Functional effects of microbiota in chronic respiratory
disease
Kurtis F Budden*, Shakti D Shukla*, Saima Firdous Rehman, Philip Hugenholtz, Darius PH
Armstrong-James, Ian M Adcock, Sanjay H Chotirmall, Kian Fan Chung, Philip M Hansbro
*Contributed equally
Priority Research Centre for Healthy Lungs, Hunter Medical Research Institute and The
University of Newcastle, Newcastle, New South Wales, Australia (K F Budden, S D Shukla
PhD, S F Rehman, P M Hansbro PhD); Australian Centre for Ecogenomics, School of
Chemistry and Molecular Biology, The University of Queensland, Queensland, Australia (P
Hugenholtz); National Heart & Lung Institute, Imperial College London, London, UK (DPH
Armstrong-James, I M Adcock PhD, K F Chung DSc); Lee Kong Chian School of Medicine,
Nanyang Technological University, Singapore (S H Chotirmall PhD); Centenary Institute and
University of Technology Sydney (P M Hansbro PhD)
Correspondence to:
Prof Philip M Hansbro,
Priority Research Centre for Healthy Lungs,
Hunter Medical Research Institute and The University of Newcastle,
Newcastle, New South Wales, 2300, Australia
1
The composition of the lung microbiome is increasingly well characterised, with dysbiosis
changes in microbial diversity or abundance a key factor in chronic respiratory diseases
(CRDs) such as asthma, cystic fibrosis, bronchiectasis and chronic obstructive pulmonary
disease (COPD). However, the precise effects of dysbiosis the microbiome and the functional
mechanisms by which itthe microbiome regulates host immunity are only now beginning to
be elucidated. Bacteria, viruses and fungi from both the upper and lower respiratory tract
produce structural ligands and metabolites which interact with the host and alter the
development and progression of CRDs. Here, we review recent advances in our
understanding of the composition of the lung microbiome, including the virome and
mycobiome, the mechanisms by which these microbes interact with host immunity, and
their functional effects on the pathogenesis of CRDs, their exacerbations and co-
morbidities., We also describe the current knowledge of interactions between respiratory
microbiota and common therapies of CRDs, and the potential manipulation of the
respiratory microbiome as a therapeutic strategy. Finally, we highlight some of the current
limitations in the field and propose how these may be addressed in future research.
2
Search Strategy and selection Criteria
References for this review were identified through searches of PubMed and Google scholar
for articles published from January, 2007, to June 2018 by use of the terms “lung
microbiome”, “microbiota”, “lung microbiota”, “gut microbiota”, “lung mycobiome”, “lung
virome”, “functional”, “respiratory disease”, “COPD”, “Cystic fibrosis”, “Bronchiectasis” and
“Asthma”. Articles were identified as relevant where studies provided mechanistic insight
into the effects of lung microbiota. Articles resulting from these searches and relevant
references cited in those articles were reviewed. Articles published in English were included.
Key Messages
Although dysbiosis of tThe composition of the respiratory microbiome has been
identified characterised in chronic respiratory diseases (CRDs), yet there is little
available information regarding the mechanisms by which the microbiota regulate
disease development and progression.
Recently, the functional effects of key structural ligands and metabolites from
bacteria, viruses and fungi of the lung microbiota on boht innate and adaptive
immunity have been characterised identified, influencing the development and
progression ofin the context of CRDs, their exacerbations and co-morbidities such as
asthma, cystic fibrosis, bronchiectasis and chronic obstructive pulmonary disease.
Respiratory microbiota may also impact on, or be impacted by, common treatments
for CRDs or extra-pulmonary co-morbidities, resulting in functional consequences in
the lungand may present novel therapeutic targets.
3
Significant limitations remain in our understanding of the functional effects of
respiratory microbiota. We propose that improved understanding in this field can be
driven by improved assessment of microbial function through integrated ‘omics,
targeted study of the virome/mycobiome and their interaction with bacteria,
improved experimental design and emphasis on interventional studies.
Improved understanding of the mechanisms by which lung microbiota interact with
the host may facilitate the development of novel therapeutic strategies to improve
outcomes of CRDs.
Introduction to the respiratory microbiome
The term “microbiome” refers to the collective sum of microorganisms (i.e. bacteria, archea,
viruses, fungi), their genomes, products and environmental conditions in a given
ecosystem.1,2 Subsets of the microbiome are defined as the bacteriome, virome and
mycobiome. “Microbiota” refers to only the microorganisms themselves at a particular
site, , and are classified as pathogenic (causing or contributing to disease
development/progression) or commensal (non-disease causing; interaction neutral or
beneficial for host), although this distinction may differ depending on the disease in
question.2,3 They are detected throughout the upper (URT) and lower respiratory tract (LRT),
with distinct populations and different burdens at different sites.2
Bacteria are not the only microbes constantly present in the respiratory tract, and
our appreciation of the virome and mycobiome is rapidly increasing. The bacteriome and
virome develop soon after birth, and are dynamic and dependent on environmental factors
and genetic background.2,4 They profoundly affect the evolution of innate and adaptive
immune responses,2,5 and can be categorised into pathogenic and commensal components
4
(for viruses; endogenous retroelements and long-term resident persisters).6 Further
complexity occurs with the propensity for rapid genetic evolution of bacteria and viruses.
Bacterial burden in the URT is 100-10,000 times greater than in the LRT, with the
nasal cavity dominated by members of the genera Propionibacterium, Cornynebacterium,
Staphylococcus and Moraxella, and the oral cavity containing primarily Prevotella,
Veillonella, Streptococcus, Haemophilus, Fusobacterium, Neisseria and Corynebacterium.7-9
Microbes from the URT (especially the oral cavity) and external environment enter the LRT,
and the balance of microbial migration (breathing, mucocilliary clearance, microaspiration),
elimination and growth results in a viable bacterial presence without long-term colonisation,
termed a transient or non-resident microbiome.2,10 Though a core microbiome dominated by
Streptococcus, Prevotella, Veillonella, Pseudomonas, Haemophilus and Fusobacterium has
been reported in healthy individuals, 8,9,11Because of the low bacterial load and transient
population, the LRT microbiome has greater variability in community composition and
susceptibility to environmental changes than the URT.,12 This is partially due to the low
bacterial load and transient population, as well as lung architecture (e.g. increasing number
of bronchial branches deeper in the lungs can unevenly disperse inhaled bacteria). Regional
variation in mucus or surfactant secretion, pH, and nutrient (e.g. iron, vitamins) or oxygen
availability (e.g. gas trapping) can also increase biogeographical variability in the LRT
microbiota, and these may be exacerbated during inflammation or structural changes in
CRDs.8but a core microbiome dominated by Streptococcus, Prevotella, Veillonella,
Pseudomonas, Haemophilus and Fusobacterium has been reported in healthy individuals.
