Review

Lung infections in cystic fibrosis: deriving clinical insight from microbial complexity Expert Rev. Mol. Diagn. 10(2), 187–196 (2010)

Geraint B Rogers, Franziska A Stressmann, Alan W Walker, Mary P Carroll and Kenneth D Bruce† Author for correspondence Molecular Microbiology Research Laboratory, Pharmaceutical Science Division, 150 Stamford Street, FranklinWilkins Building, King’s College London, London, SE1 9NH, UK Tel.: +44 (0)20 7848 4670 Fax: +44 (0)20 7848 4500 [email protected] †

Lower respiratory tract bacterial infections, such as those associated with cystic fibrosis lung disease, represent a major healthcare burden. Treatment strategies are currently informed by culture-based routine diagnostics whose limitations, including an inability to isolate all potentially clinically significant bacterial species present in a sample, are well documented. Some advances have resulted from the introduction of culture-independent molecular assays for the detection of specific pathogens. However, the application of bacterial community profiling techniques to the characterization of these infections has revealed much higher levels of microbial diversity than previously recognized. These findings are leading to a fundamental shift in the way such infections are considered. Increasingly, polymicrobial infections are being viewed as complex communities of interacting organisms, with dynamic processes key to their pathogenicity. Such a model requires an analytical strategy that provides insight into the interactions of all members of the infective community. The rapid advance in sequencing technology, along with protocols that limit analysis to viable bacterial cells, are for the first time providing an opportunity to gain such insight. Keywords : bacterial community • cystic fibrosis • lung infections • molecular diagnostics • propidium monoazide

Globally, lower respiratory tract infections (LRTIs) represent a significant healthcare and economic burden. In 2002, LRTIs were the leading cause of deaths among all infectious diseases, accounting for approximately 7% of all deaths that year [1] . In the UK and USA, respiratory tract infections are the leading reason individuals seek physician care [2–4] . Approximately, a third of these infections involve specifically the lower respiratory tract, including communityacquired pneumonia and acute exacerbations of chronic bronchitis [5] , with a significant proportion of these people requiring hospitalization [6] . Of particular concern currently is the impact of secondary bacterial pneumonia in the context of influenza infections [7] . Whether lung infection is either acute or chronic in nature, correct diagnosis of the etiological agent(s) is clearly important. Cystic fibrosis (CF) is the most common lethal autosomal recessive disorder in the Caucasian population [8,9] . In this case, lung infection is arguably the prime clinical concern. Despite advances, more than 90% of mortality in individuals suffering from CF is related to the consequences of suppurative lung disease [10] . These lung infections are a constant cause of www.expert-reviews.com

10.1586/ERM.09.81

concern for those with CF, carers and healthcare professionals. It is therefore important to constantly review, refine and optimize current diagnostic practices for respiratory samples from CF patients, and consider strategies to improve these over the relatively short term. We also address the implications of recent developments in relation to polymicrobial infection. Here, new types of data are becoming available that are at odds with the traditional concepts of infection and diagnosis. As such, there is now a need to fundamentally re-evaluate the ways in which we diagnose CF respiratory infections in order to ensure the greatest clinical insight possible. Current routine diagnostic strategy

Current standard routine diagnostic practice in microbiological analysis of CF respiratory samples involves the use of culture-based assays. These assays are designed with the intention of detecting a limited number of recognized pathogens including Pseudomonas aeruginosa, Burkholderia cepacia complex, Staphylococcus aureus, Stenotrophomonas maltophilia, Haemophilus influenzae and Alcaligenes xylosoxidans, as well as fungal species belonging to the genus Aspergillus [11] . Analysis of

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samples is directed towards providing data for two distinct goals depending on the clinical status that, for Western European CF patients, is often reflected in their age. For pediatric patients, the eradication of species such as P. aeruginosa once detected, in an attempt to prevent chronic colonization, has been seen as important in terms of long-term well-being of the patient [12] . Typically, as CF patients get older, their lungs are chronically colonized by a range of bacterial species. The focus of therapy then shifts from eradication to the management of infection [13–15] . In adult patients, a particularly important focus is on the management of the periodic crises that these patients suffer – termed infective exacerbations – which require intensive antibiotic therapy. Despite these differences in therapeutic strategy, the role played by diagnostic microbiology is the same – the detection of the presence of a limited group of species of known clinical significance and the determination of antibiotic susceptibility. However, the ability of culture-based microbiology to provide these data is questionable [16,17] . Culture-independent analyses

The advent of molecular microbiology led to the rapid proliferation of culture-independent strategies for the identification of microbes (Figure 1) . This was driven, in part, by a recognition of the difficulty of cultivating all bacteria present [18–22] . Within clinical microbiology, the use of pathogen-specific, culture-independent PCR assays, validated for the detection of a wide range of bacterial pathogens, have long been in use [23,24] . A number of such assays have also been developed specifically for the analysis of CF samples, both in terms of single-species assays for pathogens considered to be key, such as P. aeruginosa [25,26] , and through multiplex reactions for a wider group of organisms [27,28] . These assays essentially play the same role as conventional culture-based diagnostic microbiology, albeit with the advantages of increased accuracy and speed of analysis [29–31] . More recent technology is able to advance these systems. Here, further refinement of these pathogen-specific detection systems can be achieved by using quantitative PCR (Q-PCR) technology. Q-PCR assays provide both increased accuracy of quantification and increased sensitivity of detection compared with end-point PCR [32,33] , without a significant increase in running costs [34] . However, the application of Q-PCR-based diagnostics for CF remains very limited. As such, this represents an important area where direct translational research could provide clear benefits to patients. Resolving bacterial viability

