Biology subjects

Stanton, B. A.

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

11 recordsLinked to original sources

bioRxiv2025

Role of Myc family proteins in transcriptional regulation of growth and oncogenic transformation in fusion-positive rhabdomyosarcoma

Fusion-positive rhabdomyosarcoma (FP-RMS) is driven by a PAX3::FOXO1 (P3F) or PAX7::FOXO1 fusion gene. After finding that MYCN is required for P3F-induced oncogenic transformation in a human myoblast model of FP-RMS, we further investigated the role of Myc family proteins in FP-RMS. Expression studies revealed that myoblast models and a subset of FP-RMS lines have predominant MYCN or MYC expression whereas other FP-RMS lines have both high MYCN and MYC expression. In myoblast models, MYCN was required for optimal P3F binding to and high-level activation of FGF8, a P3F target that is necessary and sufficient for oncogenic transformation. MYCN or MYC knockdown suppressed transformation in myoblast and FP-RMS lines with dominant MYCN or MYC expression, respectively. In FP-RMS lines with high MYCN and MYC expression, there was partial loss of transformation when one gene was targeted and complete loss when both genes were targeted. Despite the loss of oncogenic activity in lines with knockdown of a dominant Myc family member, FGF8 expression was not decreased. Transcriptomic analyses revealed that P3F target genes were not affected by MYCN or MYC knockdown, and instead a group of Myc-specific targets was down-regulated. Collectively, these results indicate that MYCN or MYC is functionally dominant in myoblast models and FP-RMS lines with dominant expression of one Myc family protein whereas MYCN and MYC are functionally redundant in FP-RMS cell lines with high expression of both. These Myc family proteins contribute to oncogenic properties by facilitating P3F activation of FGF8 and increasing expression of Myc-specific targets.

cancer biology↗

bioRxiv2025

Let-7b-5p loaded Mesenchymal Stromal Cell Extracellular Vesicles reduce Pseudomonas- biofilm formation and inflammation in CF Bronchial Epithelial Cells

Cystic Fibrosis (CF) is a multiorgan disease caused by mutations in the CFTR gene, leading to chronic pulmonary infections and hyperinflammation. Among pathogens colonizing the CF lung, Pseudomonas aeruginosa is predominant, infecting over 50% of adults with CF, and becoming antibiotic-resistant over time. Current therapies for CF, while providing tremendous benefits, fail to eliminate persistent bacterial infections, chronic inflammation, and irreversible lung damage, necessitating novel therapeutic strategies. Our group engineered mesenchymal stromal cell derived extracellular vesicles (MSC EVs) to carry the microRNA let-7b-5p as a dual anti-infective and anti-inflammatory treatment. MSC EVs are low-immunogenicity platforms with innate antimicrobial and immunomodulatory properties, while let-7b-5p reduces biofilm formation and inflammation. In a preclinical CF mice model, we reported that let-7b-5p-loaded MSC EVs reduced P. aeruginosa burden, immune cells, and proinflammatory cytokines in the lungs. We hypothesize four complementary mechanisms for the observed in-vivo effects of the let-7b-5p loaded MSC EVs: antimicrobial activity, anti-inflammatory properties, inhibition of antibiotic-resistant P. aeruginosa biofilm formation in CF airways, and stimulation of anti-inflammatory macrophage behaviors. This study focused on the second and third mechanisms and demonstrates that MSC EVs engineered to contain let-7b-5p effectively blocked the formation of antibiotic-resistant P. aeruginosa biofilms on primary human bronchial epithelial cells (pHBECs) while also reducing P. aeruginosa-induced inflammation. This approach holds promise for improving outcomes for people with CF. Future work will focus on optimizing delivery strategies and expanding the clinical applicability of MSC EVs to target other CF-associated pathogens. NEW AND NOTEWORTHYThis is the first study demonstrating that let-7b-5p loaded Mesenchymal Stromal Cell Extracellular Vesicles (MSC EVs) block antibiotic-resistant P. aeruginosa biofilm formation and reduce inflammation in CF primary human bronchial epithelial cells. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=117 SRC="FIGDIR/small/656674v1_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@3754b3org.highwire.dtl.DTLVardef@99dadcorg.highwire.dtl.DTLVardef@efc4b3org.highwire.dtl.DTLVardef@15aed48_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2025

