How are Sequins used in a metagenomics workflow?

Sequins controls are directly spiked into samples prior to library preparation, typically at approximately 1 percent of the total calculated input to a 250 ng library. They progress through library preparation and sequencing together with the sample and are then distinguished bioinformatically using a Sequins-specific FASTA integrated with reference databases or genomes, enabling normalization and accurate quantification of microbial abundance.

What are the key features and composition of the Metagenomics Core Control Set?

The Metagenomics Core Control Set represents 52 microbial species spanning bacteria, archaea and eukaryotes, with a GC content range from 27 to 71 percent. It includes a quantitative molecular ladder, is supplied as a single-tube blend, and has been demonstrated on various samples using Illumina and Oxford Nanopore Technologies sequencing platforms.

What performance benefits do Sequins provide for metagenomics?

Sequins-based normalization provides a tighter distribution of Relative Log Expression centred around zero and reduces inter-sample variation compared with raw counts or upper-quartile normalization. The molecular ladder supports absolute quantification and determination of assay sensitivity and limit of detection, while cross-alignment testing shows that less than 0.01 percent of Sequins reads align to microbial genomes, indicating that Sequins do not interfere with sample analysis.

Are Sequins compatible with different sequencing platforms and analysis tools?

Yes. Sequins controls are compatible with most sequencing technologies, including short- and long-read approaches, and have been used with a range of library preparation methods. The provided Sequins-specific FASTA enables compatibility with both taxonomic classification tools such as Kraken 2 and alignment-based metagenomics workflows.

What kit sizes and catalog numbers are available for the Metagenomics Core Control Set?

The Metagenomics Core Control Set is available in two kit sizes based on a 1 percent spike-in for a 250 ng library input: PN-10008, providing material for 24 samples, and PN-10009, providing material for 48 samples.

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Products & Applications

Sequins Metagenomics Core Control Set

Name: Sequins Metagenomics Core Control Set
Brand: Sequins

Industry leading quantification standards for microbial populations.

Qualitative and quantitative Metagenomics allows accurate analysis of microbial populations for pathogen detection, monitoring and screening for antimicrobial resistance genes. Given the varied source of samples and mixtures the need to normalize and quantify microbial populations is paramount.

Normalization within and between samples, users, equipment and locations

The use of Sequins controls for normalization mitigates the heterogeneity of samples to enable unprecedented standardization and interoperability.

Workflow Monitoring and Optimization

Sequins are subjected to the same technical influences and errors as the samples they are combined with, enabling the evaluation of workflow performance.

Absolute Quantification

Sequins standards are combined at varying concentrations and the resultant ladder enables quantitative analysis in addition to measuring sensitivity, specificity and limit of detection.

Most Comprehensive Metagenomics Control Set

The Sequins™ Metagenomics Core Control Set is a comprehensive, easy-to-use, pre-configured control set with built-in redundancy that ensures integrity of results. It contains synthetic sequences that collectively represent 52 microbial species at varying abundances to emulate the complexity found in a natural microbial community. Features include: quantitative ladders; wide representation of domains including bacteria, archaea and eukaryotes; GC% content range (27% to 71%); single tube blend; demonstrated on various samples using Illumina and Oxford Nanopore technologies.

Genus	No. Species	Genus	No. Species	Genus	No. Species
Aciduliprofundum	1	Fusobacterium	1	Persephonella	1
Acinetobacter	2	Helicobacter	1	Porphyromonas	1
Anabaena	1	Klebsiella	1	Roseobacter	1
Bacillus	2	Lactobacillus	1	Salmonella	1
Buchnera	1	Legionella	1	Shigella	1
Caldicellulosiruptor	1	Leuconostoc	1	Staphylococcus	1
Candida	1	Listeria	2	Streptococcus	1
Candidatus Caldiarchaeum	1	Magnetococcus	1	Synechocystis	1
Candidatus Carsonella	1	Metallosphaera	1	Thermotogan	1
Candidatus Korarchaeum	1	Methanococcus	1	Thermus	1
Chlamydia	1	Methanopyrus	1	Toxoplasma	1
Chlorobium	1	Mycobacterium	1	Treponema	1
Corynebacterium	1	Neisseria	2	Vibrio	1
Desulfitobacterium	1	Nitrosopumilus	1	Vulcanisaeta	1
Desulfovibrio	1	Nostoc	1	Wolinella	1
Ehrlichia	1	Oenococcus	1	Yersinia	1

Plug & Play Simplicity

Sequins are simply ‘spiked-in’ to a sample prior to library preparation and together, progressed through a workflow. Sequins controls can then be distinguished from the native sample in the output library by their synthetic sequence enabling normalization and comparison between samples, runs, laboratories, chemistries, and sequencers.

01

Spike Sequins into samples

02

Prepare library

03

Sequence

04

Prepare custom reference/database to include Sequins sequences

05

Analyze samples using standard tools

06

Use Sequins to normalize and quantify samples

Best In-Class Quantification & LOD Determination

Sequins Metagenomics Core Control Set performance. (A) Metagenomics Core Control Set replicates in dog faecal matrix background demonstrating an accurate and reproducible ladder in complex samples. (B) Cross-alignment rate of Sequins reads to microbial genomes, demonstrating that Sequins does not interfere with samples – less than 0.01% of reads cross-align to mock community genomes. (C) Sequins ladder on various backgrounds generated using Illumina and Oxford Nanopore Technologies (ONT) sequencing. This demonstrates that Sequins is compatible with short- and long-read sequencing technologies and can be used to determine assay limit of detection (LOD). (D) Predicted input concentration estimates (predicted using Sequins v. expected based on ZymoBIOMICS DNA Standard) demonstrating that the Sequins molecular ladder enables reliable microbial abundance quantification. Internal data.

A & B

C & D

Scatter plot of theoretical fold coverage (x) vs. limit of detection (LOD) (y) for Kraken; points show samples under a one-model anonymous approach; axes large and labeled; no regression line.

Heatmap of cross-alignment rates between samples/methods, recoloured colormap; large labeled axes and legend.

Scatter plot of theoretical fold coverage (x) vs. limit of detection (LOD) (y) for GCUL, with recoloured markers and labeled axes.

Scatter plot comparing predicted NGUL (y) vs theoretical NGUL (x) for a DNA standard (Sequins-only); points are samples, with labeled axes and legend.

Best In-Class Normalization

Sequins provide superior normalization performance. Relative Log Expression (RLE) normalization using (A) raw reads counts, (B) upper quartile and (C) Sequins. Faecal samples collected from Dogs 1 to 4, each with three corresponding replicates (DP1-DP12). Sequins-based normalization showed the most pronounced improvements. This included a tighter distribution centred around zero and reduced inter-sample variation. All results are based on phylum-level abundance estimates from Kraken 2/Bracken.

Detailed plot displaying measurement values across samples: the x-axis shows [X variable], the y-axis shows [Y variable], and cell/marker color indicates value intensity; large axes labels and a legend are included to aid interpretation.

What customers are saying about Sequins™

Sequins was straightforward to implement in the wet lab and, importantly, allowed us to obtain absolute quantification — something we couldn't achieve when only measuring relative abundances. We chose Sequins after seeing a colleague's successful work, and the Metagenomics Core Control Set delivered exactly what we needed.

Alex Song

PhD student, University of Michigan

Sequins gave us the confidence to accurately quantify viruses in wastewater samples by distinguishing true biological signals from sequencing biases. Their ease of use and robust design made them an invaluable tool for improving accuracy and reliability in our metagenomics research.