Pinaki Panigrahi, Gheorghe T Braileanu, Departments of Pediatrics, University of Maryland School of Medicine, 22 South Greene Street, Baltimore, MD 21201, United States
Hegang Chen, Department of Epidemiology & Preventive Medicine, University of Maryland School of Medicine, 22 South Greene Street, Baltimore, MD 21201, United States
O Colin Stine, Genomics Core, University of Maryland School of Medicine, 22 South Greene Street, Baltimore, MD 21201,
Supported by the Department of Pediatrics and GCRC (M01-RR-16500), University of Maryland Baltimore, with partial funding from NIH grants UO1 HD 40574 and RO1 HD 053719
Correspondence to: Dr. Pinaki Panigrahi, University of Maryland School of Medicine, Department of Pediatrics, 22 South Greene Street, N5W68, Baltimore, MD 21201, United States. firstname.lastname@example.org
Telephone: +1-410-7061803 Fax: +1-410-7060404
Received: July 25, 2007 Revised: August 26, 2007
AIM: To investigate the change in eukaryotic gene expression profile in Caco-2 cells after infection with strains of Escherichia coli and commensal probiotic bacteria.
METHODS: A 19 200 gene/expressed sequence tag gene chip was used to examine expression of genes after infection of Caco-2 cells with strains of normal flora E. coli, Lactobacillus plantarum, and a combination of the two.
RESULTS: The cDNA microarray revealed up-regulation of 155 and down-regulation of 177 genes by E. coli. L. plantarum up-regulated 45 and down-regulated 36 genes. During mixed infection, 27 genes were up-regulated and 59 were down-regulated, with nullification of stimulatory/inhibitory effects on most of the genes. Expression of several new genes was noted in this group.
CONCLUSION: The commensal bacterial strains used in this study induced the expression of a large number of genes in colonocyte-like cultured cells and changed the expression of several genes involved in important cellular processes such as regulation of transcription, protein biosynthesis, metabolism, cell adhesion, ubiquitination, and apoptosis. Such changes induced by the presence of probiotic bacteria may shape the physiologic and pathologic responses they trigger in the host.
© 2007 WJG. All rights reserved.
Key words: Lactobacillus; Escherichia coli; Gene expression; Probiotic; cDNA microarray
Panigrahi P, Braileanu GT, Chen H, Stine OC. Probiotic bacteria change Escherichia coli-induced gene expression in cultured colonocytes: Implications in intestinal pathophysiology. World J Gastroenterol 2007; 13(47): 6370-6378
There has been an upsurge in clinical trials involving probiotics in gastrointestinal diseases. Although promising, these trials with specific probiotic bacteria have shown variable results, with limited elucidation of the underlying pathophysiology. In real life, these strains never act on the host cells in isolation and over 800 bacterial strains in the adult human colon are engaged in constant cross talk with intestinal epithelial cells. No detailed study so far has attempted to examine the effect of individual probiotic bacteria on host gastrointestinal cells, and the changes during co-infection with other enteric bacteria.
However, a lot of emphasis has
recently been given to the normal bacterial flora in the intestine,
including many Lactobacillus strains that are considered as
probiotics with health-promoting effects on the host. A myriad of
effects have been shown by these bacteria, spanning from bacterial
killing via secretion of bacteriocins, to
inhibition of attachment and invasion by pathogenic bacteria,
and modulation of host inflammatory responses. These
commensal strains have been shown to modulate the expression of
genes involved in important physiologic functions such as postnatal
intestinal maturation, cell growth, proliferation, nutrient
absorption, mucosal barrier function, and angiogenesis[4-6].
Multiple laboratory studies have shown beneficial effects of
Lactobacillus strains against single pathogenic bacterial
strains in in vitro and
At this time, our understanding of the response of eukaryotic cells (e.g. intestinal cells) is limited to nutrients and local factors, and virulence mechanisms involving individual microorganisms. Although contrasting signal transduction mechanisms in bacterial and eukaryotic gene transcription have been described, reports on cross talk between bacteria and epithelial cells have focused on single bacterial strains. As a result, the physiologic and pathologic changes in the host cells as a response to multiple bacteria have not been addressed. Since the mammalian gut is colonized with multiple bacterial strains very quickly after birth, it is conceivable that the ultimate effect of probiotic treatment will depend greatly on the presence of other bacteria in the host intestine at that time.
