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Journal of Bacteriology, October 2007, p. 7127-7133, Vol. 189, No. 19
0021-9193/07/$08.00+0 doi:10.1128/JB.00746-07
Copyright © 2007, American Society for Microbiology. All Rights Reserved.
Cell-to-Cell Heterogeneity in Growth Rate and Gene Expression in Methylobacterium extorquens AM1
Tim J. Strovas,1
Linda M. Sauter,2
Xiaofeng Guo,3 and
Mary E. Lidstrom2,3*
Department of Bioengineering,1
Department of Microbiology,2
Department of Chemical Engineering, Microscale Life Sciences Center, University of Washington, Seattle, Washington 98195-21803
Received 11 May 2007/
Accepted 15 July 2007

ABSTRACT
Cell-to-cell heterogeneity in gene expression and growth parameters
was assessed in the facultative methylotroph
Methylobacterium extorquens AM1. A transcriptional fusion between a well-characterized
methylotrophy promoter (
PmxaF) and
gfpuv (encoding a variant
of green fluorescent protein [GFPuv]) was used to assess single-cell
gene expression. Using a flowthrough culture system and laser
scanning microscopy, data on fluorescence and cell size were
obtained over time through several growth cycles for cells grown
on succinate or methanol. Cells were grown continuously with
no discernible lag between divisions, and high cell-to-cell
variability was observed for cell size at division (2.5-fold
range), division time, and growth rate. When individual cells
were followed over multiple division cycles, no direct correlation
was observed between the growth rate before a division and the
subsequent growth rate or between the cell size at division
and the subsequent growth rate. The cell-to-cell variability
for GFPuv fluorescence from the
PmxaF promoter was less, with
a range on the order of 1.5-fold. Fluorescence and growth rate
were also followed during a carbon shift experiment, in which
cells growing on succinate were shifted to methanol. Variability
of the response was observed, and the growth rate at the time
of the shift from succinate to methanol was a predictor of the
response. Higher growth rates at the time of the substrate shift
resulted in greater decreases in growth rates immediately after
the shift, but full induction of
PmxaF-
gfpuv was achieved faster.
These results demonstrate that in
M. extorquens, physiological
heterogeneity at the single-cell level plays an important role
in determining the population response to the metabolic shift
examined.

INTRODUCTION
A growing body of evidence shows that isogenic populations of
exponentially growing microorganisms have substantial cell-to-cell
heterogeneity at both the gene expression and growth rate levels
(
6,
9,
10,
12-
16,
19,
20,
29-
31,
36,
39). Cell-to-cell heterogeneity
in gene expression has been shown to arise from fluctuations
in the global gene expression machinery of the cell, which has
been termed "extrinsic noise," "global noise," or "gene expression
capacity" (
9,
12,
27,
29,
30). In some cases the source of the
variation has been shown to be cell-to-cell differences in transcription,
mRNA stability, and/or translation (
5,
27). Two recent studies
have also measured mRNA in individual cells (
13,
19). The results
of these studies suggest that cell-to-cell variation in gene
expression is not due to fluctuations in low-copy mRNA numbers
but rather appears to be due to variations at the bulk mRNA
stability and/or translational level.
Significant cell-to-cell variations have also been reported for generation times and growth rates. It was shown as early as 1932 that bacteria and yeast cells exhibit two- to threefold variation in individual cell division time and that the previous division time does not influence the subsequent division time; in other words, the variation appears to be stochastic (15). More recent studies with Escherichia coli found a similar range of division times (36), and studies of growth rates in yeast also found a broad range (9).
Although cell-to-cell variation in gene expression and growth rate have been suggested to generate phenotypic diversification (1, 3, 7, 17, 18, 34), very little is known concerning the connection between stochasticity in gene expression and resultant phenotypic diversity. One prediction is that gene expression might correlate with growth rate, and in the study of yeast cited above (9), a positive correlation was obtained between the output of the mating pheromone response pathway in yeast and the growth rate (increase in cell volume). However, similar studies have not yet been reported for bacteria.
Further information suggests that even minor subpopulations of bacteria in a physiological state significantly different from that of the population average (for instance, bacteria growing very slowly) can play a major role in the population response, especially under stressful conditions (1, 3, 7, 17, 18, 34). It has been suggested that cell-to-cell phenotypic heterogeneity generates physiologically distinct subpopulations that are resistant to stress (7).
We are interested in how various parts of metabolism are integrated at the transcript, protein, and flux levels in the facultative methylotroph Methylobacterium extorquens AM1. This bacterium has two strongly contrasting modes of metabolism, growth on multicarbon compounds, which is energy limited, and growth on one-carbon compounds, which is limited by reducing power (37). In addition, growth on one-carbon compounds involves high flux through the toxic intermediate formaldehyde, raising the possibility of fluctuating stress conditions (8, 24). Our studies involve perturbing the metabolic state, either by stress or by changing the growth substrate, and following the metabolic response at the global level. Therefore, in this system it is important to understand cellular heterogeneity within the populations and ultimately to link the physiological state to the phenotypic response. In this study, we began to characterize heterogeneity at the individual cell level in M. extorquens AM1 by simultaneously monitoring expression of a variant of green fluorescent protein (GFPuv) from a well-characterized methylotrophy promoter (PmxaF) (21, 40) and measuring the change in cell size over time in a flowthrough system coupled to a laser scanning microscope. We monitored these parameters both in stable growth conditions and during the response to a change in substrate from a multicarbon compound (succinate) to a one-carbon compound (methanol).

