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Microbial, host and xenobiotic diversity in the cystic fibrosis sputum metabolome.

ABSTRACT: Cystic fibrosis (CF) lungs are filled with thick mucus that obstructs airways and facilitates chronic infections. Pseudomonas aeruginosa is a significant pathogen of this disease that produces a variety of toxic small molecules. We used molecular networking-based metabolomics to investigate the chemistry of CF sputa and assess how the microbial molecules detected reflect the microbiome and clinical culture history of the patients. Metabolites detected included xenobiotics, P. aeruginosa specialized metabolites and host sphingolipids. The clinical culture and microbiome profiles did not correspond to the detection of P. aeruginosa metabolites in the same samples. The P. aeruginosa molecules that were detected in sputum did not match those from laboratory cultures. The pseudomonas quinolone signal (PQS) was readily detectable from cultured strains, but absent from sputum, even when its precursor molecules were present. The lack of PQS production in vivo is potentially due to the chemical nature of the CF lung environment, indicating that culture-based studies of this pathogen may not explain its behavior in the lung. The most differentially abundant molecules between CF and non-CF sputum were sphingolipids, including sphingomyelins, ceramides and lactosylceramide. As these highly abundant molecules contain the inflammatory mediator ceramide, they may have a significant role in CF hyperinflammation. This study demonstrates that the chemical makeup of CF sputum is a complex milieu of microbial, host and xenobiotic molecules. Detection of a bacterium by clinical culturing and 16S rRNA gene profiling do not necessarily reflect the active production of metabolites from that bacterium in a sputum sample.

SUBMITTER: Quinn RA

PROVIDER: S-EPMC5029181 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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Microbial, host and xenobiotic diversity in the cystic fibrosis sputum metabolome.

Quinn Robert A RA Phelan Vanessa V VV Whiteson Katrine L KL Garg Neha N Bailey Barbara A BA Lim Yan Wei YW Conrad Douglas J DJ Dorrestein Pieter C PC Rohwer Forest L FL

The ISME journal 20151201 6

Cystic fibrosis (CF) lungs are filled with thick mucus that obstructs airways and facilitates chronic infections. Pseudomonas aeruginosa is a significant pathogen of this disease that produces a variety of toxic small molecules. We used molecular networking-based metabolomics to investigate the chemistry of CF sputa and assess how the microbial molecules detected reflect the microbiome and clinical culture history of the patients. Metabolites detected included xenobiotics, P. aeruginosa speciali ...[more]

PMID: 26623545

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Project description:BackgroundCystic fibrosis (CF) is an autosomal recessive disease characterized by recurrent lung infections. Studies of the lung microbiome have shown an association between decreasing diversity and progressive disease. 454 pyrosequencing has frequently been used to study the lung microbiome in CF, but will no longer be supported. We sought to identify the benefits and drawbacks of using two state-of-the-art next generation sequencing (NGS) platforms, MiSeq and PacBio RSII, to characterize the CF lung microbiome. Each has its advantages and limitations.MethodsTwelve samples of extracted bacterial DNA were sequenced on both MiSeq and PacBio NGS platforms. DNA was amplified for the V4 region of the 16S rRNA gene and libraries were sequenced on the MiSeq sequencing platform, while the full 16S rRNA gene was sequenced on the PacBio RSII sequencing platform. Raw FASTQ files generated by the MiSeq and PacBio platforms were processed in mothur v1.35.1.ResultsThere was extreme discordance in alpha-diversity of the CF lung microbiome when using the two platforms. Because of its depth of coverage, sequencing of the 16S rRNA V4 gene region using MiSeq allowed for the observation of many more operational taxonomic units (OTUs) and higher Chao1 and Shannon indices than the PacBio RSII. Interestingly, several patients in our cohort had Escherichia, an unusual pathogen in CF. Also, likely because of its coverage of the complete 16S rRNA gene, only PacBio RSII was able to identify Burkholderia, an important CF pathogen.ConclusionWhen comparing microbiome diversity in clinical samples from CF patients using 16S sequences, MiSeq and PacBio NGS platforms may generate different results in microbial community composition and structure. It may be necessary to use different platforms when trying to correctly identify dominant pathogens versus measuring alpha-diversity estimates, and it would be important to use the same platform for comparisons to minimize errors in interpretation.

