Journal: Scientific Reports

Article Title: Preliminary insights into the impact of primary radiochemotherapy on the salivary microbiome in head and neck squamous cell carcinoma

doi: 10.1038/s41598-020-73515-0

Figure Lengend Snippet: Microbial diversity and profile in cancer patients (‘diseased’) did not differ significantly from healthy controls, but healthy individuals formed a sub-cluster within the diseased cohort. ( a ) No alterations were observed in alpha diversity between the two groups at the RSV level using ANOVA. ( b ) Microbiome profile of healthy controls clustered within the diseased subjects in a PCoA plot (RSV level). ( c ) LEfSe analysis of taxa associated with healthy subjects and SCC, including the top 100 most abundant genera. ( d – h ) Relative abundance of the genera Bifidobacterium , Pasteurellaceae , Eubacterium , Veillonella, and Fusobacterium in healthy subjects compared to patients.

Article Snippet: One exception is the study by Hu et al. in 2013 , in which they performed a pyrosequencing-based microbiome analysis of plaque samples taken from subjects undergoing head-and-neck radiotherapy.

Techniques:

Journal: Scientific Reports

Article Title: Preliminary insights into the impact of primary radiochemotherapy on the salivary microbiome in head and neck squamous cell carcinoma

doi: 10.1038/s41598-020-73515-0

Figure Lengend Snippet: Radiochemotherapy in cancer patients substantially impacts the microbial profile. ( a ) Shannon Diversity Index did not reveal significant differences in the salivary microbiome between patients before and after therapy at the RSV level using ANOVA. ( b ) Treatment had a significant impact on the microbiome profile (RDA plot, RSV level). ( c ) Bar plot of the microbiome composition before and after therapy, including the 35 most abundant genera. Taxa are displayed from bottom to top. ( d ) Specific taxa that were significantly increased before or after therapy are plotted in a LEfSe including the 35 most abundant genera.

Article Snippet: One exception is the study by Hu et al. in 2013 , in which they performed a pyrosequencing-based microbiome analysis of plaque samples taken from subjects undergoing head-and-neck radiotherapy.

Techniques:

Journal: Scientific Reports

Article Title: Preliminary insights into the impact of primary radiochemotherapy on the salivary microbiome in head and neck squamous cell carcinoma

doi: 10.1038/s41598-020-73515-0

Figure Lengend Snippet: The bacterial and fungal microbiome of healthy subjects and SCC patients is more similar before radiochemotherapy than after. Shannon Diversity of the ( a ) bacterial and ( b ) fungal communities at RSV level (ANOVA). Bar plot of the top 35 most abundant ( c ) bacterial and ( d ) fungal genera. Redundancy analysis of the ( e ) bacterial and ( f ) fungal profiles using ANOVA. Taxa listed in the bar-plot are displayed from bottom to top.

Article Snippet: One exception is the study by Hu et al. in 2013 , in which they performed a pyrosequencing-based microbiome analysis of plaque samples taken from subjects undergoing head-and-neck radiotherapy.

Techniques:

Journal: PLoS ONE

Article Title: Shotgun Pyrosequencing Metagenomic Analyses of Dusts from Swine Confinement and Grain Facilities

doi: 10.1371/journal.pone.0095578

Figure Lengend Snippet: Post-QC shotgun metagenomic reads from swine facility dust, swine feces, grain elevator dust and household dust without pets were aligned against the swine draft (ssc_ref_Sscrofa10) and human genome (hs_ref_GRCh37.p5) sequence. Reads that aligned against the swine draft and/or the human reference genome sequence with an expect value of less than 10 −5 were subsequently aligned against all finished and draft bacterial genome sequence assemblies currently available at the NCBI FTP site on 11/16/2011. Except were indicated, filtered reads were used in all subsequent bioinformatics analyses. * From the NCBI Sequence Read Archive; E S/H = expect values for reads aligned to swine and/or human genomes; E F = expect values for reads with poor alignment with swine or human genomes (filtered reads).

Article Snippet: DNA sequence alignment showed that 19% or 62% of shotgun pyrosequencing metagenomic DNA sequence reads from swine facility or household dusts, respectively, were of swine or human origin, respectively.

Techniques: Sequencing

Journal: PLoS ONE

Article Title: Shotgun Pyrosequencing Metagenomic Analyses of Dusts from Swine Confinement and Grain Facilities

doi: 10.1371/journal.pone.0095578

Figure Lengend Snippet: Relative abundance values are expressed on the ordinate as a fraction of the total number of genera identified in swine dust. The 15 most abundant genera identified using the swine facility dust shotgun metagenomic reads and the M5NR database are shown. Relative abundance values were calculated for these same 15 genera for dust collected from grain elevators and households without pets. See for comparisons at the Phylum, Class, Order, and Family taxonomic levels. Black = Swine dust; Gray = House dust; White = Grain dust.

Article Snippet: DNA sequence alignment showed that 19% or 62% of shotgun pyrosequencing metagenomic DNA sequence reads from swine facility or household dusts, respectively, were of swine or human origin, respectively.

Techniques:

Journal: Genomics, Proteomics & Bioinformatics

Article Title: Stereotypes About Enterotype: the Old and New Ideas

doi: 10.1016/j.gpb.2018.02.004

Figure Lengend Snippet: Enterotypes might be continuous rather than discrete Simulated microbiota samples are indicated using dots, triangles, or squares with different shapes representing different patterns of microbiota composition that these samples initially contain. The simulated samples are grouped into three enterotypes ( Prevotella , Bacteroides , and Ruminococcus ) according to their microbiota composition, plotted in the scenario showing what is expected to see ( A ) and what is actually observed ( B ). The log ratio of the relative abundance of Prevotella to Bacteroides of these simulated samples is plotted against the first principal coordinates in panels A and B, to show the expected scenario ( C ) and the observed scenario ( D ).

Article Snippet: For instance, Arumugam et al. apply enterotype analysis to two large published gut microbiome datasets (85 metagenomes of Danish individuals from a published Illumina dataset and 154 pyrosequencing-based 16S sequences from American individuals) and have detected three enterotypes.

Techniques:

Journal: Genomics, Proteomics & Bioinformatics

Article Title: Stereotypes About Enterotype: the Old and New Ideas

doi: 10.1016/j.gpb.2018.02.004

Figure Lengend Snippet: Enterotype might not always be stable Simulated microbiota samples are indicated using dots, triangles, or squares with different shapes representing different patterns of microbiota composition that these samples initially contain. In the expected scenario, the simulated samples stay in the region of their original enterotypes during a long period of time ranging from 5 to 10 years ( A – C ). In the observed scenario, the microbiota composition of the simulated samples changes a lot over the time, so that most of them do not stay in the region of enterotypes where they originally belong ( D – F ).

Article Snippet: For instance, Arumugam et al. apply enterotype analysis to two large published gut microbiome datasets (85 metagenomes of Danish individuals from a published Illumina dataset and 154 pyrosequencing-based 16S sequences from American individuals) and have detected three enterotypes.

Techniques: