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Illumina Inc 16s rrna amplicon sequencing
Prevalence of Mycoplasma lineages in Senegalese rodents, by site, and phylogenetic associations between Mycoplasma lineages and rodent species. (A) Comparison of phylogenetic trees based on the <t>16S</t> <t>rRNA</t> V4 sequences of Mycoplasma and on the mitochondrial cytochrome b gene and the two nuclear gene fragments (IRBP exon 1 and GHR) for rodents (the tree was drawn based on data from reference 92 ). Lines link the Mycoplasma lineages detected in the various rodent species (for a minimum site prevalence exceeding 10%). The numbers next to the branches are bootstrap values (shown only if > 70%). (B) Plots of OTU prevalences, with 95% confidence intervals calculated by Sterne’s exact method ( 93 ) according to rodent species and site (see reference 69 for more information about site codes and their geographic locations). The gray bars on the x axis indicate sites from which the rodent species concerned is absent.
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1) Product Images from "16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife"

Article Title: 16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife

Journal: mSystems

doi: 10.1128/mSystems.00032-16

Prevalence of Mycoplasma lineages in Senegalese rodents, by site, and phylogenetic associations between Mycoplasma lineages and rodent species. (A) Comparison of phylogenetic trees based on the 16S rRNA V4 sequences of Mycoplasma and on the mitochondrial cytochrome b gene and the two nuclear gene fragments (IRBP exon 1 and GHR) for rodents (the tree was drawn based on data from reference 92 ). Lines link the Mycoplasma lineages detected in the various rodent species (for a minimum site prevalence exceeding 10%). The numbers next to the branches are bootstrap values (shown only if > 70%). (B) Plots of OTU prevalences, with 95% confidence intervals calculated by Sterne’s exact method ( 93 ) according to rodent species and site (see reference 69 for more information about site codes and their geographic locations). The gray bars on the x axis indicate sites from which the rodent species concerned is absent.
Figure Legend Snippet: Prevalence of Mycoplasma lineages in Senegalese rodents, by site, and phylogenetic associations between Mycoplasma lineages and rodent species. (A) Comparison of phylogenetic trees based on the 16S rRNA V4 sequences of Mycoplasma and on the mitochondrial cytochrome b gene and the two nuclear gene fragments (IRBP exon 1 and GHR) for rodents (the tree was drawn based on data from reference 92 ). Lines link the Mycoplasma lineages detected in the various rodent species (for a minimum site prevalence exceeding 10%). The numbers next to the branches are bootstrap values (shown only if > 70%). (B) Plots of OTU prevalences, with 95% confidence intervals calculated by Sterne’s exact method ( 93 ) according to rodent species and site (see reference 69 for more information about site codes and their geographic locations). The gray bars on the x axis indicate sites from which the rodent species concerned is absent.

Techniques Used:

Taxonomic assignment of the V4 16S rRNA sequences in wild rodents and in negative controls for extraction and PCR. The histograms show the percentages of sequences for the most abundant bacterial genera in the two MiSeq runs combined. Notice the presence in the controls of several bacterial genera, which was likely due to the inherent contamination of laboratory reagents by bacterial DNA (termed “contaminant genera”). These contaminant genera are also present (to a lesser extent) in the rodent samples. The insertions represent the proportion of sequences from rodent samples which were incorrectly assigned to the controls. See Fig. S1 for separate histograms for the two MiSeq runs.
Figure Legend Snippet: Taxonomic assignment of the V4 16S rRNA sequences in wild rodents and in negative controls for extraction and PCR. The histograms show the percentages of sequences for the most abundant bacterial genera in the two MiSeq runs combined. Notice the presence in the controls of several bacterial genera, which was likely due to the inherent contamination of laboratory reagents by bacterial DNA (termed “contaminant genera”). These contaminant genera are also present (to a lesser extent) in the rodent samples. The insertions represent the proportion of sequences from rodent samples which were incorrectly assigned to the controls. See Fig. S1 for separate histograms for the two MiSeq runs.

Techniques Used: Polymerase Chain Reaction

Workflow of the wet laboratory, bioinformatics, and data filtering procedures in the process of data filtering for 16S rRNA amplicon sequencing. Reagent contaminants were detected by analyzing the sequences in the NC ext and NC PCR controls. Sequence number thresholds for correcting for cross-contamination (T CC ) are OTU and run dependent and were estimated by analyzing the sequences in the NC mus , NC ext , NC PCR , and PC index controls. Sequence number thresholds for correcting for false-index-pairing (T FA ) values are OTU and run dependent and were estimated by analyzing the sequences in the NC index and PC alien controls. A result was considered positive if the number of sequences was > T CC and > T FA . Samples were considered positive if a positive result was obtained for both PCR replicates. *, see Kozich et al. ( 18 ) for details on the sequencing.
Figure Legend Snippet: Workflow of the wet laboratory, bioinformatics, and data filtering procedures in the process of data filtering for 16S rRNA amplicon sequencing. Reagent contaminants were detected by analyzing the sequences in the NC ext and NC PCR controls. Sequence number thresholds for correcting for cross-contamination (T CC ) are OTU and run dependent and were estimated by analyzing the sequences in the NC mus , NC ext , NC PCR , and PC index controls. Sequence number thresholds for correcting for false-index-pairing (T FA ) values are OTU and run dependent and were estimated by analyzing the sequences in the NC index and PC alien controls. A result was considered positive if the number of sequences was > T CC and > T FA . Samples were considered positive if a positive result was obtained for both PCR replicates. *, see Kozich et al. ( 18 ) for details on the sequencing.

Techniques Used: Amplification, Sequencing, Polymerase Chain Reaction

2) Product Images from "16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife"

Article Title: 16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife

Journal: mSystems

doi: 10.1128/mSystems.00032-16

Prevalence of Mycoplasma lineages in Senegalese rodents, by site, and phylogenetic associations between Mycoplasma lineages and rodent species. (A) Comparison of phylogenetic trees based on the 16S rRNA V4 sequences of Mycoplasma and on the mitochondrial cytochrome b gene and the two nuclear gene fragments (IRBP exon 1 and GHR) for rodents (the tree was drawn based on data from reference 92 ). Lines link the Mycoplasma lineages detected in the various rodent species (for a minimum site prevalence exceeding 10%). The numbers next to the branches are bootstrap values (shown only if > 70%). (B) Plots of OTU prevalences, with 95% confidence intervals calculated by Sterne’s exact method ( 93 ) according to rodent species and site (see reference 69 for more information about site codes and their geographic locations). The gray bars on the x axis indicate sites from which the rodent species concerned is absent.
Figure Legend Snippet: Prevalence of Mycoplasma lineages in Senegalese rodents, by site, and phylogenetic associations between Mycoplasma lineages and rodent species. (A) Comparison of phylogenetic trees based on the 16S rRNA V4 sequences of Mycoplasma and on the mitochondrial cytochrome b gene and the two nuclear gene fragments (IRBP exon 1 and GHR) for rodents (the tree was drawn based on data from reference 92 ). Lines link the Mycoplasma lineages detected in the various rodent species (for a minimum site prevalence exceeding 10%). The numbers next to the branches are bootstrap values (shown only if > 70%). (B) Plots of OTU prevalences, with 95% confidence intervals calculated by Sterne’s exact method ( 93 ) according to rodent species and site (see reference 69 for more information about site codes and their geographic locations). The gray bars on the x axis indicate sites from which the rodent species concerned is absent.

Techniques Used:

Taxonomic assignment of the V4 16S rRNA sequences in wild rodents and in negative controls for extraction and PCR. The histograms show the percentages of sequences for the most abundant bacterial genera in the two MiSeq runs combined. Notice the presence in the controls of several bacterial genera, which was likely due to the inherent contamination of laboratory reagents by bacterial DNA (termed “contaminant genera”). These contaminant genera are also present (to a lesser extent) in the rodent samples. The insertions represent the proportion of sequences from rodent samples which were incorrectly assigned to the controls. See Fig. S1 for separate histograms for the two MiSeq runs.
Figure Legend Snippet: Taxonomic assignment of the V4 16S rRNA sequences in wild rodents and in negative controls for extraction and PCR. The histograms show the percentages of sequences for the most abundant bacterial genera in the two MiSeq runs combined. Notice the presence in the controls of several bacterial genera, which was likely due to the inherent contamination of laboratory reagents by bacterial DNA (termed “contaminant genera”). These contaminant genera are also present (to a lesser extent) in the rodent samples. The insertions represent the proportion of sequences from rodent samples which were incorrectly assigned to the controls. See Fig. S1 for separate histograms for the two MiSeq runs.

Techniques Used: Polymerase Chain Reaction

Workflow of the wet laboratory, bioinformatics, and data filtering procedures in the process of data filtering for 16S rRNA amplicon sequencing. Reagent contaminants were detected by analyzing the sequences in the NC ext and NC PCR controls. Sequence number thresholds for correcting for cross-contamination (T CC ) are OTU and run dependent and were estimated by analyzing the sequences in the NC mus , NC ext , NC PCR , and PC index controls. Sequence number thresholds for correcting for false-index-pairing (T FA ) values are OTU and run dependent and were estimated by analyzing the sequences in the NC index and PC alien controls. A result was considered positive if the number of sequences was > T CC and > T FA . Samples were considered positive if a positive result was obtained for both PCR replicates. *, see Kozich et al. ( 18 ) for details on the sequencing.
Figure Legend Snippet: Workflow of the wet laboratory, bioinformatics, and data filtering procedures in the process of data filtering for 16S rRNA amplicon sequencing. Reagent contaminants were detected by analyzing the sequences in the NC ext and NC PCR controls. Sequence number thresholds for correcting for cross-contamination (T CC ) are OTU and run dependent and were estimated by analyzing the sequences in the NC mus , NC ext , NC PCR , and PC index controls. Sequence number thresholds for correcting for false-index-pairing (T FA ) values are OTU and run dependent and were estimated by analyzing the sequences in the NC index and PC alien controls. A result was considered positive if the number of sequences was > T CC and > T FA . Samples were considered positive if a positive result was obtained for both PCR replicates. *, see Kozich et al. ( 18 ) for details on the sequencing.

Techniques Used: Amplification, Sequencing, Polymerase Chain Reaction

3) Product Images from "Microbial community analyses of produced waters from high‐temperature oil reservoirs reveal unexpected similarity between geographically distant oil reservoirs"

Article Title: Microbial community analyses of produced waters from high‐temperature oil reservoirs reveal unexpected similarity between geographically distant oil reservoirs

Journal: Microbial Biotechnology

doi: 10.1111/1751-7915.13281

The Nonmetric multidimentional scaling ( NMDS ) plot of the produced water microbial communities reconstructed from the 16S rRNA sequence data sets acquired experimentally in this study and from databases. Three different metrics were used for beta diversity calculation: (A) Bray‐Curtis distance metric, (B) unweighted Unifrac, (C) weighted Unifrac. The colour shades denote the communities originating from the same geographical regions as indicated in the legend. The stress values for (A), (B) and (C) are 0.213, 0.140 and 0.089 respectively. The microbial community of an agricultural soil sample was plotted as an out‐group (accession number: PRJNA 430535).
Figure Legend Snippet: The Nonmetric multidimentional scaling ( NMDS ) plot of the produced water microbial communities reconstructed from the 16S rRNA sequence data sets acquired experimentally in this study and from databases. Three different metrics were used for beta diversity calculation: (A) Bray‐Curtis distance metric, (B) unweighted Unifrac, (C) weighted Unifrac. The colour shades denote the communities originating from the same geographical regions as indicated in the legend. The stress values for (A), (B) and (C) are 0.213, 0.140 and 0.089 respectively. The microbial community of an agricultural soil sample was plotted as an out‐group (accession number: PRJNA 430535).

Techniques Used: Produced, Sequencing

4) Product Images from "The Microbiome of the Cosmopolitan Diatom Leptocylindrus Reveals Significant Spatial and Temporal Variability"

Article Title: The Microbiome of the Cosmopolitan Diatom Leptocylindrus Reveals Significant Spatial and Temporal Variability

Journal: Frontiers in Microbiology

doi: 10.3389/fmicb.2018.02758

(A,B) A Phytoplankton isolates harbor different bacterial consortium depending on the location and time of sampling from the environment. (A) Bipartite analysis of 7 location/timepoints (rectangles) and 1957 bacterial OTU nodes (circles), yielded 4605 edges (lines), each representing the sum number of 16S rRNA sequence reads for each bacterial OTU at their respective location/timepoint. Nodes representing bacterial OTUs were colored by phyla assignment; Actinobacteria (yellow), Bacteroidetes (light green), Cyanobacteria (teal), Planktomycetes (purple), Verrucomicrobia (violet), and Proteobacteria (blue). Edge colors were set to match the color of their respective location/time point nodes. Bipartite analysis revealed 1,055 “common” bacterial OTUs that were connected via an edge with > 2 location/time point nodes. Whereas, 902 bacterial OTUs were unique to only one location/timepoint, including CH_DEC (188), CLOVE_DEC (131), CLOV_FEB (131), COOG_FEB (15), FOS_FEB (305), MAR_DEC (55), and TF_OCT (77). (B) Stacked bar plots showing the phylogenetic composition and overall abundance of unique OTUs at each location/time point.
Figure Legend Snippet: (A,B) A Phytoplankton isolates harbor different bacterial consortium depending on the location and time of sampling from the environment. (A) Bipartite analysis of 7 location/timepoints (rectangles) and 1957 bacterial OTU nodes (circles), yielded 4605 edges (lines), each representing the sum number of 16S rRNA sequence reads for each bacterial OTU at their respective location/timepoint. Nodes representing bacterial OTUs were colored by phyla assignment; Actinobacteria (yellow), Bacteroidetes (light green), Cyanobacteria (teal), Planktomycetes (purple), Verrucomicrobia (violet), and Proteobacteria (blue). Edge colors were set to match the color of their respective location/time point nodes. Bipartite analysis revealed 1,055 “common” bacterial OTUs that were connected via an edge with > 2 location/time point nodes. Whereas, 902 bacterial OTUs were unique to only one location/timepoint, including CH_DEC (188), CLOVE_DEC (131), CLOV_FEB (131), COOG_FEB (15), FOS_FEB (305), MAR_DEC (55), and TF_OCT (77). (B) Stacked bar plots showing the phylogenetic composition and overall abundance of unique OTUs at each location/time point.

Techniques Used: Sampling, Sequencing

5) Product Images from "DNA extraction protocols cause differences in 16S rRNA amplicon sequencing efficiency but not in community profile composition or structure"

Article Title: DNA extraction protocols cause differences in 16S rRNA amplicon sequencing efficiency but not in community profile composition or structure

Journal: MicrobiologyOpen

doi: 10.1002/mbo3.216

Measures of success for each bacterial extraction protocol (Phenol–chloroform: PC; Qiagen DNeasy Blood Tissue Kit: Qiagen; PowerSoil DNA Isolation Kit: PowerSoil; and PowerSoil DNA Isolation Kit with the addition of a tissue homogenization and digestion step: modified PowerSoil). (A) Mean ± SE copies of bacterial 16S rRNA gene/ μ L. (B) Mean ± SE total DNA concentrations (ng/ μ L). Letters above bars show significant differences as determined by paired t -tests ( P
Figure Legend Snippet: Measures of success for each bacterial extraction protocol (Phenol–chloroform: PC; Qiagen DNeasy Blood Tissue Kit: Qiagen; PowerSoil DNA Isolation Kit: PowerSoil; and PowerSoil DNA Isolation Kit with the addition of a tissue homogenization and digestion step: modified PowerSoil). (A) Mean ± SE copies of bacterial 16S rRNA gene/ μ L. (B) Mean ± SE total DNA concentrations (ng/ μ L). Letters above bars show significant differences as determined by paired t -tests ( P

Techniques Used: DNA Extraction, Homogenization, Modification

Mean ± SE concentration of the bacterial 16S rRNA gene (rRNA/ μ L) by sample life stage and number of individuals for each species (following notation as in Fig. 1 ).
Figure Legend Snippet: Mean ± SE concentration of the bacterial 16S rRNA gene (rRNA/ μ L) by sample life stage and number of individuals for each species (following notation as in Fig. 1 ).

Techniques Used: Concentration Assay

(A) Bacterial 16S rRNA gene concentrations (rRNA/ μ L) recovered from all extracted samples by protocol (following notation as in Fig. 1 ). Colors correspond to ant species. Note the distribution of samples that we sequenced (filled circles) and that we failed to sequence (empty circles). (B) Total DNA concentration (log 10 (ng/ μ L)) versus the concentration of the bacterial 16S rRNA gene (rRNA/ μ L). (C) Correlation between concentration of the bacterial 16S rRNA gene (rRNA/ μ L) and the number of reads (×10 5 ) recovered for samples that we were able to sequence.
Figure Legend Snippet: (A) Bacterial 16S rRNA gene concentrations (rRNA/ μ L) recovered from all extracted samples by protocol (following notation as in Fig. 1 ). Colors correspond to ant species. Note the distribution of samples that we sequenced (filled circles) and that we failed to sequence (empty circles). (B) Total DNA concentration (log 10 (ng/ μ L)) versus the concentration of the bacterial 16S rRNA gene (rRNA/ μ L). (C) Correlation between concentration of the bacterial 16S rRNA gene (rRNA/ μ L) and the number of reads (×10 5 ) recovered for samples that we were able to sequence.

