Assessing the diagnostic importance of nonviable bacterial cells in respiratory infections

The airway microbiome in cystic fibrosis and implications for treatment

PURPOSE OF REVIEW

Lung disease in cystic fibrosis (CF) results from chronic airway infection and inflammation leading to progressive bronchiectasis and respiratory failure. Bacterial pathogens, including Pseudomonas aeruginosa, Staphylococcus aureus, and Burkholderia cepacia, are known contributors. Recent studies using culture-independent molecular techniques and anaerobic cultures have broadened our view of CF airway bacterial communities.

RECENT FINDINGS

Sanger sequencing, high-throughput pyrosequencing, and phylogenetic microarray analysis have been used to comprehensively examine the airway microbiome in CF. Findings confirm that CF airway bacterial communities are highly complex structures with anaerobes frequently present. Importantly, there is evidence that loss of community diversity and richness is associated with older age and decreased lung function in CF. Bacterial communities are also likely influenced by antibiotic use, chronic P. aeruginosa infection, host genetic background (ΔF508 CFTR mutation) and geographic variations. Quantitative anaerobic cultures also detect high quantities of anaerobes from CF airway samples, including during pulmonary exacerbations. The effect of antimicrobial therapy on the airway microbiome needs further investigation. In addition, probiotic approaches have been recently studied; whether probiotics act by altering microbial communities or by modulating host inflammatory response is unknown.

SUMMARY

Complex bacterial communities, including traditional CF-associated pathogens and anaerobic bacteria, are common in CF airways. Novel therapeutic approaches aimed at modulating airway bacterial communities may lead to improved treatment of CF lung disease.

Next-generation sequencing in the analysis of human microbiota: essential considerations for clinical application

The development of next-generation sequencing (NGS) presents an unprecedented opportunity to investigate the complex microbial communities that are associated with the human body. It offers for the first time a basis for detailed temporal and spatial analysis, with the potential to revolutionize our understanding of many clinically important systems. However, while advances continue to be made in areas such as PCR amplification for NGS, sequencing protocols, and data analysis, in many cases the quality of the data generated is undermined by a failure to address fundamental aspects of experimental design. While little is added in terms of time or cost by the analysis of repeat samples, the exclusion of DNA from dead bacterial cells and the extracellular matrix, the use of efficient nucleic acid extraction methodologies, and the implementation of safeguards to minimize the introduction of contaminating nucleic acids, such considerations are essential in achieving an accurate representation of the system being studied. In this review, the chronic bacterial infections that characterize lower respiratory tract infections in cystic fibrosis patients are used as an example system to examine the implications of a failure to address these issues when designing NGS-based analysis of human-associated microbiota. Further, ways in which the impact of these factors can be minimized are discussed.

The exclusion of dead bacterial cells is essential for accurate molecular analysis of clinical samples

The DNA-based techniques used to detect bacteria in clinical samples are unable to discriminate between live bacteria, dead bacteria, and extracellular DNA. This failure to limit analysis to viable bacterial cells represents a significant problem, leading to false-positive results, as well as a failure to resolve the impact of antimicrobial therapy. The use of propidium monoazide treatment significantly reduces the contribution of dead cells and extracellular DNA to such culture-independent analyses. Here, the increased ability to resolve the impact of antibiotic therapy on Pseudomonas aeruginosa load in cystic fibrosis respiratory samples reveals statistically significant changes that would otherwise go undetected.

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

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.

Revealing the dynamics of polymicrobial infections: implications for antibiotic therapy

As a new generation of culture-independent analytical strategies emerge, the amount of data on polymicrobial infections will increase dramatically. For these data to inform clinical thinking, and in turn to maximise benefits for patients, an appropriate framework for their interpretation is required. Here, we use cystic fibrosis (CF) lower airway infections as a model system to examine how conceptual and technological advances can address two clinical questions that are central to improved management of CF respiratory disease. Firstly, can markers of the microbial community be identified that predict a change in infection dynamics and clinical outcomes? Secondly, can these new strategies directly characterize the impact of antimicrobial therapies, allowing treatment efficacy to be both assessed and optimized?

