Journal: Nutrients

Article Title: Impaired Fat Absorption from Intestinal Tract in High-Fat Diet Fed Male Mice Deficient in Proglucagon-Derived Peptides

doi: 10.3390/nu16142270

Figure Lengend Snippet: Gut microbiome in HFD-fed control mice and HFD-fed GCGKO mice. ( a ) Relative abundance of the taxonomic groups at the genus level in HFD-fed control mice and HFD-fed GCGKO mice. ( b ) Differences in alpha diversity indicated by phylogenetic diversity indices. ( c ) Principal coordinate analysis of beta diversity calculated by Jenson–Shannon divergence ( p < 0.001). ( d ) Quantitative PCR (qPCR) Analysis of gene expression levels of Parabacteroides distasonis GH32 gene and the Akkermansia muciniphila Amuc_1434* gene in HFD-fed control (black dots; n = 8) and HFD-fed GCGKO mice (red dots; n = 6) after 1 week intervention. (* p < 0.05, ** p < 0.01). Data are expressed as mean ± SEM. Statistical comparisons were performed using unpaired Student’s t -test for ( b , d ).

Article Snippet: The data generated by the MiSeq sequencing system were processed, statistically analyzed, and visualized using the EzBioCloud 16S database and the 16S microbiome pipeline provided by ChunLab Inc. (Seoul, Korea EzBioCloud 16S-based MTP app, available at https://www.EZbiocloud.net accessed on 23 April 2024).

Techniques: Control, Real-time Polymerase Chain Reaction, Expressing

Journal: Frontiers in Cellular and Infection Microbiology

Article Title: Standardization of 16S rRNA gene sequencing using nanopore long read sequencing technology for clinical diagnosis of culture negative infections

doi: 10.3389/fcimb.2025.1517208

Figure Lengend Snippet: Average relative abundance (%) of bacterial organisms present in MCM2α and MCM2β obtained by ONT sequencing using the R10.4.1 MinION flow cell and ONT 16S Barcoding all-in-one kit (v14). Three concentrations of the MCM2α and MCM2β materials were tested in triplicate (neat, 1:10 and 1:100) and analysis by EPI2ME Desktop agent. The species abundance (%) of each dilution is reported, including the dPCR reported composition for the two materials ( Supplementary Data 3 ).

Article Snippet: To ensure the quality of the output, the BugSeq (v5.0) 16S pipeline requires both 80% query coverage and 80% sequence identity for the classification of consensus sequences ( ).

Techniques: Sequencing

Journal: Frontiers in Cellular and Infection Microbiology

Article Title: Standardization of 16S rRNA gene sequencing using nanopore long read sequencing technology for clinical diagnosis of culture negative infections

doi: 10.3389/fcimb.2025.1517208

Figure Lengend Snippet: Average relative abundance (%) of bacterial organisms present in MCM2α and MCM2β obtained by ONT sequencing using the R10.4.1 MinION flow cell and the in-house developed 16S ONT RBK method. Three concentrations of the MCM2α and MCM2β materials were tested in triplicate (neat, 1:10 and 1:100) and amplified in two PCRs targeting the V1-V2 and V1-V9 genomic regions of the 16S rRNA gene; analysis by EPI2ME Desktop agent. The species abundance (%) of each dilution is reported, including the dPCR reported composition for the two materials ( Supplementary data 3 ).

Article Snippet: To ensure the quality of the output, the BugSeq (v5.0) 16S pipeline requires both 80% query coverage and 80% sequence identity for the classification of consensus sequences ( ).

Techniques: Sequencing, Amplification

Journal: Journal of Translational Medicine

Article Title: Integrated next-generation sequencing of 16S rDNA and metaproteomics differentiate the healthy urine microbiome from asymptomatic bacteriuria in neuropathic bladder associated with spinal cord injury

doi: 10.1186/1479-5876-10-174

Figure Lengend Snippet: Phylogenetic diversity of Lactobacillales 16S rDNA sequences in human urine. NJ tree clustering of Lactobacillales OTU representatives labeled based on similarity to known RDP database sequences (gray), and OTU composition. Leaves are colored as follows: OTUs consisting of only healthy individuals (dark blue), mostly healthy (light blue), only NB (red), mostly NB (pink/salmon). Branches were highlighted and labeled by identifiable bacterial genera. Genus-level classification was based on the OTU representative RDP classification and the classification of nearest neighbors the RDP alignment. The nodes show SequenceID_#male/#female_#SCI/#healthy subjects.

Article Snippet: A total of 589454 quality-filtered 16S rDNA sequence reads were processed through a NextGen 16S rDNA analysis pipeline.

