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Applied and Environmental Microbiology, December 2003, p. 7310-7318, Vol. 69, No. 12
0099-2240/03/$08.00+0 DOI: 10.1128/AEM.69.12.7310-7318.2003
Copyright © 2003, American
Society for
Microbiology. All Rights Reserved.
and James J. Germida*
Department of Soil Science, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
Received 9 April 2003/ Accepted 4 September 2003
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A complicating issue in environmental risk assessments is that seasonal shifts in rhizosphere microbial communities have been documented. For example, plant development has been shown to significantly affect the biodiversity of a Burkholderia cepacia population associated with maize roots (7). Also, using a PCR-based community profiling technique, denaturing gradient gel electrophoresis, Smalla et al. (34) recently presented evidence showing that the abundance and composition of bacterial rhizosphere populations associated with strawberry, potato, and oilseed rape changed over the field season. The composition and activity of rhizosphere microflora are likely to be altered as a function of time because of changes that occur in the exudation patterns of roots as plants age, and as a consequence, genotype selection may occur as microorganisms adapt to these changes (7). Furthermore, soil microbial growth and metabolic activity often increase in the spring and summer in conjunction with higher soil temperatures, mobilization of accumulated soil organic matter, and accelerated root growth (16). For these reasons, Grayston et al. (16) suggested that caution should be taken when conclusions are drawn about root-associated microbial community structure based on results for a single time point.
Previously described studies that examined the influence of transgenic plants on the root-associated microbial communities throughout a field season showed that the effects of transgenic plants on these microbial communities are subject to seasonal variation. Lottmann et al. (25) found that a transgenic line of potato expressing T4 lysozyme influenced the composition of root-associated bacterial antagonists; however, this was dependent both on the field year and on the time of sampling. Denaturing gradient gel electrophoresis analysis of the bacterial rhizosphere community associated with the transgenic potatoes revealed seasonal shifts in the composition of the microbial community (26). Furthermore, the community-level physiological profiles (CLPP) of the microbial community associated with another transgenic potato that produced Galanthus nivalis agglutinin and concanavalin A lectins were also subject to seasonal variation (17).
Canada is currently the third largest producer of genetically modified crops in the world behind the United States and Argentina. Canola (Brassica sp., oilseed rape) is the most important genetically modified crop in Canada, and to date nearly 80 varieties of herbicide-resistant canola have been granted unrestricted registration by the Canadian Food Inspection Agency (5). Previous studies done our lab that examined genetically modified canola grown at field sites in Saskatchewan, Canada, showed that both rhizosphere and root interior microbial populations associated with a transgenic canola variety, Quest, have altered CLPP and fatty acid methyl ester (FAME) profiles compared to the profiles of a nontransgenic counterpart (12, 32, 33). However, these studies examined bacterial populations associated with canola plants at one stage of growth (flowering). The objectives of the present study were to identify changes in the soil microbial community associated with growing genetically modified canola and to determine whether these changes persisted in the soil over the growing season or were temporary and dependent on the presence of the plant. A 2-year study was conducted at two field sites in Saskatchewan during the 1999 and 2000 field seasons. The microbial communities associated with a genetically modified canola variety, a conventional canola variety, and a fallow soil were assessed at six times during the field season by using three different methods of microbial community analysis, FAME analysis, CLPP analysis, and terminal amplified ribosomal DNA (rDNA) restriction analysis (T-ARDRA).
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Field plots were located at two field sites, in Watrous and Watson, Saskatchewan, Canada. Access to field plots was provided by the Saskatchewan Wheat Pool. The plots were seeded at each site in a replicated (n = 4) randomized complete block design. The studies at Watrous were performed for two field years (1999 and 2000), while the field studies at Watson were terminated after the first field year (1999) due to loss of access to the field site. Canola seeds were planted on 8 May 1999 and 12 May 2000, and the plants were harvested in the first week of September in both field years. Canola was planted according to a standard crop rotation in Saskatchewan consisting of a maximum of one canola crop every 4 years; therefore, canola was not planted in a field in which canola would be planted within 4 years.
Sample processing.
Both field soil and rhizosphere
samples were collected on various dates corresponding to preseeding and
when plants were at the rosette, flowering, maturity, postharvest fall
stubble, and overwintered stubble stages (universal growth stages 0.0,
1.4, 6.5, 8.9, 9.7, and 9.7)
(23) (Fig.
1). The sampling dates for the 1999 field study were 8 May, 22 June, 15
July, 17 August, and 7 October 1999 and 19 April 2000. The sampling
dates for the 2000 field study were 12 May, 22 June, 20 July, 21
August, and 17 October 2000 and 25 April 2001. At growth stages at
which plants were present (i.e., rosette, flowering, maturity) 10
plants with adhering soil were taken randomly from throughout each of
the four replicate plots and combined; each grouped sample was
considered a replicate of rhizosphere soil. At growth stages at which
no root system was present (i.e., preseeding, fall stubble, and
overwintered stubble) 10 soil samples were taken randomly from
throughout each of the four replicate plots and combined; the grouped
samples were considered a replicate of fallow soil. The method used to
process soil samples was described previously
(12).
![]() View larger version (110K): [in a new window] |
FIG. 1. Growth
stages of canola sampled during the study. Microbial community samples
were obtained at designated stages of growth corresponding to
preseeding, rosette, flowering, maturity, fall stubble, and
overwintered stubble. The sampling dates were in May, June, July,
August, October, and the following
April.
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CLPP.
The CLPP analysis was performed as
described by Siciliano and Germida
(31) with Biolog
gram-negative (GN2) microplates (Biolog, Inc., Hayward, Calif.).
Briefly, 100 µl of a 10-4 dilution was
inoculated into each well, and the plates were incubated at
28°C for 5 days. Color development was measured by determining
the optical density at 590 nm with an automated microplate reader
(Molecular Devices, Inc., Sunnyvale, Calif.) and Microlog 3E software
(Biolog, Inc.). The average well color development (AWCD) was
calculated as described by Garland and Mills
(15).
FAME
analysis.
FAME analysis of
the soil microbial community was performed as described by Cavigelli et
al. (6) and Siciliano et
al. (33). Briefly,
5 g of soil was mixed with 5 ml of methanoic NaOH (15%
[wt/vol] NaOH in 50% [vol/vol] methanol) and
saponified at 100°C for 30 min. Esterfication of fatty acids
was performed with 10 ml of 3.25 N HCl in 46% (vol/vol) methanol
at 80°C for 10 min. The FAMEs were extracted in 1.5 ml of
methyl-tert-butyl ether-hexane(1:1, vol/vol) and
centrifuged at 110 x g for 5 min, and the top phase
was transferred to a 10-cm test tube. This organic extract was washed
with 3 ml of 1.2% (wt/vol) NaOH and analyzed with a
Hewlett-Packard 5890 series II gas chromatograph (Hewlett-Packard Co.,
Palo Alto, Calif.). FAME peaks were automatically integrated with the
Hewlett-Packard 3365 ChemStation software, and FAMEs were identified by
using the MIDI microbial identification system software (Sherlock TSBA
Library, version 3.80; Microbial ID, Inc., Newark, Del.). In order to
minimize the fatty acids derived from plant and animal sources, fatty
acids with chains longer than 20 carbons, which are generally more
characteristic of eukaryotic organisms than prokaryotes, were not
included in the statistical analysis
(6,
14).
T-ARDRA.
Soil DNA was extracted directly from
0.5 g of rhizosphere soil by using a FASTDNA spin kit for
soil (Bio 101, Carlsbad, Calif.) as described by Borneman et al.
(2). DNA (50 µl)
was purified by using a Sephracryl-400h MicroSpin column (Pharmacia
Biotech Inc.). The presence of DNA was confirmed by electrophoresis on
a 1% agarose gel stained with ethidium bromide.