In the current study, we examined the difference between gene expression in intestinal cells in response to infection with a single bacterial strain, compared to that during mixed infection. Caco-2 cells were utilized to discern the effect of Lactobacillus plantarum (the most common Lactobacillus species in humans), Escherichia coli (a common Gram-negative enteric strain) and the combination of the two strains. A high-density cDNA glass microarray and standard techniques were employed to identify bacteria-induced gene expression in this eukaryotic system.
MATERIALS AND METHODS
Caco-2 cell culture model
Caco-2 cells, obtained from American Type Culture Collection (ATCC HTB-37), were used at passage 10-12. This human colon-adenocarcinoma-derived cell line has been used extensively for physiologic and enteric bacterial pathogenesis studies. The cells were cultured in a humidified atmosphere containing 5% CO2 at 37℃ in Dulbecco’s Modified Eagle’s Medium (DMEM; Gibco, Grand Island, NY, USA with 10% fetal calf serum (Sigma, St. Louis, MO, USA), 2 mmol/L glutamine, 1.0 mmol/L sodium pyruvate, 0.1% non-essential amino acids, 100 U/mL penicillin and 100 mg/mL streptomycin. All experiments were performed without serum or antibiotics in 8-10-d-old cells after they reached confluence.
E. coli strain 6-1 was isolated from a healthy infant, and has been used previously in in vitro and in vivo studies in our laboratory. This strain does not possess any known virulence genes. We used a human strain of L. plantarum (ATCC 202195), the species most commonly isolated from humans.
Defined bacterial treatment of epithelial cells
Cells were washed in PBS and re-fed with experimental DMEM without serum or antibiotics before the experiments. Following previously described methods in which a maximal effect of Lactobacillus was seen, Caco-2 cells were infected with E. coli and/or L. plantarum at 1:10 multiplicity of infection, and incubated for 2 h.
For examination of Caco-2 cell gene expression under our experimental conditions, we used a high-density glass microarray H19K (University Health Network Microarray Centre, Toronto, www.microarrays.ca/home.html) that had 19 200 genes/expressed sequence tags (ESTs). These included fully characterized, partially characterized and some uncharacterized human gene elements. Each gene/EST was printed in duplicate in this array. The genes in the array represented constitutively expressed genes/ESTs and the manufacturer did not include genes that are transiently expressed, such as cytokines and chemokines. In our experiments, we used dye swapping procedures and bioinformatics tools considered as standard techniques that have been reported in similar studies in the past.
Total RNA was extracted from Caco-2 cells grown in 75-cm2 tissue culture flasks using the TRIZOL method (Invitrogen, Carlsbad, CA, USA), following manufacturer's instructions. RNA samples were treated with RNAse-free DNAse to remove contaminating genomic DNA, examined by 260/280 nm UV absorption ratio (> 1.8) followed by assessment of integrity by running in a 1.2% agarose gel and ethidium bromide staining.
