the surrounding flow and nutritional environment. Biofilm growth also increases the heterogeneity of the local microenvironment by generating complex flow fields and solute transport patterns. To investigate the development of heterogeneity in biofilms and interactions between biofilms and their local micro-habitat, we grew mono-species biofilms of Pseudomonas aeruginosa and dual-species biofilms of P. aeruginosa and Escherichia coli under nutritional gradients in a microfluidic flow cell. We provide detailed protocols for creating nutrient gradients within the flow cell and for growing and visualizing biofilm development under these conditions. We also present protocols for a series of optical methods to quantify spatial patterns in biofilm structure, flow distributions over biofilms, and mass transport around and within biofilm colonies. These methods support comprehensive investigations of the co-development of biofilm and habitat heterogeneity.

The double-inlet microfluidic flow cell allows observation of biofilm growth under a well-defined chemical gradient formed by mixing of two solutions within the flow chamber. The resulting chemical gradient was formerly observed by dye injection and characterized in detail by Song et al.14. Smooth concentration gradients were formed in the transverse direction, as shown in Figure 1. The concentration profile was steep near the inlet and got relaxed downstream due to diffusion (<strong...

Watch this Scientific Journal Video about Methods for Characterizing the Co-development of Biofilm and Habitat Heterogeneity at JoVE.com

Methods for Characterizing the Co-development of Biofilm and Habitat Heterogeneity

Biofilms have complex interactions with their surrounding environment. To comprehensively investigate biofilm-environment interactions, we present here a series of methods to create heterogeneous chemical environment for biofilm development, to quantify local flow velocity, and to analyze mass transport in and around biofilm colonies.

Biofilms are surface-attached microbial communities that have complex structures and produce significant spatial heterogeneities. Biofilm development is ...

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9.9K Views.  Northwestern University. Biofilms have complex interactions with their surrounding environment. To comprehensively investigate biofilm-environment interactions, we present here a series of methods to create heterogeneous chemical environment for biofilm development, to quantify local flow velocity, and to analyze mass transport in and around biofilm colonies. 

Video: Methods for Characterizing the Co-development of Biofilm and Habitat Heterogeneity

Fluorescence detection methods for microfluidic droplet platforms

The development of microfluidic platforms for performing chemistry and biology has in large part been driven by a range of potential benefits that accompany system miniaturisation. Advantages include the ability to efficiently process nano- to femoto- liter volumes of sample, facile integration of functional components, an intrinsic predisposition towards large-scale multiplexing, enhanced analytical throughput, improved control and reduced instrumental footprints.1
In recent years much interest has focussed on the development of droplet-based (or segmented flow) microfluidic systems and their potential as platforms in high-throughput experimentation.2-4 Here water-in-oil emulsions are made to spontaneously form in microfluidic channels as a result of capillary instabilities between the two immiscible phases. Importantly, microdroplets of precisely defined volumes and compositions can be generated at frequencies of several kHz. Furthermore, by encapsulating reagents of interest within isolated compartments separated by a continuous immiscible phase, both sample cross-talk and dispersion (diffusion- and Taylor-based) can be eliminated, which leads to minimal cross-contamination and the ability to time analytical processes with great accuracy. Additionally, since there is no contact between the contents of the droplets and the channel walls (which are wetted by the continuous phase) absorption and loss of reagents on the channel walls is prevented.
Once droplets of this kind have been generated and processed, it is necessary to extract the required analytical information. In this respect the detection method of choice should be rapid, provide high-sensitivity and low limits of detection, be applicable to a range of molecular species, be non-destructive and be able to be integrated with microfluidic devices in a facile manner. To address this need we have developed a suite of experimental tools and protocols that enable the extraction of large amounts of photophysical information from small-volume environments, and are applicable to the analysis of a wide range of physical, chemical and biological parameters. Herein two examples of these methods are presented and applied to the detection of single cells and the mapping of mixing processes inside picoliter-volume droplets. We report the entire experimental process including microfluidic chip fabrication, the optical setup and the process of droplet generation and detection.

