strains  (ATCC)

Journal: bioRxiv

Article Title: Using carrier DNA in ultra-low input library preparations for next-generation sequencing

doi: 10.64898/2026.01.26.701515

Figure Lengend Snippet: Lambda DNA and ATCC mock community DNA were sheared, mixed in a 1:1 ratio, and diluted to yield 0.05 pg to 50 pg inputs. ( A ) For each input level, total read depth is shown (brown columns) together with on-target reads (mapping to Lambda and ATCC genome sequences) in gray. The number of reads mapping to Lambda DNA (purple) and ATCC DNA references (blue) are shown. Error bars indicate standard deviation associated with three replicates. The average number of cycles of PCR used for amplification is shown at the top in brown numbering. The average measured mapping ratio of Lambda DNA to ATCC DNA is shown below the PCR cycle number in purple lettering. ( B ) The relative abundance of reads mapping to each of the 10 ATCC mock community fungal genomes are shown. Results are shown for libraries with 0.05 to 50 pg DNA input amounts. The dark gray boxes indicate the expected relative abundance of the input DNA (i.e., 10% relative abundance for each organism). Error bars indicate the standard deviation associated with three technical replicates. ( C ) Distribution of ‘Ideal Scores’ for ATCC mock community sequences across experiments. Ideal scores are a univariate metric measuring the summed divergence of observed microbial communities from expected microbial communities. The metric ranges from 0 (perfect fit) to 200, with lower numbers indicating better matching between observed and expected relative abundances across all taxa. An ANOVA was performed to determine if input DNA concentrations affected the observed microbial community structure. Error bars indicate the standard deviation associated with three replicates.

Article Snippet: Three DNA templates were used for analysis in this study, including purified Enterobacteria phage lambda DNA (Lambda DNA; Oxford Nanopore Technologies, EXP-CTL001), ZymoBIOMICS Microbial Community DNA Standard (Zymo Research, D6306), and Mycobiome Genomic DNA Mix (ATCC, MSA-1010).

Techniques: Lambda DNA Preparation, Standard Deviation, Amplification

Journal: bioRxiv

Article Title: NanoSimFormer: An end-to-end Transformer-based simulator for nanopore sequencing signal data

doi: 10.64898/2026.01.20.700442

Figure Lengend Snippet: Performance metrics were evaluated for Experimental data (blue) and simulated signals from NanoSimFormer (orange), seq2squiggle (green), and Squigulator (red) across seven datasets. The evaluation metrics include: a , Read accuracy; b , Phred quality score; c , Mismatch error rate; d , Insertion error rate; e , Deletion error rate; and f , Read length. In the box plots, the center line represents the median, the edges of the box denote the first and third quartiles, thus enclosing the interquartile range (IQR), and the whiskers extend to the most extreme data points within 1.5 × IQR from the edges of the box. Sample reads used to derive these statistics are: HG002 ( n = 320,000), E. coli ( n = 254,210), KP ( n = 365,393), MM ( n = 261,589), PA ( n = 211,667), PM ( n = 140,727), and MSA-1010 ( n = 1,884,844).

Article Snippet: Finally, for metagenomic evaluation, we used the ATCC Mycobiome Genomic DNA Mix (MSA-1010) dataset from the ont-open-data project [ ], comprising a mixture of ten distinct fungal strains, including Aspergillus fumigatus, Cryptococcus neoformans, Trichophyton interdigitale, Penicillium chrysogenum, Fusarium keratoplasticum, Candida albicans, Nakaseomyces glabratus, Malassezia globosa, Saccharomyces cerevisiae , and Cutaneotrichosporon dermatis .

Techniques:

Journal: bioRxiv

Article Title: NanoSimFormer: An end-to-end Transformer-based simulator for nanopore sequencing signal data

doi: 10.64898/2026.01.20.700442

Figure Lengend Snippet: De novo assembly performance was evaluated using simulated and experimental reads on n = 5 biologically independent bacterial datasets. The assemblies were assessed for a , Mismatches per 100 kbp; b , Indels per 100 kbp; and c , Genome fraction (%). For all box plots in panels a, b and c , the center line represents the median, the lower and upper bounds of the box represent the 25th and 75th percentiles, respectively, and the whiskers extend to the minimum and maximum values within 1.5 times the interquartile range, with outliers displayed as individual points. d , Scatter plots illustrating the correlation of read abundance (read counts classified by minimap2) between the experimental data and the simulated outputs for the MSA-1010 fungal mock community, comprising n = 10 distinct fungal strains. The solid blue line represents the linear regression fit, and the shaded region indicates the 95% confidence interval (CI) of the regression estimate. The Pearson correlation coefficient ( r ) is provided for each comparison.

