Metabolomics process modeling: A systems biology approach to understand variability in commercial biologics cell culture processes

The biopharmaceutical industry strives to develop and operate efficient, robust, reproducible commercial biologics processes. A major challenge of industrial biologics processes is optimization of cell culture conditions to increase productivity while maintaining consistent product quality. The cell culture operations, which involve the use of live cell hosts, have historically introduced significant variability to the overall process. Technological improvements which include the implementation of advanced cell line engineering, chemically defined media, quality by design (QbD) development approaches, and in-line and at-line monitoring, have significantly reduced process variability. Nonetheless, performance variability remains a challenge for many commercial programs. This variability in turn can impact both product yields and product quality. Even small performance differences can become significant in low-yield processes with large campaign sizes, or processes manufactured at multiple sites. The ability to understand and eliminate sources of variability is greatly enhanced by augmenting the quality and quantity of data available from commercial campaigns. Metabolomics Process Monitoring (MPM) is a data-driven approach to understand sources of manufacturing variability on a cellular level. Here we present a case study of MPM implementation in a legacy commercial biologics program. First, we describe how the MPM workflow was successfully integrated into a commercial manufacturing process. Second, we discuss novel data normalization techniques developed to enable long term trending. Third, we describe the selection of an orthogonal projections to latent structures (OPLS) model to link systems biology and process data. Finally, we share key mechanistic insights obtained from the case study, and provide a vision for how MPM can enhance commercial biologics capabilities going forward

Understanding and controlling sialyation in a CHO fusion protein at lab and manufacturing scale using targeted omics techniques

Biologics, including antibodies, hormones and cytokines, represent an increasingly important class of therapeutics, with 7 of the 10 top selling drugs from 2013 in this class. The glycosylation distribution of these proteins is an important characteristic that can impact biological activity, circulatory half-life, and immunogenicity. One property that affects glycoproteins is the terminal addition of N-acetylneuraminic acid (sialic acid) to glycosylation chains. Despite the importance of glycosylation in many therapeutic proteins, limited information is available to date linking process parameters to changes in glycosylation distribution. The majority of the work that has been done is limited to a small number of proteins (such as interferon gamma) and small scale systems (shake flasks and bench top bioreactors). Although this work represents a useful starting point, glycosylation is a parameter that is known to be influenced by production scale. Here we examine a glycosylated CHO fusion protein for which sialyation level is known to impact protein quality. Variation in this parameter was observed across pilot and manufacturing scale batches. In order to better understand and control the biological source of the variation in the process, we employed metabolomic and transcriptomic methods, and successfully identified metabolic biomarkers, such as extracellular mannose, for sialylation level. Additional studies demonstrated that changes to sugar metabolism were contributing to a build-up of intermediates and inhibition of glycan sialyation, thereby identifying the biological source of variation in the process. As a result of these studies, we evaluated the impact of process modifications including feed composition and gassing to enable consistent control of sialyation profiles. This work represents a novel contribution to the field. We examine sialyation control of a CHO fusion protein at laboratory and manufacturing scale. Furthermore, we combine ‘Omics techniques with bioprocess and analytical data to achieve a more detailed understanding of cell expression and metabolism [1], and leverage this understanding to refine the process and control a quality attribute. Finally, this approach can be generalized beyond this specific process and applied to additional cell lines where undesired process variation is observed

The tegula tango: A coevolutionary dance of interacting, positively selected sperm and egg proteins

Reproductive proteins commonly show signs of rapid divergence driven by positive selection. The mechanisms driving these changes have remained ambiguous in part because interacting male and female proteins have rarely been examined. We isolate an egg protein the vitelline envelope receptor for lysin (VERL) from Tegula, a genus of free-spawning marine snails. Like VERL from abalone, Tegula VERL is a major component of the VE surrounding the egg, includes a conserved zona pellucida (ZP) domain at its C-terminus, and possesses a unique, negatively charged domain of about 150 amino acids implicated in interactions with the positively charged lysin. Unlike for abalone VERL, where this unique VERL domain occurs in a tandem array of 22 repeats, Tegula VERL has just one such domain. Interspecific comparisons show that both lysin and the VERL domain diverge via positive selection, whereas the ZP domain evolves neutrally. Rates of nonsynonymous substitution are correlated between lysin and the VERL domain, consistent with sexual antagonism, although lineage-specific effects, perhaps owing to different ecologies, may alter the relative evolutionary rates of sperm- and egg-borne proteins. © 2012 The Author(s). Evolution © 2012 The Society for the Study of Evolution

