Environ. Sci. Technol. 2011, 45, 1014–1020
Shewanella oneidensis MR-1 Chemotaxis in a Diffusion Gradient Chamber R U I L I , †,‡ J E N N I F E R M . A U C H T U N G , ‡ J A M E S M . T I E D J E , ‡,§ A N D R . M A R K W O R D E N * ,†,‡ Department of Chemical Engineering and Materials Science, Departments of Microbiology and Molecular Genetics, and Center for Microbial Ecology, Michigan State University, East Lansing, Michigan 48824, United States
Received July 16, 2010. Revised manuscript received December 3, 2010. Accepted December 8, 2010.
To obtain a systems-level understanding of Shewanella biology and ecology, the influence of electron acceptor availability on Shewanella’s growth, metabolism, and transport needs to be elucidated. The diffusion gradient chamber (DGC) is an experimental tool developed to study population-level microbial growth and motility in response to concentration gradients. In this paper, the response of populations of Shewanella oneidensis MR-1 cells to an applied single gradient of the electron acceptor fumarate and applied opposing gradients of fumarate and nitrate, also an electron acceptor, were studied in the DGC. Mathematical models capable of predicting cellular growth and chemotaxis under the influence of gradients were used to analyze the results. Examining wildtype cells grown in a single gradient of fumarate, we found that MR-1 cells formed a chemotactic band that migrated up the electron acceptor gradient essentially as predicted by the model. The predicted velocity of the chemotactic cell band advancing toward the chemoattractant source (0.139 cm/h, R2 ) 0.996) closely matched that measured in the DGC (0.134 cm/h, R2 ) 0.997). Investigating the impact of opposing gradients of nitrate and fumarate on the chemotactic behaviors of S. oneidensis MR-1 fumarate reductase and nitrate reductase mutants, we found that the DGC was able to separate these mutants based upon their abilities to use the available electron acceptors in accordance with model predictions. Differences in the ability of Shewanella species to respond to and use available electron acceptors is thought to play an important role in their ecology. Therefore, these results validate the use of the DGC system to measure and simulate Shewanella chemotaxis in response to electron acceptor gradients and establish it as a research tool to help elucidate Shewanella’s role in environmental processes.
Introduction Shewanella species are known for their broad range of terminal electron acceptors and their ability to grow in a wide range of environments. Over 20 different organic and * Corresponding author phone: (517)353-9015; fax: (517)432-1105; e-mail:
[email protected]. † Department of Chemical Engineering and Materials Science. ‡ Center for Microbial Ecology. § Departments of Microbiology and Molecular Genetics. 1014
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inorganic compounds can be reduced by Shewanella species, enabling the genus to inhabit diverse ecosystems (3). Moreover, Shewanella species exhibit chemotaxis in response to electron acceptors, including both organic compounds and metals (4, 5). Chemotaxis toward electron acceptors was first considered as metabolism-independent (5) but later was proposed to be an energy taxis (4, 6). More recently, researchers confirmed that chemotaxis of S. oneidensis MR1, a Shewanella species often studied as a model for species in the Shewanella genus, was mediated by an energy taxis mechanism, as inactivation of electron-acceptor reductases or disruption of the ∆pH abolishes chemotaxis (7). Shewanella species’ ability to migrate in response to spatial gradients of electron acceptors may provide a competitive advantage, allowing shewanellae to move into more favorable environments that increase its chances of survival and growth. This ability, coupled with Shewanella species’ wide range of potential electron acceptors, may help explain its nearly ubiquitous presence in widely disparate environmental niches. It may also contribute to Shewanella species’ important ecological roles in biogeochemical cycles of nitrogen, carbon, iron, and other metals. The ability to understand and harness chemotaxis toward electron acceptors may also facilitate use of shewanellae in bioremediation processes, such as toxic metal oxide stabilization and denitrification (3). Population-level microbial chemotaxis is complex, involving a complex interplay of cellular processes (growth, metabolism, chemotaxis, and random motility) and molecular processes (diffusion of carbon sources, energy sources, and chemoattractants). The Diffusion Gradient Chamber (DGC, Supporting Information (SI) Figure 1) was developed to study these simultaneous transport and reaction processes under controlled conditions. The DGC was used to characterize microbial chemotaxis-dependent cellular phenomena, including separation of microbial species via differences in their chemotactic properties (8). A mathematical model of the DGC was developed to quantitatively describe the simultaneous cellular and molecular processes that underpin population-level cell dynamics involving chemotaxis (9). In this paper, we report on the growth and chemotaxis of S. oneidensis MR-1 in a single spatial gradient of the electron acceptor fumarate or multiple gradients including both fumarate and nitrate in the DGC. The mathematical model was adapted to describe MR-1 cells growing with fumarate and nitrate as the electron acceptors. The model was used to interpret the experimental results and reproduce the migration patterns observed in the DGC, thereby providing insights into the complex interplay of transport and reaction phenomena governing cellular growth and migration of S. oneidensis MR-1. Extension of the approach to include gradients of nitrate and fumarate and to include mutants in fumarate and nitrate reductase genes also demonstrated the DGC’s ability to separate populations of S. oneidensis MR-1 strains based on their different chemotactic responses to electron-acceptor gradients, providing insight into the role of chemotaxis in the microbial ecology of Shewanella species (1, 2, 10).
