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Unbiased Pathogen Detection and Host Gene Profiling for Conjunctivitis.

Prajna Lalitha1, Gerami D Seitzman2, Ritesh Kotecha1

  • 1Department of Ocular Microbiology, Aravind Eye Hospital, Madurai, Tamil Nadu, India.

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Summary
This summary is machine-generated.

Metagenomic RNA deep sequencing accurately identified pathogens in 86% of conjunctivitis cases, including rare fungal infections. This method offers a powerful tool for diagnosing infectious conjunctivitis and understanding host responses.

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Area of Science:

  • Ophthalmology
  • Infectious Diseases
  • Molecular Biology

Background:

  • Conjunctivitis etiology is frequently misdiagnosed, necessitating improved diagnostic methods.
  • Accurate identification of infectious agents is crucial for effective treatment and preventing spread.

Purpose of the Study:

  • To apply unbiased metagenomic RNA deep sequencing (MDS) for identifying diverse pathogens causing conjunctivitis.
  • To explore host transcriptome signatures for differentiating infectious agents.

Main Methods:

  • Prospective collection of conjunctival swabs from patients with acute infectious conjunctivitis.
  • Unbiased metagenomic RNA deep sequencing (MDS) for pathogen identification.
  • Computational pipeline for analyzing nonhost sequences and differential gene expression analysis for host transcriptome signatures.

Main Results:

  • MDS detected pathogens in 86% (12/14) of patients.
  • Human adenovirus (HAdV) was identified in 10/14 patients, and Vittaforma corneae (fungus) in 2/14 patients.
  • Distinct host transcriptome signatures were identified for HAdV and V. corneae infections.

Conclusions:

  • MDS reliably detects and quantifies common and rare conjunctivitis pathogens, including fungi.
  • The unbiased approach expands pathogen detection scope beyond typical agents.
  • Host transcriptome signatures may aid in pathogen detection even with low pathogen loads.