16s rrna amplicons  (Illumina Inc)

 
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    Name:
    SurePlex DNA Amplification System
    Description:
    VeriSeq technology uses whole genome amplification to increase the quantity of DNA in a single cell or a few cells This amplification ensures sufficient amounts of DNA for next generation sequencing of preimplantation genetic screening PGS samples The SurePlex DNA Amplification System reproducibly amplifies total DNA from single or a few cells of an embryo biopsy It follows an easy to use single tube protocol to produce 2 5 μg of amplified DNA in 2 hours Following SurePlex DNA amplification samples are ready for use in VeriSeq PGS applications
    Catalog Number:
    PR-40-415101-00
    Price:
    None
    Category:
    Clinical Research Products
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    Structured Review

    Illumina Inc 16s rrna amplicons
    SurePlex DNA Amplification System
    VeriSeq technology uses whole genome amplification to increase the quantity of DNA in a single cell or a few cells This amplification ensures sufficient amounts of DNA for next generation sequencing of preimplantation genetic screening PGS samples The SurePlex DNA Amplification System reproducibly amplifies total DNA from single or a few cells of an embryo biopsy It follows an easy to use single tube protocol to produce 2 5 μg of amplified DNA in 2 hours Following SurePlex DNA amplification samples are ready for use in VeriSeq PGS applications
    https://www.bioz.com/result/16s rrna amplicons/product/Illumina Inc
    Average 86 stars, based on 1 article reviews
    Price from $9.99 to $1999.99
    16s rrna amplicons - by Bioz Stars, 2021-07
    86/100 stars

    Images

    1) Product Images from "The Fecal Microbiome in Cats with Diarrhea"

    Article Title: The Fecal Microbiome in Cats with Diarrhea

    Journal: PLoS ONE

    doi: 10.1371/journal.pone.0127378

    Predicted functional composition of metagenomes based on 16S rRNA gene sequencing data. LEfSe based on the PICRUSt data set revealed differentially enriched bacterial functions associated either with healthy (green) or diseased cats (red).
    Figure Legend Snippet: Predicted functional composition of metagenomes based on 16S rRNA gene sequencing data. LEfSe based on the PICRUSt data set revealed differentially enriched bacterial functions associated either with healthy (green) or diseased cats (red).

    Techniques Used: Functional Assay, Sequencing

    Rarefaction analysis of 16S rRNA gene sequences obtained from feline fecal samples. Lines represent the mean and error bars represent standard deviations. The analysis was performed on a randomly selected subset of 12,000 sequences per sample. (A) Analysis based on duration of diarrhea. (B) Analysis based on the number of stools per day.
    Figure Legend Snippet: Rarefaction analysis of 16S rRNA gene sequences obtained from feline fecal samples. Lines represent the mean and error bars represent standard deviations. The analysis was performed on a randomly selected subset of 12,000 sequences per sample. (A) Analysis based on duration of diarrhea. (B) Analysis based on the number of stools per day.

    Techniques Used:

    Principal Coordinate Analysis (PCoA) of unweighted UniFrac distances of 16S rRNA genes.
    Figure Legend Snippet: Principal Coordinate Analysis (PCoA) of unweighted UniFrac distances of 16S rRNA genes.

    Techniques Used:

    2) Product Images from "Synergistic action of the gut microbiota in environmental RNA interference in a leaf beetle"

    Article Title: Synergistic action of the gut microbiota in environmental RNA interference in a leaf beetle

    Journal: Microbiome

    doi: 10.1186/s40168-021-01066-1

    Ingestion of dsRNA promotes the growth of gut bacteria in P. versicolora larvae. qRT-PCR analyses were performed to determine the relative abundance of gut bacteria in P. versicolora larvae fed with ds GFP ( a ), ds Srp54k ( b ), and ds Actin ( c ) ( n = 5), and the abundances of three major bacterial genera in non-axenic P. versicolora larvae fed with ds GFP ( d ), ds Srp54k ( e ), and ds Actin ( f ). The measurements were performed at different time points (after 2–5 days of feeding). The qRT-PCR value obtained for gut bacterial 16S rRNA in P. versicolora larvae fed with water-treated leaves was set as control. P values were calculated using the independent samples t test. Data are presented as means ± SE, *** P
    Figure Legend Snippet: Ingestion of dsRNA promotes the growth of gut bacteria in P. versicolora larvae. qRT-PCR analyses were performed to determine the relative abundance of gut bacteria in P. versicolora larvae fed with ds GFP ( a ), ds Srp54k ( b ), and ds Actin ( c ) ( n = 5), and the abundances of three major bacterial genera in non-axenic P. versicolora larvae fed with ds GFP ( d ), ds Srp54k ( e ), and ds Actin ( f ). The measurements were performed at different time points (after 2–5 days of feeding). The qRT-PCR value obtained for gut bacterial 16S rRNA in P. versicolora larvae fed with water-treated leaves was set as control. P values were calculated using the independent samples t test. Data are presented as means ± SE, *** P

    Techniques Used: Quantitative RT-PCR

    3) Product Images from "Cutaneous leishmaniasis induces a transmissible dysbiotic skin microbiota that promotes skin inflammation"

    Article Title: Cutaneous leishmaniasis induces a transmissible dysbiotic skin microbiota that promotes skin inflammation

    Journal: Cell host & microbe

    doi: 10.1016/j.chom.2017.06.006

    Skin microbiota alterations in L. major infection are dependent on disease severity C57BL/6 and BALB/c mice were intradermally infected with L. major parasites. Lesional severity was assessed by (A) ear thickness and (B) a pathology score over the course of infection. Swabs for sequencing of 16S rRNA genes were collected from the lesions at 0 and 6 weeks post-infection. (C) Alpha diversity was assessed by Shannon Index. (D) Stacked bar charts represent the proportion of the top 10 taxa present in each sample. Data are representative of two independent experiments (n = 1 skin swab each from 10 mice in each group). C57BL/6 mice were treated with an isotype or anti-IL-12 mAb and intradermally infected in the ear with L. major parasites. Lesional severity was assessed by (E) ear thickness and (F) a pathology score over the course of infection. Anti-IL-12 mAb treated mice were euthanized at 6 weeks post-infection due to severe disease. (G) Swabs were collected from the lesions at 2, 4 and 6 weeks post-infection and proportions of Staphylococcus and Streptococcus .
    Figure Legend Snippet: Skin microbiota alterations in L. major infection are dependent on disease severity C57BL/6 and BALB/c mice were intradermally infected with L. major parasites. Lesional severity was assessed by (A) ear thickness and (B) a pathology score over the course of infection. Swabs for sequencing of 16S rRNA genes were collected from the lesions at 0 and 6 weeks post-infection. (C) Alpha diversity was assessed by Shannon Index. (D) Stacked bar charts represent the proportion of the top 10 taxa present in each sample. Data are representative of two independent experiments (n = 1 skin swab each from 10 mice in each group). C57BL/6 mice were treated with an isotype or anti-IL-12 mAb and intradermally infected in the ear with L. major parasites. Lesional severity was assessed by (E) ear thickness and (F) a pathology score over the course of infection. Anti-IL-12 mAb treated mice were euthanized at 6 weeks post-infection due to severe disease. (G) Swabs were collected from the lesions at 2, 4 and 6 weeks post-infection and proportions of Staphylococcus and Streptococcus .

    Techniques Used: Infection, Mouse Assay, Sequencing

    L. major induced dysbiosis is transmissible to uninfected skin (A) C57BL/6 mice were intradermally infected with L. major and swabs were collected from the infected and contralateral ears at 6 weeks post-infected for 16S rRNA gene analysis. Stacked bar charts represent the proportion of the top 10 taxa present in each sample. Data are representative of three independent experiments (n = 1 swab of each ear from 15 mice). (B) Swabs from naïve or L. major infected C57BL/6 mice were cultured on mannitol salt agar plates and CFUs were counted to determine bacteria burden. Data are representative of 1 experiment (For naïve group, n = 1 swab from the ear of 10 mice; for infected and contralateral ears, n = 1 swab of each ear from 12 mice). (C) Naïve C57BL/6 mice were co-housed with L. major .
    Figure Legend Snippet: L. major induced dysbiosis is transmissible to uninfected skin (A) C57BL/6 mice were intradermally infected with L. major and swabs were collected from the infected and contralateral ears at 6 weeks post-infected for 16S rRNA gene analysis. Stacked bar charts represent the proportion of the top 10 taxa present in each sample. Data are representative of three independent experiments (n = 1 swab of each ear from 15 mice). (B) Swabs from naïve or L. major infected C57BL/6 mice were cultured on mannitol salt agar plates and CFUs were counted to determine bacteria burden. Data are representative of 1 experiment (For naïve group, n = 1 swab from the ear of 10 mice; for infected and contralateral ears, n = 1 swab of each ear from 12 mice). (C) Naïve C57BL/6 mice were co-housed with L. major .