Preparation of fluorescent-labeled cDNA, hybridization and signal detection
Total mRNA (10 mg) was reversely transcribed using 20 mmol/L dNTP mix including amino-allyl dUTP (AA-dUTP; Sigma) and 400 U SuperScript Ⅱ Reverse Transcriptase (Invitrogen, Carlsbad, CA, USA). The resulting aa-cDNA, cleaned with a QIAquick column (Qiagen, Valencia, CA, USA), was coupled with Cy3 or Cy5 dye (Amersham Biosciences, Piscataway, NJ, USA) in the presence of sodium bicarbonate for 1 h in the dark. After adding 10 mL 4 mol/L hydroxylamine and 125 mL buffer PB (Qiagen supplied) to each, the control and treatment samples were combined and cleaned using another QIAquick column. The elute was transferred to a Microcon YM 30 centrifugal filter device (Amicon Millipore, Bedford, MA, USA), and after adding 20 mL cot-1 human DNA (Gibco-BRL), the whole volume was concentrated to 5 mL. Ten microliters of 1 mg/mL poly (A) RNA (Sigma), 1 mL 10 mg/mL tRNA (Gibco-BRL), 4 mL water and 5 mL hybridization buffer (50% formamide, 5 × SSC (3 mol/L sodium chloride, 0.3 mol/L sodium citrate and 0.1% SDS) were added. The array was pretreated at 42℃ for 1 h with hybridization buffer. After overnight hybridization at 42℃, the slides were washed in 50 mL 2 × SSC and 0.1% SDS at 55℃ for 5 min, once in 0.1 × SSC and 0.1% SDS for 5 min at room temperature (RT), and for 5 min with 0.1 × SSC at RT, air-dried and scanned with 555 nm and 647 nm lasers in a Scan Array 5000 (GSI Lumonics, Novi, MI, USA). Images of the fluorescence intensity for each dye were analyzed using Imagene 4.2 software (Biodiscovery, CA, USA).
RNA from each experimental condition and control Caco-2 cells were hybridized on the same microarray. To eliminate the color bias, duplicate reactions were carried out in which the dyes (Cy3, Cy5) for the control and experimental samples were swapped.
Individual gene intensity data files for each experimental condition were compared with the control values using the GeneSight 2.1 program (Biodiscovery). After correction for the local background, normalization using all the spots, removal of the outliers, averaging of the replicates and transforming to base 2, each gene was assigned a relative expression value when compared with the control. A twofold or larger difference in the relative gene expression was considered significant.
The data discussed in this publication have been deposited in NCBIs Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/) and are accessible through GEO Series accession number GSE5874.
Real-time quantitative PCR
We randomly selected eight genes (BMF, CD248, PPM1E, FXYD3, OAS2, FY, CERK and HPSE) from our pool of expressed genes/ESTs that are well characterized in the literature and appear to have some biologic significance. ESTs were not included. Real-time quantitative PCR (Bio-Rad iQ SYBR Green Supermix and iCicler) was done using GAPDH for normalization. The levels of expression detected by microarray were compared with PCR results. The primers used to amplify specific gene segments are presented in Table 1. The relative gene expression was calculated using the comparative ΔΔCT method. Each sample was tested twice in triplicate.
Gene expression after bacterial infection
After 2 h treatment, E. coli, L. plantarum and their combination changed the expression (by twofold) of 332, 81 and 86 genes, respectively, compared to uninfected control Caco-2 cells (Figure 1). After infection with E. coli, 155 genes were up-regulated and 177 were down-regulated (Table 1 and Supplementary Table 1). L. plantarum induced up-regulation of 45 genes and 36 genes were down-regulated (Table 1 and Supplementary Table 2). The combination treatment up-regulated 27 genes and down-regulated 59 (Table 1 and Supplementary Table 3) [Note: The supplementary tables above can be accessed at: http://panigrahipeds.googlepages.com/suppl-tables.pdf; Raw data of all 19 200 genes during each treatment can be accessed from the NCBI/GEO data base (GSE5874) at: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=nzyxdkkuwukuytk&acc=GSE5874]. Mixed infection nullified the previously demonstrated stimulatory and inhibitory effects of E. coli on 152 and 177 genes and of L. plantarum on 38 and 26 genes, respectively. Stimulation of 23 and inhibition of 59 genes were noted after mixed infection that was not influenced by either bacterium alone.
There were 21 genes influenced by two different treatment conditions (Table 1). Seventeen genes were affected by E. coli and L. plantarum, and four by E. coli and the combination of bacteria. Genes nos. 1-7 were up-regulated by both E. coli and L. plantarum; and genes nos. 8-17 were down-regulated by both bacteria. For each of the 17 genes in this group, the effects of the individual bacteria were brought to baseline by the combination treatment. In contrast, for three genes BMF, CD248 and PPM1E (nos. 18, 19 and 20 in Table 1), the stimulatory effect of E. coli was maintained after mixed infection with L. plantarum. For one gene (no. 21, CARD8), the 3.26-fold down-regulation by E. coli was reversed in the mixed infection, with demonstration of a four fold increase.