The recently discovered diverse vertebrate viral family, the Anelloviridiae family
forms around 70% of the human virome in blood and most organs including the respiratory
5
tract,5 and other significant components include herpes viruses and human papillomavirus.4
Anellovirdiae are currently thought to be apathogenic, but our understanding of how they
influence host immunity is at a nascent stage. There is also a core set of viral predators of
bacteria (bacteriophages) in the URT and LRT, which may alter the microbiome by killing
specific bacterial subpopulations.13 Metagenomic approaches have identified many new
viruses in the respiratory tract with unknown effects, but respiratory syncytial virus (RSV),
influenza A virus (IAV) and rhinovirus are well known to have pathogenic effects.
Fungi lack detailed characterisation in the respiratory tract. Next generation
sequencing, so powerful in profiling bacteria, has substantially increased the understanding
of the pulmonary mycobiome, but is hampered by a dearth of fungal ‘reference’ genes
comparable to bacterial 16S rRNA. The eukaryotic equivalent 18S rRNA does not show good
resolution and the widely used internal transcribed spacer 1 (ITS1) region of the eukaryotic
ribosomal cluster is limited in its ability to uncover fungal diversity.14 The airway is
constantly exposed to fungal spores, but most healthy individuals effectively clear them
with no consequence. Host susceptibility and immune status determines if acute or chronic
disease results. Fungal pathogens exhibit remarkable adaptability to the human lung, partly
due to the expansion of biosynthetic gene clusters, which produce bioactive secondary
metabolites and encompass human toxins (e.g. aflatoxin).15 Given its dominance as the
primary human fungal pathogen, there is sustained interest in how the filamentous
Aspergillus fumigatus exploits these metabolites for virulence and over 30 biosynthetic gene
clusters are known.16
An improved understanding of how bacteria, viruses and fungi of the microbiome
affect the respiratory tract is required to understand their role in disease.
6
Influence on Immunity: Signals from the respiratory microbiome (figure 1)
‘Pneumotypes’, as described by Segal et al., are descriptions of microbiome composition
associated with particular phenotypesphenotypes.17 Enrichment of the LRT microbiome with
oral taxa in healthy individuals is associated with Th17-driven inflammation,17 and lung
transplant recipients with neutrophilic activation profiles or macrophage-dominant,
remodelling profiles have different patterns of dysbiosis (Firmicutes/Proteobacteria- vs
Bacteroidetes-dominant).18 In mice, lung community composition correlates with IL-1α and
IL-4 abundance. However, IL-1 receptor blockade did not alter microbiome composition,
suggesting that, at least in some circumstances, microbiota drive immune phenotypes as
opposed to immunity changing microbiome composition.12 Host immunity is contingent on
symbiosis with the microbiome, and therefore the virome and mycobiome are further important
cofactors in shaping the pulmonary inflammatory response.4,5,19
To define how microbiota shape lung and systemic immunity, it is essential to understand
the signals they present, which are broadly similar between the respiratory tract and gut
microbiota but differ in abundance, composition and localised effects.
Structural ligands
Structural microbial ligands are recognised by host pattern recognition receptors (PRRs),
including Toll-like receptors (TLRs).20 Microbiota stimulation of TLRs improves host defence
through IgA production,21 and the TLR4 agonist lipopolysaccharide (LPS) from Escherichia
coli promotes inflammatory cytokine responses in human alveolar macrophages.17
7
Moreover, intranasal treatment of exopolysaccharide from Bifidobacterium longum to mice
stimulates TLR2 to promote allergic tolerance through IL-10 production and increased
M1/M2 macrophage ratio.22 These studies demonstrate roles for microbiota-derived TLR
agonists in immune regulation yet the ligands were isolated from gut commensals. Whether
ligands from lung microbiota exert similar effects is unclear, although pathogenic members
of the lung microbiome stimulate TLRs more efficiently than commensals,3,8,20 and TLR2/4
are needed for bacteria-mediated protection against allergic airway disease (AAD).23
Furthermore, LRT microbiome composition is associated with the magnitude of TLR
responses, adding further complexity.17
Other host PRRs are involved in host-microbiome interactions, such as the NOD-like
receptor (NLR) NOD2 which is stimulated by peptidoglycan from lung microbiota to promote
alveolar macrophage responses to infection.24 Not all microbiome ligands are derived from
bacteria. RNA from the archaeum Methanosphera stadtmanae promotes antiviral immunity
and activates the inflammasome in monocytes and dendritic cells,25 and torquetenovirus
regulates inflammatory responses through stimulatory CpG (TLR9 agonists),
immunoregulatory miRNAs, and ORF2-mediated suppression of NF-κB translocation.5
Crucially, these effects are species- or strain-specific, and highlight how slight variations in
microbiome composition may have major impacts on immunity. The respiratory virome further
primes and modulates host immune responses and contains bacteriophages, influenced by
environmental exposure and the presence of CRD.4,25
8
MetabolitesMetabolites
Predicting microbial metabolic effects on the lungs from culture-based assays and
community profiling (e.g. 16S rRNA gene sequencing) is unreliable. Pseudomonas
aeruginosa cultured on yeast/malt extract or artificial sputum medium produce vastly
different metabolic profiles, with only the latter producing quinolones, phenazines and
rhamnolipids representative of sputum from cystic fibrosis (CF) patients.26 In contrast,
assessing microbial function through transcriptomics27 and metabolomics28 shows that
metabolic pathways (e.g. fatty acid, sugar and amino acid metabolism) associated with
microbiota have roles in regulating lung nutrient supply. Microbial immunoregulatory
metabolites produced at distal body sites may also affect the lung but have not been
extensively investigated. Changes in intestinal microbiomes reflect that seen in the oropharynx
(including the mycobiome) which through microaspiration directly impacts upon the respiratory
microbiome and host immune response.29 Gut and oral microbiomes reduce dietary nitrate to,
regulate oxidative stress, and produce vasoactive and anti-inflammatory nitrite, nitric oxide
and short chain fatty acids (SCFAs) from fermentation of dietary fibre. These metabolites are
linked to protection against acute and chronic respiratory diseases (CRDs) by inhibiting
histone deacetylases or activating GPR41, GPR43 and GPR109A receptors.2,7 Lung microbiota
such as Pseudomonas species are nitrate reducers7 and others (including Staphylococcus
species) also produce SCFAs.30,31 Whether other gut microbial metabolites, such as anti-
inflammatory trimethylamine or its more toxic product trimethylamine N-oxide are
produced by respiratory microbiota is unclear.32 The tryptophan metabolite indole-3-acteate
is produced by lung microbiota and suppresses macrophage inflammatory responses.31
9
Fungi such as A. fumigatus also synthesise a range of aromatic amino acids
(tryptophan, phenylalanine, tyrosine), which are precursors of toxins such as gliotoxin and
fumigaclavine C.33 Gliotoxin suppresses IFN-γ responses and induces neutrophil apoptosis,34
whilst fumigaclavine C downregulates Th1 cytokines and induces host cell apoptosis.35
Fungal tryptophan is converted by host indolamine 2,3-dioxygenase to kyneurine, which
leads to the expansion of regulatory T-cells and downregulation of Th17-mediated mucosal
inflammation.36 Thus, fungal aromatic amino acids may induce lung inflammation, and
downstream secondary metabolites suppress protective immunity.
