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Applied and Environmental Microbiology, December 1999, p. 5322-5327, Vol. 65, No. 12
0099-2240/99/$04.00+0
Copyright © 1999, American Society for Microbiology. All rights reserved.
Characterization of Unexpected Growth of
Escherichia coli O157:H7 by Modeling
Marie
Cornu,1,*
Marie Laure
Delignette-Muller,2 and
Jean-Pierre
Flandrois1
CNRS UMR 5558, Laboratoire de
Bactériologie, Faculté de Médecine Lyon Sud, 69921 Oullins Cedex,1 and Laboratoire
d'Ecologie Microbienne et Parasitaire, Ecole Nationale
Vétérinaire de Lyon, 69 280 Marcy
l'Etoile,2 France
Received 29 March 1999/Accepted 15 September 1999
 |
ABSTRACT |
Modeling of batch kinetics in minimal synthetic medium was used to
characterize Escherichia coli O157:H7 growth, which
appeared to be different from the exponential growth expected in
minimal synthetic medium and observed for E. coli K-12. The
turbidimetric kinetics of 14 of the 15 O157:H7 strains tested (93%)
were nonexponential, whereas 25 of the 36 other E. coli
strains tested (70%) exhibited exponential kinetics. Moreover, the
anomaly was almost corrected when the minimal medium was supplemented
with methionine. These observations were confirmed with two reference
strains by using plate count monitoring. In mixed cultures, E. coli K-12 had a positive effect on E. coli O157:H7
and corrected its growth anomaly. This demonstrated that commensalism
occurred, as the growth curve for E. coli K-12 was not
affected. The interaction could be explained by an exchange of
methionine, as the effect of E. coli K-12 on E. coli O157:H7 appeared to be similar to the effect of methionine.
 |
INTRODUCTION |
Infections due to enterohemorrhagic
Escherichia coli, particularly E. coli O157:H7,
are now considered a major public health problem of worldwide
importance. Serotype O157:H7 was first identified as a human pathogen
during an epidemiological investigation of two outbreaks of hemorrhagic
colitis in North America in 1982 (23). Since the early
1980s, this serotype has been implicated in numerous outbreaks of
hemorrhagic colitis and hemolytic uremic syndrome. The sources of
infection of humans by E. coli O157:H7 include consumption
of undercooked bovine food products and other uncooked foods, water,
and direct animal-to-person or person-to-person contact (1, 11,
27).
In the 1990s modeling of E. coli O157:H7 growth has been an
active area of research (9, 26, 28). For all food-borne pathogens, the recent developments in modeling have been based on
better mathematical descriptions of the growth curves in closed liquid
media (batch cultures) (2, 5, 24) and on a comprehensive understanding of the relationship between growth parameters and the
physicochemical environment (22, 25).
Application of somewhat theoretical knowledge to predictive analyses of
the development of microbial floras has given workers the opportunity
to predict the growth of bacteria and fungi in food matrices, and the
correspondence between predicted and observed kinetics has been good.
Models have been used in simulation software to determine the shelf
life of a product (8, 15, 16). However, there are some
limitations in so-called predictive microbiology; the structure and
heterogeneity of the alimentary matrix, as well as the possible
interactions of food-borne pathogens with technological or natural
spoilage flora, are poorly taken into account in the models. More
generally, batch growth modeling has been widely used for applied
objectives, but a more fundamental approach has not been taken. For
instance, data concerning the effects of bacterial interactions on
bacterial growth, which is a well-established phenomenon in continuous
cultures (4, 13, 14, 21), are limited for batch cultures
(6, 20).
Modeling of batch kinetics appears to be a promising and underexploited
way to examine growth from a physiological point of view. In this
study, the kinetics of E. coli O157:H7 growth were examined
by using minimal synthetic medium. The choice of this minimal medium,
in which all of the components were chemically defined and the only
limiting substrate was the carbon source, rather than a complex medium
(complex media are usually used as representative of foods),
illustrates our orientation towards a physiological approach rather
than an applied approach. Different monitoring and statistical tools
were used to characterize growth.
Biomass was monitored by turbidimetry; an automated system enabled us
to study 15 E. coli O157:H7 strains and 36 other E. coli strains in parallel. A dynamic study of turbidimetric
kinetics resulted in characterization of the growing phases of these
strains and to quantification of the effect of methionine on growth.
