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Human intestinal microbiota is an extremely complex community whose interactions with host are highly important for the maintenance of gut health. Few publications concerning the interactions between intestinal microbiota and Cystic Fibrosis (CF) disease are available. On the contrary, numerous studies attribute an important role to microbiota in the pathophysiology of several diseases of the large intestine, including colorectal cancer, Crohn's disease and ulcerative colitis (Finegold S. M., 1974, Horie H., 1999, Hughes R. 2003, Linskens R. K., 2001; Macfarlane S., 2005).
Little is known about the relationship between the microbiota and the intestinal and systemic inflammation in CF patients while, the beneficial effect produced by the log term administration of the probiotic strain Lactobacillus rhamnosus GG, in reducing intestinal inflammation, has already been demonstrated (Bruzzese et a; 2004).
Intestinal inflammation and small intestinal bacterial overgrowth (SIBO) represent the main features of subjects with Cystic Fibrosis (CF) (De Lisle, 2006; Singh VV, 2003) and flatulence, bloating, abdominal pain, failure to thrive and excessive mucus accumulation (distal intestinal obstructive syndrome, Eggermont E; 1996) are other important gastrointestinal symptoms. In addition to loss of pancreatic functions that, if untreated, is responsible of a severe malnutrition due to a condition of malabsorption and maldigestion, the altered function of the intestinal tract results in important effects on growth and nutrition. Small intestinal bacterial overgrowth, in fact, can be considered the principal cause of failure to thrive that is at the same time associated to the deteriorating airway function (Pedreira C. C., 2005). In CF patients SIBO has been demonstrated on the basis of breath tests that measures the production of hydrogen gas or methane by microbial fermentation only. SIBO was instead detected with the more direct quantitative PCR technique (Norkina O, 2004) in CF mouse in which administration of broad-spectrum antibiotics improved body-weight gain to confirm the important role of SIBO in failure to thrive. Many factors in the gastrointestinal tract can influence the balance of the resident bacterial species such as concentration of antimicrobial compounds, the presence of specific substrates and growth factors, gut transit, ions concentration and pH (Macfarlane and Gibson, 1995; Kleese et al., 2001; Flint et al., 2007; Duncan et al., 2003). PH can vary with anatomical site and microbial fermentation of dietary residues and these variations may consequently have a great influence on the community composition and metabolic activity (Walker et al. 2005; Belenguer et al., 2007). The abnormal environment of the CF small intestine, characterised by an altered electrolyte concentrations and acidic pH, could be responsible of the shift of bacterial balance in favour to particular genera/species creating an abnormal composition of the microbiota that could determine or be a consequence of the intestinal inflammation.
Much of our knowledge of the diversity and distribution of the intestinal microbiota derived from bacteriological studies on faecal material, employing traditional cultural techniques that are usually intensive and time consuming, moreover a large part of the intestinal microrganisms are difficult to culture even under strictly anaerobic conditions.
Molecular techniques based on the analysis of the 16SrRNA gene sequences, on the contrary, allowed detailed studies, in particular PCR coupled with the Denaturing Gradient Gel Electrophoresis (DGGE) revealed to be a useful qualitative instrument to study the complexity of intestinal ecosystem as it provides the fingerprinting of the core of gut microbiota. At the same time the real-time PCR represents a sensitive and quantitative technique for complex population analysis.
Aim of this study was to investigate the composition of intestinal microflora of CF children and its relationship with intestinal and systemic inflammation.
The study of the intestinal microbiota was performed using the qualitative PCR-DGGE technique and confirmed by the quantitative Real-time PCR method. DGGE profiles of CF patients were compared with age matched healthy controls as to identify the modifications of predominant intestinal bacterial genera and to find a possible "core" of bands characteristic to the CF disease.
MATERIALS AND METHODS
Fourteen children with Cystic Fibrosis (age range from 7 to 10 years) and thirteen age-match healthy controls were enrolled for the study. Age, sex, body weight and CF genotype have been considered for CF patients' recruitment and the intestinal inflammation was evaluated by fecal calprotectin concentration (CLP) and rectal nitric oxide (NO) production, using rectal dialysis. Systemic inflammation was evaluated by TNFÎ± serum concentration
Bacterial DNA isolation
A total of 50 mg of feces were incubated in a lysozime buffer for one hour and than processed by the MaxwellR 16 System (Promega) using MaxwellR 16 DNA purification kit. The extracted bacterial DNA was eluted in 400 Âµl of elution buffer, quantified with the Ultrospec 2100 pro Spectrophotometer (Amersham Biosciences Corporation, Piscataway, NJ) and successfully stored at -20Â°C.