Techniques Used: Sequencing, Concentration Assay

6) Product Images from "Characteristics and Evolution of sill-driven off-axis hydrothermalism in Guaymas Basin – the Ringvent site"

Article Title: Characteristics and Evolution of sill-driven off-axis hydrothermalism in Guaymas Basin – the Ringvent site

Journal: Scientific Reports

doi: 10.1038/s41598-019-50200-5

Microbial community composition. ( A ) Archaeal and ( B ) bacterial community summaries for all lineages with > 2% sequence abundance, based on 16S rRNA gene amplicons recovered from piston-cored sediments. Sample key: Core P03_4, 2.96–3.01 mbsf; Core P04_3, 2.02–2.07 mbsf; Core P06_3 and P06_4 at 2.25–2.3 and 3.75–3.80 mbsf; core P10_2 and P10_4 at 1.24–1.29 and 3.73–3.78 mbsf; Core P11_2 and P11_5 at 1.15–1.20 and 4.63–4.68 mbsf; Core P12_4 at 3.73–3.78 mbsf; Core P13_4, 3.05–3.10 mbsf. Taxonomic groups are generally shown at the class level, sometimes at the order (ANME-1) or family level ( Phycisphaerae , Anaerolineae ). Rarefaction curves for ( C ) archaeal and ( D ) bacterial 16S rRNA amplicons, for the same samples and sequence datasets.
Figure Legend Snippet: Microbial community composition. ( A ) Archaeal and ( B ) bacterial community summaries for all lineages with > 2% sequence abundance, based on 16S rRNA gene amplicons recovered from piston-cored sediments. Sample key: Core P03_4, 2.96–3.01 mbsf; Core P04_3, 2.02–2.07 mbsf; Core P06_3 and P06_4 at 2.25–2.3 and 3.75–3.80 mbsf; core P10_2 and P10_4 at 1.24–1.29 and 3.73–3.78 mbsf; Core P11_2 and P11_5 at 1.15–1.20 and 4.63–4.68 mbsf; Core P12_4 at 3.73–3.78 mbsf; Core P13_4, 3.05–3.10 mbsf. Taxonomic groups are generally shown at the class level, sometimes at the order (ANME-1) or family level ( Phycisphaerae , Anaerolineae ). Rarefaction curves for ( C ) archaeal and ( D ) bacterial 16S rRNA amplicons, for the same samples and sequence datasets.

Techniques Used: Sequencing

7) Product Images from "Comparison of the active and resident community of a coastal microbial mat"

Article Title: Comparison of the active and resident community of a coastal microbial mat

Journal: Scientific Reports

doi: 10.1038/s41598-017-03095-z

Non-metric multidimensional scaling plot (Bray-Curtis dissimilarity analysis) of the complete dataset (at genus level) including the six time points of sampling over a 24-h period, the different 16S rRNA regions analyzed and templates used (DNA versus RNA). Blue represents V3-V4 derived sequences and red represents V1-V3 derived sequences.
Figure Legend Snippet: Non-metric multidimensional scaling plot (Bray-Curtis dissimilarity analysis) of the complete dataset (at genus level) including the six time points of sampling over a 24-h period, the different 16S rRNA regions analyzed and templates used (DNA versus RNA). Blue represents V3-V4 derived sequences and red represents V1-V3 derived sequences.

Techniques Used: Sampling, Derivative Assay

8) Product Images from "16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife"

Article Title: 16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife

Journal: mSystems

doi: 10.1128/mSystems.00032-16

Prevalence of Mycoplasma lineages in Senegalese rodents, by site, and phylogenetic associations between Mycoplasma lineages and rodent species. (A) Comparison of phylogenetic trees based on the 16S rRNA V4 sequences of Mycoplasma and on the mitochondrial cytochrome b gene and the two nuclear gene fragments (IRBP exon 1 and GHR) for rodents (the tree was drawn based on data from reference 92 ). Lines link the Mycoplasma lineages detected in the various rodent species (for a minimum site prevalence exceeding 10%). The numbers next to the branches are bootstrap values (shown only if > 70%). (B) Plots of OTU prevalences, with 95% confidence intervals calculated by Sterne’s exact method ( 93 ) according to rodent species and site (see reference 69 for more information about site codes and their geographic locations). The gray bars on the x axis indicate sites from which the rodent species concerned is absent.
Figure Legend Snippet: Prevalence of Mycoplasma lineages in Senegalese rodents, by site, and phylogenetic associations between Mycoplasma lineages and rodent species. (A) Comparison of phylogenetic trees based on the 16S rRNA V4 sequences of Mycoplasma and on the mitochondrial cytochrome b gene and the two nuclear gene fragments (IRBP exon 1 and GHR) for rodents (the tree was drawn based on data from reference 92 ). Lines link the Mycoplasma lineages detected in the various rodent species (for a minimum site prevalence exceeding 10%). The numbers next to the branches are bootstrap values (shown only if > 70%). (B) Plots of OTU prevalences, with 95% confidence intervals calculated by Sterne’s exact method ( 93 ) according to rodent species and site (see reference 69 for more information about site codes and their geographic locations). The gray bars on the x axis indicate sites from which the rodent species concerned is absent.

Techniques Used:

Taxonomic assignment of the V4 16S rRNA sequences in wild rodents and in negative controls for extraction and PCR. The histograms show the percentages of sequences for the most abundant bacterial genera in the two MiSeq runs combined. Notice the presence in the controls of several bacterial genera, which was likely due to the inherent contamination of laboratory reagents by bacterial DNA (termed “contaminant genera”). These contaminant genera are also present (to a lesser extent) in the rodent samples. The insertions represent the proportion of sequences from rodent samples which were incorrectly assigned to the controls. See Fig. S1 for separate histograms for the two MiSeq runs.
Figure Legend Snippet: Taxonomic assignment of the V4 16S rRNA sequences in wild rodents and in negative controls for extraction and PCR. The histograms show the percentages of sequences for the most abundant bacterial genera in the two MiSeq runs combined. Notice the presence in the controls of several bacterial genera, which was likely due to the inherent contamination of laboratory reagents by bacterial DNA (termed “contaminant genera”). These contaminant genera are also present (to a lesser extent) in the rodent samples. The insertions represent the proportion of sequences from rodent samples which were incorrectly assigned to the controls. See Fig. S1 for separate histograms for the two MiSeq runs.

Techniques Used: Polymerase Chain Reaction

Workflow of the wet laboratory, bioinformatics, and data filtering procedures in the process of data filtering for 16S rRNA amplicon sequencing. Reagent contaminants were detected by analyzing the sequences in the NC ext and NC PCR controls. Sequence number thresholds for correcting for cross-contamination (T CC ) are OTU and run dependent and were estimated by analyzing the sequences in the NC mus , NC ext , NC PCR , and PC index controls. Sequence number thresholds for correcting for false-index-pairing (T FA ) values are OTU and run dependent and were estimated by analyzing the sequences in the NC index and PC alien controls. A result was considered positive if the number of sequences was > T CC and > T FA . Samples were considered positive if a positive result was obtained for both PCR replicates. *, see Kozich et al. ( 18 ) for details on the sequencing.
Figure Legend Snippet: Workflow of the wet laboratory, bioinformatics, and data filtering procedures in the process of data filtering for 16S rRNA amplicon sequencing. Reagent contaminants were detected by analyzing the sequences in the NC ext and NC PCR controls. Sequence number thresholds for correcting for cross-contamination (T CC ) are OTU and run dependent and were estimated by analyzing the sequences in the NC mus , NC ext , NC PCR , and PC index controls. Sequence number thresholds for correcting for false-index-pairing (T FA ) values are OTU and run dependent and were estimated by analyzing the sequences in the NC index and PC alien controls. A result was considered positive if the number of sequences was > T CC and > T FA . Samples were considered positive if a positive result was obtained for both PCR replicates. *, see Kozich et al. ( 18 ) for details on the sequencing.

Techniques Used: Amplification, Sequencing, Polymerase Chain Reaction

9) Product Images from "16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife"

Article Title: 16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife

Journal: mSystems

doi: 10.1128/mSystems.00032-16

Prevalence of Mycoplasma lineages in Senegalese rodents, by site, and phylogenetic associations between Mycoplasma lineages and rodent species. (A) Comparison of phylogenetic trees based on the 16S rRNA V4 sequences of Mycoplasma and on the mitochondrial cytochrome b gene and the two nuclear gene fragments (IRBP exon 1 and GHR) for rodents (the tree was drawn based on data from reference 92 ). Lines link the Mycoplasma lineages detected in the various rodent species (for a minimum site prevalence exceeding 10%). The numbers next to the branches are bootstrap values (shown only if > 70%). (B) Plots of OTU prevalences, with 95% confidence intervals calculated by Sterne’s exact method ( 93 ) according to rodent species and site (see reference 69 for more information about site codes and their geographic locations). The gray bars on the x axis indicate sites from which the rodent species concerned is absent.
Figure Legend Snippet: Prevalence of Mycoplasma lineages in Senegalese rodents, by site, and phylogenetic associations between Mycoplasma lineages and rodent species. (A) Comparison of phylogenetic trees based on the 16S rRNA V4 sequences of Mycoplasma and on the mitochondrial cytochrome b gene and the two nuclear gene fragments (IRBP exon 1 and GHR) for rodents (the tree was drawn based on data from reference 92 ). Lines link the Mycoplasma lineages detected in the various rodent species (for a minimum site prevalence exceeding 10%). The numbers next to the branches are bootstrap values (shown only if > 70%). (B) Plots of OTU prevalences, with 95% confidence intervals calculated by Sterne’s exact method ( 93 ) according to rodent species and site (see reference 69 for more information about site codes and their geographic locations). The gray bars on the x axis indicate sites from which the rodent species concerned is absent.

Techniques Used:

Taxonomic assignment of the V4 16S rRNA sequences in wild rodents and in negative controls for extraction and PCR. The histograms show the percentages of sequences for the most abundant bacterial genera in the two MiSeq runs combined. Notice the presence in the controls of several bacterial genera, which was likely due to the inherent contamination of laboratory reagents by bacterial DNA (termed “contaminant genera”). These contaminant genera are also present (to a lesser extent) in the rodent samples. The insertions represent the proportion of sequences from rodent samples which were incorrectly assigned to the controls. See Fig. S1 for separate histograms for the two MiSeq runs.
Figure Legend Snippet: Taxonomic assignment of the V4 16S rRNA sequences in wild rodents and in negative controls for extraction and PCR. The histograms show the percentages of sequences for the most abundant bacterial genera in the two MiSeq runs combined. Notice the presence in the controls of several bacterial genera, which was likely due to the inherent contamination of laboratory reagents by bacterial DNA (termed “contaminant genera”). These contaminant genera are also present (to a lesser extent) in the rodent samples. The insertions represent the proportion of sequences from rodent samples which were incorrectly assigned to the controls. See Fig. S1 for separate histograms for the two MiSeq runs.

Techniques Used: Polymerase Chain Reaction

Workflow of the wet laboratory, bioinformatics, and data filtering procedures in the process of data filtering for 16S rRNA amplicon sequencing. Reagent contaminants were detected by analyzing the sequences in the NC ext and NC PCR controls. Sequence number thresholds for correcting for cross-contamination (T CC ) are OTU and run dependent and were estimated by analyzing the sequences in the NC mus , NC ext , NC PCR , and PC index controls. Sequence number thresholds for correcting for false-index-pairing (T FA ) values are OTU and run dependent and were estimated by analyzing the sequences in the NC index and PC alien controls. A result was considered positive if the number of sequences was > T CC and > T FA . Samples were considered positive if a positive result was obtained for both PCR replicates. *, see Kozich et al. ( 18 ) for details on the sequencing.
Figure Legend Snippet: Workflow of the wet laboratory, bioinformatics, and data filtering procedures in the process of data filtering for 16S rRNA amplicon sequencing. Reagent contaminants were detected by analyzing the sequences in the NC ext and NC PCR controls. Sequence number thresholds for correcting for cross-contamination (T CC ) are OTU and run dependent and were estimated by analyzing the sequences in the NC mus , NC ext , NC PCR , and PC index controls. Sequence number thresholds for correcting for false-index-pairing (T FA ) values are OTU and run dependent and were estimated by analyzing the sequences in the NC index and PC alien controls. A result was considered positive if the number of sequences was > T CC and > T FA . Samples were considered positive if a positive result was obtained for both PCR replicates. *, see Kozich et al. ( 18 ) for details on the sequencing.

Techniques Used: Amplification, Sequencing, Polymerase Chain Reaction

10) Product Images from "Influence of CO2 Degassing on the Microbial Community in a Dry Mofette Field in Hartoušov, Czech Republic (Western Eger Rift)"

Article Title: Influence of CO2 Degassing on the Microbial Community in a Dry Mofette Field in Hartoušov, Czech Republic (Western Eger Rift)

Journal: Frontiers in Microbiology

doi: 10.3389/fmicb.2018.02787

Lithological profile of the reference and mofette core (A) . The water content (B) , pH (C) , TOC (D) , conductivity (E) , sulfate concentration (F) , bacterial 16s rRNA gene copy number (G) , dsrB gene copy number (H) , mcrA gene copy number (I) , Shannon H index (J) and Shannon EH index (K) of reference (blue dots) and mofette (red squares) core.
Figure Legend Snippet: Lithological profile of the reference and mofette core (A) . The water content (B) , pH (C) , TOC (D) , conductivity (E) , sulfate concentration (F) , bacterial 16s rRNA gene copy number (G) , dsrB gene copy number (H) , mcrA gene copy number (I) , Shannon H index (J) and Shannon EH index (K) of reference (blue dots) and mofette (red squares) core.

Techniques Used: Concentration Assay

11) Product Images from "16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife"

Article Title: 16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife

Journal: mSystems

doi: 10.1128/mSystems.00032-16

Prevalence of Mycoplasma lineages in Senegalese rodents, by site, and phylogenetic associations between Mycoplasma lineages and rodent species. (A) Comparison of phylogenetic trees based on the 16S rRNA V4 sequences of Mycoplasma and on the mitochondrial cytochrome b gene and the two nuclear gene fragments (IRBP exon 1 and GHR) for rodents (the tree was drawn based on data from reference 92 ). Lines link the Mycoplasma lineages detected in the various rodent species (for a minimum site prevalence exceeding 10%). The numbers next to the branches are bootstrap values (shown only if > 70%). (B) Plots of OTU prevalences, with 95% confidence intervals calculated by Sterne’s exact method ( 93 ) according to rodent species and site (see reference 69 for more information about site codes and their geographic locations). The gray bars on the x axis indicate sites from which the rodent species concerned is absent.
Figure Legend Snippet: Prevalence of Mycoplasma lineages in Senegalese rodents, by site, and phylogenetic associations between Mycoplasma lineages and rodent species. (A) Comparison of phylogenetic trees based on the 16S rRNA V4 sequences of Mycoplasma and on the mitochondrial cytochrome b gene and the two nuclear gene fragments (IRBP exon 1 and GHR) for rodents (the tree was drawn based on data from reference 92 ). Lines link the Mycoplasma lineages detected in the various rodent species (for a minimum site prevalence exceeding 10%). The numbers next to the branches are bootstrap values (shown only if > 70%). (B) Plots of OTU prevalences, with 95% confidence intervals calculated by Sterne’s exact method ( 93 ) according to rodent species and site (see reference 69 for more information about site codes and their geographic locations). The gray bars on the x axis indicate sites from which the rodent species concerned is absent.

Techniques Used:

Taxonomic assignment of the V4 16S rRNA sequences in wild rodents and in negative controls for extraction and PCR. The histograms show the percentages of sequences for the most abundant bacterial genera in the two MiSeq runs combined. Notice the presence in the controls of several bacterial genera, which was likely due to the inherent contamination of laboratory reagents by bacterial DNA (termed “contaminant genera”). These contaminant genera are also present (to a lesser extent) in the rodent samples. The insertions represent the proportion of sequences from rodent samples which were incorrectly assigned to the controls. See Fig. S1 for separate histograms for the two MiSeq runs.
Figure Legend Snippet: Taxonomic assignment of the V4 16S rRNA sequences in wild rodents and in negative controls for extraction and PCR. The histograms show the percentages of sequences for the most abundant bacterial genera in the two MiSeq runs combined. Notice the presence in the controls of several bacterial genera, which was likely due to the inherent contamination of laboratory reagents by bacterial DNA (termed “contaminant genera”). These contaminant genera are also present (to a lesser extent) in the rodent samples. The insertions represent the proportion of sequences from rodent samples which were incorrectly assigned to the controls. See Fig. S1 for separate histograms for the two MiSeq runs.

