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

• Main Authors: William H. DePas, Ruth Starwalt-Lee, Lindsey Van Sambeek, Sripriya Ravindra Kumar, Viviana Gradinaru, Dianne K. Newman
• Format: Article
• Language: English
• Published: American Society for Microbiology 2016-09-01
• Series: mBio
• Online Access: http://mbio.asm.org/cgi/content/full/7/5/e00796-16

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.