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Stanton, B. A.

Publications and source records attributed to Stanton, B. A..

5 recordsLinked to original sources

CF-Seq, An Accessible Web Application for Rapid Re-Analysis of Cystic Fibrosis Pathogen RNA Sequencing Studies

Researchers studying cystic fibrosis (CF) pathogens have produced numerous RNA-seq datasets which are available in the gene expression omnibus (GEO). Although these studies are publicly available, substantial computational expertise and manual effort are required to compare similar studies, visualize gene expression patterns within studies, and use published data to generate new experimental hypotheses. Furthermore, it is difficult to filter available studies by domain-relevant attributes such as strain, treatment, or media, or for a researcher to assess how a specific gene responds to various experimental conditions across studies. To reduce these barriers to data re-analysis, we have developed an R Shiny application called CF-Seq, which works with a compendium of 147 studies and 1,446 individual samples from 13 clinically relevant CF pathogens. The application allows users to filter studies by experimental factors and to view complex differential gene expression analyses at the click of a button. Here we present a series of use cases that demonstrate the application is a useful and efficient tool for new hypothesis generation. (CFSeq: http://scangeo.dartmouth.edu/CFSeq/)

bioinformatics↗

Computationally efficient assembly of a Pseudomonas aeruginosa gene expression compendium

Over the past two decades, thousands of RNA sequencing (RNA-seq) gene expression profiles of Pseudomonas aeruginosa have been made publicly available via the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA). In the work we present here, we draw on over 2,300 P. aeruginosa transcriptomes from hundreds of studies performed by over seventy-five different research groups. We first developed a pipeline, using the Salmon pseudo-aligner and two different P. aeruginosa reference genomes (strains PAO1 and PA14), that transformed raw sequence data into a uniformly processed data in the form of sample-wise normalized counts. In this workflow, P. aeruginosa RNA-seq data are filtered using technically and biologically driven criteria with characteristics tailored to bacterial gene expression and that account for the effects of alignment to different reference genomes. The filtered data are then normalized to enable cross experiment comparisons. Finally, annotations are programmatically collected for those samples with sufficient meta-data and expression-based metrics are used to further enhance strain assignment for each sample. Our processing and quality control methods provide a scalable framework for taking full advantage of the troves of biological information hibernating in the depths of microbial gene expression data. The re-analysis of these data in aggregate is a powerful approach for hypothesis generation and testing, and this approach can be applied to transcriptome datasets in other species. SignificancePseudomonas aeruginosa causes a wide range of infections including chronic infections associated with cystic fibrosis. P. aeruginosa infections are difficult to treat and people with CF-associated P. aeruginosa infections often have poor clinical outcomes. To aid the study of this important pathogen, we developed a methodology that facilitates analyses across experiments, strains, and conditions. We aligned, filtered for quality and normalized thousands of P. aeruginosa RNA-seq gene expression profiles that were publicly available via the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA). The workflow that we present can be efficiently scaled to incorporate new data and applied to the analysis of other species.

microbiology↗

Tobramycin suppresses cystic fibrosis lung inflammation by increasing 5' tRNA-fMet halves secreted by P. aeruginosa

Although inhaled tobramycin increases lung function in people with cystic fibrosis (pwCF), the density of P. aeruginosa in the lungs is only modestly reduced by tobramycin; hence, the mechanism whereby tobramycin improves lung function is unclear. Here, we demonstrate that tobramycin increases the abundance of two 5' tRNA-fMet halves in outer membrane vesicles (OMVs) secreted by P. aeruginosa and that the 5' tRNA-fMet halves reduce IL-8 secretion by CF bronchial epithelial cells (CF-HBECs). In mouse lung, the 5' tRNA-fMet halves attenuate KC secretion and neutrophil recruitment. We also report that the 5' tRNA-fMet halves suppress pro-inflammatory network gene expression by an Argonaut 2 (AGO2)-mediated gene silencing mechanism, thereby reducing IL-8 secretion in CF-HBECs. Moreover, tobramycin reduces the IL-8 concentration and neutrophil content in bronchoalveolar lavage fluid of pwCF. Thus, we conclude that tobramycin improves lung function in part by reducing chronic inflammation and neutrophil-mediated lung damage in pwCF.

immunology↗

Poly (acetyl arginyl) glucosamine attenuates Pseudomonas aeruginosa in a rat lung infection model

Pseudomonas aeruginosa is a common opportunistic pathogen that can cause chronic infections in multiple disease states, including respiratory infections in patients with cystic fibrosis (CF) and non-CF bronchiectasis. Like many opportunists, P. aeruginosa forms multicellular biofilm communities that are widely thought to be an important determinant of bacterial persistence and resistance to antimicrobials and host immune effectors during chronic/recurrent infections. Poly (acetyl, arginyl) glucosamine (PAAG) is a glycopolymer which has antimicrobial activity against a broad range of bacterial species, and also has mucolytic activity which can normalize rheologic properties of cystic fibrosis mucus. In this study, we sought to evaluate the effect of PAAG on P. aeruginosa bacteria within biofilms in vitro, and in the context of experimental pulmonary infection in a rodent infection model. PAAG treatment caused significant bactericidal activity against P. aeruginosa biofilms, and a reduction in the total biomass of preformed P. aeruginosa biofilms on abiotic surfaces, as well as on the surface of immortalized cystic fibrosis human bronchial epithelial cells. Studies of membrane integrity indicated that PAAG causes changes to P. aeruginosa cell morphology and dysregulates membrane polarity. PAAG treatment reduced infection and consequent tissue inflammation in experimental P. aeruginosa rat infections. Based on these findings we conclude that PAAG represents a novel means to combat P. aeruginosa infection, which may warrant further evaluation as a therapeutic.

microbiology↗

Mild CF Lung Disease is Associated with Bacterial Community Stability

Microbial communities in the airways of persons with CF (pwCF) are variable, may include genera that are not typically associated with CF, and their composition can be difficult to correlate with long-term disease outcomes. Leveraging two large datasets characterizing sputum communities of 167 pwCF and associated metadata, we identify five bacterial community types. These communities explain 24% of the variability in lung function in this cohort, far more than single factors like Simpson diversity, which explains only 4%. Subjects with Pseudomonas-dominated communities tended to be older and have reduced percent predicted FEV1 (ppFEV1) than subjects with Streptococcus-dominated communities, consistent with previous findings. To assess the predictive power of these five communities in a longitudinal setting, we used random forests to classify 346 additional samples from 24 subjects observed 8 years on average in a range of clinical states. Subjects with mild disease were more likely to be observed at baseline, that is, not in the context of a pulmonary exacerbation, and community structure in these subjects was more self-similar over time, as measured by Bray-Curtis distance. Interestingly, we found that subjects with mild disease were more likely to remain in a mixed Pseudomonas community, providing some support for the climax-attack model of the CF airway. In contrast, patients with worse outcomes were more likely to show shifts among community types. Our results suggest that bacterial community instability may be a risk factor for lung function decline and indicates the need to better understand factors that drive shifts in community composition.

microbiology↗