Cell line authentication

Confirm the identity of cell lines in your laboratory

Regulatory bodies request genetic characterization of cell lines and recombinant protein products, to confirm the species of origin and to monitor and control the genetic stability across the production process. Even in highly controlled facilities, random mutations will occur during culture expansions.

Identity: Determine the species origin vector identity. Required by regulatory authorities (FDA, WHO).
Genetic stability: Measure genetic alterations due to the culture expansion process, such as SNPs, insertions/deletions (InDels) and Copy Number Variations (CNVs). This test compares the genetic information of the Working Cell Bank (WCB) or End Of Production Cells (EOPC) with the Master Cell Bank (MCB) reference.
Purity: Proves the absence of adventitious agents such as bacteria, fungi and viruses.

GenomeScans expertise in the recommendations of regulatory authorities helps you to adhere to all guidelines for safety testing and/or to markedly reduce the time to set up a stable production line.

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See how we work with you on your project:

GenomeScan offers cell line testing on the most advanced sequencing instruments: Illumina’s NovaSeq® and PacBio Sequel®. High throughput sequencing ensures that we can offer high quality data at the most competitive prices.

Contact us for personal scientific advice on how your academic department or biomanufacturing facility can benefit from collaborating with an NGS expertise center.

Cell line characterization 01 Product page Cell line authentication

In any facility that uses cell lines for manufacturing, extensive characterization of the Master Cell Bank (MCB) is of vital importance. It provides you with the quality assurance required to maintain a stable production and to adhere to all international regulations (FDA, WHO, EMEA).

Whole Genome Sequencing (WGS) is the most accurate and powerful tool to obtain the genetic information of your cell lines. By parallel sequencing of millions of DNA fragments our bioinformaticians provide you with a reference genome that is specific for your facility. This representation of your cell line at base pair level, or de novo assembly, can be used for every future study to monitor genetic drift, randomly occurring mutation events. Alternatively, cell line transformation by viral transduction or CRISPR-Cas can be easily monitored when the precise genetic code is known.

Long-range sequencing

Pseudogenes, repetitive regions, or otherwise hard to sequence regions, make it difficult to assemble a complete reference genome. To overcome these issues for cell line characterization, ultra-long reads are required that span up to 60 Kb, instead of the 150 bp fragments of short-range sequencers. The longer the reads, the more accurate and trustworthy the analysis.
GenomeScan provides long-range sequencing using the PacBio Sequel®, since this technology provides a data quality that currently surpasses other technologies.

Our bioinformaticians provide you with a full cell line characterization report, including:

De novo analysis: Full genomic sequence
Genome annotation: prediction of genes
Confirmation of identity: Is your cell line an exact match to the database cell line?
Percentage of identity: Genetic deviations compared to the database cell line

GenomeScan bioinformaticians are experienced in answering all questions regarding cell line characterization and authentication. All projects can be tailored to you research needs.

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Cell line authentication 01 Product page Cell line authentication

Continuous culture expansion of the cell line leads to genetic alterations: SNPs, insertions/deletions (InDels) and Copy Number Variations (CNVs) might arise unnoticed. They can have a major effect on the stability of the line and the production process.

Using NGS, monitoring production lines has become easily attainable, cost-effective and will ensure that all requirements of regulatory bodies are met.

This test compares the genetic information of the working cell bank (WCB/EOPC) with the Master cell bank (MCB) reference. If a Whole Genome reference has been constructed, short-read sequences are sufficient to monitor the genetic alterations that randomly have occurred. Especially valuable is the classification of the functional consequences of these alterations: a stop-inducing SNP or a synonymous mutation (does not induce a an amino-acid change), have different biological consequences.

You will receive a comprehensive report including a tabular overview of:

Percentage identity compared to the parental line
Mutation/frequency analysis

All genetic deviations from the parental line (SNPs, InDels, CNVs)

Functional consequences of the observed mutations on the affected gene(s)

In frame insertion, stop-gained, coding sequence variants, etc.

Adventitious Agent detection: Organic contaminants in the production batch

GenomeScan provides a Cell Line Authentication Test Certificate that provides a comprehensive overview of identity scores, the methodology, and purity/adventitious agent detection. It summarizes all information required for QA statements under ISO 17025, 15189 and GMP.