    Techniques Used: Mouse Assay, Infection, Cell Culture

    4) Product Images from "Stable Isotope and Metagenomic Profiling of a Methanogenic Naphthalene-Degrading Enrichment Culture"

    Article Title: Stable Isotope and Metagenomic Profiling of a Methanogenic Naphthalene-Degrading Enrichment Culture

    Journal: Microorganisms

    doi: 10.3390/microorganisms6030065

    Distribution of bacterial and archaeal 16S rRNA gene pyrotag sequences in an active naphthalene-degrading replicate of NDC. Values are shown as the percentage of sequences per taxon based on 2034 bacterial sequences and 1881 archaeal sequences. OTUs included in ‘Other’ make up less than 0.4% of prokaryotic sequences each and include Spirochaeta (0.26%), Proteiniphilum (0.13%), and Candidatus Methanoregula (0.36%).
    Figure Legend Snippet: Distribution of bacterial and archaeal 16S rRNA gene pyrotag sequences in an active naphthalene-degrading replicate of NDC. Values are shown as the percentage of sequences per taxon based on 2034 bacterial sequences and 1881 archaeal sequences. OTUs included in ‘Other’ make up less than 0.4% of prokaryotic sequences each and include Spirochaeta (0.26%), Proteiniphilum (0.13%), and Candidatus Methanoregula (0.36%).

    Techniques Used:

    5) Product Images from "Dynamics of dark fermentation microbial communities in the light of lactate and butyrate production"

    Article Title: Dynamics of dark fermentation microbial communities in the light of lactate and butyrate production

    Journal: Microbiome

    doi: 10.1186/s40168-021-01105-x

    Taxonomic composition (genus level) of the MCs selected in the batch experiment based on hypervariable V4 region of the 16S rRNA gene, sequenced on MiSeq platform (Illumina). The taxonomy was assigned using the RDP classifier against the SILVA database. All taxa with relative abundance lower than 0.1% were removed
    Figure Legend Snippet: Taxonomic composition (genus level) of the MCs selected in the batch experiment based on hypervariable V4 region of the 16S rRNA gene, sequenced on MiSeq platform (Illumina). The taxonomy was assigned using the RDP classifier against the SILVA database. All taxa with relative abundance lower than 0.1% were removed

    Techniques Used:

    6) Product Images from "Comparison of Nitrate and Perchlorate in Controlling Sulfidogenesis in Heavy Oil-Containing Bioreactors"

    Article Title: Comparison of Nitrate and Perchlorate in Controlling Sulfidogenesis in Heavy Oil-Containing Bioreactors

    Journal: Frontiers in Microbiology

    doi: 10.3389/fmicb.2018.02423

    Relational tree for 16S rRNA gene libraries from incubations of CSBK medium, inoculated with 18PW and amended with 1 mL MHGC oil and sulfate (SO); sulfate and nitrate (SNO); sulfate and perchlorate (PSO); sulfate, nitrate, and perchlorate (PSNO); or perchlorate only (PO). Community DNA was obtained from cells harvested at day 9, 65, 85, or 123 as indicated. The fractions of reads in classes of Proteobacteria (A) and in other phyla (B) are shown.
    Figure Legend Snippet: Relational tree for 16S rRNA gene libraries from incubations of CSBK medium, inoculated with 18PW and amended with 1 mL MHGC oil and sulfate (SO); sulfate and nitrate (SNO); sulfate and perchlorate (PSO); sulfate, nitrate, and perchlorate (PSNO); or perchlorate only (PO). Community DNA was obtained from cells harvested at day 9, 65, 85, or 123 as indicated. The fractions of reads in classes of Proteobacteria (A) and in other phyla (B) are shown.

    Techniques Used:

    7) Product Images from "JTD special edition ‘Hot Topics in COPD’—The microbiome in COPD"

    Article Title: JTD special edition ‘Hot Topics in COPD’—The microbiome in COPD

    Journal: Journal of Thoracic Disease

    doi: 10.3978/j.issn.2072-1439.2014.11.08

    Bacterial community profiling using high throughput DNA sequencing of a highly conserved bacteria-specific gene ( 16S rRNA gene). In this example the microbial community composition in bronchoalveolar lavage samples obtained from lung transplant patients
    Figure Legend Snippet: Bacterial community profiling using high throughput DNA sequencing of a highly conserved bacteria-specific gene ( 16S rRNA gene). In this example the microbial community composition in bronchoalveolar lavage samples obtained from lung transplant patients

    Techniques Used: High Throughput Screening Assay, DNA Sequencing

    8) Product Images from "Dynamics and Complexity of Dark Fermentation Microbial Communities Producing Hydrogen From Sugar Beet Molasses in Continuously Operating Packed Bed Reactors"

    Article Title: Dynamics and Complexity of Dark Fermentation Microbial Communities Producing Hydrogen From Sugar Beet Molasses in Continuously Operating Packed Bed Reactors

    Journal: Frontiers in Microbiology

    doi: 10.3389/fmicb.2020.612344

    Taxonomic composition (genus level) of the microbial communities that selected out in PBRs, based on hypervariable V4 region of the 16S rRNA gene, sequenced on MiSeq platform (Illumina). The taxonomy was assigned using RDP classifier against the SILVA database. All taxa with Relative Abundance lower than 0.1% were removed.
    Figure Legend Snippet: Taxonomic composition (genus level) of the microbial communities that selected out in PBRs, based on hypervariable V4 region of the 16S rRNA gene, sequenced on MiSeq platform (Illumina). The taxonomy was assigned using RDP classifier against the SILVA database. All taxa with Relative Abundance lower than 0.1% were removed.

    Techniques Used:

    9) Product Images from "An ancient deletion in the ABO gene affects the composition of the porcine microbiome by altering intestinal N-acetyl-galactosamine concentrations"

    Article Title: An ancient deletion in the ABO gene affects the composition of the porcine microbiome by altering intestinal N-acetyl-galactosamine concentrations

    Journal: bioRxiv

    doi: 10.1101/2020.07.16.206219

    (A) Joint Principal Coordinate Analysis (PCoA) of 5,110 16S rRNA microbiome profiles. (I) Generation F6: fecal samples day 25 (D25, mauve), fecal samples day 120 (D120, red), fecal samples day 240 (D240, green), ileal content (IC, light blue), cecum content (CC, dark blue). (II) Generation F7: fecal samples day 25 (D25, mauve), fecal samples day 120 (D120, red), fecal samples day 240 (D240, green), ileal content (IC, light blue), cecum content (CC, dark blue). (III) Generation F7: ileal content (IC, light blue), cecum content (CC, dark blue), ileal mucosa (IM, pink), cecal mucosa (CM, brown). (B) Average 16S rRNA microbiota composition of the 12 porcine data series. Taxa are colored by phylum and by family within phylum, highlighting 43 families that are amongst the top 15 in at least one data series. The names of the corresponding phyla and families are provided in the legend. Average microbiota composition of 106 human feces and 6 mouse feces (C57BL/6). (C) Individual α -diversities measured using Shannon’s index for the 12 porcine data series color-labelled as in A and B. (D) Individual β -diversities measured pair-wise Bray-Curtis dissimilarities for the 12 porcine data series color-labelled as in A and B.
    Figure Legend Snippet: (A) Joint Principal Coordinate Analysis (PCoA) of 5,110 16S rRNA microbiome profiles. (I) Generation F6: fecal samples day 25 (D25, mauve), fecal samples day 120 (D120, red), fecal samples day 240 (D240, green), ileal content (IC, light blue), cecum content (CC, dark blue). (II) Generation F7: fecal samples day 25 (D25, mauve), fecal samples day 120 (D120, red), fecal samples day 240 (D240, green), ileal content (IC, light blue), cecum content (CC, dark blue). (III) Generation F7: ileal content (IC, light blue), cecum content (CC, dark blue), ileal mucosa (IM, pink), cecal mucosa (CM, brown). (B) Average 16S rRNA microbiota composition of the 12 porcine data series. Taxa are colored by phylum and by family within phylum, highlighting 43 families that are amongst the top 15 in at least one data series. The names of the corresponding phyla and families are provided in the legend. Average microbiota composition of 106 human feces and 6 mouse feces (C57BL/6). (C) Individual α -diversities measured using Shannon’s index for the 12 porcine data series color-labelled as in A and B. (D) Individual β -diversities measured pair-wise Bray-Curtis dissimilarities for the 12 porcine data series color-labelled as in A and B.

