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Mining transcriptome data for function–trait relationship of hyper productivity of recombinant antibody
Author(s) -
Charaniya Salim,
Karypis George,
Hu WeiShou
Publication year - 2009
Publication title -
biotechnology and bioengineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 189
eISSN - 1097-0290
pISSN - 0006-3592
DOI - 10.1002/bit.22210
Subject(s) - transcriptome , trait , productivity , function (biology) , recombinant dna , biology , computational biology , microbiology and biotechnology , genetics , gene , gene expression , computer science , economics , macroeconomics , programming language
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 of genes 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. Biotechnol. Bioeng. 2009;102: 1654–1669. © 2008 Wiley Periodicals, Inc.