Transcriptional profiling of Clostridium difficile and Caco-2 cells during infection (original) (raw)

. Author manuscript; available in PMC: 2011 Jul 15.

Published in final edited form as: J Infect Dis. 2010 Jul 15;202(2):282–290. doi: 10.1086/653484

Abstract

Clostridium difficile is well recognized as the most common infectious cause of nosocomial diarrhea. The incidence and severity of C. difficile infection (CDI) is increasing worldwide. Here, we examined the transcriptional changes in the human colorectal epithelial Caco-2 cells and C. difficile simultaneously following the infection. A total of 271 transcripts in Caco-2 cells and 207 transcripts in C. difficile were significantly differentially-expressed in at least one time point during CDI. We utilized the gene ontology annotations and protein-protein network interactions to underline a framework of target molecules that could potentially play a key role during CDI. These genes included those associated with cellular metabolism, transcription, transport, cell communication, and signal transduction. Our data identified certain key factors that have previously been reported to be involved in CDI as well as novel determinants that may participate in a complex mechanism underlying host response to infection, bacterial adaptation and pathogenesis.

Keywords: Clostridium difficile, infection, microarray, expression profiling, transcriptome

Introduction

Clostridium difficile is an anaerobic spore-forming rod-shaped gram-positive bacterium that can infect both humans and animals. It causes a spectrum of clinical manifestations from mild diarrhea to severe pseudomembranous colitis and has been recognized as a major nosocomial pathogen responsible for 15-20% of antibiotic-related diarrhea (1). Potential sources of C. difficile infection (CDI) in humans include domestic and farm animals since an overlap between isolates from humans and animals has been demonstrated (2). Over the past decade, there has been a progressive increase in the prevalence, severity, and mortality of CDI worldwide. Several outbreaks in North America and Europe demonstrated the increased severity of CDI due to the presence of a hypervirulent antibiotic-resistant strain, BI/NAP1/027 (3). This epidemic strain is characteristically resistant to fluoroquinolones in vitro, which was not common among clinical isolates prior to 2001 (3).

The pathogenesis of C. difficile is proposed to begin with disruption of the indigenous colonic microflora by antibiotic treatment, followed by colonization with C. difficile (4). Pathogenic C. difficile strains cause diarrhea and colitis by releasing two toxins, an enterotoxin (TcdA) and a cytotoxin (TcdB). Both TcdA and TcdB enter the cells through receptor-mediated endocytosis, thereby inactivating the Rho GTPases (5; 6). Consequently, the actin cytoskeleton is disaggregated, which causes intestinal epithelial cell damage and increased permeability of tight junctions. These toxins also trigger the release of proinflammatory mediators and cytokines, and activate the enteric nervous system, leading to neutrophil chemotaxis and fluid secretion (6). Certain C. difficile strains, including the BI/NAP1/027 strain, also produce a binary toxin CDT, which is formed by two separate, unlinked polypeptide subunits, CDTa and CDTb (7). CDTb binds to a plasma membrane receptor and mediates the entrance of CDTa into the cell. CDTa then functions as an ADP-ribosyltransferase, leading to actin depolymerization and disruption of the cytoskeleton (8). Although the role of CDT in C. difficile pathogenesis is still poorly understood, it has been suggested that it may provide an additional factor for C. difficile virulence (9). However, the majority of clinical isolates produce TcdA and/or TcdB, but not CDT (10). Recently, it was shown that only TcdB is essential for C. difficile virulence (11) and a number of CDI cases caused by TcdA- TcdB+ strains have been reported (12).

Most studies on the pathogenesis of C. difficile have focused on its toxins and their effect on host cells. However, emergence of new hypervirulent strains, which results in the increased prevalence and severity of CDI (13), and an increase in the frequency of CDI cases in low-risk groups such as young adults and patients without antibiotic exposure (14) prompted us to hypothesize that virulence factors other than toxins may account for these changes. Recently, we utilized microarrays to identify conserved and divergent genes associated with virulence in C. difficile isolates from humans and animals (15). Our data provided the first evidence of the complex mechanism underlying host adaptation and pathogenesis. Microarray technology offers an efficient high-throughput tool to study the transcriptional profiles of pathogens and infected host cells. Transcriptomes of C. difficile after exposure to environmental and antibiotic stresses (16) and those of human epithelial colorectal Caco-2 cells upon TcdA treatment (17) have been analyzed. To our knowledge, there is no information on the transcriptomic profiles for host-pathogen interactions during CDI. In vitro analysis of the interplay between host and pathogen are essential to unravel the mechanism of infection and to investigate the host response to infection. We therefore employed microarrays to study both bacterial and human cellular transcriptome kinetics during CDI of Caco-2 cells. Here we present a large-scale analysis of gene expression profiles to reveal molecular determinants playing a role in C. difficile pathogenesis and the host response. The results will not only increase our understanding of the host-pathogen interaction, but may also provide targets for drug development.