MATERIALS AND METHODS
Bacterial strains and growth conditions.
M. extorquens AM1 strains were grown in batch culture at 28°C
in minimal salts media supplemented with either 0.3% (vol/vol)
methanol or 0.4% succinate as a growth substrate (
2,
38). The
strains and plasmids used for this study are listed in Table
1. When appropriate, antibiotics were added (50 µg/ml
rifamycin and 10 µg/ml tetracycline).
Construction of vectors for deletion of flagellar gene clusters.
Allelic exchange vectors were constructed from pCM184 (
22).
Fragments (

600 bp) flanking the
motA-
fliN-
fliM-
fliG,
motC-
motB,
and
pomA-
motB flagellar gene clusters were PCR amplified and
inserted into pCR2.1 (Invitrogen, Carlsbad, CA) to make pXG1,
pXG2, pTS63, pTS64, pTS67, and pTS68. The
motA-fliN-fliM-fliG mutant insertion vector was generated by inserting the

560-bp
BglII-NdeI upstream fragment from pXG1 into pCM184 to make pXG3.
The

600-bp SacI-SacII downstream fragment from pXG2 was inserted
into pXG3 to make pXG4. The
motC-motB mutant insertion vector
was constructed by inserting the

630-bp BglII-NotI upstream
fragment from pTS63 into pCM184 to make pTS65 and then inserting
the

630-bp ApaI/SacI downstream fragment from pTS64 into pTS65
to make pTS66. The
pomA-
motB mutant insertion vector was made
by inserting the

740-bp upstream fragment from pTS67 into pCM184
to make pTS69 and then inserting the

