Towards an ecology of the lung: new conceptual models of pulmonary microbiology and pneumonia pathogenesis
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Pneumonia is a major cause of morbidity and mortality for which no new methods of treatment have entered clinical practice since the discovery of antibiotics. Innovations in the techniques of culture-independent microbial identification have shown that the lungs, previously deemed sterile in the absence of infection, contain diverse and dynamic communities of microbes. In this Personal View, we argue that these observations have shown the inadequacy of traditional conceptual models of lung microbiology and the pathogenesis of pneumonia, hampering progress in research and practice. We propose three new conceptual models to replace the traditional models of lung microbiology: an adapted island model of lung biogeography, the effect of environmental gradients on lung microbiota, and pneumonia as an emergent phenomenon propelled by unexplored positive feedback loops. We argue that the ecosystem of lung microbiota has all of the features of a complex adaptive system: diverse entities interacting with each other within a common space, showing interdependent actions and possessing the capacity to adapt to changes in conditions. Complex adaptive systems are fundamentally different in behaviour from the simple, linear systems typified by the traditional model of pneumonia pathogenesis, and need distinct analytical approaches.
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The microbiome and alveolar injury can propel each other in a dysregulated feedback loop that spans the host-microbiome divide.
“The microbiome and alveolar injury can propel each other in a dysregulated feedback loop that spans the host–microbiome divide”
From The microbiome and critical illness (2016) · cites this paper as [113]
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Schneeberger, P. H. H., Zhang, C. Y. K., Santilli, J., Chen, B., Xu, W., Lee, Y., Wijesinha, Z., Reguera-Nuñez, E., Yee, N., Ahmed, M., et al. (2022) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.202110-2413oc · Cited by 38 · see citing works
- Authors
- Dickson, R. P., Erb-Downward, J. R., & Huffnagle, G. B.
- Affiliations
- University of Michigan (US)
- Corresponding author
- Dickson, Robert P
- Venue
- The Lancet Respiratory Medicine
- Publisher
- Elsevier BV
- Published
- 2014-03
- Volume
- 2
- Issue
- 3
- Pages
- 238-246
- ISSN
- 2213-2600 (ISSN-L)
- PMC
- PMC4004084
- OpenAlex
- W2156749754
- Cited by
- 371
- References
- 84
- Citations by year
- 2026: 35 · 2025: 43 · 2024: 39 · 2023: 24 · 2022: 25 · 2021: 44 · 2020: 30 · 2019: 30 · 2018: 26 · 2017: 26 · 2016: 22 · 2015: 19 · 2014: 8
- FWCI
- 18.89
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- The Lancet Respiratory Medicine (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health
- National Heart, Lung, and Blood Institute (U01HL098961, L30 HL120241, T32HL00774921, R01HL114447, T32HL007749)
- Topics
- Health Sciences › Medicine › Epidemiology › Pneumonia and Respiratory Infections
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Health Sciences › Medicine › Critical Care and Intensive Care Medicine › Nosocomial Infections in ICU
- Keywords
- lung microbiome, pneumonia pathogenesis, island model, environmental gradients, complex adaptive systems, positive feedback loop, emergence
- MeSH terms
- Humans, Lung, Models, Biological, Pneumonia
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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