Materials and Methods Strains and Growth Conditions. All the strains used are listed in Table 1. S. oneidensis MR-1 and its mutants were grown either aerobically on LB medium at 30 °C or anaerobically on LM medium (6) containing 40 mM sodium lactate and sodium fumarate or sodium nitrate at concentrations indicated below. LB medium was amended with 30 µg of 10.1021/es102425p
2011 American Chemical Society
Published on Web 12/21/2010
TABLE 1. Strains and Plasmids strain or plasmid Strains Shewanella oneidensis MR-1 S. oneidensis MR-1 mutants CCG01 SO0970 JMA1023 Escherichia coli WM3064 BW29427
pURR25
pUX-BF13
description
reference
wild type
(8)
∆napA ∆fccA ∆fccA miniTn7-GFPmut3*
(11) (12) this study
donor strain for conjugation, dap auxotroph donor strain for conjugation, dap auxotroph, tra pir
(13)
Plasmids mini Tn7KsGFP, GFP driven by Plac (PA1/04/03) promoter, mobilizable oriTInc.PR, suicide oriRR6kγ; Apr (bla) Tn7 transposase genes tnsABCDE, mobilizable Apr (bla)
(14)
(13)
(15)
kanamycin/mL, 20 µg of streptomycin/mL, and 300 µg of diaminopimelic acid (DAP)/mL when required. The green fluorescent protein (GFP) reporter gene (gfpmut3*) was inserted into the chromosome of a fumarate mutant as described by Ciche et al. (14). Briefly, donor strain Escherichia coli WM3064 harboring the plasmid pURR25 (encoding miniTn7KSGFP) and E. coli BW29427 harboring plasmid pUXBF13 (encoding Tn7 transposase) were grown and mated with the S. oneidensis MR-1 cells by triparental mating on LB agar containing DAP. Following mating, GFP-labeled exconjugant cells were selected in the absence of DAP and presence of kanamycin and streptomycin and tested for GFP fluorescence by using a SpectraMax M2Multi-Mode microplate reader (Molecular Devices, Sunnyvale, USA) set at an excitation wavelength of 475 nm and emission detection at 515 nm. DGC Experiments. Experiments in the DGC were carried out following protocols described previously (8), except that strict anaerobic conditions were maintained by operating the DGC in a glove chamber with ∼4% H2 (the balance in N2). LM medium containing lactate and 0.15% agar was used for all experiments. When grown in the presence of lactate and fumarate, S. oneidensis MR-1 oxidizes the lactate to acetate and reduces fumarate to succinate. Swarm plate experiments, performed as described before (6), showed that lactate is not a chemoattractant for S. oneidensis MR-1, consistent with previous results (5). The metabolic byproducts, acetate and succinate, also tested in swarm plates, did not significantly affect either cellular growth or migration (data not shown). The DGC consists of a rectangular arena (50 mm × 50 mm × 10 mm) filled with 0.15% agar and is bounded on each side by a liquid reservoir. Each reservoir is separated from the agar by either a polycarbonate membrane, which allows solute exchange between the gel and the reservoir, or an impermeable rubber sheet that blocks solute exchange. In Run 1, all four reservoirs were sealed with rubber sheets, and the agar contained both lactate and 5 mM fumarate. Hence, there was no fumarate gradient across the agar at the time of inoculation. In Run 2, the south reservoir served as the fumarate source (15 mM fumarate), and the north reservoir served as the fumarate sink (0 mM fumarate). The other two reservoirs (east and west) were sealed. Fresh solution containing the specified fumarate concentration plus lactate
was continuously pumped through the reservoirs at a flow rate of approximately 2.5 mL/h to keep each reservoir’s concentration constant. Before inoculating the agar, a fumarate gradient was established by allowing fumarate to diffuse from the source reservoir, through the agar, to the sink reservoir for 10 h. S. oneidensis MR-1 cells were grown in 10 mL aerobic LB medium at 30 °C on a rotary shaker at 250 rpm overnight to an OD600 nm ∼ 0.1, pelleted by centrifugation, resuspended in 10 µL LM medium, and loaded into a sterile pipet tip. This tip was stabbed vertically into the gel at the midpoint of the DGC’s arena, and then the inoculum was gradually expelled as the pipet was withdrawn, leaving a vertical column of cell suspension. In Run 3, a nitrate gradient (0 to 2 mM) was established in the opposite direction to the fumarate gradient (12 to 0 mM). Both the fluorescent fumarate reductase mutant (JMA1023), which responded chemotactically to fumarate but not nitrate, and the nonfluorescent nitrate reductase mutant (GCC01), which responded chemotactically to nitrate but not fumarate (7), were inoculated 12 h after gradient initiation. Samples were taken from the chemotactic moving band 14 h after inoculation using a 1 mL syringe. A LSR II Flow Cytometer (BD, Sparks, USA) was used to test cell fluorescence with blue laser at 488 nm, FITC detector, 505 LP long-pass dichroic mirror, and 530/30 bandpass filter. After inoculation, the DGC was stationed on a transilluminator box (8) located in the anaerobic chamber. The box provided diffuse lighting from a 45° angle beneath the DGC, so that regions of high cell density appeared as bright regions against a dark background. Pictures were taken by a digital camera every a few hours after inoculation within the glovebox. Mathematical Model. The mathematical model (9) consists of coupled, unsteady-state, differential mass balance equations for cells, the carbon source (i.e., lactate), and the electron acceptor (i.e., fumarate). Under the experimental conditions, electron acceptor would be expected to be the rate-limiting nutrient, and toxicity due to acetate accumulation could be neglected. The cell mass balance equation is ∂u ) -∇·Ju + qu ∂t
(1)
where u is the cell density, t is the time, Ju is the cell flux, and q is the specific growth rate. Ju is expressed as a sum of random motility and chemotaxis in the direction of a chemoattractant gradient Ju ) -µ∇u + Vuu
(2)
where µ is the random motility coefficient, and Vu is the chemotactic velocity in response to the electron acceptor (S). The chemotactic velocity is expressed as Vu ) χ0
KD (KD + S)2
∇S
(3)
where χ0 is the chemotaxis coefficient, S is the fumarate concentration, and KD is the receptor dissociation constant. Equation 3 is a simplified form of the RTBL model (16, 17) that was shown by Widman (9) to adequately describe population-level E. coli chemotaxis in the DGC. The RTBL model has been successfully applied to describe bacterial chemotaxis mediated by an energy taxis mechanism (18). The cell growth rate is assumed to be limited by the electron acceptor concentration, as described by the Monod model q)ν
S CS + S
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where ν is the maximum specific growth rate, and CS is the half-saturation constant for the electron acceptor consumption. Substituting eq 2, 3, and 4 into eq 1 gives
[
]
KD ∂u S u∇S + uν ) µ∇2u-χ0∇· ∂t CS + S (KD + S)2
(5)
The fumarate balance is uν S ∂S ) DS∇2S ∂t Y CS + S
(6)
where Y is a yield coefficient (mass of electron acceptor consumed/mass of cells produced), and DS is the fumarate diffusion coefficient within the agar. A zero-flux boundary condition is applied for cells on DGC boundaries (Ω), because cells cannot cross the membranes or rubber sheets that separate the agar from the reservoirs
{ [ µ∇u-χ0
KD (KD + S)2
u∇S
]}
)0
(7)
Ω
A Neumann boundary condition (eqs 8 and 9) is used where a membrane allows fumarate exchange between the agar and a reservoir, and a zero-flux boundary condition (eqs 9 and 10) is used where a rubber sheet seals off the reservoirs ∂S ∂y ∂S ∂y
|
|
) y)0
kS (S| - Sres,S) DS y)0
)y)2R
| |
∂S ∂x ∂S ∂x
kS (S| - Sres,N) DS y)0 )0
(8)
(9)
(10)
1016
9
(
Y)
)0
(11)
x)2R
)
kSAarena S0 ) t S0 - S Varena
(12)
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St - Si u t - ui
(13)
where St and Si are the fumarate concentrations at two different times, and ut and ui are the corresponding cell densities. The CS value was estimated from chemostat experiments carried out in a glovebox under fumaratelimiting conditions (20). A peristaltic pump was used to deliver the growth medium (LM medium with 40 mM lactate and 10 mM fumarate) to the magnetically stirred, 72 mL chemostat tank. At each dilution rate, the system was run for a minimum of ten residence times, and then steady-state was confirmed by a constant OD600. The experimentally measured steadystate cell concentrations were plotted as a function of the dilution rate (D), and the half-saturation constant for the fumarate (CS) was determined from nonlinear regression using the following mass balance on the rate-limiting substrate (i.e., fumarate) (21)
