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 tube, allow to cool to room temperature (~15 min) and centrifuge (2300 x g for 5 min).</li>
	<li>Remove the supernatant and add 1 mL motility buffer to the pellet. Vortex briefly to homogenize the sample. Dilute to reach the desired cell concentration, e.g., 5 x 105 mL-1.</li>
	<li>For experiments involving natural communities, such as those derived from streams, prepare a non-selective cultivation medium. For instance, use sterile-filtered and autoclaved stream water or an artificial stream water medium amended with a complex carbon source (LB medium).</li>
</ol>
2. Preparation of a microfluidic device in polydimethylsiloxane (PDMS)
<ol>
	<li>Design the desired porous geometry by means of computer-aided drafting (CAD) software18, which consists of a matrix of circles (that is the impermeable obstacle to flow), described by radius size and center coordinates. 
	NOTE: An example of a porous geometry with randomized grain and pore sizes is provided in Figure 1A. An observation channel without obstacles close to the outlet facilitates the acquisition of BTCs.</li>
	<li>Based on the chosen geometry, prepare a mold using standard SU-8-photolithography18. 
	NOTE: Alternatively, molds can also be ordered from dedicated microfabrication facility. In order to obtain heterogeneous fluid flow in the horizontal plane, it is important to design the thickness of the microfluidics chamber of the same order of magnitude as the average pore throat size. However, make sure that the dimensions of the microfluidic device are suitable for observation under the microscope (e.g., work on microscope slides).</li>
	<li>Prepare 50 g of PDMS by adding 10% of cross linker (dimethyl, methylhydrogen siloxane copolymer) to 90% of elastomer by weight, using a syringe without needle. Work under clean conditions and avoid dust as much as possible. Mix the two reagents in a clean disposable container and apply vacuum (100 mbar) for 30 min to remove dissolved air and bubbles from the viscous PDMS.</li>
	<li>Place the mold into a Petri dish (100 mm in diameter, 15 mm high). Pour the PDMS onto the mold to the desired height (e.g., 2-5 mm). Cover the petri dish and keep it at 60 &#176;C for 4 h (overnight for thicker layers) to cure. 
	NOTE: For visualization purpose, light should be able to pass through the PDMS, thus, a thin layer between 2 mm to 5 mm is desirable. Thicker layers (&#62;5 mm) reduce the device transparency and thinner ones are subjected to deformations during application.</li>
	<li>Remove the mold from the oven and allow the microfluidic device to cool to room temperature. Once it is cooled, carefully remove the desired portion of PDMS with a scalpel. 
	NOTE: Strong pressures on the mold result in mold fractures. Do not touch the PDMS with bare hands, as fingerprints will affect optical transparency.</li>
	<li>Temporarily seal the bottom of the PDMS channel (where the desired geometry has been engraved) with tape. With a 0.5 mm diameter biopsy puncher, pierce microfluidic channel to create an inlet and an outlet fitting the 0.5 mm (inner diameter) tubing. 
	NOTE: The soft nature of PDMS will ensure tightness once the tubing will be inserted. Inlet and outlet channels cannot be made after the PDMS has been sealed to the glass.</li>
	<li>Seal the microfluidic channel via oxygen plasma bonding using the high frequency generator (plasma bonder, Table of Materials). For this, clean a silicate glass slide (25 mm x 75 mm) with ethanol and let it dry. Remove tape from the PDMS channel and place the channel with the porous side facing up. Treat the silicate glass slide and PDMS surfaces with plasma for about 45 s at room temperature.</li>
	<li>Place the PDMS channel onto the silicate glass slide and heat at 100 &#176;C for 30 min on a hot plate.</li>
