Variation of Microbial Rhizosphere Communities in Response to Crop Species, Soil Origin, and Inoculation with Sinorhizobium meliloti L33

Variation of Microbial Rhizosphere Communities in Responseto Crop Species, Soil Origin, and Inoculation withSinorhizobium meliloti L33

R. Miethling,1 G. Wieland,2 H. Backhaus,2 C.C. Tebbe,1

1 Institut fur Agrarokologie, Bundesforschungsanstalt fur Landwirtschaft, Bundesallee 50, 38116

Braunschweig, Germany2 Institut fur Pflanzenvirologie, Mikrobiologie und biologische Sicherheit, Biologische Bundesanstalt fur

Land- und Forstwirtschaft, Messeweg 11/12, 38104 Braunschweig, Germany

Received: 20 October 1999; Accepted: 15 January 2000; Online Publication: 18 July 2000

A B S T R A C T

A greenhouse study with soil–plant microcosms was conducted in order to compare the effect of

crop species, soil origin, and a bacterial inoculant on the establishment of microbial communities

colonizing plant roots. Two crop species, alfalfa (Medicago sativa) and rye (Secale cereale), were

grown separately in two soils collected from agricultural fields at different locations and with

differing histories of leguminous crop rotation. A subset of microcosms was inoculated at 106 cfu

g-1 soil with the luciferase marker gene-tagged Sinorhizobium meliloti strain L33, a symbiotic partner

of M. sativa. Microbial consortia were collected from the rhizospheres of alfalfa after 10 weeks of

incubation and from rye after 11 weeks. S. meliloti L33 populations were one to two orders of

magnitude higher in the rhizospheres of alfalfa than of rye. In soil with previous alfalfa cultivation,

80% of the alfalfa nodules were colonized by indigenous bacteria, while in the other soil alfalfa was

colonized almost exclusively (>90%) with S. meliloti L33. Three community-level targeting ap-

proaches were used to characterize the variation of the extracted microbial rhizosphere consortia:

(1) Community level physiological profiles (CLPP), (2) fatty acid methyl ester analysis (FAME), and

(3) diversity of PCR amplified 16S rRNA target sequences from directly extracted ribosomes,

determined by temperature gradient gel electrophoresis (TGGE). All approaches identified the crop

species as the major determinant of microbial community characteristics. Consistently, the influ-

ence of soil was of minor importance, while a modification of the alfalfa-associated microbial

community structure after inoculation with S. meliloti L33 was only consistently observed by using

TGGE.

Correspondence to: Dr. Christoph C. Tebbe; Fax: (+49) 531 596 375 or 366;

E-mail: christoph.tebbefal.de

MICROBIALECOLOGY

Microb Ecol (2000) 41:43–56

DOI: 10.1007/s002480000021

© 2000 Springer-Verlag New York Inc.

Introduction

The rhizosphere, generally defined as that volume of soil

adjacent to and influenced by the plant root, can be regarded

as a “hot spot” for microbial colonization and activity [2]. In

contrast to bulk soil, where available organic carbon sources

are only at low concentrations, rhizospheres are supplied

with higher concentrations of nutrient sources generated

during plant photosynthesis. This supply of carbon sources

changes depending on the physiological status and age of a

plant [60] and selects for dynamic heterotrophic microbial

communities [16]. These communities normally consist of

several bacterial species with different capabilities as well as

fungal mycelia [39] that interact with each other and also

with their “host” plant. Such interactions can be pathogenic,

neutral, or beneficial for the plant. As variation in the mi-

crobial community structure may have effects on ecosystem

processes (e.g., nutrient recycling, decomposition) or the

effectiveness of microbial invasions (e.g., growth of patho-

gens, release of plant-growth promoting rhizobacteria or ge-

netically engineered microorganisms), understanding how

community processes affect ecosystem processes is of central

interest in ecology.

Because of the complexity of this system, a lack of effec-

tive methods for describing microbial rhizosphere commu-

nities has limited our understanding of its dynamics. In re-

cent years, several cultivation-independent, community-

level targeting techniques have been developed that can be

used as an alternative to traditional methods [10, 12, 33, 38,

55]. Each of these techniques generates a set of data from a

single sample. Data sets can be based on metabolic activities

or chemical compositions of cell consortia extracted from an

environmental sample, or they can detect heterogeneities of

specific genes within the microbial community [58]. Com-

pared to time-consuming cultivation and characterization of

isolates that include only the cultivable fraction of a com-

munity [6, 14], or sum parameters such as microbial bio-

mass or enzyme activities, the new methods allow larger

amounts of samples within the same period of time. This can

be crucial in ecological studies [12, 46, 47]. Until now, few

studies have compared different community-level tech-

niques in order to generate alternative views onto the com-

munity structure or evaluate the suitability of a method [18,

19, 58].

In this study, we analyzed the effects of crop species, soil

origin, and inoculation with a luciferase gene-tagged Sino-

rhizobium meliloti strain on the composition of microbial

rhizosphere communities with three different community-

level approaches. In greenhouse studies, two plants, alfalfa

(Medicago sativa) and rye (Secale cereale) were cultivated in

two soils collected at different locations. Both soils were

similar in their physicochemical composition but probably

differed in their microbial communities: One soil had a his-

tory of legume cultivation, and the other did not. It is known

that cultivation of alfalfa can increase the titer of indigenous

rhizobia that can serve as symbiotic partners for these plants

[53]. The survival of the inoculant could be easily followed

by detecting luciferase reporter gene activity of colonies

grown on a selective substrate. This technique has already

been successfully applied in other investigations for moni-

toring of inoculants in soil [11, 52].

For characterization of microbial populations in the rhi-

zospheres, the following approaches were applied in parallel:

(1) Community level physiological profiles (CLPP) mea-

sured as carbon source utilization by rhizosphere extracts.

This technique provides information about the combined

catabolic potentials. Using this approach, microbial commu-

nities from soils and rhizospheres of different plants could

be differentiated in other studies [3, 25, 26, 30, 61]. (2) Fatty

acid methyl ester analysis (FAME), a method that reflects the

structural diversity of bacterial species present in environ-

mental samples as all microbial cells are included without

cultivation. Such profiles, extracted in most applications

from the phospholipid fraction but also from the total lipid

fraction, have been used to characterize and compare com-

munities from soils and sediments [8, 10, 23, 31, 54, 62]. (3)

As a third method, ribosomal RNA was extracted and tran-

scribed by RT-PCR in order to describe the diversity of the

16S rRNA molecules and its variation. Since the presence of

ribosomes usually is linked to growth activity of microbial

cells [4, 59], it has been assumed that the analysis of ribo-

somal RNA gives access to the most active fraction of the

microbial community [20, 21, 34, 48]. The diversity of the

amplified 16S rRNA sequences, including the variable re-

gions V6 to V8, was characterized by temperature gradient

gel electrophoresis (TGGE). Resulting banding patterns can

be compared and similarities can be characterized by cluster

analysis [16, 17,18]. Using these three independent methods

in parallel, we assumed that the ecological significance of the

results on the variance of microbial rhizosphere communi-

ties could be increased and, thus, potentially allow a more

reliable detection of variations in response to the environ-

mental factors.

44 R. Miethling et al.

Materials and MethodsCharacterisation of Soils and the Bacterial Inoculant

Two soils from the plough layer (Ap-horizon) of agricultural fields

in Braunschweig (FAL, geographical location: 52° 17’ 359 N; 10° 26’

559 E; 81.2 m above sea level) and Straß-Moos (STM, 48° 25’ 129 N,

11° 18’ E, 404.2 m above sea level) were included in this study. The

characteristics of both soils are summarized in Table 1. Both soils

were collected in March before the beginning of the growing sea-

son. Stones and root material were removed by hand and the soils

were adjusted to approx. 40% saturation of their total water hold-

ing capacity.

The inoculant strain, Sinorhizobium meliloti L33, was obtained

from A. Puhler, Bielefeld. The strain is resistant to streptomycin

and carries a chromosomally inserted luciferase (luc) marker gene

[13].

Experimental Design

A total of 16 replicate microcosm containers (size of containers: 40

cm × 30 cm × 20 cm) were each filled with 36 kg soil. For each soil,

8 containers were sown with 2 g of alfalfa seeds (approx. 1,000 seeds

of Medicago sativa, “Europa”) and the other 8 with 12.5 g of rye

seeds (approx. 500 seeds of Secale cereale). Half of the alfalfa seeded,

and of the rye seeded containers, respectively, were inoculated with

S. meliloti L33. Thus, each treatment was tested in four replicates.

The microcosm containers were placed in a block-randomized ar-

rangement in the same greenhouse compartment with inoculated

and noninoculated microcosms separated from each other.

In order to prepare the inoculant, S. meliloti L33 was cultivated

in batch culture at 28°C for 24 h to late exponential growth phase

(R2A medium; Difco Laboratories, Detroit, MI). Cells were har-

vested by centrifugation and resuspended in sterilized tap water.

Cell numbers in the suspensions were determined microscopically

using a counter chamber (Thoma; Karl Hecht GmbH, Sondheim

Rohn, Germany) and adjusted to 2.4 × 108 cells ml-1. Inoculations

were conducted one day after sowing by pouring 150 ml of cell

suspensions evenly onto the soil surface of the respective micro-

cosms. This corresponded to a total of 3.6 × 1010 cells of S. meliloti

L33 per microcosm (106 cells g-1 soil). The noninoculated controls

were poured with water. Microcosms were incubated in the green-

house at 20 ± 5°C. The experiments were stopped when plants

reached the shoot stage and were approx. 25 cm high. Microcosms

with alfalfa were harvested 10 weeks after sowing, and those sown

with rye, after 11 weeks.

Extraction and Enumeration of Bacteria from Bulk Soiland Rhizospheres

Five grams of bulk soil (wet weight) were extracted with 0.1%

sodium hexametaphosphate solution for 30 min at 4°C at 200 rpm

with an overhead shaker (KH, Guwina-Hofmann, Berlin, Ger-

many). Dilutions of these soil suspensions were inoculated onto

nutrient-poor agar (NPA, [5]) amended with streptomycin (500

mg L-1) for cultivation of S. meliloti L33 and on plate count agar

(tryptone glucose yeast agar, Oxoid, Unipath Ltd., Basingstoke,

England). The inoculated growth media were incubated in the dark

at 28°C. Colony forming units (cfu) were determined after 1 d

(plate count agar) and 7 d (NPA) of incubation, respectively.

The expression of the luciferase marker gene was tested with

NPA-grown colonies. For this purpose, colonies were blotted from

growth agar onto nylon membranes (Hybond-N, Amersham In-

ternational, Little Chalfont, Buckinghamshire, UK), which then

were soaked with a luciferin solution (1 mM luciferin, Sigma-

Aldrich GmbH, Deisenhofen, Germany; in 100 mM sodium citrate

buffer, pH 5.0). Light emission was detected on a Kodak-T-MAT

DG film (Kodak-Pathe, Paris, France) placed on the filter mem-

branes in a film cassette. In order to allow air diffusion between

cells and the film material—the luciferase reaction is oxygen de-

pendent—a 0.5 cm thick distance holder was included in the film

cassette. The film material was exposed at room temperature for 16

to 24 h and was developed according to the protocol recommended

by the manufacturer (Kodak).

To enumerate rhizosphere bacteria, roots were carefully sepa-

rated from bulk soil. Root material was then transferred into sterile

50-ml Falcon tubes (10 g wet weight per tube; Sarstedt; Numbrecht,

Germany) and washed in 40 ml saline (0.85% NaCl) at 500 rpm in

an overhead shaker (Reax II, Heidolph, Germany) for 30 min at

4°C. The extracts were slowly centrifuged (150 × g) for 5 min to

remove mineral particles. The supernatants or their appropriate

dilutions were then immediately inoculated onto the respective

growth media.

Determination of Alfalfa Root Nodule Occupancy by S.meliloti L33

To obtain root nodules, a total of 10 intact alfalfa plants, including

root material, were collected from each relevant microcosm. Nod-

ules were counted and removed from the root material with sterile

forceps. Each single nodule was transferred into a separate well of

a microtiter plate containing 100 µl of 1 mM luciferin solution (see

previous paragraph). The nodules were crushed with a micro-pestle

Table 1. Characterization of soils used in this study

FAL soil STM soil

Soil TypePara brown

earth, silty sandBrown earth,sandy loam

History of crop rotationduring the past 5 years No legumes Alfalfa, frequently

Nitrate [mg N kg−1 soil] 4.31 61.91Ammonia [mg N kg−1

soil] 2.62 2.36pH 6.5 5.9Organic carbon [g C kg−1

soil] 7.94 9.62

Variation of Microbial Rhizosphere Communities 45

and, immediately, light emission was measured in a luminometer

(Labsystems Luminoskan RS, Helsinki, Finland) in triplicate, for 2

s at intervals of 5 min.

Community Level Physiological Profiles

Aliquots of rhizosphere extracts in saline were directly used to

inoculate microtiter plates containing 95 different carbon sources

and a control without carbon source (BiologGN, Biolog, Hayworth,

Ca.). A volume of 150 µl of the suspension was pipetted into each

well. For each microcosm, analyses were done in independent du-

plicates. In order to allow comparison between microtiter plates of

different microcosms, inoculum densities for each extract were de-

termined both by microscopy using a counting chamber and by

cultivation on R2A agar (Difco Laboratories) at 28°C. Deviating

from microscopic counts of approx. 2 to 5 × 108 bacterial cells per

ml for all extracts, 2.6 ± 1.1 and 2.8 ± 1.0 × 107 cfu ml1 for alfalfa

rhizospheres grown in FAL and STM soil, respectively, were enu-

merated on R-2A agar. For rye rhizospheres grown in FAL and

STM soil, only 2.5 ± 1.1 and 3.3 ± 1.4 × 106 cfu ml-1 were counted,

respectively. These lower numbers of cfu corresponded to slower

color development in the microtiter plates inoculated with rye rhi-

zosphere extracts as compared to those of alfalfa. Inoculated mi-

crotiter plates were incubated at 28°C, and the optical density (OD,

595 nm) was measured after 15, 18, 21, 24, and 48 h in a microtiter

plate reader (Vmax, Molecular Devices, MWG Biotech AG, Ebers-

berg, Germany). Data sets were normalized for their activity ac-

cording to Garland and Mills [26]. In order to further reduce biases

caused by divergent color development kinetics, data sets with

similar average well color development (AWCD) at different read-

ing times were used for comparison. A total of 64 data sets were

included in the overall analysis with an AWCD of 2.0 absorption

units as reference point. Principal component analysis (PCA) was

applied for multivariate statistical analysis using SAS (SAS 6.1, SAS

Institute Inc., Cary, NC). The correlation of the AWCD to the first

three principal components (PCs) was calculated using Pearson

correlation. Data sets were analyzed separately for further discrimi-

nation of data obtained from microbial consortia extracted from

each crop species but grown in different soils. To evaluate the effect

of inoculation in alfalfa and rye rhizospheres in both soils, data sets

at all reading times were statistically analyzed in groups. Addition-

ally, community results were analyzed for significant differences at

the a-level [29].

Fatty Acid Analysis

Fatty acid patterns were determined from the rhizosphere cell frac-

tion extracted from 10 g of washed root material in 100 ml saline.

Analyses were done with independent duplicates of each micro-

cosm. The cell fraction was collected from the suspensions by cen-

trifugation at 10,000 × g. Alkaline methanolysis, methylation, and

extraction of the fatty acid methyl esters with hexane/ether were

performed as described by Miller and Berger [41]. The resulting

fatty acid methyl esters (FAME) were separated by capillary gas

chromatography analysis using Chrompack CP 9001 (CP-Sil 5CB

fused silica column) equipped with a flame ionization detector.

Helium was used as carrier gas with a velocity of 25 cm s-1, split

1:50, with a 20 s splitless injection. The following temperature

program was used: 1 min at 60°C, 30°C min-1 to 150°C, 3°C min-1

to 250°C, holding for 10 min.

Relative retention times of the supposed fatty acid methyl esters

were compared to those of standards (Supelco Inc., Bellefonte, PA).

Terminology of fatty acids is as follows: total number of carbon

atoms, number of double bonds, followed by the position of the

double bond; cis and trans configurations, anteiso and iso-

branching are indicated by the prefixes c, t, and a, i, respectively. Cy

refers to cyclopropane fatty acids. A total of 34 fatty acids, among

them five which were unidentified, that were typically present at

>0.5% of the total were considered for statistical analysis. Differ-

ences in the resulting fatty acid pattern were analyzed by PCA as

described for CLPP.

Sampling and Isolation of Ribosomes

From each microcosm, root material (4 g wet weight) with adher-

ing soil particles was washed twice for 2 min in 40 ml saline. The

combined washing solutions were centrifuged at 8,000 × g for 10

min and the resulting pellets were used for isolation of ribosomes.

For convenience of coordinated handling of the large sample num-

ber, two rhizosphere samples collected from replicate rye micro-

cosms were pooled, resulting in only two instead of four replicates

from these experimental variants.

Ribosome isolation was done as described by Felske et al. [20]

with the following modifications: Samples obtained after ethanol

precipitation were centrifuged at 4°C and 15,000 × g for 30 min and

DNAase incubation was performed at 37°C for 30 min to remove

contaminant DNA. The ribosomal RNA was resuspended in 100 µl

1:1 TE/glycerol solution (vol/vol) [50] and stored at -20°C until

analysis. For reverse transcriptase-PCR (see following section),

rRNA was diluted 1:10 in TE/ glycerol solution.

Amplification of 16S rRNA Molecules

Reverse transcriptase PCR (RT-PCR) was performed with rTth

DNA polymerase (Applied Biosystems GmbH, Weiterstadt, Ger-

many). RT-reaction mixture (10 µl) contained 10 mM Tris-HCl

(pH 8.3), 90 mM KCl, 1 mM MnCl2, 5% (vol/vol) dimethyl sulf-

oxide (DMSO), 250 µM of each dATP, dCTP, dGTP, and dTTP,

760 nM primer L 1346 (see last paragraph of this section), 2.5 U

rTth DNA polymerase, and 1 µl template RNA. After overlaying the

RT-samples with 50 µl of mineral oil, the samples were incubated

for 15 min at 70°C. Following the reverse transcription, 40 µl PCR

solution of the following composition was added: 10 mM Tris/HCl

(pH 8.3), 100 mM KCl, 3.75 mM MgCl2, 0.75 mM EGTA (Sigma-

Aldrich Chemie GmbH), 0.05% (vol/vol) monolaureate (Tween 20;

Sigma-Aldrich Chemie GmbH), 50 µM of each dATP, dCTP,

dGTP, and dTTP, 65 nM primer L 1346, 190 nM primer U 968/GC

(as below), and 10 U AmpliTaq DNA-Polymerase (Stoffel frag-

ment, Applied Biosystems).

Amplifications were performed in a Hybaid OmniGene tem-


perature cycler (MWG Biotech AG) with the following program: 1

cycle at 94°C for 1 min, 35 cycles of denaturation at 94°C for 15 s,

annealing at 56°C for 20 s, and extension at 68°C for 40 s; and a

single final extension at 70°C for 5 min. The amplification products

were controlled for the correct size by electrophoresis in 1.5%

agarose gels and staining with ethidium bromide [50]. Negative

control experiments were included by testing amplifications with-

out reverse transcriptase [20], to verify that the removal of con-

taminating DNA was complete.

The selected primers for the amplification of eubacterial 16S

rRNA sequences were as follows: U 968/GC (58-(GC clamp)-AAC

GCG AAG AAC CTT AC-38) forward and L 1346 (58-TAG CGA

TTC CGA CTT CA-38) reverse. The primers hybridize with se-

quences corresponding to E. coli positions 968 to 984 [7] and 1330

to 1346 [20]. The GC rich sequence (5’-CGC CCG GGG CGC GCC

CCG GGC GGG GCG GGG GCA CGG GGG G-3’) was attached to

the forward primer; PCR products thus had a GC clamp that pre-

vented complete melting during separation in the gradient gel elec-

trophoresis [43].

Temperature Gradient Gel Electrophoresis

RT-PCR products were analyzed using a TGGE apparatus (Diagen

GmbH, Dusseldorf, Germany) in a polyacrylamide gel (6% w/v

acrylamide, 0.1% w/vol. bisacrylamide, 8 M urea, 20% vol/vol

formamide, 2% vol/vol glycerol, 0.17% (vol/vol) TEMED

(N,N,N,’N’-tetramethylenediamine), 0.04% (wt/vol) ammonium

persulfate) with 1 × MOPS-Puffer [20 mM 3-(N-morpholino)

propanesulfonic acid), 1 mM EDTA pH 8.0] at a fixed current of 28

mA (about 300 V) for 5 h. The temperature gradient increased in

direction of the electrophoretic run from 35°C to 50°C. After elec-

trophoresis, gels were silver stained according to Sanguinetti [51],

except that both staining and development lasted 15 min. Follow-

ing a final washing step, gels were further incubated for 7 min in

25% ethanol/10% glycerol solution and air-dried for conservation.

To compare the resulting TGGE generated PCR product pat-

terns, gels were digitalized (pdi 420oeTM scanner, MWG Biotech

AG) and the images were analyzed with the Diversity Database

software (pdi, MWG Biotech AG). The automatic band identifica-

tion by numbering was controlled visually. Similarities of patterns

were calculated using Dice coefficient based on band intensities and

unweighted pair group with mathematical averages (UPGMA).

Results

Fate of Soil-Inoculated S. meliloti L33 and Presence ofIndigenous S. meliloti Cells in FAL and STM Soil

Three factors potentially influencing the structure of the

rhizosphere microbial community were analyzed in this

study, i.e., crop species, soil, and a bacterial inoculation. In

order to correlate community variations to the presence of

inoculated cells, titers of S. meliloti L33 were determined at

the time of harvesting in bulk soil, rhizospheres and root

nodules of alfalfa. Additionally, to characterize the indig-

enous S. meliloti population, the amount of nonbiolumines-

cent nodules was also recorded (Table 2). When microcosms

were grown with the same crop, decline of S. meliloti L33 (t0

= 106 cfu g-1) was the same in both soils. In FAL soil grown

with alfalfa the titer was higher than in the same soil grown

with rye. This difference was not observed at a significant

level in STM soil.

In rhizospheres of alfalfa population sizes of S. meliloti

Table 2. Presence of S. meliloti L33 and total cultivated bacterial populations in rhizospheres at the end of the microcosm studies (10

weeks for alfalfa, 11 weeks for rye) when rhizosphere microbial communities were analyzed

Microcosms with alfalfa Microcosms with rye

S. meliloti L33in bulk soil

[cfu g-1]

S. meliloti L33in rhizosphere[cfu g-1 rootwet weight]

Total rhizospherebacteria on R2A

[cfu g-1 rootwet weight]

S. meliloti L33in bulk soil

[cfu g-1]

S. meliloti L33in rhizosphere[cfu g-1 rootwet weight]

Total rhizospherebacteria on R2A

[cfu g-1 rootwet weight]

FAL soil,inoculated withS. meliloti L33 4.59 × 104 a 2.57 × 106 4.06 × 107 b 1.60 × 104 d 1.14 × 104 5.83 × 106 e

STM soil,inoculated withS. meliloti L33 5.75 × 104a,g 8.16 × 105 1.10 × 108 c 3.33 × 104d,g 4.33 × 104 1.06 × 107 f

FAL soil,non-inoculated — n.d. 3.11 × 107 b — n.d. 5.50 × 106 e

STM soil,non-inoculated — n.d. 1.25 × 108 c — n.d. 1.62 × 107 f

Each value represents the mean of 4 replicates; numbers followed by the same letter (a, b, c, d, e, f, g) were not significantly different from each other(P < 0.05).n.d., not detected; detection limit 10-2 cfu g-1.


L33 were one to two orders of magnitude higher than in

rhizospheres of rye. This indicated stimulated growth of S.

meliloti caused by its symbiotic host, alfalfa. Significant dif-

ferences of S. meliloti L33 population sizes were detected

when alfalfa rhizospheres of both soils were compared.

Larger S. meliloti L33 populations were found in rhizo-

spheres of alfalfa grown in FAL soil. The total number of

rhizosphere bacteria, as judged by the number of R2A grown

colonies, was not affected by inoculation with S. meliloti L33

(P < 0.05). However, numbers obtained from alfalfa grown

in both soils were approx. one order of magnitude higher

than found with rye.

Results of nodule occupancy analysis from alfalfa root

material collected at the time of harvesting are shown in

Table 3. Indigenous S. meliloti were present in both soils, as

indicated by nodulated plants grown in soils not inoculated

with S. meliloti L33. Only 48% of the alfalfa plants grown in

FAL soil were nodulated. In STM soil the proportion of

nodulated plants was higher (68%), which corresponded to

the larger population size of indigenous S. meliloti. As a

consequence of inoculation, all plants grown in FAL soil and

almost all plants (93%) grown in STM soil were nodulated.

Nodules of plants grown in inoculated FAL soil were almost

exclusively (94%) colonized by S. meliloti L33. In contrast,

nodules obtained from inoculated STM soil grown plants

were mainly (79%) colonized by indigenous (nonbiolumi-

nescent) S. meliloti cells.

Community Level Physiological Profiles

Evaluation of physiological patterns from rhizosphere

samples from inoculated and noninoculated microcosms of

alfalfa and rye grown in both soils consistently revealed

crop-specific differences. Figure 1A shows the results for the

first two principle components of the overall analysis, which

included a total of 64 data sets. The separation of the crop-

specific groups followed principle component one (PC1)

Fig. 1. Principal component analysis of community-level physi-

ological profiles generated with Biolog GN of microbial rhizosphere

communities. PC1, principal component 1; PC2, principal compo-

nent 2. (A) Result of all combined data sets. (B and C) Results

obtained with data sets separated for each crop species. Commu-

nities were extracted from roots of alfalfa (squares) and rye (tri-

angles), from FAL soil (filled symbols) and STM soil (empty sym-

bols), from microcosms inoculated with S. meliloti L33 (with point

in symbols) and from noninoculated controls (no points in sym-

bols).

Table 3. Nodule occupancy of alfalfa plants collected from microcosms after 10 weeks, at the time of microbial community analysisa

Nodulated plants(%)

Average number ofnodules per

nodulated plantTotal number ofnodules analyzed

Proportion of nodulescolonized by S. meliloti

L33 (%)

FAL soil, inoculated with S. meliloti L33 100 6.4 245 94STM soil, inoculated with S. meliloti L33 93 6.6 291 21FAL soil, noninoculated 48 4.5 89 0STM soil, noninoculated 68 6.2 155 0

a Average 40 plants per treatment were included in the test.


which explained 49.5% of the total variance in the data. PC1

was not correlated to the overall metabolic activity of the

microtiter plates (r2 = 0.04). The clustered groups were ho-

mogenous in regard to the crop species from which they had

been extracted. The underlying functional basis for the dif-

ferences were determined according to Garland [24] by

evaluating the correlation of the 95 substrates to the respec-

tive principal component (Table 4). A positive correlation

indicates that the carbon source showed a greater response

in samples with higher scores for the axis, i.e., rye, while

negative correlation indicates greater utilization in samples

with lower scores, i.e., alfalfa. For microbial communities

from alfalfa rhizospheres, substrates with high discrimina-

tory power (factor weight) were mostly carboxylic acids and

amino acids. Rye rhizosphere extracts showed a stimulated

response toward carbohydrates and amino acids.

The analysis of separate data sets obtained from alfalfa

and rye rhizosphere communities enabled a separation ac-

cording to the soil origin for each crop species that could not

be seen in the overall analysis (Figs. 1B and 1C). This indi-

Table 4. Correlation of carbon source and fatty acids variables to principal component 1 as analyzed by principal component analysis of

microbial consortia extracted from rhizospheres of alfalfa and rye grown in two different soils (see Fig. 1)

Alfalfa Rye

Carbon source Factor weight Carbon source Factor weight

Carbohydrates Carbohydrateslactulose -0.947 D-fructose 0.882

Carboxylic acids D-galactose 0.958acetic acid -0.952 gentobiose 0.857formic acid -0.963 maltose 0.868malonic acid -0.939 D-melibiose 0.921propionic acid -0.961 L-rhamnose 0.905succinic acid -0.964 D-sorbitol 0.950bromosuccinic acid -0.959 sucrose 0.853mono-methyl succinate -0.968 D-trehalose 0.919alpha-hydroxybutyric acid -0.964 Carboxylic acidsalpha-ketovaleric acid -0.904 cis-aconitic acid 0.875

Amino acids Amino acidsL-leucine -0.970 L-aspartic acid 0.874L-treonine -0.917 L-glutamic acid 0.885glycyl-L-glutamic acid -0.946 L-proline 0.899glycyl-L-aspartic acid -0.938 hydroxyproline 0.884

Amides L-pyroglutamic acid, 0.903glucuronamide -0.962 L-serine 0.934alaninamide -0.986

Miscellaneous2,3 butandiol -0.978D,L-glycerol phosphate -0.959

Fatty acids Fatty acids

Straight chain Straight chain16:0 -0.726 14:0 0.77017:0 -0.784 Hydroxy-FA18:0 -0.757 3OH-12:0 0.745

Hydroxy-FA Unsaturated2OH-14:0 -0.830 14:1(11) 0.7452OH-16:0 -0.777 18:1(7) 0.829

Unsaturated Branchedct18:1(9,11) -0.875 i15:0 0.738cy-17:0 -0.682 i17:1(7) 0.858

Not identified Not identifiedunl-C18 -0.832 un2-C18 0.851

un1-C19 0.865


cates that soil properties also affected the specific microbial

communities in the rhizospheres of both plants. The sepa-

ration was a result of a combination of PC1 and PC2. The

overlap of both groups, as detected with both crop species

indicated that soil specific factors influenced the patterns less

than the crop species.

Variation of microbial rhizosphere communities in re-

sponse to the inoculation with S. meliloti L33 could not

consistently be detected within PC1 to PC3 at any plate

reading time when analyzing the appropriate subset of data

for inoculated and noninoculated treatments (data not

shown). However, testing resulted in significant differences

between inoculated and noninoculated treatments for both

crop species and soils at an a-level of 5% when including the

first five principal components for analysis (data not

shown).

Fatty Acid Profiles

For principal component analysis, a total of 34 commonly

found bacterial fatty acids were included in our analyses

(Fig. 2). The variances between the patterns were smaller

with fatty acid profiles than with CLPP as indicated by eig-

envalues of the single principal component. As detected by

CLPP, fatty acid profile analysis showed that the crop species

generated the major differences while the effect of the soil

origin was less distinct (Figs. 2B and 2C).

Fatty acids from microbial rhizosphere communities with

high discriminating value for crop species separation are

shown in Table 4. Negative factor loadings were indicative

for alfalfa where typical fatty acids for Gram-negative bac-

teria (hydroxy fatty acids, even straight-chain fatty acids,

cyclopropane fatty acids) resulted in high factor weights. Rye

rhizosphere samples were more responsive to a number of

fatty acids typical for Gram-positive bacteria, such as

branched or odd-number fatty acids.

The effect of inoculation with S. meliloti L33 was only

detectable in one case by separate evaluation of inoculated

versus noninoculated replicates. Alfalfa grown in FAL soil

resulted in significantly different fatty acid profiles (data not

shown). This was the sample in which also the highest cell

numbers of S. meliloti L33 was measured (Table 2).

Diversity of Eubacterial RT-PCR-amplified 16S rRNA Sequences

Repeated runs of the same RT-PCR products, as well as

repeated amplification of the same RNA extracts followed by

TGGE, produced highly similar banding profiles. This indi-

cated that the approach was reproducible. In addition,

TGGE profiles of high similarity were generated from the

replicate microcosms for rhizosphere extracted ribosomal

fractions. This is shown in Fig. 3 for alfalfa rhizospheres

grown in inoculated and noninoculated FAL soil.

The crop species had the most obvious effect on the re-

sulting fingerprints. The patterns of the rhizosphere of alfalfa

differed clearly from those of rye (Fig. 4). When the same

crop species was cultivated in different soils, the resulting

fingerprints were similar, differing in only a few, but often

dominant bands. This is demonstrated for alfalfa grown in

both FAL and STM soil (Fig. 4, lanes 4–7).

Differences due to an S. meliloti L33 inoculation of mi-

crocosms with rye could not be detected either in STM soil

(Fig. 4, lane 1–2) or in FAL soil, as the resulting patterns

were highly similar. In contrast, TGGE profiles of alfalfa

rhizospheres differed in a few bands regarding their intensity

as a result of the inoculation. This can be seen in the lower

part of Fig. 3, where a band was only detectable in samples

Fig. 2. Principal component analysis of fatty acid profiles gener-

ated from microbial rhizosphere communities. (A) All data sets; (Band C) results with data sets separated for alfalfa and rye, respec-

tively. For symbols, see Fig. 1.


of inoculated variants. Although the inoculated strain con-

stituted a significant proportion of the cultivated bacterial

community of alfalfa in FAL soil (Table 2), we could not

detect bands that were identical to those generated from S.

meliloti L33 pure cultures (no figure). This may be explained

by the fact that the template concentration of the inoculant

in the community DNA was much lower than suggested by

colony forming units, since it is known that the cultivated

bacteria represent only a small fraction of the total bacterial

community.

The similarity of all generated 16S rRNA profiles was

quantified by cluster analysis, whereby the number, position

and intensity of bands was taken into account. The similarity

dendrogram of the microbial rhizosphere communities (Fig.