Finally, cross-feeding between microbiota may amplify the impacts on host immunity
through synergistic effects. Volatile metabolites from P. aeruginosa or A. fumigatus
stimulate IL-1β production in an organotypic lung model, but co-cultures of both microbes
induced IL-1β but also GM-CSF, CXCL8, IL-6 and IFN-γ.37
However, studies of CRDs through global metabolomics have been limited by technical
difficulties in sample collection (blood contamination of biopsies; sample dilution in BALF),
preparation (inflammatory cells, solute and gel phases in a single sample), metabolite
identification (library development; identification of breakdown products) and data
processing and validation.38 Investigation of microbial metabolites is further complicated, as
low biomass limits the number of unique microbial metabolites detected in dilute samples
and can lead to changes in microbial metabolism being ‘masked’ by more abundant host
metabolites (e.g. amino acids). Moreover, environmental niches in the LRT may result in
dramatic variability in microbial metabolites depending upon the collection technique or
site.8 Additionally, in spite of evidence that viral infections alter the metabolic profile of the
lung,39 the lack of a clearly defined respiratory virome and an inability to reliably manipulate
10
its composition means that its impact on host and microbial metabolism is unknown. Use of
targeted metabolomics to focus on microbial metabolism may overcome some of these
limitations but further improvements in technology and improved analysis of existing
datasets (e.g. integrated ‘omics approaches39) may yield significant information concerning
microbial metabolism in CRDs.
Gut microbiota and the gut-lung axis (figure 2)
Gut and lung microbiota differ in function both as communities and individual microbes,2
and their composition does not always undergo similar changes with similar environmental
challenges.12 The roles of gut microbiomes in respiratory disease and immunity has been
reviewed elsewhere,1,2 yet it warrants mentioning briefly. The impact of bacterial ligands
(e.g. LPS) and metabolites (e.g. SCFAs) that enter the circulation or through shared mucosal
immunity on the lung are potential contributors to CRDs, and additional variables in studies
of respiratory microbiomes. Similarly, the gut virome regulates host immunity, largely
through interactions with host TLRs and NLRs, and lung viral infections can have profound
effects on the composition of the gut microbiome.2,5,40 Gastrointestinal fungi are crucial for
the maturation of distal lymph nodes and regulate dendritic cell function, whilst fungal
dysbiosis contributes to the development of AAD in mice.41 Moreover, regurgitation and
microaspiration may result in upper gastrointestinal microbiota entering the lungs,
particularly in diseases such as asthma and COPD where reflux is a common co-morbidity.9
Distinguishing between the effects of lung and gut microbiota is important when
characterising their roles in disease and in developing effective therapies.
11
Microbiome alterations and implications in disease (figure 3)
Changes in lung microbiota during CRDs are increasingly well characterised. However,
research is now being redirected from observational studies towards elucidating the
functionality of predominant members or communities, and their interactions with host
immunity.2 These are important next steps in developing novel therapeutics.