Materials and Methods

Bacterial and Caco-2 cell culture

C. difficile strain 630 was grown in pre-reduced anaerobically sterilized peptone yeast extract broth with glucose (Anaerobe Systems, Morgan Hill, CA) at 37°C for 24 h under anaerobic conditions (15; 18). Caco-2 cells were cultured in Dulbecco's modified Eagle's medium (DMEM) supplemented with 10% (v/v) fetal bovine serum, 2mM L-glutamine, and 1% (v/v) penicillin-streptomycin (Invitrogen, Carlsbad, CA). Cells were incubated in a humidified 5% CO2 atmosphere at 37°C prior to the infection experiments. All experiments with anaerobic conditions were conducted in a Bactron IV anaerobic chamber (Shel Lab, Cornelius, OR) that was filled and purged with an anaerobic gas mixture (10% CO2, 85% N2, 5% H2). The chamber contained a catalyst which removes any trace amounts of oxygen. All materials used in the anaerobic chamber were pre-reduced by incubation in the chamber for 24 h before use.

Infection of Caco-2 cells

In all experiments, Caco-2 cells were passaged less than 10 times prior to infection. Prior to bacterial infection, Caco-2 cells were incubated in DMEM without antibiotics and fetal bovine serum. Overnight cultures of C. difficile were pelleted, washed and resuspended in the pre-reduced anaerobically sterilized DMEM. To resemble the CDI, where the colonic epithelial cells are damaged by toxins, we expected that the toxins would be slowly released from the bacteria. C. difficile toxin was measured at the different time points using Premier Toxin A&B ELISA kit following the manufacture's protocol (Meridian Bioscience, OH). An aliquot of bacterial suspension was added to infect confluent Caco-2 cells with a multiplicity of infection of 100:1 (bacteria/cell) for 30, 60, and 120 min under anaerobic conditions. Bacterial dilutions were also plated on brain-heart infusion agar plates for anaerobic culture, and colonies were counted to ensure the accuracy of dilution and viability of bacteria. In addition, the viability of Caco-2 cells under anaerobic condition for 120 min was more than 95% as observed by trypan blue staining (data not shown). At 0, 30, 60, and 120 min post-infection (p.i.), bacteria were harvested from both adherent and non-adherent fractions. The non-adherent bacterial fraction was obtained directly from medium. The cell-associated fraction was obtained by adding 4% saponin to the culture dishes. The suspension was then centrifuged at 100 × g for 1 min to pellet bacteria. Bacterial cells incubated in pre-reduced anaerobically sterilized DMEM for 30, 60, 120 min were included as controls. Both fractions were pooled and subjected to RNAprotect bacteria reagent (Qiagen, Valencia, CA) to halt transcription and RNA degradation. The infected and mock-infected Caco-2 cells were washed and treated with RNAprotect cell reagent (Qiagen). Cells were harvested by centrifugation and the pellets were stored at -80°C until use.

Caco-2 cell viability assays

MTT (5 mg/ml) was added to each well to test for Caco-2 cell viability. Following incubation at 37°C for 4 h, the formazan produced was solubilized in DMSO (100 μl per well) and absorbance at 570 nm was measured using a 96-well ELISA reader. For photomicrographs, cells were gently rinsed three times in PBS, fixed and stained with LeukoStat (Fisher Scientific, Pittsburgh, PA).

