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P792 Modulation of the fecal metagenome in patients with Crohn's disease

Rojas-Feria M.*1, Fernández Caballero-Rico J.A.2, Pastor Ramírez H.3, Castro-Fernandez M.1, Chueca Porcuna N.2, Grande Santamaría L.1, Romero-Gόmez M.3, García F.2, Del Campo J.A.1

1Valme Hospital, UGC Digestive Disease, Seville, Spain 2Complejo Hospitalario Universitario de Granada, Microbiology, Granada, Spain 3Institute of Biomedicine of Seville, UG IC Digestive Diseases Virgen Macarena-Virgen Rocío, Seville, Spain

Background

Patterns of gut microbiome dysbiosis in inflammatory bowel disease (IBD) patients are inconsistent among published studies. In this work, we explored associations between the gut microbiota and active IBD to analyze the potential of a convenient and early diagnosis of Crohn's disease (CD).

Methods

Fecal samples of new-onset CD patients and healthy controls were collected. Fecal samples were homogenized and DNA was extracted using QIAamp DNA Mini Kit (QIAGEN, Barcelona, Spain). DNA was then amplified by PCR using primers directed to targets flanking the variable regions 1 to 3 in the 16S bacterial rRNA gene.

A DNA pool with barcoded equimolar PCR products was used for clonal amplification and pyrosequencing in a GS Junior (Roche, Switzerland). For sequence analysis, MG-RAST server with the database ribosomal Project (RDP) was used, converting DNA sequences into relative abundances of microorganisms of different taxonomic levels. Statistical analysis were performed using the GraphPadPrism 7 and SPSS 20.0 software. Differences between means were performed with significance tests using an analysis of variance (ANOVA) and post-hoc test with less significance. Nonparametric data are expressed as median (range) and analyzed using the Mann-Whitney U test. Differences between proportions were analyzed by chi-square test. Significance was accepted at p<0.05.

Results

Microbial community was characterized using 16S rRNA gene sequencing in 29 samples (n=13 CD patients, and n=16 healthy controls). The mean Shannon diversity was higher in the healthy control population compared to CD group (5.5 vs. 3.7). A decreased number of species was found in the CD group.

Dysbiosis was observed in CD group due to increased population of Firmicutes, presenting a Firmicutes/Bacteroidetes ratio of 1.71 versus 0.80 in controls. 77,143 readings were obtained in the case of control samples and 69,296 reads in CD group. A grouping pattern was identified for most of the subjects in both groups, showing a marked difference between control and CD groups. A permutational ANOVA calculated by FIRST showed statistically significant differences between groups. Significant differences were found in Entomoplasmataceae, Bacteriaceae, Lachnospiraceae, Ruminococcaceae and Rikenellaceae. When relative abundance of bacterial genera was analyzed, significant differences in Ruminococus, Roseburia, Parabacteroides, Mesoplasma, Faecalibacterium, Eubacterium and Alistipes were observed, showing an increased distribution in the control group.

Conclusion

Less biodiversity and a significantly different pattern on microbiota distribution has been found in active CD patients compared to control group. Patients with CD may benefit from these findings in the early diagnosis and follow-up.