Bacterial
16S rDNA was selectively amplified by PCR performed with
oligonucleotide primers designed to anneal to conserved positions in
the 3' and 5' regions of bacterial 16S rDNA. The
forward primer, 8F (AGAGTTTGATCCTGGCTCAG),
corresponded to positions 8 to 27 of Escherichia
coli 16S rRNA (24),
and the reverse primer, R10 (CATTGTAGCATCCGTTGAAG),
corresponded to positions 1224 to 1242 of E. coli
16S rRNA (10). The
forward primer was end labeled with
[
-32P]ATP by using polynucleotide kinase.
The amplification mixtures (final volume, 12.5 µl) contained
6.25 pmol of primer R10, 0.025 pmol of primer 8F, each deoxynucleoside
triphosphate at a concentration of 1 mM, 5 mM magnesium chloride, 1.25
µl of 10x PCR buffer, and 0.625 U of Taq
polymerase (Invitrogen, Burlington, Ontario, Canada). The PCR was
performed with an automated thermal cycler (Robocycler; Stratagene, La
Jolla, Calif.). The reaction began with a denaturation step at
95°C for 5 min, and this was followed by 30 cycles of
94°C for 45 s, 57°C for 45 s, and
72°C for 45 s and then a final extension step at
72°C for 15 min. PCR products were restricted by using the
CfoI (GCG'C) and MspI (C'CGG)
restriction enzymes (Invitrogen) for 90 min at
37°C.
T-ARDRA was carried out with a Hoeffer SQ3
Sequencer vertical gel electrophoresis system (Amersham Pharmacia
Biotech, Baie d'Urfé, Quebec, Canada). Aliquots (12.5
µl) of each digested product were mixed with 10 µl of
loading dye buffer and resolved by electrophoresis through a 6%
(wt/vol) nondenaturing acrylamide gel (ratio of acrylamide to
N,N-methylenebisacrylamide, 19:1). Electrophoresis
was carried out at 65 W for 4 to 5 h. In addition, an
end-labeled [
-32P]ATP ladder (30 to 330
bp) was included on each gel.
In order to visualize the banding patterns, gels were transferred to 3-mm chromatography paper and placed along with Kodak XAR autoradiography film into an autoradiography film exposure cassette for 24 h. The film was developed and photographed with a digital camera.
Statistical analysis.
To standardize FAME data, the
adjusted response area of each sample was calculated by multiplying the
percentage of each individual FAME by the total named area for the
chromatogram (13). Soil
FAME profiles were compared by principal-component analysis (PCA) by
using a correlation matrix (Minitab v. 12; Minitab Inc., State College,
Pa.). The principal-component data were analyzed by using analysis of
variance (ANOVA).
The AWCD was used as a standardized reference point in color development (8, 15). Absorbance data (A590) from microplates having AWCD of approximately 0.75 were used for statistical analysis. PCA was performed as described above.
Because DNA quantity cannot be consistently and accurately represented by band intensity on an autoradiograph, band intensity was not assessed; instead, T-ARDRA gels were scored for the presence or absence of bands as described in Konopka et al. (22). Molecular weights of bands were determined by using the Geneprofiler software (Scanalytics Inc., Fairfax, Va.). Digital images of gels were analyzed by PCA.
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FIG. 2. PCA
of CLPP obtained for microbial communities from fallow soil and
rhizosphere microbial communities of canola varieties grown at Watson,
Saskatchewan, sampled in May, June, July, August, and October 1999 and
April 2000. Symbols: , fallow soil (n = 4);
, conventional variety Excel (n = 4);
, genetically modified variety Quest (n = 4).
The error bars indicate the standard errors of the means. The level of
variation explained by each principal component is indicated in
parentheses. P values are indicated when there was a
significant variety effect, as determined by
ANOVA.
