Dynamic gene expression for metabolic engineering of mammalian cells in culture

Huong Le, Nandita Vishwanathan, Anne Kantardjieff, Inseok Doo, Michael Srienc, Xiaolu Zheng, Nikunj Somia, Wei Shou Hu

Research output: Contribution to journalArticlepeer-review

32 Scopus citations


Recombinant mammalian cells are the major hosts for the production of protein therapeutics. In addition to high expression of the product gene, a hyper-producer must also harbor superior phenotypic traits related to metabolism, protein secretion, and growth control. Introduction of genes endowing the relevant hyper-productivity traits is a strategy frequently used to enhance the productivity. Most of such cell engineering efforts have been performed using constitutive expression systems. However, cells respond to various environmental cues and cellular events dynamically according to cellular needs. The use of inducible systems allows for time dependent expression, but requires external manipulation. Ideally, a transgene's expression should be synchronous to the host cell's own rhythm, and at levels appropriate for the objective. To that end, we identified genes with different expression dynamics and intensity ranges using pooled transcriptome data. Their promoters may be used to drive the expression of the transgenes following the desired dynamics. We isolated the promoter of the Thioredoxin-interacting protein (Txnip) gene and demonstrated its capability to drive transgene expression in concert with cell growth. We further employed this Chinese hamster promoter to engineer dynamic expression of the mouse GLUT5 fructose transporter in Chinese hamster ovary (CHO) cells, enabling them to utilize sugar according to cellular needs rather than in excess as typically seen in culture. Thus, less lactate was produced, resulting in a better growth rate, prolonged culture duration, and higher product titer. This approach illustrates a novel concept in metabolic engineering which can potentially be used to achieve dynamic control of cellular behaviors for enhanced process characteristics.

Original languageEnglish (US)
Pages (from-to)212-220
Number of pages9
JournalMetabolic Engineering
StatePublished - Nov 2013

Bibliographical note

Funding Information:
The authors would like to thank the Minnesota Supercomputing Institute (MSI) for computational support. HL was a recipient of the Vietnam Education Foundation (VEF) fellowship. The opinions, findings, and conclusions stated herein are those of the authors and do not necessarily reflect those of VEF. AK was supported by the NIH Biotechnology Training Grant ( GM08347 ). The authors are grateful to Katie Scholz, Wendy Chan, and Yu-Tin Chen for their assistance with experiments.


  • Fructose transporter (GLUT5)
  • Lactate consumption
  • Promoter engineering
  • Thioredoxin-interacting protein (Txnip)
  • Time-series transcriptome data


Dive into the research topics of 'Dynamic gene expression for metabolic engineering of mammalian cells in culture'. Together they form a unique fingerprint.

Cite this