First insights into the molecular basis association between promoter polymorphisms of the IL1B gene and Helicobacter pylori infection in the Sudanese population: computational approach

Abstract

Background: Helicobacter pylori (H. pylori) infects nearly half of the world’s population with a variation in incidence among different geographic regions. Genetic variants in the promoter regions of IL1B gene can affect cytokine expression and creates a condition of hypoacidity which favors the survival and colonization of H. pylori. Aim: To characterize the polymorphic sites in the 5’- region [-687_+297] of IL1B in H. pylori infection using in silico tools.Methods: Genomic DNA was extracted from 122 gastric biopsies and genotyping of IL1B-31 polymorphism was performed using PCR with confronting two-pair primer (PCR-CTPP) to investigate its association with the susceptibility to H. pylori infection in the Sudanese population. In addition, Sanger sequencing was applied to detect SNPs in the 5’-region [-687_+297] of IL1B in 14 H. pylori-infected patients; and bioinformatics analyses were used to predict whether these mutations would alter transcription factor binding sites (TFBSs) or composite regulatory elements (CEs) in this region. Also, comparative analysis was conducted for this region in 11 species using ECR browser and Mulan search engine. Results: A total of five nucleotide variations were detected in the 5’-regulatory region which led to the addition or alteration of the TFBSs and CEs. Genotyping of IL1B-31 C>T revealed a significant association between -31T and susceptibility to H. pylori infection in the studied population (P=0.0363). Comparative analysis showed conservation rates of IL1B upstream [−368_+10] region above 70% in chimpanzee, rhesus monkey, a domesticated dog, cow and rat.Conclusion: In H. pylori-infected patients, three detected SNPs (-338, -155 and -31) located in the IL1B promoter were predicted to alter TFBSs and CE, thereby might affecting gene expression. These in silico predictions provide insight for further experimental in vitro and in vivo studies of the regulation of IL1B expression and its relationship to H. pylori infection. However, recognition of regulatory motifs by computer algorithms is fundamental for understanding gene expression patterns.