There are significant differences between the way in which bacteria grow in vitro and the way in which they behave in vivo. This is also true in the context of CF respiratory infections, with colonizing bacteria known to exhibit modes of growth [17] and antibiotic susceptibilities [16] different to those in the laboratory. This provides the rationale for the direct characterization of bacteria present in respiratory samples. The application of any DNA-based analysis to clinical samples must take into account all potential sources of the DNA present. Extracellular DNA may persist for periods in the CF airways, 188

with the result that DNA-based analytical strategies cannot characterize short-term changes in the bacteria present, such as might result, for example, from antimicrobial therapy. This is a problem associated with DNA-based molecular detection systems more generally [35] . One solution is to analyze these bacteria using the less stable rRNA [36] . Such an approach provides an indication of relative metabolic activity. However, it is unsuitable where accurate enumeration of bacterial cells is required due to variation in the number of ribosomes [37] . Furthermore, owing to rRNA instability, particular considerations concerning sample collection and storage are needed [38,39] . As an alternative, the pretreatment of samples with propidium monoazide (PMA), followed by photocrosslinking, was developed as a strategy to prevent extracellular DNA, or DNA derived from nonviable bacteria, contributing to PCR reactions [40] . This process has recently been applied to the analysis of LRTIs in CF [41] . Within adult CF, the use of PMA treatment allows for changes in bacterial populations, over the course of antibiotic treatment to be closely monitored. Furthermore, it has the potential to limit false-positive ‘calls’ arising from nonviable cells in first-instance detection of pathogens in noncolonized patients. This is an emerging technology and there are a number of validatory areas that require attention, including the impact of collection and storage of samples on cellular viability, as well as the ability of PMA treatment to exclude DNA from nonviable cells of all bacterial species. However, once fully validated, this strategy has the potential for wide application across clinical diagnostics. Viewing polymicrobial infections as a bacterial community

The lower respiratory tract is free of bacterial colonization in healthy individuals [42] . As such, any bacterial species, regardless of its perceived pathogenicity, has the potential to cause inflammation/disease if colonizing the CF lung. There is, therefore, a need to characterize all bacterial species present within a CF respiratory sample. This led to the use of techniques such as 16S rRNA gene clone library analysis and terminal restriction fragment length polymorphism profiling – systems that had been originally applied to study microbially complex habitats of environments such as soil and water [43–48] . Moreover, these natural environments are habitats where the fundamental influence that the wider pool of microbes can have on the behavior of individual species has long been recognized [49–51] . Such inclusive, culture-independent techniques have been extended to the analysis of the bacteria within CF respiratory samples to evaluate bacterial diversity [52–55] . These studies have indicated that CF airway bacteria cover a far greater phylogenetic range than previously recognized, and have revealed species novel to the CF lung, whose clinical significance must now be determined. In addition to the bacterial species recognized as CF pathogens described previously, these culture-independent analyses have shown a range of other species from the same Phyla to be present, including Veillonella, Streptococcus, Abiotrophia, Expert Rev. Mol. Diagn. 10(2), (2010)

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1.0

1.8 mL

Lung infections in cystic fibrosis: deriving clinical insight from microbial complexity

CF respiratory sample

Electrophoretic profiling

Quantitative PCR

16S clone gene sequence analysis

High-throughput parallel sequencing

Microarrays

Includes 16S rRNA gene-based analyses such as T-RFLP and DGGE profiling

Sensitive technique for bacterial detection and quantification

16S rRNA gene sequencing considered a gold standard for species identification

Provides indepth bacterial community characterization without prior species identification

Include methods such as Phylochip [133]

Rapid, inexpensive community structure overview Limited ability of direct species identification Allows total community profiling without predetermination of species present

Can quantify speciesspecific or total bacterial load within samples Requires the selection of target species before analysis

Allows total community profiling when performed in depth Relatively expensive and time-consuming, and therefore limited application in longitudinal studies

Expensive but with costs falling with increased use Large data sets produced require sophisticated analytical techniques

Provide species identification and determination of relative species abundance based on 16S rRNA gene sequence Allows identification of a large but predetermined group of species Limited application in CF infections to date

Figure 1. Key molecular methods for bacterial community analysis of cystic fibrosis respiratory samples. CF: Cystic fibrosis; DGGE: Denaturing gradient gel electrophoresis; T-RFLP: Terminal restriction fragment length polymorphism.

