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Original article

Composition of diazotrophic bacterial assemblagesin bean-planted soil compared to unplanted soil

Pilar Juniera,b,*, Thomas Junierd, Karl-Paul Witzelb, Margarita Caruc

aEcole Polytechnique Federale de Lausanne, CH-1015 Lausanne, SwitzerlandbMax-Planck Institute for Evolutionary Biology, Postfach 165, 24306 Plon, GermanycDepartamento de Ciencias Ecologicas, Facultad de Ciencias, Universidad de Chile. Casilla 653- Santiago, ChiledUniversite de Geneve, CH-1211 Geneve, Switzerland

a r t i c l e i n f o

Article history:

Received 30 April 2008

Received in revised form

28 October 2008

Accepted 31 October 2008

Published online 28 November 2008

Keywords:

Rhizospheric effect

Diazotrophic bacteria

Phaseolus vulgaris L.

Rhizobium

nifH

Terminal restriction fragment length

polymorphism

nifD

Denaturing gradient gel

electrophoresis

* Corresponding author. EPFL ENAC ISTE EMfax: þ41 21 693 6205.

E-mail address: pilar.junier@epfl.ch (P. Ju1164-5563/$ – see front matter ª 2008 Elsevidoi:10.1016/j.ejsobi.2008.10.002

a b s t r a c t

The effect of common bean (Phaseolus vulgaris L.) on the composition of nitrogen fixing

bacterial assemblages in soil was studied by comparing planted and unplanted soil. The

community composition was studied by terminal restriction fragment length poly-

morphism (T-RFLP) of the nitrogenase reductase gene (nifH ). Principal component analysis

(PCA) of T-RFLP profiles showed the separation of profiles from planted and unplanted soil.

Terminal restriction fragments (T-RFs) corresponding to rhizobial bacteria were identified

preferentially in planted soil; however most nifH T-RFs in soil could not be assigned to

T-RFs simulated from a database of known diazotrophs. To specifically study rhizobial

bacteria in the soil and nodules, PCR products from the alpha subunit of the nitrogenase

enzyme (nifD) were analyzed by denaturing gradient gel electrophoresis (DGGE). DGGE

results showed the specific stimulation of the rhizobial microsymbionts in planted soil.

ª 2008 Elsevier Masson SAS. All rights reserved.

1. Introduction agricultural systems are prone to high annual losses of N and

Nitrogen is an essential nutrient limiting primary production

in many terrestrial and aquatic ecosystems [3]. Biological

nitrogen fixation (BNF), the reduction of atmospheric N2 to

NH4þ, constitutes the main input of combined N into

biosphere [7,16]. In tropical and subtropical regions,

L, CE 1 644 (Centre Est),

nier).er Masson SAS. All rights

land degradation. In these areas, the use of BNF in symbiotic

systems between rhizobial bacteria (Allorhizobium, Rhizobium,

Azorhizobium, Bradyrhizobium, Mesorhizobium and Sino-

rhizobium) and leguminous plants, is a common agricultural

practice for intercropping with non-leguminous plants

[13,14,25].

Station 6, CH-1015 Lausanne, Switzerland. Tel.: þ41 21 693 6396;

reserved.

e u r o p e a n j o u r n a l o f s o i l b i o l o g y 4 5 ( 2 0 0 9 ) 1 5 3 – 1 6 2154

The effect derived of BNF on the N content in soil depends

on the rates of N2 fixation in the legume rhizobial nodules,

which are in turn related to many physical, environmental,

and biological factors [14,26]. One of the biological factors that

might affect BNF is the structure of root-associated bacterial

communities and their interaction with the plant. Legumes

have been shown to affect the structure of rhizobial pop-

ulations [6], and recent studies suggested that non-rhizobial

betaproteobacteria [19] and actinobacteria [20] are also

affected by secretion of plant exudates. However, the effect of

legumes on the composition of other groups of microorgan-

isms, such as those involved in nitrogen cycling in soil, is

poorly understood.

Microorganisms capable of carrying out BNF, also called

diazotrophs, are widespread among different bacterial and

archaeal clades. Despite their diversity, nitrogen fixation is

performed using an evolutionarily conserved enzyme called

nitrogenase, which is composed of two multisubunit metallo-

proteins. Component I, containing the active site, is encoded

by the genes nifD and nifK, while component II, coupling the

electron donor with component I, is encoded by the gene nifH

[27]. Several PCR primers have been designed to amplify nifH,

nifD or the intergenic region (IGS) between nifD and nifK to

study the community composition of N2-fixers in general or of

particular groups of species [5,17,23,27,28].