The total bacterial DNA extracted from feces was used as target in the PCR reactions. The V2-V3 region of the 16S rRNA gene was amplified using universal primers Hda1-GC (5'-CGC CCG GGG CGC GCC CCG GGC GGG GCG GGG GCA CGG GGG GAC TCC TAC GGG AGG CAG CAg T-3') and Hda2 (5'-GTA TTA CCG CGG CTG CTG GCA C-3') (Walter et al., 2000) according to the following conditions: initial denaturation at 94Â°C for 5 min; then 35 cycles of denaturation (30 sec at 94Â°C), annealing(30 sec at 58Â°C), extension(1 min at 72Â°C), and a final extension at 72Â°C for 7 min. Two Âµl of template was added into a reaction mix containing 5 Âµl of 5X Colorless GoTaqR Flexi buffer (Promega, Madison, Wi, USA), 2.5 mmol/L MgCl2, 200 Âµmol/L of each deoxynucleoside triphosphate, 20 pmol of each primer and 2.5 U of GoTaqR Flexi DNA polymerase (Promega, Madison, Wi, USA) in a final volume of 50 Âµl.
The partial 16S rRNA gene of the Clostridium coccoides- Eubacterium rectale group was amplified using primer pairs Ccoc-f+GC (5'-CGC CCG GGG CGC GCC CCG GGC GGG GCG GGG GCA CGG GGG GAA ATG ACG GTA CCT GAC TAA-3') (Maukonen et al., 2006) and Cco-r (5'-CTT TGA GTT TCA TTC TTG CGA A-3') (Matsuki et al., 2002). The PCR reaction was performed in a total volume of 50 Âµl containing 2 Âµl of the template DNA, 0.4 ÂµM of each primer, 0.2 mM dNTP, 1.25 units of GoTaqR Flexi DNA polymerase (Promega, Madison, Wi, USA) and 5 Âµl of 5X Colorless GoTaqR Flexi buffer (Promega, Madison, Wi, USA) with 2 mM MgCl2. The PCR program was characterised of an initial denaturation of 5 min at 94Â°C followed by 30 cycles at 94Â°C for 45 sec, 54Â°C for 30 sec and 72Â°C for 1 min, finally extension at 72Â°C for I min.
The V6-V8 region of the 16SrRNA was amplified with primers L1401 (5'-CGG TGT GTA CAA GAC CC-3'.) and U0968-GC (5'-CGC CCG GGG CGC GCC CCG GGC GGG GCG GGG GCA CGG GGG GAA CGC GAA GAA CCT TAC-3') (Zoetendal et al., 1998, Kostantinov et al., 2003) following the PCR program consisted on 94Â°C for 5 min, 35 cycles of 94Â°C for 30s, 58Â°C for 30s, 68Â°C for 1 min, and finally extension of 68Â°C for 7 min. 2 Âµl of the template DNA were used in a total volume of 50Âµl of a reaction mix constituted of 5X Colorless GoTaqR Flexi buffer (Promega, Madison, Wi, USA), 2.5 mmol/L MgCl2, 200 Âµmol/L of each deoxynucleoside triphosphate, 20 pmol of each primer and 2.5 U of Go GoTaqR Flexi DNA polymerase (Promega, Madison, Wi, USA). The DGGE analysis of Bacteroides-Prevotella group specific 16S rRNA was performed using primers Bac303F (5'-GAA GGT CCC CCA CAT TG-3') and Bac708R (5'-CAA TCG GAG TTC TTC GTG-3') (Bartosch et al., 2004) and an amplification program of 95Â°C for 5 min, 35 cycles of 95Â°C for 1 min, 56Â°C for 1 min, 68Â°C for 45 sec, finally 68Â°C for 5 min. The 418 bp amplification product obtained was opportunely diluted and than used as target in the nested-PCR with primers Hda1-GC and Hda2 (Walter et al., 2000).
DGGE analysis of 16S rRNA gene fragments
DGGE analysis of PCR products was performed using the INGENYphorU-2x2 SYSTEM (INGENYphorâ€¦.). Amplicons obtained with Hda1-GC/Hda2 primers pair were analysed in an 8% polyacrylamide (40% acrylamide-bis, 37.5:1) gel with a 40% to 65% denaturing gradient of urea and formamide increasing in the direction of the electrophoresis. The run was conducted with a constant voltage of 80V at 60Â°C for 18 h in a 1X Tris-acetate (TAE) (pH8.0) buffer and gels were then stained for 30Â min with SYBR Green I (Roche Applied Science) in 1x TAE buffer and viewed by UV transillumination.
The V6-V8 region of the 16S rRNA obtained with primers L1401 and U0968-GC was analysed though a 30%-60% denaturing gradient of a 8% polyacrylamide (40% acrylamide-bis, 37.5:1) gel at 100V for 20h in 0.5XTAE buffer.
The analysis of the Clostridium coccoides- Eubacterium rectale group was obtained running PCR products through a 48%-60% denaturing gradient of a 6% acrylamide (40%acrylamide-bis, 37.5:1) gel at 100V and 60Â°C for 18 h in a 1X TAE buffer. The DGGE analysis of the Bacteroides-Prevotella group specific 16S rDNA amplicons was performed according to the V2-V3 region denaturing and running conditions.
DGGE profiles of samples obtained from CF patients were compared with those of healthy controls and the similarity of bands pattern was analysed using the Fingerprinting II software (BIO Rad Hercules CA, USA). Bands with a total surface area of at least 1% were considered in the analysis and the comparison between patterns was performed using the Pearson correlation as a measure of the degree of similarity (Seksik et al., 2003). Two identical profiles create a similarity value of 100 % whereas completely different profiles result in a similarity value of 0 %.
DNA amplification and sequencing
Bands cut from DGGE gels were eluted in 50 Âµl of nuclease free water at 4Â°C for 24 h and bacterial DNA was amplified with primers Hda2 and Coc-r according to the PCR conditions described above for DGGE analysis. Total PCR reaction volume was purified using Wizard PlusR SV Minipreps-DNA Purification System (Promega, Madison, Wi) and the purified PCR DGGE fragments were analysed by the BMR Genomics. The partial 16S rRNA nucleotide sequences obtained were finally identified using the NCBI BLAST (Basic Local Alignment Search Tool) and RDP (Ribosomal Database Project).
Quantification of bacterial DNA extracted from faecal samples was performed using the LightCycler System (Roche Applied Science, Mannheim Germany). The Eubacterium rectale partial 16S rRNA gene (Ahmed et al., 2007) was amplified in a total volume of 20 Âµl containing 4 Âµl of LightCyclerR FastStart DNA MasterPLUS SYBR Green I (Roche Applied Science, Mannheim Germany), 300nM of each primer (Table 1) and 5 Âµl of target DNA. The amplification protocol consisted of one cycle of 95Â°C for 10 min and 40 cycles of 95Â°C for 10s, 64Â°C for 20s and 72Â°C for 10 s. Quantification of total bacterial DNA was carried out using 5 Âµl of template DNA and 300nM of universal 16S rRNA gene primers P0 and 338r (Table 1), following the amplification program characterised by an initial denaturation of 95Â°C for 10 min and 35 cycles at 95Â°C for 20s, 62Â°C for 20s and 72Â°C for 20s.
Bacteroides/Prevotella 16S rRNA gene was quantified using 500nM of each primer according to the follwing programm (Bartosch et al., 2004) (Table 1): 95Â°C for 10 min, 95Â°C for 30s, 60Â°C for 30s and 72Â°C for 30 s for 35 cycles.
Primers Bif F and Bif R were used at a concentration of 0,3 ÂµM to amplify Bifibobacterium 16S rRNA gene, the amplification protocol consisted on one cycle of 95Â°C for 10 min and 45 cycles of 95Â°C for 10s, 60Â°C for 20s and 72Â°C for 5 s (Penders et al., 2005) (Table 1).
The melting curves were obtained by slow heating at 0.1Â°C/s increments the temperature from 65 to 95Â°C, with continuous fluorescence collection.
For the Escherichia coli-TaqMan assay, 5 Âµl of the extracted DNA were used in a final volume of 20 Âµl containing 4Âµl of LightCyclerR TaqManR Master mix, 500nM of both primers and 100nM of TaqMan Probe (Table 1, see above).