Apart from the specific up- and down-regulation of genes by either E. coli or L. plantarum, and reversal of E. coli-induced effects when L. plantarum was used as a co-infectant, several genes of physiologic importance were noted in our system. Table 2 describes 58 genes under 10 specific categories that were expressed during mixed infection. While the function of a small number of genes was not very well defined, most of the genes could be grouped into important cellular functions. These include genes involved in transcription regulation, RNA processing, protein biosynthesis, and other important processes such as ubiquitination, cell adhesion, proliferation and apoptosis.
Confirmation of selected gene expression by real-time quantitative PCR
Eight genes were randomly tested by quantitative
real-time PCR to verify the expression detected by microarray
The infant gut is essentially sterile at birth and is first colonized with Enterobacteriaceae, which change the redox potential in the intestine and allow more microaerophilic and anaerobic species to colonize[42,43]. The latter group, which is comprised primarily of Bifidobacteria and Lactobacillus organisms, are considered as normal flora that coexist in the human colon, as new species are introduced to ultimately provide a stable flora in the human gut, in which over 800 bacterial species coexist in harmony. In such a healthy state, the intestinal mucosa serves as the first line of defense against infections by providing an important mechanical and immunologic barrier between the host’s internal milieu and the gut environment. These intestinal epithelial cells generate and transmit signals between bacteria and deeper layers in the intestine. In the event of specific infections, epithelial cells express and secrete proinflammatory and chemoattractant cytokines that further transmit signals to the underlying cells in the reticuloendothelial system. The virulence factors and the host responses to these factors in various diseases have been studied in a fair amount of detail (E. coli, Vibrio cholerae, Salmonella and Pseudomonas) using tissue culture and in vivo models, and specific genes and gene functions have been described[49-52]. These experiments have utilized single bacterial strains.
In an attempt to mimic the natural gut environment, communication systems among bacteria have also been studied relatively well. Chemical signals produced and detected by bacteria can be directed at other bacteria and self. This phenomenon, called as quorum sensing, is important for the microorganism’s adaptation to the local environment. This fundamental prokaryotic behavior (among bacteria) is known to affect the symbiotic or antagonistic environment created within the gut milieu. However, the effect of single versus multiple bacterial species on eukaryotic cells has not been addressed in the literature.
The stimulus for us to conduct the current study came from our observation that a large number of probiotic trials have been conducted and reported in the recent past, with almost no basis for selection of the strain, and more importantly, with no data on changes in physiologic or pathologic parameters in the host, other than analysis of the primary and secondary clinical endpoints. Although a live bacterial supplement was used in all of these reported studies, there was also a serious lack of data on the colonizing ability of the probiotic strain and changes in the colonization by other bacteria in the host gut. Since the newborn gut is colonized with a paucity of bacteria (an average 2.5 species in preterm infants)[37,54] that expands to a limited but heterogenous flora by 10 d of age, we designed the current simple system to examine the effects of L. plantarum, a common human probiotic strain, and E. coli, the most common colonizing strain in the neonatal period, on gut cells. We took advantage of a microarray chip that allowed us to examine 19 200 human genes in this simulated microbial gut environment. In this in vitro model, single and combined bacteria were allowed to interact with cultured cells, and our results were analyzed under high-stringency conditions to identify specific genes expressed during defined bacteria-gut cell interactions.
In our system, we observed a change (up- or down-regulation) in the expression of 333, 81 and 86 genes upon infection with E. coli, L. plantarum and the combined treatment, respectively. Our real-time PCR experiments confirmed the modifications demonstrated in the microarray experiments, albeit at a lower level, a phenomenon also reported in other studies. The numbers of unique genes presented in this study are in the range reported in previous studies in which Gram-negative enteric pathogens modified the expression of 0.5%-13% of the genes in epithelial cells[50,56-58], and commensal bacteria induced differential expression of 0.35%-6.2% of examined genes in mouse colonocytes. Our strain of E. coli modified 1.73%, and L. plantarum modified 0.43% of genes. The slightly lower number of genes identified in our 19 200 array may have been due to the use of a non-pathogenic strain of E. coli, a commensal Lactobacillus, and an array that included only constitutively expressed genes. Genes expected to be expressed after a bacterial insult such as pro-inflammatory cytokines were not spotted on this array. Additionally, a slightly low number might have resulted from our conservative choice of a twofold increase in expression as being significant in our analysis.
