Name: combining fluidic devices with microscopy and flow cytometry to study microbial transport in porous media across spatial scales
Uploaded: 2020-11-25T14:00:00
Description: Watch this Scientific Journal Video about Combining Fluidic Devices with Microscopy and Flow Cytometry to Study Microbial Transport in Porous Media Across Spatial Scales at JoVE.com

We acknowledge the help of Antoine Wiedmer with the setup of the robotic dispenser and the dispenser.py script.

1. Bacterial culture conditions
<ol>
	<li>Working under a laminar flow hood, use 100 &#956;L of a glycerol stock of GFP-tagged Pseudomonas putida KT2440 (1 &#215; 107 mL-1, stored at -80 &#176;C) to inoculate 5 mL of Luria-Bertani (LB) medium. Incubate at 30 &#176;C while shaking at 250 rpm overnight.</li>
	<li>The next day, resuspend 100 &#956;L of the overnight culture in 5 mL LB medium and incubate under the same conditions for 5h (exponential phase). Sample a 1 mL aliquot into a 2 mL ...

<ol>
	<li>Stevik, K., Aa, K., Ausland, G., Fredrik Hanssen, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Retention+and+removal+of+pathogenic+bacteria+in+wastewater+percolating+through+porous+media:+a+review.">Retention and removal of pathogenic bacteria in wastewater percolating through porous media: a review.</a> Water Research. 38 (6), 1355-1367 (2004).</li><li>Ribet, D., Cossart, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=How+bacterial+pathogens+colonize+their+hosts+and+invade+deeper+tissues.">How bacterial pathogens colonize their hosts and invade deeper tissues.</a> Microbes and Infection. 17 (3), 173-183 (2015).</li><li>Ginn, T. R., Wood, B. D., Nelson, K. E., Scheibe, T. D., Murphy, E. M., Clement, T. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Processes+in+microbial+transport+in+the+natural+subsurface.">Processes in microbial transport in the natural subsurface.</a> Advances in Water Resources. 25 (8), 1017-1042 (2002).</li><li>Tufenkji, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Modeling+microbial+transport+in+porous+media:+Traditional+approaches+and+recent+developments.">Modeling microbial transport in porous media: Traditional approaches and recent developments.</a> Advances in Water Resources. 30 (6-7), 1455-1469 (2007).</li><li>Foppen, J. W., Van, M. H., Schijven, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measuring+and+modelling+straining+of+Escherichia+coli+in+saturated+porous+media.">Measuring and modelling straining of Escherichia coli in saturated porous media.</a> Journal of contaminant hydrology. 93 (1-4), 236-254 (2007).</li><li>Battin, T. J., Besemer, K., Bengtsson, M. M., Romani, A. M., Packmann, A. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+ecology+and+biogeochemistry+of+stream+biofilms.">The ecology and biogeochemistry of stream biofilms.</a> Nature Reviews Microbiology. 14 (4), 251-263 (2016).</li><li>Scheidweiler, D., Peter, H., Pramateftaki, P., Anna, P., de Battin, T. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Unraveling+the+biophysical+underpinnings+to+the+success+of+multispecies+biofilms+in+porous+environments.">Unraveling the biophysical underpinnings to the success of multispecies biofilms in porous environments.</a> The ISME Journal. 1, (2019).</li><li>Carrel, 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=Biofilms+in+3D+porous+media:+Delineating+the+influence+of+the+pore+network+geometry,+flow+and+mass+transfer+on+biofilm+development.">Biofilms in 3D porous media: Delineating the influence of the pore network geometry, flow and mass transfer on biofilm development.</a> Water Research. 134, 280-291 (2018).</li><li>Bhattacharjee, T., Datta, S. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bacterial+hopping+and+trapping+in+porous+media.">Bacterial hopping and trapping in porous media.</a> Nature Communications. 10 (1), 2075 (2019).</li><li>Scheidweiler, D., Miele, F., Peter, H., Battin, T. J., de Anna, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Trait-specific+dispersal+of+bacteria+in+heterogeneous+porous+environments:+from+pore+to+porous+medium+scale.">Trait-specific dispersal of bacteria in heterogeneous porous environments: from pore to porous medium scale.