Comparison of PCR primer-based strategies for characterization of ammonia oxidizer communities in...

ComparisonofPCRprimer-based strategies for characterizationofammonia oxidizer communities in environmental samplesShahid Mahmood, Thomas E. Freitag & James I. Prosser

School of Medical Sciences, Institute of Medical Sciences, University of Aberdeen, Foresterhill, Aberdeen, UK

Correspondence: James I. Prosser, School of

Biological Sciences, Department of Plant and

Soil Science, Cruickshark Building, St Machar

Drive, Aberdeen AB24 300, UK.

e-mail: [email protected]

Received 25 April 2005; revised 23 September

2005; accepted 28 October 2005.

First published online 2 February 2006.

doi:10.1111/j.1574-6941.2006.00080.x

Editor: Riks Laanbroek

Keywords

16S rRNA gene; denaturing gradient gel

electrophoresis; ammonia oxidizing bacteria;

grassland soil; marine sediment.

Abstract

PCR-based techniques are commonly used to characterize microbial communities,

but are subject to bias that is difficult to assess. This study aimed to evaluate bias of

several PCR primer-based strategies used to study diversity of autotrophic

ammonia oxidizers. 16S rRNA genes from soil- or sediment-DNA were amplified

using primers considered either selective or specific for betaproteobacterial

ammonia oxidizers. Five approaches were assessed: (a) amplification with primers

bAMO143f-bAMO1315r; (b) amplification with primers CTO189f-CTO654r;

(c) nested amplification with bAMO143f-bAMO1315r followed by CTO189f-

CTO654r primers; (d) nested amplification with bAMO143f-bAMO1315r

and CTO189f-Pf1053r primers; (e) nested amplification with 27f-1492r and

CTO189f-CTO654r primers. Amplification products were characterized

by denaturing gradient gel electrophoresis (DGGE) analysis after further amplifi-

cation with 357f-GC-518r primers. DGGE profiles of soil communities were

heterogeneous and depended on the approach followed. Ammonia oxidizer

diversity was higher using approaches (b), (c) and (e) than using (a) and (d),

where sequences of the most prominent bands showed similarities to nonammonia

oxidizers. Profiles from marine sediments were more consistent, regardless

of the approach adopted, and sequence analysis of excised bands indicated that

these consisted of ammonia oxidizers only. The study demonstrates the impor-

tance of choice of primer, of screening for sequences of nontarget organisms

and use of several approaches when characterizing microbial communities in

natural environments.

Introduction

Characterization of natural microbial communities is now

routinely carried out using cultivation-independent techni-

ques, many of which are based on analysis of 16S rRNA

genes. In aquatic environments, cells can be detected using

fluorescence in situ hybridization (FISH), using 16S rRNA

probes, providing direct evidence of the presence of parti-

cular phylogenetic groups. This approach is of less value in

soil environments, where FISH is not feasible, where more

comprehensive phylogenetic analysis is required or where

alternative genes are targeted, for example functional genes.

In these situations, the most commonly used approach is

PCR amplification of target genes from extracted nucleic

acids, which can introduce biases associated with cell lysis,

nucleic acid extraction, choice of primer and amplification

errors (MathieuDaude et al., 1996; Suzuki & Giovannoni,

1996; von Wintzingerode et al., 1997; Polz & Cavanaugh,

1998; Suzuki et al., 1998; Lueders & Friedrich, 2003).

Although accepted as a potential limitation of PCR-based

approaches, the extent of bias is rarely tested or quantified.

Molecular characterization has been particularly valuable

for analysis of ammonia oxidizer diversity and community

structure. These organisms oxidize ammonia to nitrite, the

first step of the nitrification process, and therefore play an

essential role in terrestrial and aquatic nitrogen cycles. They

regulate supply of nitrogen for plant growth, compete for

ammonia with primary producers in marine environments

and contribute to significant loss of ammonia-based fertili-

zers, nitrate pollution of groundwaters and production of

nitrous oxides. Ecological studies of ammonia oxidizing

bacteria (AOB), however, have been severely restricted by

difficulties in laboratory cultivation, and the isolation of

these organisms and subsequent identification are

FEMS Microbiol Ecol 56 (2006) 482–493c� 2006 Federation of European Microbiological SocietiesPublished by Blackwell Publishing Ltd. All rights reserved

traditionally based on a limited number of phenotypic

characteristics. Several molecular approaches have been

developed for characterization of ammonia oxidizer com-

munities since the initial sequencing of several AOB 16S

rRNA genes (Head et al., 1993), and the design and applica-

tion of PCR primers for amplification of AOB targeting 16S

rRNA genes (McCaig et al., 1994). Several studies have also

employed analysis of ammonia oxidizer functional genes, in

particular amoA genes that encode ammonia monooxygen-

ase, but also hydroxylamine oxidoreductase and cytochrome

c-544 (Rotthauwe et al., 1997; Bruns et al., 1998). 16S rRNA

gene-based analysis of AOB has been facilitated by the

observation that, with the exception of a few marine gam-

maproteobacterial strains, the majority of proteobacterial

AOB falls within a monophyletic group within the Betapro-

teobacteria. This has led to the design of a relatively large

number of probes, for FISH analysis, and primers, for PCR

amplification of 16S rRNA genes. These vary in the extent to

which they are inclusive of all known betaproteobacterial

AOB and are specific, excluding nonammonia oxidizers. The

specificity of the probe and primer sequences were compared

in (Purkhold et al., 2000), who concluded that the CTO

primers (Kowalchuk et al., 1997) are the most specific,

whereas the bAMO primers (McCaig et al., 1994) are the

most inclusive. Characterization of natural AOB commu-

nities by PCR amplification of 16S rRNA genes also involves

a range of approaches for the generation and analysis of PCR

products. These include direct and nested PCR amplifica-

tion, sequence analysis of representatives from clone libraries

and a number of fingerprinting techniques, most commonly

denaturing gradient gel electrophoresis (DGGE) (Muyzer

et al., 1993; Kowalchuk et al., 1997), but also temperature

gradient gel electrophoresis (TGGE) (Fouratt et al., 2003)

and single-strand conformation polymorphism (SSCP)

(Backman et al., 2003).

There is little information on the extent to which these

different approaches influence the outcome of environmen-

tal studies of AOB communities. The aim of this study was

to assess potential bias resulting from two different PCR

based approaches, direct and nested PCR amplification of

16S rRNA genes, using different combinations of AOB

‘specific’ primers. A final amplification step enabled direct

comparison of the different strategies on DGGE gels.

Although focusing on AOB, the findings are of relevance to

characterization of other bacterial groups using similar

approaches.

Materials and methods

Sampling of soil and marine sediments

Soil samples (top 8 cm depth) were collected from an

improved grassland soil at the Sourhope Research Station

located in the Borders region of Scotland (map reference NT

850 205). Further details of the vegetation cover, fertilizer

application and soil characteristics are given in (McCaig

et al., 1999). After sampling, soil was stored at 4 1C for 3 days

and passed through a 3.35-mm sieve to remove roots and

stones. Sediment samples were collected from Loch Duich, a

marine loch, located on the west coast of Scotland, from a

sediment core of 40 cm depth. Further details of the

sampling procedure are given in (Freitag & Prosser, 2003).

Before extraction of nucleic acids, the water content of

sediments was reduced to approximately 5% (w/v, weight

in volume) of the total water content by centrifugation at

16 000 g for 10 min. Soil and marine sediment samples were

stored at � 80 1C until extraction of DNA.

DNA extraction

DNA was extracted from 0.5 g soil or sediment samples

according to (Griffiths et al., 2000a). In brief, cells were lysed

for two cycles of 20 s with a Ribolyser cell disruptor (Hybaid

Ltd., Ashford, UK) at 4 m s�1 in 2 mL Blue Matrix Ribolyser

tubes (Hybaid Ltd.) containing 0.5 mL hexadecyltrimethyl-

ammonium bromide extraction buffer, 0.5 mL phenol-

chloroform–isoamyl alcohol [25 : 24 : 1 v/v (volume in

volume), pH 8.0] and ceramic and silica beads. Further

extraction and precipitation of nucleic acids involved re-

moval of phenol with an equal volume of chloroform–iso-

amyl alcohol (24 : 1) followed by precipitation from the

aqueous layer with two volumes of 30% (w/v) polyethylene

glycol 6000–1.6 M NaCl. Pelleted nucleic acids were washed

in ice-cold 70% (v/v) ethanol, air-dried and resuspended in

50 mL of RNase-free sterile water.

PCR amplification of 16S rRNA genes

16S rRNA gene amplification of extracted soil DNA was

achieved by PCR using primers considered to be either

inclusive of or specific for betaproteobacterial AOB using

five approaches (Table 1). Two involved direct amplification

using primer sets bAMO143f-bAMO1315r (McCaig et al.,

1994) or CTO189f-CTO654r (Kowalchuk et al., 1997).

bAMO143f-bAMO1315r primers amplify all known beta-

proteobacterial ammonia oxidizer sequences but can also

amplify closely related nonammonia oxidizer sequences.

CTO189f-CTO654r primers are specific for all known

betaproteobacterial ammonia oxidizers, with the exception

of some members of the Nitrosomonas oligotropha cluster

and with several mismatches with the Nitrosomonas com-

munis cluster. The remaining three approaches involved

nested PCR amplification with first round amplification

using bAMO143f-bAMO1315r or 1492r-27f (Lane, 1991)

primers, the latter comprising universal bacterial primers.

Secondary amplification was carried out using either

CTO189f-CTO654r or CTO189f in conjunction with the

FEMS Microbiol Ecol 56 (2006) 482–493 c� 2006 Federation of European Microbiological SocietiesPublished by Blackwell Publishing Ltd. All rights reserved

483Strategies for characterization of ammonia oxidizers

general bacterial primer Pf1053r (Edwards et al., 1989).

Amplification products generated by each of these ap-

proaches were characterized by DGGE analysis after a final

PCR amplification step with 357f-GC-518r primers (Muyzer

et al., 1993), which are not selective and are considered to be

universal bacterial primers. This final step generated a

161 bp 16S rRNA gene fragment and enabled comparison

of each approach following DGGE analysis. PCR amplifica-

tions were carried out in 50mL reaction volumes with a PCR

Express thermal cycler (Hybaid). The reaction mixture

contained 20 ng of template DNA, 0.2 mM of each primer,

1� PCR buffer (Bioline, London, UK), 250 mM each of

deoxynucleoside triphosphate, 1.5 mM MgCl2 (20 ng bovine

serum albumin was added to the primary PCR only) and 1 U

of BiotaqTM DNA polymerase (Bioline). The thermocycling

conditions for different primer sets are given in Table 2. PCR

amplification products were analysed by electrophoresis on

1% [weight in volume (w/v)] agarose gels and detected by

staining with ethidium bromide (Sambrook et al., 1989).

