Structural and functional analysis of whole-soil microbial communities for
risk and ef®cacy testing following microbial inoculation of wheat roots in
diverse soils
J.V. Gagliardi
a,*, J.S. Buyer
b, J.S. Angle
a, E. Russek-Cohen
caDepartment of Natural Resources Sciences, University of Maryland, College Park, MD 20742, USA
bSoil Microbial Systems Laboratory, USDA-ARS, Beltsville, MD 20705, USA
cDepartment of Animal Sciences, Univeristy of Maryland, College Park, MD 20742, USA
Received 19 April 1999; received in revised form 25 January 2000; accepted 16 May 2000
Abstract
The increasing use of genetically engineered or modi®ed microorganisms (GEMs) has led to regulations regarding the safety of their use. Intended (target) effects and unintended (non-target) effects of GEMs must currently be evaluated prior to ®eld testing or commercial use. We present soil and rhizosphere microbial community effects testing of two GEMs,Pseudomonas chlororaphis3732RN-L11 andPseudomonas ¯uorescens2-79RN-L3, parental strains of these organisms and an uninoculated treatment using ®ve diverse soils planted to wheat. An assay using BIOLOGw
GN plates measured microbial community functional responses on wheat roots with adhering soil. Overall differences using multivariate statistical methods were highest at inoculation, and these effects persisted while the inoculated organisms were detectible on selective media. Differentiation based onlacZYgenes engineered to the chromosome of both GEMs was signi®cant for the 3732 GEM in all ®ve soils tested, but not for the 2-79 GEM in a single soil. Lactose utilization in uninoculated microbial communities varied around a low baseline value. Direct fatty acid extraction and analysis of soil from around wheat roots was also performed using a novel method. Fatty acid analysis differentiated the 3732 GEM from all other treatments, but did not distinguish the 3732 parent inoculated from uninoculated treatments. As with the BIOLOG assay, multivariate statistical differences from fatty acid analysis decreased between GEM inoculated and uninoculated populations as viable counts of the GEM declined. Neither assay showed measurable community-level effects when inoculated organisms declined below detection, though three of six soils with surviving GEM populations still had signi®cant effects after 105 days. Published by Elsevier Science Ltd.
Keywords: BIOLOG; FAME; Genetically engineered microorganisms;Pseudomonas; Rhizosphere
1. Introduction
Genetically engineered microorganisms (GEMs) are coming under increasing scrutiny as their potential uses and fates are considered. During the risk assessment and review process prior to approval for release of GEMs, concerns regarding toxicity and pathogenicity are addressed, and numerous tests are employed that address speci®c acute or chronic effects (Monsanto Corporation, 1987, 1988). The potential for exposure, potential environ-mental interactions, and potential non-target effects are also considered (Levin and Strauss, 1991). Risk assessments prior to environmental release speci®cally seek to determine whether altered or inserted nucleic acids have the potential
to confer production of toxic substances or pathogenic traits to non-target organisms (Levin and Strauss, 1991). Com-munity level microbial analyses, however, have not been possible until recently, with the development of new assays and procedures that show promise for use in complex substrates. The possibility of simultaneously testing ef®cacy along with non-target effects on microbial communities would be an added bene®t.
Assessing the non-target effects of introduced microbes, including effects of GEMs, is an ongoing area of research. Several recent studies have assessed the non-target effects of inoculated strains ofPseudomonas ¯uorescens. Wheat rhizo-sphere effects on indigenous pseudomonad populations were more signi®cant than in fallow soil, but were still con-sidered minor (De Leij et al., 1995). Nutrient cycling effects were found but were deemed negligible in clover-cropped ®elds following a previous crop treatment of sugar beets
0038-0717/00/$ - see front matter Published by Elsevier Science Ltd. PII: S 0 0 3 8 - 0 7 1 7 ( 0 0 ) 0 0 1 1 0 - 3
www.elsevier.com/locate/soilbio
* Corresponding author. Tel.:11-301-504-9214; fax:11-301-504-8370.
(Moenne-Loccoz et al., 1998). Indigenous pseudomonads were reduced but there was no change in total microbial populations, some soil enzyme activities were reduced after inoculation but others increased, and diacetylphloro-glucinol (DAPG) production caused plant stress (Naseby and Lynch, 1998b). Soil enzyme activities were differen-tially affected by inoculation plus amendment with kana-mycin or lactose compared to uninoculated controls, and there were soil microbial community effects attributable to a GMM (GEM) but not the wild-type strain, implying that the inserted genes have signi®cant effects (Naseby and Lynch, 1998a). Reduced total microbial activity was reported after inoculation with a DAPG producing strain, with increased plant uptake of nitrogen for inoculated peas attributed to indigenous microbes dying off (Brimecombe et al., 1998). In a similar study, water-soluble carbon compounds increased, phosphate decreased, and there were numerous nutrient transforming enzyme effects after inoculation of pea rhizospheres, and some effects were attributable to production of the antibiotic DAPG (Naseby et al., 1999). The implication from this body of research is that there are measurable effects from both engineered and non-engineered strains ofP. ¯uorescensin different soil and rhizosphere types, though these effects may be transient, and are often dif®cult to interpret in terms of an ecological perspective.
Whole soil microbial community analyses may also be employed to assess overall impact, with results on multiple effects gained in a single assay. One method uses commer-cially available BIOLOGw GN microplates, originally developed for identi®cation of Gram-negative bacteria (Bochner, 1989). Instead of a pure culture, an extract containing portions of the soil microbial community is inoculated into the microplate, and the relative utilization of individual carbon sources is compared using multivariate statistical methods (Garland and Mills, 1991; Zak et al., 1994; Winding, 1994; Garland, 1996a,b). Multivariate methods tend to minimize type I errors while utilizing infor-mation regarding correlations among variables to improve power (Seber, 1984). However, methods that obligately subtract negative control well reactions or average well color development (AWCD) values from all plate readings (Garland and Mills, 1991), or that take multiple readings over time and select differently incubated readings for co-analysis (Garland, 1996a, 1997) to correct for inoculum density differences, may mask effects at the community level that are unrelated to inoculum density. No valid way exists to standardize inoculum prior to a BIOLOG assay without spending considerable time and effort, though there have been recent attempts to rectify this by statistically adjusting for inoculum density after taking a single plate reading, including the use of kinetic curves pre-determined for each sample type analyzed (Lindstrom et al., 1998), the use of AWCD as a covariate instead of as an obligate adjust-ment for analysis (Harch et al., 1997), and one that used the blank well as a covariate (Buyer et al., 1999). The use of
BIOLOG for community analyses currently requires signi®cant effort to inoculate, read, analyze, and understand the results, and there may be considerable bias associated with any of these steps.
