James Ross, PhD- Senior Scientist, MilliporeSigma, Bellefonte, PA -A business of Merck KGaA, Darmstadt, Germany; Geoffrey Rule, PhD- Principal Scientist, MilliporeSigma, Bellefonte, PA- A business of Merck KGaA, Darmstadt, Germany.
Metabolomics, the study of living organisms’ metabolites or small molecule biochemical components, offers great opportunities to optimize biopharmaceutical manufacturing processes that use cell cultures. An interview with two leading scientists at MilliporeSigma gives insights into current techniques and strategies.
In general terms, how can cell cultivation benefit from metabolomics?
Geoff: In cell culture, metabolomics involves the monitoring of metabolite concentrations, and typically also of the feed medium’s components. This creates a wealth of data for subsequent analysis, the results of which could suggest how cell culture conditions can be changed to tweak the metabolic activity of the cells. Software modelling and statistical tools are available to facilitate the integration of metabolic studies into multi-omics, or “systems biology” studies. These tools provide scientists the ability to perform a variety of statistical analyses, looking for correlations between genes, proteins, and metabolic pathways of an organism. So, the study of larger molecules such as proteins, DNA, and mRNA, referred to as proteomics, genomics, and transcriptomics respectively, can be integrated with the metabolomics data.
How is metabolomics used to study cell cultures?
Geoff: In recombinant cell culture studies, we investigate how cellular metabolic products relate to production efficiency, critical quality attributes, and quantity of a desired end-product, such as a monoclonal antibody. We use metabolomics to study the relationship between positive and negative biochemical influences on the therapeutic end-product.
James: So, an example would be to monitor amino acid concentrations in the culture medium. Studies in Chinese hamster ovary (CHO) cells1 have shown that proteins synthesized in proline deficient medium can lead to substitution of alanine for this amino acid. Another study has shown how citrate can boost specific productivity in cell cultures,2 that is, the amount of a certain protein produced per cell, per day. However, the build-up of undesirable metabolic by-products from an excess of nutrients has also been shown to lead to detrimental effects on end-product.3 Importantly, we want to control effects on post-translational modifications, such as glycosylation, phosphorylation, or deamination, to ensure drug quality, and this can be impacted if inhibitory metabolites accumulate.
What tools and analytical techniques are used to monitor cell cultures?
James: A variety of tools are being used including Raman, near-IR, or fluorescence spectroscopy, optical density, and various on-line, and at-line, measurements. Manufacturing processes are being developed to monitor cultures continuously and to automate periodic sample collection for further analysis.
For metabolomic studies, researchers generally use a form of chromatography, often liquid chromatography, combined with mass spectrometry. To capture a broad range of metabolic analytes, it is possible to combine several chromatographic modes, such as reversed phase and hydrophilic interaction (HILIC), with both positive and negative modes of ionization. A high resolution accurate-mass (HRAM) instrument can discover important, yet unidentified, metabolites. Such a “non-targeted study” can identify compounds that correlate with a desired outcome. For example, we characterize as many components of a cell culture supernatant as possible and then, using statistical tools, determine which of these correlate with desired product quality attributes. Once accomplished, a simpler, “targeted study” can quantify such components. So statistical tools are of special importance in understanding these relationships.
What is the ideal outcome of using metabolomics on cell cultures?
James: The desired outcome is that we define the limits for critical process parameters within which we are assured of optimum manufacturing efficiency, consistency, and quality, of our therapeutic product. This is the quality by design, or QbD, approach to manufacturing.
Geoff: Currently there is much interest in perfusion-based cultures, and we’re seeing a drive towards continuous processing. This approach strives to prolong the period of optimum cell production by using a continuous delivery of fresh medium while removing the desired protein product from the reactor, along with undesired metabolic products. To do this, we need to have a thorough understanding of the concentration of both the feed components and the metabolic by-products. This allows us to develop models that can aid in feed optimization and product intensification. So, metabolomics experiments can be used to determine concentrations of important metabolites and to develop correlations with data from instrumentation, such as Raman, and basic parameters such as reactor temperature, pH, and dissolved oxygen.
James: Ideally, we would sustain viable cells, producing the desired protein, for an indefinite period by managing a continuous addition of nutrients while at the same time isolating the desired protein product and undesirable metabolites such as inhibitory compounds and dead cells. With the aid of LC-MS, we can devise these strategies, develop cell culture models, and monitor the culture; allowing us to maintain optimum levels of both desired and undesired metabolites.
Can these strategies be used for other bioreactor cultures?
Geoff: Absolutely. It doesn’t matter what cell type we are working with, mammalian, insect, bacterial, or yeast, the same types of metabolomics experiments can be used to quantify biochemical components that are most essential to the productivity and quality characteristics of the end-product.
References
- Sun, Z., et al., High-throughput LC-MS quantitation of cell culture metabolites. Biologicals, 2019. 61: p. 44-51.
- Yao, G., et al., A metabolomics approach to increasing Chinese hamster ovary (CHO) cell productivity. Metabolites, 2021. 11(12).
- Kuang, B., et al., Identification of novel inhibitory metabolites and impact verification on growth and protein synthesis in mammalian cells. Metabolic Engineering Communications, 2021. 13.
Subscribe to our e-Newsletters
Stay up to date with the latest news, articles, and events. Plus, get special
offers from American Pharmaceutical Review delivered to your inbox!
Sign up now!