The amplification was obtained with one cycle at 95Â°C for 10 min and 45 cycles at 95Â°C for 10 s, 62Â°C for 1 min and 72Â°C for 1 s.
RESULTS AND DISCUSSION
Twenty two children with CF were enrolled (median age 10 years; age range 7-18 years). Twenty children were dF508 homo/heterozygote, of which 4 were colonised with Pseudomonas aeruginosa. Increased CLP and NO concentrations were observed in 13/22 (59%) and 16/22 (73%) children respectively. Mean value of faecal CLP and rectal NO were significantly higher (171Â±152 vs. 61Â±69 Î¼g/gr; p =0.004; 18Â±14 vs. 2.3 Â±1.6 Î¼mol/l; p < 0.001 respectively) compared to healthy controls. Increased TNFÎ± serum concentration was observed in 10/17 children (59%). No significant correlation was observed between intestinal inflammation and age, gender, genotypes, or with systemic inflammation.
The DGGE profiles of the dominant bacterial genera of CF patients and age-match healthy controls are shown in figure 1.
Healthy controls DGGE profiles appeared more complex and more homogeneous than those of CF patients. A part from obvious inter individual differences detected in the intensity of few bands and in the number of total bands constituting the DGGE pattern, many amplicons appeared common to all healthy controls as to create a "core" representative and characteristic of the microbiota of this age. Sequence identification of the majority of bands constituting the "core" is reported in table 1.
CF DGGE profiles seem lacking a group of bands localised in the upper part of the electrophoresis run and whose sequence identification revealed as belonging to the Bacteroides and Ruminococcus genera (table1). Wide inter-individual differences of the DGGE banding pattern are instead detectable in CF samples so that it becomes difficult to identify a characteristic profile of the disease, eve if some bands result common to a lot of patients (fig 2).
A band whose sequence was identified as Eubacterium rectale, a butyrate producing bacterium belonging to the Cluster XIVa (Clostridium coccoides-Eubacterium rectale group),was characteristic to all healthy controls but weakly detectable in the CF profiles (fig 2)
The same can be said for an amplicon, whose sequence corresponds to Bifidobacterium adolescentis, which disappeared from patients profiles.
Bacterial overgrowth found in CF patients and documented by some studies on the Cystic fibrosis disease (Lisowska et al., 2009, De Lisle C.; 2007) is not so evident from our qualitative analysis. CF profiles appeared on the contrary less complex than those of healthy controls also analysing another universal region of the 16S rRNA (V6-V8) (fig 3).
The patients DGGE profiles were characterised by a band common to the majority of samples analysed and whose sequence was identified as Escherichia coli (table 2) which was on the contrary weakly visible or at least not detectable in healthy control profiles.
The overgrowth of this specie and the more often isolation of enterobacteria as dominant microrganisms have already been underlined in many studies (Ruseler-van Embden et al.; 1983, Keighley et al.; 1978, Mangin et al; 2004) and associated to intestinal inflammation states such as Crhon's disease and intestinal bowel syndrome (IBS).
The analysis of the predominant bacteria DGGE profiles with the Fingerprinting II software (underlined) divided samples into two well defined groups: the one containing CF patients and the other healthy controls. The similarity calculated with the Pearson correlation was ofâ€¦â€¦..
DGGE analysis of amplicons obtained from Clostridium coccoides- Eubacterium rectale group-specific amplification didn't reveal great differences in the banding profiles even if healthy controls appeared more complex while CF patients as characterised by few common dominant bands (fig 4). Healthy controls profiles also appeared more homogeneous, many fragments are shared by the majority of samples eve if the intensity can individually change. One band particularly appeared much more represented in healthy controls as to be detectable in all samples analysed while only in 4 to 13 CF patients this fragment seemed to be present. The nucleotide sequence of the band extracted from the gel allowed the identification of Blautia luti as indicated in table 3.
The Fingerprinting analysis DGGE profiles underlinedâ€¦â€¦
DGGE running of Bacteroides-Prevotella specific amplicons (fig 5) showed a markedly presence of two bands common to all healthy profiles which correspond to the species Bacteroides uniformis and Bacteroides vulgatus (table 3). These two species seemed instead to be less represented in CF patients banding patterns.