Journal: PLoS ONE

Article Title: Community Analysis of Chronic Wound Bacteria Using 16S rRNA Gene-Based Pyrosequencing: Impact of Diabetes and Antibiotics on Chronic Wound Microbiota

doi: 10.1371/journal.pone.0006462

Figure Lengend Snippet: The families in red are those that were successfully cultured at least once during the study. The presence/absence plot on the left shows the bacteria present in each of the wound samples. The abundance plot on the right shows the number of 16S rRNA gene pyrosequences (300 maximum) in each of the wound samples. The average copy number per positive sample for each detected bacterial family is shown on the far right. Many rare bacterial families are only visible on the presence/absence plot on the left.

Article Snippet: We characterized wound bacteria from a cohort of chronic wound patients using a 16S rRNA gene-based pyrosequencing approach and assessed the impact of diabetes and antibiotics on chronic wound microbiota.

Techniques: Cell Culture, Bacteria

Journal: Gut Pathogens

Article Title: Diversified pattern of the human colorectal cancer microbiome

doi: 10.1186/1757-4749-5-2

Figure Lengend Snippet: 16S rRNA gene surveys reveal hierarchical partitioning of human tumor tissue-associated microbiomes. Bacterial communities were clustered using Principal Coordinate Analysis ( PCoA ) of the full-tree-based Unifrac matrix. Each point corresponds to a sample colored to indicate tumor or healthy status. Three principle components (PC1, PC2, and PC3) totally explained 43% of the variation. Sample name started with their corresponding studied patient number - S00X (X= 1, 2, 4, 5, 6, 7, 8, and 9), and the following tissue type (C stands for cancer tissue and H for matched adjacent health tissue).

Article Snippet: Using pyrosequencing-based molecular monitoring of bacterial 16S rRNA gene from eight tumor/normal tissue pairs of eight Chinese CRC patients, we analyzed and characterized the basic features of the CRC-associated microbiome.

Techniques:

Journal: Frontiers in Microbiology

Article Title: Past, Present, and Future of Gastrointestinal Microbiota Research in Cats

doi: 10.3389/fmicb.2020.01661

Figure Lengend Snippet: Frequently used methods in feline microbiota studies.

Article Snippet: Sequencing techniques, either based on the construction of 16S rRNA gene clone libraries or recent high-throughput methods such as 454-pyrosequencing or Illumina sequencing, have allowed the identification of previously uncharacterized bacterial groups.

Techniques: Sequencing, Epifluorescence Microscopy, Bacteria, Labeling, Shotgun Sequencing

Journal: Frontiers in Microbiology

Article Title: Past, Present, and Future of Gastrointestinal Microbiota Research in Cats

doi: 10.3389/fmicb.2020.01661

Figure Lengend Snippet: Summary of available research on the intestinal microbiota in cats with diseases.

Article Snippet: Sequencing techniques, either based on the construction of 16S rRNA gene clone libraries or recent high-throughput methods such as 454-pyrosequencing or Illumina sequencing, have allowed the identification of previously uncharacterized bacterial groups.

Techniques: Sequencing, Bacteria, Illumina Sequencing

Journal: Scientific Reports

Article Title: Time-resolved analysis of a denitrifying bacterial community revealed a core microbiome responsible for the anaerobic degradation of quinoline

doi: 10.1038/s41598-017-15122-0

Figure Lengend Snippet: Over all structural changes of microbiota community during quinoline-degrading process based 16S rRNA gene V1-V3 454 pyrosequencing. Comparison of relative abundances of the major phylotypes (relative abundances above 1%) found in the DNA and RNA data. ( a ) At phylum level ( b ) at genera level. ( a ) The left part represents the phylotypes from the DNA, and the right part represents the phylotypes from the RNA-based data. The colors correspond to the major phylogenetic groups of the phylotypes. The different parts of the stacked bars represent the phylotypes identified. ( b ) The different stars above the columns mean significant differences as assessed by Tukey’s test (*P < 0.05, ***P < 0.001). ( c ) Bray-curtis PCoA of the quinoline-degrading microbiota at time H0, H25, H80 and H144 based on pyrosequencing OTU (97% identity) data. The values in parenthesis indicate the percentage of community variation explained by the axes. ( d ) Clustering of microbiota based on mahalanobis distances between different groups calculated with multivariate analysis of variance test, ***P < 0.001.

Article Snippet: Figure 2 Over all structural changes of microbiota community during quinoline-degrading process based 16S rRNA gene V1-V3 454 pyrosequencing.

Techniques: Comparison