Disturbances in metabolic, transport and structural genes in experimental colonic inflammation in the rat: a longitudinal genomic analysis
© Martínez-Augustin et al; licensee BioMed Central Ltd. 2008
Received: 09 May 2008
Accepted: 17 October 2008
Published: 17 October 2008
Trinitrobenzenesulphonic acid (TNBS) induced rat colitis is one of the most widely used models of inflammatory bowel disease (IBD), a condition whose aetiology and pathophysiology are incompletely understood. We have characterized this model at the genomic level using a longitudinal approach. Six control rats were compared with colitic animals at 2, 5, 7 and 14 days after TNBS administration (n = 3). The Affymetrix Rat Expression Array 230 2.0 system was used.
TNBS-induced colitis had a profound impact on the gene expression profile, which was maximal 5 and 7 days post-induction. Most genes were affected at more than one time point. They were related to a number of biological functions, not only inflammation/immunity but also transport, metabolism, signal transduction, tissue remodeling and angiogenesis. Gene changes generally correlated with the severity of colitis. The results were successfully validated in a subset of genes by real-time PCR.
The TNBS model of rat colitis has been described in detail at the transcriptome level. The changes observed correlate with pathophysiological disturbances such as tissue remodelling and alterations in ion transport, which are characteristic of both this model and IBD.
Inflammatory bowel disease (IBD), comprising ulcerative colitis and Crohn's disease, is characterized by chronic and relapsing inflammation of the gastrointestinal tract. The pathogenesis of IBD is unknown, but it appears to be multifactorial in origin, and genetic, environmental and dietary factors are believed to be involved . Animal models of IBD have been central to the investigation of the pathophysiology of the disease and are valuable tools for drug testing and development. Because IBD-like diseases do not occur spontaneously in animals, several animal models that mimic different aspects of the disease are currently used, including gene knockout, transgenic, chemical, adoptive transfer and spontaneous models . To date, no single model has reproduced all features of the human disease. One of the most widely used models in both pharmacological and pathophysiological studies (72 in the past year) is murine colitis induced by trinitrobenzenesulphonic acid (TNBS) [3–5]. This simple model is based on a single rectal administration of TNBS dissolved in ethanol. TNBS is a hapten that elicits an immune response when bound to tissue proteins, while ethanol contributes to disruption of the intestinal barrier. The result is a severe and prolonged degenerative inflammation of large parts of the colon sharing several clinical and molecular characteristics with Crohn's disease. Specifically, the inflammation produced by the administration of TNBS-ethanol involves all layers of the intestinal mucosa and produces long-lasting damage with cell infiltration and ulcers, including protracted physiological dysfunction. Furthermore, both TNBS-ethanol administration to mice and human Crohn's disease are characterized by Th1-driven inflammation with infiltration of macrophages and neutrophils, producing high levels of proinflammatory cytokines such as tumour necrosis factor, interleukin (IL)-1β and IL-6, followed by T cell infiltration, mainly of the CD4+ phenotype.
Genomic profiling of disease models is of interest for characterizing the pathological response at transcriptome level and identifying putative drug targets. Animal models may overcome many of the limitations of the application of genomic technology to humans, including the need for repeated encoscopy, the large genetic and phenotypic variability, and the difficulty of studying the initial stages of the disease. There have been a few attempts at gene expression profiling in IBD models [6–10]. In general, these studies have addressed acute colitis (48–72 h after induction), employed small microarrays (containing 87 and 1252 transcripts in two of the studies), have analysed large samples (augmenting internal genomic variation, which occurs along the longitudinal axis) and include modest validation experiments (6–14 genes). Although a recent study by te Velde et al.  used 20,000 transcript microarrays, the data were not validated. Only one of the studies was longitudinal . Therefore, the present study represents the most ambitious and comprehensive investigation to date, using several microarrays to examine the progression of colitis at four time points, employing a genechip platform that includes more than 30,000 transcripts (Affymetrix Rat 230 2.0). Results were validated in a subset of almost 100 transcripts by using real-time PCR (qRT-PCR). The full results database, publicly accessible, will serve as a valuable reference for all researchers in the field. In fact, three pharmacological studies adopting this strategy are currently underway in our laboratory.