Project description:Microbial diversity in the cystic fibrosis (CF) lung decreases over decades as pathogenic bacteria such as Pseudomonas aeruginosa take over. The dynamics of the CF microbiome and metabolome over shorter time frames, however, remain poorly studied. Here, we analyze paired microbiome and metabolome data from 594 sputum samples collected over 401 days from six adult CF subjects (subject mean = 179 days) through periods of clinical stability and 11 CF pulmonary exacerbations (CFPE). While microbiome profiles were personalized (permutational multivariate analysis of variance [PERMANOVA] r2 = 0.79, P < 0.001), we observed significant intraindividual temporal variation that was highest during clinical stability (linear mixed-effects [LME] model, P = 0.002). This included periods where the microbiomes of different subjects became highly similar (UniFrac distance, <0.05). There was a linear increase in the microbiome alpha-diversity and in the log ratio of anaerobes to pathogens with time (n = 14 days) during the development of a CFPE (LME P = 0.0045 and P = 0.029, respectively). Collectively, comparing samples across disease states showed there was a reduction of these two measures during antibiotic treatment (LME P = 0.0096 and P = 0.014, respectively), but the stability data and CFPE data were not significantly different from each other. Metabolome alpha-diversity was higher during CFPE than during stability (LME P = 0.0085), but no consistent metabolite signatures of CFPE across subjects were identified. Virulence-associated metabolites from P. aeruginosa were temporally dynamic but were not associated with any disease state. One subject died during the collection period, enabling a detailed look at changes in the 194 days prior to death. This subject had over 90% Pseudomonas in the microbiome at the beginning of sampling, and that level gradually increased to over 99% prior to death. This study revealed that the CF microbiome and metabolome of some subjects are dynamic through time. Future work is needed to understand what drives these temporal dynamics and if reduction of anaerobes correlate to clinical response to CFPE therapy.IMPORTANCE Subjects with cystic fibrosis battle polymicrobial lung infections throughout their lifetime. Although antibiotic therapy is a principal treatment for CF lung disease, we have little understanding of how antibiotics affect the CF lung microbiome and metabolome and how much the community changes on daily timescales. By analyzing 594 longitudinal CF sputum samples from six adult subjects, we show that the sputum microbiome and metabolome are dynamic. Significant changes occur during times of stability and also through pulmonary exacerbations (CFPEs). Microbiome alpha-diversity increased as a CFPE developed and then decreased during treatment in a manner corresponding to the reduction in the log ratio of anaerobic bacteria to classic pathogens. Levels of metabolites from the pathogen P. aeruginosa were also highly variable through time and were negatively associated with anaerobes. The microbial dynamics observed in this study may have a significant impact on the outcome of antibiotic therapy for CFPEs and overall subject health.

Project description:Hallmarks of cystic fibrosis (CF) are increased viscosity of mucus and impaired mucociliary clearance within the airways due to mutations of the cystic fibrosis conductance regulator gene. This facilitates the colonization of the lung by microbial pathogens and the concomitant establishment of chronic infections leading to tissue damage, reduced lung function, and decreased life expectancy. Although the interplay between key CF pathogens plays a major role during disease progression, the pathophysiology of the microbial community in CF lungs remains poorly understood. Particular challenges in the analysis of the microbial population present in CF sputum is (I) the inhomogeneous, viscous, and slimy consistence of CF sputum, and (II) the high number of human proteins masking comparably low abundant microbial proteins. To address these challenges, we used 21 CF sputum samples to develop a reliable, reproducible and widely applicable protocol for sputum processing, microbial enrichment, cell disruption, protein extraction and subsequent metaproteomic analyses. As a proof of concept, we selected three sputum samples for detailed metaproteome analyses and complemented and validated metaproteome data by 16S sequencing, metabolomic as well as microscopic analyses. Applying our protocol, the number of bacterial proteins/protein groups increased from 199-425 to 392-868 in enriched samples compared to nonenriched controls. These early microbial metaproteome data suggest that the arginine deiminase pathway and multiple proteases and peptidases identified from various bacterial genera could so far be underappreciated in their contribution to the CF pathophysiology. By providing a standardized and effective protocol for sputum processing and microbial enrichment, our study represents an important basis for future studies investigating the physiology of microbial pathogens in CF in vivo - an important prerequisite for the development of novel antimicrobial therapies to combat chronic recurrent airway infection in CF.

