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  3. Co-expression Network Insights Into Leptospira Interrogans Pathogenesis.
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  3. Co-expression Network Insights Into Leptospira Interrogans Pathogenesis.

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Co-expression network insights into Leptospira interrogans pathogenesis.

João Pedro de Gomes Greco1, Natasha Rodrigues de Oliveira1, Odir Antônio Dellagostin1

  • 1Centro de Desenvolvimento Tecnológico, Universidade Federal de Pelotas, Capão do Leão, Brazil.

Research in Microbiology
|November 20, 2025

View abstract on PubMed

Summary
This summary is machine-generated.

Leptospira interrogans virulence is organized into distinct gene modules. This study maps these networks, identifying known and novel targets for leptospirosis vaccines and therapeutics.

Keywords:
GenomicsLeptospirosisRNA-SeqTranscriptomicsWGCNA

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Area of Science:

  • Bacterial Pathogenesis
  • Systems Biology
  • Transcriptomics

Background:

  • Leptospira interrogans causes leptospirosis through complex, poorly understood virulence mechanisms.
  • A systems-level understanding of L. interrogans pathogenicity is needed.

Purpose of the Study:

  • To elucidate the regulatory landscape of L. interrogans pathogenicity.
  • To map the architecture of its virulence programs using transcriptomic data.

Main Methods:

  • Weighted Gene Co-expression Network Analysis (WGCNA) was applied to a comprehensive transcriptomic dataset.
  • Gene modules associated with virulence functions were identified and characterized.

Main Results:

  • The L. interrogans transcriptome is organized into functionally coherent modules.
  • Known virulence factors concentrate in modules for host colonization, immune evasion, tissue invasion, and cytotoxicity.
  • Uncharacterized genes co-expressed with virulence factors were implicated in pathogenesis.

    • Conclusions:

    • A systems-level blueprint of L. interrogans regulatory networks driving virulence was established.
    • Novel targets for next-generation vaccines and therapeutics against leptospirosis were identified.
    • This framework advances systems-level modeling of bacterial pathogenesis and translational applications.