	<li>Remove the microfluidic device from the hot plate and cool it to room temperature. Connect the PDMS channel inlet with tubing. Apply vacuum for 30 min to remove air from PDMS, which is almost impermeable to fluids but permeable to gas.</li>
	<li>Prepare 100 mL of motility buffer (10 mM potassium phosphate, 0.1 mM EDTA, supplemented with 1% w/v glucose, pH 7.0) and inject 1 mL of it into the microfluidic device using a syringe pump operated at 10 &#181;L min-1. 
	NOTE: As the PDMS is under-saturated in gas (due to the previous vacuum step), bubbles will disappear within ~30 min.</li>
</ol>
3. Preparation of a fluidic device in poly (methyl methacrylate)
<ol>
	<li>Design the desired geometry with the CAD software. If applicable, make sure that the dimensions are suitable for observation under the microscope (e.g., dimensions of a standard 96 well plate in combination with an appropriate holder). The fluidic device is composed by a base (127 &#215; 127 &#215; 12 mm) and a lid (127 &#215; 127 &#215; 12 mm) of PMMA. 
	NOTE: Expertise with CAD software is recommended. An example technical drawing is supplied in Figure 1A.</li>
	<li>To produce the pore compartment, by means of high precision micromilling (WF31SA, Mikron), remove 0.5 mm from the bottom PMMA layer and mill a groove (1.1 &#215; 1.1 mm) for a rubber O-ring. Drill 12 threaded holes (M5). This will serve as the base of the fluidic device. 
	NOTE: The dimensions of the fluidic device need to be adjusted to fit the microscope stage and focal distance. A technical drawing is supplied in Figure S1.</li>
	<li>Drill two threaded holes (type 1/4-28UNF) for in- and outlet into the top part of the fluidic device, and 12 holes (5.5 mm) for the screws. This will serve as the lid of the fluidic device. 
	NOTE: Expertise in micro-milling is advisable; the authors use support from a specialized workshop.</li>
	<li>In order to clean and sterilize the fluidic device prior to and after each use, soak the base and lid of the fluidic device in HCl 7% and rinse three times with deionized water.</li>
	<li>Screw base and lid together using the 12 threaded holes.</li>
</ol>
4. Setup of automated dispenser
NOTE: Commercially available liquid dispensers are costly and often do not offer the flexibility to dispense directly from the outflow of the fluidic device. Therefore, assembling a cheap and flexible robotic dispenser system from an XY Plotter Robot (Table of Materials) is recommended.
<ol>
	<li>In order to dispense the outflow from the fluidic device into 96 well plates, mount the robotic dispenser onto a PMMA plate and mill cavities of 85.8 x 128 mm with a depth of 1 mm to hold several 96 well plates.</li>
	<li>Attach the outflow tube of the fluidic device to the robotic arm of the dispenser.</li>
	<li>To operate the robotic dispenser download bCNC from github:&#160;https://github.com/vlachoudis/bCNC and follow the instructions to install the program.</li>
	<li>Download dispenser.py from the supporting material of this article. 
	NOTE: This python code provides a plugin to bCNC for a simple robotic dispenser layout.</li>
	<li>Connect the robotic dispenser to the computer running bCNC and identify the correct COM port.</li>
	<li>In bCNC, click the home button to return the robotic dispenser to the home position. 
	NOTE: Homing returns the robotic dispenser to a known position (x=0, y=0) and therefore improves the accuracy of the dispenser.</li>
	<li>Prior to the experiment, prepare a sufficient number of 96 well plates, with wells containing an appropriate amount of fixative (e.g., final concentration 3.7% formaldehyde). 
	NOTE: For instance, at a flow rate of 0.2 mL min-1, 100 &#181;L are dispensed into each well every 30 s. Therefore, add 10 &#181;L of 37% formaldehyde to each well to reach a final concentration of Formaldehyde between 2 and 4%. Using eight 96 well plates will allow to operate the experiment for more than 6 h with a total of 768 data points. Moreover, note that GFP-tagged cells may lose their fluorescent signal after fixation using formaldehyde.</li>
</ol>
5. Analyze bacterial transport using PDMS microfluidic devices
<ol>
	<li>Place the PDMS microfluidic device previously saturated with the motility buffer on the microscope stage. Use tape to fix the tubing to minimize disturbance of the flow during stage movement.</li>
	<li>Move the microscope stage to the observation channel close to the outlet. Using bright field microscopy or phase contrast, focus to the center of the observation channel and adjust the magnification to visualize individual bacterial cells.</li>
	<li>Switch the light path settings to fluorescence microscopy and adjust the camera exposure time to resolve individual bacterial cells (e.g. 100 ms), or such that fluorescence signals of cells are at least 3x stronger than background noise.</li>
	<li>Next, insert the inlet tubing into a 2 mL tube containing the bacterial suspension. Reverse pump direction and start withdrawing the suspension at a flow rate of 1 &#181;L min-1.</li>
	<li>Scan the cross section of the entire observation channel recording a composite picture every 2 min, over the entire duration of the experiment.</li>
</ol>
6. Basic image processing
NOTE: The goal of these basic image processing routines is to count the number of bacteria in the recorded images. Optimal processing procedures depend on the technical specifications of the microscope and camera, as well as on the fluorescence properties of the bacterial strain used in the experiment and therefore need to be adjusted.
<ol>
	<li>First export images in .tiff format.</li>
	<li>Import images to a desired software platform (e.g., MATLAB, ImageJ, R or Python).</li>
	<li>Remove camera noise, which is a random variation of pixel intensity in images and correct for optical aberration. This can be done applying a Gaussian filter to each picture: the size of the filter depends on the quality of the camera sensor (e.g. CCD or CMOS). The optical aberration can be removed by normalizing each picture by a reference image collected in absence of the specimen with the same optical configuration.</li>
	<li>Crop the images to a region of interest.</li>
	<li>Identify a threshold value (pixel intensity), such that values above the threshold include bacterial cells. 
	NOTE: In case images are unevenly illuminated (because of optical aberration or noise) it may be useful to apply an adaptive threshold, which chooses a threshold value based on local mean intensities.</li>
	<li>Subtract from each picture the threshold defined above.</li>
	<li>Binarize the resulting image, such that bacterial cells take a value of 1, whereas background takes a value of 0.</li>
	<li>Remove clusters with an area smaller than the smallest bacterial cell size.</li>
	<li>Sum the binarized image to obtain the total number of pixels of the remaining clusters. Divide the number of pixels by the average size (in pixels) of a bacterial cell: this provides an estimate of the total number of cells.</li>
	<li>Knowing depth of view and area of investigation, transform counts into concentration (particles mL-1).</li>
	<li>It is fundamental to identify the concentration of the injected bacteria suspension. To do this, inject with a syringe 1 mL of bacteria culture suspension into the observation channel of a clean microfluidic device. Record the image and calculate the influent bacterial concentration (C0) as described above (6.1 to 6.10).</li>
	<li>Analyze BTCs by normalizing effluent bacterial concentration (C) with influent bacterial concentration (C0) and plot C/C0 versus time.</li>
</ol>
7. Analyze bacterial transport at the pore scale

<ol>
	<li>In order to analyze local velocities and trajectories of bacteria transported through the porous matrix, move the microscope stage to the region of interest and adjust the focus to the center of the microfluidic device.</li>
	<li>Set microscope to bright field or phase contrast. 
	NOTE: This only in case the fluorescence signal of bacterial cell does not allow recording images at exposure time shorter than the average bacterial time, otherwise use fluorescence microscopy.</li>
	<li>Record time-lapse images, at exposure time that captures bacteria displacement (shorter than the average displacement over a number of pixels smaller than the object size), and that optimizes bacterial cell detection (e.g. exposure of 20 ms and images recorded every 50 ms). Record pictures over a sufficient amount of time in order to record enough (to be statistically representative) of the slowest trajectories (e.g. 3 min). 
	NOTE: Make sure the computer has enough disk space.</li>
	<li>To remove background noise, subtract from each image the average of all recorded images. To do that, create a matrix whose result is the sum of intensity of all the images, for each pixel, and divide it by the number of images.</li>
	<li>From the processed image (Im), determine the modulus of the numerical gradient <img alt="Equation 1" src="/files/ftp_upload/60701/60701eq1v2.jpg" style="opacity: 0.9;" />&#160;and normalize it by its maximum value (max), as defined below. 
	<img alt="Equation 2" src="/files/ftp_upload/60701/60701eq2v2.jpg" />&#160; 
	<img alt="Equation 3" src="/files/ftp_upload/60701/60701eq3v2.jpg" /></li>
	<li>Binarize the matrix B via intensity thresholding, see steps 6.7-6.8.</li>
	<li>For each time point, record bacteria coordinates (x, y in pixel or mm) and time of image acquisition into a three-column file.</li>
	<li>Finally, apply a particle tracking script to process the recorded data and compute the trajectories of the bacteria. For instance use the established protocol19, and the freely available Matlab Particle Tracking Code: (http://site.physics.georgetown.edu/matlab/).&#160;</li>
</ol>
8. Study bacterial filtration by means of deposition profiles
<ol>
	<li>To obtain deposition profiles of GFP-tagged P. putida KT2440 cells by fluorescence microscopy, record a composite image of the entire porous channel before, that is the background, and after injection of bacterial suspension through the microfluidic device. Use an exposure time that allows acquiring bacterial fluorescent signal (e.g. 100 ms), without bleaching the signal.</li>
	<li>Export images and import in desired software platform (see 6.1-6.2).</li>
	<li>Remove background from the images recorded after bacterial injection.</li>
	<li>Integrate the total fluorescence signal of retained bacteria along transversal sections of the porous channel.</li>
	<li>In order to compute the deposition profile, plot the integrated florescence signal versus porous channel length.</li>
</ol>
9. Analyze bacterial transport using PMMA fluidic devices and flow cytometry
<ol>
	<li>Connect peristaltic pump with the inlet using 50 cm (1 mm inner diameter) tubing, and the outflow with the automated dispenser using the same tubing (50 cm, see section 4). 
	NOTE: Use the pump to dispense cultivation media, and to inject bacterial cells. Use Luer-lock connectors and three-way valves to shift between medium and bacterial suspension during the constant-rate release.</li>
	<li>Pump cultivation medium in the fluidic device. Note the arrival of medium at the outlet tubing fixed to the robotic dispenser.</li>
	<li>Start injecting the bacterial suspension through the PMMA fluidic device at a flow rate of 0.2 mL min-1,</li>
	<li>When bacteria reach the fluidic device inlet turn on the automated dispenser.</li>
	<li>In order to make a pulse injection, inject bacterial suspension for some pore volumes (e.g. 30), and then switch injection to cultivation media until experiment end. 
	NOTE: pore volume of the fluidic device is approximately 0.2 mL, thus at the prosed flow rate every minute one entire pore volume is exchanged.</li>
	<li>Once a 96 well plate is completed, cover the plate to reduce evaporation and store it at 4 &#176;C.</li>
	<li>Analyze bacterial abundance via flow cytometry, following established protocols20. 
	NOTE: For instance, add 25 &#181;L of the green-fluorescent nucleic acid stain (Table of Materials) at 0.025 mM (in ultrapure water) to each well. It stains bacterial DNA, thus allowing to quantify by flow cytometry the bacterial abundance. Incubate samples for 15 min in the dark and then analyze using a flow cytometer equipped with a 488 nm laser and detectors at 515 nm.</li>
	<li>Prior to BTC analysis, consider the dilution of the sample due to the addition of fixative and stain. Correct bacterial abundance by a factor of 1.35 to account for fixative and stain.</li>
</ol>

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The authors declare that there is no conflict of interest.

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 &amp;times; 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...

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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 ...

combining-fluidic-devices-with-microscopy-flow-cytometry-to-study

Research

JoVE Journal

Environment

6.4K Views.  École Polytechnique Fédérale de Lausanne. Het bestuderen van het transport van bacteriën in poreuze systemen is belangrijk met betrekking tot besmetting, verspreiding van ziekten en bioremediatie. Voor deze experimenten in wiskundige modellen die op de eencellige, de bevolking en de microbiële gemeenschap niveau nodig zijn. Hier presenteren we tools om bacterieel transport te bestuderen met behulp van microfluïde apparaten en microscopie, evenals grotere apparaten in combinatie met stroomcytometrie.De combinatie van microfl...

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

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 resistant to low molecular-weight oil components, unlike traditional polydimethylsiloxane (PDMS) devices. Here, we demonstrate a facile method for making a device with this property, and we use the product of this protocol for examining the pore-scale mechanisms by which foam recovers crude oil. A pattern is first designed using computer-aided design (CAD) software and printed on a transparency with a high-resolution printer. This pattern is then transferred to a photoresist via a lithography procedure. PDMS is cast on the pattern, cured in an oven, and removed to obtain a mold. A thiol-ene crosslinking polymer, commonly used as an optical adhesive (OA), is then poured onto the mold and cured under UV light. The PDMS mold is peeled away from the optical adhesive cast. A glass substrate is then prepared, and the two halves of the device are bonded together. Optical adhesive-based devices are more robust than traditional PDMS microfluidic devices. The epoxy structure is resistant to swelling by many organic solvents, which opens new possibilities for experiments involving light organic liquids. Additionally, the surface wettability behavior of these devices is more stable than that of PDMS. The construction of optical adhesive microfluidic devices is simple, yet requires incrementally more effort than the making of PDMS-based devices. Also, though optical adhesive devices are stable in organic liquids, they may exhibit reduced bond-strength after a long time. Optical adhesive microfluidic devices can be made in geometries that act as 2-D micromodels for porous media. These devices are applied in the study of oil displacement to improve our understanding of the pore-scale mechanisms involved in enhanced oil recovery and aquifer remediation.

The goal of this procedure is to easily and rapidly produce a microfluidic device with customizable geometry and resistance to swelling by organic fluids for oil recovery studies. A polydimethylsiloxane mold is first generated, and then used to cast the epoxy-based device. A representative displacement study is reported.

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

Wide-field Fluorescent Microscopy and Fluorescent Imaging Flow Cytometry on a Cell-phone

Fluorescent microscopy and flow cytometry are widely used tools in biomedical research and clinical diagnosis. However these devices are in general relatively bulky and costly, making them less effective in the resource limited settings. To potentially address these limitations, we have recently demonstrated the integration of wide-field fluorescent microscopy and imaging flow cytometry tools on cell-phones using compact, light-weight, and cost-effective opto-fluidic attachments. In our flow cytometry design, fluorescently labeled cells are flushed through a microfluidic channel that is positioned above the existing cell-phone camera unit. Battery powered light-emitting diodes (LEDs) are butt-coupled to the side of this microfluidic chip, which effectively acts as a multi-mode slab waveguide, where the excitation light is guided to uniformly excite the fluorescent targets. The cell-phone camera records a time lapse movie of the fluorescent cells flowing through the microfluidic channel, where the digital frames of this movie are processed to count the number of the labeled cells within the target solution of interest. Using a similar opto-fluidic design, we can also image these fluorescently labeled cells in static mode by e.g. sandwiching the fluorescent particles between two glass slides and capturing their fluorescent images using the cell-phone camera, which can achieve a spatial resolution of e.g. ~ 10 &mu;m over a very large field-of-view of ~ 81 mm2. This cell-phone based fluorescent imaging flow cytometry and microscopy platform might be useful especially in resource limited settings, for e.g. counting of CD4+ T cells toward monitoring of HIV+ patients or for detection of water-borne parasites in drinking water.

