1
Microbial dysbiosis in pediatric patients with Crohn’s disease 1
2
3
Nadeem O. Kaakoush1, Andrew S. Day2,3,4, Karina D. Huinao1, Steven T. Leach2, Daniel A. 4
Lemberg3, Scot E. Dowd5, and Hazel Mitchell1* 5
6 1School of Biotechnology and Biomolecular Sciences, The University of New South Wales, 7
Sydney, NSW 2052, Australia 8 2School of Women's and Children's Health, The University of New South Wales, Sydney, 9
Australia 10 3Department of Gastroenterology, Sydney Children's Hospital, Sydney, Australia 11
4Department of Paediatrics, University of Otago, Christchurch, New Zealand 12 5Department of Biology, Texas Tech University, Lubbock, Texas, USA 13
14
Corresponding author: Professor Hazel Mitchell 15
School of Biotechnology and Biomolecular Sciences 16
The University of New South Wales 17
Sydney, NSW 2052 18
Australia 19
Telephone number: +61293852040 20
Fax number: +61293851483 21
Email address: [email protected] 22
23
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Running title: Microbial composition changes and Crohn’s disease 25
26
Keywords: Crohn’s disease, dysbiosis, high-throughput sequencing, 27
Firmicutes, Bacteroides, Proteobacteria 28
Copyright © 2012, American Society for Microbiology. All Rights Reserved.J. Clin. Microbiol. doi:10.1128/JCM.01396-12 JCM Accepts, published online ahead of print on 25 July 2012
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Abstract 29
Microbial dysbiosis has been suggested to be involved in the pathogenesis of Crohn’s 30
disease, however, many studies of gut microbial communities have been confounded by 31
environmental and patient-related factors. In this study, the microbial flora of fecal samples 32
from nineteen children newly-diagnosed with CD and twenty-one age-matched controls were 33
analyzed using high throughput sequencing to determine differences in the microbial 34
composition between CD patients and controls. Analysis of the microbial composition of 35
specific bacterial groups revealed that Firmicutes were significantly lower in CD patients 36
than in controls, and that this was largely due to changes in the class Clostridia. Bacteroidetes 37
and Proteobacteria percentages were higher and significantly higher in CD patients than in 38
controls, respectively. Both the detection frequencies of Bacteroidetes and Firmicutes 39
correlated (positively and negatively, respectively) with the calculated Pediatric Crohn’s 40
Disease Activity Index scores of patients. Upon further analysis, differences in the microbial 41
compositions of patients with mild disease and moderate to severe disease were identified. 42
Our findings indicate that a combination of different bacterial species or a dynamic interplay 43
between individual species is important for disease, and is consistent with the dysbiosis 44
hypothesis of CD. 45
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Introduction 46
Crohn’s disease (CD) is a chronic relapsing idiopathic disease, and together with ulcerative 47
colitis, they are the two most common forms of inflammatory bowel diseases (IBD) (41). CD 48
is a multifactorial disease with unknown etiology. However, it is currently hypothesized that 49
intestinal microorganisms, in association with a disruption of the gastrointestinal epithelium, 50
stimulate and subsequently drive a dysregulated immune response in predisposed individuals 51
(47). 52
53
In recent literature, dysbiosis, a breakdown in the balance between commensal and 54
pathogenic intestinal bacteria, has been suggested to be involved in the pathogenesis of CD. 55
A consistent finding across studies investigating dysbiosis in CD is that, in patients the 56
abundance of members of the Firmicutes is decreased, whereas members of the 57
Proteobacteria (Escherichia coli in particular) are increased than in controls (41). These 58
findings are supported by observations in mouse models of CD where prolific colonization by 59
commensal bacteria, such as Enterobacteriaceae, drives the depletion of other groups such as 60
Firmicutes (39). 61
62
The results observed for CD-related changes in groups such as the Bacteroidetes are however 63
more inconsistent. For example, while Frank et al (21) and Ott et al (45) reported 64
Bacteroidetes to be significantly depleted in CD patients as compared with controls, Rehman 65
et al (46) and Swidsinski et al (53) showed Bacteroidetes to be more prevalent in CD patients 66
as compared with controls. The latter findings are supported by studies examining the 67
intestinal microbiota in the TRUC (T-bet, RAG, ulcerative colitis) mouse model of 68
spontaneous colitis, where bacteria belonging to the order Bacteroidales (phylum 69
Bacteroidetes) were reported to be present in high numbers (23). Furthermore, Rehman et al 70
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have reported the transcriptional activity of Bacteroidetes to be significantly increased in 71
patients with CD as compared with controls (46). 72
73
While the current literature on dysbiosis and CD provides significant insights into microbial 74
changes associated with CD, the data has not been consistent. Possible factors for these 75
inconsistencies include differences in the techniques employed to survey the intestinal 76
microbiota, study design, the stage of disease and its location, and the control populations 77
used. To avoid potential confounding factors associated with previous studies in adults, 78
including previous treatment with antibiotics or anti-inflammatory therapies, differences in 79
stage of disease, smoking and alcohol intake, we conducted the current study in children 80
newly diagnosed with CD who had not undergone prior antibiotic or anti-inflammatory 81
therapy for CD and age- matched controls. 82
83
Materials and Methods 84
Patients 85
Twenty-two symptomatic children undergoing diagnostic colonoscopy and upper endoscopy 86
at the Sydney Children’s Hospital Randwick (Sydney, Australia) were included in the study. 87
Based upon standard endoscopic, histologic, and radiologic investigations (24), 19/22 88
children (12 male, mean age: 11.6 ± 2.5 years) were newly diagnosed with ileo-colonic CD 89
with upper-gut involvement. The Pediatric Crohn’s Disease Activity Index (PCDAI) ranged 90
from 7.5 – 70 (Table 1). Of the remaining three children, one was diagnosed with reflux 91
esophagitis (female, 12.2 years), one duodenal ulcer disease (male, 13.1 years), and the 92
remaining child was diagnosed with a functional bowel disorder (male, 11.7 years). 93
94
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Along with the three children who underwent colonoscopy and who were not diagnosed with 95
IBD, 18 healthy children were also included in the study as controls. These 21 control 96
children with no histological features of IBD comprised 13 males and had a mean age of 9.5 97
± 4.2 years (P=0.07). 98
99
No child involved in this study had undergone prior antibiotic or anti-inflammatory therapy 100
in the previous four weeks. Informed consent was obtained from all children (or their 101
parent/guardian for younger children) to be included in the study. This study was approved 102
by the Research Ethics Committees of the University of New South Wales and the South East 103
Sydney Area Health Service-Eastern Section, Sydney (Ethics No.: 03/163, 03/165 and 104
06/164). Fecal samples were collected from each child prior to colonoscopic examination. 105
106
DNA extraction and microbial community sequencing 107
DNA extraction was performed using the ISOLATE Fecal DNA Kit (Bioline) according to 108
the manufacturer’s instructions. The concentration and quality of DNA was measured using a 109
Nanodrop ND-1000 Spectophotometer (Nanodrop Technologies; Wilmington, USA). 110
111
The microbial community was assessed by high-throughput sequencing of the 16S rRNA 112
gene. Tag-encoded FLX amplicon pyrosequencing (bTEFAP) was performed as described 113
previously using the primers Gray28F (5’TTTGATCNTGGCTCAG) and Gray519r (5’ 114
GTNTTACNGCGGCKGCTG) (2, 3, 20, 26) with the primers numbered in relation to E. coli 115
16S rRNA (variable regions 1-3). The sequence of the primers is not complementary to 116
human DNA, thus preventing co-amplification of human sequences. Moreover, the primers 117
span the variable region of the rRNA gene so that discrimination between closely related taxa 118
can be performed. At the same time, the positioning of the primers allows for amplification of 119
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a large proportion of known 16S rRNA sequences. Generation of the sequencing library 120
utilized a one-step PCR with a total of 30 cycles, a mixture of Hot Start and HotStar high 121
fidelity taq polymerases, and amplicons originating and sequencing extending from the 28F 122
with an average read length of 400 bp. Tag-encoded FLX amplicon pyrosequencing analyses 123
utilized a Roche 454 FLX instrument with Titanium reagents. This bTEFAP process was 124
performed at the Molecular Research laboratory (MR DNA; Shallowater, TX) based upon 125
established and validated protocols (http://www.mrdnalab.com/). 126
127
Data analysis 128
The sequence data derived from the high-throughput sequencing process was analyzed 129
employing a pipeline developed at Molecular Research LP (www.mrdnalab.com). Sequences 130
are first depleted of barcodes and primers, then short sequences <200 bp, sequences with 131
ambiguous base calls, and sequences with homopolymer runs exceeding 6 bp are all 132
removed. Sequences were then de-noised and chimeras were removed (Black Box Chimera 133
Check software B2C2, n = 2129). Operational taxonomic units (OTU) were defined after 134
removal of singleton sequences (sequences appearing only once in the whole dataset) with 135
clustering set at 3% divergence (97% similarity) (9, 14-17, 19, 51). OTU were then 136
taxonomically classified using BLASTn against a curated GreenGenes database (12) and 137
compiled into each taxonomic level. Taxonomy was defined based on the following 138
percentages: >97%, species; between 97% and 95%, unclassified species; between 95% and 139
90%, unclassified genus; between 90% and 85%, unclassified family; between 85% and 80%, 140
unclassified order; between 80% and 77%, unclassified phylum; <77%, unclassified. 141
Statistical analyses based on relative abundances of bacterial groups were performed using 142
Primer-E (http://www.primer-e.com/). Permutational multivariate analysis of variance 143
(PERMANOVA) (1), which overcomes multiple hypothesis testing, was performed to detect 144
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overall group differences between CD patients and controls. The hypothesis of the test was 145
“Are there differences in Bray-Curtis similarities between bacterial communities of CD 146
patients and controls?” In order to explore for key variables, differences in relative 147
abundances of bacterial taxa between CD patients and controls were tested using standard t-148
tests. Upon stratification of CD patients into mild and moderate/severe groups, a one-way 149
ANOVA with a post hoc Tukey’s correction was used to correct for multiple testing. 150
Although examining the multivariate significance of the data provides some protection 151
against increased chance of type I error, it is still likely that comparisons may achieve 152
statistical significance by chance. 153
154
Results and Discussion 155
Evidence to support the role of microorganisms in the pathogenesis of CD has been 156
demonstrated in both humans and animals (41). However, the specific microorganism or 157
group of microorganisms responsible for the initiation of CD are yet to be determined. Thus, 158
in an attempt to gain a better understanding of microbial involvement in CD, we examined 159
the microbial flora in fecal samples of children newly diagnosed with CD and age-matched 160
controls, as this population is relatively free of confounding factors. 161
162
The mean number of sequences per sample obtained for the 40 subjects in this study 163
following data analysis was 2609 ± 138 sequences. To check for sampling bias arising from 164
grouping the subjects into CD patients and controls, the number of sequences per sample 165
within each group was analyzed. The mean number of sequences per sample for CD patients 166
and controls were 2716 ± 220 and 2513 ± 174 sequences, respectively, and this difference 167
was not statistically significant (P=0.47), indicating that no sampling bias due to the grouping 168
existed. 169
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170
Differences in microbial compositions of the control subjects 171
Principal component analysis was performed on the detection frequencies obtained for the 172
control subjects in order to identify any outliers that could influence downstream analyses. 173
Two subjects were shown to be outliers with respect to the other controls (Figure 1). 174
Interestingly, one of these outliers was the control subject diagnosed with a functional bowel 175
disorder. Upon more specific analysis of the detection frequencies in this child, it was found 176
that they had a high Actinobacteria count (17.1%), which was due to a putative 177
Mycobacterium peregrinum infection (14.8%; 0% in all other subjects). Although M. 178
peregrinum has yet to be clearly associated with human disease, this bacterium has been 179
related to surgical site infections and catheter-related infections (44). Interestingly, infection 180
with M. peregrinum was reported to be the cause of an outbreak of mycobacteriosis in an 181
aviary containing Gouldian finches (Erythrura gouldiae) where affected birds developed 182
granulomatous lesions of the liver and intestine (54). Another study reported that exposure of 183
zebrafish to M. peregrinum led to clinical signs of mycobacteriosis (27). The second outlier 184
(Figure 1, Figure S1) was a healthy control that was found to have an unusually high level of 185
Bacteroidetes (63.8%) that was shown to result from high levels of Prevotella copri (55.2%). 186
Although P. copri has been previously isolated from human feces (28), no studies have 187
associated this bacterium with any specific disease outcome. It is unknown why this healthy 188
control had such high levels of P. copri within their fecal microbial composition. Given these 189
anomalies these two outliers were excluded from further multivariate and univariate 190
comparisons with CD patients. Thus, for the final fecal microbiota comparisons 19 control 191
children (12 males) and 19 children with CD (12 males) were included. 192
193
Variations in microbial compositions between patients with Crohn’s disease and controls 194
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Analysis of the microbial composition of CD patients and controls revealed that as a whole 195
error values within the detection frequencies of CD patients were relatively higher than that 196
within the controls (percentage standard errors on the three major phyla Firmicutes, 197
Bacteroidetes and Proteobacteria were 11.6%, 26.7% and 38.2% for CD patients and 3.0%, 198
21.8% and 31.2% for controls, respectively) indicating that higher variations existed among 199
individual CD patients than among controls. Despite this, PERMANOVA analysis showed 200
that differences between CD patients and the remaining 19 controls were significant 201
(P=0.015), and several taxa were found to be significantly different in abundance in CD 202
patients as compared with controls using univariate analyses. 203
204
Firmicutes 205
Analysis of the microbial composition for specific bacterial groups revealed that Firmicutes 206
were significantly lower in CD patients as compared with controls (P=0.0035) (Table 2, 207
Figure 2). This shift in Firmicutes was found to be largely due to changes in the detection of 208
