Denaturing gradient gel electrophoresis (DGGE) approaches to study the diversity of...

Denaturing gradient gel electrophoresis (DGGE) approaches to

study the diversity of ammonia-oxidizing bacteria

Mette Haubjerg Nicolaisen, Niels Birger Ramsing *

Department of Microbial Ecology, Institute of Biological Sciences, University of Aarhus,

Ny Munkegade, Building 540, DK-8000 Aarhus C, Denmark

Received 20 September 2001; received in revised form 5 February 2002; accepted 5 February 2002

Abstract

Denaturing gradient gel electrophoresis (DGGE) of PCR amplicons of the ammonia monooxygenase gene (amoA) was

developed and employed to investigate the diversity of ammonia-oxidizing bacteria (AOB) in four different habitats. The results

were compared to DGGE of PCR-amplified partial 16S rDNA sequences made with primers specific for ammonia-oxidizing

bacteria. Potential problems, such as primer degeneracy and multiple gene copies of the amoA gene, were investigated to

evaluate and minimize their possible impact on the outcome of a DGGE analysis. amoA and 16S rDNA amplicons were cloned,

and a number of clones screened by DGGE to determine the abundance of different motility types in the clone library. The

abundance of clones was compared to the relative intensity of bands emerging in the band pattern produced by direct

amplification of the genes from the environmental sample. Selected clones were sequenced to evaluate the specificity of the

respective primers. The 16S rDNA primer pair, reported to be specific for ammonia-oxidizing bacteria (AOB), generated several

sequences that were not related to the known Nitrosospira–Nitrosomonas group and, thus, not likely to be ammonia oxidizers.

However, no false positives were found among the sequences retrieved with the modified amoA primers. Some phylogenetic

information could be deduced from the position of amoA bands in DGGE gels. The Nitrosomonas-like sequences were found

within a denaturant range from 30% to 46%, whereas the Nitrosospira-like sequences migrated to 50% to 60% denaturant. The

majority of retrieved sequences from all four habitats with high ammonia loads were Nitrosomonas-like and only few

Nitrosospira-like sequences were detected. D 2002 Elsevier Science B.V. All rights reserved.

Keywords: Denaturing gradient gel electrophoresis; Diversity; Ammonia-oxidizing bacteria

1. Introduction

Knowledge of microbial diversity is essential to

understand the relationship between environmental

parameters and ecosystem function (Chao and Chao,

1997; Torsvik et al., 1996). For some environmentally

important but very slow growing bacteria, such as the

chemolithoautotrophic ammonia-oxidizing bacteria

(AOB), culture-dependent diversity studies can be

difficult and time consuming (Matulewich et al.,

1975), and the results may be biased due to our in-

ability to cultivate common organisms (MacDonald,

1986). Molecular techniques for identification that do

not require cultivation have been useful in studies of

different groups of microorganisms, including AOB.

0167-7012/02/$ - see front matter D 2002 Elsevier Science B.V. All rights reserved.

PII: S0167 -7012 (02 )00026 -X

* Corresponding author. Tel.: +45-8942-3248; fax: +45-8612-

7191.

E-mail address: [email protected] (N.B. Ramsing).

www.elsevier.com/locate/jmicmeth

Journal of Microbiological Methods 50 (2002) 189–203

One of these techniques is denaturing gradient gel

electrophoresis (DGGE) of PCR-amplified genes,

which can be used to evaluate the diversity of com-

plex microbial systems (Muyzer et al., 1993).

In DGGE, the separation of equal length DNA

fragments is based on sequence-dependent melting

behavior in a polyacrylamide gel containing a con-

centration gradient of increasing denaturant (Muyzer

et al., 1998). DGGE is a powerful technique whereby

the diversity of PCR-amplified genes from a large

number of samples can be compared in one gel to

reveal changes in community structure over time or

space. The DGGE technique has been applied to

investigate the diversity of AOB and other organisms

in many diverse habitats (Bano and Hollibaugh, 2000;

de Bie et al., 2001; Ivanova et al., 2000; Kowalchuk et

al., 1998, 1999, 2000; Luxmy et al., 2000; McCaig et

al., 1999). The method is much less time consuming

than traditional analysis by cloning and sequencing.

Furthermore, the gel provides direct information about

the abundance of each PCR amplicon, without intro-

ducing any additional bias inherent in a traditional

cloning step. On the other hand, the use of DGGE

primers with a GC-clamp and possibly additional PCR

cycles may likewise bias the outcome. AOB play an

important role in the global cycling of nitrogen

(Prosser, 1989), in wastewater treatment (Wagner et

al., 1995), and in many agricultural systems (McCarty,

1999), as they are responsible for the first and

frequently rate-limiting step in the process of nitrifi-

cation. 16S rDNA studies have revealed that the

autotrophic AOB are related to two distinct phyloge-

netic lineages. Most strains belong to a monophyletic

branch of the h-subclass of the Proteobacteria, whichincludes the genera Nitrosomonas and Nitrosospira

(the latter encompassing the former genera Nitrosovi-

brio and Nitrosolobus). However, a few strains belong

to the g-subclass of the Proteobacteria. This lineage

includes only two known species Nitrosococcus

oceanus and N. halophilus (Head et al., 1998; Purk-

hold et al., 2000; Teske et al., 1994). Studies of AOB

diversity using DGGE have until recently been

restricted to 16S rDNA analysis. However, a major

problem with the 16S rDNA approach is the limited

specificity of commonly used primers (Kowalchuk et

al., 1998; Rotthauwe et al., 1997). A subsequent

hybridization step (de Bie et al., 2001; Hastings et

al., 1998; Stephen et al., 1998) is usually required to

confirm the phylogenetic origin of the bands in a

DGGE analysis. A further problem with the 16S rDNA

approach is the high similarity of rDNA sequences,

which may make it impossible to resolve and identify

closely related AOB species.