Asthma
Asthma is a heterogeneous CRD characterised by allergic airway inflammation, remodelling
and hyperresponsiveness (AHR).42-44 The microbiome varies throughout disease progression
and exacerbations. Moraxella catarrhalis, Streptococcus pneumoniae and Klebsiella species
are associated with severe asthma and exacerbations.45,46 Proteobacteria, the most
abundant bacterial phylum in asthmatics, is associated with AHR47 and Th17/IL-17-driven
inflammation, and promote neutrophil recruitment via IL-17A/F in non-eosinophilic/non-Th-
2 asthma.48 In mice, infection with the proteobacterium M. catarrhalis is associated with
neutrophilic infiltrates, high levels of IL-6 and TNF-α, and moderate levels of CD4+ T-cell-
derived IFN-γ and IL-17, which were exaggerated with AAD.49 16S rRNA sequencing of
bronchial microbiota found enrichment of Haemophilus, Neisseria, Fusobacterium, and
Porphyromonas species, and Sphingomonodaceae family members, and low levels of the
Mogibacterium-like bacteria and Lactobacillales in atopic asthmatics.50 Asthmatic lung
microbiota had increased ability to metabolise butyrate and propionate, which may
potentially lead to atopic asthma by limiting the bioavailability of SCFAs. Indeed, SCFA
production by gut bacteria protects against development of AAD in mice.51 H. influenzae is
the commonest potentially pathogenic bacterial species isolated from the airways of severe
12
asthmatics.52 Experimentally this bacterium converts steroid-sensitive Th2/eosinophilic AAD
into a steroid-resistant Th1/neutrophilic phenotype dominated by IL-17 responses and
associated with chronic infection and impaired phagocytosis.53-57 Furthermore, culturing
Haemophilus parainfluenzae with macrophages from bronchoalveolar lavage resulted in p38
MAPK activation, increased CXCL8 and mitogen-activated kinase phosphatase-1, and
inhibited corticosteroid responses, which was not observed with culture with the
commensal Prevotella melaninogenica.58 Staphylococcus species enriched after house dust
mite exposure induced Th2 cytokine production suggesting that microbiomes regulate host
immunity, and thus dysbiosis changes in microbiota may be a cause as well as an effect of
disease development.30 Thus, specific pathogenic bacteria may influence the response of
immune cells to pharmacotherapy, and bacterial colonisation or dysbiosis in the airways of
asthmatics may be potential therapeutic targets. Importantly, early life viral infections are
potentially key triggers for the development of asthma and, Annelloviridae has recently
gained significant attention.5 Fungal exposures are associated with development,
progression, severity and exacerbations in asthma and fungal sensitization inherently results
in poorer functional outcomes.59,60
CF
This disease is primarily caused by mutations in the CF transmembrane conductance
regulator (CFTR) gene.61 In the initial stages of the disease in early childhood, CF microbiota
is dominated by P. aeruginosa, H. influenzae, Staphylococcus aureus, Burkholderia cepacia
complex and Stenotrophomonas maltophilia, although microbial load is negligible.62 As
13
disease progresses (1-2 years), microbiomes become rich in oral taxa (3-5 years), and then a
CF microbiome dominated by P. aeruginosa which correlates with disease features.63
Notably, both oral- and pathogen-dominated microbiomes are associated with increased
inflammation and lung structural changes characteristic of CF.63 Thus, bacteria considered as
URT contaminants may have crucial roles in shaping LRT microbiomes in CF and promoting
inflammatory responses.64 Despite marked differences in lung microbiome profiles in CF
patients, which are affected by multiple factors, the metabolic potential of the whole
microbial community is similar,27 including in including amino acid catabolism, folate
biosynthesis, and lipoic acid biosynthesis pathways.65
Studies employing computational assessments have postulated that inoculation of
bacterial predators (Bdellovibrio, Vampirovibrio) into pulmonary microbiomes at early
disease stages might help control chronic colonisation by CF pathogens.66 This implicates
direct roles for dysbiosis in pathogen-dominated lung microbiota. P. aeruginosa in CF
patients exhibit transition from non-mucoid to mucoid forms over ~11 years,67 which may
facilitate resistance to antibiotics and phagocytosis. Additionally, non-mucoid forms may
have increased survival by negating hydrogen peroxide stress through catalase (KatA)
production.68
Increasing evidence proposes key roles for the virome, particularly Rhinoviruses in
deteriorating lung function, exacerbations and facilitation of bacterial colonisation in CF
while the role of the mycobiome is more established through a range of functional clinical
consequences including colonisation, sensitisation and allergic bronchopulmonary
aspergillosis (ABPA).69-71
14
Improved understanding of inter-microbial interactions and functional and metabolic
effects of lung microbiomes in CF may lead enable the development of novel treatment
strategies.
Non-CF Bronchiectasis
Bronchiectasis is a heterogeneous disease of chronic, irreversible and progressive dilatation
of bronchi.72 A key component is microbial colonisation and infection that drive
pathogenesis,72 and changes from health to disease.73 The core microbiota are comparable
between children with bronchiectasis and CF, but is different to adults.74 This suggests that
there is an ‘early’ bronchiectasis microbiome, which changes over time.74 Adults with
bronchiectasis have Pseudomonas- or Haemophilus-dominant microbiomes or microbiomes
with neither genera dominant, but this classification does not account for the wider
microbial ecosystem, individual patient characteristics, treatments, or inter-species
relationships.75,76 Long-term low-dose erythromycin therapy is associated with greater
microbial diversity and preserved lung function.74 Microbiomes are relatively stable in
individuals despite exacerbations and antibiotic therapy,76,77 but vary considerably between
individuals, influenced by the airway milieu, community composition and degree of immune
dysfunction.78,79 Studies found poorer lung function and more exacerbations were linked to
fucosyltransferase secretors than non-secretors who had less airway P. aeruginosa.80 Other
relationships with microbiota include with clinical phenotype, antibiotic exposure and
exacerbations. Pseudomonas is the only bacterial genus consistently implicated, and is
associated with poor clinical outcomes, exacerbations and mortality.81,82 Antibiotics affect
bronchiectasis microbiota. Carbapenem promotes Stenotrophomonas maltophilia infection
15
and low-dose erythromycin causes displacement of H. influenzae with P. aeruginosa.77 There
are no consistent associations of new pathogens or altered bacterial burden with
exacerbations.75,76,83 The most likely links are with change in microbial behaviour rather than
composition, which is driven by nutrient availability, oxygen tension, bacteriophages, host
immunity and quorum sensing.72,84 Indeed, macrolides reduce exacerbation risk and the
expression of quorum sensing genes despite stable bacterial loads, and thus, potentially act
as quorum sensing inhibitors.85