class Clostridia (and order Clostridiales) that was significantly lower in CD patients than in 209
controls (P=0.0009) (Table 2). The decrease in relative abundance of members of the 210
Firmicutes in the children with CD is consistent with recent findings on microbial 211
composition changes in CD patients (41). For example, Rehman et al showed Firmicutes to 212
be significantly lower in patients with CD (52.7%) as compared with healthy controls 213
(78.6%; P<0.01) (46). 214
215
Three families (Clostridiaceae, Lachnospiraceae and Ruminococcaceae) were found to have 216
varying relative abundances when the two subject groups were compared. Clostridiaceae 217
specifically members of the Clostridium genus, which comprises several important 218
pathogens, were numerically higher in CD patients than controls (Table 2), although this was 219
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not significant (P=0.29). In contrast, Lachnospiraceae were higher in controls than in CD 220
patients (Table 2), however, again this did not reach significance (P=0.11). Closer analysis of 221
this family showed that two genera Coprococcus and Roseburia (P=4.4 x 10-5 and P=0.031, 222
respectively) were driving the results (Table 2). Species of interest (those with significantly 223
different relative abundances between CD patients and controls) were Roseburia faecis, 224
Coprococcus eutactus and Coprococcus Clostridium sp. SS2/1 (Table 2). 225
226
Ruminococcaceae were found to be significantly higher in controls than in CD patients 227
(P=0.0033). These results were partly due to significant differences in Oscillospira (P=0.033) 228
and Subdoligranulum (P=0.0029). Unlike previous observations in adult patients (41, 48), 229
where significantly lower abundances of Faecalibacterium prausnitzii have been reported in 230
CD patients as compared with controls, no significant difference in Faecalibacterium 231
prausnitzii was observed between the CD children as compared with controls (P=0.20). 232
Although, the frequency in CD children was lower than that in controls (Table 2). 233
Interestingly, F. prausnitzii is believed to be an anti-inflammatory commensal bacterium, 234
which when decreased in abundance increases the risk of CD recurrence (49). Our contrasting 235
findings may reflect differences in the immunomodulatory roles of the gut microflora in 236
adults and children, and/or the fact that our patients were newly diagnosed with the disease. 237
238
One CD patient (CD9) who had a relatively high Firmicutes count (92.2%) as compared with 239
other CD patients (average: 57.9 ± 6.7%) was found to have unusually high counts of 240
Streptococcus spp. including S. parasanguinis (30.9%), S. thermophilus (30.3%) and S. oralis 241
(8.3%). Streptococcus spp. have been previously associated with CD, with Streptococcal 242
DNA being identified in CD patients but not in healthy controls (25). 243
244
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Bacteroidetes 245
In the current study, numerically higher percentages of Bacteroidetes were observed in CD 246
patients as compared with that in controls (P=0.086) (Table 2, Figure 2). The drop in 247
Firmicutes detection levels correlated with the increase in Bacteroidetes (CD: r17 = -0.71, 248
P=0.0006; controls: r17 = -0.82, P<0.0001). Similar correlations were observed when 249
comparing the detection frequencies of Bacteroidia, Bacteroidales and Bacteroidaceae in CD 250
patients and controls. The only genus within Bacteroidaceae showing consistent results in its 251
detection frequency between CD patients and controls that was close to significance was 252
Bacteroides (P=0.065) (Table 2). While the difference between the CD patients and controls 253
improved statistically from the phylum to genus level (P=0.086 to 0.065), it still did not reach 254
significance (discussed further below). As reported previously by Swidsinski et al (52), the 255
Bacteroides within each patient were not represented by a single species but by multiple 256
species. The change in the level of bacteria from the phylum Bacteroidetes was of particular 257
interest given the study by Bloom et al (5) who showed common commensal Bacteroides 258
species such as Bacteroides vulgatus and Bacteroides thetataiotaomicron to colonize IBD-259
susceptible and -nonsusceptible mice equivalently, but to induce disease exclusively in 260
susceptible animals. 261
262
Fusobacteria 263
In the current study, Fusobacteria were detected in 8/19 CD patients (patient CD2 having a 264
high detection frequency of 29.2%) and 1/19 controls, with the one positive control patient 265
being the control diagnosed with duodenal ulcer disease (Fusobacterium canifelinum). None 266
of the healthy controls had Fusobacteria. The species detected in our CD patients were 267
Fusobacterium equinum (n=2), Fusobacterium canifelinum (n=3), Fusobacterium nucleatum 268
(n=1), Fusobacterium periodonticum (n=1) and the misclassified (10) Clostridium rectum 269
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(n=1). Fusobacterium nucleatum, which was detected in patient CD14, has been recently 270
associated with colorectal carcinoma (34). Moreover, Strauss et al (50) isolated 271
Fusobacterium spp. from a significantly higher number of IBD (CD, n=17; UC, n=4; IBD-272
unclassified, n=1) patients (15/22, 68.2%) compared with non-IBD controls (9/34, 26.5%). 273
Interestingly, these authors found that Fusobacterium strains originating from inflamed 274
biopsy tissue of IBD patients were significantly more invasive than strains isolated from 275
healthy tissue from either IBD patients or control patients (50). 276
277
Actinobacteria 278
The frequency of members of the phylum Actinobacteria was similar in both the CD and 279
control subjects (P=0.88) (Table 2, Figure 2). However, in one CD patient (CD6) a very high 280
Actinobacteria count (22.2%) was noted, which was shown to be due to the presence of two 281
species Collinsella aerofaciens (8.2%) and Bifidobacterium longum (9.9%). Interestingly, 282
Swidsinski et al (52) have previously reported a preferential increase in the frequency of C. 283
aerofaciens in IBD patients. Moreover, the frequency of members of the order 284
Actinomycetales was higher in CD patients than controls (Table 2), and these bacteria were 285
detected in 13/19 CD patients in comparison to 5/19 controls. However, these differences 286
were not significant (P=0.19). 287
288
Proteobacteria 289
In the current study Proteobacteria percentages were significantly higher in CD patients than 290
in controls (P=0.040) (Table 2, Figure 2). Further analysis revealed that the detection rates of 291
Proteobacteria were mostly driven by γ-Proteobacteria detection (P=0.056) (Table 2). 292
293
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The increased detection of γ-Proteobacteria in CD patients resulted from the detection of 294
Enterobacteriales (P=0.058), specifically Escherichia (P=0.062) and Enterobacter (P=0.061) 295
(Table 2). The specific species detected within the Escherichia genus based on our BLAST 296
sequence analyses of the pyrosequencing reads were Escherichia coli, Escherichia fergusonii 297
and Escherichia albertii. Interestingly, previous studies have reported adherent and invasive 298
E. coli (AIEC) to be associated with ileal CD, with one study reporting the isolation of AIEC 299
in 22% of ileal biopsy samples from CD patients as compared with 6.2% of controls (11). 300
Moreover, a further study has reported the isolation of AIEC in 29% of CD patients as 301
compared with 9% of controls (42). While E. coli was detected in our CD patients, whether 302
this is an AIEC strain cannot be ascertained. Within the Enterobacter genus, only one species 303
Enterobacter hormaechei was detected in our CD patients. While the detection rate in CD 304
patients was higher than in controls (Table 2), this did not quite reach significance (P=0.059). 305
306
One CD patient (CD11) who was found to have very high Proteobacteria counts (77.4%), was 307
found to possibly have an unclassified Citrobacter infection (46.2%). This is of some interest 308
given that in mice Citrobacter rodentium infection has been shown to elicit a highly polarized 309
Th1 response including up-regulation of interleukin-12, interferon-γ and tumor necrosis 310
factor alpha, and a pathology very similar to that found in mouse models of inflammatory 311
bowel disease (29). More recently, Th17 cells have been implicated in C. rodentium 312
infections (37), a finding which is of interest considering the Th17 response has also been 313
implicated in the development of Crohn’s disease (6). 314
315
The Klebsiella species K. granulomatis and K. variicola were detected in 4 and 5 CD 316
patients, respectively and 0 controls, although in one control Klebsiella pneumoniae was 317
detected. In 2009 Gutierrez et al reported Klebsiella DNA to be present in the blood of one 318
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CD patient but not in any healthy controls (25). Moreover, the presence of K. pneumoniae has 319
been correlated with colitis in a genetically deficient mouse model (23), although this is not 320
supported by our findings. 321
322
In 2008, Wagner et al used a genus specific bacterial 16S PCR as well as nested PCR to 323
investigate the prevalence and diversity of Pseudomonas species in ileal biopsies of 32 324
children with CD at initial endoscopic examination, as well as in control children with non-325
inflammatory bowel disease (non-IBD) (55). This showed that 58% of CD patients 326
demonstrated positive results for Pseudomonas spp., which was significantly higher than for 327
non-IBD controls (33%). In the current study, members of the Pseudomonadaceae were 328
detected in 5 CD patients (26.3%) and in no controls. Further analysis revealed that 329
Pseudomonas balearica was the species detected only in the CD patients. 330
331
While a higher abundance of α-Proteobacteria was detected in CD patients as compared with 332
controls (Table 2), this difference was not significant (P=0.13). Comparison of the order 333
Rhizobiales (detected in 10/19 CD patients vs. 0/19 controls) showed a significantly higher 334
abundance in CD patients than in controls (P=0.0033) (Table 2). Bradyrhizobiaceae (detected 335
in 6/19 CD patients vs. 0/19 controls) within the Rhizobiales also showed a significantly 336
higher abundance in CD patients than controls (P=0.045) (Table 2). The species identified 337
