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Article
Enhanced retention of chemotactic bacteria in a pore network with residual NAPL contamination Xiaopu Wang, Larry M. Lanning, and Roseanne Marie Ford Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.5b03872 • Publication Date (Web): 03 Dec 2015 Downloaded from http://pubs.acs.org on December 8, 2015
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Enhanced Retention of Chemotactic Bacteria in a Pore
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Network with Residual NAPL Contamination
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Xiaopu Wang§, †, Larry M. Lanning † and Roseanne M. Ford †, *
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§ School of Petroleum Engineering, China University of Petroleum, Qingdao, Shandong,
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China 266580
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† Department of Chemical Engineering, School of Engineering and Applied Science,
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University of Virginia, Charlottesville, VA, USA 22904
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* Corresponding author phone: +1-434-924-6283; email:
[email protected] 10 11 12
Running title:
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Chemotaxis in heterogeneous porous microfluidics
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Keywords:
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Chemotaxis, Pseudomonas putida, heterogeneity, porous media, microfluidics,
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bioremediation, biodegradation
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Contact grant sponsor: NSF, National Natural Science Foundation of China, the
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Fundamental Research Funds for the Central Universities
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Contact grant number: EAR-0711377, EAR-1141400, 51509260 and 15CX02008A
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Additional Supporting Information may be found in the online version of this article.
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Abstract
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Nonaqueous phase liquid (NAPL) contaminants are difficult to eliminate from natural
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aquifers due, in part, to the heterogeneous structure of the soil. Chemotaxis enhances the
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mixing of bacteria with contaminant sources in low permeable regions, which may not be
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readily accessible by advection and dispersion alone. A microfluidic device was designed
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to mimic heterogeneous features of a contaminated groundwater aquifer. NAPL droplets
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(toluene) were trapped within a fine pore network, and bacteria were injected through a
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highly conductive adjacent macrochannel. Chemotactic bacteria (Pseudomonas putida
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F1) exhibited greater accumulation near the pore network at 0.5 m/d than both the
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nonchemotactic control and the chemotactic bacteria at a higher groundwater velocity of
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5 m/d. Chemotactic bacteria accumulated in the vicinity of NAPL droplets, and the
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accumulation was 15% greater than a nonchemotactic mutant. Indirect evidence showed
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that chemotactic bacteria were retained within the contaminated low permeable region
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longer than nonchemotactic bacteria at 0.25 m/d. This retention was diminished at 5 m/d.
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Numerical solutions of the bacterial transport equations were consistent with the
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experimental results. Because toluene is degraded by P. putida F1, the accumulation of
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chemotactic bacteria around NAPL sources is expected to increase contaminant
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consumption and improve the efficiency of bioremediation.
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Introduction
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Nonaqueous phase liquids (NAPLs) are the most common industrial contaminants
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in polluted groundwater.1 NAPL contaminants, including BTEX (benzene, toluene,
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ethylbenzene, and xylenes), trichloroethylene (TCE), petroleum and chlorinated
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hydrocarbons,2 are difficult to eliminate from natural aquifers due to their low solubility,
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low volatility, low intrinsic reactivity and low release rates from soil or sediments.3,4 As a
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consequence, they have become a major threat to groundwater resources for our daily
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usage. In-situ bioremediation provides an effective and economical solution to remove
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the
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microorganisms or other forms of biomass are injected into the contaminated sites and
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directly degrade or transform contaminant chemicals into nontoxic byproducts;8 at the
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same time, microorganisms may increase their population by growth upon the
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contaminant sources, which can further accelerate the biodegradation process. However,
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in-situ bioremediation has its own limitations. Because of the heterogeneity of the natural
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groundwater systems, the NAPL contaminant sources, which are trapped in regions
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where the conductivity is fairly low, are not readily carried away by the advective flow in
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zones with high hydraulic conductivity.9-11 One prominent example is the oil spill from
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the tanker Exxon Valdez in 1989. Although soluble contaminants were removed from the
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high-permeability upper layer of the beach by conventional remediation, residual oil
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persists in the low-permeability lower layer, and continues to leach slowly into the upper
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layer.12 Therefore, a more effective method is needed to remediate the low permeable
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regions, in order to ensure complete removal of oil.