There are causal roles for the virome in exacerbations, hospitalisations and increased
airway and systemic inflammation. Human T-lymphotropic virus type-1 load was ~100-fold
higher in indigenous patients with bronchiectasis, which correlated with radiological
pulmonary injury scores and serology of the parasitic round worm Strongyloides.86 In adults,
viral exacerbations were significantly associated with increased systemic (IL-6 and TNF-α)
and airway (IL-1β and TNF-α) inflammatory markers.87 Viruses were recovered from
bronchiectasis patients at similar rates to healthy subjects,87 but whether the presence of
viruses in healthy and mild-moderate/stable patients affects overall microbiome
composition and disease progression is unknown. In children, viral exacerbations resulted in
more severe symptoms requiring hospitalisation, hypoxia and chest signs, and increased
systemic CRP and IL-6 levels.88
Aspergillus and Candida are the most frequently isolated fungi in bronchiectasis. The
bronchiectasis mycobiome is characterised by the genera Aspergillus, Cryptococcus, and
Clavispora. Aspergillus is associated with sensitisation and allergic bronchopulmonary
aspergillosis, and A. fumigatus and A. terreus dominate in Asian and European patients,
respectively.19 The latter associates with poorer lung function, fungal-associated IgE and
16
exacerbations. Fungi contribute to pathogenesis through their antigens and proteases, host
genetic susceptibility, and interactions with other microbes notably non-tuberculous
mycobacteria.89 Next-generation sequencing studies are needed to elucidate airway fungal
diversity and clinical relevance.90
COPD
COPD is a heterogeneous disease variably characterised by inflammation-driven bronchitis,
emphysema, fixed airflow obstruction and impaired lung function.91 Microbiota diversity and
relative abundance of members of the lung microbiome in COPD differs substantially from
healthy individuals,10 which is further skewed during exacerbations.92 The dynamics of
change of the lung bacterial microbiome may be attributed to disease heterogeneity,73,93,94
physiological changes with disease stage and progression,95 treatments (e.g. antibiotics and
corticosteroids),31,92 and exacerbations.96 Prevotella and Haemophilus species activate CD83,
CD40 and CD86 in human monocyte-derived dendritic cells, with Haemophilus being 3-fold
more inflammatory. However, in co-culture Prevotella reduced H. influenzae-induced IL-
12p70, highlighting differential interactions of distinct bacteria with immune cells.97 Chronic
airway inflammation in COPD is associated with microbiota dominated by
Gammaproteobacteria,94 and Proteobacteria and Actinobacteria are associated with
infiltrating immune cells in lung tissue from COPD patients, including neutrophils,
eosinophils, and B-cells.98 Enrichment with the oral taxa Veillonella and Prevotella is also
associated with increased lung inflammation.17 This pneumotype was characterised as
having increased levels of the metabolites palmitoleic acid, arachidonic acid, 4-
hydroxybenzoate and glycerol, as well as exhaled nitric oxide, but the precise role of
17
microbial metabolism in these profiles and inflammation is unknown. Conversely,
enrichment of the lung microbiome with oral taxa was also associated with blunted alveolar
macrophage TLR4 responses,17 yet inhibiting TLR activation may be a novel therapeutic
strategy for COPD.99 This suggests that the interactions of lung microbiota and immunity in
COPD are more complex than comparisons of ‘healthy’ and ‘diseased’. Recent studies also
implicate gut microbiome and physiology changes in COPD pathogenesis.100,
The gut microbiomes of smokers have increased abundance of Bacteroidetes, and
reduced Bifidobacteria101,102 and Firmicutes:Bacteroidetes ratio.102 Cigarette smoke-induced
mouse models of COPD also display pathology in the gastrointestinal tract, including
reduced colon length, epithelial barrier dysfunction, hypoxia and increased angiogenesis
and severity of chemical-induced colitis.100 Moreover, in mice, dextran sulfate sodium (DSS)-
induced colitis leads to systemic and pulmonary IL-6 dependent neutrophilia through
bacteraemia (increased endotoxins).103 These smoking-related gastrointestinal pathologies
potentially lead to further dysbiosis in the gut, as well as systemic inflammation and
circulating microbial products (bacterial metabolites, structural ligands) that may reach the
lungs and affect the progression of COPD.
A functional role for the virome in COPD beyond that established in promoting
exacerbations is an ongoing field of investigation however recent data suggest an important
influence of the mycobiome particularly a sensitisation response in COPD-bronchiectasis
overlap.104
Pollution
18
Outdoor environmental pollution with a mixture of fine and ultrafine particles and gases has been
implicated in worsening or inducing many respiratory conditions such as asthma and COPD.
Exposure of mice to ambient air pollution or particles causes gut microbial dysbiosis usually with
altered Firmicutes and Bacteroidetes, depending upon the size of particulate matter (PM;
PM10/PM2.5) and mode of administration (inhalation versus chow), as well as strain of mice
studied.105,106 In rats there was a rapid increase in lung microbiota abundance and diversity,
particularly of Proteobacteria.107 Human studies also support a link between exposure to traffic
pollution and microbiota in the gut or upper respiratory tract.1 The pathophysiological significance of
pollution-induced microbial dysbiosis in the gut was demonstrated in mice exposed to the gaseous
pollutant, ozone, where changes in the gut microbiome contributed to ozone-induced bronchial
hyperresponsiveness through its ability of produce the SCFA metabolite, propionate, providing
support for a gut-lung axis link.108 Further work is needed as to whether the lung microbiome could
produce SCFAs.
Infections and exacerbations
Complex interactions between environmental and host factors and the microbiome exist in
the lungs.109 CRD patients exhibit lung dysbiosis and are prone to bacterial and viral
infections, which further alter microbiomes and induce exacerbations.110-112 This indicates a
feedforward process by which lung dysbiosis that dysregulates host immunity, and leads to
increased risk of pathogenic infections that in turn maintains dysbiosis.2,113 Colonisation with
H. influenzae, S. pneumoniae and M. catarrhalis is associated with high risk of developing
recurrent wheeze and childhood asthma.114 In COPD, 40-50% of exacerbations are caused by
bacteria that increase airway inflammation and obstruction, sputum production and
bronchoconstriction.110,112 This involves high levels of typical Streptococcus, Pseudomonas,
19
Moraxella, Haemophilus, Neisseria, Achromobacter and Corynebacterium genera in COPD,
and atypical bacteria such as Mycoplasma pneumoniae and Chlamydia pneumoniae also
having roles in asthma and COPD exacerbations.115
The respiratory microbiome may also be altered by viral infections, which increase
susceptibility to secondary bacterial infections and/or associated exacerbations. For
instance, acute HRV infection in COPD patients chronically colonized with non-typeable H.