</a> Journal of The Royal Society Interface. 17 (164), 20200046 (2020).</li><li>Morales, V. L., Parlange, J. Y., Steenhuis, T. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Are+preferential+flow+paths+perpetuated+by+microbial+activity+in+the+soil+matrix?+A+review.">Are preferential flow paths perpetuated by microbial activity in the soil matrix? A review.</a> Journal of Hydrology. 393 (1), 29-36 (2010).</li><li>Creppy, A., Cl&#233;ment, E., Douarche, C., D'Angelo, M. V., Auradou, H. <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+motility+on+the+transport+of+bacteria+populations+through+a+porous+medium.">Effect of motility on the transport of bacteria populations through a porous medium.</a> Physical Review Fluids. 4 (1), 013102 (2019).</li><li>Camesano, T. A., Logan, B. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Influence+of+Fluid+Velocity+and+Cell+Concentration+on+the+Transport+of+Motile+and+Nonmotile+Bacteria+in+Porous+Media.">Influence of Fluid Velocity and Cell Concentration on the Transport of Motile and Nonmotile Bacteria in Porous Media.</a> Environmental Science &amp; Technology. 32 (11), 1699-1708 (1998).</li><li>Lutterodt, G., Basnet, M., Foppen, J. W. A., Uhlenbrook, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+effect+of+surface+characteristics+on+the+transport+of+multiple+Escherichia+coli+isolates+in+large+scale+columns+of+quartz+sand.">The effect of surface characteristics on the transport of multiple Escherichia coli isolates in large scale columns of quartz sand.</a> Water Research. 43 (3), 595-604 (2009).</li><li>Bozorg, A., Gates, I. D., Sen, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Impact+of+biofilm+on+bacterial+transport+and+deposition+in+porous+media.">Impact of biofilm on bacterial transport and deposition in porous media.</a> Journal of Contaminant Hydrology. 183 (Supplement C), 109-120 (2015).</li><li>Long, T., Ford, R. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Enhanced+Transverse+Migration+of+Bacteria+by+Chemotaxis+in+a+Porous+T-Sensor.">Enhanced Transverse Migration of Bacteria by Chemotaxis in a Porous T-Sensor.</a> Environmental Science &amp; Technology. 43 (5), 1546-1552 (2009).</li><li>Rusconi, R., Garren, M., Stocker, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microfluidics+Expanding+the+Frontiers+of+Microbial+Ecology.">Microfluidics Expanding the Frontiers of Microbial Ecology.</a> Annual Review of Biophysics. 43 (1), 65-91 (2014).</li><li>Xia, Y., Whitesides, G. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Soft+Lithography.">Soft Lithography.</a> Annual Review of Materials Science. 28 (1), 153-184 (1998).</li><li>Crocker, J. C., Grier, D. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Methods+of+Digital+Video+Microscopy+for+Colloidal+Studies.">Methods of Digital Video Microscopy for Colloidal Studies.</a> Journal of Colloid and Interface Science. 179 (1), 298-310 (1996).</li><li>del Giorgio, P. A., Bird, D. F., Prairie, Y. T., Planas, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Flow+cytometric+determination+of+bacterial+abundance+in+lake+plankton+with+the+green+nucleic+acid+stain+SYTO+13.">Flow cytometric determination of bacterial abundance in lake plankton with the green nucleic acid stain SYTO 13.</a> Limnology and Oceanography. 41 (4), 783-789 (1996).</li></ol>

Here we suggest two means to study the transport of microbes through porous systems at the single-cell and population level. While the study of transport phenomena using BTC modeling has provided valuable insights into the spread of pathogens or contaminants at the ecosystem scales, difficulties to scale from laboratory experiments to field conditions still exist. The tools described here allow researchers to experimentally resolve the spatial and temporal scales in order to better understand the ecological strategies of...