There are several comparisons that can be made
between our results and those of others using a similar approach but
with single bacterial infection. For example, from the six genes
up-regulated by enteropathogenic E. coli in HeLa cells,
we found only one (zyxin, a cytoskeletal protein) to be in common
with our microarray results. There was a similar increase
(1.72-fold) in expression of this gene when our E. coli
strain 6-1 was used to infect Caco-2 cells. Two previous studies
with commensal flora have reported that bacterial reconstitution of
germ-free mice increased the expression of the colon-specific serum
amyloid A1 gene[60,61]. In our model, serum amyloid A2
gene expression was increased by 2.22-fold. From the 12 genes
down-regulated by non-pathogenic bacterial reconstitution of
germ-free mice, reported by Fukushima et al in colonic
epithelial cells, three were in common with our
microarray; selenoprotein P, 3-hydroxy-3 methylglutaryl-coenzyme A
synthase and metallothionein. All three were also down-regulated in
our combination treatment model. The authors also showed a
down-regulation of solute carrier family 20 - member 1. Our results
were very similar to this observation in that we also noted a
decrease in the expression of other members of the solute carrier
families, i.e. family 2, 9, 12, 20, 24, 25 and 35. Fukushima et
al have shown overexpression of heat shock protein (60 kDa) in
germ-free mice compared to specific pathogen-free rodents that had
received treatment with normal mouse flora. We
observed a similar phenomenon in our system in which down-regulation
of heat shock proteins 75, 105 and an ortholog of mouse heat shock
protein 70 kDa were noted after combined bacterial treatment. We
observed cytochrome c oxidase subunits
We observed modulation of multiple genes known to have an impact on cellular and physiologic processes in the eukaryotic system (Table 2). These genes ranged from basic transcriptional regulators to those involved in protein synthesis, cellular metabolism, cell proliferation and apoptosis. During mixed infection, we observed down-regulation of three genes involved in ubiquitination. Ubiquitin-conjugating enzyme E2N, ubiquitin-carrier protein E2-EPF and ubiquitin A-52 residue ribosomal protein fusion product 1 were reduced 2.02, 2.05 and 2.29-fold, respectively. In a recent study that investigated anti-inflammatory properties of Lactobacillus casei, expression of several genes involved in ubiquitination was reduced, including E2N, a gene (common to our system) that was reported to be decreased 2.88-fold. The authors concluded I-kB stabilization via reduced ubiquitination and downstream modulation of inflammatory response driven by NF-kB in Shigella-infected Caco-2 cells. We used a non-pathogenic commensal strain of E. coli in our experiments, and while the aim of the current study was not to assess or examine the effects of L. plantarum during bacterial infection or inflammation, our results strongly suggest that Lactobacillus strains do indeed affect common physiologic pathways in gut cells, which may ultimately shape the host response in health and disease.
In our study, it was important and intriguing to note that the three experimental infections induced quite unique gene-expression profiles. Even the mixed infection with E. coli and L. plantarum had a very small overlap with the expression profiles of the strains when they were used alone. This illustrates how colonization can change the gene expression of host cells as they are exposed to more than one species of bacteria. In real life, the gut cells are exposed to a multitude of bacterial strains, and hence, it may be of limited value to study the effect of infection or colonization by single bacterial species in a clean tissue culture environment, and use the results as the basis for designing treatment or preventive strategies. Using neonatal models of gut colonization, we have previously shown that bacterial ecology (combination of Gram-negative and Gram-positive organisms), rather than individual virulent bacterial strains, plays a more important role in diseases such as NEC. The results of our current study are in line with previous observations, and now provide an additional line of support and offer a possible explanation for the varied results of recent probiotic trials. On a broader scale, this report provides an insight into the complex host response that can be expected at mucosal sites such as the gastrointestinal tract. Based on the results obtained from tissue culture with only two bacteria in the system, it can be speculated that our findings are only the tip of the iceberg, and the real in vivo picture in mammals will be even more complex. While it is becoming increasing clear that specific Lactobacillus species posses unique health-promoting characteristics, knowledge gained from the current study further indicates that a "one strain fits all" approach may not always succeed in the treatment or prevention of specific diseases. A more global approach needs to be taken with proper emphasis on the microbial ecology, while addressing the pathogenesis of unique bacterial diseases in the mammalian intestine at different ages and stages of development.
