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May 4, 2026Biology2 citationsOpen Access

The Muco-Microbiotic Layer in Respiratory Pathophysiology: Integrating Transcriptomics, Inflammation Phenotypes, and Clinical Biomarkers in Precision Pulmonology

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CCClaudio CandiaACAdelaide CaristaMGMelania Ionelia Gratie

Key Points

  • The aim is to explore the muco-microbiotic layer's role in respiratory health and disease, focusing on inflammation and biomarkers.
  • Utilized transcriptomic and metatranscriptomic technologies to analyze the muco-microbiotic layer.
  • Examined the role of extracellular vesicle-associated RNAs in airway inflammation.
  • Highlighted multi-omic approaches for disease classification and biomarker discovery.
  • Identified that gene activity of resident microbes correlates with airway inflammation.
  • Noted distinct biomarker profiles, like exhaled nitric oxide, associated with specific disease mechanisms.
  • Proposed the muco-microbiotic layer as central to personalized care in chronic respiratory diseases.

Abstract

The lower airways are a dynamic environment where physical, microbial, and molecular factors intersect to regulate respiratory health and disease. The muco-microbiotic (MuMi) layer, composed of mucus, resident microbes, and extracellular vesicles (EVs), is not just a passive barrier but also an active site for host–microbe communication. This layer integrates epithelial cell biology, microbial activity, and immune responses within the bronchial environment. New transcriptomic and metatranscriptomic technologies show that it is not only which microbes are present but also their gene activity that closely links to airway inflammation and disease. EV-associated RNAs from both host and microbial cells act as key messengers, influencing epithelial responses, immune activity, mucus properties, and microbial behaviour. This review highlights evidence that positions the MuMi layer as central to understanding lower airway disease, particularly asthma and chronic obstructive pulmonary disease (COPD). Distinct gene expression programs and biomarker profiles, such as exhaled nitric oxide, may reflect different disease mechanisms even in cases with similar clinical features, such as eosinophilia. Multi-omic approaches focused on the MuMi layer enable better disease classification, biomarker discovery, and therapy selection. By putting the MuMi interface at the core of precision pulmonology, we provide a framework for advancing personalised care in chronic respiratory diseases.

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Cite This Study

Candia et al. (2026) studied this question.

synapsesocial.com/papers/69f837793ed186a739981a71https://doi.org/10.3390/biology15090684
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