Mild Cystic Fibrosis Lung Disease Is Associated with Bacterial Community Stability

Hampton, Thomas H.; Thomas, D.L.; Gast, Christopher J. van der; O’Toole, George A.

doi:10.1128/spectrum.00029-21

Cited by 19 publications

(24 citation statements)

References 58 publications

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“…We sought to exploit available 16S rRNA gene amplicon library sequencing data and associated clinical metadata to identify a representative set of microbial communities found in persons with CF (pwCF) that we could model in vitro . A recent study from our team using k-means to cluster 16S rRNA gene amplicon sequencing relative abundance values and another machine learning approach (e.g., the gap statistic) identified five clusters as the most parsimonious number (21). This same study revealed, following the analysis of a large cross-sectional 16S rRNA gene sequence data sets and associated metadata, that the 5 community types explained 24% of variability in lung function, twice as high as any other factor or group of factors previously identified (21).…”

Section: Resultsmentioning

confidence: 99%

“…A recent study from our team using k-means to cluster 16S rRNA gene amplicon sequencing relative abundance values and another machine learning approach (e.g., the gap statistic) identified five clusters as the most parsimonious number (21). This same study revealed, following the analysis of a large cross-sectional 16S rRNA gene sequence data sets and associated metadata, that the 5 community types explained 24% of variability in lung function, twice as high as any other factor or group of factors previously identified (21). Thus, two different approaches, using clinical outcomes data, identified five similar community types.…”

Section: Resultsmentioning

confidence: 99%

“…Of these five communities, two were dominated by a single microbial taxa: P. aeruginosa (designated the “Pa.D” community) and Streptococcus (Strep.D); these communities included 73/167 (∼23%) of the analyzed samples (21). Several P. aeruginosa -focused CF studies make it clear that specifically targeting this pathogen does not translate to positive clinical outcomes in pwCF (18, 19, 28, 29) and there has already been a substantial focus on the study of P. aeruginosa in monoculture in the context of CF (30, 31).…”

Section: Resultsmentioning

confidence: 99%

“…Based on these factors, we decided to focus on two community types identified in the study cited above (21), which are composed of various microbial taxa (Pa.M1/Pa.M2; which we refer to as "mixed"). The Pa.M1 and Pa.M2 mixed communities represented ~50% of the analyzed samples in this study (21).…”

Section: Using Computational Approaches To Identify Community Types F...mentioning

confidence: 99%

“…The pathogenesis of mixed-species infections in the CF airway is still poorly understood but it is now appreciated that distinct community types can impact clinical outcomes (21, 22). However, one of the current missing links allowing for the translation of microbiome-informed studies back to the clinic is the establishment of in vitro mixed community models that can be used to understand community function(s) of CF pathogens (23).…”

Section: Introductionmentioning

confidence: 99%

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Community composition shapes microbial-specific phenotypes in a cystic fibrosis polymicrobial model system

Jean-Pierre

Hampton

Schultz

et al. 2022

Preprint

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Interspecies interactions can drive the emergence of unexpected microbial phenotypes that are not observed when studying monocultures. The cystic fibrosis (CF) lung consists of a complex environment where particular microbes, living as polymicrobial biofilm-like communities, are associated with negative clinical outcomes for persons with CF (pwCF). However, the current lack of in vitro models integrating the microbial diversity observed in the CF airway hampers our understanding of why polymicrobial communities are recalcitrant to therapy in this disease. Here, integrating computational approaches informed by clinical data, we built a mixed community of clinical relevance to the CF lung composed of Pseudomonas aeruginosa, Staphylococcus aureus, Streptococcus sanguinis and Prevotella melaninogenica. We developed and validated this model biofilm community with multiple isolates of these four genera. When challenged with tobramycin, a front-line antimicrobial used to treat pwCF, the microorganisms in the polymicrobial community show altered sensitivity to this antibiotic compared to monospecies biofilms. We observed that wild-type P. aeruginosa is sensitized to tobramycin in a mixed community versus monoculture, and this observation holds across a range of community relative abundances. We also report that LasR loss-of-function, a variant frequently detected in the CF airway, induces tolerance of P. aeruginosa to tobramycin specifically in the mixed community. The molecular basis of this community-specific recalcitrance to tobramycin for the LasR mutant variant is the increased production of redox-active phenazines. Our data support the importance of studying clinically-relevant model polymicrobial biofilms to understand community-specific traits relevant to infections.SIGNIFICANCE STATEMENTThe CF lung is colonized by biofilm-like microbial communities that exhibit both resistance and tolerance (collectively called “recalcitrance”) to antimicrobials used in the clinic. Here, we leveraged clinical data from pwCF to inform our understanding of communities exhibiting recalcitrance. We developed and validated an in vitro model that revealed novel, community-specific phenotypes relevant to the clinic. We used this model to explore the underlying mechanism associated with a community-specific emergent behavior. We posit that in vitro models of polymicrobial communities may help in developing new antimicrobial strategies to improve patient outcomes, and that the approach used here can be applied to other polymicrobial models.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Using Computational Approaches To Identify Community Types F...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Community composition shapes microbial-specific phenotypes in a cystic fibrosis polymicrobial model system

