Previous Article | Next Article 
Applied and Environmental Microbiology, November 2007, p. 7435-7442, Vol. 73, No. 22
0099-2240/07/$08.00+0 doi:10.1128/AEM.01143-07
Copyright © 2007, American Society for Microbiology. All Rights Reserved.
Mucosa-Associated Bacterial Diversity in Relation to Human Terminal Ileum and Colonic Biopsy Samples
Shakil Ahmed,1
George T. Macfarlane,1
Alemu Fite,1
Andrew J. McBain,2
Peter Gilbert,2 and
Sandra Macfarlane1*
Dundee University Gut Group, Dundee, United Kingdom,1
School of Pharmacy and Pharmaceutical Sciences, University of Manchester, Manchester, United Kingdom2
Received 22 May 2007/
Accepted 14 September 2007

ABSTRACT
Little is known about bacterial communities that colonize mucosal
surfaces in the human gastrointestinal tract, but they are believed
to play an important role in host physiology. The objectives
of this study were to investigate the compositions of these
populations in the distal small bowel and colon. Healthy mucosal
tissue from either the terminal ileum (
n = 6) or ascending (
n = 8), transverse (
n = 8), or descending colon (
n = 4) of 26
patients (age, 68.5 ± 1.2 years [mean ± standard
deviation]) undergoing emergency resection of the large bowel
was used to study these communities. Mucosa-associated eubacteria
were characterized by using PCR-denaturing gradient gel electrophoresis
(DGGE), while real-time PCR was employed for quantitative analysis.
Mucosal communities were also visualized in situ using confocal
laser scanning microscopy. DGGE banding profiles from all the
gut regions exhibited at least 45% homology, with five descending
colon profiles clustering at ca. 75% concordance. Real-time
PCR showed that mucosal bacterial population densities were
highest in the terminal ileum and that there were no significant
differences in overall bacterial numbers in different parts
of the colon. Bifidobacterial numbers were significantly higher
in the large bowel than in the terminal ileum (
P = 0.006), whereas
lactobacilli were more prominent in the distal large intestine
(
P = 0.019).
Eubacterium rectale (
P = 0.0004) and
Faecalibacterium prausnitzii (
P = 0.001) were dominant in the ascending and descending
colon. Site-specific colonization in the gastrointestinal tract
may be contributory in the etiology of some diseases of the
large intestine.

INTRODUCTION
The human colonic microbiota is part of a highly complex bacterial
ecosystem (
26), and several hundred different types of bacteria
are known to colonize the gut (
8,
9,
43). Evidence implicates
the microbiota in the pathophysiology of several diseases of
the large intestine, including colorectal cancer, Crohn's disease,
and ulcerative colitis (
9,
16,
18,
25,
28). These diseases usually
show distinct patterns of incidence in the large bowel. For
example, 50% of colorectal cancers occur in the distal large
gut (
4), while in contrast, the transverse colon is a relatively
rare site of tumor formation, with the incidence increasing
in the ascending colon and cecum (
4). Similarly, ulcerative
colitis principally affects the distal large bowel and most
frequently involves the rectum (
34), whereas Crohn's disease
is localized in the ileocecal junction in 60% of patients, in
the small intestine alone in 20%, and in the colon alone in
a further 20% (
12).
Much of our knowledge of the diversity and distribution of the intestinal microbiota derives from bacteriologic studies on fecal material, employing traditional techniques of culture, microscopy, and determinations of the fermentative and other biochemical capabilities of the isolates (27, 30). This work, while still important in many types of study, is labor intensive and requires the use of specialized apparatus that allows extremely oxygen-sensitive bacteria to be cultivated (23, 30, 36). Moreover, it has been reported that about two-thirds of the total microscopic count in the gut is not recovered, even using strict anaerobic culture methods (44, 48).
Molecular techniques based on the analysis of 16S rRNA gene sequences, however, allow detailed studies to be made on intestinal bacterial communities (30). In particular, PCR coupled with denaturing gradient gel electrophoresis (DGGE) has been a useful tool in providing visual fingerprints of the gut microbiota (1, 38, 49), while the more recent development of real-time PCR provides a sensitive and quantitative device for population analysis (5, 10, 15). Recent metagenomic studies, based on high-throughput PCR, cloning, and sequencing, have enabled phylogenetic information about both culturable and nonculturable species colonizing the human digestive tract to be obtained (8, 13). Such investigations have been used, for example, to demonstrate that changes in the relative abundance of the Bacteroidetes and the Firmicutes biotas in the mouse gut resulted in significant, transmissible changes in host adiposity (24) and to provide a comprehensive indication of the species present and their relative abundances (8, 13, 49).
Because they grow in close juxtaposition to host cells, mucosal bacteria are thought to play a particularly important role in gut health, and distinct bacterial populations have been observed to occur on the gut epithelium in both health and disease (29, 31). Molecular studies have been done previously on mucosal communities in the gastrointestinal tract. Using DGGE, Zoetendal et al. (49) reported that mucosa-associated bacteria were similar along the length of the gastrointestinal tract, and more recently, comparative qualitative analysis of bacterial 16S rRNA gene sequences on the colonic mucosa of three healthy individuals indicated the occurrence of a large number of uncultured bacteria (8). The objective of the present investigation was to use a combination of molecular techniques (real-time PCR, DGGE, and fluorescence in situ hybridization [FISH]) to quantitate and visualize the bacterial diversity of the predominant bacteria colonizing the bowel wall in the terminal ileum, as well as in the ascending, transverse, and descending colon.

MATERIALS AND METHODS
Patients and specimens.
Mucosal biopsies were taken from 26 patients who underwent emergency
surgery requiring colonic resection. None of the patients had
bowel preparation before surgery. For each patient, a biopsy
sample of healthy tissue was taken from one of the following
areas: the terminal ileum (
n = 6), the ascending or transverse
colon (
n = 8 each), or the descending colon (
n = 4). Fourteen
patients were male, with a mean age of 68 years (range, 59 to
81), and 12 were female, with a mean age of 65 (range, 61 to
76). Pathologists took mucosal sections at points furthest away
from diseased areas, and histology later confirmed that there
was a clear margin between healthy and diseased tissue. Diagnoses
of colorectal cancer were confirmed in all but two cases, which
were diagnosed as localized perforated diverticulitis. The biopsy
samples, with associated mucus, were collected aseptically,
rinsed gently with sterile anaerobic phosphate-buffered saline,
and frozen immediately at –80°C for subsequent PCR
analysis; biopsy samples for FISH were covered in Tissue-Tek
freezing medium (Sakura Finetek Europe B.V., The Netherlands)
to preserve the mucus layer and stored at –80°C in
sterile Eppendorf tubes. Ethical approval was obtained from
the Tayside committee on medical research ethics and the MRC/CRUK
tissue bank committee, Ninewells Hospital, Dundee.
DNA extraction and purification.
DNA was extracted from cryopreserved tissue sections using a QIAamp DNA spin column (QIAGEN Ltd., West Sussex, United Kingdom). Briefly, biopsy specimens (2 to 5 mg) were suspended in lysis buffer and lysozyme (50 mg ml–1) solutions before incubation at 55°C. Proteinase K, buffer ATL (QIAGEN), and ethanol were sequentially added. The mixture was bead beaten for 2 min before and after incubation at 70°C using a MiniBeadbeater-8 (Biospec Products, Bartlesville, OK). Bacterial cell lysates were obtained by centrifugation at 5,000 x g (3 min). The resultant DNA was adsorbed onto minicolumn membranes, washed, and eluted according to the QIAGEN DNeasy tissue kit procedure. The purified DNA was eluted in 200 µl of elution buffer and stored at –80°C until analysis.
Amplification in conventional PCR.
A Techne genius PCR machine (Techne Ltd., Duxford, United Kingdom) was used for conventional PCR. The V2-V3 region of the 16S rRNA gene (corresponding to positions 339 to 539 of the Escherichia coli gene) was then amplified with (GC-rich) eubacterium-specific primers HDA1 (5'-GC CGC CCG GGG CGC GCC CCG GGC GGG GCA CGG GGG GAC TCC TAC GGG AGG CAG CAG T-3') and HDA2 (5'-GTA TTA CCG CGG CTG CTG GCA C-3') (45). The reactions were done in 0.2-ml reaction tubes. In all cases, the reaction was carried out using 25 µl Red Taq DNA polymerase ready mix (Sigma, Poole, Dorset, United Kingdom), HDA primers (2 µl of each; 5 mM), nanopure water (16 µl), and extracted community DNA (5 µl). Previous optimization studies (21, 38) have shown that extracted DNA requires a minimum of a 1:10 dilution to ensure reliable PCRs. The thermal program was as follow: 94°C (4 min) followed by 30 thermal cycles of 94°C (30 s), 56°C (30 s), and 68°C (60 s). The procedure was completed with a final elongation step at 68°C (7 min). PCR products were run on an agarose electrophoresis gel for confirmation of product concentration, quality, and size (ca. 200 bp) against a DNA molecular weight marker (2-log DNA ladder N3200L; New England Biolabs Ltd., Herts, United Kingdom). Primers were purchased from Invitrogen Life Technologies (Paisley, United Kingdom).
DGGE analysis.
A D-Code universal mutation detection system (Bio-Rad, Hemel Hempstead, United Kingdom) with 16-cm by 16-cm (1-mm-deep) polyacrylamide gels (10%), run with 1x TAE buffer diluted from 50x TAE buffer (40 mM Tris base, 20 mM acetic acid, and 40 mM EDTA), was used for these analyses. Initially, the separation parameters were optimized by running PCR products from selected pure cultures of bacteria and PCR amplicons from extracted community DNA on gels with a 0%-to-100% denaturing gradient perpendicular to the direction of electrophoresis (a 100% denaturing solution contained 40% [vol/vol] formamide and 7.0 mM urea). Denaturing gradients were formed with two 10% acrylamide (acrylamide-bisacrylamide, 37.5:1) stock solutions (Sigma, Poole, Dorset, United Kingdom). On this basis, a denaturation gradient for parallel DGGE analysis ranging from 30 to 60% was selected. PCR amplicons from the following bacteria were run on a parallel gel in order to confirm these separation conditions: Clostridium clostridioforme DUN-120, Escherichia coli ATCC 11775, Enterococcus faecalis ATCC 51299, Eubacterium limosum DUN-112, Lactobacillus plantarum DUN-145, Collinsella aerofaciens DUN-207, Bacteroides fragilis NCTC 9343, Desulfococcus multivorans NCIMB 12965, Bifidobacterium bifidum NCIMB 702715, and Lactobacillus paracasei DUN-213. The bacteria were obtained from the National Collection of Industrial and Marine Bacteria (Aberdeen, United Kingdom), the National Collection of Type Cultures (London, United Kingdom), the American Type Culture Collection (Manassas, VA) and laboratory stock cultures at the University of Dundee (DUN-). Electrophoresis was done at 150 V at 60°C for approximately 5 h (electrophoresis was terminated when the xylene cyanol dye reached the bottom of the gels). All gels were stained using SYBR gold stain diluted to 10–4 in 1x TAE (Molecular Probes Europe, Leiden, The Netherlands) for 30 min. The gels were viewed and images documented by using a BioDocit system (UVP, Upland, CA).
Sequencing of DGGE bands.
For analysis of the major resolved DGGE amplicons, selected bands were cut out of the polyacrylamide gels using a sterile scalpel under UV illumination and incubated at 4°C for 20 h, together with 20 µl nanopure water in nuclease-free universal bottles. Portions (5 µl) were removed and used as a template for a PCR identical to that outlined in the DGGE analysis described above. PCR products were purified using QIAquick PCR purification kits (QIAGEN) and sequenced using the reverse (non-GC clamp) primer (HDA2). The sequencing cycles were 94°C (4 min) followed by 25 cycles of 96°C (30 s), 50°C (15 s), and 60°C (4 min). Once chain termination was complete, sequencing was done using BigDye terminator sequencing on an ABI 3100 genetic analyzer (Applied Biosystems, Foster City, CA). For excised DGGE bands, the presence of a GC clamp on sequence analyses confirmed that the correct target, rather than a contaminant, had been reamplified.
Sequencing of DGGE amplicons.
BLAST searches on each sequence were done against those in the EMBL nucleotide sequence database (2).
Dendrogram construction from DGGE gels.
The gel images were analyzed using the BioNumerics Fingerprint package (Applied Maths, Sint-Martens-Latem, Belgium). The bands in each lane were detected automatically. Each lane on the gel was then compared, allowing matching profiles to be generated. Matching profiles for each lane were used to produce a dendrogram by using the unweighted pair group method with arithmetic mean so that potential clustering patterns could be observed. For each band represented in the synthetic reference lane, corresponding bands that had been excised were selected for sequencing.
Real-time PCR analysis.
Quantitation of bacterial 16S rRNA genes in mucosal tissue was done using an iCycler real-time PCR detection system (Bio-Rad, Hemel Hempstead, United Kingdom), using the experimental protocols described by Fite et al. (10). Briefly, DNA melting curves were used to monitor product specificities; detection was based on fluorescence energy transfer, with SYBR green 490 as the fluorophore. The cycle number at which the signal was first detected corresponded to the original concentration of DNA template, and the starting copy number of amplicons was inversely proportional to the real-time threshold cycle. Analyses of PCR amplification and melting curves were made using iCycler Optical System software, version 3.0 (Bio-Rad). The conditions included one cycle at 95°C for 3 min, followed by 38 cycles of denaturation at 95°C for 30 s, primer annealing at the optimum temperature for 30 s (optimal temperature and primers used in the study are shown in Table 1), and one final cycle at 95°C for 30 s. The melt curve analysis was run for 43 repeats, increasing concordantly by 1°C. Plasmid standards and samples were assayed simultaneously in duplicate. A range of concentrations from 101 to 108 of plasmid DNA was used in each real-time PCR assay to generate standard curves for quantitation of target DNA in test samples. Primers were purchased from Invitrogen.
FISH and confocal laser scanning microscopy (CLSM).
Biopsy samples were cut into 10-µm sections using a cryomicrotome
and placed on Teflon-coated 10-well glass slides (VWR, Merck
Eurolab Ltd., Poole, Dorset, United Kingdom). A range of fluorescent
16S rRNA oligonucleotide probes was used to visualize bacteria
present on the mucosal surface (
7) as described previously (
29).
Probe Bif 164 (5'-CATCCGGCATTACCACCC-3') was used to identify
bifidobacteria (
20), and Bac 303 (5'-CCAATGTGGGGGACCTT-3') was
used for bacteroides and prevotella (
33). Probe Ato 291 (5'-GGTCGGTCTCTCAACCC-3')
was used for the atopobium cluster (
14), and probe Erec 482
(5'-GCTTCTTAGTCAGGTACCG-3') was used for the
Eubacterium rectale/Clostridium coccoides group (
11). The nucleic acid stain DAPI (4',6'-diamidino-2-phenylindole)
was added to the final wash buffer after hybridization (
29).
Intestinal isolates and a range of culture collection type strains
were used as controls in testing the specificities of the oligonucleotide
probes (
5). Organisms were cultured in Wilkins-Chalgren broth
(Oxoid, Basingstoke, Hamps, United Kingdom) in an anaerobic
chamber (atmosphere: 80% N
2, 10% CO
2, 10% H
2) at 37°C for
24 h. The bacteria were then fixed in fresh paraformaldehyde
for 4 h at room temperature, washed in phosphate-buffered saline,
and stored at –20°C (
3). Probes were purchased from
Thermohybaid, Interactiva Division (Ulm, Germany), and 5'-labeled
with fluorochrome Cy3, fluorescein isothiocyanate (FITC), or
Cy5. Slides were visualized using a Nikon Eclipse E800 upright
microscope attached to a Nikon PCM 2000 confocal system, with
a 488-nm argon laser (green fluorescence) and a 543-nm helium-neon
laser (red fluorescence). A 60
x Plan Apo immersion lens (numerical
aperture, 1.4) was used for all images, which were captured
and overlaid using C-Imaging software (Compix, Inc., Cranberry
Township, PA).
Statistical analysis.
Data analysis was done using GraphPad Prism version 4.0 (GraphPad Software, Inc., San Diego, CA). The copy numbers of the 16S rRNA gene per gram of sample were transformed into logarithms, and the normally distributed data was subjected to statistical analysis. One-way analysis (Tukey's multiple comparison) of variance was used for comparison of bacterial densities between different specimens. Probability values of <0.05 were taken as statistically significant.
Chemicals.
Unless stated otherwise, all chemicals were obtained from Sigma.
Nucleotide sequence accession numbers.
The 35 species-specific sequences identified from the DGGE amplicons have been placed in the EMBL/GenBank/DDBJ database under accession numbers AM850147 to AM850181.

RESULTS
DGGE analysis.
Parallel DGGE using PCR products from pure cultures of
C. clostridioforme, E. coli, E. faecalis, E. limosum, L. plantarum, C. aerofaciens, B. fragilis, D. multivorans, B. bifidum, and
L. paracasei demonstrated
that each species formed a single major band on the gels (data
not shown). Figure
1 shows a dendrogram generated from DGGE
fingerprints of mucosa-associated eubacteria. In general, most
DGGE fingerprints were characterized by the presence of 1 to
3 dominant bands, with microbial complexity varying markedly
between different regions of the gut. Thus, some ascending colon
community lanes exhibited up to 20 discrete bands of various
density. Intraindividual variation was generally low, as demonstrated
by the homology which was apparent between samples from each
region in cluster analysis, particularly for ascending colon
samples (maximum sample concordance, 90%) and transverse colon
samples (maximum concordance, 80%). DGGE banding profiles from
all gut regions exhibited at least 45% homology, with five descending
colon profiles clustering at ca. 75% concordance.
Phylogenetic analysis of selected DGGE amplicons.
In the 69 bands selected, excised, and sequenced from the gels,
35 species-specific sequences were identified (Table
2). In
the terminal ileum, the most prominent bands corresponded to
EMBL accession number EF067826 of
B. fragilis, AF418173 of
D. multivorans, and AM042696 of
Bacteroides vulgatus. A high degree
of interindividual similarity was evident in DGGE band patterns
from the ascending colon samples. The three main bands corresponded
to X83935 of
B. fragilis, AY804151 of
E. rectale, and AB021418
of
Comamonas terrigena. The major bands from the transverse
colon samples corresponded to X83935 of
B. fragilis, AY804152
of
E. rectale, and AM042696 of
B. vulgatus, while AB186304 of
Bifidobacterium pseudolongum, AY373589 of
Lactobacillus fermentum,
and M59089 of
C. clostridioforme were the sequences corresponding
to the prominent bands on DGGE gels run with bacterial DNA amplified
from the distal colon (Fig.
1).
Real-time PCR analysis.
Bacteria from colonic tissue samples were quantitated by real-time
PCR using eubacterium-, genus-, and species-specific primer
sets (Table
1). The major groups of bacteria found on the DGGE
gels were quantified, and the counts were converted to the log
number of 16S rRNA genes per milligram of mucosal tissue. The
numbers of individual bacteria measured by real-time PCR are
shown in Table
3. Enterobacteria were not identified in the
DGGE gels; however, real-time PCR analysis using a genus-specific
primer demonstrated that these organisms were present in high
levels in all parts of the colon. Statistical analysis showed
that bacterial colonization of the mucosa in the terminal ileum,
measured using real-time PCR and the universal primer set, was
significantly greater than that of all parts of the colon (
P < 0.001). However, there were no significant differences
in total bacterial counts in the ascending, transverse, and
descending colon. Bifidobacteria and
F. prausnitzii were significantly
higher in the proximal colon than in the terminal ileum (
P =
0.006 and
P = 0.003, respectively), but there were no significant
differences in the numbers of these organisms in different parts
of the large bowel. The numbers of
Eubacterium rectale, C. clostridioforme,
and
F. prausnitzii were significantly higher in the ascending
and descending colon than in the transverse colon and terminal
ileum (
P = 0.0004,
P = 0.004, and
P = 0.001, respectively),
while significantly higher numbers of lactobacilli were found
in the descending and transverse colon than in the terminal
ileum and proximal colon (
P = 0.019). Significantly higher numbers
of
E. faecalis were found in the proximal and transverse colon
than in the terminal ileum (
P = 0 003). No significant differences
were observed in the distributions of
Peptostreptococcus anaerobius (
P = 0.378), desulfovibrios (
P = 0.428), enterobacteria (
P =
0.0884),
Clostridium butyricum (
P = 0.122), or bacteroides (
P = 0.55) throughout the large gut.
View this table:
[in this window]
[in a new window]
|
TABLE 3. Quantitation of bacterial populations in the terminal ileum and different regions of the large intestine using real-time PCR
|
CLSM of tissue samples.
CLSM, in combination with 16S rRNA oligonucleotide probes, was
used to visualize the spatial organization of communities on
the tissue samples. The majority of the bacteria found by using
real-time PCR and DGGE were visualized with the range of fluorescent
probes used. Figure
2 shows transverse sections of mucosal tissue
from the terminal ileum (Fig.
2A) and ascending colon (Fig.
2B) treated with the DNA stain DAPI for visualization of the
total mucosal communities. In Fig.
2A, helical bacteria can
be seen attached in large numbers to the mucus layer lining
a crypt in the ileum. In contrast, in Fig.
2B, the presence
of a substantial, heterogeneous mixture of organisms can be
seen in the mucin layer of the descending colon. Figure
3 shows
bacteria in mucin layers of transverse sections of biopsy samples
from the ascending, transverse, and descending colon, respectively.