All reagents were obtained from Sigma (Barcelona, Spain) except where indicated.
Female Wistar rats (175–225 g) were used, housed in makrolon cages and maintained in air-conditioned animal quarters with a 12-h light-dark cycle. Animals had free access to tap water and were fed a standard chow diet (Panlab A04, Panlab, Barcelona, Spain). This study was carried out in accordance with the Directive for the Protection of Vertebrate Animals used for Experimental and other Scientific Purposes of the European Union (86/609/EEC), was approved by the Ethical Committee of the University of Granada and complies with the American Physiological Society's Guiding Principles in the Care and Use of Animals.
Induction of colitis
Colitis was induced as previously described . Briefly, rats were fasted overnight and anaesthetized with halothane. Under these conditions, rats were given 10 mg of TNBS dissolved in 0.25 ml of 50% ethanol (v/v) by means of a Teflon cannula inserted 8 cm into the anus. Rats were kept in a head-down position for an additional 30 s and returned to their cages.
Rats were randomly assigned to one of two different groups, a control (C, n = 6) group that received a saline enema and a TNBS group (n = 12) that received the TNBS challenge. Food and water intake and body weight were determined daily. To follow the progression of the colitis, three rats of the TNBS group were killed 2, 5, 7 and 14 days after the induction of colitis. Three control rats were killed on day 2 and the other three at the end (day 14) of the experiment. For the purpose of postgenomic validation, this experiment was repeated in order to perform qRT-PCR analysis on fresh samples. The magnitude and time course of the inflammatory response were similar in both experiments (data not shown).
Assessment of colonic damage
Animals were killed by cervical dislocation, and the entire colon was removed and placed on an ice-cold plate, cleaned of fat and mesentery, and blotted on filter paper. Each specimen was weighed and its length measured under a constant load (2 g). The large intestine was longitudinally opened and scored for visible damage on a 0 to 25 scale as previously described . A sample for genomic analysis was obtained from the distal colon approximately 4.5 cm proximal to the anus, taking care to avoid any areas of necrosis. The colon was subsequently divided longitudinally into several pieces for biochemical determinations. The fragments were immediately frozen in liquid nitrogen and kept at -80°C until used. Myeloperoxidase activity was measured according to the technique described by Krawisz et al. .
RNA extraction, microarray hybridization and data analysis
RNA was extracted from homogenized full-thickness colonic tissues in Trizol® reagent (Invitrogen) and purified with RNeasy affinity columns (Qiagen). Quantity and integrity of RNA were assessed by spectrophotometry and 0.8% agarose gel electrophoresis, respectively. Sample labelling, hybridization, staining and scanning procedures were carried out using Affymetrix standard protocols http://www.affymetrix.com. The microarray analysis was performed by Progenika Biopharma (Bilbao, Spain) on 18 GeneChip® Rat Expression Array 230 2.0 microchips (Affymetrix). Normalization and statistical analyses were carried out using GeneSpring v7.1 (Agilent). Gene ontology analysis was performed with GeneMapp/MappFinder http://www.genmapp.org. Specifically, biological process, cellular component and molecular function categories were scored with respect to the number of genes included in the Rattus norvegicus database that were measured in the microarray and the number of genes significantly affected by TNBS colitis in each category. The resulting z parameter  has positive values when the proportion of genes affected is higher than expected, and it was used to select the most representative gene ontology categories (i.e. those with z ≥ 4) at each time point. Non-redundant categories are shown, listing only the highest z value when nested categories exceeded the cutoff value at multiple levels. The k-means algorithm was applied to identify and group transcript changes over time in clusters. Only sequences with annotated gene identities that were present (intensity > 100 units) in at least 66% of samples per group in at least one group were considered. The data were analyzed by analysis of variance followed by Tukey post-hoc tests in order to reduce the false positive or type I error rate in inter-group comparisons. In addition, the Benjamini & Hochberg false discovery rate correction was applied to reduce the occurrence of type I error when comparing among genes. This procedure offers a reasonable balance between sensitivity and specificity. Data are expressed as fold change (mean ± SEM) over the control (uninflamed) group (n = 6) at each time point (TNBS colitis after 2, 5, 7 or 14 days). MIAME recommendations  were followed to ensure that all information needed to understand, interpret, reproduce and compare our results was given in detail. The data are accessible at the the European Bioinformatics Institute Arrayexpress database (http://www.ebi.ac.uk, reference E-MEXP-873).