Using plate count monitoring of the viable population, we confirmed that growth of E. coli O157:H7 was different from growth of
E. coli K-12 and was improved by methionine. This method
also allowed us to study a mixed culture of E. coli K-12 and
E. coli O157:H7, and the results revealed that there is an
interaction between E. coli O157:H7 and E. coli
K-12.
 |
MATERIALS AND METHODS |
Turbidimetric growth curves for pure cultures. (i) Bacterial
strains.
A total of 51 E. coli strains were used; these
strains included 15 O157:H7 strains and 36 non-O157:H7 strains. The
non-O157:H7 strains were chosen on the basis of ecological criteria or
virulence factors; we used five reference strains (including one O55:H7 strain), 13 nonverocytotoxic feces isolates, and 18 verocytotoxic SLT1+eae1+ isolates. Strains were checked for
the presence of O157 antigen by using the VIDAS System
(bioMérieux, Marcy l'Etoile, France) and for the presence of H7
antigen by using an in situ hybridization system. Details are shown in
Table 1.
All bacterial stock cultures were maintained at

196°C in brain
heart infusion broth (bioMérieux) containing 10%
glycerol.
(ii) Minimal synthetic medium.
The medium used in the
experiments was the minimal medium designed by Neidhardt et al.
(18) supplemented with thiamine. It contained (per liter)
8.372 g of MOPS (morpholinepropanesulfonic acid), 2.922 g of NaCl,
0.71668 g of Tricine, 0.5082 g of NH4Cl, 0.23 g of
K2HPO4 · 3H2O, 0.11 g
of C6H12O6 · H2O, 0.107348 g of MgCl2 · 6H2O, 0.0481 g of K2SO4, 0.01 g of thiamine, 7.351 mg of CaCl2 · 2H2O,
2.78 mg of FeSO4 · 7H2O, 0.0247 mg of
H3BO3, 0.0158 mg of MnCl2 · 4H2O, 0.0071 mg of CoCl2 · 6H2O, 0.0037 mg of
(NH4)6MO7O24 · 4H2O, 0.0029 mg of ZnSO4 · 7 H2O, and
0.0016 mg of CuSO4. This medium was designated Neidhardt medium.
(iii) Characterizing the growth phase in minimal synthetic
medium.
Prior to an experiment, each bacterial strain was grown
twice on Columbia sheep blood agar at 35°C for 24 h in order to
obtain cells in the stationary phase of growth. Suspensions obtained from the resulting precultures were standardized with a nephelometer (model ATB 1550; bioMérieux) to a no. 1 MacFarland standard and then diluted 10
2.
An MS2 Research system (Abbot Laboratories, Dallas, Tex.) was
used to monitor growth continuously. This automated system can
process
16 11-growth-chamber cartridges. Each growth chamber contained
1 ml of
Neidhardt medium inoculated with 100 µl of a bacterial
suspension.
The cartridges were inserted into the system and maintained
for 24 h at 37°C; there was constant agitation between measurements.
Transmission was measured at 5-min intervals, and evolution of
absorbance was calculated from the resulting data (
10). For
graphical representations, growth curves were smoothed by using
the
ExponentialSmoothing procedure of Mathematica (Wolfram Research,
Inc.).
To determine an approximate instantaneous growth rate, the specific
absorbance rate (µ) was calculated with the following
formula:
|
(1)
|
where µ (
tn) is the specific absorbance
rate (per hour) at time
tn and
yn is the measured absorbance at
tn.
To check the hypothesis that the instantaneous µ does not increase at
the end of the so-called exponential phase, a unilateral
t
test was performed. This test was used to determine whether
the slope
of the linear regression (µ versus time) was zero or
significantly
positive between a technical threshold (when the
measured absorbance
reached 0.005) and deceleration (obviously
detected by a swift decrease
in µ) (i.e., in the last phases of
growth).
(iv) Quantifying the effect of methionine.
To quantify the
effect of methionine for each strain, we compared two growth curves
(one determined with Neidhardt medium and one determined with Neidhardt
medium supplemented with 100 mg of methionine per liter) resulting from
identical inocula. The difference between the time when the growing
phase ended in the minimal medium and the time when the growing phase
ended in the supplemented medium was then determined and expressed as a percentage of the length of the growing phase in minimal medium.
