Scientific Publications

Two-stage microbial community experimental design.

Publication TypeJournal Article
AuthorsTickle, TL, Segata N., Waldron L., Weingart U., and Huttenhower C.
AbstractMicrobial community samples can be efficiently surveyed in high throughput by sequencing markers such as the 16S ribosomal RNA gene. Often, a collection of samples is then selected for subsequent metagenomic, metabolomic or other follow-up. Two-stage study design has long been used in ecology but has not yet been studied in-depth for high-throughput microbial community investigations. To avoid ad hoc sample selection, we developed and validated several purposive sample selection methods for two-stage studies (that is, biological criteria) targeting differing types of microbial communities. These methods select follow-up samples from large community surveys, with criteria including samples typical of the initially surveyed population, targeting specific microbial clades or rare species, maximizing diversity, representing extreme or deviant communities, or identifying communities distinct or discriminating among environment or host phenotypes. The accuracies of each sampling technique and their influences on the characteristics of the resulting selected microbial community were evaluated using both simulated and experimental data. Specifically, all criteria were able to identify samples whose properties were accurately retained in 318 paired 16S amplicon and whole-community metagenomic (follow-up) samples from the Human Microbiome Project. Some selection criteria resulted in follow-up samples that were strongly non-representative of the original survey population; diversity maximization particularly undersampled community configurations. Only selection of intentionally representative samples minimized differences in the selected sample set from the original microbial survey. An implementation is provided as the microPITA (Microbiomes: Picking Interesting Taxa for Analysis) software for two-stage study design of microbial communities.The ISME Journal advance online publication, 15 August 2013; doi:10.1038/ismej.2013.139.
Year of Publication2013
JournalThe ISME journal
Date Published (YYYY/MM/DD)2013/08/15
ISSN Number1751-7362
DOI10.1038/ismej.2013.139
PubMedhttp://www.ncbi.nlm.nih.gov/pubmed/23949665?dopt=Abstract