This study was designed to address the question whether

diazotrophic bacterial assemblages in soil are affected by the

presence of a legume crop (Phaseolus vulgaris L.). The

community composition was assayed by a culture-indepen-

dent approach targeting two functional genes for nitrogen

fixation (the nitrogenase genes nifH and nifD). Additionally,

considering that the external supply of combined N can

eventually inhibit BNF in the system, which might lead to

differentiate the effect of the plant not due to N2 fixation, three

watering regimes were assayed as well.

2. Material and methods

2.1. Bacterial strains

The bacterial strains used in this study included: Rhizobium

tropici CIAT899, Rhizobium sp. NGR234, Bradyrhizobium japoni-

cum USDA110, Bradyrhizobium sp. USDA16, Bradyrhizobium sp.

CIAT3101, Mesorhizobium loti MAFF303099. When necessary,

the strains were grown at 28 �C in yeast extract-mannitol

medium (YEM) prior to DNA extraction.

2.2. Soil samples, nodule collection and acetylenereduction assay in nodules

The soil used for the experiments was collected from the

organic layer (0–20 cm) of a field that was previously used to

cultivate the legume Medicago sativa in the central region of

Chile, near Santiago. Soil was dried and sieved through

a 10 mm mesh prior to usage. Common bean (Phaseolus vul-

garis, variety Venus) was sown in 10 6-L pots (one plant per

pot) containing 5 kg of sieved soil (treatment P). Another 10 6-L

pots, also containing 5 kg of sieved soil, were kept unplanted

(treatment S). Considering the previous use of the soil to grow

legume plants, the soil was expected to bear natural symbiotic

populations and therefore inoculation with rhizobia was not

carried out. The main chemical characteristics of the soil were

determined before the experiment. They were as follows: pH,

7.9; organic matter, 4.5%; NH4þ and NO3

� content, 7.0 mg kg�1;

phosphorus, 47.0 mg kg�1; potassium, 120.0 mg kg�1.

The pots were watered every second day with 150 mL of

water, maintaining an average humidity of 10%. Once a week,

three different watering treatments were assayed. One subset

of four pots of treatments P and S was watered with 10 mL of

Hoagland nutrient solution containing nitrate as 0.4 mM

KNO3, and also 0.4 mM MgSO4, 0.4 mM KH2PO4, 0.4 mM

Ca(NO3)24H2O (sub-treatment N). Another subset of four pots

of treatments P and S was watered with 10 mL of the same

solution but supplying 0.4 mM CaCl2 and 0.4 mM KCl instead

of nitrate (sub-treatment H). Two pots of treatments P and S

were maintained without addition of nutrient solution (sub-

treatment W). Soil samples were taken at 0 (T0), 20 (T1), 40 (T2)

and 60 (T3) days after seeding. Approximately 2 cm3 of soil

were collected from the area immediately surrounding the

main root of the plant by means of an in-house plastic corer of

1 cm diameter. The samples were kept at �20 �C until DNA

extraction. Additionally 1 g of soil was collected and dried for

analysis of percentage of nitrogen and carbon using a FLASH

2000 NC Analyzer (Thermo Scientific). An ANOVA test was

carried out for the results of the determination of nitrogen and

carbon using the R statistical software package.

After 60 days, plants were collected and nodules harvested.

For determinations of the nitrogen fixation rates 2–4 nodules

were collected and placed in 10-mL hermetic containers. 10%

of the headspace was replaced by acetylene, and ethylene

production was monitored after 6 h of incubation at 28 �C with

a Shimadzu 8A gas Chromatograph with flame ionization

detector [1,11]. Nodules for molecular studies were exten-

sively washed in sterile water (40 washes) to avoid contami-

nation with soil bacteria. Washed nodules were kept at �20 �C

until DNA extraction.

2.3. DNA extraction, nifH amplification and terminalrestriction fragment polymorphism (T-RFLP)

Total DNA from soil was extracted using the UltraClean Soil

DNA Kit (MoBio), following the manufacture’s guidelines.