Other community level assays employ the many types of biogenic molecules that differentiate living organisms on phylogenetic lines. Analysis of phospholipid fatty acids was seen as a useful tool for characterization of soil micro-bial communities (Federle, 1986). This method does not require growth in culture so it is a snapshot of the soil biological community. Fatty acid analyses speci®c for phos-pholipids were used in several studies of soil microbial communities (Zelles et al. 1992; Frostegard et al., 1993, 1996; Zelles et al. 1994; Wander et al. 1995). In a novel approach, a soil sample is directly saponi®ed and the result-ing methylated fatty acids are analyzed (Haack et al., 1994; Cavigelli et al., 1995; Buyer and Drinkwater, 1997). Extracting and esterifying fatty acids directly from soil perhaps ensures a more unbiased expression of soil com-munity structure than separation of constituent parts prior to analysis. In addition, phospholipid fatty acid analysis is more dif®cult and expensive than whole soil methods, and the two methods apparently yield equivalent information (Haack et al., 1994). A novel method employed for whole soil fatty acid analysis uses transesteri®cation (R.A. Drijber, personal communication), which was used for this study and is described here in detail. Previous comparative studies have found that BIOLOG soil microbial community multi-variate pro®les were similar when compared to phospholi-pid fatty acids, but both methods showed high variation between replicates (Baath et al., 1998), and BIOLOG provided greater differentiation of treatments compared to directly saponi®ed whole soil community fatty acid pro®les (Buyer and Drinkwater, 1997).
Several studies have used BIOLOG plates to analyze microbial communities on the root portion of plants, includ-ing equal portions of surface root material extracted by blending in buffer (Ellis et al., 1995), whole roots grown in nutrient solution and extracted by mechanical agitation with glass beads in detergent (Garland, 1996a,b), roots grown in soil using equal portions of washed roots extracted by shaking in buffer (Siciliano and Germida, 1998), and equal portions of roots with adhering soil extracted by shak-ing in buffer (Siciliano et al., 1998). Fatty acid techniques for plant root or rhizosphere analysis include direct saponi-®cation of oven-dried roots (Graham et al., 1995; Siciliano and Germida, 1998), direct saponi®cation of root tissue with adhering soil (Siciliano et al., 1998), and of germinating seeds in soil using sonication for 5 min followed by vortex-ing and removal of seed material, followed by saponi®ca-tion of the soil (Buyer et al., 1999). Previous work with
Pseudomonas chlororaphis 3732RN-L11 showed that this organism invades wheat roots and is recoverable from surface sterilized roots (Nairn and Chanway, 1999).
In this study, we apply two community level assays: (1) BIOLOG plates inoculated with unwashed wheat roots, or
soil samples, both blended in water and analyzed with a novel statistical approach; and (2) a novel whole soil transesteri®cation of fatty acids method, using soil from around the same wheat roots. Two microorganisms were chosen for this study based on the availability of wild-type strains, and of GEM strains with similar chromosomal
lacZY inserts for 3732 and 2-79. They were also chosen because of the existence of previous risk assessments and ®eld release approvals that would allow us to more easily perform later tests in the ®eld. The major differences between the two microorganisms tested are different species identi®cation, and the ability of strain 2-79 to produce the antibiotic phenazine-1-carboxylate, useful in biocontrol applications (Thomashow and Weller, 1988). Soils were inoculated with either a single genetically engineered pseu-domonad strain, a non-engineered pseupseu-domonad strain, or were not inoculated. Treatments within a soil were prepared and inoculated simultaneously to randomly chosen replicate intact soil-core microcosms (Angle et al., 1995), so all treat-ments essentially started with the same indigenous soil microbial communities and were otherwise similarly incu-bated and watered for the remainder of the study. Fresh intact soil-core microcosms were obtained from several ecologically unique Canadian sites and one US site for this experiment. Our goal was to use microcosms validated with ®eld releases (reported elsewhere for this study) for pre-release testing of GEMs. Field-survival-predictions, risk-assessment regarding indigenous soil microbial communities, and ef®cacy testing of the developed organ-ism could potentially be performed simultaneously in these microcosms.
2. Materials and methods
2.1. Intact soil-core microcosms
All assays used intact soil core microcosms planted with a single wheat plant (Triticum aestivum), a Canadian Prairie Hard Red Spring Wheat, cultivar A. C. Karma. Microcosms were constructed of 5 cm inner diameter polyvinyl chloride plumbing pipe 17.5 cm long, bevelled to 458on the outside at one end. The core was driven 15 cm into the soil and then carefully removed intact (Angle et al., 1995).
2.2. Soils for the microcosm experiment
Five ecologically distinct soils from throughout Canada were obtained in the spring of 1996 and again in 1997. All sites sent freshly obtained intact soil-core microcosms by overnight courier to Maryland for this study. Sites AG and CL were in Ottawa, Ontario; BC was in Vancouver, British Columbia; SK was in Watrous, Saskatchewan; NR was in Montreal, Quebec (NR was tested in 1997 only). The UM soil was from Calverton, MD, the same site used for a 1994 ®eld release test (Angle et al., 1995). Soil chemical, physi-cal, and textural characteristics were measured in detail at
the beginning of each year and are listed (Table 1). Micro-cosms from all sites were kept in growth chambers with 12-h daylig12-ht lengt12-h and 70% relative 12-humidity. Canadian microcosms were kept at 228C and UM microcosms were at 288C, which represents the mean growing season daytime temperature at the sites where the microcosms originated.
2.3. Bacterial inocula
In 1996, P. chlororaphis 3.732RN-L11 (3732 GEM) (Monsanto Corporation, 1987, 1988; Kleupfel et al., 199l) and an uninoculated treatment were used. In 1997, P. chlororaphis 3732RN (3732 Parent) was also inoculated into separate microcosms from each soil. In addition, separ-ate UM soil microcosms were inoculsepar-ated withP. ¯uorescens
2-79RN-L3 (2-79 GEM) and P. ¯uorescens2-79RN (2-79 Parent) (Weller, 1983; Monsanto Corp., 1987, 1988). All GEM and parent organisms utilized were spontaneous rifa-mycin and nalidixic acid resistant mutants, hence the RN in the strain names. Both GEMs were engineered to contain the
lacZY genes inserted at a single site on the chromosome (Barry, 1986, 1988). All inocula were grown to late-log phase and a density of approximately 109CFU ml21 in Pseudomonas F broth made with the same ingredients as Pseudomonas F agar (Difco, Detroit, MI) but without agar, and amended with 100mg ml21 each of rifamycin SV and nalidixic acid after autoclaving and cooling. The cells were immediately placed on ice, pelleted by centrifu-gation at 5000£g, and re-suspended in sterile distilled water to a density of 0.800 OD640, a density of
approxi-mately 5£108CFU ml21. Each microcosm received 2.5 ml of prepared inoculum on the soil surface over sown wheat seeds, followed by 2.5 ml of sterile reverse osmosis grade (R0) water. Uninoculated microcosms received 5.0 ml of RO water.