Techniques Used: Polymerase Chain Reaction

Workflow of the wet laboratory, bioinformatics, and data filtering procedures in the process of data filtering for 16S rRNA amplicon sequencing. Reagent contaminants were detected by analyzing the sequences in the NC ext and NC PCR controls. Sequence number thresholds for correcting for cross-contamination (T CC ) are OTU and run dependent and were estimated by analyzing the sequences in the NC mus , NC ext , NC PCR , and PC index controls. Sequence number thresholds for correcting for false-index-pairing (T FA ) values are OTU and run dependent and were estimated by analyzing the sequences in the NC index and PC alien controls. A result was considered positive if the number of sequences was > T CC and > T FA . Samples were considered positive if a positive result was obtained for both PCR replicates. *, see Kozich et al. ( 18 ) for details on the sequencing.
Figure Legend Snippet: Workflow of the wet laboratory, bioinformatics, and data filtering procedures in the process of data filtering for 16S rRNA amplicon sequencing. Reagent contaminants were detected by analyzing the sequences in the NC ext and NC PCR controls. Sequence number thresholds for correcting for cross-contamination (T CC ) are OTU and run dependent and were estimated by analyzing the sequences in the NC mus , NC ext , NC PCR , and PC index controls. Sequence number thresholds for correcting for false-index-pairing (T FA ) values are OTU and run dependent and were estimated by analyzing the sequences in the NC index and PC alien controls. A result was considered positive if the number of sequences was > T CC and > T FA . Samples were considered positive if a positive result was obtained for both PCR replicates. *, see Kozich et al. ( 18 ) for details on the sequencing.

Techniques Used: Amplification, Sequencing, Polymerase Chain Reaction

12) Product Images from "Petroleum hydrocarbon rich oil refinery sludge of North-East India harbours anaerobic, fermentative, sulfate-reducing, syntrophic and methanogenic microbial populations"

Article Title: Petroleum hydrocarbon rich oil refinery sludge of North-East India harbours anaerobic, fermentative, sulfate-reducing, syntrophic and methanogenic microbial populations

Journal: BMC Microbiology

doi: 10.1186/s12866-018-1275-8

Archaeal distribution and phylogenetic tree of archaeal 16S rRNA gene sequences retrieved from the samples. Distribution of archaebacterial taxa in GR1, GR3 and DB2 ( a ) using clone library analysis. Phylogentic tree was constructed using the neighbour joining method incorporating Jukes-Cantor distance corrections ( b ). Sequence of Anabaena circinalis was used as the out-group. One thousand bootstrap analyses were conducted and bootstrap values > 50% were indicated at the nodes. Scale bar = 0.05 change per nucleotide position
Figure Legend Snippet: Archaeal distribution and phylogenetic tree of archaeal 16S rRNA gene sequences retrieved from the samples. Distribution of archaebacterial taxa in GR1, GR3 and DB2 ( a ) using clone library analysis. Phylogentic tree was constructed using the neighbour joining method incorporating Jukes-Cantor distance corrections ( b ). Sequence of Anabaena circinalis was used as the out-group. One thousand bootstrap analyses were conducted and bootstrap values > 50% were indicated at the nodes. Scale bar = 0.05 change per nucleotide position

Techniques Used: Construct, Sequencing

13) Product Images from "Impact of water heater temperature setting and water use frequency on the building plumbing microbiome"

Article Title: Impact of water heater temperature setting and water use frequency on the building plumbing microbiome

Journal: The ISME Journal

doi: 10.1038/ismej.2017.14

( a ) Relative abundance (RA) of Legionella spp. in all samples under different water heater temperature settings ( T in °C); ( b ) relative abundance (RA) of Legionella spp. in influent and control rig samples across time ( t in month, mon). Relative abundance was calculated using Illumina 16S rRNA gene amplicon sequencing. Water use frequency and phase are indicated by color and shape, respectively. All influent samples were assigned a uniform temperature of 20 °C to facilitate comparison.
Figure Legend Snippet: ( a ) Relative abundance (RA) of Legionella spp. in all samples under different water heater temperature settings ( T in °C); ( b ) relative abundance (RA) of Legionella spp. in influent and control rig samples across time ( t in month, mon). Relative abundance was calculated using Illumina 16S rRNA gene amplicon sequencing. Water use frequency and phase are indicated by color and shape, respectively. All influent samples were assigned a uniform temperature of 20 °C to facilitate comparison.

Techniques Used: Amplification, Sequencing

14) Product Images from "Petroleum hydrocarbon rich oil refinery sludge of North-East India harbours anaerobic, fermentative, sulfate-reducing, syntrophic and methanogenic microbial populations"

Article Title: Petroleum hydrocarbon rich oil refinery sludge of North-East India harbours anaerobic, fermentative, sulfate-reducing, syntrophic and methanogenic microbial populations

Journal: BMC Microbiology

doi: 10.1186/s12866-018-1275-8

Archaeal distribution and phylogenetic tree of archaeal 16S rRNA gene sequences retrieved from the samples. Distribution of archaebacterial taxa in GR1, GR3 and DB2 ( a ) using clone library analysis. Phylogentic tree was constructed using the neighbour joining method incorporating Jukes-Cantor distance corrections ( b ). Sequence of Anabaena circinalis was used as the out-group. One thousand bootstrap analyses were conducted and bootstrap values > 50% were indicated at the nodes. Scale bar = 0.05 change per nucleotide position
Figure Legend Snippet: Archaeal distribution and phylogenetic tree of archaeal 16S rRNA gene sequences retrieved from the samples. Distribution of archaebacterial taxa in GR1, GR3 and DB2 ( a ) using clone library analysis. Phylogentic tree was constructed using the neighbour joining method incorporating Jukes-Cantor distance corrections ( b ). Sequence of Anabaena circinalis was used as the out-group. One thousand bootstrap analyses were conducted and bootstrap values > 50% were indicated at the nodes. Scale bar = 0.05 change per nucleotide position

Techniques Used: Construct, Sequencing

15) Product Images from "Reproducible, high-yielding, biological caproate production from food waste using a single-phase anaerobic reactor system"

Article Title: Reproducible, high-yielding, biological caproate production from food waste using a single-phase anaerobic reactor system

Journal: Biotechnology for Biofuels

doi: 10.1186/s13068-018-1101-4

Taxonomic classification of the 16S rRNA sequences showing microbial groups potentially involved in caproate production. Sequences were retrieved from Illumina MiSeq sequencing of cDNA samples generated from: a control, b ethanol, c hydrogen (H 2 ) and d hydrogen and ethanol (H 2 /ethanol)-supplemented vials during batch experiments using leach-bed reactor leachate
Figure Legend Snippet: Taxonomic classification of the 16S rRNA sequences showing microbial groups potentially involved in caproate production. Sequences were retrieved from Illumina MiSeq sequencing of cDNA samples generated from: a control, b ethanol, c hydrogen (H 2 ) and d hydrogen and ethanol (H 2 /ethanol)-supplemented vials during batch experiments using leach-bed reactor leachate

Techniques Used: Sequencing, Generated

16) Product Images from "Intestinal microbiota development and gestational age in preterm neonates"

Article Title: Intestinal microbiota development and gestational age in preterm neonates

Journal: Scientific Reports

doi: 10.1038/s41598-018-20827-x

Microbiota composition in the fecal samples of preterm infants. Principal coordinates analyses (PCoA, Bray-Curtis dissimilarities) ( a – c ). The axes represent PCoA component scores, showing the two most important gradients differentiating the microbial communities. Each circle represents a microbial community, colored in panel ( a ) by the dominant organism in the community ( > 50% of all reads). Background color corresponds to: ( b ) postnatal age of the infant at the time of fecal sample collection; ( c ) postmenstrual age of the infant at sample collection. Blue background indicates low values, green intermediate, and orange high values. Average relative abundances of the dominant families in extremely premature (EP), moderately or very premature (MVP), compared to term infants from a Dutch cohort, at different postmenstrual ages (weeks) 25 ( d ). Average total DNA concentration by postmenstrual age, divided to bacterial taxa based on their relative abundances in the 16S rRNA data ( e ).
Figure Legend Snippet: Microbiota composition in the fecal samples of preterm infants. Principal coordinates analyses (PCoA, Bray-Curtis dissimilarities) ( a – c ). The axes represent PCoA component scores, showing the two most important gradients differentiating the microbial communities. Each circle represents a microbial community, colored in panel ( a ) by the dominant organism in the community ( > 50% of all reads). Background color corresponds to: ( b ) postnatal age of the infant at the time of fecal sample collection; ( c ) postmenstrual age of the infant at sample collection. Blue background indicates low values, green intermediate, and orange high values. Average relative abundances of the dominant families in extremely premature (EP), moderately or very premature (MVP), compared to term infants from a Dutch cohort, at different postmenstrual ages (weeks) 25 ( d ). Average total DNA concentration by postmenstrual age, divided to bacterial taxa based on their relative abundances in the 16S rRNA data ( e ).

Techniques Used: Concentration Assay

17) Product Images from "16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife"

Article Title: 16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife

Journal: mSystems

doi: 10.1128/mSystems.00032-16

Prevalence of Mycoplasma lineages in Senegalese rodents, by site, and phylogenetic associations between Mycoplasma lineages and rodent species. (A) Comparison of phylogenetic trees based on the 16S rRNA V4 sequences of Mycoplasma and on the mitochondrial cytochrome b gene and the two nuclear gene fragments (IRBP exon 1 and GHR) for rodents (the tree was drawn based on data from reference 92 ). Lines link the Mycoplasma lineages detected in the various rodent species (for a minimum site prevalence exceeding 10%). The numbers next to the branches are bootstrap values (shown only if > 70%). (B) Plots of OTU prevalences, with 95% confidence intervals calculated by Sterne’s exact method ( 93 ) according to rodent species and site (see reference 69 for more information about site codes and their geographic locations). The gray bars on the x axis indicate sites from which the rodent species concerned is absent.
Figure Legend Snippet: Prevalence of Mycoplasma lineages in Senegalese rodents, by site, and phylogenetic associations between Mycoplasma lineages and rodent species. (A) Comparison of phylogenetic trees based on the 16S rRNA V4 sequences of Mycoplasma and on the mitochondrial cytochrome b gene and the two nuclear gene fragments (IRBP exon 1 and GHR) for rodents (the tree was drawn based on data from reference 92 ). Lines link the Mycoplasma lineages detected in the various rodent species (for a minimum site prevalence exceeding 10%). The numbers next to the branches are bootstrap values (shown only if > 70%). (B) Plots of OTU prevalences, with 95% confidence intervals calculated by Sterne’s exact method ( 93 ) according to rodent species and site (see reference 69 for more information about site codes and their geographic locations). The gray bars on the x axis indicate sites from which the rodent species concerned is absent.

Techniques Used:

Taxonomic assignment of the V4 16S rRNA sequences in wild rodents and in negative controls for extraction and PCR. The histograms show the percentages of sequences for the most abundant bacterial genera in the two MiSeq runs combined. Notice the presence in the controls of several bacterial genera, which was likely due to the inherent contamination of laboratory reagents by bacterial DNA (termed “contaminant genera”). These contaminant genera are also present (to a lesser extent) in the rodent samples. The insertions represent the proportion of sequences from rodent samples which were incorrectly assigned to the controls. See Fig. S1 for separate histograms for the two MiSeq runs.
Figure Legend Snippet: Taxonomic assignment of the V4 16S rRNA sequences in wild rodents and in negative controls for extraction and PCR. The histograms show the percentages of sequences for the most abundant bacterial genera in the two MiSeq runs combined. Notice the presence in the controls of several bacterial genera, which was likely due to the inherent contamination of laboratory reagents by bacterial DNA (termed “contaminant genera”). These contaminant genera are also present (to a lesser extent) in the rodent samples. The insertions represent the proportion of sequences from rodent samples which were incorrectly assigned to the controls. See Fig. S1 for separate histograms for the two MiSeq runs.

Techniques Used: Polymerase Chain Reaction

Workflow of the wet laboratory, bioinformatics, and data filtering procedures in the process of data filtering for 16S rRNA amplicon sequencing. Reagent contaminants were detected by analyzing the sequences in the NC ext and NC PCR controls. Sequence number thresholds for correcting for cross-contamination (T CC ) are OTU and run dependent and were estimated by analyzing the sequences in the NC mus , NC ext , NC PCR , and PC index controls. Sequence number thresholds for correcting for false-index-pairing (T FA ) values are OTU and run dependent and were estimated by analyzing the sequences in the NC index and PC alien controls. A result was considered positive if the number of sequences was > T CC and > T FA . Samples were considered positive if a positive result was obtained for both PCR replicates. *, see Kozich et al. ( 18 ) for details on the sequencing.
Figure Legend Snippet: Workflow of the wet laboratory, bioinformatics, and data filtering procedures in the process of data filtering for 16S rRNA amplicon sequencing. Reagent contaminants were detected by analyzing the sequences in the NC ext and NC PCR controls. Sequence number thresholds for correcting for cross-contamination (T CC ) are OTU and run dependent and were estimated by analyzing the sequences in the NC mus , NC ext , NC PCR , and PC index controls. Sequence number thresholds for correcting for false-index-pairing (T FA ) values are OTU and run dependent and were estimated by analyzing the sequences in the NC index and PC alien controls. A result was considered positive if the number of sequences was > T CC and > T FA . Samples were considered positive if a positive result was obtained for both PCR replicates. *, see Kozich et al. ( 18 ) for details on the sequencing.

Techniques Used: Amplification, Sequencing, Polymerase Chain Reaction

18) Product Images from "Community-like genome in single cells of the sulfur bacterium Achromatium oxaliferum"

Article Title: Community-like genome in single cells of the sulfur bacterium Achromatium oxaliferum

Journal: Nature Communications

doi: 10.1038/s41467-017-00342-9

Maximum likelihood tree of 16S rRNA sequences from Achromatium . The sequences were obtained from single Achromatium cells from Lake Stechlin, metagenomics data of the same cell population, and reference sequences. A similar tree which includes distance-clustered amplicon sequences is given in Supplementary Fig. 2A . A similar tree created using only full-length sequences to which the shorter ones were added by parsimony is provided as Supplementary Fig. 3
Figure Legend Snippet: Maximum likelihood tree of 16S rRNA sequences from Achromatium . The sequences were obtained from single Achromatium cells from Lake Stechlin, metagenomics data of the same cell population, and reference sequences. A similar tree which includes distance-clustered amplicon sequences is given in Supplementary Fig. 2A . A similar tree created using only full-length sequences to which the shorter ones were added by parsimony is provided as Supplementary Fig. 3

Techniques Used: Amplification

19) Product Images from "Influence of CO2 Degassing on the Microbial Community in a Dry Mofette Field in Hartoušov, Czech Republic (Western Eger Rift)"

Article Title: Influence of CO2 Degassing on the Microbial Community in a Dry Mofette Field in Hartoušov, Czech Republic (Western Eger Rift)

Journal: Frontiers in Microbiology

doi: 10.3389/fmicb.2018.02787

Lithological profile of the reference and mofette core (A) . The water content (B) , pH (C) , TOC (D) , conductivity (E) , sulfate concentration (F) , bacterial 16s rRNA gene copy number (G) , dsrB gene copy number (H) , mcrA gene copy number (I) , Shannon H index (J) and Shannon EH index (K) of reference (blue dots) and mofette (red squares) core.
Figure Legend Snippet: Lithological profile of the reference and mofette core (A) . The water content (B) , pH (C) , TOC (D) , conductivity (E) , sulfate concentration (F) , bacterial 16s rRNA gene copy number (G) , dsrB gene copy number (H) , mcrA gene copy number (I) , Shannon H index (J) and Shannon EH index (K) of reference (blue dots) and mofette (red squares) core.

Techniques Used: Concentration Assay

20) Product Images from "Serpentinization-Influenced Groundwater Harbors Extremely Low Diversity Microbial Communities Adapted to High pH"

Article Title: Serpentinization-Influenced Groundwater Harbors Extremely Low Diversity Microbial Communities Adapted to High pH

Journal: Frontiers in Microbiology

doi: 10.3389/fmicb.2017.00308

Non-parametric Multi Dimensional Scaling (MDS) plot of microbial community diversity based upon bacterial 16S rRNA gene sequences using the Bray–Curtis similarity index. Environmental variables that correlated with community composition are represented by vectors in two-dimensional space. The dark circle represents the length of a vector with perfect correlation ( R = 1).
Figure Legend Snippet: Non-parametric Multi Dimensional Scaling (MDS) plot of microbial community diversity based upon bacterial 16S rRNA gene sequences using the Bray–Curtis similarity index. Environmental variables that correlated with community composition are represented by vectors in two-dimensional space. The dark circle represents the length of a vector with perfect correlation ( R = 1).