Washed nodules were homogenized in TES buffer (Tris–HCl

0.2 M; EDTA 5 mM; NaCl 100 mM; pH 8.0) and DNA was

extracted using digestion with proteinase K (200 mg mL�1) and

lysozyme (1 mg mL�1) in TES buffer, followed by extraction

with chloroform:isoamyl alcohol, and ethanol precipitation.

A fragment of approximately 500 bp of the nitrogenase

reductase gene (nifH ) was amplified using the primers nifHF

(50-AAA GGY GGW ATC GGY AAR TCC ACC AC-30, positions

34–59 of S. meliloti) and nifHR (50-TTG TTS GCS GCR TAC ATS

GCC ATC AT-30, positions 466–491 of S. meliloti) [17]. PCR was

performed in 50 ml containing 5 pmol of each primer, 1.5 mM

MgCl2, 1� PCR buffer (25 mM MgCl2; 10 mM Tris–HCl; 50 mM

KCl, pH 8.3), 10 pmol of each dNTP and 1 U of Taq polymerase

(Roche). The amplification program consisted of: initial

denaturation at 94 �C for 5 min; 35 cycles of denaturation at

94 �C for 30 s, annealing at 52 �C for 30 s and extension at 72 �C

for 30 s; final extension at 72 �C for 7 min. These PCR products

e u r o p e a n j o u r n a l o f s o i l b i o l o g y 4 5 ( 2 0 0 9 ) 1 5 3 – 1 6 2 155

were cleaned using a multiscreen plate (Millipore), diluted 50

times and used as template in a second PCR with the labeled

primers nifHF 5-carboxyfluorescein (FAM) and nifHR 6-car-

boxil-x-rhodamine (6-ROX). In the second amplification

a touchdown program was carried out [10]. For each sample

three independent PCR reactions were pooled, gel purified,

quantified and digested overnight at 37 �C with 5 U of HaeIII,

MspI, MboI or HaeIII–MspI. Restrictions were separated on an

ABI3100 Automated Sequencer. Fragment size was estimated

by comparison with the standard ROX-500 (Applied Bio-

systems). T-RFLP data were analyzed using GeneScan 3.1

software (Applied Biosystems). For principal component

analysis (PCA, Statistica v6, Statsoft Inc.), samples were pre-

sented as points in an n-dimensional space where n is the

number of different T-RFs, which are recorded as present and

absent.

In silico T-RFLP analysis was carried out with a computer

program created during this study. The program performs

both in silico PCR screening and restriction endonuclease

digestion. PCR screening was carried out with a database of

157 nifH sequences from identified species of diazotrophs that

were downloaded from GenBank. The search engine allowed

up to three mismatches with the primers. Amplicons were

digested with the three restriction enzymes assayed experi-

mentally. Lengths of the forward and reverse terminal-

restriction fragments (T-RF) were calculated counting the

number of string characters from the terminal end to the first

cutting site for a given restriction endonuclease. Assignment

of unknown peaks in the samples to known bacteria from the

database was realized by comparing experimental and theo-

retical T-RFs allowing 1% of error in the size determination for

the experimental results. In order to improve the assignment,

the results from all the digestion were combined. The reli-

ability of the identification was measured taking into account

whether a particular species was identified with all the

enzymes or only with a subset of them.

2.4. Design of nifD primers, nifD PCR and cloning

The primers nifD432f (50-CAT CGA CGA GAT CGA GGA-30,

positions 432–449 of R. etli) and nifD785r (50-GAC CAG TTG CCG

ACC A-30, positions 770–785 of R. etli), were designed from an

alignment of all complete rhizobial nifD sequences (101

sequences) using the software GeneFisher (http://bibiserv.

techfak.uni-bielefeld.de/genefisher/). Optimized conditions

for a 50 ml PCR reaction were: 10 pmol each primer, 1� PCR

buffer (25 mM MgCl2; 10 mM Tris–HCl; 50 mM KCl, pH 8.3),

10 mmol each dNTP, 2.5–10 ng of template DNA and 1 U of Taq

polymerase (Roche). The temperature program consisted of an

initial denaturation at 94 �C for 5 min, followed by 35 cycles of

denaturation at 94 �C for 30 s, annealing at 58 �C for 30 s, and

extension at 72 �C for 30 s, with a final extension at 72 �C for

7 min. Annealing temperature was optimized at 58 �C

according to the melting temperature of the primers. For

cloning, PCR products were prepared with the proof-reading

Pfu DNA polymerase (Promega), and cloned with the Zero

Blunt PCR cloning kit (Invitrogen). From each cloned sample 48

clones were picked and checked for inserts of the expected

size by PCR with the plasmid-specific primers M13f/M13r. For

screening of the clones, one-shot sequencing with M13f was

performed using the BigDye terminator v3.1 cycle sequencing

kit (Applied Biosystems). After initial screening, clones with

identical sequences were grouped into eight groups of

sequences, and one clone representing each group was

selected for complete sequencing of both strands. These

sequences were deposited in GenBank with the following

accession numbers: DQ185054–DQ185062.