Determining cystic fibrosis-affected lung microbiology: comparison of spontaneous and serially induced sputum samples by use of terminal restriction fragment length polymorphism profiling

Sampling of the lower airways of the adult cystic fibrosis (CF) lung has received insufficient detailed consideration, with the importance of sampling strategies for bacteriological outcome not known. Although spontaneously expectorated sputum (SES) samples are often used for diagnostic bacteriological analysis, induced sputum (IS) methods have advantages. This study examined whether significant differences in bacterial content were detected when using a culture-independent, molecular profiling technique to analyze SES or IS samples. Moreover, this work examined what trends relating to bacterial species distributions and reproducibility were found in sequentially induced sputum samples and what implications this has for pathogen detection. Terminal restriction fragment length polymorphism (T-RFLP) analysis was performed on a SES sample and 4 subsequent IS samples taken at 5-min intervals from 10 clinically stable, adult CF patients. This was repeated over 3 sampling days, with variability between samples, induction periods, and sampling days determined. A diverse range of bacterial species, including potentially novel pathogens, was found. No significant difference in bacterial content was observed for either SES or serial IS samples. On average, the analysis of a single sample from any time point resolved approximately 58% of total bacterial diversity achieved by analysis of an SES sample and 4 subsequent IS samples. The reliance on analysis of a single respiratory sample was not sufficient for the detection of recognized CF pathogens in all instances. Close correlation between T-RFLP and microbiological data in the detection of key species indicates the importance of these findings in routine diagnostics for the detection of recognized and novel CF pathogens.

Studying bacterial infections through culture-independent approaches

The ability to characterize accurately the cause of infection is fundamental to effective treatment. The impact of any antimicrobial agents used to treat infection will, however, always be constrained by both the appropriateness of their use and our ability to determine their effectiveness. Traditional culture-based diagnostic microbiology is, in many cases, unable to provide this information. Molecular microbiological approaches that assess the content of clinical samples in a culture-independent manner promise to change dramatically the types of data that are obtained routinely from clinical samples. We argue that, in addition to the technical advance that these methodologies offer, a conceptual advance in the way that we reflect on the information generated is also required. Through the development of both of these advances, our understanding of infection, as well as the ways in which infections can be treated, may be improved. In the analysis of the microbiological content of certain clinical samples, such as blood, cerebrospinal fluid, brain and bone biopsy, culture-independent approaches have been well documented. Herein, we discuss how extensions to such studies can shape our understanding of infection at the many sites of the human body where a mixed flora, or in more ecological terms, a community of microbes, is present. To do this, we consider the underlying principles that underpin diagnostic systems, describe the ways in which these systems can be applied to community characterization, and discuss the significance of the data generated. We propose that at all locations within the human body where infection is routinely initiated within the context of a community of microbes, the same principles will apply. To consider this further, we take insights from areas such as the gut, oral cavity and skin. The main focus here is understanding respiratory tract infection, and specifically the infections of the cystic fibrosis lung. The impact that the use of culture-independent, molecular analyses will have on the way we approach the treatment of infections is also considered.

Bugs, biofilms, and resistance in cystic fibrosis

Bacteria infect the respiratory tract early in the course of cystic fibrosis disease, often fail to be eradicated, and together with an aggressive host inflammatory response, are thought to be key players in the irreversible airway damage from which most patients ultimately die. Although incompletely understood, certain aspects of the cystic fibrosis airway itself appear to favor the development of chronic modes of survival, in particular biofilm formation; this and the development of antibiotic resistance following exposure to multiple antibiotic courses lead to chronic, persistent infection. In addition to the common cystic fibrosis pathogens, such as Staphylococcus aureus, Haemophilus influenzae, and Pseudomonas aeruginosa, several newer species are becoming more common. Furthermore, new molecular techniques have led to the identification of multiple different organisms within respiratory secretions, many of which are not cultured with conventional tools. Future work should aim to develop clinically applicable methods to identify these and to determine which have the potential to impact pulmonary health. We outline the basic tenets of infection control and treatment.