Although Chinese hamster ovary (CHO) cells have dominated therapeutic protein expression systems for decades, biomanufacturers still must deal with their inconsistent expression levels and varying productivity. A new method developed by researchers in Korea offers a way around those limitations, generating cell lines with significantly higher productivity, efficiency, and stability compared to existing practices that achieve between 2.2- and 15-fold higher relative specific productivity.
Dong-Yup Lee, PhD, and Seo-Young Park, PhD, both senior researchers in the department of chemical engineering at South Korea’s Sungkyunkwan University, and their team from Sungkyunkwan University and GC Biopharma, developed a framework for systematically identifying genomic hotspots that enable high-yield protein (enzyme, monoclonal antibody) production in CHO cells.
“Leveraging these hotspot regions can streamline cell line development by improving predictability and consistency in productivity, ultimately reducing timelines and cost for biomanufacturing,” Park tells GEN.
Rather than relying upon random transgene integration, their targeted method “utilized site-specific integration methods involving CRISPR/Cas9 and recombinase-mediated cassette exchange (RMCE) to precisely insert genes into genomic loci,” Park says, that support stable, high-level expression.
The overall approach combined whole-genome analysis with transcriptome data from more than 200 RNA-seq databases “to systematically identify genomic hotspots in CHO cells that potentially enhance protein yield,” he adds.
Loci with favorable attributes were identified “based upon their proximity and association with highly expressed endogenous genes.” Three targeted integration approaches were used: inserting genes of interest into the flanking regions within 20 kb of a highly expressed gene; targeting intergenic regions near clusters of consecutively located highly expressed genes; or selecting intron regions larger than 10 kb within highly expressed genes. These hotspots were chosen because of their ability to retain robust functionality across various culture conditions and among different CHO paternal cell lines.
Candidates were then filtered to remove structural variations, copy number losses, and repetitive sequences, “while also considering sequence homology within the genome,” Park says. After narrowing the field to 20 candidate hotspots, the team experimentally validated their effectiveness.
Ultimately, Park says, “Five top-performing hotspots were validated from the initial pool of candidates, demonstrating significantly improved expression levels for both enzyme and monoclonal antibody production compared to previously known insertion sites.” To further boost productivity, Park and colleagues also suggested strategies such as integrating multiple hotspots or amplifying the gene of interest.
This work suggests the importance for biomanufacturers of considering transcriptomic stability, DNA sequence complexity, and genomic location collectively when selecting gene insertion points as part of CHO cell line development.
Future refinements, Park says, include “integrating AI-powered genomics and transcriptomic analysis, and validating these hotspots using multiple therapeutic proteins—including complex antibodies—to ensure robustness across different production contexts. More specifically, future technologies and methodologies should address technologies that precisely target genomic loci with stable long-term protein expression, as well as advanced AI and machine learning tools to predict optimal insertion sites, thus minimizing trial-and-error during early development stages.”
The post Fresh Hotspots ID’d for More Productive CHO Cell Lines appeared first on GEN - Genetic Engineering and Biotechnology News.
Dong-Yup Lee, PhD, and Seo-Young Park, PhD, both senior researchers in the department of chemical engineering at South Korea’s Sungkyunkwan University, and their team from Sungkyunkwan University and GC Biopharma, developed a framework for systematically identifying genomic hotspots that enable high-yield protein (enzyme, monoclonal antibody) production in CHO cells.
“Leveraging these hotspot regions can streamline cell line development by improving predictability and consistency in productivity, ultimately reducing timelines and cost for biomanufacturing,” Park tells GEN.
Leverage highly expressed genes
Rather than relying upon random transgene integration, their targeted method “utilized site-specific integration methods involving CRISPR/Cas9 and recombinase-mediated cassette exchange (RMCE) to precisely insert genes into genomic loci,” Park says, that support stable, high-level expression.
The overall approach combined whole-genome analysis with transcriptome data from more than 200 RNA-seq databases “to systematically identify genomic hotspots in CHO cells that potentially enhance protein yield,” he adds.
Loci with favorable attributes were identified “based upon their proximity and association with highly expressed endogenous genes.” Three targeted integration approaches were used: inserting genes of interest into the flanking regions within 20 kb of a highly expressed gene; targeting intergenic regions near clusters of consecutively located highly expressed genes; or selecting intron regions larger than 10 kb within highly expressed genes. These hotspots were chosen because of their ability to retain robust functionality across various culture conditions and among different CHO paternal cell lines.
Candidates were then filtered to remove structural variations, copy number losses, and repetitive sequences, “while also considering sequence homology within the genome,” Park says. After narrowing the field to 20 candidate hotspots, the team experimentally validated their effectiveness.
Ultimately, Park says, “Five top-performing hotspots were validated from the initial pool of candidates, demonstrating significantly improved expression levels for both enzyme and monoclonal antibody production compared to previously known insertion sites.” To further boost productivity, Park and colleagues also suggested strategies such as integrating multiple hotspots or amplifying the gene of interest.
This work suggests the importance for biomanufacturers of considering transcriptomic stability, DNA sequence complexity, and genomic location collectively when selecting gene insertion points as part of CHO cell line development.
Future refinements, Park says, include “integrating AI-powered genomics and transcriptomic analysis, and validating these hotspots using multiple therapeutic proteins—including complex antibodies—to ensure robustness across different production contexts. More specifically, future technologies and methodologies should address technologies that precisely target genomic loci with stable long-term protein expression, as well as advanced AI and machine learning tools to predict optimal insertion sites, thus minimizing trial-and-error during early development stages.”
The post Fresh Hotspots ID’d for More Productive CHO Cell Lines appeared first on GEN - Genetic Engineering and Biotechnology News.