P. aeruginosa tRNA-fMet halves secreted in outer membrane vesicles suppress lung inflammation in cystic fibrosis.

Although tobramycin increases lung function in people with cystic fibrosis (pwCF), the density of Pseudomonas aeruginosa (P. aeruginosa) in the lungs is only modestly reduced by tobramycin; hence, the mechanism whereby tobramycin improves lung function is not completely understood. Here, we demonstrate that tobramycin increases 5' tRNA-fMet halves in outer membrane vesicles (OMVs) secreted by laboratory and CF clinical isolates of P. aeruginosa. The 5' tRNA-fMet halves are transferred from OMVs into primary CF human bronchial epithelial cells (CF-HBEC), decreasing OMV-induced IL-8 and IP-10 secretion. In mouse lungs, increased expression of the 5' tRNA-fMet halves in OMVs attenuated KC (murine homolog of IL-8) secretion and neutrophil recruitment. Furthermore, there was less IL-8 and neutrophils in bronchoalveolar lavage fluid isolated from pwCF during the period of exposure to tobramycin versus the period off tobramycin. In conclusion, we have shown in mice and in vitro studies on CF-HBEC that tobramycin reduces inflammation by increasing 5' tRNA-fMet halves in OMVs that are delivered to CF-HBEC and reduce IL-8 and neutrophilic airway inflammation. This effect is predicted to improve lung function in pwCF receiving tobramycin for P. aeruginosa infection.NEW & NOTEWORTHY The experiments in this report identify a novel mechanism, whereby tobramycin reduces inflammation in two models of CF. Tobramycin increased the secretion of tRNA-fMet halves in OMVs secreted by P. aeruginosa, which reduced the OMV-LPS-induced inflammatory response in primary cultures of CF-HBEC and in mouse lung, an effect predicted to reduce lung damage in pwCF.

P. aeruginosa tRNA-fMet halves secreted in outer membrane vesicles suppress lung inflammation in Cystic Fibrosis.

Although tobramycin increases lung function in people with cystic fibrosis (pwCF), the density of Pseudomonas aeruginosa (P. aeruginosa) in the lungs is only modestly reduced by tobramycin; hence, the mechanism whereby tobramycin improves lung function is not completely understood. Here, we demonstrate that tobramycin increases 5' tRNA-fMet halves in outer membrane vesicles (OMVs) secreted by laboratory and CF clinical isolates of P. aeruginosa . The 5' tRNA-fMet halves are transferred from OMVs into primary CF human bronchial epithelial cells (CF-HBEC), decreasing OMV-induced IL-8 and IP-10 secretion. In mouse lung, increased expression of the 5' tRNA-fMet halves in OMVs attenuated KC secretion and neutrophil recruitment. Furthermore, there was less IL-8 and neutrophils in bronchoalveolar lavage fluid isolated from pwCF during the period of exposure to tobramycin versus the period off tobramycin. In conclusion, we have shown in mice and in vitro studies on CF-HBEC that tobramycin reduces inflammation by increasing 5' tRNA-fMet halves in OMVs that are delivered to CF-HBEC and reduce IL-8 and neutrophilic airway inflammation. This effect is predicted to improve lung function in pwCF receiving tobramycin for P. aeruginosa infection. New and noteworthy: The experiments in this report identify a novel mechanim whereby tobramycin reduces inflammation in two models of CF. Tobramycin increased the secretion of tRNA-fMet haves in OMVs secreted by P. aeruginiosa , which reduced the OMV-LPS induced inflammatory response in primary cultures of CF-HBEC and in mouse lung, an effect predicted to reduce lung damage in pwCF. Graphical abstract: The anti-inflammatory effect of tobramycin mediated by 5' tRNA-fMet halves secreted in P. aeruginosa OMVs. (A) P. aeruginosa colonizes the CF lungs and secrets OMVs. OMVs diffuse through the mucus layer overlying bronchial epithelial cells and induce IL-8 secretion, which recruits neutrophils that causes lung damage. ( B ) Tobramycin increases 5' tRNA-fMet halves in OMVs secreted by P. aeruginosa . 5' tRNA-fMet halves are delivered into host cells after OMVs fuse with lipid rafts in CF-HBEC and down-regulate protein expression of MAPK10, IKBKG, and EP300, which suppresses IL-8 secretion and neutrophils in the lungs. A reduction in neutrophils in CF BALF is predicted to improve lung function and decrease lung damage.