2.4. Extraction and assay of the rhizosphere
Sampling began 4 h after inoculation, on day 0. Day 0 samples consisted of only bulk soil, since seed had not yet germinated. Subsequent samplings at 14, 28 and 42 days after inoculation occurred when there was suf®cient root growth to constitute a sample for analysis. At 56 days the wheat had matured and begun to senesce. Sampling after 84 days again required the use of bulk soil since the roots had disintegrated. Soils were extracted from microcosms by inverting the core and hammering on the bottom edge until the sample was extruded. The sample was sieved (4 mm) while carefully separating out wheat roots. The entire root with adhering soil was used for BIOLOG analysis, while the sieved soil from around the roots was used for fatty acid analysis. Since the microcosms had a diameter of only 5 cm and were 15 cm deep, after 14 days all portions of the microcosms had contact with wheat roots. Sieved soil was saved in Te¯on capped glass vials at 2208C then freeze dried in uncapped vials and re-stored at 2208C prior to fatty acid analysis, explained in a subsequent section. For
BIOLOG analysis of root samples and enumeration of bacteria, extraction and sampling took place immediately. Sterile RO water was added as a diluent to a ®nal volume of 100 ml for extraction of root samples. Blending with a Waring blender for 1 min at top speed in a 1-l glass vessel homogenized the root samples prior to analysis, followed by 1 min of settling to remove large particulates before taking a sub-sample. Aliquots were taken from the top third of the solution to avoid pieces of ¯oating organic matter. Samples were then diluted in an isotonic magnesium±phosphate buffer (pH 7.0) prior to inoculation onto growth media, or in 0.85% NaCl for inoculation to BIOLOG plates. Total culturable bacteria were enumerated using Rhizosphere Isolation Media (Buyer, 1995) containing 100mg ml21 cycloheximide (Fluka Chemicals, St. Louis, MO) and 50mg ml21 nystatin (Sigma Chemicals, St. Louis, MO) after 48-h incubation at 288C. Selective media used to enumerate all the inoculated organisms was Pseudomonas F agar (Difco Labs, Detroit, MI) with 10 ml l21 glycerol (Fisher Scienti®c, Pittsburgh, PA), supplemented after auto-claving with 100mg ml21each of rifamycin SV, nalidixic acid, and cycloheximide (Fluka Chemicals, St. Louis, MO), and 60mg ml21X-GAL (5-Bromo-4-chloro-3-indoyl B-d
-galactopyranoside) (Diagnostic Chemicals, Ltd, Oxford, CT).
2.5. Incubation and reading of BIOLOG plates
Blended root samples were serially diluted 1 to 1000 in sterile 0.85% NaCl for inoculation to BIOLOG plates. Each well of a BIOLOGw
GN microplate was inoculated with 150ml using a multi-channel pipettor. BIOLOG plates were covered and incubated at 228C in the dark for 72 h. All plates were read once in a microplate reader equipped with a 590 nm barrier ®lter (Molecular Devices, E-MAX). The 96 optical density readings from each microplate were stored as an ASCII ®le then later combined with readings from other replicates for statistical analysis.
2.6. Whole soil transesteri®cation and extraction of fatty acids
Transesteri®cation is one of many methods that catalyze the esteri®cation and methylation of fatty acids from lipids (Christie, 1995). Transesteri®cation as reported here was modi®ed for whole soil analysis (R.A. Drijber, personal communcation) and differs from previous methods that were based on MIDI microbial fatty acid identi®cation tech-niques (Microbial ID Inc., 1992) applied to whole soils (Cavigelli et al., 1995; Buyer and Drinkwater, 1997). Essen-tially, this method eliminates the need for boiling, which is necessary when using the MIDI chemistry. All glassware was soaked in 1 N HCl, rinsed with sterile distilled water, then inverted in metal racks and autoclaved for 20 min to prevent sample contamination. All equipment was made of stainless steel, glass or was Te¯on lined to prevent hydrocarbon contamination. Each sample consisted of 2 g
J.V. Gagliardi et al. / Soil Biology & Biochemistry 33 (2001) 25±40
freeze-dried soil in a 50 ml Pyrex centrifuge tube. Ten ml of 0.2 N KOH in HPLC grade methanol was added and the tube was vortexed and placed in a 378C water bath for 1 h with occasional agitation by hand. Following incubation, the mixture was neutralized with 1 N acetic acid (typically 2 ml). Extraction of fatty acids was accomplished using 5 ml HPLC grade hexane added to the mixture, which was then vortexed and centrifuged at 2000 rpm in a ®xed angle rotor to separate the phases. The hexane layer was then trans-ferred to a 15 ml Pyrex tube using a sterile Pasteur pipette and the entire hexane extraction repeated, for a total of 10 ml hexane with solubilized fatty acids in the tube. Hexane was evaporated from each tube under a slow stream of nitrogen gas in a fume hood. The resulting residue was re-dissolved in 0.5 ml of a 1:1 mixture of methyl tert-butyl ether and hexane. Samples were analyzed using a gas chro-matograph (Hewlett Packard 5890A, FID detector) using MIDI EUKARY standards and the MIDI EUKARY (eukar-yote) fatty acid database. Individual peaks were identi®ed based on the relative retention time of known fatty acids in the standard mixture, which was re-veri®ed every 10 samples. If any calibration failed, the preceding samples were not used for analysis, and the gas chromatograph auto-matically shut down until it was re-calibrated. Peak areas were quanti®ed by integration and the percent of total peak area for each named peak was calculated. Individual sample ®les were stored, then combined later as a single ASCII ®le for analysis.
2.7. Statistical analysis for the BIOLOG and FAME assays
A completely randomized design was used, with micro-cosms of each soil randomly assigned to treatments. Four replicate samples from each treatment £ soil combination were analyzed at each time point over the course of 105 days. Data generated from each soil for both assays were analyzed separately due to concerns that ecological, physical, and chemical differences would confound results. A total of 784 samples were analyzed using BIOLOG plates and 736 using fatty acid analysis. We used Q±Qplots of multivariate data (Khattree and Naik, 1995) to assess multi-variate normality, a requisite prior to multimulti-variate analysis. With multivariate methods one also needs to be sensitive to situations where large numbers of variables are used with comparatively poor replication. For BIOLOG analysis, the number of variables was reduced to the nine carbon sources most signi®cantly different for each soil by utilizing an F-ratio test of signi®cance (proc GLM; SAS 1988). Covariates were used for univariate and multivariate functional analy-sis to adjust for variations of inoculum density, sample size and plate variations (see Appendix A for SAS program-ming). The covariates used were the negative control well O.D., the log(10) transformed number of inoculated cultur-able bacteria, and the fresh root weight for each sample. BIOLOG optical density data was multivariate normally distributed using the covariates, so no transformation was
used. Fatty acids were analyzed as percent of total peak area. The ten most signi®cantly different fatty acids for each soil comparison were used for analysis. To improve multivariate normality, fatty acid peak values were trans-formed (%11)21. Multivariate statistical analysis for both assays was a canonical discriminant analysis (CDA) using SAS (Cary, NC) software (see Appendix A for SAS programming). Multivariate treatment differences are reported as an overall Wilk's F ratio, a Mahalanobis distance for paired comparisons, or a MANOVA F ratio performed on CDA variables for selected time points (Glimm et al., 1997).