    Techniques Used:

    We observed an excess of negative correlations between genetic similarity (from SNP genotype data) and microbiota dissimilarity (Bray Curtis distance computed from 16S rRNA data) both within litter as well as between generations, supporting an effect of host genetics and intestinal microbiota composition ( Fig. 3A B ). We took care in these analyses to mitigate effects of litter on both genetic and microbiota distance metrics, (as these may inflate statistical significance) by applying permutations tests. Regressing squared phenotypic difference on genetic distance is a standard way to estimate local or global heritability ( Haseman Elston, 1972 ; Visscher et al., 2006 ). It can be shown that estimates the narrow sense heritability . In these, is the least square regression coefficient and an estimate of the phenotypic variance. In our analyses, and following standard procedures (f.i. Rothschild et al., 2017), we used Bray-Curtis as distance measure for microbiota composition. For this metric, there is no corresponding individual phenotype p i per se . We therefore used simulations to translate the observed negative correlations in measures of heritability. For the within-generation/within-litter analyses, we first used the actual measures of kinship for all litter-mates computed with GEMMA ( Zhou Stephens, 2012 ) and corresponding to the x-axis in Fig. 3A . We standardized them (mean 0 and SD 1), scaled them (mean of 0.5 and SD 0.04, following Visscher et al., 2006 ) and multiplied them by h 2 (0.2, 0.4, 0.6, 0.8 or 1.0). We sampled “breeding values” from a multivariate normal distribution with means 0 and corresponding variance-covariance matrix using the mvrnorm R function. For each individual, we sampled an environmental effect from a normal distribution with mean 0 and variance (1 – h 2 ) using the rnorm R function. Breeding values and environmental effects were added to yield a phenotypic value p i for each individual. We then computed Spearman’s rank correlation between abs ( p i – p j ) and Θ ij for all pairs of litter mates i and j using the cor.test(method=”spearman”) R function. In this Θ ij is the kinship metric computed by GEMMA. We repeated the simulations 1,000 times. Suppl. Fig. 7A B show the distribution of the corresponding correlations ( r ) for the 12 data series and 5 values of h 2 . The black vertical line corresponds to zero. The red vertical line to the median of the simulations. It can be seen that as the heritability increases the value of the median decreases as expected. The green lines correspond to the corrected correlation ( r c ) obtained with the real data. A rough estimate of the heritability of the real trait (microbiota composition) was deduced from the coincidence between the red and green lines. As an example, the heritability of microbiome composition for data series F7-D120 was assumed to be close to 0.8. We proceeded in the same way for the across generation analysis ( Suppl. Fig. 7C ). We used the actual measur es of kinship across the F6 and F7 generations computed with GEMMA. We standardized them (mean 0 and SD 1), and then scaled them such that the values for an individual with itself would center on 1, and for full-sibs on 0.5. Breeding values and environmental effects were sampled using mvrnorm and rnorm as above. As the number of individuals is much higher in these analyses we only performed 100 simulations.
    Figure Legend Snippet: We observed an excess of negative correlations between genetic similarity (from SNP genotype data) and microbiota dissimilarity (Bray Curtis distance computed from 16S rRNA data) both within litter as well as between generations, supporting an effect of host genetics and intestinal microbiota composition ( Fig. 3A B ). We took care in these analyses to mitigate effects of litter on both genetic and microbiota distance metrics, (as these may inflate statistical significance) by applying permutations tests. Regressing squared phenotypic difference on genetic distance is a standard way to estimate local or global heritability ( Haseman Elston, 1972 ; Visscher et al., 2006 ). It can be shown that estimates the narrow sense heritability . In these, is the least square regression coefficient and an estimate of the phenotypic variance. In our analyses, and following standard procedures (f.i. Rothschild et al., 2017), we used Bray-Curtis as distance measure for microbiota composition. For this metric, there is no corresponding individual phenotype p i per se . We therefore used simulations to translate the observed negative correlations in measures of heritability. For the within-generation/within-litter analyses, we first used the actual measures of kinship for all litter-mates computed with GEMMA ( Zhou Stephens, 2012 ) and corresponding to the x-axis in Fig. 3A . We standardized them (mean 0 and SD 1), scaled them (mean of 0.5 and SD 0.04, following Visscher et al., 2006 ) and multiplied them by h 2 (0.2, 0.4, 0.6, 0.8 or 1.0). We sampled “breeding values” from a multivariate normal distribution with means 0 and corresponding variance-covariance matrix using the mvrnorm R function. For each individual, we sampled an environmental effect from a normal distribution with mean 0 and variance (1 – h 2 ) using the rnorm R function. Breeding values and environmental effects were added to yield a phenotypic value p i for each individual. We then computed Spearman’s rank correlation between abs ( p i – p j ) and Θ ij for all pairs of litter mates i and j using the cor.test(method=”spearman”) R function. In this Θ ij is the kinship metric computed by GEMMA. We repeated the simulations 1,000 times. Suppl. Fig. 7A B show the distribution of the corresponding correlations ( r ) for the 12 data series and 5 values of h 2 . The black vertical line corresponds to zero. The red vertical line to the median of the simulations. It can be seen that as the heritability increases the value of the median decreases as expected. The green lines correspond to the corrected correlation ( r c ) obtained with the real data. A rough estimate of the heritability of the real trait (microbiota composition) was deduced from the coincidence between the red and green lines. As an example, the heritability of microbiome composition for data series F7-D120 was assumed to be close to 0.8. We proceeded in the same way for the across generation analysis ( Suppl. Fig. 7C ). We used the actual measur es of kinship across the F6 and F7 generations computed with GEMMA. We standardized them (mean 0 and SD 1), and then scaled them such that the values for an individual with itself would center on 1, and for full-sibs on 0.5. Breeding values and environmental effects were sampled using mvrnorm and rnorm as above. As the number of individuals is much higher in these analyses we only performed 100 simulations.

    Techniques Used: Gas Phase Electrophoretic Molecular Mobility Analysis

    10) Product Images from "Comprehensive evaluation of a cost-effective method of culturing Chlorella pyrenoidosa with unsterilized piggery wastewater for biofuel production"

    Article Title: Comprehensive evaluation of a cost-effective method of culturing Chlorella pyrenoidosa with unsterilized piggery wastewater for biofuel production

    Journal: Biotechnology for Biofuels

    doi: 10.1186/s13068-019-1407-x

    LEfSe analysis identified the most differentially abundant taxa between CA and PA. The taxonomic cladogram was obtained from LEfSe analysis of 16S rRNA sequences; only taxa meeting an LDA significance threshold of 4.0 are shown. Small circles and shading with different colors in the diagram represent the abundance of those taxa in the respective group. Yellow circles represent nonsignificant differences in abundance between CA and PA for that particular taxonomic group. The brightness of each dot is proportional to its effect size. Taxa enriched in PA are shown with a positive LDA score (green) and taxa enriched in CA have a negative score (red). CA means sparging air; PA means culturing C. pyrenoidosa with sparging air
    Figure Legend Snippet: LEfSe analysis identified the most differentially abundant taxa between CA and PA. The taxonomic cladogram was obtained from LEfSe analysis of 16S rRNA sequences; only taxa meeting an LDA significance threshold of 4.0 are shown. Small circles and shading with different colors in the diagram represent the abundance of those taxa in the respective group. Yellow circles represent nonsignificant differences in abundance between CA and PA for that particular taxonomic group. The brightness of each dot is proportional to its effect size. Taxa enriched in PA are shown with a positive LDA score (green) and taxa enriched in CA have a negative score (red). CA means sparging air; PA means culturing C. pyrenoidosa with sparging air

    Techniques Used: Sparging

    LEfSe analysis identified the most differentially abundant taxa between CC and PC. The taxonomic cladogram was obtained from LEfSe analysis of 16S rRNA sequences; only taxa meeting an LDA significance threshold of 4.0 are shown. Small circles and shading with different colors in the diagram represent the abundance of those taxa in the respective group. Yellow circles represent nonsignificant differences in abundance between CC and PC for that particular taxonomic group. The brightness of each dot is proportional to its effect size. Taxa enriched in PC are shown with a positive LDA score (green), and taxa enriched in CC have a negative score (red). CC means sparging simulated flue gas; PC means culturing C. pyrenoidosa with sparging simulated flue gas
    Figure Legend Snippet: LEfSe analysis identified the most differentially abundant taxa between CC and PC. The taxonomic cladogram was obtained from LEfSe analysis of 16S rRNA sequences; only taxa meeting an LDA significance threshold of 4.0 are shown. Small circles and shading with different colors in the diagram represent the abundance of those taxa in the respective group. Yellow circles represent nonsignificant differences in abundance between CC and PC for that particular taxonomic group. The brightness of each dot is proportional to its effect size. Taxa enriched in PC are shown with a positive LDA score (green), and taxa enriched in CC have a negative score (red). CC means sparging simulated flue gas; PC means culturing C. pyrenoidosa with sparging simulated flue gas

    Techniques Used: Sparging

    The absolute bacterial abundance based on 16S rRNA copies in unsterilized piggery wastewater. CA means sparging air, CC means sparging simulated flue gas, PA means culturing C. pyrenoidosa with sparging air, and PC means culturing C. pyrenoidosa with sparging simulated flue gas. Data are presented as the mean ± standard deviation of the mean. The different letters indicate that there was a significant difference with P
    Figure Legend Snippet: The absolute bacterial abundance based on 16S rRNA copies in unsterilized piggery wastewater. CA means sparging air, CC means sparging simulated flue gas, PA means culturing C. pyrenoidosa with sparging air, and PC means culturing C. pyrenoidosa with sparging simulated flue gas. Data are presented as the mean ± standard deviation of the mean. The different letters indicate that there was a significant difference with P

    Techniques Used: Sparging, Standard Deviation

    11) Product Images from "K-Selection as Microbial Community Management Strategy: A Method for Improved Viability of Larvae in Aquaculture"

    Article Title: K-Selection as Microbial Community Management Strategy: A Method for Improved Viability of Larvae in Aquaculture

    Journal: Frontiers in Microbiology

    doi: 10.3389/fmicb.2018.02730

    Effects of r- and K-selection on microbial community composition in four different experiments with different seawater inoculum. Each experimental group was sampled twice during the periods of r- and K-selection. r-selection was obtained by pulsing with resources for growth (organic and mineral nutrients), whereas K-selection was obtained by resource depletion and competition for more than 2 weeks. r-selected communities were sampled at days 1 and 2 after addition of resources, whereas K-selected communities were sampled on days 17 and 24. Microbial community composition was analysed by Illumina sequencing of 16S-rDNA amplicons. Unpublished results.
    Figure Legend Snippet: Effects of r- and K-selection on microbial community composition in four different experiments with different seawater inoculum. Each experimental group was sampled twice during the periods of r- and K-selection. r-selection was obtained by pulsing with resources for growth (organic and mineral nutrients), whereas K-selection was obtained by resource depletion and competition for more than 2 weeks. r-selected communities were sampled at days 1 and 2 after addition of resources, whereas K-selected communities were sampled on days 17 and 24. Microbial community composition was analysed by Illumina sequencing of 16S-rDNA amplicons. Unpublished results.

