Brindangnanam Pownraj, Coumar Mohane Selvaraj
Department of Bioinformatics, School of Life Sciences, Pondicherry University, Kalapet, Pondicherry, 605014, India.
Curr Microbiol. 2025 Aug 30;82(10):483. doi: 10.1007/s00284-025-04464-y.
The human microbiome is pivotal in maintaining health and managing diseases. By examining the core microbiome in intensive care units (ICU) patients with pneumonia, we can gain valuable insights into the microbial communities associated with disease conditions. Pneumonia is the second most common infection in ICU settings, and recent research has highlighted the significance of endotracheal aspirate (ETA) microbiota in influencing pneumonia. Analysis of 16S rRNA sequencing data from lung microbiota of ICU patients revealed Pseudomonas as a key microbial biomarker, with machine learning model (xgbTree) achieving high predictive accuracy (prAUC: 0.98 and 0.7 log loss). Functional profile analysis revealed that the ATP-binding cassette (ABC) transporters and tetracycline-resistant ribosomal protection (Tet RPPs) proteins were possible molecular biomarkers that can be targeted to address the abundant pathogenic microbiome in pneumonia patients. These findings provide critical insights into pneumonia-specific microbiome signatures, highlighting Pseudomonas as a diagnostic marker and resistance-associated functional pathways as potential intervention targets. This study contributes to the development of precision medicine strategies for pneumonia management in ICU settings.
人类微生物群落在维持健康和控制疾病方面起着关键作用。通过研究重症监护病房（ICU）肺炎患者的核心微生物群，我们可以深入了解与疾病状况相关的微生物群落。肺炎是ICU环境中第二常见的感染，最近的研究强调了气管内吸出物（ETA）微生物群在影响肺炎方面的重要性。对ICU患者肺部微生物群的16S rRNA测序数据进行分析后发现，铜绿假单胞菌是关键的微生物生物标志物，机器学习模型（xgbTree）具有较高的预测准确性（prAUC：0.98和0.7对数损失）。功能谱分析表明，ATP结合盒（ABC）转运蛋白和四环素抗性核糖体保护（Tet RPPs）蛋白可能是分子生物标志物，可作为靶点来应对肺炎患者中丰富的致病微生物群。这些发现为肺炎特异性微生物群特征提供了关键见解，突出了铜绿假单胞菌作为诊断标志物以及与耐药相关的功能途径作为潜在干预靶点。本研究有助于制定ICU环境下肺炎管理的精准医学策略。