Techniques Used: Plasmid Preparation

21) Product Images from "The Microbiome of Endophytic, Wood Colonizing Bacteria from Pine Trees as Affected by Pine Wilt Disease"

Article Title: The Microbiome of Endophytic, Wood Colonizing Bacteria from Pine Trees as Affected by Pine Wilt Disease

Journal: Scientific Reports

doi: 10.1038/s41598-017-04141-6

Diversity of endophytic, wood colonizing bacterial communities at the level of classes from pine trees of six different symptomatic classes from the two sampling areas (A and M) based on sequencing of PCR amplified 16S rRNA gene fragments. Only bacterial classes higher in abundance than 0.5% were included.
Figure Legend Snippet: Diversity of endophytic, wood colonizing bacterial communities at the level of classes from pine trees of six different symptomatic classes from the two sampling areas (A and M) based on sequencing of PCR amplified 16S rRNA gene fragments. Only bacterial classes higher in abundance than 0.5% were included.

Techniques Used: Sampling, Sequencing, Polymerase Chain Reaction, Amplification

Principal component of endophytic, wood colonizing bacterial communities at different phylogenetic levels from pine trees of six different symptomatic classes from the two sampling areas ( A : Malhada B : Avo) based on sequencing of PCR amplified 16S rRNA gene fragments.
Figure Legend Snippet: Principal component of endophytic, wood colonizing bacterial communities at different phylogenetic levels from pine trees of six different symptomatic classes from the two sampling areas ( A : Malhada B : Avo) based on sequencing of PCR amplified 16S rRNA gene fragments.

Techniques Used: Sampling, Sequencing, Polymerase Chain Reaction, Amplification

Principal component analysis (PCA) of DGGE fingerprinting of endophytic, wood colonizing bacterial communities from all pine wood tree samples from the two sampling sites obtained after PCR amplification of 16S rRNA gene fragments. The samples grouped according to the different symptomatic physiological classes in Malhada site ( A ); no clear clustering was observed in Avô site ( B ).
Figure Legend Snippet: Principal component analysis (PCA) of DGGE fingerprinting of endophytic, wood colonizing bacterial communities from all pine wood tree samples from the two sampling sites obtained after PCR amplification of 16S rRNA gene fragments. The samples grouped according to the different symptomatic physiological classes in Malhada site ( A ); no clear clustering was observed in Avô site ( B ).

Techniques Used: Denaturing Gradient Gel Electrophoresis, Sampling, Polymerase Chain Reaction, Amplification

α-Diversity analysis of endophytic, wood colonizing bacterial communities from pine trees of six different symptomatic classes from the two sampling areas based on sequencing of PCR amplified 16S rRNA gene fragments (Chao1). ( A ) Comparison of different symptomatic stages ( B ) Comparison of sites.
Figure Legend Snippet: α-Diversity analysis of endophytic, wood colonizing bacterial communities from pine trees of six different symptomatic classes from the two sampling areas based on sequencing of PCR amplified 16S rRNA gene fragments (Chao1). ( A ) Comparison of different symptomatic stages ( B ) Comparison of sites.

Techniques Used: Sampling, Sequencing, Polymerase Chain Reaction, Amplification

22) Product Images from "Evaluation of DNA extraction kits and phylogenetic diversity of the porcine gastrointestinal tract based on Illumina sequencing of two hypervariable regions"

Article Title: Evaluation of DNA extraction kits and phylogenetic diversity of the porcine gastrointestinal tract based on Illumina sequencing of two hypervariable regions

Journal: MicrobiologyOpen

doi: 10.1002/mbo3.312

Numerical comparison of terminal restriction fragment length polymorphism (T‐ RFLP ) analysis and Illumina 16S rRNA gene amplicon sequencing. (A) Number of terminal restriction fragments (TRFs) and operational taxonomic units (OTUs) obtained. TRF s are plotted in blue on the left y ‐axis and OTU s are plotted in red‐orange on the right. (B) Diversity indices of bacterial communities recovered by evaluated DNA extraction kits. Circle symbols show Shannon diversity and bars show Pielou's evenness. Diversity indices of fecal samples are plotted in shades of blue and ileal digesta samples in shades of red.
Figure Legend Snippet: Numerical comparison of terminal restriction fragment length polymorphism (T‐ RFLP ) analysis and Illumina 16S rRNA gene amplicon sequencing. (A) Number of terminal restriction fragments (TRFs) and operational taxonomic units (OTUs) obtained. TRF s are plotted in blue on the left y ‐axis and OTU s are plotted in red‐orange on the right. (B) Diversity indices of bacterial communities recovered by evaluated DNA extraction kits. Circle symbols show Shannon diversity and bars show Pielou's evenness. Diversity indices of fecal samples are plotted in shades of blue and ileal digesta samples in shades of red.

Techniques Used: Terminal Restriction Fragment Length Polymorphism, Amplification, Sequencing, DNA Extraction

Heat map plots depicting the bacterial communities of the ileal digesta and fecal sample at family level. Operational taxonomic units detected by Illumina sequencing in a relative abundance higher than 1%, in at least one of the 16S rRNA regions, are assigned to bacteria families and listed on the right of the heat maps. The relative abundance of these bacteria families in each DNA extract is coded according to the color key on the top of the figure. K3* indicates missing data for sequencing 16S rRNA gene region V1–2 of DNA extracted with K3 from ileal digesta, data were excluded because of low read numbers.
Figure Legend Snippet: Heat map plots depicting the bacterial communities of the ileal digesta and fecal sample at family level. Operational taxonomic units detected by Illumina sequencing in a relative abundance higher than 1%, in at least one of the 16S rRNA regions, are assigned to bacteria families and listed on the right of the heat maps. The relative abundance of these bacteria families in each DNA extract is coded according to the color key on the top of the figure. K3* indicates missing data for sequencing 16S rRNA gene region V1–2 of DNA extracted with K3 from ileal digesta, data were excluded because of low read numbers.

Techniques Used: Sequencing

23) Product Images from "16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife"

Article Title: 16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife

Journal: mSystems

doi: 10.1128/mSystems.00032-16

Prevalence of Mycoplasma lineages in Senegalese rodents, by site, and phylogenetic associations between Mycoplasma lineages and rodent species. (A) Comparison of phylogenetic trees based on the 16S rRNA V4 sequences of Mycoplasma and on the mitochondrial cytochrome b gene and the two nuclear gene fragments (IRBP exon 1 and GHR) for rodents (the tree was drawn based on data from reference 92 ). Lines link the Mycoplasma lineages detected in the various rodent species (for a minimum site prevalence exceeding 10%). The numbers next to the branches are bootstrap values (shown only if > 70%). (B) Plots of OTU prevalences, with 95% confidence intervals calculated by Sterne’s exact method ( 93 ) according to rodent species and site (see reference 69 for more information about site codes and their geographic locations). The gray bars on the x axis indicate sites from which the rodent species concerned is absent.
Figure Legend Snippet: Prevalence of Mycoplasma lineages in Senegalese rodents, by site, and phylogenetic associations between Mycoplasma lineages and rodent species. (A) Comparison of phylogenetic trees based on the 16S rRNA V4 sequences of Mycoplasma and on the mitochondrial cytochrome b gene and the two nuclear gene fragments (IRBP exon 1 and GHR) for rodents (the tree was drawn based on data from reference 92 ). Lines link the Mycoplasma lineages detected in the various rodent species (for a minimum site prevalence exceeding 10%). The numbers next to the branches are bootstrap values (shown only if > 70%). (B) Plots of OTU prevalences, with 95% confidence intervals calculated by Sterne’s exact method ( 93 ) according to rodent species and site (see reference 69 for more information about site codes and their geographic locations). The gray bars on the x axis indicate sites from which the rodent species concerned is absent.

Techniques Used:

Taxonomic assignment of the V4 16S rRNA sequences in wild rodents and in negative controls for extraction and PCR. The histograms show the percentages of sequences for the most abundant bacterial genera in the two MiSeq runs combined. Notice the presence in the controls of several bacterial genera, which was likely due to the inherent contamination of laboratory reagents by bacterial DNA (termed “contaminant genera”). These contaminant genera are also present (to a lesser extent) in the rodent samples. The insertions represent the proportion of sequences from rodent samples which were incorrectly assigned to the controls. See Fig. S1 for separate histograms for the two MiSeq runs.
Figure Legend Snippet: Taxonomic assignment of the V4 16S rRNA sequences in wild rodents and in negative controls for extraction and PCR. The histograms show the percentages of sequences for the most abundant bacterial genera in the two MiSeq runs combined. Notice the presence in the controls of several bacterial genera, which was likely due to the inherent contamination of laboratory reagents by bacterial DNA (termed “contaminant genera”). These contaminant genera are also present (to a lesser extent) in the rodent samples. The insertions represent the proportion of sequences from rodent samples which were incorrectly assigned to the controls. See Fig. S1 for separate histograms for the two MiSeq runs.

Techniques Used: Polymerase Chain Reaction

Workflow of the wet laboratory, bioinformatics, and data filtering procedures in the process of data filtering for 16S rRNA amplicon sequencing. Reagent contaminants were detected by analyzing the sequences in the NC ext and NC PCR controls. Sequence number thresholds for correcting for cross-contamination (T CC ) are OTU and run dependent and were estimated by analyzing the sequences in the NC mus , NC ext , NC PCR , and PC index controls. Sequence number thresholds for correcting for false-index-pairing (T FA ) values are OTU and run dependent and were estimated by analyzing the sequences in the NC index and PC alien controls. A result was considered positive if the number of sequences was > T CC and > T FA . Samples were considered positive if a positive result was obtained for both PCR replicates. *, see Kozich et al. ( 18 ) for details on the sequencing.
Figure Legend Snippet: Workflow of the wet laboratory, bioinformatics, and data filtering procedures in the process of data filtering for 16S rRNA amplicon sequencing. Reagent contaminants were detected by analyzing the sequences in the NC ext and NC PCR controls. Sequence number thresholds for correcting for cross-contamination (T CC ) are OTU and run dependent and were estimated by analyzing the sequences in the NC mus , NC ext , NC PCR , and PC index controls. Sequence number thresholds for correcting for false-index-pairing (T FA ) values are OTU and run dependent and were estimated by analyzing the sequences in the NC index and PC alien controls. A result was considered positive if the number of sequences was > T CC and > T FA . Samples were considered positive if a positive result was obtained for both PCR replicates. *, see Kozich et al. ( 18 ) for details on the sequencing.

Techniques Used: Amplification, Sequencing, Polymerase Chain Reaction

24) Product Images from "Dynamic transition of chemolithotrophic sulfur-oxidizing bacteria in response to amendment with nitrate in deposited marine sediments"

Article Title: Dynamic transition of chemolithotrophic sulfur-oxidizing bacteria in response to amendment with nitrate in deposited marine sediments

Journal: Frontiers in Microbiology

doi: 10.3389/fmicb.2015.00426

Dynamic transition of microbial communities during anoxic incubation of marine sediments as determined by Illumina sequencing of 16S rRNA genes (A) and transcripts (B). Relative abundances of 16S rRNA genes (‘G’) and transcripts (‘T’) defined phylogenetically are represented by the colors shown at the right side of the graph. The sequence libraries were obtained from the incubation at day 0 (designated the G0 and T0 libraries) and at days 2 and 5 in the nitrate-amended sediment (‘N’; designated the NG2, NG5, NT2, and NT5 libraries) and in the control (‘C’; designated the CG2, CG5, CT2, and CT5 libraries). The sequence library is indicated at the top of each bar.
Figure Legend Snippet: Dynamic transition of microbial communities during anoxic incubation of marine sediments as determined by Illumina sequencing of 16S rRNA genes (A) and transcripts (B). Relative abundances of 16S rRNA genes (‘G’) and transcripts (‘T’) defined phylogenetically are represented by the colors shown at the right side of the graph. The sequence libraries were obtained from the incubation at day 0 (designated the G0 and T0 libraries) and at days 2 and 5 in the nitrate-amended sediment (‘N’; designated the NG2, NG5, NT2, and NT5 libraries) and in the control (‘C’; designated the CG2, CG5, CT2, and CT5 libraries). The sequence library is indicated at the top of each bar.

Techniques Used: Incubation, Sequencing

Phylogenetic tree showing the taxonomic distribution of 16S rRNA genes from isolates (the strains HDS01, HDNS4, and HDS22), and their known cultivated relatives. The tree was constructed by the neighbor-joining method using the nearly full-length 16S rRNA gene sequences. Bootstrap values were obtained from 1,000 replications. The scale bar represents 5% sequence divergence.
Figure Legend Snippet: Phylogenetic tree showing the taxonomic distribution of 16S rRNA genes from isolates (the strains HDS01, HDNS4, and HDS22), and their known cultivated relatives. The tree was constructed by the neighbor-joining method using the nearly full-length 16S rRNA gene sequences. Bootstrap values were obtained from 1,000 replications. The scale bar represents 5% sequence divergence.

Techniques Used: Construct, Sequencing

25) Product Images from "Reproducible, high-yielding, biological caproate production from food waste using a single-phase anaerobic reactor system"

Article Title: Reproducible, high-yielding, biological caproate production from food waste using a single-phase anaerobic reactor system

Journal: Biotechnology for Biofuels

doi: 10.1186/s13068-018-1101-4

Taxonomic classification of the 16S rRNA sequences showing microbial groups potentially involved in caproate production. Sequences were retrieved from Illumina MiSeq sequencing of cDNA samples generated from: a control, b ethanol, c hydrogen (H 2 ) and d hydrogen and ethanol (H 2 /ethanol)-supplemented vials during batch experiments using leach-bed reactor leachate
Figure Legend Snippet: Taxonomic classification of the 16S rRNA sequences showing microbial groups potentially involved in caproate production. Sequences were retrieved from Illumina MiSeq sequencing of cDNA samples generated from: a control, b ethanol, c hydrogen (H 2 ) and d hydrogen and ethanol (H 2 /ethanol)-supplemented vials during batch experiments using leach-bed reactor leachate

Techniques Used: Sequencing, Generated

26) Product Images from "Hydrogen Limitation and Syntrophic Growth among Natural Assemblages of Thermophilic Methanogens at Deep-sea Hydrothermal Vents"

Article Title: Hydrogen Limitation and Syntrophic Growth among Natural Assemblages of Thermophilic Methanogens at Deep-sea Hydrothermal Vents

Journal: Frontiers in Microbiology

doi: 10.3389/fmicb.2016.01240

Phylogenetic diversity of Archaea and Bacteria in the 80°C and 55°C microcosms. Taxonomic breakdown and relative abundance at the genus level for archaeal (A) and bacterial (B) 97% 16S rRNA gene OTUs from microcosms following incubation at 80°C and 55°C using diffuse hydrothermal fluids collected from the Marker 113 vent site.
Figure Legend Snippet: Phylogenetic diversity of Archaea and Bacteria in the 80°C and 55°C microcosms. Taxonomic breakdown and relative abundance at the genus level for archaeal (A) and bacterial (B) 97% 16S rRNA gene OTUs from microcosms following incubation at 80°C and 55°C using diffuse hydrothermal fluids collected from the Marker 113 vent site.

