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Keywords:

  • bioinformatics;
  • recombinant monoclonal antibodies;
  • Chinese hamster;
  • ovary cells;
  • difficult-to-express proteins

Despite the development of high-titer bioprocesses capable of producing >10 g L−1 of recombinant monoclonal antibody (MAb), some so called “difficult-to-express” (DTE) MAbs only reach much lower process titers. For widely utilized “platform” processes the only discrete variable is the protein coding sequence of the recombinant product. However, there has been little systematic study to identify the sequence parameters that affect expression. This information is vital, as it would allow us to rationally design genetic sequence and engineering strategies for optimal bioprocessing. We have therefore developed a new computational tool that enables prediction of MAb titer in Chinese hamster ovary (CHO) cells based on the recombinant coding sequence of the expressed MAb. Model construction utilized a panel of MAbs, which following a 10-day fed-batch transient production process varied in titer 5.6-fold, allowing analysis of the sequence features that impact expression over a range of high and low MAb productivity. The model identified 18 light chain (LC)-specific sequence features within complementarity determining region 3 (CDR3) capable of predicting MAb titer with a root mean square error of 0.585 relative expression units. Furthermore, we identify that CDR3 variation influences the rate of LC-HC dimerization during MAb synthesis, which could be exploited to improve the production of DTE MAb variants via increasing the transfected LC:HC gene ratio. Taken together these data suggest that engineering intervention strategies to improve the expression of DTE recombinant products can be rationally implemented based on an identification of the sequence motifs that render a recombinant product DTE. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 30:188–197, 2014