Glossary of terms and definitions.
The chronic colonisation of the lower airways by bacterial pathogens is the leading cause of morbidity and mortality in patients with cystic fibrosis (CF). The use of novel culture-independent techniques such as next-generation sequencing (NGS) to analyse the lungs has allowed us to further understand the diversity, the complexity, the effects of acute exacerbations and the use of antibiotics on the bacterial communities. The understanding of the CF microbiome to airway disease remains a fascinating area of research; it presents new opportunities for disease management in CF and has the potential to explore the effects of cystic fibrosis transmembrane conductance regulator (CFTR) modulators. It also allows further appreciation regarding the roles played by anaerobic organisms within the CF airways. It is also of interest that a number of studies have demonstrated that the fluctuations of microbiome are not necessarily associated with the patient’s clinical status. Despite the available evidence, there remain many challenges that must be overcome if microbiome profiling is going to influence future clinical practice. The effects of fungus and the emergence of nontuberculous mycobacteria in CF are also briefly discussed in this chapter.
- cystic fibrosis
- CFTR modulators
- nontuberculous mycobacteria
Traditional culture techniques rely on growing bacteria on media in laboratory conditions often optimised for growth of specific organisms so that they can then subsequently be identified. In the last 20 years, novel techniques utilising next-generation sequencing (NGS) to identify bacteria have become available, enabling detection and description of bacterial communities without the need for conventional culture. These technologies have allowed a greater understanding of bacterial communities throughout the human body and have revealed functional roles in both health and disease.
A healthy human gut, for example, is home to a highly diverse community of bacteria, termed as microbiome, which has symbiotic functions including metabolism of otherwise indigestible compounds and defence against opportunistic pathogens [1, 2]. Furthermore, bacteria in the gut influence the stimulation and development of the innate mucosal immune system . In addition to the roles in health, there has been significant interest in the relationship between microbiomes and diseases such as obesity, inflammatory bowel disease and diabetes mellitus [4, 5, 6].
Studies utilising culture-independent techniques to analyse the lungs have identified the presence of bacterial communities that are much more complex than the previously appreciated. The lungs were long considered to be an inherently sterile environment, in part due to the fact that conventional culture techniques often yielded negative results during health and it was only during disease that pathogens were detected. However, the advent of culture-independent techniques has demonstrated that multiple organisms comprise a community, termed the ‘microbiome’, in the lungs of patients, both healthy and diseased [7, 8, 9]. In this chapter, we discuss the techniques employed in 16S rRNA sequencing and the evidence these techniques have generated so far in relation to cystic fibrosis.
2. 16S rRNA gene sequencing
The 16S rRNA gene codes for a ribosomal subunit present in nearly all bacteria. The gene itself is approximately 1.5 kb long and consists of conserved regions, similar in nearly all microorganisms, and nine variable regions labelled, V1–V9, which are practically specific to each microorganism . The identification of a specific DNA sequence that corresponds to the known variable region of 16S rRNA gene can allow discrimination of the presence and relative abundance of different microorganisms (Figure 1).
Once the samples have been processed, DNA is extracted, and the 16S rRNA gene is amplified using polymerase chain reaction (PCR). Next-generation sequencing allows elucidation of the precise gene sequences, and online reference databases can then be used to match each sequence to an organism and quantify its relative proportion within a multispecies population. However, it is important to note that sequencing of the 16S rRNA gene has limited resolution and often cannot distinguish species with similar gene sequences apart. Therefore, instead of distinct species, sequences are referenced against and assigned into operational taxonomic units (OTU) (see Table 1).