Extracellular vesicles secreted by primary human bronchial epithelial cells reduce Pseudomonas aeruginosa burden and inflammation in cystic fibrosis mouse lung.

Cystic fibrosis (CF) results in a reduction in the volume of airway surface liquid, increased accumulation of viscous mucus, persistent antibiotic-resistant lung infections that cause chronic inflammation, and a decline in lung function. More than 50% of adults with CF are chronically colonized by Pseudomonas aeruginosa (P. aeruginosa), the primary reason for morbidity and mortality in people with CF (pwCF). Although highly effective modulator therapy (HEMT) is an important part of disease management in CF, HEMT does not eliminate P. aeruginosa or lung inflammation. Thus, new treatments are required to reduce lung infection and inflammation in CF. In a previous in vitro study, we demonstrated that primary human bronchial epithelial cells (HBECs) secrete extracellular vesicles (EVs) that block the ability of P. aeruginosa to form biofilms by reducing the abundance of several proteins necessary for biofilm formation as well as enhancing the sensitivity of P. aeruginosa to ß-lactam antibiotics. In this study, using a CF mouse model of P. aeruginosa infection, we demonstrate that intratracheal administration of EVs secreted by HBEC reduced P. aeruginosa lung burden and several proinflammatory cytokines including IFN-γ, TNF-α, and MIP-1ß in bronchoalveolar lavage fluid (BALF), even in the absence of antibiotics. Moreover, EVs decreased neutrophils in BALF. Thus, EVs secreted by HBEC reduce the lung burden of P. aeruginosa, decrease inflammation, and reduce neutrophils in a CF mouse model. These results suggest that HBEC via the secretion of EVs may play an important role in the immune response to P. aeruginosa lung infection.NEW & NOTEWORTHY Our findings show that extracellular vesicles secreted by primary human bronchial epithelial cells significantly reduce Pseudomonas aeruginosa burden, inflammation, and weight loss in a cystic fibrosis mouse model of infection.

APPLICATION OF QUANTILE DISCRETIZATION AND BAYESIAN NETWORK ANALYSIS TO PUBLICLY AVAILABLE CYSTIC FIBROSIS DATA SETS.

The availability of multiple publicly-available datasets studying the same phenomenon has the promise of accelerating scientific discovery. Meta-analysis can address issues of reproducibility and often increase power. The promise of meta-analysis is especially germane to rarer diseases like cystic fibrosis (CF), which affects roughly 100,000 people worldwide. A recent search of the National Institute of Health's Gene Expression Omnibus revealed 1.3 million data sets related to cancer compared to about 2,000 related to CF. These studies are highly diverse, involving different tissues, animal models, treatments, and clinical covariates. In our search for gene expression studies of primary human airway epithelial cells, we identified three studies with compatible methodologies and sufficient metadata: GSE139078, Sala Study, and PRJEB9292. Even so, experimental designs were not identical, and we identified significant batch effects that would have complicated functional analysis. Here we present quantile discretization and Bayesian network construction using the Hill climb method as a powerful tool to overcome experimental differences and reveal biologically relevant responses to the CF genotype itself, exposure to virus, bacteria, and drugs used to treat CF. Functional patterns revealed by cluster Profiler included interferon signaling, interferon gamma signaling, interleukins 4 and 13 signaling, interleukin 6 signaling, interleukin 21 signaling, and inactivation of CSF3/G-CSF signaling pathways showing significant alterations. These pathways were consistently associated with higher gene expression in CF epithelial cells compared to non-CF cells, suggesting that targeting these pathways could improve clinical outcomes. The success of quantile discretization and Bayesian network analysis in the context of CF suggests that these approaches might be applicable to other contexts where exactly comparable data sets are hard to find.