Droplet-based microfluidic platforms are promising candidates for high throughput experimentation since they are able to generate picoliter, self-compartmentalized vessels inexpensively at kHz rates. Through integration with fast, sensitive and high resolution fluorescence spectroscopic methods, the large amounts of information generated within these systems can be efficiently extracted, harnessed and utilized.

The development of microfluidic platforms for performing chemistry and biology has in large part been driven by a range of potential benefits that ...

Candida albicans Biofilm Chip (CaBChip) for High-throughput Antifungal Drug Screening

Candida albicans remains the main etiological agent of candidiasis, which currently represents the fourth most common nosocomial bloodstream infection in US hospitals1. These opportunistic infections pose a growing threat for an increasing number of compromised individuals, and carry unacceptably high mortality rates. This is in part due to the limited arsenal of antifungal drugs, but also to the emergence of resistance against the most commonly used antifungal agents. Further complicating treatment is the fact that a majority of manifestations of candidiasis are associated with the formation of biofilms, and cells within these biofilms show increased levels of resistance to most clinically-used antifungal agents2. Here we describe the development of a high-density microarray that consists of C. albicans nano-biofilms, which we have named CaBChip3. Briefly, a robotic microarrayer is used to print yeast cells of C. albicans onto a solid substrate. During printing, the yeast cells are enclosed in a three dimensional matrix using a volume as low as 50 nL and immobilized on a glass substrate with a suitable coating. After initial printing, the slides are incubated at 37 &deg;C for 24 hours to allow for biofilm development. During this period the spots grow into fully developed "nano-biofilms" that display typical structural and phenotypic characteristics associated with mature C. albicans biofilms (i.e. morphological complexity, three dimensional architecture and drug resistance)4. Overall, the CaBChip is composed of ~750 equivalent and spatially distinct biofilms; with the additional advantage that multiple chips can be printed and processed simultaneously. Cell viability is estimated by measuring the fluorescent intensity of FUN1 metabolic stain using a microarray scanner. This fungal chip is ideally suited for use in true high-throughput screening for antifungal drug discovery. Compared to current standards (i.e. the 96-well microtiter plate model of biofilm formation5), the main advantages of the fungal biofilm chip are automation, miniaturization, savings in amount and cost of reagents and analyses time, as well as the elimination of labor intensive steps. We believe that such chip will significantly speed up the antifungal drug discovery process.

Candida albicans Biofilm Chip CaBChip for High-throughput Antifungal Drug Screening

We have developed a high-density microarray platform consisting of 3D nano-biofilms of C. albicans called CaBChip. The susceptibility profile of drugs tested on a CaBChip is comparable to the conventional 96-well plate model, suggesting that the fungal chip is ideally suited for true high-throughput screening of antifungal drugs.

Candida  albicans remains the main etiological agent of candidiasis, which  currently represents the fourth most common nosocomial bloodstream infection ...

Models and Methods to Evaluate Transport of Drug Delivery Systems Across Cellular Barriers

Sub-micrometer carriers (nanocarriers; NCs) enhance efficacy of drugs by improving solubility, stability, circulation time, targeting, and release. Additionally, traversing cellular barriers in the body is crucial for both oral delivery of therapeutic NCs into the circulation and transport from the blood into tissues, where intervention is needed. NC transport across cellular barriers is achieved by: (i) the paracellular route, via transient disruption of the junctions that interlock adjacent cells, or (ii) the transcellular route, where materials are internalized by endocytosis, transported across the cell body, and secreted at the opposite cell surface (transyctosis). Delivery across cellular barriers can be facilitated by coupling therapeutics or their carriers with targeting agents that bind specifically to cell-surface markers involved in transport. Here, we provide methods to measure the extent and mechanism of NC transport across a model cell barrier, which consists of a monolayer of gastrointestinal (GI) epithelial cells grown on a porous membrane located in a transwell insert. Formation of a permeability barrier is confirmed by measuring transepithelial electrical resistance (TEER), transepithelial transport of a control substance, and immunostaining of tight junctions. As an example, ~200&#160;nm polymer NCs are used, which carry a therapeutic cargo and are coated with an antibody that targets a cell-surface determinant. The antibody or therapeutic cargo is labeled with 125I for radioisotope tracing and labeled NCs are added to the upper chamber over the cell monolayer for varying periods of time. NCs associated to the cells and/or transported to the underlying chamber can be detected. Measurement of free 125I allows subtraction of the degraded fraction. The paracellular route is assessed by determining potential changes caused by NC transport to the barrier parameters described above. Transcellular transport is determined by addressing the effect of modulating endocytosis and transcytosis pathways.

Many therapeutic applications require safe and efficient transport of drug carriers and their cargoes across cellular barriers in the body. This article describes an adaptation of established methods to evaluate the rate and mechanism of transport of drug nanocarriers (NCs) across cellular barriers, such as the gastrointestinal (GI) epithelium.

Sub-micrometer carriers (nanocarriers; NCs) enhance efficacy of drugs by improving solubility, stability, circulation time, targeting, and release. ...

Protocol for Biofilm Streamer Formation in a Microfluidic Device with Micro-pillars

Several bacterial species possess the ability to attach to surfaces and colonize them in the form of thin films called biofilms. Biofilms that grow in porous media are relevant to several industrial and environmental processes such as wastewater treatment and CO2 sequestration. We used Pseudomonas fluorescens, a Gram-negative aerobic bacterium, to investigate biofilm formation in a microfluidic device that mimics porous media. The microfluidic device consists of an array of micro-posts, which were fabricated using soft-lithography. Subsequently, biofilm formation in these devices with flow was investigated and we demonstrate the formation of filamentous biofilms known as streamers in our device. The detailed protocols for fabrication and assembly of microfluidic device are provided here along with the bacterial culture protocols. Detailed procedures for experimentation with the microfluidic device are also presented along with representative results.

Protocols for the study of biofilm formation in a microfluidic device that mimics porous media are discussed. The microfluidic device consists of an array of micro-pillars and biofilm formation by Pseudomonas fluorescens in this device is investigated.

Several bacterial species possess the ability to attach to surfaces and colonize them in the form of thin films called biofilms. Biofilms that grow in ...

Methods for the Self-integration of Megamolecular Biopolymers on the Drying Air-LC Interface

Living organisms that use water are always prone to drying in the environment. Their activities are driven by biopolymer-based micro- and macro-structures, as seen in the cases of moving water in vascular bundles and moisturizing water in skin layers. In this study, we developed a method for assessing the effect of aqueous liquid crystalline (LC) solutions composed of biopolymers on drying. As LC biopolymers have megamolecular weight, we chose to study polysaccharides, cytoskeletal proteins, and DNA. The observation of biopolymer solutions during drying under polarized light reveals milliscale self-integration starting from the unstable air-LC interface. The dynamics of the aqueous LC biopolymer solutions can be monitored by evaporating water from a one-side-open cell. By analyzing the images taken using cross-polarized light, it is possible to recognize the spatio-temporal changes in the orientational order parameter. This method can be useful for the characterization of not only artificial materials in various fields, but also natural living tissues. We believe that it will provide an evaluation method for soft materials in the biomedical and environmental fields.

A method for the drying-induced self-integration of megamolecular biopolymers on the air-liquid crystalline interface is provided here. This methodology will be useful not only for understanding the macroscopic potentials of biopolymers, but also as an evaluation method for soft materials in biomedical and environmental fields.

Living organisms that use water are always prone to drying in the environment. Their activities are driven by biopolymer-based micro- and ...