2.5. Denaturing gradient gel electrophoresis (DGGE) andsequencing of DGGE bands

For DGGE, PCR products were re-amplified using the modified

primer nifD432f with a 40 bp GC-clamp attached [10]. PCR

conditions remained the same, but the first 20 cycles were

performed with a touchdown of the annealing temperature

from 68–58 �C. DGGE was performed with the D-Gene System

(BioRad) in 7.5% polyacrylamide gels with a denaturing

gradient of 35–70% (100% denaturants contained 420 g L�1

urea and 400 mL L�1 deionized formamide in 0.5� TAE). Gels

were run in 0.5� TAE buffer at 200 V and constant tempera-

ture of 60 �C for 12 h. Band patterns were highly reproducible

under these experimental conditions. After staining the gels

with SYBRgold (Molecular Probes), bands were punched with

a sterile pipette tip, transferred to 100 ml HPLC water and

frozen at �18 �C until reamplification, purification and

sequencing as mentioned above.

2.6. Phylogenetic analysis

The sequences were compared with those in GenBank using

BLASTN [2], on the NCBI’s homepage (http://www.ncbi.nlm.

nih.gov/blast/Blast). Phylogenetic analyses were carried out

with the ARB program version 07.12.07org (http://www.arb-

home.de). All nifD sequences in GenBank (173 sequences)

were integrated and aligned into the database, correcting the

alignments by visual inspection. The alignments were made

for both nucleotide and amino acid sequences. One hundred

and eighteen positions in the alignment of proteins were

considered for the phylogenetic reconstruction. No filter was

applied for the calculation. The phylogenetic tree was con-

structed using the PHYLIP subroutine in ARB by the neighbor-

joining algorithm using a distance matrix calculated with the

Jones–Taylor–Thornton (JTT) as substitution model. One

thousand bootstraps were calculated to test the robustness of

the clades obtained. The NifD sequence of the cyanobacte-

rium Nostoc sp. PCC7120 was used as an outgroup.

3. Results

3.1. Plant growth and nitrogen fixation

All bean plants grown in the laboratory developed mature

fruits after 60 days and displayed similar foliar C/N ratios

(Table 1). Visual inspection of the roots showed that they

possessed 7–10 rhizobial nodules. The nitrogen fixation

activity in nodules measured by ethylene production varied

between 1405.1 to 1673.5 nmol C4H4 d�1 g�1 (Table 1). The

number of nodules and the fixation activity were similar

Table 1 – Percentage of foliar nitrogen and carbon, C/Nratios and nitrogen fixation rates determined forcommon bean plants.

Soiltreatment

%N %C C/N ratio Ethylene production(ppm h�1 g�1)

PH 2.8 49.4 18.0 1521.9

PN 3.1 50.1 16.2 1040.3

PW 2.7 52.4 19.6 918.3

3.5 T0 T1 T2 T3

0

0.05

0.1

0.15

0.2

0.25

0.3

PH PN PW SH SN SWTreatment

T0 T1 T2 T3A

B

e u r o p e a n j o u r n a l o f s o i l b i o l o g y 4 5 ( 2 0 0 9 ) 1 5 3 – 1 6 2156

between the different watering regimes and did not show any

effect of NO3� addition.

Additionally, the effect of the plant on the content of

nitrogen in soil was evaluated. The percentage of nitrogen, as

well as carbon, was measured at the different time points

(Fig. 1). An ANOVA carried out with the results did not show

any statistically significant effect of the plant (nitrogen

P-value ¼ 0.54 and carbon P-value ¼ 0.23), nor the watering

regime (nitrogen P-value ¼ 0.05 and carbon P-value ¼ 0.48), on

N- and C-contents in soil. However, a statistically significant

effect of the sampling time over the content of N and C was

found (nitrogen P-value ¼ 2.31e-07 and carbon P-value ¼ 0.03).

