Jochen Schaub

Integrated sampling procedure for metabolome analysis

Metabolome analysis, the analysis of large sets of intracellular metabolites, has become an important systems analysis method in biotechnological and pharmaceutical research. In metabolic engineering, the integration of metabolome data with fluxome and proteome data into large‐scale mathematical models promises to foster rational strategies for strain and cell line improvement. However, the development of reproducible sampling procedures for quantitative analysis of intracellular metabolite concentrations represents a major challenge, accomplishing (i) fast transfer of sample, (ii) efficient quenching of metabolism, (iii) quantitative metabolite extraction, and (iv) optimum sample conditioning for subsequent quantitative analysis. In addressing these requirements, we propose an integrated sampling procedure. Simultaneous quenching and quantitative extraction of intracellular metabolites were realized by short‐time exposure of cells to temperatures ≤95 °C, where intracellular metabolites are released quantitatively. Based on these findings, we combined principles of heat transfer with knowledge on physiology, for example, turnover rates of energy metabolites, to develop an optimized sampling procedure based on a coiled single tube heat exchanger. As a result, this sampling procedure enables reliable and reproducible measurements through (i) the integration of three unit operations into a one unit operation, (ii) the avoidance of any alteration of the sample due to chemical reagents in quenching and extraction, and (iii) automation. A sampling frequency of 5 s−1 and an overall individual sample processing time faster than 30 s allow observing responses of intracellular metabolite concentrations to extracellular stimuli on a subsecond time scale. Recovery and reliability of the unit operations were analyzed. Impact of sample conditioning on subsequent IC‐MS analysis of metabolites was examined as well. The integrated sampling procedure was validated through consistent results from steady‐state metabolite analysis of Escherichia coli cultivated in a chemostat at D = 0.1 h−1.

Into the unknown: expression profiling without genome sequence information in CHO by next generation sequencing

The arrival of next-generation sequencing (NGS) technologies has led to novel opportunities for expression profiling and genome analysis by utilizing vast amounts of short read sequence data. Here, we demonstrate that expression profiling in organisms lacking any genome or transcriptome sequence information is feasible by combining Illumina’s mRNA-seq technology with a novel bioinformatics pipeline that integrates assembled and annotated Chinese hamster ovary (CHO) sequences with information derived from related organisms. We applied this pipeline to the analysis of CHO cells which were chosen as a model system owing to its relevance in the production of therapeutic proteins. Specifically, we analysed CHO cells undergoing butyrate treatment which is known to affect cell cycle regulation and to increase the specific productivity of recombinant proteins. By this means, we identified sequences for >13 000 CHO genes which added sequence information of ∼5000 novel genes to the CHO model. More than 6000 transcript sequences are predicted to be complete, as they covered >95% of the corresponding mouse orthologs. Detailed analysis of selected biological functions such as DNA replication and cell cycle control, demonstrated the potential of NGS expression profiling in organisms without extended genome sequence to improve both data quantity and quality.

CHO gene expression profiling in biopharmaceutical process analysis and design

Increase in both productivity and product yields in biopharmaceutical process development with recombinant protein producing mammalian cells can be mainly attributed to the advancements in cell line development, media, and process optimization. Only recently, genome-scale technologies enable a system-level analysis to elucidate the complex biomolecular basis of protein production in mammalian cells promising an increased process understanding and the deduction of knowledge-based approaches for further process optimization. Here, the use of gene expression profiling for the analysis of a low titer (LT) and high titer (HT) fed batch process using the same IgG producing CHO cell line was investigated. We found that gene expression (i) significantly differed in HT versus LT process conditions due to differences in applied chemically defined, serum-free media, (ii) changed over the time course of the fed batch processes, and that (iii) both metabolic pathways and 14 biological functions such as cellular growth or cell death were affected. Furthermore, detailed analysis of metabolism in a standard process format revealed the potential use of transcriptomics for rational media design as is shown for the case of lipid metabolism where the product titer could be increased by about 20% based on a lipid modified basal medium. The results demonstrate that gene expression profiling can be an important tool for mammalian biopharmaceutical process analysis and optimization.

In vivo dynamics of glycolysis in Escherichia coli shows need for growth‐rate dependent metabolome analysis

Metabolomics emerges to become an important profiling technique in bio(techno)logical systems. In addition to intracellular metabolite concentrations at (quasi) stationary conditions, stimulus‐response experiments provide information on the dynamic behavior of metabolic pathways. These data are relevant for bioprocess analysis on the level of metabolism and for application of metabolic engineering principles aiming at a metabolic redesign of producer cells. However, even for the well‐studied bacteria Escherichia coli only limited growth‐rate dependent intracellular metabolite information is currently available, thereby impeding comprehensive metabolome analysis. Here, we present intracellular metabolite concentration data of representative glycolytic intermediates in E. coli cultivated in glucose‐limited chemostats, (i) at systematic variation of growth‐rate (D = 0.1, 0.2, 0.3, and 0.4 h−1) and (ii) at both steady‐state and after a glucose pulse applying a recently introduced integrated sampling procedure and LC‐MS analytical method. Whereas intracellular steady‐state concentrations of upper part glycolytic intermediates FBP and DHAP+GAP increased 2.3‐fold, respectively 2.8‐fold, when specific growth‐rate is raised from μ = 0.1 h−1 to μ = 0.4 h−1, the opposite trend was observed for 2PG+3PG and PEP pools with a decrease by a factor of 2.1, respectively 1.9. In glucose pulse experiments FBP and DHAP+GAP showed a 3.3 (1.8)‐fold, respectively 2.8 (2.0)‐fold, increase relative to the steady‐state level at μ = 0.1 (0.4) h−1. Also, the dynamics changed with growth‐rate for these two metabolite pools. In contrast, 2PG+3PG and PEP were characterized by decreased concentrations in response to a glucose pulse and the relative changes related to steady‐state values were significantly smaller compared with FBP and DHAP+GAP. The observed growth‐rate dependency of our data clearly indicates the necessity for metabolome studies covering a broader range of physiological growth conditions.