Techniques: Labeling

Journal: Journal of Translational Medicine

Article Title: Integrated next-generation sequencing of 16S rDNA and metaproteomics differentiate the healthy urine microbiome from asymptomatic bacteriuria in neuropathic bladder associated with spinal cord injury

doi: 10.1186/1479-5876-10-174

Figure Lengend Snippet: Phylogenetic diversity of Enterobacteriales 16S rDNA sequences in human urine. NJ tree clustering of Enterobacteriales OTU representatives labeled based on similarity to known RDP database sequences (gray), and OTU composition. Leaves are colored as follows: OTUs consisting of only healthy individuals (dark blue), mostly healthy (light blue), only NB (red), mostly NB (pink/salmon). Branches were highlighted and labeled by identifiable bacterial genera. Genus-level classification was based on the OTU representative RDP classification and the classification of nearest neighbors the RDP alignment. The nodes show SequenceID_#male/#female_#SCI/#healthy subjects.

Article Snippet: A total of 589454 quality-filtered 16S rDNA sequence reads were processed through a NextGen 16S rDNA analysis pipeline.

Techniques: Labeling

Journal: Journal of Translational Medicine

Article Title: Integrated next-generation sequencing of 16S rDNA and metaproteomics differentiate the healthy urine microbiome from asymptomatic bacteriuria in neuropathic bladder associated with spinal cord injury

doi: 10.1186/1479-5876-10-174

Figure Lengend Snippet: Bacterial profiles of urinary samples

Article Snippet: A total of 589454 quality-filtered 16S rDNA sequence reads were processed through a NextGen 16S rDNA analysis pipeline.

Techniques:

Journal: European Journal of Clinical Microbiology & Infectious Diseases

Article Title: Nationwide multicentre study of Nanopore long-read sequencing for 16S rRNA-species identification

doi: 10.1007/s10096-025-05158-w

Figure Lengend Snippet: Workflow overview used by the participating laboratories. Seven different extraction methods were followed by library preparation using a modified ONT 16S Barcoding kit 24 V14 protocol (52 °C annealing, 40 cycles), or in-house PCR systems with the Ligation Sequencing V14 kit. Sequencing was conducted on various ONT devices. Species identification was performed using the commercial 1928 Diagnostics-16S pipeline and the GMS-16S pipeline (EMU classification tool). Created in BioRender. Wang, H. (2024) https://BioRender.com/i45i214

Article Snippet: Initially, each laboratory uploaded the FASTQ files to the 1928 Diagnostic platform for analysis using the 1928 16S V1 V9 pipeline for amplicon data generated with Nanopore ( https://www.1928diagnostics.com/ ).

Techniques: Extraction, Modification, Ligation, Sequencing

Journal: European Journal of Clinical Microbiology & Infectious Diseases

Article Title: Nationwide multicentre study of Nanopore long-read sequencing for 16S rRNA-species identification

doi: 10.1007/s10096-025-05158-w

Figure Lengend Snippet: Relative abundance (%) of reads per sample for each laboratory ( r-y ) and species using the GMS-16S pipeline. (a) monomicrobial QCMD samples (top), (b) monomicrobial GMS samples (middle) (c) polymicrobial samples for both sample sets (bottom). Bacterial load (CFU/mL) is provided for the GMS panel, while QCMD concentrations are unknown (N/A). See Supplementary file for detailed classification

Article Snippet: Initially, each laboratory uploaded the FASTQ files to the 1928 Diagnostic platform for analysis using the 1928 16S V1 V9 pipeline for amplicon data generated with Nanopore ( https://www.1928diagnostics.com/ ).

Techniques:

Journal: European Journal of Clinical Microbiology & Infectious Diseases

Article Title: Nationwide multicentre study of Nanopore long-read sequencing for 16S rRNA-species identification

doi: 10.1007/s10096-025-05158-w

Figure Lengend Snippet: a Comparison of species identification between GMS-16S and 1928-16S for samples with the largest discrepancies (G12-G4). The relative abundance (%) for each laboratory is represented by a box, with similar identification on the left and differences on the right . See Supplementary File and for details. b Comparison of species distribution in the polymicrobial samples G11 and Q6 across the laboratories ( a - y ). Relative abundance (%) of reads are shown for both pipelines (GMS-16S vs 1928-16S)

Article Snippet: Initially, each laboratory uploaded the FASTQ files to the 1928 Diagnostic platform for analysis using the 1928 16S V1 V9 pipeline for amplicon data generated with Nanopore ( https://www.1928diagnostics.com/ ).

