Download Broad-Range PCR for Detection and Identification

Molecular Microbiology: Diagnostic Principles and Practice, 2nd Ed.
Edited by David H. Persing et al.
䉷2011 ASM Press, Washington, DC
Maiwald M. Broad-range PCR for detection and identification of bacteria.
pp. 491-505. In: Persing DH, Tenover FC, Tang YW, Nolte FS, Hayden RT,
van Belkum A (eds.). Molecular microbiology: diagnostic principles and
practice. 2nd edition. American Society for Microbiology, Washington DC,
2011. ISBN 978-1-55581-497-7.
31
Broad-Range PCR for Detection
and Identification of Bacteria
MATTHIAS MAIWALD
BACKGROUND
ecules, though, provide suitable priming sites as well as
phylogenetically informative sequences (see chapter 9). For
example, sequences of genes coding for conserved proteins
(e.g., heat shock proteins and RNA polymerases) can be
very useful for identification within bacterial families (99)
but generally do not provide sufficiently conserved sites for
primers across the domain Bacteria. rRNAs, on the other
hand, fulfill many of the necessary requirements (104).
rRNA molecules have been described as the ultimate molecular chronometers (163); they reflect evolutionary
changes, while functional constraints in protein translation
prevent these changes from being too extensive.
In the 1980s, oligonucleotides from conserved regions
were first used for reverse transcriptase sequencing of bacterial 16S rRNA (77). Subsequently, such conserved oligonucleotides were utilized as primers in PCR (23, 38).
The two main molecules that are suitable for bacterial
broad-range PCR are the 16S rRNA gene, consisting of
approximately 1,540 bp (in Escherichia coli, 1,542 bp), and
the 23S rRNA gene, consisting of approximately 2,900 bp
(in E. coli, 2,904 bp). The 5S rRNA gene, the third structural rRNA gene with about 120 bp, is too small for this
purpose. While the 23S rRNA gene possesses greater information content and more potential priming sites due to
its larger size, the 16S rRNA gene was adopted earlier, has
become a quasistandard, and has many more reference sequences available for comparison. For example, the SILVA
online resource (111) contained 324,342 different smallsubunit (16S rRNA-like) sequences of 1,200 bp or greater
(900 bp or greater for Archaea) and 12,506 different largesubunit (23S rRNA-like) sequences of 1,900 bp or greater
in its release of 14 October 2008 (http: / / www.arb-silva.de).
The numbers of small partial 16S and 23S rRNA sequences
of ⬎300 bp are much greater.
Broad-range PCR is based on the recognition that there
are a number of broadly conserved molecules across a range
of many different organisms. rRNA genes, for example, are
present in all cellular forms of life, namely the domains
Bacteria, Archaea, and Eukarya (163). rRNA genes possess
highly conserved regions that are suitable as sites for PCR
primers that recognize large, diverse groups of organisms
(e.g., all members of the Bacteria) and possess variable
regions that provide distinct signatures for identification at
phylogenetic levels below the level initially targeted by the
primers. Commonly, broad-range PCR are aimed at members of the domain Bacteria, although broad-range PCRs
have also been developed for other large relevant groups
of organisms or combinations of such groups. For example,
broad-range PCRs may target Eukarya (91, 119), Archaea
(1, 4, 143), Eukarya and Archaea (10), fungi (70, 130, 159),
or fungi and protists (44). Fungal broad-range PCRs are
often termed panfungal PCRs in the medical literature. Below the level of broad groups of organisms, PCRs may be
constructed to target organisms at various other phylogenetic levels; for example, within the Bacteria it is possible
to design phylum-, family-, or genus-specific PCRs, depending on the availability of phylogenetically informative
signature sequences.
The strength of broad-range PCR for diagnostic microbiology lies in the relative absence of selectivity, assuming
little or no prior knowledge of an infecting organism, so
that—in principle—any bacterium (in the case of bacterial
assays) can be detected and identified. This is an area of
analogy to the detection by culture and is in contrast to
typical organism-specific PCR assays.
The aim of most broad-range PCRs is to amplify as
broadly as possible within the domain Bacteria and, at the
same time, to obtain sufficient portions of variable sequence for identification. Not all broadly conserved mol-
PATHOGEN DISCOVERY
Broad-range ribosomal PCR and sequence analysis have
played key roles in the characterization of novel bacterial
pathogens, particularly in settings where detection by culture has failed. The first agent discovered by this technique
Matthias Maiwald, Department of Pathology and Laboratory Medicine, KK Women’s and Children’s Hospital, Singapore 229899, Singapore.
491
492 ■
MAIWALD
was the agent of bacillary angiomatosis in AIDS patients
(118), which was microscopically visible in clinical samples
but had not been cultivated. The 16S rRNA sequence revealed a relationship to Rochalimaea (subsequently named
Bartonella) quintana, the agent of trench fever. The novel
bacterium was subsequently cultivated, named Bartonella
henselae, and found also to be an agent of cat scratch disease (13, 17, 157). Other examples of pathogen discoveries
by broad-range PCR and sequencing are Ehrlichia chaffeensis, an agent of human tick-borne monocytic ehrlichiosis
(5), Tropheryma whipplei, the agent of Whipple’s disease
(120, 160), and Mycobacterium genavense, a cause of disseminated infections in AIDS patients (15). Thus, broad-range
PCR joined several other molecular methods that were capable of gathering insight into distinguishing features of
pathogens by obtaining molecular signatures before other
characteristic traits were known (46). It was also recognized
that the mere identification of a microbial molecular signature in a person with a disease does not establish a causal
relationship between microbe and disease, and a set of nucleic acid-based criteria for causality was proposed, by analogy with the historic Koch’s postulates (46). Broad-range
PCR and sequencing is not only suitable for the characterization of uncultivated bacteria; 16S rRNA sequence
deposition has become a mainstay of established procedures
whenever a new bacterial species is described. One review
article (165) counted 215 newly described bacterial species
(obtained mostly by culture) from human specimens between the years 2000 and 2007, of which 29 were assigned
to novel genera and 100 were found in four or more patients.
PRIMER SYSTEMS FOR BROAD-RANGE PCR
rRNA molecules consist of conserved as well as variable
regions; a depiction of these regions and the corresponding
priming sites in the bacterial 16S rRNA gene is given in
Fig. 1A. A selection of broad-range primers for the 16S
and 23S rRNA genes is provided in Table 1. Further primer
and probe sequences for 16S and 23S rRNA gene can be
found in other articles (1, 4, 6, 9, 61, 63, 76, 88, 123, 133,
150, 155), as well as in the European rRNA database (http:
/ / bioinformatics.psb.ugent.be / webtools / rRNA) (166) and
in the ProbeBase database (http: / / www.microbial-ecology.
net / probebase) (84). When looking at rRNA secondary
structure, conserved regions tend to lie in loops, while
variable regions tend to lie in stems, where nucleotides are
paired with those of the opposite strand (76). Primers for
diagnostic broad-range PCR need to amplify sufficiently
long stretches of variable sequence to be able to identify
bacteria at or close to species level; generally, targets of
⬃300 to 900 bp are used in most diagnostic broad-range
PCRs (e.g., primers 533 forward [f] plus 806 reverse [r], 27f
plus 556r, 27f plus 806r, or 533f plus 1371r). Targets towards the shorter end of this range may be preferable when
the extracted DNA is likely to be damaged (e.g., formalinfixed, paraffin-embedded tissue); longer targets (e.g., primers 27f / 1492r) may be used when bacteria in samples are
abundant. Generally, longer targets provide more variable
sequence for more accurate identification. Primers that anneal to eukaryotic nuclear or mitochondrial DNA (‘‘universal’’ primers; e.g., 533f plus 1492r) should not be used
as pairs in the same assay when working with human samples (117).
The distinction between conserved and variable regions
in rRNA molecules is not as sharp as the depiction in Fig.
1A suggests and is instead better reflected in Fig. 1B. With
an increasing number of rRNA sequences in databases, it
has been recognized that some nucleotide positions that
are less conserved are interspersed in highly conserved sequence stretches, and some taxa that are part of an intended target group of organisms have mismatches to commonly used broad-range primers (9, 42). This is in part
accounted for by the ambiguous nucleotides in the primers
FIGURE 1 (A) Schematic drawing of the bacterial 16S rRNA gene, with conserved (open bars)
and variable (shaded bars) regions. The location of broad-range primers (Table 1) is shown. Modified from reference 117, with permission from the American Society for Microbiology. (B) Conservation profile of 16S rRNA across the domain Bacteria, constructed with the software package
ARB (85) and the SILVA (111) data set. The graph shows the relative frequency (y axis) of the
most common nucleotide for each position (x axis) in 16S rRNA. Courtesy of Frank Oliver
Glöckner and Elmar Pruesse (Max Planck Institute for Marine Microbiology, Bremen, Germany).
31. Broad-Range PCR for Bacterial Identification ■
493
TABLE 1 Commonly used primers and probes for broad-range PCR with bacterial 16S and 23S rRNA genes
Name a
Sequence b
Location c
Specificity d
Reference(s) b
16S rRNA
27f
355f
338r
533f
515r
556r
806f
787r
926f
907r
930f
911r
1194f
1175r
1371r
1391r
1492r
1525r
5⬘-AGAGTTTGATYMTGGCTCAG
5⬘-ACTCCTACGGGAGGCAGC
5⬘-GCTGCCTCCCGTAGGAGT
5⬘-GTGCCAGCMGCCGCGGTAA
5⬘-TTACCGCGGCKGCTGGCAC
5⬘-CTTTACGCCCARTRAWTCCG
5⬘-ATTAGATACCCTGGTAGTCC
5⬘-GGACTACCAGGGTATCTAAT
5⬘-AAACTYAAAKGAATTGACGG
5⬘-CCGTCAATTCMTTTRAGTTT
5⬘-TCAAAKGAATTGACGGGGGC
5⬘-CCGTCAATTCMTTTRAGTTT
5⬘-GAGGAAGGTGGGGATGACGT
5⬘-ACGTCATCCCCACCTTCCTC
5⬘-AGGCCCGGGAACGTATTCAC
5⬘-TGACGGGCGGTGWGTRCA
5⬘-GGTTACCTTGTTACGACTT
5⬘-AAGGAGGTGWTCCARCC
8–27
338–355
33–355
51–533
515–533
556–575
787–806
787–806
907–926
907–926
911–930
911–930
1175–1194
1175–1194
1390–1371
1391–1408
1510–1492
1525–1541
Most Bacteria
Most Bacteria
Most Bacteria
Universal
Universal
Most Bacteria
Most Bacteria
Most Bacteria
Most Bacteria
Most Bacteria
Most Bacteria
Most Bacteria
Most Bacteria
Most Bacteria
Most Bacteria
Universal
Universal
Most Bacteria and Archaea
38
3
3
77, 120
77, 120
13
162
162
77
77
120
120
23
23
23
77
37, 156
38
23S rRNA
1077f
1950r
5⬘-AGGATGTTGGCTTAGAAGCAGCCA
5⬘-CCCGACAAGGAATTTCGCTACCTTA
1054–1077
1950–1926
Most Bacteria
Most Bacteria
73
73
a
Names of 16S rRNA primers are based on the 3⬘ nucleotide position and the orientation (f, forward; r, reverse), according to the numbering system by Lane
(76).
b
Sequences may have been modified from the indicated references by subsequent authors. References are given for the original publications of the priming sites.
Location in E. coli 16S rRNA or 23 S rRNA.
d
Universal includes Bacteria, Archaea, and Eukarya.
c
in Table 1, but in some instances it may necessitate the
redesign of commonly used broad-range primers or hybridization probes to achieve more complete coverage of bacterial phyla (30, 42). While the impact of this appears to
be somewhat smaller for diagnostic broad-range PCR in
cases of suspected monomicrobial infections, it can be dramatic for polymicrobial infections, microbial flora studies,
or environmental studies, where certain bacterial taxa may
become significantly over- or underrepresented after PCR
amplification (11, 39, 59, 63, 137, 142, 155).
In a general sense, the performance of PCR assays may
be affected by (i) length of the PCR product, (ii) annealing
temperature, (iii) number of cycles, (iv) template concentration, (v) internal composition (e.g., G⫹C richness) of
the target, and (vi) primer base composition (G⫹C richness and internal base pairing). Longer distances between
primer pairs generally result in less analytical sensitivity,
but this may be partially offset by the finding that DNA
contaminations in PCR reagents (see below) appear to be
fragmented into smaller sizes (132), so that the ratio between target and contaminations becomes more favorable.
A large study of broad-range PCR has in fact shown quite
robust amplification of an ⬃850-bp target from the 23S
rRNA gene with diverse clinical samples (115). In addition
to the possible mismatches of rRNA gene primers (see
above), broad-range PCR has also been found to be affected by rRNA gene copy numbers in different bacterial
genomes and even by interference from bacterial DNA outside the PCR target region (53, 154). In some instances,
different primer sets show different amplification efficiency
despite perfect primer-to-target matches (39).
As a consequence of performance and coverage differences between broad-range PCR primers, they may have
to be redesigned and reevaluated, depending on the needs
of particular diagnostic or scientific applications. There are
a number of tools to establish and check the matches of
primers and probes against large 16S rRNA and 23S rRNA
data sets. The Ribosomal Database Project (RDP) website
(http: / / rdp.cme.msu.edu) (27) has a probe match tool for
that purpose. A computer program called PRIMROSE can
also be used to construct primers and probes in conjunction with the RDP data set (8). Other web interface
tools are the probeBase (http: / / www.microbial-ecology.
net / probebase) (84) and probeCheck (http: / / www.
microbial-ecology.net / probecheck) (83) resources. In addition, the ARB phylogeny program package (http: / /
www.arb-home.de) (85) has probe design and probe match
functions that can be used, for example, in conjunction
with the SILVA 16S and 23S rRNA data sets (111).
CONTAMINATION ISSUES OF
BROAD-RANGE PCR
Broad-range PCR is subject to much of the same contamination problems and requires much of the same prevention
measures as specific PCRs (see chapter 8). In addition, the
inherent nonselective nature of broad-range PCR makes it
494 ■
MAIWALD
susceptible to minute amounts of any bacterial DNA that
might be encountered along the various steps of testing.
While specific PCR does not amplify DNA from nontarget
organisms, broad-range PCR, by its design, can amplify
DNA from almost any bacterium. Soon after broad-range
PCR was originally implemented, it was found that negative controls often yielded amplified DNA of the appropriate size. Such false-positive results would not be avoided
by common anticontamination measures. Several types of
reagents have been implicated as being sources of DNA
contamination: Taq polymerase was commonly implicated
(14, 113, 132), but also other reagents, such as water and
oligonucleotide solutions (49) and buffers or enzymes for
sample preparation (144). The application of restriction
analysis (113) suggested that Thermus aquaticus and E. coli
(the host species for native and recombinant Taq polymerase) are unlikely sources of contamination in Taq polymerase. By contrast, the columns and buffers used for the
industrial purification of Taq polymerase were thought to
be likely sources. Sequencing methods identified contaminating DNA as originating from within the pseudomonad
group of organisms (86, 118), which are known waterborne
contaminants. The amount of contaminating DNA was estimated to be in the range of 100 copies of 16S rRNA gene
per Taq portion needed for a single reaction (113). Taq
polymerases from different manufacturers were found to
be affected (14, 62, 132), and there appears to be
manufacturer-to-manufacturer and even batch-to-batch
variation in the amount of contaminating DNA (113, 128,
132). As a consequence, the detectable limit (i.e., analytical sensitivity) of PCR assays using such Taq preparations
lies well above 100 copies per PCR, if one wants to distinguish ‘‘real’’ from contaminating DNA. Shorter PCR targets tend to be more susceptible to the presence of background DNA, since this DNA appears to be fragmented
into small sizes (132). There also seems to be a physiochemical affinity between Taq polymerase and contaminating DNA, since they appear to be strongly associated
with each other (113).
Several protocols have been developed to avoid or reduce contaminating DNA in PCR reagents. There are a
few commercial Taq polymerase preparations, such as
AmpliTaq LD or AmpliTaq Gold LD (Applied Biosystems),
where LD stands for low DNA, and these enzymes have
been purified to contain 10 or fewer bacterial rRNA gene
copies in a standard 2.5-U aliquot. Published protocols also
include the treatment of PCR mixes, including Taq polymerase, with DNase I (56, 124, 136, 139, 147, 148), restriction enzymes (20), or UV light (47, 105). DNase I and
restriction enzymes need to be heat inactivated before the
addition of samples and commencement of cycling (20,
124). Some authors pointed out that UV treatment should
take place prior to adding deoxynucleoside triphosphates
(dNTPs), because dNTPs absorb UV light and prevent exposure of other PCR mix contents (47). Several others
(62, 92, 128) described a combined protocol of 8methoxypsoralen and UV treatment of PCR mixes. 8Methoxypsoralen acts as UV-induced cross-linker of DNA
in contaminated reagents. However, it was pointed out that
the 8-methoxypsoralen concentration and time of UV exposure need to be carefully adjusted, because intense exposure damages Taq polymerase and leads to reduced PCR
sensitivity. Other published approaches include the ultrafiltration of PCR reagents (136) and treatment with ethidium monoazide or propidium monoazide (55, 129). Ultrafiltration with a 100-kDa exclusion size (e.g., Microcon
YM-100; Millipore) lets Taq polymerase (94 kDa) pass
through the filter, while typical contaminating DNA is retained; however, some Taq polymerase loss may be observed. Ethidium monoazide and propidium monoazide are
photoreactive DNA-intercalating substances that are activated by visible light. Some protocols involve splitting
PCR mix components for different treatments. For example, Steinman et al. (139) subjected the PCR mix without
primers to DNase I treatment and treated the primers separately with UV light before combining the mix. Table 2
contains an overview of the different anticontamination
methods for broad-range PCR.
Several authors have examined different anticontamination procedures in parallel (28, 71, 136). It became clear
that most anticontamination measures provide a trade-off
between reducing contaminating DNA and retaining PCR
TABLE 2 Methods to reduce bacterial background DNA in PCR reagents
Measure(s)
Comment(s)
Low-DNA Taq polymerase (e.g.,
AmpliTaq LD, AmpliTaq Gold LD)
DNase I treatment of PCR mix
Commercially available, contains 10 or fewer bacterial
rRNA gene copies per 2.5 U
Effective in DNA elimination; inactivation critical; minor
loss of PCR sensitivity; some authors treat PCR mix
without primers
Mixed results concerning DNA elimination and retained
sensitivity; some authors treat PCR mix without
dNTPs and primers
Taq polymerase may be sensitive to UV action; dNTPs
can impede UV action; probable loss of sensitivity
8-Methoxypsoralen concn and UV exposure have to be
fine-tuned; longer exposure reduces PCR sensitivity
Concn of ethidium monoazide in PCR mix is critical;
good elimination of contaminating DNA and retained
sensitivity
Type of filter and centrifugation time and speed are
critical; good elimination of contaminating DNA and
retained sensitivity
Restriction enzyme treatment of PCR
mix
UV irradiation of PCR mix
8-Methoxypsoralen and UV light
treatment of PCR mix
Treatment of PCR mix with ethidium
monoazide or propidium monoazide
and light exposure
Ultrafiltration of PCR mix with
exclusion size of 100 kDa
Reference(s)
147
28, 56, 57, 71, 124, 136,
139, 147, 148
20, 28, 71
28, 47, 71, 105
28, 62, 71, 92, 128
55, 129
136
31. Broad-Range PCR for Bacterial Identification ■
sensitivity. Corless et al. (28) examined UV irradiation, 8methoxypsoralen plus UV, DNase I digestion, restriction
enzyme digestion, and DNase I plus restriction enzyme
treatment, using broad-range PCR in a quantitative realtime format; this format facilitates the monitoring of DNA
contamination (see below). A significant reduction in analytical sensitivity accompanied the reduction of contaminating DNA in most of the treatment protocols, except
DNase I treatment, for which the reduction in sensitivity
was relatively small, with only a 1- to 2-log reduction. The
combination of DNase I and restriction enzyme digestion
suffered from problems with test-to-test reproducibility.
The authors concluded that DNA contamination in broadrange PCR assays will continue to be a problem. Klaschik
et al. (71) compared DNase I treatment, restriction enzyme
digestion, UV irradiation, and 8-methoxypsoralen plus UV
and found that all methods inhibited PCR. Only DNase I
was able to eliminate contaminating DNA while retaining
a useful distinction between negative controls and low levels of template DNA. Silkie et al. (136) compared DNase
I digestion and ultrafiltration with Microcon YM-100 (Millipore) filters. It was found that both methods eliminated
contaminating DNA and retained sensitivity, but for
DNase I digestion, the concentration of DNase and the
presence of Ca2⫹ ions in the digestion mix was critical, as
was thorough inactivation of DNase in the presence of
dithiothreitol.
Complementing the specific protocols to avoid or eliminate DNA in PCR reagents, Millar et al. (95) proposed a
set of broad, general guidelines for laboratory practice in
order to avoid contamination in the setting of broad-range
PCR assays. These included guidelines for the sampling of
clinical specimens, separation of rooms for pre- and postPCR work, and the use of high-quality reagents.
SAMPLE PREPARATION FOR
BROAD-RANGE PCR
In contrast to microbial culture, where a sample in a volume of up to about 10 ml can be collected and used for
inoculation (e.g., into a blood culture bottle) and one single viable bacterium may lead to a positive result, the typical sample volume added to a PCR tube is only about 5
␮l. Sample preparation for PCR is therefore extremely important; its aims are to crack microbial wall structures, remove PCR inhibitors, and purify and concentrate the template DNA, but also to avoid DNA overload (see chapter
7). There are two important issues concerning broad-range
PCR: (i) sample preparation should be kept simple in order
to reduce the risk of introducing external contamination,
and (ii) some reagents used for sample preparation may
contain intrinsic DNA. Proteinase K is one example of a
potentially contaminated reagent; it is commonly used in
sample preparation and requires purification during manufacturing, in analogy to Taq polymerase.
There are a number of in-house and commercial sample
preparation products and protocols; these include, among
others, classical proteinase K digestion and phenolchloroform extraction, crude lysis with proteinase K and
boiling with Chelex resin, simple alkaline lysis of blood
samples, DNA spin column kits (e.g., Qiagen kits), and
fully automated sample preparation workstations, such as
the MagNA Pure LC Instrument and Kit (Roche) (35, 93,
94, 114, 135, 140). There are relatively few published sideby-side evaluations of different techniques; however, they
may differ considerably in DNA recovery and the resultant
495
analytical sensitivity (114). It is also clear that any of these
protocols can introduce DNA contamination. For example,
some lots of Qiagen kits have been found to contain Legionella DNA (151). Reagents for the MagNA Pure LC
workstation have also been found to contain bacterial
DNA (98, 109), and subsequently, the company (Roche)
released ‘‘M-grade’’ MagNA Pure reagents that were free of
detectable bacterial DNA.
Interesting observations were published by Tanner et al.
(144); the authors conducted broad-range PCRs exposed
to common sample preparation reagents and prepared a
PCR product clone library from amplified DNA, presumed
to be from reagents for sample preparation or PCR. They
found that the obtained sequences matched published sequences from a range of ‘‘uncultured environmental bacteria’’ well. These sequences had been amplified from very
diverse environmental samples, all with low total biomass
in common, and had been deposited by various authors in
databases. This suggests that some published sequences
from ‘‘environmental bacteria’’ were in fact due to PCR
contamination.
There are also unusual examples of contamination involving sample acquisition and preparation, affecting not
just bacterial broad-range PCR. Zymolyase, an enzyme digesting fungal cell walls and commonly used for panfungal
PCRs, was found to contain fungal DNA; it is manufactured by a brewery company that also handles yeast (122).
Another group found an unusually high number of positive
Bordetella pertussis PCRs from one particular pediatric examination room; this room had previously been used for
administration of cellular pertussis vaccine, and environmental swabs from the room also yielded positive PCRs
(146). Another study aimed at broad-range PCR diagnosis
of bacterial endophthalmitis from vitreous fluid samples; all
14 tested samples revealed Pseudomonas spp. sequences.
The povidone-iodine antiseptic solution used for preoperative eye antisepsis was subsequently found to be contaminated (149).
DETECTION OF PCR PRODUCTS AND
SEQUENCE ANALYSIS
The classical way to detect and identify bacteria by broadrange PCR is via visualization of PCR products by standard
gel electrophoresis, followed by sequencing, preferably for
both DNA strands of the products (26). This is the most
accurate method. Direct sequencing of PCR products is
feasible when it can be assumed that a sample contains a
single species of microorganism. However, when direct sequencing reveals ambiguous reads or when multiple organisms are present, it is generally necessary to clone PCR
products (e.g., by using commercial plasmid vectors for
PCR product cloning) and to sequence an adequate number of clones (45, 116). The latter technique can also be
applied to the construction of 16S rRNA gene clone libraries, in which a single PCR product from a polymicrobial sample may result in a few hundred plasmid clones
with different sequences, representing different organisms
(74, 107, 108).
There are a number of tools for analysis of 16S or 23S
rRNA gene sequences from broad-range PCR. The simplest
method is to perform BLAST similarity searches in public sequence databases, such as in GenBank at the National Center for Biotechnology Information (http: / /
www.ncbi.nlm.nih.gov). These searches provide a percentage of similarity to the closest sequences in the database.
496 ■
MAIWALD
However, this may not suffice for accurate species identification; searches may reveal no identical sequences, or
they may reveal identical sequences from different species,
and there is no defined similarity cutoff above which a new
sequence can be assigned to the same genus or species (26,
66, 165). In addition, public databases contain many sequence errors, incorrect species and strain assignments, and
rRNA gene sequence chimeras. A chimera is an artificial
sequence that may be generated from a mixed microbial
sample when PCR, after partial amplification of a DNA
strand of one species, continues to amplify the homologous
strand of another species, so that a phylogenetically heterogenous sequence is generated (154). Thus, it is advisable
to check sequences obtained with broad-range PCR from
polymicrobial samples; available tools are the programs Bellerophon (60) or Pintail (7).
More accurate rRNA gene sequence assessment is possible with curated rRNA databases, web-based or commercial identification tools, and phylogenetic analysis. BIBI
(http://pbil.univ-lyon1.fr / bibi) is a web-based identification
tool aimed at clinically relevant bacteria (33). MicroSeq
(Applied Biosystems) is a commercial kit, with PCR reagents included, that aims at 16S rRNA-based identification
of cultivated bacterial isolates in clinical microbiology. It
comes with its proprietary database of quality-checked sequences from reference strains and is available in two versions, covering either about 500 bp or almost the full
length of the 16S rRNA gene (164). The Ribosomal Database Project website (http: / / rdp.cme.msu.edu) contains a
curated 16S rRNA database with over 715,000 partial and
full-length sequences in its 2008 release (27). It can be
searched via a web interface that generates provisional taxonomic assignments, and a set of aligned sequences can
be downloaded and imported into a phylogeny program.
Greengenes (http: / / greengenes.lbl.gov) is a taxonomically
and chimera-checked 16S rRNA database with over
290,000 sequences of ⬎1,250 bp in length (in its 2008
release) that can be interrogated via a web interface, and
it has a fully aligned data set for download (31). SILVA
(http: / / www.arb-silva.de) is a large database of qualitychecked, aligned 16S and 23S rRNA sequences with ‘‘Ref’’
and ‘‘Parc’’ data sets for each gene, where Ref stands for
near-full-length sequences and Parc for all sequences over
300 bp (111). While the majority of entries in these data
sets are comprised of environmental or microbial flora sequences from uncultivated organisms, SILVA contains
nearly 20,000 16S rRNA and nearly 2,000 23S rRNA sequences from cultivated isolates (2008 release). Both the
data sets from Greengenes and SILVA can be downloaded
and imported into ARB (http: / / www.arb-home.de), which
is a large phylogeny program package with a graphical user
interface (85).
Quantitative real-time PCR provides an alternative detection method that is rapidly replacing gel-based detection
of broad-range PCR amplicons (28, 35, 36, 68, 100, 102,
127, 168). It offers several advantages. In gel-based assays,
cycle numbers and other conditions need to be carefully
adjusted, so that negative controls show no bands while
sufficiently small amounts of positive control DNA become
visible. In real-time PCR, the product is detected during
cycling, so that negative controls (e.g., water controls, sample preparation controls, and known negative samples),
positive controls with known copy numbers of 16S rRNA
gene, and actual samples can be continuously monitored,
and the quantification cycle (Cq [see chapter 4]) can be
used as a criterion to compare the amount of DNA in
controls to that in samples. As a consequence, real-time
PCR offers much improved distinction between ‘‘true’’ and
background DNA. Detection of amplicons can be achieved
with fluorescent broad-range probes that simultaneously
hybridize to the target sequence during each cycle (102),
or with nonspecific nucleic acid dyes, such as SYBR Green
(168). Products from real-time broad-range PCR can be
sequenced and analyzed using standard procedures. Realtime PCR products can be subjected to melting (i.e., thermal DNA dissociation) analysis, and a variant technique,
high-resolution melting analysis, may be used for a provisional species assignment among a limited range of medically relevant bacteria (24). As with gel-based assays, background DNA in PCR mixes or sample preparation reagents
causes most negative controls to reach the threshold of
amplified DNA at high numbers of cycles (Fig. 2).
Pyrosequencing is an emerging alternative to standard
Sanger type sequencing. It is much more rapid and cheaper
per base than standard sequencing, detects the incorporation of nucleotides by light emission, and can be highly
automated. Earlier generations of pyrosequencing instruments were limited to short sequence reads (e.g., 30 bp)
and could be used in conjunction with broad-range PCR
to interrogate short, informative sequence stretches that
allowed preliminary identification of bacteria, such as gram
negative or gram positive (72), Streptococcus sp., Staphylococcus sp., enteric gram-negative rod, etc. (67). More recent instruments allow for massively parallel pyrosequencing with increased read lengths (up to 400 bp) and can be
used for accurate characterization of broad-range PCR
products from highly complex polymicrobial communities
(64, 82).
Broad-range PCR can also be combined with amplicon
detection by DNA microarrays. Several formats have been
developed, ranging from low-density arrays that contain a
set of probes for a limited number of medically relevant
pathogens (96) to high-density arrays that cover large numbers of diverse taxa across a wide phylogenetic range (18).
Such high-density arrays are commonly termed ‘‘phylochips’’ or ‘‘phyloarrays.’’ For example, a high-density microarray has been developed on the Affymetrix platform
that contains 500,000 oligonucleotide probes covering
about 9,000 distinct prokaryotic taxa (18). This array has
been used, in a research setting, to characterize bacterial
populations in urban atmospheric aerosols (19) and in
uranium-contaminated soils (18). Another type of highdensity array has been used to characterize the development and diversification of intestinal flora of infants during
the first year of life (107). High-density microarrays after
broad-range PCR can be used for the quantitative analysis
of PCR products across a wide range of taxa.
CLINICAL APPLICATIONS
Clinical microbiology has a constant need for alternative
diagnostic methods that complement or expand on the existing ones. Most diagnostic methods have limitations: microscopy requires a significant number of organisms present
in samples to become positive, and identification based on
morphology is often not possible, serologic testing often
only provides retrospective information, and culture may
fail when fastidious or ‘‘culture-resistant’’ microorganisms
cause infections. For many common pathogens, the rate of
isolation is significantly reduced after the initiation of antibiotic therapy. Some pathogens may not be difficult to
cultivate but may require special media, growth conditions,
31. Broad-Range PCR for Bacterial Identification ■
497
FIGURE 2 Logarithmic amplification plot of a broad-range bacterial 16S rRNA gene PCR in
real-time format. This amplification pattern has arisen in a study in which blood from healthy
subjects was compared with negative controls (102). Samples were analyzed in triplicate and for
40 cycles. The Cq value is derived from the number of cycles needed for the amplified DNA to
reach the quantification cycle (threshold). ⌬Rn, relative fluorescence. Reprinted from reference
102, with permission from the American Society for Microbiology.
or lengthy incubation times; thus, they normally need to
be considered in order to become detected (45). Broadrange PCR offers two potential benefits: it lacks selectivity
for particular groups of bacteria, and it can detect as well
as identify culture-resistant, fastidious, damaged, and slowgrowing microorganisms.
Since the inception of broad-range PCR in the late
1980s, many clinical microbiology laboratories have implemented this technique for research and clinical applications. In diagnostic settings, broad-range testing usually
takes place in selected cases, with selected specimen types,
on specific request by physicians, and by using in-house
assays (115). When implemented, broad-range PCR testing
is usually done with samples from primary ‘‘sterile’’ sites,
such as blood, cerebrospinal fluid, synovial fluid, and tissue.
Clinical applications of broad-range PCR have been published in multiple case reports, small case series, and a
number of large prospective and retrospective evaluation
studies.
Published case reports include instances where the diagnosis was missed because all standard tests using conventional diagnostic methods (culture, serology, and microscopy) were unrevealing. Examples are the detection of B.
quintana in culture-negative endocarditis (65), T. whipplei
in spondylodiscitis (2) and endocarditis (51), Mycoplasma
pneumoniae in osteomyelitis (78), and Granulicatella elegans
in endocarditis (22).
A number of clinical scenarios and specimen types have
attracted particular interest and more thorough evaluation
studies for broad-range PCR. These include excised heart
valves in suspected bacterial endocarditis (16, 50, 89, 153),
bloodstream infections in neonates or hematologyoncology patients (69, 80, 103, 110, 138), cerebrospinal
fluid in suspected meningitis or shunt infections (32, 73,
134, 158, 167), bone samples or synovial fluid samples in
osteomyelitis or septic arthritis (40, 41, 127), vitreous or
aqueous fluid in intraocular infections (152), tissue or pus
from brain or spinal abscesses (75, 115), amniotic fluid in
chorioamnionitis or preterm labor (34, 58), and various
other scenarios.
In one of the earlier studies, Goldenberger et al. (50)
applied broad-range PCR to resected heart valves in a series of 18 endocarditis cases. Cultures of the valves were
positive in only 4 cases, blood cultures were positive in 15
cases, and PCR was positive in 15 cases. Tentative bacterial
identification based on 16S rRNA sequences was possible
in 13 cases. Two PCR-positive cases were missed by cultures: DNA sequences of a Streptococcus sp. and of T. whipplei were detected in these valves. Similar findings were
made in other studies of heart valve PCR: at the time of
operation, most patients were treated with antibiotics and
valve cultures were often negative, and among the cases
detected by PCR but not by culture were pretreated cases
and infections by fastidious bacteria (16, 89, 153).
Ley et al. (80) published findings of broad-range PCR
directly from EDTA-anticoagulated blood samples from
111 episodes of fever and neutropenia in cancer patients
and compared the results with those of conventional blood
cultures. Broad-range PCR was positive in 9 of 11 culturepositive episodes but also in 20 culture-negative episodes,
18 of which occurred under antibiotic treatment. It was
concluded that broad-range PCR can augment culture in
patients under antibiotic treatment. Another study (69)
examined 1,233 blood samples from neonates being evaluated for early-onset sepsis. Whole blood samples taken for
cell count analysis were preincubated for 5 h in broth and
examined by PCR, and the results were compared to conventional blood cultures. Seven samples were concordantly
positive. PCR failed to detect 10 of 17 culture-positive
samples, some of which yielded skin organisms, and was
positive in 30 culture-negative cases. The authors pointed
out that due to ethical reasons for study design, samples for
498 ■
MAIWALD
PCR were often taken by heel pricks, which may have
introduced skin organisms that were then multiplied by
preincubation. Bloodstream infections have also been addressed by the design of a commercial kit, the SeptiFast
test (Roche). This kit is based on real-time PCR with different sets of primers and probes for a limited range of 25
gram-positive, gram-negative, and fungal organisms commonly involved in bloodstream infections and requires
about 6 h to obtain results (21).
Kotilainen et al. (73) examined 56 cerebrospinal fluid
samples from patients with suspected meningitis and found
that PCR detected Neisseria meningitidis sequences in 5
samples, 4 of which were also culture positive. One PCRpositive sample from a patient under antibiotic treatment
was negative by microscopy and culture, but autopsy findings were consistent with meningococcal disease. One additional case of culture-positive Listeria monocytogenes meningitis was missed by broad-range PCR. Similar findings
were made in larger studies evaluating broad-range PCR
for the diagnosis of meningitis: PCR failed in some cases
that were positive by culture but was often successful when
patients were pretreated with antibiotics (134, 158).
A large study of 525 bone and joint samples, comprising
tissues and fluid aspirates, was published by Fenollar et al.
(41). Concordantly negative results between culture and
PCR were obtained in 386 cases, concordantly positive results in 89 cases, and discrepant results in 50 cases. Culture
and PCR each had similar rates of false-positive and falsenegative results. Among 21 culture-negative, PCR-positive
cases were 7 cases with antibiotic treatment and 2 cases
with fastidious organisms. Seven cases revealed mixed sequences by PCR; some of the sequences in these cases belonged to established bone and joint pathogens, others to
environmental organisms rarely involved in bone and joint
infections.
A large study from Finland (115) applied broad-range
PCR to 536 diverse clinical samples from 459 hospitalized
patients and compared PCR with culture. Samples consisted of body fluids and tissues and were collected over a
4-year period in a routine diagnostic setting. Results of culture and PCR were concordant in 447 (83%) specimens.
PCR-positive but culture-negative results occurred in 19
samples, which included specimens taken during antibiotic
treatment or infections caused by bacteria with unusual
growth requirements. For 11 patients in the study, broadrange PCR was the only method that provided evidence of
the etiologic agent of the infection, and for 10 of these
patients, the agent identified by sequencing was considered
significant in the clinical context. The tendency of broadrange PCR to be positive after the initiation of antibiotic
therapy, as opposed to culture, was statistically significant.
A large, population-based study of unexplained deaths
and critical illnesses due to possible infectious causes was
initiated by the Centers for Disease Control and Prevention (CDC) and conducted in four states of the United
States (52, 101). Included were cases in which all conventional diagnostic methods had yielded negative results, although the patients demonstrated clinical signs and symptoms suggestive of infection. A total of 137 cases were
identified, and broad-range PCR was performed in 46 cases.
The PCR results were positive for eight cases, and bacterial
sequences (e.g., N. meningitidis and Streptococcus pneumoniae) recovered from six patients were consistent with the
clinical symptoms. Seven of the eight patients had been
pretreated with antibiotics.
Bacterial broad-range PCR has also attracted interest in
transfusion medicine, in order to assess blood products for
bacterial contamination (35, 36, 97, 126). Platelet concentrates are of particular concern, because they require storage and agitation at room temperature, thus making them
prone to bacterial growth from very small inocula. Culture
in blood culture bottles requires several days, and slowgrowing bacteria such as Propionibacterium spp. may require
4 to 5 days, so that cultures may become positive at a time
when platelets have been transfused. Several broad-range
real-time PCR assays have been designed and evaluated for
that purpose (35, 36, 97, 126). One study evaluated 2,146
platelet concentrate samples in parallel with culture and
PCR (97). The test had a turnaround time of 4 h and
showed concordant results between the two methods, thus
showing the feasibility of PCR testing for platelet concentrates.
ANALYSIS OF POLYMICROBIAL INFECTIONS
AND MICROBIAL COMMUNITIES
Broad-range PCR can also be applied to mixed infections
or to determine the composition of complex polymicrobial
communities, such as in samples from the environment or
samples containing microbial flora of humans and animals.
This type of analysis has originally been established in environmental microbiology (48). Such studies as well as in
situ hybridization experiments (4) have provided estimates
that ⬎99% of microorganisms in environmental communities are not detectable by standard culture techniques.
PCR-based community studies usually involve the construction and phylogenetic analysis of 16S rRNA gene
clone libraries and commonly reveal many sequences corresponding to new species (‘‘phylotypes’’ or ‘‘operational
taxonomic units’’) that are not detected by culture.
Analysis of human microbial flora has been performed
on specimens such as feces (141, 161) and subgingival
plaque material (74, 108). These studies revealed a considerable fraction (40 to 75%) of sequences that did not belong to known bacterial species. The diversity of sequences
was greater for PCR-amplified clone libraries than for bacterial colonies from cultures that were set up in parallel
(74, 161), but larger numbers of cycles (35 cycles versus 9)
in the initial PCRs reduced diversity, probably due to preferential amplification (161). Based on clone library data,
it was estimated that the number of different bacterial species in subgingival plaque communities exceeds 400 (108).
Another study, combining broad-range PCR with both
clone libraries and microarray analysis, examined the stool
flora development of 14 infants during the first year of life
(107). Each of the babies had and retained a distinct community profile, and by the end of the first year, the profiles
had diversified into patterns that were similar to those of
the adult gastrointestinal tract.
Other studies have focused on the association between
human microbial flora disturbances and conditions of impaired health. One study examined samples from women
with bacterial vaginosis and women with normal vaginal
flora by broad-range PCR followed by clone libraries, as
well as by in situ hybridization (43). Bacterial vaginosis
samples contained much greater microbial diversity, including 16 presumptive new species, among which three
species were very strongly associated with bacterial vaginosis and were only distantly related to any other known
bacteria. Another set of interesting findings was reported
by Ley et al. (81). The authors examined the stool flora of
31. Broad-Range PCR for Bacterial Identification ■
obese and lean people, as well as obese people during the
course of diet. For the two dominant phyla in stool, the
Firmicutes and the Bacteroidetes, they found that the number of Bacteroidetes was smaller in obese people than in lean
people and that obese people under diet underwent a shift
towards fewer Firmicutes and more Bacteroidetes, approaching the ratios of lean people. It was pointed out that these
changes constitute a major shift of bacterial phyla that is
associated with health disturbance.
Broad-range PCR has also been applied to polymicrobial
infections, such as destructive periodontitis (25), prostatitis
(145), dental root canal infections (125), and destructive
keratitis (131). These studies also revealed the unexpected
diversity of bacteria associated with polymicrobial infections, as well as sequences corresponding to unknown species.
499
enormous implications on the analysis of samples from supposedly sterile sites by broad-range PCR.
Among the clinical evaluation studies of broad-range
PCR, there were some that reported largely consistent results between PCR and culture, with moderate numbers of
samples positive by PCR but negative by culture, and vice
versa (50, 73, 89, 115, 134). Others reported a greater proportion of samples that were positive by PCR and negative
by culture (54, 80, 138, 167). As pointed out by Peters et
al. (110), the interpretation of such studies is difficult, with
culture being the reference. A positive PCR may be the
result of greater sensitivity of PCR, or it may be a falsepositive result. It may be the result of true pathogen DNA
or of presumed normal background DNA in human blood
or tissue, or it may be due to bacterial DNA in reagents.
Interpretation in the context of clinical findings and other
laboratory results is necessary. This is feasible in thorough
scientific evaluation studies, but it may not be feasible in
a routine diagnostic setting.
UNANSWERED QUESTIONS
Interesting questions were raised in a study by Nikkari et
al. (102). By use of a real-time broad-range PCR assay,
blood samples from healthy volunteers were compared with
negative controls (i.e., water treated as for sample preparation), human tissue culture cells, and known amounts of
extracted bacterial DNA (Fig. 2). Negative controls consistently gave rise to amplification products, reaching the
quantification cycle around cycle 38. The quantification
cycles of healthy blood samples were four to six cycles earlier, indicating a higher load of bacterial DNA. Clone libraries were prepared from both a negative control and a
blood sample and revealed sequences that belonged to phylogenetic groups similar to those of sequences previously
reported from negative controls (144), but blood samples
yielded additional sequences from phylogenetic groups that
were not represented in negative controls. The origin and
significance of the blood-derived sequences remained unclear, but the possibility was raised that supposedly sterile
body compartments may harbor a ‘‘normal’’ burden of bacterial DNA. This appears consistent with previous findings
of culture-positive bacteremia after toothbrushing (12) and
with pneumococcal DNA found in the blood of healthy
children (29).
Apparently similar findings were made by another group
after the incidental observation of pleomorphic bacteria by
dark-field microscopy in the blood of one healthy subject
(90). The findings were confirmed by in situ hybridization
and broad-range PCR in several more healthy subjects; 16S
rRNA gene and gyrB gene sequences were similar but not
identical to those of Stenotrophomonas maltophilia, but cultures on standard media remained negative. The significance of these findings remained unclear. Interesting observations were also made in two other studies, examining
coronary arteries after death from various causes (79) and
atherosclerotic lesions from abdominal aortas (121) by
broad-range PCR. In the second study (121), the authors
took particular care to avoid background DNA from reagents by cloning and subtracting sequences obtained after
extensive cycling of negative controls, but despite this, sequences from typical oral commensals and low-level pathogens were detected in both studies. The significance
remained unclear, but the authors speculated that commensals may become embedded in vascular tissues during
transient bacteremias. Again, these studies point towards
the possibility that human blood and tissue may have a
normal background of bacterial DNA, and this may have
CONCLUSIONS
Conducting broad-range PCR analysis at a level of high
analytical and clinical sensitivity is a complex task and
remains one of the most difficult and challenging PCR applications. Implementation of broad-range PCR in a diagnostic setting requires appropriate laboratory facilities and
staff, familiarity with the theoretical underpinnings and
practical aspects, extensive precautions to avoid contamination, and thorough in-house evaluations of analytical as
well as clinical sensitivity and specificity. The presence of
ubiquitous bacterial background DNA and the problems
associated with its elimination suggest that dealing with a
certain, low level of interfering DNA will be unavoidable,
at least in the foreseeable future. Some of the decontamination methods in Table 2 describe the reduction of contaminating DNA to levels of about 10 copies of rRNA gene
per PCR test, which means that the amount of real target
DNA that can be distinguished will have to be significantly
above that level, and broad-range PCRs will not achieve
the same level of sensitivity as organism-specific PCRs.
Careful implementation of positive and negative controls is necessary. The presence of bacterial DNA in PCR
mixes, in sample preparation reagents, and presumably in
some normal human tissues mandates that negative controls should include DNA-free controls in the PCR mix,
sample preparation controls, and control samples from patients without the disease in question, in order to detect
and be aware of the levels of background DNA in all of
these settings. Positive controls must contain serial dilutions of known copy numbers of bacterial DNA or bacterial
cells, both in the PCR mix and spiked into negative samples, to determine the threshold of detectable bacterial
DNA that is clearly above the background level.
Sequence-based identification of positive diagnostic
broad-range PCR products is generally advisable, even
when real-time technology is used. Some authors have proposed using a second, independent, broad-range primer system in order to confirm results (73, 112, 115). Additional
controls may include PCRs using a human gene (e.g., the
beta-globin gene) in order to assess the presence of amplifiable DNA in a sample or inhibition of PCR. Some
PCR tests use internal, coamplified DNA controls (126).
In addition to the specific measures to eliminate background DNA (Table 2), a wide range of general anticontamination precautions is necessary, including separate
500 ■
MAIWALD
rooms for pre- and post-PCR work, UV decontamination
of surface areas, use of high-quality reagents, and adequate
sampling techniques and vials for clinical specimens (95).
It is important to understand that the traditional concepts
of sterile laboratory techniques from culture-based microbiology do not apply in the same way in the setting of
molecular tests, as shown by experiments in which extensive autoclaving failed to eliminate amplifiable DNA (87).
Clinical studies have shown a number of situations in
which bacterial broad-range PCR can provide considerable
benefits. Clear benefits exist when bacteria are seen by microscopy but fail to be recovered in culture, when infections may be caused by fastidious or slow-growing organisms, and when patients have been pretreated with
antibiotics. The examination of resected heart valves exemplifies these benefits very well: endocarditis can be
caused by various organisms, including fastidious ones,
valve resection is a highly invasive sampling procedure that
warrants considerable diagnostic efforts, the examination
by blood cultures may fail to detect the pathogen, and patients have often been pretreated with antibiotics, so that
heart valves at the time of operation are often culturenegative (50). However, diagnostic broad-range PCR, with
full amplicon sequencing, is expensive and time-consuming
and requires appropriate laboratory facilities (115).
The primary diagnostic utility of broad-range PCR lies
in the testing of specimens from primary sterile sites, especially if they are difficult to obtain, and in clinical situations in which other methods are known to pose difficulties. The analysis of polymicrobial infections and complex
communities becomes feasible with the aid of clone libraries and the emerging techniques of pyrosequencing and
high-density microarrays, but it still requires considerably
more effort and resources and is currently done almost exclusively in research laboratory settings.
Other emerging technologies may take the current place
of broad-range PCR as a nonprescient tool for the examination of unknown infections. This has been exemplified
by the discovery of a novel transplant-associated arenavirus
that caused fatal infection in three organ recipients (106).
The virus was discovered by random amplification of RNA
transcripts from infected organs, followed by unbiased highthroughput pyrosequencing. The resulting sequences were
then subjected to bioinformatic subtraction of human sequences, and the novel arenavirus sequence was found.
This was subsequently confirmed by virus culture, specific
PCRs, and antibody testing.
I thank David A. Relman, Paul Eckburg, and Elisabeth M. Bik
(Stanford University, Palo Alto, CA) for providing helpful comments
on this chapter in the earlier edition; Linda L. Blackall and Tim Beckenham (University of Queensland, Brisbane St Lucia, QLD, Australia) for help with selecting primers for Table 1; and Frank Oliver Glöckner and Elmar Pruesse (Max Planck Institute for Marine Microbiology,
Bremen, Germany) for providing Fig. 1B.
REFERENCES
1. Achenbach, L., and C. R. Woese. 1995. 16S and 23S
rRNA-like primers, p. 521–523. In K. R. Sowers and H. J.
Schreier (ed.), Archaea—A Laboratory Manual: Methanogens. Cold Spring Harbor Laboratory Press, Cold Spring
Harbor, NY.
2. Altwegg, M., A. Fleisch-Marx, D. Goldenberger, S. Hailemariam, A. Schaffner, and R. Kissling. 1996. Spondylodiscitis caused by Tropheryma whippelii. Schweiz. Med.
Wochenschr. 126:1495–1499.
3. Amann, R. I., L. Krumholz, and D. A. Stahl. 1990.
Fluorescent-oligonucleotide probing of whole cells for determinative, phylogenetic, and environmental studies in
microbiology. J. Bacteriol. 172:762–770.
4. Amann, R. I., W. Ludwig, and K. H. Schleifer. 1995.
Phylogenetic identification and in situ detection of individual microbial cells without cultivation. Microbiol. Rev.
59:143–169.
5. Anderson, B. E., J. E. Dawson, D. C. Jones, and K. H.
Wilson. 1991. Ehrlichia chaffeensis, a new species associated with human ehrlichiosis. J. Clin. Microbiol. 29:2838–
2842.
6. Anthony, R. M., T. J. Brown, and G. L. French. 2000.
Rapid diagnosis of bacteremia by universal amplification
of 23S ribosomal DNA followed by hybridization to an
oligonucleotide array. J. Clin. Microbiol. 38:781–788.
7. Ashelford, K. E., N. A. Chuzhanova, J. C. Fry, A. J.
Jones, and A. J. Weightman. 2005. At least 1 in 20 16S
rRNA sequence records currently held in public repositories is estimated to contain substantial anomalies. Appl.
Environ. Microbiol. 71:7724–7736.
8. Ashelford, K. E., A. J. Weightman, and J. C. Fry. 2002.
PRIMROSE: a computer program for generating and estimating the phylogenetic range of 16S rRNA oligonucleotide probes and primers in conjunction with the RDPII database. Nucleic Acids Res. 30:3481–3489.
9. Baker, G. C., J. J. Smith, and D. A. Cowan. 2003. Review and re-analysis of domain-specific 16S primers. J. Microbiol. Methods 55:541–555.
10. Barns, S. M., R. E. Fundyga, M. W. Jeffries, and N. R.
Pace. 1994. Remarkable archaeal diversity detected in a
Yellowstone National Park hot spring environment. Proc.
Natl. Acad. Sci. USA 91:1609–1613.
11. Ben-Dov, E., O. H. Shapiro, N. Siboni, and A. Kushmaro. 2006. Advantage of using inosine at the 3’ termini
of 16S rRNA gene universal primers for the study of microbial diversity. Appl. Environ. Microbiol. 72:6902–6906.
12. Berger, S. A., S. Weitzman, S. C. Edberg, and J. I.
Casey. 1974. Bacteremia after the use of an oral irrigation
device. A controlled study in subjects with normalappearing gingiva: comparison with use of toothbrush.
Ann. Intern. Med. 80:510–511.
13. Bergmans, A. M., J. W. Groothedde, J. F. Schellekens,
J. D. van Embden, J. M. Ossewaarde, and L. M. Schouls.
1995. Etiology of cat scratch disease: comparison of polymerase chain reaction detection of Bartonella (formerly
Rochalimaea) and Afipia felis DNA with serology and skin
tests. J. Infect. Dis. 171:916–923.
14. Böttger, E. C. 1990. Frequent contamination of Taq polymerase with DNA. Clin. Chem. 36:1258–1259.
15. Böttger, E. C., A. Teske, P. Kirschner, S. Bost, H. R.
Chang, V. Beer, and B. Hirschel. 1992. Disseminated
‘‘Mycobacterium genavense’’ infection in patients with
AIDS. Lancet 340:76–80.
16. Breitkopf, C., D. Hammel, H. H. Scheld, G. Peters, and
K. Becker. 2005. Impact of a molecular approach to improve the microbiological diagnosis of infective heart
valve endocarditis. Circulation 111:1415–1421.
17. Brenner, D. J., S. P. O’Connor, H. H. Winkler, and
A. G. Steigerwalt. 1993. Proposals to unify the genera
Bartonella and Rochalimaea, with descriptions of Bartonella
quintana comb. nov., Bartonella vinsonii comb. nov., Bartonella henselae comb. nov., and Bartonella elizabethae
comb. nov., and to remove the family Bartonellaceae from
the order Rickettsiales. Int. J. Syst. Bacteriol. 43:777–786.
18. Brodie, E. L., T. Z. Desantis, D. C. Joyner, S. M. Baek,
J. T. Larsen, G. L. Andersen, T. C. Hazen, P. M. Richardson, D. J. Herman, T. K. Tokunaga, J. M. Wan, and
M. K. Firestone. 2006. Application of a high-density oli-
31. Broad-Range PCR for Bacterial Identification ■
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
gonucleotide microarray approach to study bacterial population dynamics during uranium reduction and reoxidation. Appl. Environ. Microbiol. 72:6288–6298.
Brodie, E. L., T. Z. DeSantis, J. P. Parker, I. X. Zubietta,
Y. M. Piceno, and G. L. Andersen. 2007. Urban aerosols
harbor diverse and dynamic bacterial populations. Proc.
Natl. Acad. Sci. USA 104:299–304.
Carroll, N. M., P. Adamson, and N. Okhravi. 1999.
Elimination of bacterial DNA from Taq DNA polymerases
by restriction endonuclease digestion. J. Clin. Microbiol.
37:3402–3404.
Casalta, J. P., F. Gouriet, V. Roux, F. Thuny, G. Habib,
and D. Raoult. 2009. Evaluation of the LightCycler(R)
SeptiFast test in the rapid etiologic diagnostic of infectious
endocarditis. Eur. J. Clin. Microbiol. Infect. Dis. 28:569–
573.
Casalta, J. P., G. Habib, B. La Scola, M. Drancourt, T.
Caus, and D. Raoult. 2002. Molecular diagnosis of Granulicatella elegans on the cardiac valve of a patient with
culture-negative endocarditis. J. Clin. Microbiol. 40:1845–
1847.
Chen, K., H. Neimark, P. Rumore, and C. R. Steinman.
1989. Broad range DNA probes for detecting and amplifying eubacterial nucleic acids. FEMS Microbiol. Lett. 48:
19–24.
Cheng, J. C., C. L. Huang, C. C. Lin, C. C. Chen, Y. C.
Chang, S. S. Chang, and C. P. Tseng. 2006. Rapid detection and identification of clinically important bacteria
by high-resolution melting analysis after broad-range ribosomal RNA real-time PCR. Clin. Chem. 52:1997–
2004.
Choi, B. K., B. J. Paster, F. E. Dewhirst, and U. B.
Göbel. 1994. Diversity of cultivable and uncultivable oral
spirochetes from a patient with severe destructive periodontitis. Infect. Immun. 62:1889–1895.
Clarridge, J. E., III. 2004. Impact of 16S rRNA gene
sequence analysis for identification of bacteria on clinical
microbiology and infectious diseases. Clin. Microbiol. Rev.
17:840–862.
Cole, J. R., Q. Wang, E. Cardenas, J. Fish, B. Chai,
R. J. Farris, A. S. Kulam-Syed-Mohideen, D. M. McGarrell, T. Marsh, G. M. Garrity, and J. M. Tiedje. 2009.
The Ribosomal Database Project: improved alignments
and new tools for rRNA analysis. Nucleic Acids Res. 37:
D141–D145.
Corless, C. E., M. Guiver, R. Borrow, V. Edwards-Jones,
E. B. Kaczmarski, and A. J. Fox. 2000. Contamination
and sensitivity issues with a real-time universal 16S rRNA
PCR. J. Clin. Microbiol. 38:1747–1752.
Dagan, R., O. Shriker, I. Hazan, E. Leibovitz, D. Greenberg, F. Schlaeffer, and R. Levy. 1998. Prospective study
to determine clinical relevance of detection of pneumococcal DNA in sera of children by PCR. J. Clin. Microbiol.
36:669–673.
Daims, H., A. Brühl, R. Amann, K. H. Schleifer, and
M. Wagner. 1999. The domain-specific probe EUB338 is
insufficient for the detection of all Bacteria: development
and evaluation of a more comprehensive probe set. Syst.
Appl. Microbiol. 22:434–444.
DeSantis, T. Z., P. Hugenholtz, N. Larsen, M. Rojas,
E. L. Brodie, K. Keller, T. Huber, D. Dalevi, P. Hu, and
G. L. Andersen. 2006. Greengenes, a chimera-checked
16S rRNA gene database and workbench compatible with
ARB. Appl. Environ. Microbiol. 72:5069–5072.
Deutch, S., D. Dahlberg, J. Hedegaard, M. B. Schmidt,
J. K. Moller, and L. Ostergaard. 2007. Diagnosis of ventricular drainage-related bacterial meningitis by broadrange real-time polymerase chain reaction. Neurosurgery
61:306–312.
501
33. Devulder, G., G. Perriere, F. Baty, and J. P. Flandrois.
2003. BIBI, a bioinformatics bacterial identification tool.
J. Clin. Microbiol. 41:1785–1787.
34. DiGiulio, D. B., R. Romero, H. P. Amogan, J. P. Kusanovic, E. M. Bik, F. Gotsch, C. J. Kim, O. Erez, S.
Edwin, and D. A. Relman. 2008. Microbial prevalence,
diversity and abundance in amniotic fluid during preterm
labor: a molecular and culture-based investigation. PLoS
ONE 3:e3056.
35. Dreier, J., M. Störmer, and K. Kleesiek. 2007. Real-time
polymerase chain reaction in transfusion medicine: applications for detection of bacterial contamination in blood
products. Transfus. Med. Rev. 21:237–254.
36. Dreier, J., M. Störmer, and K. Kleesiek. 2004. Two novel
real-time reverse transcriptase PCR assays for rapid detection of bacterial contamination in platelet concentrates.
J. Clin. Microbiol. 42:4759–4764.
37. Eden, P. A., T. M. Schmidt, R. P. Blakemore, and N. R.
Pace. 1991. Phylogenetic analysis of Aquaspirillum magnetotacticum using polymerase chain reaction-amplified
16S rRNA-specific DNA. Int. J. Syst. Bacteriol. 41:324–
325.
38. Edwards, U., T. Rogall, H. Blöcker, M. Emde, and E. C.
Böttger. 1989. Isolation and direct complete nucleotide
determination of entire genes. Characterization of a gene
coding for 16S ribosomal RNA. Nucleic Acids Res. 17:
7843–7853.
39. Farris, M. H., and J. B. Olson. 2007. Detection of Actinobacteria cultivated from environmental samples reveals
bias in universal primers. Lett. Appl. Microbiol. 45:376–
381.
40. Fenollar, F., P. Y. Levy, and D. Raoult. 2008. Usefulness
of broad-range PCR for the diagnosis of osteoarticular infections. Curr. Opin. Rheumatol. 20:463–470.
41. Fenollar, F., V. Roux, A. Stein, M. Drancourt, and D.
Raoult. 2006. Analysis of 525 samples to determine the
usefulness of PCR amplification and sequencing of the
16S rRNA gene for diagnosis of bone and joint infections.
J. Clin. Microbiol. 44:1018–1028.
42. Frank, J. A., C. I. Reich, S. Sharma, J. S. Weisbaum,
B. A. Wilson, and G. J. Olsen. 2008. Critical evaluation
of two primers commonly used for amplification of bacterial 16S rRNA genes. Appl. Environ. Microbiol. 74:
2461–2470.
43. Fredricks, D. N., T. L. Fiedler, and J. M. Marrazzo.
2005. Molecular identification of bacteria associated with
bacterial vaginosis. N. Engl. J. Med. 353:1899–1911.
44. Fredricks, D. N., J. A. Jolley, P. W. Lepp, J. C. Kosek,
and D. A. Relman. 2000. Rhinosporidium seeberi: a human
pathogen from a novel group of aquatic protistan parasites.
Emerg. Infect. Dis. 6:273–282.
45. Fredricks, D. N., and D. A. Relman. 1999. Application
of polymerase chain reaction to the diagnosis of infectious
diseases. Clin. Infect. Dis. 29:475–486.
46. Fredricks, D. N., and D. A. Relman. 1996. Sequencebased identification of microbial pathogens: a reconsideration of Koch’s postulates. Clin. Microbiol. Rev. 9:18–33.
47. Frothingham, R., R. B. Blitchington, D. H. Lee, R. C.
Greene, and K. H. Wilson. 1992. UV absorption complicates PCR decontamination. BioTechniques 13:208–
210.
48. Giovannoni, S. J., T. B. Britschgi, C. L. Moyer, and
K. G. Field. 1990. Genetic diversity in Sargasso Sea bacterioplankton. Nature 345:60–63.
49. Goldenberger, D., and M. Altwegg. 1995. Eubacterial
PCR: contaminating DNA in primer preparations and its
elimination by UV light. J. Microbiol. Methods 21:27–32.
50. Goldenberger, D., A. Künzli, P. Vogt, R. Zbinden, and
M. Altwegg. 1997. Molecular diagnosis of bacterial en-
502 ■
51.
52.
53.
54.
55.
56.
57.
58.
59.
60.
61.
62.
63.
64.
65.
MAIWALD
docarditis by broad-range PCR amplification and direct
sequencing. J. Clin. Microbiol. 35:2733–2739.
Gubler, J. G. H., M. Kuster, F. Dutly, F. Bannwart, M.
Krause, H. P. Vogelin, G. Garzoli, and M. Altwegg.
1999. Whipple endocarditis without overt gastrointestinal
disease: report of four cases. Ann. Intern. Med. 131:112–
116.
Hajjeh, R. A., D. Relman, P. R. Cieslak, A. N. Sofair,
D. Passaro, J. Flood, J. Johnson, J. K. Hacker, W. J.
Shieh, R. M. Hendry, S. Nikkari, S. Ladd-Wilson, J.
Hadler, J. Rainbow, J. W. Tappero, C. W. Woods, L.
Conn, S. Reagan, S. Zaki, and B. A. Perkins. 2002. Surveillance for unexplained deaths and critical illnesses due
to possibly infectious causes, United States, 1995–1998.
Emerg. Infect. Dis. 8:145–153.
Hansen, M. C., T. Tolker-Nielsen, M. Givskov, and S.
Molin. 1998. Biased 16S rDNA PCR amplification caused
by interference from DNA flanking the template region.
FEMS Microbiol. Ecol. 26:141–149.
Harris, K. A., and J. C. Hartley. 2003. Development of
broad-range 16S rDNA PCR for use in the routine diagnostic clinical microbiology service. J. Med. Microbiol. 52:
685–691.
Hein, I., W. Schneeweiss, C. Stanek, and M. Wagner.
2007. Ethidium monoazide and propidium monoazide for
elimination of unspecific DNA background in quantitative universal real-time PCR. J. Microbiol. Methods 71:
336–339.
Heininger, A., M. Binder, A. Ellinger, K. Botzenhart, K.
Unertl, and G. Döring. 2003. DNase pretreatment of
master mix reagents improves the validity of universal 16S
rRNA gene PCR results. J. Clin. Microbiol. 41:1763–
1765.
Hilali, F., P. Saulnier, E. Chachaty, and A. Andremont.
1997. Decontamination of polymerase chain reaction reagents for detection of low concentrations of 16S rRNA
genes. Mol. Biotechnol. 7:207–216.
Hitti, J., D. E. Riley, M. A. Krohn, S. L. Hillier, K. J.
Agnew, J. N. Krieger, and D. A. Eschenbach. 1997.
Broad-spectrum bacterial rDNA polymerase chain reaction assay for detecting amniotic fluid infection among
women in premature labor. Clin. Infect. Dis. 24:1228–
1232.
Hongoh, Y., H. Yuzawa, M. Ohkuma, and T. Kudo.
2003. Evaluation of primers and PCR conditions for the
analysis of 16S rRNA genes from a natural environment.
FEMS Microbiol. Lett. 221:299–304.
Huber, T., G. Faulkner, and P. Hugenholtz. 2004. Bellerophon: a program to detect chimeric sequences in multiple sequence alignments. Bioinformatics 20:2317–2319.
Hugenholtz, P., and B. M. Goebel. 2001. The polymerase
chain reaction as a tool to investigate microbial diversity
in environmental samples, p. 31–42. In P. A. Rochelle
(ed.), Environmental Molecular Microbiology: Protocols and
Applications. Horizon Scientific Press, Wymondham, UK.
Hughes, M. S., L. A. Beck, and R. A. Skuce. 1994.
Identification and elimination of DNA sequences in Taq
DNA polymerase. J. Clin. Microbiol. 32:2007–2008.
Hunt, D. E., V. Klepac-Ceraj, S. G. Acinas, C. Gautier,
S. Bertilsson, and M. F. Polz. 2006. Evaluation of 23S
rRNA PCR primers for use in phylogenetic studies of bacterial diversity. Appl. Environ. Microbiol. 72:2221–2225.
Huse, S. M., L. Dethlefsen, J. A. Huber, D. M. Welch,
D. A. Relman, and M. L. Sogin. 2008. Exploring microbial diversity and taxonomy using SSU rRNA hypervariable tag sequencing. PLoS Genet. 4:e1000255.
Jalava, J., P. Kotilainen, S. Nikkari, M. Skurnik, E.
Vanttinen, O. P. Lehtonen, E. Eerola, and P. Toivanen.
1995. Use of the polymerase chain reaction and DNA
66.
67.
68.
69.
70.
71.
72.
73.
74.
75.
76.
77.
78.
79.
80.
sequencing for detection of Bartonella quintana in the aortic valve of a patient with culture-negative infective endocarditis. Clin. Infect. Dis. 21:891–896.
Janda, J. M., and S. L. Abbott. 2007. 16S rRNA gene
sequencing for bacterial identification in the diagnostic
laboratory: pluses, perils, and pitfalls. J. Clin. Microbiol.
45:2761–2764.
Jordan, J. A., A. R. Butchko, and M. B. Durso. 2005.
Use of pyrosequencing of 16S rRNA fragments to differentiate between bacteria responsible for neonatal sepsis. J.
Mol. Diagn. 7:105–110.
Jordan, J. A., and M. B. Durso. 2005. Real-time polymerase chain reaction for detecting bacterial DNA directly from blood of neonates being evaluated for sepsis.
J. Mol. Diagn. 7:575–581.
Jordan, J. A., M. B. Durso, A. R. Butchko, J. G. Jones,
and B. S. Brozanski. 2006. Evaluating the near-term infant for early onset sepsis: progress and challenges to consider with 16S rDNA polymerase chain reaction testing.
J. Mol. Diagn. 8:357–363.
Kappe, R., C. N. Okeke, C. Fauser, M. Maiwald, and
H. G. Sonntag. 1998. Molecular probes for the detection
of pathogenic fungi in the presence of human tissue. J.
Med. Microbiol. 47:811–820.
Klaschik, S., L. E. Lehmann, A. Raadts, A. Hoeft, and
F. Stuber. 2002. Comparison of different decontamination
methods for reagents to detect low concentrations of bacterial 16S DNA by real-time-PCR. Mol. Biotechnol. 22:
231–242.
Kobayashi, N., T. W. Bauer, D. Togawa, I. H. Lieberman, H. Sakai, T. Fujishiro, M. J. Tuohy, and G. W.
Procop. 2005. A molecular gram stain using broad range
PCR and pyrosequencing technology: a potentially useful
tool for diagnosing orthopaedic infections. Diagn. Mol.
Pathol. 14:83–89.
Kotilainen, P., J. Jalava, O. Meurman, O. P. Lehtonen,
E. Rintala, O. P. Seppala, E. Eerola, and S. Nikkari.
1998. Diagnosis of meningococcal meningitis by broadrange bacterial PCR with cerebrospinal fluid. J. Clin. Microbiol. 36:2205–2209.
Kroes, I., P. W. Lepp, and D. A. Relman. 1999. Bacterial
diversity within the human subgingival crevice. Proc.
Natl. Acad. Sci. USA 96:14547–14552.
Kupila, L., K. Rantakokko-Jalava, J. Jalava, S. Nikkari,
R. Peltonen, O. Meurman, R. J. Marttila, E. Kotilainen,
and P. Kotilainen. 2003. Aetiological diagnosis of brain
abscesses and spinal infections: application of broad range
bacterial polymerase chain reaction analysis. J. Neurol.
Neurosurg. Psychiatry 74:728–733.
Lane, D. J. 1991. 16S / 23S rRNA sequencing, p. 115–
175. In E. Stackebrandt and M. Goodfellow (ed.), Nucleic
Acid Techniques in Bacterial Systematics. John Wiley &
Sons, Chichester, United Kingdom.
Lane, D. J., B. Pace, G. J. Olsen, D. A. Stahl, M. L.
Sogin, and N. R. Pace. 1985. Rapid determination of 16S
ribosomal RNA sequences for phylogenetic analyses. Proc.
Natl. Acad. Sci. USA 82:6955–6959.
La Scola, B., G. Michel, and D. Raoult. 1997. Use of
amplification and sequencing of the 16S rRNA gene to
diagnose Mycoplasma pneumoniae osteomyelitis in a patient with hypogammaglobulinemia. Clin. Infect. Dis. 24:
1161–1163.
Lehtiniemi, J., P. J. Karhunen, S. Goebeler, S. Nikkari,
and S. T. Nikkari. 2005. Identification of different bacterial DNAs in human coronary arteries. Eur. J. Clin. Investig. 35:13–16.