|Microbiome||The microorganisms in a particular environment|
|16S rRNA gene||A gene which codes for a ribosomal subunit. Present in all prokaryotes and has variable regions, which differ slightly between bacterial species|
|Richness||A measure of the number of species in a community|
|Evenness||A measure of similarity of the relative abundance for each species in a community That is, does one species dominate, or do all species have similar relative abundance?|
|Diversity||A measure of variety in a community. Combination of richness and evenness|
|Alpha diversity||Within-sample diversity|
|Beta diversity||Between-sample diversity|
|Operational taxonomic unit (OTU)||Group of strains/species with similar 16S rRNA gene sequences|
Given the large number of species identified even in healthy lungs, ecological theory and analyses are often employed to understand community dynamics . According to ecological principles, the composition of the lung microbiome is determined by three factors:
Immigration of organisms into the lung
Elimination of microbes from the airways
Regional growth factors 
The lung microbiome in healthy individuals is dictated largely by immigration and elimination and hence generally consists predominantly of those Gram-negative anaerobes also resident in the oral flora such as
3. CF respiratory microbiota in early life
Understanding the development of the CF respiratory microbiota in early life has attracted interest in order to appreciate the driving factors behind the distinct microbiota seen later in life and also to identify potential opportunities for intervention. Neonates and infants cannot expectorate sputum independently, and bronchoalveolar lavage (BAL) is only used sparingly; hence, upper respiratory tract samples are often used as surrogates. The imperfection of this approach was recently highlighted where large differences in concordance between BAL samples and upper respiratory tract (URT) samples were observed in some taxa . Nevertheless, concordance was high for some important taxa such as
The composition of CF nasopharyngeal microbiota diverges from that of non-CF infants as early as the first few months of life [13, 14]. Newborn healthy infants appear to have nasopharyngeal microbiota dominated by
The divergence observed in the first few months of life usually precedes antibiotic administration and demonstrates that CF itself is associated with compositional changes in the microbiota, but as CF infants grow older, exposure to antibiotics, either via acute treatment for respiratory illnesses or prophylaxis against classic CF pathogens, becomes inevitable. Mika et al. investigated the relationship between antibiotics and the nasal microbiota by prospectively following 30 newborn infants with CF with fortnightly sampling for the first 12 months of life . Antibiotic administration was associated with an increase in the Shannon diversity measure (a measure of the richness and evenness of a community), but this was judged to be most likely secondary to an increase in transient colonisers. Interestingly, antibiotic therapy was staphylococcal directed, but decreases in
As babies grow older, sampling from the lower airways becomes more common, and comparisons between the lower and upper airways become feasible. Given the close proximity and interrelated spaces of the nose, throat and lungs, it could be expected that they all may share similar community structures; however, the reality is that the nasal community appears different from that of the throat and lung, which are much more closely aligned. Boutin et al. found differences in the community structure of the nasal cavity compared to throat and sputum samples; in that diversity, richness and evenness were significantly higher in nasal samples, and up to 21 of the 76 most abundant nasal OTUs were not present in the throat or sputum samples . Interestingly, the authors also found that subjects could be broadly defined into one of two ecotypes based on the presence or absence of
4. Progressive loss of diversity
Once the lungs are colonised with CF pathogens, a pattern of progressively uneven community structures ensues. Cox et al. examined biobanked sputum samples from a cohort of 63 clinically stable people with CF of ages ranging from 9 months to 72 years . This cross-sectional approach identified the loss of community richness, evenness and diversity as age increased.
Zhao et al. were the first to confirm these findings longitudinally when they followed up six patients over a 9-year period with serial sputum collections. It was observed that the three patients with what they termed as more ‘progressive’ disease had significant decreases in community diversity over the course of several years. Decreasing lung function and increasing age were also associated with decreasing community diversity . This study was soon followed by Fodor et al. who focussed more on changes in the microbiota associated with acute changes in clinical status but did observe a strong correlation between low species richness and poor lung function . Stokell et al. followed up a single patient up to over 3 years and observed increasing total bacterial load as well as diminishing community richness and diversity .
Contrastingly, Whelan et al. recently published a study of six patients who submitted thrice-weekly sputum samples for a year . No overall changes in community structure were observed over the course of the year, and the authors concluded that the respiratory microbiome is unique to each patient and the previously reported associations between community structure and clinical parameters may be true on a cohort/population level but not at an individual level. There is some merit in this argument, but it is also worth noting that the six patients in the study appeared relatively stable with a median of only one exacerbation in the 12-month study period. It is also therefore a possibility that the follow-up period was not long enough to capture the more indolent changes likely to be present in those patients . A much longer study period was adopted by Acosta et al.  who analysed samples from matched patients with biobanked sputum samples in three historic cohorts spanning nearly 20 years at a single centre. Across all the three cohorts, the core microbiome constituents were preserved, but the proportion of
The association reported in most studies between community structure and clinical outcomes has inevitably led to the question of whether a less diverse or even rich microbiome is simply a marker of increased pulmonary disease or is itself a driver in disease pathogenesis . If the latter were true, efforts to promote a more diverse community could have the potential to slow pulmonary disease progression. An Italian group has led efforts to find patterns or signatures in the microbiome that may predispose patients to accelerated lung function decline; however, no causal association has been elucidated [26, 27, 28]. Instead, Zhao et al. found that the relationship between age, lung function and community diversity disappeared once controlled for antibiotic use, thus suggesting antibiotic therapy is the predominant driver of reducing community diversity . The same group later developed a statistical approach to more precisely correct the antibiotic exposure when examining relationships between microbiota and clinical outcomes. The approach was applied to 478 sputum samples and confirmed that antibiotic use was an independent predictor for decreased diversity .
Accurately recording antibiotic use is troublesome in longitudinal studies due to the frequent episodic use of antibiotics in CF which is often self-directed by patients themselves, due to the widespread use of long-term antibiotics for which compliance may be heterogeneous and also due to the retrospective nature of a number of CF microbiome studies . However, Pittman et al. were able to prospectively perform bronchoscopy and record antibiotic exposure of 32 subjects as part of the AREST-CF study. In that study, community diversity was much lower in the BAL of those patients receiving antibiotics .
Thus it appears likely that the strong association between community structure and degree of lung disease is related to the inevitable prolonged and aggressive use of antibiotics in CF rather than direct pathogenesis from a less diverse microbiome.
5. Community changes with acute pulmonary exacerbations
Despite the importance of exacerbations on long-term outcomes of people with CF, the pathophysiology of these events remains undefined [32, 33]. Clinically, exacerbations are frequent and are characterised by rapid changes in symptoms such as an increase in sputum volume or purulence, shortness of breath and fatigue. The precise mechanisms underlying these important events remain elusive, and studies looking for answers using culture-independent techniques have not found consistent answers. For example, one may expect to find evidence of increases in known pathogens at the time of exacerbations, yet there is no consistent evidence of this . In fact, a number of studies have found the CF microbiota to be extremely stable over time and resilient to change at exacerbation and following subsequent treatment [19, 20, 34, 35].
However, when the community structure as a whole is considered, a number of larger studies have found reduced diversity or richness at the times of exacerbation compared to clinical stability. Coburn et al. found small decreases in Shannon diversity in exacerbation samples compared to their baseline study of 269 people with CF . Similarly, Filkins et al. found that samples taken during exacerbations had significantly lower diversity than samples taken when patients were stable . Perhaps most convincingly, Li et al. collated data from 18 previous studies to analyse over 700 sputum samples and found that there were significant reductions in community richness at exacerbation .
Whilst increases in
The first concept is supported by Whelan et al. who found in longitudinal sampling of six patients that some but not all exacerbations were associated with changes in the microbiota . Attempts to identify different types of exacerbations in COPD have identified four distinct aetiological clusters, bacterial, viral, eosinophilic predominant and ‘paucinflammatory’, and even though these clusters may not be mirrored in CF, it is plausible that not all exacerbation clusters would be associated with changes apparent in either individual taxa or overall bacterial community structure .
Changes in the metabolic activity of specific taxa or the community as a whole triggering an exacerbation could be another explanation for an apparent lack of change in the community structure seen in some studies. The metabolites lactate and putrescine were found by Twomey et al. to increase during exacerbation in the absence of clear changes in the community structure . Quinn et al. used the ecological functional networking to identify the non-mevalonate pathway of isoprenoid synthesis as a ‘keystone’ pathway in CF infections. Intriguingly fosmidomycin, an antimalarial agent, is known to be effective at targeting this pathway .
The second concept to emerge from the study of Carmody et al. relates to the changes in
To summarise, the aetiologies underpinning the transition from a stable state to an acute exacerbation are not well understood. It is likely that there multiple aetiological clusters but only some of which may be associated with changes in community structure.
