Dynamic association of microbial community types across the human body

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1. This paper answers has three observation.

   • there were strong associations between whether individuals had been breastfed as an infant, their gender, and their level of education with their community types at several body sites.

   • although the specific taxonomic compositions of the oral and gut microbiomes were different, the community types observed at these sites were predictive of each other.

   • over the course of the sampling period, the community types from sites within the oral cavity were the least stable, whereas those in the vagina and gut were the most stable.

2. In order to build/discover community types, they discuss that there are mainly two approaches. first partitioning aroung the medoid(PAM) and Dirichlet Mixture Models (DMM). (Their accronym for DMM is, Dirichlet multinomial mixture, which says the had a multinomial assumption on the distributions); any how, they showed that DMM outperforms PAM and for the rest of analysis they utilize DMM.

3. They identify four main types of community per body size A: highest level of Bacteroides but lack of Prevotella and Ruminococcaceae B, C and D ...

4. They identify demographic and life style characteristics that could correlated with different community types at each body site.

Looking forward, prospective studies that include individuals with varied levels of health and varied backgrounds are needed to achieve a better understanding of the mechanisms of change in community types as well as to provide more details about correlations between community type and life-history factors such as genetics, age, diet, health status and envirornemt (that rural or urban)

Last but not the least, this nature letter is a first example (that I've seen) of a high profile academic paper that uses an IPython Notebook for reproduction of results. For those of us in academia I think this is a sign of where things will be going.