2.8. Survival of inoculated organisms
Selective media plate counts for inoculated micro-organisms were measured from 0 to 105 days after inocula-tion and transformed by log10 x11;which improved the univariate normal distribution and homogeneity of variance for the data. Linear regression was used since linear effects compared to quadratic and cubic effects were most signi®-cant. The x-intercept value of linear regression represents the predicted number of days until viable populations fall below detectible levels, while the slope of the regression line represents the rate at which inoculated bacteria declined. Signi®cance between GEM and parent strains is reported as anFratio from pair-wise comparison of slopes (Sokal and Rohlf, 1995) (Table 2).
3. Results
The introduced microorganisms on wheat roots were detectable on selective media in all treatments for the length of this experiment, and predicted survival using linear regression ranged from 133 to 391 days in the MD and SK soils, respectively. Survival was similar for the 3732 GEM and parent in all cases (Table 2). R-square values for the linear regressions range from 0.52 for the 2-79 GEM in the UM soil, to 0.84 for the 3732 parent in the CL and SK soils (Table 2).
Microbial community responses using BIOLOG plates were not visible in most reaction wells until after 48 h of incubation. At 72 h, there were visible reactions in the majority of wells and all plates had several wells with no visible reaction. Least square O.D. means were analyzed in a linear covariance regression model (SAS 1988; Appendix A) for all carbon sources and graphed, but only lactose utilization showed a consistent response. This analysis showed that lactose response values for the 3732 GEM inoculated to the wheat rhizosphere ®t a regression model better using covariables R20:82; in comparison to unadjusted well readings R20:65 or when negative control well values were subtracted from unadjusted well readings R20:64 (Fig. 1). O.D. response values analyzed with covariables and expressed as least square
means also tended not to vary with inoculum density as much as other methods (Fig. 1).
Lactose utilization values were the only BIOLOG assay variable that showed a consistent response when comparing inoculated treatments to uninoculated controls. Lactose utilization patterns are shown for the 3732 GEM, 3732 parent, and uninoculated treatments in the SK soil, compared to 3732 GEM survival and total inoculum levels (Fig. 1). Uninoculated and 3732 parent inoculated lactose utilization values were indistinguishable and varied below the visible range (OD,0.5) throughout the experiment (Fig. 1). Wheat root microbial populations inoculated with the 3732 GEM exhibited high lactose utilization readings, with levels declining to background as viable 3732 GEM declined (Fig. 1). These results were similar in the UM soil (Fig. 2) and in the AG, BC, CL and NR soils (not shown). When the 2-79 GEM and parent were assayed over time in the UM soil, lactose utilization by wheat root populations was not seen for any treatment and the pattern of inoculated treatments was not differentiable from uninoculated controls (Fig. 3). Survival rates (slopes) for the 2-79 and 3732 GEMs in the UM soil were similar (Table 2) as were inoculum CFU, though recoverable organisms were lower for 2-79 in the UM soil than for 3732 at most time points (Figs. 2 and 3). Pure cultures of the 3732 and 2-79 GEM and parent inoculated to BIOLOGw
GN plates indicated that the insertedlacZYgenes in both the 3732 and 2-79 GEM strains conferred the ability to utilize lactose and lactulose.
J.V. Gagliardi et al. / Soil Biology & Biochemistry 33 (2001) 25±40
Table 2
Regression parameters for GEM and parent strains ofPseduomonas
chlor-oraphis3732 andPseudomonas ¯uorescenes2-79 survival and recovery
over time in six soils are reported as selective plate counts from 14 to 105 days after inoculation transformed log10(x11). Linear regression was used
since linear effects compared to quadratic and cubic effects were most signi®cant. Signi®cance between GEM and parent survival for each strain is reported as an F ratio from pair-wise comparison of slopes (Sokal and Rohlf, 1995)
Soil Inoculum Y-int Slope R2 X-inta Pr.Fb
AG 3732 Parent 4.87 20.031 0.53 157 NS GEM 5.77 20.034 0.76 170
BC 3732 Parent 5.13 20.028 0.54 184 NS GEM 6.21 20.034 0.70 182
CL 3732 Parent 5.87 20.023 0.75 261 NS GEM 6.07 20.020 0.76 303
NR 3732 Parent 6.11 20.028 0.82 218 NS GEM 6.76 20.023 0.80 291
SK 3732 Parent 6.14 20.027 0.84 256 NS GEM 6.74 20.017 0.54 391
UM 3732 Parent 5.61 20.038 0.70 146 NS GEM 6.16 20.036 0.81 171 Parent 5.41 20.041 0.61 133 NS 2-79 GEM 4.78 20.026 0.52 181
a The x-intercept represents the predicted number of days the GEM will
survive.
bThe probability of a signi®cant difference between slopes using anF
-ratio test; NSNot signi®cantly different ata0:05:
Colonies of both the 2-79 and 3732 GEMs were also lactose positive on differential media containing X-GAL.
The most signi®cantly different carbon sources between treatments in the majority of soils are shown (Table 3). Lactose and lactulose utilization were signi®cantly different
when comparing 3732 GEM inoculated and uninoculated treatments (Table 3), though not between uninoculated and 3732 parent inoculated wheat root communities. Lactose and lactulose utilization, representing function of the inserted lacZY genes, did not differentiate 2-79 GEM
J.V. Gagliardi et al. / Soil Biology & Biochemistry 33 (2001) 25±40
Fig. 2. UM soil 3732 GEM survival (dark hexagons) and total viable bacteria (light hexagons) are shown with lactose utilization patterns over time. BIOLOG least square mean optical density readings adjusted for covariates are shown for 3732 GEM inoculated (dark circles), 3732 parent inoculated (dark squares) and uninoculated (dark diamonds) treatments. Lines represent linear regressions extending to both axes.
inoculated, from 2-79 parent inoculated, or uninoculated wheat root communities in the UM soil (Table 3).
Functional diversity, de®ned as the total number of visible BIOLOG well responses (O.D..0.5), showed a small signi®cant difference in 2 out of 90 time point comparisons. Total community response for uninoculated treatments, de®ned as the least square mean of all covariate adjusted well O.D.s in a BIOLOG plate, gave the highest values for NR, followed by CL, SK, BC, UM and AG, respectively. The mean ofx-intercepts from survival predic-tions for all organisms inoculated to each soil (Table 2), a measure of survival longevity, showed the highest values for SK followed by CL, NR, BC, AG and UM, respectively.
CDA revealed that approximately 65% of the variance was represented by graphing the ®rst variable; adding a second variable represented up to 85% of the variance. Figures shown use only the ®rst two canonical variables, though MANOVA utilized the ®rst three CDA variables. The CDA variables for the SK soil analysis are graphed for all time points together (Fig. 4), and the same variables were culled for select time points (Figs. 5 and 6). No signif-icant difference between treatments was seen with the BIOLOG analysis after day 42 in the SK soil; effects are shown for day 84 (Fig. 6). The SK soil results are similar for the other soils, although the CL and NR soils in 1997 still showed signi®cant multivariate differences at 105 days. Signi®cant effects (MANOVA F ratios) in all soils
decreased over time in all soils as levels of the inoculated organisms also decreased.