Postgenomic validation was carried out by measuring 93 of the genes in fresh samples (n = 3 per group) using qRT-PCR with TaqMan® Low Density Arrays (Applied Biosystems). Genes were selected to include both significantly and non-significantly changed genes pertaining to different families affected by inflammation, i.e., those related to transport, immunity or metabolism. The relative Ct values of each gene with respect to the reference gene (18S) were used to calculate the RQ (relative quantitation) parameter, which represents the change in mRNA expression compared to a control sample. The RQ was then used to calculate fold change ratios. Results are expressed as mean ± SEM.
2340 genes were significantly modified at 2 days after TNBS instillation (1238 upregulated, 1102 downregulated). This number was almost doubled at day 5 (4266, 2073 of which were upregulated) and rose to 5752 (2356 upregulated) by day 7. The pool of altered gene expression fell to 1953 by day 14 (1146 upregulated), coinciding with a marked recovery from the inflammatory bout. The dendogram in Figure 2 shows that samples from TNBS colitic rats at each time point were clustered together, forming groups that significantly differed from control samples. As expected, many of the genes that showed significant changes are directly related to the inflammatory response, including genes for chemokines, cytokines and inflammatory markers such as Cp, Ptgs2, or Lyz (see below).
Gene ontology categories most affected by TNBS colitis at different time points
Gene ontology category
Positive regulation of anti-apoptosis
Phosphoinositide 3-kinase complex
1-Phosphatidylinositol 3-kinase activity
Unfolded protein binding
Immune system process
Response to external stimulus
Antigen processing and presentation of peptide antigen via MHC class II
Lymphocyte mediated immunity
Response to other organism
Cytokine biosynthetic process
Positive regulation of lymphocyte differentiation
Protein amino acid dephosphorylation
Regulation of inflammatory response
T cell differentiation
Peptide antigen transport
Regulation of protein binding
MHC class II protein complex
Mitochondrial respiratory chain
Haematopoietin/interferon-class (D200-domain) cytokine receptor activity
Protein tyrosine phosphatase activity
NADH dehydrogenase activity
Peptide antigen-transporting ATPase activity
Immune system process
Response to external stimulus
Antigen processing and presentation of exogenous peptide antigen
Extracellular matrix part
Proteinaceus extracellular matrix
Extracellular matrix constituent
Prophyrin catabolic process
DNA damage response, signal transduction by p53 class mediator
Glial cell migration
Positive regulation of interferon-gamma production
Cytokine biosynthetic process
External side of plasma membrane
B cell receptor complex
Double-stranded DNA adenosine deaminase activity
Interleukin 1, Type I receptor binding
DNA ligase (ATP) activity
Heme oxygenase (decyclizing) activity
Saccharopine dehydrogenase (NAD+, L-glutamate-forming) activity
Thyroid hormone receptor activity
Cannabinoid receptor activity
Time course analysis
Genes modulated specifically at day 2
Major histocompatibility complex, class II, DM beta
F-box and leucine-rich repeat protein 7 (predicted)
Acyl-CoA thioesterase 12
Prolactin family 8, subfamily a, member 2
Adenylate cyclase activating polypeptide 1 receptor 1
Sp2 transcription factor
Vitelliform macular dystrophy 2-like protein 1 (predicted)
Corticotropin releasing hormone
Frizzled homolog 4 (Drosophila)
Insulin-like growth factor binding protein 5
Ataxia, cerebellar, Cayman type (caytaxin) (predicted)
Phosphatidylinositol 3-kinase, C2 domain containing, gamma polypeptide
Flavin containing monooxygenase 2