670-bp downstream fragment
from pTS68 into pTS69 to make pTS70.
Construction of the nonmotile mutant TSX.
Using the insertion vectors described above (pXG4, pTS66, and pTS70), flagellar gene cluster mutations were sequentially introduced by electroporation (35) into M. extorquens AM1 and screening for kanamycin resistance (33 µg/ml) and tetracycline sensitivity (22). All mutations were confirmed by PCR analysis. Antibiotic markers in mutants were removed using the cre-lox system with pCM157 as described previously (22, 23). The motility of M. extorquens AM1 strain TSX was assessed by visual observation with a Zeiss Axioplan microscope using a 100x 1.3 N.A. objective (Thornwood, NY). The first two constructions were motile (TS66 and TS70), while the final construction (TSX) showed no detectable motility.
Fluorimetry analysis.
Fluorescence measurements were carried out with a Shimadzu RF-5301PC fluorimeter (Columbia, MD). GFPuv excitation was performed at 405 nm, and emission was monitored at 509 nm with excitation-emission slit widths of 5:5.
Flow system setup for microscopy.
A continuous-flow system was assembled to facilitate microscope experiments (Fig. 1).
(i) Design.
The tubing and adapters used were all obtained from Upchurch
Scientific (Oak Harbor, WA). All tubing used was PEEK tubing
(outside diameter, 1/16 in.; inside diameter, 0.75 mm). One-liter
Pyrex bottles were used for a medium reservoir and waste. The
bottle caps for the reservoir and waste were modified to house
a 0.2-µm syringe filter and to accommodate the intake
or output lines. The intake line was weighted with an inline
solvent filter housing to ensure that the intake stayed submerged.
Fluid control was conducted with a Global FIA Milligat pump
(Fox Island, WA) controlled using LabView (National Instruments,
Austin, TX). A gas equilibration system was constructed to equilibrate
the medium with air before it entered the culture chamber. This
system consisted of a 250-ml Pyrex bottle with a modified cap
that had four holes drilled into it. Two holes housed the inlet
and outlet lines, and the other two holes allowed the interior
of the bottle to stay equilibrated with atmospheric gases. The
inlet and outlet lines were connected to 50 ft of silastic tubing
(inside diameter, 0.51 mm; outside diameter, 0.94 mm; VWR, West
Chester, PA) within the Pyrex bottle. A luer inline check valve
was used for injection of cell samples into the culture chamber.
A Bioptechs FCS2 closed system chamber (Butler, PA) was used
for cell culturing, with a 0.5-mm gasket generating a volume
of 350 µl. For carbon shift experiments, a 0.5-cm channel
was cut into a solid 0.5-mm gasket to reduce mixing of medium
containing the two substrates. For all experiments, the coverslip
for the FCS2 chamber was treated with a 0.01% (wt/vol) poly-
L-lysine
solution (Sigma Aldrich, St. Louis, MO) so that cells could
be anchored in place by their flagella (
4). The slides were
immersed in the solution for 10 min and allowed to cure in air
at 37°C for 1 h. The temperature of the medium prior to
entry into the culture chamber was controlled by immersion of
the medium reservoir and gas equilibration system in a water
bath. The temperature of the FCS2 chamber was maintained with
an objective heater and a chamber heater (Bioptechs, Butler,
PA). For carbon shift experiments, two sets of a medium reservoir,
a pump, and a gas equilibration system were connected to the
rest of the flow system using a four-port switch valve.
(ii) System preparation and maintenance.
Prior to experiments, the flow system was primed by flowing medium at a rate of 10 µl/s for 30 min to eliminate any air bubbles. All experiments were conducted at a flow rate of 1 µl/s. For cleaning and sterilization, the system was flushed with 10% hypochlorite for 30 min, followed by distilled H2O for at least 2 h, all at a flow rate of 10 µl/s. The entire flow system was then autoclaved.
Microscopy.
Microscopy experiments were conducted with a Zeiss LSM 510 META using a 100x 1.45 N.A. objective (Thornwood, NY). All experiments were conducted using minimal medium supplemented with rifamycin and a carbon source. Cells were injected into the FCS2 chamber and allowed to settle onto the poly-L-lysine-treated glass slide for 10 min. Once the cells were attached, 10 to 15 locations were marked using the microscope's software and monitored for the duration of the experiment. GFPuv excitation was obtained with a 488-nm argon laser at 1% power, and emissions were detected through a 505-nm longpass filter in channel 3. For analysis of growth, images were acquired every 10 min. However, for observation of the amount of fluorescence per cell, images were taken every 30 min at 1% laser power to minimize photobleaching effects. Microscope experiments were conducted for up to 96 h. The Zeiss LSM 510 META imaging software (version 3.2, SP2) was used for image analysis, and data were imported into Excel.

