BMC Microbiology (Jan 2021)

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

  • Abeer Babiker Idris,
  • Einas Babiker Idris,
  • Amany Eltayib Ataelmanan,
  • Ali Elbagir Ali Mohamed,
  • Bashir M. Osman Arbab,
  • El-Amin Mohamed Ibrahim,
  • Mohamed A. Hassan

DOI
https://doi.org/10.1186/s12866-020-02072-3
Journal volume & issue
Vol. 21, no. 1
pp. 1 – 15

Abstract

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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 the IL1B gene can affect cytokine expression and creates a condition of hypoacidity which favors the survival and colonization of H. pylori. Therefore, the aim of this study was to characterize the polymorphic sites in the 5′- region [−687_ + 297] of IL1B in H. pylori infection using in silico tools. Results A total of five nucleotide variations were detected in the 5′-regulatory region [−687_ + 297] of IL1B which led to the addition or alteration of transcription factor binding sites (TFBSs) or composite regulatory elements (CEs). Genotyping of IL1B − 31 C > T revealed a significant association between -31 T 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. Conclusions In H. pylori-infected patients, three detected SNPs (− 338, − 155 and − 31) located in the IL1B promoter were predicted to alter TFBSs and CE, which might affect the 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, the recognition of regulatory motifs by computer algorithms is fundamental for understanding gene expression patterns.

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