0

0.5

1

1.5

2

2.5

3

PH PN PW SH SN SWTreatment

Fig. 1 – Percentage of nitrogen (A) and carbon (B) in soil at 3

(T0), 16 (T1), 40 (T2), and 60 (T3) days after seeding. P, soil

3.2. Composition of diazotrophic assemblages in soil

A positive PCR amplification of the nifH gene was obtained

from all soil samples. The digestion of the PCR products with

four restriction enzymes produced in total 212 T-RFs. When

these T-RFLP patterns were submitted to principal component

analysis (PCA) the percentage of the variance attributed to

component 1 and 2 was 21% and 34%, respectively. In the

graphic representation, the T-RFLP patterns were separated

into two main groups: one consisting mainly of samples from

planted soil and the other from unplanted soil. The sole

exceptions to this separation were the samples SHT2 and

PWT1 that were grouped with the opposite treatment (Fig. 2).

However, there was no a clear factor explaining the position of

these two particular samples on the PCA. The separation of

the T-RFLP patterns into these groups was confirmed by

cluster analysis (data not shown). The different water regimes

did not have an effect reflected on the grouping of the samples

in the PCA.

planted with P. vulgaris; S, soil without plants; H, addition

of Hoagland nutrient solution without nitrate; N, addition

of Hoagland nutrient solution with nitrate; W, addition of

water.

3.3. In silico determination of composition of thediazotrophic assemblages

The nifH database has become one of the largest non-

ribosomal gene sequence collections [27], facilitating the

inference of diazotrophs composition based on in silico

analysis. The comparison of experimental and theoretical

T-RFs predicted from a nifH database allowed the tentative

identification of 40 T-RFs with groups reported in the database

(Table 2). However, the majority of the T-RFs observed

experimentally (172 T-RFs) did not coincide with any predicted

T-RF, indicating the existence of a high proportion of

unidentified diazotrophs in the analyzed soil.

In general, individual fragments could not be assigned to

a single species, but rather to a group of related species. Thus,

in order to increase the reliability of the T-RF assignation, the

results were scored according to the number of enzymes

where it was possible to assign experimental and theoretical

T-RF to a particular species (Table 2). Among the identified

T-RFs, the most frequent species were rhizobial bacteria,

including the genera Rhizobium, Sinorhizobium, and Bradyrhi-

zobium. T-RFs coinciding with those from these species were

identified in the results from all the enzymes assayed

(Table 2). Clostridium cellobioparum and the cyanobacteria

Anabaena sp. L-31 were the only non-rhizobial species

potentially identified in the results from all the enzymes.

Fig. 2 – PCA analysis of T-RFLP profiles in soil. P, soil planted with P. vulgaris; S, soil without plants; H, addition of Hoagland

nutrient solution without nitrate; N, addition of Hoagland nutrient solution with nitrate; W, addition of water. Samples were

taken at 3 (T0), 16 (T1), 40 (T2), and 60 (T3) days after seeding.

Table 2 – In silico identification of T-RFs in soil.

