STRaM: A genetic framework for improved cell product provenance for research and clinical translations
Abstract Multiple assessment checks are required to handle the increasingly complex engineered-cell and cell-line provenance. To manage the biosafety and efficacy demands, we developed a bioinformatic pipeline for de novo profiling of short tandem repeats and mutations (STRaM) to identify and track...
Saved in:
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-08-01
|
| Series: | Communications Biology |
| Online Access: | https://doi.org/10.1038/s42003-025-08547-1 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Abstract Multiple assessment checks are required to handle the increasingly complex engineered-cell and cell-line provenance. To manage the biosafety and efficacy demands, we developed a bioinformatic pipeline for de novo profiling of short tandem repeats and mutations (STRaM) to identify and track homologous edited/engineered cells. The core technology of STRaM comprises an error-sensing bioinformatic pipeline with 3 analysis modules (STR analysis, STR flanking analysis and EMS analysis) for profiling, and an integrated assessment system with three indices for the respective reporting of identity, purity and genetic modifications of tested cells. STRaM maintains a transformed pathway for backward compatibility with traditional capillary gel electrophoresis (CE) based DNA databases. To introduce our integrative and cost-effective STRaM system to best practices in the management of modern cell products, we applied our enhanced DNA fingerprinting technique to several basic and translational cell research examples. |
|---|---|
| ISSN: | 2399-3642 |