Characterizing Cell Migration Within Three-dimensional In Vitro Wound Environments

Currently, most in vitro models of wound healing, such as well-established scratch assays, involve studying cell migration and wound closure on two-dimensional surfaces. However, the physiological environment in which in vivo wound healing takes place is three-dimensional rather than two-dimensional. It is becoming increasingly clear that cell behavior differs greatly in two-dimensional vs. three-dimensional environments; therefore, there is a need for more physiologically relevant in vitro models for studying cell migration behaviors in wound closure. The method described herein allows for the study of cell migration in a three-dimensional model that better reflects physiological conditions than previously established two-dimensional scratch assays. The purpose of this model is to evaluate cell outgrowth via the examination of cell migration away from a spheroid body embedded within a fibrin matrix in the presence of pro- or anti-migratory factors. Using this method, cell outgrowth from the spheroid body in a three-dimensional matrix can be observed and is easily quantifiable over time via brightfield microscopy and analysis of spheroid body area. The effect of pro-migratory and/or inhibitory factors on cell migration can also be evaluated in this system. This method provides researchers with a simple method of analyzing cell migration in three-dimensional wound associated matrices in vitro, thus increasing the relevance of in vitro cell studies prior to the use of in vivo animal models.

Characterizing Cell Migration Within Three-dimensional In Vitro Wound Environments

The goal of this protocol is to evaluate the effect of pro- and anti-migratory factors on cell migration within a three-dimensional fibrin matrix.

Currently, most in vitro models of wound healing, such as well-established scratch assays, involve studying cell migration and wound closure on ...

Two Methods for Decellularization of Plant Tissues for Tissue Engineering Applications

The autologous, synthetic, and animal-derived grafts currently used as scaffolds for tissue replacement have limitations due to low availability, poor biocompatibility, and cost. Plant tissues have favorable characteristics that make them uniquely suited for use as scaffolds, such as high surface area, excellent water transport and retention, interconnected porosity, preexisting vascular networks, and a wide range of mechanical properties. Two successful methods of plant decellularization for tissue engineering applications are described here. The first method is based on detergent baths to remove cellular matter, which is similar to previously established methods used to clear mammalian tissues. The second is a detergent-free method adapted from a protocol that isolates leaf vasculature and involves the use of a heated bleach and salt bath to clear the leaves and stems. Both methods yield scaffolds with comparable mechanical properties and low cellular metabolic impact, thus allowing the user to select the protocol which better suits their intended application.

Here we present, and contrast two protocols used to decellularize plant tissues: a detergent-based approach and a detergent-free approach. Both methods leave behind the extracellular matrix of the plant tissues used, which can then be utilized as scaffolds for tissue engineering applications.

The autologous, synthetic, and animal-derived grafts currently used as scaffolds for tissue replacement have limitations due to low availability, poor ...

Comprehensive Evaluation of the Effectiveness and Safety of Placenta-Targeted Drug Delivery Using Three Complementary Methods

No effective treatments currently exist for placenta-associated pregnancy complications, and developing strategies for the targeted delivery of drugs to the placenta while minimizing fetal and maternal side effects remains challenging. Targeted nanoparticle carriers provide new opportunities to treat placental disorders. We recently demonstrated that a synthetic placental chondroitin sulfate A binding peptide (plCSA-BP) could be used to guide nanoparticles to deliver drugs to the placenta. In this protocol, we describe in detail a system for assessing the efficiency of drug delivery to the placenta by plCSA-BP that employs three separate methods used in combination: in vivo imaging, high-frequency ultrasound (HFUS), and high-performance liquid chromatography (HPLC). Using in vivo imaging, plCSA-BP-guided nanoparticles were visualized in the placentas of live animals, while HFUS and HPLC demonstrated that plCSA-BP-conjugated nanoparticles efficiently and specifically delivered methotrexate to the placenta. Thus, a combination of these methods can be used as an effective tool for the targeted delivery of drugs to the placenta and development of new treatment strategies for several pregnancy complications.

We describe a system that utilizes three methods to evaluate the safety and effectiveness of placenta-targeted drug delivery: in vivo imaging to monitor nanoparticle accumulation, high-frequency ultrasound to monitor placental and fetal development, and HPLC to quantify drug delivery to tissue.

No effective treatments currently exist for placenta-associated pregnancy complications, and developing strategies for the targeted delivery of drugs to ...

Electric and Magnetic Field Devices for Stimulation of Biological Tissues

Electric fields (EFs) and magnetic fields (MFs) have been widely used by tissue engineering to improve cell dynamics such as proliferation, migration, differentiation, morphology, and molecular synthesis. However, variables such stimuli strength and stimulation times need to be considered when stimulating either cells, tissues or scaffolds. Given that EFs and MFs vary according to cellular response, it remains unclear how to build devices that generate adequate biophysical stimuli to stimulate biological samples. In fact, there is a lack of evidence regarding the calculation and distribution when biophysical stimuli are applied. This protocol is focused on the design and manufacture of devices to generate EFs and MFs and implementation of a computational methodology to predict biophysical stimuli distribution inside and outside of biological samples. The EF device was composed of two parallel stainless-steel electrodes located at the top and bottom of biological cultures. Electrodes were connected to an oscillator to generate voltages (50, 100, 150 and 200 Vp-p) at 60 kHz. The MF device was composed of a coil, which was energized with a transformer to generate a current (1 A) and voltage (6 V) at 60 Hz. A polymethyl methacrylate support was built to locate the biological cultures in the middle of the coil. The computational simulation elucidated the homogeneous distribution of EFs and MFs inside and outside of biological tissues. This computational model is a promising tool that can modify parameters such as voltages, frequencies, tissue morphologies, well plate types, electrodes and coil size to estimate the EFs and MFs to achieve a cellular response.

This protocol describes the step-by-step process to build both electrical and magnetic stimulators used to stimulate biological tissues. The protocol includes a guideline to simulate computationally electric and magnetic fields and manufacture of stimulator devices.

Electric fields (EFs) and magnetic fields (MFs) have been widely used by tissue engineering to improve cell dynamics such as proliferation, migration, ...

Formulating and Characterizing Lipid Nanoparticles for Gene Delivery using a Microfluidic Mixing Platform

Lipid-based drug carriers have been used for clinically and commercially available delivery systems due to their small size, biocompatibility, and high encapsulation efficiency. Use of lipid nanoparticles (LNPs) to encapsulate nucleic acids is advantageous to protect the RNA or DNA from degradation, while also promoting cellular uptake. LNPs often contain multiple lipid components including an ionizable lipid, helper lipid, cholesterol, and polyethylene glycol (PEG) conjugated lipid. LNPs can readily encapsulate nucleic acids due to the ionizable lipid presence, which at low pH is cationic and allows for complexation with negatively charged RNA or DNA. Here LNPs are formed by encapsulating messenger RNA (mRNA) or plasmid DNA (pDNA) using rapid mixing of the lipid components in an organic phase and the nucleic acid component in an aqueous phase. This mixing is performed using a precise microfluidic mixing platform, allowing for nanoparticle self-assembly while maintaining laminar flow. The hydrodynamic size and polydispersity are measured using dynamic light scattering (DLS). The effective surface charge on the LNP is determined by measuring the zeta potential. The encapsulation efficiency is characterized using a fluorescent dye to quantify entrapped nucleic acid. Representative results demonstrate the reproducibility of this method and the influence that different formulation and process parameters have on the developed LNPs.

Lipid nanoparticles are developed using a microfluidic mixing platform approach for mRNA and DNA encapsulation.

Lipid-based drug carriers have been used for clinically and commercially available delivery systems due to their small size, biocompatibility, and high ...