Bigdata analytics identifies metabolic inhibitors and promoters for productivity improvement and optimization of monoclonal antibody (mAb) production process
| Autor: | Ashli Polanco, Seo-Young Park, Zheng Jian Li, Kevin S. McFarland, Jia Zhao, Jianlin Xu, Michael D. Reily, Andrew Yongky, Caitlin Morris, Zhuangrong Huang, Seongkyu Yoon, Bethanne M. Warrack, Michael C. Borys |
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| Rok vydání: | 2020 |
| Předmět: |
0106 biological sciences
0301 basic medicine medicine.drug_class lcsh:Biotechnology Metabolite Biomedical Engineering Computational biology Biology Titer improvement lcsh:Chemical technology Monoclonal antibody lcsh:Technology 01 natural sciences 03 medical and health sciences chemistry.chemical_compound Metabolomics lcsh:TP248.13-248.65 010608 biotechnology Partial least squares regression medicine lcsh:TP1-1185 Multivariate data analysis lcsh:T Renewable Energy Sustainability and the Environment business.industry Promoter Feed media optimization Titer 030104 developmental biology chemistry Analytics Industrial and production engineering business Food Science Biotechnology |
| Zdroj: | Bioresources and Bioprocessing, Vol 7, Iss 1, Pp 1-13 (2020) |
| ISSN: | 2197-4365 |
| DOI: | 10.1186/s40643-020-00318-6 |
| Popis: | Recent advances in metabolite quantification and identification have enabled new research into the detection and control of titer inhibitors and promoters. This paper presents a bigdata analytics study to identify both inhibitors and promoters using multivariate data analysis of metabolomics data. By applying multi-way partial least squares (PLS) model to metabolite data from four fed-batch bioreactor conditions where feed formulation and selection agent concentrations varied, metabolites which exhibited the most significant impact on titer during cultivation were ranked from highest to lowest. The model outputs were then constrained to reduce the number of statistically relevant inhibitors or promoters to the top ten, which were used to conduct metabolic pathway analysis. Furthermore, a method is presented for identifying amino acids that prevent the accumulation of the inhibitors and/or enhance the formation of promoters during production. Finally, the metabolomics and pathway analysis results were integrated and validated with transcriptomics data to characterize metabolic changes occurring among different growth conditions. From these results, new feeding strategies were implemented which resulted in increased fed-batch production titer. Methodology from this work could be applied to future process optimization strategies for biotherapeutic production. |
| Databáze: | OpenAIRE |
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