Signi®cantly different fatty acids between treatments were compared to signature fatty acids (Vestal and White, 1989; Frostegard et al., 1993; Cavigelli et al., 1995) then sorted by type for each soil and treatment combination (Table 4) and the patterns compared. When comparing signi®cant effects (fatty acids) between treatments using previously reported signature fatty acids (Table 4), inoculation changed both the eubacterial and eukaryotic structure when comparing GEM by parent, GEM by uninoculated or parent by unino-culated effects in most of the soils. There were no reported signature fatty acids that consistently differentiated treat-ments. The inoculated pseudomonads mostly contained fatty acids common to all living organisms (10:0, 12:0, 14:0, 16:0) (data not shown). Some Gram-negative eubac-terial signature fatty acids (10.0 30H, 12:0 20H, 12:1 30H, 17:0 cyclo) were constituent to the inoculated organisms, but were not signi®cantly different between the uninocu-lated and inocuuninocu-lated wheat root communities (data not shown). Using a method for measuring biomass with fatty acids (Cavigelli et al., 1995), treatments were analyzed for signi®cant levels of the fatty acids 14:0, 16:0 and 18:0. Few signi®cant differences were seen, and the highest biomass at day 0 was not always for inoculated treatments. Fatty acids that were signi®cantly different between inoculated and uninoculated treatments were 25:0 (for 3732) and 24:0
J.V. Gagliardi et al. / Soil Biology & Biochemistry 33 (2001) 25±40
Table 3
The most signi®cantly different carbon sources were determined using an F-ratio test within each soil (SAS Ð proc GLM) and then results were compared to look for common effects. If these signi®cant carbon sources appeared in more than half of these tested soils, they are reported here. Percent signi®cance indicates the number of soils where the listed effect is seen
Treatment comparison 1996 1997
Carbon source %Sig.a Carbon source %Sig.a
3732 GEM vs. uninoculated a-d-Lactoseb 80 a-d-Lactoseb 100
Lactuloseb 80 Lactuloseb 67
p-hydroxy Phenylacetic acid 60 p-hydroxy Phenylacetic acid 50
l-Aspartic acid 50
3732 Parent vs unionculated d-Psicose 50
Mono-methyl Succiante 50
3732 GEM vs. 3732 Parent a-d-Lactoseb 100
Lactuloseb 67
b-methyl-d-glucoside 50
2-79 GEM vs. uninoculated d-Psicose c
a-keto-Butyric acid
2-79 Parent vs. uninoculated l-Leucine c
a-keto-Butyric acid Lactulose
a The percent of soils where this carbon source utilization is signi®cantly different for the treatment comparison.
30H (for 3732 and 2-79). Levels of these fatty acids were highest on day 0, and in some soils levels remained above background through day 14, then were indistinguishable from levels in uninoculated treatments (data not shown).
MANOVA using CDA variables from the fatty acid analysis showed decreasing signi®cance with time and with decreasing numbers of inoculated organisms in all soils. The greatest multivariate signi®cant differences were seen just after inoculation, when there were high levels of the inoculated organisms. In most soils there was no signi®cant difference 42 days after inoculation, though in the SK soil (Figs. 7±9) and NR soil (not shown), treatments were still signi®cantly different after 84 days, though sig-ni®cance steadily decreased over time. For the 2-79 GEM and parent in the UM soil (not shown), effects were similar to multivariate separation patterns and signi®cant differ-ences seen for the 3732 GEM and parent.
Comparing the two multivariate methods, BIOLOG proved more sensitive using MANOVA analysis for the BC, CL, and UM (with 3732) soils. Fatty acid MANOVA analysis was a more sensitive indicator of overall inoculated organism effects for the AG, SK and UM (with 2-79) soils. Both methods were equally sensitive with MANOVA analysis for the NR soil.
4. Discussion
We processed and inoculated dilutions from entire wheat root samples and chose a single plate incubation time of
72 h for the BIOLOG assay to simplify previously reported methods (Garland and Mills, 1991; Garland, 1996a) and to prevent bias due to sub-sampling of root tissue. It was not possible to standardize inoculum density for each BIOLOG plate and equally impossible to read the plates multiple times. We also used a different method for calculating BIOLOG well readings than those previously reported (Garland and Mills, 1991; Garland, 1996a, 1997). Subtract-ing the negative control well from other plate values caused deterioration of multivariate normality, an assumption that must be met prior to parametric multivariate analysis (Johnson and Wichern, 1992). Adjusting each data point of a plate, regardless of the signi®cance of the adjusting variable, produces a bias that alters measured effects, which mutes otherwise obvious trends. For these reasons, we found that using covariables with BIOLOG readings, in both univariate and multivariate models, gave the most repeatable results. This technique proved repeatable in two separate years using six different soils, and we observed the same univariate and multivariate effects following inoculation of P. chlororaphis 3732RN-L11 (3732 GEM) compared to uninoculated controls.
The BIOLOG assay was sensitive to small changes, as shown by the lactose utilization response by a small group of organisms in a large total viable population (Figs. 1 and 2). The lacZ trait is rare in soil bacteria (Barry, 1986, 1988) so this was a good indicator of the inoculated GEMS. Lactose utilization was the most signi®cant difference seen between 3732 GEM inoculated and all other treatments
J.V. Gagliardi et al. / Soil Biology & Biochemistry 33 (2001) 25±40
(Table 3). Linear regression of lactose utilization compared to viable 3732 GEM regression showed that BIOLOG analysis accurately portrayed potential activity of the inocu-lated 3732 GEM in a whole community analysis, since the
regressions were parallel (Fig. 1), though in other soils func-tion was reduced compared to survival (Fig. 2). Linear regression for lactose utilization (Fig. 1) showed that when viable 3732 GEM dropped below 104CFU g21root,
J.V. Gagliardi et al. / Soil Biology & Biochemistry 33 (2001) 25±40
Fig. 6. Functional assay (BIOLOG) canonical discriminant analysis results 84 days after inoculation for the SK soil. G3732 GEM inoculated (gray circles); P3732 parent inoculated (black circles); Uunionculated (light squares). MANOVA analysis of CDA variables indicates a signi®cant difference between treatments.
utilization by microbial communities in 3732 GEM inocu-lated microcosms was indistinguishable from uninocuinocu-lated or 3732 parent inoculated treatments. This puts BIOLOG assay sensitivity for activity of the 3732 GEM at a theor-etical 10 CFU g21root, since a 1023dilution was inoculated to the plates. We can infer that when the 2-79 and 3732 GEMs were at similar levels, that lacZY activity should have been similar. We cannot fully explain why the inserted genes in the 2-79 GEM functioned in pure culture but not as part of the wheat rhizosphere microbial population here, though 2-79 was only tested in one soil, and recoverable 2-79 was lower than for 3732 at most sampling times. Also, the UM soil was among the poorest in terms of survi-val of inoculated organisms, which may have played a role. Using other reporter genes or traits should yield equally sensitive responses, and functional assays may therefore be applicable for testing introduced organisms containing other
traits. Judging non-target effects to an indigenous microbial community is another matter. The signi®cant multivariate functional assay effects seen were mostly from responses of the inoculated microorganisms, and uninoculated treatments were not signi®cantly different from inoculated treatments after the introduced microorganisms had died off. Most effects other than lactose utilization varied randomly with no de®nable pattern. We assume that if there were effects in these already diverse metabolic communities, we could have quanti®ed them due to the sensitivity of this assay. Since 2-79 was intended as the microorganism to produce the most signi®cant community level effects, and it did not function in the UM soil microbial community as we had expected, we cannot de®nitively say if this functional assay will effectively show non-target effects at the micro-bial community level though if they occur, they may be masked by activity of the introduced microbes.
