Analysis of Mucosal Microbiota in Inflammatory Bowel Disease using a Custom Phylogenetic Microarray

Special Article-Inflammatory Bowel Disease

Austin J Gastroenterol. 2014;1(4): 1020.

Analysis of Mucosal Microbiota in Inflammatory Bowel Disease using a Custom Phylogenetic Microarray

Arun Gupta1,2*, Seungha Kang3, Josef Wagner4, Carl Kirkwood4, Mark Morrison3, Chris McSweeney3 and Finlay Macrae5

1Gastroenterology and Hepatology Unit, the Canberra Hospital, Australia

2The University of Melbourne, Australia

3CSIRO Livestock Industries, St Lucia

4Enteric Viruses Unit, Murdoch Childrens Research Institute, Australia

5Department of Colorectal Medicine and Genetics, Royal Melbourne Hospital, Australia

*Corresponding author: : Arun Gupta, Department of Gastroenterology, The Canberra Hospital, Post Box: 11, Woden, Australian Capital Territory, 2606, Australia

Received: August 11, 2014; Accepted: September 09, 2014; Published: September 12, 2014


Background and Aims: The pathogenesis of inflammatory bowel disease is likely to involve interaction between genetic factors, innate immunity, and the enteric microbiota. Alterations in the composition of the normal commensal microbiota may play a pathogenic role.

Methods: A custom 2240 probe oligonucleotide microarray based on 16s RNA sequences was used to compare the microbiota profiles of patients with inflammatory bowel disease with controls. Twenty mucosal samples obtained from colonoscopic biopsies were analysed - five from Crohn’s Disease Inflamed (CDI) tissue, five from Crohn’s Disease Non-Inflamed (CDNI), five from Ulcerative Colitis (UC), and five healthy control samples. Analysis was performed using principal components analysis and between group analysis.

Results: The microbiota from both Crohn’s disease and ulcerative colitis differed significantly from the control group, though not between CDI and CDNI groups. Alterations in the abundance of Faecalibacterium prausnitzii, Shigella flexneri, Dorea longicatena, and Xenorhabdus bovienii were associated with Crohn’s disease. Alterations in the abundance of Yersinia pestis and Eubacterium rectale were associated with ulcerative colitis.

Conclusion: The gastrointestinal microbiota differed in mucosal samples from patients with inflammatory bowel disease compared to those taken from controls. The composition of the microbiota was not altered by the presence of inflammation. The abundance of particular organisms including the previously described F. prausnitzii was found to be different in patients with inflammatory bowel disease compared to healthy controls, and new putative aetiological organisms were identified. These findings support the hypothesis that a bacterial ‘dysbiosis’ may contribute to the pathogenesis of inflammatory bowel disease.

Keywords: Microbiota; Microarray; Inflammatory bowel disease; Crohn’s disease; Ulcerative colitis


Crohn’s disease and ulcerative colitis are inflammatory disorders of the gastrointestinal tract, which can cause significant morbidity in patients. Treatment is often with medications affecting the immune system, with the aim of reducing gastrointestinal inflammation. Advances in genetics and microbiology have shed light on factors that are likely to be playing a role in pathogenesis of these inflammatory bowel diseases. Single nucleotide polymorphisms affecting genes relating to the innate immune system have been associated with inflammatory bowel disease (IBD), including mutations of the NOD2, TLR4, IL23R and ATG16L1genes [1-4]. Functional studies have shown that some of these genes affect bacterial sensing within the gastrointestinal tract, possibly affecting immunological tolerance and disrupting the delicate homeostasis between the mucosal lining of the gut and the bacterial microbiota [5-8].

The role of the bacterial microbiota within the gastrointestinal tract in IBD is less well characterised. Many studies have suggested a role for individual organisms playing a role in initiation or perpetuation of IBD, such as Mycobacterium avium subspp. Paratuberculosis (MAP) and adherent-invasive Escherichiacoli (AIEC) [9-11]. Although found in increased abundance in patients with IBD in many studies, the evidence to support a pathogenic role for these organisms has been inconsistent, possibly due to differing tissues being analysed, differing specimen handling and analysis techniques, and different populations being studied. A multi-centre trial assessing patients with Crohn’s disease treated empirically for MAP with clarithromycin, rifabutin and clofazimine did not reach the primary outcome of decreased rate of relapse [12].

