www.elsevier.com/locate/jmicmeth

Journal of Microbiological Methods 6

A ribosomal RNA gene intergenic spacer based PCR and

DGGE fingerprinting method for the analysis of

specific rhizobial communities in soil

Valeria Maia de Oliveira a, Gilson Paulo Manfio a, Heitor Luiz da Costa Coutinho b,

Anneke Christina Keijzer-Wolters d, Jan Dirk van Elsas c,*

aCentro Pluridisciplinar de Pesquisas Quımicas, Biologicas e Agrıcolas- CPQBA/UNICAMP, CP 6171, CEP 13081-970, Campinas, SP, BrazilbEmbrapa Solos, Rua Jardim Botanico, 1024, CEP 22460-000, Rio de Janeiro, RJ, Brazil

cMicrobial Ecology Department, University of Groningen, P.O.Box 14, 9750AA, Haren, The NetherlandsdPlant Research International, P.O. Box 16, 6700AA Wageningen, The Netherlands

Received 26 May 2005; received in revised form 30 May 2005; accepted 30 May 2005

Available online 12 July 2005

Abstract

A direct molecular method for assessing the diversity of specific populations of rhizobia in soil, based on nested PCR

amplification of 16S-23S ribosomal RNA gene (rDNA) intergenic spacer (IGS) sequences, was developed. Initial generic

amplification of bacterial rDNA IGS sequences from soil DNA was followed by specific amplification of (1) sequences

affiliated with Rhizobium leguminosarum bsensu latoQ and (2) R. tropici. Using analysis of the amplified sequences in clone

libraries obtained on the basis of soil DNA, this two-sided method was shown to be very specific for rhizobial subpopulations in

soil. It was then further validated as a direct fingerprinting tool of the target rhizobia based on denaturing gradient gel

electrophoresis (DGGE).

The PCR-DGGE approach was applied to soils from fields in Brazil cultivated with common bean (Phaseolus vulgaris)

under conventional or no-tillage practices. The community fingerprints obtained allowed the direct analysis of the respective

rhizobial community structures in soil samples from the two contrasting agricultural practices. Data obtained with both primer

sets revealed clustering of the community structures of the target rhizobial types along treatment. Moreover, the DGGE profiles

obtained with the R. tropici primer set indicated that the abundance and diversity of these organisms were favoured under NT

practices.

These results suggest that the R. leguminosarum—as well as R. tropici—targeted IGS-based nested PCR and DGGE are

useful tools for monitoring the effect of agricultural practices on these and related rhizobial subpopulations in soils.

D 2005 Elsevier B.V. All rights reserved.

Keywords: Culture-independent analysis; Rhizobia; rDNA spacer; Soil management; Diversity; DGGE

0167-7012/$ - s

doi:10.1016/j.mi

* Correspondin

E-mail addre

4 (2006) 366–379

ee front matter D 2005 Elsevier B.V. All rights reserved.

met.2005.05.015

g author. Tel.: +31 50 3632151; fax: +31 50 3632154.

ss: j.d.van.elsas@rug.nl (J.D. van Elsas).

V.M. de Oliveira et al. / Journal of Microbiological Methods 64 (2006) 366–379 367

1. Introduction

The use of the microbial diversity of soil to ensure

environmental sustainability is a major challenge in

agriculture (Van Elsas et al., 2002; http://www.biodiv.

org/). In particular, biological nitrogen fixation (BNF)

mediated by rhizobia is likely to become increasingly

important in this respect (Hirsh, 1992; Kahindi et al.,

1997), as it may allow a significant reduction of

nitrogen fertiliser input (Coutinho et al., 2000).

Since rhizobial-host plant interactions are often highly

specific (Hungria and Stacey, 1997), the diversity of

rhizobial species in soil will certainly affect the effi-

ciency of natural BNF. For instance, BNF in most

bean crops in the tropics is typically carried out by

different rhizobial species within the Rhizobium legu-

minosarum/R. tropici radiation, e.g. R. legumino-

sarum, R. tropici and several other related groups

(Laguerre et al., 1996; Vlassak et al., 1996; Aguilar

et al., 1999).

There is great conservation potential in the use of

no-tillage (NT) instead of conventional-tillage (CT)

agricultural systems (e.g. Kahindi et al., 1997). In

Brazil, NT has already been applied to large areas

of commercial legume (including soybean and com-

mon bean) cropping and it is widely used in the

Brazilian Cerrado biome.

Given the importance of natural rhizobial commu-

nities for legume cropping, a better understanding of

the extant rhizobial diversity in soil is primordial for a

sound assessment of the efficiency of these agricul-

tural practices. Rhizobial communities might even

serve as bioindicators to estimate the impact caused

by the agricultural practices (Coutinho et al., 1999).

Hence, a method for the direct monitoring of these

target rhizobial populations in soil is needed.

In particular due to the non-culturability conun-

drum (Pace, 1997), traditional microbiological techni-

ques based on cultivation are not adequate as the sole

basis for the monitoring of soil rhizobial communities

(Hugenholtz et al., 1998). Common techniques for

isolating and enumerating rhizobia from soil involve

the use of trap plants, a practice which only selects for

those strains that are efficient in nodulating the very

plant species used as the trap (Handley et al., 1998;

Mercante et al., 1998). Direct soil DNA-based molec-

ular techniques are the methods of choice to overcome

the limitations of these culture-dependent approaches

(Hugenholtz et al., 1998; Van Elsas et al., 2000). For

instance, the use of PCR in conjunction with cloning

and sequencing for the analysis of ribosomal RNA

gene (rDNA) fragments directly from soil can be

highly informative (Akkermans et al., 1995; Kowal-

chuk et al., 2004). In addition, denaturing gradient gel

electrophoresis (DGGE) of PCR-amplified DNA frag-

ments offers a rapid means for the study of complex

bacterial populations in environmental samples, either

at a gross taxonomic level (Muyzer et al., 1993, 1995;

Heuer and Smalla, 1997) or at more refined, e.g.

genus, levels (Garbeva et al., 2003, 2004; Salles et

al., 2002).

In the current study, we aimed at the development

and validation of a soil DNA based method for gen-

erating 16S–23S rDNA IGS fragments specific for

rhizobial groups that commonly nodulate bean, cen-

tered around (1) R. leguminosarum (R. legumino-

sarum bsensu latoQ, including R. tropici) and (2) R.

tropici. We then used the method to assess its suit-

ability in the evaluation of the effect of NT versus CT

practices on the diversity of the target rhizobial com-

munities in soil.

2. Materials and methods

2.1. Bacterial strains and growth conditions

The bacterial strains used and their sources are

listed in Table 1. Rhizobium strains were grown in

yeast–mannitol (YM) broth (0.5 g KH2PO4, 0.2 g

MgSO4d 7H2O, 0.1 g NaCl, 0.5 g yeast extract, 10 g

mannitol and 0.5% bromothymol blue litre�1 distilled

water) for 48 h at 28 8C under constant shaking.

Long-term storage was at �80 8C in 50% (v/v) glyc-

erol and by lyophilization.

