With studies estimating that 10–40% of all popular cell lines are misidentified or contaminated, the importance of cell-line authentication is abundantly clear. However, traditional authentication methods are labor-intensive and have limited sensitivity, highlighting the need for an alternative approach. NGS-based single nucleotide polymorphism (SNP) genotyping offers several advantages over established techniques used for cell-line authentication including superior accuracy, sensitivity, and throughput. It can also be applied to advanced models such as organoids and xenografts that are increasingly being used for scientific research.
The use of misidentified cells for scientific research is a major problem, with the number of publications citing the use of cells classified as misidentified by the International Cell Line Authentication Committee (ICLAC) continuing to grow. Not only does using misidentified cells mean wasted time and effort spent generating unreliable data, but it can lead to publishers and funding agencies rejecting applications where proof of cell-line authentication is not supplied. Additionally, failure to detect mycoplasma and/or viral contamination can further compromise results.
Short tandem repeat (STR) profiling has been widely used for human cell-line authentication, where it produces a genetic fingerprint of the cell line in question by detecting short, repeated segments of DNA, typically 2–6 base pairs in length. Drawbacks of this method are that it is low throughput and labor-intensive, making it impractical and costly for authenticating large batches of samples. STR profiling also has limited sensitivity, reportedly around 5–10%, and requires that other assays be performed to detect the presence of mycoplasma and/or viral contamination.
Compared to STR profiling, SNP genotyping benefits from improved accuracy and greater sensitivity (reportedly 3–5%) by evaluating variation at the single DNA nucleotide level. Although SNPs are naturally occurring variants, they are also known to be involved in the etiology of many human diseases, making SNP genotyping a powerful tool to advance pharmacogenomics research. SNP genotyping additionally provides the ability to authenticate species-specific tumor models or mismatch repair (MMR) deficient human cancer cell lines—something that STR profiling cannot do.
Despite seeing increased use for cell-line authentication in recent years, conventional SNP genotyping based on multiplex PCR/qPCR methodology has inherent disadvantages. Like STR profiling, SNP genotyping is both cumbersome and low-throughput, restricting its utility to processing only low sample numbers. SNP genotyping is also inconvenient to detect interspecies contaminants and quickly becomes challenging to implement as the number of SNPs requiring surveillance grows.
NGS technologies overcome many common problems associated with traditional methods used for cell-line authentication. Specifically, barcode deep NGS—a method that uses multiplex PCR to amplify targeted DNA regions (“barcodes”) for sequencing at high-depth—provides superior accuracy, sensitivity, and throughput at a comparable cost to conventional STR or SNP techniques. This is achieved through assessing hundreds of SNPs simultaneously to produce a unique SNP fingerprint; by comparing this to a reference library (e.g., a library of cancer cell lines or syngeneic cell lines), the sample or its major component can be identified with 100% accuracy.
Further advantages of barcode deep NGS include a digital readout that provides clean data with a near-zero quantification error; the capacity for mouse sample authentication (currently impossible for many mouse cell lines with traditional STR or SNP methods); and improved monitoring of contamination. Critically, due to using a reference library, it is possible to both accurately identify contaminants and determine the contamination ratio. In combination, these features of barcode deep NGS make it well-suited to screening large biobanks.
Another defining feature of barcode deep NGS is its ability to estimate mix ratios for three or more cell lines. With organoids, homograft models, and xenograft models increasingly being used for scientific research, authenticating these complex systems is more important than ever. For example, in mouse tumor models such as patient-derived xenografts, mouse stromal cells can gradually replace human tumor cells over time to adversely impact traditional STR- and SNP-based authentication methods. Barcode deep NGS addresses this issue to deliver more reliable results.
Crown Bioscience provides an NGS-based SNP profiling cell line and model authentication service for accurately characterizing mouse and human samples including cell lines, organoids, xenograft models, and patient tissues. To find out more, visit crownbio.com