Biology subjects

Taub, L.

Publications and source records attributed to Taub, L..

3 recordsLinked to original sources

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

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↗