Project description:Stenotrophomonas maltophilia is a Gram-negative opportunistic pathogen that can infect the lungs of people with cystic fibrosis (CF). The highly viscous mucus in the CF lung, expectorated as sputum, serves as the primary nutrient source for microbes colonizing this site and induces virulence-associated phenotypes and gene expression in several CF pathogens. Here, we characterized the transcriptional responses of three S. maltophilia strains during exposure to synthetic CF sputum medium (SCFM2) to gain insight into how this organism interacts with the host in the CF lung. These efforts led to the identification of 881 transcripts differentially expressed by all three strains, many of which reflect the metabolic pathways used by S. maltophilia in sputum, as well as altered stress responses. The latter correlated with increased resistance to peroxide exposure after pregrowth in SCFM2 for two of the strains. We also compared the SCFM2 transcriptomes of two S. maltophilia CF isolates to that of the acute infection strain, S. maltophilia K279a, allowing us to identify CF isolate-specific signatures in differential gene expression. The expression of genes from the accessory genomes was also differentially altered in response to SCFM2. Finally, a number of biofilm-associated genes were differentially induced in SCFM2, particularly in K279a, which corresponded to increased aggregation and biofilm formation in this strain relative to both CF strains. Collectively, this work details the response of S. maltophilia to an environment that mimics important aspects of the CF lung, identifying potential survival strategies and metabolic pathways used by S. maltophilia during infections.IMPORTANCEStenotrophomonas maltophilia is an important infecting bacterium in the airways of people with cystic fibrosis (CF). However, compared to the other CF pathogens, S. maltophilia has been relatively understudied. The significance of our research is to provide insight into the global transcriptomic changes of S. maltophilia in response to a medium that was designed to mimic important aspects of the CF lung. This study elucidates the overall metabolic changes that occur when S. maltophilia encounters the CF lung and generates a road map of candidate genes to test using in vitro and in vivo models of CF.

Project description:Chronic lung infections in cystic fibrosis (CF) could be treated more effectively if the effects of antimicrobials on pathogens in situ were known. Here, we compared changes in the microbial community composition and pathogen growth rates in longitudinal studies of seven pediatric CF patients undergoing intravenous antibiotic administration during pulmonary exacerbations. The microbial community composition was determined by counting rRNA with NanoString DNA analysis, and growth rates were obtained by incubating CF sputum with heavy water and tracing incorporation of deuterium into two branched-chain ("anteiso") fatty acids (a-C15:0 and a-C17:0) using gas chromatography-mass spectrometry (GC/MS). Prior to this study, both lipids were thought to be specific for Staphylococcaceae; hence, their isotopic enrichment was interpreted as a growth proxy for Staphylococcus aureus Our experiments revealed, however, that Prevotella is also a relevant microbial producer of a-C17:0 fatty acid in some CF patients; thus, deuterium incorporation into these lipids is better interpreted as a more general pathogen growth rate proxy. Even accounting for a small nonmicrobial background source detected in some patient samples, a-C15:0 fatty acid still appears to be a relatively robust proxy for CF pathogens, revealing a median generation time of ∼1.5 days, similar to prior observations. Contrary to our expectation, pathogen growth rates remained relatively stable throughout exacerbation treatment. We suggest two straightforward "best practices" for application of stable-isotope probing to CF sputum metabolites: (i) parallel determination of microbial community composition in CF sputum using culture-independent tools and (ii) assessing background levels of the diagnostic metabolite.IMPORTANCE In chronic lung infections, populations of microbial pathogens change and mature in ways that are often unknown, which makes it challenging to identify appropriate treatment options. A promising tool to better understand the physiology of microorganisms in a patient is stable-isotope probing, which we previously developed to estimate the growth rates of S. aureus in cystic fibrosis (CF) sputum. Here, we tracked microbial communities in a cohort of CF patients and found that anteiso fatty acids can also originate from other sources in CF sputum. This awareness led us to develop a new workflow for the application of stable-isotope probing in this context, improving our ability to estimate pathogen generation times in clinical samples.

Dataset Information

Microbial, host and xenobiotic diversity in the cystic fibrosis sputum metabolome.

Publications

Microbial, host and xenobiotic diversity in the cystic fibrosis sputum metabolome.

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