2.2. Field experiment and soil samples

Soil samples were collected, as outlined below,

from a field experiment conducted by Embrapa

Meio Ambiente (http://www.cnpma.embrapa.br) in

Guaıra, located in the North of the State of Sao

Paulo, Brazil. The soil was typical of the Brazilian

Cerrado (acid oxisol), with an average pH (CaCl2) of

5.0 and an organic matter content of 2.8% in the top

layer (0–20 cm). The experimental area comprised

Table 1

Bacterial strains and responses to specific primer sets I and II

Strains Host plant/remark PCR with set: DGGE band:

I II

R. leguminosarum

bv trifolii R62 Trifolium repens + � I A

bv phaseoli CCT4168 Phaseolus vulgaris + � I B

bv viciae CCT5087 Vicia sativa + � I C

CCT 6305* Trifolium pratense + � I D

CCT 6308* V. sativa + � I E

CCT 6310 T. procumbens + � I F

CCT 6314 P. vulgaris + � I G

CCT 6315 P. vulgaris + � I H, I

CCT 6317 Lathyrus sp. + � I J

CCT 6323 Lathyrus sp. + � I K

R. tropici

CCT4160 + + I L1 II, A

CCT4164 + + I L2 II, B

Sinorhizobium meliloti

CCT4167 � � NA

Sinorhizobium loti Lotus spp.

CCT4063 � � NA

Agrobacterium spp.* Compiled data � � NA

Rhodopseudomonas palustris* Tested close relatives � � NA

Soil isolates (unidentified) Random isolates from soil � � NA

CCT, Tropical Culture Collection, Fundacao Andre Tosello (Campinas, SP, Brazil).

*CCT6305: also at this position: CCT6306 (from T. repens) and CCT6320 (Lens sp). CCT6308: also at this position: CCT6321 (Lathyrus sp)

and G49 (Cajanus Cajan).

Agrobacterium spp.: A. tumefaciens, A. rhizogenes and A. vitis (Partially from De Oliveira et al., 1999). R. palustris: strains NCIB8288 and

WS17. Ten random soil isolates were also subjected to PCR amplification with systems I and II.

DGGE band: I indicates system I band visualised on DGGE, II similarly for system II. NA: not applicable. A, B, . . .: indicate different positions

in gel.

V.M. de Oliveira et al. / Journal of Microbiological Methods 64 (2006) 366–379368

four plots established at random: two no-tillage treat-

ment plots (NT I and NT II) and two plots under

conventional tillage (CT I and CT II). In the former

plots, the remains from the previous soybean crop

were treated with 2.0 L ha�1 of glyphosate bNortoxQand 1.5 L ha�1 of 2,4-dichlorophenoxyacetate-amine

20 days prior to sowing common bean, and the top

soil was not ploughed or disc-harrowed. In the latter

plots, the remains from the previous crop were incor-

porated into the soil by ploughing and disc-harrowing

the top soil. Common bean (Phaseolus vulgaris) was

sown over rows supplemented with 300 kg ha�1 N–

P–K (2 :20 :20) fertiliser.

Thirty days after sowing, ten individual samples

(approx. 100 g each) from each plot were collected at

random, from the top soil layers (20 cm), between the

bean rows. These samples were pooled per plot and

stored at �20 8C for subsequent DNA extraction. In

addition, a pooled sample was similarly obtained from

the area before establishment of the experiment, yield-

ing a time-zero (T0) sample.

2.3. Extraction of DNA from pure cultures and soil

Total genomic DNA was isolated from pure cul-

tures of reference strains essentially according to

Pitcher et al. (1989). As evidenced by gel electropho-

resis (Sambrook et al., 1989), high molecular weight

genomic DNA of sufficient purity to allow direct PCR

was obtained from all strains under study.

Direct extraction of soil DNA using mechanical lysis

was based on a modification of a previously described

Table 2

Sequence, target and reference of primers used in this study

Primer Sequencea (5VY3V) Target group Reference

pHr TGC GGC TGG ATC ACC TCC TT Bacteria Massol-Deya et al., 1995

p23S uni322anti GGT TCT TTT CAC CTT TCC CTC Bacteria Honeycutt et al., 1995

U968 AAC GCG AAG AAC CTT AC Bacteria Heuer et al., 1997

L1401 CGG TGT GTA CAA GGC CCG GGA ACG Bacteria Heuer et al., 1997

rhizo2f GAT GGC ACC AGT CAG GTG AC R. leguminosarum

and R. tropici

De Oliveira et al., 1999

trop1f CGG ACR TGS CCC GAT AT R. tropici De Oliveira et al., 1999

rhizo3r GGA AGA CTT GAA YTT CCG A R. leguminosarum

and R. tropici

De Oliveira et al., 1999

GC clampb CGCCCGGGGCGCGCCCCGGGCGGGGCGGGGGCACGGGGGG – Muyzer et al., 1993

a Y=T or C; R=A or G; S=C or G.b GC clamp was attached to the 5V end of the primer rhizo3r.

V.M. de Oliveira et al. / Journal of Microbiological Methods 64 (2006) 366–379 369

protocol (Smalla et al., 1993), using 2 g of soil. Two

final purification steps with theWizard DNAClean-Up

System (Promega, Madison, WI, USA) were used, as

recommended (Van Elsas et al., 1997). To assess the

robustness of the method, duplicate DNA extractions

were performed for each composite soil sample. The

integrity and concentration of the purified soil DNA

were assessed by electrophoresis on 0.8% agarose gels

(Sambrook et al., 1989). All soil DNA obtained was

10–25 kb in size. On estimation from gel (visual com-

parison to bands of marker DNA at known quantity),

5–15 Ag DNAwas obtained per g of each soil.

2.4. PCR amplification of 16S–23S rDNA IGS

fragments

A nested PCR approach was used with soil DNA to

amplify R. leguminosarum and/or R. tropici IGS frag-

ments. Two sets of primers were used (Table 2).

Independent nested PCRs were performed using com-

munity DNA from each soil. In the first PCR reaction,

bacterial 16S–23S rDNA IGS sequences were gener-

ically amplified using the conserved primers pHr

(Massol-Deya et al., 1995) and p23Suni322anti (Hon-

eycutt et al., 1995). PCR was performed in 50 ALreaction volumes as described previously (Rosado et

al., 1996). Phage T4 gene 32 protein and formamide

were added to improve the efficiency of target ampli-

fication when using soil DNA (Tebbe and Vahjen,

1993; Van Elsas et al., 1997). PCR amplifications

were carried out using initial denaturation at 95 8Cfor 2 min, followed by 30 cycles of 1 min at 94 8C, 1min at 60 8C and 3 min at 72 8C; and a final extension

at 72 8C for 5 min, in a Perkin Elmer thermal cycler

model 480 (Perkin-Elmer, Nieuwerkerk aan de IJssel,

The Netherlands).

In the second PCR, the primer sets I (rhizo2f/rhi-

zo3r) and II (trop1f/rhizo3r) as in De Oliveira et al.

(1999) were employed, in separate reactions, to ampli-

fy R. leguminosarum/R. tropici and R. tropici-specific

rDNA spacer fragments, respectively. Products for

subsequent DGGE analyses were prepared with the

GC-clamped reverse primer rhizo3r (Table 2). Aliquots

of 1 AL from the first PCRwere used as templates in the

subsequent (50 AL) reactions, from which formamide

or phage T4 gene 32 protein were omitted. Touchdown

PCR (Muyzer et al., 1995) was performed in order to

optimize both specificity and sensitivity. An initial

denaturation step at 95 8C for 2 min and a final exten-

sion step at 72 8C for 10 min were performed for all

samples. For primer set I, after denaturation at 94 8C for

1 min, the annealing temperature was initially set at 62

8C for 30 s, and then decreased to 60 8C by 1 8C every 3

cycles, followed by 26 additional cycles at 58 8C;primer extension was performed at 72 8C for 45 sec.