RESULTS
Flowthrough system to observe individual tethered cells.
To microscopically observe single cells of
M. extorquens AM1
growing on methanol or succinate, a flowthrough culture system
for the Zeiss LSM 510 META microscope was designed and set up
as described in Materials and Methods. To facilitate long-term
observations of large numbers of individual cells in this flowthrough
system, cells were attached to a poly-
L-lysine-coated glass
slide by their polar flagella. A nonmotile mutant was necessary
to facilitate long-term observations. This
M. extorquens AM1
mutant (TSXCM174) was constructed by deleting three clusters
of genes required for the flagellum motor function. This strain
could not be distinguished from the corresponding motile strain
in bulk culture based on the growth rate, dynamics of the growth
curve, and gene expression from the
mxaF promoter-
gfpuv fusion
(
23) used in this study (data not shown). In the flowthrough
system, attached cells were observed over several division times,
and after division, the daughter cells were swept away by the
flow before they could attach. Using this system, it was possible
to monitor the length of time between cell divisions, the size
of the cells over time (growth rate), and the GFPuv fluorescence
intensity at each time point for actively growing individual
attached cells. Under these growth conditions with methanol
or succinate as a carbon source, cells grew well and showed
no discernible lag between divisions.
Distribution of cell doubling times.
To determine the range and distribution of cell doubling times, cells were observed in the flowthrough growth system during growth with either succinate or methanol. In many cases, cells were observed for multiple divisions. The time between divisions was determined, and the data are expressed in Fig. 2 as doubling times. The variability was high, ranging from 2.5- to 2.6-fold, respectively, for the two growth conditions. The doubling times ranged between 1.9 and 4.6 h on succinate (mean doubling time, 3.12 ± 0.55 h) and between 2.6 and 6.6 h on methanol (mean doubling time, 3.73 ± 0.63 h). These means are significantly lower than those obtained for batch cultures (
4 and
5.5 h, respectively). From the data available, the distribution of division rates did not appear to follow either a Gaussian or lognormal distribution; rather, a more random pattern was observed (Fig. 2). The cells with the longest and shortest generation times made up a few percent of the total population.
Distribution of cell size and growth rates.
Growth dynamics was monitored for a group of individual tethered
cells for a length of time sufficient for multiple consecutive
divisions, and cell size was monitored as a function of time.
For individual cells followed over multiple divisions, significant
variability was observed for cell length before and after each
division, for the growth rate (increase in length over time)
between divisions, and for the duration of time between the
divisions. There was no obvious correlation between the size
of a cell at the time of division and the subsequent growth
rate or between previous and subsequent growth rates (data not
shown). Figure
3 shows an example of one such set of results.
A cell was followed over several growth periods and divisions,
and significant variability was observed from one division to
the next in terms of cell size at the time of division and growth
rate. For example, the growth rate in growth period B was 33%
higher than the growth rate in the previous growth period, growth
period A. In addition, the cell length at the time of division
preceding growth period A was 20% greater than the cell length
at the end of growth period A.
Distribution of fluorescence from promoter-GFPuv fusion.
In order to analyze gene expression from a promoter of interest,
a transcriptional fusion between a well-characterized methylotrophy
promoter,
PmxaF (the promoter for the methanol dehydrogenase
operon), and
gfpuv (
23) was inserted into the chromosome of
the nonmotile strain in a standard insertion site for this organism
(see Materials and Methods). The intensity of GFPuv-based fluorescent
emissions (in relative fluorescence units [RFU]) from single
cells containing this
PmxaF-
gfpuv fusion was measured in both
succinate- and methanol-grown cells, normalized to cell size,
and expressed in RFU/µm
2 (average RFU/pixel of a whole
cell). The fluorescence intensity per µm
2 of individual
cells was variable for cells from both growth conditions (1.6-
and 1.7-fold, respectively), but the variability was not as
great as that of the growth rate. Calculated using approximately
1,000 cells, the mean relative fluorescence for a cell grown
on succinate was 1,993 ± 468 RFU/µm
2, with a range
of 1,202 to 2,084 RFU/µm
2, and the mean relative fluorescence
for a cell grown on methanol was 3,075 ± 243 RFU/µm
2,
with a range of 1,649 to 2,610 RFU/µm
2. These means are
similar to previous results showing that the difference in expression
of the promoter in succinate- and methanol-grown bulk cultures
is about 1.5- to 2-fold (
21,
40).
Relationship of fluorescence to growth rate and cell size.
In order to determine whether fluorescence resulting from expression from the mxaF promoter correlated with growth rate or cell size, these parameters were measured for individual cells with a single data set from experiments in which cells were grown in the flowthrough system either on methanol or on succinate. The data collected from 25 individual cells at different time points are shown in Fig. 4. When RFU/µm2 was plotted against these two parameters, no correlation was observed for either parameter for methanol-grown cells. For succinate-grown cells, no correlation was observed for growth rate, but a small positive correlation (R2 = 0.26) was found for cell size.
Response during carbon shift.
In order to assess whether variability in gene expression and/or
growth rate influenced the response of individual cells during
the transition from succinate growth to methanol growth, these
parameters were measured for individual cells during a shift
from succinate to methanol as the growth substrate. Relative
fluorescence as a function of time was observed for approximately
1,000 random cells in each experiment for up to 20 h before
the shift and for up to 20 h after the shift, and 25 individual
cells were followed throughout the transition. The data from
one of the succinate-to-methanol shift experiments are shown
in Fig.
5. The range for the amount of fluorescence per µm
2 in individual cells was about 1.6-fold both before and after
the shift (Fig.
5A). However, when the dynamics of individual
cells were tracked throughout the experiment, the patterns of
these cells also showed significant variability during the experiment,
both before and after the shift (Fig.
5B). Variability was observed
not only in the patterns of fluorescence with time but also
in the total increase in fluorescence of the
mxaF promoter and
in the time required to achieve full induction. While fluorescence
emissions from individual cells were variable, the difference
in intensity between succinate and methanol growth could be
easily discerned and was in keeping with the earlier results
from batch cultures (
21,
40).
The growth rate was also measured for the same 25 cells described
above immediately before the shift, immediately after the shift,
and throughout the remainder of the postshift adaptation period.
Again, significant variability was observed for individual cells,
and the range was on the order of twofold for this data set.
Immediately after the shift, all cells showed a change in growth
rate, and the magnitude of the change was also variable.
The data set for these 25 cells undergoing the transition from succinate to methanol was analyzed for correlations with regard to the following parameters: growth rates and RFU/µm2 immediately before and after the shift, change in growth rate immediately after the shift, total increase in fluorescence after the shift, and the time until the cells exhibited full induction of PmxaF-gfpuv. Each of these variables was compared to each of the other variables to assess correlations and trends. Only two trends were observed (Fig. 6). Cells growing faster before the switch to methanol achieved full induction of the mxaF promoter faster than more slowly growing cells (Fig. 6A), and the cells that showed faster induction were also the cells that exhibited a greater decline in growth rate immediately after the carbon shift (Fig. 6B). These trends suggested that the cells growing faster before the switch should exhibit a greater decline in growth rate immediately after the carbon shift, and this correlation was confirmed (Fig. 6C).