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Agent detection 01 Product page Cell line authentication

Safety testing for adventitious agents is recommended by regulatory authorities. Cell lines and their products can be efficiently tested for identification, classification and quantitation of microbes.

Next Generation Sequencing provides a higher level of biosafety assurance, since it analyzes all nucleic acid contaminants present in an unbiased manner. GenomeScan offers a test to detect contaminants (from mycoplasm to (exotic) virus) based on a proprietary metagenome database. This test can complement or replace traditional methods such as in vitro or qPCR-based assays.

Adventitious agent detection is a part of GenomeScan’s cell line authentication service.

For raw materials, cell banks, virus banks, vaccine stocks, culture media and bulk harvests
Identification of contamination of any organism, generally of bacterial, viral or fungal origin
Timely notification allows for immediate investigation of biological contamination events during biomanufacturing

Microbial contamination can also be tested using a dedicated test, which specifically targets bacteria using 16S rRNA sequencing.

GenomeScan can provide a Cell LineTest Certificate that provides a comprehensive overview of identity scores, the methodology, and purity/adventitious agent detection. It summarizes all information required for QA statements under ISO 17025, 15189 and GMP.

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Genotypic indentity testing 01 Product page Cell line authentication

After transformation of cell lines, Genotypic Identity Testing can provide you with reliable data to monitor your production lines. Transcriptome analysis shows the identity and quantity of the genes that are expressed.

The data-analysis can be used to select clones that will show stable growth throughout the production phase.

Transcriptome analysis can show the similarity of your (transformed) lines with the parental line and allows monitoring of stable/unaltered expression of specific (trans)genes. By unsupervised statistical clustering of the transcripts, the variation between cell lines can be visualized and compared to the parental line. For example, cell lines that show excess growth may have (partly) lost one or more chromosomes.

At greater sequencing depth more data is generated to reach a higher accuracy in monitoring the genetic drift in the coding regions that are functionally expressed. Thus, transcriptome analysis can accurately detect all types of genetic alterations, such as SNPs, insertions and deletions (InDels).

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Vector identification check 01 Product page Cell line authentication

Verification of cell line characteristics is important at all stages of drug development: from the initial transformation to compound production. GenomeScan provides the NGS tools to accurately characterize the expression constructs that can be used in the production of recombinant DNA.

The early product development track can be boosted by a single NGS test providing all information to predict genetic stability. NGS helps to drastically shorten the process that leads to a stably growing production line.

Transformation of cell lines can affect clonal stability in multiple ways:

Number of inserted copies into the genome
Insert location (disruption of genes at insert site)
Full/partial insertion of the target sequence
Orientation of the integrated construct(s)
Sequence variants of the integrated construct(s)

Vector figure Product page Cell line authentication

The most optimal method for full analysis of the vector sequence is PacBio long-read sequencing. This technique produces accurate ultra-long reads of up to 60 Kb, which is enough to sequence most expression vectors fully including complex vectors with repeat elements or repeated sequences. PacBio provides a single-molecule solution that can detect the whole spectrum from single base level to large insertions or deletions.

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Frequently Asked Questions

What is the difference between cell line authentication using STR analysis and Whole Genome analysis?

Cell line authentication can be performed by Short Tandem Repeat (STR) or DNA fingerprint analysis, which solely measures the number of repeats at several points. This is based on the assumption that cell lines are very stable, and that genetic alterations such as point mutations, insertions, deletions, inversions and copy number variations (CNVs) do not have an effect on production or outcome of the experiment.
For production facilities, regulatory bodies require that genetic information on the cell line is available and is monitored throughout production. Cell line characterization by Whole Genome Sequencing (WGS) analysis is then the method of choice.

Are there other methods to perform long-read sequencing?

Yes, Oxford Nanopore also produces ultra-long reads. At the moment PacBio is our method of choice (insert size up to 10kb), because it utilizes Circular Consensus Sequencing (CCS reads). This means that sequences are circularized, so that the bases are read multiple times. During processing, the random errors can be easily corrected, hence leading to a high quality data-set.