For primer set II, after denaturation at 94 8C for 1 min,

the annealing temperature was set at 55 8C for 1 min

and then decreased to 51 8C by 2 8C every 3 cycles;

then 26 additional cycles were carried out at 50 8C;primer extensionwas performed at 72 8C for 1min. The

same amplification conditions were used to amplify

IGS fragments from the reference strains, using 50 ng

of genomic DNA.

On the basis of an analysis of database sequences,

the expected fragment sizes were 200–320 bp (primer

set I) and 240–400 bp (primer set II). The amplicons

V.M. de Oliveira et al. / Journal of Microbiological Methods 64 (2006) 366–379370

were checked by electrophoresis on 1.4% agarose gels

in 0.5 strength TBE buffer (Sambrook et al., 1989)

and stored at �20 8C for subsequent cloning and

DGGE analyses.

2.5. Construction and analysis of IGS fragment clone

libraries

Clone libraries were constructed on the basis of

IGS fragments generated with both primer set I and II

from soil DNA obtained from treatments T0, NT and

0.1

Brucella abortus (X95889)

RH CL78 (=RH CL117; RH CL191; RH CLAgrobacterium rhizogenes CCT 4832T (AAgrobacterium rhizogenes CCT 4842 (AF

RH CL8

RH CL59Rhizobium leguminosarum CCT 6323 (AF17604

Rhizobium leguminosarum CCT 6308 (AF1

Rhizobium leguminosarum bv. trRhizobium leguminosarum strain D

RH CL64

RH CL57 RH CL46 (=RH CL49)

RH CL14 (=RH CLRhizobium leguminos

RH CL7 (=RH CL6; RH CL56; RH CL73RH CL11 (=RH CL4; RH CL

Rhizobium leguminosarum bv. phRhizobium sp. Glm 12 (AF510884)

TR CL126 (=TR CL136; TR CL142) Rhizobium sp. vgs 5 (AF510902)

Rhizobium etli strain LMG 17827 (AF5Rhizobium mongolense USD

Rhizobium gallicum strain R602 clonTR CL119

RH CL93 (=RH CL22; RH CL76; RH Rhizobium sp. Glm 10 (AF510882)

TR CL108 (=TR CL121) Rhizobium tropici CCT 4160T (A

Rhizobium tropici LMG 9503 (AF34

TR CL148 (=TR CL127; TR CL128TR CL157 (=TR CL149; TR CL15Rhizobium hainanense USDA 3TR CL125

RH CL196 (=RH CL9; RH CL10; RH CL

RH CL198 RH CL29 (=RH CL66; RH CL83; R

RH CL19 (=RH CL81) Agrobacterium vitis (U4532

Rhizobium galegae LMG 61Agrobacterium tumefaciens DSM 3020Rhizobium sp. Phr 8 (AF510898)

RhizoRH CL50

RH CL21 (=RH CL20; RH CL24; RHRH CL203 (=RH CL32

Rhizobium sp. Phr 9

SinorhizobiumSinorhizobium

SinorhizoRH CL183

TR CL103 TR CL113 (=TR

RH CL15 (=RH CL38) RH CL31

Rhizobium rubi DSM 6772 clone

Rhizobium sp. IRBG 74 clone 20 (AF364839)

100

100

74

100

100

96

100

96

79

91

77

92

83

98

78 100

100

95

100

99 96

98

Fig. 1. Phylogenetic analysis of partial 16S–23S rDNA IGS sequences of

(clones named TR), and related species mostly obtained from RISSC (Ga

and the neighbor joining method for tree reconstruction. Bootstrap values (

in brackets showed z97% similarity with the clone represented in the b

Brucella abortus was used as the outgroup (distantly-related group used

CT. The PCR products were first purified using the

bHigh-pure PCR product purification kitQ (Roche).

They were then ligated into the pGEM-T vector

using the Promega (Oss, NL) cloning kit, after

which competent Escherichia coli cells were trans-

formed with the ligation mixes. Using blue/white

screening, for each treatment 19 clones with putative

inserts were selected, and the presence of inserts was

verified by specific PCR. The products generated

from the clones were (1) assessed for migration on

DGGE gel (after re-amplification to introduce the GC

199; RH CL205) F091795) 091797)

7) 76046)

ifolii CCT 4179 (AF091791) SM 30141 (AF345272)

5; RH CL33; RH CL71)arum bv. viceae CCT 5087T (AF091793) ; RH CL90; RH CL194) 52; RH CL75; RH CL79; RH CL87; RH CL184; RH CL187) aseoli CCT 4168 (AF091789)

41974) A 1844 (AF321873) e1 (AF345267)

CL84; RH CL92; RH CL192)

F091801) 5278)

; TR CL129; TR CL131; TR CL147; TR CL153; TR CL155; TR CL197) 8)

588 (AF345269)

12; RH CL55; RH CL67; RH CL72)

H CL85; RH CL86; RH CL200)

9) 24 (AF345265) 5 (AF345274)

bium sp. Trr 9 (AF510897)

CL37; RH CL43) ) (AF510901)

xinjiangense strain CCBAU 110 (AF284450) fredii LMG 6217 (AF345282)

bium arboris LMG 14919 (AF345281)

CL109; TR CL115; TR CL116; TR CL118; TR CL122; TR CL123; TR CL124)

2 (AF345277)

Cluster I

Cluster II

Cluster III

Cluster IV

Cluster V

Cluster VI

Cluster VII

Cluster VIII

soil clones, obtained with PCR systems I (clones named RH) and II

rcia-Martinez et al., 2001) using the Kimura 2p evolutionary model

1000 replicate runs, shown as %) greater than 70% are listed. Clones

ranch. GenBank accession numbers are listed after species names.

for tree rooting).

V.M. de Oliveira et al. / Journal of Microbiological Methods 64 (2006) 366–379 371

clamp), and (2) electrophoresed on agarose gel to

assess their sizes. Clones with inserts of the expected

sizes were selected for sequencing. About 190–200 bp

of high-quality sequence was obtained per clone, and

all analyses were based on this sequence information.

For phylogenetic analysis and tree construction, 91

clones from the total (102) were used. The sequences

removed from the analyses were mostly too small or

of too low quality to be analysed, as described later.

2.6. DGGE analysis

DGGE was carried out in the PhorU2 System

(Ingeny, Goes, The Netherlands), as described else-

where (Rosado et al., 1998), using a linear denaturing

gradient of urea and formamide ranging from 45% to

65%. Gels were run at 100 Vand 60 8C for 16 h in 0.5

X TAE buffer (Sambrook et al., 1989). A DGGE

marker, composed of a mixture of 16S rDNA frag-

ments from Enterobacter cloaceae BE1; Listeria

innocua ALM105; R. leguminosarum bv. trifolii

R62; Arthrobacter sp. Ar1 and Burkholderia cepacia

P2 (listed in order of migration on DGGE gel) gener-

ated with primer set U968-GC and L1401 (Table 2),

was used as the reference in the gels (De Oliveira et

al., 1999). Gels were stained and documented as

described (Rosado et al., 1998).

DGGE patterns were analysed by using GelCom-

par v. 4.1 (Applied Maths, Kortrijk, Belgium) and

UPGMA-based dendrograms constructed from Pear-

son (product–moment) correlation coefficient matrices

(Pearson, 1926).