    Techniques Used: Selection, Sequencing

    12) Product Images from "Comparison of Nitrate and Perchlorate in Controlling Sulfidogenesis in Heavy Oil-Containing Bioreactors"

    Article Title: Comparison of Nitrate and Perchlorate in Controlling Sulfidogenesis in Heavy Oil-Containing Bioreactors

    Journal: Frontiers in Microbiology

    doi: 10.3389/fmicb.2018.02423

    Relational tree for 16S rRNA gene libraries from incubations of CSBK medium, inoculated with 18PW and amended with 1 mL MHGC oil and sulfate (SO); sulfate and nitrate (SNO); sulfate and perchlorate (PSO); sulfate, nitrate, and perchlorate (PSNO); or perchlorate only (PO). Community DNA was obtained from cells harvested at day 9, 65, 85, or 123 as indicated. The fractions of reads in classes of Proteobacteria (A) and in other phyla (B) are shown.
    Figure Legend Snippet: Relational tree for 16S rRNA gene libraries from incubations of CSBK medium, inoculated with 18PW and amended with 1 mL MHGC oil and sulfate (SO); sulfate and nitrate (SNO); sulfate and perchlorate (PSO); sulfate, nitrate, and perchlorate (PSNO); or perchlorate only (PO). Community DNA was obtained from cells harvested at day 9, 65, 85, or 123 as indicated. The fractions of reads in classes of Proteobacteria (A) and in other phyla (B) are shown.

    Techniques Used:

    Neighbor-joining phylogenetic tree indicating the affiliation of isolates PRB2 and PRB4 with members of the genus Magnetospirillum based on the 16S rRNA gene sequences. Branching points are determined as percentage of bootstrap values based on 1000 replications with those having a cut-off at 50% shown. The scale bar of 0.05 represents the fractional change per nucleotide. The sequence of Magnetococcus marinus MC-1 (NR_074371) was used as an outgroup.
    Figure Legend Snippet: Neighbor-joining phylogenetic tree indicating the affiliation of isolates PRB2 and PRB4 with members of the genus Magnetospirillum based on the 16S rRNA gene sequences. Branching points are determined as percentage of bootstrap values based on 1000 replications with those having a cut-off at 50% shown. The scale bar of 0.05 represents the fractional change per nucleotide. The sequence of Magnetococcus marinus MC-1 (NR_074371) was used as an outgroup.

    Techniques Used: Sequencing

    13) Product Images from "The metagenomic approach to characterization of the microbial community shift during the long-term cultivation of anammox-enriched granular sludge"

    Article Title: The metagenomic approach to characterization of the microbial community shift during the long-term cultivation of anammox-enriched granular sludge

    Journal: Journal of Applied Genetics

    doi: 10.1007/s13353-017-0418-1

    Family level affiliations assigned to contigs with 16S rRNA genes in analyzed samples. Only orders with abundance higher than 1.0% are given
    Figure Legend Snippet: Family level affiliations assigned to contigs with 16S rRNA genes in analyzed samples. Only orders with abundance higher than 1.0% are given

    Techniques Used:

    14) Product Images from "Anaerobic digestion of pig manure supernatant at high ammonia concentrations characterized by high abundances of Methanosaeta and non-euryarchaeotal archaea"

    Article Title: Anaerobic digestion of pig manure supernatant at high ammonia concentrations characterized by high abundances of Methanosaeta and non-euryarchaeotal archaea

    Journal: Scientific Reports

    doi: 10.1038/s41598-017-14527-1

    Relative abundances of bacterial classes ( A ) and archaeal genera ( B ) represented in the v3–4 16S rDNA amplicons obtained for individual reactor samples. Each bar represents one sample, and is labelled as follows: D indicates the experimental day; HA1 and HA2 refer to the two reactors operated at 3.7 ± 0.2 g NH 4 -N L −1 , and LA1, and LA2 refers to the reactors operated at 1.9 ± 0.2 g NH 4 -N L −1 . OTUs that could not be classified at the domain level are labeled “Unclassified”, while OTUs that could not be classified at class or genus level for bacteria and archaea, respectively, are labeled *. Only taxa represented by a portion of ≥1% of the sequence reads in at least one of the samples are shown. “Others” include all reads representing the taxa with
    Figure Legend Snippet: Relative abundances of bacterial classes ( A ) and archaeal genera ( B ) represented in the v3–4 16S rDNA amplicons obtained for individual reactor samples. Each bar represents one sample, and is labelled as follows: D indicates the experimental day; HA1 and HA2 refer to the two reactors operated at 3.7 ± 0.2 g NH 4 -N L −1 , and LA1, and LA2 refers to the reactors operated at 1.9 ± 0.2 g NH 4 -N L −1 . OTUs that could not be classified at the domain level are labeled “Unclassified”, while OTUs that could not be classified at class or genus level for bacteria and archaea, respectively, are labeled *. Only taxa represented by a portion of ≥1% of the sequence reads in at least one of the samples are shown. “Others” include all reads representing the taxa with

    Techniques Used: Labeling, Sequencing

    15) Product Images from "Acute porcine epidemic diarrhea virus infection reshapes the intestinal microbiota"

    Article Title: Acute porcine epidemic diarrhea virus infection reshapes the intestinal microbiota

    Journal: Virology

    doi: 10.1016/j.virol.2020.07.001

    PEDV infection affects the intestinal microbiota of piglets. (A) PCoA analysis of the relative abundance of intestinal bacterial distribution after PEDV infection. (The 16S rRNA data from uninfected pigs is the same as in Fig. 1 , Fig. 2 .) (B) The bacterial distribution diagram at the level of the genus. The changes of intestinal microbe in 1-week-old (C) and 2-week-old piglets (D) were analyzed by LEfSe. (E) Absolute numbers of intestinal microbe in 1-week-old and 2-week-old piglets.
    Figure Legend Snippet: PEDV infection affects the intestinal microbiota of piglets. (A) PCoA analysis of the relative abundance of intestinal bacterial distribution after PEDV infection. (The 16S rRNA data from uninfected pigs is the same as in Fig. 1 , Fig. 2 .) (B) The bacterial distribution diagram at the level of the genus. The changes of intestinal microbe in 1-week-old (C) and 2-week-old piglets (D) were analyzed by LEfSe. (E) Absolute numbers of intestinal microbe in 1-week-old and 2-week-old piglets.

    Techniques Used: Infection

    Analysis of intestinal microbe in different segments in the small intestine of healthy piglets. Intestinal contents from duodenum, jejunum, and ileum of 1-week-old, 2-week-old, and 4-week-old healthy piglets were collected and subjected to 16S rRNA sequencing. (A) NMDS analysis of the relative abundance of microbe in duodenum, jejunum, and ileum from a different age of piglets. (B) Shannon index of microbial diversity in duodenum, jejunum, and ileum from a different age of piglets. (C) Heatmap of bacterial distribution in the level of phylum.
    Figure Legend Snippet: Analysis of intestinal microbe in different segments in the small intestine of healthy piglets. Intestinal contents from duodenum, jejunum, and ileum of 1-week-old, 2-week-old, and 4-week-old healthy piglets were collected and subjected to 16S rRNA sequencing. (A) NMDS analysis of the relative abundance of microbe in duodenum, jejunum, and ileum from a different age of piglets. (B) Shannon index of microbial diversity in duodenum, jejunum, and ileum from a different age of piglets. (C) Heatmap of bacterial distribution in the level of phylum.

    Techniques Used: Sequencing

    16) Product Images from "Changes in rhizosphere bacterial communities during remediation of heavy metal-accumulating plants around the Xikuangshan mine in southern China"

    Article Title: Changes in rhizosphere bacterial communities during remediation of heavy metal-accumulating plants around the Xikuangshan mine in southern China

    Journal: Scientific Reports

    doi: 10.1038/s41598-018-38360-2

    Number of sequences analyzed and diversity/richness indices of the 16S rRNA bacterial libraries obtained from clustering at 97% identity.
    Figure Legend Snippet: Number of sequences analyzed and diversity/richness indices of the 16S rRNA bacterial libraries obtained from clustering at 97% identity.