An alternative approach is to use a translated gene

as a molecular marker (Sinigalliano et al., 1995; Wag-

ner et al., 1998; Wawer et al., 1997). AOB convert

ammonia to nitrite in a two step process, where the first

step is the conversion of ammonia to hydroxylamine

catalyzed by the enzyme ammonia monooxygenase

(Hooper et al., 1997). Rotthauwe et al. (1997) have

developed a primer pair (AmoA-1F and AmoA-2R),

which amplify a 491 bp fragment of the ammonia mo-

nooxygenase subunit A gene (amoA). amoA is present

in all autotrophic AOB and is believed to contain

enough information to make phylogenetic inferences

based on its sequence (Purkhold et al., 2000; Rot-

thauwe et al., 1997). The primers only amplify amoA

genes from AOB belonging to the h-Proteobacteriallineage; however, they were shown to be very specific

for detecting AOB in complex environments, includ-

ing soils and sediment (Rotthauwe et al., 1997).

Recently, Oved et al. (2001) have applied the amoA

amplicons to DGGE analysis in their analysis of AOB

diversity in soil, but without a thorough evaluation of

this new approach. In this study, we describe optimi-

zation and characterization of DGGE of partial amoA

amplicons. We have evaluated potential problems such

as multiple copies of the amoA gene and primer

degeneracy. Finally, we have compared a DGGE ana-

lysis of amoA amplicons from four environmental

samples with clone libraries from the same samples.

A similar analysis of amplicons obtained with the 16S

rDNA primers for AOB made an overall comparison

of the two approaches possible.

2. Materials and methods

2.1. Environmental samples

Samples were collected at four locations. (1) S:

Activated sludge from the aeration tank of Marselis-

borg sewage treatment plant, Arhus, Denmark, where

aeration cycles promote removal of nitrogen com-

pounds by coupled nitrification–denitrification. (2)

T: Air-exposed water-saturated surface sediment from

M.H. Nicolaisen, N.B. Ramsing / Journal of Microbiological Methods 50 (2002) 189–203190

an intertidal mudflat in the Tagus Estuary, Portugal.

The mudflat received discharge from Lisbon and the

average annual load of nitrogen to the estuary was 323

Amol m�2 h�1 (130 kg N ha�1 (4 months)�1) (Ottosen

et al., 2001). The tidal amplitude was 1 to 4 m, and the

salinity varied from 5–30xat low tide to 20–33xat high tide. (3) R: Surface soil from rice fields at

the International Rice Research Institute (IRRI), Los

Banos, Philippines. The fields were supplied with

nitrogen fertilizer (130 kg N ha�1 crop cycle�1). (4)

K: Surface sediment from Kysing Fjord, Denmark.

The Fjord is a shallow estuary with virtually no tidal

flow and a stable salinity of 14x. The nitrogen load

from freshwater input to the Fjord is high and keeps

the nitrogen content in the estuary at a constant high

level (Nielsen et al., 1995). All samples were imme-

diately frozen after sampling until DNA extraction.

2.2. Pure cultures

Cultures of N. europaea NCIMB #11850 and N.

multiformis ATCC #25196 were kindly provided by

Kristian Brandt, KVL, Denmark, and used for GC-

clamp evaluation as well as time travel experiments.

Both strains were grown at 30 jC in liquid media to

stationary phase as described by Donaldson and

Henderson (1989).

2.3. DNA extraction

For pure cultures, 20 ml of log phase cultures were

centrifuged for 30 min at 5000 rpm. The pellet was

dissolved in 2 ml of media. Two hundred microliters

was used for DNA extraction with the Fast DNA MH

kit (Bio 101, Vista, CA). For environmental samples,

direct DNA extractions were performed with the

FastDNA spin kit for soil (Bio 101, Vista, CA). In

both procedures, cell lysis was performed by vigorous

shaking in a bead beater at intensity 5.5 for 2� 15 s

(FastPrep DNA extractor, Bio 101, Vista, CA). The

kits were used according to the manufacturer’s

instructions. The quality of the DNA extracts was

evaluated by electrophoresis on a 1% SeaKem GTG

agarose gel (FMC BioProducts, Rockland, ME) that

was subsequently stained with 100 ng/ml SYBRGold

(Molecular Probes, Leiden, NL) for 20 min. The DNA

was visualized by UV transillumination (Gel Doc

2000, BioRad, Hercules, CA). Digital images of the

gels were acquired with a CCD camera controlled by

the software Quantity One (BioRad). This staining

and imaging protocol was used for all subsequent

gels. DNA extracts were stored at � 20 jC. To obtain

suitable amplicons, 10- to 100-fold dilutions of the

extract were used as template for subsequent PCR

reactions.

2.4. PCR-primers

Primers AmoA-1F (forward) and AmoA-2R (re-

verse), targeting a stretch corresponding to positions

332 to 349 and 802 to 822 of the open reading frame of

the ammonia monooxygenase subunit A gene (amoA)

of N. europaea, were developed and tested by Rot-

thauwe et al. (1997). This primer pair targets the amoA

gene from h-Proteobacteria AOB. For DGGE-PCR,

adding a 33 nt GC-clamp to one of the primers sta-

bilizes melting behavior of the amplified PCR frag-

ments (Kowalchuk et al., 1997; Sheffield et al., 1989).