Figure
3A was stained with a bacteroides-specific, fluorescently
labeled (Cy3) 16S rRNA oligonucleotide probe (Bac 303) and with
a bifidobacterium-specific 16S rRNA oligonucleotide probe with
an FITC fluorophore (Bif 164). Figure
3B and C were both stained
in combination with a Cy3-labeled probe (Erec 482) specific
for the
E. rectale/C. coccoides group and an FITC-labeled atopobium
cluster probe (Ato 291). In Fig.
3A, large numbers of bacteroides
and bifidobacteria can be seen attached to the mucus layer in
the ascending colon, while in Fig.
3B and C, members of both
the
E. rectale group and the atopobium cluster were found to
be present in the loosely attached mucin layer of the transverse
and descending colon.

DISCUSSION
In the majority of previous studies on mucosal communities in
humans, tissues were taken from colons that had been cleaned
out with strong bowel cleansers or laxatives prior to sampling
(
8,
22,
40,
46,
49), which may change the composition of mucosal
populations. In the present study, samples were taken from patients
undergoing emergency surgery required for resection of the colon,
which involved no prophylactic antibiotic treatment or bowel
evacuation before the operation. The samples were obtained from
parts of the gut remote from any diseased areas, and in all
cases, histopathology reports confirmed the presence of localized
disease and clear margins between healthy and diseased tissue.
Two patients were diagnosed with colonic carcinoma and two with
localized diverticulitis. The mean age of the patients in the
study was 68 years in males and 65 in females, reflecting an
aging cohort. This is because colonic pathologies requiring
bowel resection are more common in this age group and are relatively
rare in the population below age 50.
Although DGGE analysis has previously been used in studies to produce fingerprints of colonic mucosal samples, to date, few investigations have combined DGGE, cluster analysis, and sequencing with quantitative PCR and FISH in a relatively large subject group.
The DGGE profiles of bacterial communities in the ascending, transverse, and descending colon of the different individuals were shown to be similar to each other, which contrasts with previous studies reporting a high degree of consortial conservation along the length of the colon but marked interindividual variation (21, 22, 46, 49).
Quantitative analysis with real-time PCR using universal primers indicated that the terminal ileum had higher bacterial cell densities than the colon and that overall bacterial numbers were generally similar within the ascending, transverse, and descending colon. This may be due to higher numbers of unidentified bacteria in the terminal ileum, since no differences were found with genus- and species-specific primers. At the genus level, bifidobacteria were more prominent in the colon as a whole than in the terminal ileum, whereas lactobacilli were more dominant further down the large intestine (transverse and descending colon). However, bacteroides, enterobacteria, and dissimilatory sulfate-reducing bacteria were distributed uniformly in the large bowel and terminal ileum. This observation is in agreement with the results of work published by Zoetendal et al. (49). At the species level, variations in the numbers of some organisms in different parts of the large gut could be seen. Enterococcus faecalis occurred in higher numbers in the colon than in the ileum, while E. rectale, F. prausnitzii, and C. clostridioforme were more important in the proximal bowel (ascending and descending colon). However, no significant differences were seen for P. anaerobius or C. butyricum numbers in different parts of the large intestine. In summary, therefore, at both the genus and species level, changing bacterial cell densities in mucosa-associated biofilms were seen at various sites in the large gut. This may be of some health significance, because differences in these communities could contribute to the pathogenesis of some large intestine diseases. For example, over half of large bowel cancers occur in the descending colon and distal large gut (4), while the rectum is always involved in ulcerative colitis (34).
Although a number of molecularly based techniques are now available for studying bacterial populations colonizing the bowel wall, PCR-DGGE, real-time PCR, and FISH in combination provide a useful assessment of microbiological diversity in qualitative and quantitative terms. An advantage of DGGE over other qualitative techniques is that, in principle, any amplifiable target sequence that is above the detection threshold can be identified (37). DGGE is therefore not biased towards those phyla for which probes can be designed, which by definition will normally be limited to those expected to be important in the target community. However, PCR-DGGE has a number of limitations in that bias can be introduced during PCR amplification: DNA fragments with similar electrophoretic mobilities may migrate to the same position, while the relative concentrations of PCR products do not necessarily reflect the composition of the community under study (17, 30, 37). Real-time PCR provides a more specific, sensitive, and reproducible measure of the initial amount of template sample and is preferable to other forms of quantitative PCR, which only detect the final amount of amplified product. With real-time PCR, fluorescence emission is monitored during the reaction as an indicator of amplicon production during each PCR cycle, as opposed to endpoint detection by conventional quantitative PCR methods (10). A drawback of the technique is that its usefulness is dependent on the availability of specific PCR primer sets, so that investigators can only find what they are looking for in a sample.
Due to the presence of microcolonies in mucosal biofilms, many of the bacteria cannot be reliably quantitated in situ using microscopic techniques. However, FISH methods have the advantage of showing cell localization and providing an identification of groups of bacteria directly on the mucosal surface. Hence, a combination of techniques that allows fingerprinting, quantitation, and visualization enhances studies of mucosa-associated bacterial populations in the gut.
Microscopy using CLSM and DGGE using a range of 16S rRNA probes which covered the major groups of bacteria found on the gut mucosa showed that the organisms were present as heterogeneous assemblages in the mucosal layer, being present as individual colonies or dispersed in the biofilms. Many of the bacteria quantitated by using real-time PCR were visualized with the fluorescent probes. Members of the group of organisms in the atopobium cluster, which includes C. aerofaciens, were also visualized in tissues; however, they were not detected by DGGE or the real-time PCR primer sets used. Using FISH, these organisms were previously shown to be a major constituent of the fecal microbiota of formula-fed infants (15), and primers have now been developed allowing their quantification in fecal material (35).
It was of note that some of the ileal biopsies harbored large numbers of helical bacteria (Fig. 2A). These organisms were not detected in colonic tissues and were not seen by using the range of FISH probes or detected by DGGE. The presence of these helical organisms and of members of the atopobium cluster warrants further study, and these organisms may account for some of the differences in bacterial numbers detected in the ileum.
In conclusion, it has been demonstrated that using a combination of culture-independent techniques, i.e., PCR-DGGE, real-time PCR, and FISH, allows the identification and quantitation of different populations of bacteria in mucosal biofilms in the human digestive tract. Whether differences in mucosal communities can be related to the etiology of gut disease now needs to be investigated. Further work is also needed to determine how epithelial biofilm communities interact with host immunity and metabolic processes in the mucosa.

ACKNOWLEDGMENTS
This work was funded by the Biotechnology and Biological Sciences
Research Council.

FOOTNOTES
* Corresponding author. Mailing address: Dundee University Gut Group, Ninewells Hospital and Medical School, Dundee DD1 9SY, Scotland, United Kingdom. Phone: 44 1382 632535. Fax: 44 1382 633952. E-mail:
s.macfarlane{at}dundee.ac.uk 
Published ahead of print on 21 September 2007. 

REFERENCES
1 - Akkermans, A. D. L., E. G. Zoetendal, C. F. Favier, H. G. H. J. Heilig, W. M. Akkermans-van Vliet, and W. M. de Vos. 2000. Temperature and denaturing gradient gel electrophoresis analysis of 16S rRNA from human fecal samples. Biosci. Microflora 19:93-98.
2 - Altschul, S. F., W. Gish, W. Miller, E. W. Myers, and D. J. Lipman. 1990. Basic local alignment search tool. J. Mol. Biol. 215:403-410.[CrossRef][Medline]
3 - Amann, R. I., B. J. Binder, R. J. Olson, S. W. Chrisholm, R. Devereux, and D. A. Stahl. 1990. Combination of 16S rRNA-targeted oligonucleotide probes with flow cytometry for analyzing mixed microbial populations. Appl. Environ. Microbiol. 56:1919-1925.[Abstract/Free Full Text]
4 - Anonymous. 2004. Cancer Statistics registrations; registrations of cancer diagnosed in 2001, England. Series MB1, no. 32. Office for National Statistics, London, United Kingdom.
5 - Bartosch, S., A. Fite, G. T. Macfarlane, and M. E. T. McMurdo. 2004. Characterization of bacterial communities in feces from healthy elderly volunteers and hospitalized elderly patients by using real-time PCR and effects of antibiotic treatment on the fecal microbiota. Appl. Environ. Microbiol. 70:3575-3581.[Abstract/Free Full Text]
6 - Bernhard, A. E., and K. G. Field. 2000. Identification of nonpoint sources of fecal pollution in coastal water by using host-specific 16S ribosomal DNA genetic markers from fecal anaerobes. Appl. Environ. Microbiol. 66:1587-1594.[Abstract/Free Full Text]
7 - Child, M. W., A. Kennedy, A. W. Walker, B. Bahrami, S. Macfarlane, and G. T. Macfarlane. 2006. Studies on the effect of system retention time on bacterial populations colonizing a three-stage continuous culture model of the human large gut using FISH techniques. FEMS Microbiol. Ecol. 55:299-310.[CrossRef][Medline]
8 - Eckburg, P. B., E. M. Bik, C. N. Bernstein, E. Purdom, L. Dethlefsen, M. Sargent, S. R. Gill, K. E. Nelson, and D. A. Relman. 2000. Diversity of the human intestinal microbial flora. Science 10:1635-1638.
9 - Finegold, S. M., H. R. Attebery, and V. L. Sutter. 1974. Effect of diet on human fecal flora: comparison of Japanese and American diets. Am. J. Clin. Nutr. 27:1456-1469.[Medline]
10 - Fite, A., G. T. Macfarlane, J. H. Cummings, M. J. Hopkins, S. C. Kong, E. Furrie, and S. Macfarlane. 2004. Identification and quantitation of mucosal and faecal desulfovibrios using real-time PCR. Gut 53:523-529.[Abstract/Free Full Text]
11 - Franks, A. H., H. J. Harmsen, G. C. Raangs, G. J. Jansen, F. Schut, and G. W. Welling. 1998. Variations of bacterial populations in human feces quantified by fluorescence in situ hybridization with group-specific 16S rRNA-targeted oligonucleotide probes. Appl. Environ. Microbiol. 64:3336-3345.[Abstract/Free Full Text]
12 - Gasche, C., J. Scholmerich, J. Brynskov, G. d'Haens, S. B. Hanauer, E. J. Irvine, D. P. Jewell, D. Rachmilewitz, D. B. Sachar, W. J. Sandborn, and L. R. Sutherland. 2000. A simple classification of Crohn's disease: report of the working party for the World Congress of Gastroenterology, Vienna 1998. Inflamm. Bowel Dis. 6:8-15.[Medline]
13 - Gill, S. R., M. Pop, R. T. Deboy, P. B. Eckburg, P. J. Turnbaugh, B. S. Samuel, J. I. Gordon, D. A. Relman, C. M. Fraser-Liggett, and K. E. Nelson. 2006. Metagenomic analysis of the human distal gut microbiome. Science 312:1355-1359.[Abstract/Free Full Text]
14 - Harmsen, H. J. M., A. C. Wildeboer-Veloo, J. Grijpstra, J. Knol, J. E. Degener, and G. W. Welling. 2000. Development of 16S rRNA-based probes for the Coriobacterium group and the Atopobium cluster and their application for enumeration of Coriobacteriaceae in human feces from volunteers of different age groups. Appl. Environ. Microbiol. 66:4523-4527.[Abstract/Free Full Text]
15 - Hopkins, M. J., G. T. Macfarlane, E. Furrie, A. Fite, and S. Macfarlane. 2005. Characterisation of intestinal bacteria in infant stools using real-time PCR and Northern hybridisation analyses. FEMS Microbiol. Ecol. 54:77-85.[CrossRef][Medline]
16 - Horie, H., K. Kanazawa, M. Okada, S. Narushima, K. Itoh, and A. Terada. 1999. Effects of intestinal bacteria on the development of colonic neoplasm: an experimental study. Eur. J. Cancer Prev. 8:237-245.[Medline]
17 - Hugenholtz, P., B. M. Goebel, and N. R. Pace. 1998. Impact of culture-independent studies on the emerging phylogenetic view of bacterial diversity. J. Bacteriol. 180:4765-4774.[Free Full Text]
18 - Hughes, R., and I. R. Rowland. 2003. Nutritional and microbial modulation of carcinogenesis, p. 208-220. In R. Fuller and G. Perdigon (ed.), Gut flora, nutrition, immunity and health. Blackwell Publishing, Oxford, United Kingdom.