Gemella species (Firmicutes), and Neisseria and Acinetobacter species (Proteobacteria). However, species belonging to four other bacterial Phyla, Actinobacteria (including Actinomyces spp. and Rothia spp.), Bacteroidetes/Chlorobi (including Prevotella spp., Porphyromonas spp. and Capnocytophaga spp.), Spirochaetes (Treponema spp.) and Fusobacteria (Fusobacterium spp.), have been detected. The presence of groups of organisms previously excluded by conventional routine assays (e.g., those bacteria requiring anaerobic conditions for growth) have also been detected. These data highlight the disparity between the limited number of species targeted by culture-dependent routine microbiology, and the much wider array of potentially pathogenic species detectable by culture-independent profiling. Determining the role in disease of these species that are not recognized as CF pathogens is of obvious importance. An initial step in this process is expanding Q-PCR assays to include them. In this way, the size and stability of populations of these species could be determined. Furthermore, many species found in respiratory CF samples, such as Veillonella dispar and Streptococcus mitis, are known pathogens in other contexts [56–58] . As such, there is potential scope to exploit diagnostic tools already developed, thereby giving further understanding of the role that these organisms play in human infection. In polymicrobial infections more generally, it is increasingly common to regard the bacteria present as constituting a bacterial community. In this context, ‘community’ can be seen as an integrated assemblage of populations that coexist in a given environment [59] . Traditionally, infections such as those of the CF lower www.expert-reviews.com

airway have been analyzed with diagnostic approaches focused on reductionist processes. This involves the isolation of individual species from a community, based on the precept that the infection as a whole can be understood by isolated examination of the constituent components. However, for the microbiota associated with many human infectious diseases, the influence of the bacterial community as a whole may very often be greater than the simple sum of its parts. Human oral microbiology has led the way in the context of our understanding of complex communities [60,61] . Infections, such as apical periodontitis, are not caused by any single pathogen, but rather result from the activity of species organized into a community [59,62,63] . As such, this differs from diseases caused by pathogens that have single-species etiology. This ‘holistic’ approach to understanding the community and its impact on disease is required [59,64] . This conceptual change in thinking has underlined the importance of using inclusive community analysis strategies to characterize CF respiratory samples [65] . Bacterial community dynamics

The application of culture-independent strategies is increasingly revealing the complexity of the bacterial communities that colonize the CF airways. However, the interactions between these communities and their host are not static. Periods of relative stability in airway disease are punctuated by periods of infective exacerbations, typified by an increase in pulmonary symptoms. These infective exacerbations significantly contribute to both lung 189

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function loss [66] and CF lung disease progression [67] . These infective episodes have been postulated to relate to a complex relationship between host defence and airway microbiology [68] . However, the nature of such a relationship remains to be characterized. As yet, culture-independent strategies have not been applied to characterizing the processes involved in the transition between stability and infective exacerbation, but the possibility that these events may be driven by changes in the polymicrobial community must be investigated. Single time-point analysis is of course unable to show how community dynamics change as a result of immune response or treatment. For this, longitudinal analysis is necessary. This may lead to the identification of predictors of clinical change. Furthermore, such data can be used to construct a coherent overview of a chronic infection. Longitudinal studies can also provide insight into relationships between bacteria and the host in CF. For example, culture-based studies have shown that P. aeruginosa behaves differently over time to pathogens as we have traditionally viewed them. The P. aeruginosa strain present in advanced CF infections differs systematically from ‘wild-type’ P. aeruginosa, with virulence factors required for the initiation of acute infection lost over time [69] . This may result from a reduction in the immune response to the presence of P. aeruginosa in the airways [69,70] . Therefore, as airway disease progresses, primary colonizing species appear to behave less and less like traditional pathogens. In addition, the expression of virulence may not be necessary for pathogenesis. The presence of bacteria growing as biofilms on tissues that are not adapted to their presence can trigger destructive inflammatory responses [59] . Therefore, in chronic infections, susceptible tissues can respond in a detrimental way to bacteria only maintaining their presence [71] . This apparent triggering of disease by the presence of an organism that does not, or is not capable of, expressing pathogenic behavior raises the question of what constitutes a pathogen? If we consider P. aeruginosa to be a respiratory pathogen under such circumstances, do we need to extend the definition to encompass other species not known to exhibit pathogenic behavior that can be shown to chronically colonize the lower airways of CF patients? While no clear answer can be given to these questions, it is worth noting that a range of bacterial species regarded as normal oral flora can modify the degree of virulence exhibited by a species such as P. aeruginosa [72] . Equally, therefore, the potential for behavioral modification may occur for those species regarded typically as not pathogenic to the host. If so, a set of complex diagnostic and therapeutic implications when detecting such ‘contextual pathogenic’ species would emerge. Diagnosis in relation to antibiotic therapy