Ley, B. E., C. J. Linton, D. M. Bennett, H. Jalal, A. B.
Foot, and M. R. Millar. 1998. Detection of bacteraemia
in patients with fever and neutropenia using 16S rRNA
31. Broad-Range PCR for Bacterial Identification ■
81.
82.
83.
84.
85.
86.
87.
88.
89.
90.
91.
92.
93.
94.
gene amplification by polymerase chain reaction. Eur. J.
Clin. Microbiol. Infect. Dis. 17:247–253.
Ley, R. E., P. J. Turnbaugh, S. Klein, and J. I. Gordon.
2006. Microbial ecology: human gut microbes associated
with obesity. Nature 444:1022–1023.
Liu, Z., T. Z. DeSantis, G. L. Andersen, and R. Knight.
2008. Accurate taxonomy assignments from 16S rRNA
sequences produced by highly parallel pyrosequencers. Nucleic Acids Res. 36:e120.
Loy, A., R. Arnold, P. Tischler, T. Rattei, M. Wagner,
and M. Horn. 2008. probeCheck—a central resource for
evaluating oligonucleotide probe coverage and specificity.
Environ. Microbiol. 10:2894–2898.
Loy, A., F. Maixner, M. Wagner, and M. Horn. 2007.
probeBase—an online resource for rRNA-targeted oligonucleotide probes: new features 2007. Nucleic Acids Res.
35:D800–D804.
Ludwig, W., O. Strunk, R. Westram, L. Richter, H.
Meier, Yadhukumar, A. Buchner, T. Lai, S. Steppi, G.
Jobb, W. Förster, I. Brettske, S. Gerber, A. W. Ginhart,
O. Gross, S. Grumann, S. Hermann, R. Jost, A. König,
T. Liss, R. Lüssmann, M. May, B. Nonhoff, B. Reichel,
R. Strehlow, A. Stamatakis, N. Stuckmann, A. Vilbig,
M. Lenke, T. Ludwig, A. Bode, and K. H. Schleifer.
2004. ARB: a software environment for sequence data.
Nucleic Acids Res. 32:1363–1371.
Maiwald, M., H. J. Ditton, H. G. Sonntag, and M. von
Knebel Doeberitz. 1994. Characterization of contaminating DNA in Taq polymerase which occurs during amplification with a primer set for Legionella 5S ribosomal
RNA. Mol. Cell. Probes 8:11–14.
Maiwald, M., K. Kissel, S. Srimuang, M. von Knebel
Doeberitz, and H. G. Sonntag. 1994. Comparison of
polymerase chain reaction and conventional culture for
the detection of legionellas in hospital water samples. J.
Appl. Bacteriol. 76:216–225.
Marchesi, J. R., T. Sato, A. J. Weightman, T. A. Martin,
J. C. Fry, S. J. Hiom, D. Dymock, and W. G. Wade.
1998. Design and evaluation of useful bacterium-specific
PCR primers that amplify genes coding for bacterial 16S
rRNA. Appl. Environ. Microbiol. 64:795–799.
Marin, M., P. Munoz, M. Sanchez, M. del Rosal, L. Alcala, M. Rodriguez-Creixems, and E. Bouza. 2007. Molecular diagnosis of infective endocarditis by real-time
broad-range polymerase chain reaction (PCR) and sequencing directly from heart valve tissue. Medicine (Baltimore) 86:195–202.
McLaughlin, R. W., H. Vali, P. C. Lau, R. G. Palfree,
A. De Ciccio, M. Sirois, D. Ahmad, R. Villemur, M.
Desrosiers, and E. C. Chan. 2002. Are there naturally
occurring pleomorphic bacteria in the blood of healthy
humans? J. Clin. Microbiol. 40:4771–4775.
Medlin, L., H. J. Elwood, S. Stickel, and M. L. Sogin.
1988. The characterization of enzymatically amplified eukaryotic 16S-like rRNA-coding regions. Gene 71:491–
499.
Meier, A., D. H. Persing, M. Finken, and E. C. Böttger.
1993. Elimination of contaminating DNA within polymerase chain reaction reagents: implications for a general
approach to detection of uncultured pathogens. J. Clin.
Microbiol. 31:646–652.
Millar, B. C., X. Jiru, J. E. Moore, and J. A. Earle. 2000.
A simple and sensitive method to extract bacterial, yeast
and fungal DNA from blood culture material. J. Microbiol.
Methods 42:139–147.
Millar, B. C., and J. E. Moore. 2004. Current trends in
the molecular diagnosis of infective endocarditis. Eur. J.
Clin. Microbiol. Infect. Dis. 23:353–365.
503
95. Millar, B. C., J. Xu, and J. E. Moore. 2002. Risk assessment models and contamination management: implications for broad-range ribosomal DNA PCR as a diagnostic tool in medical bacteriology. J. Clin. Microbiol.
40:1575–1580.
96. Mitterer, G., M. Huber, E. Leidinger, C. Kirisits, W.
Lubitz, M. W. Mueller, and W. M. Schmidt. 2004.
Microarray-based identification of bacteria in clinical
samples by solid-phase PCR amplification of 23S ribosomal DNA sequences. J. Clin. Microbiol. 42:1048–1057.
97. Mohammadi, T., R. N. Pietersz, C. M. VandenbrouckeGrauls, P. H. Savelkoul, and H. W. Reesink. 2005. Detection of bacteria in platelet concentrates: comparison
of broad-range real-time 16S rDNA polymerase chain
reaction and automated culturing. Transfusion 45:731–
736.
98. Mohammadi, T., H. W. Reesink, C. M.
Vandenbroucke-Grauls, and P. H. Savelkoul. 2005. Removal of contaminating DNA from commercial nucleic
acid extraction kit reagents. J. Microbiol. Methods 61:
285–288.
99. Mollet, C., M. Drancourt, and D. Raoult. 1997. rpoB
sequence analysis as a novel basis for bacterial identification. Mol. Microbiol. 26:1005–1011.
100. Nadkarni, M. A., F. E. Martin, N. A. Jacques, and N.
Hunter. 2002. Determination of bacterial load by realtime PCR using a broad-range (universal) probe and
primers set. Microbiology 148:257–266.
101. Nikkari, S., F. A. Lopez, P. W. Lepp, P. R. Cieslak, S.
Ladd-Wilson, D. Passaro, R. Danila, and D. A. Relman. 2002. Broad-range bacterial detection and the analysis of unexplained death and critical illness. Emerg. Infect. Dis. 8:188–194.
102. Nikkari, S., I. J. McLaughlin, W. Bi, D. E. Dodge, and
D. A. Relman. 2001. Does blood of healthy subjects
contain bacterial ribosomal DNA? J. Clin. Microbiol. 39:
1956–1959.
103. Ohlin, A., A. Bäckman, M. Björkqvist, P. Mölling, M.
Jurstrand, and J. Schollin. 2008. Real-time PCR of the
16S-rRNA gene in the diagnosis of neonatal bacteraemia. Acta Paediatr. 97:1376–1380.
104. Olsen, G. J., and C. R. Woese. 1993. Ribosomal RNA:
a key to phylogeny. FASEB J. 7:113–123.
105. Ou, C. Y., J. L. Moore, and G. Schochetman. 1991.
Use of UV irradiation to reduce false positivity in polymerase chain reaction. BioTechniques 10:442, 444, 446.
106. Palacios, G., J. Druce, L. Du, T. Tran, C. Birch, T.
Briese, S. Conlan, P. L. Quan, J. Hui, J. Marshall, J. F.
Simons, M. Egholm, C. D. Paddock, W. J. Shieh, C. S.
Goldsmith, S. R. Zaki, M. Catton, and W. I. Lipkin.
2008. A new arenavirus in a cluster of fatal transplantassociated diseases. N. Engl. J. Med. 358:991–998.
107. Palmer, C., E. M. Bik, D. B. Digiulio, D. A. Relman,
and P. O. Brown. 2007. Development of the human infant intestinal microbiota. PLoS Biol. 5:e177.
108. Paster, B. J., S. K. Boches, J. L. Galvin, R. E. Ericson,
C. N. Lau, V. A. Levanos, A. Sahasrabudhe, and F. E.
Dewhirst. 2001. Bacterial diversity in human subgingival
plaque. J. Bacteriol. 183:3770–3783.
109. Peters, R. P., T. Mohammadi, C. M. VandenbrouckeGrauls, S. A. Danner, M. A. van Agtmael, and P. H.
Savelkoul. 2004. Detection of bacterial DNA in blood
samples from febrile patients: underestimated infection
or emerging contamination? FEMS Immunol. Med. Microbiol. 42:249–253.
110. Peters, R. P., M. A. van Agtmael, S. A. Danner, P. H.
Savelkoul, and C. M. Vandenbroucke-Grauls. 2004.
New developments in the diagnosis of bloodstream infections. Lancet Infect. Dis. 4:751–760.
504 ■
MAIWALD
111. Pruesse, E., C. Quast, K. Knittel, B. M. Fuchs, W.
Ludwig, J. Peplies, and F. O. Glöckner. 2007. SILVA:
a comprehensive online resource for quality checked and
aligned ribosomal RNA sequence data compatible with
ARB. Nucleic Acids Res. 35:7188–7196.
112. Qin, X., and K. B. Urdahl. 2001. PCR and sequencing
of independent genetic targets for the diagnosis of culture
negative bacterial endocarditis. Diagn. Microbiol. Infect.
Dis. 40:145–149.
113. Rand, K. H., and H. Houck. 1990. Taq polymerase contains bacterial DNA of unknown origin. Mol. Cell.
Probes 4:445–450.
114. Rantakokko-Jalava, K., and J. Jalava. 2002. Optimal
DNA isolation method for detection of bacteria in clinical specimens by broad-range PCR. J. Clin. Microbiol.
40:4211–4217.
115. Rantakokko-Jalava, K., S. Nikkari, J. Jalava, E. Eerola,
M. Skurnik, O. Meurman, O. Ruuskanen, A. Alanen,
E. Kotilainen, P. Toivanen, and P. Kotilainen. 2000. Direct amplification of rRNA genes in diagnosis of bacterial infections. J. Clin. Microbiol. 38:32–39.
116. Relman, D. A. 1993. The identification of uncultured
microbial pathogens. J. Infect. Dis. 168:1–8.
117. Relman, D. A. 1993. Universal bacterial 16S rDNA amplification and sequencing, p. 489–495. In D. H. Persing,
T. F. Smith, F. C. Tenover, and T. J. White (ed.), Diagnostic Molecular Microbiology: Principles and Applications.
American Society for Microbiology, Washington, DC.
118. Relman, D. A., J. S. Loutit, T. M. Schmidt, S. Falkow,
and L. S. Tompkins. 1990. The agent of bacillary angiomatosis. An approach to the identification of uncultured pathogens. N. Engl. J. Med. 323:1573–1580.
119. Relman, D. A., T. M. Schmidt, A. Gajadhar, M. Sogin,
J. Cross, K. Yoder, O. Sethabutr, and P. Echeverria.
1996. Molecular phylogenetic analysis of Cyclospora, the
human intestinal pathogen, suggests that it is closely related to Eimeria species. J. Infect. Dis. 173:440–445.
120. Relman, D. A., T. M. Schmidt, R. P. MacDermott, and
S. Falkow. 1992. Identification of the uncultured bacillus
of Whipple’s disease. N. Engl. J. Med. 327:293–301.
121. Renko, J., P. W. Lepp, N. Oksala, S. Nikkari, and S. T.
Nikkari. 2008. Bacterial signatures in atherosclerotic lesions represent human commensals and pathogens. Atherosclerosis 201:192–197.
122. Rimek, D., A. P. Garg, W. H. Haas, and R. Kappe.
1999. Identification of contaminating fungal DNA sequences in Zymolyase. J. Clin. Microbiol. 37:830–831.
123. Rivas, R., E. Velazquez, J. L. Zurdo-Pineiro, P. F. Mateos, and E. Martinez Molina. 2004. Identification of
microorganisms by PCR amplification and sequencing of
a universal amplified ribosomal region present in both
prokaryotes and eukaryotes. J. Microbiol. Methods 56:
413–426.