Techniques: Comparison

Journal: Genes

Article Title: Comparison of Illumina versus Nanopore 16S rRNA Gene Sequencing of the Human Nasal Microbiota

doi: 10.3390/genes11091105

Figure Lengend Snippet: Nose swab samples of individuals and negative controls that were sequenced using and Illumina and nanopore 16S rRNA gene sequencing technologies. (a) = a maximum of 5000 raw Illumina sequence reads were analyzed for the classification of genera. (b) = samples with read numbers below the 500 read cut-off. NA = not applicable.

Article Snippet: To determine whether upgrades in the basecaller and the 16S EPI2ME 16S pipeline improved the detection of genera with an assigned num_genus_taxid of 2, we re-basecalled and re-analyzed the raw reads of all nose swab samples sequenced with the Oxford Nanopore technology.

Techniques: Sequencing, Infection, Control

Journal: Genes

Article Title: Comparison of Illumina versus Nanopore 16S rRNA Gene Sequencing of the Human Nasal Microbiota

doi: 10.3390/genes11091105

Figure Lengend Snippet: Nasal microbiota profiles generated using nanopore and Illumina 16S rRNA gene sequencing. DNA was isolated from 57 nose swab samples, and 16S rRNA gene sequencing was performed using both Illumina ( a ) and nanopore ( b ) technologies. Each bar in the graph represents a nasal microbiota profile from a single individual. The dashed lines in ( b ) represent genera that, by default, were reported as unclassified at genus level in the EPI2ME report but were identified when next to reads with a top three blast hit with one genera (num_genus_taxid is 1); reads with a top three blast hit with two genera (num_genus_taxid is 2) were also included. A phylogenetic tree was generated by Pearson/UPGMA clustering of bacterial genera in microbiota profiles, as determined using Illumina sequencing. To compare between the two techniques, the sample order of the samples that were sequenced with the Oxford Nanopore platform was matched to the sample order of the samples that were sequenced with the Illumina platform, and the percentage of agreement was calculated for each nose swab sample ( c ). The horizontal black line in ( c ) indicates the mean percentage of agreement.

Article Snippet: To determine whether upgrades in the basecaller and the 16S EPI2ME 16S pipeline improved the detection of genera with an assigned num_genus_taxid of 2, we re-basecalled and re-analyzed the raw reads of all nose swab samples sequenced with the Oxford Nanopore technology.

Techniques: Generated, Sequencing, Isolation, Illumina Sequencing

Journal: Genes

Article Title: Comparison of Illumina versus Nanopore 16S rRNA Gene Sequencing of the Human Nasal Microbiota

doi: 10.3390/genes11091105

Figure Lengend Snippet: Agarose gel with 16S rRNA gene amplicons. Total DNA was isolated from pure bacterial cultures in a similar manner as the isolation of DNA from the nasal swab samples; the DNA concentration was determined by picogreen and a PCR was performed as described for nanopore sequencing using equal amounts of template DNA, with the exception that 30 PCR cycli instead of 25 cycli were used.

Article Snippet: To determine whether upgrades in the basecaller and the 16S EPI2ME 16S pipeline improved the detection of genera with an assigned num_genus_taxid of 2, we re-basecalled and re-analyzed the raw reads of all nose swab samples sequenced with the Oxford Nanopore technology.

Techniques: Agarose Gel Electrophoresis, Isolation, Concentration Assay, Nanopore Sequencing

Journal: Genes

Article Title: Comparison of Illumina versus Nanopore 16S rRNA Gene Sequencing of the Human Nasal Microbiota

doi: 10.3390/genes11091105

Figure Lengend Snippet: Genus and species level identification on pure culture species. Pure cultures of bacterial ATCC strains were sequenced using an R9.2 or R9.4 nanopore flowcell and Albacore or Guppy basecalling. Taxonomic assignment was performed at genus ( a ) and species ( b ) level using the EPI2ME 16S pipeline and the following thresholds: read length ≥1400 bp ≤ 1700 bp, num_genus_taxid is 1 or lca is 0 and accuracy ≥80%, QC ≥ 7 when albacore basecalling was used, or accuracy ≥85%, QC score ≥9 when Guppy basecalling was used. Similar criteria and the highest scoring BLAST identification (top rank) was used for species level identification. A is Albacore; G is Guppy basecalling.

Article Snippet: To determine whether upgrades in the basecaller and the 16S EPI2ME 16S pipeline improved the detection of genera with an assigned num_genus_taxid of 2, we re-basecalled and re-analyzed the raw reads of all nose swab samples sequenced with the Oxford Nanopore technology.

Techniques: