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

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.