Total RNA isolation

Bacteria or Caco-2 cells were pooled from at least four culture dishes for each time point. RNA extraction was performed using an RNeasy kit (Qiagen) according to the manufacturer's instructions. For Caco-2 cells, the pellets were resuspended in lysis buffer and were subjected to QIAshredder homogenizer columns (Qiagen) before proceeding with the RNeasy kit. Contaminated DNA was removed by adding 20 units RNase-free DNase in DNA digesting buffer (Qiagen) for 15 min at room temperature. RNA was quantified by a NanoDrop-1000 spectrophotometer (Thermo Scientific, Wilmington, DE) and its integrity was evaluated using an Agilent Bioanalyzer 2100 (Agilent Technologies, Palo Alto, CA). RNA samples with a RNA integrity number >8 were labeled and used in microarray or qRT-PCR experiments.

Template labeling and hybridization

For C. difficile transcriptional profiling, 5 μg of RNA were reverse-transcribed using SuperScript III reverse transcriptase with random hexamers (Invitrogen) according to the manufacturer's instructions. The corresponding cDNA was labeled with 25 U of Klenow fragment (New England Biolabs, Ipswich, MA), 10 μg of exo-resistant random primers (Fermentas, Glen Burnie, MD), dNTP mix (0.12 mM each dATP, dCTP, and dGTP and 0.03 mM dTTP), and 0.1 mM of Cy5-dUTP (Amersham Biosciences, Piscataway, NJ) at 37°C for 24 h. Genomic DNA (2 μg) from C. difficile 630 was fragmented by _Dra_I digestion, labeled with Cy3-dUTP under the same conditions and used as the reference channel on each slide to allow comparison of each time point and different samples. Unbound dye was removed from the template using a QIAquick PCR Purification Kit (Qiagen). The efficiency of dye incorporation and the labeled sample yields were monitored by UV spectrometry as previously described (19). The Cy5-labeled cDNA and Cy3-labeled genomic DNA probes were hybridized on a C. difficile spotted array as described previously (15). For Caco-2 cell transcriptional profiling, 5 μg of total RNA were used as a template for antisense RNA amplification using MessageAmp aRNA Kit (Ambion, Austin, TX). The resulting aRNA was then labeled with Cy5-dUTP using an Amino Allyl cDNA Labeling Kit (Ambion) according to the manufacturer's instructions. Ten micrograms of Cy5-labeled aRNA were hybridized to the Human Whole Genome OneArray (Phalanx Biotech Group, Palo Alto, CA) in accordance with the company's recommendations. Three biological replicates were conducted for each time point and two technical replicates were performed for all samples.

Microarray data analysis

Arrays were scanned using a GenePix 4000B scanner (Molecular Devices, Sunnyvale, CA). The Cy3 and Cy5 signals and the local background intensities were quantified using GenePix Pro 6.1 software. The signal intensity of each spot was corrected by subtracting background signals in the immediate surroundings. Spots were examined manually, and poor spots were flagged for elimination from the analysis. The net intensities were log2 transformed, within-chip normalized using lowess algorithm, and quantile normalized across all chips using the TM4 suite of programs (20). The mean normalized log2 ratio and standard deviation were calculated from all replicates. All subsequent data analyses were performed using Microsoft Excel and TM4. The paired two-sample T-test was performed to identify differentially expressed (DE) genes. The significantly up- and down-regulated genes in each comparison group were identified by applying a p value of <0.05. Hierarchical clustering analysis was performed using Pearson's correlation coefficient and the average linkage method to group together genes with similar expression patterns. Genes were analyzed according to generic Gene Ontology (GO) Slims terms (http://www.geneontology.org/GO.slims.shtml). Known and predicted functional interaction networks of DE genes were derived from the STRING 8.1 database (21). The microarray data have been deposited in the NCBI Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/projects/geo/) with the GEO accession number GSE18407.

Quantitative real-time PCR (qRT-PCR)

Differential gene expression data were validated using qRT-PCR. Total RNA (1 μg) from each sample was converted to cDNA by using SuperScript III reverse transcriptase (Invitrogen) with random hexamers, following the manufacturer's instructions. The real-time reaction mixture included 5 μl of cDNA template, 200 nM of each of both forward and reverse primers, and 1× Power SYBR Green master mix (Applied Biosystems, Foster, CA). Primers used in this study are listed in the supplementary Table S1. RT-PCR was performed in 96-well optical plates using the ABI 7500 Sequence Detection System instrument and software (Applied Biosystems). The thermal cycling consisted of an initial denaturing step at 95°C for 10 min followed by 40 cycles consisting of 95°C for 15 s and 60°C for 1 min. For Ct determination, three parallels were assayed for each gene. qRT-PCR was performed in triplicate to evaluate reproducibility of data.

Results

Caco-2 cell infection with C. difficile

Initial experiments were performed to investigate the viability of Caco-2 cells at 30, 60, and 120 min p.i. MTT assays showed that cell viability was drastically reduced in a time-dependent fashion following infection (Fig. 1A). Morphological changes of cells were also examined. Cell disruption and aggregation was observed at 30 min p.i. and became increasingly evident at 60 and 120 min p.i. (Fig. 1B).

Figure 1.

Figure 1

Infection of Caco-2 cells with C. difficile. (A) Quantification of Caco-2 cell viability at different times post-infection. All assays were conducted in triplicate and repeated independently three times. Cell viability is as expressed as the percentage of survival of the control wells. Results are expressed as means ± 1 standard deviation for the replicate experiments, and the Student t test was used for statistical analysis of the data. Significant difference from the control (p < 0.05) is indicated by an asterisk. Caco-2 cells under anaerobic conditions at different time points without the infection were also evaluated but they were not significantly different from the control cells. (B) Photomicrographs of infected Caco-2 cells with C. difficile at 30, 60 and 120 min post-infection.

Transcriptome of Caco-2 and C. difficile during infection

The global gene expression profiles of Caco-2 cells and C. difficile at 30, 60, and 120 min p.i. were compared with those of uninfected cells. A total of 271 genes in Caco-2 cells and 207 genes in C. difficile were significantly DE in at least one time point during the infection. The numbers of up- and down-regulated genes in Caco-2 cells and C. difficile at each time point are shown in Fig. 2A. We also performed hierarchical clustering of DE genes at each time point (Fig. 2B and 2C). The clustered data demonstrate a clear pattern of transcriptional regulation during the infection.

Figure 2.

Figure 2

Transcriptional dialogue between Caco-2 cells and C. difficile during infection. (A) The number of up- or down-regulated genes after 30, 60, and 120 min p.i., as compared to the expression levels at the time of infection. (B, C) Hierarchical clustering analysis of differentially expressed genes in Caco-2 cells and C. difficile during infection. Genes identified to be significantly differentially expressed at 30, 60 or 120 min in Caco-2 or C. difficile cells p.i. relative to in vitro growth. Genes significantly different with _p_-value < 0.05 after the infection were pooled and used to create heatmaps for (B) Caco-2 cells, and (C) C. difficile. Genes are ordered in rows, conditions as columns. Red color indicates genes induced post-infection vs. prior to infection (fold change); green color denotes repression.

Functional classes of DE genes and their network interaction

To further characterize the DE genes in Caco-2 cells and C. difficile according to their functional groups, an enrichment analysis based on the biological process categories of the GO database was performed (Fig. 3). For Caco-2 cells, ∼43.9% of the DE transcripts were annotated as being involved in metabolic processes including metabolism of nucleic acids (17.3%), proteins (16.7%), lipids (3%). A significant number of transcripts were assigned known functions in cell organization and biosynthesis (13.9%), transport (11.4%), cell communication (10.5%), signal transduction (9.9%), and transcription (9.3%). Genes associated with cell differentiation (5.7%), cell cycle (4.2%), response to stress (3.2%), cell death (3.0%), and cytoskeleton organization and biogenesis (2.3%) were also differentially expressed during the infection. Similarly, DE genes with metabolic functions in C. difficile were found to be most prevalent (68.0%). Genes involved in transport (18.9%), transcription (17.2%), biosynthesis (16.0%), cell communication (10.2%), signal transduction (10.2%), cell organization and biogenesis (4.1%), and protein modification (2.9%) were also abundant.

Figure 3.

Figure 3

Functional annotation of genes in Caco-2 cells and C. difficile, which are differentially expressed between infected and uninfected conditions. All differentially expressed genes were annotated using generic GO-slim for biological process.

To understand the biological interaction between the DE genes, we constructed functional networks using String v.8.1. Network analysis of the DE genes in Caco-2 cells facilitated the identification of genes involved in signal transduction including Rho and Wnt pathways, cytoskeleton, cell cycle, immune response, and cell death. For C. difficile, the results revealed a complex network of ribosomal proteins, as well as genes associated with cell envelope biosynthesis, purine biosynthesis, regulatory proteins, two component systems, and phosphotransferase systems.