Treatment with antimicrobial agents during exacerbation reduces symptoms and improves lung function [73–75] . However, the extent of in vitro impact is not easy to determine. This inability to monitor the direct impact of therapy greatly hampers the real time therapeutic refinement or the detection of a successful outcome. Furthermore, in some cases, determining drug impacts is made more complicated when the antibiotics 190

used have both antimicrobial and immunomodulatory activities (e.g., macrolide antibiotics) [76,77] . Differentiation of these roles can only be achieved through direct analysis of viable bacterial numbers longitudinally over a treatment period relating these data to clinical information. There is increased recognition of extensive biofilm growth of CF pathogens [78–80] , where bacteria overproduce mucoid exopolysaccharide (alginate), which surrounds them and protects them from external challenges, such as mucociliary clearance, the host immune response and antibiotics, and is highly pro­ inflammatory [81] . The impact here is that antibiotic impact of such treatment is greatly reduced, with infection typically persisting [82–85] . In addition to a failure to clear infections, this increases the likelihood of antibiotic resistance developing, as well as increasing side effects for the patient. It is, therefore, important that current antibiotic strategies are fundamentally re-evaluated in recognition of their role. Increasingly, the role of antimicrobial therapy against chronic CF lung infections should be targeted towards controlling the behavior of colonizing species rather than trying to eradicate them. For example, bismuth-ethanedithiols have been shown to dampen the virulence of P. aeruginosa at subinhibitory concentrations [86] . However, while culture-based antibiotic sensitivity testing often fails to accurately reflect antibiotic impact in vivo [87] , cultureindependent techniques are, as yet, unable to provide clinicians with comparable data. The extent to which culture-independent techniques replace the use of culture-based diagnostics may depend, to a large degree, on their ability to provide this type of information. Extending our view of the infective community

Taking a holistic view of infection requires the concept of community to extend beyond the bacteria to encompass other microbes. Fungi are common in the CF respiratory tract [88] , with the filamentous fungi Aspergillus fumigatus and Scedosporium apiospermum in particular associated with serious clinical complications [67] . Furthermore, phylogenetically diverse fungal species are being increasingly isolated from CF respiratory samples [89] . The involvement of fungi in respiratory infections remains controversial [89] . The application of fungal community analysis, such as those developed in nonclinical contexts [90–92] , to CF lung disease, may, therefore, be of great value. However, the impact of fungi may extend beyond the direct causation of disease, and involve the well-recognized ability of fungi and bacteria to influence one another [93–95] . Respiratory viral infection may be linked to exacerbation and disease progression [96–101] . However, opinion as to whether these infections precipitate bacterial infection or change colonization remains divided [102–105] . The impact of respiratory viruses may have been underestimated owing to the relative insensitivity of traditional tissue culture and immunofluorescence detection assays [106] . However, as the use of molecular-based techniques for viral detection increases [102,106–108] , this will greatly enhance our understanding. The development of multiplex PCR arrays [109,110] and the application of Q-PCR [111] have increased the speed and Expert Rev. Mol. Diagn. 10(2), (2010)

Lung infections in cystic fibrosis: deriving clinical insight from microbial complexity

accuracy of detection of respiratory viruses. However, phylogenetic diversity among respiratory viruses makes direct community analyses, such as those based on conserved regions in bacteria and fungi, difficult. Bacteriophages – bacterial viruses – may also influence bacteria colonizing the CF lung and may be important in relation to both biofilm development and disruption, antibiotic resistance and virulence [112–119] . Furthermore, the microbial metacommunity represents only one half of the dynamic infection system. Casadevall and Pirofski, pointed out that existing definitions of microbial pathogenicity and virulence are inadequate to explain many infectious diseases as they do not incorporate the contribution of the host to these processes [120] . As such, characterizing host response, as well as microbial activity, is vital if the dynamics of infection are to be understood. Expert commentary

The integration of molecular analyses into routine diagnostics will fundamentally change both the amount and type of data available to clinicians. In turn, this will require a shift in the way in which these data are handled, and will be used to inform clinical decision making. Moreover, data that reflect the interaction between host and microbial community in greater detail may provide a measure of the impact of therapies in relation to patient health. In a respiratory context, this may also be invaluable where attempting to assess changes in underlying lung biology, for example, those changes resulting from successful gene therapy of the underlying genetic defect in CF. In such circumstances, measurable improvements in lung function may only result after changes in airway–microbe interactions have occurred. In the shorter term, determining opportunities for early antibiotic intervention on the basis of changes in the characteristics or behavior of the microbes present in the lung, prior to the establishment of any corresponding inflammatory response, has the potential to reduce damage to the airways significantly. As such, this would represent a shift from delivering therapy in response to a worsening of respiratory health, to prophylactic interventions prior to the manifestation of symptoms. As discussed, molecular assessment of microbial communities in chronic respiratory infections can directly report on the efficacy of antibiotic or antimicrobial therapies. Such data have important implications for antibiotic selection, with drugs chosen on the basis of demonstrated effectiveness in vivo, rather than poorly translatable in vitro antibiotic susceptibility results. Furthermore, in addition to providing a basis for selecting the most appropriate therapy, the application of these analytical strategies will also provide a means by which to re-evaluate the way in which treatment is administered. Current standard practice in treating pulmonary exacerbations in CF lung infections involves a combination of two antibiotics given over a 2-week period. However, while this period of treatment is suitable for eradication of bacteria in many types of acute infection, it is not necessarily appropriate where the aim is the reduction of symptoms associated with pulmonary exacerbation. In such circumstances, eradication of the bacteria present is not a realistic aim. As such, determining accurately the www.expert-reviews.com

