In-depth analysis of cagY in worldwide Helicobacter pylori strains unmasks a strong correlation between sequence diversity and gastric cancer

Abstract

BACKGROUND

Helicobacter pylori (H. pylori) interacts with gastric epithelial cells using a multi-protein type 4 secretion system (T4SS) whose function is regulated by cagY, the backbone of the T4SS that connects the bacterial cytoplasm with the epithelial cytoplasm. cagY is a large, highly diverse gene whose complexity has hindered its study.

AIM

To analyze cagY in a worldwide H. pylori strains collection to unmask any correlation between sequence diversity and gastric cancer (GC).

METHODS

We used 674 cagY sequences derived from 1012 H. pylori genomes, sequenced with single molecule real-time from the H. pylori genome project. Dimensional reduction analysis with principal component analyses (PCA) and linear discriminant analyses (LDA) were used to minimize the strong interference of population structure. Then, cagY genes were fragmented using unitig-caller with a designed pipeline before studying a possible association with disease.

RESULTS

Phylogenetic and PCA revealed a strong population structure with European, Asian, African and American clusters, which markedly interfered with other analyses. The PCA, LDA and unitig-caller analyses resulted in a clear separation of non-atrophic gastritis (NAG), advanced intestinal metaplasia and GC groups. Sixty-four unitigs significantly separated GC from NAG whereas the most GC-associated unitig localized in module A of the middle repeat region of the protein. This module includes the cysteine-containing motif YLDCVSQ, forming a cysteine-rich region associated with the structure of the protein and with its rheostat function. The KLIGLGKGRSER motive was also associated with GC in a region suggested to recognize the integrin receptor on gastric cells.

CONCLUSION

A proper informatic analyses of cagY variants distinguished GC from NAG patients. Localization of cagY variants may explain the mechanisms by which it regulates T4SS function, modulating inflammation and tissue damage.

Keywords: Bioinformatics; Helicobacter pylori; cagY; Machine learning; Phenotype association

Core Tip: cagY is a Helicobacter pylori gene with a strong population structure, attesting to an ancient co-evolution with humans. We report that with a proper bioinformatic analyses cagY variants may distinguish patients with gastric cancer (GC) from those with non-atrophic gastritis. The GC-associated variants localized in two relevant regions of cagY, one in a cysteine-enriched repetitive region that sustains the complex structure of the multimer-protein, and the other in a region of the protein that interacts with the epithelial cells. Mutations in these regions might be part of the mechanisms by which cagY modulates the inflammatory response and causes tissue damage.