Validation of microarray data using qRT-PCR

To confirm the microarray results and the involvement of key biological pathways, two sets of 11 DE genes as well as one house-keeping gene each from Caco-2 cells and C. difficile were selected for qRT-PCR (See Supplementary Table S1). Although the differences in gene expression appeared to be underestimated in the microarray results, overall the expression ratios obtained by microarray and qRT-PCR analyses were consistent, with a correlation coefficient (R2) of 0.869 (Fig. 4).

Figure 4.

Figure 4

Validation of microarray data by qRT-PCR. Gene expression changes in infected versus uninfected cells measured by microarray analysis or qRT-PCR are compared. Data are plotted as log2 ratios of microarray data (x-axis) compared to those of qRT-PCR (y-axis).

Discussion

The interaction between host and pathogen during infection is complex and requires multiple players from both sides. The host response attempts to clear the invasive pathogen and the pathogen needs to adapt to the host environment. In the present study, we investigated the host-pathogen interplay by assessing global transcriptional profiles of human colorectal Caco-2 cells and C. difficile simultaneously over a time course of infection to identify DE transcripts, which might potentially play roles in host response and C. difficile pathogenesis. First, we observed that there was a ∼20% mortality of Caco-2 cells at 30 min p.i. and the mortality rate increased at the later time points p.i. (Fig. 1A). Evidence of cell membrane lysis that might have been caused by toxin release was also observed (Fig. 1B). Based on these findings, we evaluated the transcriptome of Caco-2 cells and C. difficile at the time points of 30, 60, and 120 min p.i.

Our results indicate that ∼7% of the C. difficile genome is differentially expressed during CDI of Caco-2 cells. Most of the DE genes appear to be involved in nucleic acid metabolism, transcription, protein synthesis and modification, pointing toward a bacterial response to various stresses. These include the up-regulation of genes encoding (i) ribosomal proteins such as rplW (CD0075), rpmC (CD0080A), rpsZ (CD0084A), and CD0093; (ii) ribosomal protein methyltransferase prmA (CD2450); (iii) DNA repair proteins such as recJ (CD2746) and CD3398, as well as the down-regulation of genes encoding the transcriptional repressor nrdR (CD2640) and transcription-repair coupling factor Mfd (CD3501). A large set of genes involved in cellular metabolism, especially in energy production, was also found to be differentially regulated during infection. Examples include genes involved in carbohydrate utilization through a phosphotransferase system (CD1078, CD2327, CD3030, CD3082, CD3127, and CD3276) and other transport proteins. These genes might be essential in the pathogenesis of C. difficile as a link between metabolic states of the bacterium and its pathogenic properties is becoming evident (22; 23). Furthermore, we observed differential expression of multiple regulatory genes encoding two-component systems, transcriptional regulators, and antiterminators, underlining a high degree of regulation required for adaptation of C. difficile to the host environment. We found the up-regulation of codY (CD1275), an important regulator of genes whose expression changes upon nutrient limitation (24) and acts as a repressor of toxin gene expression in C. difficile (25). Transcription levels of several virulent factors also changed during infection. Examples include the up-regulation of genes encoding the cell wall proteins murF (CD2655), a putative cell wall hydrolase (CD2402), a cell surface protein (CD2735), capsular proteins (CD2769, CD2770), chemosensory proteins (CD0537, CD0542), and a putative hemolysin-like membrane protein (CD1546), as well as the down-regulation of genes encoding flagellar proteins (CD0250, CD0268) and the cell surface protein cwp84 (CD2787). These molecules play a role in remodeling of the bacterial envelope and enhancing exposure of virulence proteins at the surface, which may be important in bacterial pathogenesis either during colonization or spread/invasion stages. Interestingly, up to one-fourth of the DE genes encode proteins with unknown functions and hypothetical proteins with no homologs to those in other organisms (Table S2). These genes might function in the uncharacterized infection mechanism of C. difficile.