Solute carrier family 13 (sodium-dependent citrate transporter), member 5
Extra cellular link domain-containing 1 (predicted)
Vacuolar protein sorting 4a (yeast)
Complement component 1, q subcomponent binding protein
Exosome component 2 (predicted)
Mitogen-activated protein kinase kinase kinase 6 (predicted)
Resistin like alpha
Cysteine and glycine-rich protein 2
Doublesex and mab-3 related transcription factor like family A1 (predicted)
Retina and anterior neural fold homeobox
Insulin degrading enzyme
Opioid-binding protein/cell adhesion molecule-like
WD repeat domain 22 (predicted)
Neuro-oncological ventral antigen 1
Fibroblast growth factor 20
Alcohol dehydrogenase 6 (class V)
Candidate plasticity gene 1
Glycoprotein hormone alpha 2
Myelin transcription factor 1-like
Neuropeptide FF receptor 2
Neuronal calcium binding 2
Carbonyl reductase 3 (predicted)
Alkaline phosphatase 1, intestinal, defined by SSR
Glycoprotein 2 (zymogen granule membrane)
CD248 antigen, endosialin (predicted)
Protein tyrosine phosphatase, receptor type, f polypeptide (PTPRF), interacting protein (liprin), alpha 3
Zinc finger protein 580 (predicted)
Pituitary tumour-transforming 1 interacting protein
Genes modulated specifically at day 14
T-box 15 (predicted)
Thyrotropin releasing hormone receptor
Protein phosphatase 3 (formerly 2B), catalytic subunit, gamma isoform (calcineurin A gamma)
Eukaryotic translation initiation factor 2 alpha kinase 3
Histamine receptor H3
Kruppel-like factor 15
Glycine dehydrogenase (decarboxylating; glycine decarboxylase, glycine cleavage system protein P) (predicted)
Galanin receptor 1
Chymase 1, mast cell
Transcriptional regulating factor 1 (predicted)
Serpine1 mRNA binding protein 1
Leukotriene B4 12-hydroxydehydrogenase
Fibroblast growth factor 1
Angiotensin 1 converting enzyme
Eukaryotic translation initiation factor 4A1
Adenosine deaminase, RNA-specific
Damage-specific DNA binding protein 1
Muscleblind-like 1 (Drosophila)
Leucine zipper, putative tumour suppressor 1
High mobility group AT-hook 1
Striatin, calmodulin binding protein
Cell division cycle 2-like 5 (cholinesterase-related cell division controller)
Sorting nexin associated golgi protein 1 (predicted)
Serine (or cysteine) proteinase inhibitor, clade A, member 3M
Ankyrin 1, erythroid (predicted)
Histone 1, h1t
Insulin-like growth factor 2, binding protein 1
Calcium channel, voltage-dependent, gamma subunit 7
RNA binding motif protein 9 (predicted)
Dystrophin-related protein 2 A-form splice variant
Eukaryotic translation initiation factor 4 gamma, 1
Wilms tumor 1
PQ loop repeat containing 2 (predicted)
Cannabinoid receptor 1 (brain)
LIM domain only 3
Brain-specific angiogenesis inhibitor 3 (predicted)
Sp3 transcription factor
Amyloid beta (A4) precursor protein-binding, family A, member 1
Potassium voltage gated channel, Shaw-related subfamily, member 3
Actin alpha cardiac 1
Wingless-type MMTV integration site family, member 11
UDP-N-acetyl-alpha-D-galactosamine:polypeptide N-acetylgalactosaminyltransferase 2 (predicted)
Chondroitin sulphate proteoglycan 4
Zinc finger protein 503 (predicted)
RNA binding motif (RNP1, RRM) protein 3
Membrane protein, palmitoylated 5 (MAGUK p55 subfamily member 5) (predicted)
Plasticity related gene 1
Casein kinase 1, delta
Genes involved in the inflammatory response
The prostaglandin biosynthetic pathway was strongly activated by TNBS through the concerted induction of Pla2g2a, Ptgs2, and Ptges, especially during the chronic phase (confirmed by qRT-PCR, data not shown). Other affected genes are related to cell adhesion, bacteria binding or reactive oxygen species generation. There were also marked changes in the expression of numerous transcripts involved in antioxidative defence, most of which were downregulated.