Plate count growth curves for pure and mixed cultures. (i)
Bacterial strains.
Two reference strains, E. coli K-12
strain NC 4100 and E. coli O157:H7 strain ATCC 33150, were
used in this study. Cultures were stored at
196°C in brain heart
infusion (bioMérieux) supplemented with 10% glycerol.
(ii) Inoculum preparation.
Prior to each experiment, the
bacterial strains were grown on Columbia sheep blood agar
(bioMérieux) at 35°C for 24 h and then in Neidhardt medium
at 37°C with turbidimetric growth monitoring (the growth conditions
used are described above). The resulting precultures were stopped
either in the early exponential phase (i.e., when the absorbance had
increased 0.01) or in the stationary phase (4 ± 1 h after
the end of growth) and then used to inoculate the experimental
cultures. Thus, the inocula used for the main cultures could be in two
different initial physiological states; they contained either growing
cells (preculture stopped in the early exponential phase) or resting
cells (preculture stopped in the stationary phase).
(iii) Growth conditions.
Each 250-ml Erlenmeyer flask
contained 200 ml of Neidhardt medium. Spinal needles (Becton Dickinson,
San Jose, Calif.) in the caps of the flasks allowed us to inoculate the
medium and retrieve samples under sterile conditions. The flasks were
incubated in thermostat-controlled water baths (the temperature was
regulated at 37 ± 0.1°C), and the medium was aerated by using a
magnetic stirrer.
(iv) Growth monitoring.
At each sampling time (every 30 min
for each culture), the number of viable cells was determined by plating
two 0.1-ml portions of appropriate dilutions of the sample onto
MacConkey agar (Oxoid, Basingstoke, England) containing sorbitol.
We checked whether this medium could be used to distinguish between the
two strains since only
E. coli K-12 ferments sorbitol,
and
we found that it does not inhibit growth. The plate counts
on MacConkey
Agar (Oxoid) containing sorbitol were not different
from the plate
counts on Columbia sheep blood agar (bioMérieux).
(v) Experimental design.
We performed an experiment to
confirm previously described results. Two cultures were grown in
parallel, one in minimal medium and the other in minimal medium
supplemented with 100 mg of methionine per liter. Each culture was
inoculated with 0.5 ml of a preculture of E. coli O157:H7 in
the stationary phase.
For the main experiments we carried out three parallel cultures, a pure
culture of
E. coli K-12, a pure culture of
E. coli O157:H7, and a mixed culture. We performed eight main
experiments,
including two replicates for each of the four combinations
of
possible initial physiological states for
E. coli K-12
and
E. coli O157:H7.
Three flasks were used for each main experiment. The first flask was
inoculated with x milliliters an
E. coli K-12 preculture,
the second flask was inoculated with y milliliters of an
E. coli O157:H7 preculture, and the third flask was inoculated with x
milliliters of an
E. coli K-12 preculture and y milliliters
of
an
E. coli O157:H7 preculture. The population sizes in
the precultures
were determined, and x and y were chosen so that the
initial population
contained 10
4 to 10
5 CFU/ml;
x and y were between 0.5 and 10. Each mixed-culture experiment
was
carried out with two parallel control pure
cultures.
(vi) Growth models.
The data obtained were then analyzed.
The final data obtained (in the stationary phase) were not included so
that only growth was examined.
Two growth models were used in this study. The first model (which
included a lag phase and an exponential phase) was a three-parameter
model:
|
(2)
|
where
x is the number of CFU per milliliter,
x0 is the initial number of CFU per milliliter,
t is the time (hours), lag is
the lag time (hours), and µ is the growth rate (per
hour).
The lag phase was the period during which the growth rate was zero; the
transition to the exponential phase was then supposed
to be
instantaneous. There are different ways to describe acceleration
more
precisely (
2,
29), but our simple model was sufficient
when
the monitoring period was 30 min long. Moreover, it had the
advantage
that it allowed testing of the nullity of the lag time
by comparing
equation 2 and a two-parameter model without a lag
phase:
|
(3)
|
An F test based on the likelihood ratio (
3) confirmed
for both strains that equation 3 was sufficient for a growing-cell
inoculum but that equation 2 was necessary for a resting-cells
inoculum. It has been known since the 1950s that the lag time
is zero
if the inoculum is obtained in the exponential phase (
17).
Eventually, the hypothesis that a strain in a particular experiment has
the same growth parameters in a pure culture and in
a mixed culture (or
in minimal medium and in medium supplemented
with methionine) was
tested by performing an F test based on the
likelihood ratio
(
3). A model common to the two growth curves
obtained in one
experiment was fitted. The equality of µ and lag
was tested by
comparing a full model (µ
p and
lag
p in pure culture; µ
m and
lag
m in a mixed culture or a
culture
supplemented with methionine) to a partial model (with
the constraints
µ
p = µ
m and
lag
p = lag
m). We
assumed
that
x0 for the pure culture and
x0 for the mixed culture
were the same (the
methods used resulted in sufficient repeatability
of the initial
concentration of one strain). These analyses were
performed by using
Mathematica (Wolfram Research, Inc.), and the
risk factor

used for
the F tests was 5%.
(vii) Evaluation of fit.
For each model, the quality of the
fit was visually evaluated by examining superimposed data sets and
theoretical growth curves. The autocorrelation and the
heteroscedasticity in the distribution of the residual values were
examined on the graphs of residual values versus time.
 |
RESULTS |
Characterization of E. coli turbidimetric
kinetics.
We investigated the growth of 15 O157:H7 strains by
monitoring the changes in absorbance. The growth did not appear to be exponential. µ, which theoretically is supposed to be constant according to the exponential-phase hypothesis, obviously varied during
growth. The detection limit of the method did not allow us to detect an
obvious decrease in µ at the beginning of growth, but an increase in µ at the end of growth was clearly observed (Fig.
1). A t test was performed for
the slope of µ versus time. For 94% of the strains tested (14 of 15 strains), this test indicated that there was a significant increase in µ at the end of growth (Table 1).

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FIG. 1.
E. coli O157:H7 nonexponential growing
phases, showing the effect of methionine. (a) Strain 40. (b) Strain 42. (Upper graphs) The solid line is the smoothed turbidimetric growth
curve obtained with minimal synthetic medium; the dotted line is the
smoothed turbidimetric growth curve obtained with medium supplemented
with methionine. (Lower graphs) µ, calculated from smoothed data.
|
|
The observed variations in the instantaneous µ for most O157:H7
strains were all the more unexpected since such variations
were not
observed for most non-O157:H7 strains. Of 36 non-O157:H7
strains, 25 (70%) exhibited exponential growth until a swift transition
to the
stationary phase characterized by a sharp decrease in µ
(Fig.
2). For these 25 strains, µ did not
significantly increase
at the end of growth (Table
1). The kinetics of
the 11 other
strains were similar to those of
E. coli
O157:H7.

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FIG. 2.
E. coli non-O157:H7 exponential growing
phases. (a) Strain 13. (b) Strain 17. (Upper graphs) Smoothed
turbidimetric growth curves in minimal synthetic medium. (Lower graphs)
µ, calculated from smoothed data.
|
|
Since such an anomaly had never been detected in complex medium,
different modifications of the minimal synthetic medium were
examined.
In particular, the medium was supplemented with different
mixtures of
the 18 essential amino acids. We found that methionine
had a positive
effect on the growth of
E. coli O157:H7 strain
ATCC 33150 (data not
shown).
For each strain that exhibited nonexponential growth, the effect of
methionine was quantified by determining the difference
between the
length of the growing phase in minimal medium and
the length of the
growing phase in medium supplemented with methionine
expressed as a
percentage. Table
1 clearly shows that the effect
of methionine was
greater for serotype O157:H7 strains than for
other
E. coli
strains. Both a significant growth anomaly (
P <
0.05)
and a methionine effect greater than 5% were observed for
93% (14 of
15) of the O157:H7 strains, 22% (4 of 18) of the verocytotoxic
non-O157:H7 strains, 8% (1 of 13) of the nonverocytotoxic feces
isolates, and none of the reference
strains.
Modeling of E. coli plate count kinetics.
Using
plate count monitoring, we confirmed the results obtained with
turbidimetric monitoring and investigated mixed cultures of E. coli K-12 and E. coli O157:H7.
We performed an experiment to determine the effect of methionine with
plate count monitoring. The growth of
E. coli O157:H7
in
minimal medium supplemented with methionine appeared to be
faster than
the growth in minimal medium and closer to the expected
exponential
growth (Fig.