organic
pollutants
from
groundwater.5-7
3
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speaking,
indigenous
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Chemotaxis, the microbial property by which microorganisms sense the
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concentration gradient of chemicals and migrate towards the preferential regions for their
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survival and growth, may be a key factor to achieve more efficient bioremediation.13,14
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Chemotaxis phenomena were associated with the biodegradation of many environmental
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chemicals, including NAPL and various aromatic compounds; because of the ability to
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locate and degrade the pollutants, such bacteria have a selective advantage to survive and
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grow in various contaminated sites, and as a consequence, reduce the pollutants in these
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areas.10,13,15-23 An indigenous bacterial strain P. putida F1 was studied, because it showed
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strong chemotactic responses to and degraded many chlorinated hydrocarbons, such as
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toluene, benzene, trichloroethylene etc.,16,20 and was widely applied to study bacterial
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chemotaxis.
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Microfluidic devices have proven to be effective tools in a wide range of
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scientific fields,24 and have some ideal features for the study of bacterial chemotaxis.
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Microfluidic devices allow accurate fabrication of microscopic scale features and precise
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manipulation of very small amounts of fluid, which is ideal for the study of NAPL
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contaminants in pore-scale geometries that are representative of the natural aquifer
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environment. Moreover, the microscale channel operates under laminar flow in most
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scenarios, so that the concentration gradient of attractant is smooth and mathematically
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predictable. Its absolute transparency and small size allow direct and quantitative
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measurement of the bacterial distributions inside the device under a microscope.
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Amongst the earlier studies, microfluidic devices with pore-scale features were
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created to study colloid transport.25-27 More recently, a variety of microfluidics designs
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were applied to the study of bacterial chemotaxis with advective flow. Under flow
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conditions, parallel-flow devices were among the first approaches to generate steep and
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steady concentration gradients and assess chemotaxis by the extent of transverse bacterial
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movement towards the chemoeffector stream.28-30 Long and Ford observed bacterial
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chemotaxis in a direction transverse to flow under fluid velocities typical of groundwater
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flow rates in a T-shaped homogeneous porous channel with a staggered array of
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cylindrical posts.31 Singh and Olson created a heterogeneous porous microfluidic device
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to study transverse chemotaxis, and an increase of chemotactic bacterial population was
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detected in the low permeable regions containing attractant.32 All the previous studies
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successfully detected the effect of bacterial chemotaxis in porous structure under typical
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groundwater flow rates; however, they all evaluated contaminants in the aqueous phase
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rather than the organic phase. A two-phase heterogeneous porous system is more
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representative of the actual NAPL contaminated sites. Wan and coworkers published
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several studies of bacterial transport in two-phase systems with water and air in the
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microfluidic device,25,26 and several researchers continued to study unsaturated
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(liquid/gas interfaced) porous media at different scales.33-37 Wang and co-workers
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developed a single-pore microfluidic device to quantify the chemotaxis effect in the
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vicinity of a NAPL/water interface.38
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In this study, a heterogeneous porous microfluidic device was designed to trap
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organic phase chemicals in the low permeable regions in order to test the following
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hypothesis: In well-defined heterogeneous porous media, chemotaxis facilitates bacterial
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migration preferentially towards NAPL attractant sources trapped in regions with lower
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hydraulic conductivity, which leads to accumulation of bacteria at chemically favorable
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locations, and, furthermore, an increase in the groundwater velocity beyond typical rates
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diminishes the impact of chemotaxis.