    Techniques Used:

    17) Product Images from "Cutaneous leishmaniasis induces a transmissible dysbiotic skin microbiota that promotes skin inflammation"

    Article Title: Cutaneous leishmaniasis induces a transmissible dysbiotic skin microbiota that promotes skin inflammation

    Journal: Cell host & microbe

    doi: 10.1016/j.chom.2017.06.006

    Skin microbiota alterations in L. major infection are dependent on disease severity C57BL/6 and BALB/c mice were intradermally infected with L. major parasites. Lesional severity was assessed by (A) ear thickness and (B) a pathology score over the course of infection. Swabs for sequencing of 16S rRNA genes were collected from the lesions at 0 and 6 weeks post-infection. (C) Alpha diversity was assessed by Shannon Index. (D) Stacked bar charts represent the proportion of the top 10 taxa present in each sample. Data are representative of two independent experiments (n = 1 skin swab each from 10 mice in each group). C57BL/6 mice were treated with an isotype or anti-IL-12 mAb and intradermally infected in the ear with L. major parasites. Lesional severity was assessed by (E) ear thickness and (F) a pathology score over the course of infection. Anti-IL-12 mAb treated mice were euthanized at 6 weeks post-infection due to severe disease. (G) Swabs were collected from the lesions at 2, 4 and 6 weeks post-infection and proportions of Staphylococcus and Streptococcus .
    Figure Legend Snippet: Skin microbiota alterations in L. major infection are dependent on disease severity C57BL/6 and BALB/c mice were intradermally infected with L. major parasites. Lesional severity was assessed by (A) ear thickness and (B) a pathology score over the course of infection. Swabs for sequencing of 16S rRNA genes were collected from the lesions at 0 and 6 weeks post-infection. (C) Alpha diversity was assessed by Shannon Index. (D) Stacked bar charts represent the proportion of the top 10 taxa present in each sample. Data are representative of two independent experiments (n = 1 skin swab each from 10 mice in each group). C57BL/6 mice were treated with an isotype or anti-IL-12 mAb and intradermally infected in the ear with L. major parasites. Lesional severity was assessed by (E) ear thickness and (F) a pathology score over the course of infection. Anti-IL-12 mAb treated mice were euthanized at 6 weeks post-infection due to severe disease. (G) Swabs were collected from the lesions at 2, 4 and 6 weeks post-infection and proportions of Staphylococcus and Streptococcus .

    Techniques Used: Infection, Mouse Assay, Sequencing

    L. major induced dysbiosis is transmissible to uninfected skin (A) C57BL/6 mice were intradermally infected with L. major and swabs were collected from the infected and contralateral ears at 6 weeks post-infected for 16S rRNA gene analysis. Stacked bar charts represent the proportion of the top 10 taxa present in each sample. Data are representative of three independent experiments (n = 1 swab of each ear from 15 mice). (B) Swabs from naïve or L. major infected C57BL/6 mice were cultured on mannitol salt agar plates and CFUs were counted to determine bacteria burden. Data are representative of 1 experiment (For naïve group, n = 1 swab from the ear of 10 mice; for infected and contralateral ears, n = 1 swab of each ear from 12 mice). (C) Naïve C57BL/6 mice were co-housed with L. major .
    Figure Legend Snippet: L. major induced dysbiosis is transmissible to uninfected skin (A) C57BL/6 mice were intradermally infected with L. major and swabs were collected from the infected and contralateral ears at 6 weeks post-infected for 16S rRNA gene analysis. Stacked bar charts represent the proportion of the top 10 taxa present in each sample. Data are representative of three independent experiments (n = 1 swab of each ear from 15 mice). (B) Swabs from naïve or L. major infected C57BL/6 mice were cultured on mannitol salt agar plates and CFUs were counted to determine bacteria burden. Data are representative of 1 experiment (For naïve group, n = 1 swab from the ear of 10 mice; for infected and contralateral ears, n = 1 swab of each ear from 12 mice). (C) Naïve C57BL/6 mice were co-housed with L. major .

    Techniques Used: Mouse Assay, Infection, Cell Culture

    18) Product Images from "The Cyanobacteria-Dominated Sponge Dactylospongia elegans in the South China Sea: Prokaryotic Community and Metagenomic Insights"

    Article Title: The Cyanobacteria-Dominated Sponge Dactylospongia elegans in the South China Sea: Prokaryotic Community and Metagenomic Insights

    Journal: Frontiers in Microbiology

    doi: 10.3389/fmicb.2017.01387

    Taxonomic abundance of microbial reads in sponges and seawater at the phylum level. Microbial reads of 16S rRNA gene amplicons were assigned taxonomically using the RDP classifier against the SILVA 111 database with a confidence threshold of 50%. Sample IDs are referred to Table 1 .
    Figure Legend Snippet: Taxonomic abundance of microbial reads in sponges and seawater at the phylum level. Microbial reads of 16S rRNA gene amplicons were assigned taxonomically using the RDP classifier against the SILVA 111 database with a confidence threshold of 50%. Sample IDs are referred to Table 1 .

    Techniques Used:

    Phylogenetic tree of representative highly abundant OTUs and their relatives. The tree was constructed based on partial 16S rRNA gene sequences by the neighbor-joining method. Bootstrap values are expressed based on 1,000 replications, and only values more than 50% are shown. Bar, 5% estimated sequences divergence. The abundance of OTUs included on the tree are shown in Figure 3 . The brackets including “G” indicates strains with reported genomes.
    Figure Legend Snippet: Phylogenetic tree of representative highly abundant OTUs and their relatives. The tree was constructed based on partial 16S rRNA gene sequences by the neighbor-joining method. Bootstrap values are expressed based on 1,000 replications, and only values more than 50% are shown. Bar, 5% estimated sequences divergence. The abundance of OTUs included on the tree are shown in Figure 3 . The brackets including “G” indicates strains with reported genomes.

    Techniques Used: Construct

    19) Product Images from "An improved dual-indexing approach for multiplexed 16S rRNA gene sequencing on the Illumina MiSeq platform"

    Article Title: An improved dual-indexing approach for multiplexed 16S rRNA gene sequencing on the Illumina MiSeq platform

    Journal: Microbiome

    doi: 10.1186/2049-2618-2-6

    Dual-indexed 16S rRNA gene PCR amplification strategy with heterogeneity spacer primers for sequencing on the MiSeq platform. (A) Dual-indexed PCR amplification primers targeting the V3-V4 hypervariable regions of the 16S rRNA gene contain a heterogeneity spacer region and linker sequence optimized for sequencing on the Illumina MiSeq platform. Using this approach enables sequencing using the standard Illumina HP10 and HP11 sequencing primers allowing for additional sequencing flexibility. (B) Schematic showing the first thirty sequencing cycles of eight mock amplicons prepared using the dual-indexed approach. This diagram illustrates how the index sequence and heterogeneity spacer (colored letters, white background) helps to alleviate the “low sequence diversity” issue associated with the MiSeq platform by creating a more even base composition at each cycle of the run.
    Figure Legend Snippet: Dual-indexed 16S rRNA gene PCR amplification strategy with heterogeneity spacer primers for sequencing on the MiSeq platform. (A) Dual-indexed PCR amplification primers targeting the V3-V4 hypervariable regions of the 16S rRNA gene contain a heterogeneity spacer region and linker sequence optimized for sequencing on the Illumina MiSeq platform. Using this approach enables sequencing using the standard Illumina HP10 and HP11 sequencing primers allowing for additional sequencing flexibility. (B) Schematic showing the first thirty sequencing cycles of eight mock amplicons prepared using the dual-indexed approach. This diagram illustrates how the index sequence and heterogeneity spacer (colored letters, white background) helps to alleviate the “low sequence diversity” issue associated with the MiSeq platform by creating a more even base composition at each cycle of the run.

    Techniques Used: Polymerase Chain Reaction, Amplification, Sequencing

    20) Product Images from "Microbial Functional Responses to Cholesterol Catabolism in Denitrifying Sludge"

    Article Title: Microbial Functional Responses to Cholesterol Catabolism in Denitrifying Sludge

    Journal: mSystems

    doi: 10.1128/mSystems.00113-18

    (A) Maximum likelihood tree of 16S rRNA gene of steroid-degrading anaerobes and Sterolibacterium -like OTUs. Only enriched OTUs are highlighted. (B) AtcA and its homologues and other molybdopterin-containing xanthine oxidase family members. (C) Alpha subunit of C25DH and its homologues. Subunits (A1 to A4) displaying specificity for side chain substrates are highlighted in blue. Branch support of higher than 50% of bootstrapping time is shown. Details for all reference sequences are provided in Table S3 .
    Figure Legend Snippet: (A) Maximum likelihood tree of 16S rRNA gene of steroid-degrading anaerobes and Sterolibacterium -like OTUs. Only enriched OTUs are highlighted. (B) AtcA and its homologues and other molybdopterin-containing xanthine oxidase family members. (C) Alpha subunit of C25DH and its homologues. Subunits (A1 to A4) displaying specificity for side chain substrates are highlighted in blue. Branch support of higher than 50% of bootstrapping time is shown. Details for all reference sequences are provided in Table S3 .

    Techniques Used:

    21) Product Images from "Cecal microbiota of Tibetan Chickens from five geographic regions were determined by 16S rRNA sequencing"

    Article Title: Cecal microbiota of Tibetan Chickens from five geographic regions were determined by 16S rRNA sequencing

    Journal: MicrobiologyOpen

    doi: 10.1002/mbo3.367

    Denaturing gradient gel electrophoresis band profiles of the V3 region of 16S rRNA produced from the cecal bacterial communities of seven types of chicken. LM , Lohmann laying hens; DH , Daheng broiler chickens; LS , Lhasa Tibetan Chicken; GZ , Ganzi Tibetan Chicken; AB , Aba Tibetan Chicken; QH , Qinghai Tibetan Chicken; and DQ , Diqing Tibetan Chicken.
    Figure Legend Snippet: Denaturing gradient gel electrophoresis band profiles of the V3 region of 16S rRNA produced from the cecal bacterial communities of seven types of chicken. LM , Lohmann laying hens; DH , Daheng broiler chickens; LS , Lhasa Tibetan Chicken; GZ , Ganzi Tibetan Chicken; AB , Aba Tibetan Chicken; QH , Qinghai Tibetan Chicken; and DQ , Diqing Tibetan Chicken.

