Table 1.

Summary of key studies on the lung microbiota in chronic, acute, and other types of lung diseases

Disease	Study	Specimen	Design and sample size	Methods	Key findings
COPD	Wang et al. (2016)	Sputum	Stable, exacerbations, posttherapy, recovery, 476 samples, 87 patients	16S V3–V5	● Moraxella increased in exacerbations. ● Proteobacteria increased in bacterial versus eosinophil exacerbations.
COPD	Wang et al. (2018)	Sputum	Stable, exacerbations, 715 samples, 287 patients	16S V4	● Veillonella decreased in exacerbations. ● Proteobacteria increased in bacterial versus eosinophil exacerbations. ● Microbiome temporal variability increased in frequent exacerbators.
COPD	Dicker et al. (2020)	Sputum	Stable, exacerbations, 252 patients	16S V4	● Proteobacteria increased in noneosinophilic phenotype, and associated with increased mortality and neutrophil markers.
COPD	Wang et al. (2020)	Sputum	1666 Microbiome samples, 1340 human transcriptome samples	16S, metagenomics, host transcriptome	● Haemophilius, Moraxella, Streptococcus, and Lactobacillus increased in COPD. ● Butyrate, homocysteine, and palmitate associated with COPD host genes.
COPD	Wang et al. (2021)	Sputum	Stable, exacerbations, 1706 sputum samples, 510 patients	16S V4, V3–V5	● Two microbial communities in neutrophilic COPD differentiated by Haemophilus and associated with IL‐1β and TNF‐α, or IL‐17A. ● Campylobacter and Granulicatella were associated with sputum eosinophilia over time.
Asthma	Huang et al. (2015)	Bronchial brushing	40 Patients	16S phylochip, host transcriptomics	● Proteobacteria associated with airway leukocytes. ● Actinobacteria associated with FKBP5, an indicator of steroid responsiveness.
Asthma	Taylor et al. (2018)	Sputum	167 Patients	16S V1–V3	● Haemophilus was dominant in neutrophilic asthma. ● Gemella and Porphyromonas enriched in eosinophilic asthma.
Asthma	Abdel‐Aziz et al. (2020)	Sputum	100 Severe and 24 mild‐moderate asthma	16S, metagenomics	● Two microbiome clusters identified. ● The cluster 2 patients had dysbiosis, increased neutrophils, and worse outcomes.
Asthma	Sharma et al. (2019)	BAL, endobronchial brush	39 Asthma and 19 controls	16S V4, ITS	● Fusarium, Cladosporium, and Aspergillus enriched in T2‐high asthma. ● Aspergillus, Fusarium, and Penicillium correlated with FEV1.
Bronchiectasis	Guan et al. (2018)	Sputum	106 Patients and 17 controls	16S V4	● Patients divided into three groups (PA, PPM, and commensal). ● α‐Diversity decreased in the PA group. ● Haemophilus increased in the PPM group.
Bronchiectasis	Mac Aogain et al. (2018)	Sputum	238 Patients and 10 controls	ITS	● Aspergillus, Cryptococcus, and Clavispora are bronchiectasis‐associated. ● Aspergillus terreus associated with exacerbations.
Bronchiectasis	Mac Aogain et al. (2021)	Sputum	217 Patients and 30 controls. A validation cohort with 166 patients	16S V3–V4, ITS, viral qPCR, metagenomics	● Complexity of microbial co‐occurrence networks decreased in frequent exacerbators. ● Microbial antagonism during exacerbations, which resolves following treatment.
Cystic fibrosis	Zemanick et al. (2017)	BAL	146 Patients and 45 controls	16S V1–V2	● Streptococcus, Prevotella, and Veillonella associated with airway inflammation. ● Streptococcus predominated in patients aged <2 years.
IPF	Molyneaux et al. (2017)	BALF, blood	60 Patients and 20 controls, patients sampled longitudinally	16S V3–V5, human transcriptome	● Two gene modules are associated with airway microbiome, bacterial burden, and neutrophilia.
Pneumonia	Kitsios et al. (2018)	Endotracheal aspirates	56 Patients	16S V4	● Sequencing is congruent and more sensitive than culture in detecting pathogenic bacteria.
Sepsis/ARDS	Dickson et al. (2016)	BALF	100 Samples from 68 patients	16S V4	● Lung communities were dominated by gut‐associated bacteria (Bacteroides spp.). ● Alveolar TNF‐α was correlated with altered lung microbiota.