19 - Kok, R. G., A. de Waal, F. Schut, G. W. Welling, G. Weenk, and K. J. Hellingwerf. 1996. Specific detection and analysis of a probiotic Bifidobacterium strain in infant feces. Appl. Environ. Microbiol. 62:3668-3672.[Abstract]
20 - Langendijk, P. S., F. Schut, G. J. Jansen, G. C. Raangs, G. R. Kamphuis, M. H. F. Wilkinson, and G. W. Welling. 1995. Quantitative fluorescence in situ hybridization of Bifidobacterium spp. with genus-specific 16S rRNA-targeted probes and its application in fecal samples. Appl. Environ. Microbiol. 61:3069-3075.[Abstract]
21 - Ledder, R. G., P. Gilbert, S. A. Huws, L. Aarons, M. P. Ashley, P. S. Hull, and A. J. McBain. 2007. Molecular analysis of the subgingival microbiota in health and disease. Appl. Environ. Microbiol. 73:516-523.[Abstract/Free Full Text]
22 - Lepage, P., P. Seksik, M. Sutren, M. F. de la Cochetiere, R. Jian, P. Marteau, and J. Dore. 2005. Biodiversity of the mucosa-associated microbiota is stable along the digestive tract in healthy individuals and patients with IBD. Inflamm. Bowel Dis. 11:473-480.[CrossRef][Medline]
23 - Levett, P. N. 1991. Anaerobic microbiology. Oxford University Press, Oxford, United Kingdom.
24 - 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.[CrossRef][Medline]
25 - Linskens, R. K., X. W. Huijsdens, P. H. Savelkoul, C. M. Vandenbroucke-Grauls, and S. G. Meuwissen. 2001. The bacterial flora in inflammatory bowel disease: current insights in pathogenesis and the influence of antibiotics and probiotics. Scand. J. Gastroenterol. 234:29-40.[CrossRef]
26 - Macfarlane, G. T., and A. J. McBain. 1999. The human colonic microbiota, p. 1-25. In G. R. Gibson and M. B. Roberfroid (ed.), Colonic microbiota, nutrition and health. Kluwer Academic Publishers, Doordrecht, The Netherlands.
27 - Macfarlane, G. T., G. R. Gibson, and J. H. Cummings. 1992. Comparison of fermentation reactions in different regions of the human colon. J. Appl. Bacteriol. 72:57-64.[Medline]
28 - Macfarlane, S., E. Furrie, A. Kennedy, J. H. Cummings, and G. T. Macfarlane. 2005. Mucosal bacteria in ulcerative colitis. Br. J. Nutr. 93:S67-S72.[CrossRef][Medline]
29 - Macfarlane, S., E. Furrie, J. H. Cummings, and G. T. Macfarlane. 2004. Chemotaxonomic analysis of bacterial populations colonizing the rectal mucosa in patients with ulcerative colitis. Clin. Infect. Dis. 38:1690-1699.[CrossRef][Medline]
30 - Macfarlane, S., and G. T. Macfarlane. 2004. Bacterial diversity in the human gut. Adv. Appl. Microbiol. 54:261-289.[CrossRef][Medline]
31 - Macfarlane, S., M. J. Hopkins, and G. T. Macfarlane. 2000. Bacterial growth and metabolism on surfaces in the large intestine. Microb. Ecol. Health Dis. 2:64-72.[CrossRef]
32 - Malinen, E., A. Kassinen, T. Rinttila, and A. Palva. 2003. Comparison of real-time PCR with SYBR green 1 or 5'-nuclease assays and dot-blot hybridization with rDNA-targeted oligonucleotide probes in quantification of selected faecal bacteria. Microbiology 149:269-277.[Abstract/Free Full Text]
33 - Manz, W., R. Amann, W. Ludwig, M. Vancanneyt, and K. H. Schleifer. 1996. Application of a suite of 16S rRNA-specific oligonucleotide probes designed to investigate bacteria of the phylum cytophaga-flavobacter-bacteroides in the natural environment. Microbiology 142:1097-1106.[Abstract/Free Full Text]
34 - Maratka, Z. 1986. Pathogenesis and aetiology of inflammatory bowel disease. p. 29-65. In F. T. de Dombal, J. Myrer, I. A. D. Bouchier, and G. Watkinson (ed.), Inflammatory bowel disease. Some international data and reflections. Oxford Medical Publications, Oxford, United Kingdom.