5) showed that crop species had the most pronounced effect

on the patterns, followed by the influence of soil origin. A

shift in the microbial community due to an inoculation with

S. meliloti L33 was detectable by pattern clustering only in

fingerprints generated from the host plant rhizospheres

(with both soils). This effect was more pronounced in FAL

than in STM soil, as detected by cluster analysis. However,

the pattern variations detected as a response to inoculation

were only minor compared to the influence of the factors

crop species and soil origin. In case of rye rhizosphere de-

rived patterns from inoculated and noninoculated treat-

ments, the variation of experimental replicates outweighed

any effect of inoculation.

Discussion

Bacterial colonization and selection of specific microbial

communities in rhizospheres are potentially influenced by a

large variety of environmental factors. From these factors we

compared three that we considered to be important: (i) crop

species, which is the crucial factor for the supply of energy

and carbon to the heterotrophic microbial community by

producing root exudates, (ii) soil origin, which presumably

harbours a reservoir of microbial cells selected by the specific

history (e.g., climate, land use), and (iii) presence of an

Fig. 3. TGGE generated patterns of RT-PCR products amplified

from ribosomal fractions extracted from alfalfa rhizosphere grown

in FAL soil in four replicate microcosms: noninoculated (lanes 2 to

5) and inoculated with S. meliloti L33 (lanes 6 to 9). Lanes 1 and 10

show pure culture products that were used as markers. Fig. 4. TGGE of RT-PCR products amplified from ribosomal

fractions extracted from alfalfa and rye rhizospheres grown in FAL

and STM soil: lane 1–2, rye grown in STM soil, noninoculated and

inoculated; lane 3, pure culture products that were used as markers;

lanes 4–5, alfalfa grown in FAL soil, inoculated (4) and non-

inoculated (5); lanes 6–7, alfalfa grown in STM soil, inoculated (6)

and noninoculated (7).


additional bacterial strain with a potentially high capacity for

rhizosphere colonization.

All three community-level approaches (CLPP, FAME,

and TGGE) applied in our study showed that the crop spe-

cies had the most significant influence on the microbial rhi-

zosphere community. Alfalfa and rye grown in the same soil,

either FAL or STM, enriched two significantly different mi-

crobial rhizosphere communities from the same pool of soil

bacteria. Both rhizosphere communities degraded similar

carbon sources when extracted from the same crop species

(CLPP analysis, Fig. 1). Discriminative substrates of the rhi-

zospheres from alfalfa and rye (Table 4) are known as typical

root exudates [9] and were identical in both soils. This

means that the specific plant rhizosphere selected in each

case a microbial consortium that had the same immediate

metabolic activity. The fatty acid patterns from the microbial

cell fraction of the rhizosphere extracts could be also differ-

entiated by principal component analysis and resulted in

major differences for the crop species. The overall calculated

differences in the fatty acid profiles resulted in less total

variance (20–25%) than with CLPP (60–70%) in the first

three principal components, mainly because of the univer-

sality of fatty acids. Thus, changes in the bacterial diversity

resulted only in shifts of quantities of single fatty acids. As

dominating fatty acids exist in wide range of taxa [37, 49], it

is difficult to relate differences in fatty acid profiles to certain

groups of microorganisms [32]. Nevertheless, the commu-

nities of alfalfa and rye were assembled by Gram-negative as

well as Gram-positive bacteria, as indicated by the occur-

rence of hydroxy fatty acids, cyclopropane acids, and

branched, odd-numbered fatty acids, respectively.

The diversity analysis of 16S rRNA TGGE generated pro-

files corroborated the results obtained with CLPP and

FAME. Cluster analysis of the TGGE patterns (Fig. 5), which

Fig. 5. Dendrogram illustrating the similarities of RT-PCR amplified ribosomal sequence TGGE profiles obtained from rhizospheres and

evaluated by Dice similarity analysis and unweighted pair group algorithm with arithmetic averages. The line chart in the right part of the

figure shows the normalized TGGE patterns.


were based on fingerprints with up to 35 bands per sample,

generated a major distance between the microbial rhizo-

sphere communities of both crop species. However, it has to

be considered that the number and intensity of bands does

not exactly represent the number and abundance of active

species within the microbial community, as one organism

may produce more than one TGGE band because of se-

quence heterogeneity in the ribosomal genes [45]. By con-

trast, it has been demonstrated that it is not always possible

to separate 16S fragments that have a certain amount of

sequence variation [57]. Resolution as a function of separa-

tion distance and band dimension, as well as the sensitivity

of signal generation and band detection, determines the

maximum of separable bands. In general terms, only the

most dominant species of very complex communities will

contribute to the fingerprint [22, 42]. Furthermore, banding

patterns are subject to the selectivity of RNA extraction and

bias inherent in PCR-based techniques, e.g., preferential am-

plification and chimera and heteroduplex formation [56].

Even though such limitations of TGGE analysis are partly

compensated by an approach relying on pattern comparison,

the diversity represented by TGGE has to be considered as a

relative term [17]. Here we have shown that TGGE analysis

of 16S rRNA fragments is applicable to complex microbial

communities and is especially well suited for sensitive com-

parisons of large sets of samples from the same habitat. As a

precondition, pattern variations between independent rep-

licates need to be characterized and distinguished from treat-

ment-dependent modifications. Digital image analysis and

calculations of pattern similarities could be utilized in our

study to detect these treatment-specific effects.

Soil factors played a minor role in affecting the microbial

community in the rhizosphere; however, they were consis-

tently detectable with all three methods used in this study.

Similar results were reported by Germida et al. [27], who

investigated the bacterial communities associated with roots

of canola and wheat plants grown in soils from two different

climatic zones by means of isolate-based diversity analysis.