Group Species Enzymes

Rhizobial Rhizobium sp. ANU289 4

Rhizobial Rhizobium sp. NGR234 4

Rhizobial Sinorhizobium meliloti 4

Rhizobial Mesorhizobium loti 4

Rhizobial Bradyrhizobium japonicum

USDA110

4

Clostridia Clostridium cellobioparum 4

Cyanobacteria Anabaena sp. L-31 4

Actinobacteria Frankia alni 3

Cyanobacteria Plectonema boryanum 3

Cyanobacteria Cyanothece sp. ATCC51142 3

Alphaproteobacteria Azospirillum brasilense 3

Alphaproteobacteria Rhodospirillum rubrum 3

Betaproteobacteria Azoarcus sp. BH72 3

Gammaproteobacteria Azotobacter vinelandii 3

Gammaproteobacteria Azotobacter chroococcum 3

Cyanobacteria Anabaena variabilis 2

Cyanobacteria Anabaena azollae 2

Cyanobacteria Fischerella sp. UTEX1931 2

Betaproteobacteria Burkholderia cepacia 2

Deltaproteobacteria Geobacter sulfurreducens 2

Gammaproteobacteria Klebsiella pneumoniae 2

Rhizobial Rhizobium etli 2

Rhizobial Rhodopseudomonas palustris 2

Chlorobia Chlorobium tepidum 1

Cyanobacteria Trichodesmium sp. IMS101 1

Cyanobacteria Synechococcus sp. 1

Cyanobacteria Nostoc sp. 7120 1

Cyanobacteria Nostoc commune 1

Deltaproteobacteria Desulfovibrio gigas 1

Epsilonproteobacteria Wolinella succinogenes 1

Species were sorted according to the number of positive detection

in the different restrictions carried out (enzymes). Frequency of the

species in the planted and unplanted treatments is shown.

e u r o p e a n j o u r n a l o f s o i l b i o l o g y 4 5 ( 2 0 0 9 ) 1 5 3 – 1 6 2 157

Experimental T-RFs coinciding with those from typical soil

bacteria such as Rhodospirillum rubrum, Azospirillum, Bur-

kholderia and Frankia were observed too, as well as those from

non-typical soil diazotrophs such as cyanobacteria (Anabaena,

Nostoc and Cyanothece). In all these species, the match between

experimental and theoretical T-RFs was obtained only in three

of the four enzymes assayed.

The frequency of the identified T-RFs in the samples was

estimated for those species that were found at least with three

of the enzymes. T-RFs coincident with fragments from

rhizobial bacteria such as Rhizobium sp. ANU234, Sinorhizobium

meliloti and Bradyrhizobium japonicum were more frequent in

samples from planted soil, whereas other groups including

Rhodospirillum, Azotobacter, Azospirillum and different cyano-

bacteria, were a slightly more frequent in unplanted soil.

3.4. nifD primer specificity and PCR evaluation

In order to assess specifically the effect of the plant on the

rhizobial communities, new primers were designed to amplify

specifically the gene nifD. The theoretical evaluation of the

primers showed that the forward and reverse primer each

matched completely all nifD sequences from the genera

Rhizobium, Sinorhizobium and Mesorhizobium, but they have

several mismatches with bacteria from the genus Bradyrhi-

zobium and non-rhizobial bacteria (Fig. 3). nifD sequences from

Allorhizobium and Azorhizobium were not available and there-

fore similarity could not be evaluated. Additionally, specificity

was evaluated in silico by a BLAST search in GenBank. The

sequences retrieved by BLAST corresponded only to Rhizo-

bium, Sinorhizobium and Mesorhizobium, indicating that this

primer combination is specific for these genera.

Primer specificity was analyzed experimentally using DNA

from rhizobial and non-rhizobial diazotrophic bacteria as

template. A PCR band with the expected size was obtained

Fig. 3 – Alignment of the forward (A) and reverse (B) primers with nifD sequences from rhizobial and non-rhizobial bacteria.

Rhizobial sequences were selected from an alignment of all complete nifD sequences available in GenBank. Shade indicates

mismatching positions with the primers.

e u r o p e a n j o u r n a l o f s o i l b i o l o g y 4 5 ( 2 0 0 9 ) 1 5 3 – 1 6 2158

from R. tropici CIAT899, Rhizobium sp. NGR234, R. meliloti

CIAT44, and M. loti MAFF303099, but failed with B. japonicum

USDA110 and Bradyrhizobium sp. USDA16. Amplification was

also obtained with a strain isolated from a bean-nodule

(RN131), which belongs to Phyllobacterium spp. based on 16S

rDNA similarity. With other non-rhizobial diazotrophs

(Frankia sp., Anabaena sp. PCC7120, Acidithiobacillus ferrooxidans

ATCC 23270 and Burkholderia cepacia LB400) amplification was

not obtained. The amplification from environmental samples

produced a single PCR product of the expected size (351 bp)

with DNA from all the nodules and the soil samples (Fig. 4).

Fig. 4 – Agarose gel electrophoresis of nifD PCR products

amplified from nodules and soil. Individual nodules were

sampled from three Phaseolus vulgaris plants. Soil samples

were obtained at two different times from pots with beans.

The bands corresponding to 507 and 344 bp are indicated.

3.5. DGGE of nifD

Rhizobial cultures used as standard showed a distinct band

pattern after DGGE. The band from R. tropici CIAT899 was

located at the higher denaturing concentrations around 58%

(Fig. 5). Bands from M. loti MAFF303099 and Rhizobium sp.