To evaluate the optimal position of the GC-clamp, both

primers were tested with the GC-clamp. Primer

sequences are shown in Table 1. The AmoA-2R primer

has two degeneracies: a K ( =G or T) and a S ( =G or

C) at seven and nine nucleotides from the 5V-end,respectively. Primers with one or no degeneracy were

also constructed, giving a total of seven different

versions of the reverse primers (Table 1).

An alternative AOB primer pair, CTO189f-GC and

CTO654r, described by Kowalchuk et al. (1997) to

amplify a 465 bp fragment of the 16S rDNA gene

from Proteobacteria h-subgroup AOB, was used for

comparison. The length of both the amoA and the

partial 16S rDNA amplicons are less than 500 bp,

which makes them amenable to DGGE analysis

(Myers et al., 1985).

2.5. PCR

For GC-clamp evaluation, 50 Al PCR reactions

were performed with the two different primer pairs

AmoA-1F-Clamp/AmoA-2R and AmoA-1F/AmoA-

2R-Clamp [35.5 Al dH2O, 5 Al buffer (100 nM

Tris–HCl pH 8.8, 750 mM KCl, 15 mM MgCl2); 5

Al dNTP (1.25 mM of each dNTP); 1 Al forward

primer (50 pmol/Al); 1 Al reverse primer (50 pmol/Al);5U Taq DNA polymerase (Amersham Pharmacia

Biotech, Uppsala, Sweden); and 2 Al template]. The

M.H. Nicolaisen, N.B. Ramsing / Journal of Microbiological Methods 50 (2002) 189–203 191

PCR thermocycling regime was: 92 jC for 1 min, 35

cycles of 92 jC for 30 s, 57 jC for 30 s, 72 jC for 45

s + 1 s/cycle; the last cycle had a 5-min final extension

(modified from Kowalchuk et al., 1997). The time

travel experiments (Muyzer et al., 1993) were done

with the same setup and PCR conditions as above, but

with the primer pair AmoA-1F-Clamp/AmoA-2R-T

(Table 1). PCR amplicon aliquots were loaded every

half hour to evaluate the progressive migration of

bands in the gel.

All other PCR were performed as semi-nested

PCR. An initial hotstart PCR using primers without

the GC-clamp [7.5 Al HotstartTaq mastermix (Qiagen,

Hilden, Germany), 5.5 Al primer mix [0.3 Al AmoA-

1F primer, 0.3 Al AmoA-2R-TC primer and 4.9 AldH2O], 2 Al template,] was made with a 15-min pre-

incubation at 95 jC added to the program listed above.

The outcome was evaluated by agarose gel electro-

phoresis (see below). Bands of the expected length

from this PCR were cut out and used as templates for a

second PCR that was run with 16–18 cycles in a 50-Alsetup as described for GC-clamp evaluation. The latter

PCR reaction was made with GC-clamp primers for

DGGE analysis or with non-GC-clamp primers for

cloning. Partial 16S rDNA amplicons were obtained

with the CTO-16S rDNA primer pair using the same

nested protocol and PCR conditions as was used for

the amoA amplification.

When checking the clone insert size, a pipet tip was

used to transfer a small amount (less than 1 Al) of cellsfrom growing colonies directly into the PCR tube. The

AmoA-1F-Clamp/AmoA-2R-TC or the CTO 16S

rDNA primer pair was used in a 50-Al setup as de-

scribed above for the GC-clamp evaluation, but with

an initial step of 8 min at 95 jC to soften the cell walls.

All PCR products were evaluated by electropho-

resis on a 2% Nusieve 3:1 agarose gel (FMC Bio-

Products), and subsequently stained, illuminated and

photographed as described above.

2.6. Cloning

PCR amplicons were purified using the QIAquick

PCR purification kit (Qiagen) prior to cloning. The

amplicons were ligated into the pCR II-TOPO vector

(Invitrogen, Groningen, NL) and were further trans-

formed into competent cells using the TOPO TA

cloning kit (Invitrogen), following the manufacturer’s

protocol. White colonies were randomly picked from

each cloned sample, grown overnight, reamplified and

run on DGGE.

2.7. DGGE

DGGE of PCR products generated by the amoA

and CTO-16S rDNA primers were performed with the

D-Gene System (BioRad). Polyacrylamide gels [8%

of a 37:1 acrylamide–bisacrylamide mixture in

0.5�TAE buffer, 0.75 mm thick, 16� 10 cm], with

a gradient of 30–70% denaturant, were made with a

gradient maker (BioRad) according to the manufac-

turer’s guidelines. 100% denaturing acrylamide was

defined as 7 M Urea and 40% formamide by Muyzer

et al. (1993) so that 30% denaturant corresponds to

2.1 M Urea and 12% formamide. A top gel without

denaturant was cast above the denaturing gel before

the polymerization started. Gels were run for 6 h at

200 Vor 15 h at 100 V in 1�TAE buffer at a constant

Table 1

Primers used for PCR

Primer Sequence

AmoA-1F-Clampa 5V-Clamp-GGG GTT

TCT ACT GGT GGT-3VAmoA-1F 5V-GGG GTT TCT ACT

GGT GGT-3VAmoA-2R-Clampa,b 5V-Clamp-CCC CTC KGS

AAA GCC TTC TTC-3VAmoA-2R-KSb 5V-CCC CTC KGS AAA

GCC TTC TTC-3VAmoA-2R-TSb 5V-CCC CTC TGS AAA

GCC TTC TTC-3VAmoA-2R-GSb 5V-CCC CTC GGS AAA

GCC TTC TTC-3VAmoA-2R-TC 5V-CCC CTC TGC AAA

GCC TTC TTC-3VAmoA-2R-TG 5V-CCC CTC TGG AAA

GCC TTC TTC-3VAmoA-2R-GC 5V-CCC CTC GGC AAA

GCC TTC TTC-3VAmoA-2R-GG 5V-CCC CTC GGG AAA

GCC TTC TTC-3VCTO189f-Clampa,b 5V-Clamp-GGA GRA AAG

YAG GGG ATC G-3VCTO654rb 5V-CTA GCY TTG TAG

TTT CAA ACG C-3Va The GC-clamp added for DGGE-PCR: 5V-CGCCGCGCGGC-

GGGCGGGGCGGGGGC.b Degeneracies are shown in bold.


temperature of 60 jC. The gels were stained for 20

min in 150 ml 1�TAE buffer containing 100 ng/ml

SYBR Gold (Molecular Probes). Visualization and di-

gital photography was performed as described above

for agarose gels.