We review our recent results on the integration of fluorescent microscopy and imaging flow cytometry tools on a cell-phone using compact and cost-effective opto-fluidic attachments. These cell-phone based micro-analysis devices might be useful for cytometric analysis, such as performing various cell counting tasks as well as for high-throughput screening of e.g., water samples in resource limited settings.

Fluorescent microscopy and flow cytometry are widely used tools in biomedical research and clinical diagnosis. However these devices are in general ...

Bioengineering

Characterizing Microbiome Dynamics &#8211; 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 applications driven by microorganisms. Next generation sequencing methods are widely utilized to resolve microbiomes, but they are generally resource and time intensive and deliver mostly qualitative information. Flow cytometric microbiome analysis does not suffer from those disadvantages and can provide relative subcommunity abundances and absolute cell numbers at-line. Although it does not deliver direct phylogenetic information, it can enhance the analysis depth and resolution of sequencing approaches. In sharp contrast to medical applications in both research and routine settings, flow cytometry is still not widely used for microbiome analysis. Missing information on sample preparation and data analysis pipelines may create an entry barrier for the researchers facing microbiome analysis challenges that would often be textbook flow cytometry applications. Here, we present three comprehensive workflows for pure cultures, complex communities in clear medium and complex communities in challenging matrices, respectively. We describe individual sampling and fixation procedures and optimized staining protocols for the respective sample sets. We elaborate the cytometric analysis with a complex research centered and an application focused bench top device, describe the cell sorting procedure and suggest data analysis packages. We furthermore propose important experimental controls and apply the presented workflows to the respective sample sets.

Flow cytometric analysis has proven valuable for investigating pure cultures and monitoring microbial community dynamics. We present three comprehensive workflows, from sampling to data analysis, for pure cultures and complex communities in clear medium as well as in challenging matrices, respectively.

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

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.

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 ...

A Microfluidic Platform to Study Bioclogging in Porous Media

Bacterial biofilms are found in several environmental and industrial porous media, including soils and filtration membranes. Biofilms grow under certain flow conditions and can clog pores, thereby redirecting the local fluid flow. The ability of biofilms to clog pores, the so-called bioclogging, can have a tremendous effect on the local permeability of the porous medium, creating a pressure buildup in the system, and impacting the mass flow through it. To understand the interplay between biofilm growth and fluid flow under different physical conditions (e.g., at different flow velocities and pore sizes), in the present study, a microfluidic platform is developed to visualize biofilm development using a microscope under externally-imposed, controlled physical conditions. The biofilm-induced pressure buildup in the porous medium can be measured simultaneously using pressure sensors and, later, correlated with the surface coverage of the biofilm. The presented platform provides a baseline for a systematic approach to investigate bioclogging caused by biofilms in porous media under flow conditions and can be adapted to studying environmental isolates or multispecies biofilms.

The present protocol describes a microfluidic platform to study biofilm development in quasi-2D porous media by combining high-resolution microscopy imaging with simultaneous pressure difference measurements. The platform quantifies the influence of pore size and fluid flow rates in porous media on bioclogging.

Bacterial biofilms are found in several environmental and industrial porous media, including soils and filtration membranes. Biofilms grow under certain ...

