UniFrac: an effective distance metric for microbial community comparison

Lozupone, Catherine; Lladser, Manuel E.; Knights, Dan; Stombaugh, Jesse; Knight, Rob

doi:10.1038/ismej.2010.133

Cited by 2,335 publications

(1,813 citation statements)

References 12 publications

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“…Overall structural changes of rhizosphere and bulk soil bacterial communities were evaluated by principal coordinates analysis (PCoA) in Fast UniFrac (http://bmf.colorado.edu/fastunifrac/) (Lozupone et al, 2011). Representative sequences of OTUs were aligned with MUSCLE (Edgar, 2004), and then used to generate a phylogenetic tree using FastTree (Price et al, 2010).…”

Section: Resultsmentioning

confidence: 99%

Dynamics of the bacterial community structure in the rhizosphere of a maize cultivar

Rui

Mao

et al. 2014

Soil Biology and Biochemistry

325

155

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Section: Resultsmentioning

confidence: 99%

Dynamics of the bacterial community structure in the rhizosphere of a maize cultivar

Rui

Mao

et al. 2014

Soil Biology and Biochemistry

325

155

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“…The alpha diversity was calculated using the Shannon indices, Faith’s phylogenetic diversity [50], OTU richness, and Chao1 index, and compared between groups using nonparametric two sample t -tests, using the default Monte Carlo permutations. The beta diversity was performed using the Weighted Distance Matrix Analysis (UniFrac), calculated by the difference in probability of mass of OTUs of each community for each branch [51] and Principal Coordinates Analysis (PCoA) plots to evaluate the degree of variation among the samples. The ANOSIM test was used to compare the ranged distances of beta diversity between groups, and to calculate the correlation coefficient and p value by permutation.…”

Section: Methodsmentioning

confidence: 99%

Defining the gut microbiota in individuals with periodontal diseases: an exploratory study

Lourenςo

Spencer

Alm

et al. 2018

Journal of Oral Microbiology

122

109

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Background: This exploratory study aimed to characterize the gut microbiome of individuals with different periodontal conditions, and correlate it with periodontal inflammation and tissue destruction.Methods: Stool samples were obtained from individuals presenting periodontal health (PH = 7), gingivitis (G = 14) and chronic periodontitis (CP = 23). The intestinal microbiome composition was determined by Illumina MiSeq sequencing.Results: A lower alpha-diversity in the gut microbiome of individuals with CP was observed, although no significant difference among groups was found (p > 0.01). Firmicutes, Proteobacteria, Verrucomicrobia and Euryarchaeota were increased, whereas Bacteroidetes were decreased in abundance in patients with periodontitis compared to PH. Prevotella (genus), Comamonadaceae (family) and Lactobacillales (order) were detected in higher numbers in G, while Bacteroidales (order) was predominant in PH (p < 0.01). Significant correlations (rho = 0.337–0.468, p < 0.01) were found between OTUs representative of periodontal pathogens and attachment loss. Mogibacteriaceae, Ruminococcaceae and Prevotella were able to discriminate individuals with periodontal diseases from PH (overall accuracy = 84%). Oral taxa were detected in high numbers in all stool samples.Conclusions: Individuals with periodontal diseases present a less diverse gut microbiome consistent with other systemic inflammatory diseases. High numbers of oral taxa related to periodontal destruction and inflammation were detected in the gut microbiome of individuals regardless of periodontal status.

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“…The beta diversity analysis was performed using UniFrac (Lozupone et al 2011) to compare the results of the principal component analysis (PCA) using the community ecology package, R-forge (Vegan 2.0 package was used to generate a PCA figure). Venn diagrams were implemented by Venn Diagram, while Mantel test, Redundancy analysis (RDA), and Heatmap figures were performed in Vegan packages in R.…”

Section: Illumina Miseq Sequencingmentioning

confidence: 99%

Illumina MiSeq sequencing investigation on the contrasting soil bacterial community structures in different iron mining areas

Chen

Xing

et al. 2015

Environ Sci Pollut Res

196

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Mine activities leaked heavy metals into surrounding soil and may affected indigenous microbial communities. In the present study, the diversity and composition of the bacterial community in soil collected from three regions which have different pollution degree, heavy pollution, moderate pollution, and non-pollution, within the catchment of Chao River in Beijing City, were compared using the Illumina MiSeq sequencing technique. Rarefaction results showed that the polluted area had significant higher bacterial alpha diversity than those from unpolluted area. Principal component analysis (PCA) showed that microbial communities in the polluted areas had significant differences compared with the unpolluted area. Moreover, PCA at phylum level and Matastats results demonstrated that communities in locations shared similar phyla diversity, indicating that the bacterial community changes under metal pollution were not reflected on phyla structure. At genus level, the relative abundance of dominant genera changed in sites with degrees of pollution. Genera Bradyrhizobium, Rhodanobacter, Reyranella, and Rhizomicrobium significantly decreased with increasing pollution degree, and their dominance decreased, whereas several genera (e.g., Steroidobacter, Massilia, Arthrobacter, Flavisolibacter, and Roseiflexus) increased and became new dominant genera in the heavily metal-polluted area. The potential resistant bacteria, found within the genera of Thiobacillus, Pseudomonas, Arthrobacter, Microcoleus, Leptolyngbya, and Rhodobacter, are less than 2.0 % in the indigenous bacterial communities, which play an important role in soil ecosystem. This effort to profile the background diversity may set the first stage for better understanding the mechanism underlying the community structure changes under in situ mild heavy metal pollution.

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UniFrac: an effective distance metric for microbial community comparison

Cited by 2,335 publications

References 12 publications

Dynamics of the bacterial community structure in the rhizosphere of a maize cultivar

Dynamics of the bacterial community structure in the rhizosphere of a maize cultivar

Defining the gut microbiota in individuals with periodontal diseases: an exploratory study

Illumina MiSeq sequencing investigation on the contrasting soil bacterial community structures in different iron mining areas

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