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Materials and Methods
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Preparation of the Bacteria/Attractant System. C. S. Harwood provided the
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wild type Pseudomonas putida F1,16 and R. E. Parales constructed the nonchemotactic
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mutant P. putida F1 CheA.39 The bacterial cultivation, harvest, resuspension and staining
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were thoroughly described in the previous work.40 The two bacterial suspensions with
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different dyes (the wild type with FM 4-64 and the mutant with DAPI) were then mixed
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for later experimental use, together with 1.2 mM sodium nitrate (Sigma-Aldrich, ACS
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reagent). 7 mL pure toluene (Sigma-Aldrich, HPLC grade) was stained with 1 mg Oil
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Red O (FisherBiotech, CAT#: BP112-10) to show observable red color.
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Microfluidic Design, Fabrication and Operation. The design used for the
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microfluidic device is presented in Figure 1 (a), in which the higher permeable region is
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represented by the horizontal channel (macrochannel) above and the lower permeable
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region with contaminant sources is represented below by the fine cross-hatched pore
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network with aligned round NAPL source zones. Figure 1c shows a closer view of the
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fine pore network with one round NAPL source zone. The dimensions of the
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microchannels and grids are typical of pores and soil grains within a low permeable layer.
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The round NAPL source zones were etched into a separate borofloat glass layer, which
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was distinct from the pore network, as shown in Figure 1d. The channel depth was
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chosen to be 20 µm, so that the channel ceiling did not interfere with bacterial motility.41
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Note that while Molaei and coworkers found that the cell-boundary interactions can trap
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E. coli on channel surfaces, and thus suppress its chemotactic ability;42 P. putida tends to
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reverse direction between runs and, unlike E. coli, it exhibits relatively fast association
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and dissociation with solid surfaces.43 Thus, any interaction with the surface was
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considered to be negligible for P. putida. The NAPL source zones had a depth of 100 µm
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to retain the toluene droplets. The microfabrication process and the thermal bonding
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method to assemble the two etched glass layers were well described by Roper and
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coworkers.44
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DI water was injected into the microfluidic device from both the bacterial and
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NAPL inlets, in order to saturate the system. Air bubbles were eliminated by continuous
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high-pressure water flow and the microfluidic system was kept saturated during the entire
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experiment. Toluene stained with Oil-Red-O was injected from the NAPL inlet to replace
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the water in the fine pore network, and then DI water was injected again to wash out the
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toluene in the fine pore network, while toluene droplets remained in all the NAPL source
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zones, as shown in Figure 1b. The entrapment of toluene droplets was facilitated by the
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different physical properties between glass that is hydrophilic and toluene that is
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hydrophobic. Therefore, toluene exhibits a high contact angle in the water-saturated
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spaces with glass walls and keeps a round intact shape. When water pushes toluene out of
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the pore network, it flows along the glass surface because both water and glass are
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hydrophilic, so the residual toluene in the pores can be carried away easily by water flow
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due to the their poor attachment to the glass surface; however, the toluene droplets are
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difficult to wash out, because surface tension at the openings to the pore network
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prevents the toluene droplets from floating out of NAPL source zones, and also there is
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not enough pressure from the flow to push the droplets out. More details about the
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mechanism of NAPL trapping are available in the Supporting Information. After NAPL
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droplets were trapped in designated locations, the NAPL inlet was closed by a solid pin,
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and saturated with 10% RMB to prevent the introduction of air bubbles into the system
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from the inlet.
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The mixed bacterial suspension was injected into the macrochannel using 100 µL
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point-style syringes (Spectrum Laboratory Products Inc), and then the syringes were
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loaded onto a syringe pump (PHD 2000 Infusion, Harvard Apparatus) and pushed at a
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constant flow rate of 100 µL/h, which was comparable to 40 m/d in the macrochannel.
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After 30 min of continuous injection, the experimental system was saturated with the
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bacterial suspension.
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The Wide-Field epifluorescence microscope (Olympus IX-70) was used for all
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experimental observation and image acquisition with the 2×/0.05 (Olympus, Plan) and
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20×/0.40 objectives (Olympus, PlanFI). An arc lamp and dichroic filter (Chroma
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51001bs, double coated for TRITC and DAPI) were used to look at the FM 4-64
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(excitation at 515 nm, emission at 640 nm) and DAPI (excitation at 345 nm, emission at
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455 nm) stained bacterial strains.