    Techniques Used: Denaturing Gradient Gel Electrophoresis, Produced

    22) Product Images from "A prevalent and culturable microbiota links ecological balance to clinical stability of the human lung after transplantation"

    Article Title: A prevalent and culturable microbiota links ecological balance to clinical stability of the human lung after transplantation

    Journal: Nature Communications

    doi: 10.1038/s41467-021-22344-4

    Combining BALF amplicon sequencing and bacterial culturing to deduce the microbial ecology of deep lung microbiota. a Schematic of the sampling of Bronchoalveolar lavage fluid (BALF) from lung transplant recipients over time (months post-transplant). b Relative abundances (%) of most abundant phyla across BALF samples. Box plots show median (middle line), 25th, 75th percentile (box) and 5th and 95th percentile (whiskers) as well as outliers (single points). c Prevalence (% samples) vs contribution to total reads across samples for most abundant phyla. Dot color shows different genera and size show total rarefied reads. Gray dashed horizontal line shows prevalence ≥50%. d Scatter plot shows correlation between number of observed OTUs and bacterial counts per BALF sample obtained by quantifying 16S rRNA gene copies with qPCR. Linear regression is shown by the blue line with gray shaded area showing 95% confidence interval ( n = 234, two-sided, F (1, 232) = 91.04, P = 2.2 × 10 −16 ), Coefficient of correlation; R 2 = 0.28. e Bar chart shows lung taxa (genera; OTU IDs) that contributed ≥75% of total bacterial biomass across samples ( n = 234). Venn diagram inset shows overlap (yellow) between the most prevalent (≥50% incidence, light blue) and the most abundant (≥75% total count, red) taxa in the transplanted lung. Bar colors also show the same.
    Figure Legend Snippet: Combining BALF amplicon sequencing and bacterial culturing to deduce the microbial ecology of deep lung microbiota. a Schematic of the sampling of Bronchoalveolar lavage fluid (BALF) from lung transplant recipients over time (months post-transplant). b Relative abundances (%) of most abundant phyla across BALF samples. Box plots show median (middle line), 25th, 75th percentile (box) and 5th and 95th percentile (whiskers) as well as outliers (single points). c Prevalence (% samples) vs contribution to total reads across samples for most abundant phyla. Dot color shows different genera and size show total rarefied reads. Gray dashed horizontal line shows prevalence ≥50%. d Scatter plot shows correlation between number of observed OTUs and bacterial counts per BALF sample obtained by quantifying 16S rRNA gene copies with qPCR. Linear regression is shown by the blue line with gray shaded area showing 95% confidence interval ( n = 234, two-sided, F (1, 232) = 91.04, P = 2.2 × 10 −16 ), Coefficient of correlation; R 2 = 0.28. e Bar chart shows lung taxa (genera; OTU IDs) that contributed ≥75% of total bacterial biomass across samples ( n = 234). Venn diagram inset shows overlap (yellow) between the most prevalent (≥50% incidence, light blue) and the most abundant (≥75% total count, red) taxa in the transplanted lung. Bar colors also show the same.

    Techniques Used: Amplification, Sequencing, Sampling, Real-time Polymerase Chain Reaction

    23) Product Images from "Impact of DNA Sequencing and Analysis Methods on 16S rRNA Gene Bacterial Community Analysis of Dairy Products"

    Article Title: Impact of DNA Sequencing and Analysis Methods on 16S rRNA Gene Bacterial Community Analysis of Dairy Products

    Journal: mSphere

    doi: 10.1128/mSphere.00410-18

    Relative abundance of taxa in the 16S rRNA PCR amplicon and gDNA mock communities. Relative abundances of expected taxa are labeled with the corresponding taxonomic level from sequencing results. “Amplicon” represents the 16S rRNA PCR amplicon mock community, and “gDNA” represents the gDNA mock community. The results shown were analyzed following the DADA2 pipeline with the Greengenes database. Each bar represents the mean ± SD from three replicates. Proportions for each community were compared to expected proportions using ANOVA with Bonferroni’s multiple-comparison test. P values of
    Figure Legend Snippet: Relative abundance of taxa in the 16S rRNA PCR amplicon and gDNA mock communities. Relative abundances of expected taxa are labeled with the corresponding taxonomic level from sequencing results. “Amplicon” represents the 16S rRNA PCR amplicon mock community, and “gDNA” represents the gDNA mock community. The results shown were analyzed following the DADA2 pipeline with the Greengenes database. Each bar represents the mean ± SD from three replicates. Proportions for each community were compared to expected proportions using ANOVA with Bonferroni’s multiple-comparison test. P values of

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

    24) Product Images from "Sialylated milk oligosaccharides promote microbiota-dependent growth in models of infant undernutrition"

    Article Title: Sialylated milk oligosaccharides promote microbiota-dependent growth in models of infant undernutrition

    Journal: Cell

    doi: 10.1016/j.cell.2016.01.024

    Cultured bacterial strain collection generated from the fecal microbiota of a 6-month old stunted Malawian infant ( A ) Taxonomic representation of 97% ID OTUs in the intact, uncultured infant fecal sample from which the culture collection was generated. ( B ) Comparison of culture collection strains and representative type strains. Black dots indicate percent identity between full-length 16S rRNA gene sequences from each strain and its most similar reference type strain’s 16S rRNA sequence. Bars indicate percent nucleotide sequence similarity between the strain’s de novo assembled genome and its most similar type strain’s genome. Strains are clustered by Euclidean distance between full-length 16S rRNA gene sequences. ( C .
    Figure Legend Snippet: Cultured bacterial strain collection generated from the fecal microbiota of a 6-month old stunted Malawian infant ( A ) Taxonomic representation of 97% ID OTUs in the intact, uncultured infant fecal sample from which the culture collection was generated. ( B ) Comparison of culture collection strains and representative type strains. Black dots indicate percent identity between full-length 16S rRNA gene sequences from each strain and its most similar reference type strain’s 16S rRNA sequence. Bars indicate percent nucleotide sequence similarity between the strain’s de novo assembled genome and its most similar type strain’s genome. Strains are clustered by Euclidean distance between full-length 16S rRNA gene sequences. ( C .

    Techniques Used: Cell Culture, Generated, Sequencing

    25) Product Images from "Anaerobic digestion of pig manure supernatant at high ammonia concentrations characterized by high abundances of Methanosaeta and non-euryarchaeotal archaea"

    Article Title: Anaerobic digestion of pig manure supernatant at high ammonia concentrations characterized by high abundances of Methanosaeta and non-euryarchaeotal archaea

    Journal: Scientific Reports

    doi: 10.1038/s41598-017-14527-1

    Relative abundances of bacterial classes ( A ) and archaeal genera ( B ) represented in the v3–4 16S rDNA amplicons obtained for individual reactor samples. Each bar represents one sample, and is labelled as follows: D indicates the experimental day; HA1 and HA2 refer to the two reactors operated at 3.7 ± 0.2 g NH 4 -N L −1 , and LA1, and LA2 refers to the reactors operated at 1.9 ± 0.2 g NH 4 -N L −1 . OTUs that could not be classified at the domain level are labeled “Unclassified”, while OTUs that could not be classified at class or genus level for bacteria and archaea, respectively, are labeled *. Only taxa represented by a portion of ≥1% of the sequence reads in at least one of the samples are shown. “Others” include all reads representing the taxa with
    Figure Legend Snippet: Relative abundances of bacterial classes ( A ) and archaeal genera ( B ) represented in the v3–4 16S rDNA amplicons obtained for individual reactor samples. Each bar represents one sample, and is labelled as follows: D indicates the experimental day; HA1 and HA2 refer to the two reactors operated at 3.7 ± 0.2 g NH 4 -N L −1 , and LA1, and LA2 refers to the reactors operated at 1.9 ± 0.2 g NH 4 -N L −1 . OTUs that could not be classified at the domain level are labeled “Unclassified”, while OTUs that could not be classified at class or genus level for bacteria and archaea, respectively, are labeled *. Only taxa represented by a portion of ≥1% of the sequence reads in at least one of the samples are shown. “Others” include all reads representing the taxa with

    Techniques Used: Labeling, Sequencing

    26) Product Images from "Reduced Epithelial Na+/H+ Exchange Drives Gut Microbial Dysbiosis and Promotes Inflammatory Response in T Cell-Mediated Murine Colitis"

    Article Title: Reduced Epithelial Na+/H+ Exchange Drives Gut Microbial Dysbiosis and Promotes Inflammatory Response in T Cell-Mediated Murine Colitis

    Journal: PLoS ONE

    doi: 10.1371/journal.pone.0152044

    PICRUSt prediction of functional profiling of the microbial communities based on the 16S rRNA gene sequences. Extended error bar plot indicating differences in functional profiles of the Rag+AT and DKO+AT microbiota (at taxonomic Level 3). All unclassified reads were removed and categories with minimum of 20 reads, and P value greater than 0.01 is displayed. Categories are sorted by P value calculated using two-sided Welch’s t-test.
    Figure Legend Snippet: PICRUSt prediction of functional profiling of the microbial communities based on the 16S rRNA gene sequences. Extended error bar plot indicating differences in functional profiles of the Rag+AT and DKO+AT microbiota (at taxonomic Level 3). All unclassified reads were removed and categories with minimum of 20 reads, and P value greater than 0.01 is displayed. Categories are sorted by P value calculated using two-sided Welch’s t-test.