While C. difficile develops different strategies to exploit host cell function for infection, the host cell also establishes defense mechanisms involving multiple factors in a complex regulatory network in response to the infection. It has been suggested that C. difficile invades the epithelial barrier by disaggregation of actin microfilaments in colonocytes via glycosylation of the Rho proteins leading to epithelial cell disruption and opening of tight junctions (26). However, individual determinants in cell communication through tight junction have not been fully identified. Here, we found the up-regulation of RhoB, a Rho-related GTP-binding protein involved in the intracellular trafficking of a number of proteins. RhoB also affects cell adhesion, growth factor signaling and preferentially regulates tight junctions by controlling the contraction of actin-myosin filaments (27). Our results are consistent with previous studies reporting that C. difficile TcdA induces the expression of RhoB in Caco-2 cells (17). At the same time, ROCK2, a Rho-associated protein kinase 2 that phosphorylates a large number of important signaling proteins and thereby regulates the assembly of the actin cytoskeleton, stress fibers and focal adhesion complexes (28), was down-regulated during CDI. Transcription levels of genes involved in cytoskeletal assembly including myosin-like protein-3 MYL3, myosin-1E MYO1E, myosin regulatory protein MYLIP, tight-junction protein ZO-1, β-filamin FlnB, and actin-depolymerizing factor DSTN were also reduced.

It is postulated that extracellular matrix proteins (ECM), including fibronectin, are targets for bacterial invasion since the fbpA gene, which encodes a fibronectin-binding protein, is conserved among C. difficile strains from different host species (15) and the Cwp84 protease exhibits ECM-degrading activity (29). We found that the transcription of the β1 integrin ITGB1 was elevated during infection. ITGB1 is known to interact with ECM, providing cell-cell attachment and may activate intracellular signaling cascades leading to the modulation of gene expression (30). Our data revealed the up-regulation of genes involved in signaling and immune response including (i) RIPK4, which encodes a receptor-interacting protein kinase that binds to TNF receptor-associated factor (TRAF) proteins and whose up-regulation leads to activation of NFκB (31); (ii) SOCS-1, which encodes a suppressor of cytokine signaling-1 that regulates cytokine signal transduction (32); (iii) STK4, which encodes a serine-threonine protein kinase-4 that is a stress-activated, pro-apoptotic kinase that functions in apoptosis through the caspase cascade (33); (iv) Wnt pathway genes encoding GSK-3-binding protein (FRAT2) and F-box/WD repeat protein 1A (BTRC), which are involved in NFκB regulation (34); (v) TANK, which encodes a TRAF family member-associated NFκB activator that stimulates innate immune responses through toll-like receptors (35); and (vi) MPO, which encodes myeloperoxidase that forms a part of the innate immune system responsible for microbicidal activity (36). The expression of several cell cycle and cell death regulatory genes including CHED, TUSC2, CCNE, CRADD and SKB1 was significantly DE during infection. The list of DE genes in Caco-2 cells is shown in the supplementary Table S3. Taken together, our data suggest that host response to CDI may involve early release of proinflammatory cytokines from intestinal epithelial cells probably via activation of signaling pathways.

The present study demonstrates the transcriptome of the Caco-2 cells and C. difficile following infection, thereby providing a framework for understanding host-bacterial interactions during infection. The identification of transcripts unique to this work will be useful as functional and regulatory networks can be interrogated to clarify the molecular and cellular function of individual factors and to unravel the complex mechanisms involved in the host response and bacterial adaptation to host environments during CDI.

Supplementary Tables

Table S1: Primers used for qRT-PCR

Table S2: List of differentially expressed genes in C. difficile following infection

Table S3: List of differentially expressed genes in Caco-2 cells following infection

Acknowledgments

We would like to thank Dr. D.N. Gerding at Hines Veterans Affairs Hospital for providing C. difficile strain 630 and Suzanne Klaessig for providing Caco-2 cells. Thanks to Dr. Sean P. McDonough for editing and his critical reading of this manuscript.

Financial support: Federal funds from the National Institute of Allergy and Infectious Diseases, National Institute of Health, Department of Health and Human Services under contract, N01-AI-30054, Project No. ZC005-06

Footnotes

All authors listed in the title page do not have a commercial or other association that might pose a conflict of interest.

References

Associated Data

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Supplementary Materials

Table S1: Primers used for qRT-PCR

Table S2: List of differentially expressed genes in C. difficile following infection

Table S3: List of differentially expressed genes in Caco-2 cells following infection