Periconceptional and Prenatal Exposure to Metals and Extracellular Vesicle and Particle miRNAs in Human Milk: A Pilot Study.

Human milk is a rich source of microRNAs (miRNAs), which can be transported by extracellular vesicles and particles (EVPs) and are hypothesized to contribute to maternal-offspring communication and child development. Environmental contaminant impacts on EVP miRNAs in human milk are largely unknown. In a pilot study of 54 mother-child pairs from the New Hampshire Birth Cohort Study, we examined relationships between five metals (arsenic, lead, manganese, mercury, and selenium) measured in maternal toenail clippings, reflecting exposures during the periconceptional and prenatal periods, and EVP miRNA levels in human milk. 798 miRNAs were profiled using the NanoString nCounter platform; 200 miRNAs were widely detectable and retained for downstream analyses. Metal-miRNA associations were evaluated using covariate-adjusted robust linear regression models. Arsenic exposure during the periconceptional and prenatal periods was associated with lower total miRNA content in human milk EVPs (PBonferroni < 0.05). When evaluating miRNAs individually, 13 miRNAs were inversely associated with arsenic exposure, two in the periconceptional period and 11 in the prenatal period (PBonferroni < 0.05). Other metal-miRNA associations were not statistically significant after multiple testing correction (PBonferroni ≥ 0.05). Many of the arsenic-associated miRNAs are involved in lactation and have anti-inflammatory properties in the intestine and tumor suppressive functions in breast cells. Our findings raise the possibility that periconceptional and prenatal arsenic exposure may reduce levels of multiple miRNAs in human milk EVPs. However, larger confirmatory studies, which can apply environmental mixture approaches, evaluate potential effect modifiers of these relationships, and examine possible downstream consequences for maternal and child health and breastfeeding outcomes, are needed.

Rocket-miR, a translational launchpad for miRNA-based antimicrobial drug development.

IMPORTANCE: Antimicrobial-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 application's target audience are microbiologists that have the laboratory resources to test the application's predictions. The Rocket-miR application currently supports 24 recognized human pathogens that are relevant to numerous diseases including cystic fibrosis, chronic obstructive pulmonary disease (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.

Bacterial Outer Membrane Vesicles and Immune Modulation of the Host.

This article reviews the role of outer membrane vesicles (OMVs) in mediating the interaction between Gram-negative bacteria and their human hosts. OMVs are produced by a diverse range of Gram-negative bacteria during infection and play a critical role in facilitating host-pathogen interactions without requiring direct cell-to-cell contact. This article describes the mechanisms by which OMVs are formed and subsequently interact with host cells, leading to the transport of microbial protein virulence factors and short interfering RNAs (sRNA) to their host targets, exerting their immunomodulatory effects by targeting specific host signaling pathways. Specifically, this review highlights mechanisms by which OMVs facilitate chronic infection through epigenetic modification of the host immune response. Finally, this review identifies critical knowledge gaps in the field and offers potential avenues for future OMV research, specifically regarding rigor and reproducibility in OMV isolation and characterization methods.

An rRNA fragment in extracellular vesicles secreted by human airway epithelial cells increases the fluoroquinolone sensitivity of P. aeruginosa.