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Data Acquisition and Processing. Three independent studies were carried out
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under different operating conditions, including steady, transient, and no flow conditions
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with continuous or step change inputs, and at different observation locations, as shown in
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Figure 1b. The first study was conducted at steady state to examine the bacterial
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distribution at the interface between the macrochannel and the pore network (which
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contained toluene droplets) at different flow rates of 0.5 and 5 m/d. These two values of
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flow velocity were chosen because they were within the typical range of groundwater
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flow rates from 0.1 to 10 m/d,45 and were representative of slow and fast flows,
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respectively. Images of bacterial accumulation based on gray-level light intensity (gray
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scale) were taken at eight evenly distributed positions in the macrochannel near the
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adjacent porous network, as shown by the red dashed box marked with “I” in Figure 1b.
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Each of the eight observation positions covered an area with a distance range of 0 to 100
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µm from the junction and a width of 100 µm; the eight positions were numbered from 1
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to 8 along the flow direction to facilitate identification of the plotted data. The details of
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image processing were explained in our previous study.38 The second study took place
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under no-flow conditions; after 10 minutes of the quiescent status, observations of
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bacterial distributions were recorded in the vicinity of randomly selected toluene droplets.
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Thirty images were taken in different microchannels of the pore network near the edge of
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the droplets, and then were averaged via the function of Image Calculator in ImageJ to
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reduce data fluctuation and produce a more continuous bacterial distribution. The third
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study, conducted under transient flow conditions, was to compare the washout of a
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mixture of chemotactic and nonchemotactic bacteria at two different flow rates, 0.25 and
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5 m/d. Once the pore network was saturated with the bacterial mixture, the injectate fluid
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was changed from bacteria to 10% random motility buffer (RMB), and the speed was
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reduced to either 0.25 or 5 m/day to wash the bacteria out of the microfluidic device over
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a period of 18 continuous hours. Bacterial density, which was correlated as fluorescence
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intensity and normalized with initial intensity in the macrochannel at a certain speed, was
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recorded at the outlet of the macrochannel at different time points. Image analysis for all
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of the three studies followed the same protocol in Wang et al., 2012.
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Two-way ANOVA tests were used to determine statistical differences in bacterial
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distribution among various experimental data. Averages and standard deviations were
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calculated based on three independent experimental runs for each data set. The tests were
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evaluated in Prism 5.0a (GraphPad Software Inc., San Diego, CA).
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Mathematical Modeling. Because the height of the macrochannel was much less
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than its width and the fluid velocity in the pore network was slower than the bacterial
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swimming speed (i.e. bacterial movement dominated transport within the pore network) a
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two-dimensional Brinkman equation (Equation 1), u + ∇ ∙ − (∇u+(∇u) ) + I = − u ∇∙u=0
(1) (2)
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was suitable to describe the flow profile in the porous microfluidic device where u
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denotes the flow velocity vector (m/s), ρ the fluid density (kg/m3), εp the porosity
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(dimensionless), κbr the permeability of the porous medium (m2), µ the dynamic viscosity
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(Pa.s), and p the pressure (Pa). The boundary conditions are no slip conditions except at
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the inlet which is laminar flow at a certain flow rate and at the outlet which has no
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viscous stress (pout = 0). Equation 2 is the continuity equation under the assumption of an
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incompressible fluid. A two-dimensional form of the advection-dispersion governing
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equation was adopted to represent bacterial transport including the effect of chemotaxis.