NGR234 were located at denaturant concentrations around

55%. DGGE band patterns of nifD from nodules showed one

band common to all the samples, which was also observed in

Fig. 5 – DGGE of nifD amplicons from soil and nodules of

Phaseolus vulgaris. Coding of nodules according to Fig. 4.

Soil samples from unplanted (S) or planted pots (P) were

taken at 0 (T0) and 60 (T3) days after seeding. Arrow

indicates the common band between nodules and soil. The

bands excised from the gel and sequenced are indicated by

numbers on the DGGE gel (see Table 3).

e u r o p e a n j o u r n a l o f s o i l b i o l o g y 4 5 ( 2 0 0 9 ) 1 5 3 – 1 6 2 159

the soil samples. DGGE analysis with soil produced more

complex patterns with several bands located in the region of

lower denaturant concentration (40–50%) that do not coincide

with any of the standards.

Some of the DGGE bands were sequenced directly from the

gel for identification of the products. Sequences from bands of

the cultured strains Mesorhizobium loti MAFF303099 and

Rhizobium sp. NGR234 corresponded to sequences of the same

species in the database (Table 3). The sequence of the band

common to all nodules coincided with nifD from R. etli CFN42.

Table 3 – Identification of bands from the DGGE gel afterexcision, reamplification and sequencing.

DGGEband

First Hit in BLAST Accessionno.

Identity

1 Rhizobium sp.NGR234 AE000105 100%

2 Mesorhizobium loti MAFF303099 BA000012 100%

3 Rhizobium etli strain CFN42 REU80928 100%

4 Sinorhizobium medicae AJ584682 98%

5 Rhizobium etli strain 8c-3 DQ058415 90%

6 Sinorhizobium meliloti AJ584696 91%

7 Rhizobium etli strain CFN42 REU80928 100%

8 Rhizobium etli strain CFN42 REU80928 100%

For the position of the DGGE band in the gel see Fig. 3.

This was also the case for the band from soil with the same

mobility. Sequences of additional bands from the soil samples

corresponded to S. medicae, S. meliloti and R. etli strain 8c-3.

3.6. Effect of the plant on the composition of rhizobialcommunities

The DGGE analysis was applied in all the samples from plan-

ted and unplanted soil. The composition of rhizobial bacteria

in soil analyzed by nifD DGGE showed that in samples from

planted soil, the band patterns remained stable the different

sampling times, whereas in samples from unplanted soil, they

were less constant and some bands that have been observed

in samples from planted soil disappeared (Fig. 6A). Cluster

analysis of the DGGE patterns showed that samples from

planted soil are more related to each other than to those of

unplanted soil. The cluster analysis did not show any effect of

the water regime (Fig. 6B).

The band observed in all samples from planted soil was

identified by direct sequencing and shown to be identical to

nifD from R. etli CFN42 (Band level indicated by arrow in Fig. 5).

In the soil, also sequences related to nifD from Sinorhizobium

were identified (band located around 40% of denaturant

concentration). This band appears more or less constantly in

all samples from planted and unplanted soil.

3.7. Sequence analysis of clone libraries

In order to complement the results of DGGE band sequencing,

PCR products from a nodule and a soil sample were cloned and

sequenced. All 38 clones from the nodule were identified as

nitrogenase alpha-subunit (nifD) from R. etli CFN42, confirming

the results obtained from the sequencing of bands from the

DGGE gel. In the clone library from the soil sample, nifD

sequences were similar to R. etli and S. medicae and S. meliloti,

also coinciding with the results from the direct band

sequencing. No unspecific amplifications were detected in the

clone libraries. In a phylogenetic analysis, clonal nifD

sequences grouped in two clusters (Fig. 7). The first cluster

contains nifD sequences from nodules and soil similar to R.

etli. The second cluster contains those sequences related to

Sinorhizobium.