In contrast, other reports demonstrated that soil factors had

a larger impact in determining the composition of microbial

rhizosphere communities. For example this was shown for

the fluorescent Pseudomonas populations in rhizospheres of

flax and tomato [36]. Bachmann and Kinzel [1] investigated

soil–plant interactions from six different plants in four ag-

ricultural soils and found that in most cases the soil was the

dominating factor in the combination. However, some

plants, among them alfalfa, were able to predominate certain

soil factors. The heterogenic results of these studies seemed

to be strongly dependent upon plant species being investi-

gated and/or the choice of the applied methods of charac-

terization.

In our study, the soil factor also had an important impact

on another aspect: in STM soil, with a history of legume

cultivation, approx. 70% of the alfalfa plants were nodulated,

in FAL soil only 50%. In microcosms inoculated with 106S.

meliloti L33 cells per g soil the ratio changed to almost 100%

nodulation in both soils with the distinction that only 6% of

the nodules from alfalfa grown in FAL soil were induced by

the indigenous strains, but 79% of the nodules in STM soil

were. This indicated that the impact of an exogenous inocu-

lant was dependent on soil factors providing a different pool

of soil bacteria.

Variation of the microbial rhizosphere community struc-

ture due to the inoculation with S. meliloti L33 was detect-

able with all applied approaches, but to different extents:

TGGE and fatty acid profiles in FAL soil were able to detect

an effect of inoculation with alfalfa, but not with rye rhizo-

spheres. This is in accordance with cell numbers determined

in the rhizospheres. Whereas the rhizospheres of rye were

colonized with approx. 104 cfu S. meliloti L33 per g root

fresh wt., 106 cfu S. meliloti L33 per g root fresh wt were

enumerated for alfalfa rhizospheres (Table 2). Compared to

the total number of alfalfa rhizosphere bacteria grown on

R2A agar, S. meliloti L33 represented approx. 6% of the total

cultivable community in FAL soil and 0.7% in STM soil, but

only 0.3% in average of the microbial community of rye

rhizospheres. Therefore, the impact of inoculation on the

structure of the rhizosphere communities was related to the

threshold of detection for the assay used (TGGE, fatty acid

analysis). However, higher number of indigenous S. meliloti

in STM soil compared to FAL soil did not affect the survival

of the inoculant in rhizospheres of alfalfa, as cell numbers

were determined in the same order of magnitude. This is

consistent with the results obtained from the comparison of

TGGE fingerprints: the differences between inoculated and

noninoculated microcosms from either FAL or STM soil

were in the same order of magnitude. A shift in the fre-

quency distribution of active microbes, as caused by inocu-

lation, could not be noted in response to different levels of

indigenous S. meliloti populations in FAL and STM soil.

With CLPP the effect of inoculation of alfalfa could be

expected to be minor, because indigenous S. meliloti pre-

sumably show the same metabolic activity as the inoculated

strain. This is consistent with our evaluation of data by prin-

cipal component analysis, shown in Fig. 1B, as well as with

the separate evaluation for alfalfa rhizospheres. In rhizo-


spheres of rye, S. meliloti is not necessarily present in rel-

evant numbers or activity; therefore, a “stranger” such as S.

meliloti L33 could hypothetically alter the metabolic re-

sponse. Because of the small cell numbers found in the rhi-

zosphere of rye, the effect will probably not be detectable in

the metabolic potential of the whole community. However,

Fig. 2C indicates a clustering of noninoculated and inocu-

lated replicates of rye rhizosphere. Single evaluation of data

sets that should improve the discrimination did not show a

clear distinction among the first three principal components.

Statistical analysis according to Glimm et al. [29], which

included the first five principal components, resulted in sig-

nificant differences at a a-level of 5% for alfalfa and rye

rhizosphere profiles in response to the inoculation with S.

meliloti L33. Despite this result, the question of ecological

relevance arises when data need to be mathematically con-

densed and analyzed with the first five principal components

in order to detect significant differences. In our opinion, the

results indicate that the impact of S. meliloti L33 on the

microbial rhizosphere communities of alfalfa and rye in re-

gard to their physiological profiles is minor, especially when

compared to the factors crop species and soil origin.

Other studies, investigating the impact of inoculation,

showed similar results. The colonization of rhizospheres

from maize was not significantly affected by the presence of

an exogenous strain, even when the inoculant Burkholderia

cepacia was more abundant [44]. Only a short-term distur-

bance was observed in rhizospheres of young wheat roots

inoculated with Pseudomonas fluorescens [14]. In that study,

the inoculant caused a significant decrease of the percentage

of fast-growing soil bacteria in the first 4 weeks and was

restricted on the upper part of the roots. In contrast, Gilbert

et al. [28] reported a higher species richness assessed as

physiological attributes of bacterial isolates from soy bean

rhizospheres inoculated with Bacillus cereus UW85n1.

The results of our study demonstrate that the crop species

had the most pronounced effect on the structure of the

microbial rhizosphere community, followed by the soil,

whereas the colonization of the rye roots by indigenous mi-

croorganisms was not considerably affected by the presence

of an exogenous strain. However, inoculation with S. meliloti

L33 showed a minor impact on the composition of microbial

rhizosphere community of alfalfa, as detected with TGGE

patterns. The fact that three independent methods yielded

similar results confirms our conclusions. Even though the

crop species most strongly influenced the selection of a mi-

crobial rhizosphere community in our study, it should be

taken into consideration that our results only referred to a

“snapshot” in the succession of microbial root colonization

during plant growth. There is evidence that the microbial

diversity in rhizospheres varies over time [14, 15, 35, 40, 44].

Thus, the influence of different environmental factors may

underlie temporal changes and need to be investigated with

appropriate community-level techniques, in order to further

advance our understanding of microbial community dy-

namics in rhizospheres.

Acknowledgments

We thank Phoung Tuong Nyguen and Regine Neumann for

their excellent technical assistance and Bert Engelen for his

help on the statistical analysis of CLPP. The work was sup-

ported by the grants of the German Ministry for Education

and Research, BMBF (grant no. 11203).

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