Techniques Used: Incubation, Marker

27) Product Images from "Molecular assessment of bacterial vaginosis by Lactobacillus abundance and species diversity"

Article Title: Molecular assessment of bacterial vaginosis by Lactobacillus abundance and species diversity

Journal: BMC Infectious Diseases

doi: 10.1186/s12879-016-1513-3

Organism clustering on the basis of microarray analysis, plotted versus clustering on the basis of the 16S rRNA amplicon sequencing. In the middle, the uppermost color bar represents the color coding of the fluorescence intensity (arbitrary units, numbers 0.0–50.0) of DNA hybridizations, the middle color bar shows the cluster the individual was classified into and the lower color bar shows the low ( blue ) to high ( red ) Nugent score of the individuals. On the right, the upper color bar shows the clustering color code and the lower color bar the Nugent score color code
Figure Legend Snippet: Organism clustering on the basis of microarray analysis, plotted versus clustering on the basis of the 16S rRNA amplicon sequencing. In the middle, the uppermost color bar represents the color coding of the fluorescence intensity (arbitrary units, numbers 0.0–50.0) of DNA hybridizations, the middle color bar shows the cluster the individual was classified into and the lower color bar shows the low ( blue ) to high ( red ) Nugent score of the individuals. On the right, the upper color bar shows the clustering color code and the lower color bar the Nugent score color code

Techniques Used: Microarray, Amplification, Sequencing, Fluorescence

IS-profiling of phyla found in BV negative and BV positive women in relation to cluster group based on 16S rRNA amplicon sequencing data. The abscissa quantifies the cluster of each of 13 samples and 2 cultured strains. In dark green the Lactobacillus- dominated samples classified as BV negative are shown, in light green two strains of L. crispatus and L. iners , and in red the BV positive samples. On the ordinate the phyla are shown, Bacteroidetes ( pink ), FAFV ( blue ), and Proteobacteria ( yellow ). The numbers shown in the ordinate represent the IS-profiling length in the nucleotides. The mean log2 intensity in Relative Fluorescence Units (RFU) is shown by the color intensity as defined by the color bars on the left. FAFV: Firmicutes/Actinobacteria/Fusobacteria/Verrucomicrobia
Figure Legend Snippet: IS-profiling of phyla found in BV negative and BV positive women in relation to cluster group based on 16S rRNA amplicon sequencing data. The abscissa quantifies the cluster of each of 13 samples and 2 cultured strains. In dark green the Lactobacillus- dominated samples classified as BV negative are shown, in light green two strains of L. crispatus and L. iners , and in red the BV positive samples. On the ordinate the phyla are shown, Bacteroidetes ( pink ), FAFV ( blue ), and Proteobacteria ( yellow ). The numbers shown in the ordinate represent the IS-profiling length in the nucleotides. The mean log2 intensity in Relative Fluorescence Units (RFU) is shown by the color intensity as defined by the color bars on the left. FAFV: Firmicutes/Actinobacteria/Fusobacteria/Verrucomicrobia

Techniques Used: Amplification, Sequencing, Cell Culture, Fluorescence

Correlation between Lactobacillus crispatus and Lactobacillus iners based on 16S rRNA amplicon sequencing. The abscissa and ordinate show, respectively, the fractions of L. iners and L. crispatus sequences relative to the total number of sequences. The color bar shows the color code: low ( blue ) to high ( red ) Nugent score of the women
Figure Legend Snippet: Correlation between Lactobacillus crispatus and Lactobacillus iners based on 16S rRNA amplicon sequencing. The abscissa and ordinate show, respectively, the fractions of L. iners and L. crispatus sequences relative to the total number of sequences. The color bar shows the color code: low ( blue ) to high ( red ) Nugent score of the women

Techniques Used: Amplification, Sequencing

A boxplot relating species diversity based on 16S rRNA amplicon sequencing to BV. Individuals were first classified in clusters shown in sequence of increasing BV diagnosis on the abscissa. The dots give the Gini-Simpson index for individuals in different clusters. The boxes represent the distributions of the Gini-Simpson index and show its median and interquartile range (IQR) for each cluster. Whiskers extend to the furthest data point that is within 1.5 times the IQR
Figure Legend Snippet: A boxplot relating species diversity based on 16S rRNA amplicon sequencing to BV. Individuals were first classified in clusters shown in sequence of increasing BV diagnosis on the abscissa. The dots give the Gini-Simpson index for individuals in different clusters. The boxes represent the distributions of the Gini-Simpson index and show its median and interquartile range (IQR) for each cluster. Whiskers extend to the furthest data point that is within 1.5 times the IQR

Techniques Used: Amplification, Sequencing

Predictive power of various microbial species for BV. The abscissa shows the mean “increase in node purity” for the prediction of the Nugent score (a measure of how the sequence abundance of the specific species or family denoted on the ordinate contributes to the classification of the sample). The ordinate presents the family, genus, species determination on the basis of 16S rRNA amplicon sequencing. Two different strains of G. vaginalis are presented
Figure Legend Snippet: Predictive power of various microbial species for BV. The abscissa shows the mean “increase in node purity” for the prediction of the Nugent score (a measure of how the sequence abundance of the specific species or family denoted on the ordinate contributes to the classification of the sample). The ordinate presents the family, genus, species determination on the basis of 16S rRNA amplicon sequencing. Two different strains of G. vaginalis are presented

Techniques Used: Sequencing, Amplification

28) Product Images from "Impact of water heater temperature setting and water use frequency on the building plumbing microbiome"

Article Title: Impact of water heater temperature setting and water use frequency on the building plumbing microbiome

Journal: The ISME Journal

doi: 10.1038/ismej.2017.14

( a ) Relative abundance (RA) of Legionella spp. in all samples under different water heater temperature settings ( T in °C); ( b ) relative abundance (RA) of Legionella spp. in influent and control rig samples across time ( t in month, mon). Relative abundance was calculated using Illumina 16S rRNA gene amplicon sequencing. Water use frequency and phase are indicated by color and shape, respectively. All influent samples were assigned a uniform temperature of 20 °C to facilitate comparison.
Figure Legend Snippet: ( a ) Relative abundance (RA) of Legionella spp. in all samples under different water heater temperature settings ( T in °C); ( b ) relative abundance (RA) of Legionella spp. in influent and control rig samples across time ( t in month, mon). Relative abundance was calculated using Illumina 16S rRNA gene amplicon sequencing. Water use frequency and phase are indicated by color and shape, respectively. All influent samples were assigned a uniform temperature of 20 °C to facilitate comparison.

Techniques Used: Amplification, Sequencing

29) Product Images from "CD40-signalling abrogates induction of RORγt+ Treg cells by intestinal CD103+ DCs and causes fatal colitis"

Article Title: CD40-signalling abrogates induction of RORγt+ Treg cells by intestinal CD103+ DCs and causes fatal colitis

Journal: Nature Communications

doi: 10.1038/ncomms14715

Breakdown of B- and T-cell tolerance. ( a ) T-cell functionality was analysed by stimulating single-cell suspensions with PMA/Ionomycin and subsequently staining cells intracellular for the production of IL-17 and IFNγ as shown in Supplementary Fig. 1c, d . Shown are representative FACS plots for the respective organs as well as pooled statistics from more than five experiments ( n =14–18). ( b ) Binding of serum antibodies from 8-week-old mice to cecal content was analysed in an ELISA experiment using anti-mouse IgA-specific antibodies as detection antibodies. ( c ) Overall antibody amount specific for cecal content was measured as in b ( n =4, one out of three experiments with similar results is shown). ( d ) IgA-coated fecal bacteria from control and DC-LMP1/CD40 animals. Faeces homogenates were stained with anti-mouse IgA and analysed by flow cytometry as shown in Supplementary Fig. 1f . Data shows one representative histogram (upper panel) with percentage (lower left panel) or MFI (lower right panel) of IgA + bacteria (two pooled experiments, n =6). ( e ) Differences in alpha diversity of co-housed 8-week-old control and DC-LMP1/CD40 animals. On the basis of 16S rRNA gene sequencing of the V3-V4 regions the number of observed OTUs on the y axis versus the number of sequences per sample on the x axis are shown as rarefaction curve. Data indicates mean±s.d. ( n =5). Statistical analysis was done with a two-tailed unpaired Student's t -test. Dot blots and graphs show representatives of three ( b , c ) or five ( a ) independent experiments. Depicted is the mean±s.e.m. of (n =4; b , c ), ( n =5; e ), ( n =18, a ) individual 8–10-week-old female animals per group. ( d ) shows pooled data from two individual experiments with n =6 animals. * P
Figure Legend Snippet: Breakdown of B- and T-cell tolerance. ( a ) T-cell functionality was analysed by stimulating single-cell suspensions with PMA/Ionomycin and subsequently staining cells intracellular for the production of IL-17 and IFNγ as shown in Supplementary Fig. 1c, d . Shown are representative FACS plots for the respective organs as well as pooled statistics from more than five experiments ( n =14–18). ( b ) Binding of serum antibodies from 8-week-old mice to cecal content was analysed in an ELISA experiment using anti-mouse IgA-specific antibodies as detection antibodies. ( c ) Overall antibody amount specific for cecal content was measured as in b ( n =4, one out of three experiments with similar results is shown). ( d ) IgA-coated fecal bacteria from control and DC-LMP1/CD40 animals. Faeces homogenates were stained with anti-mouse IgA and analysed by flow cytometry as shown in Supplementary Fig. 1f . Data shows one representative histogram (upper panel) with percentage (lower left panel) or MFI (lower right panel) of IgA + bacteria (two pooled experiments, n =6). ( e ) Differences in alpha diversity of co-housed 8-week-old control and DC-LMP1/CD40 animals. On the basis of 16S rRNA gene sequencing of the V3-V4 regions the number of observed OTUs on the y axis versus the number of sequences per sample on the x axis are shown as rarefaction curve. Data indicates mean±s.d. ( n =5). Statistical analysis was done with a two-tailed unpaired Student's t -test. Dot blots and graphs show representatives of three ( b , c ) or five ( a ) independent experiments. Depicted is the mean±s.e.m. of (n =4; b , c ), ( n =5; e ), ( n =18, a ) individual 8–10-week-old female animals per group. ( d ) shows pooled data from two individual experiments with n =6 animals. * P

Techniques Used: Staining, FACS, Binding Assay, Mouse Assay, Enzyme-linked Immunosorbent Assay, Flow Cytometry, Cytometry, Sequencing, Two Tailed Test

30) Product Images from "16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife"

Article Title: 16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife

Journal: mSystems

doi: 10.1128/mSystems.00032-16

Prevalence of Mycoplasma lineages in Senegalese rodents, by site, and phylogenetic associations between Mycoplasma lineages and rodent species. (A) Comparison of phylogenetic trees based on the 16S rRNA V4 sequences of Mycoplasma and on the mitochondrial cytochrome b gene and the two nuclear gene fragments (IRBP exon 1 and GHR) for rodents (the tree was drawn based on data from reference 92 ). Lines link the Mycoplasma lineages detected in the various rodent species (for a minimum site prevalence exceeding 10%). The numbers next to the branches are bootstrap values (shown only if > 70%). (B) Plots of OTU prevalences, with 95% confidence intervals calculated by Sterne’s exact method ( 93 ) according to rodent species and site (see reference 69 for more information about site codes and their geographic locations). The gray bars on the x axis indicate sites from which the rodent species concerned is absent.
Figure Legend Snippet: Prevalence of Mycoplasma lineages in Senegalese rodents, by site, and phylogenetic associations between Mycoplasma lineages and rodent species. (A) Comparison of phylogenetic trees based on the 16S rRNA V4 sequences of Mycoplasma and on the mitochondrial cytochrome b gene and the two nuclear gene fragments (IRBP exon 1 and GHR) for rodents (the tree was drawn based on data from reference 92 ). Lines link the Mycoplasma lineages detected in the various rodent species (for a minimum site prevalence exceeding 10%). The numbers next to the branches are bootstrap values (shown only if > 70%). (B) Plots of OTU prevalences, with 95% confidence intervals calculated by Sterne’s exact method ( 93 ) according to rodent species and site (see reference 69 for more information about site codes and their geographic locations). The gray bars on the x axis indicate sites from which the rodent species concerned is absent.

Techniques Used:

Taxonomic assignment of the V4 16S rRNA sequences in wild rodents and in negative controls for extraction and PCR. The histograms show the percentages of sequences for the most abundant bacterial genera in the two MiSeq runs combined. Notice the presence in the controls of several bacterial genera, which was likely due to the inherent contamination of laboratory reagents by bacterial DNA (termed “contaminant genera”). These contaminant genera are also present (to a lesser extent) in the rodent samples. The insertions represent the proportion of sequences from rodent samples which were incorrectly assigned to the controls. See Fig. S1 for separate histograms for the two MiSeq runs.
Figure Legend Snippet: Taxonomic assignment of the V4 16S rRNA sequences in wild rodents and in negative controls for extraction and PCR. The histograms show the percentages of sequences for the most abundant bacterial genera in the two MiSeq runs combined. Notice the presence in the controls of several bacterial genera, which was likely due to the inherent contamination of laboratory reagents by bacterial DNA (termed “contaminant genera”). These contaminant genera are also present (to a lesser extent) in the rodent samples. The insertions represent the proportion of sequences from rodent samples which were incorrectly assigned to the controls. See Fig. S1 for separate histograms for the two MiSeq runs.

Techniques Used: Polymerase Chain Reaction

Workflow of the wet laboratory, bioinformatics, and data filtering procedures in the process of data filtering for 16S rRNA amplicon sequencing. Reagent contaminants were detected by analyzing the sequences in the NC ext and NC PCR controls. Sequence number thresholds for correcting for cross-contamination (T CC ) are OTU and run dependent and were estimated by analyzing the sequences in the NC mus , NC ext , NC PCR , and PC index controls. Sequence number thresholds for correcting for false-index-pairing (T FA ) values are OTU and run dependent and were estimated by analyzing the sequences in the NC index and PC alien controls. A result was considered positive if the number of sequences was > T CC and > T FA . Samples were considered positive if a positive result was obtained for both PCR replicates. *, see Kozich et al. ( 18 ) for details on the sequencing.
Figure Legend Snippet: Workflow of the wet laboratory, bioinformatics, and data filtering procedures in the process of data filtering for 16S rRNA amplicon sequencing. Reagent contaminants were detected by analyzing the sequences in the NC ext and NC PCR controls. Sequence number thresholds for correcting for cross-contamination (T CC ) are OTU and run dependent and were estimated by analyzing the sequences in the NC mus , NC ext , NC PCR , and PC index controls. Sequence number thresholds for correcting for false-index-pairing (T FA ) values are OTU and run dependent and were estimated by analyzing the sequences in the NC index and PC alien controls. A result was considered positive if the number of sequences was > T CC and > T FA . Samples were considered positive if a positive result was obtained for both PCR replicates. *, see Kozich et al. ( 18 ) for details on the sequencing.

Techniques Used: Amplification, Sequencing, Polymerase Chain Reaction

31) Product Images from "Influence of Plant Species on Microbial Activity and Denitrifier Population Development in Vegetated Denitrifying Wood-Chip Bioreactors"

Article Title: Influence of Plant Species on Microbial Activity and Denitrifier Population Development in Vegetated Denitrifying Wood-Chip Bioreactors

Journal: Plants

doi: 10.3390/plants9030289

Gene copy numbers (a: nirK , b: nirS , c: nosZ and d: 16S rRNA) in the extracted biofilm from the bioreactors’ media at 3 depths and in plant roots. Error bars: standard deviations.
Figure Legend Snippet: Gene copy numbers (a: nirK , b: nirS , c: nosZ and d: 16S rRNA) in the extracted biofilm from the bioreactors’ media at 3 depths and in plant roots. Error bars: standard deviations.

Techniques Used:

32) Product Images from "Intestinal microbiota development and gestational age in preterm neonates"

Article Title: Intestinal microbiota development and gestational age in preterm neonates

Journal: Scientific Reports

doi: 10.1038/s41598-018-20827-x

Microbiota composition in the fecal samples of preterm infants. Principal coordinates analyses (PCoA, Bray-Curtis dissimilarities) ( a – c ). The axes represent PCoA component scores, showing the two most important gradients differentiating the microbial communities. Each circle represents a microbial community, colored in panel ( a ) by the dominant organism in the community ( > 50% of all reads). Background color corresponds to: ( b ) postnatal age of the infant at the time of fecal sample collection; ( c ) postmenstrual age of the infant at sample collection. Blue background indicates low values, green intermediate, and orange high values. Average relative abundances of the dominant families in extremely premature (EP), moderately or very premature (MVP), compared to term infants from a Dutch cohort, at different postmenstrual ages (weeks) 25 ( d ). Average total DNA concentration by postmenstrual age, divided to bacterial taxa based on their relative abundances in the 16S rRNA data ( e ).
Figure Legend Snippet: Microbiota composition in the fecal samples of preterm infants. Principal coordinates analyses (PCoA, Bray-Curtis dissimilarities) ( a – c ). The axes represent PCoA component scores, showing the two most important gradients differentiating the microbial communities. Each circle represents a microbial community, colored in panel ( a ) by the dominant organism in the community ( > 50% of all reads). Background color corresponds to: ( b ) postnatal age of the infant at the time of fecal sample collection; ( c ) postmenstrual age of the infant at sample collection. Blue background indicates low values, green intermediate, and orange high values. Average relative abundances of the dominant families in extremely premature (EP), moderately or very premature (MVP), compared to term infants from a Dutch cohort, at different postmenstrual ages (weeks) 25 ( d ). Average total DNA concentration by postmenstrual age, divided to bacterial taxa based on their relative abundances in the 16S rRNA data ( e ).

Techniques Used: Concentration Assay

33) Product Images from "16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife"

Article Title: 16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife

Journal: mSystems

doi: 10.1128/mSystems.00032-16

Prevalence of Mycoplasma lineages in Senegalese rodents, by site, and phylogenetic associations between Mycoplasma lineages and rodent species. (A) Comparison of phylogenetic trees based on the 16S rRNA V4 sequences of Mycoplasma and on the mitochondrial cytochrome b gene and the two nuclear gene fragments (IRBP exon 1 and GHR) for rodents (the tree was drawn based on data from reference 92 ). Lines link the Mycoplasma lineages detected in the various rodent species (for a minimum site prevalence exceeding 10%). The numbers next to the branches are bootstrap values (shown only if > 70%). (B) Plots of OTU prevalences, with 95% confidence intervals calculated by Sterne’s exact method ( 93 ) according to rodent species and site (see reference 69 for more information about site codes and their geographic locations). The gray bars on the x axis indicate sites from which the rodent species concerned is absent.
Figure Legend Snippet: Prevalence of Mycoplasma lineages in Senegalese rodents, by site, and phylogenetic associations between Mycoplasma lineages and rodent species. (A) Comparison of phylogenetic trees based on the 16S rRNA V4 sequences of Mycoplasma and on the mitochondrial cytochrome b gene and the two nuclear gene fragments (IRBP exon 1 and GHR) for rodents (the tree was drawn based on data from reference 92 ). Lines link the Mycoplasma lineages detected in the various rodent species (for a minimum site prevalence exceeding 10%). The numbers next to the branches are bootstrap values (shown only if > 70%). (B) Plots of OTU prevalences, with 95% confidence intervals calculated by Sterne’s exact method ( 93 ) according to rodent species and site (see reference 69 for more information about site codes and their geographic locations). The gray bars on the x axis indicate sites from which the rodent species concerned is absent.

