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<p><i>Helicobacter pylori (H. pylori)</i> is a Class I carcinogen whose pathogenic success in the harsh gastric environment depends on a complex repertoire of virulence factors (virulome). Despite extensive research, the systems-level coordination of these factors remains poorly understood. This study employed computational network biology to construct and analyze a Protein–Protein Interaction (PPI) network of 139 potential virulence factors. Integrating data from PATRIC, VFDB, and STRING, we generated a core network of 94 nodes and 811 high-confidence functional interactions. Topological analysis identified critical “hub” and “bottleneck” proteins that act as central regulators of information flow. Specifically, proteins such as CheAY, FlgH, FlaB, and FlgK, primarily involved in chemotaxis and flagellar assembly, exhibited the highest degree and betweenness centrality (BC). Interestingly, the CagA effector was classified as a “nonhub-bottleneck,” suggesting its role as a high-leverage architectural bridge between the Type IV Secretion System and host-signaling pathways rather than a structural hub. Functional enrichment analysis further confirmed that motility-related pathways are central to the network’s modular architecture. To ensure robustness, the biological network was validated against 1000 Barabási-Albert random simulations, revealing a non-random, specialized organization designed for coordinated pathogenesis (<i>p</i> &lt; 0.001). These findings provide a prioritized roadmap of hub-bottleneck genes as high-priority candidates for novel anti-virulence therapeutics.</p>

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Co-expression network analysis and systems-level mapping of hub-bottleneck regulators deciphers the virulence architecture of Helicobacter pylori

  • 期刊论文

  • 发表日期：

    2026年2月12日

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  • G. Tamizh Selvan,
  • H. S. Santosh Kumar,
  • Pavan Gollapalli

摘要

Helicobacter pylori (H. pylori) is a Class I carcinogen whose pathogenic success in the harsh gastric environment depends on a complex repertoire of virulence factors (virulome). Despite extensive research, the systems-level coordination of these factors remains poorly understood. This study employed computational network biology to construct and analyze a Protein–Protein Interaction (PPI) network of 139 potential virulence factors. Integrating data from PATRIC, VFDB, and STRING, we generated a core network of 94 nodes and 811 high-confidence functional interactions. Topological analysis identified critical “hub” and “bottleneck” proteins that act as central regulators of information flow. Specifically, proteins such as CheAY, FlgH, FlaB, and FlgK, primarily involved in chemotaxis and flagellar assembly, exhibited the highest degree and betweenness centrality (BC). Interestingly, the CagA effector was classified as a “nonhub-bottleneck,” suggesting its role as a high-leverage architectural bridge between the Type IV Secretion System and host-signaling pathways rather than a structural hub. Functional enrichment analysis further confirmed that motility-related pathways are central to the network’s modular architecture. To ensure robustness, the biological network was validated against 1000 Barabási-Albert random simulations, revealing a non-random, specialized organization designed for coordinated pathogenesis (p < 0.001). These findings provide a prioritized roadmap of hub-bottleneck genes as high-priority candidates for novel anti-virulence therapeutics.