6. Community changes associated with treatment for acute pulmonary exacerbations
Traditional dogma would dictate that intensive, targeted antimicrobial therapy with dual anti-pseudomonal agents will result in significant reductions in abundance of
One of the predominant themes that has emerged from studies of the respiratory microbiota response to acute antibiotics is that
In contrast, two studies have found reductions in
There are a number of factors that may explain the differences between the studies mentioned in this section, and many of them apply to studies of the CF microbiome in general. The most obvious is the heterogeneous study designs, which are mostly retrospective and observational in nature and include a wide range of antibiotic regimens. For example, some authors such as Cuthbertson and Daniels included exacerbations treated with oral antibiotics as well as those requiring intravenous therapy [35, 45]. Milder exacerbations are often treated with oral antibiotics, and hence associated changes in the microbiota may also be expected to be more subtle. Even in those studies where only intravenous regimens were used, the antibiotic regimens or doses given are often not listed. The lack of a control or comparator group further makes interpreting results difficult [35, 45].
A further consideration is the sampling timeframes in each study, where again there exists a considerable variation that may have implications for interpreting results, particularly given that Smith et al. reported significant but transient reductions in
Sample collection, storage, handling and DNA extraction techniques all also have the potential to impact on subsequent sequencing results. For example, multiple freeze–thaw cycles have been demonstrated to affect the results of microbiota analysis in respiratory samples . Furthermore, different sequencing platforms can also produce different profiles .
There is no universally standardised protocol for the extraction of DNA from respiratory samples, and hence methods are often inconsistent between study groups. One obvious inconsistency is the use of propidium monoazide (PMA), a chemical compound that binds DNA in cells with damaged membranes and hence allows exclusion of non-viable DNA from sequencing. Excluding non-viable DNA has been suggested to be important for accurately identifying which members of the community are active at times of exacerbation and helps to avoid overestimation of viable microorganisms following treatment with antibiotics, but it is not utilised by all groups [51, 52]. There are concerns that PMA may incompletely penetrate sputum, hence only identifying a portion of non-viable cells. PMA is also known to stain viable cells of some species and stain dead cells in others . In CF exacerbations, PMA treatment was not found to significantly alter the community as a whole, and only changes in low abundance ‘satellite’ taxa were apparent .
Overall, there is certainly evidence that acute antibiotic administration alters the respiratory microbiota; however, in the absence of prospective controlled trials, it is difficult to interpret these results given the confounders mentioned above. Indeed there have been calls for future clinical trials in CF to include biobanking of samples to allow a more rigorous scrutiny of the effect of antibiotic agents on the microbiome .
7. Community changes associated with chronic suppressive antibiotics
Inhaled antibiotics such as colistimethate (COL), tobramycin (TOB), aztreonam (AZLI) and levofloxacin (LIS) preparations are all licenced in the UK for the treatment of chronic
8. Community changes associated with CFTR modulators
In the last 5 years, treatments targeted towards correcting the underlying defect in CF have become available. Ivacaftor, a cystic fibrosis transmembrane conductance regulator (CFTR) potentiator, is licenced specifically for the treatment of people with a G551D mutation and a number of other rare gating mutations, which together account for approximately 5–10% of the CF population in the UK . In this subset of the CF population, ivacaftor use has been associated with improvements in lung function, reductions in exacerbations, reductions in sweat chloride, improved weight gain and improved quality of life [61, 62]. The restoration of CFTR activity by ivacaftor and the associated clinical benefits, in particular improved lung function and reductions in exacerbation, has inevitably raised questions as to whether ivacaftor has an antimicrobial effect.
