A primary goal of the Human Microbiome Project (HMP) was to provide a reference collection of 16S rRNA gene sequences collected from sites across the human body that would allow microbiologists to better associate changes in the microbiome with changes in health 1. The HMP Consortium has reported the structure and function of the human microbiome in 300 healthy adults at 18 body sites from a single time point 2,3. Using additional data collected over the course of 12–18 months, we used Dirichlet multinomial mixture models 4 to partition the data into community types for each body site and made three important observations. First, there were strong associations between whether they had been breastfed as an infant, their gender, and their level of education with their community types at several body sites. Second, although the specific taxonomic compositions of the oral and gut microbiomes were different, the community types observed at these sites these sites were predictive of each other. Finally, over the course of the sampling period, the community types from sites within the oral cavity were the least stable, while those in the vagina and gut were the most stable. Our results demonstrate that even with the considerable intra- and inter-personal variation in the human microbiome, this variation can be partitioned into community types that are predictive of each other and are likely the result of life history characteristics. Understanding the diversity of community types and the mechanisms that result in an individual having a particular type or changing types, will allow us to use their community types to assess disease risk and to personalize therapies.
BackgroundPlant endophytic bacteria play an important role benefiting plant growth or being pathogenic to plants or organisms that consume those plants. Multiple species of bacteria have been found co-inhabiting plants, both cultivated and wild, with viruses and fungi. For these reasons, a general understanding of plant endophytic microbial communities and their diversity is necessary. A key issue is how the distributions of these bacteria vary with location, with plant species, with individual plants and with plant growing season.ResultsFive common plant species were collected monthly for four months in the summer of 2010, with replicates from four different sampling sites in the Tallgrass Prairie Preserve in Osage County, Oklahoma, USA. Metagenomic DNA was extracted from ground, washed plant leaf samples, and fragments of the bacterial 16S rDNA genes were amplified for analysis of terminal restriction fragment length polymorphism (T-RFLP). We performed mono-digestion T-RFLP with restriction endonuclease DdeI, to reveal the structures of leaf endophytic bacterial communities, to identify the differences between plant-associated bacterial communities in different plant species or environments, and to explore factors affecting the bacterial distribution. We tested the impacts of three major factors on the leaf endophytic bacterial communities, including host plant species, sampling dates and sampling locations.ConclusionsResults indicated that all of the three factors were significantly related (α = 0.05) to the distribution of leaf endophytic bacteria, with host species being the most important, followed by sampling dates and sampling locations.
The fecal microbiota is a rich source of biomarkers that have previously been shown to be predictive of numerous disease states. Less well studied is the effect of immunomodulatory therapy on the microbiota and its role in response to therapy. This study explored associations between the fecal microbiota and therapeutic response of Crohn’s disease (CD) patients treated with ustekinumab (UST; Stelara) in the phase 2 CERTIFI study. Using stool samples collected over the course of 22 weeks, the composition of these subjects’ fecal bacterial communities was characterized by sequencing the 16S rRNA gene. Subjects in remission could be distinguished from those with active disease 6 weeks after treatment using random forest models trained on subjects’ baseline microbiota and clinical data (area under the curve [AUC] of 0.844, specificity of 0.831, sensitivity of 0.774). The most predictive operational taxonomic units (OTUs) that were ubiquitous among subjects were affiliated with Faecalibacterium and Escherichia or Shigella. The median baseline community diversity in subjects in remission 6 weeks after treatment was 1.7 times higher than that in treated subjects with active disease (P = 0.020). Their baseline community structures were also significantly different (P = 0.017). Two OTUs affiliated with Faecalibacterium (P = 0.003) and Bacteroides (P = 0.022) were significantly more abundant at baseline in subjects who were in remission 6 weeks after treatment than those with active CD. The microbiota diversity of UST-treated clinical responders increased over the 22 weeks of the study, in contrast to nonresponsive subjects (P = 0.012). The observed baseline differences in fecal microbiota and changes due to therapeutic response support the potential for the microbiota as a response biomarker.
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