In addition, close examination of the expression level of a number of genes that act as inflammatory cell markers indicated the nature of the inflammatory infiltrate. Thus, TNBS colitis was characterized by an absence of significant changes in markers of T cells (Thy1, Tcrb, Tcrg, Zap70, Lck), B cells (Ptprc -B220-, Ms4a1 -Cd20-, Cd22, Cd79b) and NK cells (Baat, Ncam1 -Cd56-, B3gat1 -Cd57-). In contrast, several neutrophil/macrophage markers such as S100a8, Itgb2 (Cd18), Cd68_predicted, Csf1r, Cybb, Csf2rb1 and Lcn2 were significantly increased by inflammation, especially at days 5 and 7.
Genes involved in metabolism
With regard to lipid metabolism, the fatty acid biosynthetic enzymes Fasn and Scd1 were inhibited, as was the related gene Acly. Several transcripts related to cholesterol biosynthesis and transport were also affected (Hmgcr, Srebf1, Bzrp, Dhcr7, Dhcr24, Apoa1, Abca1). In addition, both ApoE and the apolipoprotein B mRNA editing gene Apobec1 were upregulated, suggesting a higher lipoprotein biosynthesis, although ApoE may also play a protective role against lipopolysaccharide . A number of other metabolic pathways appeared to be altered by TNBS colitis, including purine de novo biosynthesis, arginine and heme catabolism.
Genes involved in signalling
The signalling-related genes that exhibited the highest changes in expression included Gp49b and Plek. Gp49b encodes an immunoglobulin-like receptor expressed in myeloid cells that appears to counter-regulate the cytokine and chemokine attraction of neutrophils . The function of Plek appears to be related to the regulation of macrophage phagocytosis .
Genes involved in transport
Genes involved in tissue remodelling
The main features of the TNBS model of colitis have been well defined. Ethanol causes direct toxic damage to the epithelium, which in turn grants TNBS access to the colonic mucosa, where it acts as a hapten. Although the toxic effect of ethanol is a requisite for TNBS to act effectively, the immunogenic nature of the 'chronic' phase has been unequivocally established by various authors [23–25]. Without TNBS, ethanol produces only a short-lived inflammatory reaction that resolves without sequelae and was therefore not of interest in the present study. During the 'chronic' phase, TNBS rat colitis shares a number of features in common with IBD, e.g., transmural inflammation (Crohn's disease only), abnormal ion transport, diarrhoea, fibrosis and abnormal intestinal motility. Furthermore, TNBS rat colitis is amenable to treatment with corticoids, sulfasalazine or tacrolimus, making it an attractive model for the preclinical testing of putative IBD drugs. Our aim was to perform a detailed genomic characterization of the model.
The TNBS colonic inflammatory response was characterized by a marked increase in the expression of multiple genes involved in inflammation/immunity, including cytokines, chemokines, adhesion molecules, eicosanoid-related genes, and a number of effectors and cell markers. There was a dramatic increase in Il1b, Il1a, Il6, Tgfb1 and Tnf and in various chemokine and chemokine receptors. In addition, a nonsignificant increase was observed in the pivotal Il23a and Ifng cytokine genes, which was found to be significant after re-examination using the more sensitive qRT-PCR. Although no protein data are avaliable, it is tempting to speculate that the combined upregulation of Il23a, Il6 and Tgfb1 are indicative of Th17 induction . In fact, although Il17a was not represented in the microarray, qRT-PCR findings showed an increase in the mRNA levels (data not shown), suggesting the involvement of Th17 cells in rat TNBS colitis. A contribution of Th1 cells is also likely in view of the Ifng upregulation and lack of Il4 changes, although Il12a and Il12b were not augmented. Our group  and other authors [28, 29] previously reported an increase in the IFN-γ or IFN-γ/IL-4 protein ratio in this model. A staggering increase was observed in some of the genes, e.g. S100a9/S100a8, suggesting that they may be highly sensitive markers to follow intestinal inflammation, as previously observed in humans [30, 31]. These genes encode proteins expressed by macrophages and neutrophils and are involved in bacterial defence, chemotaxis and signalling [32, 33].