DGGE analysis

Denaturing gradient gel electrophoresis analysis of PCR

products was carried out using the D-Code Universal

Mutation Detection System (Bio-Rad, Hemel Hempstead,

UK). Briefly, 8% polyacrylamide gels containing gradients of

30–60 or 40–60% denaturant were prepared using a

gradient maker (Fisher Scientific, Loughborough, UK).

A denaturing solution strength of 100% was defined as 7 M

urea and 40% formamide (McCaig et al., 2001). Gels were

run for 16 h at 75 V in 1� Tris-acetate EDTA buffer at a

constant temperature of 60 1C. Following electrophoresis,

the gels were silver-stained and scanned. Silver-staining of

DGGE gels involved incubation of the gel in fixing

solution (10% ethanol10.5% acetic acid) for 10 min

followed by incubation in silver nitrate solution (0.2% silver

nitrate dissolved in the fixing solution) for 10 min, three

washings in double-distilled water (ddH2O) for 3 min,

incubation in developing solution (10% KOH10.05% for-

maldehyde) for 10–15 min. Gels were scanned after removal

of solution and washing with ddH2O for 2 min, fixation and

incubation for 10 min and further rinsing with ddH2O for

5–10 min. This protocol for rapid silver-staining of DGGE

gels enabled subsequent reamplification of excised DGGE

bands and significantly reduced the time required for

staining.

Recovery and purification of DNA template fromDGGE bands

Most of the major and some of the minor or less intense

bands that were either common or specific to different

AOB approaches were excised for sequencing. To ascertain

that the selected bands that migrate to similar positions

have identical sequences, several bands were excised from

different lanes but with identical positions and subjected to

sequencing after purification. Based on the judgment

that the bands with identical migratory positions yield

identical sequences, 15 distinct bands were excised from

Table 2. Primers and PCR conditions used in this study

Primer set Reference Target group

Thermocycling conditions�

Denaturation

time (min)

Annealing

temp. ( 1C)

Extension

time (s)

bAMO143f-bAMO1315r McCaig et al. (1994) Betaproteobacterial ammonia oxidizers 5 55 80

CTO189f-CTO654r Kowalchuk et al. (1997) Betaproteobacterial ammonia oxidizers 5 55 45w

CTO189f- Pf1053r Edwards et al. (1989) Betaproteobacterial ammonia oxidizers 5 55 45w

27f-1492r Lane (1991) Bacteria 5 50 90

357f-GC-518r Muyzer et al. (1993) Bacteria 2 55 30w

�The following thermocycling programme was used: 5 min at 94 1C, followed by 10 cycles of 30 s at 94 1C, 30 s at the specified annealing temperature,

and the specified extension time at 72 1C, followed by 25 cycles of 30 s at 92 1C, 30 s at the specified annealing temperature, and the specified extension

time at 72 1C (increasing by 1 s per cycle), followed by a 10 min final extension at 72 1C.wFinal extension time, 5 min.

Table 1. PCR primer-based strategies used for characterization of

ammonia oxidizer communities in environmental samples

Analysis

approach�

Primary PCR

amplification

(fragment size)

Secondary (nested)

PCR amplification

(fragment size)

(a) bAMO143f-bAMO1315r

(�1.1 kbp)

–

(b) CTO189f-CTO654r (465 bpp) –

(c) bAMO143f-bAMO1315r

(�1.1 kbp)

CTO189f-CTO654r

(465 bp)

(d) bAMO143f-bAMO1315r

(�1.1 kbp)

CTO189f- Pf1053r

(696 bp)

(e) 27f-1492r (�1.5 kbp) CTO189f-CTO654r

(465 bp)

�The resultant amplification products were characterized by denaturing

gradient gel electrophoresis analysis after a final amplification with 357f-

GC-518r primers that amplified a 161 bp fragment.


484 S. Mahmood et al.

soil- and 11 from marine sediment-DGGE gels, respectively,

to cover most of the major and minor bands and to assist

unbiased comparisons between different AOB approaches.

DGGE bands of interest were excised with a sterile razor

and DNA was eluted by incubation of the crushed band

in 25 mL sterile ddH2O at 65 1C for 30 min, followed

by centrifugation at 5000 g for 1 min. The eluted DNA

(1mL) was used as template for PCR amplification with

primers 357f-GC-518r, under the conditions described

above, and the resultant amplified products were analysed

on an agarose gel to estimate product concentration. The

purity of amplification products was assessed by DGGE

analysis and, in most cases, products yielded several bands,

in addition to the band of interest, necessitating further

(typically 2–3) rounds of band excision, PCR amplification

and DGGE analysis to confirm purity. The migration

patterns of PCR products reamplified from excised bands

were verified by DGGE analysis and comparison with the

initial environmental PCR products on the same gel. Pur-

ified PCR products were subjected to a final cleaning step as

described by Boyle & Lew (1995).

DNA sequencing and phylogenetic analysis

Purified PCR products were sequenced with the 518r primer

(Muyzer et al., 1993) using the BigDye Terminator cycle-

sequencing kit (PE Biosystems, Warrington, UK) and

sequences were analysed using an ABI377 automated se-

quencer (PE Biosystems, UK). The BLASTN search tool

(Altschul et al., 1990) was used to determine sequence

homology and the most similar sequences in the GenBank

database. All 16S rRNA gene fragments have been deposited

in the GenBank database under accession numbers

AY958433 to AY958458.

Analysis of DGGE banding profiles

DGGE banding profiles were compared on the basis of

presence or absence of bands at certain positions in

each lane using PHORETIX 1D gel analysis software (version

4.0, Phoretix International, Newcastle upon Tyne, UK)

(McCaig et al., 2001). Binary similarity matrices were

produced using the Dice coefficient which allowed construc-

tion of dendrograms using the unweighted pairwise

grouping method with mathematical averages (UPGMA)

(Griffiths et al., 2000b; McCaig et al., 2001; Nicol et al.,

2003). In addition, comparisons based on DGGE bands

confirmed, by sequencing analysis, to be AOB were made

using PHORETIX 1D gel analysis software, and Sorenson’s

index of similarity (Sorensen, 1948) was used for pairwise

calculations of bands shared between PCR amplification

strategies.

Results

Analysis of soil ammonia oxidizer communities

No differences could be detected between DGGE profiles

obtained from triplicate soil samples generated by the same

amplification method and gels are therefore presented with

duplicates only (Fig. 1a). This enables comparison of profiles

on a single gel, avoiding consideration of variation between

gels. DGGE profiles of soil communities differed between

PCR approaches (Fig. 1a; Table 3). In general, the number of

shared bands, indicating different sequence types, was higher

in approaches (b), (c) and (e) than in approaches (a) and (d)

(Table 3). Sequence analysis of the excised bands indicated

that the community was composed mostly of uncultured

Nitrosospira spp. (Table 4). However, profiles generated by

methods (a) and (d) were dominated by three bands (S1–S3)

whose sequences were most closely related to the nonammo-

nia oxidizer Variovorax (Fig. 1, Table 4).

Qualitative and quantitative analyses confirmed simila-

rities in banding patterns between replicates and indicated

similarities between DGGE profiles generated by approaches

(a) and (d) and by approaches (b), (c) and (e) (Fig. 1b, Table

3). Both (a) and (d) involved primary PCR amplification

with bAMO143f-bAMO1315r primers, but secondary,

nested amplification using CTO189f-Pf1053r primers (ap-

proach (d)) had no significant effect on the number or

identity of the major bands in DGGE profiles. There was,

however, an increase in relative intensity of bands S5–S8 and

S15, suggesting some difference between the two ap-

proaches. Approaches (b), (c) and (e) involved amplifica-

tion with the complete CTO primer set and sequences of all

detectable bands were most closely related to AOB (Table 4),

demonstrating the specificity of these primers.

Identical DGGE profiles were generated by approaches

(c) and (e), which involved primary amplification by

bAMO143f-bAMO1315r or bacterial 27f-1492r primers,

respectively, and secondary amplification with CTO189f-

CTO654r primers. Bands S1 and S2 (Variovorax-like) were

absent in approaches (b), (c) and (e), whereas band S3

(Variovorax-like) decreased in relative intensity in approach

(c) and could not be seen in approaches (b) or (e) (Fig. 1a).

This suggests the effectiveness of CTO189f-CTO654r pri-

mers, when employed either for primary (b) or secondary

(c and e) PCR amplification of betaproteobacterial AOB.

However, approaches involving primary amplification by

bAMO143f-bAMO1315r primers also generated Vario-

vorax-like sequences. Bands S5 (Variovorax-like), S6 and S7

(Nitrosospira-like) could only be seen in approaches (a) and

(d) (Fig. 1a). This suggests a further difference in bias

between bAMO143f-bAMO1315r and CTO189f-CTO654r

primers. Although the former amplified Variovorax-like

strains (bands S1–S3 and S5) (potentially nonammonia



oxidizers), they were able to amplify Nitrosospira-like strains

(bands S6 and S7) that otherwise could not be detected by

CTO189f-CTO654r primer-based strategies.

The relative intensity of band S8 (Nitrosospira-like strain)

was high in the CTO-based approaches (b)–(e) and extre-

mely low in approach (a), indicating that this particular

sequence type was present at relatively high abundance

within the AOB community, but at relatively low abundance

when compared with the Variovorax-like sequence types.

Bands S9, S10, S13 and S14 were only present in approaches

(b), (c) and (e) that employed CTO primers. Band S15

(Nitrosospira briensis-like sequence) was absent in approach

(a), probably as a result of low copy numbers compared to

Variovorax-like sequence types.

Analysis of marine ammonia oxidizercommunities

Reproducibility of DGGE profiles from triplicate marine

sediment samples was good, as for soil, and no differences

could be detected by visual comparison of migration

patterns. However, unlike soil samples, profiles were similar

for all amplification methods used (Fig. 2; Table 5). Closest

database matches for all sequences amplified from excised

bands were either cultivated ammonia oxidizers or environ-

mental clone sequences falling within the betaproteobacter-

ial ammonia oxidizer group, and there was no evidence of

sequences from nonammonia oxidizers (Table 6). Sequences

indicated that the AOB community consisted mainly of

Fig. 1. (a) Denaturing gradient gel electophoresis banding profiles of

betaproteobacterial ammonia oxidizing bacterial 16S rRNA genes ampli-

fied by direct PCR amplification (a, b) or nested PCR amplification (c–e)

from DNA extracted directly from soil, as described in Table 1. Banding

profiles of triplicate samples were indistinguishable and each method is

therefore represented by duplicate analyses (lanes 1, 2) for each method.

White arrowheads indicate the major bands that differed in presence/

absence or relative intensity between different PCR-amplification strate-

gies. A black arrowhead indicates bands that were PCR artefacts, from

which a sequence could not be generated. The bands marked S1–S15

were excised and sequenced (see Table 4 for identities). Although efforts

were made to sequence other bands, it was not possible to obtain good

quality sequences from some of the relatively weak bands. The band

located above band S8 is an artifact that often appears above exception-

ally strong bands in denaturing gradient gel electophoresis profiles,

possibly due to excessive loading of strong PCR amplification products.

An asterisk designates the bands that were confirmed to be of non-

ammonia oxidizing bacteria by 16S rRNA sequence analysis. Markers in

lane M consisted of seven ammonia oxidizing bacteria cluster controls

I–VII: I, EnvB1-8 (Nitrosospira); II, pH4.2A/27 (Nitrosospira); III, pH4.2A/4

(Nitrosospira); IV, pH7B/C3 (Nitrosospira); V, EnvA1-21 (Nitrosomonas);

VI, EnvC1-19 (Nitrosomonas); VII, N. europaea (Nitrosomonas). (b)

Unweighted pairwise grouping method with mathematical averages

dendrogram describing clustering of related denaturing gradient gel

electrophoresis banding profiles based on presence or absence of bands

in each lane. The dendrogram is derived from all bands (including those

that were sequenced and found to be of ammonia oxidizing bacteria or

nonammonia oxidizing bacteria and those that were not sequenced) in

each lane and ammonia oxidizing bacteria approach.

Table 3. Comparison of sequenced bands present in denaturing gradi-

ent gel electrophoresis profiles using different approaches to character-

ize ammonia oxidizing bacteria in soil samples

Ammonia oxidizing

bacteria approach (a) (b) (c) (d) (e)

(a) 5 (1.00)

(b) 2 (0.40) 8 (1.00)

(c) 2 (0.40) 8 (1.00) 8 (1.00)

(d) 2 (0.44) 4 (0.73) 4 (0.73) 7 (1.00)

(e) 2 (0.40) 8 (1.00) 8 (1.00) 4 (0.67) 8 (1.00)

Comparisons were based on bands confirmed to be derived from

ammonia oxidizing bacteria by 16S rRNA gene sequence analysis. Values

represent the number of sequenced bands found in each approach

(values on diagonal) or shared among different approaches. Similarity

coefficients (Cs) for ammonia oxidizer communities determined using

different approaches are given in parentheses.

(a)

(b)



Table 4. Closest matches between 16S rRNA gene sequences of bands� excised from soil-derived denaturing gradient gel electrophoresis (DGGE)

profiles and sequences from the GenBank databases obtained, using the BLASTN search tool

Band

no.

GenBank

accession no.

No. of bases similar/total no. of

bases (percentage similarity)wTotal entries with

similar score

Closest relative in GenBankz [name, (accession

number)]

S1 AY958433 160/160 (100%) 6 Variovorax sp. MB16 (AB013416)

Soil bacterium S78M1 (AY039395)

Earthworm cast bacterium C19M1 (AY039388)

S2 AY958434 160/160 (100%) 2 Uncultured Variovorax sp. clone Cl-16-TB3-I

(AY599730)

Proteobacterium 5S2.G8 (AY043560)

S3 AY958435 161/161 (100%) 6 Earthworm cast bacterium C21M1 (AY039389)

160/161 (99%) 10 Betaproteobacterium PII_GH1.2.B8 (AY162061)

Uncultured Betaproteobacterium clone

NMW3.196WL (AY043780)

Uncultured Variovorax sp. isolate 4f48 (AY177770)

S4 AY958436 143/144 (99%) 39 Uncultured Nitrosospira sp. single-stranded

conformational polymorphism (SSCP) band S3

(AY274172)

Nitrosospira sp. Nsp12 (AY123801)

Uncultured Nitrosospira SM-168 (AJ27588)

S5 AY958437 142/144 (98%) 2 Uncultured Betaproteobacterium clone C47.33PG

(AF431314)

141/144 (97%) 39 Uncultured bacterium clone 160ds20 (AY212612)

Uncultured bacterium clone PL-32B12 (AY570617)

Variovorax sp. c59 (AB167220)

S6 AY958438 150/150 (100%) 2 Uncultured Nitrosospira sp. DGGE band D12

(AY274196)

Uncultured Nitrosospira sp. SSCP band S6

(AY274175)


(AY274192)


(AY274170)


(AY274189)


(AY274173)

S9 AY958441 143/144 (99%) 47 Uncultured Nitrosospira sp. DGGE band D5 (AY274189)


(AY274173)

S10 AY958442 150/150 (100%) 20 Uncultured Nitrosospira sp. DGGE gel band

MG12-JLMBR (AY150281)

Uncultured Nitrosospira sp. clone LD1-A2

(AY114339)

S11 AY958443 147/147 (100%) 40 Uncultured Nitrosospira sp. SSCP band S3

(AY274172)


S12 AY958444 144/144 (100%) 34 Uncultured Nitrosospira sp. DGGE band D9 (AY274193)

Nitrosospira sp. III7 (AY123809)

S13 AY958445 144/144 (100%) 5 Unidentified bacterium clone Mul1P2-27 (AJ518169)

Uncultured Betaproteobacterium clone C17.45WL

(AF431242)

S14 AY958446 144/144 (100%) 28 Nitrosospira briensis (AY123800)

Nitrosospira sp. EnU4a (AY727034)

S15 AY958447 144/144 (100%) 28 Nitrosospira briensis (AY123800)

Nitrosospira sp. EnU4a (AY727034)

�The prominent bands in the DGGE profiles of soil (Fig. 1a) were excised and sequenced.wPercentage similarity between the sequence of a band excised from DGGE gel and the closest match in GenBank.zIdentities are based on closest NCBI sequences of phylogenetically related bacteria.



uncultured Nitrosospira, Nitrosomonas and some unidenti-

fied betaproteobacterial ammonia oxidizers (Table 6). The

majority of sequences had strong similarities to sequences

obtained by a cloning approach using the bAMO143f-

bAMO1315r primers in previous studies of sediment sam-

ples from the same site (Freitag & Prosser, 2003, 2004;

Freitag et al., 2003).

With the exception of bands M6 and M9 (Nitrosospira-

like strains), most of the major bands were common to the

different approaches followed (Fig. 2; Table 5). Qualitative

analysis (presence or absence of bands) and quantitative

analysis (visual comparison of relative band intensity)

indicated that similar profiles were generated by approaches

(a) and (d) and by approaches (c) and (e) (Fig. 2; Table 5).

However, UPGMA values were higher than those obtained

for soil DGGE profiles and indicated similarities between all

profiles (Figs 1b and 2b). Bands M6 and M9 appeared

exclusively and with relatively high intensities in approaches

involving the complete CTO primer set (c, e), with relatively

low intensities in the approach involving CTO189f-primer

(d) and could not be seen in approaches (a) or (b). In

contrast, some weak bands (M1, M4 and M5) in DGGE

profiles of strategies (a, b and d) decreased in relative

intensity in profiles of strategies (c) and (e).

CTO-DGGE analysis of soil and marine ammoniaoxidizers

Soil and marine ammonia oxidizers were also analysed using

approaches (c) and (e), but omitting the third-stage ampli-

fication of CTO products. Profiles contained four to five

prominent bands (Fig. 3), much fewer than those illustrated

in Figs 1a and 2a, which employed the complete (c) and (e)

protocols. In addition, several of the bands did not comi-

grate precisely with AOB cluster controls.

Discussion

Differences between approaches

The major differences in DGGE profiles were found between

approaches using bAMO143f-bAMO1315r and other pri-

mers for first round amplification. For both soil and marine

sediments, approaches based only on the bAMO primer set

(a)

(b)

Fig. 2. (a) Denaturing gradient gel electrophoresis banding profiles of


fied by direct PCR amplification (a, b) or nested PCR amplification (c–e)

from DNA extracted directly from marine sediment. The bands marked

M1–M11 were excised and sequenced (see Table 6 for identities). Other

information is as described in the legend for Fig. 1. (b) Unweighted

pairwise grouping method with mathematical averages dendrogram

describing clustering of related denaturing gradient gel electrophoresis

banding profiles based on presence or absence of bands in each lane.

The dendrogram is derived from all bands (including those that were

sequenced and found to be of ammonia oxidizing bacteria or nonam-

monia oxidizing bacteria and those that were not sequenced) in each

lane and ammonia oxidizing bacteria approach.

Table 5. Comparison of sequenced bands present in denaturing gradi-

ent gel electrophoresis profiles using different approaches for character-

ization of ammonia oxidizing bacteria in marine sediments

Ammonia oxidizing

bacteria approach (a) (b) (c) (d) (e)

(a) 8 (1.00)

(b) 8 (0.94) 9 (1.00)

(c) 7 (0.82) 8 (0.89) 10 (1.00)

(d) 8 (0.89) 8 (0.89) 9 (0.95) 10 (1.00)

(e) 7 (0.82) 8 (0.89) 10 (1.00) 9 (0.95) 10 (1.00)

Comparisons were based on bands confirmed to be derived from

ammonia oxidizing bacteria by 16S rRNA gene sequence analysis. Values

represent the number of sequenced bands found in each approach

(values on diagonal) or shared among different approaches. Similarity

coefficients (Cs) for ammonia oxidizer communities determined using

different approaches are given in parentheses.



(a) generated fewest confirmed AOB sequences (Tables 3

and 5). Approaches (b), (c) and (e) were equally efficient (in

generating similar numbers of bands) for amplification of

AOB sequences from soil, followed by approach (d) (Table

3). For marine sediments, approaches (c)–(e) amplified

equal numbers of ammonia oxidizer sequences, followed by

approach (b) (Table 5). Despite these differences, banding

patterns derived from marine samples showed relatively

minor variation with the approach adopted.

Profiles derived from soil using the bAMO primer set

differed significantly from those using either bacterial or

CTO primers alone. The most likely explanation for this is

the preferential amplification of Variovorax-like sequences,

which were present on DGGE gels at high relative intensities.

Table 6. Closest matches between 16S rRNA gene sequences of bands� excised from denaturing gradient gel electophoresis (DGGE) profiles of marine

sediments and sequences from the GenBank databases obtained using the BLASTN search tool

Band

no.

GenBank

accession no.

No. of bases similar/total

no. of bases (percentage

similarity)w

Total entries

with similar

score Closest relative in GenBankz [name (accession number)]

M1 AY958448 144/144 (100%) 1 Uncultured ammonia-oxidizing bacterium clone LD1-B6

(AY114347)

143/144 (99%) 1 Uncultured ammonia-oxidizing bacterium clone LD1-B37

(AY114346)

M2 AY958449 144/144 (100%) 1 Uncultured ammonia-oxidizing bacterium clone LD1-B6

(AY114347)

143/144 (99%) 1 Uncultured ammonia-oxidizing bacterium clone LD1-B37

(AY114346)

M3 AY958450 143/144 (99%) 4 Uncultured Nitrosomonas sp. isolate DGGE gel band NS3-F-Tancarville

(AY583682)

Uncultured Nitrosococcus sp. isolate DGGE gel band NJ2-F-Honfleur

(AY583668)

M4 AY958451 144/144 (100%) 37 Uncultured Nitrosospira sp. SSCP band S3

(AY274172)


M5 AY958452 144/144 (100%) 44 Uncultured Nitrosospira sp. DGGE band D5

(AY274189)


(AY274173)

M6 AY958453 142/142 (100%) 2 Uncultured Nitrosospira sp. isolate DGGE band LD1-env-a8

(AY157002)

Uncultured Nitrosospira sp. isolate DGGE band LD1-env-a1

(AY156995)

M7 AY958454 159/159 (100%) 1 Uncultured Nitrosospira sp. clone LD1-B28 (AY114345)

158/159 (99%) 6 Uncultured Nitrosospira sp. clone LD1-A1 (AY114337)


(AY156998)

157/158 (99%) 2 Uncultured Nitrosospira sp. isolate DGGE band LD1-env-a6

(AY157001)


(AY156995)

152/153 (99%) 9 Uncultured Nitrosospira sp. isolate DGGE band LD1-en-a5

(AY157000)

M10 AY958457 157/157 (100%) 1 Uncultured Nitrosospira sp. isolate DGGE band LD1-en-a5

(AY157000)

152/153 (99%) 1 Uncultured Nitrosospira sp. isolate DGGE band LD1-env-a1

(AY156995)


(AY156998)

141/142 (99%) 10 Uncultured ammonia-oxidizing bacterium clone: GC9-06

(AB103548)

�The prominent bands in the DGGE profiles of marine sediments were excised and sequenced.wPercentage similarity between the sequence of a band excised from DGGE gel and the closest match in GenBank.zIdentities are based on closest NCBI sequences of phylogenetically related bacteria.



This could result from the relatively high abundance of

these strains in soil, in comparison with AOB, and the close

similarities in 16S rRNA gene sequences, with only one

mismatch against both forward and reverse bAMO primers

(Table 7). High copy numbers of such sequences, after

amplification with the bAMO143f-bAMO1315r primers,

may result in carryover, even following secondary PCR

using AOB-specific CTO189f-CTO654r primers. This is

exemplified in banding profiles generated by approach

(c), where bands S1 and S2 (Variovorax-like) had re-

latively low band intensity in approach (a), and were not

detectable using approach (c), whereas band S3 (Variovorax-

like) had relatively high band intensity using approach (a)

and could be seen faintly in profiles generated using

approach (c).

Stephen et al. (1996) analysed diversity of soil and marine

sequences using bAMO143f-bAMO1315r primer-based

clone libraries and reported that a significant fraction of soil

clones was related to a non-AOB, betaproteobacterium clade

containing Comamonas testosteroni and Rubrivivax gelatino-

sus, whereas only two such sequences were recovered among

the 40 marine sediment clones. Similarly, (Bruns et al., 1999)

reported a high percentage of nonspecific amplification

products in clone libraries generated using bAMO PCR

products from native, tilled and successional soils. Other

investigations (Kowalchuk et al., 2000a, b) involved use of

CTO primers for screening of bAMO clone libraries of soil-

extracted DNA and found only 20–55% AOB-like se-

quences. A disadvantage of CTO primers is that they amplify

non-AOB sequences when AOB are present at low relative

abundance. For example, Cebron et al. (2004) reported non-

AOB sequences amplified from wastewater effluent using

CTO primers.

In the present study, nested PCR-based approaches (c)

and (e) gave higher resolution (more bands) than direct

PCR-based approaches for detection and community char-

acterization of AOB in soil and marine sediment environ-

ments. Nested PCR-based approaches are common practice

on low-copy-number targets in environmental samples that

may also contain PCR inhibitors, and generate good-quality

amplification products for community profile fingerprint-

ing and sequencing. High PCR cycle numbers may intro-

duce Taq-polymerase reading errors and consequent

erroneous sequences (Tindall & Kunkel, 1988; Barnes,

1992), but the reproducible DGGE banding patterns

obtained, even after three consecutive rounds of PCR

amplification, and the high similarity of all excised bands

to sequences derived from pure cultures or environmental

clones strongly support the validity of the analysed se-

quences.

Fig. 3. Denaturing gradient gel electophoresis banding profiles of


fied by nested PCR using the CTO primer set (approaches (c) and (e),

Table 1, omitting the third amplification step) from DNA extracted

directly from soil or marine sediment. The banding pattern is based on

465-bp CTO PCR-amplification products. Ammonia oxidizing bacteria

cluster controls (lanes 1–7) correspond to cluster controls I–VII as

described in the legend for Fig. 1, except that the cluster control 3 is

replaced by controls for cluster 3a, pH4.2A/4 (Nitrosospira) and 3b, N.

briensis C-128 (Nitrosospira).

Table 7. Mismatches in target sequences of genera Nitrosospira and Nitrosomonas and of Variovorax-associated soil bacteria for the ammonia

oxidizing bacteria primer set CTO189f-CTO654r

CTO189f 50-GGA GRA AAG YAG GGG ATC G-30

Nitrosomonas � � � � D � � � � � R � � � � � � � �Variovorax-like � � � T� � � � � � � � � � � � � � �CTO654r 50-CTA GCY TTG TAG TTT CAA ACG C-30

Nitrosospira � � � � � � � � � � � � � R � � � � � � � �Nitrosomonas� � � � � Y � H � R Y � � � � � � � � � � � �Variovorax-likew � � � � � G A � � C � � � C � � � � � T � �

Mismatches in ammonia oxidizsing (AOB) bacteria sequences were counted only when identical substitutions were present at the same site in at least

two sequences. The co-occurring mismatches within sequences are highlighted in bold typeface. The nonvariable positions are indicated by dots.�Co-occurring mismatches within the Nitrosomonas communis/N. nitrosa lineage.wMinimum number of co-occurring mismatches for Variovorax-like sequences AY570617 and AY212612.