4. Discussion

The results from this study showed for the first time that

Phaseolus vulgaris affects the composition of indigenous diaz-

otrophic communities in soil. The results suggested that while

the plant has an effect, the different watering regimes assayed

did not modify the composition of diazotrophic assemblages

in both, planted and unplanted soil. Similar results have been

reported by Bardgett et al. [4], who found that diazotrophic

assemblages in upland grasslands were more affected by

differences in the vegetation than by N fertilization. Other

study addressing the effect of nitrogen on the composition of

diazotrophic bacteria in the rhizosphere of Spartina alterniflora

found that plant rhizosphere limits the short-term (2 and

8 weeks) impact of nutrient amending [15]. However, recently

Tan et al. [21] found that fertilization significantly affected the

Fig. 6 – Analysis of rhizobial nifD by DGGE. (A) DGGE gel of nifD PCR products. (B) Cluster analysis. P, soil with P. vulgaris; S,

soil without plants; H, addition of Hoagland nutrient solution without nitrate; N, addition of Hoagland nutrient solution with

nitrate; W, addition of water. Samples were taken at 3 (T0), 16 (T1), 40 (T2), and 60 (T3) days after seeding.

Fig. 7 – Phylogenetic tree based on the NifD sequences obtained in this study (in bold, with number of identical clones

indicated) and from rhizobial bacteria. For details see Section 2.6.

e u r o p e a n j o u r n a l o f s o i l b i o l o g y 4 5 ( 2 0 0 9 ) 1 5 3 – 1 6 2160

e u r o p e a n j o u r n a l o f s o i l b i o l o g y 4 5 ( 2 0 0 9 ) 1 5 3 – 1 6 2 161

composition and activity of diazotrophic assemblages asso-

ciated with rice rhizosphere. In rice, this effect was attributed

to the rapidly decaying of the plant biomass that affects the

exchange of indigenous diazotrophic communities differently

adapted to N-depleted conditions. In our experiment, several

factors might explain the lack of a significant effect of the

watering regime. Although, in the case of planted soil it is

possible that the rhizosphere of P. vulgaris contributed to limit

the effect of nutrient addition, in unplanted soil, the existence

on indigenous diazotrophic communities adapted to variable

nutrient conditions seems to be more a likely explanation.

It is widely accepted that the addition of combined N such

as NH4þ, NO3

�, and urea reduces the potential of the legumes to

fix atmospheric N [14,24]. However, hydroponic experiments

of nodulation in Pisum sativum have demonstrated that

concentrations of 0.1–0.5 mM NH4þ [24] and 0.625 mM NO3

� [12]

stimulated nodulation. In the case of Phaseolus vulgaris no

extensive studies have been carried out in this respect, and

based on the above results, we tend to assume that NO3�

concentrations assayed in our study were neither inhibitory

nor stimulant, since all the plants analyzed here presented

similarly active nodules.

This study also describes a fast procedure to analyze

rhizobial populations in situ without cultivation. Despite the

fact that rhizobial-legume symbiotic interaction is very

important in agricultural practices, few attempts have been

made to analyze directly rhizobial populations in their natural

habitats [18]. Plant trapping, the most popular technique to

study rhizobial populations, present some limitations, such as

the underestimation of non-actively infecting and unculti-

vable rhizobia and the lost of information concerning the

original distribution in undisturbed soil [18,22]. Therefore, the

development of alternative methodologies allowing strain

identification directly from nodules or soil might be of great

interest for the study of rhizobial bacteria. The nifD primers

described here amplified a wide spectrum of rhizobia, which

included Rhizobium, Mesorhizobium and Sinorhizobium, and

therefore they could have a great potential for studying

natural communities of rhizobial bacteria. The results pre-

sented here showed that nifD amplification can be applied

directly in DNA from nodules as well as in soil samples,

including those of unplanted soil.

In comparison with other studies addressing the effect of

legumes on the composition of bacterial communities’ prior

inoculation with Rhizobium, in this study the inoculation was

avoided. The results obtained by T-RFLP and DGGE coincided

showing that P. vulgaris affects the community composition of

indigenous rhizobial bacteria in soil. The preferential obser-

vation of rhizobial bacteria in planted soil can be due to the

specific stimulation proliferation by the legume, as has been

postulated before [8], or to the formation of microhabitats

more favorable for the saprophytic growth of rhizobia, as has

been observed in sweet clover rhizosphere [9].

Acknowledgments

We thank to the DAAD regional fellowship for Latin-America

for economical support to P.J. This project was partially

supported by Fondecyt project No. 1040880. We are indebted

to Dr. Francisco Tapia (Instituto de Invesitigaciones Agro-

pecuarias INIA, Chile) for the Phaseolus vulgaris seeds. We

thank Lorena Bravo and Rafael Guevara for valuable

comments on an earlier version of the manuscript.

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