(
u ) Y S0 -
x)0
where Sres,S and Sres,N are the fumarate concentrations in the south and north reservoirs, respectively, and kS is the mass transfer coefficient for fumarate transport through the membrane. To simulate Run 3, the model used for Runs 1 and 2 was used to describe the fumarate gradient and nitrate reductase mutant. Additional balances were added to describe the nitrate gradient and fumarate reductase mutant. Briefly, the balances for both strains had the same random motility term. However, the balance for JMA1023 contained chemotaxis and consumption terms depending on nitrate concentration, and the balance for GCC01 contained chemotaxis and consumption terms depending on fumarate concentration. The balance for both electron acceptors had same diffusion term but different consumption terms for the two strains. The model was solved numerically using an alternating direction implicit (ADI) algorithm as described previously (9). Estimation of Model Parameters. The mass transfer coefficient for fumarate transport across the membrane was determined using the approach described previously (9). Briefly, the fumarate transport rate from the reservoir to a well-mixed, water-filled arena was measured using HPLC. The following mass balance describes how S varies with time as fumarate diffuses across the membrane ln
where S0 is fumarate concentration in the arena, Aarena is the membrane area, and Varena is the liquid volume in the arena. The experimental data were plotted in the linear form suggested by eq 12, and the resulting slope was used to calculate a kS value. The DS value was first estimated using the Nernst equation (19); then a fumarate gradient was allowed to develop across the DGC arena for fixed periods of time and then measured using HPLC. The Ds value was then adjusted to optimize agreement between the experimentally measured profile and that predicted by eqs 6 and 8-11. The ν value was determined as the slope of the ln(cell density) versus time plot during exponential growth under anaerobic conditions. The yield coefficient (Y) was determined by applying the following relationship during the exponential growth phase
DCS ν-D
)
(14)
A capillary assay was performed to estimate cellular motility parameters. Briefly, a capillary containing an attractant solution was placed into a suspension of motile bacteria, and the number of bacteria that accumulated inside the capillary was determined. A simplified approach described by Mazumder et al. was used (6, 22), in which 1 mL syringes with 22G, 1-in., blunt-ended, stainless-steel cannulae were used instead of glass capillary tubes. The µ values were estimated using eq 15 (16) µ)
( )
π NRM 4t πr2b c
2
(15)
where NRM is the number of cells accumulating in the cannula of radius (r) without attractant after time (t), and bc is the initial cell number concentration in the chamber. Sensitivity curves were obtained by performing the capillary assay with a set of capillaries containing fumarate at different concentrations. The KD value was estimated by fitting eq 16 to the data using nonlinear regression (23, 24) N)C
KDS
(16)
(KD + S)2
where N is the number of cells accumulating in the cannula with attractant (i.e., fumarate), and C is a constant. The χ0 value was estimated by eq 17 (16) χ0 ) √µDS
(
)
(1 + Sj 0)2 N -1 Sj ∞ - Sj 0 NRM
(17)
where Sj0 and Sj∞ are the dimensionless attractant concentrations initially present at the mouth of the capillary, and far into the capillary, respectively, scaled by KD. Over ten independent replicates of the capillary assay were used to estimate both µ and KD. Parameters for nitrate related phenomena were all estimated from DGC experiments.
Results and Discussion Formation of Fumarate Gradients. The kS value for fumarate, determined using eq 12, was 0.168 cm/h. This value was then used with eqs 6 and 8-11 to determine an optimal DS value for fumarate diffusion through the agar of 0.0365 cm2/h (SI Figure 2). Batch and Continuous Culture Cultivation. Cultures grown on 5 to 40 mM fumarate exhibited similar growth rates. Analysis of these data gave a yield coefficient of 0.0144 g dry cell per mol fumarate (0.0189 cell density OD600 per mM fumarate (R2 ) 0.98), a half-saturation constant of 2.92 mM, and a maximum specific growth rate of 0.693 h-1 (R2 ) 0.99) (SI Figure 3). Motility and Chemotaxis. Capillary assay experiments conducted in the absence of fumarate gave a µ value of 0.020 cm2/h with standard deviation of 0.011. Nonlinear regression of eq 16 to the data gave an optimal KD value of 20 mM (SI Figure 4). The χ0 value calculated using eq 17 was 1.96 cm2/h with a standard deviation of 1.17. These values for random motility and chemotaxis coefficient are larger than those typically reported for other bacteria (16, 24, 25). Additional capillary assays were conducted using traditional capillary tubes, but similar results were obtained. When the experimentally determined microbial transport constants were used in the DGC model, the model significantly overpredicted random cell motility observed in DGC experiments. A trialand-error approach was then used, in which µ, χ0, KD values were manually adjusted to provide reasonable agreement between the model’s predictions and the experimentally observed behavior. The resulting values (µ ) 0.001 cm2/h, χ0 ) 0.09 cm2/h, and KD ) 0.750 mM) are similar in magnitude to published values for other bacteria. Other researchers have also reported problems using capillary assays for S. oneidensis MR-1. Nealson et al. demonstrated S. oneidensis MR-1 chemotaxis toward electron acceptors using both swarm and plug agar assays but failed to detect chemotaxis using the capillary assay (5). Li and co-workers attempted to characterize chemotactic responses of MR-1 to electron acceptors using capillary assays and cell enumeration via counting under a microscope. They found that fumarate elicited a response at 2 mM and that saturation occurred at electron acceptor concentrations above 100 mM (6). These results are similar to our results (SI Figure 4) obtained using cell enumeration via colony forming units. The reason(s) for the apparent discrepancy between MR-1’s chemotactic behavior in the capillary assay and the agar used in the DGC are unclear. Response of S. oneidensis MR-1 to Fumarate Gradient in DGC. Run 1 measured S. oneidensis MR-1’s growth and migration patterns in the absence of a pre-established gradient (i.e., a swarm plate). Results are shown in Figure 1, rows one and two. The experimentally observed cell-density patterns (left column) are reasonably well predicted by the model (middle column). The predicted velocity of the chemotactic band (0.136 cm/h, R2)0.999) was about 15% less than the experimental value DGC (0.159 cm/h, R2)0.998). The predicted fumarate gradient, which results from cells’ metabolism and drives formation of the chemotactic band, is shown in the right column. Run 2 measured the comparable cell and fumarate patterns (Figure 1, rows three and four) that result when a well-defined fumarate concentration is established in the
DGC prior to inoculation. Two nonobvious features of the experimentally observed patterns (left) are reproduced in the model’s prediction (middle). First, an arc-shaped chemotactic band developed and migrated selectively up the applied fumarate gradient. The velocity of the chemotactic band measured in the DGC (0.134 cm/h, R2)0.997) closely matched that predicted by the model (0.139 cm/h, R2)0.996). The asymmetric chemotactic pattern observed in response to the applied gradient is strikingly different from the symmetrical, circular chemotactic band observed in Run 1. The reason for the trend is shown in the predicted fumarate profiles (right). Cellular uptake of fumarate south of the inoculation point generates a steep concentration gradient that triggers chemotactic band formation; however, north of the inoculation point, the fumarate gradient remains