were an unclassified Balneimonas (n=3) and Afipia broomae (n=3). Other α-Proteobacteria 338
species identified were Methylobacterium adhaesivum (n=2) and Methylobacterium 339
hispanicum (n=2) (within Methylobacteriaceae), Aurantimonas coralicida (n=2) (within 340
Aurantimonadaceae), Rhodoplanes cryptolactis (n=1) and Gemmiger formicilis (n=1) (within 341
Hyphomicrobiaceae), and Rhizobium spp. IRBG 74 (n=1) (within Rhizobiaceae). While it 342
appears that A. broomae may be an opportunistic pathogen in elderly people (7), the higher 343
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abundance of α-Proteobacteria in CD patients is more likely to have resulted from changes in 344
the gut environment of patients (eg. higher methane production and higher reactive nitrogen 345
species production) as these bacteria tend to be environmental rather than host-related. 346
347
ß-Proteobacteria were also higher in abundance in CD patients than controls, the predominant 348
order detected being Burkholderiales (Table 2). Three species of interest were detected within 349
this order, Cupriavidus gilardii (4 CD patients vs. 0 controls), Massilia timonae (5 CD 350
patients vs. 0 controls) and Paucimonas lemoignei (4 CD patients vs. 0 controls). C. gilardii 351
is not known for its pathogenicity, however, it has been reported to infect humans, in one 352
case causing fatal sepsis following the dissemination of an infection with intestinal focus 353
(33). M. timonae has also been reported to infect humans, being isolated from blood, 354
cerebrospinal fluid, and bone samples (36). Interestingly, Neisseriales were detected in 6 CD 355
patients and in 1 control, the species detected being Eikenella corrodens (3 CD patients vs. 0 356
controls) and an unclassified Vogesella (3 CD patients vs. 1 control). 357
358
δ-Proteobacteria, which have been associated with IBD (38), were detected in four CD 359
patients (CD3, CD5, CD6 and CD12) and no controls. The bacteria were identified as an 360
unclassified Entotheonella (belonging to Entotheonellales) (CD3 and CD5), Bilophila 361
wadsworthia (belonging to Desulfovibrionales) (CD6 and CD12) and an unclassified 362
Haliangium (belonging to Myxococcales) (CD6). Both Entotheonella spp. and Haliangium 363
spp. appear to be environmental bacteria with no association with human disease (8, 22). In 364
contrast, B. wadsworthia has been associated with human infections including appendicitis 365
and cholecystitis (4). 366
367
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Bacteria from the class ε-Proteobacteria were detected in two patients (CD1 and CD8) and no 368
controls. The bacterium was identified as Campylobacter concisus, a species recently been 369
associated with IBD (32, 41). Interestingly, C. concisus strains isolated from chronic 370
intestinal diseases such as CD have been shown to be more invasive than strains isolated 371
from acute intestinal disease and healthy subjects (31, 40). 372
373
Possible bacterial species associated with initiating and driving CD in the 19 CD patients in 374
this study are detailed in Table 3. These bacteria were chosen based on their previous 375
association with CD in other studies, their pathogenic potential in humans or their relative 376
abundance in CD patients versus controls in this study. 377
378
Effect of age and gender on microbial composition 379
While age has been reported to affect the intestinal microbial composition in infants or old 380
people (18) in the current study no correlation between microbial composition and age was 381
observed, and this may relate to the fact that the children were not infants and had a fairly 382
narrow age range. While Lay et al (35) and Dicksved et al (13) have both reported no 383
significant correlation between microbial composition and age, Mueller et al (43) reported 384
both Enterobacteria and Bacteroides-Prevotella detection levels to be influenced by the 385
subject’s age. In addition to age, a number of previous studies have also investigated the 386
effect of gender on the fecal microbial composition of subjects. In the current study the 387
detection frequencies of Firmicutes, Bacteroidetes and Proteobacteria were compared in 388
females and males in both the CD patients and controls. This showed that although 389
Bacteroidetes appeared to be higher in females (both CD patients and controls) and 390
Proteobacteria appeared to be higher in males (both CD patients and controls), no statistical 391
difference was observed between females and males within either subject subgroup (Table 4). 392
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393
Associations between the inflammatory index of Crohn’s disease patients 394
As one of the key hallmarks of CD is chronic inflammation, the microbial composition of 395
patients was assessed with respect to their calculated PCDAI at diagnosis. Correlation 396
analysis revealed that there existed a strong positive correlation between the detection 397
frequencies of Bacteroidetes and the calculated PCDAI scores of each patient (r17 = 0.544, 398
P=0.016) (Figure 3). In contrast, a negative correlation was identified between the detection 399
frequencies of Firmicutes and PCDAI (r17 = -0.425, P=0.070) (Figure 3), however, this did 400