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FIG. 3. PCA
of CLPP obtained for rhizosphere microbial communities of conventional
canola variety Excel (A) and genetically modified canola
variety Quest (B) grown at Watrous, Saskatchewan, in 1999.
Each symbol indicates the average for four replicates at one field site
(n = 4). The error bars indicate the standard errors
of the means. The levels of variation explained by individual principal
components are indicated in parentheses. P values are
indicated when there was a significant sampling time effect, as
determined by
ANOVA.
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FIG. 4. PCA
of FAME profiles obtained for microbial communities from fallow soil
and for rhizosphere microbial communities of canola varieties grown at
Watrous, Saskatchewan, sampled in May, June, July, August, and October
1999 and April 2000. Symbols: , fallow soil (n
= 4); , conventional variety Excel (n
= 4); , genetically modified variety Quest (n
= 4). The error bars indicate the standard errors of the means.
The level of variation explained by each principal component is
indicated in parentheses. P values are indicated when there
was a significant variety effect, as determined by
ANOVA.
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FIG. 5. PCA
of FAME profiles obtained for microbial communities from fallow soil
and for the rhizosphere microbial communities of canola varieties grown
at Watson, Saskatchewan, sampled in May, June, July, August, and
October 1999 and April 2000. Symbols: , fallow soil
(n = 4); , conventional variety Excel
(n = 4); , genetically modified variety Quest
(n = 4). The error bars indicate the standard errors
of the means. The level of variation explained by each principal
component is indicated in parentheses. P values are indicated
when there was a significant variety effect, as determined by
ANOVA.
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FIG. 6. PCA
of FAME profiles obtained for rhizosphere microbial communities of
conventional canola variety Excel (A) and genetically
modified canola variety Quest (B) grown at Watrous,
Saskatchewan, in 2000. Each symbol indicates the average for four
replicates at one field site (n = 4). The error bars
indicate the standard errors of the means. The levels of variation
explained by individual principal components are indicated in
parentheses. P values are indicated when there was a
significant sampling time effect, as determined by
ANOVA.
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T-ARDRA profiles of
microbial communities.
PCA revealed no significant
influence of plant growth stage on the T-ARDRA banding patterns
associated with canola plants (data not shown). Moreover, at one of the
field sites, Watrous, PCA of T-ARDRA profiles indicated that there were
no significant differences between the banding patterns of microbial
communities associated with canola plants and the banding patterns of
the microbial communities associated with the unplanted fallow plot.
Similarly, at the second field site, Watson, at five of the six
sampling times there were no differences in the banding patterns of the
microbial communities. The one exception was the June 1999 sampling
time; at this time the T-ARDRA banding patterns of the microbial
communities associated with genetically modified Quest plants and the
communities from fallow soil were significantly different from the
T-ARDRA banding patterns of the rhizosphere communities associated with
Excel plants (Fig.
7).
![]() View larger version (36K): [in a new window] |
FIG. 7. PCA
of T-ARDRA profiles obtained for microbial communities from fallow soil
and for rhizosphere microbial communities of canola varieties grown at
Watson, Saskatchewan, sampled in May, June, July, August, and October
1999 and April 2000. Symbols: , fallow soil (n
= 4); , conventional variety Excel (n
= 4); , genetically modified variety Quest (n
= 4). The error bars indicate the standard errors of the means.
The level of variation explained by each principal component is
indicated in parentheses. P values are indicated when there
was a significant variety effect, as determined by
ANOVA.
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Previous studies in which microbial communities were examined throughout a field season have often indicated that there is seasonal variability (7, 16, 17, 19, 25, 26, 34). The results of the present study also show that microbial community structure was influenced by seasonal variation, as indicated by significant changes in the CLPP and fatty acid composition of the microbial community associated with the time of sampling.