2.7. Sequencing of clone inserts and DGGE bands

To obtain sequences from the IGS fragment clones,

specific PCR products were generated by primer sets I

and II. To obtain sequences from DGGE bands, small

blocks of acrylamide gel containing fragments of

interest were excised from gel and DNAwas extracted

by using the bcrush and soakQ method (Sambrook et

al., 1989). Pellets were resuspended in 15 AL TE

buffer for subsequent PCR and cloning. The DNA

from selected bands was then diluted and subjected to

PCR using the DGGE primer set. The dilution that

yielded one single band with migration distance

equivalent to the band of interest in DGGE was then

used as the template in subsequent PCR reactions,

using primers without GC clamp. PCR products (2

AL) were cloned into the pCRR2.1 vector (TA cloning

kit; Invitrogen, Leek, The Netherlands).

Sequencing of the inserts of IGS clones was per-

formed on PCR products generated from the respec-

tive clones. Sequencing of DGGE bands was

performed on both strands. The Thermo sequenase

fluorescently-labelled primer cycle sequencing kit

was used with 7-deaza-dGTP (Amersham Nederland

BV, s Hertogenbosch, The Netherlands) in an auto-

matic sequence analyser (ALF DNA sequencer;

Amersham).

2.8. Phylogenetic analysis of 16S–23S rDNA IGS

fragments

Sequences of the 16S–23S rDNA IGS fragments

generated in this study were compared with reference

sequences that showed highest similarity values in

BLAST-N searches as well as a selected outgroup

sequence, all recovered from GenBank and/or RISSC

(Garcia-Martinez et al., 2001). The sequences were

aligned using the CLUSTAL-X program (Thompson

et al., 1994) and analysed using PAUP (version 4.0

beta 10) (Swofford, 2000). Evolutionary distances

were calculated using the Kimura 2p DNA substitution

model with settings for gap spacing of 10 and gap

extension of 5 (Kimura, 1980). The phylogenetic re-

construction (Fig. 1) was done using the neighbor-

joining algorithm (Saitou and Nei, 1987), with boot-

strap values calculated from 1000 replicate runs, using

the routines included in the PAUP software.

2.9. Genbank accession numbers

Sequences obtained from the clone libraries were

deposited in the Genbank database under the acces-

sion numbers AY736379 to AY736469.

3. Results

3.1. Development and validation of PCR for detection

of target rhizobial groups in soil

The primers composing the R. leguminosarum

bsensu latoQ (rhizo2f/rhizo3r-primer set I) and R. tro-

pici (trop1f/rhizo3r-primer set II)-targeted detection

V.M. de Oliveira et al. / Journal of Microbiological Methods 64 (2006) 366–379372

systems (De Oliveira et al., 1999) were checked for

their specificities by BLAST-N versus the GenBank

database in March 2004. The analysis of primer rhi-

zo2f revealed a total of 89 hits at full homology, all

belonging to bacterial IGS sequences. Of these, 81

(91%) were classified as brhizobialQ and 8 (9%) as

bagrobacterialQ. Similar analysis of the rhizo3r primer

sequence revealed a total of 488 hits, all representing

bacterial IGS sequences. Of these, 466 (95%) were

brhizobialQ, 8 (b2%) from Nitrobacter spp., 8 (b2%)

from Rhodopseudomonas palustris, 4 (b1%) of di-

verse origin and 2 others (b0.5%) bagrobacterialQ.Surprisingly, the R. tropici forward primer sequence

did not show homology to any database sequence.

However, previous work showed that it— in combi-

nation with primer rhizo3r — specifically amplifies

sequences that all belong to or are closely related to R.

tropici (De Oliveira et al., 1999). On the basis of these

combined data, it was hypothesized that the two sys-

tems would specifically amplify sequences centered

around the target species R. leguminosarum and R.

tropici from soils. Prior to assessing soil, we exten-

sively tested the specificity of the two primer sets

directly with selected rhizobial strains as well as

other, related and non-related strains (Table 1). This

analysis corroborated the view that both primer sets

were specific for their intended targets (De Oliveira et

al., 1999).

Amplification products were not obtained when

primer sets I and II were used directly on DNA

from any of the (NT, CT, T0) soils (data not

shown). In contrast, both primer sets yielded PCR

products from all treatments in the nested set-up, as

evidenced by direct gel electrophoresis. Primer set I

generated amplicons of about 200–400 bp, whereas

primer set II yielded amplicons estimated to be about

240 to 450 bp in size. The products appeared as one to

up to four discrete bands on agarose gel, indicating the

occurrence of size heterogeneity in the targets that

were amplified (data not shown).

3.2. Evaluation of IGS-based PCR for the detection of

rhizobial diversity in soil

To evaluate the specificity of the R. legumino-

sarum bsensu latoQ and R. tropici primer sets when

used with DNA from soil communities, clone libraries

were constructed on the basis of soil-extracted DNA

from the NT and CT treatments, as well as from T0

soil. A total of 71 clones was obtained with primer set

I (31 clones from treatment NT, 25 from CT and 15

from T0). For primer set II, another 31 clones were

generated in total (16 from NT, 15 from CT, none

from T0). All clones were subjected to sequence

analysis and the sequences obtained were analysed

for (1) their similarity to database sequences using

BLAST-N, and (2) their phylogenetic relatedness,

both to each other and to a limited set of reference

sequences selected from the database.

BLAST-N analysis revealed that, without any ex-

ception, the sequences of all clones had as their

closest affiliates database entries of IGS regions of

diverse rhizobial/agrobacterial species, including

those of as-yet-uncultured rhizobial-type organisms

(18% of the sequences). The latter (obtained with

primer set I) exclusively referred to hits with three

sequences previously obtained by us from pasture soil

from a field adjacent to the soils under study here (De

Oliveira, unpublished).

Primer set I specifically generated sequences that

showed hits with a range of database entries, mainly

described as belonging to R. leguminosarum, R. tro-

pici, R. gallicum and Rhizobium spp. with diverse

strain designations. In respect of the similarity levels,

about 50% of these sequences had N97% similarity

with database entries, however often with rhizobia

without species designation, or with the aforemen-

tioned as-yet-uncultured putative rhizobia. The per-

centage of hits with database sequences using the 95%

similarity level was 80%, leaving 20% of the

sequences at 89– 95% similarity to database entries.

Primer set II generated sequences which by BLAST-N

analysis fell into only a limited number of types. A

large group of sequences (14 /31; 43%) had IGS

regions of R. tropici as their closest affiliates, all at

97% similarity or higher. A second group of

sequences resembled database sequences assigned to

just a few Rhizobium spp.: phr-9 (12 /31; 37%– N97%

homology), vgs-5 (2 /31; 7%– 90% homology), glm-

10 (1 /31; 3%– 90%) and IRBG74 (1 /31; 3%– 91%).

One sequence resembled R. hainanense (1 /31– N99%

homology).

After removal of repeat sequences from the analysis

and addition of relevant database sequences of closely-

related strains, a phylogenetic tree was constructed

(Fig. 1). When taken together, all sequences clustered,

Fig. 2. a — PCR-DGGE analysis of agricultural treatments using

primer set I (R. leguminosarum/R.tropici specific; primers rhizo2f/

rhizo3r-GC clamp), showing amplification products from replicate

plots (I and II) and duplicate soil DNA extractions (a and b). Lanes:

1—T0, 2—void; 3a, 3b—NTI; 4a, 4b—CTI; 5a, 5b—NTII; 6a,

6b—CTII. M—marker composed of 16S rDNA fragments from

E. cloaceae BE1; L. innocua ALM105; R. leguminosarum bv.

trifolii R62; Arthrobacter sp. Ar1 and B. cepacia P2 (listed in

order of migration on DGGE gel). R—R. leguminosarum

CCT6306. Arrows indicate bands used for identification; upper

arrow: band 1, lower arrow: band 1V. b — Cluster analysis of the

DGGE profiles generated with primer set I, using the Pearson

correlation coefficient and UPGMA method. The marker was

used as an outgroup.