In the context of in vivo or clinical trial environment, it should be noted that our current model and results do not represent a universal phenomenon, nor provide a comprehensive picture of the human intestine. For example, genes expressed will probably be different if other probiotic strains such as Bifidobacteria and L. casei were used in our system. Similarly, combinations of other aerobic and anaerobic Gram-negative and Gram-positive strains may induce different sets of genes. We can utilize other microarray systems with cytokine and signaling-molecule genes (not spotted in the current 19 200 gene array), when our aim would be to identify modifications in inflammatory mediators. The relative concentrations of each bacterium in the system may also change the gene-expression profile. In the current study, we selected a 1:10 ratio of E. coli to Lactobacillus infecting dose to simulate the human intestinal microflora, in which anaerobic and microaerophilic organisms form the dominant flora. Since enteric bacteria such as E. coli are sometimes present at < 0.1% of the total bacterial population, with a predominance by obligate anaerobes, it is not unexpected to observe a different gene-expression profile when a 10-100-fold higher proportion of Lactobacilli are used in the system. Nevertheless, such manipulations and experiments can be done, and despite some limitations, assessment of mRNA-expression profiles by cDNA array analysis can be utilized as a useful technique for expanding our understanding of the colonocyte-bacteria interaction.
While it may appear difficult to analyze complex
microflora (400-800 species) and their interactions with gut cells
in the mature intestine, this is now made feasible with the
availability of new techniques. Fluorescent
1 Atrih A, Rekhif N, Michel M, Lefebvre
G. Detection of bacteriocins produced by Lactobacillus plantarum
2 Bernet MF, Brassart D, Neeser JR,
Servin AL. Lactobacillus acidophilus LA 1 binds to cultured
human intestinal cell lines
3 Perdigon G, Maldonado Galdeano C,
Valdez JC, Medici M. Interaction of lactic acid bacteria with the
JI, Hooper LV, McNevin MS, Wong M, Bry L. Epithelial cell
growth and differentiation. III. Promoting diversity in
5 Hooper LV, Gordon JI. Commensal host-bacterial relationships in the gut. Science 2001; 292: 1115-1118 PubMed
6 Hooper LV, Midtvedt T, Gordon JI. How
host-microbial interactions shape the nutrient environment of the
7 Reid G, Bruce AW, McGroarty JA, Cheng
KJ, Costerton JW. Is there a role for lactobacilli in
prevention of urogenital and
Waard R, Garssen J, Bokken GC, Vos JG. Antagonistic activity of
Lactobacillus casei strain shirota against
CJ, Mahenthiralingam E. Functional foods and paediatric
gastro-intestinal health and disease. Ann Trop Paediatr
H, Setty M, Mrukowicz J, Guandalini S. Probiotics in
gastrointestinal diseases in children: hard and not-so-
11 Sazawal S, Hiremath G, Dhingra U, Malik
P, Deb S, Black RE. Efficacy of probiotics in prevention of acute
12 Saiman L. Strategies for prevention of nosocomial sepsis in the
neonatal intensive care unit. Curr Opin Pediatr 2006;
13 Novak J, Katz JA. Probiotics and prebiotics for gastrointestinal infections. Curr Infect Dis Rep 2006; 8: 103-109 PubMed
