UniFrac: a New Phylogenetic Method for Comparing Microbial Communities

Abstract

We introduce here a new method for computing differences between microbial communities based on phylogenetic information. This method, UniFrac, measures the phylogenetic distance between sets of taxa in a phylogenetic tree as the fraction of the branch length of the tree that leads to descendants from either one environment or the other, but not both. UniFrac can be used to determine whether communities are significantly different, to compare many communities simultaneously using clustering and ordination techniques, and to measure the relative contributions of different factors, such as chemistry and geography, to similarities between samples. We demonstrate the utility of UniFrac by applying it to published 16S rRNA gene libraries from cultured isolates and environmental clones of bacteria in marine sediment, water, and ice. Our results reveal that (i) cultured isolates from ice, water, and sediment resemble each other and environmental clone sequences from sea ice, but not environmental clone sequences from sediment and water; (ii) the geographical location does not correlate strongly with bacterial community differences in ice and sediment from the Arctic and Antarctic; and (iii) bacterial communities differ between terrestrially impacted seawater (whether polar or temperate) and warm oligotrophic seawater, whereas those in individual seawater samples are not more similar to each other than to those in sediment or ice samples. These results illustrate that UniFrac provides a new way of characterizing microbial communities, using the wealth of environmental rRNA sequences, and allows quantitative insight into the factors that underlie the distribution of lineages among environments.

Heart failure is associated with depletion of core intestinal microbiota

“…The OTU sequences were aligned using Muscle20, 21 and from the alignment a Maximum‐Likelihood Phylogenetic Tree was constructed using a generally time‐reversible model in FastTree 22, 23. Using this tree and the OTU abundance table unweighted and weighted UniFrac24 and phylogenetic diversity25 were calculated using the unifrac.unweighted , unifrac.weighted and phylo.diversity function, respectively, in Mothur 26. Further, these sequences were taxonomically annotated using the RDP classifier27 and most recent Training Set provided on the RDP website (v14; https://rdp.cme.msu.edu/).…”

Mosquito vector‐associated microbiota: Metabarcoding bacteria and eukaryotic symbionts across habitat types in Thailand endemic for dengue and other arthropod‐borne diseases

“…To assess beta‐diversity, indicative of the intersample differences between mosquito microbiota, we calculated the normalized weighted UniFrac distances (Lozupone & Knight, 2005) of all sample pairs using Fast UniFrac (Hamady, Lozupone, & Knight, 2009). The input phylogenetic trees for Fast UniFrac were constructed using FastTree (Price, Dehal, & Arkin, 2009) which infers approximately maximum‐likelihood tree with the GTR + CAT model.…”

Evaluating community–environment relationships along fine to broad taxonomic resolutions reveals evolutionary forces underlying community assembly

“…In addition, we applied abundance-weighted UniFrac (unique fraction metric) (Lozupone and Knight, 2005) to quantify the phylogeny-based compositional variation, based on the site-by-otu97 matrix with the pruned GreenGenes phylogenetic tree (containing only taxa found in each data set), using the QIIME platform .…”

“…In this study, we used both types of hierarchical systems to generate composition profiles at fine to broad taxonomic resolutions and evaluated how the strength of community-environment relationships changed along taxonomic ranks. In addition, we calculated the phylogeny-based UniFrac metric (Lozupone and Knight, 2005) as a standard to contrast our multi-level taxonomy-based composition analyses, as this metric has recently gained popularity in microbial community analyses and believed to be more informative than taxonomy-based estimates (Lozupone and Knight, 2005;Swenson, 2014). Moreover, given the potential scale dependency (Levin, 1992;Cavender-Bares et al, 2006Swenson et al, 2006Swenson et al, , 2007 in community-environment relationships, we considered case studies covering sampling sites from either global or local scales (Table 1) and which may provide insight into the scale dependency of microbial community assembly.…”