Analyzing Mixing Inhomogeneity in a Microfluidic Device by Microscale Schlieren Technique

In this paper, we introduce the use of microscale schlieren technique to measure mixing inhomogeneity in a microfluidic device. The microscale schlieren system is constructed from a Hoffman modulation contrast microscope, which provides easy access to the rear focal plane of the objective lens, by removing the slit plate and replacing the modulator with a knife-edge. The working principle of microscale schlieren technique relies on detecting light deflection caused by variation of refractive index1-3. The deflected light either escapes or is obstructed by the knife-edge to produce a bright or a dark band, respectively. If the refractive index of the mixture varies linearly with its composition, the local change in light intensity in the image plane is proportional to the concentration gradient normal to the optical axis. The micro-schlieren image gives a two-dimensional projection of the disturbed light produced by three-dimensional inhomogeneity.
To accomplish quantitative analysis, we describe a calibration procedure that mixes two fluids in a T-microchannel. We carry out a numerical simulation to obtain the concentration gradient in the T-microchannel that correlates closely with the corresponding micro-schlieren image. By comparison, a relationship between the grayscale readouts of the micro-schlieren image and the concentration gradients presented in a microfluidic device is established. Using this relationship, we are able to analyze the mixing inhomogeneity from associate micro-schlieren image and demonstrate the capability of microscale schlieren technique with measurements in a microfluidic oscillator4. For optically transparent fluids, microscale schlieren technique is an attractive diagnostic tool to provide instantaneous full-field information that retains the three-dimensional features of the mixing process.

Herein, we describe a procedure that employs microscale schlieren technique to measure mixing inhomogeneity in a microfluidic device. Through calibration, distribution of concentration gradient can be derived from the micro-schlieren image.

In this paper, we introduce the use of microscale schlieren technique to measure mixing inhomogeneity in a microfluidic device. The microscale schlieren ...

Window on a Microworld: Simple Microfluidic Systems for Studying Microbial Transport in Porous Media

Microbial growth and transport in porous media have important implications for the quality of groundwater and surface water, the recycling of nutrients in the environment, as well as directly for the transmission of pathogens to drinking water supplies. Natural porous media is composed of an intricate physical topology, varied surface chemistries, dynamic gradients of nutrients and electron acceptors, and a patchy distribution of microbes. These features vary substantially over a length scale of microns, making the results of macro-scale investigations of microbial transport difficult to interpret, and the validation of mechanistic models challenging. Here we demonstrate how simple microfluidic devices can be used to visualize microbial interactions with micro-structured habitats, to identify key processes influencing the observed phenomena, and to systematically validate predictive models. Simple, easy-to-use flow cells were constructed out of the transparent, biocompatible and oxygen-permeable material poly(dimethyl siloxane). Standard methods of photolithography were used to make micro-structured masters, and replica molding was used to cast micro-structured flow cells from the masters. The physical design of the flow cell chamber is adaptable to the experimental requirements: microchannels can vary from simple linear connections to complex topologies with feature sizes as small as 2 &mu;m. Our modular EcoChip flow cell array features dozens of identical chambers and flow control by a gravity-driven flow module. We demonstrate that through use of EcoChip devices, physical structures and pressure heads can be held constant or varied systematically while the influence of surface chemistry, fluid properties, or the characteristics of the microbial population is investigated. Through transport experiments using a non-pathogenic, green fluorescent protein-expressing Vibrio bacterial strain, we illustrate the importance of habitat structure, flow conditions, and inoculums size on fundamental transport phenomena, and with real-time particle-scale observations, demonstrate that microfluidics offer a compelling view of a hidden world.

Microfluidic devices can be used to visualize complex natural processes in real time and at the appropriate physical scales. We have developed a simple microfluidic device that mimics key features of natural porous media for studying growth and transport of bacteria in the subsurface.

Microbial growth and transport in porous media have important implications for the quality of groundwater and surface water, the recycling of nutrients in ...