V.M. de Oliveira et al. / Journal of Microbiological Methods 64 (2006) 366–379 373

at high bootstrap values, into eight clearly separable

clusters (clusters I through VIII, Fig. 1). All clusters

exclusively contained sequences from the rhizobial/

agrobacterial radiation, and will be denoted by the

rhizobial species central to it. Cluster I (9 sequences)

was denoted the R. leguminosarum bv trifolii cluster,

although R. rhizogenes (formerly Agrobacterium rhi-

zogenes) also made part of it. Cluster II (6 sequences)

was, after its main identifier, denoted the R. legumino-

sarum bv viciae cluster, cluster III (24 sequences) the

R. leguminosarum bv phaseoli cluster (although

sequences of strains designated as R. gallicum, R.

etli, R. mongolense and Rhizobium spp. also made

part of it), and cluster IV (15 sequences) the R. tropici

cluster (including R. hainanense). Cluster V (8

sequences) had no identifier, as it only contained

sequences from clones. Cluster VI (16 sequences)

was denoted the R. galegae cluster, although sequences

of R. radiobacter (formerly A. tumefaciens) and R. vitis

(formerly A. vitis) also made part if it. Cluster VII (10

sequences) was denoted the Sinorhizobium sp. cluster,

as several different species of Sinorhizobum were in-

cluded. Finally, cluster VIII (3 sequences) was denoted

the R. rubi cluster. Sequences generated with primer set

I were distributed among most of the clusters, whereas

those generated with primer set II were spread only

among clusters III, IV and VII, of which cluster IV

contained the sequences of strains designated as R.

tropici. Probably as a result of the relatively low num-

ber of sequences analysed, we could not discern any

bpreferenceQ of clusters for soil treatment.

3.3. Analysis of rhizobial PCR-DGGE profiles

Amplicons generated with primer set I from the

various R. leguminosarum and two R. tropici strains

were clearly separable on denaturing gels (Table 1),

and in most cases single bands were found per strain,

confirming the results published earlier (De Oliveira

et al., 1999). Bands from strains or clones of clusters I

through IV mostly migrated to different positions in

the gel, but this was not fully consistent, not allowing

a clear rhizobial type-migration distance relationship

(Table 1).

Primer set I yielded relatively complex fingerprints

for all soil samples analysed (Fig. 2a). The profiles

obtained from the T0, NT and CT soil samples consis-

tently contained a total of about 25 to 30 bands (both

faint and clearly visible to intense), of which 12 to 19

appeared as intense bands. Visual inspection of the

profiles revealed a high consistency of the profiles

between the replicate plots per treatment. In addition,

there were substantial similarities across treatments.

This is reflected in the clustering data performed by

using GelCompar software (Fig. 2b). As expected,

profiles obtained by replicate extractions from the

same plot clustered most closely together (similarity

levels of roughly 84–90%), whereas profiles from rep-

licate plots clustered at lower similarity levels (82%

CT

I-b

NT

II-b

NT

I-b

CT

II-b

CT

II-a

CT

I-a

NT

II-a

NT

I-a

M M

a

b

CT I-aCT I-bCT II-a CT II-bNT I-aNT I-bNT II-bNT II-a

100806040200

Fig. 3. a — DGGE analysis of agricultural treatments NT and CT

(T0 not included, as amplification yielded only faint products) using

primer set II (R. tropici specific; trop1f/rhizo3r-GC clamp), showing

amplification products from duplicate soil DNA extractions (a, b).

from replicate plots (I, II) M: DGGE marker (see Fig. 2a). b —

Cluster analysis of the R. tropici DGGE profiles.

M CTI a b c d e f M g h I j k l m n o CTII M

Fig. 4. Example of matching of clones generated by primer set I and

directly obtained DGGE profiles of agricultural treatments. Treat-

ment CT (CTI, CTII) is shown. Letters indicate different clones. M

DGGE marker (see Fig. 2a). A fair representation of the direc

DGGE patterns is reflected in the clones.

V.M. de Oliveira et al. / Journal of Microbiological Methods 64 (2006) 366–379374

NT; 72% CT). Since the between-treatment differences

were often larger than the within-treatment differences,

this resulted in a predicted overall clustering of the

community profiles approximately along treatment

(Fig. 2b).

Primer set II generated clearly less complex DGGE

profiles from the DNA from the NT and CT soils, with

7–8 (NT) and 4–5 (CT) bands per profile found (Fig.

3a). The within-treatment variation of the DGGE

profiles obtained with primer set II was dependent

on the treatment. Whereas the profiles from replicate

plots of treatment CT (each performed in duplicate)

showed a high level of similarity (96%, Fig. 3b), those

of treatment NT showed greater variation (~80% sim-

ilarity, Fig. 3b). One profile from the NT treatment

appeared distinct from the remaining ones (Fig. 3a,

NT I-a), showing bands also found in the CT profiles.

However, there were remarkable differences between

the treatments, with both CT-derived profiles being

dominated by just one very strong band in contrast to

the more even NT-derived profiles.

3.4. Matching of clones with bands in DGGE gels

In an attempt to match the clones obtained with the

rhizobial community DGGE profiles generated from

the differently-treated soils, GC-clamped amplicons

produced from all clones were run on denaturing

gels side-by-side with the soil-derived community

profiles they were generated from. Overall, the analy-

ses showed that the clone fragments generated with

primer set I migrated to a total of 22 gel positions.

Visual comparison indicated that these gel positions all

carried (faint to intense) bands in the original soil-

derived profiles. Per soil community profile, coverage

by the GC-clamped clone-derived products was vari-

able but substantial (generally over 60% of discernable

bands), but it was in no case complete. Fig. 4 shows an

example of this analysis (primer set I, CT treatment).

The GC-clamped amplicons generated with primer

set II in all cases each migrated to a single dominant

:

t

V.M. de Oliveira et al. / Journal of Microbiological Methods 64 (2006) 366–379 375

band position, often accompanied by two fainter (pos-

sibly heteroduplex) bands. Analysis of all clones

showed that a total of 6 to 8 dominant band positions

were occupied on gel, of which most were associated

with the bands in the original soil-derived profiles

(data not shown).

3.5. Identification of selected DGGE bands

As a more direct proof of principle, two clear bands

in the soil profiles generated with primer set I, denoted

1 and 1V (Fig. 2a, arrows) were selected for sequence

analysis. Band 1 was shared by all profiles, whereas

band 1V was faint in several lanes and more variable

across profiles. The analyses revealed that both bands

were quite similar in sequence. The two sequences

were aligned and clustered with those from reference

organisms. The data showed that both fell in separate

radiations of a broad cluster of rhizobial sequences

mainly comprised by R. leguminosarum and R. rhi-

zogenes reference strains (not shown). This supported

the conclusion that amplicons characteristic for sepa-

rate lineages within R. leguminosarum and related

rhizobial species were recoverable as separate bands

on denaturing gradient gels.