The solution structure of a cyclic endothelin antagonist, BQ-123, based on 1H1H and 13H1H three bond oupling constants

AbstractA cyclic pentapeptide endothelin antagonist, cyclo(dTrp-dAsp-Pro-dVal-Leu), recently reported (K. Ishikawa et al., 13th Am. Pept. Symp., Cambridge MA, 1991) has been studied by NMR spectroscopy and molecular modeling. A stable structure has been determined without the use of nuclear Overhauser effects and is based primarily on homonuclear and heteronuclear three bond coupling constants. The 13C-edited TOCSY experiment is demonstrated at natural abundance and ∼30 mM peptide concentrations. Three bond 13C1H coupling constants obtained by this method are shown to reduce the ambiguity in φ angle determination which exists when only interproton coupling constants are used. Three out of four φ angles were determined uniquely by this method and the fourth was reduced to two possible values. The proline φ angle was determined to be −78° based on the 3JHzHα and 3JHzHβ coupling constants. Comparison of amide proton temperature dependence, chemical shifts and vicinal proton coupling constants in a 20% acetonitrile/80% water solvent mixture and in (CD3)2SO indicates that the structure is similar in both solvents

Applying genome scale metabolic models integrated with OMICs technologies for improvemwent of commercial CHO cell culture process

Although metabolic flux analysis has been established in microbial fermentation, their application in CHO cell culture is sparse. In general CHO cell culture process development is highly rely on empirical experience with limited cell and metabolite data without good mechanism understanding. The purpose of this research is to apply genome scale metabolic modeling for CHO cell culture process improvement. Recently we found that several medium components had significant impact on mAb production by BMSCHO1, a proprietary cell line (Fig. 1). Some of medium components at a low concentration, though within normal ranges for CHO cell culture, caused the BMSCHO1 crashed. Meanwhile some of the other medium components at a low concentration did not cause cell crash, but significantly decreased productivity. The preliminary genetic test results indicated no change in DNA copy number and southern blot integration profile under different medium conditions. Currently we are investigating both supernatant and cell pellets for metabolomics analysis using NMR and LCMS, and assessing epigenetic characteristics. In addition, transcriptomics data have been analyzed by RNA sequence and RT-PCR. Genome-scale modeling integrated with these OMICS datasets have been built and analyzed. In the presentation, we plan to share the investigation details of commercial cell-line and manufacturing process based on the application of genome scale modeling integrated with OMICS technology. Please click Additional Files below to see the full abstract

Prevention of diabetic nephropathy in Ins2+/−AkitaJ mice by the mitochondria-targeted therapy MitoQ

Mitochondrial production of ROS (reactive oxygen species) is thought to be associated with the cellular damage resulting from chronic exposure to high glucose in long-term diabetic patients. We hypothesized that a mitochondria-targeted antioxidant would prevent kidney damage in the Ins2+/−AkitaJ mouse model (Akita mice) of Type 1 diabetes. To test this we orally administered a mitochondria-targeted ubiquinone (MitoQ) over a 12-week period and assessed tubular and glomerular function. Fibrosis and pro-fibrotic signalling pathways were determined by immunohistochemical analysis, and mitochondria were isolated from the kidney for functional assessment. MitoQ treatment improved tubular and glomerular function in the Ins2+/−AkitaJ mice. MitoQ did not have a significant effect on plasma creatinine levels, but decreased urinary albumin levels to the same level as non-diabetic controls. Consistent with previous studies, renal mitochondrial function showed no significant change between any of the diabetic or wild-type groups. Importantly, interstitial fibrosis and glomerular damage were significantly reduced in the treated animals. The pro-fibrotic transcription factors phospho-Smad2/3 and β-catenin showed a nuclear accumulation in the Ins2+/−AkitaJ mice, which was prevented by MitoQ treatment. These results support the hypothesis that mitochondrially targeted therapies may be beneficial in the treatment of diabetic nephropathy. They also highlight a relatively unexplored aspect of mitochondrial ROS signalling in the control of fibrosis

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead