Advisor(s)

William S. Hancock

Contributor(s)

Zhaohui S. Zhou, Carolyn Lee-Parsons, Li Zang

Date of Award

2011

Date Accepted

9-2011

Degree Grantor

Northeastern University

Degree Level

Ph.D.

Degree Name

Doctor of Philosophy

Department or Academic Unit

College of Science. Department of Chemistry and Chemical Biology.

Keywords

biopharmaceutical, cell culture, CHO, iTRAQ, mass spectrometry, proteomics

Subject Categories

Pharmaceutical biotechnology, Proteomics

Disciplines

Biochemistry | Medicinal Chemistry and Pharmaceutics

Abstract

The production of biological drugs for the treatment of serious diseases is a complex process utilizing a mammalian cell expression system combined with a complex set of purifications steps to produce drugs of high quality and at optimized yields. In order to maximize both quality and yield, the cell culture process must be developed ensuring maximal cell growth and productivity characteristics, as well as scalability and robustness in a manufacturing setting. The purification method must also be optimized for high yield of product, while maintaining or enhancing the product quality profile of the drug and removing cell culture related impurities to acceptably low levels. Limitations of the biopharmaceutical process can have great impact on the cost of drug production, as well as on the safety and efficacy of the drug. Understanding the biology of the cells used to produce biopharmaceuticals can enable the development of better processes. This thesis describes the characterization of biopharmaceutical processes using proteomics technology.

In chapter 1, the biopharmaceutical process is described, including the development of cell culture processes, and methods used to enhance cell culture performance through various genetic engineering strategies. Proteomics analysis can enable the identification of new cell culture biomarkers related to cell growth and productivity. Tools used in the proteomics field are outlined, as well as reported proteomics studies of mammalian cell cultures.

In chapter 2, a high-producing Chinese hamster ovarian cell culture which had been transfected with the apoptosis inhibitor Bcl-XL gene was compared to a low-producing control. Shotgun proteomics was used to compare the high and low-producing fed-batch cell cultures at different growth timepoints. A total of 392 proteins were identified in this study, and 32 of these proteins were determined to be differentially expressed, including several proteins related to protein metabolism such as eukaryotic translation initiation factor 3, and ribosome 40S. In addition, several intermediate filament proteins such as vimentin and annexin, as well as histone H1.2 and H2A, were downregulated in the high producer. A growth inhibitor, galectin-1, was downregulated in the high-producer, which may be related to lower cell growth in the control. The molecular chaperone BiP was upregulated significantly in the high-producer and may indicate an unfolded protein response due to ER stress.

In chapter 3, an advanced proteomics method using two-dimensional liquid chromatography and iTRAQ chemical labeling was used to probe the proteomic changes occurring in CHO cells during exponential and stationary phases of cell culture. Using this approach, 59 proteins were identified with significant dynamic trends. These proteins were analyzed using pathway analysis tools, which identified a network of proteins associated with cell growth and apoptosis. Molecular chaperones and isomerases, such as GRP78 and PDI, were upregulated during stationary phase, and are associated with cellular response to endoplasmic reticulum (ER) stress. Nucleic acid binding proteins including MCM2 and MCM5 were downregulated during stationary phase, and are known cell growth markers. In addition, two proteins with growth-regulating properties, transglutaminase-2 and clusterin, were identified. These proteins are associated with tumor proliferation and apoptosis, and were observed to be expressed at relatively high levels during stationary phase, which was confirmed by western blotting.

Gene order in eukaryotes is not random, but rather genes related by function tend to be clustered together and are regulated in similar patterns. It is thought that the co-regulation of nearby genes is related to chromatin remodeling and histone activity. In chapter 4, genes of interest related to cell culture performance are mapped to mouse chromosomes, and analyzed for evidence of clustering. Several clusters of known oncogenes are identified. Several other clusters of genes of interest are identified from the list of differentially expressed proteins described in chapter 3. This work provides some initial evidence of potential clustering of growth-related genes in CHO, which can be expanded on with availability of the CHO genome and gene expression data.

In the fifth chapter, the application of proteomics techniques to the analysis of secreted host-cell proteins in process intermediate samples is described. Proteins present in the cell culture media are identified, including glycolytic enzymes released from damaged cells and several growth-regulating proteins secreted by the cells. In addition, the clearance of the host cell proteins is studied by performing proteomics analysis on process intermediates from various stages within the downstream purification process. Several relatively abundance proteins co-purified throughout the process are identified, and physiochemical properties of these co-purified proteins are analyzed.

Document Type

Dissertation

Rights Holder

Tyler Carlage


View Full Text

Click button above to open, or right-click to save.

Share

COinS