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##Metagenome Prediction with PICRUSt  Because of the vast, historical effort to make the 16S rRNA gene sequence available for hundreds of thousands of organisms, we are typically able to fully characterize the taxonomic diversity of most microbial communities. We One might  assume that these organisms have important each organism present in a community has some  functional roles role  to play, and the most straightforward way to predict what these roles are that role each organism might play  is to use metagenomic sequencing to interrogate theentire  genomes of all members of the community. Unfortunately, in many cases, cases and with current sequencing technology,  the amount of microbial DNA relative to host or other environmental DNA is small enough to make metagenomic sequencing infeasible. This is the case here, where the plant and animal DNA present in the food we eat is typically much more abundant than the microbial DNA. Some exceptions may exist with respect to fermented foods, but we are equally interested the microbiota associated with a wide variety of food types. In a case like this for which metagenomic sequencing is infeasible, another approach suggests itself. There is good evidence that a correlation exists between the evolutionary relatedness of two organisms and the similarity of their genomic content \cite{Martiny_2012}. This means that we can leverage the information obtained by sequencing the genome of one organism to predict the functional potential of another, even if that other genome is represented by a single 16S rRNA sequence. The power of this approach is increased when very many, very closely-related genome sequences are available. This predictive approach has recently been implemented in the software package PICRUSt. PICRUSt uses the phylogenetic placement of a 16S rRNA sequence within a phylogeny of sequenced genomes to “reconstruct” what the genome of the organism containing that 16S rRNA sequence might look like.