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period over which treatment provides a significant impact, while minimizing the likelihood of both drug-related side effects and the development of resistance, will be of major benefit. Five-year view

Impressive advances in our ability to perform massively parallel sequencing offer, for the first time, a possible route to achieving analysis of entire systems as single entities. These strategies have been applied to single time-point samples in a number of clinical contexts, including CF sputum [121–123] . However, they are yet to be applied longitudinally to characterize metacommunity dynamics. Recent improvements to next-generation sequencing technologies, including greater sequencing throughput, longer read lengths and multiplexing of samples, however, mean that large studies of this kind are now feasible [124] . The quality profile of next-generation sequencing introduce challenges when individual reads are used as primary data (as opposed to sequence assemblies) but recent bioinformatic developments aimed at removing artifacts from these large datasets should greatly improve fidelity [125,126] . The implications of current trends in molecular diagnostics of infectious disease suggest movement in the shorter term towards high-throughput, automated, array-type technologies. However, while these strategies lend themselves to translation into routine diagnostics, they are likely to be overtaken rapidly by sequencingbased approaches, which provide far higher depth of analysis for relatively low cost. These systems will provide a wealth of data regarding types of organisms present in a sample and the virulence factors/resistance determinants that influence disease severity [30] . However, the data generated using these techniques are, by their nature, complex and challenging to analyze. To facilitate this, a steady stream of new bioinformatic tools to interpret them is gradually being made available [127–132] . Consideration must be given to which elements of these data should be provided to clinicians as part of routine diagnostics in order to improve upon the data currently available to them. As such, this will also require consideration of which data are able to give clinical insight. The establishment of a close dialogue between basic scientists, diagnostic service providers and clinicians will, therefore, be essential. Furthermore, while detecting the presence of an organism of known clinical significance is clearly important, it is not sufficient to indicate disease alone. Conversely, disease can be triggered by the presence of organisms not recognized in themselves as pathogens. As such, moving the focus of the management of chronic polymicrobial infections from individual species, to take in the wider microbial community, may be helpful. Financial & competing interests disclosure

This work was supported by a research grant from the Anna Trust. Geraint B Rogers and Kenneth D Bruce are members of the ISHAM working group on fungal respiratory infections in cystic fibrosis. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed. No writing assistance was utilized in the production of this manuscript. 191

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Key issues • The introduction of culture-independent, PCR-based analytical approaches represents an advance over the culture-based routine diagnostics currently employed in analysis of cystic fibrosis (CF) respiratory samples. • Propidium monoazide photocrosslinking pretreatment of samples limits DNA-based analysis to viable bacterial cells. This allows dynamic changes in bacterial populations, such as those resulting from the impact of therapy, to be rapidly identified using culture-independent techniques. • Bacterial community-profiling techniques have revealed much higher bacterial diversity in CF respiratory infections than previously recognized, including groups of bacterial species such as anaerobes. This underlines the importance of using nonselective community profiling analyses. • Longitudinal profiling of samples from individual patients, as well as cross-sectional profiling within patient groups sharing common characteristics, will be necessary if the complex interactions between the bacterial community present in the CF lung and the host are to be characterized. • The holistic view of CF lung infection is increasingly subscribed to. However, it must also be expanded to include the potential significant impact of fungi, viruses and the host immune response. • The development of massively parallel sequencing provides, for the first time, a basis for the characterization of the complex interacting systems that form the basis for these infections.

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Ecker DJ, Sampath R, Massire C et al. Ibis T5000, a universal biosensor approach for microbiology. Nat. Rev. Microbiol. 6(7), 553–558 (2008).

•

Describes a novel approach to bacterial community profiling.

56

Zaninetti-Schaerer A, Van Delden C, Genevay S, Gabay C. Total hip prosthetic joint infection due to Veillonella species. Joint Bone Spine 71(2), 161–163 (2004).

57

Stackebrandt E, Liesack W, Goebel BM. Bacterial diversity in a soil sample from a subtropical Australian environment as determined by 16S rDNA analysis. FASEB J. 7(1), 232–236 (1993).

Kutlu SS, Sacar S, Cevahir N, Turgut H. Community-acquired Streptococcus mitis meningitis, a case report. Int. J. Infect. Dis. 12(6), E107–E109 (2008).

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Fuhrman JA, McCallum K, Davis AA. Phylogenetic diversity of subsurface marine microbial communities from the Atlantic and Pacific oceans. Appl. Environ. Microbiol. 59(5), 1294–1302 (1993).

Tunney MM, Field TR, Moriarty TF et al. Detection of anaerobic bacteria in high numbers in sputum from patients with cystic fibrosis. Am. J. Respir. Crit. Care Med. 177(9), 995–1001 (2008).

•

Describes the potential significance of anaerobic bacteria in CF respiratory infections.

41

Holland NT, Smith MT, Eskenazi B, Bastaki M. Biological sample collection and processing for molecular epidemiological studies. Mutat. Res. 543(3), 217–234 (2003).