    Techniques Used: Functional Assay

    27) Product Images from "High-Throughput 16S rRNA Sequencing to Assess Potentially Active Bacteria and Foodborne Pathogens: A Case Example in Ready-to-Eat Food"

    Article Title: High-Throughput 16S rRNA Sequencing to Assess Potentially Active Bacteria and Foodborne Pathogens: A Case Example in Ready-to-Eat Food

    Journal: Foods

    doi: 10.3390/foods8100480

    Principal component analysis (PcoA) of bacterial community structure at the genus level from the analysed RTE salads. The PcoA was performed with “qiime tool collapse” at the desired taxa level using the Euclidean metric to calculate the matrix distance. Samples from total bacterial cells (dormant, dead, and active cells containing 16S rDNA genes) and metabolically active bacteria (cells containing ribosomal RNA, 16S rRNA) are depicted in red and blue colors, respectively. Two close samples in the PcoA indicated that they had similar bacterial species composition and relative abundances of taxa. Although no major differences were observed regarding the abundant bacterial species composition, significant differences in relative abundances were observed (see Figure 2 ), especially for those low abundant species.
    Figure Legend Snippet: Principal component analysis (PcoA) of bacterial community structure at the genus level from the analysed RTE salads. The PcoA was performed with “qiime tool collapse” at the desired taxa level using the Euclidean metric to calculate the matrix distance. Samples from total bacterial cells (dormant, dead, and active cells containing 16S rDNA genes) and metabolically active bacteria (cells containing ribosomal RNA, 16S rRNA) are depicted in red and blue colors, respectively. Two close samples in the PcoA indicated that they had similar bacterial species composition and relative abundances of taxa. Although no major differences were observed regarding the abundant bacterial species composition, significant differences in relative abundances were observed (see Figure 2 ), especially for those low abundant species.

    Techniques Used: Metabolic Labelling

    Workflow of the molecular approach (DNA- and RNA-based) used to characterize the bacterial community and the active bacterial fraction in the studied RTE salads. Electrophoresis shows the PCR and RT-PCR results of the 16S rDNA/rRNA. PCR control of undigested 16S rDNA genes is shown. C+: positive control of PCR and RT-PCR; C-: negative control of PCR and RT-PCR; L: ladder indicating the size (bp). Lanes marked as S1, S2, and S3 correspond to the analyzed RTE samples.
    Figure Legend Snippet: Workflow of the molecular approach (DNA- and RNA-based) used to characterize the bacterial community and the active bacterial fraction in the studied RTE salads. Electrophoresis shows the PCR and RT-PCR results of the 16S rDNA/rRNA. PCR control of undigested 16S rDNA genes is shown. C+: positive control of PCR and RT-PCR; C-: negative control of PCR and RT-PCR; L: ladder indicating the size (bp). Lanes marked as S1, S2, and S3 correspond to the analyzed RTE samples.

    Techniques Used: Electrophoresis, Polymerase Chain Reaction, Reverse Transcription Polymerase Chain Reaction, Positive Control, Negative Control

    High-throughput sequencing data of 16S rDNA and rRNA from RTE salads. Taxonomic assignment of reads at the phylum and genus level is shown. From each RTE salad brand, taxonomic assignment data from total bacterial cells (dormant, dead, and active cells containing 16S rDNA genes) and metabolically active bacteria (cells containing ribosomal RNA, 16S rRNA) is indicated as “DNA” and “RNA”, respectively. Those low abundant genera that showed
    Figure Legend Snippet: High-throughput sequencing data of 16S rDNA and rRNA from RTE salads. Taxonomic assignment of reads at the phylum and genus level is shown. From each RTE salad brand, taxonomic assignment data from total bacterial cells (dormant, dead, and active cells containing 16S rDNA genes) and metabolically active bacteria (cells containing ribosomal RNA, 16S rRNA) is indicated as “DNA” and “RNA”, respectively. Those low abundant genera that showed

    Techniques Used: Next-Generation Sequencing, Metabolic Labelling

    28) Product Images from "Synergism of gut microbiota to double-stranded RNAs in RNA interference of a leaf beetle"

    Article Title: Synergism of gut microbiota to double-stranded RNAs in RNA interference of a leaf beetle

    Journal: bioRxiv

    doi: 10.1101/824581

    Ingestion of dsRNA alters gut microbiota composition of P. versicolora . ( a ) Principal co-ordinates analysis (PCoA) of Bray-Curtis distances at the genus level for 16S rRNA gene sequences. ( b ) Typing analysis of Jensen-Shannon divergence distance at the OTU level for 16S rRNA gene sequence data. ( c ) Kruskal-Wallis H test bar plot analysis of the relative proportions of major genera of gut bacteria. The relative abundances of the identified microbial taxa were determined in gut samples collected from larvae fed with ds GFP, ds Srp54k , ds Actin , or H 2 O. P -values were calculated using the Kruskal-Wallis H test. ** P
    Figure Legend Snippet: Ingestion of dsRNA alters gut microbiota composition of P. versicolora . ( a ) Principal co-ordinates analysis (PCoA) of Bray-Curtis distances at the genus level for 16S rRNA gene sequences. ( b ) Typing analysis of Jensen-Shannon divergence distance at the OTU level for 16S rRNA gene sequence data. ( c ) Kruskal-Wallis H test bar plot analysis of the relative proportions of major genera of gut bacteria. The relative abundances of the identified microbial taxa were determined in gut samples collected from larvae fed with ds GFP, ds Srp54k , ds Actin , or H 2 O. P -values were calculated using the Kruskal-Wallis H test. ** P

    Techniques Used: Sequencing

    Ingestion of dsRNA promotes the growth of gut bacteria in P. versicolora larvae. qRT-PCR analyses were performed to determine the relative abundance of gut bacteria in P. versicolora larvae fed with ds GFP ( a ), ds Srp54k ( b ) and ds Actin ( c ) (n = 5), and the abundances of three major bacterial genera in non-axenic P. versicolora larvae fed with ds GFP ( d ), ds Srp54k ( e ) and ds Actin ( f ). The measurements were performed at different time points (after 2-5 days of feeding). The qRT-PCR value obtained for gut bacterial 16S rRNA in P. versicolora control larvae (fed with water-treated leaves) was set as 1.0. P -values were calculated using the independent-samples t -test. Data are presented as means ± SE, *** P
    Figure Legend Snippet: Ingestion of dsRNA promotes the growth of gut bacteria in P. versicolora larvae. qRT-PCR analyses were performed to determine the relative abundance of gut bacteria in P. versicolora larvae fed with ds GFP ( a ), ds Srp54k ( b ) and ds Actin ( c ) (n = 5), and the abundances of three major bacterial genera in non-axenic P. versicolora larvae fed with ds GFP ( d ), ds Srp54k ( e ) and ds Actin ( f ). The measurements were performed at different time points (after 2-5 days of feeding). The qRT-PCR value obtained for gut bacterial 16S rRNA in P. versicolora control larvae (fed with water-treated leaves) was set as 1.0. P -values were calculated using the independent-samples t -test. Data are presented as means ± SE, *** P

    Techniques Used: Quantitative RT-PCR

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    16s Rrna Gene Library Preparation, supplied by Illumina Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Illumina Inc 16s rrna gene amplicon paired end sequencing
    Distribution of sequence lengths for matching barcodes. Once all the forward and reverse reads from the Illumina sequencer are joined one can see – in gray here – a pattern in the size of the fragments produced. Superposing in red the abundance of length variation found in the SILVAMOD database, one can see that the variation we uncovered follows closely the natural variation of the V3–V4 region of the <t>16S</t> <t>rRNA</t> gene. As shown in Fig. 3 , each of the three peaks are composed of characteristic phyla.
    16s Rrna Gene Amplicon Paired End Sequencing, supplied by Illumina Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/16s rrna gene amplicon paired end sequencing/product/Illumina Inc
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    16s rrna gene amplicon paired end sequencing - by Bioz Stars, 2021-07
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    Illumina Inc 16s rrna gene
    Affiliation of the sequences of the 14 bacterial strains showing the best PGP traits with the existing <t>16S</t> <t>rRNA</t> gene sequences. Phylogenetic analysis was inferred by using the Neighbor-Joining method. The evolutionary distances were computed using the Tamura 3-parameter method. The rate variation among sites was modeled with a gamma distribution (shape parameter = 1). Bootstrap (1,000 replicates) values below 70 are not shown. Evolutionary analyses were conducted in MEGA10.
    16s Rrna Gene, supplied by Illumina Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/16s rrna gene/product/Illumina Inc
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    16s rrna gene - by Bioz Stars, 2021-07
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    Illumina Inc 16s rrna gene based amplicon sequencing
    Dynamics of OTUs that displayed relative abundances above 5% of the bacterial community over the experimental period in the four reactors operated with synthetic urine (UR-K and UR-Na) and synthetic wastewater (WWR-K and WWR-Na). Their relative abundances and closest neighbors were retrieved from the high-resolution MiSeq data sets of <t>16S</t> <t>rRNA</t> gene-based <t>amplicon</t> sequencing and after mapping against MIDAS. These phylotypes were identified at family ( -aceae suffix) and genus levels.
    16s Rrna Gene Based Amplicon Sequencing, supplied by Illumina Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/16s rrna gene based amplicon sequencing/product/Illumina Inc
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    Image Search Results


    The bacterial populations derived from 16S rRNA sequence classification for the indicated eye swab pools. The populations are displayed aggregated and colored at the taxonomic class and phylum levels, respectively.