J.V. Gagliardi et al. / Soil Biology & Biochemistry 33 (2001) 25±40
Table 4
The ten most signi®cantly different fatty acids for each treatment comparison were determined using aF-ratio test within each soil (SAS Ð pro GLM). These fatty acids were then compared to previously reported signature fatty acids (Vestal and White 1989; Frostegard et al., 1993; Cavigelli et al., 1995). Each row contains 10 `*' symbols (one for each of the fatty acids analyzed) divided into columns corresponding to their reported signature fatty acid grouping, if any. G3732 GEM inoculated, P3732 parent inoculated, L2279 GEM inoculated, N2-79 parent inoculated, UUninoculated)
Soil Inoculum Year Comparison G-Nega G-Posb Eubc Eukd Nonee
AG 3732 1996 G-U ** *** ** ***
1997 G-U *** ** *****
P-U * * * ** ****
G-P * **** *****
3732 1996 G-U *** *******
BC 1997 G-U * *** * * ****
P-U * *** *** ***
G-P ** * *******
3732 1996 G-U *** ** * ** **
CL 1997 G-U ** *** *****
P-U * ** ** * ****
G-P *** *** ****
3732 1996 NDf
NR 1997 G-U * ** ** ****
P-U * *** * * ****
G-P ** ** * *****
3732 1996 G-U ** ** * *****
SK G-U * ** *******
P-U * * * * *****
G-P **** *** ***
UM 3732 1996 G-U * * * ** *****
G-U * *** * * ****
P-U ** * *** ****
G-P * *** * * *****
2-79 1997 L-U ** * ** ****
N-U * * ** *****
L-N * ** * * *****
a Characteristic of Gram negative eubacteria b Characteristic of Gram positive eubacteria c Characteristic of eubacteria in general d Characteristic of eukaryotes in general
Risk analysis of genetic constructs, in terms of transfer to indigenous microorganisms, may employ the lacZY genes prior to constructing a similar GEM with other inserted traits. In other words, test the overall safety of the genetic construct with lacZY only, and infer whether this trait is transferable to non-target microbes. Also, for ef®cacy test-ing of the genetic construct, assess whether this inserted `model' gene functions in the target environment.
The fatty acid assay results complemented the functional assay in terms of total microbial community response when quanti®ed with multivariate statistical methods. Multi-variate effects decreased as viable inoculated organisms declined. However, we lacked a signature fatty acid to complement lactose utilization as an indicator of sensitivity for the inoculated organisms. Signi®cant effects between treatments using previously reported signature fatty acids (Table 4) for eubacteria and eukaryotes indicate effects by the inoculated organisms, but not in populations that we quanti®ed. No de®nable trends for individual fatty acids constituent to the inoculated microorganisms were seen, though others (Tunlid et al., 1989) have reported increases in a microorganism constituent fatty acid following inocu-lation with Flavobacterium balustinum 299 to cucumber roots, along with an increase in a community fatty acid. The lack of signature fatty acids to track the microbes inocu-lated here was not a drawback, since multivariate statistical methods quantify changes to multiple variables, and repre-sent effects not visible in any single variable.
The fatty acids that were signi®cantly different in all
soils between inoculated and uninoculated treatments (25:0 and 24:0 30H) may be components of eukaryotes. Higher molecular weight fatty acids typically are reported as constituents of eukaryotic organisms (Vestal and White, 1989; Frostegard et al., 1993; Cavigelli et al., 1995), although these particular fatty acids have not yet been attributed to a speci®c group of organisms. These fatty acids could be constituents of grazing protozoa or nematodes that bene®ted from the inoculated organisms as a food source. Protozoa and nematodes have been distinguished in soils previously using phospholipid fatty acids (Grif®ths et al., 1999). Protozoa proved to be rare when we attempted to enumerate them (data not shown) so these comparisons were inconclusive. The inoculated pseudomonads were originally proposed for use as biocontrol agents (Monsanto Corp., 1987, 1988), so these fatty acids could be constituent to fungi that were inhibited. We could not measure speci®c pathogenic fungal levels directly during this study since selective media is currently not available (D.M. Weller, personal communication). These fatty acids also may have been from germinating seeds. Increased soil levels of these fatty acids seen just after inoculation and until 14 days may indicate that the inoculated pseudomonads stimu-lated the growing plants.
Since the fatty acid assay assessed the entire soil organ-ism population and not just viable and culturable bacteria, it was potentially a better method for determining non-target effects. The fatty acid assay contains more variables so there
J.V. Gagliardi et al. / Soil Biology & Biochemistry 33 (2001) 25±40
Fig. 7. Structural assay (FAME) canonical discriminant analysis results for the SK soil. Canonical discriminant analysis used the 10 most signi®cantly different fatty acid measurements between treatments within each soil. G3732 GEM inoculated (gray circles); P3732 parent inoculated (black circles); U
is a greater potential to assess rare, slow growing, or metabolically less active members of the microbial com-munity. In many cases, speci®cally when showing all time point variables for the SK soil (Fig. 7), parent inoculated
treatments were often indistinguishable from uninoculated populations Pr.F0:0893 here). This may indicate a greater in¯uence by the 3732 GEM than by the 3732 parent, or subtle differences in 3732 GEM fatty acid composition
J.V. Gagliardi et al. / Soil Biology & Biochemistry 33 (2001) 25±40
Fig. 9. Structural assay (FAME) canonical discriminant analysis results on day 84 after inoculation for the SK soil. G3732 GEM inoculated (gray circles); P3732 parent inoculated (black circles); Uunionculated (light squares). MANOVA analysis of CDA variables indicates a signi®cant difference between treatments.
compared to the 3732 parent. This may also indicate that the 3732 parent is most similar to the indigenous pseudomonads on wheat roots in these soils, and that the inoculated numbers do not overwhelm the indigenous pseudomonad populations in these soils. Differences in fatty acid compo-sition were not detected in pure 3732 GEM and parent cultures grown on media (data not shown). Fatty acid differ-ences between parent and GEM strains, if they occur, might only take place in a mixed culture environment. This may also indicate a differing competitive ability of the GEM strain compared to the parent and a displacement or enhancement of indigenous microorganisms.
Another calculation designed to measure non-target effects, did not show any effects, though it proved useful for another purpose. Total community response was measured in BIOLOG plates using uninoculated treatments only. A higher total community response in the SK, CL and NR soils coincided with extended survival (Table 2) of inoculated organisms in these soils. For the organisms tested here, a more actively respiring indigenous microbial community prior to inoculation meant that the inoculated organisms would survive longer compared to the other soils tested. This may indicate that soils already supporting diverse and active microbial communities will better support newly introduced microorganisms. Total microbial community function analysis using BIOLOG plates prior to inoculation may be a good indicator of expected survival for use in pre-release risk assessments.