Techniques Used:

Taxonomic assignment of the V4 16S rRNA sequences in wild rodents and in negative controls for extraction and PCR. The histograms show the percentages of sequences for the most abundant bacterial genera in the two MiSeq runs combined. Notice the presence in the controls of several bacterial genera, which was likely due to the inherent contamination of laboratory reagents by bacterial DNA (termed “contaminant genera”). These contaminant genera are also present (to a lesser extent) in the rodent samples. The insertions represent the proportion of sequences from rodent samples which were incorrectly assigned to the controls. See Fig. S1 for separate histograms for the two MiSeq runs.
Figure Legend Snippet: Taxonomic assignment of the V4 16S rRNA sequences in wild rodents and in negative controls for extraction and PCR. The histograms show the percentages of sequences for the most abundant bacterial genera in the two MiSeq runs combined. Notice the presence in the controls of several bacterial genera, which was likely due to the inherent contamination of laboratory reagents by bacterial DNA (termed “contaminant genera”). These contaminant genera are also present (to a lesser extent) in the rodent samples. The insertions represent the proportion of sequences from rodent samples which were incorrectly assigned to the controls. See Fig. S1 for separate histograms for the two MiSeq runs.

Techniques Used: Polymerase Chain Reaction

Workflow of the wet laboratory, bioinformatics, and data filtering procedures in the process of data filtering for 16S rRNA amplicon sequencing. Reagent contaminants were detected by analyzing the sequences in the NC ext and NC PCR controls. Sequence number thresholds for correcting for cross-contamination (T CC ) are OTU and run dependent and were estimated by analyzing the sequences in the NC mus , NC ext , NC PCR , and PC index controls. Sequence number thresholds for correcting for false-index-pairing (T FA ) values are OTU and run dependent and were estimated by analyzing the sequences in the NC index and PC alien controls. A result was considered positive if the number of sequences was > T CC and > T FA . Samples were considered positive if a positive result was obtained for both PCR replicates. *, see Kozich et al. ( 18 ) for details on the sequencing.
Figure Legend Snippet: Workflow of the wet laboratory, bioinformatics, and data filtering procedures in the process of data filtering for 16S rRNA amplicon sequencing. Reagent contaminants were detected by analyzing the sequences in the NC ext and NC PCR controls. Sequence number thresholds for correcting for cross-contamination (T CC ) are OTU and run dependent and were estimated by analyzing the sequences in the NC mus , NC ext , NC PCR , and PC index controls. Sequence number thresholds for correcting for false-index-pairing (T FA ) values are OTU and run dependent and were estimated by analyzing the sequences in the NC index and PC alien controls. A result was considered positive if the number of sequences was > T CC and > T FA . Samples were considered positive if a positive result was obtained for both PCR replicates. *, see Kozich et al. ( 18 ) for details on the sequencing.

Techniques Used: Amplification, Sequencing, Polymerase Chain Reaction

34) Product Images from "Diet-induced extinction in the gut microbiota compounds over generations"

Article Title: Diet-induced extinction in the gut microbiota compounds over generations

Journal: Nature

doi: 10.1038/nature16504

Microbiota diversity is not regained upon direct weaning the diet-switching group onto the high-MAC diet a , Alpha-diversity as measured by Shannon index of fecal microbiota from generation 5 mice from the high-MAC diet control (control) (n=6), generation 5, diet-switching group that was weaned directly onto the high-MAC diet (Gen 5 diet switching) (n=6), and generation 4 mice from the diet switching group after weaning and maintenance on the low-MAC diet for 13 weeks and returned to the high-MAC diet for four weeks (Gen 4 diet switching) (n=5). Error bars are shown as s.e.m. and P values are from a two-tailed Student’s t-test b , Principal coordinate analysis of unweighted UniFrac distance for 16S rRNA amplicon profiles from fecal samples collected from first generation control mice on a high-MAC diet (green), fourth generation, diet-switching mice (purple), and fifth generation mice from the diet-switching lineage weaned directly onto the high-MAC diet (orange). Control is plotted as weeks post-humanization and generation 4 and 5 are plotted as age.
Figure Legend Snippet: Microbiota diversity is not regained upon direct weaning the diet-switching group onto the high-MAC diet a , Alpha-diversity as measured by Shannon index of fecal microbiota from generation 5 mice from the high-MAC diet control (control) (n=6), generation 5, diet-switching group that was weaned directly onto the high-MAC diet (Gen 5 diet switching) (n=6), and generation 4 mice from the diet switching group after weaning and maintenance on the low-MAC diet for 13 weeks and returned to the high-MAC diet for four weeks (Gen 4 diet switching) (n=5). Error bars are shown as s.e.m. and P values are from a two-tailed Student’s t-test b , Principal coordinate analysis of unweighted UniFrac distance for 16S rRNA amplicon profiles from fecal samples collected from first generation control mice on a high-MAC diet (green), fourth generation, diet-switching mice (purple), and fifth generation mice from the diet-switching lineage weaned directly onto the high-MAC diet (orange). Control is plotted as weeks post-humanization and generation 4 and 5 are plotted as age.

Techniques Used: Mouse Assay, Two Tailed Test, Amplification

Inefficient inter-generational transfer of taxa driven to low abundance by low dietary MACs a , Schematic of multigeneration mouse experiment. Second (n=6), third (n=6), and fourth generation mice (n=6) were weaned onto a low-MAC diet. After mice generated a litter of pups that were weaned, low-MAC diet mice were switched to the high-MAC diet for 4 weeks. A parallel group of control mice were maintained on the high-MAC diet throughout (generation 2, n=6; generation 3, n=6; generation 4, n=5). b , Microbiota diversity as measured by Shannon index observed in the microbiota of mice at five weeks old (top panel, n=6 for each group) or four weeks after shift to high-MAC diet (bottom panel, n=6 for each group) from three generations of diet switching mice (grey) or control high-MAC diet mice (black). Error bars are shown as s.e.m and P values are from two-tailed Student’s t-test. c , Principal coordinate analysis of UniFrac distance for 16S rRNA amplicon profiles from fecal samples collected from first generation mice from the control group consuming a high-MAC diet (green, n=5) or the diet switching group from generation 1 (yellow, n=5), 2 (blue, n=6), 3 (red, n=6), and 4 (purple, n=6). d , Heat map of abundance of high-confidence OTUs (number of sequencing reads, columns) from the diet switching group (top panel) and controls (bottom panel); taxonomic assignment is indicated at the top of each column (Bacteroidetes, green; Firmicutes, orange; other, grey). Each row represents an individual mouse microbiota from four weeks post-humanization (initial), while consuming the low-MAC diet (week 9, lo, shaded yellow), and four weeks after switching to the high-MAC diet (week 15, hi, shaded grey). Corresponding time points from controls are similarly shaded. N=5, 6, 6, and 6 for the diet-switching group and n=5, 6, 6, and 5 for the control group for generations one through four respectively.
Figure Legend Snippet: Inefficient inter-generational transfer of taxa driven to low abundance by low dietary MACs a , Schematic of multigeneration mouse experiment. Second (n=6), third (n=6), and fourth generation mice (n=6) were weaned onto a low-MAC diet. After mice generated a litter of pups that were weaned, low-MAC diet mice were switched to the high-MAC diet for 4 weeks. A parallel group of control mice were maintained on the high-MAC diet throughout (generation 2, n=6; generation 3, n=6; generation 4, n=5). b , Microbiota diversity as measured by Shannon index observed in the microbiota of mice at five weeks old (top panel, n=6 for each group) or four weeks after shift to high-MAC diet (bottom panel, n=6 for each group) from three generations of diet switching mice (grey) or control high-MAC diet mice (black). Error bars are shown as s.e.m and P values are from two-tailed Student’s t-test. c , Principal coordinate analysis of UniFrac distance for 16S rRNA amplicon profiles from fecal samples collected from first generation mice from the control group consuming a high-MAC diet (green, n=5) or the diet switching group from generation 1 (yellow, n=5), 2 (blue, n=6), 3 (red, n=6), and 4 (purple, n=6). d , Heat map of abundance of high-confidence OTUs (number of sequencing reads, columns) from the diet switching group (top panel) and controls (bottom panel); taxonomic assignment is indicated at the top of each column (Bacteroidetes, green; Firmicutes, orange; other, grey). Each row represents an individual mouse microbiota from four weeks post-humanization (initial), while consuming the low-MAC diet (week 9, lo, shaded yellow), and four weeks after switching to the high-MAC diet (week 15, hi, shaded grey). Corresponding time points from controls are similarly shaded. N=5, 6, 6, and 6 for the diet-switching group and n=5, 6, 6, and 5 for the control group for generations one through four respectively.

Techniques Used: Magnetic Cell Separation, Mouse Assay, Generated, Two Tailed Test, Amplification, Sequencing

Taxa reduction observed in low-MAC diet is largely reversible in a single generation a , Schematic of mouse experiment. Humanized mice (n=10) were maintained on a high-MAC diet for four weeks after which half of the mice were switched to a low-MAC diet for 7 weeks. These mice were then switched back to the high-MAC diet for > 4 weeks. b , Principle coordinate analysis of the UniFrac distance for 16S rRNA amplicon profiles from fecal samples collected from the diet switching mice (yellow, n=5) and control high-MAC diet mice (green, n=5). c , Distribution of OTUs fold changes for diet switching (blue, n=5) or control (red, n=5) groups comparing baseline (4 weeks post-humanization) versus week 9 (5 weeks post-low MAC diet for “diet switch” group; top panel) and baseline versus week 15 (4 weeks after return to high-MAC diet for “diet switch” group, bottom panel).
Figure Legend Snippet: Taxa reduction observed in low-MAC diet is largely reversible in a single generation a , Schematic of mouse experiment. Humanized mice (n=10) were maintained on a high-MAC diet for four weeks after which half of the mice were switched to a low-MAC diet for 7 weeks. These mice were then switched back to the high-MAC diet for > 4 weeks. b , Principle coordinate analysis of the UniFrac distance for 16S rRNA amplicon profiles from fecal samples collected from the diet switching mice (yellow, n=5) and control high-MAC diet mice (green, n=5). c , Distribution of OTUs fold changes for diet switching (blue, n=5) or control (red, n=5) groups comparing baseline (4 weeks post-humanization) versus week 9 (5 weeks post-low MAC diet for “diet switch” group; top panel) and baseline versus week 15 (4 weeks after return to high-MAC diet for “diet switch” group, bottom panel).

Techniques Used: Mouse Assay, Amplification

Reintroduction of lost taxa and a high-MAC diet restores microbiota diversity and composition a , Schematic of fecal transplant mouse experiment. b , Principal coordinate analysis of UniFrac distance for 16S rRNA amplicon profiles from fecal samples collected from fourth generation control mice on a high-MAC diet (green, n=6), fourth generation, diet-switching mice that received a fecal transplant (red, n=3), or did not (blue, n=3). c , Microbiota diversity as measured by Shannon index observed in the microbiota of mice that received a fecal transplant (red, n=3) or did not (blue, n=3). A green circle denotes the number of OTUs observed in fourth generation control mice consuming a high-MAC diet (n=6). Error bars are shown as s.e.m. d , Heat map of abundance of high-confidence OTUs (number of sequencing reads) from fourth generation diet-switching mice (n=3) three to 14 days after FMT (fecal microbiota transplant) and no FMT controls (n=3); taxonomic assignment is indicated at the top of each column (Bacteroidetes, green; Firmicutes, orange; other, grey). FMT donor (fourth generation control mice, n=5) and fourth generation diet-switching mice (n=5) four weeks after consuming high-MAC diet are also shown.
Figure Legend Snippet: Reintroduction of lost taxa and a high-MAC diet restores microbiota diversity and composition a , Schematic of fecal transplant mouse experiment. b , Principal coordinate analysis of UniFrac distance for 16S rRNA amplicon profiles from fecal samples collected from fourth generation control mice on a high-MAC diet (green, n=6), fourth generation, diet-switching mice that received a fecal transplant (red, n=3), or did not (blue, n=3). c , Microbiota diversity as measured by Shannon index observed in the microbiota of mice that received a fecal transplant (red, n=3) or did not (blue, n=3). A green circle denotes the number of OTUs observed in fourth generation control mice consuming a high-MAC diet (n=6). Error bars are shown as s.e.m. d , Heat map of abundance of high-confidence OTUs (number of sequencing reads) from fourth generation diet-switching mice (n=3) three to 14 days after FMT (fecal microbiota transplant) and no FMT controls (n=3); taxonomic assignment is indicated at the top of each column (Bacteroidetes, green; Firmicutes, orange; other, grey). FMT donor (fourth generation control mice, n=5) and fourth generation diet-switching mice (n=5) four weeks after consuming high-MAC diet are also shown.

Techniques Used: Amplification, Mouse Assay, Sequencing

35) Product Images from "Cold Adapted Nitrosospira sp.: A Potential Crucial Contributor of Ammonia Oxidation in Cryosols of Permafrost-Affected Landscapes in Northeast Siberia"

Article Title: Cold Adapted Nitrosospira sp.: A Potential Crucial Contributor of Ammonia Oxidation in Cryosols of Permafrost-Affected Landscapes in Northeast Siberia

Journal: Microorganisms

doi: 10.3390/microorganisms7120699

Maximum-likelihood tree based on phylogenic relationships between the bacterial 16S rRNA gene of known Nitrosospira and Nitrosospira -like bacteria enriched in this study. The tree was constructed using sequences of ±1400 b.p. Nodes supported by bootstrap values are indicated. Scale bar = 5% sequence divergence. Tree is based on Purkhold et al. [ 77 ].
Figure Legend Snippet: Maximum-likelihood tree based on phylogenic relationships between the bacterial 16S rRNA gene of known Nitrosospira and Nitrosospira -like bacteria enriched in this study. The tree was constructed using sequences of ±1400 b.p. Nodes supported by bootstrap values are indicated. Scale bar = 5% sequence divergence. Tree is based on Purkhold et al. [ 77 ].

Techniques Used: Construct, Sequencing

Maximum-likelihood tree depicting the phylogenetic relationships between the archaeal 16S rRNA gene sequences of cloning products of soils from the beach and other Thaumarchaeota -like sequences in group 1a + b and selected cultured representatives. The tree was constructed using sequences of ±900 b.p. Nodes supported by bootstrap values are indicated. Scale bar = 2% sequence divergence.
Figure Legend Snippet: Maximum-likelihood tree depicting the phylogenetic relationships between the archaeal 16S rRNA gene sequences of cloning products of soils from the beach and other Thaumarchaeota -like sequences in group 1a + b and selected cultured representatives. The tree was constructed using sequences of ±900 b.p. Nodes supported by bootstrap values are indicated. Scale bar = 2% sequence divergence.

Techniques Used: Clone Assay, Cell Culture, Construct, Sequencing

36) Product Images from "A Plant Growth-Promoting Microbial Soil Amendment Dynamically Alters the Strawberry Root Bacterial Microbiome"

Article Title: A Plant Growth-Promoting Microbial Soil Amendment Dynamically Alters the Strawberry Root Bacterial Microbiome

Journal: Scientific Reports

doi: 10.1038/s41598-019-53623-2

Treatment effect on strawberry root microbiome. 16S rRNA bacterial profiling indicates treatment impacts Shannon’s Diversity most distinctly in soil and rhizosphere samples and that samples distinctly cluster by sample type and treatment. ( a ) Box and whisker plots representing Shannon’s Diversity indices for all samples based on Bray-Curtis distances in amendment-treated (blue) and control (yellow) samples for each sample type and at each of the four sampling time points; soil (upper panel), rhizosphere (middle panel), and root (lower panel) indicate that amendment treatment correlates with a decrease in the within-sample diversity in soil and rhizosphere samples, but not in roots. The horizontal line within each box represents the median index value, and the bottom and top edges of each box indicate the 25th and 75th percentiles, respectively. Individual points are outliers. ( b ) Principal coordinate analysis (PCoA) plot for all samples using Bray-Curtis distances indicates that the largest source of variation between microbial communities is sample type (PCo 1, 36.8%) and the second largest source of variation is treatment (PCo 2, 15.7%). Both control soil (light brown circles), rhizosphere (light yellow), and root (light green) samples and amendment-treated soil (dark brown), rhizosphere (dark yellow), and root (dark green) samples cluster together within their respective treatment and sample types.
Figure Legend Snippet: Treatment effect on strawberry root microbiome. 16S rRNA bacterial profiling indicates treatment impacts Shannon’s Diversity most distinctly in soil and rhizosphere samples and that samples distinctly cluster by sample type and treatment. ( a ) Box and whisker plots representing Shannon’s Diversity indices for all samples based on Bray-Curtis distances in amendment-treated (blue) and control (yellow) samples for each sample type and at each of the four sampling time points; soil (upper panel), rhizosphere (middle panel), and root (lower panel) indicate that amendment treatment correlates with a decrease in the within-sample diversity in soil and rhizosphere samples, but not in roots. The horizontal line within each box represents the median index value, and the bottom and top edges of each box indicate the 25th and 75th percentiles, respectively. Individual points are outliers. ( b ) Principal coordinate analysis (PCoA) plot for all samples using Bray-Curtis distances indicates that the largest source of variation between microbial communities is sample type (PCo 1, 36.8%) and the second largest source of variation is treatment (PCo 2, 15.7%). Both control soil (light brown circles), rhizosphere (light yellow), and root (light green) samples and amendment-treated soil (dark brown), rhizosphere (dark yellow), and root (dark green) samples cluster together within their respective treatment and sample types.

Techniques Used: Whisker Assay, Sampling

37) Product Images from "16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife"

Article Title: 16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife

Journal: mSystems

doi: 10.1128/mSystems.00032-16

Prevalence of Mycoplasma lineages in Senegalese rodents, by site, and phylogenetic associations between Mycoplasma lineages and rodent species. (A) Comparison of phylogenetic trees based on the 16S rRNA V4 sequences of Mycoplasma and on the mitochondrial cytochrome b gene and the two nuclear gene fragments (IRBP exon 1 and GHR) for rodents (the tree was drawn based on data from reference 92 ). Lines link the Mycoplasma lineages detected in the various rodent species (for a minimum site prevalence exceeding 10%). The numbers next to the branches are bootstrap values (shown only if > 70%). (B) Plots of OTU prevalences, with 95% confidence intervals calculated by Sterne’s exact method ( 93 ) according to rodent species and site (see reference 69 for more information about site codes and their geographic locations). The gray bars on the x axis indicate sites from which the rodent species concerned is absent.
Figure Legend Snippet: Prevalence of Mycoplasma lineages in Senegalese rodents, by site, and phylogenetic associations between Mycoplasma lineages and rodent species. (A) Comparison of phylogenetic trees based on the 16S rRNA V4 sequences of Mycoplasma and on the mitochondrial cytochrome b gene and the two nuclear gene fragments (IRBP exon 1 and GHR) for rodents (the tree was drawn based on data from reference 92 ). Lines link the Mycoplasma lineages detected in the various rodent species (for a minimum site prevalence exceeding 10%). The numbers next to the branches are bootstrap values (shown only if > 70%). (B) Plots of OTU prevalences, with 95% confidence intervals calculated by Sterne’s exact method ( 93 ) according to rodent species and site (see reference 69 for more information about site codes and their geographic locations). The gray bars on the x axis indicate sites from which the rodent species concerned is absent.

Techniques Used:

Taxonomic assignment of the V4 16S rRNA sequences in wild rodents and in negative controls for extraction and PCR. The histograms show the percentages of sequences for the most abundant bacterial genera in the two MiSeq runs combined. Notice the presence in the controls of several bacterial genera, which was likely due to the inherent contamination of laboratory reagents by bacterial DNA (termed “contaminant genera”). These contaminant genera are also present (to a lesser extent) in the rodent samples. The insertions represent the proportion of sequences from rodent samples which were incorrectly assigned to the controls. See Fig. S1 for separate histograms for the two MiSeq runs.
Figure Legend Snippet: Taxonomic assignment of the V4 16S rRNA sequences in wild rodents and in negative controls for extraction and PCR. The histograms show the percentages of sequences for the most abundant bacterial genera in the two MiSeq runs combined. Notice the presence in the controls of several bacterial genera, which was likely due to the inherent contamination of laboratory reagents by bacterial DNA (termed “contaminant genera”). These contaminant genera are also present (to a lesser extent) in the rodent samples. The insertions represent the proportion of sequences from rodent samples which were incorrectly assigned to the controls. See Fig. S1 for separate histograms for the two MiSeq runs.

Techniques Used: Polymerase Chain Reaction

Workflow of the wet laboratory, bioinformatics, and data filtering procedures in the process of data filtering for 16S rRNA amplicon sequencing. Reagent contaminants were detected by analyzing the sequences in the NC ext and NC PCR controls. Sequence number thresholds for correcting for cross-contamination (T CC ) are OTU and run dependent and were estimated by analyzing the sequences in the NC mus , NC ext , NC PCR , and PC index controls. Sequence number thresholds for correcting for false-index-pairing (T FA ) values are OTU and run dependent and were estimated by analyzing the sequences in the NC index and PC alien controls. A result was considered positive if the number of sequences was > T CC and > T FA . Samples were considered positive if a positive result was obtained for both PCR replicates. *, see Kozich et al. ( 18 ) for details on the sequencing.
Figure Legend Snippet: Workflow of the wet laboratory, bioinformatics, and data filtering procedures in the process of data filtering for 16S rRNA amplicon sequencing. Reagent contaminants were detected by analyzing the sequences in the NC ext and NC PCR controls. Sequence number thresholds for correcting for cross-contamination (T CC ) are OTU and run dependent and were estimated by analyzing the sequences in the NC mus , NC ext , NC PCR , and PC index controls. Sequence number thresholds for correcting for false-index-pairing (T FA ) values are OTU and run dependent and were estimated by analyzing the sequences in the NC index and PC alien controls. A result was considered positive if the number of sequences was > T CC and > T FA . Samples were considered positive if a positive result was obtained for both PCR replicates. *, see Kozich et al. ( 18 ) for details on the sequencing.

Techniques Used: Amplification, Sequencing, Polymerase Chain Reaction

38) Product Images from "Intestinal microbiota development and gestational age in preterm neonates"

Article Title: Intestinal microbiota development and gestational age in preterm neonates

Journal: Scientific Reports

doi: 10.1038/s41598-018-20827-x

Microbiota composition in the fecal samples of preterm infants. Principal coordinates analyses (PCoA, Bray-Curtis dissimilarities) ( a – c ). The axes represent PCoA component scores, showing the two most important gradients differentiating the microbial communities. Each circle represents a microbial community, colored in panel ( a ) by the dominant organism in the community ( > 50% of all reads). Background color corresponds to: ( b ) postnatal age of the infant at the time of fecal sample collection; ( c ( d ). Average total DNA concentration by postmenstrual age, divided to bacterial taxa based on their relative abundances in the 16S rRNA data ( e ).
Figure Legend Snippet: Microbiota composition in the fecal samples of preterm infants. Principal coordinates analyses (PCoA, Bray-Curtis dissimilarities) ( a – c ). The axes represent PCoA component scores, showing the two most important gradients differentiating the microbial communities. Each circle represents a microbial community, colored in panel ( a ) by the dominant organism in the community ( > 50% of all reads). Background color corresponds to: ( b ) postnatal age of the infant at the time of fecal sample collection; ( c ( d ). Average total DNA concentration by postmenstrual age, divided to bacterial taxa based on their relative abundances in the 16S rRNA data ( e ).

Techniques Used: Concentration Assay

39) Product Images from "Microbial community analyses of produced waters from high‐temperature oil reservoirs reveal unexpected similarity between geographically distant oil reservoirs"

Article Title: Microbial community analyses of produced waters from high‐temperature oil reservoirs reveal unexpected similarity between geographically distant oil reservoirs

Journal: Microbial Biotechnology

doi: 10.1111/1751-7915.13281

The Nonmetric multidimentional scaling ( NMDS ) plot of the produced water microbial communities reconstructed from the 16S rRNA sequence data sets acquired experimentally in this study and from databases. Three different metrics were used for beta diversity calculation: (A) Bray‐Curtis distance metric, (B) unweighted Unifrac, (C) weighted Unifrac. The colour shades denote the communities originating from the same geographical regions as indicated in the legend. The stress values for (A), (B) and (C) are 0.213, 0.140 and 0.089 respectively. The microbial community of an agricultural soil sample was plotted as an out‐group (accession number: PRJNA 430535).
Figure Legend Snippet: The Nonmetric multidimentional scaling ( NMDS ) plot of the produced water microbial communities reconstructed from the 16S rRNA sequence data sets acquired experimentally in this study and from databases. Three different metrics were used for beta diversity calculation: (A) Bray‐Curtis distance metric, (B) unweighted Unifrac, (C) weighted Unifrac. The colour shades denote the communities originating from the same geographical regions as indicated in the legend. The stress values for (A), (B) and (C) are 0.213, 0.140 and 0.089 respectively. The microbial community of an agricultural soil sample was plotted as an out‐group (accession number: PRJNA 430535).

Techniques Used: Produced, Sequencing

40) Product Images from "The long-term stability of the human gut microbiota"

Article Title: The long-term stability of the human gut microbiota

Journal: Science (New York, N.Y.)

doi: 10.1126/science.1237439

Measuring the stability of an individual’s fecal microbiota over time with LEA-Seq (A) The Jaccard Index (fraction of shared strains) was calculated between all possible pairwise combinations of fecal samples collected from each individual, where bacterial strains were considered shared if the nucleotide sequence was 100% identical across 100% of the length of the V1V2 region of their 16S rRNA genes. Jaccard Indexes were binned into intervals of
Figure Legend Snippet: Measuring the stability of an individual’s fecal microbiota over time with LEA-Seq (A) The Jaccard Index (fraction of shared strains) was calculated between all possible pairwise combinations of fecal samples collected from each individual, where bacterial strains were considered shared if the nucleotide sequence was 100% identical across 100% of the length of the V1V2 region of their 16S rRNA genes. Jaccard Indexes were binned into intervals of

Techniques Used: Sequencing

Multiplex bacterial 16S rRNA gene sequencing using LEA-Seq; comparison with previous methods using mock communities composed of sequenced gut bacterial species (A) Schematic of how the LEA-Seq method is used to redundantly sequence PCR amplicons from a set of linear PCR template extensions of bacterial 16S rDNA. This approach results in amplicon sequences with a higher precision than standard amplicon sequencing at lower abundance thresholds. ( B ) Performance of 16S rRNA amplicon sequencing methods assayed as the precision obtained for different sequence abundance thresholds. Standard methods for amplicon sequencing using the 454 pyrosequencer and the Illumina MiSeq instrument exhibit increased precision as less abundant reads are filtered out. By redundantly sequencing each amplicon with LEA-Seq, the precision of amplicon sequencing is increased at lower abundance thresholds for both the V1V2 region of the bacterial 16S rRNA gene (compare red and blue lines) and the V4 region (compare magenta and blue lines), thereby enabling detection of lower-abundance bacterial taxa at high precision.
Figure Legend Snippet: Multiplex bacterial 16S rRNA gene sequencing using LEA-Seq; comparison with previous methods using mock communities composed of sequenced gut bacterial species (A) Schematic of how the LEA-Seq method is used to redundantly sequence PCR amplicons from a set of linear PCR template extensions of bacterial 16S rDNA. This approach results in amplicon sequences with a higher precision than standard amplicon sequencing at lower abundance thresholds. ( B ) Performance of 16S rRNA amplicon sequencing methods assayed as the precision obtained for different sequence abundance thresholds. Standard methods for amplicon sequencing using the 454 pyrosequencer and the Illumina MiSeq instrument exhibit increased precision as less abundant reads are filtered out. By redundantly sequencing each amplicon with LEA-Seq, the precision of amplicon sequencing is increased at lower abundance thresholds for both the V1V2 region of the bacterial 16S rRNA gene (compare red and blue lines) and the V4 region (compare magenta and blue lines), thereby enabling detection of lower-abundance bacterial taxa at high precision.

Techniques Used: Multiplex Assay, Sequencing, Polymerase Chain Reaction, Amplification

Related Articles

Sequencing:

Article Title: DNA extraction protocols cause differences in 16S rRNA amplicon sequencing efficiency but not in community profile composition or structure
Article Snippet: .. While bacterial community composition recovered using Illumina 16S rRNA amplicon sequencing was not detectably biased by any method, the quantity of bacterial DNA varied drastically, reducing the number of samples that could be amplified and sequenced. .. These results indicate that the concentration necessary for dependable sequencing is around 10,000 copies of target DNA per microliter.

Article Title: Comparison of the active and resident community of a coastal microbial mat
Article Snippet: .. The 6 DNA and 6 cDNA samples were submitted to BGI (Hong Kong, China) (http://www.genomics.cn/en/index) for bacterial 16S rRNA amplicon sequencing using the Illumina MiSeq platform. ..

Article Title: 16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife
Article Snippet: .. Such HTS microbial identification approaches are based on the sequencing of all (WGS [whole-genome sequencing]) or some (RNA-seq [whole-RNA sequencing] or 16S rRNA amplicon sequencing) of the bacterial DNA or RNA in a sample, followed by comparison to a reference sequence database ( ). ..

Article Title: 16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife
Article Snippet: .. These findings demonstrate the considerable potential of 16S rRNA amplicon sequencing for the rapid identification of zoonotic agents in wildlife, provided that the postsequencing data are cleaned beforehand. ..

Article Title: The Microbiome of the Cosmopolitan Diatom Leptocylindrus Reveals Significant Spatial and Temporal Variability
Article Snippet: .. 16S rRNA amplicon sequencing was subsequently performed on the Illumina MiSeq platform (Molecular Research LP; Shallowater, TX, United States) following the manufacturer’s guidelines. .. Raw data files in FASTQ format were deposited in NCBI Sequence Read Archive (SRA), with the study accession numbers PRJNA488135 and SRP143624 (diatom and bulk water samples, respectively).

Article Title: Characteristics and Evolution of sill-driven off-axis hydrothermalism in Guaymas Basin – the Ringvent site
Article Snippet: .. 16S rRNA amplicon sequencing was performed using an Illumina MiSeq Benchtop sequencer (Illumina, San Diego, CA, USA) at the Marine Biological Laboratory in Woods Hole, MA as described on the Visualization and Analysis of Microbial Population Structures (VAMPSs) website ( https://vamps.mbl.edu/resources/primers.php ). .. Sequence analyses To complement taxonomy assignments in VAMPS and to further explore the taxonomic identifications of uncultured groups, archaeal and bacterial sequences were processed with mothur v.1.39.5 following the mothur Illumina MiSeq Standard operation procedures .

Article Title: Microbial community analyses of produced waters from high‐temperature oil reservoirs reveal unexpected similarity between geographically distant oil reservoirs
Article Snippet: .. Summary of 16S rRNA amplicon sequencing of the produced water samples. ..

Article Title: 16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife
Article Snippet: .. Razzauti et al. ( ) recently showed that the sensitivity of 16S rRNA amplicon sequencing on the MiSeq platform was equivalent to that of whole-RNA sequencing (RNA-seq) on the HiSeq platform for detecting bacteria in rodent samples. .. However, little is known about the comparative sensitivities of HTS approaches relative to the sensitivity of quantitative PCR (qPCR) performed with specific primers, the current gold standard for bacterial detection within biological samples.

Produced:

Article Title: Microbial community analyses of produced waters from high‐temperature oil reservoirs reveal unexpected similarity between geographically distant oil reservoirs
Article Snippet: .. Summary of 16S rRNA amplicon sequencing of the produced water samples. ..

Amplification:

Article Title: DNA extraction protocols cause differences in 16S rRNA amplicon sequencing efficiency but not in community profile composition or structure
Article Snippet: .. While bacterial community composition recovered using Illumina 16S rRNA amplicon sequencing was not detectably biased by any method, the quantity of bacterial DNA varied drastically, reducing the number of samples that could be amplified and sequenced. .. These results indicate that the concentration necessary for dependable sequencing is around 10,000 copies of target DNA per microliter.

Article Title: Comparison of the active and resident community of a coastal microbial mat
Article Snippet: .. The 6 DNA and 6 cDNA samples were submitted to BGI (Hong Kong, China) (http://www.genomics.cn/en/index) for bacterial 16S rRNA amplicon sequencing using the Illumina MiSeq platform. ..

Article Title: 16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife
Article Snippet: .. Such HTS microbial identification approaches are based on the sequencing of all (WGS [whole-genome sequencing]) or some (RNA-seq [whole-RNA sequencing] or 16S rRNA amplicon sequencing) of the bacterial DNA or RNA in a sample, followed by comparison to a reference sequence database ( ). ..

Article Title: 16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife
Article Snippet: .. These findings demonstrate the considerable potential of 16S rRNA amplicon sequencing for the rapid identification of zoonotic agents in wildlife, provided that the postsequencing data are cleaned beforehand. ..

Article Title: The Microbiome of the Cosmopolitan Diatom Leptocylindrus Reveals Significant Spatial and Temporal Variability
Article Snippet: .. 16S rRNA amplicon sequencing was subsequently performed on the Illumina MiSeq platform (Molecular Research LP; Shallowater, TX, United States) following the manufacturer’s guidelines. .. Raw data files in FASTQ format were deposited in NCBI Sequence Read Archive (SRA), with the study accession numbers PRJNA488135 and SRP143624 (diatom and bulk water samples, respectively).