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Rogers GB, Stressmann FA, Koller G et al. Assessing the diagnostic importance of nonviable bacterial cells in respiratory infections. Diagn. Microbiol. Infect. Dis. 62(2), 133–141 (2008).

•• Describes the use of propidium monoazide photocrosslinking to limit DNA-based profiling to viable bacterial cells. This allows determination of the impact of treatment in real time and has important implications for all DNA-based diagnostic analyses. 42

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Rogers GB, Carroll MP, Serisier DJ et al. Bacterial activity in cystic fibrosis lung infections. Respir. Res. 6, 49 (2005).

•

Review

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Siqueira JF Jr, Rocas IN. Community as the unit of pathogenicity: an emerging concept as to the microbial pathogenesis of apical periodontitis. Oral Surg. Oral Med. Oral Pathol. Oral Radiol. Endod. 107(6), 870–878 (2009). Grenier D, Mayrand D. Nutritional relationships between oral bacteria. Infect. Immun. 53(3), 616–620 (1986).

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Costerton JW. The Biofilm Primer. Springer-Verlag, Berlin, Germany (2007).

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Regelmann WE, Elliott GR, Warwick WJ, Clawson CC. Reduction of sputum Pseudomonas aeruginosa density by antibiotics improves lung function in cystic fibrosis more than do bronchodilators and chest physiotherapy alone. Am. Rev. Respir. Dis. 141(4 Pt 1), 914–921 (1990).

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Smith AL, Redding G, Doershuk C et al. Sputum changes associated with therapy for endobronchial exacerbation in cystic fibrosis. J. Pediatr. 112(4), 547–554 (1988).

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Ramsey BW, Pepe MS, Quan JM et al. Intermittent administration of inhaled tobramycin in patients with cystic fibrosis. cystic fibrosis inhaled tobramycin study group. N. Engl. J. Med. 340(1), 23–30 (1999).

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Amsden GW. Anti-inflammatory effects of macrolides – an underappreciated benefit in the treatment of community-acquired respiratory tract infections and chronic inflammatory pulmonary conditions? J. Antimicrob. Chemother. 55(1), 10–21 (2005).

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Kuramitsu HK, He X, Lux R, Anderson MH, Shi W. Interspecies interactions within oral microbial communities. Microbiol. Mol. Biol. Rev. 71(4), 653–670 (2007).

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Rogers GB, Carroll MP, Bruce KD. Studying bacterial infections through culture independent approaches. J. Med. Microbiol. 58(Pt 11), 1401–1418.

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Amadori A, Antonelli A, Balteri I et al. Recurrent exacerbations affect FEV(1) decline in adult patients with cystic fibrosis. Respir. Med. 103(3), 407–413 (2008).

Bjarnsholt T, Kirketerp-Moller K, Jensen PO et al. Why chronic wounds will not heal, a novel hypothesis. Wound Repair Regen. 16(1), 2–10 (2008).

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Balfour-Lynn IA, Elborn JS. Respiratory disease, infection. In: Cystic Fibrosis. Hodson M, Geddes D, Bush A (Eds). Hodder Arnold, London, UK, 137–158 (2007).

Worlitzsch D, Tarran R, Ulrich M et al. Effects of reduced mucus oxygen concentration in airway pseudomonas infections of cystic fibrosis patients. J. Clin. Invest. 109(3), 317–325 (2002).

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Bjarnsholt T, Jensen, PO, Fiandaca MJ et al. Pseudomonas aeruginosa biofilms in the respiratory tract of cystic fibrosis patients. Pediatr. Pulmonol. 44, 547–558 (2009).

81

Davies JC, Bilton D. Bugs, biofilms, and resistance in cystic fibrosis. Respir. Care 54, 628–640 (2009).

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Kobayashi H. Airway biofilms, implications for pathogenesis and therapy of respiratory tract infections. Treat Respir. Med. 4(4), 241–253 (2005).

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Goss CH, Burns JL. Exacerbations in cystic fibrosis. 1, epidemiology and pathogenesis. Thorax 62(4), 360–367 (2007).

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Smith EE, Buckley DG, Wu Z et al. Genetic adaptation by Pseudomonas aeruginosa to the airways of cystic fibrosis patients. Proc. Natl Acad. Sci. USA 103(22), 8487–8492 (2006).

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Tre-Hardy M, Mace C, El Manssouri N et al. Effect of antibiotic co-administration on young and mature biofilms of cystic

fibrosis clinical isolates, the importance of the biofilm model. Int. J. Antimicrob. Agents 33(1), 40–45 (2009). •

Describes the implications of biofilm growth of bacteria in the CF lung for antibiotic efficacy and in vitro analysis.

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Rose WE, Poppens PT. Impact of biofilm on the in vitro activity of vancomycin alone and in combination with tigecycline and rifampicin against Staphylococcus aureus. J. Antimicrob. Chemother. 63(3), 485–488 (2009).

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Moskowitz SM, Foster JM, Emerson J, Burns JL. Clinically feasible biofilm susceptibility assay for isolates of Pseudomonas aeruginosa from patients with cystic fibrosis. J. Clin. Microbiol. 42(5), 1915–1922 (2004).

