Dataset Information

Profiling of Bacterial and Fungal Microbial Communities in Cystic Fibrosis Sputum Using RNA.

ABSTRACT: Here, we report an approach to detect diverse bacterial and fungal taxa in complex samples by direct analysis of community RNA in one step using NanoString probe sets. We designed rRNA-targeting probe sets to detect 42 bacterial and fungal genera or species common in cystic fibrosis (CF) sputum and demonstrated the taxon specificity of these probes, as well as a linear response over more than 3 logs of input RNA. Culture-based analyses correlated qualitatively with relative abundance data on bacterial and fungal taxa obtained by NanoString, and the analysis of serial samples demonstrated the use of this method to simultaneously detect bacteria and fungi and to detect microbes at low abundance without an amplification step. Compared at the genus level, the relative abundances of bacterial taxa detected by analysis of RNA correlated with the relative abundances of the same taxa as measured by sequencing of the V4V5 region of the 16S rRNA gene amplified from community DNA from the same sample. We propose that this method may complement other methods designed to understand dynamic microbial communities, may provide information on bacteria and fungi in the same sample with a single assay, and with further development, may provide quick and easily interpreted diagnostic information on diverse bacteria and fungi at the genus or species level.IMPORTANCE Here we demonstrate the use of an RNA-based analysis of specific taxa of interest, including bacteria and fungi, within microbial communities. This multiplex method may be useful as a means to identify samples with specific combinations of taxa and to gain information on how specific populations vary over time and space or in response to perturbation. A rapid means to measure bacterial and fungal populations may aid in the study of host response to changes in microbial communities.

SUBMITTER: Grahl N

PROVIDER: S-EPMC6083091 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Profiling of Bacterial and Fungal Microbial Communities in Cystic Fibrosis Sputum Using RNA.

Grahl Nora N Dolben Emily L EL Filkins Laura M LM Crocker Alex W AW Willger Sven D SD Morrison Hilary G HG Sogin Mitchell L ML Ashare Alix A Gifford Alex H AH Jacobs Nicholas J NJ Schwartzman Joseph D JD Hogan Deborah A DA

mSphere 20180808 4

Here, we report an approach to detect diverse bacterial and fungal taxa in complex samples by direct analysis of community RNA in one step using NanoString probe sets. We designed rRNA-targeting probe sets to detect 42 bacterial and fungal genera or species common in cystic fibrosis (CF) sputum and demonstrated the taxon specificity of these probes, as well as a linear response over more than 3 logs of input RNA. Culture-based analyses correlated qualitatively with relative abundance data on bac ...[more]

PMID: 30089648

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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:Retained respiratory tract (RT) secretions, infection, and exuberant inflammatory responses are core abnormalities in cystic fibrosis (CF) lung disease. Factors contributing to the destructive CF airway inflammatory processes remain incompletely characterized. The pro-oxidative inflammatory CF RT milieu is known to contain enzymatically and nonenzymatically produced regulatory lipid mediators, a panel of structurally defined oxidized metabolites of polyunsaturated fatty acids known to play a role in pathology related to inflammation. Using an extraction protocol that maximizes recoveries of sputum-spiked deuterated standards, coupled with an LC/MS/MS detection system, this study presents a metabolomic method to assess a broad spectrum of regulatory lipid mediators in freshly obtained sputum from CF patients. A broad range of both proinflammatory and anti-inflammatory lipid mediators was detected, including PGE2, PGD2, TXB2, LTB4, 6-trans-LTB4, 20-OH-LTB4, 20-COOH-LTB4, 20-HETE, 15-HETE, 11-HETE, 12-HETE, 8-HETE, 9-HETE, 5-HETE, EpETrEs, diols, resolvin E1, 15-deoxy-PGJ2, and LXA4. The vast majority of these oxylipins have not been reported previously in CF RT secretions. Whereas direct associations of individual proinflammatory lipid mediators with compromised lung function (FEV-1) were observed, the relationships were not robust. However, multiple statistical analyses revealed that the regulatory lipid mediators profile taken in aggregate proved to have a stronger association with lung function in relatively stable outpatient adult CF patients. Our data reveal a relative paucity of the anti-inflammatory lipid mediator lipoxin A4 in CF sputum. Patients displaying detectable levels of the anti-inflammatory lipid mediator resolvin E1 demonstrated a better lung function compared to those patients with undetectable levels. Our data suggest that comprehensive metabolomic profiling of regulatory lipid mediators in CF sputum should contribute to a better understanding of the molecular mechanisms underlying CF RT inflammatory pathobiology. Further studies are required to determine the extent to which nutritional or pharmacological interventions alter the regulatory lipid mediators profile of the CF RT and the impact of potential modulations of RT regulatory lipid mediators on the clinical progression of CF lung disease.

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:Culture-independent studies of the cystic fibrosis (CF) airway microbiome typically rely on expectorated sputum to assess the microbial makeup of lower airways. These studies have revealed rich bacterial communities. There is often considerable overlap between taxa observed in sputum and those observed in saliva, raising questions about the reliability of expectorated sputum as a sample representing lower airway microbiota. These concerns prompted us to compare pairs of sputum and saliva samples from 10 persons with CF. Using 16S rRNA gene sequencing and droplet digital PCR (ddPCR), we analyzed 37 pairs of sputum and saliva samples, each collected from the same person on the same day. We developed an in silico postsequencing decontamination procedure to remove from sputum the fraction of DNA reads estimated to have been contributed by saliva during expectoration. We demonstrate that while there was often sizeable overlap in community membership between sample types, expectorated sputum typically contains a higher bacterial load and a less diverse community compared to saliva. The differences in diversity between sputum and saliva were more pronounced in advanced disease stage, owing to increased relative abundance of the dominant taxa in sputum. Our effort to model saliva contamination of sputum in silico revealed generally minor effects on community structure after removal of contaminating reads. Despite considerable overlap in taxa observed between expectorated sputum and saliva samples, the impact of saliva contamination on measures of lower airway bacterial community composition in CF using expectorated sputum appears to be minimal.IMPORTANCE Cystic fibrosis is an inherited disease characterized by chronic respiratory tract infection and progressive lung disease. Studies of cystic fibrosis lung microbiology often rely on expectorated sputum to reflect the microbiota present in the lower airways. Passage of sputum through the oropharynx during collection, however, contributes microbes present in saliva to the sample, which could confound interpretation of results. Using culture-independent DNA sequencing-based analyses, we characterized the bacterial communities in pairs of expectorated sputum and saliva samples to generate a model for "decontaminating" sputum in silico Our results demonstrate that salivary contamination of expectorated sputum does not have a large effect on most sputum samples and that observations of high bacterial diversity likely accurately reflect taxa present in cystic fibrosis lower airways.

Dataset Information

Profiling of Bacterial and Fungal Microbial Communities in Cystic Fibrosis Sputum Using RNA.

Publications

Profiling of Bacterial and Fungal Microbial Communities in Cystic Fibrosis Sputum Using RNA.

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