4. Discussion

Common bean (P. vulgaris) is nodulated by spe-

cific rhizobia, belonging to groups such as R. legumi-

nosarum, R. tropici and some other related groups

(Laguerre et al., 1996; Vlassak et al., 1996; Aguilar et

al., 1999). Direct assessments of the diversity as well

as the abundance of such natural rhizobial populations

in field soils, in conjunction with nodulation studies,

are necessary to understand the potential of these soils

to establish BNF interactions with legumes. However,

such data are still sparse, the main reason being the

difficulty of directly assessing rhizobial diversity in

soil.

As rhizobial populations in soil are often present

in low numbers, estimated to represent less than

0.01% of the total bacterial community (Ballard et

al., 2004), direct PCR methods based on soil DNA

are indicated for their detection. However, such

methods may be limited by template concentrations

being below directly detectable levels. The approach

used in this study was, thus, based on nested PCR,

which is known to strongly enhance the sensitivity

of PCR-based fingerprintings of specific bacterial

groups in soil (Heuer et al., 1997; Salles et al.,

2002). An initial amplification round with conserved

primers which target the bacterial rDNA 16S–23S

IGS region in a generic fashion was followed by a

second round using two rhizobial-specific primer

sets. This two-way approach allowed the successful

amplification of R. leguminosarum sensu lato and R.

tropici related IGS sequences from soil DNA. Nested

amplification was indeed necessary, since direct am-

plification using the rhizobial-specific primers did

not yield any detectable signal with DNA from any

of the soils tested.

The analysis of the sequences in the clone library

obtained from soil with the two primer sets confirmed

the specificity of the PCR-based method for rhizobial

species related to the targets. Indeed, all sequences

generated with both primer sets were IGS-like and fell

into the rhizobial/agrobacterial radiation. Primer set I

generated a rather broad range of sequences in differ-

ent radiations of the R. leguminosarum, R. tropici and

related clusters, whereas primer set II produced a

range of sequences centered around R. tropici. The

fairly close relatedness of all strains falling within

these two groups was recently confirmed in a phylo-

genetic analysis of both 16S rDNA and IGS

sequences (Tan et al., 2001).

Our conclusions in respect of the specificity of

detection based on the IGS sequences were supported

by the BLAST-N as well as phylogenetic analyses

performed (Fig. 1). The resemblance of several

sequences found in soil with database ones denoted

as agrobacterial-like was interesting. The taxonomy of

Agrobacterium has recently undergone a major over-

haul, in the sense that this taxon is currently consid-

ered to belong to Rhizobium (Young et al., 2001). In

fact, organisms formerly classified as avirulent Agro-

bacterium species might be rhizobia, and genome

fluidity (Sullivan and Ronson, 1998) might determine

the exact ecological roles of these organisms. We

hypothesized that the pool of organisms accessed by

us were in fact fairly clonal and hence potentially

nitrogen-fixing. For obvious reasons, future work

should still address the extent of linkage of the phy-

logenetic (IGS based) and functional (nitrogen fixa-

tion) genes.

V.M. de Oliveira et al. / Journal of Microbiological Methods 64 (2006) 366–379376

On a more specific note, several of the sequences

generated with primer sets I and II were shown to be

related to Rhizobium species designated as R. etli-, R.

mongolense-, R. gallicum-, R. rubi-and Sinorhizo-

bium-like (Fig. 1), thus indicating that a broader

range of target species was amplified than had been

anticipated on the basis of the original primer design

(De Oliveira et al., 1999). The phylogenetic relation-

ships between the rhizobial taxa observed in this

study, based on the 16S–23S IGS sequences (Fig.

1), were also observed when analyses were performed

using 16S rDNA sequences (Phylip Interface, RDP;

http://rdp.cme.msu.edu/html/analyses.html). Hence,

the R. gallicum/R. mongolense, R. galegae/R. vitis/

R. tumefaciens, R. etli/R. leguminosarum and Sinor-

hizobium species clusterings were all confirmed.

These results thus corroborate the robustness of the

groupings found by the IGS analysis.

Analysis of the clone library further showed that

there was no discernible relationship between the

sets of IGS types found and soil treatment. In

other words, similar, apparently brandomQ numbers

of different sequences were obtained from the repli-

cates of the different treatments. This result was not

unexpected, as the time elapsed since the different

land use (CT versus NT) was established was short,

and the numbers of sequences recovered per treat-

ment were likely to be too low for any inference

about the environmental impact to be made with

sound statistical support.

Additional analysis of rhizobial diversity in pasture

soils adjacent to the treatment plots using primer set I

corroborated the results presented here. Briefly, anal-

ysis of a limited set of IGS based sequences revealed

the presence of sequences related to R. tropici (type

strain) as well as that of a cluster of four sequences of

potentially novel rhizobial strains within the cluster

(not shown). These combined data validated the use-

fulness of the specific PCR/DGGE system described

herein.

As already predicted (De Oliveira et al., 1999), the

PCR-DGGE system yielded rhizobial community fin-

gerprints useful for the comparison of soils under

different treatment (e.g. Fig. 2a), albeit with the

biases inherent in all PCR-DGGE analyses of com-

plex bacterial communities. First, we cannot exclude

that IGS microheterogeneity within one organism

played a role, as at least one reference strain, R.

leguminosarum CCT 6315, yielded two different

DGGE bands with primer set I. Such microhetero-

geneity has also been observed for IGS regions of

other taxons such as Enterococcus faecalis (Gortler et

al., 1999), as well as for Paenibacillus species 16S

ribosomal RNA regions (Da Silva et al., 2003). Sec-

ondly, migration distance on gel can only be used as

a very rough, presumptive, estimator of sequence

identity. In our system, migration is governed by

both the melting behaviour (related to G+C% and

nucleotide sequence— Muyzer et al., 1993, 1995),

and the length of the DNA fragments. This combi-

nation of factors, whilst adding extra separation

power to the method, also introduces uncertainty

about the exact nature of separated bands (fragment

length versus sequence). Hence, assigning identity to

the bands in the DGGE profiles should ideally be

supported by sequence analysis, as performed for two

bands of the community in the NT treatment. There-

fore, individual bands in the rhizobial DGGE gels

should not be taken as precise measures of organis-

mal diversity in these communities, since numbers of

bands cannot be strictly related to numbers of differ-

ent bacterial types. On the other hand, it is likely that

the highly similar DGGE profiles produced with

primer set I for the NT and CT soils comprised

related sets of co-migrating bands. Hence, we feel

confident in our conclusion that the differences in the

R leguminosarum sensu lato communities brought

about by the short-term effect of the treatment, al-

though detectable, were likely of fairly minor nature.

Vallaeys et al. (1997) also assessed that co-migrating

bands derived from similar environmental samples

represent fragments with identical sequences, and

thus, the same organisms. On the other hand, larger

differences between NT and CT treatments were

detected when using primer set II, albeit in a more

variable data landscape. The numbers of bands in the

profiles from the CT samples were reduced in com-

parison to those in the NT samples. These data

suggested that the short-term impact of the agricul-

tural practices on the rhizobial community structures

was related to the specific organisms targeted.

Whereas the R. tropici community might have under-

gone a change, changes in the diversities of natural R.

leguminosarum sensu lato populations were minor.

However, interpretation of the dataset obtained with

primer set II needs great caution, as there was en-

V.M. de Oliveira et al. / Journal of Microbiological Methods 64 (2006) 366–379 377

hanced variation in the data. This greater variability

may have been related to the presence of lower

numbers of specific targets in the soils, as DNA

template number can affect the amplification in com-

plex template mixtures (Chandler et al., 1997). Spe-

cifically, targets of low prevalence may be amplified

in a non-representative manner as a result of erratic

amplification in the first cycles (Heuer et al., 1997).