    Journal: Frontiers in Veterinary Science

    Article Title: Chlamydia pecorum Associated With an Outbreak of Infectious Keratoconjunctivitis in Semi-domesticated Reindeer in Sweden

    doi: 10.3389/fvets.2019.00014

    Figure Lengend Snippet: The bacterial populations derived from 16S rRNA sequence classification for the indicated eye swab pools. The populations are displayed aggregated and colored at the taxonomic class and phylum levels, respectively.

    Article Snippet: 16S rRNA Gene Library Preparation and NGS Amplicon Sequencing Libraries of a ca 460 nt long amplicon carrying the variable V3 and V4 regions of the 16S ribosomal RNA gene were obtained according to the protocol 16S Metagenomic Sequencing Library Preparation (Rev.B) recommended and applied for the Illumina MiSeq System (Illumina Inc, San Diego).

    Techniques: Derivative Assay, Sequencing

    A maximum likelihood phylogenetic tree based on alignment of a 427 nucleotides segment of the 16S rRNA gene V3 and V4 variable regions was inferred using the HKY model of sequence evolution. Bootstrap support values > 50 percent obtained from 1,000 replications are indicated next to the relevant nodes. Sequences for the reference Chlamydia species obtained by discontinuous BLASTn searches against the NCBI GenBank database were aligned with the reindeer Chlamydia 16S rRNA gene sequence generated in this study, using the CLC genomics workbench algorithm in the slow and very accurate mode. The P787 (CP004035.1) and W73 (CP004034.1) C. pecorum strains, both isolated from sheep, are identical to the C. pecorum reindeer identified from six DNA pools of 12 animals with clinical signs of IKC in this study, across the gene regions characterized.

    Journal: Frontiers in Veterinary Science

    Article Title: Chlamydia pecorum Associated With an Outbreak of Infectious Keratoconjunctivitis in Semi-domesticated Reindeer in Sweden

    doi: 10.3389/fvets.2019.00014

    Figure Lengend Snippet: A maximum likelihood phylogenetic tree based on alignment of a 427 nucleotides segment of the 16S rRNA gene V3 and V4 variable regions was inferred using the HKY model of sequence evolution. Bootstrap support values > 50 percent obtained from 1,000 replications are indicated next to the relevant nodes. Sequences for the reference Chlamydia species obtained by discontinuous BLASTn searches against the NCBI GenBank database were aligned with the reindeer Chlamydia 16S rRNA gene sequence generated in this study, using the CLC genomics workbench algorithm in the slow and very accurate mode. The P787 (CP004035.1) and W73 (CP004034.1) C. pecorum strains, both isolated from sheep, are identical to the C. pecorum reindeer identified from six DNA pools of 12 animals with clinical signs of IKC in this study, across the gene regions characterized.

    Article Snippet: 16S rRNA Gene Library Preparation and NGS Amplicon Sequencing Libraries of a ca 460 nt long amplicon carrying the variable V3 and V4 regions of the 16S ribosomal RNA gene were obtained according to the protocol 16S Metagenomic Sequencing Library Preparation (Rev.B) recommended and applied for the Illumina MiSeq System (Illumina Inc, San Diego).

    Techniques: Sequencing, Generated, Isolation

    Distribution of sequence lengths for matching barcodes. Once all the forward and reverse reads from the Illumina sequencer are joined one can see – in gray here – a pattern in the size of the fragments produced. Superposing in red the abundance of length variation found in the SILVAMOD database, one can see that the variation we uncovered follows closely the natural variation of the V3–V4 region of the 16S rRNA gene. As shown in Fig. 3 , each of the three peaks are composed of characteristic phyla.

    Journal: PLoS ONE

    Article Title: Microbial Community Composition and Diversity via 16S rRNA Gene Amplicons: Evaluating the Illumina Platform

    doi: 10.1371/journal.pone.0116955

    Figure Lengend Snippet: Distribution of sequence lengths for matching barcodes. Once all the forward and reverse reads from the Illumina sequencer are joined one can see – in gray here – a pattern in the size of the fragments produced. Superposing in red the abundance of length variation found in the SILVAMOD database, one can see that the variation we uncovered follows closely the natural variation of the V3–V4 region of the 16S rRNA gene. As shown in Fig. 3 , each of the three peaks are composed of characteristic phyla.

    Article Snippet: Here we report on the reliability and biases of performing bacterial 16S rRNA gene amplicon paired-end sequencing on the MiSeq Illumina platform.

    Techniques: Sequencing, Produced

    Affiliation of the sequences of the 14 bacterial strains showing the best PGP traits with the existing 16S rRNA gene sequences. Phylogenetic analysis was inferred by using the Neighbor-Joining method. The evolutionary distances were computed using the Tamura 3-parameter method. The rate variation among sites was modeled with a gamma distribution (shape parameter = 1). Bootstrap (1,000 replicates) values below 70 are not shown. Evolutionary analyses were conducted in MEGA10.

    Journal: Frontiers in Plant Science

    Article Title: Bacteria Associated With a Commercial Mycorrhizal Inoculum: Community Composition and Multifunctional Activity as Assessed by Illumina Sequencing and Culture-Dependent Tools

    doi: 10.3389/fpls.2018.01956

    Figure Lengend Snippet: Affiliation of the sequences of the 14 bacterial strains showing the best PGP traits with the existing 16S rRNA gene sequences. Phylogenetic analysis was inferred by using the Neighbor-Joining method. The evolutionary distances were computed using the Tamura 3-parameter method. The rate variation among sites was modeled with a gamma distribution (shape parameter = 1). Bootstrap (1,000 replicates) values below 70 are not shown. Evolutionary analyses were conducted in MEGA10.

    Article Snippet: Library Preparation Three 16S rRNA gene amplicon libraries were prepared by PCR amplification of an approximate 630 bp region within the hypervariable (V3-V4) region of the 16S rRNA gene according to the Illumina 16S metagenomic sequencing library protocol.

    Techniques:

    Dynamics of OTUs that displayed relative abundances above 5% of the bacterial community over the experimental period in the four reactors operated with synthetic urine (UR-K and UR-Na) and synthetic wastewater (WWR-K and WWR-Na). Their relative abundances and closest neighbors were retrieved from the high-resolution MiSeq data sets of 16S rRNA gene-based amplicon sequencing and after mapping against MIDAS. These phylotypes were identified at family ( -aceae suffix) and genus levels.

    Journal: Environmental Science & Technology

    Article Title: Growth of Nitrosococcus-Related Ammonia Oxidizing Bacteria Coincides with Extremely Low pH Values in Wastewater with High Ammonia Content

    doi: 10.1021/acs.est.7b00392

    Figure Lengend Snippet: Dynamics of OTUs that displayed relative abundances above 5% of the bacterial community over the experimental period in the four reactors operated with synthetic urine (UR-K and UR-Na) and synthetic wastewater (WWR-K and WWR-Na). Their relative abundances and closest neighbors were retrieved from the high-resolution MiSeq data sets of 16S rRNA gene-based amplicon sequencing and after mapping against MIDAS. These phylotypes were identified at family ( -aceae suffix) and genus levels.

    Article Snippet: DNA extracts were sent to Research and Testing Laboratory (Lubbock, TX, USA) for 16S rRNA gene-based amplicon sequencing according to facility’s protocol adapted to the MiSeq Illumina desktop technology.

    Techniques: Amplification, Sequencing

    Neighbor Joining tree of Nitrosococcus -like sequences based on 16S rRNA gene-based amplicon sequencing and reference sequences, based on 421 nucleotide positions. Numbers indicate % of 500 bootstrapped tree topologies supporting the displayed phylogeny. Scale indicates substitutions per position. Chromatium okenii was included as an outgroup within the class of γ- Proteobacteria .

    Journal: Environmental Science & Technology

    Article Title: Growth of Nitrosococcus-Related Ammonia Oxidizing Bacteria Coincides with Extremely Low pH Values in Wastewater with High Ammonia Content

    doi: 10.1021/acs.est.7b00392

    Figure Lengend Snippet: Neighbor Joining tree of Nitrosococcus -like sequences based on 16S rRNA gene-based amplicon sequencing and reference sequences, based on 421 nucleotide positions. Numbers indicate % of 500 bootstrapped tree topologies supporting the displayed phylogeny. Scale indicates substitutions per position. Chromatium okenii was included as an outgroup within the class of γ- Proteobacteria .

    Article Snippet: DNA extracts were sent to Research and Testing Laboratory (Lubbock, TX, USA) for 16S rRNA gene-based amplicon sequencing according to facility’s protocol adapted to the MiSeq Illumina desktop technology.

    Techniques: Amplification, Sequencing