Flux Sampling Suggests Metabolic Signatures of High Antibody-Producing CHO Cells

Abstract

Chinese hamster ovary (CHO) cells remain the industry standard for producing numerous therapeutic proteins, particularly monoclonal antibodies (mAbs). However, achieving higher recombinant protein titers remains an ongoing challenge and a fundamental understanding of the cellular mechanism driving improved bioprocess performance remains elusive. To directly address these challenges and achieve substantial improvements, a more in-depth understanding of cellular function within a bioprocess environment may be required. Over the past decade, significant advancements have been made in the building of genome-scale metabolic models (GEMs) for CHO cells, bridging the gap between high information content 'omics data and the ability to perform in silico phenotypic predictions. Here, time-course transcriptomics has been employed to constrain culture phase-specific GEMs, representing the early exponential, late exponential, and stationary/death phases of CHO cell fed-batch bioreactor culture. Temporal bioprocess data, including metabolite uptake and secretion rates, as well as growth and productivity, has been used to validate flux sampling results. Additionally, high mAb-producing solutions have been identified and the metabolic signatures associated with improved mAb production have been hypothesized. Finally, constraint-based modeling has been utilized to infer specific amino acids, cysteine, histidine, leucine, isoleucine, asparagine, and serine, which could drive increased mAb production and guide optimal media and feed formulations.