Hence, the extent of the community divergence be-

tween the NT and CT treatments needs further as-

sessment, also in the light of the rather small clone

libraries analysed.

The strategy developed in the current study,

based on IGS-based clone libraries and DGGE

analysis of soil community DNA, enabled us to

rapidly estimate the relative diversity of R. legumi-

nosarum, R. tropici and related rhizobial types in

soils subjected to different treatments. The same

approach should be used and validated in future

studies, of longer duration, to evaluate and monitor

the impact of agricultural practices on natural rhi-

zobial populations.

Acknowledgements

The authors are grateful to Rob Pastoor and Lud-

wina Lankwarden for technical assistance and to P.

Valarini for allowing access to the field experiment.

V.M.O was supported by an SPE grant from Conselho

Nacional de Desenvolvimento Cientıfico e Tecnolo-

gico (RHAE/CNPq, Brazil) and a doctoral fellowship

from Fundacao de Amparo a Pesquisa do Estado de

Sao Paulo (FAPESP, Brazil). H.L.C.C. was supported

by a Research Productivity grant from CNPq. The

support by the EU project POTATOCONTROL to

JDVE is acknowledged.

References

Aguilar, O.M., Grasso, D.H., Riccillo, P.M., Lopez, M.V., Szafer,

E., 1999. Rapid identification of bean Rhizobium isolates by a

nifH gene-PCR assay. Soil Biol. Biochem. 30, 1655–1661.

Akkermans, A.D.L., De Bruijn, F.J., Van Elsas, J.D., 1995. Molec-

ular Microbial Ecology Manual I. Kluwer Acad. Press, Dor-

drecht, NL.

Ballard, R.A., Charman, N., McInnes, A., Davidson, J.A., 2004.

Size, symbiotic effectiveness and genetic diversity of field pea

rhizobia (Rhizobium leguminosarum bv. viciae) populations in

South Australian soils. Soil Biol. Biochem. 36, 1347–1355.

Chandler, D.P., Fredrickson, J.K., Brockman, F.J., 1997. Effect of

PCR template concentration on the composition and distribution

of total community 16S rDNA clone libraries. Mol. Ecol. 6,

475–482.

Coutinho, H.L.C., De Oliveira, V.M., Lovato, A., Maia, A.H.N.,

Manfio, G.P., 1999. Evaluation of the diversity of rhizobia in

Brazilian agricultural soils cultivated with soybeans. Appl. Soil

Ecol. 13, 159–167.

Coutinho, H.L.C., De Oliveira, V.M., Moreira, F.M.S., 2000. Sys-

tematics of legume nodule nitrogen fixing bacteria: agronomic

and ecological applications. In: Priest, F.G., Goodfellow, M.

(Eds.), Applied Microbial Systematics. Kluwer Academic Pub-

lishers, The Netherlands, pp. 107–134.

Da Silva, K.R.A., Salles, J.F., Seldin, L., Van Elsas, J.D., 2003.

Application of a novel Paenibacillus-specific PCR-DGGE

method and sequence analysis to assess the diversity of Paeni-

bacillus spp. in the maize rhizosphere. J. Microbiol. Methods

54, 213–231.

De Oliveira, V.M., Coutinho, H.L.C., Sobral, B.W.S., Guimaraes,

C.T., Van Elsas, J.D., Manfio, G.P., 1999. Discrimination of

Rhizobium tropici and R. leguminosarum strains by PCR-spe-

cific amplification of 16S–23S rDNA spacer region fragments

and denaturing gradient gel electrophoresis (DGGE). Lett. Appl.

Microbiol. 28, 137–141.

Garbeva, P., Van Veen, J.A., Van Elsas, J.D., 2003. Predominant

Bacillus spp. in agricultural soil under different management

regimes detected via PCR-DGGE. Microb. Ecol. 45, 302–316.

Garbeva, P., Van Veen, J.A., Van Elsas, J.D., 2004. Assessment of

the diversity and antagonism towards Rhizoctonia solani AG3

of Pseudomonas species in soil from different agricultural

regimes. FEMS Microbiol. Ecol. 47, 51–64.

Garcia-Martinez, J., Bescos, I., Rodriguez-Sala, J.J., Rodriguez-

Valera, F., 2001. RISSC: a novel database for ribosomal

16S–23S RNA gene spacer regions. Nucleic Acids Res.

29, 178–180.

Gortler, V., Rao, Y., Pearson, S.R., Bates, S.M., Mayall, B.C., 1999.

DNA sequence heterogeneity in three copies of the long 16S–

23S rDNA spacer of Enterococcus faecalis isolates. Microbiol-

ogy 145, 1785–1796.

Handley, B.A., Hedges, A.J., Beringer, J.E., 1998. The importance

of host plants for detecting the population diversity of Rhizobi-

um leguminosarum biovar viciae in soil. Soil Biol. Biochem.

30, 241–249.

Heuer, H., Smalla, K., 1997. Application of denaturing gradient gel

electrophoresis (DGGE) and temperature gradient gel electro-

phoresis for studying soil microbial communities. In: van Elsas,

J.D., Wellington, E.M.H., Trevors, J. (Eds.), Modern Soil Mi-

crobiology. Marcel Dekker Inc., New York, pp. 353–373.

Heuer, H., Krsek, M., Baker, P., Smalla, K., Wellington, E.M.H.,

1997. Analysis of actinomycete communities by specific ampli-

fication of genes encoding 16S rRNA and gel-electrophoretic

separation in denaturing gradients. Appl. Environ. Microbiol.

63, 3233–3241.

Hirsh, A.M., 1992. Developmental biology of legume nodulation.

New Phytologist 122, 211–237.

V.M. de Oliveira et al. / Journal of Microbiological Methods 64 (2006) 366–379378

Honeycutt, R.J., Sobral, B.W.S., McClelland, M., 1995. tRNA

intergenic spacers reveal polymorphisms diagnostic for Xantho-

monas albilineans. Microbiology 141, 3229–3239.

Hugenholtz, P., Goebel, B.M., Pace, N.R., 1998. Impact of culture-

independent studies on the emerging phylogenetic view of

bacterial diversity. J. Bacteriol. 180, 4765–4774.

Hungria, M., Stacey, G., 1997. Molecular signals exchanged be-

tween host plants and rhizobia: basic aspects and potential

application in agriculture. Soil Biol. Biochem. 29, 819–830.

Kahindi, J.H.P., Woomer, P., George, T., Moreira, F.M.S., Karanja,

N.K., Giller, K.E., 1997. Agricultural intensification, soil bio-

diversity and ecosystem function in the tropics: the role of

nitrogen-fixing bacteria. Appl. Soil Ecol. 6, 55–76.

Kimura, M., 1980. A simple method for estimating evolutionary

rate of base substitutions through comparative studies of nucle-

otide sequences. J. Mol. Evol. 16, 111–120.

Kowalchuk, G., Akkermans, A.D.L., De Bruijn, F.J., Head, I.M.,

Van Elsas, J.D., 2004. Molecular Microbial Ecology Manual II.

Kluwer Acad. Press, Dordrecht, NL.