The DGGE-ladder consist of the following ampli-

cons (read from low denaturant concentration to high

denaturant concentration): amoA N. europaea, amoA

S clone #14 and #31, amoA T clone #27, CTO-16S

rDNA K clone #29, amoA N. multiformis (producing

four bands; two weak and two strong bands). For all

pictures, the uppermost visible band is N. europaea at

approximately 35% denaturant and the lowest N.

multiformis at about 55% denaturant.

2.8. Sequencing of DGGE bands

DGGE bands were excised using a sterile pipet tip,

transferred to 100 Al DNA buffer and frozen at � 20

jC until reamplification. Reamplification was done as

described for excised agarose bands. The reamplifica-

tion product was evaluated by DGGE to verify purity

and correct mobility of the reamplified product com-

pared to the environmental sample. Excised and ream-

plified bands, which in the DGGE rerun gave one band

at the expected position, were chosen for sequencing.

The PCR product was purified by the QIAquick

PCR purification kit (Qiagen) according to the man-

ufacturer’s instructions. Sequences were obtained

using Cy-5-labelled PCR primers and the Thermose-

quenase fluorescent cycle sequencing kit (Amersham

Pharmacia Biotech) according to manufacturer’s

guidelines. The cycle sequencing reactions were run

as 94 jC for 3 min, then 40 cycles of 92 jC for 30 s

and 57 jC for 30 s; 5-min final extension. Sequencing

products were subsequently loaded on an acrylamide

gel (Reprogelk Long Read, Amersham Pharmacia

Biotech) and run for 15 h at constant temperature (55

jC) and high voltage using an Alfexpressk DNA se-

quencer (Amersham Pharmacia Biotech).

2.9. Sequencing of clones

PCR amplicons of clone inserts were evaluated

with DGGE. Representative clones were picked for

plasmid isolation (Qiagen). The sequencing was done

as described above, but using Cy-5-labelled M13 F or

M13 R vector primers for the sequence reactions

(Invitrogen). Sequences were deposited at Genbank

with the following accession numbers: amoA partial

sequences: K_1: AF489630; K_2: AF489631; K_3:

AF489632; K_4: AF489633; K_5: AF489634; K_6:

AF489635; K_7: AF489636; K_8: AF489637; K_9:

AF489638; K_10: AF489639; K_11: AF489640;

K_12: AF489641; K_13: AF489642; K_14:

AF489643; T_1: AF489644; T_2: AF489645; T_3:

AF489646; T_4: AF489647; T_5: AF489648; T_6:

AF489649; T_7: AF489650; T_8: AF489651; T_9:

AF489652; T_10: AF489653; T_11: AF489654;

T_12: AF489655; T_13: AF489656; T_14:

AF489657; T_15: AF489658; S_1: AF489659; S_2:

AF489660; S_3: AF489661; S_4: AF489662; S_5:

AF489663; S_6: AF489664; S_7: AF489665; S_8:

AF48966; S_9: AF489667; S_10: AF489668; S_11:

AF489669; S_12: AF489670; S_13: AF489671;

S_14: AF489672; S_15: AF489673; R_1:

AF489674; R_2: AF489675; R_3: AF489676; R_4:

AF489677; R_5: AF489678; R_6: AF489679; R_7:

AF489680 16S rDNA partial sequences:K_1:

AF489681; K_2: AF489682; K_3: AF489683; K_4:

AF489684; K_5: AF489685; K_6: AF489686; K_7:

AF489687; K_8: AF489688; K_9: AF489689; R_1:

AF489690; R_2: AF489691; R_3: AF489692; R_4:

AF489693; R_5: AF489694.

2.10. Phylogenetic analysis

amoA sequences were manually aligned in SeqPup

v. 0.6 (http://www.iubio.bio.indiana.edu/soft/molbio/

seqpup/java/seqpup-doc.html) against a pure culture

sequence database kindly provided by Ulrike Purk-

hold, TU, Munich. 16S rDNA sequences were aligned

using the general small-subunit alignment from the

Ribosomal Database Project v. 7.1 (http://www.rdp.

cme.msu.edu/html/analyses.html). Aligned amoA

nucleotide sequences were translated to amino acid

sequences by SeqPup. Only nucleotide or amino acid

positions that were unambiguously aligned were used

in the subsequent phylogenetic analysis. Phylogenetic

analysis was performed by the computer program

PAUP v. 4.0 (Sinauer Associates, Sunderland, MA)

using default settings for the various algorithms. Phy-

logenetic relationships were inferred by distance

matrix, maximum likelihood and maximum parsimony

algorithms, whereas the amino acid sequences were

only evaluated by distance matrix and parsimony


algorithms. A bootstrap analysis with 100 resamplings

was made for all datasets to evaluate the stability of the

phylogeny derived from distance matrices.