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The advection-dispersion governing equations that follow were modified from Olson et
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al., 46 = , + , − −
(3)
!" !" = , + , − − − − 215
where
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(4)
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, =
(5)
!" =
(6)
2 +, -. tanh * / 3 2 (-. + )
2 +, -. !" = tanh * / 3 2 (-. + )
(7)
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where a refers to the attractant concentration, b the bacterial concentration, vx and vy the
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longitudinal and transverse fluid velocity solved from the two-dimensional Brinkman
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equation, Da the diffusion coefficient for attractant, Db the bacterial random motility, De,a
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and De,b are their effective values. vChx and vChy are the longitudinal and transverse
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chemotactic velocities describing the advective transport of bacteria caused by
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chemotaxis toward attractant gradients, χ0 the chemotactic sensitivity coefficient and Kc
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the chemotactic receptor constant. Bacterial adaptation is not accounted for explicitly in
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Equations 6 and 7 because of the shallow and steady state chemical gradients in the
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experimental system. We chose “no flux” as the overall boundary conditions, and then
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applied a fixed concentration of attractant/bacteria to the inlets, as well as the NAPL
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source zones, and “Convective Flux” to the outlet.
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The commercial finite-element solver COMSOL Multiphysics 4.3 (COMSOL,
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Burlington, MA) was used to solve the system of differential equations for the fluid
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velocity and the attractant and bacterial concentrations. Three two-dimensional modules
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were included in this simulation: one Incompressible Free and Porous Media Flow
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module for the advective flow profile, and two Species Transport in Porous Media
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modules for attractant and bacteria. Input parameters included the initial toluene
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concentration a0 =5.65 mol/m3, attractant diffusion coefficient Da = 9.5 × 10-10 m2/s,
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initial bacterial density b0 =1 mol/m3, bacterial swimming speed vb = 44 µm/s,14 bacterial
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random motility coefficient Db = 13 × 10-10 m2/s,14 chemotactic sensitivity coefficient χ0
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= 1.8 × 10-8 m2/s,40 chemotactic receptor constant Kc = 1.0 mM,40 the calculated pore
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network porosity εp = 0.43 and permeability κbr = 1.0 × 10-11 m2. κbr is the only fitting
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parameter, while all other parameters are either calculated in this study or reported in the
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literature.
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Results and Discussion
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The impact of chemotaxis was observed in three facets of the heterogeneous
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environment of the microfluidic device. First, chemotactic bacteria in the macrochannel
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accumulated at higher density near the connections to the pore network, which contained
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the toluene droplets. Second, chemotactic bacteria within the pore network accumulated
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in greater number near the vicinity of the toluene droplets. Third, chemotactic bacteria
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were retained to a greater extent within the pore network than nonchemotactic bacteria at
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a fluid velocity of 0.25 m/d. This effect was reduced at a higher fluid velocity of 5.0 m/d.
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Bacterial Accumulation in the Macrochannel near the Pore Network
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In Figure 2 bacterial abundance at the interface of the macrochannel with the pore
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network is plotted at eight positions along the length of the macrochannel. The bacterial
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abundance is normalized with the bulk concentration near the inlet in the macrochannel;
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for nonchemotactic bacteria, as expected, the normalized concentration was near unity
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(open triangles and dashed line) at 0.5 m/d as shown in Figure 2a. At a fluid velocity
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typical of natural groundwater flow rates 0.5 m/d, we observed an average 7.3% increase
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in the chemotactic bacterial accumulation at the eight positions (black squares and black
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line). When we increased the fluid velocity by an order of magnitude, the accumulation
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of chemotactic bacteria decreased (gray circles and gray line in Figure 2b) and was
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comparable to the control case with nonchemotactic bacteria. The solid lines connect
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simulation results from solving the governing equations for mass and momentum transfer
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using COMSOL software packages.
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The effect of fluid velocity on chemotactic accumulation in Figure 2b was
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consistent with the findings for a microfluidic device with a macrochannel connected to a
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single pore filled with toluene;38 Wang and coworkers reported that bacterial
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accumulation transverse to flow was observed in the vicinity of a NAPL interface at a
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velocity of 0.5 m/d, but the accumulation decreased dramatically when the flow rate was
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increased to 5 m/d. The slower advective flow rate resulted in a greater retention time,
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which allowed the chemotactic bacteria time to respond to the attractant source in the
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transverse direction.