Laguerre, G., Mavingui, P., Allard, M.R., Charnay, M.P., Louvrier,

P., Mazurier, S.I., Rigottier-Gois, L., Amarger, N., 1996. Typing

of rhizobia by PCR DNA fingerprinting and PCR-restriction

fragment length polymorphism analysis of chromosomal and

symbiontic gene regions — application to Rhizobium legumi-

nosarum and its different biovars. Appl. Environ. Microbiol. 62,

2029–2036.

Massol-Deya, A.A., Odelson, D.A., Hickey, R.F., Tiedje, J.M.,

1995. Bacterial community fingerprinting of amplified 16S

and 16S–23S ribosomal DNA gene sequences and restriction

endonuclease analysis (ARDRA). In: Akkermans, A.D.L., Van

Elsas, J.D., De Bruijn, F.J. (Eds.), Molecular Microbial Ecology

Manual. Kluwer Academic Press, Dordrecht, The Netherlands,

pp. 1–8 (section 3.3.2).

Mercante, F.M., Cunha, C.O., Straliotto, R., Ribeiro Jr., W.Q.,

Vanderleyden, J., Franco, A.A., 1998. Leucaena leucocephala

as a trap-host for Rhizobium tropici strains from the Brazilian

bcerradoQ region. Rev. Microbiol. 29, 49–58.

Muyzer, G., De Waal, E.C., Uitterlinden, A.G., 1993. Profiling of

complex microbial populations by denaturing gradient gel elec-

trophoresis analysis of polymerase chain reaction-amplified

genes coding for 16S rRNA. Appl. Environ. Microbiol. 59,

695–700.

Muyzer, G., Hottentrager, S., Teske, A., Wawer, C., 1995. Denatur-

ing gradient gel electrophoresis of PCR-amplified 16S rDNA—

a new molecular approach to analyse the genetic diversity of

mixed microbial communities. In: Akkermans, A.D.L., Van

Elsas, J.D., De Bruijn, F.J. (Eds.), Molecular Microbial Ecology

Manual. Kluwer Academic Publishers, Dordrecht, The Nether-

lands, pp. 1–23 (section 3.4.4).

Pace, N.R., 1997. A molecular view of the microbial diversity and

the biosphere. Science 276, 734–740.

Pearson, K., 1926. On the coefficient of racial likeliness. Biometrika

18, 105–117.

Pitcher, D.G., Saunders, N.A., Owen, R.J., 1989. Rapid extraction

of bacterial genomic DNA with guanidium thiocyanate. Lett.

Appl. Microbiol. 8, 151–156.

Rosado, A.S., Seldin, L., Wolters, A.C., Van Elsas, J.D., 1996.

Quantitative 16S rDNA-targeted polymerase chain reaction

and oligonucleotide hybridization for the detection of Paeniba-

cillus azotofixans in soil and the wheat rhizosphere. FEMS

Microbiol. Ecol. 19, 153–164.

Rosado, A.S., Duarte, G.F., Seldin, L., Van Elsas, J.D., 1998.

Genetic diversity of nifH gene sequences in Paenibacillus azo-

tofixans strains and soil samples analysed by denaturing gradi-

ent gel electrophoresis of PCR-amplified gene fragments. Appl.

Environ. Microbiol. 64, 2770–2779.

Saitou, N., Nei, M., 1987. The neighbor-joining method: a new

method for reconstructing phylogenetic trees. Mol. Biol. Evol.

4, 406–425.

Salles, J.F., De Souza, F.A., Van Elsas, J.D., 2002. Molecular

method to assess the diversity of Burkholderia species in envi-

ronmental samples. Appl. Environ. Microbiol. 68, 1595–1603.

Sambrook, J., Fritsch, E.F., Maniatis, T., 1989. Molecular Cloning:

A Laboratory Manual, 2nd ed. Cold Spring Harbor Laboratory

Press, Cold Spring Harbor, NY, USA.

Smalla, K., Cresswell, N., Mendonca-Hagler, L.C., Wolters, A.C.,

Van Elsas, J.D., 1993. Rapid DNA extraction protocol from soil

for polymerase chain reaction-mediated amplification. J. Appl.

Bacteriol. 74, 78–85.

Sullivan, J.T., Ronson, C.W., 1998. Evolution of rhizobia by acqui-

sition of a 500-kb symbiosis island that integrates into the phe-

tRNA gene. Proc. Nat. Acad. Sc. U. S. A. 95, 5145–5149.

Swofford, D.L., 2000. PAUP*. Phylogenetic Analysis Using Parsi-

mony (*and Other Methods). Sinauer Associates, Sunderland,

MA.

Tan, Z., Hurek, T., Vinuesa, P., Muller, P., Ladha, J.K., Reinhold-

Hurek, B., 2001. Specific detection of Bradyrhizobium and

Rhizobium strains colonizing rice (Oryza sativa) roots by

16S–23S ribosomal DNA intergenic spacer-targeted PCR.

Appl. Environ. Microbiol. 67, 3655–3664.

Tebbe, C.C., Vahjen, W., 1993. Interference of humic acids and

DNA extracted directly from soil in detection and transforma-

tion of recombinant DNA from bacteria and a yeast. Appl.

Environ. Microbiol. 59, 2657–2665.

Thompson, J.D., Higgins, D.G., Gibson, T.J., 1994. CLUSTAL W:

improving the sensitivity of progressive multiple sequence

alignment through sequence weighting, position specific gap

penalties and weight matrix choice. Nucleic Acids Res. 22,

4673–4680.

Vallaeys, T., Top, E., Muyzer, G., Macheret, V., Laguerre, G.,

Rigaud, A., Souglas, G., 1997. Evaluation of denaturing gradi-

ent gel electrophoresis in the detection of 16S rDNA sequence

variation in rhizobia and methanotrophs. FEMS Microbiol.

Ecol. 24, 279–285.

Van Elsas, J.D., Mantynen, V., Wolters, A.C., 1997. Soil DNA

extraction and assessment of the fate of Mycobacterium chlor-

ophenolicum strain PCP-1 in different soils by 16S ribosomal

RNA gene sequence based most-probable-number PCR and

immunofluorescence. Biol. Fertil. Soils 24, 188–195.

Van Elsas, J.D., Smalla, K., Tebbe, A.C., 2000. Extraction and

analysis of microbial community nucleic acids from environ-

mental matrices. In: Jansson, J.K., Van Elsas, J.D., Bailey, M.J.

V.M. de Oliveira et al. / Journal of Microbiological Methods 64 (2006) 366–379 379

(Eds.), Tracking Genetically-Engineered Microorganisms.

Landes Bioscience, Georgetown, Texas, USA, pp. 29–52.

Van Elsas, J.D., Garbeva, P., Salles, J.F., 2002. Effects of agrono-

mical measures on the microbial diversity of soils as related to

the suppression of soil-borne plant pathogens. Biodegradation

13, 29–40.

Vlassak, K., Vanderleyden, J., Franco, A.A., 1996. Competition and

persistence of Rhizobium tropici and Rhizobium etli in tropical

soil during successive bean (Phaseolus vulgaris L) cultures.

Biol. Fertil. Soils 21, 61–68.

Young, J.M., Kuykendall, I.D., Martinez-Romero, E., Kerr, A.,

Sawada, H., 2001. A revision of Rhizobium Frank 1889, with

an emended description of the genus, and the inclusion of all

species of Agrobacterium Conn 1942 and Allorhizobium undi-

cola de Lajudie et al. 1998 as new combinations: Rhizobium

radiobacter, R. rhizogenes, R. rubi, R. undicola and R. vitis. Int.

J. Syst. Evol. Microbiol. 51, 89–103.