Jean-Pierre

Hampton

Schultz

et al. 2022

Preprint

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Mathematical models of cystic fibrosis as a systemic disease

Olivença

Davis

Kumbale

et al. 2023

WIREs Mechanisms of Disease

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Cystic fibrosis (CF) is widely known as a disease of the lung, even though it is in truth a systemic disease, whose symptoms typically manifest in gastrointestinal dysfunction first. CF ultimately impairs not only the pancreas and intestine but also the lungs, gonads, liver, kidneys, bones, and the cardiovascular system. It is caused by one of several mutations in the gene of the epithelial ion channel protein CFTR. Intense research and improved antimicrobial treatments during the past eight decades have steadily increased the predicted life expectancy of a person with CF (pwCF) from a few weeks to over 50 years. Moreover, several drugs ameliorating the sequelae of the disease have become available in recent years, and notable treatments of the root cause of the disease have recently generated substantial improvements in health for some but not all pwCF. Yet, numerous fundamental questions remain unanswered. Complicating CF, for instance in the lung, is the fact that the associated insufficient chloride secretion typically perturbs the electrochemical balance across epithelia and, in the airways, leads to the accumulation of thick, viscous mucus and mucus plaques that cannot be cleared effectively and provide a rich breeding ground for a spectrum of bacterial and fungal communities. The subsequent infections often become chronic and respond poorly to antibiotic treatments, with outcomes sometimes only weakly correlated with the drug susceptibility of the target pathogen. Furthermore, in contrast to rapidly resolved acute infections with a single target pathogen, chronic infections commonly involve multi‐species bacterial communities, called “infection microbiomes,” that develop their own ecological and evolutionary dynamics. It is presently impossible to devise mathematical models of CF in its entirety, but it is feasible to design models for many of the distinct drivers of the disease. Building upon these growing yet isolated modeling efforts, we discuss in the following the feasibility of a multi‐scale modeling framework, known as template‐and‐anchor modeling, that allows the gradual integration of refined sub‐models with different granularity. The article first reviews the most important biomedical aspects of CF and subsequently describes mathematical modeling approaches that already exist or have the potential to deepen our understanding of the multitude aspects of the disease and their interrelationships. The conceptual ideas behind the approaches proposed here do not only pertain to CF but are translatable to other systemic diseases.This article is categorized under: Congenital Diseases > Computational Models

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The lung microbiome in cystic fibrosis: A gap of knowledge still to be filled

Boutin¹,

Nurjadi²

2023

Journal of Cystic Fibrosis

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Mild Cystic Fibrosis Lung Disease Is Associated with Bacterial Community Stability

Cited by 19 publications

References 58 publications

Community composition shapes microbial-specific phenotypes in a cystic fibrosis polymicrobial model system

Community composition shapes microbial-specific phenotypes in a cystic fibrosis polymicrobial model system

Mathematical models of cystic fibrosis as a systemic disease

The lung microbiome in cystic fibrosis: A gap of knowledge still to be filled

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