Extracellular Vesicles Derived from Mesenchymal Stromal Cells Reduce Pseudomonas aeruginosa Lung Infection and Inflammation in Mice

The World Health Organization and the U.S. Centers for Disease Control and Prevention have reported that antibiotic resistant infections with Pseudomonas aeruginosa present a significant health risk world-wide. In the genetic disease Cystic Fibrosis (CF), chronic antibiotic resistant Pseudomonas lung infections and persistent inflammation remain the leading causes of mortality. While highly effective modulator therapy (HEMT) dramatically improves lung function in CF, they fail to eradicate chronic infections or eliminate the associated hyperinflammatory state. Thus, there is an urgent need for innovative therapies that can simultaneously eliminate antibiotic resistant P. aeruginosa lung infection and the attendant hyperinflammatory lung environment. Mesenchymal stromal cell-derived extracellular particles (MSC EPs) represent a promising solution, offering potent anti-inflammatory and antimicrobial properties while being safe and non-toxic. This study demonstrates using a CF mouse model of infection that MSC EPs reduce acute P. aeruginosa lung infection and inflammation. As the first investigation of MSC EPs in CF mice, this research underscores the dual effects of MSC EPs; reducing inflammation and bacterial burden. These findings mark an important advancement in antimicrobial therapy, addressing the unmet need for reducing antibiotic resistant infections and hyperinflammation in CF as well as other diseases with chronic, antibiotic resistant P. aeruginosa infections.

microbiology↗

bioRxiv2024

Gene expression responses of CF airway epithelial cells exposed to elexacaftor/tezacaftor/ivacaftor (ETI) suggest benefits beyond improved CFTR channel function

The combination of elexacaftor/tezacaftor/ivacaftor (ETI, Trikafta) reverses the primary defect in Cystic Fibrosis (CF) by improving CFTR mediated Cl- and HCO3- secretion by airway epithelial cells (AEC), leading to improved lung function and less frequent exacerbations and hospitalizations. However, studies have shown that CFTR modulators like ivacaftor, a component of ETI, has numerous effects on CF cells beyond improved CFTR channel function. Because little is known about the effect of ETI on CF AEC gene expression we exposed primary human AEC to ETI for 48 hours and interrogated the transcriptome by RNA-seq and qPCR. ETI increased defensin gene expression (DEFB1) an observation consistent with reports of decreased bacterial burden in the lungs of people with CF (pwCF). ETI also decreased MMP10 and MMP12 gene expression, suggesting that ETI may reduce proteolytic induced lung destruction in CF. ETI also reduced the expression of the stress response gene heme oxygenase (HMOX1). qPCR analysis confirmed DEFB1, HMOX1, MMP10 and MMP12 gene expression results observed by RNA-seq. Gene pathway analysis revealed that ETI decreased inflammatory signaling, cellular proliferation and MHC Class II antigen presentation. Collectively, these findings suggest that the clinical observation that ETI reduces lung infections in pwCF is related in part to drug induced increases in DEFB1, and that ETI may reduce lung damage by reducing MMP10 and MMP12 gene expression, which is predicted to reduce matrix metalloprotease activity. Moreover, pathway analysis also identified several genes responsible for the ETI induced reduction in inflammation observed in people with CF. New and NoteworthyGene expression responses by CF AEC exposed to ETI suggest that in addition to improving CFTR channel function, ETI is likely to increase resistance to bacterial infection by increasing levels of beta defensin 1 (hBD-1). ETI may also reduce lung damage by suppressing MMP10, and reduce airway inflammation by repressing proinflammatory cytokine secretion by AEC cells.

pharmacology and toxicology↗

bioRxiv2024

E.PathDash, pathway activation analysis of public cystic fibrosis pathogen gene expression data

E.PathDash facilitates re-analysis of gene expression data from pathogens clinically relevant to chronic respiratory diseases, including a total of 48 studies, 548 samples, and 404 unique treatment comparisons. The application enables users to assess broad biological stress responses at the KEGG pathway or Gene Ontology level and also provides data for individual genes. E.PathDash reduces the time required to gain access to data from multiple hours per dataset to seconds. Users can download high quality images such as volcano plots and boxplots, differential gene expression results and raw count data, making it fully interoperable with other tools. Importantly, users can rapidly toggle between experimental comparisons and different studies of the same phenomenon, enabling them to judge the extent to which observed responses are reproducible. As a proof of principle, we invited two cystic fibrosis scientists to use the application to explore scientific questions relevant to their specific research areas. Reassuringly, pathway activation analysis recapitulated results reported in original publications, but it also yielded new insights into pathogen responses to changes in their environments, validating the utility of the application. All software and data are freely accessible and the application is available at scangeo.dartmouth.edu/EPathDash. ImportanceChronic respiratory illnesses impose a high disease burden on our communities and people with respiratory diseases are susceptible to robust bacterial infections from pathogens, including Pseudomonas aeruginosa and Staphylococcus aureus, that contribute to morbidity and mortality. Public gene expression datasets generated from these and other pathogens are abundantly available and an important resource for synthesizing existing pathogenic research, leading to interventions that improve patient outcomes. However, it can take many hours or weeks to render publicly available datasets usable; significant time and skills are needed to clean, standardize, and apply reproducible and robust bioinformatic pipelines to the data. Through collaboration with two microbiologists we have shown that E.PathDash addresses this problem, enabling them to elucidate pathogen responses to a variety of over 400 experimental conditions and generate mechanistic hypotheses for cell-level behavior in response to disease-relevant exposures, all in a fraction of the time.

bioinformatics↗

bioRxiv2023

Rocket-miR, a Translational Launchpad for miRNA-based Antimicrobial Drug Development

Developing software tools that leverage biological datasets to accelerate drug discovery is an important aspect of bioinformatics research. Here we present a novel example: a web application called Rocket-miR that applies an existing bioinformatics algorithm (IntaRNA) to predict cross-species miRNA-mRNA interactions and identify human miRNAs with potential antimicrobial activity against antibiotic resistant bacterial infections. Rocket-miR is the logical extension of our prior finding that human miRNA let-7b-5p impairs the ability of the ubiquitous opportunistic pathogen P. aeruginosa to form biofilms and resist the bactericidal effect of beta lactam antibiotics. Rocket-miRs point and click interface enables researchers without programming expertise to predict additional human-miRNA-pathogen interactions. Identified miRNAs can be developed into novel antimicrobials effective against the 24 clinically relevant pathogens, implicated in diseases of the lung, gut and other organs, that are included in the application. The manuscript incorporates three case studies contributed by microbiologists that study human pathogens to demonstrate the usefulness and usability of the application. Rocket-miR is accessible at the following link: http://scangeo.dartmouth.edu/RocketmiR/. ImportanceAntimicrobial resistant infections contribute to millions of deaths worldwide every year. In particular, the group of bacteria collectively known as ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa and Enterobacter sp.) pathogens are of considerable medical concern due to their virulence and exceptional ability to develop antibiotic resistance. New kinds of antimicrobial therapies are urgently needed to treat patients for whom existing antibiotics are ineffective. The Rocket-miR application predicts targets of human miRNAs in bacterial and fungal pathogens, rapidly identifying candidate miRNA-based antimicrobials. The applications target audience is microbiologists that have the laboratory resources to test the applications predictions. The Rocket-miR application currently supports 24 recognized human pathogens that are relevant to numerous diseases including CF, COPD, urinary tract infections and pneumonia. Furthermore, the application code was designed to be easily extendible to other human pathogens that commonly cause hospital-acquired infections.

bioinformatics↗

bioRxiv2022

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↗

bioRxiv2022

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↗

bioRxiv2021

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↗

bioRxiv2021

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↗

bioRxiv2021

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↗