Analysis of the microarray data offered insights into the nature of the inflammatory infiltrate. TNBS colitis was previously characterized at this level . In brief, macrophages and neutrophils are initially recruited to the colonic mucosa and submucosa, followed by a more predominant role of lymphocytes in later stages of colitis, which are characterized by progressive healing, reepithelialization, crypt enlargement and prominent fibrosis . The predominance of neutrophils/macrophages in the inflammatory response was confirmed in our study by the global increase in gene markers of these cell types and the absence of effects on B, T and NK cells (at significance level of p < 0.05). It should be noted that the sample used for genomic analysis did not include lymphoid follicles, in which lymphocytes accumulate in this model , which explains the lack of a significant increase. However, gene ontology analysis indicated that lymphocyte differentiation was already prominent at day 5.
Our data also revealed important changes that were not directly linked to inflammation/immunity. Thus, marked alterations were found in metabolism-related genes, indicating a reduced functionality of numerous biochemical pathways, including glycolysis, purine biosynthesis, Krebs cycle, cholesterol biosynthesis and transport, fatty acid biosynthesis and respiratory chain. Taken together, these data demonstrate a decrease in biosynthesis of macromolecules, an increase in catabolism, and a decrease in aerobic and anaerobic respiration. Therefore, mucosal cells may be have inadequate energy resources during the inflammatory response. Similar changes have been reported in IBD patients  and in experimental colitis .
A number of genes encoding ion transporters were affected by TNBS colitis, including: Atp1a1, encoding the catalytic subunit of the Na+/K+ pump; Scnn1a, encoding the alpha polypeptide of the epithelial sodium channel; Nhe1, encoding the housekeeping Na+/H+ exchanger; and Slc12a2, encoding Nkcc2, the Na+/K+/Cl- cotransporter. These were generally downregulated, as were the transporters involved in NaCl absorption, e.g., Nhe2, Nhe3, and Slc26a3. However, Cftr was unchanged. These modifications are consistent with severe alterations of ionic transport, as demonstrated in IBD and animal models [17, 36, 37].
A striking finding of our analysis was the vast number of upregulated genes involved in tissue remodelling in TNBS colitis, generally during the chronic phase, as indicated by the gene ontology analysis. The chronic phase is characterized by mucosal wound healing and submucosal fibrosis and by the scarring and deposition of excess muscular tissue, extending through day 14 and eventually leaving sequelae . These features are often detectable by the naked eye as colonic shortening, deformation and rigidity. Two features are related to the intestinal fibrosis suffered by IBD patients: an increase in collagen synthesis by smooth muscle cells, fibroblasts and myofibroblasts, and an increase in muscle layer thickness. IGFBP-5 expression is known to increase in ulcerative colitis, while IGF-1 and TGF-β1 expression is known to increase in both ulcerative colitis and Crohn's disease [38, 39]. These molecules have been related to extracellular matrix remodelling and may therefore be relevant to the fibrosis observed in IBD. Our results are in agreement with these IBD findings, showing an increase in Igf1, Igfbp5 and Tgfb1 expression in the inflamed colon. Hence, the TNBS model may be appropriate for the study of molecular mechanisms implicated in the development of fibrosis in intestinal inflammation. In addition, expressions of procollagen/collagen genes, most notably Tgm1, and of several enzymes related to collagen processing were increased in the TNBS colitic animals.
Our results include some intriguing findings, including: the severe repression of nuclear receptors Nr1d1 and Nr1d2, involved in circadian expression patterns and recently shown to be regulated by heme ; the synthesis and marked upregulation of Tg in the inflamed colon; and the downregulation of the thyroid receptor. Further experiments are warranted to clarify the role of these changes in colonic inflammation.
