Yan Wei Lim1, Robert Schmieder2, Matthew Haynes3, Dana Willner4, Mike Furlan5, Merry Youle6, Katelynn Abbott5, Robert Edwards7, Jose Evangelista8, Douglas Conrad8, Forest Rohwer5. 1. Department of Biology, San Diego State University, San Diego, CA, 92182, USA. Electronic address: ylim@rohan.sdsu.edu. 2. Computational Science Research Center, San Diego State University, San Diego, CA, 92182, USA. 3. Department of Biology, San Diego State University, San Diego, CA, 92182, USA; DOE Joint Genome Institute, Walnut Creek, CA 94598, USA. 4. Australian Centre for Ecogenomics, School of Chemistry and Molecular Biosciences, University of Queensland, St. Lucia, QLD, Australia. 5. Department of Biology, San Diego State University, San Diego, CA, 92182, USA. 6. Rainbow Rock, Ocean View, HI 96737, USA. 7. Computational Science Research Center, San Diego State University, San Diego, CA, 92182, USA; Mathematics and Computer Science Division, Argonne National, Laboratory, Argonne, IL 60439, USA. 8. Department of Medicine, University of California San Diego, La Jolla, CA 92037, USA.
Abstract
BACKGROUND: Samples collected from CF patient airways often contain large amounts of host-derived nucleic acids that interfere with recovery and purification of microbial and viral nucleic acids. This study describes metagenomic and metatranscriptomic methods that address these issues. METHODS: Microbial and viral metagenomes, and microbial metatranscriptomes, were successfully prepared from sputum samples from five adult CF patients. RESULTS: Contaminating host DNA was dramatically reduced in the metagenomes. Each CF patient presented a unique microbiome; in some Pseudomonas aeruginosa was replaced by other opportunistic bacteria. Even though the taxonomic composition of the microbiomes is very different, the metabolic potentials encoded by the community are very similar. The viral communities were dominated by phages that infect major CF pathogens. The metatranscriptomes reveal differential expression of encoded metabolic potential with changing health status. CONCLUSIONS: Microbial and viral metagenomics combined with microbial transcriptomics characterize the dynamic polymicrobial communities found in CF airways, revealing both the taxa present and their current metabolic activities. These approaches can facilitate the development of individualized treatment plans and novel therapeutic approaches.
BACKGROUND: Samples collected from CF patient airways often contain large amounts of host-derived nucleic acids that interfere with recovery and purification of microbial and viral nucleic acids. This study describes metagenomic and metatranscriptomic methods that address these issues. METHODS:Microbial and viral metagenomes, and microbial metatranscriptomes, were successfully prepared from sputum samples from five adult CF patients. RESULTS: Contaminating host DNA was dramatically reduced in the metagenomes. Each CF patient presented a unique microbiome; in some Pseudomonas aeruginosa was replaced by other opportunistic bacteria. Even though the taxonomic composition of the microbiomes is very different, the metabolic potentials encoded by the community are very similar. The viral communities were dominated by phages that infect major CF pathogens. The metatranscriptomes reveal differential expression of encoded metabolic potential with changing health status. CONCLUSIONS:Microbial and viral metagenomics combined with microbial transcriptomics characterize the dynamic polymicrobial communities found in CF airways, revealing both the taxa present and their current metabolic activities. These approaches can facilitate the development of individualized treatment plans and novel therapeutic approaches.
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