influenzae had greater likelihood of seasonal AECOPD. 116 Notably, significant increases in
16S copy number (6-fold) and numbers of proteobacterial sequence (16%; especially pre-
existing H. influenzae) was reported 15-days post experimental RV infection, though only in
sputum of patients with COPD117 indicating selective outgrowth of newly favored species in
the setting of exacerbations. Importantly, RSV, IAV and HRV infections upregulate bacterial
adhesion molecules (ICAM-1, PAFR, CEACAM-1) on epithelial cells and thereby promote
adherence and growth of specific bacteria in the lung microbiome, including non-typeable
H. influenzae, S. pneumoniae and P. aeruginosa. Viral infections also impair mucociliary
clearance and damage epithelial cells, facilitating host tissue invasion by pathogenic bacteria
(e.g. S. pneumoniae) and thus persistence of pathogens in the lung microbiota. RSV infection
in adults causes exacerbations in CRDs. Binding to nucleolin and CX3CR1 on airway
epithelium and inducing Nox signalling pathways to activate epidermal growth factor
receptor (EGFR) results in CXCL8/10-dependent airway inflammation and mucin production,
and suppressing IFN-lambda responses. Inhibiting EGFR to activate endogenous epithelial
antiviral defences may be a potential treatment in respiratory infections.118 RSV infection
aggravates impaired immune responses from alveolar macrophages involving mitochondrial
dysfunction and suppression of type I IFN responses involving TGF-β1.119 RSV or HRV
20
infection in infants produced different profiles of metabolites and bacterial functional
potential in nasopharangeal samples, although it is unclear whether the virome impacts
host or bacterial metabolism in CRDs or their exacerbations.39 Alternatively, bacterial SCFAs
derived from the gastrointestinal tract protect against respiratory viral infection120, and thus
it is feasible that metabolites produced by the respiratory microbiome an individuals
susceptibility to viral exacerbations. These different responses or susceptibility to infections
and exacerbations (both viral and bacterial) may contribute to heterogeneity in CRDs.
Critically, the role of fungi (and the mycobiome) has emerged as an important contributor to
exacerbations in asthma, COPD, CF and non-CF bronchiectasis with the Aspergillus genus
best studied.19,59,71,104
It is crucial to better understand the role of infections in disease induction,
progression and exacerbation, which can be achieved with advance omics techniques of
high throughput sequencing, metagenomics, and microbiome analysis. This will assist in
developing new treatments for CRDs and will open new avenues of precision medicine.
Lung microbiome in co-morbidities of CRDs (figure 4)
CRDs are complicated by co-morbidities including cardiovascular disease (CVD),
cerebrovascular diseases, diabetes mellitus, neurological and psychiatric disorders, gut and
renal disorders, musculoskeletal disorders, and malignancies. Although, the direct role of
lung microbiomes in extra-pulmonary co-morbidities has not yet been established, the
respiratory and gut microbiome has been implicated in several gastrointestinal co-
morbidities through the gut-lung axis, as well as other “organ-lung” axes in the heart, brain,
21
muscle, and lymph tissue. These interactions should be fully investigated to dissect the roles
of the respiratory microbiome in co-morbidities of CRDs.
Oral microbiota are altered in smokers and CRD patients (especially COPD and
asthma), which then affects the microbial community composition in the lung and gut
through microaspiration and swallowing, respectively. Furthermore, specific members of
oral microbiota that are increased in COPD121 are directly implicated in rheumatoid arthritis
and CVD. Porphyromonas species increase the production of autoantibodies (anti-
citrullinated protein antibodies and rheumatoid factor) that result in the onset and/or
progression of arthritis.122 Moreover, the combined abundances of Streptococcus and
Veillonella in atherosclerotic plaques correlated with their levels in the oral cavity. Notably,
levels of specific oral taxa implicated in CRDs such as Fusobacterium and Streptococcus
significantly correlated with plasma cholesterol and low- and high-density lipoprotein (LDL
and HDL) and apolipoprotein A1 (ApoA1) levels, respectively, which are major CVD risk
factors.123
Recently, Millares et al., showed that despite similar overall bronchial microbiomes
in stable COPD and during exacerbations, the predictive in silico analysis of functional
metabolic pathways of microbial communities are were significantly altered, especially
those related to tumourigenesis, which may increase the risk of lung cancer in COPD
patients.124 In particular, non-typeable H. influenzae, a major pathogen in CRDs, induced
epithelial IL-17C production in TLR-2/4 dependent pathways that promote tumour-
associated inflammation and tumour proliferation.125
Epidemiological studies show increased risk of inflammatory bowel diseases (IBDs)
associated with CRDs, and vice versa, and dysbiosis is independently linked to the
22
pathogenesis of both. The aberrant immune responses in CRDs accentuated by dysbiotic
lung communities, as well as the transition of CRD-associated microbiota from the URT to
the gastrointestinal tract could play crucial roles in the onset and progression of gut
diseases. Oral-derived Klebsiella pneumoniae ectopically colonize colitis-prone mouse
intestines and elicit TH-1 cell responses and associated gut inflammation.126 IAV infections,
frequent in CRDs, result in migration of lung-derived CCR9+CD4+ T-cells to the small intestine
of mice where they produce IFN-γ leading to dysbiosis and intestinal immune injury.2,127
Thus, recurrent infections with these respiratory pathogens could lead to inflammation in
the gastrointestinal tract that often precedes IBD.
Therapeutics
ThreeTwo classes of medications, antibiotics, and corticosteroids and beta agonists, are
commonly used to treat respiratory conditions where lung dysbiosis ismicrobiota are
involved in pathogenesis. Their effects on the microbiome are only now being investigated,
and extending their efficiency or preventing side-effects might be achieved by regulating gut
and/or lung microbiota. Targeting specific pathogens may also have therapeutic potential.
Antibiotics
Long-term antibiotic therapy, particularly with macrolides, is now established for the
treatment of CRDs including uncontrolled/severe Antibiotics are widely used to treat acute
respiratory infections and long-term antibiotic therapy (especially macrolides) has been
introduced for the treatment of chronic respiratory conditions including
uncontrolled/severe asthma,128 CF,129 bBronchiectasis,130 and COPD.131 They limit both the
23
duration and severity of asthma exacerbations induced by Haemophilus, Chlamydiae and
Mycoplasma.55,128 Despite the undeniablethe therapeutic benefits of antibiotics, prenatal or
early-life use is linked to the development of allergies and asthma through changes in the
gut microbiome.132,133 Infants and adults have reduced microbial richness and abundance in
gut microbiota following azithromycin treatment,134,135 and treated asthmatics have reduced
abundance of lung Prevotella, Staphylococcus and Haemophilus.136 However, in
bronchiectasis divergent effects occur with long-term erythromycin treatment increasing
the levels of H. parainfluenzae and decreasing Streptococcus pseudopneumoniae and
Actinomyces odontolyticus.137 In patients without Pseudomonas-dominated infection and
who had no change in exacerbation rates after azithromycin, there were decreases in H.
influenzae.77 In smokers with emphysema, azithromycin did not suppress lung bacterial
burden, but reduced α-diversity and pro-inflammatory cytokines, and increased anti-
inflammatory bacterial metabolites (glycolic acid, indol-3-acetate, linoleic acid).138 Thus,
antibiotics although reducing diversity may act beneficially on bacterial metabolism to
induce anti-inflammatory effects.
Corticosteroids
Corticosteroids may alter immune responses to bacteria, and thus their pro-inflammatory
effects. Corticosteroid use in asthma increases the abundance of airway Proteobacteria,
including Pseudomonas, and decreases in Bacteroidetes, Fusobacteria and Prevotella
species.139 Similarly, inhaled corticosteroid use in COPD is associated with greater richness
and diversity, while systemic treatment during exacerbations enriched Proteobacteria,
Bacteroidetes and Firmicutes.140 In a mouse model of RV-induced COPD exacerbation,
24
fluticasone propionate impairs both innate (type I IFNs) and adaptive (activated CD4+ and
CD8+ T cells) antiviral responses leading to delayed virus clearance, mucus hypersecretion
and increased lung bacterial loads.141 Moreover, COPD patients on ICS therapy had
suppressed sputum cell IFNβ and IFNλ2/3 expression at exacerbation onset, and
significantly increased bacterial loads 2-weeks post exacerbation onset compared to ICS
non-users.141
Finally, H. parainfluenzae may induce corticosteroid insensitivity suggesting that lung
dysbiosis in asthma might contribute to corticosteroid non-responsiveness.58 Indeed,
experimentally although Chlamydia, H. influenzae, RSV and IAV induce different immune
responses they can all drive steroid-resistant airway inflammation and AHR through miR-
21/PTEN/PI3K/HDAC2 and NLRP3 inflammasome responses.55-57 These effects can be
reversed using miR-21, PI3K and NLRP3 inhibitors.142
Beta Agonists
Data from in vitro studies have demonstrated that salmeterol reduces bacterial adherence
to airway mucosa, as well as bacteria-induced epithelial damage (tight junction leakiness,
epithelial stripping and preventing loss of ciliated cells) caused by both P.
aeruginosa and Haemophilus influenzae.143,144 In contrast, data from cultured mouse
macrophages exhibits that inhalation of beta2-agonist impairs clearance of nontypeable H.
influenzae.145
Probiotics and prebiotics therapies
Probiotics are live microorganisms while prebiotics are non-digestible carbohydrates that
are metabolised by gut bacteria and stimulate the growth and activity of beneficial colonic
25
bacteria. Both change the balance of gut microbiota, interact with innate and adaptive
immunity, promote the release of anti-inflammatory metabolites and secretory products,
and can deliver health benefits.2 Typically, they are taken orally, which implies interference
with the gut-lung axis as being important in maintaining normal microbiota and influencing
immunity in both compartments.2 Randomised clinical trials using single strains of probiotic
Lactobacilli and Bifidobacteria had no effect in preventing allergic asthma.146 However, small
studies showed that Lactobacillus gasseri improved asthma and allergic rhinitis symptoms,
home peak expiratory flow rates, and inflammatory cytokine release from blood
mononuclear cells.147 In children with mild-to-moderate atopic asthma, Lactobacillus
acidophilus and Bifidobacterium bifidum also improved lung function and reduced
exacerbations.148 In CF, probiotics may restore beneficial intestinal microbiomes which have
been altered by frequent antibiotic courses through effects on gut microbiota, including
improved gut motility and intestinal barrier function, inhibition of pathogenic bacteria,
enhanced metabolism and by modulating gut and lung immunity.149 There is evidence for
probiotics reducing pulmonary exacerbations and intestinal inflammation, but studies were
of variable quality.150 An unexplored potential is the administration of probiotics or
prebiotics to the URT to target the lung microbiome directly. Intranasal administration of E.
coli or Acinetobacter iwoffii and Lactococcus lactis strains that promote immunoregulation
reduced allergic inflammation in mice.151,152 Other specific components of gut and lung
bacteria induce anti-inflammatory effects including by promoting regulatory T-cell responses
that may also be harnessed therapeutically.23,153-155 Although these studies are promising,
larger controlled trials are needed to determine whether changes in gut and lung
26
microbiomes occur as a result of prebiotic and probiotic therapies and are potential
treatments.
Pathogen targeting
Other strategies involve targeting major bacterial pathogens to reduce hospitalisations and
mortality. Vaccination against major bacterial pathogens in asthma and COPD patients, may
result in reduced pathogenic burden and associated inflammation.53 Chronic H. influenzae
infection promotes neutrophilic and Th17-driven inflammation, and steroid insensitive AAD,
and thus preventing bacterial colonisation may be beneficial perhaps as adjunct therapies in
asthma and COPD.53 Influenza vaccination may also reduce secondary bacterial infections
with Streptococcus pyogenes.156 Vaccines against S. pneumoniae are strongly recommended
and administered in susceptible populations (children and adults >60 years).157 Nevertheless,
it remains a major bacterial pathogen in susceptible individuals,158 necessitating further
research to improve vaccines to provide sustained protection. The protective effects of
commensal bacteria may also be harnessed. Haemophilus haemolyticus, a common lung
commensal, produces a bacteriocin-like protein that inhibits the growth of pathogenic
nontypeable H. influenzae.159 Also, administration of probiotic Streptococcus salivarius
significantly reduced (~80%) episodes of S. pyogenes-induced pharyngeal infections.160 Thus,
strategies that promote growth of commensal respiratory bacteria may be utilised to
manage infections in CRDs.