3. Results

3.1. Pure culture studies

Preliminary investigations revealed that separation

of amoA fragments from different organisms by

DGGE was possible. With the GC-clamp affixed to

the forward primer, amplicons of pure cultures pro-

duced a clear and sharp band pattern after DGGE,

whereas a smear of bands was found when the GC-

clamp was affixed to the reverse primer (data not

shown). The GC-clamp was, therefore, affixed to the

AmoA-1F primer in all following PCR amplifications

of amoA for DGGE. A time travel experiment

(Muyzer et al., 1993), where identical samples were

loaded at half-hour intervals on a DGGE gel, was used

to determine the optimal runtime, which was found to

be 6 h at 200 V (data not shown). DGGE of the pure

culture amplicons revealed four bands for N. multi-

formis (Fig. 1). Excision and reamplification of bands

1 and 2 gave a single band at their respective positions

on a DGGE rerun. However, reamplification of either

of the two uppermost bands, bands 3 and 4, gave rise

to all four bands with similar intensities as in the

original band pattern (Fig. 1). Bands 3 and 4 appeared

to be heteroduplexes of the two lower bands, bands 1

and 2, which was confirmed when a mixture of bands

1 and 2 likewise reproduced the original four-band

pattern. This indicates that N. multiformis has at least

two copies of the amoA gene and that, though similar,

there are differences in the gene sequence of these

copies.

N. europaea only produced one band after the

DGGE (Fig. 1), suggesting that the organism only

carry one copy of the amoA gene or possibly multiple

copies with identical mobility.

Sequencing of the two lower bands from N. multi-

formis and the one band from N. europaea confirmed

the interpretation. The sequence obtained from N.

europaea was identical to the sequence published by

Hommes et al. (1998). The N. multiformis sequences

differed at two base positions; yet both sequences

were virtually identical to the sequence published by

Rotthauwe et al. (1995), with only 3 and 4 nt differ-

ences, respectively.

3.2. Optimization of PCR

Direct use of DGGE primers to amplify environ-

mental DNA, often caused unspecific priming (data

not shown). It was especially pronounced when only

small numbers of AOB were expected in the sample

(e.g. soil from rice paddies without fertilizer amend-

Fig. 1. DGGE of amoA amplicons from Nitrosomonas europaea and

Nitrosospira multiformis. The N. europaea amplicon only contain

one band which was sequenced and found to be identical to the

sequence published by (Hommes et al., 1998). N. multiformis gene-

rate four bands. Bands 1 and 2 were sequenced and found to be two

different copies of the amoA gene. Bands 3 and 4 of N. multiformis

are heteroduplexes of bands 1 and 2 since a reamplification of ex-

cised band 3 or of band 4 recreate the complete band pattern of four

bands.


ment). However, changing the PCR protocol to a

semi-nested strategy, comprised of an initial PCR

without the GC-clamp using a hotstart polymerase

setup, followed by a second PCR using the GC-clamp

primers and a standard Taq polymerase, solved the

problem. All amplifications of the amoA gene using

this protocol produced a single band of the expected

length on agarose gels and the product was amendable

to DGGE analysis.

3.3. AmoA-2R primer degeneracy

Fig. 2 shows PCR amplicons of amoA genes in a

rice soil sample, R, made using seven different ver-

sions of the AmoA reverse primer (see Table 1 for

primer sequences). The original reverse primer,

AmoA-2R, proposed by Rotthauwe et al. (1997), con-

tains two base degeneracies: a mixture of G and T at

position 7 and a mixture of G and C at position 9. This

primer gave a complex picture with many indistinct

bands and high background intensity, presumably due

to heteroduplex formation. However, the nondegener-

ate primers gave a much clearer band pattern produc-

ing only four bands each. The patterns obtained from

the four nondegenerate primers each consisted of two

distinct bands and a double band. The AmoA-2R-TC

and AmoA-2R-GG, which were believed to be the

most different of the four nondegenerate primers (see

discussion), were evaluated more closely. The two

distinct bands from each primer amplicon were

excised from the DGGE gel and sequenced. The

sequences of the upper bands with either primer were

found to be identical, except for the reverse priming

site. The same was found for the lower band with

either primer. The observed differences in mobility by

DGGE between the two-band patterns were, thus,

ascribed to the primer sequence difference. Hence,

the primers seem to amplify the same target sequences

and the distinct differences in the banding patterns

produced by the nondegenerate primers simply arise

because of differences in the primer sequence. The

apparent complexity of the DGGE pattern produced

by the original primer set AmoA-1F/AmoA-2R is,

thus, a side effect of using a degenerate primer and

does not reflect the original diversity. We, therefore,

chose of the AmoA-2R-TC primer as the reverse

primer in all further studies.

3.4. DGGE

Primer specificity and PCR reproducibility is essen-

tial when working with the PCR-DGGE approach. The

DGGE band pattern of environmental samples showed

a high degree of reproducibility both between PCR

amplifications, when the same DNA extract was am-

plified multiple times, and between DGGE gels, when

the same PCR product was loaded several times. How-

ever, a few samples were encountered in which a direct

PCR protocol with fewer cycles was required to obtain

a reproducible DGGE band pattern.

DGGE was run on both amoA and 16S rDNA

amplicons from the four environments to reveal the

differences in band pattern (Fig. 3). The band pattern

for amoA amplicons were generally more complex

than the band pattern obtained by the 16S rDNA am-

plicons. A notable exception was the R sample. To

evaluate the specificity of the amoA primer pair and

compare it to the CTO-16S rDNA approach, we cloned

and sequenced both types of amplicons from different

environments. Amplified amoA fragments from four

Fig. 2. DGGE of sample R amplified with seven different reverse

primers. The same template is amplified with all primerpairs The

complex pattern generated by degenerate primers is a simple sum of

the band patterns generated by the respective nondegenerate

primers. Subsequent sequencing of bands produced by the two

nondegenerate primers AmoA-2R-GG and AmoA-2R-TC thus gave

identical sequences except for the primer sequences themselves.


locations, S, T, R and K and 16S rDNA fragments of

AOB from two locations R and K were investigated.

