Mining transcriptome data for function-trait relationship of hyper productivity of recombinant antibody

Salim Charaniya, George Karypis, Wei Shou Hu

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

In the past decade we have witnessed a drastic increase in the productivity of mammalian cell culture-based processes. High-producing cell lines that synthesize and secrete these therapeutics have contributed largely to the advances in process development. To elucidate the productivity trait in the context of physiological functions, the transcriptomes of several NS0 cell lines with a wide range of antibody productivity were compared. Gene set testing (GST) analysis was used to identify pathways and biological functions that are altered in high producers. Three complementary tools for GST-gene set enrichment analysis (GSEA), gene set analysis (GSA), and MAPPFinder, were used to identify groups of functionally coherent genes that are up- or downregulated in high producers. Major functional classes identified include those involved in protein processing and transport, such as protein modification, vesicle trafficking, and protein turnover. A significant proportion ofgenes involved in mitochondrial ribosomal function, cell cycle regulation, cytoskeleton-related elements are also differentially altered in high producers. The observed correlation of these functional classes with productivity suggests that simultaneous modulation of several physiological functions is a potential route to high productivity.

Original languageEnglish (US)
Pages (from-to)1654-1669
Number of pages16
JournalBiotechnology and bioengineering
Volume102
Issue number6
DOIs
StatePublished - Apr 15 2009

Keywords

  • Cell culture
  • Data mining
  • Pathway analysis
  • Recombinant antibody production
  • Transcrip-tome

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