Lung infections caused by antibiotic-resistant strains of Pseudomonas aeruginosa are difficult to eradicate in immunocompromised hosts such as those with cystic fibrosis. We previously demonstrated that extracellular vesicles (EVs) secreted by primary human airway epithelial cells (AECs) deliver microRNA let-7b-5p to P. aeruginosa to suppress biofilm formation and increase sensitivity to beta-lactam antibiotics. In this study, we show that EVs secreted by AECs transfer multiple distinct short RNA fragments to P. aeruginosa that are predicted to target the three subunits of the fluoroquinolone efflux pump MexHI-OpmD, thus increasing antibiotic sensitivity. Exposure of P. aeruginosa to EVs resulted in a significant reduction in the protein levels of MexH (-48%), MexI (-50%), and OpmD (-35%). Moreover, EVs reduced planktonic growth of P. aeruginosa in the presence of the fluoroquinolone antibiotic ciprofloxacin by 20%. A mexGHI-opmD deletion mutant of P. aeruginosa phenocopied this increased sensitivity to ciprofloxacin. Finally, we found that a fragment of an 18S ribosomal RNA (rRNA) external transcribed spacer that was transferred to P. aeruginosa by EVs reduced planktonic growth of P. aeruginosa in the presence of ciprofloxacin, reduced the minimum inhibitory concentration of P. aeruginosa for ciprofloxacin by over 50%, and significantly reduced protein levels of both MexH and OpmD. In conclusion, an rRNA fragment secreted by AECs in EVs that targets the fluoroquinolone efflux pump MexHI-OpmD downregulated these proteins and increased the ciprofloxacin sensitivity of P. aeruginosa. A combination of rRNA fragments and ciprofloxacin packaged in nanoparticles or EVs may benefit patients with ciprofloxacin-resistant P. aeruginosa infections.NEW & NOTEWORTHY Human RNA fragments transported in extracellular vesicles interfere with Pseudomonas aeruginosa drug efflux pumps. A combination of rRNA fragments and ciprofloxacin packaged in nanoparticles or EVs may benefit patients with antibiotic-resistant P. aeruginosa infections.

Computationally Efficient Assembly of Pseudomonas aeruginosa Gene Expression Compendia.

Thousands of Pseudomonas aeruginosa RNA sequencing (RNA-seq) gene expression profiles are publicly available via the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA). In this work, the transcriptional profiles from hundreds of studies performed by over 75 research groups were reanalyzed in aggregate to create a powerful tool for hypothesis generation and testing. Raw sequence data were uniformly processed using the Salmon pseudoaligner, and this read mapping method was validated by comparison to a direct alignment method. We developed filtering criteria to exclude samples with aberrant levels of housekeeping gene expression or an unexpected number of genes with no reported values and normalized the filtered compendia using the ratio-of-medians method. The filtering and normalization steps greatly improved gene expression correlations for genes within the same operon or regulon across the 2,333 samples. Since the RNA-seq data were generated using diverse strains, we report the effects of mapping samples to noncognate reference genomes by separately analyzing all samples mapped to cDNA reference genomes for strains PAO1 and PA14, two divergent strains that were used to generate most of the samples. Finally, we developed an algorithm to incorporate new data as they are deposited into the SRA. Our processing and quality control methods provide a scalable framework for taking advantage of the troves of biological information hibernating in the depths of microbial gene expression data and yield useful tools for P. aeruginosa RNA-seq data to be leveraged for diverse research goals. IMPORTANCE Pseudomonas aeruginosa is a causative agent of a wide range of infections, including chronic infections associated with cystic fibrosis. These P. aeruginosa infections are difficult to treat and often have negative outcomes. To aid in the study of this problematic pathogen, we mapped, 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 resulting compendia facilitate analyses across experiments, strains, and conditions. Ultimately, the workflow that we present could be applied to analyses of other microbial species.

ESKAPE Act Plus: Pathway Activation Analysis for Bacterial Pathogens.

The last 20 years have witnessed an explosion in publicly available gene expression and proteomic data and new tools to help researchers analyze these data. Tools typically include statistical approaches to identify differential expression, integrate prior knowledge, visualize results, and suggest how differential expression relates to changes in phenotype. Here, we provide a simple web-based tool that bridges some of the gaps between the functionality available to those studying eukaryotes and those studying prokaryotes. Specifically, our Shiny web application ESKAPE Act PLUS allows researchers to upload results of high-throughput bacterial gene or protein expression experiments from 13 species, including the six ESKAPE pathogens, to our system and receive (i) an analysis of which KEGG pathways or GO terms are significantly activated or repressed, (ii) visual representations of the magnitude of activation or repression in each category, and (iii) detailed diagrams showing known relationships between genes in each regulated KEGG pathway and fold changes of individual genes. Importantly, our statistical approach does not require users to identify which genes or proteins are differentially expressed. ESKAPE Act PLUS provides high-quality statistics and graphical representations not available using other web-based systems to assess whether prokaryotic biological functions are activated or repressed by experimental conditions. To our knowledge, ESKAPE Act PLUS is the first application that provides pathway activation analysis and pathway-level visualization of gene or protein expression for prokaryotes. IMPORTANCE ESKAPE pathogens are bacteria of concern because they develop antibiotic resistance and can cause life-threatening infections, particularly in more susceptible immunocompromised people. ESKAPE Act PLUS is a user-friendly web application that will advance research on ESKAPE and other pathogens commonly studied by the biomedical community by allowing scientists to infer biological phenotypes from the results from high-throughput bacterial gene or protein expression experiments. ESKAPE Act PLUS currently supports analysis of 23 strains of bacteria from 13 species and can also be used to re-analyze publicly available data to generate new findings and hypotheses for follow-up experiments.

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 128 studies and 1,322 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. (CF-Seq: http://scangeo.dartmouth.edu/CFSeq/ ).

Pseudomonas aeruginosa PAO1 Is Attracted to Bovine Bile in a Novel, Cystic Fibrosis-Derived Bronchial Epithelial Cell Model.

Cystic fibrosis (CF) is a life-threatening, inherited, multi-organ disease that renders patients susceptible throughout their lives to chronic and ultimately deteriorating protracted pulmonary infections. Those infections are dominated in adulthood by the opportunistic pathogen, Pseudomonas aeruginosa (Pa). As with other advancing respiratory illnesses, people with CF (pwCF) also frequently suffer from gastroesophageal reflux disease (GERD), including bile aspiration into the lung. GERD is a major co-morbidity factor in pwCF, with a reported prevalence of 35-81% in affected individuals. Bile is associated with the early acquisition of Pa in CF patients and in vitro studies show that it causes Pa to adopt a chronic lifestyle. We hypothesized that Pa is chemoattracted to bile in the lung environment. To evaluate, we developed a novel chemotaxis experimental system mimicking the lung environment using CF-derived bronchial epithelial (CFBE) cells which allowed for the evaluation of Pa (strain PAO1) chemotaxis in a physiological scenario superior to the standard in vitro systems. We performed qualitative and quantitative chemotaxis tests using this new experimental system, and microcapillary assays to demonstrate that bovine bile is a chemoattractant for Pa and is positively correlated with bile concentration. These results further buttress the hypothesis that bile likely contributes to the colonization and pathogenesis of Pa in the lung, particularly in pwCF.

Poly (acetyl, arginyl) glucosamine disrupts Pseudomonas aeruginosa biofilms and enhances bacterial clearance 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 that has antimicrobial activity against a broad range of bacterial species, and also has mucolytic activity, which can normalize the rheological 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, and may warrant further evaluation as a therapeutic.

Model Systems to Study the Chronic, Polymicrobial Infections in Cystic Fibrosis: Current Approaches and Exploring Future Directions.

A recent workshop titled "Developing Models to Study Polymicrobial Infections," sponsored by the Dartmouth Cystic Fibrosis Center (DartCF), explored the development of new models to study the polymicrobial infections associated with the airways of persons with cystic fibrosis (CF). The workshop gathered 35+ investigators over two virtual sessions. Here, we present the findings of this workshop, summarize some of the challenges involved with developing such models, and suggest three frameworks to tackle this complex problem. The frameworks proposed here, we believe, could be generally useful in developing new model systems for other infectious diseases. Developing and validating new approaches to study the complex polymicrobial communities in the CF airway could open windows to new therapeutics to treat these recalcitrant infections, as well as uncovering organizing principles applicable to chronic polymicrobial infections more generally.

Extracellular Vesicles and Host-Pathogen Interactions: A Review of Inter-Kingdom Signaling by Small Noncoding RNA.