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The experimental data of chemotactic distribution at 0.5 m/d were compared
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statistically with the nonchemotactic group at the same flow rate and chemotactic group
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at 5 m/d by a two-way ANOVA test. The results showed that the chemotaxis group at 0.5
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m/d was significantly different from either the nonchemotaxis control or the chemotaxis
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group at 5 m/d, with a p-value less than 0.0001 in both cases. Such a difference was not
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found when the nonchemotaxis group was compared with the 5 m/d group with p =
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0.1492, which implies that transport by advection dominated microbial motility and
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chemotaxis at the higher flow rate.
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These results suggested that the chemotactic bacteria carried along with the flow
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in the macrochannel sensed the concentration gradient from the NAPL attractant trapped
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in the low permeable region (pore network), and accumulated in the vicinity of the
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positions between these two regions, which facilitated the movement of bacteria into the
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pore network, to facilitate contact with the contaminant sources. Because the rate of
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biodegradation is proportional to the bacterial population density,47 we expect this
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accumulation of bacteria will ultimately enhance the biodegradation rate.
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Bacterial Accumulation near the Toluene Sources
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Figures 3 and 4 show the bacterial distribution within pores at the edge of toluene
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droplets under quiescent conditions. The schematic in Figure 3a illustrates the expected
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bacterial distribution in a microchannel near one droplet. Figure 3b shows a single field-
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of-view image cropped for a single channel of the actual bacterial distribution and Figure
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3c represents an average of 30 images from multiple fields-of-view taken at different
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locations around different droplets under 20×/0.40 objective. The values of bacterial
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density in Figure 4 were normalized to the initial value in the macrochannel at the point
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of injection. Accumulation of P. putida F1 increased as the distance from the toluene
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source decreased, while nonchemotactic bacteria were distributed evenly over the same
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distances and no accumulation was evident. This indicated that chemotactic bacteria
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responded to the concentration gradient of the attractant and migrated toward the regions
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where the toluene concentration was higher, and conversely, the nonchemotactic mutant
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did not present any observable response to the attractant gradient. Approximately 15%
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more chemotactic bacteria accumulated at the visual edge of the toluene sources than at a
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distance of 500 µm away from the sources. The differences in the distribution between
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the wild type and the mutant were statistically significant in the range of 0-300 µm, with
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p < 0.0001 by the two-way ANOVA. The results of both chemotactic accumulation and
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statistical analysis were consistent with what was reported from a previous study using a
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single-pore device.38 Note that the previous study measured the chemotaxis effect near
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one single pore slit, while this study successfully captured similar results in a porous
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structure that is more representative of a complex groundwater system with distributed
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contaminant sources.
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Bacterial Retention within the Pore Network
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In the third experiment we monitored bacterial concentration in the effluent from
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the macrochannel as a breakthrough curve. To conceptualize the expected output, we
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compared it to an ideal scenario in which the heterogeneous µchip was represented as
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two flow paths analogous to electrical resistances in parallel. The macrochannel
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represented the lower resistance path, essentially a plug flow situation, with the buffer
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solution replacing the bacterial solution to yield a step-change in concentration. Within
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the fine pore network the resistance to flow was greater and the time frame over which
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the bacterial suspension in the pore network was replaced by buffer was much longer
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with a more gradual change in concentration.
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Bacterial concentration in the effluent was monitored as a function of time and
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was scaled with the steady state concentration prior to the step-change of the influent to
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buffer. For the case at the lower fluid velocity of 0.25 m/d, we observed a sharp drop in
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concentration around the 2-hour time point and then a more gradual decrease in the
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concentration over time with measurable concentrations continuing up to 18 hours for
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both the chemotactic and nonchemotactic bacteria (Figure 5). The 2-hour time point
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corresponded to the time needed to replace the bacterial suspension in the 2-cm long
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macrochannel with buffer flowing at a velocity of 0.25 m/d. For the chemotactic bacteria,
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the concentration was significantly less than the nonchemotactic control at all the time
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points greater than 2 hours. The difference in concentration between chemotactic and
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nonchemotactic bacteria in the effluent was comparable to the simulations from the
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mathematical models and was shown to be significant by a two-way ANOVA with p