Randomly picked clones from each site were amplified

and the mobility on a DGGE gel was determined. The

most intense bands from the DGGE analysis of envi-

ronmental samples were also the bands most fre-

quently encountered amongst the examined clones

(Fig. 4). This indicated a semiquantitative performance

of the cloning step, which is supported by the fact that

only a few weak bands present in the environmental

sample were not retrieved among the clones. The slight

discrepancy is likely to be a statistical effect of picking

too few clones. However, one prominent DGGE band

from the sewage sample and another prominent DGGE

band from the Tagus Estuary were never found among

the examined clones. Reamplification and rerun of

these bands did not reproduce their position and they

were interpreted as PCR artifacts such as single

stranded DNA or heteroduplexes. Some of the cloned

bands were not directly visible in the DGGE pattern of

the environmental sample. Possible explanations are

discussed below.

3.5. Phylogeny

The overall branching order for the phylogenetic

trees shown in Figs. 5 and 6 was supported by all the

different algorithms used (i.e. maximum parsimony,

distance matrix and maximum likelihood). The amoA

amino acid-based tree and the amoA nucleotide-based

tree revealed similar branching patterns (Fig. 5a and

b). Even though amino acid-based trees are probably

less biased by multiple substitutions, fine scale reso-

lution of the very closely related amoA sequences is

often better resolved by the nucleotide-based trees

(Rotthauwe et al., 1997).

3.5.1. Activated sludge and Tagus Estuary amoA

sequences

As seen in Fig. 5a, the major part of the retrieved S

and T clones belonged to two distinct phylogenetic

lineages. Group I were related to the N. europaea/N.

eutropha cluster 7 (according to Kowalchuk et al.,

2000) and group II were related to N. oligotropha

cluster 6a.

Fig. 3. DGGE of amplicons from a waste water treatment plant, S;

an estuary, K; a tidal mudflat, T; and rice paddy soil, R after

amplification with the amoA primers and the CTO-16S rDNA

primers, respectively. amoA amplicons always gave clear bandpat-

terns with several distinct bands, whereas the CTO amplicons often

gave a smeary pattern with no distinct bands (e.g. sample S).

However, the number of bands cannot be used as a direct indication

of diversity due to the multiple copies of amoA.

Fig. 4. Relative clone abundance in library vs. the relative intensity

of the corresponding DGGE band from the environmental amplicon.


Fig. 5. Phylogenetic trees of amoA sequences based on an uncorrected distance matrix. (a) Phylogenetic tree based on amino acid sequences. (b)

Phylogenetic tree based on nucleotide sequences. Branching patterns that were not supported by bootstrap values above 50% have been

collapsed to multifurcations. Closely related sequences originating from the same sample are represented by triangles to give a better overview.


3.5.2. Kysing Fjord amoA sequences

Eleven out of 14 sequences from K were related to

N. marina and N. aestuarii (cluster 6). Two sequences

(K1 and K22) were positioned together and possibly

related to the Nitrosospira group, but not closely

related to any pure cultures. One sequence was very

closely related to N. europaea.

3.5.3. Rice field amoA sequences

The retrieved R sequences all fell together in one

group with the closest relative in pure culture being N.

nitrosa.

3.5.4. 16S rDNA sequences

16S rDNA sequences from K fell into two groups,

both closely related to the Nitrosomonas group (Fig.

6). One group was related to N. marina (cluster 6) and

the other one a distinct, but related, sister group. This

was in excellent agreement with the sequences found

for the K sample with the amoA primers, where 11 of

14 sequences were related to N. marina.

The 16S rDNA sequences retrieved with the CTO

primer pair from rice field sample R only revealed one

AOB sequence, which was related to the Nitrosospira

branch of AOB. Four other sequences retrieved with

these primers belonged to a lineage related to Meth-

ylophilus methylotrophus in another branch of the h-Proteobacteria (Fig. 6). It is difficult to compare the

consistency of the phylogeny obtained from R using

the two different genes since there is only a single

sequence from the 16S rDNA that is related to known

AOB sequences.

All sequences retrieved with the amoA primers

were positive, whereas only 20% of the clones re-

Fig. 6. Phylogenetic tree based on 16S rDNA nucleotide sequences using a distance matrix algorithm. Representative sequences from the h-Proteobacterial subclass are included.


trieved with the CTO primer set fell into the expected

AOB lineages.

3.10. Sequence variation vs. mobility in DGGE

By sequencing several amoA and some CTO-16S

rDNA clones with identical mobility patterns, it was

found that the sequences obtained could differ consid-

erably despite identical mobility. However, in most

cases, bands with equal mobility gave identical se-

quences.

By comparing the phylogenetic distance (percent

base difference) and the mobility differences by

DGGE (percent denaturant difference at band position)

of the amoA sequences, it seems that some information

regarding sequence similarity can be revealed by

DGGE analysis. Fig. 7, based on S and T clones, show

that a large difference between band mobility on the

DGGE gel implies at least a minimal amount of

sequence divergence. On the other hand, nothing can

be said about sequences with very similar mobility.

Furthermore, there was a separation of the Nitro-

somonas- and the Nitrosospira-like sequences on the

DGGE gel, where Nitrosomonas-like sequences had a

melting point in the range f 30% to f 46% and the

Nitrosospira-like sequences had a melting point in the

range f 50% to f 60%.

