1. Airway Bacterial Community Structure and Correlation during Health and Disease G.G. Einarsson 1, M.M. Tunney 1, E.R. Klem 2, A.A. Fodor 2, M.C. Wolfgang 2 and J.S. Elborn 1 1 CF & Airways Microbiology Research Group, Queen’s University Belfast, Belfast, United Kingdom 2 University of North Carolina at Chapel Hill, Chapel Hill, United States WS8.5 ePoster can be accessed by a download from the conference computer terminal or by sending email to gisligeir01@gmail.com

2. Aims To determine: What are the marked differences between what we term as “health” associated and “disease” associated microbiota? Is it possible to detect “core” community structure (hubs) in samples from the airways? BackgroundMethodsResultsConclusions

3. 879 samples analysed 2.5 million sequence reads from a normalised dataset 10 body sites of the “upper” airways from “The Human Microbiome Project” as a surrogate for the “healthy” microbiome CF Sputum CF Mouthwash Data based on 454-FLX Titanium runs Methods BackgroundMethodsResultsConclusions

4. Nestedness for community structures evaluated by C-Score statistics. Ranked Spearman’s Correlation Coefficient of  >0.5 used as an indication of a “strong” correlation between two groups. Adjusted P-values of p<0.0001 used as an indicator of statistical significance. Community matrix streamlined for network analysis to contain taxa detected in ≥50% of all samples. Methods BackgroundMethodsResultsConclusions

5. Bacterial Distribution in the Airways 424 different taxa detected. Common bacterial taxa found at most sampling sites (  ). Anterior nares harbour distinct microbiota (  ) with respect to their dominant taxa. CF sputum, but not CF mouthwash, affected by a disproportionally high load of Pseudomonas sp. and Burkholderia sp. (  ) compared to other sites. Pseudomonas sp. found in 6.5% of the healthy cohort. BackgroundMethodsResultsConclusions

6. Network – CF Sputum BackgroundMethodsResultsConclusions

7. Network – CF Mouthwash BackgroundMethodsResultsConclusions

8. Network - All Sampling Sites BackgroundMethodsResultsConclusions

9. Key findings “Core” communities of “strongly” correlating taxa detected in most sampling sites. Number of taxa, including Streptococcus sp., Prevotella sp., Veillonella sp., Actinomyces sp. and Rothia sp., detected in over 90% of samples. Streptococcus sp., the most common taxa detected in most sampling sites, lacks correlation with most of the other major community hubs. A number of anaerobic bacteria commonly associated with the “upper” airways form a major part of the main community hubs in most sites. By excluding principal pathogens associated with CF marked similarities between “core” communities can be detected. BackgroundMethodsResultsConclusions

10. Summary “Core” communities detected at the level of genera regardless of host state. Current microbiome studies lack the resolution to inform us of species specific association with disease, especially for heterogeneous genera such as Streptococcus sp., Prevotella sp. and Veillonella sp. Improvement in culture technologies may improve our understanding. Co-culture with relevant taxa may increase our understanding of the potential role they play in the progression of chronic pulmonary disease. Pseudomonas sp. and Burkholderia sp. form a signature taxa associated with CF sputum, but not CF mouthwash and other sampling sites. BackgroundMethodsResultsConclusions

11. Acknowledgements G.G.E., M.M.T. and J.S.E. were supported through a US-Ireland Project Partnership Grant by the HSC Research and Development, Public Health Agency, Northern Ireland. M.M.T. was supported by a Health and Social Care Research and Development, Public Health Agency, Northern Ireland, funded UK National Institute for Health Research Career Scientist Award. E.R.K., A.A.F. and M.C.W. were supported by a grant from the United States National Institutes of Health (HL092964).