Theoretically, ivacaftor could have an antimicrobial effect in a number of ways. Firstly, the restoration of CFTR activity should result in a rehydrated airway surface layer, and this in turn will allow the mucociliary escalator to function physiologically. The improved clearance of airway secretions would then result in the elimination of bacteria. Secondly, the restoration of CFTR activity could result in a dramatic change in the local pulmonary microenvironment, turning a previously favourable environmental niche into an inhospitable one for resident microbiota. There is evidence to support a similar effect in the GI tract, where CFTR modulation with ivacaftor was associated with improved proximal small intestinal pH, likely secondary to improved bicarbonate secretion . Thirdly, a direct bactericidal effect of ivacaftor itself has been postulated given that its chemical structure contains a quinolone ring and many quinolone derivatives have antimicrobial properties . This theory is supported by evidence that ivacaftor exerted in vitro antibacterial effects on clinical respiratory isolates of
Interest has since focussed on clinical microbiological outcomes of patients commenced on ivacaftor therapy in an effort to investigate differences post-treatment initiation. Interestingly, despite ivacaftor appearing to have no innate activity against
In contrast to the relative lack of focus on inhaled antibiotics, a number of studies have investigated the effects of ivacaftor on the respiratory microbiome. Peleg et al.  conducted the only placebo-controlled trial in this field when they performed a double-blind, placebo-controlled, cross-over study of 28-day ivacaftor treatment. Sputum was collected at the start and end of each 28-day treatment period, and 16S rRNA sequencing with qPCR correlation was subsequently performed. No significant differences were observed for either total bacterial load or
In longer-term observational studies, a number of changes have been observed. Bernarde et al.  noted no significant changes in bacteria load and also no significant changes in overall community composition at 1 year following ivacaftor initiation. However, individual taxa were observed to change in that the relative abundance of
9. Nontuberculous mycobacteria
Nontuberculous mycobacteria (NTM) are identified in approximately 10% of CF patients, but only a small proportion will go on to develop NTM pulmonary disease (NTM-PD) warranting treatment. First and foremost, the management of CF pulmonary disease should be optimised, including antibiotic therapy targeted to the individual’s usual airway bacteria, prior to considering treatment for NTM-PD. Those who fulfil criteria for NTM lung disease may not necessarily require treatment and could be monitored expectantly if symptoms and radiographic findings are minimal or stable over a period of surveillance. However, the presence of
|Clinical (both required)|
Inhaled liposomal amikacin for maintenance treatment has also drawn interest. In a randomised placebo-controlled trial, CF subjects with NTM lung disease refractory to standard therapy were assigned to 590 mg OD inhaled liposomal amikacin or placebo, in addition to their standard CF treatments and ongoing NTM therapy . The group of 90 patients was stratified based on MAC (64%) and MABSC (36%) . At the end of the 6-month treatment period, there was a statistically significant increase in culture negativity overall and for the MAC group.
Reported NTM prevalence in CF ranges from 3  to 23% . The majority (95%) of NTM isolated from CF patients are
MABSC has been demonstrated to accelerate lung function decline in CF patients compared to uninfected CF controls [83, 84]. In CF, a common measure of lung disease severity is percent-predicted forced expiratory volume in 1 second (FEV1), with lower values indicating more severe lung disease. Qvist et al. showed that MABSC had a greater rate of FEV1% predicted decline than other organisms, including
Individuals who are NTM culture positive but who do not meet ATS criteria for disease should be monitored closely . Patients with CF meeting criteria for NTM-PD should be considered for therapy; however, treatment decisions should be individualised [74, 85]. It may be reasonable to monitor individuals with mild CF lung disease, MAC lung disease with mild symptoms and radiographic changes or a high possibility of drug intolerance or drug interactions . However, CF patients with MABSC and/or severe CF lung disease should generally be treated in the absence of contraindications .
10. Fungal lung disease in CF
Clinical manifestations of respiratory fungal diseases in adult CF patients are very heterogeneous, ranging from asymptomatic colonisation to chronic infections, allergic disorders or invasive diseases in immunosuppressed CF patients following lung transplantation.
Allergic bronchopulmonary aspergillosis (ABPA) refers to a complex hypersensitivity reaction which often occurs in patients affected by CF or asthma. ABPA is beyond the scope of discussion in this chapter.
In CF patients, the disease-related progressive damage of the lungs may favour the development of chronic
The pulmonary microbiome of people with CF diverging significantly from that of the healthy individuals has been the focus of much research in the last 5 years often producing more questions than answers. As the disease progresses, community structure becomes progressively less diverse, most likely as a consequence of long-term aggressive antibiotic therapy. The impact of acute antibiotic therapy, antifungal treatments and CFTR modulators are less well defined, and prospective clinical trials with sputum biobanking are needed to answer these questions.