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Integrated Microbiome Data Analysis Reveals Potential Pneumonia Microbial Biomarkers in ICU Patients: A Machine

Pownraj Brindangnanam1, Mohane Selvaraj Coumar2

  • 1Department of Bioinformatics, School of Life Sciences, Pondicherry University, Kalapet, Pondicherry, 605014, India.

Current Microbiology
|August 30, 2025
PubMed

Insights

This study identifies Pseudomonas as a key microbial biomarker for pneumonia in intensive care unit (ICU) patients. Targeting specific functional pathways may offer new precision medicine strategies for managing this common ICU infection.

Area of Science:

  • Microbiology
  • Medical Science
  • Computational Biology

Background:

  • The human microbiome plays a crucial role in health and disease.
  • Pneumonia is a significant infection in intensive care units (ICUs).
  • Endotracheal aspirate (ETA) microbiota are increasingly recognized for their influence on pneumonia development.

Purpose of the Study:

  • To investigate the core microbiome in ICU patients with pneumonia.
  • To identify microbial and functional biomarkers associated with pneumonia.
  • To explore potential precision medicine targets for pneumonia management.

Main Methods:

  • Analysis of 16S rRNA sequencing data from lung microbiota of ICU patients.
  • Application of machine learning models (xgbTree) for predictive analysis.
  • Functional profile analysis of identified microbial communities.

Main Results:

  • Pseudomonas was identified as a key microbial biomarker for pneumonia.
  • A machine learning model achieved high predictive accuracy (prAUC: 0.98).
  • ATP-binding cassette (ABC) transporters and tetracycline-resistant ribosomal protection (Tet RPPs) proteins were highlighted as potential molecular targets.

Conclusions:

  • Pneumonia exhibits specific microbiome signatures in ICU settings.
  • Pseudomonas serves as a potential diagnostic marker for pneumonia.
  • Functional pathways related to antibiotic resistance present viable targets for therapeutic intervention in pneumonia.

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