Evidence map›Paper›PMID 39065215›Full record

ArticleMicroorganisms2024

The Metabolic Potential of the Human Lung Microbiome.

Florian Semmler, Matheus Regis Belisário-Ferrari, Maria Kulosa, Leonard Kaysser

Abstract read
In one paragraph

Article in Microorganisms, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Review
  2. Establishment of anmSystems · 2026
    Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Florian SemmlerDepartment of Pharmaceutical Biology, Institute for Drug Discovery, University of Leipzig, 04317 Leipzig, Germany.
Matheus Regis Belisário-FerrariDepartment of Pharmaceutical Biology, Institute for Drug Discovery, University of Leipzig, 04317 Leipzig, Germany.
Maria KulosaDepartment of Pharmaceutical Biology, Institute for Drug Discovery, University of Leipzig, 04317 Leipzig, Germany.
Leonard KaysserDepartment of Pharmaceutical Biology, Institute for Drug Discovery, University of Leipzig, 04317 Leipzig, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The human lung microbiome remains largely underexplored, despite its potential implications in the pharmacokinetics of inhaled drugs and its involvement in lung diseases. Interactions within these bacterial communities and with the host are complex processes which often involve microbial small molecules. In this study, we employed a computational approach to describe the metabolic potential of the human lung microbiome. By utilizing antiSMASH and BiG-SCAPE software, we identified 1831 biosynthetic gene clusters for the production of specialized metabolites in a carefully compiled genome database of lung-associated bacteria and fungi. It was shown that RiPPs represent the largest class of natural products within the bacteriome, while NRPs constitute the largest class of natural products in the lung mycobiome. All predicted BGCs were further categorized into 767 gene cluster families, and a subsequent network analysis highlighted that these families are widely distributed and contain many uncharacterized members. Moreover, in-depth annotation allowed the assignment of certain gene clusters to putative lung-specific functions within the microbiome, such as osmoadaptation or surfactant synthesis. This study establishes the lung microbiome as a prolific source for secondary metabolites and lays the groundwork for detailed investigation of this unique environment.

Indexed as

bacterial interactionbiosynthetic gene clustergenome mininglung microbiomemetabolic potentialmycobiome

Identifiers

PMID39065215
PMCPMC11278768

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.