35 - Matsuki, T., K. Wartanabe, J. Fujimoto, T. Takada, and R. Tanaka. 2004. Use of 16S rRNA gene-targeted group-specific primers for real-time PCR analysis of predominant bacteria in human feces. Appl. Environ. Microbiol. 70:7220-7228.[Abstract/Free Full Text]
36 - Moore, W. E., E. P. Cato, and L. V. Holdeman. 1978. Special problems associated with the isolation and identification of intestinal bacteria in fecal flora studies. Am. J. Clin. Nutr. 31:1450-1455.
37 - Muyzer, G., C. Brinkhoff, U. Nübel, C. Santegoeds, H. Schafer, and C. Wawer. 1998. Denaturing gradient gel electrophoresis, (DGGE) in microbial ecology, p. 1-23. In A. D. L. Akkermans, J. D. van Elsas, and F. J. de Bruijn (ed.), Molecular microbial ecology manual, vol. 3. Kluwer Academic Publishers, Doordrecht, The Netherlands.
38 - Muyzer, G., and K. Smalla. 1998. Application of denaturant gradient gel electrophoresis (DGGE) and temperature gradient gel electrophoresis (TGGE) in microbial ecology. Antonie Leeuwenhoek 73:127-141.[CrossRef][Medline]
39 - Nadkarni, M. A., F. E. Martin, N. A. Jacques, and N. Hunter. 2002. Determination of bacterial load by real-time PCR using a broad-range (universal) probe and primer set. Microbiology 148:257-266.[Abstract/Free Full Text]
40 - Poxton, I. R., R. Brown, A. Sawyer, and A. Ferguson. 1997. Mucosa-associated flora of the human colon. J. Med. Microbiol. 46:85-91.[Abstract/Free Full Text]
41 - Riggio, M. P., and A. Lennon. 2002. Development of a PCR assay specific for Peptostreptococcus anaerobius. J. Med. Microbiol. 51:1097-1101.[Abstract/Free Full Text]
42 - Schwiertz, A., U. Lehmann, G. Jacobisch, and M. Blaut. 2002. Influence of resistant starch on the SCFA production and cell counts of butyrate-producing Eubacterium spp. in the human intestine. J. Appl. Microbiol. 93:157-162.[CrossRef][Medline]
43 - Simon, G. L., and S. L. Gorbach. 1984. Intestinal flora in health and disease. Gastroenterology 86:174-193.[Medline]
44 - Tannock, G. W., K. Munro, K. J. M. Harmsen, G. W. Welling, J. Smart, and P. K. Gopal. 2000. Analysis of the fecal microflora of human subjects consuming a probiotic containing Lactobacillus rhamnosus DR20. Appl. Environ. Microbiol. 66:2578-2588.[Abstract/Free Full Text]
45 - Walter, J., G. W. Tannock, A. Tilsala-Timisjarvi, S. Rodtong, D. M. Loach, K. Munro, and T. Alatossava. 2000. Detection and identification of gastrointestinal Lactobacillus species by using denaturant gradient gel electrophoresis and species-specific PCR primers. Appl. Environ. Microbiol. 66:297-303.[Abstract/Free Full Text]
46 - Wang, M., S. Ahrne, B. Jeppsson, and G. Molin. 2005. Comparison of bacterial diversity along the human intestinal tract by direct cloning and sequencing of 16S rRNA genes. FEMS Microbiol. Ecol. 54:219-231.[CrossRef][Medline]
47 - Wang, R. F., W. W. Cao, and C. E. Cerniglia. 1996. PCR detection and quantitation of predominant anaerobic bacteria in human and animal fecal samples. Appl. Environ. Microbiol. 62:1242-1247.[Abstract]
48 - Wilson, K. H., and R. B. Blitchington. 1996. Human colonic biota studied by ribosomal DNA sequence analysis. Appl. Environ. Microbiol. 62:2273-2278.[Abstract]
49 - Zoetendal, E. G., A. von Wright, T. Vilpponen-Salmela, K. Ben-Amor, A. D. Akkermans, and W. M. de Vos. 2002. Mucosa-associated bacteria in the human gastrointestinal tract are uniformly distributed along the colon and differ from the community recovered from feces. Appl. Environ. Microbiol. 68:3401-3407.[Abstract/Free Full Text]
Applied and Environmental Microbiology, November 2007, p. 7435-7442, Vol. 73, No. 22
0099-2240/07/$08.00+0 doi:10.1128/AEM.01143-07
Copyright © 2007, American Society for Microbiology. All Rights Reserved.
This article has been cited by other articles:
-
Hartman, A. L., Lough, D. M., Barupal, D. K., Fiehn, O., Fishbein, T., Zasloff, M., Eisen, J. A.
(2009). Human gut microbiome adopts an alternative state following small bowel transplantation. Proc. Natl. Acad. Sci. USA
106: 17187-17192
[Abstract]
[Full Text]
-
Zoetendal, E G, Rajilic-Stojanovic, M, de Vos, W M
(2008). High-throughput diversity and functionality analysis of the gastrointestinal tract microbiota. Gut
57: 1605-1615
[Abstract]
[Full Text]