An alternative hypothesis to the single pathogen hypothesis is that alterations in the composition of the normal gastrointestinal microbiota (also termed ‘dysbiosis’) may play a pathogenic role in IBD. Traditional microbiological techniques have been based on culture of organisms on nutrient rich plates, however approximately 80% of organisms in the gastrointestinal tract are not able to be cultured ex vivo [13]. Molecular techniques based on the bacterial 16s ribosomal RNA ‘fingerprint’ can identify these culture negative bacteria, and can be used to categorise previously undiscovered bacteria into the bacterial taxonomy. Techniques to analyse the microbiota including Temporal Temperature Gradient gel Electrophoresis (TTGE), Denaturing Gradient Gel Electrophoresis (DGGE), Automated Ribosomal Intergenic Spacer Analysis (ARISA) to generate microbial community ‘profiles’, as well as metagenomic approaches where the entire library of organisms in a particular community are catalogued and described [13-17]. Different studies comparing the microbiota in IBD compared to controls have assessed the microbiota in mucosal samples, faecal samples and surgical resection specimens. The current study aims to assess the difference in microbiota in mucosal samples from patients with IBD compared to controls using a custom built 2240 probe microarray based on 40-mer 16s ribosomal RNA oligonucleotides.

Materials and Methods

Recruitment & Sample collection

Approval was obtained from the human research ethics committees at Melbourne Health, Melbourne Private Hospital and Cabrini Health (HREC.2006.267). Patients aged between eighteen and eighty years of age who were already scheduled for a colonoscopy were recruited after informed consent was obtained. Patients were recruited from two separate groups, the first comprising patients without a diagnosis of IBD who were planned for a colonoscopy to investigate diarrhoea, and the second group with a pre-existing diagnosis of IBD. Patient epidemiology was collected, and phenotype was recorded if the patient was known to have IBD.

Mucosal biopsies were collected at the time of colonoscopy from both inflamed and non-inflamed areas. Biopsy specimens were transferred immediately to tubes containing RNA later buffer (Applied Bio systems, Austin, Texas, USA) and then frozen. DNA extraction was later performed from these samples in accordance with previously described methods [18]. A total of 109 samples were collected from 35 patients. A subset of samples were analysed as part of this study; five samples from the Crohn’s Disease Inflamed (CDI) group, five from Crohn’s Disease Non-Inflamed (CDNI), five from Ulcerative Colitis (UC) and five from the control group. The control group comprised of patients who had a normal colonoscopy and normal histopathology.

Oligonucleotide probe design and microarray preparation

Between group analyses between all four groups

A custom phylogenetic microarray was designed and validated according to the methods described by Kang et al. (2010) [19]. Briefly, the probes based on 16s ribosomal RNA sequences from gastrointestinal bacteria identified on the Entre z Nucleotide database situated on the National Centre for Biotechnology Information (NCBI) website were included. The particular oligonucleotides selected were derived from a literature search of published papers [20,21] Individual probes were then designed using the Go Array oligonucleotide program [22]. The resultant 40-mer oligonucleotide probes represented diverse taxonomy groups, with differing specificities ranging from species to phylum levels; the majority were targeted at the species level. These were synthesised on to a custom 4X2K probe microarray by Combimatrix (USA). The microarray was synthesized with four replicates of each probe distributed across the array to allow validation of results. Samples were analysed as per the Combimatrix hybridisation and imaging protocol. Resultant microarray images were analysed using Gene Pix Pro 6.0 software [23,24].

Statistical analysis

The microarray data were normalized using the quantile normalization method, then analysed using the R statistical environment [25,26]. The four different groups were compared using betweengroup analysis (BGA), correspondence analysis (CoA), and Monte-Carlo tests. These were performed using the multivariable analysis, ADE4 and MADE4 software packages [26-29].The analysis is classified as a ‘supervised’ microarray analysis in that different groups were defined beforehand. The Monte-Carlo permutation test was used to generate P values for differences between samples.


20 samples were analysed using the microarray platform; 5 from the CDI group, five from the CDNI group, 5 from the UC group and 5 control samples.

Between group analyses between all four groups

Between Group Analysis (BGA) suggested significant separation between the four sample groups analysed, Crohn’s Disease Inflamed (CDI), Crohn’s Disease Non-Inflamed (CDNI), Ulcerative Colitis (UC) and controls when comparing all bacterial species (Figure 1). The principal components analysis of the four groups was analysed using a Monte Carlo test, giving a p-value of 0.005.