Bioresources and Bioprocessing

Big-data analysis is becoming more and more important. In particular, the integration of transcriptomics data with metabolic profiling (metabolomics) data and metabolic flux analysis is useful for the improvement and optimization of bioprocesses. The present research shows a novel method of multi-variate analysis (multi-way partial least square, PLS) for the chemometrics models that can identify the key metabolites (amino acids) that influence the monoclonal antibody production. Then new feeding strategies were implemented based on such data analysis for the improvement of the titer in the fed-batch cultivation. Big-data analysis is becoming more and more important. In particular, the integration of transcriptomics data with metabolic profiling (metabolomics) data and metabolic flux analysis is useful for the improvement and optimization of bioprocesses. The present research shows a novel method of multi-variate analysis (multi-way partial least square, PLS) for the chemometrics models that can identify the key metabolites (amino acids) that influence the monoclonal antibody production. Then new feeding strategies were implemented based on such data analysis for the improvement of the titer in the fed-batch cultivation.