Studies aiming to understand the transport of microbes through porous media have mainly been driven by concerns of contamination1, the transmission of disease2 and bioremediation3. In this regard, bacteria have mostly been treated as particles in transport models4 and processes such as filtration, straining, gravitational settling or remobilization from biofilms have been identified as drivers of retention or transport of microbes5. However, studying the transport of bacteria through porous landscapes can also inform us on the ecological strategies underpinning their success in these complex environments. Yet, this requires novel experiments and mathematical models operating at the single cell, population or microbial community level.
Natural porous environments, such as those found in the hyporheic zone of streams and rivers, are densely colonized by diverse communities of biofilm-forming microbes6. Biofilms form structures that modify the flow and thus the transport and dispersal of bacteria in the liquid phase7,8. The transport of bacteria at pore scale depends to the constrained space availability in the porous matrix and motility-related dispersal may be an effective way to increase the individual fitness through reduced competition for resources in less densely populated areas. On the other hand, motile bacteria can also reach more isolated regions of the porous matrix and the extended exploration of such areas may provide ecological opportunities to motile populations10. At larger spatial scales, biofilm growth diverts the flow paths also leading to (partial) clogging of pores and, thus, to the establishment of even more channelized and heterogeneous flow conditions11. This has consequences for nutrient supply and dispersal capacity, frequency and distance. Preferential flow, for instance, can generate so-called &#34;fast-tracks&#34; and motile bacteria can attain even higher velocities than the local flow along these tracks12. This is an effective way to increase the exploration of novel habitats.
A variety of tools avail themselves for the study of transport of motile and non-motile bacteria (and particles) in porous media. Numerical models have great predictive capacities important for applications, however are often limited by inherent assumptions4. Laboratory-scale experiments13, 14 combined with breakthrough curve (BTC) modeling have provided important insights in the importance of bacterial cell surface properties for sticking efficiency15. Typically, BTCs (i.e., times series of particle concentration at a fixed location) are obtained via constant-rate releases and measurement of cell numbers at the outflow of the experimental device. In this context, BTCs reflect the advection-dispersion dynamics of bacteria in the porous matrix and can be extended by a sink term accounting for attachment. However, modeling of BTCs alone does not resolve the role of spatial organization of the porous substrate or biofilm for transport processes. Other macroscopic observables like dispersivity or deposition profiles have been proven to provide important information about the spatial distribution or the retained particles or growing communities. Microfluidics is a technology that allows studying transport in porous media by microscopy investigation9,12,16, and except a recent work10, experimental systems are typically constrained to a single length scale of resolution, that is, the pore scale or the entire fluidic device scale.
Here, we introduce a suite of combined methods to study the transport of motile and non-motile bacteria in porous landscapes at different scales. We combine observations of bacterial transport at the pore scale with information at larger scale, by means of BTC analysis. Microfluidic devices built from soft lithography using polydimethylsiloxane (PDMS) are bio-compatible, resistant to a range of chemicals, allow replicability at low costs and provide excellent optical transparency as well as low autofluorescence critical for microscopic observation. Microfluidics based on PDMS has been previously used to study the transport of microbes in simple channels17 or in more complex geometries12. However, typically microfluidics experiments focus on short-term horizons and epi-fluorescence microscopic observation of living cells is commonly restricted to genetically-modified strains (e.g., GFP-tagged strains). Here we present tools to study bacterial transport using PDMS-based microfluidic devices in combination with microscopy and larger devices fabricated from poly(methyl methacrylate) (PMMA, also known as plexiglass) in combination with flow cytometry. PDMS and PMMA differ in gas permeability and surface properties, thus providing complementary opportunities to study bacterial transport. While the microfluidic device provides a more controlled environment, the larger device allows for experiments over extended periods of time or using natural bacterial communities. Microscopy counting at high temporal resolution in a dedicated area is used to obtain BTC in the PDMS-based microfluidic device. To obtain cell counts for BTC modeling from the PMMA-based device, we introduce a self-constructed automated liquid dispenser in combination with flow cytometry. In this setup, cells pass the fluidic device and are consecutively dispensed into 96 well plates. The temporal resolution is restricted by the minimum volume that can be accurately dispensed and thus the medium flow rate through the fluidic device. Fixative in the wells prevents growth and facilitates DNA staining for downstream flow-cytometric enumeration. To prevent bacterial growth during transport experiments we use a minimal medium (termed motility buffer).
Since protocols for the preparation of fluidic devices at different scales are readily available, we only briefly introduce the techniques to produce such devices and rather focus on the experimental procedures to record BTCs. Similarly, various routines exist for the flow cytometric enumeration of microbes and users require expert knowledge to interpret results obtained by flow cytometry. We report the novel use of microfluidic devices in combination with microscopic imaging to record BTCs of fluorescently-tagged cells. At the pore scale, local velocities and trajectories are obtained by means of image processing. Further, we demonstrate the use of a PMMA-based fluidic device in combination with flow-cytometric counting to observe bacterial transport of motile and non-motile cells in porous environments colonized by a native stream biofilm.