We have shown that two whole soil community analyses, one measuring carbon source utilization patterns and the other fatty acids extracted from soil, can be used to differ-entiate inoculated organisms from indigenous populations on wheat roots in diverse soils. Results using multivariate analysis methods were similar between the six soils but differed in ability to detect speci®c changes. The assays yield ecologically different information, and both have the potential for assessing effects of many types of organisms or speci®c genes. Using these assays in tandem for non-target effects testing of microbial communities can provide useful information for pre-release risk assessment purposes at comparatively low cost and time input. We think that more stringent testing of organisms, including non-target effects testing, is warranted if: (1) extended survival, longer than six months of an introduced organism is expected; (2) effects on an indigenous microbial community are expected, such as when toxic compounds are produced by the inocu-lated organism, or; (3) if traits may be transferred from inoculated organisms to indigenous microbial community members and may persist, potentially changing microbial community structure and function.
Acknowledgements
This work was funded through a grant from the Canadian National Biotechnology Strategy. We wish to acknowledge
technical support from Terry McIntyre at Environment Canada and assistance from Mr Stan Tesch at the USDA.
Appendix A. SAS programming for univariate and multivariate analyses using covariates
(A) Univariate least square means for a BIOLOG well reading adjusted for covariates of the blank well OD, the inoculated bacterial density and the sample (root) weight.
PROC GLM DATABIOLOGOD NOPRINT; CLASS TRT TIME;
MODEL ODTRT|TME BLANK PC RWT/SS3; LSMEANS TRT|TIME /STDERR OUTLSDATA PDIFF; RUN;
PROC PRINT DATALSDATA; RUN
(B) Multivariate canonical discriminant analysis for select BIOLOG well readings adjusted for three covariates, and MANOVA analysis of canonical discriminant variables for each time point.
PROC DISCRIM DATEBIOLOGOD OUTOUT METHODNORMAL POOLYES MANOVA DISTANCE CAN NCAN3;
CLASS TRT; PRIORS PROP;
VAR OD1 OD2 OD3 OD4 OD5 OD6 OD7 OD8 OD9 OD10 BLANK PC RWT; RUN;
PROC SORT DATAOUT; BY DAY TRT CAN1 CAN2 CAN3; RUN;
PROC PRINT DATAOUT; VAR DAY TRT CAN1 CAN2 CAN3; RUN;
PROC ANOVA DATAOUT; BY DAY;
CLASS TRT;
MODEL CAN1±CAN3TRT/NOUNI; MANOVA HTRT;
RUN;
TRTTreatment; TIMENumber of days since inocu-lation that the sample was assayed; ODOptical density reading of a BIOLOG well, BLANKoptical density read-ing for the BIOLOG negative control well; PClog10(total
bacteria count); RWTFresh root weight with loosely adhering soil.
References
Angle, J.S., Levin, M.A., Gagliardi, J.V., McIntosh, M.S., 1995. Validation of microcosms for examining the survival ofPseudomonas
aureo-faciens(lacZY) in soil. Applied and Environmental Microbiology 61,
2835±2839.
Baath, E., Diaz-Ravina, M., Frostegard, A., Campbell, C.D., 1998. Effect of metal-rich sludge on the soil microbial community. Applied and Environmental Microbiology 61, 238±245.
Barry, G.F., 1986. Permanent insertion of foreign genes into the chromo-some of soil bacteria. Bio/technology 4, 446±449.
Barry, G.F., 1988. A broad host-range shuttle system for gene insertion into the chromosome of gram-negative bacteria. Gene 71, 75±84. Bochner, B.R., 1989. Breathprints at the microbial level. American Society
for Microbiology News 55, 536±539.
Brimecombe, M.J., De Leij, F.A.A.M., Lynch, J.M., 1998. Effect of geneti-cally modi®edPseudomonas ¯uorescensstrains on the uptake of nitro-gen by pea from 15N enriched organic residues. Letters in Applied Microbiology 26, 155±160.
Buyer, J.S., 1995. A soil and rhizosphere microorganism isolation and enumeration medium that inhibits Bacillus mycoides. Applied and Environmental Microbiology 61, 1839±1842.
Buyer, J.S., Drinkwater, L.E., 1997. Comparison of substrate utilization assay and fatty acid analysis of soil microbial communities. Journal of Microbiological Methods 30, 3±11.
Buyer, J.S., Roberts, D.P., Russek-Cohen, E., 1999. Microbial community structure and function in the spermosphere as affected by soil and seed type. Canadian Journal of Microbiology 45, 138±144.
Cavigelli, M.A., Robertson, G.P., Klug, M.J., 1995. Fatty acid methyl ester (fame) pro®les as measures of soil microbial community structure. Plant and Soil 170, 99±113.
Christie, W.W. (Ed.), 1995. Advances in Lipid Methodology Ð Two The Oily Press, Ayr, Scotland.
De Leij, F.A.A.M., Sutton, E.J., Whipps, J.M., Fenlon, J.-S., Lynch, J.M., 1995. Impact of ®eld release of genetically modi®edPseudomonas
¯uorescenson indigenous microbial populations of wheat. Applied
and Environmental Microbiology 61, 3443±3453.
Ellis, R.J., Thompson, I.P., Bailey, M.J., 1995. Metabolic pro®ling as a means of characterizing plant-associated microbial communities. FEMS Microbiology Ecology 16, 9±18.
Federle, T.W., 1986. Microbial distribution in soil: new techniques. In: Megusar, F., Gautar, M. (Eds.). Perspectives in Microbial Ecology, Slovene Society for Microbial Ecology, Ljublana, Yugoslavia, pp. 493±498.
Frostegard, A., Baath, E., Tunlid, A., 1993. Shifts in the structure of soil microbial communities in limed forests as revealed by phospholipid fatty acid analysis. Soil Biology and Biochemistry 25, 723±730. Frostegard, A., Tunlid, A., Baath, E., 1996. Changes in microbial
commu-nity structure during long term incubation in two soils experimentally contaminated with metals. Soil Biology and Biochemistry 28, 55±63. Garland, J.L., 1996a. Analytical approaches to the characterization of
samples of microbial communities using patterns of potential c source utilization. Soil Biology and Biochemistry 28, 213±221.
Garland, J.L., 1996b. Patterns of potential C source utilization by rhizo-sphere communities. Soil Biology and Biochemistry, 223±230. Garland, J.L., 1997. Analysis and interpretation of community-level
physiological pro®les in microbial ecology. FEMS Microbiology Ecol-ogy 24, 289±300.
Garland, J.L., Mills, A.L., 1991. Classi®cation and characterization of heterotrophic microbial communities on the basis of patterns of community-level sole-carbon-source utilization. Applied and Environ-mental Microbiology 57, 2351±2359.
Glimm, E., Heuer, H., Engelen, B., Smalla, K., Backhaus, H., 1997. Statis-tical comparisons of community catabolic pro®les. Journal of Micro-biological Methods 30, 71±80.