The focus of this brief review is to describe the role of noncoding regulatory RNAs, including short RNAs (sRNA), transfer RNA (tRNA) fragments and microRNAs (miRNA) secreted in extracellular vesicles (EVs), in inter-kingdom communication between bacteria and mammalian (human) host cells. Bacteria secrete vesicles that contain noncoding regulatory RNAs, and recent studies have shown that the bacterial vesicles fuse with and deliver regulatory RNAs to host cells, and similar to eukaryotic miRNAs, regulatory RNAs modulate the host immune response to infection. Recent studies have also demonstrated that mammalian cells secrete EVs containing miRNAs that regulate the gut microbiome, biofilm formation and the bacterial response to antibiotics. Thus, as evidence accumulates it is becoming clear that the secretion of noncoding regulatory RNAs and miRNAs in extracellular vesicles is an important mechanism of bidirectional communication between bacteria and mammalian (human) host cells. However, additional research is necessary to elucidate how noncoding regulatory RNAs and miRNA secreted in extracellular vesicles mediate inter-kingdom communication.

Let-7b-5p in vesicles secreted by human airway cells reduces biofilm formation and increases antibiotic sensitivity of P. aeruginosa.

Pseudomonas aeruginosa is an opportunistic pathogen that forms antibiotic-resistant biofilms, which facilitate chronic infections in immunocompromised hosts. We have previously shown that P. aeruginosa secretes outer-membrane vesicles that deliver a small RNA to human airway epithelial cells (AECs), in which it suppresses the innate immune response. Here, we demonstrate that interdomain communication through small RNA-containing membrane vesicles is bidirectional and that microRNAs (miRNAs) in extracellular vesicles (EVs) secreted by human AECs regulate protein expression, antibiotic sensitivity, and biofilm formation by P. aeruginosa Specifically, human EVs deliver miRNA let-7b-5p to P. aeruginosa, which systematically decreases the abundance of proteins essential for biofilm formation, including PpkA and ClpV1-3, and increases the ability of beta-lactam antibiotics to reduce biofilm formation by targeting the beta-lactamase AmpC. Let-7b-5p is bioinformatically predicted to target not only PpkA, ClpV1, and AmpC in P. aeruginosa but also the corresponding orthologs in Burkholderia cenocepacia, another notorious opportunistic lung pathogen, suggesting that the ability of let-7b-5p to reduce biofilm formation and increase beta-lactam sensitivity is not limited to P. aeruginosa Here, we provide direct evidence for transfer of miRNAs in EVs secreted by eukaryotic cells to a prokaryote, resulting in subsequent phenotypic alterations in the prokaryote as a result of this interdomain communication. Since let-7-family miRNAs are in clinical trials to reduce inflammation and because chronic P. aeruginosa lung infections are associated with a hyperinflammatory state, treatment with let-7b-5p and a beta-lactam antibiotic in nanoparticles or EVs may benefit patients with antibiotic-resistant P. aeruginosa infections.

Mild Cystic Fibrosis 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 data sets characterizing sputum communities of 167 pwCF and associated metadata, we identified 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) compared to 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 understand factors that drive shifts in community composition. IMPORTANCE While much research supports a polymicrobial view of the CF airway, one in which the community is seen as the pathogenic unit, only controlled experiments using model bacterial communities can unravel the mechanistic role played by different communities. This report uses a large data set to identify a small number of communities as a starting point in the development of tractable model systems. We describe a set of five communities that explain 24% of the variability in lung function in our data set, far more than single factors like Simpson diversity, which explained only 4%. In addition, we report that patients with severe disease experienced more shifts among community types, suggesting that bacterial community instability may be a risk factor for lung function decline. Together, these findings provide a proof of principle for selecting bacterial community model systems.

Transfer RNA-Derived Fragments, the Underappreciated Regulatory Small RNAs in Microbial Pathogenesis.

In eukaryotic organisms, transfer RNA (tRNA)-derived fragments have diverse biological functions. Considering the conserved sequences of tRNAs, it is not surprising that endogenous tRNA fragments in bacteria also play important regulatory roles. Recent studies have shown that microbes secrete extracellular vesicles (EVs) containing tRNA fragments and that the EVs deliver tRNA fragments to eukaryotic hosts where they regulate gene expression. Here, we review the literature describing microbial tRNA fragment biogenesis and how the fragments secreted in microbial EVs suppress the host immune response, thereby facilitating chronic infection. Also, we discuss knowledge gaps and research challenges for understanding the pathogenic roles of microbial tRNA fragments in regulating the host response to infection.