3). An F test comparison of
a full model
(µ
p and
lag
p in pure culture; and
µ
m and lag
m with
methionine) and a partial model (with the
constraints
µ
p = µ
m and
lag
m) led us to reject the hypothesis
that
µ
p was equal to µ
m
and lag
p was equal to
lag
m (
P = 7 × 10
5).

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FIG. 3.
Comparison of growth curves for E. coli
O157:H7 strain ATCC 33150 obtained with and without methionine (resting
cell inoculum). Solid circles, minimal medium; shaded circles, medium
supplemented with methionine; lines, fitted models.
|
|
Another model was fitted to the same pair of growth curves by using the
following assumptions: the inocula were equal
(
x0p =
x0m) and the lag times
were equal (lag
m = lag
m);
exponential growth occurred with
methionine (at constant growth
rate µ
m); and
triphasic growth occurred in pure cultures
(first and last phases at
growth rate µ
m and no growth
in the
intermediary phase). This model fit the data well (Fig.
3) and was
statistically the best model
tested.
The eight main experiments were carried out to characterize the growth
of the two strains separately and together. In order
to detect any
interaction between the two populations in mixed
cultures, the
experiment was designed so that we could rigorously
compare the growth
of each strain in pure culture and in a mixed
culture by examining the
growth
parameters.
Equations
2 and
3 were fitted to the eight growth curves for
E. coli K-12 pure cultures. In all cases, the graphs obtained
(residues and growth curves) proved that the exponential models
(with
or without a lag phase) were relevant. Then the growth curves
for pure
cultures were compared to the growth curves for mixed
cultures. In each
main experiment, the two curves obtained for
E. coli K-12
could obviously be superimposed. There was not a
significant difference
between growth parameters for any pair
of growth curves (Table
2). Thus, the growth parameters of
E. coli K-12 were not significantly modified by the presence
of
E. coli O157:H7 in the same medium, whatever the
physiological states
of the two inocula (Fig.
4).

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FIG. 4.
Comparison of mixed and pure cultures of E. coli K-12 strain NC4100. (a) Growing cell inoculum. (b) Resting
cell inoculum. Solid circles, pure culture; shaded circles, mixed
culture; lines, fitted exponential model with a lag phase (b) or
without a lag phase (a).
|
|
Equations
2 and
3 were fitted to the eight growth curves for
E. coli O157:H7 pure cultures. An obvious autocorrelation of
residues
was detected, which meant that the exponential-growth
hypothesis was
not adapted to the data obtained. When pure and
mixed cultures were
compared, it appeared in each experiment that
the two curves for
E. coli O157:H7 could not be superimposed.
For six of the
eight experiments (all combinations of initial
physiological states
except the growing cell-growing cell combination),
there were
significant differences between the growth parameters
for pairs of
pure-culture-mixed-culture growth curves for
E. coli O157:H7 (Table
2). Another model was fitted to these pairs by
using the
following assumptions: the inocula were the same
(
x0p =
x0m) and the lag times
were the same (lag
p = lag
m)
exponential growth occurred in mixed
cultures (at constant growth
rate µ
m); and
biphasic growth occurred in pure cultures
(first at the growth rate of
the mixed culture [µ
p1 = µ
m] and then at a lower growth rate,
µ
p2).
This model fit the data well (Fig.
5) and
was statistically the best model tested. The second growth phase could
have been
divided into a slower growth phase followed by a faster
growth
phase, but our data were not sufficient to obtain a satisfactory
fit.

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FIG. 5.
Comparison of mixed and pure cultures of E. coli O157:H7 strain ATCC 33150. (a) Growing cell inoculum. (b)
Resting cell inoculum. Solid circles, pure culture; shaded circles,
mixed culture; lines, fitted nonexponential model with a lag phase (b)
or without a lag phase (a).
|
|
 |
DISCUSSION |
In pure cultures in minimal synthetic medium, E. coli
O157:H7 growth curves were obviously not exponential. To our knowledge, the triphasic kinetics described here has not been described previously and cannot a priori be explained by a simple phenomenon. Moreover, coculture with E. coli K-12 and adding methionine resulted
in partially or totally normal growth. It could be supposed both treatments had the same effect, namely, reestablishing what occurs at
the beginning and end of growth. Thus, E. coli K-12 could
release methionine into the medium, and the slow intermediate phase in pure cultures in minimal synthetic medium could be explained by a lack
of methionine. Nonetheless, none of these biological hypotheses has
been proven. Essentially, the aim of this study was to demonstrate the
existence of this unexpected phenomenon. A complete biological interpretation would require complementary tools.