Future directions and conclusions (figure 4)
27
The characterisation of dysbiosis microbiome composition in CRDs has helped to understand
the functional effectsfunctions of the respiratory microbiome, but the precise effects of
these functions must be further elucidated to be targeted therapeutically. Increasingly,
‘omics technologies and novel bioinformatics techniques are being employed to further
elucidate the microbial ligands and metabolites that interact with host immunity. Building
on this, future studies must account for the inherent variability in respiratory microbiota,
contributions from the gut-lung axis, and the interaction between different constituents of
the microbiome through shared microbial pathways. In-vivo, bacteriomes co-exist with
viromes and mycobiomes and a collective interpretation of the inter- and intra-kingdom
signalling between them in the context of functional consequence for the host and CRD is
necessary in future work. Most current work assesses the functional consequence of a single
microbiome alone and rarely integrates them, a feature that will be necessary in our current
era of precision medicine. Moreover, the improved ability to discern species- or strain-
specific differences in microbial functions should continue to be explored, including where
purified ligands (e.g. LPS) are administered in animal models. Most importantly, the majority
of studies investigating the respiratory microbiome are observational, and generally fail to
discern the cause-effect relationship between microbial dysbiosis and disease development
or progression. Longitudinal studies in human subjects, and targeted interventions in
validated animal models are crucial to definitively characterise the functional effects of
microbiota on CRDs. Overall, the functional effects of the respiratory microbiota hold
significant potential as therapeutic targets for CRDs, and continued emphasis on the
improved characterisation of these functions is essential to developing such therapies.
28
Contributors
All authors contributed to the design and writing of the manuscript. These are the views of
the senior authors PH, DPHAJ, IMA, SHC, KFC and PMH. KFB, SDS and SFR performed the
literature reviews and drafted text.
Declaration of interests
We declare no competing interests.
Acknowledgements
The authors are supported by fellowships from the National Health and Medical Research
Council (PMH) of Australia, the Australian Research Council (ARC, PH) and the Brawn
Foundation, Faculty of Health and Medicine, University of Newcastle, and grants from the
NHMRC and the Rainbow Foundation (PMH). The authors thank Felicity and Michael
Thomson for their continued support. SHC is supported by the Singapore Ministry of Health’s
National Medical Research Council under its Transition Award (NMRC/TA/0048/2016), the Singapore
Ministry of Education under its Singapore Ministry of Education Academic Research Fund Tier 1
(2016-T1-001-050), the Lee Kong Chian School of Medicine, Nanyang Technological University
Singapore Start-Up Grant and acknowledges The Academic Respiratory Initiative for
Pulmonary Health (TARIPH). SHC is supported by a Singapore National Medical Research
Council, Ministry of Education, the Lee Kong Chian School of Medicine, Nanyang
Technological University, and acknowledges The Academic Respiratory Initiative for
Pulmonary Health (TARIPH). KFC is a Senior Investigator of the UK National institute for
Health Research (NIHR) and is supported by grants from European Union Horizon 2020 and
National Environmental Research Council grants. PMH is supported by fellowships and
29
grants from the National Health and Medical Research Council of Australia, the Australian
Research Council, the Brawn Foundation, Faculty of Health and Medicine, University of
Newcastle, and the Rainbow Foundation, and thanks Felicity and Michael Thomson for
continued support.
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Figure headings
Figure headings
Figure 1: Signals from the microbiome influence lung immunity. Respiratory microbiota produce
structural ligands (A) or metabolites (B) which influence host immune activity in health and disease.
TLR=Toll-like receptor. IL= Interleukin. MIP=Macrophage inflammatory protein. MDC = Macrophage-
derived chemokine. NOD = Nucleotide-binding oligomerization domain-containing protein. GPR = G
protein-coupled receptor. HDAC = Histone deacetylase. TMA = Trimethylamine. IFN = Interferon.
Figure 2: The gut-lung axis. The gastrointestinal and respiratory tracts are part of a shared mucosal
immune system and interact with the microbiome and each other in numerous ways, including
bacterial ligands (e.g. lipopolysaccharide; LPS) or metabolites (e.g. short chain fatty acids; SCFAs),
migrating immune cells, cytokines, hormones, and microbial migration between sites.
Figure 3: Roles of lung microbiomes in chronic respiratory diseases (CRDs). The abundance and
metabolic potential of specific microbes is increased in CRDs, contributing to immune dysregulation
and lung structural changes leading to progression of asthma, cystic fibrosis, bronchiectasis and
COPD as well as their exacerbations.
AHR= Airway hyperreactivity. CXCL-8= C-X-C Motif Chemokine Ligand 8. DC= Dendritic cell. IFN-γ=
Interferon-gamma. IL= Interleukin. MAPK= Mitogen-activated protein kinase. SCFA= Short chain fatty
acid. TNF-α= Tumor necrosis factor-alpha. TLR=Toll-like receptors.
39
Figure 4: Chronic respiratory disease (CRD)-associated extra-pulmonary comorbidities and roles of
bacterial microbiomes. The oral microbiome influences the composition of both lung and gut
microbiomes, and a bi-directional gut-lung axis exists. Oral, lung and gut microbiomes have been
linked to several extra-pulmonary complications that often co-exist with CRDs. The abundance and
metabolic potential of specific microbes in the gut leads to host immune dysregulation and the
production of specific metabolites implicated in various CRD-associated comorbidities.
APCA=Anti-citrullinated protein antibodies. GABA=Gamma-aminobutyric acid. HPA=The
hypothalamic pituitary adrenal. Ig=Immunoglobulin. IL=Interleukin. LPS=Lipopolysaccharide. NF-
kB=Nuclear factor kappa-light-chain-enhancer of activated B cells. NO=Nitric oxide. NLR=Nod-like
receptors. SCFA=Short chain fatty acid. TLR=Toll-like receptors. TMAO=Trimethylamine-N-oxide.
Figure 5: Current understanding of the roles of respiratory microbiomes in chronic respiratory
diseases (CRDs). Most studies of the respiratory microbiome in CRDs have been observational.
Integration of ‘omics’ technologies has improved our understanding of the functions of microbiota.
Future studies must now assess microbial function through longitudinal and interventional studies,
considering emerging concepts in experimental design such as variability of microbiota and species/
strain-specific effects.
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