4. Discussion

The strength of DGGE as a screening method for

diversity is the ability to monitor changes in com-

munity structure in response to changes in environ-

mental parameters over space and time. Studies where

we seek to evaluate the stability of community struc-

ture in relation to perturbations of the environment

may benefit from using the DGGE approach because

of the high resolution and the large amount of samples

that can be analyzed in a short time.

The reproducibility of the initial PCR is critical for

the reliability of the subsequent DGGE analysis and

the PCR protocol should, therefore, be optimized for

the environmental system investigated. Detailed

knowledge of primer specificity is also essential for

proper interpretation of DGGE analysis results. The

methane monooxygenase (pmmo) gene of methano-

trophic bacteria from the g-subclass of Proteobacteria

and the amoA gene of g-subclass AOB are more

closely related than the amoA gene from the g-sub-

class is to the h-subclass amoA gene (Holmes et al.,

1995; Klotz and Norton, 1998; Rotthauwe et al.,

1997). It is, therefore, not possible to target the g-

subclass amoA, together with the h-subclass amoA,

without targeting the pmmo from the methane oxidiz-

ing bacteria at the same time. The amoA primer pair

and the 16S rDNA CTO primers, therefore, only

target the h-subclass AOB. However, presently, onlytwo AOB species belonging to the g-subclass of

Proteobacteria have been described and both of these

are from marine environments. The vast majority of

the known autotrophic AOB still belong to the h-subclass. Finally, it should be emphasized that the

heterotrophic AOB are not targeted by the amoA-

primer set, nor with the 16S rDNA primers (Kowal-

chuk et al., 1997; Rotthauwe et al., 1997). It is, thus,

likely that the amoA-based approach underestimates

the functional diversity.

In the present study, the choice of reverse primer

AmoA-2R-TC was based on both experimental and

theoretical considerations. The original reverse primer

Fig. 7. Correlation between amoA sequence similarity and band

position in a DGGE gel. For each pair of sequences, the percent

sequence divergence was plotted against the difference in band

mobility measured as percent denaturant. Bands with similar DGGE

mobility could have very different sequences. However, bands with

very dissimilar mobility in the DGGE gel (e.g. > 17% denaturant)

were also always shown to have very different nucleotide sequences

(e.g. < 80% amoA sequence similarity).


sequence described by (Rotthauwe et al., 1997) had

two ambiguous positions (Table 1). As the DGGE

analysis is able to discriminate between sequences that

only differ at a single base position (Myers et al.,

1987), degenerate primer sequences can result in addi-

tional bands, or produce a smear of bands in a DGGE

analysis, even in environmental samples with low

diversity. This was found to be the case for the original

AmoA-2R primer as shown in Fig. 2. Similar obser-

vations have been made by Kowalchuk et al. (1997)

when using the CTO primers. Degenerate primers can

potentially amplify a wider range of sequences since it,

in theory, is able to anneal to more targets. However,

investigations by Bjerrum et al. (submitted for pub-

lication) indicate that the degeneracies in the AmoA-

2R reverse primer sequence are not critical for efficient

amplification of different target sequences. They

showed using competitive PCR that amplification

efficiency for templates with each of the four possible

priming sites did not differ significantly when using

the nondegenerate AmoA-2R-TC primer. Conse-

quently, we find that the primer pair AmoA-1F and

AmoA-2R-TC is a reasonable choice for PCR-DGGE

analysis of environmental amoA sequences.

The amoA gene is present in three copies in Nitro-

sospira sp. NpAV (Norton et al., 1996) and two copies

in N. europaea (McTavish et al., 1993). The copies of

the amoA gene is supposed to have arisen from gene

duplication and not by horizontal gene transfer, as

there is a higher similarity between different gene

copies in each investigated strain than between genes

from different strains (Klotz and Norton, 1998; Norton

et al., 1996). A hypothesis is that the high similarity

between gene copies is maintained through homolo-

gous recombination since third codon mutations are

almost absent (Norton et al., 1996). However, as single

base mutations may be readily detected by DGGE,

even highly similar gene sequences from a given or-

ganism may give rise to multiple bands in a DGGE gel.

In our study, DGGE analysis of N. multiformis amoA

amplicons produced four bands, whereas N. europaea

amoA amplicons only gave one band (Fig. 1). It is

possible that the strains we were working with had a

different number of gene copies than the ones inves-

tigated by Norton et al. (1996) and McTavish et al.

(1993). Alternatively, some of the gene copies could

be identical. Finally, it is possible that some of the se-

quences could contain several mutations, which in

combination has no net effect on the melting behavior.

Multiple gene copies and heteroduplex formation dur-

ing the last PCR cycles is a large potential problem

when using the complexity of a DGGE band pattern to

evaluate the biodiversity present in any given sample.

We are generally skeptical about attempts to use

DGGE for this purpose as the nature of each band

and the relationship between number of species and

band numbers are rarely known. However, when using

DGGE to evaluate gradual changes in community

structure over space and time following a perturbation,

in which case reproducible changes in band intensities

are more interesting than the band pattern itself, the

DGGE approach seems appropriate. Still, the number

of PCR cycles applied should always be as low as

possible.

Several cloned amoA sequences produced bands

that were not directly visible in DGGE analysis of the

environmental samples. Most of these sequences dif-

fered only by a few bases from sequenced bands that

were found in the same environmental sample. These

clones may also have been present in the environ-

mental PCR amplicon, but of such low abundance that

they were not visible as bands on the DGGE gel.