124. Rochelle, P. A., A. J. Weightman, and J. C. Fry. 1992.
DNase I treatment of Taq DNA polymerase for complete
PCR decontamination. BioTechniques 13:520.
125. Rolph, H. J., A. Lennon, M. P. Riggio, W. P. Saunders,
D. MacKenzie, L. Coldero, and J. Bagg. 2001. Molecular identification of microorganisms from endodontic
infections. J. Clin. Microbiol. 39:3282–3289.
126. Rood, I. G., M. H. Koppelman, A. Pettersson, and
P. H. Savelkoul. 2008. Development of an internally
controlled PCR assay for broad range detection of bacteria in platelet concentrates. J. Microbiol. Methods 75:
64–69.
127. Rosey, A. L., E. Abachin, G. Quesnes, C. Cadilhac, Z.
Pejin, C. Glorion, P. Berche, and A. Ferroni. 2007.
Development of a broad-range 16S rDNA real-time PCR
128.
129.
130.
131.
132.
133.
134.
135.
136.
137.
138.
139.
140.
141.
142.
143.
for the diagnosis of septic arthritis in children. J. Microbiol. Methods 68:88–93.
Rowther, F. B., C. Rodrigues, A. P. Mehta, M. S. Deshmukh, F. N. Kapadia, A. Hegde, and V. R. Joshi. 2005.
An improved method of elimination of DNA from PCR
reagents. Mol. Diagn. 9:53–57.
Rueckert, A., and H. W. Morgan. 2007. Removal of
contaminating DNA from polymerase chain reaction using ethidium monoazide. J. Microbiol. Methods 68:596–
600.
Sandhu, G. S., B. C. Kline, L. Stockman, and G. D.
Roberts. 1995. Molecular probes for diagnosis of fungal
infections. J. Clin. Microbiol. 33:2913–2919.
Schabereiter-Gurtner, C., S. Maca, S. Kaminsky, S.
Rolleke, W. Lubitz, and T. Barisani-Asenbauer. 2002.
Investigation of an anaerobic microbial community associated with a corneal ulcer by denaturing gradient gel
electrophoresis and 16S rDNA sequence analysis. Diagn.
Microbiol. Infect. Dis. 43:193–199.
Schmidt, T. M., B. Pace, and N. R. Pace. 1991. Detection of DNA contamination in Taq polymerase. BioTechniques 11:176–177.
Schmidt, T. M., and D. A. Relman. 1994. Phylogenetic
identification of uncultured pathogens using ribosomal
RNA sequences. Methods Enzymol. 235:205–222.
Schuurman, T., R. F. de Boer, A. M. Kooistra-Smid,
and A. A. van Zwet. 2004. Prospective study of use of
PCR amplification and sequencing of 16S ribosomal
DNA from cerebrospinal fluid for diagnosis of bacterial
meningitis in a clinical setting. J. Clin. Microbiol. 42:
734–740.
Sefers, S., Z. H. Pei, and Y. W. Tang. 2005. False positives and false negatives encountered in diagnostic molecular microbiology. Rev. Med. Microbiol. 16:59–67.
Silkie, S. S., M. P. Tolcher, and K. L. Nelson. 2008.
Reagent decontamination to eliminate false-positives in
Escherichia coli qPCR. J. Microbiol. Methods 72:275–282.
Sipos, R., A. J. Szekely, M. Palatinszky, S. Revesz, K.
Marialigeti, and M. Nikolausz. 2007. Effect of primer
mismatch, annealing temperature and PCR cycle number
on 16S rRNA gene-targetting bacterial community analysis. FEMS Microbiol. Ecol. 60:341–350.
Sleigh, J., R. Cursons, and M. La Pine. 2001. Detection
of bacteraemia in critically ill patients using 16S rDNA
polymerase chain reaction and DNA sequencing. Intensive Care Med. 27:1269–1273.
Steinman, C. R., B. Muralidhar, G. J. Nuovo, P. M.
Rumore, D. Yu, and M. Mukai. 1997. Domain-directed
polymerase chain reaction capable of distinguishing bacterial from host DNA at the single-cell level: characterization of a systematic method to investigate putative
bacterial infection in idiopathic disease. Anal. Biochem.
244:328–339.
Störmer, M., K. Kleesiek, and J. Dreier. 2007. Highvolume extraction of nucleic acids by magnetic bead
technology for ultrasensitive detection of bacteria in
blood components. Clin. Chem. 53:104–110.
Suau, A., R. Bonnet, M. Sutren, J. J. Godon, G. R.
Gibson, M. D. Collins, and J. Doré. 1999. Direct analysis of genes encoding 16S rRNA from complex communities reveals many novel molecular species within
the human gut. Appl. Environ. Microbiol. 65:4799–4807.
Suzuki, M. T., and S. J. Giovannoni. 1996. Bias caused
by template annealing in the amplification of mixtures
of 16S rRNA genes by PCR. Appl. Environ. Microbiol.
62:625–630.
Takai, K., D. P. Moser, M. DeFlaun, T. C. Onstott,
and J. K. Fredrickson. 2001. Archaeal diversity in wa-
31. Broad-Range PCR for Bacterial Identification ■
144.
145.
146.
147.
148.
149.
150.
151.
152.
153.
154.
155.
ters from deep South African gold mines. Appl. Environ.
Microbiol. 67:5750–5760.
Tanner, M. A., B. M. Goebel, M. A. Dojka, and N. R.
Pace. 1998. Specific ribosomal DNA sequences from diverse environmental settings correlate with experimental
contaminants. Appl. Environ. Microbiol. 64:3110–3113.
Tanner, M. A., D. Shoskes, A. Shahed, and N. R.
Pace. 1999. Prevalence of corynebacterial 16S rRNA sequences in patients with bacterial and ‘‘nonbacterial’’
prostatitis. J. Clin. Microbiol. 37:1863–1870.
Taranger, J., B. Trollfors, L. Lind, G. Zackrisson, and
K. Beling-Holmquist. 1994. Environmental contamination leading to false-positive polymerase chain reaction
for pertussis. Pediatr. Infect. Dis. J. 13:936–937.
Tondeur, S., O. Agbulut, M. L. Menot, J. Larghero, D.
Paulin, P. Menasche, J. L. Samuel, C. Chomienne, and
B. Cassinat. 2004. Overcoming bacterial DNA contamination in real-time PCR and RT-PCR reactions for LacZ
detection in cell therapy monitoring. Mol. Cell. Probes
18:437–441.
Tseng, C. P., J. C. Cheng, C. C. Tseng, C. Wang, Y. L.
Chen, D. T. Chiu, H. C. Liao, and S. S. Chang. 2003.
Broad-range ribosomal RNA real-time PCR after removal of DNA from reagents: melting profiles for clinically important bacteria. Clin. Chem. 49:306–309.
Ugahary, L., W. van de Sande, J. C. van Meurs, and
A. van Belkum. 2004. An unexpected experimental pitfall in the molecular diagnosis of bacterial endophthalmitis. J. Clin. Microbiol. 42:5403–5405.
Van Camp, G., S. Chapelle, and R. De Wachter. 1993.
Amplification and sequencing of variable regions in bacterial 23S ribosomal RNA genes with conserved primer
sequences. Curr. Microbiol. 27:147–151.
van der Zee, A., M. Peeters, C. de Jong, H. Verbakel,
J. W. Crielaard, E. C. Claas, and K. E. Templeton.
2002. Qiagen DNA extraction kits for sample preparation for legionella PCR are not suitable for diagnostic
purposes. J. Clin. Microbiol. 40:1126.
Varghese, B., C. Rodrigues, M. Deshmukh, S. Natarajan, P. Kamdar, and A. Mehta. 2006. Broad-range bacterial and fungal DNA amplification on vitreous humor
from suspected endophthalmitis patients. Mol. Diagn.
Ther. 10:319–326.
Voldstedlund, M., L. Norum Pedersen, U. Baandrup,
K. E. Klaaborg, and K. Fuursted. 2008. Broad-range
PCR and sequencing in routine diagnosis of infective
endocarditis. APMIS 116:190–198.
von Wintzingerode, F., U. B. Göbel, and E. Stackebrandt. 1997. Determination of microbial diversity in
environmental samples: pitfalls of PCR-based rRNA
analysis. FEMS Microbiol. Rev. 21:213–229.
Watanabe, K., Y. Kodama, and S. Harayama. 2001. Design and evaluation of PCR primers to amplify bacterial
16S ribosomal DNA fragments used for community fingerprinting. J. Microbiol. Methods 44:253–262.
505
156. Weisburg, W. G., S. M. Barns, D. A. Pelletier, and
D. J. Lane. 1991. 16S ribosomal DNA amplification for
phylogenetic study. J. Bacteriol. 173:697–703.
157. Welch, D. F., D. A. Pickett, L. N. Slater, A. G. Steigerwalt, and D. J. Brenner. 1992. Rochalimaea henselae sp.
nov., a cause of septicemia, bacillary angiomatosis, and
parenchymal bacillary peliosis. J. Clin. Microbiol. 30:
275–280.
158. Welinder-Olsson, C., L. Dotevall, H. Hogevik, R.
Jungnelius, B. Trollfors, M. Wahl, and P. Larsson.
2007. Comparison of broad-range bacterial PCR and culture of cerebrospinal fluid for diagnosis of communityacquired bacterial meningitis. Clin. Microbiol. Infect. 13:
879–886.
159. White, T. J., T. Bruns, S. Lee, and J. Taylor. 1990.
Amplification and direct sequencing of fungal ribosomal
RNA genes for phylogenetics, p. 315–322. In M. A. Innis, D. H. Gelfand, J. J. Sninsky, and T. J. White (ed.),
PCR Protocols: A Guide to Methods and Applications. Academic Press, San Diego, CA.
160. Wilson, K. H., R. Blitchington, R. Frothingham, and
J. A. Wilson. 1991. Phylogeny of the Whipple’s-diseaseassociated bacterium. Lancet 338:474–475.
161. Wilson, K. H., and R. B. Blitchington. 1996. Human
colonic biota studied by ribosomal DNA sequence analysis. Appl. Environ. Microbiol. 62:2273–2278.
162. Wilson, K. H., R. B. Blitchington, and R. C. Greene.
1990. Amplification of bacterial 16S ribosomal DNA
with polymerase chain reaction. J. Clin. Microbiol. 28:
1942–1946.
163. Woese, C. R. 1987. Bacterial evolution. Microbiol. Rev.
51:221–271.
164. Woo, P. C., L. M. Chung, J. L. Teng, H. Tse, S. S.
Pang, V. Y. Lau, V. W. Wong, K. L. Kam, S. K. Lau,
and K. Y. Yuen. 2007. In silico analysis of 16S ribosomal
RNA gene sequencing-based methods for identification
of medically important anaerobic bacteria. J. Clin.
Pathol. 60:576–579.
165. Woo, P. C., S. K. Lau, J. L. Teng, H. Tse, and K. Y.
Yuen. 2008. Then and now: use of 16S rDNA gene sequencing for bacterial identification and discovery of
novel bacteria in clinical microbiology laboratories. Clin.
Microbiol. Infect. 14:908–934.
166. Wuyts, J., G. Perriere, and Y. Van De Peer. 2004. The
European ribosomal RNA database. Nucleic Acids Res.
32:D101–D103.
167. Xu, J., J. E. Moore, B. C. Millar, H. Webb, M. D.
Shields, and C. E. Goldsmith. 2005. Employment of
broad range 16S rDNA PCR and sequencing in the detection of aetiological agents of meningitis. New Microbiol. 28:135–143.
168. Zucol, F., R. A. Ammann, C. Berger, C. Aebi, M. Altwegg, F. K. Niggli, and D. Nadal. 2006. Real-time quantitative broad-range PCR assay for detection of the 16S
rRNA gene followed by sequencing for species identification. J. Clin. Microbiol. 44:2750–2759.