Mishits in AOB sequences were counted only when identical substitutions were present at the same site in at least two sequences.



Differences between soil and marine sedimentprofiles

The major difference between profiles obtained from soil

and marine samples was the influence on the former of the

PCR strategy employed. The most likely explanation is the

low relative abundance, in the marine sediment samples, of

non-AOB with 16S rRNA gene sequences with high similar-

ity to bAMO primer sequences. Low recovery of AOB-

associated sequences from soil environments using the

bAMO primer set has been observed in other studies (Bruns

et al., 1999; Kowalchuk et al., 2000a, b), and Freitag &

Prosser (2004) reported that 61 and 100% of bAMO clones

generated from marine water and sediment samples, respec-

tively, incorporated the CTO primer motif. This suggests

that the use of the bAMO primer set may be generally more

appropriate in marine molecular surveys but the presence of

non-AOB sequence types should always be checked.

Benefits and limitations of different approaches

Amplification of non-AOB sequences by bAMO143f-bA-

MO1315r primers is a particular disadvantage when rela-

tively long sequences are required for the phylogenetic

discrimination of closely related Nitrosospira strains, which

frequently dominate soil AOB communities. In such cases,

labour-intensive and time-consuming screening of bAMO

clones with the CTO primer set is required and may generate

only incomplete clone libraries. CTO primers are selective

for known betaproteobacterial AOB, with the exception of

some members of the N. oligotropha cluster and with several

mismatches with the N. communis cluster (Purkhold et al.,

2000). However, when AOB are present at low abundance,

they can generate non-AOB sequences, frequently related to

Gammaproteobacteria (Backman et al., 2003), possibly in-

dicating insufficient stringency of PCR conditions. This was

not the case in this study, where AOB were at relatively high

abundance.

Approach (a) (direct PCR using bAMO143f-bA-

MO1315r) showed higher diversity (based on total number

of bands) than other approaches employed for soil but also

generated most non-AOB sequences. This approach also

amplified Nitrosospira-like strains that could not be ampli-

fied by the CTO189f-CTO654r primers. This may be due to

mismatches in the CTO primer set to these Nitrosospira-like

strains. However, the CTO primer set is generally considered

to be biased towards the Nitrosospira lineage (Purkhold

et al., 2000) and may limit AOB diversity studies in

environments where N. nitrosa and N. communis are pre-

valent (Koops & Pommerening-Roser, 2001). Because uni-

versal bacterial 27f-1492r primers are expected to amplify

most templates, and are considered to be unbiased against

AOB, they may be used for a primary PCR amplification of

environmental templates followed by AOB-specific CTO

primers (approach (e)).

Although amplification products of CTO primers are

suitable for cloning, sequencing and some basic phylo-

genetic analysis, fewer bands were obtained when CTO

products were analysed prior to third-stage amplification

(Fig. 3). Because the bands did not always comigrate with

AOB cluster controls, it is difficult to establish whether each

of the multiple bands represents a distinct sequence or

whether degeneracy of CTO primers generated multiple

bands in the profiles of AOB cluster controls. However, a

further round of PCR amplification using bacterial 357f-

GC-518r primers reveals a more complex community con-

sisting of at least 17–20 different bands, representing diverse

bacterial sequences (Figs 1a and 2a). Cloning of CTO

products of these samples might also have resulted in a

more complex profile than that depicted in CTO-DGGE

profiles (Fig. 3). The lower number of bands observed in

CTO-DGGE gels may result from the larger size of the CTO

amplification product (465 bp), reducing resolution. PCR

products of 357f-GC-518r primers can either be cloned or

bands of interest from DGGE gels can be excised (as in this

study) for sequencing, but their short length (161 bp)

restricts phylogenetic analysis. In this respect, a combined

approach of DGGE analysis following a nested PCR ap-

proach with CTO189f-CTO654r and 357f-GC-518r primers,

in conjunction with cloning and 357f-GC-518r DGGE

screening of CTO products, enables the analysis of AOB

communities within most environments. This analysis is,

however, restricted to amplification of the 16S rRNA gene,

which may itself bias community analysis, and additional

information may be provided by analysis of additional

targets, such as functional genes.

Conclusion

Of the five strategies evaluated, nested PCR amplification

with first-round amplification using 27f-1492r bacterial

primers and a second PCR using ammonia-oxidizer-specific

CTO189f-CTO654r primers was found to provide the best

approach for characterization of ammonia oxidizing com-

munities in soil and marine sediments. However, there are

concerns regarding possible bias in selectivity and specificity

of CTO189f-CTO654r primers, especially when applied to

environments containing low abundance of AOB. This study

therefore demonstrates the importance of correct choice of

primer strategies, the requirement for screening for se-

quences of nontarget organisms and the requirement for

multiple approaches, particularly during investigation of

previously unstudied environments. Although focussing on

AOB, these considerations are likely to apply equally to

molecular-based characterization of other microbial groups.



Acknowledgements

This work was carried out as part of a Marie Curie

Individual Fellowship (contract No. QLK3-CT-2000-

52161) awarded by the European Commission.

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