too shallow to trigger a chemotactic band. Second, as the chemotactic band migrates away from the inoculation zone, a significant fraction of the S. oneidnesis MR-1 cells is left behind (Figure 1). This observation suggests that chemotactic bands have a maximum cell-carrying capacity. If, as the chemotactic band forms, the local cell concentration exceeds the band’s carrying capacity, excess cells are left behind. The carrying capacity of the chemotactic band in Run 2 would be expected to be less than that in Run 1, because the Run 2 band only covers a polar angle less than π radians with respect to the inoculation point, whereas the Run 1 chemotactic band covers the full 2π radians. The experimental curves for Run 2 show a slight flattening of the chemotactic band as the cells migrate into higher fumarate concentrations. A similar behavior was observed for E. coli growing into an advancing gradient of the chemoattractant aspartate in the DGC (8, 9). The degree of flattening was underpredicted by the DGC model. This minor discrepancy may arise from inaccuracies inherent in the use of a relatively simple chemotaxis model (i.e., eq 3). In Run 3, we exposed a mixture of two mutants, one unable to reduce fumarate and the other unable to reduce nitrate, to opposing gradients of fumarate and nitrate. The mutants were created by deletions of the fumarate reductase or nitrate reductase gene (∆fccA or ∆napA), respectively. (The ∆fccA mutants also contained the green fluorescent protein gene gfpmut3 stably integrated into the chromosome in the Tn7 attachment site, which allowed us to distinguish the cell populations based upon fluorescence). We found that this mixture of mutant strains could be partially separated into two populations via formation of two separate chemotactic bands, one moving toward each chemoattractant (Figure 2). Flow cytometry for cells collected from the leading edge of each chemotactic band indicated that 92.1% ( 5.0% of cells moving toward the fumarate source were nonfluorescent (i.e., nitrate reductase mutants), while 87.5% ( 5.2% of cells moving toward the nitrate source were fluorescent (i.e., fumarate reductase mutants). The percentage of cells having the fluorescence trait expected for that chemotactic band may have been less than 100% due to background noise from agar and dead cells; our positive control (only fluorescent cells inoculated under same conditions) also showed a similar fluorescent percentage (89.4% ( 6.1%). However, we cannot rule out the possibility that a small amount of nitrate reductase mutants were attracted by the nitrite produced during nitrate reduction of the other strain. Cruz-Garcı´a et al. reported that during S. onediensis MR-1 nitrate reduction in liquid culture, the intermediate product nitrite accumulates to levels that strongly inhibit cell growth (11). Our batch growth experiments in liquid culture confirmed that the fumarate reductase mutant cells cannot grow with 2 mM nitrite in the liquid LM media (data not shown). However, in separate control experiments these cells grew and migrated chemotactically in LM agar containing 2 mM nitrite (data not shown), and no evidence of inhibition was VOL. 45, NO. 3, 2011 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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FIGURE 1. Experimental (left) and modeling (middle and right) results for DGC Runs 1 and 2. Brightness and contrast of experimental images were adjusted for clarity. In Run 1 (shown in rows one and two), all four reservoirs were sealed off. S. oneidensis MR-1 cells were inoculated without a pre-established fumarate gradient. In Run 2 (shown in rows three and four), the fumarate concentration was 15 mM in the south reservoir and 0 mM in the north reservoir; the west and east reservoirs were sealed off. S. oneidensis MR-1 cells were inoculated 10 h after gradient initiation. Brighter areas correspond to higher cell densities. In the three-dimensional graphs of simulated fumarate gradient profiles (right), the z axis represents the fumarate concentration (mM), and the x and y axes correspond to the dimensions of the DGC (mm). The time shown in the upper left-hand corner of experimental results corresponds to the time after inoculation.