Graham, J.H., Hodge, N.C., Morton, J.B., 1995. Fatty acid methyl ester
pro®les for characterization of glomalean fungi and their endoymcor-rhizae. Applied and Environmental Microbiology 61, 58±64. Grif®ths, B.S., Bonkowski, M., Dobson, G., Caul, S., 1999. Changes in soil
microbial community structure in the presence of microbial-feeding nematodes and protoza. Pedobiologia 43, 297±304.
Haack, S.K., Garchow, H., Odelson, D.A., Forney, L.J., Klug, M.J., 1994. Accuracy, reproducibility, and interpretation of fatty acid methyl ester pro®les of model bacterial communities. Applied and Environmental Microbiology 60, 2483±2493.
Harch, B.D., Correll, R.L., Meech, W., Kirkby, C.A., Parkhurst, C.E., 1997. Using the Gini Coef®cient with BIOLOG substrate utilisation data to provide an alternative quantitative measure for comparing bacterial soil communities. Journal of Microbiological Methods 30, 91±101. Johnson, R.A., Wichern, D.W., 1992. Applied Multivariate Statistical
Analysis, . 3rd ed.Prentice Hall, Englewood Cliffs, NJ.
Khattree, R., Naik, D.N., 1995. Applied Multivariate Statistics with SAS Software, SAS Institute, Inc, Cary, NC.
Kleupfel, D.A., Kline, E.L., Skipper, H.D., Hughes, T.A., Gooden, D.T., Drahos, D.J., Barry, G.F., Hemming, B.C., Brandt, E.J., 1991. The release and tracking of genetically engineered bacteria in the environ-ment. Phytopathology 81, 348±352.
Levin, M., Strauss, H. (Eds.), 1991. Risk Assessment in Genetic Engineer-ing McGraw Hill, New York.
Lindstrom, J.E., Barry, R.P., Braddock, J.F., 1998. Microbial community analysis: a kinetic approach to constructing potential C source utiliza-tion patterns. Soil Biology and Biochemistry 30, 231±239.
Microbial ID Inc. (1992). Microbial Identi®cation System Operating Manual, Version 4, Newark, DE.
Moenne-Loccoz, Y., Powell, J., Higgins, P., Britton, J., O'Gara, P., 1998. Effect of the biocontrol agentPseudomonas ¯uorescenesF113 released as sugarbeet inoculant on the nutrient contents of soil and foliage of a red clover rotation crop. Biology and Fertility of Soils 27, 380±385. Monsanto Corporation (1987). Biotechnology Pre-manufacturing
Noti®ca-tion. Proposal for ®eld testing of hostPseudomonas ¯uorescenes(Ps. 3732RN) and genetically engineeredPseudomonas ¯uorescenes (Ps. 3732RNL11): a collaborative Study by Monsanto Co. and Clemson University: as submitted to the USEPA.
Monsanto Corporation (1988). Small scale ®eld testing of a lacZY (E. coli
K-12) engineering microbial fungicide: evaluation of wheat root colon-ization by Ps. 2-79RN-L3 and level of root infection by take all (Ggt) disease. Field testing information, volume 1: as submitted to the USEPA.
Nairn, J.D., Chanway, C.P., 1999. Recovery of a rhizosphere-colonizing gem from inside wheat roots. Canadian Journal of Microbiology 45, 612±615.
Naseby, D.C., Lynch, J.M., 1998a. Establishment and impact of
Pseudo-monas ¯uorescenes genetically modi®ed for lactose utilization and
kanamycin resistance in the rhizosphere of pea. Journal of Applied Microbiology 84, 169±175.
Naseby, D.C., Lynch, J.M., 1998b. Impact of wild-type and genetically modi®ed Pseudomonas ¯uorescenes on soil enzyme activities and microbial population structure in the rhizosphere of pea. Molecular Ecology 7, 617±625.
Naseby, D.C., Pascual, J.A., Lynch, J.M., 1999. Carbon fractions in the rhizosphere of pea inoculated with 2,4 diacetylphloroglucinol producing and non-producingPseudomonas ¯uorescenesF113. Journal of Applied Microbiology 87, 173±181.
SAS Corporation, 1988. SAS/STAT User's Guide, . Release 6.03 ed.SAS Institute, Inc, Cary, NC.
Seber, G.A.F., 1984. Multivariate Observations, Wiley, New York. Siciliano, S.D., Germida, J.J., 1998. BIOLOG analysis and fatty acid
methyl ester pro®les indicate that Pseudomonad incoulants that promote phytoremediation alter the root-associated microbial commu-nity ofBromus bibersteinii. Soil Biology and Biochemistry 30, 1717± 1723.
Siciliano, S.D., Theoret, C.M., de Freitas, J.R., Hucl, P.J., Germida, J.J., 1998. Differences in the microbial communities associated with the
roots of different cultivars of canola and wheat. Canadian Journal of Microbiology 44, 844±851.
Sokal, R.R., Rohlf, F.J., 1995. Biometry: the Principles and Practice of Statistics in Biological Research, W.H. Freeman and Company, New York.
Thomashow, L.S., Weller, D.M., 1988. Role of a phenazine antibiotic from
Pseudomonas ¯uorescens in biological control of Gaemannomyces
graminisvar.triticii. Journal of Bacteriology 170, 3499±3508.
Tunlid, A., Hoitink, H.A.J., Low, C., White, D.C., 1989. Characterization of bacteria that suppress rhizoctonia damping-off in bark compost media by analysis of fatty acid biomarkers. Applied and Environmental Microbiology 55, 1368±1374.
Vestal, J.R., White, D.C., 1989. Lipid analysis in microbial ecology. BioScience 39, 535±541.
Wander, M.C., Hedrick, D.S., Kaufman, D., Traina, S.J., Stinner, B.J., Kehrmeyer, S., R, ., White, D.C., 1995. The functional signi®cance of the microbial biomass in organic and conventionally managed soils. Plant and Soil 170, 87±97.
Weller, D.M., 1983. Colonization of wheat roots by a ¯uorescent pseudo-monad suppressive to take-all. Phytopathology 73, 1548±1553. Winding, A.K., 1994. Fingerprinting bacterial soil communities with
BIOLOG microtiter plates. In: Ritz, K., Dighton, J., Giller, K.E. (Eds.). Beyond the Biomass: Compositional and Functional Analysis of Soil Microbial Communities, Wiley, Chichester, UK.
Zak, J.C., Willig, M.R., Moorhead, D.L., Wildman, H.G., 1994. Functional diversity of microbial communities: a quantitative approach. Soil Biol-ogy and Biochemistry 26, 1101±1108.
Zelles, L., Bai, Q.Y., Beck, T., Beese, F., 1992. Signature fatty aids in phospholipids and lipooligosaccharides as indicators of microbial biomass and community structure in agricultural soils. Soil Biology and Biochemistry 24, 317±323.
Zelles, I., Bai, Q.Y., Ma, R.X., Rackwitz, R., Winter, K., Beese, F., 1994. Microbial biomass, metabolic activity and nutritional status determined from fatty acid patterns and poly-hydroxybutyrate in agriculturally managed soils. Soil Biology and Biochemistry 26, 439±446.