ARDS	Kyo et al. (2019)	BALF	40 Patients, 7 controls	16S V5–V6	● Microbiota diversity decreased and bacterial loads increased in ARDS. ● Staphylococcus, Streptococcus, and Enterobacteriaceae associated with mortality.
ARDS	Panzer et al. (2018)	Endotracheal aspirate	74 On ICU admission, 30 at 48 h after admission	16S V4	● Streptococcus, Fusobacterium, Prevotella, and Treponema associated with smoking. ● ARDS associated with Enterobacteriaceae, Prevotella, and Fusobacterium.
COVID‐19	Sulaiman et al. (2021)	Bronchoscopies	142 Patients	Metagenomics, metatranscriptomics, host transcriptome	● Poor clinical outcome was associated with Mycoplasma salivarium. ● Increased SARS‐CoV‐2 abundance and host transcriptome profile predict mortality.
COVID‐19	Zhong et al. (2021)	Sputum, nasal and throat swab, anal swab and feces	8 Mildly and 15 severely ill patients, 47 airway samples, 20 anal swab and feces	Metatranscriptomics	● Burkholderia cepacia, Staphylococcus epidermidis, or Mycoplasma increased in severely ill patients.
COVID‐19	Ren et al. (2021)	Oropharyngeal swab	588 Samples, 192 patients and 95 controls	Metatranscriptomics	● Streptococcus increased in recovered patients. ● Streptococcus parasanguinis correlated with prognosis in nonsevere patients.
Lung cancer	Tsay et al. (2018)	Airway brushings	39 Lung cancer, 36 noncancer, and 10 healthy controls	16S V4, human transcriptome	● Streptococcus and Veillonella increased in lung cancer. ● Veillonella, Prevotella, and Streptococcus associated with ERK and PI3K signaling.
Lung cancer	Tsay et al. (2021)	Bronchoscope, airway brushing	83 Lung cancer patients	16S V4, human transcriptome	● Veilonella parvula led to decreased survival, increased tumor burden, IL‐17 inflammatory, and activation of checkpoint inhibitor markers.
Lung transplantation	Combs et al. (2021)	BALF	134 Patients	16S, droplet digital PCR	● Increased bacterial burden, but no individual taxa associated with CLAD.
Lung transplantation	Bernasconi et al. (2016)	BALF	203 Samples from 112 patients postlung transplantation	16S V1–V2	● Lung microbiota profile aligned with distinct innate cell gene expression. ● “Inflammatory” and “remodeling” profiles linked to bacterial dysbiosis.
Lung transplantation	Watzenboeck et al. (2022)	BALF	78 Lung donors and recipients	16S V1–V2, lipidomics, and metabolome	● Recipient‐specific and environmental factors shape the long‐term lung microbiome. ● Multiomics predict future changes of FEV1.
HIV	Lozupone et al. (2013)	BALF	82 HIV‐positive, 77 HIV‐negative	16S, metagenomics	● Tropheryma whipplei increased in HIV and decreased with antiretroviral therapy.
HIV	Twigg 3rd et al. (2016)	BALF	30 HIV‐positive, 22 HIV‐negative	16S V1–V3	● Streptococcus increased in HIV and Flavobacterium increased in controls. ● Prevotella and Veillonella increased after 1 year of treatment.
Tuberculosis	Hu et al. (2020)	BALF	30 MTB+, 30 MTB−	16S V3–V4, metagenomics	● Mycobacterium tuberculosis dominated in MTB+ subjects and impacted the microbial functional profile and fungal community.
Tuberculosis	Zhou et al. (2015)	BALF	32 MTB+, 24 MTB−	16S V3	● Cupriavidus increased in TB. ● Mycobacteria and Porphyromonas increased inside TB lesions.

Abbreviations: ARDS, acute respiratory distress syndrome; BAL, bronchoalveolar lavage; COPD, chronic obstructive pulmonary disease; ERK, extracellular signal‐regulated kinase; HIV, human immunodeficiency virus; IL, interleukin; IPF, idiopathic pulmonary fibrosis; ITS, internal transcribed spacer; PA, pseudomonas aeruginosa; PI3K, phosphatidylinositol 3‐kinase; PPM, potentially pathogenic microorganisms; qPCR, quantitative polymerase chain reaction; SARS‐CoV‐2, severe acute respiratory syndrome coronavirus 2; TB, tuberculosis; TNF‐α, tumor necrosis factor alpha.