Healthy versus inflamed lung environments differentially affect mesenchymal stromal cells.

BACKGROUND: Despite increased interest in mesenchymal stromal cell (MSC)-based cell therapies for acute respiratory distress syndrome (ARDS), clinical investigations have not yet been successful and our understanding of the potential in vivo mechanisms of MSC actions in ARDS remains limited. ARDS is driven by an acute severe innate immune dysregulation, often characterised by inflammation, coagulation and cell injury. How this inflammatory microenvironment influences MSC functions remains to be determined. AIM: The aim of this study was to comparatively assess how the inflammatory environment present in ARDS lungs versus the lung environment present in healthy volunteers alters MSC behaviour. METHODS: Clinical-grade human bone marrow-derived MSCs (hMSCs) were exposed to bronchoalveolar lavage fluid (BALF) samples obtained from ARDS patients or from healthy volunteers. Following exposure, hMSCs and their conditioned media were evaluated for a broad panel of relevant properties, including viability, levels of expression of inflammatory cytokines, gene expression, cell surface human leukocyte antigen expression, and activation of coagulation and complement pathways. RESULTS: Pro-inflammatory, pro-coagulant and major histocompatibility complex (self-recognition) related gene expression was markedly upregulated in hMSCs exposed ex vivo to BALF obtained from healthy volunteers. These changes were less apparent and often opposite in hMSCs exposed to ARDS BALF samples. CONCLUSION: These data provide new insights into how hMSCs behave in healthy versus inflamed lung environments, and strongly suggest that the inflamed environment in ARDS induces hMSC responses that are potentially beneficial for cell survival and actions. This further highlights the need to understand how different disease environments affect hMSC functions.

GAUGE-Annotated Microbial Transcriptomic Data Facilitate Parallel Mining and High-Throughput Reanalysis To Form Data-Driven Hypotheses.

The NCBI Gene Expression Omnibus (GEO) provides tools to query and download transcriptomic data. However, less than 4% of microbial experiments include the sample group annotations required to assess differential gene expression for high-throughput reanalysis, and data deposited after 2014 universally lack these annotations. Our algorithm GAUGE (general annotation using text/data group ensembles) automatically annotates GEO microbial data sets, including microarray and RNA sequencing studies, increasing the percentage of data sets amenable to analysis from 4% to 33%. Eighty-nine percent of GAUGE-annotated studies matched group assignments generated by human curators. To demonstrate how GAUGE annotation can lead to scientific insight, we created GAPE (GAUGE-annotated Pseudomonas aeruginosa and Escherichia coli transcriptomic compendia for reanalysis), a Shiny Web interface to analyze 73 GAUGE-annotated P. aeruginosa studies, three times more than previously available. GAPE analysis revealed that PA3923, a gene of unknown function, was frequently differentially expressed in more than 50% of studies and significantly coregulated with genes involved in biofilm formation. Follow-up wet-bench experiments demonstrate that PA3923 mutants are indeed defective in biofilm formation, consistent with predictions facilitated by GAUGE and GAPE. We anticipate that GAUGE and GAPE, which we have made freely available, will make publicly available microbial transcriptomic data easier to reuse and lead to new data-driven hypotheses.IMPORTANCE GEO archives transcriptomic data from over 5,800 microbial experiments and allows researchers to answer questions not directly addressed in published papers. However, less than 4% of the microbial data sets include the sample group annotations required for high-throughput reanalysis. This limitation blocks a considerable amount of microbial transcriptomic data from being reused easily. Here, we demonstrate that the GAUGE algorithm could make 33% of microbial data accessible to parallel mining and reanalysis. GAUGE annotations increase statistical power and, thereby, make consistent patterns of differential gene expression easier to identify. In addition, we developed GAPE (GAUGE-annotated Pseudomonas aeruginosa and Escherichia coli transcriptomic compendia for reanalysis), a Shiny Web interface that performs parallel analyses on P. aeruginosa and E. coli compendia. Source code for GAUGE and GAPE is freely available and can be repurposed to create compendia for other bacterial species.