observed in Run 3. This result indicates that the DGC can be used to study cell growth, metabolism, and chemotactic migration under conditions that inhibit cell growth in liquid culture. In fact, the concentration of nitrite accumulating in the agar was very low (1 ppm, about 0.071 mM) around cell migration rings in Run 3 (tested as described by Cruz-Garcı´a et al. (11)). Based on these observations, we did not include nitrite accumulation, inhibition, or chemotaxis toward nitrite in the DGC model. 1018
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Cell-transport constants for modified DGC model were adjusted to reasonably match the experimental results from Run 3 (Figure 2). The simulation results predicted that near the nitrate source, 100% of cells are fumarate reductase mutants, and close to fumarate source, 100% of cells are nitrate reductase mutants. Thus the model was able to reproduce the experimentally observed, chemotaxis-driven, physical separation of two MR-1 mutants based on differences in their ability to metabolize, and thus create spatial gradients
FIGURE 2. Experimental (left) and modeling (right) results for DGC Run 3. Brightness and contrast of experimental images were adjusted for clarity. Fumarate concentration was 12 mM in the south reservoir and 0 mM in the north reservoir. Nitrate concentration was 2 mM in the north reservoir and 0 mM in the north reservoir. The west and east reservoirs were sealed off. A mixture of S. oneidensis MR-1 fumarate-reductase mutants and nitrate-reductase mutants was inoculated 12 h after gradient initiation. Brighter areas correspond to higher cell densities. The time shown in the upper left-hand corner of experimental results corresponds to the time after inoculation. of, electron acceptors.This finding is relevant to Brettar and Ho¨fle’s discovery that Shewanella baltica was the dominant denitrifier in the Baltic Sea, which was heavily polluted by nitrate (1, 2). Ziemke et al. proposed that ecological niches constructed by various electron acceptor gradients might be responsible for the distribution of S. baltica strains with different genotypes (2), and our results support their hypothesis. While the vertical gradients in average nitrate concentration the Baltic Sea should be too shallow to induce chemotaxis, the average nitrate concentration provides a background in which S. baltica populations can generate local nitrate gradients steep enough to induce chemotaxis when carbon sources become available. Strains whose genotype is ideally suited for a given background nitrate concentration would migrate most effectively into nutrientrich areas. Over many generations, even subtle competitive advantages between strains could result in a genetic stratification with depth in the Baltic Sea in response to stratification in nitrate concentration. The DGC’s ability to customize electron-acceptor concentration gradients enables the impact of differences in chemotactic properties on competition to be investigated. While our study demonstrated competition between strains having extreme differences in ability to use
nitrate (wild-type vs nitrate-reductase mutant), a similar approach could be also used with strains having more subtle differences. Recently, Harris et al. (26) reported that fumarate and other electron acceptors could increase the swimming speed of S. oneidensis MR-1 cells. Specifically, after adding fumarate, the swimming speed increased from 9.1 ( 2.1 µm/s to 38.4 ( 6.7 µm/s. Some solid electron acceptors also increased run lengths. Because random motility is a linear function of swimming speed (27), µ may not be constant across a wide range of electron acceptor concentrations. However, our simulations indicated that the S. oneidensis MR-1 migration patterns were relatively insensitive to µ under the experimental conditions tested (SI Figure 5). This trend, which has also been reported by other researchers (28), reinforces the importance of chemotaxis in understanding community-level metabolism, growth, and migration of Shewanella. This study validates the DGC system’s ability to experimentally characterize, and mathematically predict, S. oniednesis MR-1’s growth and chemotactic response under the influence of well-controlled gradients of electron acceptors. Fumarate was initially used as the electron acceptor because its high solubility and one-step reduction were ideal for demonstrating the DGC system’s capabilities. Extension of the approach to the ecologically relevant electron acceptor nitrate allowed demonstration of (a) competition and separation of Shewanella strains based on their different chemotactic responses to electronacceptor gradients, and (b) cell growth, metabolism, and chemotactic migration under conditions that inhibit cell growth in liquid culture. These results help clarify the role of chemotaxis in the microbial ecology of Shewanella species (10). Future studies will integrate Shewanella chemotaxis studies with genomic (29), transcriptomic (30), and proteomic (29) analyses to develop a systems-level understanding of how Shewanella’s versatile redox capabilities contribute to its role in environmental processes, including elemental cycling (31).
Acknowledgments The authors thank Todd Ciche (Michigan State University) for strains used for triparental mating, Margaret Romine (Pacific Northwest National Laboratories) for the S. oneidensis MR-1 ∆fccA strain, and members of the Tiedje lab for helpful discussion. This research was supported by the Office of Science (BER), U.S. Department of Energy, Grant No. DEFG02-07ER64389.
NOMENCLATURE Aarena bc CS D DS Ju KD kS N NRM q r S S0 Si St Sj0
area of membrane between arena and reservoirs of DGC initial cell density in the chamber for capillary assay half-saturation constants dilution rate diffusion coefficient cell flux receptor dissociation constant mass transfer coefficient cell accumulation with attractant in the capillary cell accumulation without attractant in the capillary specific growth rate radius of capillary fumarate concentration fumarate feeding concentration initial fumarate concentration final fumarate concentration dimensionless attractant concentrations initially present at the capillary mouth
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Sj∞ t td u ui ut Varena Y
dimensionless attractant concentrations initially present far into the capillary time doubling time cell density initial cell density final cell density volume of arena of DGC yield coefficient
Greek letters χ0 chemotaxis coefficient ν maximum specific growth rate
Supporting Information Available Additional information on schematic diagram and parameter estimation. This material is available free of charge via the Internet at http://pubs.acs.org.
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