Sloan Qiime/Vamps - Adams/BIMERC
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This document summarizes a study that analyzed microbial communities found indoors. Samples of bioaerosols, settled dust, and surfaces from classrooms, residences, and outdoors were collected and analyzed using qPCR and pyrosequencing. Metadata on the building characteristics, human activities, and locations was also recorded but poses challenges to publish due to privacy concerns. Data analysis involved clustering sequences into OTUs and assigning taxonomy using BLAST. The main roadblocks to publishing the full data are protecting privacy in the metadata and having sufficient time and resources to prepare the data.
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- Benefits of bioinformatics include advances in medicine, agriculture, forensics
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- 1. Processes and sources for indoor microbial communities Rachel Adams, Tom Bruns, John Taylor, MarziaMiletto, Steve Lindow, SeemaBhangar, Bill Nazaroff, Allen Goldstein, Gary Andersen, Ed Ahrens
- 2. Background
- 4. Study design: samples Bioaerosols Settled dust Vacuum-pumped Size-fractionated Household Surfaces surfaces + foreheads Environments Classrooms Residences Outdoors qPCR + Pyrosequencedamplicons- 16S & ITS (&18S)
- 5. #metadata Building & room characteristics Geographic location Function Temperature & relative humidity Construction materials Building floors Ventilation system (& exchange rate) Human behavior Occupancy Activity & its frequency
- 6. Data and metadata sharing • Genetic data – deposition in NCBI’s SRA – Raw data, no link between individual sample and its metadata • Metadata – no formal development for our binders full of metadata – General factors included in papers • IRB requirements – anonymity of human subjects: we do not know identity, gender, age – building location not exact but general area – promised an easy-to-digest explanation to the volunteers and university administration
- 7. Data analysis - founder effects • Mothur for conversion of .sff file to .sff.txt file • QIIME for pyrosequencing pipeline: barcode assignment, denoising, chimera-checking, and OTU clustering to make an OTU table • R and QIIME for community analysis • BLAST on lab server for fungal taxonomy assignment against the UNITE database, analyze output in MEGAN and FHiTINGS
- 8. • What are the main roadblocks at present to publishing your data? Hours in the day
- 9. QIIME/VAMPS workshop • What tools would allow us to better utilize our data? Fungal tree of life – one locus gives species identity & phylogenic relationships for the kingdom fungi Detecting live from dead with PCR-based surveys Long (enough) reads from Illumina to get near- species status