A global RNA-seq-driven analysis of CHO host and production cell lines reveals distinct differential expression patterns of genes contributing to recombinant antibody glycosylation

Boehringer Ingelheim uses two CHO-DG44 lines for manufacturing biotherapeutics, BI-HEX-1 and BI-HEX-2, which produce distinct cell type-specific antibody glycosylation patterns. A recently established CHO-K1 descended host, BI-HEX-K1, generates antibodies with glycosylation profiles differing from CHO-DG44. Manufacturing process development is significantly influenced by these unique profiles. To investigate the underlying glycosylation related gene expression, we leveraged our CHO host and production cell RNA-seqtranscriptomics and product quality database together with the CHO-K1 genome. We observed that each BI-HEX host and antibody producing cell line has a unique gene expression fingerprint. CHO-DG44 cells only transcribe Fut10, Gfpt2 and ST8Sia6 when expressing antibodies. BI-HEX-K1 cells express ST8Sia6 at host cell level. We detected a link between BI-HEX-1/BI-HEX-2 antibody galactosylation and mannosylation and the gene expression of the B4galt gene family and genes controlling mannose processing. Furthermore, we found major differences between the CHO-DG44 and CHO-K1 lineages in the expression of sialyl transferases and enzymes synthesizing sialic acid precursors, providing a rationale for the lack of immunogenic NeuGc/NGNA synthesis in CHO. Our study highlights the value of systems biotechnology to understand glycoprotein synthesis and product glycoprofiles. Such data improve future production clone selection and process development strategies for better steering of biotherapeutic product quality.

Process parameters impacting product quality

Background and novelty Product quality is a result of the entire production process including protein sequence, cell substrate and process parameters. Many of the desired product properties are defined by posttranslational modifications with impact on biological activity, immunogenicity, half-life or stability. In-depth process understanding enables the targeted modulation of product quality attributes by rationally designed bioprocesses. This is valuable for new biological molecules in order to improve efficacy, reduce side effects, access new patient populations. For biosimilars this allows developing into defined quality attribute profiles. The identification of suitable process parameters and media compositions to modulate quality attributes is challenging due to the complexity of cell culture processes. Here, this challenge was approached by comprehensive data analysis, in-depth characterization of charge variant formation and high-throughput screening of process parameters and media compounds.

BI-HEX ® -GlymaxX ® cells enable efficient production of next generation biomolecules with enhanced ADCC activity

Background Despite the succes story of therapeutic monoclonal antibodies (mAbs), a medical need remains to improve their efficacy. One possibility to achieve this is to modulate important effector functions such as the antibody dependent cellular cytotoxicity (ADCC). The advantage of highly active biotherapeutic molecules is apart from the enhanced efficacy the reduction of side effects due to lower administered doses. Furthermore, these therapeutic antibodies may enable treatment of current nonresponders, e.g. patients with low antigen bearing tumors. Enhancement of the effector functions of antibodies can be achieved either by directly mutating the antibody’s amino acid sequence or by modifying its glycosylation pattern, e.g. by using a novel host cell line able to attach a desired glycostructure to the product. The latter approach has the advantage of not impacting the antibody structure itself, thereby avoiding negative effects on the PK/PD of the molecule. During the last decade it has been shown that antibodies with a reduced level of glycan fucosylation are much more potent in mediating ADCC, a mode of action particularly relevant for cancer therapeutics. Therefore, defucosylated antibodies are of major interest for biotherapeutics developers. To produce such antibodies, Boehringer Ingelheim has inlicensed the GlymaxX system from ProBioGen, Germany. This technology utilises the bacterial protein RMD (GDP-6-deoxy-D-lyxo-4-hexulose reductase) which, when stably integrated into host cell lines, inhibits fucose de-novo biosynthesis. The enzyme deflects the fucosylation pathway by turning an intermediate (GDP-4-Keto-6-Deoxymannose) into GDP-Rhamnose, a sugar that cannot be metabolised by CHO cells. As a consequence, recombinant antibodies generated by such host cells exhibit reduced glycan fucosylation and 20100 fold higher ADCC activity. Here, we show the establishment of a new host cell line, termed BI-HEXGlymaxX which is capable of producing highly active therapeutic antibodies. We furthermore present data on the cell line properties concerning cell culture performance (e.g. titer, growth, transfection efficiency), process robustness and product quality reproducibility.