<table>
	<tbody>
		<tr>
			<td>EDTA</td>
			<td>Sigma</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Elastomer Sylgard 184</td>
			<td>Dowsil</td>
			<td>101697</td>
			<td></td>
		</tr>
		<tr>
			<td>Flow cytometer NovoCyte</td>
			<td>Acea</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Glucose</td>
			<td>Sigma</td>
			<td></td>
			<td>https://www.makeblock.com/project/xy-plotter-robot-kit</td>
		</tr>
		<tr>
			<td>LB broth</td>
			<td>BD</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Liquid dispenser, XY Plotter Robot Kit</td>
			<td>makeblock</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Microscope Axio Imager</td>
			<td>Zeiss</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Microscope AxioZoom v16</td>
			<td>Zeiss</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Microscope slides, 75 mm &#215; 25 mm</td>
			<td>Corning</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Minipuls 3 peristaltic pump</td>
			<td>Gilson</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Plasma bonder Corona SB</td>
			<td>BlackHole Lab</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Potassium phosphate</td>
			<td>Sigma</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Syringe pump New Era NE 4000</td>
			<td>New Era</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Syto 13 Green Fluorescent Nucleic Acid Stain</td>
			<td>Molecular Probes, Invitrogen</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Tygon tubing</td>
			<td>Ismatec</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>WF31SA universal milling machine</td>
			<td>Mikron</td>
			<td></td>
			<td></td>
		</tr>
	</tbody>
</table>

combining fluidic devices with microscopy and flow cytometry to study microbial transport in porous media across spatial scales

Understanding the transport, dispersion and deposition of microorganisms in porous media is a complex scientific task comprising topics as diverse as hydrodynamics, ecology and environmental engineering. Modeling bacterial transport in porous environments at different spatial scales is critical to better predict the consequences of bacterial transport, yet current models often fail to up-scale from laboratory to field conditions. Here, we introduce experimental tools to study bacterial transport in porous media at two spatial scales. The aim of these tools is to obtain macroscopic observables (such as breakthrough curves or deposition profiles) of bacteria injected into transparent porous matrices. At the small scale (10-1000 &#181;m), microfluidic devices are combined with optical video-microscopy and image processing to obtain breakthrough curves and, at the same time, to track individual bacterial cells at the pore scale. At larger scale, flow cytometry is combined with a self-made robotic dispenser to obtain breakthrough curves. We illustrate the utility of these tools to better understand how bacteria are transported in complex porous media such as the hyporheic zone of streams. As these tools provide simultaneous measurements across scales, they pave the way for mechanism-based models, critically important for upscaling. Application of these tools may not only contribute to the development of novel bioremediation applications but also shed new light on the ecological strategies of microorganisms colonizing porous substrates.