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Wu CL, Domenico P, Hassett DJ et al. Subinhibitory bismuth-thiols reduce virulence of Pseudomonas aeruginosa. Am. J. Respir. Cell. Mol. Biol. 26(6), 731–738 (2002).

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Nagano Y, Millar BC, Goldsmith CE et al. Emergence of Scedosporium apiospermum in patients with cystic fibrosis. Arch. Dis. Child 92(7), 607 (2007).

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Bouchara JP, Hsieh HY, Croquefer S et al. Development of an oligonucleotide array for direct detection of fungi in sputum samples from patients with cystic fibrosis. J. Clin. Microbiol. 47(1), 142–152 (2009).

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Kennedy N, Brodie E, Connolly J, Clipson N. Seasonal influences on fungal community structure in unimproved and improved upland grassland soils. Can. J. Microbiol. 52(7), 689–694 (2006).

91

Anderson IC, Cairney JW. Diversity and ecology of soil fungal communities. Increased understanding through the application of molecular techniques. Environ. Microbiol. 6(8), 769–779 (2004).

92

Hansgate AM, Schloss PD, Hay AG, Walker LP. Molecular characterization of fungal community dynamics in the initial stages of composting. FEMS Microbiol. Ecol. 51(2), 209–214 (2005).

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Woo S, Fogliano V, Scala F, Lorito M. Synergism between fungal enzymes and bacterial antibiotics may enhance biocontrol. Antonie Van Leeuwenhoek 81(1–4), 353–356 (2002).

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Lung infections in cystic fibrosis: deriving clinical insight from microbial complexity

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Rousk J, Demoling LA, Bahr A, Baath E. Examining the fungal and bacterial niche overlap using selective inhibitors in soil. FEMS Microbiol. Ecol. 63(3), 350–358 (2008). Romano JD, Kolter R. Pseudomonas– saccharomyces interactions. Influence of fungal metabolism on bacterial physiology and survival. J. Bacteriol. 187(3), 940–948 (2005). Pribble CG, Black PG, Bosso JA, Turner RB. Clinical manifestations of exacerbations of cystic fibrosis associated with nonbacterial infections. J. Pediatr. 117(2 Pt 1), 200–204 (1990). Ong EL, Ellis ME, Webb AK et al. Infective respiratory exacerbations in young adults with cystic fibrosis, role of viruses and atypical microorganisms. Thorax 44(9), 739–742 (1989).

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Armstrong D, Grimwood K, Carlin JB et al. Severe viral respiratory infections in infants with cystic fibrosis. Pediatr. Pulmonol. 26(6), 371–379 (1998).

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Hament JM, Kimpen JL, Fleer A, Wolfs TF. Respiratory viral infection predisposing for bacterial disease, a concise review. FEMS Immunol. Med. Microbiol. 26(3–4), 189–195 (1999). Van Ewijk BE, Wolfs TF, Aerts PC et al. RSV mediates Pseudomonas aeruginosa binding to cystic fibrosis and normal epithelial cells. Pediatr. Res. 61(4), 398–403 (2007). Petersen NT, Hoiby N, Mordhorst CH et al. Respiratory infections in cystic fibrosis patients caused by virus, chlamydia and mycoplasma – possible synergism with Pseudomonas aeruginosa. Acta Paediatr. Scand. 70(5), 623–628 (1981).

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Punch G, Syrmis MW, Rose BR et al. Method for detection of respiratory viruses in the sputa of patients with cystic fibrosis. Eur. J. Clin. Microbiol. Infect. Dis. 24(1), 54–57 (2005). Kim SR, Ki CS, Lee NY. Rapid detection and identification of 12 respiratory viruses using a dual priming oligonucleotide system-based multiplex PCR assay. J. Virol. Methods 156(1–2), 111–116 (2009). Murali S, Langston AA, Nolte FS et al. Detection of respiratory viruses with a multiplex polymerase chain reaction assay (MultiCode-PLx respiratory virus panel) in patients with hematologic malignancies. Leuk. Lymphoma 50(4), 619–624 (2009). Terlizzi ME, Massimiliano B, Francesca S et al. Quantitative RT real time PCR and indirect immunofluorescence for the detection of human parainfluenza virus 1, 2, 3. J. Virol. Methods 160(1–2), 172–177 (2009). Rolain JM, Francois P, Hernandez D et al. Genomic analysis of an emerging multiresistant Staphylococcus aureus strain rapidly spreading in cystic fibrosis patients revealed the presence of an antibiotic inducible bacteriophage. Biol. Direct 4, 1 (2009). Pal C, Macia MD, Oliver A, Schachar I, Buckling A. Coevolution with viruses drives the evolution of bacterial mutation rates. Nature 450(7172), 1079–1081 (2007). Poullain V, Gandon S, Brockhurst MA, Buckling A, Hochberg ME. The evolution of specificity in evolving and coevolving antagonistic interactions between a bacteria and its phage. Evolution 62(1), 1–11 (2008). Brockhurst MA, Buckling A, Rainey PB. The effect of a bacteriophage on diversification of the opportunistic bacterial pathogen, Pseudomonas aeruginosa. Proc. Biol. Sci. 272(1570), 1385–1391 (2005). Rice SA, Tan CH, Mikkelsen PJ et al. The biofilm life cycle and virulence of Pseudomonas aeruginosa are dependent on a filamentous prophage. ISME J. 3(3), 271–282 (2009).