Article Title: Characteristics and Evolution of sill-driven off-axis hydrothermalism in Guaymas Basin – the Ringvent site
Article Snippet: .. 16S rRNA amplicon sequencing was performed using an Illumina MiSeq Benchtop sequencer (Illumina, San Diego, CA, USA) at the Marine Biological Laboratory in Woods Hole, MA as described on the Visualization and Analysis of Microbial Population Structures (VAMPSs) website ( https://vamps.mbl.edu/resources/primers.php ). .. Sequence analyses To complement taxonomy assignments in VAMPS and to further explore the taxonomic identifications of uncultured groups, archaeal and bacterial sequences were processed with mothur v.1.39.5 following the mothur Illumina MiSeq Standard operation procedures .

Article Title: Microbial community analyses of produced waters from high‐temperature oil reservoirs reveal unexpected similarity between geographically distant oil reservoirs
Article Snippet: .. Summary of 16S rRNA amplicon sequencing of the produced water samples. ..

Article Title: 16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife
Article Snippet: .. Razzauti et al. ( ) recently showed that the sensitivity of 16S rRNA amplicon sequencing on the MiSeq platform was equivalent to that of whole-RNA sequencing (RNA-seq) on the HiSeq platform for detecting bacteria in rodent samples. .. However, little is known about the comparative sensitivities of HTS approaches relative to the sensitivity of quantitative PCR (qPCR) performed with specific primers, the current gold standard for bacterial detection within biological samples.

RNA Sequencing Assay:

Article Title: 16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife
Article Snippet: .. Such HTS microbial identification approaches are based on the sequencing of all (WGS [whole-genome sequencing]) or some (RNA-seq [whole-RNA sequencing] or 16S rRNA amplicon sequencing) of the bacterial DNA or RNA in a sample, followed by comparison to a reference sequence database ( ). ..

Article Title: 16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife
Article Snippet: .. Razzauti et al. ( ) recently showed that the sensitivity of 16S rRNA amplicon sequencing on the MiSeq platform was equivalent to that of whole-RNA sequencing (RNA-seq) on the HiSeq platform for detecting bacteria in rodent samples. .. However, little is known about the comparative sensitivities of HTS approaches relative to the sensitivity of quantitative PCR (qPCR) performed with specific primers, the current gold standard for bacterial detection within biological samples.

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    Illumina Inc 16s rdna v4 region amplicon deep sequencing
    Comparison of the relative abundances of top 10 dominant genera in the rhizospheric soil between N698 and MD12. ( A ) Results revealed by <t>16S</t> <t>rDNA</t> V5–V7 hypervariable region <t>amplicon</t> deep sequencing. ( B ) Results revealed by 16S rDNA V4 hypervariable region amplicon deep sequencing. ( C ) Results revealed by shotgun metagenomic approaches (analyzed by One Codex). Error bars indicate standard errors; * p
    16s Rdna V4 Region Amplicon Deep Sequencing, supplied by Illumina Inc, used in various techniques. Bioz Stars score: 93/100, based on 4 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Illumina Inc 16s rrna gene amplicon illumina miseq sequencing
    <t>16S</t> <t>rRNA</t> gene <t>amplicon</t> sequencing of 15 samples including 8 whole community samples and 7 sorted subcommunities. Data are shown for Setup 1. The 8 whole community samples included inoculum, silver ion negative control (Neg, 7 and 24 d) and 0.1 mg/L AgNP-10 (LAg10, 7 and 24 d), silver ion positive control (Pos, 24 d), 2.25 mg/L AgNP-10 (EC 50 Ag10, 24 d), 7.13 mg/L AgNP-30 (EC 50 .
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    Illumina Inc bacterial microbial 16s rrna amplicons
    Sequence diversity among treatment groups. a Bar chart showing mean + standard deviation (SD) Chao1 a-diversity index of fecal microbiota in mice pre- and post-vaccination with the indicated antigens, as detected using <t>16S</t> <t>rRNA</t> amplicon sequencing. b Mean Shannon diversity indices. c Mean number of unique sequences in treatment groups
    Bacterial Microbial 16s Rrna Amplicons, supplied by Illumina Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Illumina Inc archaeal 16s rrna amplicon illumina sequencing raw data
    Abundances of bacterial and <t>archaeal</t> <t>16S</t> <t>rRNA</t> genes and archaeal and bacterial amoA genes (AOA- amoA , AOB- amoA ) per gram soil in savanna soil samples taken from 5 cm depth at different locations along the granitic (GI-GIV) and the basaltic (BI-BIII) catena . Bars represent mean abundances of replicate samples, each measured in triplicate qPCR reactions, and respective standard deviations. Abundances of bacterial amoA genes were below the quantification limit (50 genes per qPCR reaction) in all samples except BII and maximum estimates based on this limit are shown.
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    Comparison of the relative abundances of top 10 dominant genera in the rhizospheric soil between N698 and MD12. ( A ) Results revealed by 16S rDNA V5–V7 hypervariable region amplicon deep sequencing. ( B ) Results revealed by 16S rDNA V4 hypervariable region amplicon deep sequencing. ( C ) Results revealed by shotgun metagenomic approaches (analyzed by One Codex). Error bars indicate standard errors; * p

    Journal: Genes

    Article Title: Identification of Major Rhizobacterial Taxa Affected by a Glyphosate-Tolerant Soybean Line via Shotgun Metagenomic Approach

    doi: 10.3390/genes9040214

    Figure Lengend Snippet: Comparison of the relative abundances of top 10 dominant genera in the rhizospheric soil between N698 and MD12. ( A ) Results revealed by 16S rDNA V5–V7 hypervariable region amplicon deep sequencing. ( B ) Results revealed by 16S rDNA V4 hypervariable region amplicon deep sequencing. ( C ) Results revealed by shotgun metagenomic approaches (analyzed by One Codex). Error bars indicate standard errors; * p

    Article Snippet: By contrast, Yersinia /Serratia , Pedobacter , Luteibacter and Flavisolibacter were detected only by 16S rDNA V4 region amplicon deep sequencing ( , ).

    Techniques: Amplification, Sequencing

    16S rRNA gene amplicon sequencing of 15 samples including 8 whole community samples and 7 sorted subcommunities. Data are shown for Setup 1. The 8 whole community samples included inoculum, silver ion negative control (Neg, 7 and 24 d) and 0.1 mg/L AgNP-10 (LAg10, 7 and 24 d), silver ion positive control (Pos, 24 d), 2.25 mg/L AgNP-10 (EC 50 Ag10, 24 d), 7.13 mg/L AgNP-30 (EC 50 .

    Journal: Frontiers in Microbiology

    Article Title: AgNPs Change Microbial Community Structures of Wastewater

    doi: 10.3389/fmicb.2018.03211

    Figure Lengend Snippet: 16S rRNA gene amplicon sequencing of 15 samples including 8 whole community samples and 7 sorted subcommunities. Data are shown for Setup 1. The 8 whole community samples included inoculum, silver ion negative control (Neg, 7 and 24 d) and 0.1 mg/L AgNP-10 (LAg10, 7 and 24 d), silver ion positive control (Pos, 24 d), 2.25 mg/L AgNP-10 (EC 50 Ag10, 24 d), 7.13 mg/L AgNP-30 (EC 50 .

    Article Snippet: In this lab-scale study, flow cytometry as a high-throughput method and 16S rRNA gene amplicon Illumina MiSeq sequencing were used to track microbial community structure changes when being exposed to AgNPs.

    Techniques: Amplification, Sequencing, Negative Control, Positive Control

    Sequence diversity among treatment groups. a Bar chart showing mean + standard deviation (SD) Chao1 a-diversity index of fecal microbiota in mice pre- and post-vaccination with the indicated antigens, as detected using 16S rRNA amplicon sequencing. b Mean Shannon diversity indices. c Mean number of unique sequences in treatment groups

    Journal: BMC Research Notes

    Article Title: Vaccinating with conserved Escherichia coli antigens does not alter the mouse intestinal microbiome

    doi: 10.1186/s13104-016-2208-y

    Figure Lengend Snippet: Sequence diversity among treatment groups. a Bar chart showing mean + standard deviation (SD) Chao1 a-diversity index of fecal microbiota in mice pre- and post-vaccination with the indicated antigens, as detected using 16S rRNA amplicon sequencing. b Mean Shannon diversity indices. c Mean number of unique sequences in treatment groups

    Article Snippet: Bacterial Microbial 16S rRNA amplicons were generated via amplification of the V4 hypervariable region of the 16S rRNA gene using single-indexed universal primers as described previously [U515F/806R; ] flanked by Illumina standard adapter sequences.

    Techniques: Sequencing, Standard Deviation, Mouse Assay, Amplification

    Principal component analyses and UniFrac distances. a Unweighted principal component analyses showing β-diversity of fecal microbiota in mice pre- and post-vaccination with the indicated antigens, as detected via 16S rRNA amplicon sequencing. Principal component 1 (PC1) versus PC2 ( left ) and PC1 versus PC3 ( right ) are shown. Color-coding is identical to Fig. 2 , with open symbols representing pre-vaccination and closed symbols representing post-vaccination samples. b Mean intragroup unweighted UniFrac distances between pre- and post-vaccination samples

    Journal: BMC Research Notes

    Article Title: Vaccinating with conserved Escherichia coli antigens does not alter the mouse intestinal microbiome

    doi: 10.1186/s13104-016-2208-y

    Figure Lengend Snippet: Principal component analyses and UniFrac distances. a Unweighted principal component analyses showing β-diversity of fecal microbiota in mice pre- and post-vaccination with the indicated antigens, as detected via 16S rRNA amplicon sequencing. Principal component 1 (PC1) versus PC2 ( left ) and PC1 versus PC3 ( right ) are shown. Color-coding is identical to Fig. 2 , with open symbols representing pre-vaccination and closed symbols representing post-vaccination samples. b Mean intragroup unweighted UniFrac distances between pre- and post-vaccination samples

    Article Snippet: Bacterial Microbial 16S rRNA amplicons were generated via amplification of the V4 hypervariable region of the 16S rRNA gene using single-indexed universal primers as described previously [U515F/806R; ] flanked by Illumina standard adapter sequences.

    Techniques: Mouse Assay, Amplification, Sequencing

    Vaccination with ETEC MipA, Skp, and ETEC_2479. a Serum IgG responses in mice. Data are plotted as the fold-change in serum IgG after immunization with the indicated antigens, n = 5/group. b Bar chart showing relative abundance of all operational taxonomic units (OTUs) detected in the feces of mice prior to (pre) and 6 weeks after (post) vaccination with the indicated antigens, as detected using 16S rRNA amplicon sequencing. The identities of dominant taxa are shown at the right. c Mean number + standard deviation (SD) of sequence reads that were specific to Bacteriodales or Proteobacteria in indicated treatment groups

    Journal: BMC Research Notes

    Article Title: Vaccinating with conserved Escherichia coli antigens does not alter the mouse intestinal microbiome

    doi: 10.1186/s13104-016-2208-y

    Figure Lengend Snippet: Vaccination with ETEC MipA, Skp, and ETEC_2479. a Serum IgG responses in mice. Data are plotted as the fold-change in serum IgG after immunization with the indicated antigens, n = 5/group. b Bar chart showing relative abundance of all operational taxonomic units (OTUs) detected in the feces of mice prior to (pre) and 6 weeks after (post) vaccination with the indicated antigens, as detected using 16S rRNA amplicon sequencing. The identities of dominant taxa are shown at the right. c Mean number + standard deviation (SD) of sequence reads that were specific to Bacteriodales or Proteobacteria in indicated treatment groups

    Article Snippet: Bacterial Microbial 16S rRNA amplicons were generated via amplification of the V4 hypervariable region of the 16S rRNA gene using single-indexed universal primers as described previously [U515F/806R; ] flanked by Illumina standard adapter sequences.

    Techniques: Mouse Assay, Amplification, Sequencing, Standard Deviation

    Abundances of bacterial and archaeal 16S rRNA genes and archaeal and bacterial amoA genes (AOA- amoA , AOB- amoA ) per gram soil in savanna soil samples taken from 5 cm depth at different locations along the granitic (GI-GIV) and the basaltic (BI-BIII) catena . Bars represent mean abundances of replicate samples, each measured in triplicate qPCR reactions, and respective standard deviations. Abundances of bacterial amoA genes were below the quantification limit (50 genes per qPCR reaction) in all samples except BII and maximum estimates based on this limit are shown.

    Journal: Frontiers in Microbiology

    Article Title: Community Composition and Abundance of Bacterial, Archaeal and Nitrifying Populations in Savanna Soils on Contrasting Bedrock Material in Kruger National Park, South Africa

    doi: 10.3389/fmicb.2016.01638

    Figure Lengend Snippet: Abundances of bacterial and archaeal 16S rRNA genes and archaeal and bacterial amoA genes (AOA- amoA , AOB- amoA ) per gram soil in savanna soil samples taken from 5 cm depth at different locations along the granitic (GI-GIV) and the basaltic (BI-BIII) catena . Bars represent mean abundances of replicate samples, each measured in triplicate qPCR reactions, and respective standard deviations. Abundances of bacterial amoA genes were below the quantification limit (50 genes per qPCR reaction) in all samples except BII and maximum estimates based on this limit are shown.

    Article Snippet: Bacterial and archaeal 16S rRNA amplicon Illumina sequencing raw data were deposited in the European Nucleotide Archive database under the study accession number PRJEB13568 .

    Techniques: Real-time Polymerase Chain Reaction

    Classification of sequences obtained from archaeal 16S rRNA gene-targeted Illumina sequencing of savanna soil samples taken from 5 cm depth at different locations along the granitic (GI-GIV) and the basaltic (BI-BIII) catena . Eur, Euryarchaeota; RC, Rice Cluster; Woes, Woesearchaeota; DHVE, Deep Sea Hydrothermal Vent Euryarchaeota Group; Thaum, Thaumarchaeota; uncl, unclassified; (F)SCG, (Forest) Soil Creanarchaeota Group. For some samples, replicates had to be excluded from further analysis of the normalized data set due to low read numbers. Results based on the non-normalized sequence data, including more soil replicates, are presented in Supplementary Figure 8 .

    Journal: Frontiers in Microbiology

    Article Title: Community Composition and Abundance of Bacterial, Archaeal and Nitrifying Populations in Savanna Soils on Contrasting Bedrock Material in Kruger National Park, South Africa

    doi: 10.3389/fmicb.2016.01638

    Figure Lengend Snippet: Classification of sequences obtained from archaeal 16S rRNA gene-targeted Illumina sequencing of savanna soil samples taken from 5 cm depth at different locations along the granitic (GI-GIV) and the basaltic (BI-BIII) catena . Eur, Euryarchaeota; RC, Rice Cluster; Woes, Woesearchaeota; DHVE, Deep Sea Hydrothermal Vent Euryarchaeota Group; Thaum, Thaumarchaeota; uncl, unclassified; (F)SCG, (Forest) Soil Creanarchaeota Group. For some samples, replicates had to be excluded from further analysis of the normalized data set due to low read numbers. Results based on the non-normalized sequence data, including more soil replicates, are presented in Supplementary Figure 8 .

    Article Snippet: Bacterial and archaeal 16S rRNA amplicon Illumina sequencing raw data were deposited in the European Nucleotide Archive database under the study accession number PRJEB13568 .

    Techniques: Sequencing

    Phlyum-level taxonomic classification of sequences obtained from bacterial 16S rRNA gene-targeted Illumina sequencing of savanna soil samples taken from 5 cm depth at different locations along the granitic (GI-GIV) and the basaltic (BI-BIII) catena . Cand. Div., Candidate Division. For some samples, replicates had to be excluded from further analysis of the normalized data set due to low read numbers. Results based on the non-normalized sequence data, including more soil replicates, are presented in Supplementary Figure 7 .

    Journal: Frontiers in Microbiology

    Article Title: Community Composition and Abundance of Bacterial, Archaeal and Nitrifying Populations in Savanna Soils on Contrasting Bedrock Material in Kruger National Park, South Africa

    doi: 10.3389/fmicb.2016.01638

    Figure Lengend Snippet: Phlyum-level taxonomic classification of sequences obtained from bacterial 16S rRNA gene-targeted Illumina sequencing of savanna soil samples taken from 5 cm depth at different locations along the granitic (GI-GIV) and the basaltic (BI-BIII) catena . Cand. Div., Candidate Division. For some samples, replicates had to be excluded from further analysis of the normalized data set due to low read numbers. Results based on the non-normalized sequence data, including more soil replicates, are presented in Supplementary Figure 7 .

    Article Snippet: Bacterial and archaeal 16S rRNA amplicon Illumina sequencing raw data were deposited in the European Nucleotide Archive database under the study accession number PRJEB13568 .

    Techniques: Sequencing