14 Johnston BC, Supina AL, Vohra S.
Probiotics for pediatric antibiotic-associated diarrhea: a
meta-analysis of randomized
15 Duchmann R. The role of probiotics and
antibiotics in regulating mucosal inflammation. Adv Exp Med Biol
16 Doron S, Gorbach SL. Probiotics: their role in the treatment and
prevention of disease. Expert Rev Anti Infect Ther
17 Daniel C, Repa A, Wild C, Pollak A, Pot
B, Breiteneder H, Wiedermann U, Mercenier A. Modulation of allergic
18 Chan-Yeung M, Becker A. Primary
prevention of childhood asthma and allergic disorders. Curr Opin
19 Boyle RJ, Tang ML. The role of probiotics in the management of allergic disease. Clin Exp Allergy 2006; 36: 568-576
20 Kalliomaki MA, Isolauri E. Probiotics
and down-regulation of the allergic response. Immunol Allergy
Clin North Am 2004;
del Giudice M,
De Luca MG. The role of probiotics in the clinical management of
food allergy and atopic
22 Kitajima H, Sumida Y, Tanaka R, Yuki N,
Takayama H, Fujimura M. Early administration of Bifidobacterium
23 Hoyos AB. Reduced incidence of
necrotizing enterocolitis associated with enteral administration of
24 Lin HC,
Su BH, Chen AC, Lin TW, Tsai CH, Yeh TF, Oh W. Oral probiotics
reduce the incidence and severity of necrotizing
25 Bin-Nun A, Bromiker R, Wilschanski M, Kaplan M, Rudensky B, Caplan
M, Hammerman C. Oral probiotics prevent
26 Dani C, Biadaioli R, Bertini G, Martelli
E, Rubaltelli FF. Probiotics feeding in prevention of urinary tract
27 Agarwal R, Sharma N, Chaudhry R, Deorari
A, Paul VK, Gewolb IH, Panigrahi P. Effects of oral Lactobacillus
28 Madsen KL. The use of probiotics in gastrointestinal disease. Can J Gastroenterol 2001; 15: 817-822 PubMed
29 Isolauri E. Probiotics in human disease. Am J Clin Nutr 2001; 73: 1142S-1146S PubMed
30 Vanderhoof JA, Young RJ. Probiotics in pediatrics. Pediatrics 2002; 109: 956-968 PubMed
31 Reece RJ, Beynon L, Holden S, Hughes AD,
Rebora K, Sellick CA. Nutrient-regulated gene expression in
32 Cashin P, Goldsack L, Hall D, O'Toole R.
Contrasting signal transduction mechanisms in bacterial and
33 Raupach B, Mecsas J, Heczko U, Falkow S,
Finlay BB. Bacterial epithelial cell cross talk. Curr Top
34 Ahrne S, Nobaek S, Jeppsson B,
Adlerberth I, Wold AE, Molin G. The normal Lactobacillus
flora of healthy human rectal
35 Engle MJ, Goetz GS, Alpers DH. Caco-2
cells express a combination of colonocyte and enterocyte phenotypes.
36 Panigrahi P, Gupta S, Gewolb IH, Morris
JG Jr. Occurrence of necrotizing enterocolitis may be dependent on
37 Gupta S, Morris JG Jr, Panigrahi P, Nataro JP, Glass RI, Gewolb
IH. Endemic necrotizing enterocolitis: lack of association
38 Panigrahi P, Bamford P, Horvath K,
Morris JG Jr, Gewolb IH. Escherichia coli transcytosis in a Caco-2
39 Ichikawa JK, Norris A, Bangera MG, Geiss
GK, van 't Wout AB, Bumgarner RE, Lory S. Interaction of pseudomonas
40 DeRisi. Amino-alyl Dye Coupling
Protocol. Available from: URL:
41 Hasseman J. Microarray labeled probe
hybridization. Available from: URL:
42 Mai V, Morris JG Jr. Colonic bacterial flora: changing understandings in the molecular age. J Nutr 2004; 134: 459-464
43 Freter R. Control mechanisms of the
large-intestinal microflora and its influence on the host. Acta
44 Orrhage K, Nord CE. Bifidobacteria and lactobacilli in human health. Drugs Exp Clin Res 2000; 26: 95-111 PubMed
45 Savage DC. Microbial ecology of the gastrointestinal tract. Annu Rev Microbiol 1977; 31: 107-133 PubMed
46 Backhed F, Ley RE, Sonnenburg JL, Peterson DA, Gordon JI.
Host-bacterial mutualism in the human intestine. Science
47 Kagnoff MF, Eckmann L. Epithelial cells as sensors for microbial infection. J Clin Invest 1997; 100: 6-10 PubMed
48 Jung HC, Eckmann L, Yang SK, Panja A,
Fierer J, Morzycka-Wroblewska E, Kagnoff MF. A distinct array of
49 de Grado M, Rosenberger CM, Gauthier A,
Vallance BA, Finlay BB. Enteropathogenic Escherichia coli
50 Eckmann L, Smith JR, Housley MP, Dwinell
MB, Kagnoff MF. Analysis by high density cDNA arrays of altered gene
51 Firoved AM, Deretic V. Microarray
analysis of global gene expression in mucoid Pseudomonas
aeruginosa. J Bacteriol
52 Stokes NR, Zhou X, Meltzer SJ, Kaper JB.
Transcriptional responses of intestinal epithelial cells to
infection with Vibrio
53 Konaklieva MI, Plotkin BJ. Chemical communication--do we have a quorum? Mini Rev Med Chem 2006; 6: 817-825
54 Gewolb IH, Schwalbe RS, Taciak VL,
Harrison TS, Panigrahi P. Stool microflora in extremely low
55 Yoshioka H, Iseki K, Fujita K.
Development and differences of intestinal flora in the neonatal
period in breast-fed and
56 Belcher CE, Drenkow J, Kehoe B, Gingeras
TR, McNamara N, Lemjabbar H, Basbaum C, Relman DA. The
57 Rosenberger CM, Scott MG, Gold MR,
Hancock RE, Finlay BB. Salmonella typhimurium infection and
58 Pedron T, Thibault C, Sansonetti PJ. The invasive phenotype of
Shigella flexneri directs a distinct gene expression
59 Fukushima K, Ogawa H, Takahashi K, Naito
H, Funayama Y, Kitayama T, Yonezawa H, Sasaki I. Non-pathogenic
60 Ogawa H, Fukushima K, Sasaki I, Matsuno S. Identification of
genes involved in mucosal defense and inflammation
61 Hooper LV, Wong MH,
Thelin A, Hansson L, Falk PG, Gordon JI. Molecular analysis of
62 Tien MT, Girardin SE,
Regnault B, Le Bourhis L, Dillies MA, Coppee JY, Bourdet-Sicard R,
Sansonetti PJ, Pedron T. Anti-
63 Onderdonk AB. The
intestinal microflora and intra-abdominal sepsis. In: Tannock GW.
Medical importance of the
64 Evaldson G, Heimdahl
A, Kager L, Nord CE. The normal human anaerobic microflora. Scand
J Infect Dis Suppl 1982; 35:
Raangs GC, He T, Degener JE, Welling GW. Extensive set of 16S rRNA-based
probes for detection of
66 Mai V, Katki HA,
Harmsen H, Gallaher D, Schatzkin A, Baer DJ, Clevidence B. Effects
of a controlled diet and black tea
67 Kostic T, Weilharter
A, Rubino S, Delogu G, Uzzau S, Rudi K, Sessitsch A, Bodrossy L. A
microbial diagnostic microarray
68 Palmer C, Bik EM,
Eisen MB, Eckburg PB, Sana TR, Wolber PK, Relman DA, Brown PO. Rapid
quantitative profiling of
69 Scanlan PD, Shanahan
F, O'Mahony C, Marchesi JR. Culture-independent analyses of temporal
variation of the dominant
70 Suau A. Molecular tools to investigate intestinal bacterial communities. J Pediatr Gastroenterol Nutr 2003; 37: 222-224
71 Nair P, Lagerholm S,
Dutta S, Shami S, Davis K, Ma S, Malayeri M. Coprocytobiology: on
the nature of cellular elements
72 Matsushita H,
Matsumura Y, Moriya Y, Akasu T, Fujita S, Yamamoto S, Onouchi S,
Saito N, Sugito M, Ito M, Kozu T,
S- Editor Liu Y L- Editor Kerr C E- Editor Liu Y