Last, the double phenotype (growth anomaly and correction by adding
methionine) was detected for most O157:H7 strains. An O157:H7 strain
(strain 5), which was found to be phylogenetically linked to serotype
O157:H7 by Feng et al. (12), appeared to behave similarly.
Thus, it could be supposed that the physiological anomaly described
here characterizes the O55:H7-O157:H7 phylogenetic branch.
In addition to the results concerning E. coli O157:H7
specifically, this study allowed us to develop tools for modeling the different life phases in a bacterial culture (7) by using
two monitoring methods (turbidimetry and plate counting) and different statistical procedures. Our use of a minimal synthetic medium resulted
in some theoretical simplifications.
One of the main advantages of using a minimal synthetic medium is that
there is theoretically only one deceleration phase, corresponding to
the disappearance of the limiting substrate (which in this case was the
carbon source, glucose). The deceleration phase was actually
characterized by a sharp decrease in µ. For the same reasons, the
exponential model, which provides approximations in most complex media,
should theoretically be suitable for describing bacterial growth in
minimal synthetic medium. Actually, this hypothesis was confirmed by
the statistical results obtained for plate count growth curves for one
reference E. coli strain and by the results of a dynamic
study of the turbidimetric growth curves obtained for 25 E. coli strains. However, growth of E. coli O157:H7 was not consistent with the prototypical exponential model for minimal synthetic medium. New methods to investigate the nonexponential growth
observed were developed; for the most part these methods were based on
calculating an instantaneous µ (for a period of 10 min) instead of
estimating a growth rate based on the whole growth curve. This approach
was possible because we used a sensitive and precise apparatus to
monitor growth by turbidimetry with a short monitoring period.
Nonexponential growth may not be rare and might be observed with other
species. The lack of adequate monitoring and modeling processes could
explain why it is not detected or is ignored.
Using a minimal synthetic medium simplified detection of interactions;
as growth was supposed to be limited only by the limiting substrate,
there was no competition for the substrate as long as the concentration
of the substrate was not limiting (i.e., in the whole exponential
phase). The plate count method was adequate for monitoring two
different populations in a mixed culture, as long as there were
differential or selective media. Plate count results were studied by
using a statistical method based on comparisons of growth curves.
Assuming that there is no competition for the substrate during the
growth phase, the growth curves for one strain under certain conditions
should be superimposable for pure and mixed cultures if there is no
other interaction. The assumptions mentioned above and the use of the F
test allowed us to detect any significant effect of one strain on the
growth of the other and then to characterize the interaction. The
interaction between E. coli K-12 and E. coli
O157:H7 detected, in which one strain had a positive effect on the
growth of the other without being modified itself, was classified as
commensalism as described by Odum (19). A similar
statistical approach (but with organisms grown in a complex medium) was
also used very recently by Pin and Baranyi (20).
The unexpected growth of E. coli O157:H7 showed that the
batch growth modeling approach is a useful tool for characterizing bacterial strains physiologically. Conversely, taking into account physiological information (such as interactions with other bacteria, the state of the inoculum, abnormal growth characteristics, etc.) could
enrich the bacterial growth modeling process, especially in the area of
predictive microbiology.
 |
ACKNOWLEDGMENTS |
We thank Catherine Pichat for technical assistance and
Véronique Guérin and Frédéric Laurent for
helpful discussions. All of the workers who provided E. coli
strains are gratefully acknowledged.
We thank bioMerieux Inc. for supporting this work.
 |
FOOTNOTES |
*
Corresponding author. Mailing address: CNRS UMR 5558, Laboratoire de Bactériologie, Faculté de Médecine
Lyon Sud, BP 12, 69921 Oullins Cedex, France. Phone: 33 4 78 86 31 67. Fax: 33 4 78 86 31 49. E-mail:
cornu{at}biomserv.univ-lyon1.fr.
 |
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Applied and Environmental Microbiology, December 1999, p. 5322-5327, Vol. 65, No. 12
0099-2240/99/$04.00+0
Copyright © 1999, American Society for Microbiology. All rights reserved.
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