We were especially interested in establishing a correlation between the known characteristics of the model and the time course of gene expression. Because the time points selected cover all stages of the TNBS-induced inflammatory response, from acute (2 d) to chronic (5–7 d) and healing/recovery (14 d) phases, we expected to find substantial differences in the pattern of expression. For instance, genes involved in inflammation/immunity and tissue regeneration were expected to predominate in the early and late stages, respectively. However, the vast majority of transcripts followed a common trend, namely a change of expression that was maximal at days 5 and 7, when colitis is most prominent, and was normal (or almost normal) at day 14. Hence, there is a close correlation between the pathological features of TNBS colitis and the changes observed in the transcriptome. The genes that were up- or downregulated only at days 2 or 14 did not conform to any specific category. Some of the transcripts involved are of interest. Thus, Retnla, which encodes resistin-like alpha, which is dramatically repressed soon after colitis induction, may be involved in monocyte activation, as is the beta isoform . Both Ace and Cma1, which encode enzymes with angiotensin I cleaving capacity, are induced specifically at day 14. Some specific receptors involved in cellular signalling are differentially regulated, such as Galr1, Hrh3, Npffr2 and Cnr1. Further analysis is warranted to explore the implications of these findings.
Despite using a technical approach (triplicate samples per time point) that meets or surpasses common standards in genomic studies, we carried out more than 1100 qRT-PCR determinations in 15 additional samples for a posteriori data validation. As expected, the overall correlation was excellent. In some cases, microarray analysis appeared to be less prone to pick up statistically significant variations, i.e. it was less sensitive than qRT-PCR. The fact that we examined four different time points adds to the complexity of the analysis, since a marked change at one time point may not be enough in many cases to reach significance in the ANOVA. Further validation is provided by the fact that the changes (or lack thereof) observed in many genes, including Il1b, Il1rn, Cftr, Tnf, Alpl, Alpi, Ifng, Il4, Il6, Pgts2, Nos2 and Ccl2, among many others, are in line with previous observations from our own group, either at the RNA or protein level [12, 18, 27].
Previous studies have examined changes in the transcriptome in intestinal inflammation, especially in mouse colitis elicited by TNBS and other manoeuvres [6–10]. These studies are somewhat limited because they either use small microarrays, examine animals shortly after colitis induction (consistent with acute but not chronic colitis), offer limited or no postgenomic validation or use longitudinal tissue samples. One of these studies addressed the time course of gene expression, but it studied recovery from repeated TNBS challenges . In general, the changes in gene expression documented in the present study are much stronger and wider than those found in previous reports. For example, 175 genes were differentially expressed in the above study in compared to the thousands of genes in our investigation. On the other hand, there have been several human IBD microarray studies [30, 31, 42–47], which have detected some key gene expression changes associated with human intestinal inflammation, including some specifically linked to either ulcerative colitis or Crohn's disease . However, it is poorly understood how genomic data are related to IBD pathology and therapy, partly because of the variability inherent to human studies and partly because of methodological differences . For instance, the most important source of variation in gene expression measurement (54%) is the microarray platform itself , and all of the above studies used different arrays. There are also differences in design and especially in sample selection, i.e., individual vs. pooled or mucosal vs. full thickness. Nevertheless, there are some similarities with the rat TNBS model, including increases in Chi3l1, Mmp3, 10 and 12, Apoe, S100a8, Ltb, Sod2, Cxcl1, Cxcl2, Il6 and many other genes.
We have characterized the rat TNBS model of IBD at the genomic level, obtaining novel data on individual genes, metabolic pathways and biological functions that are altered during colitis. These findings establish a basis for further mechanistic studies on drug action and research into the pathophysiology of intestinal inflammation. The full genomic database will serve as a reference standard for all future investigations using this model and for comparisons with other animal models of colitis, an approach that is currently being applied in our laboratory.
inflammatory bowel disease
quantitative real time PCR
The authors acknowledge the technical help of Dietmar Fernández and David Arteta from Progenika Biopharma and the assistance of the European Bioinformatics Institute. This study was supported by the Instituto de Investigación Carlos III (PI051651, PI051625), the Spanish Junta de Andalucía (ARM/LD 43035), the Ministry of Industry, and Fundación Genoma España.
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