DISCUSSION
In this study, cell-to-cell heterogeneity was assessed in
M. extorquens AM1 by comparing expression from a promoter-
gfpuv fusion to growth parameters. A flowthrough system was designed
to grow cells in a culture chamber placed under a microscope
to allow acquisition of data for individual cells over multiple
divisions. Most single-cell analyses to date have involved cells
imbedded in soft agar (
3,
15,
25,
32), which involves microcolony
formation and the possible development of chemical and physical
gradients. Such environmental heterogeneity might alter intrinsic
biological heterogeneity. The system used in this study involving
a commercial flowthrough chamber, attachment by flagella, and
a nonmotile mutant allows observation of individual cells maintained
in a constant environment. In this system, cells grew significantly
faster than cells in batch cultures, with mean growth rates
that were on the order of 25 to 35% greater, especially during
growth on methanol. Although the reason for this is not known,
the flowthrough system does not allow buildup of wastes or cell
signaling molecules, which could contribute to this difference.
Other parameters measured in this system correlated well with
population-based culture data when population means were calculated
from the single-cell data, including fluorescence per cell from
the
PmxaF-
gfpuv fusion, magnitude of induction of the promoter
as measured by fluorescence, and time for induction after the
shift from succinate to methanol. These results suggest that
this single-cell analysis system generates response results
comparable to those of population-based culture systems.
It has previously been reported for E. coli that both growth rate and gene expression are highly variable between cells in isogenic populations (10, 13, 15, 16, 19, 20, 29, 36, 39). We have confirmed a similar level of cell-to-cell heterogeneity for both growth characteristics and expression from the PmxaF-gfpuv fusion for a more slowly growing bacterium, M. extorquens AM1, using the flowthrough system noted above. As described previously for division times in bacteria (15), no correlation was obtained between a specific division time and the next division time. In addition, we found no correlation between cell size at the time of division and the immediately previous or subsequent division time or growth rate or between growth rate and the immediately previous or subsequent division time or growth rate. Such results are consistent with suggestions from studies cited above that the variability results from stochastic processes in the cell.
This experimental system allowed assessment of correlations between expression of the mxaF promoter, as judged by the GFPuv reporter, and growth parameters. Several studies have suggested that cell-to-cell variations in gene expression are the result of extrinsic noise, that is, variations in gene expression capacity between cells (11, 27, 29, 30). However, the sources of cell-to-cell variations in growth rate are not known. If these variations were due to cell-to-cell variations in gene expression capacity, then a correlation would be expected between growth rate and gene expression, as measured by the gfpuv reporter construct. For instance, a cell with higher-than-average gene expression might be expected to also exhibit a higher-than-average growth rate, as noted in a previous study with yeast (9). However, no such correlation was obtained in our study, suggesting that in M. extorquens AM1, the mechanisms generating heterogeneity in expression of the gfpuv reporter fusion and growth rate are different. If growth rate is not controlled by overall gene expression capacity, other possibilities are functions such as energy metabolism rate or cell pool parameters, such as the NADH/NAD+ ratio, the energy charge, amino acid pool levels, etc.
The existence of physiological heterogeneity predicts that individual cells in a population will respond differently to the same environmental perturbation, depending on their physiological state at the time of the perturbation. In such a case, the population average would not capture the true response at the cellular level. In order to test this hypothesis directly in M. extorquens AM1, we used the flowthrough system to monitor individual cells during the metabolic transition from succinate growth to methanol growth. In M. extorquens AM1, a shift from multicarbon compounds to one-carbon compounds results in a major change in metabolism; there is a shift from energy limitation to reducing power limitation, with over 100 genes involved in methylotrophy (8, 37). Therefore, at the individual cell level this transition might be expected to depend on parameters such as growth rate and gene expression. Under these conditions, we found that the faster-growing cells had an advantage. A trend was observed in which the faster-growing cells showed the greatest drop in growth rate immediately after the switch, suggesting that they were the most stressed. The same cells also recovered fastest and induced the mxaF promoter the maximum amount in the shortest time.
These results are in contrast to the example of antibiotic persistence in E. coli, in which the mostly slowly growing cells have an advantage over the faster-growing cells. However, with antibiotic persistence, most of the cells in the population die, and the slowly growing cells continue to grow slowly for multiple generations (3). In the perturbation described here, viability is maintained and growth is affected only transiently. Under these conditions it is likely that more rapid growth poises the cells to respond more quickly. During the transition to growth on methanol, cultures not only experience transient starvation but also accumulate formaldehyde due to an initial imbalance between the formaldehyde production and consumption fluxes (8, 24). Thus, it would be expected that faster-growing cells would metabolize more rapidly and would experience a greater initial drop in the growth rate from more rapid starvation or formaldehyde accumulation or both. However, these cells would also be poised to recover most quickly, by rapidly inducing methylotrophic pathways and thus allowing formaldehyde detoxification as well as energy extraction and biosynthesis from methanol. As technology to study both gene expression and physiological parameters in large numbers of single cells expands, it should be possible to test this hypothesis to determine the underlying causes for the behavior of individual cells during this transition. However, these results demonstrate that the preexisting physiological state of individual M. extorquens cells does dictate a differential response to a shift from multicarbon to methylotrophic growth.
Simulations predict that physiological heterogeneity is an important selective factor for populations subjected to intermittent environmental change (17, 18). Methylobacterium strains live on the surface of leaves, utilizing methanol emitted by stomata (33), and can also be found in freshwater and soil environments. These environments are characterized by highly fluctuating methanol concentrations (26), and it is possible that the heterogeneity of response demonstrated in this study contributes to the success of natural populations of Methylobacterium under these conditions.

ACKNOWLEDGMENTS
We thank Joseph Chao for assistance with microscopy and Deirdre
Meldrum for use of facilities.
This work was supported by grant P50 HG02360 from NHGRI for a Center of Excellence in Genomic Sciences.

FOOTNOTES
* Corresponding author. Mailing address: Department of Chemical Engineering, University of Washington, Box 352125, Seattle, WA 98195. Phone: (206) 616-5282. Fax: (206) 616-5721. E-mail:
lidstrom{at}u.washington.edu 
Published ahead of print on 20 July 2007. 

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Journal of Bacteriology, October 2007, p. 7127-7133, Vol. 189, No. 19
0021-9193/07/$08.00+0 doi:10.1128/JB.00746-07
Copyright © 2007, American Society for Microbiology. All Rights Reserved.
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