Review

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Hughes KA, Sutherland IW, Jones MV. Biofilm susceptibility to bacteriophage attack. The role of phage-borne polysaccharide depolymerase. Microbiology 144(Pt 11), 3039–3047 (1998).

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Lu TK, Collins JJ. Dispersing biofilms with engineered enzymatic bacteriophage. Proc. Natl Acad. Sci. USA 104(27), 11197–11202 (2007).

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Zegans ME, Wagner JC, Cady KC et al. Interaction between bacteriophage DMS3 and host CRISPR region inhibits group behaviors of Pseudomonas aeruginosa. J. Bacteriol. 191(1), 210–219 (2009).

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Casadevall A, Pirofski LA. Microbial virulence results from the interaction between host and microorganism. Trends Microbiol. 11(4), 157–158; author reply 158–159 (2003).

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Krober M, Bekel T, Diaz NN et al. Phylogenetic characterization of a biogas plant microbial community integrating clone library 16S-rDNA sequences and metagenome sequence data obtained by 454-pyrosequencing. J. Biotechnol. 142(1), 38–49 (2009).

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Lauber CL, Hamady M, Knight R, Fierer N. Soil pH as a predictor of soil bacterial community structure at the continental scale, a pyrosequencing-based assessment. Appl. Environ. Microbiol. 75(15), 5111–5120 (2009).

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Armougom F, Bittar F, Stremler N et al. Microbial diversity in the sputum of a cystic fibrosis patient studied with 16S rDNA pyrosequencing. Eur. J. Clin. Microbiol. Infect. Dis. 28(9), 1151–1154 (2009).

•• Describes the first application of pyrosequencing to CF respiratory samples. 124

Tringe SG, Hugenholtz P. A renaissance for the pioneering 16S rRNA gene. Curr. Opin. Microbiol. 11, 442–446 (2008).

125

Quince C, Lanzén A, Curtis TP et al. Accurate determination of microbial diversity from 454 pyrosequencing data. Nat. Methods 6(9), 639–641 (2009).

126

Gomez-Alvarez V, Teal TK, Schmidt TM. Systematic artifacts in metagenomes from complex microbial communities. ISME J. 3(11), 1314–1317 (2009).

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Huse SM, Dethlefsen L, Huber JA et al. Exploring microbial diversity and taxonomy using SSU rRNA hypervariable tag sequencing. PLOS Genet. 4(11), E1000255 (2008).

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White JR, Nagarajan N, Pop M. Statistical methods for detecting differentially abundant features in clinical metagenomic samples. PLoS Comput. Biol. 5(4), E1000352 (2009).

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Sun Y, Cai Y, Liu L et al. ESPRIT: estimating species richness using large collections of 16S rRNA pyrosequences. Nucleic Acids Res. 37(10), E76 (2009).

130

Hamady M, Lozupone C, Knight R. Fast UniFrac: facilitating high-throughput phylogenetic analyses of microbial communities including analysis of pyrosequencing and PhyloChip data. ISME J. 4(1), 17–27 (2009).

131

Brady A, Salzberg SL, Phymm BL. Metagenomic phylogenetic classification with interpolated Markov models. Nat. Methods 6(9), 673–676 (2009).

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Schloss PD, Westcott SL, Ryabin T et al. Introducing mothur: open source, platform-independent, communitysupported software for describing and comparing microbial communities. Appl. Environ. Microbiol. 75(23), 7537–7541 (2009).

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Affiliations •

•

Geraint B Rogers Molecular Microbiology Research Laboratory, Pharmaceutical Science Division, 150 Stamford Street, FranklinWilkins Building, King’s College London, London, SE1 9NH, UK Tel.: +44 207 848 4467 Fax: +44 207 848 4500 [email protected] Franziska A Stressmann Molecular Microbiology Research Laboratory, Pharmaceutical Science Division, 150 Stamford Street, FranklinWilkins Building, King’s College London, London SE1 9NH, UK Tel.: +44 207 848 3245 Fax: +44 207 848 4500 [email protected]

•

Alan W Walker The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK Tel.: +44 122 349 6802 Fax: +44 122 383 4244 [email protected]

•

Mary P Carroll Cystic Fibrosis Unit, Southampton University Hospitals NHS Trust, Tremona Road, Southampton SO16 6YD, UK Tel.: +44 238 079 4719 Fax: +44 238 079 4961 [email protected]

•

Kenneth D Bruce Molecular Microbiology Research Laboratory, Pharmaceutical Science Division, 150 Stamford Street, FranklinWilkins Building, King’s College London, London SE1 9NH, UK Tel.: +44 207 848 4670 Fax: +44 207 848 4500 [email protected]

Expert Rev. Mol. Diagn. 10(2), (2010)