Biology

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

Microfluidic processing of biological samples typically involves differential manipulations of suspended particles under various force fields in order to spatially fractionate the sample based on a biological property of interest. For the resultant spatial distribution to be used as the assay readout, microfluidic devices are often subjected to microscopic analysis requiring complex instrumentation with higher cost and reduced portability. To address this limitation, we have developed an integrated electronic sensing technology for multiplexed detection of particles at different locations on a microfluidic chip. Our technology, called Microfluidic CODES, combines Resistive Pulse Sensing with Code Division Multiple Access to compress 2D spatial information into a 1D electrical signal. In this paper, we present a practical demonstration of the Microfluidic CODES technology to detect and size cultured cancer cells distributed over multiple microfluidic channels. As validated by the high-speed microscopy, our technology can accurately analyze dense cell populations all electronically without the need for an external instrument. As such, the Microfluidic CODES can potentially enable low-cost integrated lab-on-a-chip devices that are well suited for the point-of-care testing of biological samples.

We demonstrate a microfluidic platform with an integrated surface electrode network that combines resistive pulse sensing (RPS) with code division multiple access (CDMA), to multiplex detection and sizing of particles in multiple microfluidic channels.

Microfluidic processing of biological samples typically involves differential manipulations of suspended particles under various force fields in order to ...

Traction Microscopy Integrated with Microfluidics for Chemotactic Collective Migration

Cells change migration patterns in response to chemical stimuli, including the gradients of the stimuli. Cellular migration in the direction of a chemical gradient, known as chemotaxis, plays an important role in development, the immune response, wound healing, and cancer metastasis. While chemotaxis modulates the migration of single cells as well as collections of cells in vivo, in vitro research focuses on single-cell chemotaxis, partly due to the lack of the proper experimental tools. To fill that gap, described here is a unique experimental system that combines microfluidics and micropatterning to demonstrate the effects of chemical gradients on collective cell migration. Furthermore, traction microscopy and monolayer stress microscopy are incorporated into the system to characterize changes in cellular force on the substrate as well as between neighboring cells. As proof-of-concept, the migration of micropatterned circular islands of Madin-Darby canine kidney (MDCK) cells is tested under a gradient of hepatocyte growth factor (HGF), a known scattering factor. It is found that cells located near the higher concentration of HGF migrate faster than those on the opposite side within a cell island. Within the same island, cellular traction is similar on both sides, but intercellular stress is much lower on the side of higher HGF concentration. This novel experimental system can provide new opportunities to studying the mechanics of chemotactic migration by cellular collectives.

Collective cell migration in development, wound healing, and cancer metastasis is often guided by the gradients of growth factors or signaling molecules. Described here is an experimental system combining traction microscopy with a microfluidic system and a demonstration of how to quantify the mechanics of collective migration under biochemical gradient.

Cells change migration patterns in response to chemical stimuli, including the gradients of the stimuli. Cellular migration in the direction of a chemical ...

Microfluidic Tools for Probing Fungal-Microbial Interactions at the Cellular Level

Filamentous fungi are successful inhabitants of soil and play a major role in soil ecosystems, such as in the decomposition of organic and inorganic matter, as well as regulation of nutrient levels. There they also find numerous opportunities to interact with a variety of other microbes such as bacteria or other fungi. Studying fungal interactions at the cellular level, however, can be challenging owing to the black box-like nature of soil. New microfluidic tools are being developed for the study of fungal interactions; two platforms designed to study bacterial-fungal and fungal-fungal interactions are highlighted. Within these microchannels, fungal-microbial interactions can be monitored in controlled physico-chemical environments at higher temporal and spatial resolution than previously possible. Application of these tools have yielded numerous novel biological insights, such as the observation of bacterial polar attachment to hyphae or revealing uncharacterised fungal-fungal antagonisms. A key feature of these methodologies regards the ease of use of this tool by non-experts, yielding highly translatable technologies for use in microbiology labs.

Owing to the opacity of soil, interactions between its constituent microbes cannot easily be visualised with cellular resolution. Here, two microfluidic tools are presented, which offer new opportunities for investigating fungal-microbial interactions. The devices are versatile and simple to use, enabling high spatiotemporal control and high-resolution imaging at the cellular level.

Filamentous fungi are successful inhabitants of soil and play a major role in soil ecosystems, such as in the decomposition of organic and inorganic ...

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

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