Exposing the Three-Dimensional Biogeography and Metabolic States of Pathogens in Cystic Fibrosis Sputum via Hydrogel Embedding, Clearing, and rRNA Labeling

Physiological resistance to antibiotics confounds the treatment of many chronic bacterial infections, motivating researchers to identify novel therapeutic approaches. To do this effectively, an understanding of how microbes survive in vivo is needed. Though much can be inferred from bulk approaches to characterizing complex environments, essential information can be lost if spatial organization is not preserved. Here, we introduce a tissue-clearing technique, termed MiPACT, designed to retain and visualize bacteria with associated proteins and nucleic acids in situ on various spatial scales. By coupling MiPACT with hybridization chain reaction (HCR) to detect rRNA in sputum samples from cystic fibrosis (CF) patients, we demonstrate its ability to survey thousands of bacteria (or bacterial aggregates) over millimeter scales and quantify aggregation of individual species in polymicrobial communities. By analyzing aggregation patterns of four prominent CF pathogens, Staphylococcus aureus, Pseudomonas aeruginosa, Streptococcus sp., and Achromobacter xylosoxidans, we demonstrate a spectrum of aggregation states: from mostly single cells (A. xylosoxidans), to medium-sized clusters (S. aureus), to a mixture of single cells and large aggregates (P. aeruginosa and Streptococcus sp.). Furthermore, MiPACT-HCR revealed an intimate interaction between Streptococcus sp. and specific host cells. Lastly, by comparing standard rRNA fluorescence in situ hybridization signals to those from HCR, we found that different populations of S. aureus and A. xylosoxidans grow slowly overall yet exhibit growth rate heterogeneity over hundreds of microns. These results demonstrate the utility of MiPACT-HCR to directly capture the spatial organization and metabolic activity of bacteria in complex systems, such as human sputum

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 351 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

Exposing the Three-Dimensional Biogeography and Metabolic States of Pathogens in Cystic Fibrosis Sputum via Hydrogel Embedding, Clearing, and rRNA Labeling

Physiological resistance to antibiotics confounds the treatment of many chronic bacterial infections, motivating researchers to identify novel therapeutic approaches. To do this effectively, an understanding of how microbes survive in vivo is needed. Though much can be inferred from bulk approaches to characterizing complex environments, essential information can be lost if spatial organization is not preserved. Here, we introduce a tissue-clearing technique, termed MiPACT, designed to retain and visualize bacteria with associated proteins and nucleic acids in situ on various spatial scales. By coupling MiPACT with hybridization chain reaction (HCR) to detect rRNA in sputum samples from cystic fibrosis (CF) patients, we demonstrate its ability to survey thousands of bacteria (or bacterial aggregates) over millimeter scales and quantify aggregation of individual species in polymicrobial communities. By analyzing aggregation patterns of four prominent CF pathogens, Staphylococcus aureus, Pseudomonas aeruginosa, Streptococcus sp., and Achromobacter xylosoxidans, we demonstrate a spectrum of aggregation states: from mostly single cells (A. xylosoxidans), to medium-sized clusters (S. aureus), to a mixture of single cells and large aggregates (P. aeruginosa and Streptococcus sp.). Furthermore, MiPACT-HCR revealed an intimate interaction between Streptococcus sp. and specific host cells. Lastly, by comparing standard rRNA fluorescence in situ hybridization signals to those from HCR, we found that different populations of S. aureus and A. xylosoxidans grow slowly overall yet exhibit growth rate heterogeneity over hundreds of microns. These results demonstrate the utility of MiPACT-HCR to directly capture the spatial organization and metabolic activity of bacteria in complex systems, such as human sputum

Human FcRn expression and Type I Interferon signaling control Echovirus 11 pathogenesis in mice.

Neonatal echovirus infections are characterized by severe hepatitis and neurological complications that can be fatal. Here, we show that expression of the human homologue of the neonatal Fc receptor (hFcRn), the primary receptor for echoviruses, and ablation of type I interferon (IFN) signaling are key host determinants involved in echovirus pathogenesis. We show that expression of hFcRn alone is insufficient to confer susceptibility to echovirus infections in mice. However, expression of hFcRn in mice deficient in type I interferon (IFN) signaling, hFcRn-IFNAR-/-, recapitulate the echovirus pathogenesis observed in humans. Luminex-based multianalyte profiling from E11 infected hFcRn-IFNAR-/- mice revealed a robust systemic immune response to infection, including the induction of type I IFNs. Furthermore, similar to the severe hepatitis observed in humans, E11 infection in hFcRn-IFNAR-/- mice caused profound liver damage. Our findings define the host factors involved in echovirus pathogenesis and establish in vivo models that recapitulate echovirus disease in humans

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