Enhanced Retention of Chemotactic Bacteria in a Pore Network with

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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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Environmental Science & Technology

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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]

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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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ACS Paragon Plus Environment


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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

Generally


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

239

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

256

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 =

275

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

278

in the macrochannel sensed the concentration gradient from the NAPL attractant trapped

279

in the low permeable region (pore network), and accumulated in the vicinity of the

280

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

287

bacterial distribution in a microchannel near one droplet. Figure 3b shows a single field-

288

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

290

locations around different droplets under 20×/0.40 objective. The values of bacterial

291

density in Figure 4 were normalized to the initial value in the macrochannel at the point

292

of injection. Accumulation of P. putida F1 increased as the distance from the toluene

293

source decreased, while nonchemotactic bacteria were distributed evenly over the same

294

distances and no accumulation was evident. This indicated that chemotactic bacteria

295

responded to the concentration gradient of the attractant and migrated toward the regions

296

where the toluene concentration was higher, and conversely, the nonchemotactic mutant

297

did not present any observable response to the attractant gradient. Approximately 15%

298

more chemotactic bacteria accumulated at the visual edge of the toluene sources than at a

299

distance of 500 µm away from the sources. The differences in the distribution between

300

the wild type and the mutant were statistically significant in the range of 0-300 µm, with

301

p < 0.0001 by the two-way ANOVA. The results of both chemotactic accumulation and

302

statistical analysis were consistent with what was reported from a previous study using a

303

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

305

structure that is more representative of a complex groundwater system with distributed

306

contaminant sources.

307

Bacterial Retention within the Pore Network

308

In the third experiment we monitored bacterial concentration in the effluent from

309

the macrochannel as a breakthrough curve. To conceptualize the expected output, we

310

compared it to an ideal scenario in which the heterogeneous µchip was represented as

311

two flow paths analogous to electrical resistances in parallel. The macrochannel

312

represented the lower resistance path, essentially a plug flow situation, with the buffer

313

solution replacing the bacterial solution to yield a step-change in concentration. Within

314

the fine pore network the resistance to flow was greater and the time frame over which

315

the bacterial suspension in the pore network was replaced by buffer was much longer

316

with a more gradual change in concentration.

317

Bacterial concentration in the effluent was monitored as a function of time and

318

was scaled with the steady state concentration prior to the step-change of the influent to

319

buffer. For the case at the lower fluid velocity of 0.25 m/d, we observed a sharp drop in

320

concentration around the 2-hour time point and then a more gradual decrease in the

321

concentration over time with measurable concentrations continuing up to 18 hours for

322

both the chemotactic and nonchemotactic bacteria (Figure 5). The 2-hour time point

323

corresponded to the time needed to replace the bacterial suspension in the 2-cm long

324

macrochannel with buffer flowing at a velocity of 0.25 m/d. For the chemotactic bacteria,

325

the concentration was significantly less than the nonchemotactic control at all the time

326

points greater than 2 hours. The difference in concentration between chemotactic and

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327

nonchemotactic bacteria in the effluent was comparable to the simulations from the

328

mathematical models and was shown to be significant by a two-way ANOVA with p

Enhanced Retention of Chemotactic Bacteria in a Pore Network with

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