Alternatively, these sequences could have been pro-

duced by PCR errors in amplification of the more

dominant environmental bands. The general impor-

tance of using a polymerase which perform proof-

reading, e.g. have 3V–5Vexonuclease activity, has beenstressed before (Simpson et al., 1999). Yet, in the

present study, a Taq polymerase without the 3V–5Vexonuclease activity was used, which could have

produced erroneous sequences with slightly different

migration patterns in the DGGE. However, as the re-

producibility of the DGGE pattern of environmental

samples was always evaluated and found to be excel-

lent, random sequence mutations during amplification

was not a likely explanation for our findings.

The CTO-16S rDNA primer-based sequence anal-

ysis of the Kysing Fjord K samples (Fig. 6) revealed

two clusters of sequences related to the Nitrosomonas

group, one of which was more closely related to N.

marina. This result was remarkably similar to what

was found for the retrieved amoA sequences and a ge-

neral agreement between the results of the two

approaches was observed. Additional sequences be-

longing to other AOB lineages were found by the

amoA primers, indicating that a higher diversity was


revealed by this primer pair. The results from the R

sample was quite different as there was only one

sequence from the 16S rDNA approach branching

among known AOB sequences. The amplification of

R sequences outside the Nitrosomonas–Nitrosospira

clade by the CTO-16S rDNA primers illustrates the

difficulties to be expected when attempting to make a

specific primer pair for selective amplification of an

ultraconservative gene, such as the 16S rDNA gene,

from particular organisms (see also Kowalchuk et al.,

1997; Rotthauwe et al., 1997). The apparently higher

diversity revealed with these primers compared to

amoA primers for the R sample (Fig. 3) was, therefore,

not a correct picture of the actual AOB diversity found

in the sample.

To illuminate a possible discrepancy between the

two approaches, more sequences from this environ-

ment are required. With the amoA primers, even se-

quences belonging to novel phylogenetic lineages are

likely to be from strains capable of doing the process,

assuming that no paralogous sequence is detected.

It has previously been assumed very difficult to

infer phylogenetic relatedness from DGGE band mobi-

lity (Kowalchuk et al., 1997, 2000; Muyzer et al.,

1993). However, distantly related sequences always

displayed very different melting behavior and, con-

sequently, different mobility in a DGGE gel (Fig. 7).

On the other hand, identical mobility did not imply

sequence identity, which has also been confirmed in

other DGGE studies (Kowalchuk et al., 1998). Purk-

hold et al. (2000) have through a thorough analysis of

the phylogeny of AOB pure cultures suggested that

20% difference in amoA nucleic acid sequence could

be a reliable indication of a novel species in environ-

mental samples. For all amoA amplicons whose cor-

responding band position in a DGGE gel differed by

more than 17% denaturant, the nucleic acid sequence

difference was found to be larger than 20% (Fig. 7).

Indications of new species can, therefore, also be

obtained from DGGE gels directly in that amoA bands

separated by more than 17% denaturant are not likely

to be from the same species. However, it should be

stressed that for bands separated by less than 17% de-

naturant, no direct conclusions can be made. Another

important finding of this study was a marked differ-

ence in mobility between clones related to Nitroso-

spira vs. clones related to Nitrosomonas. The mobility

of the former was much larger, producing bands within

a denaturant concentration gradient from 50% to 60%,

whereas cloned Nitrosomonas sequences ceased to

move at much lower concentrations of denaturant

(30–46%). This observation has subsequently been

confirmed in our lab with cloned amoA sequences

from a broad range of habitats and is consistent with

the data obtained and described by Oved et al. (2001).

The amoA primer set has previously been used to

study AOB diversity in environmental samples (Ste-

phen et al., 1999). In that study, only sequences related

to Nitrosospira were detected and it was mentioned

that this could suggest that the amoA primer set was

not compatible with the Nitrosomonas present in the

soil. Most sequences retrieved in this study from the

four habitats were from the Nitrosomonas cluster 6a;

our findings do not support the suggestion that Nitro-

somonas sequences might be less amplifiable by the

amoA primers. Furthermore, sequences retrieved from

a particular habitat were often strongly related; thus,

they formed a cluster in the subsequent phylogenetic

analysis (Figs. 5 and 6). The fact that environmental

sample sequences appear to be genetically related

indicates that environmental factors select for partic-

ular strains of AOB. This ecological impact of the

environment on AOB community structure has pre-

viously been reported by other investigators (e.g.

Kowalchuk et al., 1998; Rotthauwe et al., 1997; Ste-

phen et al., 1998).

We find that the DGGE analysis of amoA ampli-

cons is a reliable screening tool to investigate AOB

diversity in a wide range of environments. Changes in

band pattern and relative intensities are informative

and may well contribute to a quantitative understand-

ing of the system. However, general limitations of

DGGE-based approaches also apply to this setup. The

limitations have been reviewed by Muyzer et al.

(1998).

Even though molecular tools are important in the

investigation of AOB, attempts to obtain pure cul-

tures, especially from novel lineages not yet repre-

sented in culture collections, should remain a priority.

To exploit the molecular information collected in

recent years, it is necessary to allocate more time to

obtain environmental strains in pure culture. Informa-

tion from pure culture studies of environmental strains

will illuminate the relative potential and weaknesses

of the 16S rDNA approach, as well as the amoA

approach, in investigating AOB diversity.


Acknowledgements

This study was supported by RUF, Danish Interna-

tional Development Agency. We want to thank Dorte

Ganzhorn and Pernille Vester Thykier for their ex-

cellent technical assistance, Lotte Bjerrum for her in-

put through many useful discussions, and the anony-

mous reviewers for their helpful comments. We would

also like to thank Prof. Wolfgang Reichardt and co-

workers for inspiring discussions and a hospitable

collaboration.

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