not reach significance. 401
402
Due to the observed correlation between microbial composition and PCDAI, patients were 403
stratified into two groups consisting of mild disease (PCDAI < 30) and moderate to severe 404
disease (PCDAI ≥ 30) (30). This categorization of CD patients based on disease activity 405
revealed that Bacteroidetes were present at significantly higher levels in moderate to severe 406
disease (31.8 ± 9.5%) than controls (11.1 ± 2.4%, P=0.021), whereas patients with mild 407
disease (12.1 ± 5.7%) had similar levels to controls (P=0.99) (Figure 4). The finding that 408
Bacteroidetes were similar in patients with mild disease and controls, would suggest that their 409
abundance is either as a result of inflammation or is driving inflammation. Interestingly, 410
Firmicutes were present at numerically lower levels in mild (63.0 ± 10.3%, P=0.15) and 411
significantly lower levels in moderate to severe disease (53.3 ± 9.0%, P=0.0097) than in 412
controls (80.0 ± 2.4%) (Figure 4), suggesting that inflammation may have a negative effect 413
on Firmicutes or that changes in the Bacteroidetes and Proteobacteria (below) may affect 414
their abundance. Of particular interest was the finding that Proteobacteria were present at 415
higher levels in mild (18.1 ± 8.7%) compared with moderate to severe disease (4.6 ± 1.5%, 416
P=0.070) and controls (1.6 ± 0.5%, P=0.0085) (Figure 4). Given the higher levels of 417
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Proteobacteria in patients with mild disease as compared with moderate/severe disease, this 418
may suggest that this group could play a role in the initiation of the disease. 419
420
Conclusions 421
In conclusion, significant differences in the microbial composition of patients with CD and 422
controls were detected, highlighting specific bacterial groups that may be associated with 423
disease outcome. Furthermore, the observed correlation between specific bacterial groups and 424
patient PCDAI emphasizes the involvement of these groups in initiating or driving 425
inflammation, and possibly the disease. 426
427
We propose the hypothesis (Figure 5) whereby an invasive pathogen (possibly a member of 428
the Proteobacteria) capable of surviving intracellularly (as evidenced by the association 429
between autophagy and CD) establishes an infection in patients. Defective pathogen sensing 430
and reduced ability for pathogen clearance by the host (47) results in a chronic intracellular 431
infection. As a result of a dysregulated immune response, chronic inflammation occurs, 432
which is driven by the dysbiotic intestinal microflora, and in particular Bacteroides species. 433
Following treatment, disease remission occurs, however, re-infection leads to relapse of the 434
disease. 435
436
Acknowledgements 437
This work was made possible by the support of the National Health and Medical Research 438
Council, Australia and The University of New South Wales Goldstar award. NOK is 439
supported by an Early Career fellowship from the National Health and Medical Research 440
Council, Australia. 441
No conflicts of interest exist. 442
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634
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Figure legends 635
Figure 1 636
Principal component analysis of the bacterial community compositions of the control 637
subjects. 638
639
Figure 2 640
Bacterial diversity observed in Crohn’s disease patients and age-matched controls. 641
Differences in detection frequencies of bacterial phyla between CD patients (gray) and 642
controls (white). Firmicutes (CD patients: 57.9 ± 6.7%, controls: 80.0 ± 2.4%, P=0.0035); 643
Proteobacteria (CD patients: 11.0 ± 4.2%, controls: 1.6 ± 0.5%, P=0.040); Bacteroidetes (CD 644
patients: 22.5 ± 6.0%, controls: 11.1 ± 2.4%, P=0.086); Actinobacteria (CD patients: 3.2 ± 645
1.2%, controls: 3.4 ± 0.8%, P=0.88). Error bars are the standard error of the mean. 646
647
Figure 3 648
Correlations between detection frequencies of Firmicutes and Bacteroidetes and patient 649
PCDAI. Firmicutes, black (r17 = -0.425, P=0.070); Bacteroidetes, grey (r17 = 0.544, 650
P=0.016). 651
652
Figure 4 653
Microbial composition of patients with mild CD, moderate/severe CD and in controls. 654
A, Bacteroidetes; B, Firmicutes; C, Proteobacteria. 655
656
Figure 5 657
Proposed mechanism of initiation and recurrence of Crohn’s disease. 658
659
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Table captions 660
Table 1 661
Characteristics of children with Crohn’s disease included in the study, the location of 662
their disease and their PCDAI at diagnosis. 663
Patient Age (years) Gender Disease location PCDAICD1 9 F L3 + L4 (ileocolon) 7.5 CD2 12 F L3 + L4 (ileocolon) 57.5 CD3 14 M L3 + L4 (ileocolon) 45 CD4 13 M L3 + L4 (ileocolon) 22.5 CD5 14 M L3 + L4 (ileocolon) 52.5 CD6 15 F L3 + L4 (ileocolon) 52 CD7 14 F L3 + L4 (ileocolon) 25 CD8 9 M L3 + L4 (ileocolon) 35 CD9 10 M L3 + L4 (ileocolon) 20 CD10 13 M L3 + L4 (ileocolon) 20CD11 14 M L3 + L4 (ileocolon) 27.5 CD12 15 M L3 + L4 (ileocolon) 37.5 CD13 9 M L3 + L4 (ileocolon) 27.5 CD14 8.6 M L3 + L4 (ileocolon) 25 CD15 11.4 F L3 + L4 (ileocolon) 37.5 CD16 13 F L3 + L4 (ileocolon) 70 CD17 8.7 M L3 + L4 (ileocolon) 10 CD18 7.2 M L3 + L4 (ileocolon) 42.5 CD19 11 F L3 + L4 (ileocolon) 52.5
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Table 2 665
Differences in detection frequencies of bacterial groups between CD patients and controls. 666
Phylum Class Order/Family Genus Species CD (%) Controls (%) P-value Firmicutes 57.9 ± 6.7 80.0 ± 2.4 0.0035* Clostridia 49.6 ± 7.3 77.4 ± 2.4 0.0009* Clostridiaceae 10.3 ± 4.1 5.7 ± 1.4 0.29 Clostridium 14.4 ± 3.9 8.8 ± 1.1 0.21 Lachnospiraceae 18.0 ± 5.7 30.8 ± 4.6 0.11 Coprococcus 0.93 ± 0.26 5.1 ± 0.8 4.4 x 10-5* Roseburia 4.4 ± 1.8 10.4 ± 2.0 0.031* Roseburia faecis 1.5 ± 0.7 4.5 ± 0.9 0.016* Coprococcus eutactus 0.025 ± 0.017 0.95 ± 0.29 0.0045* Coprococcus Clostridium sp. SS2/1 0.33 ± 0.13 2.4 ± 0.7 0.012* Ruminococcaceae 15.0 ± 3.0 27.4 ± 2.2 0.0033* Oscillospira 0.26 ± 0.16 1.8 ± 0.6 0.033* Subdoligranulum 0.68 ± 0.45 3.5 ± 0.7 0.0029* Faecalibacterium prausnitzii 9.9 ± 2.4 14.1 ± 2.2 0.20 Bacteroidetes 22.5 ± 6.0 11.1 ± 2.4 0.086 Bacteroides 19.6 ± 5.4 8.4 ± 2.3 0.065 Actinobacteria 3.2 ± 1.2 3.4 ± 0.8 0.88 Actinomycetales 0.24 ± 0.12 0.069 ± 0.031 0.19 Proteobacteria 11.0 ± 4.2 1.6 ± 0.5 0.040* γ-Proteobacteria 9.6 ± 4.1 1.1 ± 0.5 0.056 Enterobacteriales 9.2 ± 4.3 0.71 ± 0.36 0.058 Escherichia 3.2 ± 1.4 0.29 ± 0.16 0.062 Enterobacter 2.3 ± 1.0 0.13 ± 0.05 0.061 Enterobacter hormaechei 2.3 ± 1.0 0.11 ± 0.05 0.059 α-Proteobacteria 0.34 ± 0.13 0.10 ± 0.08 0.13 Rhizobiales 0.10 ± 0.03 0 0.0033* Bradyrhizobiaceae 0.036 ± 0.016 0 0.045* ß-Proteobacteria 1.0 ± 0.3 0.43 ± 0.19 0.12 Burkholderiales 0.91 ± 0.28 0.42 ± 0.19 0.11
*P<0.05 667
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Table 3 668
Possible bacterial species associated with initiating and driving Crohn’s disease in the 669
CD patients in this study. These bacteria were chosen based on their previous association 670
with CD in other studies, their pathogenic potential in humans or their relative abundance in 671
CD patients versus controls in this study. 672
Patient Possible agents associated with disease CD1 Campylobacter concisus; Pseudomonas balearica; Cupriavidus gilardii CD2 Fusobacterium equinum (27.4%); Klebsiella spp. CD3 Cupriavidus gilardii; Pseudomonas balearica; Massilia timonae;
Fusobacterium equinumCD4 Ruminococcus torques (21.1%) CD5 Klebsiella variicola; Escherichia fergusonii; Bacteroides spp. (73.7%);
Fusobacterium canifelinum CD6 Massilia timonae; Escherichia fergusonii; Bilophila wadsworthia; Collinsella
aerofaciens (8.2%); Fusobacterium canifelinum CD7 Cupriavidus gilardii; Pseudomonas balearica; Massilia timonae; Escherichia
fergusonii; Clostridium difficile (6.5%) CD8 Campylobacter concisus; Clostridium difficile (24.7%); Cupriavidus gilardii;
Pseudomonas balearica; Massilia timonae; Klebsiella spp.; Escherichia fergusonii
CD9 Streptococcus spp. (74.0%) CD10 Klebsiella spp.; Escherichia fergusonii; Bacteroides spp. (50.2%);
Fusobacterium canifelinumCD11 Citrobacter unclassified (46.2%); Escherichia fergusonii; Klebsiella spp.;
Pseudomonas balearica; Massilia timonae CD12 Bilophila wadsworthia; Fusobacterium canifelinum CD13 Clostridium difficile (2.2%) CD14 Escherichia coli; Shigella sonnei; Fusobacterium nucleatum; Fusobacterium
periodonticum; Peptostreptococcus anaerobius (13.9%) CD15 Unusual α-Proteobacteria detected CD16 Escherichia coli; Shigella sonnei; Bacteroides spp. (56.3%) CD17 Escherichia coli; Shigella sonnei CD18 Bacteroides spp. (30.0%) CD19 Clostridium rectum (Fusobacteria); Bacteroides spp. (57.1%);
Parabacteroides spp. (19.1%) 673
674
675
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Table 4 676
Effect of gender on the detection frequencies of three bacterial phyla. 677
Subjects Gender Bacterial detection frequencies (%) Firmicutes P-value Bacteroidetes P-value Proteobacteria P-value CD patients Female 53.9 0.66 26.6 0.61 6.8 0.47 Male 60.2 20.1 13.5 Controls Female 80.2 0.95 13.5 0.45 0.47 0.085 Male 79.9 9.6 2.3
678
679
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1.2
1.0
0 6
0.8
nent
2
0.4
0.6
Com
pon
0.2
0.0-1.2 -1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4
-0.2Component 1
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90 P = 0.0035
70
80
50
60
ncy
(%)
40
ectio
n fr
eque
n
P = 0.086
20
30
Det
e
P = 0.040
0
10 P = 0.88
Bacteroidetes Firmicutes Proteobacteria ActinobacteriaPhylum
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100
80
90
60
70
uenc
y (%
) Firmicutes
40
50
tect
ion
freq
u
20
30Det
i
0
10Bacteroidetes
0 10 20 30 40 50 60 70 80
PCDAI
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30354045
ncy
(%)
A
51015202530
etec
tion
freq
uen
05
Controls Mild CD Moderate and severe CD
D
8090
%)B
304050607080
n fr
eque
ncy
(%
0102030
Controls Mild CD Moderate and severe CD
Det
ectio
n
C
20
25
30
quen
cy (%
)
0
5
10
15
Det
ectio
n fr
eq
0Controls Mild CD Moderate and severe CD
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1 I fe tio by i a i e atho e1. Infection by invasive pathogen
3. Reduced ability for pathogen clearance (Autophagy defect)
11. Relapse
2. Defective pathogen sensing
clearance (Autophagy defect)
5. Dysregulated immune response4. Chronic intracellular infection
6. Dysbiosis
7. Chronic inflammation10. Remission 7. Chronic inflammation
8. Crohn’s disease
9. Treatment
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