Article Snippet: Finally, for metagenomic evaluation, we used the ATCC Mycobiome Genomic DNA Mix (MSA-1010) dataset from the ont-open-data project [ ], comprising a mixture of ten distinct fungal strains, including Aspergillus fumigatus, Cryptococcus neoformans, Trichophyton interdigitale, Penicillium chrysogenum, Fusarium keratoplasticum, Candida albicans, Nakaseomyces glabratus, Malassezia globosa, Saccharomyces cerevisiae , and Cutaneotrichosporon dermatis .

Techniques: Comparison

Journal: Environmental Microbiome

Article Title: Microbial community characterization in Red Sea-derived samples using a field-deployable DNA extraction system and nanopore sequencing

doi: 10.1186/s40793-025-00819-x

Figure Lengend Snippet: Schematic representation of the experimental design. Samples were obtained from two coral colonies ( P. verrucosa and Xenia sp.), mangrove sediments, and associated seawater (i.e., seawater surrounding the corals and mangroves sediments). Each sample was subjected to in-field and in-lab DNA extraction using the xTitan system. During this process, several pretreatments were carried out (e.g., coral pulverization, seawater filtration, bead beating, and enzymatic cell lysis; see methods). Photos of some specific processes were displayed at the left of the figure: from top to bottom, ( A ) coral sampling, ( B ) bead beating, ( C ) in-lab xTitan extraction, ( D ) mangrove sampling, and ( E ) seawater filtration using InnovaPrep CP Select™. Two sets of samples were stored in liquid nitrogen (corals) or ice (seawater and sediments) and processed in the laboratory around 24 h after sampling. These samples were used for DNA extraction using a lab-based commercial kit (DNeasy PowerSoil Pro Kit, Qiagen). DNA was extracted from a sterilized PBS and saline solution to serve as negative controls. All DNA samples were quantified using Qubit and subjected to full-length 16S rRNA gene amplicon and shotgun metagenome sequencing (using Oxford Nanopore Technology, ONT) at KAUST core lab. Figure partially created using bioRender ( https://BioRender.com )

Article Snippet: Triplicate sequencing of a standardized mock DNA (ATCC MSA-1000TM) confirmed ONT sequencing accuracy, with over 90% of reads correctly assigned to mock taxa (Fig. B).

Techniques: DNA Extraction, Filtration, Lysis, Sampling, Extraction, Saline, Amplification, Sequencing

Journal: Environmental Microbiome

Article Title: Microbial community characterization in Red Sea-derived samples using a field-deployable DNA extraction system and nanopore sequencing

doi: 10.1186/s40793-025-00819-x

Figure Lengend Snippet: Metagenomic analysis of coral colony-derived microbiomes. Clustering of coral colony-derived microbial communities assessed using three total DNA extraction systems, in-field xTitan (F), in-lab xTitan (L), and Qiagen, based on ( A ) taxonomic profiles at the species level (only Bacteria -, Archaea- , and Virus -derived genes are included). ( B ) Taxon relative abundance (%) plot at the phylum level using metagenome sequencing data from coral 1 and coral 2. This data only includes genes associated with Bacteria , Archaea , and Viruses . ( C ) and ( D ) Chord diagrams of the number of metagenome-derived genes associated with the abundant genera identified by 16S rRNA gene amplicon sequencing across the three DNA extraction systems

Article Snippet: Triplicate sequencing of a standardized mock DNA (ATCC MSA-1000TM) confirmed ONT sequencing accuracy, with over 90% of reads correctly assigned to mock taxa (Fig. B).

Techniques: Derivative Assay, DNA Extraction, Bacteria, Virus, Sequencing, Amplification