To illustrate the functionality of the presented workflow, we performed experiments using genetically modified Pseudomonas putida KT2440, a gram negative motile bacterium important for bioremediation and biotechnology. Genetically modified versions of this strain that express GFP production are commercially available. A non-motile strain of P. putida KT2440 which lacks the relevant structural and regulatory genes for motility is also available. Using both, motile and non...

Watch this Scientific Journal Video about Combining Fluidic Devices with Microscopy and Flow Cytometry to Study Microbial Transport in Porous Media Across Spatial Scales at JoVE.com

Combining Fluidic Devices with Microscopy and Flow Cytometry to Study Microbial Transport in Porous Media Across Spatial Scales

Breakthrough curves (BTCs) are efficient tools to study the transport of bacteria in porous media. Here we introduce tools based on fluidic devices in combination with microscopy and flow cytometric counting to obtain BTCs.

Understanding the transport, dispersion and deposition of microorganisms in porous media is a complex scientific task comprising topics as diverse as ...

Studying the transport of bacteria in porous systems is important with regards to contamination, spread of disease, and bioremediation. For these experiments in mathematical models operating at the single cell, the population and the microbial community level are required. Here we present tools to study bacterial transport using microfluidic devices and microscopy, as well as larger devices in combination with flow cytometry.The combination of microfluidic devices with microscopy and flow cytometry offers a range of possibilities to study bacterial transport phenomena at different spatial scales. In order to fully explore this protocol, it is suggested to have previous experience in microscopy, basic image processing, designing microfluidic devices, and mastering flow cytometry. This video describes two methods to study bacterial transport at different spatial scales.The first method, based on microfluidic devices, relies on microscopy to count individual cells. This system can be used to study bacterial transport across multiple spatial scales from the pore to the entire porous system scale. The second method, using larger fluidic devices coupled to an automated dispenser and flow cytometry, can be used to study bacterial transport phenomenon at the scale of entire porous systems.Such methods can also be deployed in laboratory-scale column studies, as well as small field surveys. To begin, design the desired porous geometry that consists of a matrix of circles. Based on the chosen geometry, prepare a mold using standard SU-8 photolithography.Prepare 50 grams of PDMS by adding 90%of elastomer to 10%of curing agent to 90%of elastomer by weight in a clean disposable container and mix the two reagents with a clean tool. Apply a vacuum of 100 millibar for 30 minutes to remove dissolved air and bubbles. Place the mold into a Petri dish and pour the PDMS onto the mold to the desired height between two and five millimeters.Cover the Petri dish with a lid and keep it at 60 degrees Celsius for at least four hours. After that, allow the microfluidic device to cool to room temperature. Once it is cooled, carefully remove the desired portion of PDMS with a scalpel.Temporarily seal the bottom of the PDMS channel with tape. With a 0.5 millimeter diameter puncher, pierce channels to create an inlet and an outlet. Remove the tape from the PDMS channel and place the channel with the porous side facing up.Treat the glass slide and PDMS surfaces with plasma for about 45 seconds each at room temperature. Place the pretreated PDMS channel onto the pretreated glass slide and heat at 100 degrees Celsius for 30 minutes on a hot plate, then remove the microfluidic device from the hot plate and cool it to room temperature. Apply vacuum for 30 minutes to remove air from PDMS.To produce the base containing the pore compartment, use high-precision micro milling to remove 0.5 millimeters from the base PMMA layer and mill a groove at the size of 1.1 by 1.1 millimeters for a rubber O-ring. Drill two threaded holes for an inlet and outlet into the top part of the fluidic device and 12 holes for screws. This serves as the lid of the fluidic device.After cleaning the fluidic device, screw the base and lid together using the 12 threaded holes. Remove the microfluidic from vacuum and place it on the microscope stage. Use the syringe pump to saturate it with motility buffer.Using Brightfield microscopy or phase contrast, adjust the magnification to visualize individual bacterial cells and focus on the center of the observation channel. Switch the light path settings to fluorescence microscopy. Adjust focus through an offset and the camera exposure time to resolve individual bacterial cells.In this case, 100 milliseconds. Next, insert the inlet tubing into a two milliliter tube containing the bacterial suspension. Reverse the pump direction and start withdrawing the suspension at a flow rate of one microliter per minute.Scan the cross-section of the entire observation channel, recording an image every minute. Import images to a desired software platform. Record the background as the average of the first images when no particles have been recorded.Subtract the background from each image to remove camera noise and optical aberration. Crop the images to a region of interest. Identify a threshold value equal to the cell fluorescence pixel intensity so that values greater than the threshold include bacterial cells.Use image processing to subtract the threshold value from each picture. Binarize the resulting image so that bacterial cells take a value of one, whereas the background takes a value of zero. Remove clusters of pixel with an area smaller than the smallest bacterial cell size in pixels.Sum the binarized image to obtain the total number of pixels of the remaining clusters. Divide the number of pixels by the average size of a bacterial cell in pixels to obtain an estimate of the number of cells. Transform the counts into concentration in particles per milliliter.To identify the concentration of the injected bacterial suspension, inject the bacterial suspension into the observation channel of a clean microfluidic device with a syringe. Record the image and calculate the influent bacterial concentration as previously shown. Visualize breakthrough curves by normalizing the effluent bacterial concentration C with the influent bacterial concentration C0 and plotting C over C0 versus time.In order to analyze the local velocities and trajectories of bacteria transported through the porous matrix, move the microscope stage to a region of interest and adjust the focus to the center of the microfluidic device. Set the optical configuration to phase contrast or fluorescence microscopy. Record time-lapse images and an exposure time short enough to capture bacterial displacement.In this case, 50 milliseconds. Record pictures over a sufficient amount of time, for example three minutes. To remove noise from each image, subtract the background, which is the average of the sum of all recorded images.Determine the modulus of the numerical gradient and normalize it by its maximum value. Find and record bacterial coordinates and the time of image acquisition into a three-column file. Perform particle tracking analysis to process the recorded data and compute the trajectories.To obtain deposition profiles, record a composite image of the entire porous channel before, that is the background, and after injection of the bacterial suspension through the microfluidic device. Remove background from the images recorded after bacterial injection. Compute the deposition profile D as the sum of the bacterial fluorescence signal along transversal sections of length x of the porous channel.Visualize the deposition profile as the local fluorescence signal versus the porous channel length. To set up the automated dispenser, place the robotic dispenser close to the fluidic device. Connect the robotic dispenser to the computer running BCNC and identify the correct com port.In BCNC, click the home button to return the robotic dispenser to the home position. Connect the peristaltic pump with the inlet using 50 centimeter long, one millimeter inner diameter tubing, and the outflow with the automated dispenser using the same tubing. Pump cultivation medium through the fluidic device.Note the arrival of medium at the outlet tubing fixed to the robotic dispenser and place a 96-well plate which will collect the outflow. At the same time, activate the robotic dispenser and inject the bacterial suspension through the PMMA fluidic device at a flow rate of 0.2 milliliters per minute. Inject bacterial suspension equivalent to several pore volumes.For example, 30 times the volume of the fluidic device. After injection, switch to sterile cultivation medium until the end of the experiment. Once a 96-well plate is completed, cover the plate and store at four degrees Celsius until flow cytometry analysis.Analyze samples with flow cytometry and visualize breakthrough curves by normalizing the effluent bacterial concentration C with the influent bacterial concentration C0 and plotting C over C0 versus time. In this study, using both motile and non-motile Pseudomonas putida KT2440, sequential experiments were performed in PDMS microfluidic devices with a random array of pillars. Breakthrough curves normalized to the concentration of injected cells, as well as bacterial trajectories at the pore scale are shown here.Experiments with large-scale fluidic devices milled from PMMA were also performed. Motile and non-motile Pseudomonas putida KT2440 were injected into a regularly spaced porous matrix. Strikingly, in a porous environment devoid of biofilm, motile and non-motile Pseudomonas putida KT2440 showed a markedly different transport behavior based on breakthrough curves.In a porous matrix colonized for 48 hours with a complex stream biofilm community, these differences in breakthrough curves between motile and non-motile Pseudomonas putida KT2440 vanished. We use this system to study bacterial transport in the streams, but these tools can be readily adjusted to study bacterial transport phenomena in other engineered and environmental systems. Bacterial transport through hydrated porous media encapsulate processes over multiple spatial scales.The methodology here presented allows linking the local displacement of bacteria at the pore scale to the microscopic transport at the entire porous medium.

Research

JoVE Journal

Environment

Preparation and Testing of Impedance-based Fluidic Biochips with RTgill-W1 Cells for Rapid Evaluation of Drinking Water Samples for Toxicity

This manuscript describes how to prepare fluidic biochips with Rainbow trout gill epithelial (RTgill-W1) cells for use in a field portable water toxicity ...

Extraction and Analysis of Microbial Phospholipid Fatty Acids in Soils

Phospholipid fatty acids (PLFAs) are key components of microbial cell membranes. The analysis of PLFAs extracted from soils can provide information about ...

Implementation of Portable Emissions Measurement Systems (PEMS) for the Real-driving Emissions (RDE) Regulation in Europe

Implementation of Portable Emissions Measurement Systems PEMS for the Real-driving Emissions RDE Regulation in Europe

Vehicles are tested in controlled and relatively narrow laboratory conditions to determine their official emission values and reference fuel consumption. ...

Using Pharmacological Manipulation and High-precision Radio Telemetry to Study the Spatial Cognition in Free-ranging Animals

An animal&#39;s ability to perceive and learn about its environment plays a key role in many behavioral processes, including navigation, migration, ...

Dispersion of Nanomaterials in Aqueous Media: Towards Protocol Optimization

The sonication process is commonly used for de-agglomerating and dispersing nanomaterials in aqueous based media, necessary to improve homogeneity and ...

Microfluidic Devices for Characterizing Pore-scale Event Processes in Porous Media for Oil Recovery Applications

Microfluidic devices are versatile tools for studying transport processes at a microscopic scale. A demand exists for microfluidic devices that are ...

Characterization of Aquatic Biofilms with Flow Cytometry

Biofilms are dynamic consortia of microorganism that play a key role in freshwater ecosystems. By changing their community structure, biofilms respond ...

Metal Corrosion and the Efficiency of Corrosion Inhibitors in Less Conductive Media

Material corrosion can be a limiting factor for different materials in many applications. Thus, it is necessary to better understand corrosion processes, ...

Isolation and Analysis of Microbial Communities in Soil, Rhizosphere, and Roots in Perennial Grass Experiments

Plant and soil microbiome studies are becoming increasingly important for understanding the roles microorganisms play in agricultural productivity. The ...

Characterizing Microbiome Dynamics &#8211; Flow Cytometry Based Workflows from Pure Cultures to Natural Communities

Characterizing Microbiome Dynamics ÃƒÆ’Ã‚Â¢ÃƒÂ¢Ã¢â‚¬Å¡Ã‚Â¬ÃƒÂ¢Ã¢â€šÂ¬Ã…â€œ Flow Cytometry Based Workflows from Pure Cultures to Natural Communities

The investigation of pure cultures and monitoring of microbial community dynamics is vital to understand and control natural ecosystems and technical ...