The microbial community associated with the rhizosphere of the transgenic Quest plants was significantly different from microbial community associated with the rhizosphere of conventional Excel plants; however, the differences depended on the time of sampling, and communities were not consistently different throughout the entire field season. Most of the observed differences occurred at the July sampling time, at the midflowering stage of growth. Previous studies have shown that there are differences in the composition of the rhizosphere microbial community associated with transgenic Quest plants compared to the compositions of the communities associated with Excel plants and six other canola varieties tested (12, 32, 33). It is interesting that July was the time period selected for these studies. By comparison of the relative abundance of 16S rDNA targets, Smalla et al. (34) also found that enrichment of bacterial populations associated with canola was most pronounced when canola was flowering.
In this study, the CLPP of the microbial communities, rather than the fatty acid composition or the genetic diversity, was affected more by seasonal variation. Slight changes in bacterial diversity are sometimes not revealed by FAME analysis because fatty acids can be present in a wide range of bacteria, FAME profiles may be dominated by fatty acids from numerically dominant bacteria, and rare microbial populations may be missed in a profile. Therefore, slight differences in community structure may not translate to significant differences in fatty acid profiles (28). Similarly, microbial communities with similar structures as determined by T-ARDRA may still have ecologically significant differences in community composition, as this method is not sensitive to changes in community composition that may occur at the level of individual strains or species (4). In addition, T-ARDRA assesses changes in the numerically dominant populations of bacteria in a population. Rare microbial populations are not represented because the template DNAs from these populations represent a small fraction of the total community and are not amplified by PCR or are present at levels that are not detected above the background (24). Furthermore, in our study T-ARDRA banding patterns were analyzed by considering the presence or absence of bands rather than the intensity. Duineveld et al. (11) pointed out that bands can be present at all times but differ in intensity. The differences in intensity indicate that bacterial numbers are changing and hence altering the diversity of the community. In the present study, there may have been differences in the numbers of bacteria present in the rhizosphere that caused a shift in the functional diversity of the rhizosphere microbial community that was not identified as a shift in the genetic diversity of the microbial population. For these reasons, differences in the CLPP of the community over the field season did not coincide with significant changes in the FAME or T-ARDRA banding patterns.
In the present study, both CLPP and FAME analyses indicated that there were differences between the microbial communities associated with fall stubble from Quest and Excel plants. Other authors have found differences in microbial communities associated with transgenic plants at the senescence plant growth stage. For example, Lukow et al. (27) found differences in the community fingerprint patterns of rhizosphere soil samples associated with senescent potato plants. Similarly, Lottmann et al. (25, 26) only found differences in the composition of the population of the beneficial bacteria associated with senescent potato plants. One critical role of soil microorganisms in soil ecosystem functioning is the decomposition of plant residues and nutrient cycling (21). It is possible that decomposition of genetically modified plant tissue affects the composition of the soil microbial community. Donegan et al. (9) investigated the potential ecological impact of genetically engineered plants on soil ecosystems by burying litterbags containing leaves of transgenic tobacco that expressed proteinase inhibitor I in field plots. They found differences in carbon content between the decomposing parental plant litter and the transgenic plant litter along with differences in the numbers of nematodes and Collembola in the soil surrounding the transgenic plant litterbags.
Seasonal variation in microbial community structure is a complicating factor in the environmental assessment of transgenic plants. The question arises whether differences in microbial communities associated with transgenic plants at a single time point are ecologically significant. This study affirmed that future ecological assessments of genetically modified plants should be conducted at several time points in a field season. Furthermore, this study suggests that in the Canadian agricultural system, in which plants are harvested in early fall and senescent plant roots are left over a long winter season, any differences in the microbial communities associated with transgenic plants are minimized or eliminated. This suggests that changes in the soil microbial community are temporary and dependent on the presence of the transgenic plants.
This research was funded by the Natural Sciences and Engineering Research Council of Canada and the Saskatchewan Wheat Pool. Kari E. Dunfield was supported by a Canadian Wheat Board Ph.D. fellowship.
Present address: Darling Marine Center, University of Maine, Walpole, Maine. ![]()
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